Search results for: hardy cross networks accuracy

Authors: Georgiana Onicescu, Yuqian Shen

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Due to the complex nature of geo-referenced data, multicollinearity of the risk factors in public health spatial studies is a commonly encountered issue, which leads to low parameter estimation accuracy because it inflates the variance in the regression analysis. To address this issue, we proposed a two-stage variable selection method by extending the least absolute shrinkage and selection operator (Lasso) to the Bayesian spatial setting, investigating the impact of risk factors to health outcomes. Specifically, in stage I, we performed the variable selection using Bayesian Lasso and several other variable selection approaches. Then, in stage II, we performed the model selection with only the selected variables from stage I and compared again the methods. To evaluate the performance of the two-stage variable selection methods, we conducted a simulation study with different distributions for the risk factors, using geo-referenced count data as the outcome and Michigan as the research region. We considered the cases when all candidate risk factors are independently normally distributed, or follow a multivariate normal distribution with different correlation levels. Two other Bayesian variable selection methods, Binary indicator, and the combination of Binary indicator and Lasso were considered and compared as alternative methods. The simulation results indicated that the proposed two-stage Bayesian Lasso variable selection method has the best performance for both independent and dependent cases considered. When compared with the one-stage approach, and the other two alternative methods, the two-stage Bayesian Lasso approach provides the highest estimation accuracy in all scenarios considered.

Keywords: Lasso, Bayesian analysis, spatial analysis, variable selection

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Authors: Yuexi Xiong, Jingwu He

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The structural components in an energy facility such as steam turbine machines are operated under high stress and elevated temperature in an endured time period and thus the creep deformation and creep rupture failure are important issues that need to be addressed in the design of such components. There are numerous creep models being used for creep analysis that have both advantages and disadvantages in terms of accuracy and efficiency. The Isochronous Creep Analysis is one of the simplified approaches in which a full-time dependent creep analysis is avoided and instead an elastic-plastic analysis is conducted at each time point. This approach has been established based on the rupture dependent creep equations using the well-known Larson-Miller parameter. In this paper, some fundamental aspects of creep deformation and the rupture dependent creep models are reviewed and the analysis procedures using isochronous creep curves are discussed. Four rupture failure criteria are examined from creep fundamental perspectives including criteria of Stress Damage, Strain Damage, Strain Rate Damage, and Strain Capability. The accuracy of these criteria in predicting creep life is discussed and applications of the creep analysis procedures and failure predictions of simple models will be presented. In addition, a new failure criterion is proposed to improve the accuracy and effectiveness of the existing criteria. Comparisons are made between the existing criteria and the new one using several examples materials. Both strain increase and stress relaxation form a full picture of the creep behaviour of a material under high temperature in an endured time period. It is important to bear this in mind when dealing with creep problems. Accordingly there are two sets of rupture dependent creep equations. While the rupture strength vs LMP equation shows how the rupture time depends on the stress level under load controlled condition, the strain rate vs rupture time equation reflects how the rupture time behaves under strain-controlled condition. Among the four existing failure criteria for rupture life predictions, the Stress Damage and Strain Damage Criteria provide the most conservative and non-conservative predictions, respectively. The Strain Rate and Strain Capability Criteria provide predictions in between that are believed to be more accurate because the strain rate and strain capability are more determined quantities than stress to reflect the creep rupture behaviour. A modified Strain Capability Criterion is proposed making use of the two sets of creep equations and therefore is considered to be more accurate than the original Strain Capability Criterion.

Keywords: creep analysis, high temperature mateials, rapture evalution, steam turbine machines

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Authors: Mohamad Mahdi Namdari

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In today's rapidly changing and evolving business competition, companies and organizations require advanced and efficient tools to manage their markets and sales networks. Big data analysis, quick response in competitive markets, process and operations optimization, and forecasting customer behavior are among the concerns of executive managers. Artificial intelligence, as one of the emerging technologies, has provided extensive capabilities in this regard. The use of artificial intelligence in market and sales network management can lead to improved efficiency, increased decision-making accuracy, and enhanced customer satisfaction. Specifically, AI algorithms can analyze vast amounts of data, identify complex patterns, and offer strategic suggestions to improve sales performance. However, many companies are still distant from effectively leveraging this technology, and those that do face challenges in fully exploiting AI's potential in market and sales network management. It appears that the general public's and even the managerial and academic communities' lack of knowledge of this technology has caused the managerial structure to lag behind the progress and development of artificial intelligence. Additionally, high costs, fear of change and employee resistance, lack of quality data production processes, the need for updating structures and processes, implementation issues, the need for specialized skills and technical equipment, and ethical and privacy concerns are among the factors preventing widespread use of this technology in organizations. Clarifying and explaining this technology, especially to the academic, managerial, and elite communities, can pave the way for a transformative beginning. The aim of this research is to elucidate the capacities of artificial intelligence in market and sales network management, identify its opportunities and benefits, and examine the existing challenges and obstacles. This research aims to leverage AI capabilities to provide a framework for enhancing market and sales network performance for managers. The results of this research can help managers and decision-makers adopt more effective strategies for business growth and development by better understanding the capabilities and limitations of artificial intelligence.

Keywords: artificial intelligence, market management, sales network, big data analysis, decision-making, digital marketing

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Authors: Jing Wu, Wei Lv, Yibing Li, Yuanfan You

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The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.

Keywords: DBSCAN, potential function, speech signal, the UBSS model

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Authors: Muhammad Imran, Iqra Basit, Mobushir Riaz Khan, Sajid Rasheed Ahmad

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The present study investigates the space-time impact of climate change on the rice crop calendar in tropical Gujranwala, Pakistan. The climate change impact was quantified through the climatic variables, whereas the existing calendar of the rice crop was compared with the phonological stages of the crop, depicted through the time series of the Normalized Difference Vegetation Index (NDVI) derived from Landsat data for the decade 2005-2015. Local maxima were applied on the time series of NDVI to compute the rice phonological stages. Panel models with fixed and cross-section fixed effects were used to establish the relation between the climatic parameters and the time-series of NDVI across villages and across rice growing periods. Results show that the climatic parameters have significant impact on the rice crop calendar. Moreover, the fixed effect model is a significant improvement over cross-sectional fixed effect models (R-squared equal to 0.673 vs. 0.0338). We conclude that high inter-annual variability of climatic variables cause high variability of NDVI, and thus, a shift in the rice crop calendar. Moreover, inter-annual (temporal) variability of the rice crop calendar is high compared to the inter-village (spatial) variability. We suggest the local rice farmers to adapt this change in the rice crop calendar.

