Search results for: raw complex data

Authors: Sarah K. Hagi, Majdi Alnowaimi

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In the last decade, there were immense advancements in the medical imaging modalities. These advancements can scan a whole volume of the lung organ in high resolution images within a short time. According to this performance, the physicians can clearly identify the complicated anatomical and pathological structures of lung. Therefore, these advancements give large opportunities for more advance of all types of lung cancer treatment available and will increase the survival rate. However, lung cancer is still one of the major causes of death with around 19% of all the cancer patients. Several factors may affect survival rate. One of the serious effects is the breathing process, which can affect the accuracy of diagnosis and lung tumor treatment plan. We have therefore developed a semi automated algorithm to localize the 3D lung tumor positions across all respiratory data during respiratory motion. The algorithm can be divided into two stages. First, a lung tumor segmentation for the first phase of the 4D computed tomography (CT). Lung tumor segmentation is performed using an active contours method. Then, localize the tumor 3D position across all next phases using a 12 degrees of freedom of an affine transformation. Two data set where used in this study, a compute simulate for 4D CT using extended cardiac-torso (XCAT) phantom and 4D CT clinical data sets. The result and error calculation is presented as root mean square error (RMSE). The average error in data sets is 0.94 mm ± 0.36. Finally, evaluation and quantitative comparison of the results with a state-of-the-art registration algorithm was introduced. The results obtained from the proposed localization algorithm show a promising result to localize alung tumor in 4D CT data.

Keywords: automated algorithm , computed tomography, lung tumor, tumor localization

Procedia PDF Downloads 598

Authors: Manuel Alves, Angelica Reis, Armindo Lobo, Valdemar Leiras

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In industry 4.0, it is common to have a lot of sensor data. In this deluge of data, hints of possible problems are difficult to spot. The digital twin concept aims to help answer this problem, but it is mainly used as a monitoring tool to handle the visualisation of data. Failure detection is of paramount importance in any industry, and it consumes a lot of resources. Any improvement in this regard is of tangible value to the organisation. The aim of this paper is to add the ability to forecast test failures, curtailing detection times. To achieve this, several anomaly detection algorithms were compared with a symbolic regression approach. To this end, Isolation Forest, One-Class SVM and an auto-encoder have been explored. For the symbolic regression PySR library was used. The first results show that this approach is valid and can be added to the tools available in this context as a low resource anomaly detection method since, after training, the only requirement is the calculation of a polynomial, a useful feature in the digital twin context.

Keywords: anomaly detection, digital twin, industry 4.0, symbolic regression

Procedia PDF Downloads 114

Authors: Kerem Rızvanoğlu, Serhat Güney, Emre Kızılkaya, Betül Aydoğan, Ayşegül Boyalı, Onurcan Güden

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This study addresses the re-construction and implementation process of the methodological framework developed to evaluate how locative media applications accompany the urban experiences of international students coming to Istanbul with exchange programs in 2022. The research design was built on a three-stage model. The research team conducted a qualitative questionnaire in the first stage to gain exploratory data. These data were then used to form three persona groups representing the sample by applying cluster analysis. In the second phase, a semi-structured digital diary study was carried out on a gamified task list with a sample selected from the persona groups. This stage proved to be the most difficult to obtaining valid data from the participant group. The research team re-evaluated the design of this second phase to reach the participants who will perform the tasks given by the research team while sharing their momentary city experiences, to ensure the daily data flow for two weeks, and to increase the quality of the obtained data. The final stage, which follows to elaborate on the findings, is the “Walk & Talk,” which is completed with face-to-face and in-depth interviews. It has been seen that the multiple methods used in the research process contribute to the depth and data diversity of the research conducted in the context of urban experience and locative technologies. In addition, by adapting the research design to the experiences of the users included in the sample, the differences and similarities between the initial research design and the research applied are shown.

Keywords: digital diary study, gamification, multi-model research, persona analysis, research design for urban experience, user-centered research, “Walk & Talk”

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Authors: S. M. C. Kelly, M. Goulden

