Search results for: parallel output

Authors: Liliana Villavicencio, Yohn Garcia, Pallavi Singh, Luis Fernando Cruz, Wilfrido Moreno

Abstract:

Psychophysiological adaptive automation is a concept that combines human physiological data and computer algorithms to create personalized interfaces and experiences for users. This approach aims to enhance human learning by adapting to individual needs and preferences and optimizing the interaction between humans and machines. According to neurosciences, the working memory demand during the student learning process is modified when the student is learning a new subject or topic, managing and/or fulfilling a specific task goal. A sudden increase in working memory demand modifies the level of students’ attention, engagement, and cognitive load. The proposed psychophysiological adaptive automation system will adapt the task requirements to optimize cognitive load, the process output variable, by monitoring the student's brain activity. Cognitive load changes according to the student’s previous knowledge, the type of task, the difficulty level of the task, and the overall psychophysiological state of the student. Scaling the measured cognitive load as low, medium, or high; the system will assign a task difficulty level to the next task according to the ratio between the previous-task difficulty level and student stress. For instance, if a student becomes stressed or overwhelmed during a particular task, the system detects this through signal measurements such as brain waves, heart rate variability, or any other psychophysiological variables analyzed to adjust the task difficulty level. The control of engagement and stress are considered internal variables for the hypermedia system which selects between three different types of instructional material. This work assesses the feasibility of a fuzzy controller to track a student's physiological responses and adjust the learning content and pace accordingly. Using an industrial automation approach, the proposed fuzzy logic controller is based on linguistic rules that complement the instrumentation of the system to monitor and control the delivery of instructional material to the students. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the delivery of academic content based on the working memory demand without compromising students’ health. This work has a potential application in the instructional design of virtual reality environments for training and education.

Keywords: fuzzy logic controller, hypermedia control system, personalized education, psychophysiological adaptive automation

Procedia PDF Downloads 57

Authors: Nurten Akgun, Dilum Dissanayake, Neil Thorpe, Margaret C. Bell

Abstract:

Cycling has gained a great attention with comparable speeds, low cost, health benefits and reducing the impact on the environment. The main challenge associated with cycling is the provision of safety for the people choosing to cycle as their main means of transport. From the road safety point of view, cyclists are considered as vulnerable road users because they are at higher risk of serious casualty in the urban network but more specifically at roundabouts. This research addresses the development of an enhanced mathematical model by including a broad spectrum of casualty related variables. These variables were geometric design measures (approach number of lanes and entry path radius), speed limit, meteorological condition variables (light, weather, road surface) and socio-demographic characteristics (age and gender), as well as contributory factors. Contributory factors included driver’s behavior related variables such as failed to look properly, sudden braking, a vehicle passing too close to a cyclist, junction overshot, failed to judge other person’s path, restart moving off at the junction, poor turn or manoeuvre and disobeyed give-way. Tyne and Wear in the UK were selected as a case study area. The cyclist casualty data was obtained from UK STATS19 National dataset. The reference categories for the regression model were set to slight and serious cyclist casualties. Therefore, binary logistic regression was applied. Binary logistic regression analysis showed that approach number of lanes was statistically significant at the 95% level of confidence. A higher number of approach lanes increased the probability of severity of cyclist casualty occurrence. In addition, sudden braking statistically significantly increased the cyclist casualty severity at the 95% level of confidence. The result concluded that cyclist casualty severity was highly related to approach a number of lanes and sudden braking. Further research should be carried out an in-depth analysis to explore connectivity of sudden braking and approach number of lanes in order to investigate the driver’s behavior at approach locations. The output of this research will inform investment in measure to improve the safety of cyclists at roundabouts.

