Search results for: openings in deep beams

Authors: Chua Si Wen Alicia, Marcus Goh Tian Xi, Eunice Gan Ghee Wu, Helen Bound, Lee Liang Ying, Albert Lee

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In a world full of rapid changes, people often need a set of skills to help them navigate an ever-changing workscape. These skills, often known as “future-oriented skills,” include learning to learn, critical thinking, understanding multiple perspectives, and knowledge creation. Future-oriented skills are typically assumed to be domain-general, applicable to multiple domains, and can be cultivated through a learning approach called Dialogical Inquiry. Dialogical Inquiry is known for its benefits of making sense of multiple perspectives, encouraging critical thinking, and developing learner’s capability to learn. However, it currently exists as a quantitative tool, which makes it hard to track and compare learning processes over time. With these concerns, the present research aimed to develop and validate a quantitative tool for the Map of Dialogical Inquiry, focusing Imagining aspect of learning. The Imagining aspect four dimensions: 1) speculative/ look for alternatives, 2) risk taking/ break rules, 3) create/ design, and 4) vision/ imagine. To do so, an exploratory literature review was conducted to better understand the dimensions of Imagining. This included deep-diving into the history of the creation of the Map of Dialogical Inquiry and a review on how “Imagining” has been conceptually defined in the field of social psychology, education, and beyond. Then, we synthesised and validated scales. These scales measured the dimension of Imagination and related concepts like creativity, divergent thinking regulatory focus, and instrumental risk. Thereafter, items were adapted from the aforementioned procured scales to form items that would contribute to the preliminary version of the Imagining Scale. For scale validation, 250 participants were recruited. A Confirmatory Factor Analysis (CFA) sought to establish dimensionality of the Imagining Scale with an iterative procedure in item removal. Reliability and validity of the scale’s dimensions were sought through measurements of Cronbach’s alpha, convergent validity, and discriminant validity. While CFA found that the distinction of Imagining’s four dimensions could not be validated, the scale was able to establish high reliability with a Cronbach alpha of .96. In addition, the convergent validity of the Imagining scale was established. A lack of strong discriminant validity may point to overlaps with other components of the Dialogical Map as a measure of learning. Thus, a holistic approach to forming the tool – encompassing all eight different components may be preferable.

Keywords: learning, education, imagining, pedagogy, dialogical teaching

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Authors: Yitian Ren, Liyin Shen, Tao Zhou, Xiao Li

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The past urbanization process in China has brought out series of problems, the Chinese government has then positioned small towns in essential roles for implementing the strategy 'The National New-type Urbanization Plan (2014-2020)'. As the connector and transfer station of cities and countryside, small towns are important force to narrow the gap between urban and rural area, and to achieve the mission of new-type urbanization in China. The sustainable development of small towns plays crucial role because cities are not capable enough to absorb the surplus rural population. Nevertheless, there are various types of barriers hindering the sustainable development of small towns, which led to the limited development of small towns and has presented a bottleneck in Chinese urbanization process. Therefore, this paper makes deep understanding of these barriers, thus effective actions can be taken to address them. And this paper chooses the perspective of Southwest China (refers to Sichuan province, Yunnan province, Guizhou province, Chongqing Municipality City and Tibet Autonomous Region), cause the urbanization rate in Southwest China is far behind the average urbanization level of the nation and the number of small towns accounts for a great proportion in mainland China, also the characteristics of small towns in Southwest China are distinct. This paper investigates the barriers of sustainable development of small towns which located in Southwest China by using the content analysis method, combing with the field work and interviews in sample small towns, then identified and concludes 18 barriers into four dimensions, namely, institutional barriers, economic barriers, social barriers and ecological barriers. Based on the research above, questionnaire survey and data analysis are implemented, thus the key barriers hinder the sustainable development of small towns in Southwest China are identified by using fuzzy set theory, those barriers are, lack of independent financial power, lack of construction land index, financial channels limitation, single industrial structure, topography variety and complexity, which mainly belongs to institutional barriers and economic barriers. In conclusion part, policy suggestions are come up with to improve the politic and institutional environment of small town development, also the market mechanism are supposed to be introduced to the development process of small towns, which can effectively overcome the economic barriers, promote the sustainable development of small towns, accelerate the in-situ urbanization by absorbing peasants in nearby villages, and achieve the mission of new-type urbanization in China from the perspective of people-oriented.

Keywords: barrier analysis, sustainable development, small town, Southwest China

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Authors: Michael T. Lobmann, Camilla Wellstein, Stefan Zerbe

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Vegetation plays an important role for the stabilization of slopes against erosion processes, such as shallow erosion and landslides. Plant roots reinforce the soil, increase soil cohesion and often cross possible shear planes. Hence, plant roots reduce the risk of slope failure. Generally, shrub and tree roots penetrate deeper into the soil vertically, while roots of forbs and grasses are concentrated horizontally in the topsoil and organic layer. Therefore, shrubs and trees have a higher potential for stabilization of slopes with deep soil layers than forbs and grasses. Consequently, research mainly focused on the vertical root effects of shrubs and trees. Nevertheless, a better understanding of the stabilizing effects of grasses and forbs is needed for better evaluation of the stability of natural and artificial slopes with herbaceous vegetation. Despite the importance of vertical root effects, field observations indicate that horizontal root effects also play an important role for slope stabilization. Not only forbs and grasses, but also some shrubs and trees form tight horizontal networks of fine and coarse roots and rhizomes in the topsoil. These root networks increase soil cohesion and horizontal tensile strength. Available methods for physical measurements, such as shear-box tests, pullout tests and singular root tensile strength measurement can only provide a detailed picture of vertical effects of roots on slope stabilization. However, the assessment of horizontal root effects is largely limited to computer modeling. Here, a method for measurement of in-situ cumulative horizontal root tensile strength is presented. A traction machine was developed that allows fixation of rectangular grass sods (max. 30x60cm) on the short ends with a 30x30cm measurement zone in the middle. On two alpine grass slopes in South Tyrol (northern Italy), 30x60cm grass sods were cut out (max. depth 20cm). Grass sods were pulled apart measuring the horizontal tensile strength over 30cm width over the time. The horizontal tensile strength of the sods was measured and compared for different soil depths, hydrological conditions, and root physiological properties. The results improve our understanding of horizontal root effects on slope stabilization and can be used for improved evaluation of grass slope stability.