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Introduction: Chronic Pancreatitis is an increasing problem worldwide. Pain is the main symptom and the main reason for hospital readmission following diagnosis, despite the use of strong analgesics including opioids. Ketamine infusions reduce pain in complex regional pain syndrome and other neuropathic pain conditions. Our centre has trialed the use of ketamine infusions in patients with chronic pancreatitis. We have evaluated this service to assess whether ketamine reduces emergency department admissions and analgesia requirements. Methods: This study collected retrospective data from 2010 in all patients who received a ketamine infusion for chronic pain secondary to a diagnosis of chronic pancreatitis. The day-case ketamine infusions were initiated in theatre by an anaesthetist, with standard monitoring and the assistance of an anaesthetic practitioner. A bolus dose of 0.5milligrams/kilogram was given in theatre. The infusion of 0.5 milligrams/kilogram per hour was then administered over a 6 hour period in the theatre recovery area. A study proforma detailed the medical history, analgesic use and admissions to hospital. Patients received a telephone follow up consultation. Results: Over the last eight years, a total of 30 patients have received intravenous ketamine infusions, with a total of 92 ketamine infusions being administered. 53% of the patients were male with the average age of 47. A total of 27 patients participated with the telephone consultation. A third of patients reported a reduction in hospital admissions with pain following the ketamine infusion. Analgesia requirements were reduced by an average of 48.3% (range 0-100%) for an average duration of 69.6 days (range 0-180 days.) Discussion: This service evaluation illustrates that ketamine infusions can reduce analgesic requirements and the number of hospital admissions in patients with chronic pancreatitis. In the light of increasing pressures on Emergency departments and the increasing evidence of the dangers of long-term opioid use, this is clearly a useful finding. We are now performing a prospective study to assess the long-term effectiveness of ketamine infusions in reducing analgesia requirements and improving patient’s quality of life.

Keywords: acute-on-chronic pain, intravenous analgesia infusion, ketamine, pancreatitis

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Authors: Umberto Di Staso, Marco Soave, Alessio Giori, Federico Prandi, Raffaele De Amicis

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The increasing availability of information about earth surface elevation (Digital Elevation Models DEM) generated from different sources (remote sensing, Aerial Images, Lidar) poses the question about how to integrate and make available to the most than possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the quality of data management plays a fundamental role. Due to the high acquisition costs and the huge amount of generated data, highresolution terrain surveys tend to be small or medium sized and available on limited portion of earth. Here comes the need to merge large-scale height maps that typically are made available for free at worldwide level, with very specific high resolute datasets. One the other hand, the third dimension increases the user experience and the data representation quality, unlocking new possibilities in data analysis for civil protection, real estate, urban planning, environment monitoring, etc. The open-source 3D virtual globes, which are trending topics in Geovisual Analytics, aim at improving the visualization of geographical data provided by standard web services or with proprietary formats. Typically, 3D Virtual globes like do not offer an open-source tool that allows the generation of a terrain elevation data structure starting from heterogeneous-resolution terrain datasets. This paper describes a technological solution aimed to set up a so-called “Terrain Builder”. This tool is able to merge heterogeneous-resolution datasets, and to provide a multi-resolution worldwide terrain services fully compatible with CesiumJS and therefore accessible via web using traditional browser without any additional plug-in.

Keywords: Terrain Builder, WebGL, Virtual Globe, CesiumJS, Tiled Map Service, TMS, Height-Map, Regular Grid, Geovisual Analytics, DTM

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Authors: Mehdi Brahimi, Kamal Medjaher, Noureddine Zerhouni, Mohammed Leouatni

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The Prognostics and Health Management is a system engineering discipline which provides solutions and models to the implantation of a predictive maintenance. The approach is based on extracting useful information from monitoring data to assess the “health” state of an industrial equipment or an asset. In this paper, we examine multiple extracted features from Pantograph-Catenary contact force in order to select the most relevant ones to achieve a diagnostics function. The feature extraction methodology is based on simulation data generated thanks to a Pantograph-Catenary simulation software called INPAC and measurement data. The feature extraction method is based on both statistical and signal processing analyses. The feature selection method is based on statistical criteria.

Keywords: catenary/pantograph interaction, diagnostics, Prognostics and Health Management (PHM), quality of current collection

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Authors: Deepa Shokeen, Bani Tamber Aeri

