Search results for: data access

Authors: Powei Happiness Kerry

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Introducing wireless technologies in Nigeria have improved the quality of lives of Nigerians, however, not everyone sees it in that light. The paper on the environmental impact of wireless technologies in Nigeria summarizes the scholarly views on the impact of wireless technologies on the environment, beaming its searchlight on 5G and internet of things in Nigeria while also exploring the theory of the Technology Acceptance Model (TAM). The study used a qualitative research method to gather important data from relevant sources and contextually draws inference from the derived data. The study concludes that the Federal Government of Nigeria, before agreeing to any latest development in the world of wireless technologies, should weigh the implications and deliberate extensively with all stalk holders putting into consideration the confirmation it will receive from the National Assembly.  

Keywords: Internet of Things, radiofrequency, electromagnetic radiation, information and communications technology, ICT, 5G

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Authors: Zafer Cakmak, Birol Bulut, Cengiz Taskiran

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Technological advances, the world becoming smaller and increasing world population increase our interdependence with individuals that we maybe never meet face to face. It is impossible for the modern individuals to escape global developments and their impact. Furthermore, it is very unlikely for the global societies to turn back from the path they are in. These effects of globalization in fact encumber the humankind at a certain extend. We succumb to these responsibilities for we desire a better future, a habitable world and a more peaceful life. In the present study, global responsibility levels of the participants were measured and the significance of global reactions that individuals have to develop on global issues was reinterpreted under the light of the existing literature. The study was conducted with general survey model, one of the survey methodologies General survey models are surveys conducted on the whole universe or a group, sample or sampling taken from the universe to arrive at a conclusion about the universe, which includes a high number of elements. The study was conducted with data obtained from 350 pre-service teachers attending 2016 spring semester to determine 'Global Social Responsibility' levels of social studies pre-service teachers based on several variables. Collected data were analyzed using SPSS 21.0 software. T-test and ANOVA were utilized in the data analysis.

Keywords: social studies, globalization, global social responsibility, education

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Authors: Ivan Ramos Sampe Immanuel, Linung Kresno Adikusumo, Liston Sitanggang

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Achieving the production targets of oil and gas in an upstream oil and gas company represents a complex undertaking necessitating collaborative engagement from a multidisciplinary team. In addition to conducting exploration activities and executing well intervention programs, an upstream oil and gas enterprise must assess the feasibility of attaining predetermined production goals. The monitoring of production performance serves as a critical activity to ensure organizational progress towards the established oil and gas performance targets. Subsequently, decisions within the upstream oil and gas management team are informed by the received information pertaining to the respective production performance. To augment the decision-making process, the implementation of a production performance dashboard emerges as a viable solution, providing an integrated and centralized tool. The deployment of a production performance dashboard manifests as an instrumental mechanism fostering a user-friendly interface for monitoring production performance, while concurrently preserving the intrinsic characteristics of granular data. The integration of diverse data sources into a unified production performance dashboard establishes a singular veritable source, thereby enhancing the organization's capacity to uphold a consolidated and authoritative foundation for its business requisites. Additionally, the heightened accessibility of the production performance dashboard to business users constitutes a compelling substantiation of its consequential impact on facilitating the monitoring of organizational targets.

Keywords: production, performance, dashboard, data analytics

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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Authors: Alina Hamid Bari

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Intellectual Property (IP) policies of a country have a huge impact on the pharmaceutical industry as this industry is all about patents. Developed countries have used IP protection to boost their economy; developing countries are concerned about access to medicine for poor people. U.S. company, Pfizer had a monopoly for 14 years for Lipitor and it all came to end when Pfizer decided to operate in India. This research will focus at the effects of Indian IP policies on USA by comparing Pfizer & Ranbaxy with regards to Trade Related Aspects of Intellectual Property Rights. For this research inductive approach has been used. Main source of material is Annual reports, theory based on academic books and articles along with rulings of court, policy statements and decisions, websites and newspaper articles. SWOT analysis is done for both Pfizer & Ranbaxy. The main comparison was done by doing ratio analysis and analyses of annual reports for the year 2011-2012 for Pfizer and Ranbaxy to see the impact on their profitability. This research concludes that Indian intellectual laws do affect the profitability of the U.S. pharmaceutical industry which can in turn have an impact on the US economy. These days India is only granting patents on products which it feels are deserving of it. So the U.S. companies operating in India have to defend their invention to get a patent. Thus, to operate in India and maintain monopoly in market, US firms have to come up with different strategies.

Keywords: atorvastatin, India, intellectual property, lipitor, Pfizer, pharmaceutical industry, Ranbaxy, TRIPs, U.S.