Keywords: Landsat NDVI, panel models, temperature, rainfall

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Authors: Léa Chawki, Émilie Cappe

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Context: Nowadays, supporting parents of children with autism spectrum disorder (ASD) and helping them adjust to their child’s condition represents a core clinical and scientific necessity and is encouraged by the French National Strategy for Autism (2018). In France, ASD remains a challenging condition, causing distress, segregation and social stigma to concerned family members concerned by this handicap. The literature highlights that neurodevelopmental disorders in children, such as ASD, influence parental well-being. This impact could be different according to parents’ culture and the child’s particular disorder manifestation, such as developmental coordination disorder (DCC), for instance. Objectives: This present study aims to explore parental stress, anxiety and depressive symptoms, as well as the quality of life in parents of children with ASD or DCD, as well as the explicit individual, psychosocial and cultural factors of parental well-being. Methods: Participants will be recruited through diagnostic centers, child and specialized adolescent units, and organizations representing families with ASD and DCD. Our sample will include five groups of 150 parents: four groups of parents having children with ASD – one living in France, one in the US, one in Canada and the other in Lebanon – and one group of French parents of children with DCD. Self-evaluation measures will be filled directly by parents in order to measure parental stress, anxiety and depressive symptoms, quality of life, coping and emotional regulation strategies, internalized stigma, perceived social support, the child’s problem behaviors severity, as well as motor coordination deficits in children with ASD and DCD. A sociodemographic questionnaire will help collect additional useful data regarding participants and their children. Individual and semi-structured research interviews will be conducted to complete quantitative data by further exploring participants’ distinct experiences related to parenting a child with a neurodevelopmental disorder. An interview grid, specially designed for the needs of this study, will strengthen the comparison between the experiences of parents of children with ASD with those of parents of children with DCD. It will also help investigate cultural differences regarding parent support policies in the context of raising a child with ASD. Moreover, interviews will help clarify the link between certain research variables (behavioral differences between ASD and DCD, family leisure activities, family and children’s extracurricular life, etc.) and parental well-being. Research perspectives: Results of this study will provide a more holistic understanding of the roles of individual, psychosocial and cultural variables related to parental well-being. Thus, this study will help direct the implementation of support services offered to families of children with neurodevelopmental disorders (ASD and DCD). Also, the implications of this study are essential in order to guide families through changes related to public policies assisting neurodevelopmental disorders and other disabilities. The between-group comparison (ASD and DCD) is also expected to help clarify the origins of all the different challenges encountered by those families. Hence, it will be interesting to investigate whether complications perceived by parents are more likely to arise from child-symptom severity, or from the lack of support obtained from health and educational systems.

Keywords: Autism spectrum disorder, cross-cultural, cross-disorder, developmental coordination delay, well-being

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Authors: A. Afrashi

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Introduction: Synaesthesia is a term denoting the perception or description of the perception of one sense modality in terms of another. In literature, synaesthesia refers to a technique adopted by writers to present ideas, characters or places in such a manner that they appeal to more than one sense like hearing, seeing, smell etc. at a given time. In everyday language too we find many examples of synaesthesia. We commonly hear phrases like ‘loud colors’, ‘frozen silence’ and ‘warm colors’, ‘bitter cold’ etc. Empirical cognitive studies have proved that synaesthetic representations both in literature and everyday languages are constrained ie. they do not map randomly among sensory domains. From the beginning of the 20th century Synaesthesia has been a research domain both in literature and structural linguistics. However the exploration of cognitive mechanisms motivating synaesthesia, have made it an important topic in 21st century cognitive linguistics and literary studies. Synaesthetic metaphors are linguistic representations of those mental mechanisms, the study of which reveals invaluable facts about perception, cognition and conceptualization. According to the main tenets of cognitive approach to language and literature, unified and similar cognitive mechanisms are active both in everyday language and literature, and synaesthesia is one of those cognitive mechanisms. Main objective of the present research is to answer the following questions: What types of sense transfers are accessible in Persian synaesthetic metaphors. How are these types of sense transfers cognitively explained. What are the results of cross-linguistic comparative study of synaestetic metaphors based on the existing observations? Methodology: The present research employs a cognitive - corpus based method, and the theoretical framework adopted to analyze linguistic synaesthesia is the contemporary theory of metaphor, where conceptual metaphor is the result of systemic mappings across cognitive domains. Persian Language Data- base (PLDB) in the Institute for Humanities and Cultural Studies which consists mainly of Persian modern prose, is searched for synaesthetic metaphors. Then for each metaphorical structure, the source and target domains are determined. Then sense transfers are identified and the types of synaesthetic metaphors recognized. Findings: Persian synaesthetic metaphors conform to the hierarchical distribution principle, according to which transfers tend to go from touch to taste to smell to sound and to sight, not vice versa. In other words mapping from more accessible or basic concepts onto less accessible or less basic ones seems more natural. Furthermore the most frequent target domain in Persian synaesthetic metaphors is sound. Certain characteristics of Persian synaesthetic metaphors are comparable with existing related researches carried on English, French, Hungarian and Chinese synaesthetic metaphors. Conclusion: Cognitive corpus based approaches to linguistic synaesthesia, are applicable to stylistics and literary criticism and this recent research domain is an efficient approach to study cross linguistic variations to find out which of the five senses is dominant cross linguistically and cross culturally as the target domain in metaphorical mappings , and so forth receiving dominance in conceptualizations.