Keywords: binary logistic regression, casualty severity, cyclist safety, roundabout

Procedia PDF Downloads 161

Authors: Catia Correia Caeiro, Kun Guo, Daniel Mills

Abstract:

Despite its growing interest, emotions are still an understudied cognitive process and their origins are currently the focus of much debate among the scientific community. The use of facial expressions as traditional hallmarks of discrete and holistic emotions created a circular reasoning due to a priori assumptions of meaning and its associated appearance-biases. Ekman and colleagues solved this problem and laid the foundations for the quantitative and systematic study of facial expressions in humans by developing an anatomically-based system (independent from meaning) to measure facial behaviour, the Facial Action Coding System (FACS). One way of investigating emotion cognition processes is by applying comparative psychology methodologies and looking at either closely-related species (e.g. chimpanzees) or phylogenetically distant species sharing similar present adaptation problems (analogy). In this study, the domestic dog was used as a comparative animal model to look at facial expressions in social interactions in parallel with human facial expressions. The orofacial musculature seems to be relatively well conserved across mammal species and the same holds true for the domestic dog. Furthermore, the dog is unique in having shared the same social environment as humans for more than 10,000 years, facing similar challenges and acquiring a unique set of socio-cognitive skills in the process. In this study, the spontaneous facial movements of humans and dogs were compared when interacting with hetero- and conspecifics as well as in solitary contexts. In total, 200 participants were examined with FACS and DogFACS (The Dog Facial Action Coding System): coding tools across four different emotionally-driven contexts: a) Happiness (play and reunion), b) anticipation (of positive reward), c) fear (object or situation triggered), and d) frustration (negation of a resource). A neutral control was added for both species. All four contexts are commonly encountered by humans and dogs, are comparable between species and seem to give rise to emotions from homologous brain systems. The videos used in the study were extracted from public databases (e.g. Youtube) or published scientific databases (e.g. AM-FED). The results obtained allowed us to delineate clear similarities and differences on the flexibility of the facial musculature in the two species. More importantly, they shed light on what common facial movements are a product of the emotion linked contexts (the ones appearing in both species) and which are characteristic of the species, revealing an important clue for the debate on the origin of emotions. Additionally, we were able to examine movements that might have emerged for interspecific communication. Finally, our results are discussed from an evolutionary perspective adding to the recent line of work that supports an ancient shared origin of emotions in a mammal ancestor and defining emotions as mechanisms with a clear adaptive purpose essential on numerous situations, ranging from maintenance of social bonds to fitness and survival modulators.

Keywords: comparative and evolutionary psychology, emotion, facial expressions, FACS

Procedia PDF Downloads 414

Authors: Aymen Arfaoui, Abdelkader Soumaya, Noureddine Ben Ayed

Abstract:

The study region is located in the Tunisian Dorsal Backland (Central Mediterranean), which is the easternmost part of the Saharan Atlas mountain range, trending southwest-northeast. Based on our fieldwork, seismic tomography images, seismicity, and previous studies, we propose an interpretation of the relationship between the surface deformation and fault kinematics in the study area and the internal dynamic processes acting in the Central Mediterranean from the Cenozoic to the present. The subduction and dynamics of internal forces beneath the complicated Maghrebides mobile belt have an impact on the Tertiary and Quaternary tectonic regimes in the Pelagian and Atlassic foreland that is part of our study region. The left lateral reactivation of the major "Tunisian N-S Axis fault" and the development of a compressional relay between the Hammamet Korbous and Messella-Ressas faults are possibly a result of tectonic stresses due to the slab roll-back following the Africa/Eurasia convergence. After the slab segmentation and its eastward migration (5–4 Ma) and the formation of the Strait of Sicily "rift zone" further east, a transtensional tectonic regime has been installed in this area. According to seismic tomography images, the STEP fault of the "North-South Axis" at Hammamet-Korbous coincides with the western edge of the "Slab windows" of the Sicilian Channel and the eastern boundary of the positive anomalies attributed to the residual Slab of Tunisia. On the other hand, significant E-W Plio-Quaternary tectonic activity may be observed along the eastern portion of this STEP fault system in the Grombalia zone as a result of recent vertical lithospheric motion in response to the lateral slab migration eastward to Sicily Channel. According to SKS fast splitting directions, the upper mantle flow pattern beneath Tunisian Dorsal is parallel to the NE-SW to E-W orientation of the Shmin identified in the study area, similar to the Plio-Quaternary extensional orientation in the Central Mediterranean. Additionally, the removal of the lithosphere and the subsequent uplift of the sub-lithospheric mantle beneath the topographic highs of the Dorsal and its surroundings may be the cause of the dominant extensional to transtensional Quaternary regime. The occurrence of strike-slip and extensional seismic events in the Pelagian block reveals that the regional transtensional tectonic regime persists today. Finally, we believe that the geodynamic history of the study area since the Cenozoic is primarily influenced by the preexisting weak zones, the African slab detachment, and the upper mantle flow pattern in the central Mediterranean.

