Search results for: statistical model

Authors: Marine Hascoet, Valentina Giaconi, Ludivine Jamain

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The aim of our study is to examine if the family socio-economic status (SES) has an influence on students’ academic achievement. We first make the hypothesis that the more their families have financial and social resources, the more students succeed at school. We second make the hypothesis that this family SES has also an impact on parents’ expectations about their children educational outcomes. Moreover, we want to study if that parents’ expectations play the role of mediator between parents’ socio-economic status and the student’ self-concept and academic outcome. We test this model with a longitudinal design thanks to the census-based assessment from the System of Measurement of the Quality of Education (SIMCE). The SIMCE tests aim to assess all the students attending to regular education in a defined level. The sample used in this study came from the SIMCE assessments done three times: in 4th, 8th and 11th grade during the years 2007, 2011 and 2014 respectively. It includes 156.619 students (75.084 boys and 81.535 girls) that had valid responses for the three years. The family socio-economic status was measured at the first assessment (in 4th grade). The parents’ educational expectations and the students’ self-concept were measured at the second assessment (in 8th grade). The achievement score was measured twice; once when children were in 4th grade and a second time when they were in 11th grade. To test our hypothesis, we have defined a structural equation model. We found that our model fit well the data (CFI = 0.96, TLI = 0.95, RMSEA = 0.05, SRMR = 0.05). Both family SES and prior achievements predict parents’ educational expectations and effect of SES is important in comparison to the other coefficients. These expectations predict students’ achievement three years later (with prior achievement controlled) but not their self-concept. Our model explains 51.9% of the achievement in the 11th grade. Our results confirm the importance of the parents’ expectations and the significant role of socio-economic status in students’ academic achievement in Chile.

Keywords: Chilean context, parent’s expectations, school achievement, self-concept, socio-economic status

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Authors: Godwin Chigozie Okpara

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This paper using standard GARCH, EGARCH, and TARCH models on day of the week return series (of 246 days) from the Nigerian Stock market estimated the model variants’ VaR. An asymmetric return distribution and fat-tail phenomenon in financial time series were considered by estimating the models with normal, student t and generalized error distributions. The analysis based on Akaike Information Criterion suggests that the EGARCH model with student t innovation distribution can furnish more accurate estimate of VaR. In the light of this, we apply the likelihood ratio tests of proportional failure rates to VaR derived from EGARCH model in order to determine the short and long positions VaR performances. The result shows that as alpha ranges from 0.05 to 0.005 for short positions, the failure rate significantly exceeds the prescribed quintiles while it however shows no significant difference between the failure rate and the prescribed quantiles for long positions. This suggests that investors and portfolio managers in the Nigeria stock market have long trading position or can buy assets with concern on when the asset prices will fall. Precisely, the VaR estimates for the long position range from -4.7% for 95 percent confidence level to -10.3% for 99.5 percent confidence level.

Keywords: downside risk, value-at-risk, failure rate, kupiec LR tests, GARCH models

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Djelloul Addad, Fatiha Belkhadem Mokhtari

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The objective of this work is to study the retention of methylene blue (MB) by biomass. The Biomass is characterized by X-ray diffraction (XRD), infrared absorption (IRTF). Results show that the biomass contains organic and mineral substances. The effect of certain physicochemical parameters on the adsorption of MB is studied (effect of the pH). This study shows that the increase in the initial concentration of MB leads to an increase in the adsorbed quantity. The adsorption efficiency of MB decreases with increasing biomass mass. The adsorption kinetics show that the adsorption is rapid, and the maximum amount is reached after 120 min of contact time. It is noted that the pH has no great influence on the adsorption. The isotherms are best modelled by the Langmuir model. The adsorption kinetics follow the pseudo-second-order model. The thermodynamic study of adsorption shows that the adsorption is spontaneous and exothermic.

Keywords: dyes, adsorption, biomass, methylene blue, langmuir

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Authors: Sameh Shahin, Nannang Arrys