Keywords: cognitive semantics, conceptual metaphor, synaesthesia, corpus based approach

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Authors: Robert John Godby

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To be responsive now and in the future, workplaces must address the demands of multicultural teams as they become more common elements of the global labor force. This is especially the case for aged care due to the aging population, industry growth and migrant recruitment. This research identifies influences on and improvements for learning in these environments. Its unique contribution is to illuminate how culturally diverse workplaces can work and learn together more effectively. A mixed-methods approach was used to gather data about this topic in two phases. Firstly, the research methods included a survey of 102 aged care workers around Australia from two multi-site aged care organisations. The questionnaire elicited both quantitative and qualitative data about worker characteristics and perspectives on working and learning in aged care. Secondly, a case study of one aged care worksite was formulated drawing on worksite information and interviews with workers. A review of the literature suggests that learning in multicultural work environments is influenced by three main factors: 1) the individual workers themselves, 2) their interaction with each other and 3) the environment in which they work. There are various accounts of these three factors, how they are manifested and how they lead to a change in workers’ disposition, knowledge, or expertise when confronted with new circumstances. The study has found that a key individual factor influencing learning is cultural background. Their unique view of the world was shown to affect their approach to both their work and co-working. Interactional factors suggest that the high requirement for collaboration in aged care positively supports learning in this context; however, it can be hindered by cultural bias and spoken accent. The study also found that environmental factors, such as disruptions caused by the pandemic, were another key influence. For example, the need to wear face masks hindered the communication needed for workplace learning. This was especially challenging due to the diverse language backgrounds and abilities within the teams. Potential improvements for learning in multicultural aged care work environments were identified. These include more frequent and structured inter-peer learning (e.g. buddying), communication training (e.g. English language usage for both native and non-native speaking workers) and support for cross-cultural habitude (e.g. recognizing and adapting to cultural differences). Workplace learning in cross-cultural aged care environments is an area that is not extensively dealt with in the literature. This study addresses this gap and holds the potential to contribute practical insights to aged care and other diverse industries.

Keywords: cross-cultural learning, learning in aged care, migrant learning, workplace learning

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Authors: Orit Wolf

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Classical music performance is undergoing a profound transformation, marked by a confluence of technological advancements and evolving cultural dynamics. This academic paper explores the multifaceted changes and challenges faced by classical music performance, considering the impact of artificial intelligence (AI) along with other vital factors shaping this evolution. In the contemporary era, classical music is experiencing shifts in performance practices. This paper delves into these changes, emphasizing the need for adaptability within the classical music world. From repertoire selection and concert formats to artistic expression, performers and institutions navigate a delicate balance between tradition and innovation. We explore how these changes impact the authenticity and vitality of classical music performances. Furthermore, the influence of AI in the classical music concert world cannot be underestimated. AI technologies are making inroads into various aspects, from composition assistance to rehearsal and live performances. This paper examines the transformative effects of AI, considering how it enhances precision, adaptability, and creative exploration for musicians. We explore the implications for composers, performers, and the overall concert experience while addressing ethical concerns and creative opportunities. In addition to AI, there is the importance of cross-genre interactions within the classical music sphere. Mash-ups and collaborations with artists from diverse musical backgrounds are redefining the boundaries of classical music and creating works that resonate with a wider and more diverse audience. The benefits of cross-pollination in classical music seem crucial, offering a fresh perspective to listeners. As an active concert artist, Orit Wolf will share how the expectations of classical music audiences are evolving. Modern concertgoers seek not only exceptional musical performances but also immersive experiences that may involve technology, multimedia, and interactive elements. This paper examines how classical musicians and institutions are adapting to these changing expectations, using technology and innovative concert formats to deliver a unique and enriched experience to their audiences. As these changes and challenges reshape the classical music world, the need for a harmonious coexistence of tradition, technology, and innovation becomes evident. Musicians, composers, and institutions are striving to find a balance that ensures classical music remains relevant in a rapidly changing cultural landscape while maintaining the value it brings to compositions and audiences. This paper, therefore, aims to explore the evolving trends in classical music performance. It considers the influence of AI as one element within the broader context of change, highlighting the necessity of adaptability, cross-genre interactions, and a response to evolving audience expectations. By doing so, the classical music world can navigate this transformative period while preserving its timeless traditions and adding value to both performers and listeners. Orit Wolf, an international concert pianist, fulfils her vision to bring this music in new ways to mass audiences and will share her personal and professional experience as an artist who goes on stage and makes disruptive concerts.

Keywords: cross culture collaboration, music performance and ai, classical music in the digital age, classical concerts, innovation and technology, performance innovation, audience engagement in classical concerts

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Authors: Manish Kumar Asthana, Alicia Bundis, Zahn Xu, Braj Bhushan

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Despite ample cross-cultural studies with emotional valence, it is unclear if the emotions are universal or particular. Previous studies have shown that the individualist culture favors high-valence emotions compared to low-valence emotions. In contrast, collectivist culture favors low-valence emotions compared to high-valence emotions. In this current study, Chinese, Mexicans, and Indians reported valence and semantic-contingency. In total, 120 healthy participants were selected by ethnicity and matched for age and education. Each participant was presented 45 non-chromatic pictures, which were converted from chromatic pictures selected from International Affective Picture Database (IAPS) belonging to five-categories, i.e. (i) less pleasant, (ii) high pleasant, (iii) less unpleasant (iv) high unpleasant (v) neutral. The valence scores assigned to neutral, less-unpleasant, and high-pleasant pictures differed significantly between Chinese, Indian, and Mexicans participants. Significant effects demonstrated from the two-way ANOVAs, confirmed main significant effects of valence (F(1,117) = 24.83, p =0.000) and valence x country (F(2,117) = 2.74, p = 0.035). Significant effects emerging from the one-way ANOVAs were followed up through Bonferroni’s test post-hoc comparisons (p < 0.01). This analysis showed significant effect of neutral (F(2,119) = 6.50, p =0.002), less-unpleasant (F(2,119) = 13.79, p =0.000), and high-unpleasant (F(2,119) = 5.99, p =0.003). There were no significant differences in valence scores for the less-pleasant and more-pleasant between participants from three countries. The IAPS norms require modification for their appropriate application in individualist and collectivist cultures.