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Food choice is a complex process influenced by the interplay of multiple factors, including physical, socio-cultural and economic factors comprising macro or micro level food environments. While a clear understanding of the relationship between what we eat and the environmental context in which these food choices are made is still needed; it has however now been shown that food environments do play a significant role in the obesity epidemic and increasing cardio-metabolic risk factors. Evidence in other countries indicates that the food environment may strongly influence the prevalence of obesity and cardio-metabolic risk factors among young adults. Although in the Indian context, data does indicate the associations between sedentary lifestyle, stress, faulty diets but very little evidence supports the role of food environment in influencing cardio-metabolic health among employed adults. Thus, this research is required to establish how different environments affect different individuals as individuals interact with the environment on a number of levels. Methodology: The objective of the present study is to assess the effect of selected food and nutrition environments with emphasis on worksite environment and to analyse its impact on the food choices and dietary behaviour of the employees (25-45 years of age) of the organizations under study. In the proposed study an attempt will be made to randomly select various worksite environments from Delhi and NCR. The study will be conducted in two phases. In phase I, Information will be obtained on their socio-demographic profile and various factors influencing their food choices including most commonly consumed foods and most frequently visited eating outlets in and around the work place. Data will also be gathered on anthropometry (height, weight, waist circumference), biochemical parameters (lipid profile and fasting glucose), blood pressure and dietary intake. Based on the findings of phase I, a list of the most frequently visited eating outlets in and around the workplace will be prepared in Phase II. These outlets will then be subjected to nutrition environment assessment survey (NEMS). On the basis of the information gathered from phase I and phase II, influence of selected food and nutrition environments on food choice, dietary behaviour and prevalence of cardio-metabolic risk factors among employed adults will be assessed. Expected outcomes: The proposed study will try to ascertain the impact of selected food and nutrition environments on food choice and dietary intake of the working adults as it is important to learn how these food environments influence the eating perceptions and health behavior of the adults. In addition to this, anthropometry blood pressure and biochemical assessment of the subjects will be done to assess the prevalence of cardio-metabolic risk factors. If the findings indicate that the work environment, where most of these young adults spend their productive hours of the day, influence their health, than perhaps steps maybe needed to make these environments more conducive to health.

Keywords: food and nutrition environment, cardio-metabolic risk factors, India, worksite environment

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Authors: Lana Damaj, Vincent Laur, Azar Maalouf, Alexis Chevalier

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Matched termination is an important part of the passive waveguide components. It is typically used at the end of a waveguide transmission line to prevent reflections and improve signal quality. Waveguide terminations (loads) are commonly used in microwave and RF applications. In traditional microwave architectures, usually, waveguide termination consists of a standard rectangular waveguide made by a lossy resistive material, and ended by shorting metallic plate. These types of terminations are used, to dissipate the energy as heat. However, these terminations may increase the size and the weight of the overall system. New alternative solution consists in developing terminations based on 3D-printing of materials. Designing such terminations is very challenging since it should meet the requirements imposed by the system. These requirements include many parameters such as the absorption, the power handling capability in addition to the cost, the size and the weight that have to be minimized. 3D-printing is a shaping process that enables the production of complex geometries. It allows to find best compromise between requirements. In this paper, a comparison study has been made between different existing and new shapes of waveguide terminations. Indeed, 3D printing of absorbers makes it possible to study not only standard shapes (wedge, pyramid, tongue) but also more complex topologies such as exponential ones. These shapes have been designed and simulated using CST MWS®. The loads have been printed using the carbon-filled PolyLactic Acid, conductive PLA from ProtoPasta. Since the terminations has been characterized in the X-band (from 8GHz to 12GHz), the rectangular waveguide standard WR-90 has been selected. The classical wedge shape has been used as a reference. First, all loads have been simulated with the same length and two parameters have been compared: the absorption level (level of |S11|) and the dissipated power density. This study shows that the concave exponential pyramidal shape has the better absorption level and the convex exponential pyramidal shape has the better dissipated power density level. These two loads have been printed in order to measure their properties. A good agreement between the simulated and measured reflection coefficient has been obtained. Furthermore, a study of material structuring based on the honeycomb hexagonal structure has been investigated in order to vary the effective properties. In the final paper, the detailed methodology and the simulated and measured results will be presented in order to show how 3D-printing can allow controlling mass, weight, absorption level and power behaviour.

Keywords: additive manufacturing, electromagnetic composite materials, microwave measurements, passive components, power handling capacity (PHC), 3D-printing

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Authors: Danuvasin Charoen

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The study investigates the business process and business model of GRABTAXI. The paper also discusses how the company implemented strategies to gain competitive advantages. The data is derived from the analysis of secondary data and the in-depth interviews among staffs, taxi drivers, and key customers. The findings indicated that the company’s competitive advantages come from being the first mover, emphasising on the ease of use and tangible benefits of application, and using network effect strategy.

Keywords: taxi, mobile application, innovative business model, Thailand

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Nindyo Cahyo Kresnanto, Muhamad Willdan, Wika Harisa Putri

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Gunungkidul is one of the emerging tourism industry areas in Yogyakarta Province, Indonesia. This article describes how GIS can predict the development of tourism potential in Gunungkidul. The tourism sector in Gunungkidul Regency contributes 3.34% of the total gross regional domestic product and is the economic sector with the highest growth with a percentage of 18.37% in the post-Covid-19 period. This contribution makes researchers consider that several tourist sites need to be explored more to increase regional economic development gradually. This research starts by collecting spatial data from tourist locations tourists want to visit in Gunungkidul Regency based on survey data from 571 respondents. Then the data is visualized with ArcGIS software. This research shows an overview of tourist destinations interested in travellers depicted from the lowest to the highest from the data visualization. Based on the data visualization results, specific tourist locations potentially developed to influence the surrounding economy positively. The visualization of the data displayed is also in the form of a desire line map that shows tourist travel patterns from the origin of the tourist to the destination of the tourist location of interest. From the desire line, the prediction of the path of tourist sites with a high frequency of transportation activity can figure out. Predictions regarding specific tourist location routes that high transportation activities can burden can consider which routes will be chosen. The route also needs to be improved in terms of capacity and quality. The goal is to provide a sense of security and comfort for tourists who drive and positively impact the tourist sites traversed by the route.

