Search results for: artificial oil bodies

Authors: Bhargavi G. Iyer, Ojaswi Bhagat

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It is often noted that the value of a novel idea lies in its successful implementation. However, successful implementation requires the nurturing and encouragement of innovation. Nascent competitors are a true representation of innovation in any given industry. A nascent competitor is an entity whose prospective innovation poses a future threat to an incumbent dominant competitor. While a nascent competitor benefits in several ways, it is also exposed significantly and is at greater risk of facing the brunt of exclusionary practises and abusive conduct by dominant incumbent competitors in the industry. This research paper aims to explore the risks and threats faced by nascent competitors and analyse the benefits they accrue as well as the advantages they proffer to the economy; through an analytical, critical study. In such competitive market environments, a rise of the acquisitions of nascent competitors by the incumbent dominants is observed. Therefore, this paper will examine the dynamics of nascent acquisition. Further, this paper hopes to specifically delve into the role of antitrust bodies in regulating nascent acquisition. This paper also aspires to deal with the question how to distinguish harmful from harmless acquisitions in order to facilitate ideal enforcement practice. This paper proposes mechanisms of scrutiny in order to ensure healthy market practises and efficient merger control in the context of nascent acquisitions. Taking into account the scope and nature of the topic, as well as the resources available and accessible, a combination of the methods of doctrinal research and analytical research were employed, utilising secondary sources in order to assess and analyse the subject of research. While legally evaluating the Killer Acquisition theory and the Nascent Potential Acquisition theory, this paper seeks to critically survey the precedents and instances of nascent acquisitions. In addition to affording a compendious account of the legislative framework and regulatory mechanisms in the United States, the United Kingdom, and the European Union; it hopes to suggest an internationally practicable legal foundation for domestic legislation and enforcement to adopt. This paper hopes to appreciate the complexities and uncertainties with respect to nascent acquisitions and attempts to suggest viable and plausible policy measures in antitrust law. It additionally attempts to examine the effects of such nascent acquisitions upon the consumer and the market economy. This paper weighs the argument of shifting the evidentiary burden on to the merging parties in order to improve merger control and regulation and expounds on its discovery of the strengths and weaknesses of the approach. It is posited that an effective combination of factual, legal, and economic analysis of both the acquired and acquiring companies possesses the potential to improve ex post and ex ante merger review outcomes involving nascent companies; thus, preventing anti-competitive practises. This paper concludes with an analysis of the possibility and feasibility of industry-specific identification of anti-competitive nascent acquisitions and implementation of measures accordingly.

Keywords: acquisition, antitrust law, exclusionary practises merger control, nascent competitor

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Authors: H. Aljabiry, L. Bailey, S. Young

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Qatar is a desert with an average temperature 37⁰C, reaching over 40⁰C during summer. Precipitation is uncommon and mostly in winter. Qatar depends on desalination for drinking water and on groundwater and recycled water for irrigation. Water consumption and network leakage per capita in Qatar are amongst the highest in the world; re-use of treated wastewater is extremely limited with only 14% of treated wastewater being used for irrigation. This has led to the country disposing of unwanted water from various sources in lagoons situated around the country, causing concern over the possibility of environmental pollution. Accordingly, our hypothesis underpinning this research is that the quality and quantity of water in lagoons is having an impact on the groundwater reservoirs in Qatar. Lagoons (n = 14) and wells (n = 55) were sampled for both summer and winter in 2018 (summer and winter). Water, adjoining soil and plant samples were analysed for multiple elements by Inductively Coupled Plasma Mass Spectrometry. Organic and inorganic carbon were measured (CN analyser) and the major anions were determined by ion chromatography. Salinization in both the lagoon and the wells was seen with good correlations between Cl⁻, Na⁺, Li, SO₄, S, Sr, Ca, Ti (p-value < 0.05). Association of heavy metals was observed of Ni, Cu, Ag, and V, Cr, Mo, Cd which is due to contamination from anthropological activities such as wastewater disposal or spread of contaminated dust. However, looking at each elements none of them exceeds the Qatari regulation. Moreover, gypsum saturation in the system was observed in both the lagoon and wells water samples. Lagoons and the water of the well are found to be of a saline type as well as Ca²⁺, Cl⁻, SO₄²⁻ type evidencing both gypsum dissolution and salinization in the system. Moreover, Maps produced by Inverse distance weighting showed an increasing level of Nitrate in the groundwater in winter, and decrease chloride and sulphate level, indicating recharge effect after winter rain events. While E. coli and faecal bacteria were found in most of the lagoons, biological analysis for wells needs to be conducted to understand the biological contamination from lagoon water infiltration. As a conclusion, while both the lagoon and the well showed the same results, more sampling is needed to understand the impact of the lagoons on the groundwater.

Keywords: groundwater quality, lagoon, treated wastewater, water management, wastewater treatment, wetlands

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Authors: Fatih Frank Alparslan

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The aviation industry is at a crucial turning point due to modern technologies, environmental concerns, and changing ways of transporting people and goods globally. The paper examines these challenges and opportunities comprehensively. It emphasizes the role of innovative management and advanced technology in shaping the future of air travel. This study begins with an overview of the current state of the aviation industry, identifying key areas where innovation and technology could be highly beneficial. It explores the latest advancements in airplane design, propulsion, and materials. These technological advancements are shown to enhance aircraft performance and environmental sustainability. The paper also discusses the use of artificial intelligence and machine learning in improving air traffic control, enhancing safety, and making flight operations more efficient. The management of these technologies is critically important. Therefore, the research delves into necessary changes in organization, culture, and operations to support innovation. It proposes a management approach that aligns with these modern technologies, underlining the importance of forward-thinking leaders who collaborate across disciplines and embrace innovative ideas. The paper addresses challenges in adopting these innovations, such as regulatory barriers, the need for industry-wide standards, and the impact of technological changes on jobs and society. It recommends that governments, aviation businesses, and educational institutions collaborate to address these challenges effectively, paving the way for a more innovative and eco-friendly aviation industry. In conclusion, the paper argues that the future of aviation relies on integrating new management practices with innovative technologies. It urges a collective effort to push beyond current capabilities, envisioning an aviation industry that is safer, more efficient, and environmentally responsible. By adopting a broad approach, this research contributes to the ongoing discussion about resolving the complex issues facing today's aviation sector, offering insights and guidance to prepare for future advancements.