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Authors: Petra Gergelova, Sofia Ioannidou, Davide Arcella, Alexandra Tard, Polly E. Boon, Oliver Lindtner, Christina Tlustos, Jean-Charles Leblanc

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Objectives: To assess chronic dietary exposure to food additives in different European countries and population groups. Method and Design: The European Food Safety Authority’s (EFSA) Panel on Food Additives and Nutrient Sources added to Food (ANS) estimates chronic dietary exposure to food additives with the purpose of re-evaluating food additives that were previously authorized in Europe. For this, EFSA uses concentration values (usage and/or analytical occurrence data) reported through regular public calls for data by food industry and European countries. These are combined, at individual level, with national food consumption data from the EFSA Comprehensive European Food Consumption Database including data from 33 dietary surveys from 19 European countries and considering six different population groups (infants, toddlers, children, adolescents, adults and the elderly). EFSA ANS Panel estimates dietary exposure for each individual in the EFSA Comprehensive Database by combining the occurrence levels per food group with their corresponding consumption amount per kg body weight. An individual average exposure per day is calculated, resulting in distributions of individual exposures per survey and population group. Based on these distributions, the average and 95th percentile of exposure is calculated per survey and per population group. Dietary exposure is assessed based on two different sets of data: (a) Maximum permitted levels (MPLs) of use set down in the EU legislation (defined as regulatory maximum level exposure assessment scenario) and (b) usage levels and/or analytical occurrence data (defined as refined exposure assessment scenario). The refined exposure assessment scenario is sub-divided into the brand-loyal consumer scenario and the non-brand-loyal consumer scenario. For the brand-loyal consumer scenario, the consumer is considered to be exposed on long-term basis to the highest reported usage/analytical level for one food group, and at the mean level for the remaining food groups. For the non-brand-loyal consumer scenario, the consumer is considered to be exposed on long-term basis to the mean reported usage/analytical level for all food groups. An additional exposure from sources other than direct addition of food additives (i.e. natural presence, contaminants, and carriers of food additives) is also estimated, as appropriate. Results: Since 2014, this methodology has been applied in about 30 food additive exposure assessments conducted as part of scientific opinions of the EFSA ANS Panel. For example, under the non-brand-loyal scenario, the highest 95th percentile of exposure to α-tocopherol (E 307) and ammonium phosphatides (E 442) was estimated in toddlers up to 5.9 and 8.7 mg/kg body weight/day, respectively. The same estimates under the brand-loyal scenario in toddlers resulted in exposures of 8.1 and 20.7 mg/kg body weight/day, respectively. For the regulatory maximum level exposure assessment scenario, the highest 95th percentile of exposure to α-tocopherol (E 307) and ammonium phosphatides (E 442) was estimated in toddlers up to 11.9 and 30.3 mg/kg body weight/day, respectively. Conclusions: Detailed and up-to-date information on food additive concentration values (usage and/or analytical occurrence data) and food consumption data enable the assessment of chronic dietary exposure to food additives to more realistic levels.

Keywords: α-tocopherol, ammonium phosphatides, dietary exposure assessment, European Food Safety Authority, food additives, food consumption data

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Authors: Pedro M. Abreu, Bruno R. Mendes

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The management of pharmacotherapy and the process of dispensing medicines is becoming critical in clinical pharmacy due to the increase of incidence and prevalence of chronic diseases, the complexity and customization of therapeutic regimens, the introduction of innovative and more expensive medicines, the unbalanced relation between expenditure and revenue as well as due to the lack of rationalization associated with medication use. For these reasons, co-payments emerged in Europe in the 70s and have been applied over the past few years in healthcare. Co-payments lead to a rationing and rationalization of user’s access under healthcare services and products, and simultaneously, to a qualification and improvement of the services and products for the end-user. This analysis, under hospital practices particularly and co-payment strategies in general, was carried out on all the European regions and identified four reference countries, that apply repeatedly this tool and with different approaches. The structure, content and adaptation of European co-payments were analyzed through 7 qualitative attributes and 19 performance indicators, and the results expressed in a scorecard, allowing to conclude that the German models (total score of 68,2% and 63,6% in both elected co-payments) can collect more compliance and effectiveness, the English models (total score of 50%) can be more accessible, and the French models (total score of 50%) can be more adequate to the socio-economic and legal framework. Other European models did not show the same quality and/or performance, so were not taken as a standard in the future design of co-payments strategies. In this sense, we can see in the co-payments a strategy not only to moderate the consumption of healthcare products and services, but especially to improve them, as well as a strategy to increment the value that the end-user assigns to these services and products, such as medicines.

Keywords: clinical pharmacy, co-payments, healthcare, medicines

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Authors: N. Ipiña, R. Basagoiti, O. Jimenez, I. Arriaran

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Higher education students are increasingly enrolling in online courses, they are, at the same time, generating data about their learning process in the courses. Data collected in those technology enhanced learning spaces can be used to identify patterns and therefore, offer recommendations/personalized courses to future online students. Moreover, recommendations are considered key aspects for personalization in online learning. Taking into account the above mentioned context, the aim of this paper is to explore the perception of higher education students and teachers towards receiving recommendations in online courses. The study was carried out with 322 students and 10 teachers from two different faculties (Engineering and Education) from Mondragon University. Online questionnaires and face to face interviews were used to gather data from the participants. Results from the questionnaires show that most of the students would like to receive recommendations in their online courses as a guide in their learning process. Findings from the interviews also show that teachers see recommendations useful for their students’ learning process. However, teachers believe that specific pedagogical training is required. Conclusions can also be drawn as regards the importance of personalization in technology enhanced learning. These findings have significant implications for those who train online teachers due to the fact that pedagogy should be the driven force and further training on the topic could be required. Therefore, further research is needed to better understand the impact of recommendations on online students’ learning process and draw some conclusion on pedagogical concerns.