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Optimizing pit slope stability and reducing strip ratio of a mining operation are two key tasks in geotechnical engineering. With a growing demand for minerals and an increasing cost associated with extraction, companies are constantly re-evaluating the viability of mineral deposits and challenging their geological understanding. Within Rio Tinto Iron Ore, the Structural Geology (SG) team investigate and collect critical data, such as point based orientations, mapping and geological inferences from adjacent pits to re-model deposits where previous interpretations have failed to account for structurally controlled slope failures. Utilizing innovative data collection methods and data-driven investigation, SG aims to address the root causes of slope instability. Committing to a resource grid drill campaign as the primary source of data collection will often bias data collection to a specific orientation and significantly reduce the capability to identify and qualify complexity. Consequently, these limitations make it difficult to construct a realistic and coherent structural model that identifies adverse structural domains. Without the consideration of complexity and the capability of capturing these structural domains, mining operations run the risk of inadequately designed slopes that may fail and potentially harm people. Regional structural trends have been considered in conjunction with surface and in-pit mapping data to model multi-batter fold structures that were absent from previous iterations of the structural model. The risk is evident in newly identified dip-slope and rock-mass controlled sectors of the geotechnical design rather than a ubiquitous dip-slope sector across the pit. The reward is two-fold: 1) providing sectors of rock-mass controlled design in previously interpreted structurally controlled domains and 2) the opportunity to optimize the slope angle for mineral recovery and reduced strip ratio. Furthermore, a resulting high confidence model with structures and geometries that can account for historic slope instabilities in structurally controlled domains where design assumptions failed.

Keywords: structural geology, geotechnical design, optimization, slope stability, risk mitigation

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Authors: Noam Markovitz

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People with physical disabilities constitute a very large and simultaneously a diverse group of general population, as the term physical disabilities is extensive and covers a wide range of disabilities. Therefore, individuals with physical disabilities are often faced with a new, threatening and stressful reality leading possibly to a multi-crisis in their lives due to the great changes they experience in somatic, socio-economic, occupational and psychological level. The current study seeks to advance understanding of the complex adaptation to physical disabilities by expanding the dynamic-adaptational model of the pursuit of happiness in a hostile world with a new conception of physical self-integrity. Physical self-integrity incorporates an objective dimension, namely physical self-functioning (PSF), and a subjective dimension, namely physical self-concept (PSC). Both of these dimensions constitute an experience of wholeness in the individual’s identification with her or his physical body. The model guiding this work is dialectical in nature and depicts two systems in the individual’s sense of happiness: subjective well-being (SWB) and meaning in life (MIL). Both systems serve as self-adaptive agents that moderate the complementary system of the hostile-world scenario (HWS), which integrates one’s perceived threats to one’s integrity. Thus, in situations of increased HWS, the moderation may take a form of joint activity in which SWB and MIL are amplified or a form of compensation in which one system produces a stronger effect while the other system produces a weaker effect. The current study investigated PSC in relations to SWB and MIL through pleasantness and meanings that are physically or metaphorically grounded in one’s body. In parallel, PSC also relates to HWS by activating representations of inappropriateness, deformation and vulnerability. In view of possibly dialectical positions of opposing and complementary forces within the current model, the current field study that aims to explore PSC as appearing in an independent, cross-sectional, design addressing the model’s variables in a focal group of people with physical disabilities. This study delineated the participation of the PSC in the adaptational functions of SWB and MIL vis-à-vis HWS-related life adversities. The findings showed that PSC could fully complement the main variables of the pursuit of happiness in a hostile world model. The assumed dialectics in the form of a stronger relationship between SWB and MIL in the face of physical disabilities was not supported. However, it was found that when HWS increased, PSC and MIL were strongly linked, whereas PSC and SWB were weakly linked. This highlights the compensatory role of MIL. From a conceptual viewpoint, the current investigation may clarify the role of PSC as an adaptational agent of the individual’s positive health in complementary senses of bodily wholeness. Methodologically, the advantage of the current investigation is the application of an integrative, model-based approach within a specially focused design with a particular relevance to PSC. Moreover, from an applicative viewpoint, the current investigation may suggest how an innovative model may be translated to therapeutic interventions used by clinicians, counselors and practitioners in improving wellness and psychological well-being, particularly among people with physical disabilities.

Keywords: older adults, physical disabilities, physical self-concept, pursuit of happiness in a hostile-world

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Authors: Preeyaphorn Kosa, Thanutch Sukwimolseree

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The climate change is a main parameter which affects the element of hydrological cycle especially runoff. Then, the purpose of this study is to determine the impact of the climate change on surface runoff using land use map on 2008 and daily weather data during January 1, 1979 to September 30, 2010 for SWAT model. SWAT continuously simulate time model and operates on a daily time step at basin scale. The results present that the effect of temperature change cannot be clearly presented on the change of runoff while the rainfall, relative humidity and evaporation are the parameters for the considering of runoff change. If there are the increasing of rainfall and relative humidity, there is also the increasing of runoff. On the other hand, if there is the increasing of evaporation, there is the decreasing of runoff.