Keywords: grassland, horizontal root effect, landslide, mountain, pasture, shallow erosion

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Rosaline Govender, Shubnam Rambharos

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Universities are, to a certain extent, the source of under-preparedness ideologically, structurally, and pedagogically, particularly since organizational cultures often alienate students by failing to enable epistemological access. This is evident in the unsustainably low graduation rates that characterize South African higher education, which indicate that under 30% graduate in minimum time, under two-thirds graduate within 6 years, and one-third have not graduated after 10 years. Although the statistics for the Faculty of Accounting and Informatics at the Durban University of Technology (DUT) in South Africa have improved significantly from 2019 to 2021, the graduation (32%), throughput (50%), and dropout rates (16%) are still a matter for concern as the graduation rates, in particular, are quite similar to the national statistics. For our students to succeed, higher education should take a multi-pronged approach to ensure student success, and student engagement is one of the ways to support our students. Student engagement depends not only on students’ teaching and learning experiences but, more importantly, on their social and academic integration, their sense of belonging, and their emotional connections in the institution. Such experiences need to challenge students academically and engage their intellect, grow their communication skills, build self-discipline, and promote confidence. The aim of this mixed methods study is to explore the multi-pronged nature of student success within the Faculty of Accounting and Informatics at DUT and focuses on the enabling and constraining factors of student success. The sources of data were the Mid-year student experience survey (N=60), the Hambisa Student Survey (N=85), and semi structured focus group interviews with first, second, and third year students of the Faculty of Accounting and Informatics Hambisa program. The Hambisa (“Moving forward”) focus area is part of the Siyaphumelela 2.0 project at DUT and seeks to understand the multiple challenges that are impacting student success which create a large “middle” cohort of students that are stuck in transition within academic programs. Using the lens of the sociocultural influences on student engagement framework, we conducted a thematic analysis of the two surveys and focus group interviews. Preliminary findings indicate that living conditions, choice of program, access to resources, motivation, institutional support, infrastructure, and pedagogical practices impact student engagement and, thus, student success. It is envisaged that the findings from this project will assist the university in being better prepared to enable student success.

Keywords: social and academic integration, socio-cultural influences, student engagement, student success

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Authors: Zarina Chokparova, Ighor Uzhinsky

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Carbon dioxide emissions resulting from burning of the fossil fuels on large scales, such as oil industry or power plants, leads to a plenty of severe implications including global temperature raise, air pollution and other adverse impacts on the environment. Besides some precarious and costly ways for the alleviation of CO₂ emissions detriment in industrial scales (such as liquefaction of CO₂ and its deep-water treatment, application of adsorbents and membranes, which require careful consideration of drawback effects and their mitigation), one physically and commercially available technology for its capture and disposal is supersonic system for inertial extraction of CO₂ in after-combustion streams. Due to the flue gas with a carbon dioxide concentration of 10-15 volume percent being emitted from the combustion system, the waste stream represents a rather diluted condition at low pressure. The supersonic system induces a flue gas mixture stream to expand using a converge-and-diverge operating nozzle; the flow velocity increases to the supersonic ranges resulting in rapid drop of temperature and pressure. Thus, conversion of potential energy into the kinetic power causes a desublimation of CO₂. Solidified carbon dioxide can be sent to the separate vessel for further disposal. The major advantages of the current solution are its economic efficiency, physical stability, and compactness of the system, as well as needlessness of addition any chemical media. However, there are several challenges yet to be regarded to optimize the system: the way for increasing the size of separated CO₂ particles (as they are represented on a micrometers scale of effective diameter), reduction of the concomitant gas separated together with carbon dioxide and provision of CO₂ downstream flow purity. Moreover, determination of thermodynamic conditions of the vapor-solid mixture including specification of the valid and accurate equation of state remains to be an essential goal. Due to high speeds and temperatures reached during the process, the influence of the emitted heat should be considered, and the applicable solution model for the compressible flow need to be determined. In this report, a brief overview of the current technology status will be presented and a program for further evaluation of this approach is going to be proposed.

Keywords: CO₂ sequestration, converging diverging nozzle, fossil fuel power plant emissions, inertial CO₂ extraction, supersonic post-combustion carbon dioxide capture

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Authors: Bill D. Geis

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Even with significantly increased spending, suicide rates continue to climb—with alarming increases among traditionally low-risk groups. This has caused clinicians and researchers to call for a complete rethinking of all assumptions about suicide prevention, assessment, and intervention. A form of therapy--Internal Family Systems Therapy--affords tremendous promise in sustained diminishment of lethal suicide risk. Though a form of therapy that is most familiar to trauma therapists, Internal Family Systems Therapy, involving direct work with suicidal parts, is a promising therapy for meaningful and sustained reduction in suicide deaths. Developed by Richard Schwartz, Internal Family Systems Therapy proposes that we are all influenced greatly by internal parts, frozen by development adversities, and these often-contradictory parts contribute invisibly to mood, distress, and behavior. In making research videos of patients from our database and discussing their suicide attempts, it is clear that many persons who attempt suicide are in altered states at the time of their attempt and influenced by factors other than conscious intent. Suicide intervention using this therapy involves direct work with suicidal parts and other interacting parts that generate distress and despair. Internal Family Systems theory posits that deep experiences of pain, fear, aloneness, and distress are defended by a range of different parts that attempt to contain these experiences of pain through various internal activities that unwittingly push forward inhibition, fear, self-doubt, hopelessness, desires to cut and engage in destructive behavior, addictive behavior, and even suicidal actions. These suicidal parts are often created (and “frozen”) at young ages, and these very young parts do not understand the consequences of this influence. Experience suggests that suicidal parts can create impulsive risk behind the scenes when pain is high and emotional support reduced—with significant crisis potential. This understanding of latent suicide risk is consistent with many of our video accounts of serious suicidal acts—compiled in a database of 1104 subjects. Since 2016, consent has been obtained and records kept of 23 highly suicidal patients, with initial Intention-to-Die ratings (0= no intent, 10 = conviction to die) between 5 and 10. In 67% of these cases using IFST parts-work intervention, these highly suicidal patients’ risk was reduced to 0-1, and 83% of cases were reduced to 4 or lower. There were no suicide deaths. Case illustrations will be offered.