Keywords: aviation innovation, technology integration, environmental sustainability, management strategies, multidisciplinary approach

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Authors: M. Y. Abubakar, Ipinjolu J. K., Yuzine B. Esa, Magawata I., Hassan W. A., Turaki A. A.

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Catfish (Heterobranchus spp.) is a major freshwater fish that are widely distributed in Nigeria waters and are gaining rapid aquaculture expansion. However, indiscriminate artificial crossbreeding of the species with others poses a threat to their biodiversity. There is a paucity of information about the genetic variability, hence this insight on the genetic variability is badly needed, not only for the species conservation but for aquaculture expansion. In this study, we tested the level of Genetic diversity, population differentiation and phylogenetic relationship analysis on 35 individuals of two populations of Heterobranchus bidorsalis and 29 individuals of three populations of Heterobranchus longifilis using the mitochondrial cytochrome c oxidase subunit I (mtDNA COI) gene sequence. Nucleotide sequences of 650 bp fragment of the COI gene of the two species were compared. In the whole 4 and 5 haplotypes were distinguished in the populations of H. bidorsalis & H. longifilis with accession numbers (MG334168 - MG334171 & MG334172 to MG334176) respectively. Haplotypes diversity indices revealed a range of 0.59 ± 0.08 to 0.57 ± 0.09 in H. bidorsalis and 0.000 to 0.001051 ± 0.000945 in H. longifilis population, respectively. Analysis of molecular variance (AMOVA) revealed no significant variation among H. bidorsalis population of the Niger & Benue Rivers, detected significant genetic variation was between the Rivers of Niger, Kaduna and Benue population of H. longifilis. Two main clades were recovered, showing a clear separation between H. bidorsalis and H. longifilis in the phylogenetic tree. The mtDNA COI genes studied revealed high gene flow between populations with no distinct genetic differentiation between the populations as measured by the fixation index (FST) statistic. However, a proportion of population-specific haplotypes was observed in the two species studied, suggesting a substantial degree of genetic distinctiveness for each of the population investigated. These findings present the description of the species character and accessions of the fish’s genetic resources, through gene sequence submitted in Genetic database. The data will help to protect their valuable wild resource and contribute to their recovery and selective breeding in Nigeria.

Keywords: AMOVA, genetic diversity, Heterobranchus spp., mtDNA COI, phylogenetic tree

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Authors: Saad Zagloul Shokri Melika

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The London College of Communication is one of the only universities in the world to offer a lifestyle journalism master’s degree. A hybrid originally constructed largely out of a generic journalism program crossed with numerous cultural studies approaches, the degree has developed into a leading lifestyle journalism education attracting students worldwide. This research project seeks to present a framework for structuring the degree as well as to understand how students in this emerging field of study value the program. While some researchers have addressed questions about journalism and higher education, none have looked specifically at the increasingly important genre of lifestyle journalism, which Folker Hanusch defines as including notions of consumerism and critique among other identifying traits. Lifestyle journalism, itself poorly researched by scholars, can relate to topics including travel, fitness, and entertainment, and as such, arguably a lifestyle journalism degree should prepare students to engage with these topics. This research uses the existing Masters of Arts and Lifestyle Journalism at the London College of Communications as a case study to examine the school’s approach. Furthering Hanusch’s original definition, this master’s program attempts to characterizes lifestyle journalism by a specific voice or approach, as reflected in the diversity of student’s final projects. This framework echoes the ethos and ideas of the university, which focuses on creativity, design, and experimentation. By analyzing the current degree as well as student feedback, this research aims to assist future educators in pursuing the often neglected field of lifestyle journalism. Through a discovery of the unique mix of practical coursework, theoretical lessons, and broad scope of student work presented in this degree program, researchers strive to develop a framework for lifestyle journalism education, referring to Mark Deuze’s ten questions for journalism education development. While Hanusch began the discussion to legitimize the study of lifestyle journalism, this project strives to go one step further and open up a discussion about teaching of lifestyle journalism at the university level.

Keywords: Journalism, accountability, education, television, publicdearth, investigative, journalism, Nigeria, journalismeducation, lifestyle, university

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Authors: Shewit Kidane, Abebe Getahun, Wassie Anteneh, Admassu Demeke, Peter Goethals

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We have reviewed major findings of scientific studies on Lake Tana fish resources and their threats. The aim was to provide summarized information for all concerned bodies and international readers to get full and comprehensive picture about the lake’s fish resource and conservation problems. The Lake Tana watershed comprise 28 fish species, of which 21 are endemic. Moreover, Lake Tana is the one among the top 250 lake regions of global importance for biodiversity and it is world recognized migratory birds wintering site. Lake Tana together with its adjacent wetlands provide directly and indirectly a livelihood for more than 500,000 people. However, owing to anthropogenic activities, the lake ecosystem as well as fish and attributes of the fisheries sector are severely degraded. Fish species in Lake Tana are suffering due to illegal fishing, damming, habitat/breeding ground degradation, wastewater disposal, introduction of exotic species, and lack of implementing fisheries regulations. Currently, more than 98% of fishers in Lake Tana are using the most destructive monofilament. Indeed, dams, irrigation schemes and hydropower are constructed in response to the emerging development need only. Mitigation techniques such as construction of fish ladders for the migratory fishes are the most forgotten. In addition, water resource developers are likely unaware of both the importance of the fisheries and the impact of dam construction on fish. As a result, the biodiversity issue is often missed. Besides, Lake Tana wetlands, which play vital role to sustain biodiversity, are not wisely utilised in the sense of the Ramsar Convention’s definition. Wetlands are considered as unhealthy and hence wetland conversion for the purpose of recession agriculture is still seen as advanced mode of development. As a result, many wetlands in the lake watershed are shrinking drastically over time and Cyprus papyrus, one of the characteristic features of Lake Tana, has dramatically declined in its distribution with some local extinction. Furthermore, the recently introduced water hyacinth (Eichhornia crassipes) is creating immense problems on the lake ecosystem. Moreover, currently, 1.56 million tons of sediment have deposited into the lake each year and wastes from the industries and residents are directly discharged into the lake without treatment. Recently, sign of eutrophication is revealed in Lake Tana and most coarsely, the incidence of cyanobacteria genus Microcystis was reported from the Bahir Dar Gulf of Lake Tana. Thus, the direct dependency of the communities on the lake water for drinking as well as to wash their body and clothes and its fisheries make the problem worst. Indeed, since it is home to many endemic migratory fish, such kind of unregulated developmental activities could be detrimental to their stocks. This can be best illustrated by the drastic stock reduction (>75% in biomass) of the world unique Labeobarbus species. So, unless proper management is put in place, the anthropogenic impacts can jeopardize the aquatic ecosystems. Therefore, in order to sustainably use the aquatic resources and fulfil the needs of the local people, every developmental activity and resource utilization should be carried out adhering to the available policies.