Keywords: Tunisia, lithospheric discontinuity (STEP fault), geodynamic evolution, Tunisian dorsal backland, strike-slip fault, seismic tomography, seismicity, central Mediterranean

Procedia PDF Downloads 46

Authors: Noam Markovitz

Abstract:

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

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

Procedia PDF Downloads 123

Authors: Madushani Rodrigo, Banuka Athuraliya

Abstract:

In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

Procedia PDF Downloads 56

Authors: Alexander Norbach

Abstract:

The script in this paper describes the use of advanced simulation environment using electronic systems (Microcontroller, Operational Amplifiers, and FPGA). The simulation may be used for all dynamic systems with the diffusion and the ionisation behaviour also. By additionally required observer structure, the system works with parallel real-time simulation based on diffusion model and the state-space representation for other dynamics. The proposed deposited model may be used for electrodynamic effects, including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time. For further purpose, the spatial temperature distribution may be used also. With upon system, the uncertainties, unknown initial states and disturbances may be determined. This provides the estimation of the more precise system states for the required system, and additionally, the estimation of the ionising disturbances that occur due to radiation effects. The results have shown that a system can be also developed and adopted specifically for space systems with the real-time calculation of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. In order to be able to react to these processes, it must be calculated within a shorter time that ionising radiation and dose is present. All available sensors shall be used to observe the spatial distributions. By measured value of size and known location of the sensors, the entire distribution can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of kind of systems space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms. For the modelling and derivation of equations, the extended current equation is used. The size K represents the proposed charge density drifting vector. The extended diffusion equation was derived and shows the quantising character and has similar law like the Klein-Gordon equation. These kinds of PDE's (Partial Differential Equations) are analytically solvable by giving initial distribution conditions (Cauchy problem) and boundary conditions (Dirichlet boundary condition). For a simpler structure, a transfer function for B- and E- fields was analytically calculated. With known discretised responses g₁(k·Ts) and g₂(k·Ts), the electric current or voltage may be calculated using a convolution; g₁ is the direct function and g₂ is a recursive function. The analytical results are good enough for calculation of fields with diffusion effects. Within the scope of this work, a proposed model of the consideration of the electromagnetic diffusion effects of arbitrary current 'waveforms' has been developed. The advantage of the proposed calculation of diffusion is the real-time capability, which is not really possible with the FEM programs available today. It makes sense in the further course of research to use these methods and to investigate them thoroughly.

Keywords: advanced observer, electrodynamics, systems, diffusion, partial differential equations, solver

Procedia PDF Downloads 105

Authors: Niina Jallinoja, Anu Moisio

Abstract:

Focus on adult learning is vital to overcome economic challenges as well as to respond to the demand for new competencies and sustained productivity in the digitalized world economy. Employees of all ages must be able to carry on continuous professional development to remain competitive in the labor market. According to EU policies, countries should offer more flexible opportunities for adult learners who study online and in so-called ‘second chance’ qualification programmes. Traditionally, adult education in Finland has comprised of not only liberal adult education but also the government funding to study for Bachelor, Master's, and Ph.D. degrees in Finnish Universities and Universities of Applied Sciences (UAS). From the beginning of 2021, public funding is allocated not only to degrees but also to courses to achieve new competencies for adult learners in Finland. Consequently, there will be degree students (often younger of age) and adult learners studying in the same evening, online and blended courses. The question is thus: How are combined studies meeting the different needs of degree students and adult learners? Haaga-Helia University of Applied Sciences (UAS), located in the metropolitan area of Finland, is taking up the challenge of continuous learning for adult learners. Haaga-Helia has been reforming the bachelor level education and respective shorter courses from 2019 in the biggest project in its history. By the end of 2023, Haaga-Helia will have a flexible, modular curriculum for the bachelor's degrees of hospitality management, business administration, business information technology, journalism and sports management. Building on the shared key competencies, degree students will have the possibility to build individual study paths more flexibly, thanks to the new modular structure of the curriculum. They will be able to choose courses across all degrees, and thus, build their own unique competence combinations. All modules can also be offered as separate courses or learning paths to non-degree students, both publicly funded and as commercial services for employers. Consequently, there will be shared course implementations for degree studies and adult learners with various competence requirements. The newly designed courses are piloted in parallel of the designing of the curriculum in Haaga-Helia during 2020 and 2021. Semi-structured online surveys are composed among the participants for the key competence courses. The focus of the research is to understand how students in the bachelor programme and adult learners from Open UAE perceive the learning experience in such a diverse learning group. A comparison is also executed between learning methods of in-site teaching, online implementation, blended learning and virtual self-learning courses to understand how the pedagogy is meeting the learning objectives of these two different groups. The new flexible curricula and the study modules are to be designed to fill the most important competence gaps that exist in the Finnish labor markets. The new curriculum will be dynamic and constantly evolving over time according to the future competence needs in the labor market. This type of approach requires constant dialogue between Haaga-Helia and workplaces during and after designing of the shared curriculum.

Keywords: ccompetence development, continuous learning, curriculum, higher education

Procedia PDF Downloads 107

Authors: Jan Schmitt, Sophie Fischer

Abstract:

After the Corona pandemic, climate change is a further, long-lasting challenge the society must deal with. An ongoing climate change need to be prevented. Nevertheless, the adoption tothe already changed climate conditionshas to be focused in many sectors. Recently, the decisive role of the economic sector with high value added can be seen in the Corona crisis. Hence, manufacturing industry as such a sector, needs to be prepared for climate change and adaption. Several examples from the manufacturing industry show the importance of a strategic effort in this field: The outsourcing of a major parts of the value chain to suppliers in other countries and optimizing procurement logistics in a time-, storage- and cost-efficient manner within a network of global value creation, can lead vulnerable impacts due to climate-related disruptions. E.g. the total damage costs after the 2011 flood disaster in Thailand, including costs for delivery failures, were estimated at 45 billion US dollars worldwide. German car manufacturers were also affected by supply bottlenecks andhave close its plant in Thailand for a short time. Another OEM must reduce the production output. In this contribution, a game-based learning approach is presented, which should enable manufacturing companies to derive their own strategies for climate adaption out of a mix of different actions. Based on data from a regional study of small, medium and large manufacturing companies in Mainfranken, a strongly industrialized region of northern Bavaria (Germany) the game-based learning approach is designed. Out of this, the actual state of efforts due to climate adaption is evaluated. First, the results are used to collect single actions for manufacturing companies and second, further actions can be identified. Then, a variety of climate adaption activities can be clustered according to the scope of activity of the company. The combination of different actions e.g. the renewal of the building envelope with regard to thermal insulation, its benefits and drawbacks leads to a specific strategy for climate adaption for each company. Within the game-based approach, the players take on different roles in a fictionalcompany and discuss the order and the characteristics of each action taken into their climate adaption strategy. Different indicators such as economic, ecologic and stakeholder satisfaction compare the success of the respective measures in a competitive format with other virtual companies deriving their own strategy. A "play through" climate change scenarios with targeted adaptation actions illustrate the impact of different actions and their combination onthefictional company.