Keywords: suicide, internal family systems therapy, crisis management, suicide prevention

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Authors: Vallence Ngabo Maniragaba

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This study aimed at examining the variations of undernutrition among children below 5 years of age in Uganda. The approach of spatial and spatiotemporal analysis helped in identifying cluster patterns, hot spots and emerging hot spots. Data from the 6 Uganda Demographic and Health Surveys spanning from 1990 to 2016 were used with the main outcome variable being undernutrition among children <5 years of age. All data that were relevant to this study were retrieved from the survey datasets and combined with the 214 shape files for the districts of Uganda to enable spatial and spatiotemporal analysis. Spatial maps with the spatial distribution of the prevalence of undernutrition, both in space and time, were generated using ArcGIS Pro version 2.8. Moran’s I, an index of spatial autocorrelation, rules out doubts of spatial randomness in order to identify spatially clustered patterns of hot or cold spot areas. Furthermore, space-time cubes were generated to establish the trend in undernutrition as well as to mirror its variations over time and across Uganda. Moreover, emerging hot spot analysis was done to help identify the patterns of undernutrition over time. The results indicate a heterogeneous distribution of undernutrition across Uganda and the same variations were also evident over time. Moran’s I index confirmed spatial clustered patterns as opposed to random distributions of undernutrition prevalence. Four hot spot areas, namely; the Karamoja, the Sebei, the West Nile and the Toro regions were significantly evident, most of the central parts of Uganda were identified as cold spot clusters, while most of Western Uganda, the Acholi and the Lango regions had no statistically significant spatial patterns by the year 2016. The spatio-temporal analysis identified the Karamoja and Sebei regions as clusters of persistent, consecutive and intensifying hot spots, West Nile region was identified as a sporadic hot spot area while the Toro region was identified with both sporadic and emerging hotspots. In conclusion, undernutrition is a silent pandemic that needs to be handled with both hands. At 31.2 percent, the prevalence is still very high and unpleasant. The distribution across the country is nonuniform with some areas such as the Karamoja, the West Nile, the Sebei and the Toro regions being epicenters of undernutrition in Uganda. Over time, the same areas have experienced and exhibited high undernutrition prevalence. Policymakers, as well as the implementers, should bear in mind the spatial variations across the country and prioritize hot spot areas in order to have efficient, timely and region-specific interventions.

Keywords: undernutrition, spatial autocorrelation, hotspots analysis, geographically weighted regressions, emerging hotspots analysis, under-fives, Uganda

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: Mernoosh Abouzari, Shahrokh Sahraei

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Electronic government is a way for governments to use new technology that provides people with the necessary facilities for proper access to government information and services, improving the quality of services and providing broad opportunities to participate in democratic processes and institutions. That leads to providing the possibility of easy use of information technology in order to distribute government services to the customer without holidays, which increases people's satisfaction and participation in political and economic activities. The expansion of e-government services and its movement towards intelligentization has the ability to re-establish the relationship between the government and citizens and the elements and components of the government. Electronic government is the result of the use of information and communication technology (ICT), which by implementing it at the government level, in terms of the efficiency and effectiveness of government systems and the way of providing services, tremendous commercial changes are created, which brings people's satisfaction at the wide level will follow. The main level of electronic government services has become objectified today with the presence of artificial intelligence systems, which recent advances in artificial intelligence represent a revolution in the use of machines to support predictive decision-making and Classification of data. With the use of deep learning tools, artificial intelligence can mean a significant improvement in the delivery of services to citizens and uplift the work of public service professionals while also inspiring a new generation of technocrats to enter government. This smart revolution may put aside some functions of the government, change its components, and concepts such as governance, policymaking or democracy will change in front of artificial intelligence technology, and the top-down position in governance may face serious changes, and If governments delay in using artificial intelligence, the balance of power will change and private companies will monopolize everything with their pioneering in this field, and the world order will also depend on rich multinational companies and in fact, Algorithmic systems will become the ruling systems of the world. It can be said that currently, the revolution in information technology and biotechnology has been started by engineers, large economic companies, and scientists who are rarely aware of the political complexities of their decisions and certainly do not represent anyone. Therefore, it seems that if liberalism, nationalism, or any other religion wants to organize the world of 2050, it should not only rationalize the concept of artificial intelligence and complex data algorithm but also mix them in a new and meaningful narrative. Therefore, the changes caused by artificial intelligence in the political and economic order will lead to a major change in the way all countries deal with the phenomenon of digital globalization. In this paper, while debating the role and performance of e-government, we will discuss the efficiency and application of artificial intelligence in e-government, and we will consider the developments resulting from it in the new world and the concepts of governance.

Keywords: electronic government, artificial intelligence, information and communication technology., system

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Authors: Mariateresa Torchia, Helene Cristini, Hannele Kauppinen