Keywords: anthropogenic impacts, dams, endemic fish, wetland degradation

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Authors: Neha Adsul, Rohit Shah

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Background: The global history of nursing is exclusively a history of deep contradictions as it seeks to negotiate inclusion in an already gendered world. Although a powerful 'clinical gaze exists, nurses have toiled to re-negotiate and subvert the 'medical gaze' by practicing the 'therapeutic gaze' to tether back 'care into nursing practice.' This helps address the duality of the 'body' and 'mind' wherein the patient is not just limited to being an object of medical inquiry. Nevertheless, there has been a consistent effort to fit 'nursing' into being an art or an emerging science over the years. Especially with advances in hospital-based techno-centric medical practices, the boundaries between technology and nursing practices are becoming more blurred as the technical process becomes synonymous with nursing, eroding the essence of nursing care. Aim: This paper examines the history of nursing and offers insights into how gendered relations and the ideological belief of 'nursing as gendered work' have propagated to the subjugation of the nursing profession. It further aims to provide insights into the patriarchally imbibed techno-centrism that negates the gendered caregiving which lies at the crux of a nurse's work. Method: A literature search was carried out using Google Scholar, Web of Science and PubMed databases. Search words included: technology and nursing, medical technology and nursing, history of nursing, sociology and nursing and nursing care. The history of nursing is presented in a discussion that weaves together the historical events of the 'Birth of the Clinic' and the shift from 'bed-side medicine' to 'hospital-based medicine' that legitimizes exploitation of the bodies of patients to the 'medical gaze while the emergence of nursing as acquiescent to instrumental, technical, positivist and dominant views of medicine. The resultant power asymmetries, wherein in contemporary nursing, the constant struggle of nurses to juggle between being the physicians "operational right arm" to harboring that subjective understanding of the patients to refrain from de-humanizing nursing-care. Findings: The nursing profession suffers from being rendered invisible due to gendered relations having patrifocal societal roots. This perpetuates a notion rooted in the idea that emphasizes empiricism and has resulted in theoretical and epistemological fragmentation of the understanding of body and mind as separate entities. Nurses operate within this structure while constantly being at the brink of being pushed beyond the legitimate professional boundaries while being labeled as being 'unscientific' as the work does not always corroborate and align with the existing dominant positivist lines of inquiries. Conclusion: When understood in this broader context of how nursing as a practice has evolved over the years, it provides a particularly crucial testbed for understanding contemporary gender relations. Not because nurses like to live in a gendered work trap but because the gendered relations at work are written in a covert narcissistic patriarchal milieu that fails to recognize the value of intangible yet utmost necessary 'caring work in nursing. This research urges and calls for preserving and revering the humane aspect of nursing care alongside the emerging tech-savvy expectations from nursing work.

Keywords: nursing history, technocentric, power relations, scientific duality

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Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: Asif Ali, Daud Salim Faruquie

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With the advancement of knowledge about the utility and impact of sustainability, its feasibility has been explored into different walks of life. Scientists, however; have established their knowledge in four areas viz environmental, economic, social and cultural, popularly termed as four pillars of sustainability. Aspects of environmental and economic sustainability have been rigorously researched and practiced and huge volume of strong evidence of effectiveness has been founded for these two sub-areas. For the social and cultural aspects of sustainability, dependable evidence of effectiveness is still to be instituted as the researchers and practitioners are developing and experimenting methods across the globe. Therefore, the present research aimed to identify globally used practices of social and cultural sustainability and through evidence synthesis assess their outcomes to determine the effectiveness of those practices. A PICO format steered the methodology which included all populations, popular sustainability practices including walkability/cycle tracks, social/recreational spaces, privacy, health & human services and barrier free built environment, comparators included ‘Before’ and ‘After’, ‘With’ and ‘Without’, ‘More’ and ‘Less’ and outcomes included Social well-being, cultural co-existence, quality of life, ethics and morality, social capital, sense of place, education, health, recreation and leisure, and holistic development. Search of literature included major electronic databases, search websites, organizational resources, directory of open access journals and subscribed journals. Grey literature, however, was not included. Inclusion criteria filtered studies on the basis of research designs such as total randomization, quasi-randomization, cluster randomization, observational or single studies and certain types of analysis. Studies with combined outcomes were considered but studies focusing only on environmental and/or economic outcomes were rejected. Data extraction, critical appraisal and evidence synthesis was carried out using customized tabulation, reference manager and CASP tool. Partial meta-analysis was carried out and calculation of pooled effects and forest plotting were done. As many as 13 studies finally included for final synthesis explained the impact of targeted practices on health, behavioural and social dimensions. Objectivity in the measurement of health outcomes facilitated quantitative synthesis of studies which highlighted the impact of sustainability methods on physical activity, Body Mass Index, perinatal outcomes and child health. Studies synthesized qualitatively (and also quantitatively) showed outcomes such as routines, family relations, citizenship, trust in relationships, social inclusion, neighbourhood social capital, wellbeing, habitability and family’s social processes. The synthesized evidence indicates slight effectiveness and efficacy of social and cultural sustainability on the targeted outcomes. Further synthesis revealed that such results of this study are due weak research designs and disintegrated implementations. If architects and other practitioners deliver their interventions in collaboration with research bodies and policy makers, a stronger evidence-base in this area could be generated.