Keywords: climate, runoff, SWAT, upper Mun River basin

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Authors: Maria Reichenber Arcilla

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Objective: To determine the risk factors for maternal and neonatal complications associated with operative vaginal deliveries. Methods: A retrospective chart review of 435 patients who underwent operative vaginal deliveries was done. Patient profiles – age, parity, AOG, duration of labor – and outcomes – birthweight, maternal and neonatal complications - were tabulated and multivariable analysis and logistic regression were performed using SPSS® Statistics Base. Results and Conclusion: There was no significant difference in the incidence of maternal and neonatal complications between those that underwent vacuum and forceps extraction. Among the variables analysed, parity and duration of labor reached statistical significance. The odds of maternal complications were 3 times higher among nulliparous patients. Neonatal complications were seen in those whose labor lasted more than 9 hours.

Keywords: operative vaginal deliveries, maternal, neonatal, morbidity

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Authors: Miriam Borchardt, Agata M. Ritter, Macaliston G. da Silva, Mauricio N. de Carvalho, Giancarlo M. Pereira

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This paper aims to analyze the barriers faced by social enterprises and based on that to propose a social business model framework that helps them to leverage their businesses and the social value delivered. A business model for social enterprises should amplify the value perception including social value for the beneficiaries while generating enough profit to escalate the business. Most of the social value beneficiaries are people from the base of the economic pyramid (BOP) or the ones that have specific needs. Because of this, products and services should be affordable to consumers while solving social needs of the beneficiaries. Developing products and services with social value require tie relationship among the social enterprises and universities, public institutions, accelerators, and investors. Despite being focused on social value and contributing to the beneficiaries’ quality of life as well as contributing to the governments that cannot properly guarantee public services and infrastructure to the BOP, many barriers are faced by the social enterprises to escalate their businesses. This is a work in process and five micro- and small-sized social enterprises in Brazil have been studied: (i) one has developed a kit for cervical uterine cancer detection to allow the BOP women to collect their own material and deliver to a laboratory for U$1,00; (ii) other has developed special products without lactose and it is about 70% cheaper than the traditional brands in the market; (iii) the third has developed prosthesis and orthosis to surplus needs that health public system have not done efficiently; (iv) the fourth has produced and commercialized menstrual panties aiming to reduce the consumption of dischargeable ones while saving money to the consumers; (v) the fifth develops and commercializes clothes from fabric wastes in a partnership with BOP artisans. The preliminary results indicate that the main barriers are related to the public system to recognize these products as public money that could be saved if they bought products from these enterprises instead of the multinational pharmaceutical companies, to the traditional distribution system (e.g. pharmacies) that avoid these products because of the low or non-existing profit, to the difficulty buying raw material in small quantities, to leverage investment by the investors, to cultural barriers and taboos. Interesting strategies to reduce the costs have been observed: some enterprises have focused on simplifying products, others have invested in partnerships with local producers and have developed their machines focusing on process efficiency to leverage investment by the investors.

Keywords: base of the pyramid, business model, social business, social business model, social enterprises

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Authors: Chandan Jha, Amit Sachan, Arnab Adhikari, Sayantan Kundu

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The purpose of this study is to evaluate the performance of Higher Education Institutions (HEIs) of India and examine the impact of urbanization on the performance of HEIs. In this study, the Data Envelopment Analysis (DEA) has been used, and the authors have collected the required data related to performance measures from the National Institutional Ranking Framework web portal. In this study, the authors have evaluated the performance of HEIs by using two different DEA models. In the first model, geographic locations of the institutes have been categorized into two categories, i.e., Urban Vs. Non-Urban. However, in the second model, these geographic locations have been classified into three categories, i.e., Urban, Semi-Urban, Non-Urban. The findings of this study provide several insights related to the degree of urbanization and the performance of HEIs.

Keywords: DEA, higher education, performance evaluation, urbanization

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Authors: Moulana Mohammed

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Topic models are widely used in building clusters of documents for more than a decade, yet problems occurring in choosing optimal number of topics. The main problem is the lack of a stable metric of the quality of topics obtained during the construction of topic models. The authors analyzed from previous works, most of the models used in determining the number of topics are non-parametric and quality of topics determined by using perplexity and coherence measures and concluded that they are not applicable in solving this problem. In this paper, we used the parametric method, which is an extension of the traditional topic model with visual access tendency for visualization of the number of topics (clusters) to complement clustering and to choose optimal number of topics based on results of cluster validity indices. Developed hybrid topic models are demonstrated with different Twitter datasets on various topics in obtaining the optimal number of topics and in measuring the quality of clusters. The experimental results showed that the Visual Non-negative Matrix Factorization (VNMF) topic model performs well in determining the optimal number of topics with interactive visualization and in performance measure of the quality of clusters with validity indices.