Keywords: cultural difference, affective processing, valence, non-chromatic, international affective picture system (IAPS)

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Authors: Tawanda Mushiri, Charles Mbohwa

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When an external load is applied to one of its ends, a pipe’s bends cross section tends to deform significantly both in and out of its end plane. This shell type behaviour characteristic of pipe bends and mainly due to their curves geometry accounts for their greater flexibility. This added flexibility is also accompanied by stressed and strains that are much higher than those present in a straight pipe. The primary goal of this research is to study the elastic-plastic behaviour of pipe bends under out of plane moment loading. It is also required to study the effects of changing the value of the pipe bend factor and the value of the internal pressure on that behaviour and to determine the value of the limit moments in each case. The results of these analyses are presented in the form of load deflection plots for each load case belonging to each model. From the load deflection curves, the limit moments of each case are obtained. The limit loads are then compared to those computed using some of the analytical and empirical equation available in the literature. The effects of modelling parameters are also studied. The results obtained from small displacement and large displacement analyses are compared and the effects of using a strain hardened material model are also investigated. To better understand the behaviour of pipe elbows under out of plane bending and internal pressure, it was deemed important to know how the cross section deforms and to study the distribution of stresses that cause it to deform in a particular manner. An elbow with pipe bend factor h=0.1 to h=1 is considered and the results of the detailed analysis are thereof examined.

Keywords: elasto-plastic, finite element analysis, pipe bends, simulation

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Authors: Aditya Sharma

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Profits earned from relative strength strategy of zero-cost portfolio i.e. taking long position in winner stocks and short position in loser stocks from recent past are termed as momentum profits. In recent times, there has been lot of controversy and concern about sources of momentum profits, since the existence of these profits acts as an evidence of earning non-normal returns from publicly available information directly contradicting Efficient Market Hypothesis. Literature review reveals conflicting theories and differing evidences on sources of momentum profits. This paper aims at re-examining the sources of momentum profits in Indian capital markets. The study focuses on assessing the effect of fundamental as well as behavioral sources in order to understand the role of investor behavior in stock returns and suggest (if any) improvements to existing behavioral asset pricing models. This Paper adopts calendar time methodology to calculate momentum profits for 6 different strategies with and without skipping a month between ranking and holding period. For each J/K strategy, under this methodology, at the beginning of each month t stocks are ranked on past j month’s average returns and sorted in descending order. Stocks in upper decile are termed winners and bottom decile as losers. After ranking long and short positions are taken in winner and loser stocks respectively and both portfolios are held for next k months, in such manner that at any given point of time we have K overlapping long and short portfolios each, ranked from t-1 month to t-K month. At the end of period, returns of both long and short portfolios are calculated by taking equally weighted average across all months. Long minus short returns (LMS) are momentum profits for each strategy. Post testing for momentum profits, to study the role market risk plays in momentum profits, CAPM and Fama French three factor model adjusted LMS returns are calculated. In the final phase of studying sources, decomposing methodology has been used for breaking up the profits into unconditional means, serial correlations, and cross-serial correlations. This methodology is unbiased, can be used with the decile-based methodology and helps to test the effect of behavioral and fundamental sources altogether. From all the analysis, it was found that momentum profits do exist in Indian capital markets with market risk playing little role in defining them. Also, it was observed that though momentum profits have multiple sources (risk, serial correlations, and cross-serial correlations), cross-serial correlations plays a major role in defining these profits. The study revealed that momentum profits do have multiple sources however, cross-serial correlations i.e. the effect of returns of other stocks play a major role. This means that in addition to studying the investors` reactions to the information of the same firm it is also important to study how they react to the information of other firms. The analysis confirms that investor behavior does play an important role in stock returns and incorporating both the aspects of investors’ reactions in behavioral asset pricing models help make then better.

Keywords: investor behavior, momentum effect, sources of momentum, stock returns

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Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: J. J. Lee, S. R. Sung, E. J. Yum, S. C. Kim, B. H. Hyun, M. Her, H. S. Lee

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Canine brucellosis is a critical problem in dogs leading to reproductive diseases which are mainly caused by Brucella canis. There are, nonetheless, not clear symptoms so that it may go unnoticed in most of the cases. Serodiagnosis for canine brucellosis has not been confirmed. Moreover, it has substantial difficulties due to broad cross-reactivity between the rough cell wall antigens of B. canis and heterospecific antibodies present in normal, uninfected dogs. Thus, this study was conducted to characterize the immunogenic proteins in cytoplasmic antigen (CPAg) of B. canis, which defined the antigenic sensitivity of the humoral antibody responses to B. canis-infected dogs. In analysis of B. canis CPAg, first, we extracted and purified the cytoplasmic proteins from cultured B. canis by hot-saline inactivation, ultrafiltration, sonication, and ultracentrifugation step by step according to the sonicated antigen extract method. For characterization of this antigen, we checked the sort and range of each protein on SDS-PAGE and verified the immunogenic proteins leading to reaction with antisera of B. canis-infected dogs. Selected immunodominant proteins were identified using MALDI-MS/MS. As a result, in an immunoproteomic assay, several polypeptides in CPAg on one or two-dimensional electrophoresis (DE) were specifically reacted to antisera from B. canis-infected dogs but not from non-infected dogs. The polypeptides with approximate 150, 80, 60, 52, 33, 26, 17, 15, 13, 11 kDa on 1-DE were dominantly recognized by antisera from B. canis-infected dogs. In the immunoblot profiles on 2-DE, ten immunodominant proteins in CPAg were detected with antisera of infected dogs between pI 3.5-6.5 at approximate 35 to 10 KDa, without any nonspecific reaction with sera in non-infected dogs. Ten immunodominant proteins identified by MALDI-MS/MS were identified as superoxide dismutase, bacteroferritin, amino acid ABC transporter substrate-binding protein, extracellular solute-binding protein family3, transaldolase, 26kDa periplasmic immunogenic protein, Rhizopine-binding protein, enoyl-CoA hydratase, arginase and type1 glyceraldehyde-3-phosphate dehydrogenase. Most of these proteins were determined by their cytoplasmic or periplasmic localization with metabolism and transporter functions. Consequently, this study discovered and identified the prominent immunogenic proteins in B. canis CPAg, highlighting that those antigenic proteins may accomplish a specific serodiagnosis for canine brucellosis. Furthermore, we will evaluate those immunodominant proteins for applying to the advanced diagnostic methods with high specificity and accuracy.