Keywords: higher education, perceptions, recommendations, online courses

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Authors: Gary Young, David Zepeda, Gilbert Nyaga

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This study investigated whether vertical integration of hospitals and physicians is associated with better care for patients with cardiac conditions. A dramatic change in the U.S. hospital industry is the integration of hospital and physicians through hospital acquisition of physician practices. Yet, there is little evidence regarding whether this form of vertical integration leads to better operational performance of hospitals. The study was conducted as an observational investigation based on a pooled, cross-sectional database. The study sample comprised over hospitals in the State of California. The time frame for the study was 2010 to 2012. The key performance measure was hospitals’ degree of compliance with performance criteria set out by the federal government for managing patients with cardiac conditions. These criteria relate to the types of clinical tests and medications that hospitals should follow for cardiac patients but hospital compliance requires the cooperation of a hospital’s physicians. Data for this measure was obtained from a federal website that presents performance scores for U.S. hospitals. The key independent variable was the percentage of cardiologists that a hospital employs (versus cardiologists who are affiliated but not employed by the hospital). Data for this measure was obtained from the State of California which requires hospitals to report financial and operation data each year including numbers of employed physicians. Other characteristics of hospitals (e.g., information technology for cardiac care, volume of cardiac patients) were also evaluated as possible complements or substitutes for physician employment by hospitals. Additional sources of data included the American Hospital Association and the U.S. Census. Empirical models were estimated with generalized estimating equations (GEE). Findings suggest that physician employment is positively associated with better hospital performance for cardiac care. However, findings also suggest that information technology is a substitute for physician employment.

Keywords: physician employment, hospitals, verical integration, cardiac care

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Authors: Acumsiri Tantikarnpanit

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This paper aims to examine the relationship between urbanization and income inequality in Thailand during the period 2002–2020. Using a panel of data for 76 provinces collected from Thailand’s National Statistical Office (Labor Force Survey: LFS), as well as geospatial data from the U.S. Air Force Defense Meteorological Satellite Program (DMSP) and the Visible Infrared Imaging Radiometer Suite Day/Night band (VIIRS-DNB) satellite for nineteen selected years. This paper employs two different definitions to identify urban areas: 1) Urban areas defined by Thailand's National Statistical Office (Labor Force Survey: LFS), and 2) Urban areas estimated using nighttime light data from the DMSP and VIIRS-DNB satellite. The second method includes two sub-categories: 2.1) Determining urban areas by calculating nighttime light density with a population density of 300 people per square kilometer, and 2.2) Calculating urban areas based on nighttime light density corresponding to a population density of 1,500 people per square kilometer. The empirical analysis based on Ordinary Least Squares (OLS), fixed effects, and random effects models reveals a consistent U-shaped relationship between income inequality and urbanization. The findings from the econometric analysis demonstrate that urbanization or population density has a significant and negative impact on income inequality. Moreover, the square of urbanization shows a statistically significant positive impact on income inequality. Additionally, there is a negative association between logarithmically transformed income and income inequality. This paper also proposes the inclusion of satellite imagery, geospatial data, and spatial econometric techniques in future studies to conduct quantitative analysis of spatial relationships.

Keywords: income inequality, nighttime light, population density, Thailand, urbanization

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Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Hamad Albadr

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With a rapid influence to sustain the needs for global trends that had arisen for the increasing complexities in health-care provision, the increasing number of health professionals at different levels, and the need to assure more equitable access to health care, the great variation in the levels of initial education for health care professional around the world had been assign bachelor's degree as the minimum point of entry to the health professions. This intent had affected all the health care professions including biomedical engineering. In Saudi Arabia, these challenges add more pressure to retain the global trends for associate degree graduates to upgrade their education to the bachelor's degree or called birding. This paper is to review the reality of biomedical technology programs that offered in Saudi Arabia by Technical Colleges or Community Colleges nationwide and the challenges that face these colleges to run such bridging program to achieve the Bachelor's degree in biomedical engineering and the official requirements by the Ministry of Higher Education and to maintain the international standards. The author will use strategic planning methodology for designing the biomedical engineering bridging of bachelor's program by reviewing the responsibilities of the biomedical engineers in hospitals through their job descriptions to determine the job assessment needs in advance to Developing a Curriculum (DACUM) through Instructional System Design (ISD) approach via five steps: Analysis, Design, Development, Implement, Evaluate (ADDIE).