Keywords: interactive visualization, visual mon-negative matrix factorization model, optimal number of topics, cluster validity indices, Twitter data clustering

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Authors: N. Nivedita, S. Durbha

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Critical Infrastructure (CI) consists of services and technological networks such as healthcare, transport, water supply, electricity supply, information technology etc. These systems are necessary for the well-being and to maintain effective functioning of society. Critical Infrastructures can be represented as nodes in a network where they are connected through a set of links depicting the logical relationship among them; these nodes are interdependent on each other and interact with each at other at various levels, such that the state of each infrastructure influences or is correlated to the state of another. Disruption in the service of one infrastructure nodes of the network during a disaster would lead to cascading and escalating disruptions across other infrastructures nodes in the network. The operation of Healthcare Infrastructure is one such Critical Infrastructure that depends upon a complex interdependent network of other Critical Infrastructure, and during disasters it is very vital for the Healthcare Infrastructure to be protected, accessible and prepared for a mass casualty. To reduce the consequences of a disaster on the Critical Infrastructure and to ensure a resilient Critical Health Infrastructure network, knowledge, understanding, modeling, and analyzing the inter-dependencies between the infrastructures is required. The paper would present inter-dependencies related to Healthcare Critical Infrastructure based on Hierarchical Coloured Petri Nets modeling approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The model properties are being analyzed for the various state changes which occur when there is a disruption or damage to any of the Critical Infrastructure. The failure probabilities for the failure risk of interconnected systems are calculated by deriving a reachability graph, which is later mapped to a Markov chain. By analytically solving and analyzing the Markov chain, the overall vulnerability of the Healthcare CI HCPN model is demonstrated. The entire model would be integrated with Geographic information-based decision support system to visualize the dynamic behavior of the interdependency of the Healthcare and related CI network in a geographically based environment.

Keywords: critical infrastructure interdependency, hierarchical coloured petrinet, healthcare critical infrastructure, Petri Nets, Markov chain

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Authors: Sarah Mueller-Saegebrecht, André Brendler

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Business model innovation (BMI) as an intentional change of an existing business model (BM) or the design of a new BM is essential to a firm's development in dynamic markets. The relevance of BMI is also evident in the ongoing COVID-19 pandemic, in which start-ups, in particular, are affected by limited access to resources. However, first studies also show that they react faster to the pandemic than established firms. A strategy to successfully handle such threatening dynamic changes represents BMI. Entrepreneurship literature shows how and when firms should utilize BMI in times of crisis and which barriers one can expect during the BMI process. Nevertheless, research merging BMI barriers and crises is still underexplored. Specifically, further knowledge about antecedents and the effect of moderators on the BMI process is necessary for advancing BMI research. The addressed research gap of this study is two-folded: First, foundations to the subject on how different crises impact BM change intention exist, yet their analysis lacks the inclusion of barriers. Especially, entrepreneurship literature lacks knowledge about the individual perception of BMI barriers, which is essential to predict managerial reactions. Moreover, internal BMI barriers have been the focal point of current research, while external BMI barriers remain virtually understudied. Second, to date, BMI research is based on qualitative methodologies. Thus, a lack of quantitative work can specify and confirm these qualitative findings. By focusing on the crisis context, this study contributes to BMI literature by offering a first quantitative attempt to embed BMI barriers into a structural equation model. It measures managers' perception of BMI development and implementation barriers in the BMI process, asking the following research question: How does a manager's perception of BMI barriers influence BMI development and implementation in times of crisis? Two distinct research streams in economic literature explain how individuals react when perceiving a threat. "Prospect Theory" claims that managers demonstrate risk-seeking tendencies when facing a potential loss, and opposing "Threat-Rigidity Theory" suggests that managers demonstrate risk-averse behavior when facing a potential loss. This study quantitively tests which theory can best predict managers' BM reaction to a perceived crisis. Out of three in-depth interviews in the German chemical industry, 60 past BMIs were identified. The participating start-up managers gave insights into their start-up's strategic and operational functioning. After, each interviewee described crises that had already affected their BM. The participants explained how they conducted BMI to overcome these crises, which development and implementation barriers they faced, and how severe they perceived them, assessed on a 5-point Likert scale. In contrast to current research, results reveal that a higher perceived threat level of a crisis harms BM experimentation. Managers seem to conduct less BMI in times of crisis, whereby BMI development barriers dampen this relation. The structural equation model unveils a mediating role of BMI implementation barriers on the link between the intention to change a BM and the concrete BMI implementation. In conclusion, this study confirms the threat-rigidity theory.