Keywords: tourism development, GIS and survey, transportation, potential desire line

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Authors: Tulasi Acharya

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The paper is a qualitative analysis of status of women and women in politics and administration in Nepal Himalaya. The paper reviews data of women in civil service and in administrative levels. Looking at the Nepali politics and administration from the social constructivist perspective, the paper highlights some social and cultural issues that have othered women as “second sex.” As the country is heading towards modernity, gender friendly approaches are being instituted. Although the data reflects on the progress on women’s status and on women’s political and administrative participation, the data is not enough to predict the democratic gender practices in political and administrative levels. The political and administrative culture of Nepal Himalaya should be changed by promoting gender practices and deconstructing gender images in administrative culture through representative bureaucracy and by introducing democratic policies.

Keywords: politics, policy, administration, culture, women, Nepal, democracy

Procedia PDF Downloads 533

Authors: Qiaoyun Yang

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Organizational scholars have paid enormous attention on how local governments manage their knowledge during the past two decades. Government knowledge management (KM) research recognizes that the management of knowledge flows and networks is critical to reforms on government service efficiency and the effect of administration. When dealing with complex affairs, all the limitations resulting from a lack of KM concept, processes and technologies among all the involved organizations begin to be exposed and further compound the processing difficulty of the affair. As a result, the challenges for individual or group knowledge sharing, knowledge digging and organizations’ collaboration in government's activities are diverse and immense. This analysis presents recent situation of government KM in China drawing from a total of more than 300 questionnaires and highlights important challenges that remain. The causes of the lapses in KM processes within and across the government agencies are discussed.

Keywords: KM processes, KM technologies, government, KM situation

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Authors: Yong Hwang, Kang Yeol Suh, Yundeok Jang, Tae Hoon Kim

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Introduction: Rhabdomyolysis is a syndrome characterized by muscle necrosis and the release of intracellular muscle constituents into the circulation. Acute kidney injury is a potential complication of severe rhabdomyolysis and the prognosis is substantially worse if renal failure develops. We try to identify the factors that were predictive of AKI in severe trauma patients with rhabdomyolysis. Methods: This retrospective study was conducted at the emergency department of a level Ⅰ trauma center. Patients enrolled that initial creatine phosphokinase (CPK) levels were higher than 1000 IU with acute multiple trauma, and more than 18 years older from Oct. 2012 to June 2016. We collected demographic data (age, gender, length of hospital day, and patients’ outcome), laboratory data (ABGA, lactate, hemoglobin. hematocrit, platelet, LDH, myoglobin, liver enzyme, and BUN/Cr), and clinical data (Injury Mechanism, RTS, ISS, AIS, and TRISS). The data were compared and analyzed between AKI and Non-AKI group. Statistical analyses were performed using IMB SPSS 20.0 statistics for Window. Results: Three hundred sixty-four patients were enrolled that AKI group were ninety-six and non-AKI group were two hundred sixty-eight. The base excess (HCO3), AST/ALT, LDH, and myoglobin in AKI group were significantly higher than non-AKI group from laboratory data (p ≤ 0.05). The injury severity score (ISS), revised Trauma Score (RTS), Abbreviated Injury Scale 3 and 4 (AIS 3 and 4) were showed significant results in clinical data. The patterns of CPK level were increased from first and second day, but slightly decreased from third day in both group. Seven patients had received hemodialysis treatment despite the bleeding risk and were survived in AKI group. Conclusion: We recommend that HCO3, CPK, LDH, and myoglobin should be checked and be concerned about ISS, RTS, AIS with injury mechanism at the early stage of treatment in the emergency department.

Keywords: acute kidney injury, emergencies, multiple trauma, rhabdomyolysis

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Authors: Estevan B. Costa, Armando M. Toda, Marcell A. A. Mesquita, Jacques D. Brancher

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The advances in technology in the last five years allowed an improvement in the educational area, as the increasing in the development of educational software. One of the techniques that emerged in this lapse is called Gamification, which is the utilization of video game mechanics outside its bounds. Recent studies involving this technique provided positive results in the application of these concepts in many areas as marketing, health and education. In the last area there are studies that cover from elementary to higher education, with many variations to adequate to the educators methodologies. Among higher education, focusing on IT courses, data structures are an important subject taught in many of these courses, as they are base for many systems. Based on the exposed this paper exposes the development of an interactive web learning environment, called DSLEP (Data Structure Learning Platform), to aid students in higher education IT courses. The system includes basic concepts seen on this subject such as stacks, queues, lists, arrays, trees and was implemented to ease the insertion of new structures. It was also implemented with gamification concepts, such as points, levels, and leader boards, to engage students in the search for knowledge and stimulate self-learning.