Keywords: bachelor's degree bridging, biomedical engineering program, Saudi Arabia, Riyadh College of Technology

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Authors: Tamadu Perry Egedegu

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Rapid growth in the use of electronic data has affected both the employee and work place. Our experience shows that jobs that have multiple risk factors have a greater likelihood of causing Work Related Musculoskeletal Disorder (WRMSDs), depending on the duration, frequency and/or magnitude of exposure to each. The study investigated musculoskeletal disorder among office workers. Thus, it is important that ergonomic risk factors be considered in light of their combined effect in causing or contributing to WRMSDs. Fast technological growth in the use of electronic system; have affected both workers and the work environment. Awkward posture and long hours in front of these visual display terminals can result in work-related musculoskeletal disorders (WRMSD). The study shall contribute to the awareness creation on the causes and consequences of WRMSDs due to lack of ergonomics training. The study was conducted using an observational cross-sectional design. A sample of 109 respondents was drawn from the target population through purposive sampling method. The sources of data were both primary and secondary. Primary data were collected through questionnaires and secondary data were sourced from journals, textbooks, and internet materials. Questionnaires were the main instrument for data collection and were designed in a YES or NO format according to the study objectives. Content validity approval was used to ensure that the variables were adequately covered. The reliability of the instrument was done through test-retest method, yielding a reliability index at 0.84. The data collected from the field were analyzed with a descriptive statistics of chart, percentage and mean. The study found that the most affected body regions were the upper back, followed by the lower back, neck, wrist, shoulder and eyes, while the least affected body parts were the knee calf and the ankle. Furthermore, the prevalence of work-related 'musculoskeletal' malfunctioning was linked with long working hours (6 - 8 hrs.) per day, lack of back support on their seats, glare on the monitor, inadequate regular break, repetitive motion of the upper limbs, and wrist when using the computer. Finally, based on these findings some recommendations were made to reduce the prevalent of WRMSDs among office workers.

Keywords: work related musculoskeletal disorder, Nigeria, office computer users, ergonomic risk factor

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Authors: Libena Cernohorska, Jan Cernohorsky

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This article aims to evaluate the impact of loans provided within the Czech banking sector on the growth of the Czech economy. The article is based on research of current scientific findings in respect to bank loans and economic development. The paper is based on data taken from the Czech Statistical Office on the development of the gross domestic product and data from the Czech National Bank on the development of loans from the period 2004-2015. Links between selected variables are tested using Granger causality tests. The results calculated confirm the hypothesis of the impact of the loans on economic growth, with a six-month delay. The results thus correspond to the standard economic findings and results of most previous studies.

Keywords: bank, business cycle, economic growth, loans

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Authors: Kristina Sakalauskiene, Renaldas Raisutis, Gintare Linkeviciute, Skaidra Valiukeviciene

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Cutaneous melanoma is a melanocytic skin tumour, which has a very poor prognosis while is highly resistant to treatment and tends to metastasize. Thickness of melanoma is one of the most important biomarker for stage of disease, prognosis and surgery planning. In this study, we hypothesized that the automatic analysis of spectrophotometric images and high-frequency ultrasonic 2D data can improve differential diagnosis of cutaneous melanoma and provide additional information about tumour penetration depth. This paper presents the novel complex automatic system for non-invasive melanocytic skin tumour differential diagnosis and penetration depth evaluation. The system is composed of region of interest segmentation in spectrophotometric images and high-frequency ultrasound data, quantitative parameter evaluation, informative feature extraction and classification with linear regression classifier. The segmentation of melanocytic skin tumour region in ultrasound image is based on parametric integrated backscattering coefficient calculation. The segmentation of optical image is based on Otsu thresholding. In total 29 quantitative tissue characterization parameters were evaluated by using ultrasound data (11 acoustical, 4 shape and 15 textural parameters) and 55 quantitative features of dermatoscopic and spectrophotometric images (using total melanin, dermal melanin, blood and collagen SIAgraphs acquired using spectrophotometric imaging device SIAscope). In total 102 melanocytic skin lesions (including 43 cutaneous melanomas) were examined by using SIAscope and ultrasound system with 22 MHz center frequency single element transducer. The diagnosis and Breslow thickness (pT) of each MST were evaluated during routine histological examination after excision and used as a reference. The results of this study have shown that automatic analysis of spectrophotometric and high frequency ultrasound data can improve non-invasive classification accuracy of early-stage cutaneous melanoma and provide supplementary information about tumour penetration depth.

Keywords: cutaneous melanoma, differential diagnosis, high-frequency ultrasound, melanocytic skin tumours, spectrophotometric imaging

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Authors: W. Mahmood Mat Yunus, Faris Mohammed Ali, Zainal Abidin Talib

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In this study we present new data for the thermal conductivity enhancement in four nanofluids containing 11, 25, 50, 63 nm diameter aluminum oxide (Al2O3) nanoparticles in distilled water. The nanofluids were prepared using single step method (i.e. by dispersing nanoparticle directly in base fluid) which was gathered in ultrasonic device for approximately 7 hours. The transient hot-wire laser beam displacement technique was used to measure the thermal conductivity and thermal diffusivity of the prepared nanofluids. The thermal conductivity and thermal diffusivity were obtained by fitting the experimental data to the numerical data simulated for aluminum oxide in distilled water. The results show that the thermal conductivity and thermal diffusivity of nanofluids increases in non-linear behavior as the particle size increases. While, the thermal conductivity and thermal diffusivity of Al2O3 nanofluids was observed increasing linearly with concentration as the volume fraction concentration increases. We believe that the interfacial layer between solid/fluid is the main factor for the enhancement of thermal conductivity and thermal diffusivity of Al2O3 nanofluids in the present work.