Keywords: built environment, cultural sustainability, social sustainability, sustainable architecture

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Authors: Shalaka Kadam, Dinesh Apte, Sagar Mainkar

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The life cycle of products is becoming shorter and shorter due to increased competition in market, shorter product development time and increased product diversity. Short life cycles are normal in retail industry, style business, entertainment media, and telecom and semiconductor industry. The subject of accurate forecasting for demand of short lifecycle products is of special enthusiasm for many researchers and organizations. Due to short life cycle of products the amount of historical data that is available for forecasting is very minimal or even absent when new or modified products are launched in market. The companies dealing with such products want to increase the accuracy in demand forecasting so that they can utilize the full potential of the market at the same time do not oversupply. This provides the challenge to develop a forecasting model that can forecast accurately while handling large variations in data and consider the complex relationships between various parameters of data. Many statistical models have been proposed in literature for forecasting time series data. Traditional time series forecasting models do not work well for short life cycles due to lack of historical data. Also artificial neural networks (ANN) models are very time consuming to perform forecasting. We have studied the existing models that are used for forecasting and their limitations. This work proposes an effective and powerful forecasting approach for short life cycle time series forecasting. We have proposed an approach which takes into consideration different scenarios related to data availability for short lifecycle products. We then suggest a methodology which combines statistical analysis with structured judgement. Also the defined approach can be applied across domains. We then describe the method of creating a profile from analogous products. This profile can then be used for forecasting products with historical data of analogous products. We have designed an application which combines data, analytics and domain knowledge using point-and-click technology. The forecasting results generated are compared using MAPE, MSE and RMSE error scores. Conclusion: Based on the results it is observed that no one approach is sufficient for short life-cycle forecasting and we need to combine two or more approaches for achieving the desired accuracy.

Keywords: forecast, short life cycle product, structured judgement, time series

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Dorian Audot, Isobel Margaret Thompson, Dominic Hudson, Joseph Banks, Martin Warner

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In competitive swimming, after dives and turns, athletes perform underwater undulatory swimming (UUS), copying marine mammals’ method of locomotion. The body, performing this wave-like motion, accelerates the fluid downstream in its vicinity, generating propulsion with minimal resistance. Through this technique, swimmers can maintain greater speeds than surface swimming and take advantage of the overspeed granted by the dive (or push-off). Almost all previous work has considered UUS when performed at maximum effort. Critical parameters to maximize UUS speed are frequently discussed; however, this does not apply to most races. In only 3 out of the 16 individual competitive swimming events are athletes likely to attempt to perform UUS with the greatest speed, without thinking of the cost of locomotion. In the other cases, athletes will want to control the speed of their underwater swimming, attempting to maximise speed whilst considering energy expenditure appropriate to the duration of the event. Hence, there is a need to understand how swimmers adapt their underwater strategies to optimize the speed within the allocated energetic cost. This paper develops a consistent methodology that enables different sets of UUS kinematics to be investigated. These may have different propulsive efficiencies and force generation mechanisms (e.g.: force distribution along with the body and force magnitude). The developed methodology, therefore, needs to: (i) provide an understanding of the UUS propulsive mechanisms at different speeds, (ii) investigate the key performance parameters when UUS is not performed solely for maximizing speed; (iii) consistently determine the propulsive efficiency of a UUS technique. The methodology is separated into two distinct parts: kinematic data acquisition and computational fluid dynamics (CFD) analysis. For the kinematic acquisition, the position of several joints along the body and their sequencing were either obtained by video digitization or by underwater motion capture (Qualisys system). During data acquisition, the swimmers were asked to perform UUS at a constant depth in a prone position (facing the bottom of the pool) at different speeds: maximum effort, 100m pace, 200m pace and 400m pace. The kinematic data were input to a CFD algorithm employing a two-dimensional Large Eddy Simulation (LES). The algorithm adopted was specifically developed in order to perform quick unsteady simulations of deforming bodies and is therefore suitable for swimmers performing UUS. Despite its approximations, the algorithm is applied such that simulations are performed with the inflow velocity updated at every time step. It also enables calculations of the resistive forces (total and applied to each segment) and the power input of the modeled swimmer. Validation of the methodology is achieved by comparing the data obtained from the computations with the original data (e.g.: sustained swimming speed). This method is applied to the different kinematic datasets and provides data on swimmers’ natural responses to pacing instructions. The results show how kinematics affect force generation mechanisms and hence how the propulsive efficiency of UUS varies for different race strategies.

Keywords: CFD, efficiency, human swimming, hydrodynamics, underwater undulatory swimming

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Authors: Kremena Ivanona, Bistra Kunovska, Jana Djunova, Desislava Djunakova, Zdenka Stojanovska

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In recent decades, the general public has become increasingly interested in the impact of air pollutions on their health. Currently, numerous studies are aimed at identifying pollutants in the indoor environment where they carry out daily activities. Internal pollutants can be of both natural and artificial origin. With regard to natural pollutants, special attention is paid to natural radioactivity. In recent years, radon has been one of the most studied indoor pollutants because it has the greatest contribution to human exposure to natural radionuclides. It is a known fact that lung cancer can be caused by radon radiation and it is the second risk factor after smoking for the onset of the disease. The main objective of the study under the National Science Fund of Bulgaria, in the framework of grant No КП-06-Н23/1/07.12.2018 is to evaluate the indoor radon as an important air pollutant in school buildings in order to reduce the exposure to children. The measurements were performed in 48 schools located in 55 buildings in one Bulgarian administrative district (Kardjaly). The nuclear track detectors (CR-39) were used for measurements. The arithmetic and geometric means of radon concentrations are AM = 140 Bq/m3, and GM = 117 Bq/m3 respectively. In 51 school rooms, the radon levels were greater than 200 Bq/m3, and in 28 rooms, located in 17 school buildings, it exceeded the national reference level of 300 Bq/m3, defined in the Bulgarian ordinance on radiation protection (or 30% of the investigated buildings). The statistically significant difference in the values of radon concentration by municipalities (KW, р < 0.001) obtained showed that the most likely reason for the differences between the groups is the geographical location of the buildings and the possible influence of the geological composition. The combined effect of the year of construction (technical condition of the buildings) and the energy efficiency measures was considered. The values of the radon concentration in the buildings where energy efficiency measures have been implemented are higher than those in buildings where they have not been performed. This result confirms the need for investigation of radon levels before conducting the energy efficiency measures in buildings. Corrective measures for reducing the radon levels have been recommended in school buildings with high radon levels in order to decrease the children's exposure.