Keywords: business strategy, climate change, climate adaption, game-based learning

Procedia PDF Downloads 180

Authors: Min-Hua Wu

Abstract:

The untranslatability of an established poet’s tour de force is thoroughly explored by Matthew Arnold (1822-1888). In his On Translating Homer (1861), Arnold lists the four most striking poetic qualities of Homer, namely his rapidity, plainness and directness of style and diction, plainness and directness of ideas, and nobleness. He concludes that such celebrated English translators as Cowper, Pope, Chapman, and Mr. Newman are all doomed, due to their respective failure in rendering the totality of the four Homeric poetic qualities. Why poetic translation always amounts to being proven such a mission impossible for the translator? According to Arnold, it is because there constantly exists a mist interposed between the translator’s own literary self-obsession and the objective artistic qualities that reside in the work of the original author. Foregrounding such a seemingly empowering yet actually detrimental poetic mist, he explains why the aforementioned translators fail in their attempts to bring the Homeric charm to the British reader. Drawing on Arnold’s analytical study on Homeric translation, the research attempts to bring Yu Kwang-chung the poet vis-à-vis Yu Kwang-chung the translator, with an aim not so much to find any similar mist as revealed by Arnold between his Chinese poetry and English translation as to probe into a latent and veiled literary and lingual mist interposed between Chinese and English, if not between Chinese and English literatures. The major work studied and analyzed for this study is Yu’s own Chinese poetry and his own English translation collected in The Night Watchman: Yu Kwang-chung 1958-2004. The research argues that the following critical elements that characterizes Yu’s poetics are to a certain extent 'transformed,' if not 'lost,' in his English translation: a. the Chinese pictographic and ideographic unit terms which so unfailingly characterize the poet’s incredible creativity, allowing him to habitually and conveniently coin concrete textual images or word-scapes almost at his own will; b. the subtle wordplay and punning which appear at a reasonable frequency; c. the parallel contrastive repetitive syntactic structure within a single poetic line; d. the ambiguous and highly associative diction in the adjective and noun categories; e. the literary allusion that harks back to the old times of Chinese literature; f. the alliteration that adds rhythm and smoothness to the lines; g. the rhyming patterns that bring about impressive sonority and lingering echo to the ears of the reader; h. the grandeur-imposing and sublimity-arousing word-scaping which hinges on the employment of verbs; i. the meandering cultural heritage that embraces such elements as Chinese medicine and kung fu; and j. other features of the like. Once we appeal to the Arnoldian tribunal and resort to the strict standards of such a Victorian cultural and literary critic who insists 'to see the object as in itself it really is,' we may serve as a potential judge for the tug of war between Yu Kwang-chung the poet and Yu Kwang-chung the translator, a tug of war that will not merely broaden our understating of Chinese poetics but deepen our apprehension of Chinese-English translatology.

Keywords: Yu Kwang-chung, The Night Watchman, poetry translation, Chinese-English translation, translation studies, Matthew Arnold

Procedia PDF Downloads 372

Authors: M. Tarik Boyraz, M. Bilge Imer

Abstract:

Conventionally cast nickel-based super alloys, such as commercial alloy IN 738 LC, are widely used in manufacturing of industrial gas turbine blades. With carefully designed microstructure and the existence of alloying elements, the blades show improved mechanical properties at high operating temperatures and corrosive environment. The aim of this work is to model and estimate these mechanical properties of IN 738 LC alloy solely based on simulations for projected heat treatment conditions or service conditions. The microstructure (size, fraction and frequency of gamma prime- γ′ and carbide phases in gamma- γ matrix, and grain size) of IN 738 LC needs to be optimized to improve the high temperature mechanical properties by heat treatment process. This process can be performed at different soaking temperature, time and cooling rates. In this work, micro-structural evolution studies were performed experimentally at various heat treatment process conditions, and these findings were used as input for further simulation studies. The operation time, soaking temperature and cooling rate provided by experimental heat treatment procedures were used as micro-structural simulation input. The results of this simulation were compared with the size, fraction and frequency of γ′ and carbide phases, and grain size provided by SEM (EDS module and mapping), EPMA (WDS module) and optical microscope for before and after heat treatment. After iterative comparison of experimental findings and simulations, an offset was determined to fit the real time and theoretical findings. Thereby, it was possible to estimate the final micro-structure without any necessity to carry out the heat treatment experiment. The output of this microstructure simulation based on heat treatment was used as input to estimate yield stress and creep properties. Yield stress was calculated mainly as a function of precipitation, solid solution and grain boundary strengthening contributors in microstructure. Creep rate was calculated as a function of stress, temperature and microstructural factors such as dislocation density, precipitate size, inter-particle spacing of precipitates. The estimated yield stress values were compared with the corresponding experimental hardness and tensile test values. The ability to determine best heat treatment conditions that achieve the desired microstructural and mechanical properties were developed for IN 738 LC based completely on simulations.