Keywords: transient hot wire-laser beam technique, Al2O3 nanofluid, particle size, volume fraction concentration

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Authors: Azazhu Wassie

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This study tried to evaluate the maximum design flood for appurtenance structure design using the given climatological and hydrological data analysis on the referenced study area. The maximum design flood is determined by using flood frequency analysis. Using this method, the peak discharge is 32,583.67 m3/s, but the data is transferred because the dam site is not on the gauged station. Then the peak discharge becomes 38,115 m3/s. The study was conducted in June 2023. This dam is built across a river to create a reservoir on its upstream side for impounding water. The water stored in the reservoir is used for various purposes, such as irrigation, hydropower, navigation, fishing, etc. The total average volume of annual runoff is estimated to be 115.1 billion m3. The total potential of the land for irrigation development can go beyond 3 million ha.

Keywords: dam design, flow duration curve, peak flood, rainfall, reservoir capacity, risk and reliability

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Authors: Mohammed Wadi, Bedri Kekezoglu, Mustafa Baysal, Mehmet Rida Tur, Abdulfetah Shobole

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This paper investigates the technical evaluation of the wind potential for present and future investments in Turkey taking into account the feasibility of sites, installments, operation, and maintenance. This evaluation based on the hourly measured wind speed data for the three years 2008–2010 at 30 m height for Çatalca district. These data were obtained from national meteorology station in Istanbul–Republic of Turkey are analyzed in order to evaluate the feasibility of wind power potential and to assure supreme assortment of wind turbines installing for the area of interest. Furthermore, the data are extrapolated and analyzed at 60 m and 80 m regarding the variability of roughness factor. Weibull bi-parameter probability function is used to approximate monthly and annually wind potential and power density based on three calculation methods namely, the approximated, the graphical and the energy pattern factor methods. The annual mean wind power densities were to be 400.31, 540.08 and 611.02 W/m² for 30, 60, and 80 m heights respectively. Simulation results prove that the analyzed area is an appropriate place for constructing large-scale wind farms.

Keywords: wind potential in Turkey, Weibull bi-parameter probability function, the approximated method, the graphical method, the energy pattern factor method, capacity factor

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Authors: Benmessaoud Hassen

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The sensitivity to the desertification map of the south of Aurès region has been elaborated by the crossing of four thematic layers capable to have an impact on the process of desertification. The following step is inspired of MEDALUS (Mediterranean desertification and land Use), which use qualitative index to define the environment zones sensitive to the desertification. The cartographical information of vegetation, the climate, the soil and the socioeconomic state descended from cartographic data transformed to numerical data then seized on, structured and managed by an algorithm dedicated to a geographical information system. In step with information, each layer makes object of 3 or 4 classes, the geometrical median of the four layers used are leaded to sensitivity classes (ISD) of different mapped environment.

Keywords: information systems, thematic layers, the sensitivity to the desertification map, concept MEDALUS, South of Aurès

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Authors: Ali Nabavi, Farimah Safari, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Hossein Molavi Vardanjani

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Cognitive impairment presents a significant and increasing health concern as populations age. Environmental risk factors such as heavy metal exposure are suspected contributors, but their specific roles remain incompletely understood. Machine learning offers a promising approach to integrate multi-factorial data and improve the prediction of cognitive outcomes. This study aimed to develop and validate machine learning models to predict early risk of cognitive impairment by incorporating demographic, clinical, and biomarker data, including measures of heavy metal exposure. A retrospective analysis was conducted using 2011-2014 National Health and Nutrition Examination Survey (NHANES) data. The dataset included participants aged 20 years and older who underwent cognitive testing. Variables encompassed demographic information, medical history, lifestyle factors, and biomarkers such as blood and urine levels of lead, cadmium, manganese, and other metals. Machine learning algorithms were trained on 90% of the data and evaluated on the remaining 10%, with performance assessed through metrics such as accuracy, area under curve (AUC), and sensitivity. Analysis included 2,933 participants. The stacking ensemble model demonstrated the highest predictive performance, achieving an AUC of 0.778 and a sensitivity of 0.879 on the test dataset. Key predictors included age, gender, hypertension, education level, urinary cadmium, and blood manganese levels. The findings indicate that machine learning can effectively predict the risk of cognitive impairment using a comprehensive set of clinical and environmental exposure data. Incorporating biomarkers of heavy metal exposure improved prediction accuracy and highlighted the role of environmental factors in cognitive decline. Further prospective studies are recommended to validate the models and assess their utility over time.