Keywords: barrier perception, business model innovation, business model innovation barriers, crises, prospect theory, start-ups, structural equation model, threat-rigidity theory

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Authors: Taleb Lotfi, Benarbia Maheidine, Allam Hamza, Boutira Fatima, Boukerche Abdelbaki

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Introduction and purpose of the study: This is a retrospective single-center study with an analytical aim to determine the prognostic factors for relapse in patients treated with radiotherapy after total laryngectomy with lymph node dissection for laryngeal cancer at the Emir Abdelkader cancer center in Oran (Algeria). Material and methods: During the study period from January 2014 to December 2018, eighty-nine patients (n=89) with squamous cell carcinoma of the larynx were treated with postoperative radiotherapy. Relapse-free survival was studied in the univariate analysis according to pre-treatment criteria using Kaplan-Meier survival curves. We performed a univariate analysis to identify relapse factors. Statistically significant factors have been studied in the multifactorial analysis according to the Cox model. Results and statistical analysis: The average age was 62.7 years (40-86 years). It was a squamous cell carcinoma in all cases. Postoperatively, the tumor was classified as pT3 and pT4 in 93.3% of patients. Histological lymph node involvement was found in 36 cases (40.4%), with capsule rupture in 39% of cases, while the limits of surgical excision were microscopically infiltrated in 11 patients (12.3%). Chemotherapy concomitant with radiotherapy was used in 67.4% of patients. With a median follow-up of 57 months (23 to 104 months), the probabilities of relapse-free survival and five-year overall survival are 71.2% and 72.4%, respectively. The factors correlated with a high risk of relapse were locally advanced tumor stage pT4 (p=0.001), tumor site in case of subglottic extension (p=0.0003), infiltrated surgical limits R1 (p=0.001), l lymph node involvement (p=0.002), particularly in the event of lymph node capsular rupture (p=0.0003) as well as the time between surgery and adjuvant radiotherapy (p=0.001). However, in the subgroup analysis, the major prognostic factors for disease-free survival were subglottic tumor extension (p=0.001) and time from surgery to adjuvant radiotherapy (p=0.005). Conclusion: Combined surgery and postoperative radiation therapy are effective treatment modalities in the management of laryngeal cancer. Close cooperation of the entire cervicofacial oncology team is essential, expressed during a multidisciplinary consultation meeting, with the need to respect the time between surgery and radiotherapy.

Keywords: laryngeal cancer, laryngectomy, postoperative radiotherapy, survival

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Authors: Daneal Rorke, Gueguim Kana

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The shift towards renewable energy sources for biofuel production has received increasing attention. However, the use and pre-treatment of lignocellulosic material are inundated with the generation of fermentation inhibitors which severely impact the feasibility of bioprocesses. This study reports the profiling of all volatile compounds generated during microwave assisted chemical pre-treatment of sorghum leaves. Furthermore, the optimization of reducing sugar (RS) from microwave assisted acid pre-treatment of sorghum leaves was assessed and gave a coefficient of determination (R2) of 0.76, producing an optimal RS yield of 2.74 g FS/g substrate. The development of an intelligent model to predict volatile compound fractions gave R2 values of up to 0.93 for 21 volatile compounds. Sensitivity analysis revealed that furfural and phenol exhibited high sensitivity to acid concentration, alkali concentration and S:L ratio, while phenol showed high sensitivity to microwave duration and intensity as well. These findings illustrate the potential of using an intelligent model to predict the volatile compound fraction profile of compounds generated during pre-treatment of sorghum leaves in order to establish a more robust and efficient pre-treatment regime for biofuel production.

Keywords: artificial neural networks, fermentation inhibitors, lignocellulosic pre-treatment, sorghum leaves

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Authors: Rahul Jain, Pradhir Parmar, Dhruvesh Patel

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Planning and drawing are the important aspects of civil engineering. For testing theories about spatial location and interaction between land uses and related activities the computer based solution of urban models are used. The planner’s primary interest is in creation of 3D models of building and to obtain the terrain surface so that he can do urban morphological mappings, virtual reality, disaster management, fly through generation, visualization etc. 3D city models have a variety of applications in urban studies. Gujarat International Finance Tec-City (GIFT) is an ongoing construction site between Ahmedabad and Gandhinagar, Gujarat, India. It will be built on 3590000 m2 having a geographical coordinates of North Latitude 23°9’5’’N to 23°10’55’’ and East Longitude 72°42’2’’E to 72°42’16’’E. Therefore to develop 3D city models of GIFT city, the base map of the city is collected from GIFT office. Differential Geographical Positioning System (DGPS) is used to collect the Ground Control Points (GCP) from the field. The GCP points are used for the registration of base map in QGIS. The registered map is projected in WGS 84/UTM zone 43N grid and digitized with the help of various shapefile tools in QGIS. The approximate height of the buildings that are going to build is collected from the GIFT office and placed on the attribute table of each layer created using shapefile tools. The Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global (30 m X 30 m) grid data is used to generate the terrain of GIFT city. The Google Satellite Map is used to place on the background to get the exact location of the GIFT city. Various plugins and tools in QGIS are used to convert the raster layer of the base map of GIFT city into 3D model. The fly through tool is used for capturing and viewing the entire area in 3D of the city. This paper discusses all techniques and their usefulness in 3D city model creation from the GCP, base map, SRTM and QGIS.