Keywords: gamification, Interactive learning environment, data structures, e-learning

Procedia PDF Downloads 487

Authors: Marlin Mubarak

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Background: Endometriosis is a complex disabling disease affecting young females in the reproductive period mainly. The aim of this project is to generate a diagnostic model to predict severity and stage of endometriosis prior to Laparoscopic surgery. This will help to improve the pre-operative diagnostic accuracy of stage 3 & 4 endometriosis and as a result, refer relevant women to a specialist centre for complex Laparoscopic surgery. The model is based on the British Society of Gynaecological Endoscopy (BSGE) pain questionnaire, clinical examination and ultrasound scan. Design: This is a prospective, observational, study, in which women completed the BSGE pain questionnaire, a BSGE requirement. Also, as part of the routine preoperative assessment patient had a routine ultrasound scan and when recto-vaginal and deep infiltrating endometriosis was suspected an MRI was performed. Setting: Luton & Dunstable University Hospital. Patients: Symptomatic women (n = 56) scheduled for laparoscopy due to pelvic pain. The age ranged between 17 – 52 years of age (mean 33.8 years, SD 8.7 years). Interventions: None outside the recognised and established endometriosis centre protocol set up by BSGE. Main Outcome Measure(s): Sensitivity and specificity of endometriosis diagnosis predicted by symptoms based on BSGE pain questionnaire, clinical examinations and imaging. Findings: The prevalence of diagnosed endometriosis was calculated to be 76.8% and the prevalence of advanced stage was 55.4%. Deep infiltrating endometriosis in various locations was diagnosed in 32/56 women (57.1%) and some had DIE involving several locations. Logistic regression analysis was performed on 36 clinical variables to create a simple clinical prediction model. After creating the scoring system using variables with P < 0.05, the model was applied to the whole dataset. The sensitivity was 83.87% and specificity 96%. The positive likelihood ratio was 20.97 and the negative likelihood ratio was 0.17, indicating that the model has a good predictive value and could be useful in predicting advanced stage endometriosis. Conclusions: This is a hypothesis-generating project with one operator, but future proposed research would provide validation of the model and establish its usefulness in the general setting. Predictive tools based on such model could help organise the appropriate investigation in clinical practice, reduce risks associated with surgery and improve outcome. It could be of value for future research to standardise the assessment of women presenting with pelvic pain. The model needs further testing in a general setting to assess if the initial results are reproducible.

Keywords: deep endometriosis, endometriosis, minimally invasive, MRI, ultrasound.

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Authors: Mykola G. Boichuk

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The paper concerns predatory pricing incentives and mechanisms in the markets of services, as well as its anti-competitive effects. As cost estimation at services markets is more complex in comparison to markets of goods, predatory pricing is more difficult to detect in the provision of services. For instance, this is often the case for professional services, which is analyzed in the paper. The special attention is given to employment markets as de-facto main supply markets for professional services markets. Also, the paper concerns such instances as travel agents' services, where predatory pricing may have implications not only on competition but on a wider range of public interest as well. Thus, the paper develops on effective ways to apply competition law rules on predatory pricing to the provision of services.

Keywords: employment markets, predatory pricing, services markets, unfair competition

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Authors: Victoria Goodall, Paul Fatti, Norman Owen-Smith

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Hidden Markov Models have become popular for the analysis of animal tracking data. These models are being used to model the movements of a variety of species in many areas around the world. A common assumption of the model is that the observations need to have regular time steps. In many ecological studies, this will not be the case. The objective of the research is to modify the movement model to allow for irregularly spaced locations and investigate the effect on the inferences which can be made about the latent states. A modification of the likelihood function to allow for these irregular spaced locations is investigated, without using interpolation or averaging the movement rate. The suitability of the modification is investigated using GPS tracking data for lion (Panthera leo) in South Africa, with many observations obtained during the night, and few observations during the day. Many nocturnal predator tracking studies are set up in this way, to obtain many locations at night when the animal is most active and is difficult to observe. Few observations are obtained during the day, when the animal is expected to rest and is potentially easier to observe. Modifying the likelihood function allows the popular Hidden Markov Model framework to be used to model these irregular spaced locations, making use of all the observed data.