Keywords: air pollution, indoor radon, children exposure, schools

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Sayed M. Ahmed, Sawsan S. Darwish, Nagib A. Elmarzugi, Mohammad A. Al-Dosari, Mahmoud A. Adam, Nadia A. Al-Mouallimi

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The preservation of cultural heritage is a worldwide problem. Stone monuments represent an important part of this heritage, but due to their prevalently outdoor location, they are generally subject to a complex series of weathering and decay processes, in addition to physical and chemical factors, also biological agents usually play an important role in deterioration phenomena. The aim of this paper is to experimentally verify applicability and feasibility of titanium dioxide (TiO2) nanoparticles for the preservation of historical (architectural, monumental, archaeological) stone surfaces which enables to reduce the deterioration behaviors mentioned above. TiO2 nanoparticles dispersed in an aqueous colloidal suspension were applied directly on travertine (Marble and limestone often used in historical and monumental buildings) by spray-coating in order to obtain a nanometric film on stone samples. SEM, coupled with EDX microanalysis. (SEM-EDX), in order to obtain information oncoating homogeneity, surface morphology before and after aging and penetration depth of the TiO2 within the samples. Activity of the coated surface was evaluated with UV accelerated aging test. Capillary water absorption, thermal aging and colorimetric measurements have been performed on on coated and uncoated samples to evaluate their properties and estimate change of appearance with colour variation. Results show Tio2 nanoparticles good candidate for coating applications on calcareous stone, good water-repellence was observed on the samples after treatment; analyses were carried out on both untreated and freshly treated samples as well as after artificial aging. Colour change showed negligible variations on the coated or uncoated stone as well as after aging. Results showed that treated stone surfaces seem to be not affected after 1000 hours of exposure to UV radiation, no alteration of the original features.

Keywords: architectural and archaeological heritage, calcareous stone, photocatalysis TiO2, self-cleaning, thermal aging

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Authors: Sungpil Ha, Ju Yong Kang, Sangbaek Park, Seung-Ju Lee, Soo-Won Chae

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The growing number of obese patients in aging societies has led to an increase in the number of patients with knee medial osteoarthritis (OA). Artificial joint insertion is the most common treatment for knee medial OA. Surgery is effective for patients with serious arthritic symptoms, but it is costly and dangerous. It is also inappropriate way to prevent a disease as an early stage. Therefore Non-operative treatments such as toe-in gait are proposed recently. Toe-in gait is one of non-surgical interventions, which restrain the progression of arthritis and relieves pain by reducing knee adduction moment (KAM) to facilitate lateral distribution of load on to knee medial cartilage. Numerous studies have measured KAM in various foot progression angle (FPA), and KAM data could be obtained by motion analysis. However, variations in stress at knee cartilage could not be directly observed or evaluated by these experiments of measuring KAM. Therefore, this study applied motion analysis to major gait points (1st peak, mid –stance, 2nd peak) with regard to FPA, and to evaluate the effects of FPA on the human lower extremity, the finite element (FE) method was employed. Three types of gait analysis (toe-in, toe-out, baseline gait) were performed with markers placed at the lower extremity. Ground reaction forces (GRF) were obtained by the force plates. The forces associated with the major muscles were computed using GRF and marker trajectory data. MRI data provided by the Visible Human Project were used to develop a human lower extremity FE model. FE analyses for three types of gait simulations were performed based on the calculated muscle force and GRF. We observed the maximum stress point during toe-in gait was lower than the other types, by comparing the results of FE analyses at the 1st peak across gait types. This is the same as the trend exhibited by KAM, measured through motion analysis in other papers. This indicates that the progression of knee medial OA could be suppressed by adopting toe-in gait. This study integrated motion analysis with FE analysis. One advantage of this method is that re-modeling is not required even with changes in posture. Therefore another type of gait simulation or various motions of lower extremity can be easily analyzed using this method.

Keywords: finite element analysis, gait analysis, human model, motion capture

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Authors: Carmen Sica, Elena M. Scalisi, Sara Ignoto, Ludovica Palmeri, Martina Contino, Greta Ferruggia, Antonio Salvaggio, Santi C. Pavone, Gino Sorbello, Loreto Di Donato, Roberta Pecoraro, Maria V. Brundo

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Recently, a rise in the use of wireless internet technologies such as Wi-Fi and 5G routers/modems have been demonstrated. These devices emit a considerable amount of electromagnetic radiation (EMR), which could interact with the male reproductive system either by thermal or non-thermal mechanisms. The aim of this study was to investigate the direct in vitro influence of 5G radiation on sperm quality in Mytilus galloprovincialis, considered an excellent model for reproduction studies. The experiments at 27 GHz were conducted by using a no commercial high gain pyramidal horn antenna. To evaluate the specific absorption rate (SAR), a numerical simulation has been performed. The resulting incident power density was significantly lower than the power density limit of 10 mW/cm2 set by the international guidelines as a limit for nonthermal effects above 6 GHz. However, regarding temperature measurements of the aqueous sample, it has been verified an increase of 0.2°C, compared to the control samples. This very low-temperature increase couldn’t interfere with experiments. For experiments, sperm samples taken from sexually mature males of Mytilus galloprovincialis were placed in artificial seawater, salinity 30 + 1% and pH 8.3 filtered with a 0.2 m filter. After evaluating the number and quality of spermatozoa, sperm cells were exposed to electromagnetic fields a 27GHz. The effect of exposure on sperm motility and quality was evaluated after 10, 20, 30 and 40 minutes with a light microscope and also using the Eosin test to verify the vitality of the gametes. All the samples were performed in triplicate and statistical analysis was carried out using one-way analysis of variance (ANOVA) with Turkey test for multiple comparations of means to determine differences of sperm motility. A significant decrease (30%) in sperm motility was observed after 10 minutes of exposure and after 30 minutes, all sperms were immobile and not vital. Due to little literature data about this topic, these results could be useful for further studies concerning a great diffusion of these new technologies.