Keywords: Brucella canis, Canine brucellosis, cytoplasmic antigen, immunogenic proteins

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Authors: Lana Singleton

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Achieving a sufficient global solution to climate change seems elusive through disappointing climate agreements and lack of cooperation. However, is this reluctance of coordination deep rooted on a more individual, societal level within countries due to a fundamental lack of social and institutional trust? The risks of climate change are illustrious and widely accepted, yet responses on an individual level are also largely inadequate. This research looks to further investigate types of trust, risk perception of climate change, and their interaction to build a greater understanding of whether a social trap (Rothstein, 2005) – where an absence of trust can overwhelm an individuals’ risk perception and result in minimal action despite knowing the dangers of no action – exists and where it is more prevalent. Presence of the social trap will be analysed for willingness to act in favour of climate change mitigation as well as attitude (acceptance) of different types of renewable energy forms. Using probit models with cross-sectional survey data on four developed European countries (UK, France, Germany, and Norway), we find evidence of the social trap in the aggregated data model, which highlights the importance of social trust regarding willingness to act in favour of climate mitigation as there is a high probability of action regardless of risk perception of climate change when social trust is high. In contrast, the same is not true for renewables, as interactions were mainly insignificant, although there were interesting findings involving institutional trust, gender, and country specific results for particular renewables.

Keywords: climate risk, renewables, risk perception, social trap, trust, willingness to act

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Authors: Barbara Peric

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The study of acquiring a third and additional language has garnered significant focus within second language acquisition (SLA) research. Initially, it was commonly viewed as merely an extension of second language acquisition (SLA). However, in the last two decades, numerous researchers have emphasized the need to recognize the unique characteristics of third language acquisition (TLA). This recognition is crucial for understanding the intricate cognitive processes that arise from the interaction of more than two linguistic systems in the learner's mind. This study investigates cross-linguistic influences in the acquisition of Spanish as a fourth language by students who have Croatian as a first language (L1). English as a second language (L2), and Italian as a third language (L3). Observational data suggests that influence or transfer of linguistic elements can arise not only from one's native language (L1) but also from non-native languages. This implies that, for individuals proficient in multiple languages, the native language doesn't consistently hold a superior position. Instead, it should be examined alongside other potential sources of linguistic transfer. Earlier studies have demonstrated that high proficiency in a second language can significantly impact cross-linguistic influences when acquiring a third and additional language. Among the extensively examined factors, the typological relationship stands out as one of the most scrutinized variables. The goal of the present study was to explore whether language typology and formal similarity or proficiency in the second language had a more significant impact on L4 acquisition. Participants in this study were third-year undergraduate students at Rochester Institute of Technology’s subsidiary in Croatia (RIT Croatia). All the participants had exclusively Croatian as L1, English as L2, Italian as L3 and were learning Spanish as L4 at the time of the study. All the participants had a high level of proficiency in English and low level of proficiency in Italian. Based on the error analysis the findings indicate that for some types of lexical errors such as coinage, language typology had a more significant impact and Italian language was the preferred source of transfer despite the law proficiency in that language. For some other types of lexical errors, such as calques, second language proficiency had a more significant impact, and English language was the preferred source of transfer. On the other hand, Croatian, Italian, and Spanish are more similar in the area of morphology due to higher degree of inflection compared to English and the strongest influence of the Croatian language was precisely in the area of morphology. The results emphasize the need to consider linguistic resemblances between the native language (L1) and the third and additional language as well as the learners' proficiency in the second language when developing successful teaching strategies for acquiring the third and additional language. These conclusions add to the expanding knowledge in the realm of Second Language Acquisition (SLA) and offer practical insights for language educators aiming to enhance the effectiveness of learning experiences in acquiring a third and additional language.

Keywords: third and additional language acquisition, cross-linguistic influences, language proficiency, language typology

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Authors: Nelomi Anandagoda, Leanne J. Eveson

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During the COVID-19 pandemic, the surge in in-patient admissions across the medical directorate of a district general hospital necessitated the implementation of an incident rota. Conscious of the impact on training and professional development, the idea of developing a virtual teaching programme was conceived. The programme initially aimed to provide junior doctors, specialist nurses, pharmacists, and allied healthcare professionals from medical specialties and those re-deployed from other specialties (e.g., ophthalmology, GP, surgery, psychiatry) the knowledge and skills to manage the deteriorating patient with COVID-19. The programme was later developed to incorporate the general internal medicine curriculum. To facilitate continuing medical education whilst maintaining social distancing during this period, a virtual platform was used to deliver teaching to junior doctors across two large district general hospitals and two community hospitals. Teaching sessions were recorded and uploaded to a common platform, providing a resource for participants to catch up on and re-watch teaching sessions, making strides towards reducing discrimination against the professional development of less than full-time trainees. Thus, creating a learning environment, which is inclusive and accessible to adult learners in a self-directed manner. The negative impact of the pandemic on the well-being of healthcare professionals is well documented. To support the multi-disciplinary team, the virtual teaching programme evolved to included sessions on well-being, resilience, and work-life balance. Providing teaching for learners across the multi-disciplinary team (MDT) has been an eye-opening experience. By challenging the concept that learners should only be taught within their own peer groups, the authors have fostered a greater appreciation of the strengths of the MDT and showcased the immense wealth of expertise available within the trust. The inclusive nature of the teaching and the ease of joining a virtual teaching session has facilitated the dissemination of knowledge across the MDT, thus improving patient care on the frontline. The weekly teaching programme has been running for over eight months, with ongoing engagement, interest, and participation. As described above, the teaching programme has evolved to accommodate the needs of its learners. It has received excellent feedback with an appreciation of its inclusive, multi-disciplinary, and holistic nature. The COVID-19 pandemic provided a catalyst to rapidly develop novel methods of working and training and widened access/exposure to the virtual technologies available to large organisations. By merging pedagogical expertise and technology, the authors have created an effective online learning environment. Although the authors do not propose to replace face-to-face teaching altogether, this model of virtual multidisciplinary team, cross-site teaching has proven to be a great leveler. It has made high-quality teaching accessible to learners of different confidence levels, grades, specialties, and working patterns.