Keywords: hidden Markov Models, irregular observations, animal movement modelling, nocturnal predator

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Authors: Tsai-Hsiu Lin

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Dan C. Lortie’s Schoolteacher: A sociological study is one of the best works on the sociology of teaching since W. Waller’s classic study. It is a book worthy of review. Following the tradition of symbolic interactionists, Lortie demonstrated the qualities who studied the occupation of teaching. Using several methods to gather effective data, Lortie has portrayed the ethos of the teaching profession. Therefore, the work is an important book on the teaching profession and teacher culture. Though outstanding, Lortie’s work is also flawed in that his perspectives and methodology were adopted largely from symbolic interactionism. First, Lortie in his work analyzed many points regarding teacher culture; for example, he was interested in exploring “sentiment,” “cathexis,” and “ethos.” Thus, he was more a psychologist than a sociologist. Second, symbolic interactionism led him to discern the teacher culture from a micro view, thereby missing the structural aspects. For example, he did not fully discuss the issue of gender and he ignored the issue of race. Finally, following the qualitative sociological tradition, Lortie employed many qualitative methods to gather data but only foucused on obtaining and presenting interview data. Moreover, he used measurement methods that were too simplistic for analyzing quantitative data fully.

Keywords: education reform, teacher culture, teaching profession, Lortie’s Schoolteacher

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Authors: Elnaz Kanani-Kuchesfehani, Andrea Schiffauerova

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Due to the novelty of the nanotechnology science, its highly knowledge intensive content, and its invaluable application in almost all technological fields, the close interaction between university and industry is essential. A possible gap between academic strengths to generate good nanotechnology ideas and industrial capacity to receive them can thus have far-reaching consequences. In order to be able to enhance the collaboration between the two parties, a better understanding of knowledge transfer within the university-industry relationship is needed. The objective of this research is to investigate the research collaboration between academia and industry in Canadian nanotechnology and to propose the best cooperative strategy to maximize the quality of the produced knowledge. First, a network of all Canadian academic and industrial nanotechnology inventors is constructed using the patent data from the USPTO (United States Patent and Trademark Office), and it is analyzed with social network analysis software. The actual level of university-industry collaboration in Canadian nanotechnology is determined and the significance of each group of actors in the network (academic vs. industrial inventors) is assessed. Second, a novel methodology is proposed, in which the network of nanotechnology inventors is assessed from a game theoretic perspective. It involves studying a cooperative game with n players each having at most n-1 decisions to choose from. The equilibrium leads to a strategy for all the players to choose their co-worker in the next period in order to maximize the correlated payoff of the game. The payoffs of the game represent the quality of the produced knowledge based on the citations of the patents. The best suggestion for the next collaborative relationship is provided for each actor from a game theoretic point of view in order to maximize the quality of the produced knowledge. One of the major contributions of this work is the novel approach which combines game theory and social network analysis for the case of large networks. This approach can serve as a powerful tool in the analysis of the strategic interactions of the network actors within the innovation systems and other large scale networks.

Keywords: cooperative strategy, game theory, industry-university collaboration, knowledge production, social network analysis

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Authors: Jeena Gupta

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In the today’s world of pharmaceutical products, one should not forget the healing properties of inexpensive food materials especially spices. They are known to possess hidden pharmaceutical ingredients, imparting them the qualities of being anti-microbial, anti-oxidant, anti-inflammatory and anti-carcinogenic. Further aberrant epigenetic regulatory mechanisms like DNA methylation, histone modifications or altered microRNA expression patterns, which regulates gene expression without changing DNA sequence, contribute significantly in the development of various diseases. Changing lifestyles and diets exert their effect by influencing these epigenetic mechanisms which are thus the target of dietary phytochemicals. Bioactive components of plants have been in use since ages but their potential to reverse epigenetic alterations and prevention against diseases is yet to be explored. Spices being rich repositories of many bioactive constituents are responsible for providing them unique aroma and taste. Some spices like curcuma and garlic have been well evaluated for their epigenetic regulatory potential, but for others, it is largely unknown. We have evaluated the biological activity of phyto-active components of Fennel, Cardamom and Fenugreek by in silico molecular modeling, in vitro and in vivo studies. Ligand-based similarity studies were conducted to identify structurally similar compounds to understand their biological phenomenon. The database searching has been done by using Fenchone from fennel, Sabinene from cardamom and protodioscin from fenugreek as a query molecule in the different small molecule databases. Moreover, the results of the database searching exhibited that these compounds are having potential binding with the different targets found in the Protein Data Bank. Further in addition to being epigenetic modifiers, in vitro study had demonstrated the antimicrobial, antifungal, antioxidant and cytotoxicity protective effects of Fenchone, Sabinene and Protodioscin. To best of our knowledge, such type of studies facilitate the target fishing as well as making the roadmap in drug design and discovery process for identification of novel therapeutics.