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Leadership plays a vital role in organizations. Leaders provide directions and facilitate the processes that enable organizations to achieve their goals and objectives. However, while productivity and financial objectives are often given the greatest emphasis, leaders also have the responsibility for instituting standards of ethical conduct and moral values that guide the behavior of employees. Leaders’ behaviors such as support, empowerment and a high-quality relationship with their employees might not only prevent stress, but also improve employees’ stress coping meanwhile contributing to their affective well-being. Stemming from Girard’s Mimetic Theory, this study aims at understanding how leaders can foster well-being in organizations. To do so, we explore which is the role leaders play in conflict management, resentment management and negative emotions dissipation. Furthermore, we examine whether and to what extent religiosity impacts the way in which leaders operate in relation to employees’ well-being. Indeed, given that organizational values are crucial to ethical behavior and firms’ values may be steeled by a deep sense of spirituality and religious identification, there is a need to take a closer look at the role religion and spirituality play in influencing the way leaders impact employees’ well-being. Thus, religion might work as an overarching logic that provides a set of principles guiding leaders’ everyday practices and relations with employees. We answer our research questions using a qualitative approach. We interviewed 27 Christian leaders (members of the Christian Entrepreneurs and Leaders Association – EDC, a non-profit organization created in 1926 including 3,000 French Christian Leaders & Entrepreneurs). Our results show that well-being can have a different meaning in relation to the type of companies, size, culture, country of analysis. Moreover the values and believes of leaders influence the way they see and foster well-being among employees. Furthermore, leaders can have both a positive or negative impact on well-being. Indeed on the one side, they could increase well-being in the company while on the other hand, they could be the source of resentment and conflicts among employees. Finally, we observed that Christian leaders possess characteristics that are sometimes missing in leaders (humility, inability to compare with others, attempt to be coherent with their values and beliefs, interest in the common good instead of the personal interest, having tougher dilemmas, collectively undertaking the firm). Moreover the Christian leader believes that the common good should come before personal interest. In other words, to them, not only short –termed profit shouldn’t guide strategical decisions but also leaders should feel responsible for their employees’ well-being. Last but not least, the study is not an apologia of Christian, yet it discusses the implications of these values through the light of Girard’s mimetic theory for both theory and practice.

Keywords: Christian leaders, employees well-being, leadership, mimetic theory

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Authors: Zhe Xu, Jian Li, Lvping Li, Zezheng Dong

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This work is to study an optimized transfer strategy of connecting Earth and Mars via the vicinity of libration points, which have been playing an increasingly important role in trajectory designing on a deep space mission, and can be used as an effective alternative solution for Earth-Mars direct transfer mission in some unusual cases. The use of vicinity of libration points of the sun-planet body system is becoming potential gateways for future interplanetary transfer missions. By adding fuel to cargo spaceships located in spaceports, the interplanetary round-trip exploration shuttle mission of such a system facility can also be a reusable transportation system. In addition, in some cases, when the S/C cruising through invariant manifolds, it can also save a large amount of fuel. Therefore, it is necessary to make an effort on looking for efficient transfer strategies using variant manifold about libration points. It was found that Earth L1/L2 Halo/Lyapunov orbits and Mars L2/L1 Halo/Lyapunov orbits could be connected with reasonable fuel consumption and flight duration with appropriate design. In the paper, the halo hopping method and coplanar circular method are briefly introduced. The former used differential corrections to systematically generate low ΔV transfer trajectories between interplanetary manifolds, while the latter discussed escape and capture trajectories to and from Halo orbits by using impulsive maneuvers at periapsis of the manifolds about libration points. In the following, designs of transfer strategies of the two methods are shown here. A comparative performance analysis of interplanetary transfer strategies of the two methods is carried out accordingly. Comparison of strategies is based on two main criteria: the total fuel consumption required to perform the transfer and the time of flight, as mentioned above. The numeric results showed that the coplanar circular method procedure has certain advantages in cost or duration. Finally, optimized transfer strategy with engineering constraints is searched out and examined to be an effective alternative solution for a given direct transfer mission. This paper investigated main methods and gave out an optimized solution in interplanetary transfer via the vicinity of libration points. Although most of Earth-Mars mission planners prefer to build up a direct transfer strategy for the mission due to its advantage in relatively short time of flight, the strategies given in the paper could still be regard as effective alternative solutions since the advantages mentioned above and longer departure window than direct transfer.

Keywords: circular restricted three-body problem, halo/Lyapunov orbit, invariant manifolds, libration points

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Authors: Golnoush Rostami, Farzam Kharvari

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In recent years, developments in the field of architectural education have resulted in a shift from conventional teaching methods to alternative state-of-the-art approaches in teaching methods and strategies. Criticism in architecture has been a key player both in the profession and education, but it has been mostly offered by renowned individuals. Hence, not only students or other professionals but also critics themselves may not have the option to experience buildings and rely on available 2D materials, such as images and plans, that may not result in a holistic understanding and evaluation of buildings. On the other hand, immersive environments provide students and professionals the opportunity to experience buildings virtually and reflect their evaluation by experiencing rather than judging based on 2D materials. Therefore, the aim of this study is to compare the effect of experiencing buildings in immersive environments and 2D drawings, including images and plans, on architecture criticism and architectural education. As a result, three buildings that have parametric brick facades were studied through 2D materials and in Unreal Engine v. 24 as an immersive environment among 22 architecture students that were selected using convenient sampling and were divided into two equal groups using simple random sampling. This study used mixed methods, including quantitative and qualitative methods; the quantitative section was carried out by a questionnaire, and deep interviews were used for the qualitative section. A questionnaire was developed for measuring three constructs, including privacy regulation based on Altman’s theory, the sufficiency of illuminance levels in the building, and the visual status of the view (visually appealing views based on obstructions that may have been caused by facades). Furthermore, participants had the opportunity to reflect their understanding and evaluation of the buildings in individual interviews. Accordingly, the collected data from the questionnaires were analyzed using independent t-test and descriptive analyses in IBM SPSS Statistics v. 26, and interviews were analyzed using the content analysis method. The results of the interviews showed that the participants who experienced the buildings in the immersive environment were able to have a thorough and more precise evaluation of the buildings in comparison to those who studied them through 2D materials. Moreover, the analyses of the respondents’ questionnaires revealed that there were statistically significant differences between measured constructs among the two groups. The outcome of this study suggests that integrating immersive environments into the profession and architectural education as an effective and efficient tool for architecture criticism is vital since these environments allow users to have a holistic evaluation of buildings for vigorous and sound criticism.