Keywords: mussel, spermatozoa, sperm motility, millimeter waves

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Authors: Haobin Zheng, Xiang Zhang, Yong Shen, Hongxin Zou

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The research focuses on mode-locked fiber lasers with a non-linear amplifying loop mirror (NALM). Although these lasers have shown potential, they still have limitations in terms of low repetition rate. The self-starting of mode-locking in NALM is influenced by the cross-phase modulation (XPM) effect, which has not been thoroughly studied. The aim of this study is two-fold. First, to overcome the difficulties associated with increasing the repetition rate in mode-locked fiber lasers with NALM. Second, to analyze the influence of XPM on self-starting of mode-locking. The power distributions of two counterpropagating beams in the NALM and the differential non-linear phase shift (NPS) accumulations are calculated. The analysis is conducted from the perspective of NPS accumulation. The differential NPSs for continuous wave (CW) light and pulses in the fiber loop are compared to understand the inverse saturable absorption (ISA) mechanism during pulse formation in NALM. The study reveals a difference in differential NPSs between CW light and pulses in the fiber loop in NALM. This difference leads to an ISA mechanism, which has not been extensively studied in artificial saturable absorbers. The ISA in NALM provides an explanation for experimentally observed phenomena, such as active mode-locking initiation through tapping the fiber or fine-tuning light polarization. These findings have important implications for optimizing the design of NALM and reducing the self-starting threshold of high-repetition-rate mode-locked fiber lasers. This study contributes to the theoretical understanding of NALM mode-locked fiber lasers by exploring the ISA mechanism and its impact on self-starting of mode-locking. The research fills a gap in the existing knowledge regarding the XPM effect in NALM and its role in pulse formation. This study provides insights into the ISA mechanism in NALM mode-locked fiber lasers and its role in selfstarting of mode-locking. The findings contribute to the optimization of NALM design and the reduction of self-starting threshold, which are essential for achieving high-repetition-rate operation in fiber lasers. Further research in this area can lead to advancements in the field of mode-locked fiber lasers with NALM.

Keywords: inverse saturable absorption, NALM, mode-locking, non-linear phase shift

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Authors: Mohammed Al Sulaimani, Hamad Al Manhi

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With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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Authors: Zhende Hou, Fan Yang, Guoli Zhang

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Dielectric elastomer is a promising class of Electroactive polymers which can deform in response to an applied electric field. Comparing general smart material, the Dielectric elastomer is more compliance and can achieve higher energy density, which can be for diverse applications such as actuators, artificial muscles, soft robotics, and energy harvesters. The coupling of the Electroactive polymers and the electric field is that the elastomer is sandwiched between two compliant electrodes and when the electrodes are subjected to a voltage, the positive and negative charges on the two electrodes compress the polymer, so that the polymer reduces in thickness and expands in area. However, the pre-stretched dielectric elastomer film not only can achieve large electric-field induced deformation but also is prone to wrinkling, under the interaction of its own strain energy and the applied electric field energy. For a uniaxially pre-stretched dielectric elastomer film, the electrode area is an important parameter to the electric-field induced deformation and may also be a key factor affecting the film wrinkling. To determine and quantify the effect experimentally, VHB 9473 tapes were employed and compliant electrodes with different areas were pant on each of them. The tape was first tensed to a uniaxial stretch of 8. Then a DC voltage was applied to the electrodes and increased gradually until wrinkling occurred in the film. Then, the critical wrinkling voltages of the film with different electrode areas were obtained, and the wrinkle wavelengths were obtained simultaneously for analyzing the wrinkling characteristics. Experimental results indicate when the electrode area is smaller the wrinkling voltage is higher, and with the increases of electrode area, the wrinkling voltage decreases rapidly until a specific area. Beyond that, the wrinkling voltage becomes larger gradually with the increases of the area. While the wrinkle wavelength decreases gradually with the increase of voltage monotonically. That is, the relation between the critical wrinkling voltage and the electrode areas is U-shaped. Analysis believes that the film wrinkling is a kind of local effect, the interaction and the energy transfer between electrode region and non-electrode region have great influence on wrinkling. In the experiment, very thin copper wires are used as the electrode leads that just contact with the electrodes, which can avoid the stiffness of the leads affecting the wrinkling.

Keywords: elastomers, uniaxial stretch, electrode area, wrinkling

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Authors: M. Cabrera, W. Tizani, J. Ninic, F. Wang

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Open section beam to concrete-filled tubular column structures has been increasingly utilized in construction over the past few decades due to their enhanced structural performance, as well as economic and architectural advantages. However, the use of this configuration in construction is limited due to the difficulties in connecting the structural members as there is no access to the inner part of the tube to install standard bolts. Blind-bolted systems are a relatively new approach to overcome this limitation as they only require access to one side of the tubular section to tighten the bolt. The performance of these connections in concrete-filled steel tubular sections remains uncharacterized due to the complex interactions between concrete, bolt, and steel section. Over the last years, research in structural performance has moved to a more sophisticated and efficient approach consisting of machine learning algorithms to generate metamodels. This method reduces the need for developing complex, and computationally expensive finite element models, optimizing the search for desirable design variables. Metamodels generated by a data fusion approach use numerical and experimental results by combining multiple models to capture the dependency between the simulation design variables and connection performance, learning the relations between different design parameters and predicting a given output. Fully characterizing this connection will transform high-rise and multistorey construction by means of the introduction of design guidance for moment-resisting blind-bolted connections, which is currently unavailable. This paper presents a review of the steps taken to develop metamodels generated by means of artificial neural network algorithms which predict the connection stress and stiffness based on the design parameters when using Extended Hollo-Bolt blind bolts. It also provides consideration of the failure modes and mechanisms that contribute to the deformability as well as the feasibility of achieving blind-bolted rigid connections when using the blind fastener.

Keywords: blind-bolted connections, concrete-filled tubular structures, finite element analysis, metamodeling

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Authors: Maatouk Khoukhi

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Nowadays the reduction of the energy consumed by buildings to achieve mainly the thermal comfort for the occupants represent the main concern for architects and building designers. The common and traditional solution to achieve this target is the design of a highly insulated envelope and reduce the opening and the transparent elements such windows. However, this will lead to the artificial lighting system to consume more energy to compensate the lack of natural lighting coming through the glazed parts of the building envelope. Therefore, a good balance between sufficient daylight and control thermal heat through the building envelope should be considered for energy saving purpose. To achieve a better indoor environment the windows size and spacing including the interior finishing and the location of the partition must be assessed accurately. Daylighting is the controlled admission of natural light into space through windows and transparent elements of the building envelope which helps create a visually stimulating and productive environment for building occupants. The main concern is not to provide enough daylight to an occupied space, but how to achieve this without any undesirable side effect. Indeed, the glare is a major problem in glazed façade buildings, and this could be reduced by using tinted windows. The main target of this research is to investigate the daylight adequacy of functional needs in old Omani Forts and how they have been designed and built to avoid glare and overheating with the appropriate window-to-floor ratio. Because more windows do not automatically result in more daylighting but that is natural light has been controlled and distributed properly throughout the space. Spaces from different Omani and Portuguese Forts under the same climate conditions are considered in order to compare the daylight illuminance levels and examine the similarities and differences in visual attributes between them. The result of this study indicates that lighting preference is not universal and people from different geographical locations are adapted to certain illuminance levels. Therefore, the standards could not be generalized for the entire world. This would be useful to practitioners who are designing to effectively address the diversity of user’s lighting levels preferences in our globally connected society.