Keywords: cross-site, cross-speciality, inter-disciplinary, multidisciplinary, virtual teaching

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Authors: Cecilia Amponsem-Boateng, Timothy Bonney Oppongx, Weidong Zhang, Jonathan Boakye Yiadom, Lianke Wang, Kwabena Acheampong, Godfrey Opolot

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In Ghana, the management of hypertension in primary health care is a cost-effective way of addressing premature deaths from vascular disorders that include hypertension. There is little or no evidence of large-scale studies on the prevalence, risk, and knowledge/awareness of hypertension in students aged 12–22 years in Ghana. In a cross-sectional study, blood pressure, anthropometric indices, and knowledge/awareness assessment of students at second-cycle schools were recorded from 2018 to 2020 in three regions of Ghana. Multistage cluster sampling was used in selecting regions and the schools. Prevalence of prehypertension and hypertension was categorized by the Joint National Committee 7, where appropriate, chi-square, scatter plots, and correlations were used in showing associations. A total of 3165 students comprising 1776 (56.1%) females and 1389 (43.9%) males participated in this study within three regions of Ghana. The minimum age was 12 years and the maximum age was 22 years. The mean age was 17.21 with standard deviation (SD: 1.59) years. A 95% confidence interval was set for estimations and a P value < 0.05 was set as significant. The prevalence rate of overall hypertension was 19.91% and elevated (prehypertension) was 26.07%. Risk indicators such as weight, BMI, waist circumference, physical activity, and form of the diet were positively correlated with hypertension. Among Ghanaian students currently in second-cycle educational institutions, 19.91% were hypertensive and 26.07% were prehypertensive. This may indicate a probable high prevalence of hypertension in the future adult population if measures are not taken to curb the associated risks.

Keywords: hypertension, second-cycle schools, Ghana, youth

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Authors: Adekunle Adesina, Dorcas Adesina

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This Research investigated the influence of alcohol consumption on attention in Wister albino rats. It was designed to test whether or not alcohol consumption affected visual and auditory attention. The sample of this study comprise of 3males albino rats and 3 females albino rats which were randomly assigned to 3 (male/female each) groups, 1, 2 and 3. The first group which was experimental Group 1 received 4ml of alcohol ingestion with cannula twice daily (morning and evening). The second group which was experimental group 2 received 2ml of alcohol ingestion with cannula twice daily (morning and evening). Third group which was the control group only received water (placebo), all these happened within a period of 2 days. Three hypotheses were advanced and testedf in the study. Hypothesis 1 stated that there will be no significant difference between the response speed of albino rats that consume alcohol and those that consume water on visual attention using 5-CSRTT. This was confirmed (DF (2, 9) = 0.72, P <.05). Hypothesis 2 stated that albino rats who consumed alcohol will perform better than those who consume water on auditory accuracy using 5-CSRTT. This was also tested but not confirmed (DF (2, 9) = 2.10, P< .05). The third hypothesis which stated that female albino rats who consumed alcohol would not perform better than male albino rats who consumed alcohol on auditory accuracy using 5-CSRTT was tested and not confirmed. (DF (4) = 0.17, P < .05). Data was analyzed using one-way ANOVA and T-test for independent measures. It was therefore recommended that government policies and programs should be directed at reducing to the barest minimum the rate of alcohol consumption especially among males as it is detrimental to the human auditory attentional organ.

Keywords: alcohol, attention, influence, rats, Wistar

Procedia PDF Downloads 255

Authors: Andreas Lind, Aitor Iriondo Pascual, Dan Hogberg, Lars Hanson

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Factory setup lifecycles are most often described and prepared in CAD environments; the preparation is based on experience and inputs from several cross-disciplinary processes. Early in the factory setup preparation, a so-called block layout is created. The intention is to describe a high-level view of the intended factory setup and to claim area reservations and allocations. Factory areas are then blocked, i.e., targeted to be used for specific intended resources and processes, later redefined with detailed factory setup layouts. Each detailed layout is based on the block layout and inputs from cross-disciplinary preparation processes, such as manufacturing sequence, productivity, workers’ workplace requirements, and resource setup preparation. However, this activity is often not carried out with all variables considered simultaneously, which might entail a risk of sub-optimizing the detailed layout based on manual decisions. Therefore, this work aims to realize a digital method for assembly manufacturing layout planning where productivity, area utilization, and ergonomics can be considered simultaneously in a cross-disciplinary manner. The purpose of the digital method is to support engineers in finding optimized designs of detailed layouts for assembly manufacturing factories, thereby facilitating better decisions regarding setups of future factories. Input datasets are company-specific descriptions of required dimensions for specific area reservations, such as defined dimensions of a worker’s workplace, material façades, aisles, and the sequence to realize the product assembly manufacturing process. To test and iteratively develop the digital method, a demonstrator has been developed with an adaptation of existing software that simulates and proposes optimized designs of detailed layouts. Since the method is to consider productivity, ergonomics, area utilization, and constraints from the automatically generated block layout, a multi-objective optimization approach is utilized. In the demonstrator, the input data are sent to the simulation software industrial path solutions (IPS). Based on the input and Lua scripts, the IPS software generates a block layout in compliance with the company’s defined dimensions of area reservations. Communication is then established between the IPS and the software EPP (Ergonomics in Productivity Platform), including intended resource descriptions, assembly manufacturing process, and manikin (digital human) resources. Using multi-objective optimization approaches, the EPP software then calculates layout proposals that are sent iteratively and simulated and rendered in IPS, following the rules and regulations defined in the block layout as well as productivity and ergonomics constraints and objectives. The software demonstrator is promising. The software can handle several parameters to optimize the detailed layout simultaneously and can put forward several proposals. It can optimize multiple parameters or weight the parameters to fine-tune the optimal result of the detailed layout. The intention of the demonstrator is to make the preparation between cross-disciplinary silos transparent and achieve a common preparation of the assembly manufacturing factory setup, thereby facilitating better decisions.