Keywords: cognitive impairment, heavy metal exposure, predictive models, aging

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: M. R. Babaei, S. M. Hosseini, S. Rahmani, L. Moradi

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Today, the quality of education and training systems and the effectiveness of the education systems of most concern to stakeholders and decision-makers of our country's development in each country. In Iran this is a double issue of concern to numerous reasons; So that governments, over the past decade have hardly even paid the running costs of education. ICT is claiming it has the power to change the structure of a program for training, reduce costs and increase quality, and do education systems and products consistent with the needs of the community and take steps to practice education. Own of the areas that the introduction of information technology has fundamentally changed is the field of education. The aim of this research is process reengineering management in schools simultaneously has been using field studies to collect data in the form of interviews and a questionnaire survey. The statistical community of this research has been the country of Iran and smart schools under the education. Sampling was targeted. The data collection tool was a questionnaire composed of two parts. The questionnaire consists of 36 questions that each question designates one of effective factors on the management of smart schools. Also each question consists of two parts. The first part designates the operating position in the management process, which represents the domain's belonging to the management agent (planning, organizing, leading, controlling). According to the classification of Dabryn and in second part the factors affect the process of managing the smart schools were examined, that Likert scale is used to classify. Questions the validity of the group of experts and prominent university professors in the fields of information technology, management and reengineering of approved and Cronbach's alpha reliability and also with the use of the formula is evaluated and approved. To analyse the data, descriptive and inferential statistics were used to analyse the factors contributing to the rating of (Linkert scale) descriptive statistics (frequency table data, mean, median, mode) was used. To analyse the data using analysis of variance and nonparametric tests and Friedman test, the assumption was evaluated. The research conclusions show that the factors influencing the management process re-engineering smart schools in school performance is affected.

Keywords: re-engineering, management process, smart school, Iran's school

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Authors: Shorena Tsiklauri

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Out-migration is an important issue for Georgia as well as since independence has loosed due to emigration one fifth of its population. During Soviet time out-migration from USSR was almost impossible and one of the most important instruments in regulating population movement within the Soviet Union was the system of compulsory residential registrations, so-called “propiska”. Since independent here was not any regulation for migration from Georgia. The majorities of Georgian migrants go abroad by tourist visa and then overstay, becoming the irregular labor migrants. The official statistics on migration published for this period was based on the administrative system of population registration, were insignificant in terms of numbers and did not represent the real scope of these migration movements. This paper discusses the data quality and methodology of migration statistics in Georgia and we are going to answer the questions: what is the real reason of increasing immigration flows according to the official numbers since 2000s?

Keywords: data quality, Georgia, methodology, migration

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Authors: Gabriel Chenevert, Abhilash Arora, Zeljko Pantic

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The major problem underwater acoustic communication faces is the low data rate due to low signal frequency. By contrast, the Wi-Fi communication protocol offers high throughput but limited operating range due to the attenuation effect of the sea and ocean medium. However, short-range near-field underwater wireless power transfer systems offer an environment where Wi-Fi communication can be effectively integrated to collect data and deliver instructions to sensors in underwater sensor networks. In this paper, low-power, low-cost off-the-shelf Wi-Fi modules are explored experimentally for four selected parameters for different distances between units and water salinities. The results reveal a shorter operating range and stronger dependence on water salinity than reported so far for high-end Wi-Fi modules.

Keywords: Wi-Fi, wireless power transfer, underwater communications, ESP

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Authors: Bruna P. De Souza, Ricardo C. De Almeida

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In some cities in the State of Parana – Brazil and in other countries atmospheric bromeliads (Tillandsia spp - Bromeliaceae) are considered weeds in trees, electric power lines, satellite dishes and other artificial supports. In this study, a numerical model was developed to simulate the seed dispersal of the Tillandsia recurvata species by wind with the objective of evaluating seeds displacement in the city of Ponta Grossa – PR, Brazil, since it is considered that the region is already infested. The model simulates the dispersal of each individual seed integrating parameters from the atmospheric boundary layer (ABL) and the local wind, simulated by the Weather Research Forecasting (WRF) mesoscale atmospheric model for the 2012 to 2015 period. The dispersal model also incorporates the approximate number of bromeliads and source height data collected from most infested electric power lines. The seeds terminal velocity, which is an important input data but was not available in the literature, was measured by an experiment with fifty-one seeds of Tillandsia recurvata. Wind is the main dispersal agent acting on plumed seeds whereas atmospheric turbulence is a determinant factor to transport the seeds to distances beyond 200 meters as well as to introduce random variability in the seed dispersal process. Such variability was added to the model through the application of an Inverse Fast Fourier Transform to wind velocity components energy spectra based on boundary-layer meteorology theory and estimated from micrometeorological parameters produced by the WRF model. Seasonal and annual wind means were obtained from the surface wind data simulated by WRF for Ponta Grossa. The mean wind direction is assumed to be the most probable direction of bromeliad seed trajectory. Moreover, the atmospheric turbulence effect and dispersal distances were analyzed in order to identify likely regions of infestation around Ponta Grossa urban area. It is important to mention that this model could be applied to any species and local as long as seed’s biological data and meteorological data for the region of interest are available.