Keywords: day lighting, energy, forts, thermal comfort

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Authors: LouAnne Boyd

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From the perspective of self-advocates, the biggest unaddressed problem is not the symptoms of an autism spectrum diagnosis but the social stigma that accompanies autism. This societal perspective is in contrast to the focus on the majority of interventions. Autism interventions, and consequently, most innovative technologies for autism, aim to improve deficits that occur within the person. For example, the most common Human-Computer Interaction research projects in assistive technology for autism target social skills from a normative perspective. The premise of the autism technologies is that difficulties occur inside the body, hence, the medical model focuses on ways to improve the ailment within the person. However, other technological approaches to support people with autism do exist. In the realm of Human Computer Interaction, there are other modes of research that provide critique of the medical model. For example, critical design, whose intended audience is industry or other HCI researchers, provides products that are the opposite of interventionist work to bring attention to the misalignment between the lived experience and the societal perception of autism. For example, parodies of interventionist work exist to provoke change, such as a recent project called Facesavr, a face covering that helps allistic adults be more independent in their emotional processing. Additionally, from a critical disability studies’ perspective, assistive technologies perpetuate harmful normalizing behaviors. However, these critical approaches can feel far from the frontline in terms of taking direct action to positively impact end users. From a critical yet more pragmatic perspective, projects such as Counterventions lists ways to reduce the likelihood of perpetuating ableism in interventionist’s work by reflectively analyzing a series of evolving assistive technology projects through a societal lens, thus leveraging the momentum of the evolving ecology of technologies for autism. Therefore, all current paradigms fall short of addressing the largest need—the negative impact of social stigma. The current work introduces a new paradigm for technologies for autism, borrowing from a paradigm introduced two decades ago around changing the narrative related to eating disorders. It is the shift from reprimanding poor habits to celebrating positive aspects of eating. This work repurposes Celebratory Technology for Neurodiversity and intended to reduce social stigma by targeting for the public at large. This presentation will review how requirements were derived from current research on autism social stigma as well as design sessions with autistic adults. Congruence between these two sources revealed three key design implications for technology: provide awareness of the autistic experience; generate acceptance of the neurodivergence; cultivate an appreciation for talents and accomplishments of neurodivergent people. The current pilot work in Celebratory Technology offers a new paradigm for supporting autism by shifting the burden of change from the person with autism to address changing society’s biases at large. Shifting the focus of research outside of the autistic body creates a new space for a design that extends beyond the bodies of a few and calls on all to embrace humanity as a whole.

Keywords: neurodiversity, social stigma, accessibility, inclusion, celebratory technology

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Authors: Batuhan Kocaoglu

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Nowadays digital transformation is a hot topic both in service and production business. For the companies who want to stay alive in the following years, they should change how they do their business. Industry leaders started to improve their ERP (Enterprise Resource Planning) like backbone technologies to digital advances such as analytics, mobility, sensor-embedded smart devices, AI (Artificial Intelligence) and more. Selecting the appropriate technology for the related business problem also is a hot topic. Besides this, to operate in the modern environment and fulfill rapidly changing customer expectations, a digital transformation of the business is required and change the way the business runs, affect how they do their business. Even the digital transformation term is trendy the literature is limited and covers just the philosophy instead of a solid implementation plan. Current studies urge firms to start their digital transformation, but few tell us how to do. The huge investments scare companies with blur definitions and concepts. The aim of this paper to solidify the steps of the digital transformation and offer a roadmap for the companies and academicians. The proposed roadmap is developed based upon insights from the literature review, semi-structured interviews, and expert views to explore and identify crucial steps. We introduced our roadmap in the form of 8 main steps: Awareness; Planning; Operations; Implementation; Go-live; Optimization; Autonomation; Business Transformation; including a total of 11 sub-steps with examples. This study also emphasizes four dimensions of the digital transformation mainly: Readiness assessment; Building organizational infrastructure; Building technical infrastructure; Maturity assessment. Finally, roadmap corresponds the steps with three main terms used in digital transformation literacy as Digitization; Digitalization; and Digital Transformation. The resulted model shows that 'business process' and 'organizational issues' should be resolved before technology decisions and 'digitization'. Companies can start their journey with the solid steps, using the proposed roadmap to increase the success of their project implementation. Our roadmap is also adaptable for relevant Industry 4.0 and enterprise application projects. This roadmap will be useful for companies to persuade their top management for investments. Our results can be used as a baseline for further researches related to readiness assessment and maturity assessment studies.

Keywords: digital transformation, digital business, ERP, roadmap

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Authors: komal verma, V. S. Moholkar

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In this current study, the challenge of effectively treating and mineralizing industrial wastewater prior to its discharge into natural water bodies, such as rivers and lakes, is being addressed. Particularly, the focus is on the wastewater produced by chemical process industries, including refineries, petrochemicals, fertilizer, pharmaceuticals, pesticides, and dyestuff industries. These wastewaters often contain stubborn organic pollutants that conventional techniques, such as microbial processes cannot efficiently degrade. To tackle this issue, a ternary hybrid technique comprising of adsorption, heterogeneous Fenton process, and sonication has been employed. The study aims to evaluate the effectiveness of this approach for treating and mineralizing wastewater from a fertilizer industry located in Northeast India. The study comprises several key components, starting with the synthesis of the Fe3O4@AC nanocomposite using the co-precipitation method. The nanocomposite is then subjected to comprehensive characterization through various standard techniques, including FTIR, FE-SEM, EDX, TEM, BET surface area analysis, XRD, and magnetic property determination using VSM. Next, the process parameters of wastewater treatment are statistically optimized, focusing on achieving a high level of COD (Chemical Oxygen Demand) removal as the response variable. The Fe3O4@AC nanocomposite's adsorption characteristics and kinetics are also assessed in detail. The remarkable outcome of this study is the successful application of the ternary hybrid technique, combining adsorption, Fenton process, and sonication. This approach proves highly effective, leading to nearly complete mineralization (or TOC removal) of the fertilizer industry wastewater. The results highlight the potential of the Fe3O4@AC nanocomposite and the ternary hybrid technique as a promising solution for tackling challenging wastewater pollutants from various chemical process industries. This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result results from synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Micro-convection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe3O4@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater. The Fe3O4@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: chemical oxygen demand (cod), fe3o4@ac nanocomposite, kinetics, lc-ms, rsm, toxicity