Keywords: factory setup, multi-objective, optimization, simulation

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Authors: Gule Teri

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The effective validation of analytical methods forms a crucial component of pharmaceutical manufacturing. However, traditional validation techniques can occasionally fail to fully account for inherent variations within datasets, which may result in inconsistent outcomes. This deficiency in validation accuracy is particularly noticeable when quantifying low concentrations of active pharmaceutical ingredients (APIs), excipients, or impurities, introducing a risk to the reliability of the results and, subsequently, the safety and effectiveness of the pharmaceutical products. In response to this challenge, we introduce an enhanced, tolerance-based Design of Experiments (DoE) approach for the validation of analytical methods. This approach distinctly measures variability with reference to tolerance or design margins, enhancing the precision and trustworthiness of the results. This method provides a systematic, statistically grounded validation technique that improves the truthfulness of results. It offers an essential tool for industry professionals aiming to guarantee the accuracy of their measurements, particularly for low-concentration components. By incorporating this innovative method, pharmaceutical manufacturers can substantially advance their validation processes, subsequently improving the overall quality and safety of their products. This paper delves deeper into the development, application, and advantages of this tolerance-based DoE approach and demonstrates its effectiveness using High-Performance Liquid Chromatography (HPLC) data for verification. This paper also discusses the potential implications and future applications of this method in enhancing pharmaceutical manufacturing practices and outcomes.

Keywords: tolerance-based design, design of experiments, analytical method validation, quality control, biopharmaceutical manufacturing

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Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices.

Keywords: Industry 4.0., mass customization, production networks, virtual process-chain

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Authors: Mohammad Naeem Lakanwall, Jamshid Abdul-Ghafar

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Background: Endocrinopathies are a commonly occurring entity, particularly those of the thyroid gland; however, there is a lack of scientific literature from Afghanistan, a country with very limited health care facilities and resources. To our best knowledge, this is the first study aimed to describe the frequency of occurrence and factors associated with thyroid dysfunction in the Afghan population. The aim of this study is to estimate the frequency and to identify factors associated with thyroid dysfunction among individuals coming to a tertiary care facility in Kabul, Afghanistan. Methods: A cross-sectional study was conducted from July to Sep 2018 at the Department of Clinical Pathology, French Medical Institute for Mothers and Children (FMIC), Kabul, Afghanistan. Blood samples were obtained, serum TSH levels were analyzed, and the patients were divided into three diagnostic categories according to their serum TSH concentrations: 1) hypothyroidism, 2) hyperthyroidism, 3) normal. Results: A total of 127 individuals were included in the final analysis. The majority of study participants (77%) were females. A large number of the participants (92%) did not have a family history of thyroid dysfunction. 74% of the participants in the study had normal TSH levels classified as normal thyroid function, (14%) had lower TSH levels, and (12%) higher TSH levels, classified as hyper and hypothyroid, respectively. Conclusions: The findings of the current study showed a high frequency of thyroid dysfunctions from a single center. Further large-scale studies are needed to find out the prevalence and document this entity for better health outcomes in the country.

Keywords: Afghanistan, factors, frequency, hypothyroid, hyperthyroid, thyroid, thyroid stimulating hormone

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Authors: Ahmed El-Banbi, Ahmed El-Maraghi

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PVT properties are needed as input data in all reservoir, production, and surface facilities engineering calculations. In the absence of PVT reports on valid reservoir fluid samples, engineers rely on PVT correlations to generate the required PVT data. The accuracy of PVT correlations varies, and no correlation group has been found to provide accurate results for all oil types. The effect of inaccurate PVT data can be significant in engineering calculations and is well documented in the literature. Bubble point pressure can sometimes be obtained from external sources. In this paper, we show how to utilize the known bubble point pressure to improve the accuracy of calculated PVT properties from correlations. We conducted a systematic study using around 250 reservoir oil samples to quantify the effect of pre-knowledge of bubble point pressure. The samples spanned a wide range of oils, from very volatile oils to black oils and all the way to low-GOR oils. A method for shifting both undersaturated and saturated sections of the PVT properties curves to the correct bubble point is explained. Seven PVT correlation families were used in this study. All PVT properties (e.g., solution gas-oil ratio, formation volume factor, density, viscosity, and compressibility) were calculated using the correct bubble point pressure and the correlation estimated bubble point pressure. Comparisons between the calculated PVT properties and actual laboratory-measured values were made. It was found that pre-knowledge of bubble point pressure and using the shifting technique presented in the paper improved the correlation-estimated values by 10% to more than 30%. The most improvement was seen in the solution gas-oil ratio and formation volume factor.

Keywords: PVT data, PVT properties, PVT correlations, bubble point pressure

Procedia PDF Downloads 59

Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis

Procedia PDF Downloads 322

Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

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Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

Procedia PDF Downloads 68

Authors: Merav Ben Natan, Moran Makhoul Khuri, Haviel Hammer, Maya Yarkoni

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Background: Studies indicate that nursing students often rank hospice nursing among their least preferred career paths. Understanding factors influencing their intent to work in hospice care is essential for improving interest in this field. Aim: This study aimed to explore the relationship between nursing students' intention to pursue a career in hospice care and various factors, including their attitudes towards caring for dying patients, death anxiety, personal or professional experience with dying patients, and the type of nursing program they are enrolled in. Methods: In this cross-sectional study, 200 nursing students completed an online survey using the Frommelt Attitude Toward Care of the Dying Scale and the Turkish Death Anxiety Scale. The survey assessed students' intentions to work in hospice care and related variables. Results: Only 11% of participants expressed an interest in working in hospice care. Students in the accelerated program for non-nursing Bachelor of Arts graduates showed a higher intention to work in hospice care compared to those in the generic program (β = 0.27, P < .001). Conversely, completion of clinical experience in a medical ward was associated with a lower intention to work in hospice care (β = −0.21, P < .01). Conclusions: The findings suggest that nursing students in accelerated programs for non-nursing graduates are more likely to intend to work in hospice care. Enhanced experience and support are recommended to sustain their interest. Clinical experience in medical wards does not effectively substitute for hospice-specific clinical experience.