Keywords: epigenetics, spices, phytochemicals, fenchone

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Authors: Omar Hamdy, Schichen Zhao, Hussein Abd El-Atty, Ayman Ragab, Muhammad Salem

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One of the most risky areas in Aswan is Abouelreesh, which is suffering from flood disasters, as heavy deluge inundates urban areas causing considerable damage to buildings and infrastructure. Moreover, the main problem was the urban sprawl towards this risky area. This paper aims to identify the urban areas located in the risk areas prone to flash floods. Analyzing this phenomenon needs a lot of data to ensure satisfactory results; however, in this case the official data and field data were limited, and therefore, free sources of satellite data were used. This paper used ArcGIS tools to obtain the storm water drains network by analyzing DEM files. Additionally, historical imagery in Google Earth was studied to determine the age of each building. The last step was to overlay the urban area layer and the storm water drains layer to identify the vulnerable areas. The results of this study would be helpful to urban planners and government officials to make the disasters risk estimation and develop primary plans to recover the risky area, especially urban areas located in torrents.

Keywords: risk area, DEM, storm water drains, GIS

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Authors: Martin Juckel

Abstract:

Probably no other field of inorganic chemistry has undergone such a rapid development in the past two decades than the low oxidation state chemistry of main group elements. This rapid development has only been possible by the development of new bulky ligands. In case of our research group, super-bulky monodentate amido ligands and β-diketiminate ligands have been used to a great success. We first synthesized the unprecedented magnesium(I) dimer [ᴹᵉˢNacnacMg]₂ (ᴹᵉˢNacnac = [(ᴹᵉˢNCMe)₂CH]-; Mes = mesityl, which has since been used both as reducing agent and also for the synthesis of new metal-magnesium bonds. In case of the zinc bromide precursor [L*ZnBr] (L*=(N(Ar*)(SiPri₃); (Ar* = C₆H₂{C(H)Ph₂}₂Me-2,6,4, the reduction with [ᴹᵉˢNacnacMg]₂ led to such a metal-magnesium bond. This [L*ZnMg(ᴹᵉˢNacnac)] compound can be seen as an ‘inorganic Grignard reagent’, which can be used to transfer the metal fragment onto other functional groups or other metal centers; just like the conventional Grignard reagent. By simple addition of (TBoN)GeCl (TBoN = N(SiMe₃){B(DipNCH)₂) to the aforesaid compound, we were able to transfer the amido-zinc fragment to the Ge center of the germylene starting material and to synthesize the first example of a germanium(II)-zinc bond: [:Ge(TBoN)(ZnL*)]. While these reactions typically led to complex product mixture, [:Ge(TBoN)(ZnL*)] could be isolated as dark blue crystals in a good yield. This new compound shows interesting reactivity towards small molecules, especially dihydrogen gas. This is of special interest as dihydrogen is one of the more difficult small molecules to activate, due to its strong (BDE = 108 kcal/mol) and non-polar bond. In this context, the interaction between H₂ σ-bond with the tetrelylene p-Orbital (LUMO), with concomitant donation of the tetrelylene lone pair (HOMO) into the H₂ σ* orbital are responsible for the activation of dihydrogen gas. Accordingly, the narrower the HOMO-LUMO gap of tertelylene, the more reactivity towards H₂ it typically is. The aim of a narrow HOMO-LUMO gap was reached by transferring electropositive substituents respectively metal substituents with relatively low Pauling electronegativity (zinc: 1.65) onto the Ge center (here: the zinc-amido fragment). In consideration of the unprecedented reactivity of [:Ge(TBoN)(ZnL*)], a computational examination of its frontier orbital energies was undertaken. The energy separation between the HOMO, which has significant Ge lone pair character, and the LUMO, which has predominantly Ge p-orbital character, is narrow (40.8 kcal/mol; cf.∆S-T= 24.8 kcal/mol), and comparable to the HOMO-LUMO gaps calculated for other literature known complexes). The calculated very narrow HOMO-LUMO gap for the [:Ge(TBoN)(ZnL*)] complex is consistent with its high reactivity, and is remarkable considering that it incorporates a π-basic amide ligand, which are known to raise the LUMO of germylenes considerably.