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Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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Authors: Covadonga Rodrigo, Felipe Alvarez Arrieta, Ana Garcia Serrano

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Mobile augmented reality technologies have become very popular in the last years in the educational field. Researchers have studied how these technologies improve the engagement of the student and better understanding of the process of learning. But few studies have been made regarding the accessibility of these new technologies applied to digital humanities. The goal of our research is to develop an accessible mobile application with embedded augmented reality main characters of the art work and gamification events accompanied by multi-sensorial activities. The mobile app conducts a learning itinerary around the artistic work, driving the user experience in and out the museum. The learning design follows the inquiry-based methodology and social learning conducted through interaction with social networks. As for the software application, it’s being user-centered designed, following the universal design for learning (UDL) principles to assure the best level of accessibility for all. The mobile augmented reality application starts recognizing a marker from a masterpiece of a museum using the camera of the mobile device. The augmented reality information (history, author, 3D images, audio, quizzes) is shown through virtual main characters that come out from the art work. To comply with the UDL principles, we use a version of the technology acceptance model (TAM) to study the easiness of use and perception of usefulness, extended by the authors with specific indicators for measuring accessibility issues. Following a rapid prototype method for development, the first app has been recently produced, fulfilling the EN 301549 standard and W3C accessibility guidelines for mobile development. A TAM-based web questionnaire with 214 participants with different kinds of disabilities was previously conducted to gather information and feedback on user preferences from the artistic work on the Museo del Prado, the level of acceptance of technology innovations and the easiness of use of mobile elements. Preliminary results show that people with disabilities felt very comfortable while using mobile apps and internet connection. The augmented reality elements seem to offer an added value highly engaging and motivating for the students.

Keywords: H.5.1 (multimedia information systems), artificial, augmented and virtual realities, evaluation/methodology

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Authors: Madhawa Basnayaka, Jouni Paltakari

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Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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Authors: Ali Al-Shehri, Abdulaziz Al-Qasim, Abdulkarim Sofi, Ali Yousef

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The oil and gas industry has played a major role in improving the prosperity of mankind and driving the world economy. According to the International Energy Agency (IEA) and Integrated Environmental Assessment (EIA) estimates, the world will continue to rely heavily on hydrocarbons for decades to come. This growing energy demand mandates taking sustainability measures to prolong the availability of reliable and affordable energy sources, and ensure lowering its environmental impact. Unlike any other industry, the oil and gas upstream operations are energy-intensive and scattered over large zonal areas. These challenging conditions require unique sustainability solutions. In recent years there has been a concerted effort by the oil and gas industry to develop and deploy innovative technologies to: maximize efficiency, reduce carbon footprint, reduce CO2 emissions, and optimize resources and material consumption. In the past, the main driver for research and development (R&D) in the exploration and production sector was primarily driven by maximizing profit through higher hydrocarbon recovery and new discoveries. Environmental-friendly and sustainable technologies are increasingly being deployed to balance sustainability and profitability. Analyzing technology and its sustainability impact is increasingly being used in corporate decision-making for improved portfolio management and allocating valuable resources toward technology R&D.This paper articulates and discusses a novel workflow to identify strategic sustainable technologies for improved portfolio management by addressing existing and future upstream challenges. It uses a systematic approach that relies on sustainability key performance indicators (KPI’s) including energy efficiency quotient, carbon footprint, and CO2 emissions. The paper provides examples of various technologies including CCS, reducing water cuts, automation, using renewables, energy efficiency, etc. The use of 4IR technologies such as Artificial Intelligence, Machine Learning, and Data Analytics are also discussed. Overlapping technologies, areas of collaboration and synergistic relationships are identified. The unique sustainability analyses provide improved decision-making on technology portfolio management.

Keywords: sustainability, oil& gas, technology portfolio, key performance indicator

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Authors: Vincenzo Piemonte

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The liver is a complex, large-scale biochemical reactor which plays a unique role in the human physiology. When liver ceases to perform its physiological activity, a functional replacement is required. Actually, liver transplantation is the only clinically effective method of treating severe liver disease. Anyway, the aforementioned therapeutic approach is hampered by the disparity between organ availability and the number of patients on the waiting list. In order to overcome this critical issue, research activities focused on liver support device systems (LSDs) designed to bridging patients to transplantation or to keep them alive until the recovery of native liver function. In recirculating albumin dialysis devices, such as MARS (Molecular Adsorbed Recirculating System), adsorption is one of the fundamental steps in albumin-dialysate regeneration. Among the albumin-bound toxins that must be removed from blood during liver-failure therapy, bilirubin and tryptophan can be considered as representative of two different toxin classes. The first one, not water soluble at physiological blood pH and strongly bounded to albumin, the second one, loosely albumin bound and partially water soluble at pH 7.4. Fixed bed units are normally used for this task, and the design of such units requires information both on toxin adsorption equilibrium and kinetics. The most common adsorptive media used in LSDs are activated carbon, non-ionic polymeric resins and anionic resins. In this paper, bilirubin adsorption isotherms on different adsorptive media, such as polymeric resin, albumin-coated resin, anionic resin, activated carbon and alginate beads with entrapped albumin are presented. By comparing all the results, it can be stated that the adsorption capacity for bilirubin of the five different media increases in the following order: Alginate beads < Polymeric resin < Albumin-coated resin < Activated carbon < Anionic resin. The main focus of this paper is to provide useful guidelines for the optimization of liver support devices which implement adsorption columns to remove albumin-bound toxins from albumin dialysate solutions.

Keywords: adsorptive media, adsorption equilibrium, artificial liver devices, bilirubin, mathematical modelling

Procedia PDF Downloads 246