Keywords: 3D model, DGPS, GIFT City, QGIS, SRTM

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Authors: Elahe Sarfi, Esmat Noroozi, Farhad Hosseinzadeh Lotfi

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One of the important issues in Data Envelopment Analysis is the ranking of Decision Making Units. In this paper, a method for ranking DMUs is presented through which the weights related to efficient units should be chosen in a way that the other units preserve a certain percentage of their efficiency with the mentioned weights. To this end, a model is presented for ranking DMUs on the base of their superefficiency by considering the mentioned restrictions related to weights. This percentage can be determined by decision Maker. If the specific percentage is unsuitable, we can find a suitable and feasible one for ranking DMUs accordingly. Furthermore, the presented model is capable of ranking all of the efficient units including nonextreme efficient ones. Finally, the presented models are utilized for two sets of data and related results are reported.

Keywords: data envelopment analysis, efficiency, ranking, weight

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Authors: Ivana Yuniarti, Iwan Ridwansyah

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This paper delivers a review of various methodologies for habitat assessment and a proposed methodology to assess an endemic fish species habitat in Lake Maninjau, Indonesia as a part of a Ph.D. project. This application is mainly aimed to assess the trade-off between the economic value of aquaculture and the fisheries. The proposed methodology is a generalized linear model (GLM) combined with GIS to assess presence-absence data or habitat suitability index (HSI) combined with the analytical hierarchy process (AHP). Further, a cost of habitat replacement approach is planned to be used to calculate the habitat value as well as its trade-off with the economic value of aquaculture. The result of the study is expected to be a scientific consideration in local decision making and to provide a reference for other areas in the country.

Keywords: AHP, habitat, GLM, HSI, Maninjau

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Authors: Al Omari Mohammed Ahmed

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This paper focuses on Maximum Likelihood Estimator with Covariate. Covariates are incorporated into the Weibull model. Under this regression model with regards to maximum likelihood estimator, the parameters of the covariate, shape parameter, survival function and hazard rate of the Weibull regression distribution with right censored data are estimated. The mean square error (MSE) and absolute bias are used to compare the performance of Weibull regression distribution. For the simulation comparison, the study used various sample sizes and several specific values of the Weibull shape parameter.

Keywords: weibull regression distribution, maximum likelihood estimator, survival function, hazard rate, right censoring

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Authors: M. O. Durojaye, J. T. Agee

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This paper is on the one-dimensional, positive temperature coefficient (PTC) thermistor model with a hyperbolic tangent function approximation for the electrical conductivity. The method of asymptotic expansion was adopted to obtain the steady state solution and the unsteady-state response was obtained using the method of lines (MOL) which is a well-established numerical technique. The approach is to reduce the partial differential equation to a vector system of ordinary differential equations and solve numerically. Our analysis shows that the hyperbolic tangent approximation introduced is well suitable for the electrical conductivity. Numerical solutions obtained also exhibit correct physical characteristics of the thermistor and are in good agreement with the exact steady state solutions.

Keywords: electrical conductivity, hyperbolic tangent function, PTC thermistor, method of lines

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Authors: Osama A. Terfas, Abdelhakim A. Hameda, Abdusalam A. Alktiwi

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An investigation on ductile crack growth of shallow semi-elliptical surface cracks with a/w=0.2, a/c=0.33 under bending was carried out, where a is the crack depth, w is the plate thickness and c is the crack length at surface. Finite element analysis and experiments were modelling and the crack growth model were verified with experimental data. The results showed that the initial crack shape was no longer maintained as the crack developed under ductile tearing. The maximum growth at the deepest point at early stages was stopped when the crack depth reached half thickness and growth occurred beneath surface. Excellent agreement in the crack shape patterns was observed between the experiments and the crack growth model.