Keywords: immersive environments, architecture criticism, architectural education, occupant-centric evaluation, pre-occupancy evaluation

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Authors: Ashok Kumar Rastogi

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Glass is a material commonly used for Glassdoor, glass bottles, cookware, and containers. It can be harmful, as it is a hard and blunt object. Glass has been associated with severe injury and is a common cause of injuries warranting hospital visits to the emergency department (ED). These injuries can be accidental or intentionally inflicted. Broken glass injuries can be severe, even deadly. If broken glass shards fall out on your arm, it may cause fatal injuries. Case history: A 20-year-old male dead body was found aside the road, police informed, and a video recording ceased during an investigation. In the video recording, the person was in a drunken state (unable to walk and disoriented), wandering in the residential area road. He saw a barber shop, the shop door made of Glass. Suddenly, he hit the Glassdoor with his right hand forcefully. The Glassdoor broke into multiple pieces, and multiple injuries were seen over the right hand. Observations: Multiple small and large lacerations were seen over the right anterior part of the elbow. The main injury looked like an incised wound caused by a hard and sharp object. The main injury was noted as a laceration of size 13 x 06 cm bone deep, placed obliquely over the anteromedial aspect of the right elbow joint, its medial end at medial end of elbow joint while its anterior end was 04 cm below the elbow joint with laceration of underline brachialis muscles and complete transaction of ulnar artery and vein, skin margins looking sharply cut with irregular margins with tiny cuts at the medial lower border of laceration. Injuries were antemortem and fresh in nature, caused by hard and blunt objects but looking like hard and sharp objects. All organs were found pale, and the cause of death was shock and hemorrhage because of ulnar vessel injury. Conclusion: The findings of this case report highlight the potentially lethal consequences of glass injuries, especially those involving Glassdoors. The study underscores the importance of accurate interpretation and identification of wounds caused by Glass, as they may resemble injuries caused by other objects. It emphasizes the challenges faced by autopsy surgeons when determining the cause and manner of death in cases where visual evidence of injury is absent or when the weapon is not recovered. Ultimately, this case report serves as a reminder of the potential dangers posed by Glass and the importance of comprehensive forensic examinations.

Keywords: glassdoor, incised, wound, laceration, autopsy

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Authors: Gilberto Goracci, Fabio Curti

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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

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Authors: Ilona Pavlovska, Aneka Klavina, Agris Auce, Ivars Vanadzins, Alise Silova, Laura Komarovska, Linda Paegle, Baiba Silamikele, Linda Dobkevica

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Freshwater sapropel is a common material formed by complex biological transformations of Holocene sediments in the water basement of the lakes in Latvia that has the potential to be used as medical mud. Sapropel forms over a long period in shallow waters by slowly decomposing organic sediment and has different compositions depending on the location of the source, surroundings, the water regime, etc. Official geological survey of Latvia lakes, from Latvian lake database (ezeri.lv), used in the selection of the area of the exploration. The multifunctional effect of sapropel on the whole organism explained by its complex chemical and biological structure. This unique, organic substance and its ability to maintain heat for a long time ensures deep tissue warming and has a positive effect on the treatment of various joint and skin diseases. Sapropel is a valuable resource with multiple areas of application. Investigation of sapropel sediments and survey of the five sites selected according to the criteria performed in the current study. Also, our study includes sampling at different depths and their initial treatment, evaluation of external signs, and study of physical-chemical parameters, as well as analysis of biochemical parameters and evaluation of microbiological indicators. The main selection criteria were sapropel deposits depth, hydrological regime, the history of agriculture next to the lake, and the potential exposure to industrial waste. One hundred and five sapropel samples obtained from five lakes (Audzelu, Dunakla, Ivusku, Zielu, and Mazars Kivdalova) during the wintertime. The main goal of the study is to carry out detailed and systematic research on the medical properties of sapropel to be obtained in Latvia, to promote its scientifically based use in balneology, to develop new medical procedures and services, and to promote the development of new exportable products. Latvian freshwater sapropel could be used as raw material for getting sapropel extract and use it as a remedy. All mentioned above brings us to the main question for sapropel usage in medicine, balneology, and pharmacy “how to develop quality criteria for raw sapropel and its extracts. The research was co-financed by the project "Analysis of characteristics of medical sapropel and its usage for medical purposes and elaboration of industrial extraction methods" No.1.1.1.1/16/A/165.

Keywords: balneology, extracts, freshwater sapropel, Latvian lakes, medical mud, sapropel

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Authors: In-Lee Choi, Sung Mi Hong, Min Jae Jeong, Jun Pill Baek, Ho-Min Kang

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Gomchwi (Ligularia fischeri) is grown in the wetland of the deep mountains in Korea and East Asia and has properties that are, inflammation control, whitening, antimutagenic and antigenotoxic. Jangajji is a type of pickle in Korean fermented food which is made by pickling or marinating vegetables in a sauce, such as soy sauce, chili pepper paste, soybean paste, or diluted vinegar for a long period of time. Handaeri-gomchwi jangajii is generally packed a film that has very low or no gas permeability in the Korean domestic market, so packages have a risk of swelling or bursting as a result of internal gas generation during storage or sale This study was conducted to improve secure distribution of Handaeri-gomchwi (Ligularia fischeri var. spiciformis Nakai) Jangajji using laser ablation OTR (oxygen transmission rate) films. Handaeri-gomchwi cultivated in Yangu, Gangwon province, Republic of Korea (Ligularia fischeri var. spiciformis Nakai) was processed in to Jangajji using soy sauce. They were packed by different OTR films, and were stored for 90 days in 7℃(10,000 cc, 20,000 cc, 40,000 cc and 80,000 cc O2/m²• day • atm), 20 days in 20℃ (10,000 cc, 30,000 cc, 70,000 cc and 100,000 cc) and compared with the control film(PP film, 1,300cc). The fresh weight loss, carbon dioxide, oxygen, and ethylene concentrations of Handaeri–gomchwi packages were measured during storage. On the final day of storage, incidence rate of fungi, pH, salinity, firmness, and off-flavor were measured. The fresh weight loss rate of Handaeri–gomchwi was less than 2.0% in 10,000cc OTR films at two different storage periods and temperatures. At 80,000cc(7℃) and 100,000cc(20℃), carbon dioxide contents were 2.0% and 6.4% respectively, whereas the control treatment had the highest concentration. Which was 35%(20℃) and 15%(7℃) , that resulted the packages to swell during storage. The control treatment Showed the lowest oxygen concentration at 2.5% in 7℃ and 0.8% in 20℃. Packages in 7℃ (0.3-1.7μL/L) showed very lower ethylene concentration than in 20℃(10-25μL/L), they also had no significant relation. On the final storage day, fungi were found in every film at both temperatures, except the 10,000cc, as oxygen permeability increased so did the pH, while the salinity decreased. Firmness and off-flavor Showed the best results at 10,000cc in both temperatures best result at 10,000cc in both temperature. Following the results, 10,000cc film is the most reasonable treat in storing Handaeri–gomchwi. For it had a suitable oxygen transmission rate, which prevents billowing, and maintained good qualities in both temperatures.