Keywords: atmospheric turbulence, bromeliad, numerical model, seed dispersal, terminal velocity, wind

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Authors: Ankur P. Sati, Manju Mohan

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The hazardous combination of smoke and pollutant gases, smog, is harmful for health. There are strong evidences that the Agricultural waste burning (AWB) in the Northern India leads to adverse air quality in Delhi and its surrounding regions. A severe smog episode was observed over Delhi, India during November 2012 which resulted in very low visibility and various respiratory problems. Very high values of pollutants (PM10 as high as 989 µg m-3, PM2.5 as high as 585 µg m-3 an NO2 as high as 540 µg m-3) were measured all over Delhi during the smog episode. Ultra Violet Aerosol Index (UVAI) from Aura satellite and Aerosol Optical Depth (AOD) are used in the present study along with the output trajectories from HYSPLIT model and the in-situ data. Satellite data also reveal that AOD, UVAI are always at its highest during the farmfires duration in Punjab region of India and the extent of these farmfires may be increasing. It is observed that during the smog episode all the AOD, UVAI, PM2.5 and PM10 values surpassed those of the Diwali period (one of the most polluted events in the city) by a considerable amount at all stations across Delhi. The parameters used from the remote sensing data and the ground based observations at various stations across Delhi are very well in agreement about the intensity of Smog episode. The analysis clearly shows that regional pollution can have greater contributions in deteriorating the air quality than the local under adverse meteorological conditions.

Keywords: smog, farmfires, AOD, remote sensing

Procedia PDF Downloads 245

Authors: Aleksandra Czubek

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As AI systems increasingly shape content creation, existing copyright frameworks face significant challenges in determining liability for AI-generated outputs. Current legal discussions largely focus on who bears responsibility for infringing works, be it developers, users, or entities benefiting from AI outputs. This paper introduces a novel concept of algorithmic obligations, proposing that AI developers be subject to proactive duties that ensure their models prevent copyright infringement before it occurs. Building on principles of obligations law traditionally applied to human actors, the paper suggests a shift from reactive enforcement to proactive legal requirements. AI developers would be legally mandated to incorporate copyright-aware mechanisms within their systems, turning optional safeguards into enforceable standards. These obligations could vary in implementation across international, EU, UK, and U.S. legal frameworks, creating a multi-jurisdictional approach to copyright compliance. This paper explores how the EU’s existing copyright framework, exemplified by the Copyright Directive (2019/790), could evolve to impose a duty of foresight on AI developers, compelling them to embed mechanisms that prevent infringing outputs. By drawing parallels to GDPR’s “data protection by design,” a similar principle could be applied to copyright law, where AI models are designed to minimize copyright risks. In the UK, post-Brexit text and data mining exemptions are seen as pro-innovation but pose risks to copyright protections. This paper proposes a balanced approach, introducing algorithmic obligations to complement these exemptions. AI systems benefiting from text and data mining provisions should integrate safeguards that flag potential copyright violations in real time, ensuring both innovation and protection. In the U.S., where copyright law focuses on human-centric works, this paper suggests an evolution toward algorithmic due diligence. AI developers would have a duty similar to product liability, ensuring that their systems do not produce infringing outputs, even if the outputs themselves cannot be copyrighted. This framework introduces a shift from post-infringement remedies to preventive legal structures, where developers actively mitigate risks. The paper also breaks new ground by addressing obligations surrounding the training data of large language models (LLMs). Currently, training data is often treated under exceptions such as the EU’s text and data mining provisions or U.S. fair use. However, this paper proposes a proactive framework where developers are obligated to verify and document the legal status of their training data, ensuring it is licensed or otherwise cleared for use. In conclusion, this paper advocates for an obligations-centered model that shifts AI-related copyright law from reactive litigation to proactive design. By holding AI developers to a heightened standard of care, this approach aims to prevent infringement at its source, addressing both the outputs of AI systems and the training processes that underlie them.

Keywords: ip, technology, copyright, data, infringement, comparative analysis

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Authors: Nabamita Nath, Sanghamitra Sarkar

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Urban development in traditional neighbourhoods of cities is undergoing a sea change due to imposition of irregular development patterns on a predominantly inclusive urban fabric. In recent times, traditional neighbourhoods of Kolkata have experienced irregular urban development which has resulted in transformation of its immediate urban character. The goal is to study and analyse impact of new urban developments within traditional neighbourhoods of Kolkata and establish development guidelines to balance the old with the new. Various cities predominantly in third world countries are also experiencing similar development patterns in their traditional neighbourhoods. Existing literature surveys of development patterns in such neighbourhoods have established 9 major parameters viz. edge, movement, node, landmark, size-density, pattern-grain-texture, open spaces, urban spaces, urban form and views-vistas of the neighbourhood. To evaluate impact of urban development in traditional neighbourhoods of Kolkata, 3 different areas have been chronologically selected based on their settlement patterns. Parameters established through literature surveys have been applied to the selected areas to study and analyse the existing patterns of development. The main sources of this study included extensive on-site surveys, academic archive, census data, organisational records and informational websites. Applying the established parameters, 5 major conclusions were derived. Firstly, it was found that pedestrian friendly neighbourhoods of the city were becoming more car-centric. This has resulted in loss of interactive and social spaces which defined the cultural heritage of Kolkata. Secondly, the urban pattern which was composed of dense and compact fabric is gradually losing its character due to incorporation of new building typologies. Thirdly, the new building typologies include gated communities with private open spaces which is a stark departure from the existing built typology. However, these open spaces have not contributed in creation of inclusive public places for the community which are a significant part of such heritage neighbourhood precincts. Fourthly, commercial zones that primarily developed along major access routes have now infiltrated within these neighbourhoods. Gated communities do not favour formation of on-street commercial activities generating haphazard development patterns. Lastly, individual residential buildings that reflected Indo-saracenic and Neo-gothic architectural styles are converting into multi-storeyed residential apartments. As a result, the axis that created a definite visual identity for a neighbourhood is progressively following an irregular pattern. Thus, uniformity of the old skyline is gradually becoming inconsistent. The major issue currently is threat caused by irregular urban development to heritage zones and buildings of traditional neighbourhoods. Streets, lanes, courtyards, open spaces and buildings of old neighbourhoods imparted a unique cultural identity to the city that is disappearing with emerging urban development patterns. It has been concluded that specific guidelines for urban development should be regulated primarily based on existing urban form of traditional neighbourhoods. Such neighbourhood development strategies should be formulated for various cities of third world countries to control irregular developments thereby balancing heritage and development.