Keywords: crack growth, ductile tearing, mean stress, surface cracks

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Authors: M. Khazam, M. Altawil, A. Eljabri

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Fluid properties in states near a vapor-liquid critical region are the most difficult to measure and to predict with EoS models. The principal model difficulty is that near-critical property variations do not follow the same mathematics as at conditions far away from the critical region. Libyan NC98 field in Sirte basin is a typical example of near critical fluid characterized by high initial condensate gas ratio (CGR) greater than 160 bbl/MMscf and maximum liquid drop-out of 25%. The objective of this paper is to model NC98 phase behavior with the proper selection of EoS parameters and also to model reservoir depletion versus gas cycling option using measured PVT data and EoS Models. The outcomes of our study revealed that, for accurate gas and condensate recovery forecast during depletion, the most important PVT data to match are the gas phase Z-factor and C7+ fraction as functions of pressure. Reasonable match, within -3% error, was achieved for ultimate condensate recovery at abandonment pressure of 1500 psia. The smooth transition from gas-condensate to volatile oil was fairly simulated by the tuned PR-EoS. The predicted GOC was approximately at 14,380 ftss. The optimum gas cycling scheme, in order to maximize condensate recovery, should not be performed at pressures less than 5700 psia. The contribution of condensate vaporization for such field is marginal, within 8% to 14%, compared to gas-gas miscible displacement. Therefore, it is always recommended, if gas recycle scheme to be considered for this field, to start it at the early stage of field development.

Keywords: EoS models, gas-condensate, gas cycling, near critical fluid

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Authors: Mladen Milicevic

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This presentation will address how the statistical analysis of digitized popular music influences the music creation and emotionally manipulates consumers.Furthermore, it will deal with semiological aspect of uniformization of musical taste in order to predict the potential revenues generated by popular music sales. In the USA, we live in an age where most of the popular music (i.e. music that generates substantial revenue) has been digitized. It is safe to say that almost everything that was produced in last 10 years is already digitized (either available on iTunes, Spotify, YouTube, or some other platform). Depending on marketing viability and its potential to generate additional revenue most of the “older” music is still being digitized. Once the music gets turned into a digital audio file,it can be computer-analyzed in all kinds of respects, and the similar goes for the lyrics because they also exist as a digital text file, to which any kin of N Capture-kind of analysis may be applied. So, by employing statistical examination of different popular music metrics such as tempo, form, pronouns, introduction length, song length, archetypes, subject matter,and repetition of title, the commercial result may be predicted. Polyphonic HMI (Human Media Interface) introduced the concept of the hit song science computer program in 2003.The company asserted that machine learning could create a music profile to predict hit songs from its audio features Thus,it has been established that a successful pop song must include: 100 bpm or more;an 8 second intro;use the pronoun 'you' within 20 seconds of the start of the song; hit the bridge middle 8 between 2 minutes and 2 minutes 30 seconds; average 7 repetitions of the title; create some expectations and fill that expectation in the title. For the country song: 100 bpm or less for a male artist; 14-second intro; uses the pronoun 'you' within the first 20 seconds of the intro; has a bridge middle 8 between 2 minutes and 2 minutes 30 seconds; has 7 repetitions of title; creates an expectation,fulfills it in 60 seconds.This approach to commercial popular music minimizes the human influence when it comes to which “artist” a record label is going to sign and market. Twenty years ago,music experts in the A&R (Artists and Repertoire) departments of the record labels were making personal aesthetic judgments based on their extensive experience in the music industry. Now, the computer music analyzing programs, are replacing them in an attempt to minimize investment risk of the panicking record labels, in an environment where nobody can predict the future of the recording industry.The impact on the consumers taste through the narrow bottleneck of the above mentioned music selection by the record labels,created some very peculiar effects not only on the taste of popular music consumers, but also the creative chops of the music artists as well. What is the meaning of this semiological shift is the main focus of this research and paper presentation.

Keywords: music, semiology, commercial, taste

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Authors: Rabia Aslam

Abstract:

Overwhelming evidence from all around the world suggests that high-quality teacher professional development facilitates the improvement of teaching practices which in turn could improve student learning outcomes. The new Continuous Professional Development (CPD) model for primary school teachers in Punjab uses a blended approach in which pedagogical content knowledge is delivered through technology (high-quality instructional videos and lesson plans delivered to school tablets or mobile phones) with face-to-face support by Assistant Education Officers (AEOs). The model also develops Communities of Practice operationalized through formal meetings led by the AEOs and informal interactions through social media groups to provide opportunities for teachers to engage with each other and share their ideas, reflect on learning, and come up with solutions to issues they experience. Using Kirkpatrick’s 4 levels of the learning evaluation model, this paper investigates how school tablets and teacher mobile phones may act as transformational cultural tools to potentially expand perceptions and access to teaching and learning resources and explore some of the affordances of social media (Facebook, WhatsApp groups) in learning in an informal context. The results will be used to inform policy-level decisions on what shape could CPD of all teachers take in the context of a developing country like Pakistan.