Keywords: carbon dioxide, Korean pickle, marketable, oxygen

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Authors: Khasim Munir Bhasha Shaik

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Veligonda and adjoining hill range spread along about 170 Km North to South in Kadapa and Nellore Districts stretching a little further into Prakasam District. The latitude in general ranges up to 1000m. The forests are generally dry deciduous type. Veligonda and adjoining hill ranges comprise of Palakonda, Seshachalam, Lankamala and the terminal part of Nallamalais from mid-region of Southern Eastern Ghats. The Veligonda range which separates the Nellore district from Kadapa and Kurnool is the backbone of the Eastern Ghats, starting from Nagari promontory in Chittoor district. It runs in a northerly direction along the western border of the Nellore district, with a raising elevation of 3,626 ft at Penchalakona in Raipur thaluk. Veligonda hill ranges are high in altitude and have deep valleys. Among the Veligondas range of hills the Durgam in Venkatagiri range and Penchalakona are the most prominent and are situated 914 meters above mean sea level. It has more than 3000 species of plants along with 500 animal species. The unique specialty of this region is the presence of Pterocarpus santalinus(endangered) and Santalum album (vulnerable). In the present study, an attempt is made to assess the efforts that are going on to conserve the biodiversity of flora and fauna of this region. Various conservation strategies were suggested to protect the biodiversity and richness of Veligonda forest, hill region of Eastern Ghats of Andhra Pradesh. The major threats and the reasons for the dwindling species richness are poor rainfall, adverse climatic conditions, robbery of Red sanders and poaching of animals by the local tribals. Efforts are to be made to conserve some of the animals by both in situ and ex-situ methods. More awareness is to be developed among the local communities who are dwelling in the vicinity and importance of conservation is to be emphasized to them. Anthropogenic attachments are to be made by introducing more numbers of sacred groves. Gross enforcement of law is to be made to protect the various forest resources in this area. The important species with the medicinal values are to be identified. It was found that two important wildlife sanctuaries named Sri Lankamalleswarawildlife sanctuary and Sripenusila Narasimha wildlife sanctuary are working for the comprehensive conservation of the environment in this area. Apart from this more than 38 important sacred grooves are there where the plants and animals are protected by local Yanadi and other communities.

Keywords: biodiversity, wild life sanctuary, habitat destruction, eastern Ghats

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Authors: Ghada Ben Brahim, Aicha El Rabia, Mohamed Hedi Inoubli

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Climate change has exacerbated disparities in the distribution of water resources in Tunisia, resulting in significant degradation in quantity and quality over the past five decades. The Mio-Plio-Quaternary aquifer, the primary water source in the Zarzis region, is subject to climatic, geographical, and geological challenges, as well as human stress. The region is experiencing uneven distribution and growing threats from groundwater salinity and saltwater intrusion. Addressing this challenge is critical for the arid region’s socioeconomic development, and effective water resource management is required to combat climate change and reduce water deficits. This study uses a multidisciplinary approach to determine the groundwater potential of this aquifer, involving geophysics and hydrogeology data analysis. We used advanced techniques such as 3D Euler deconvolution and power spectrum analysis to generate detailed anomaly maps and estimate the depths of density sources, identifying significant Bouguer anomalies trending E-W, NW-SE, and NE-SW. Various techniques, such as wavelength filtering, upward continuation, and horizontal and vertical derivatives, were used to improve the gravity data, resulting in consistent results for anomaly shapes and amplitudes. The Euler deconvolution method revealed two prominent surface faults, trending NE-SW and NW-SE, that have a significant impact on the distribution of sedimentary facies and water quality within the Mio-Plio-Quaternary aquifer. Additionally, depth maxima greater than 1400 m to the North indicate the presence of a Cretaceous paleo-fault. Geoelectrical models and resistivity pseudo-sections were used to interpret the distribution of electrical facies in the Mio-Plio-Quaternary aquifer, highlighting lateral variation and depositional environment type. AI optimises the analysis and interpretation of exploration data, which is important to long-term management and water security. Machine learning algorithms and deep learning models analyse large datasets to provide precise interpretations of subsurface conditions, such as aquifer salinisation. However, AI has limitations, such as the requirement for large datasets, the risk of overfitting, and integration issues with traditional geological methods.

Keywords: mio-plio-quaternary aquifer, Southeastern Tunisia, geophysical methods, hydrogeological analysis, artificial intelligence

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Authors: Zakiullah Kalwar, Shabeer Abbassi

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This research encompasses the study of structural styles and evaluation of the hydrocarbon potential of Kotrum and Drigri anticlines located in Rajanpur Area, Midddle Indus Basin of Pakistan with the approach of geophysical data integration. The study area is situated between the Sulaiman Foldbelt on the west and Indus River in the east. It is an anticlinal fold, located to the southeast of Sakhi Sarwar anticline and separated from a prominent syncline. The structure has a narrow elongated crest, with the axis running in SSW-NNE direction. In the east, the structure is bounded by a gentle syncline. Structural Styles are trending East-West and perpendicular to tectonic transport and stress direction and the base of the structures gradually dipping Eastward beneath the deformation frontal part in Eastern Sulaiman Fold Belt. Middle Indus Basin can be divided into Foreland, Sulaiman fold belt and a broad foredeep. Sulaiman represents a blind thrust front, which suggests that all frontal folds of the fold belt are cored by blind thrust. The deformation of frontal part of Sulaiman Lobe represents the passive roof duplex stacked beneath the frontal passive roof thrust. The passive roof thrust, which has a back thrust sense of motion and extends into the interior of Fold belt. Left lateral Kingri Fault separates Eastern and Central Sulaiman fold belt. In Central Sulaiman fold belt the deformation front moved further towards fore deep as compared to Eastern Sulaiman. Two wells (Kotrum-01, Drigri-01) have been drilled in the study area with the objective to determine the potential of oil and gas in Habib Rahi Limestone of Eocene age, Dunghan Limestone of Paleocene age and Pab Sandstone of cretaceous age and role of structural styles in hydrocarbon potential of study area. Kotrum-01 well was drilled to its T.D of 4798m. Besides fishing and side tracking, tight whole conditions, high pressure, and losses of circulation were also encountered. During production, testing Pab sandstone were tested but abandoned found. Drigri-01 well was drilled to its T.D 3250 m. RFT was carried out at different points, but all points showed no pressure / seal failure and the well was plugged and declared abandoned.