Keywords: heat treatment, IN738LC, simulations, super-alloys

Procedia PDF Downloads 229

Authors: Ferzat Anka

Abstract:

Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

Procedia PDF Downloads 54

Authors: Yusuf U. Datti

Abstract:

It is becoming increasingly clear that the consumption of resources now enjoyed in the developed nations will be impossible to be sustained worldwide. While developing countries still have the advantage of low consumption and a smaller ecological footprint per person, they cannot simply develop in the same way as other western cities have developed in the past. The severe reality of population and consumption inequalities makes it contentious whether studies done in developed countries can be translated and applied to developing countries. Additional to this disparities, there are few or no metabolism of energy studies in Nigeria. Rather more contentious majority of energy metabolism studies have been done only in developed countries. While researches in Nigeria concentrate on other aspects/principles of sustainability such as water supply, sewage disposal, energy supply, energy efficiency, waste disposal, etc., which will not accurately capture the environmental impact of energy flow in Nigeria, this research will set itself apart by examining the flow of energy in Nigeria and the impact that the flow will have on the environment. The aim of the study is to examine and quantify the metabolic flows of energy in Nigeria and its corresponding environmental impact. The study will quantify the level and pattern of energy inflow and the outflow of greenhouse emissions in Nigeria. This study will describe measures to address the impact of existing energy sources and suggest alternative renewable energy sources in Nigeria that will lower the emission of greenhouse gas emissions. This study will investigate the metabolism of energy in Nigeria through a three-part methodology. The first step involved selecting and defining the study area and some variables that would affect the output of the energy (time of the year, stability of the country, income level, literacy rate and population). The second step involves analyzing, categorizing and quantifying the amount of energy generated by the various energy sources in the country. The third step involves analyzing what effect the variables would have on the environment. To ensure a representative sample of the study area, Africa’s most populous country, with economy that is the second biggest and that is among the top largest oil producing countries in the world is selected. This is due to the understanding that countries with large economy and dense populations are ideal places to examine sustainability strategies; hence, the choice of Nigeria for the study. National data will be utilized unless where such data cannot be found, then local data will be employed which will be aggregated to reflect the national situation. The outcome of the study will help policy-makers better target energy conservation and efficiency programs and enables early identification and mitigation of any negative effects in the environment.

Keywords: built environment, energy metabolism, environmental impact, greenhouse gas emissions and sustainability

Procedia PDF Downloads 160

Authors: Vikas Kumar, Kailash Chandra, Kaomud Tyagi

Abstract:

The insect order Thysanoptera includes small insects commonly called thrips. As insect vectors, only thrips are capable of Tospoviruses transmission (genus Tospovirus, family Bunyaviridae) affecting various crops. Currently, fifteen species of subfamily Thripinae (Thripidae) have been reported as vectors for tospoviruses. Frankliniella schultzei, which is reported as act as a vector for at least five tospovirses, have been suspected to be a species complex with more than one species. It is one of the historical unresolved issues where, two species namely, F. schultzei Trybom and F. sulphurea Schmutz were erected from South Africa and Srilanaka respectively. These two species were considered to be valid until 1968 when sulphurea was treated as colour morph (pale form) and synonymised under schultzei (dark form) However, these two have been considered as valid species by some of the thrips workers. Parallel studies have indicated that brown form of schultzei is a vector for tospoviruses while yellow form is a non-vector. However, recent studies have shown that yellow populations have also been documented as vectors. In view of all these facts, it is highly important to have a clear understanding whether these colour forms represent true species or merely different populations with different vector carrying capacities and whether there is some hidden diversity in 'Frankliniella schultzei species complex'. In this study, we aim to study the 'Frankliniella schultzei species complex' with molecular spectacles with DNA data from India and Australia and Africa. A total of fifty-five specimens was collected from diverse locations in India and Australia. We generated molecular data using partial fragments of mitochondrial cytochrome c oxidase I gene (mtCOI) and 28S rRNA gene. For COI dataset, there were seventy-four sequences, out of which data on fifty-five was generated in the current study and others were retrieved from NCBI. All the four different tree construction methods: neighbor-joining, maximum parsimony, maximum likelihood and Bayesian analysis, yielded the same tree topology and produced five cryptic species with high genetic divergence. For, rDNA, there were forty-five sequences, out of which data on thirty-nine was generated in the current study and others were retrieved from NCBI. The four tree building methods yielded four cryptic species with high bootstrap support value/posterior probability. Here we could not retrieve one cryptic species from South Africa as we could not generate data on rDNA from South Africa and sequence for rDNA from African region were not available in the database. The results of multiple species delimitation methods (barcode index numbers, automatic barcode gap discovery, general mixed Yule-coalescent, and Poisson-tree-processes) also supported the phylogenetic data and produced 5 and 4 Molecular Operational Taxonomic Units (MOTUs) for mtCOI and 28S dataset respectively. These results of our study indicate the likelihood that F. sulphurea may be a valid species, however, more morphological and molecular data is required on specimens from type localities of these two species and comparison with type specimens.