Keywords: heritage, Kolkata, traditional neighbourhood, urban development

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Authors: Bonnie R. Brammall, Rhonda M. Garad, Helena J. Teede, Cheryce L. Harrison

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Introduction: Reproductive aged women are at high-risk for accelerated weight gain and obesity development, with pregnancy recognised as a critical contributory life phase. Healthy lifestyle interventions during the preconception and antenatal period improve maternal and infant health outcomes. Yet, interventions from preconception through to postpartum and translation and implementation into real-world healthcare settings remain limited. OptimalMe is a randomised, hybrid implementation effectiveness study of evidence-based healthy lifestyle intervention. Here, we report engagement, acceptability of the intervention during preconception, and self-reported behaviour change outcomes as a result of the preconception phase of the intervention. Methods: Reproductive aged women who upgraded their private health insurance to include pregnancy and birth cover, signalling a pregnancy intention, were invited to participate. Women received access to an online portal with preconception health and lifestyle modules, goal-setting and behaviour change tools, monthly SMS messages, and two coaching sessions (randomised to video or phone) prior to pregnancy. Results: Overall n=527 expressed interest in participating. Of these, n=33 did not meet inclusion criteria, n=8 were not contactable for eligibility screening, and n=177 failed to engage after the screening, leaving n=309 who were enrolled in OptimalMe and randomised to intervention delivery method. Engagement with coaching sessions dropped by 25% for session two, with no difference between intervention groups. Women had a mean (SD) age of 31.7 (4.3) years and, at baseline, a self-reported mean BMI of 25.7 (6.1) kg/m², with 55.8% (n=172) of a healthy BMI. Behaviour was sub-optimal with infrequent self-weighing (38.1%), alcohol consumption prevalent (57.1%), sub-optimal pre-pregnancy supplementation (61.5%), and incomplete medical screening. Post-intervention 73.2% of women reported engagement with a GP for preconception care and improved lifestyle behaviour (85.5%), since starting OptimalMe. Direct pre-and-post comparison of individual participant data showed that of 322 points of potential change (up-to-date cervical screening, elimination of high-risk behaviours [alcohol, drugs, smoking], uptake of preconception supplements and improved weighing habits) 158 (49.1%) points of change were achieved. Health coaching sessions were found to improve accountability and confidence, yet further personalisation and support were desired. Engagement with video and phone sessions was comparable, having similar impacts on behaviour change, and both methods were well accepted and increased women's accountability. Conclusion: A low-intensity digital health and lifestyle program with embedded health coaching can improve the uptake of preconception care and lead to self-reported behaviour change. This is the first program of its kind to reach an otherwise healthy population of women planning a pregnancy. Women who were otherwise healthy showed divergence from preconception health and lifestyle objectives and benefited from the intervention. OptimalMe shows promising results for population-based behaviour change interventions that can improve preconception lifestyle habits and increase engagement with clinical health care for pregnancy preparation.

Keywords: preconception, pregnancy, preventative health, weight gain prevention, self-management, behaviour change, digital health, telehealth, intervention, women's health

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Authors: Stoyan Nedeltchev, Markus Schubert

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By means of the ultrafast X-ray tomography facility, data were obtained at different superficial gas velocities U_G in a bubble column (0.1 m in ID) operated with an air-deionized water system at ambient conditions. Raw reconstructed images were treated by both the information entropy (IE) and the reconstruction entropy (RE) algorithms in order to identify the main transition velocities in a bubble column. The IE values exhibited two well-pronounced minima at U_G=0.025 m/s and U_G=0.085 m/s identifying the boundaries of the homogeneous, transition and heterogeneous regimes. The RE extracted from the central region of the column’s cross-section exhibited only one characteristic peak at U_G=0.03 m/s, which was attributed to the transition from the homogeneous to the heterogeneous flow regime. This result implies that the transition regime is non-existent in the core of the column.

Keywords: bubble column, ultrafast X-ray tomography, information entropy, reconstruction entropy

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