Keywords: hydrocarbon potential, structural style, reserve calculation, enhance production

Procedia PDF Downloads 429

Authors: Hsin-Hung Lai, Wei Lo

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Whether it is in virtue or vice for a construction quality of public construction project, it is one of the important indicators for national economic development and overall construction, the impact on the quality of national life is very deep. In recent years, a number of scandal of public construction project occurred, the requirements of the government agencies and the public require the quality of construction of public construction project are getting stricter than ever, the three-level public construction project construction quality of quality control system implemented by the government has a profound impact. This study mainly aggregated the evolution of ISO 9000 quality control system, the difference between the practice of implementing management of construction quality by many countries and three-level quality control of our country, so we explored and found that almost all projects of enhancing construction quality are dominated by civil organizations in foreign countries, whereas, it is induced by the national power in our country and develop our three-level quality control system and audit mechanism based on IOS system and implement the works by legislation, we also explored its enhancement and relevance with construction quality of public construction project that are intervened by such system and national power, and it really presents the effectiveness of construction quality been enhanced by the audited result. The three-level quality control system of our country to promote the policy of public construction project is almost same with the quality control system of many developed countries; however our country mainly implements such system on public construction project only, we promote the three-level quality control system is for enhancing the quality of public construction project, for establishing effective quality management system, so as to urge, correct and prevent the defects of quality management by manufacturers, whereas, those developed countries is comprehensively promoting (both public construction project and civil construction) such system. Therefore, this study is to explore the scope for public construction project only; the most important is the quality recognition by the executor, either good quality or deterioration is not a single event, there is a certain procedure extends from the demand and feasibility analysis, design, tendering, contracting, construction performance, inspection, continuous improvement, completion and acceptance, transferring and meeting the needs of the users, all of mentioned above have a causal relationship and it is a systemic problems. So the best construction quality would be manufactured and managed by reasonable cost if it is by extensive thinking and be preventive. We aggregated the implemented results in the past 10 years (2005 to 2015), the audited results of both in central units and local ones were slightly increased in A-grade while those listed in B-grade were decreased, although the levels were not evidently upgraded, yet, such result presents that the construction quality of concept of manufacturers are improving, and the construction quality has been established in the design stage, thus it is relatively beneficial to the enhancement of construction quality of overall public construction project.

Keywords: ISO 9000, three-level quality control system, audit and review mechanism for construction implementation, quality of construction implementation

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

Procedia PDF Downloads 174

Authors: Fizza Saghir

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Rohingyas are an ethnic minority of predominantly Buddhist-Myanmar. Living in ghettos in Rakhine, one of the poorest states of Myanmar, for decades, they have been marginalized, discriminated, deprived of the basic amenities and have faced ghastly violations of their rights- politically, socially, economically and culturally. In 2012, in violence that, erupted between ethnic Rakhine Buddhists and Rohingya Muslims, hundreds of Rohingyas were slayed and many more displaced. The state does not recognize them as ‘citizens’ and the military and police have constantly persecuted and pushed them to either migrate to other countries like India, Bangladesh or else die of deprivation. Amidst the deadly violence, Rohingya women are the most vulnerable. Many of them have faced sexual abuse and gender-based violence. Minimalistic to insignificant studies have been done on the plight of Rohingya women refugees in context of India. Thus, this paper focuses on psycho-social status of Rohingya women refugees settled in Delhi, India. The research study used both quantitative and qualitative methods. It was explorative in nature and used non-probability sampling, purposive sampling, in particular. A sample size of 30 Rohingya women refugees was interviewed out of the universe of 45 Rohingya refugee families living in Kalindi Kunj Refugee Camp of Delhi. Case studies were developed. The paper explores the psychological and social status of the respondents along with a deep understanding of their issues and concerns. Moreover, it assesses the impact of violence and migration on respondents. It was found that Rohingya women refugees are deeply and severely affected by a violent past, an insecure present and an uncertain future. Major problems they face in Delhi, India are finding employment, lack of identity cards to avail government services, language barrier, lack of health and education facilities. All they desire is peace and shelter in India. Besides, recommendations and suggestions have been given to various stakeholders of the forced mass migration of Rohingya refugees which includes, Government of Myanmar, Government of India, other bordering nations of Myanmar, international NGOs and media and the Rohingya community, itself. Only an immediate, peaceful and continuous dialogue process can help resolve the issue of exodus of Rohingyas. Countries, including India, must come together to help the Rohingyas who are in need of urgent humanitarian aid and assistance.

Keywords: dialogue process, ethnic minority, forced mass migration, impact of violence and migration, psycho-social status, Rohingya women refugees, sexual abuse

Procedia PDF Downloads 177

Authors: Florence Ibeh, David Oyewmi Oyekunle, David Boohene

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The continuous advancement of information technology has completely transformed how businesses and organizations operate on a global scale. The widespread availability of virtual communication tools enables individuals to opt for remote work. While remote employment offers various benefits, such as facilitating corporate growth and enhancing customer support, it also presents distinct challenges. Therefore, investigating the intricacies of virtual team morale is crucial for ensuring the achievement of project objectives. For this study, content analysis of pre-existing secondary data was employed to examine the phenomenon. Essential elements vital for improving the success of projects within virtual teams were identified. These factors include technology adoption, creating a distraction-free work environment, effective leadership, trust-building, clear communication channels, well-defined task allocation, active team participation, and motivation. Furthermore, the study established a substantial correlation between morale levels and the participation and productivity of virtual team members. Higher levels of morale were associated with optimal performance among virtual teams. The study determined that the key factors for enhancing project performance in virtual teams are the adoption of technology, a focused environment, effective leadership, trust, communication, well-defined tasks, collaborative teamwork, and motivation. Additionally, the study discovered that modifying the optimal strategies employed by in-office teams can enhance the diminished morale prevalent in remote teams to sustain a high level of team morale for virtual teams. The findings of this study are highly significant in the dynamic field of project management. Currently, there is limited information regarding strategies that address challenges arising from external factors in virtual teams, such as ambient noise and disruptions caused by family members. The findings underscore the significance of selecting appropriate communication technologies, delineating distinct roles and responsibilities for virtual team members, and nurturing a culture of accountability and trust. Promoting seamless collaboration and instilling motivation among virtual team members are deemed highly effective in augmenting employee engagement and performance within virtual team setting.