Keywords: activation of dihydrogen gas, narrow HOMO-LUMO gap, first germanium(II)-zinc bond, inorganic Grignard reagent

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Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir

Abstract:

Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

Procedia PDF Downloads 379

Authors: Mohammad Nadeem, Haider Banka, R. Venugopal

Abstract:

Granulation or agglomeration is a size enlargement process to transform the fine particulates into larger aggregates since the fine size of available materials and minerals poses difficulty in their utilization. Though a long list of methods is available in the literature for the modeling of granulation process to facilitate the in-depth understanding and interpretation of the system, there is still scope of improvements using novel tools and techniques. Intelligent techniques, such as artificial neural network, fuzzy logic, self-organizing map, support vector machine and others, have emerged as compelling alternatives for dealing with imprecision and complex non-linearity of the systems. The present study tries to review the applications of intelligent techniques in the modeling of size enlargement process for fine materials.

Keywords: fine material, granulation, intelligent technique, modelling

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Authors: Zama Mahmood

Abstract:

The increasing demand of food management, monitoring of the crop growth and forecasting its yield well before harvest is very important. These days, yield assessment together with monitoring of crop development and its growth are being identified with the help of satellite and remote sensing images. Studies using remote sensing data along with field survey validation reported high correlation between vegetation indices and yield. With the development of remote sensing technique, the detection of crop and its mechanism using remote sensing data on regional or global scales have become popular topics in remote sensing applications. Punjab, specially the southern Punjab region is extremely favourable for wheat production. But measuring the exact amount of wheat production is a tedious job for the farmers and workers using traditional ground based measurements. However, remote sensing can provide the most real time information. In this study, using the Normalized Differentiate Vegetation Index (NDVI) indicator developed from Landsat satellite images, the yield of wheat has been estimated during the season of 2013-2014 for the agricultural area around Bahawalpur. The average yield of the wheat was found 35 kg/acre by analysing field survey data. The field survey data is in fair agreement with the NDVI values extracted from Landsat images. A correlation between wheat production (ton) and number of wheat pixels has also been calculated which is in proportional pattern with each other. Also a strong correlation between the NDVI and wheat area was found (R2=0.71) which represents the effectiveness of the remote sensing tools for crop monitoring and production estimation.

Keywords: landsat, NDVI, remote sensing, satellite images, yield

Procedia PDF Downloads 326

Authors: Anastasiia Yu. Timofeeva

Abstract:

Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.

Keywords: grade point average, orthogonal regression, penalized regression spline, locally weighted regression

Procedia PDF Downloads 408

Authors: Lihua Zhu, Jianfeng Du, Yu Wang, Zhiqiang Wu

Abstract:

Collision avoidance problems of a swarm of unmanned air vehicles (UAVs) flying in an obstacle-laden environment are investigated in this paper. Given that the UAV swarm needs to adapt to the obstacle distribution in dynamic operation, a priority configuration is designed to guide the UAVs to pass through the obstacles in turn. Based on the collision cone approach and the prediction of the collision time, a collision evaluation model is established to judge the urgency of the imminent collision of each UAV, and the evaluation result is used to assign the priority of each UAV to further instruct them going through the obstacles in descending order. At last, the simulation results provide the promising validation in terms of the efficiency and scalability of the proposed approach.

Keywords: UAV swarm, collision avoidance, complex environment, online priority design

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Authors: Rana Th. A. Al-rubaye

Abstract:

A novel chromium-free protective coating films based on a zeolite coating was growing onto a FeCrAlloy metal using in –situ hydrothermal method. The zeolite film was obtained using in-situ crystallization process that is capable of coating large surfaces with complex shape and in confined spaces has been developed. The zeolite coating offers an advantage of a high mechanical stability and thermal stability. The physico-chemical properties were investigated using X-ray diffraction (XRD), Electron microscopy (SEM), Energy Dispersive X–ray analysis (EDX) and Thermogravimetric Analysis (TGA). The transition from oxide-on-alloy wires to hydrothermally synthesised uniformly zeolite coated surfaces was followed using SEM and XRD. In addition, the robustness of the prepared coating was confirmed by subjecting these to thermal cycling (ambient to 550°C).

Keywords: fecralloy, zsm-5 zeolite, zeolite coatings, hydrothermal method

Procedia PDF Downloads 388

Authors: Soroor K. H. Al-Khafaji, Manal Mohammad Abed

Abstract:

The research aim of this paper is to evaluate the reliability of a complex engineering system and to design a fuzzy model for the reliability estimation. The designed model has been applied on Vegetable Oil Purification System (neutralization system) to help the specialist user based on the concept of FMEA (Failure Mode and Effect Analysis) to estimate the reliability of the repairable system at the vegetable oil industry. The fuzzy model has been used to predict the system reliability for a future time period, depending on a historical database for the two past years. The model can help to specify the system malfunctions and to predict its reliability during a future period in more accurate and reasonable results compared with the results obtained by the traditional method of reliability estimation.

Keywords: fuzzy logic, reliability, repairable systems, FMEA

Procedia PDF Downloads 609