Keywords: CPD, teaching & learning, blended learning, learning technologies

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Authors: Stephen E. Cross, Donald P. McConnell

Abstract:

In the past decade, market pressures and decreasing U.S. federal budgets for science and technology have led to a fundamental change in expectations for corporate investments in innovation. The trend to significant, sustained corporate research collaboration with major academic centres has called for rethinking the balance between academic and corporate roles in these relationships. The Georgia Institute of Technology has developed a system-focused strategy for transformational research focused on grand challenges in areas of importance both to faculty and to industry collaborators. A model of an innovation ecosystem is used to guide both research and university-industry collaboration. The paper describes the strategy, the model, and the results to date including the benefits both to university research and industry collaboration. Key lessons learned are presented based on this experience.

Keywords: ecosystem, industry collaboration, innovation, research strategy

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Authors: Ginger Egberts, Marianne Schaaphok, Fred Vermolen, Paul van Zuijlen

Abstract:

A few years ago, a promising morphoelastic model was developed for the simulation of contraction formation after burn injuries. Contraction can lead to a serious reduction in physical mobility, like a reduction in the range-of-motion of joints. If this is the case in a healing burn wound, then this is referred to as a contracture that needs medical intervention. The morphoelastic model consists of a set of partial differential equations describing both a chemical part and a mechanical part in dermal wound healing. These equations are solved with the numerical finite element method (FEM). In this method, many calculations are required on each of the chosen elements. In general, the more elements, the more accurate the solution. However, the number of elements increases rapidly if simulations are performed in 2D and 3D. In that case, it not only takes longer before a prediction is available, the computation also becomes more expensive. It is therefore important to investigate alternative possibilities to generate the same results, based on the input parameters only. In this study, a surrogate neural network has been designed to mimic the results of the one-dimensional morphoelastic model. The neural network generates predictions quickly, is easy to implement, and there is freedom in the choice of input and output. Because a neural network requires extensive training and a data set, it is ideal that the one-dimensional FEM code generates output quickly. These feed-forward-type neural network results are very promising. Not only can the network give faster predictions, but it also has a performance of over 99%. It reports on the relative surface area of the wound/scar, the total strain energy density, and the evolutions of the densities of the chemicals and mechanics. It is, therefore, interesting to investigate the applicability of a neural network for the two- and three-dimensional morphoelastic model for contraction after burn injuries.

Keywords: biomechanics, burns, feasibility, feed-forward NN, morphoelasticity, neural network, relative surface area wound

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Authors: Guebli Abdelkader, Zerf Mohammed, Mekkades Moulay Idriss, BenGoua Ali, Atouti Nouredinne, Habchi Nawel

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The paper aims to show the influence of angles in the results of triple jump. Whereas our background confirms that a series of motions are characterized by complex angles in the properties phase (hop, step, and jump) as a combination of the pushed phase on ultimate phases in the result. For the purpose, our results are obtained from the National Athletics Championship 2013, which was filmed and analysis by the software kinovea. Based on the statistical analysis we confirm: there is a positive relationship between angle of the leg, hip angle, angle of the trunk in the collision during (hop, step, and jump), and there is a negative correlation to the angle of the knee relationship in a collision during.

Keywords: kinematics variables, the triple jump, the finale results, digital achievement

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Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

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Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations

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Authors: Mahdieh Jajroudi

Abstract:

Developing a pharmacokinetic model for the neuroendocrine tumors therapy agent 177Lu-DOTATATE in nude mice bearing AR42J rat pancreatic tumor to investigate and evaluate the behavior of the complex was the main purpose of this study. The utilization of compartmental analysis permits the mathematical differencing of tissues and organs to become acquainted with the concentration of activity in each fraction of interest. Biodistribution studies are onerous and troublesome to perform in humans, but such data can be obtained facilely in rodents. A physiologically based pharmacokinetic model for scaling up activity concentration in particular organs versus time was developed. The mathematical model exerts physiological parameters including organ volumes, blood flow rates, and vascular permabilities; the compartments (organs) are connected anatomically. This allows the use of scale-up techniques to forecast new complex distribution in humans' each organ. The concentration of the radiopharmaceutical in various organs was measured at different times. The temporal behavior of biodistribution of 177Lu labeled somatostatin analogues was modeled and drawn as function of time. Conclusion: The variation of pharmaceutical concentration in all organs is characterized with summation of six to nine exponential terms and it approximates our experimental data with precision better than 1%.

Keywords: biodistribution modeling, compartmental analysis, 177Lu labeled somatostatin analogues, neuroendocrine tumors

Procedia PDF Downloads 362