Keywords: virtual teams, morale, project performance, distract-free environment, technology adaptation

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Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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Authors: Mohammad Arabi

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The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

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Authors: Fernando Araujo, Sandra Cardoso, Fátima Fonseca, Sandra Cavaca

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A debureaucratization strategy for the Portuguese Health Service was assumed by the Executive Board of the SNS, in deep articulation with the Shared Services of the Ministry of Health. Two of the main dimensions were focused on sick leaves (SL), that transform primary health care (PHC) in administrative institutions, limiting access to patients. The self-declaration of illness (SDI) project, through the National Health Service Contact Centre (SNS24), began on May 1, 2023, and has already resulted in the issuance of more than 300,000 SDI without the need to allocate resources from the National Health Service (NHS). This political decision allows each citizen, in a maximum 2 times/year, and 3 days each time, if ill, through their own responsibility, report their health condition in a dematerialized way, and by this way justified the absence to work, although by Portuguese law in these first three days, there is no payment of salary. Using a digital approach, it is now feasible without the need to go to the PHC and occupy the time of the PHC only to obtain an SL. Through this measure, bureaucracy has been reduced, and the system has been focused on users, improving the lives of citizens and reducing the administrative burden on PHC, which now has more consultation times for users who need it. The second initiative, which began on March 1, 2024, allows the SL to be issued in emergency departments (ED) of public hospitals and in the health institutions of the social and private sectors. This project is intended to allow the user who has suffered a situation of acute urgent illness and who has been observed in an ED of a public hospital or in a private or social entity no longer need to go to PHC only to apply for the respective SL. Since March 1, 54,453 SLs have been issued, 242 in private or social sector institutions and 6,918 in public hospitals, of which 134 were in ED and 47,292 in PHC. This approach has proven to be technically robust, allows immediate resolution of problems and differentiates the performance of doctors. However, it is important to continue to qualify the proper functioning of the ED, preventing non-urgent users from going there only to obtain SL. Thus, in order to make better use of existing resources, it was operationalizing this extension of its issuance in a balanced way, allowing SL to be issued in the ED of hospitals only to critically ill patients or patients referred by INEM, SNS24, or PHC. In both cases, an intense public campaign was implemented to explain the way it works and the benefits for patients. In satisfaction surveys, more than 95% of patients and doctors were satisfied with the solutions, asking for extensions to other areas. The administrative simplification agenda of the NHS continues its effective development. For the success of this debureaucratization agenda, the key factors are effective communication and the ability to reach patients and health professionals in order to increase health literacy and the correct use of NHS.

Keywords: debureaucratization strategy, self-declaration of illness, sick leaves, SNS24

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Authors: Isabella Maurizio

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This research analyses the pronunciation of Hebrew consonants 'bgdkpt' in II- III C. E. in Palestine, through the confrontation of two kinds of data: the fragments of transliteration of Old Testament in the Greek alphabet, from the second column of Origen’s synopsis, called Hexapla, and Hebrew names transliterated in Greek documents, especially epigraphs. Origen is a very important author, not only for his bgdkpt theological and exegetic works: the Hexapla, synoptic six columns for a critical edition of Septuaginta, has a relevant role in attempting to reconstruct the pronunciation of Hebrew language before Masoretic punctuation. For this reason, at the beginning, it is important to analyze the column in order to study phonetic and linguistic phenomena. Among the most problematic data, there is the evidence from bgdkpt consonants, always represented as Greek aspirated graphemes. This transcription raised the question if their pronunciation was the only spirant, and consequently, the double one, that is, the stop/spirant contrast, was introduced by Masoretes. However, the phonetic and linguistic examination of the column alone is not enough to establish a real pronunciation of language: this paper is significant because a confrontation between the second column’s transliteration and Hebrew names found in Greek documents epigraphic ones mainly, is achieved. Palestine in II - III was a bilingual country: Greek and Aramaic language lived together, the first one like the official language, the second one as the principal mean of communication between people. For this reason, Hebrew names are often found in Greek documents of the same geographical area: a deep examination of bgdkpt’s transliteration can help to understand better which the real pronunciation of these consonants was, or at least it allows to evidence a phonetic tendency. As a consequence, the research considers the contemporary documents to Origen and the previous ones: the first ones testify a specific stadium of pronunciation, the second ones reflect phonemes’ evolution. Alexandrian documents are also examined: Origen was from there, and the influence of Greek language, spoken in his native country, must be considered. The epigraphs have another implication: they are totally free from morphological criteria, probably used by Origen in his column, because of their popular origin. Thus, a confrontation between the hexaplaric transliteration and Hebrew names is absolutely required, in Hexapla’s studies: first of all, it can be the second clue of a pronunciation already noted in the column; then because, for documents’ specific nature, it has more probabilities to be real, reflecting a daily use of language. The examination of data shows a general tendency to employ the aspirated graphemes for bgdkpt consonants’ transliteration. This probably means that they were closer to Greek aspirated consonants rather than to the plosive ones. The exceptions are linked to a particular status of the name, i.e. its history and origin. In this way, this paper gives its contribution to onomastic studies, too: indeed, the research may contribute to verify the diffusion and the treatment of Jewish names in Hellenized world and in the koinè language.

Keywords: bgdkpt consonants, Greek epigraphs, Jewish names, origen's Hexapla

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

Abstract:

Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

Procedia PDF Downloads 121

Authors: Vincent Andrew Cappellano

Abstract:

In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

Procedia PDF Downloads 109