Keywords: hospice nursing, nursing students, death anxiety, career intentions

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Authors: Nadia K. Thalji

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In the timeless tapestry of human culture, theater, mythology, and psychology intersect to weave narratives that transcend temporal and spatial boundaries. For millennia, actors have stood as guardians of intuitive wisdom, their craft serving as a conduit for the collective unconscious. This paper embarks on a journey through the realms of creative expression, melding the insights of cross-cultural psychology with the mystical allure of serendipity and synchronicity. At the nexus of these disciplines lies the enigmatic process of active imagination, a gateway to the depths of the psyche elucidated by Jung. Within the hallowed confines of the black box theater at the Department of Performing Arts, UFRGS University in Brazil, this study unfolds. Over the span of four months, a cadre of artists embarked on a voyage of exploration, harnessing the powers of imagery, movement, sound, and dreams to birth a performance that resonated with the echoes of ancient wisdom. Drawing inspiration from the fabled Oracle of Delphi and the priestesses who once dwelled within its sacred precincts, the production delves into the liminal spaces where myth and history intertwine. Through the alchemy of storytelling, participants navigate the labyrinthine corridors of cultural memory, unraveling the threads that bind the past to the present. Central to this endeavor is the phenomenon of synchronicity, wherein seemingly disparate elements coalesce in a dance of cosmic resonance. Serendipity becomes a guiding force, leading actors and audience alike along unexpected pathways of discovery. As the boundaries between performer and spectator blur, the performance becomes a crucible wherein individual narratives merge to form a collective tapestry of shared experience. Yet, beneath the surface of spectacle lies a deeper truth: the exploration of the spiritual dimensions of artistic expression. Through intuitive inquiry and embodied practice, artists tap into reservoirs of insight that transcend rational comprehension. In the communion of minds and bodies, the stage becomes a sacred space wherein the numinous unfolds in all its ineffable glory. In essence, this paper serves as a testament to the transformative power of the creative act. Across cultures and epochs, the theater has served as a crucible wherein humanity grapples with the mysteries of existence. Through the lens of cross-cultural psychology, we glimpse the universal truths that underlie the myriad manifestations of human creativity. As we navigate the turbulent currents of modernity, the wisdom of the ancients beckons us to heed the call of the collective unconscious. In the synthesis of myth and meaning, we find solace amidst the chaos, forging connections that transcend the boundaries of time and space. And in the sacred precincts of the theater, we discover the eternal truth that art is, and always shall be, the soul's journey into the unknown.

Keywords: theater, mythology, cross-cultural, synchronicity, creativity, serendipity, spiritual

Procedia PDF Downloads 56

Authors: J. C. Hoyos, J. Zambrano Nájera

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Increasing urbanization has led to changes in the natural dynamics of watersheds, causing problems such as increases in volumes of runoff, peak flow rates, and flow rates so that the risk of storm flooding increases. Sewerage networks designed 30 – 40 years ago don’t account for these increases in flow volumes and velocities. Besides, Andean cities with high slopes worsen the problem because velocities are even higher not allowing sewerage network work and causing cities less resilient to landscape changes and climatic change. In Latin America, especially Colombia, this is a major problem because urban population at late XX century was more than 70% is in urban areas increasing approximately in 790% in 1940-1990 period. Thus, it becomes very important to study how changes in hydrological behavior affect hydraulic capacity of sewerage networks in Andean Urban Watersheds. This research aims to determine the impact of urbanization in high-sloped urban watersheds in its hydrology. To this end it will be used as study area experimental urban watershed named Palogrande-San Luis watershed, located in the city of Manizales, Colombia. Manizales is a city in central western Colombia, located in Colombian Central Mountain Range (part of Los Andes Mountains) with an abrupt topography (average altitude is 2.153 m). The climate in Manizales is quite uniform, but due to its high altitude it presents high precipitations (1.545 mm/year average) with high humidity (83% average). Behavior of the current sewerage network will be reviewed by the hydraulic model SWMM (Storm Water Management Model). Based on SWMM the hydrological response of urban watershed selected will be evaluated under the design storm with different frequencies in the region, such as drainage effect and water-logging, overland flow on roads, etc. Cartographic information was obtained from a Geographic Information System (GIS) thematic maps of the Institute of Environmental Studies of the Universidad Nacional de Colombia and the utility Aguas de Manizales S.A. Rainfall and streamflow data is obtained from 4 rain gages and 1 stream gages. This information will allow determining critical issues on drainage systems design in urban watershed with very high slopes, and which practices will be discarded o recommended.

Keywords: land cover changes, storm sewer system, urban hydrology, urban planning

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Authors: Toshifumi Hiramatsu, Satoshi Morita, Manuel Pencelli, Marta Niccolini, Matteo Ragaglia, Alfredo Argiolas

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Automation technologies for agriculture field are needed to promote labor-saving. One of the most relevant problems in automated agriculture is represented by controlling the robot along a predetermined path in presence of rough terrain or incline ground. Unfortunately, disturbances originating from interaction with the ground, such as slipping, make it quite difficult to achieve the required accuracy. In general, it is required to move within 5-10 cm accuracy with respect to the predetermined path. Moreover, lateral velocity caused by gravity on the incline field also affects slipping. In this paper, a path-tracking controller for tracked mobile robots moving on rough terrains of incline field such as vineyard is presented. The controller is composed of a disturbance observer and an adaptive controller based on the kinematic model of the robot. The disturbance observer measures the difference between the measured and the reference yaw rate and linear velocity in order to estimate slip. Then, the adaptive controller adapts “virtual” parameter of the kinematics model: Instantaneous Centers of Rotation (ICRs). Finally, target angular velocity reference is computed according to the adapted parameter. This solution allows estimating the effects of slip without making the model too complex. Finally, the effectiveness of the proposed solution is tested in a simulation environment.

Keywords: the agricultural robot, autonomous control, path-tracking control, tracked mobile robot

Procedia PDF Downloads 168