Keywords: DNA barcoding, species complex, thrips, species delimitation

Procedia PDF Downloads 110

Authors: Fatih Ercin Guney, Hami Karagol

Abstract:

Day by day, humanity's energy needs increase, to facilitate access to energy sources by energy importing countries is of great importance in terms of issues both in terms of economic security and political security. The geographical location of the oil exporting countries in the Middle East (Iran, Iraq, Kuwait, Libya, Saudi Arabia, United Arab Emirates, Qatar) today, it is observed that evaluated by emerging Arab Spring(from Tunisia to Egypt) and freedom battles(in Syria) with security issues arise sourced from terrorist activities(ISIS). Progresses related with limited natural resources, energy and it's transportation issues which worries the developing countries, the energy in the region is considered to how to transfer safely. North Region of the Black Sea , the beginning of the conflict in the regional nature formed between Russia and Ukraine (2010), followed by the relevant regions of the power transmission line (From Russia to Europe) the discovery is considered to be the east's hand began to strengthen in terms of both the economical and political sides. With the growing need for safe access to the west of the new energy transmission lines are followed by Turkey, re-interest is considered to be shifted to the Mediterranean and the Middle East by West. Also, Russia, Iran and China (three axis of east) are generally performing as carry out parallel policies about energy , economical side and security in both United Nations Security Council (Two of Five Permanent Members are Russia and China) and Shanghai Cooperation Organization. In addition, Eastern Mediterranean Region Tension are rapidly increasing about research new oil and natural gas sources by Israel, Egypt, Cyprus, Lebanon. This paper provides, new energy corridor(s) are needed to transfer sources (Oil&Natural Gas) by Europe from East to West. So The West needs either safe bridge country to transfer natural sources to Europe in region or is needed to discovery new natural sources in extraterritorial waters of Eastern Mediterranean Region. But in two opportunities are evaluated with secure transfer corridors form region to Europe in safely. Even if the natural sources can be discovered, they are considered to transfer in safe manner. This paper involved, Turkey’s importance as a leader country in region over both of political and safe energy transfer sides as bridge country between south and north of Turkey why natural sources shall be transferred over Turkey, Even if diplomatic issues-For Example; Cyprus membership in European Union, Turkey membership candidate duration, Israel-Cyprus- Egypt-Lebanon researches about new natural sources in Mediterranean - occurred. But politic balance in Middle-East is changing quickly because of lack of democratic governments in region. So it is evaluated that the alliance of natural sources researches may not be long-time relations due to share sources after discoveries. After evaluating over causes and reasons, aim to reach finding foresight about future of region for energy transfer periods in secure manner.

Keywords: Middle East, natural gas, oil, Turkey

Procedia PDF Downloads 279

Authors: Eliane Abdo, Olivier Colot

Abstract:

SMEs are always considered as a national priority due to their contribution to job creation, innovation and growth. Once the start-up phase is crossed with encouraging results, the company enters the phase of growth. In order to improve its competitiveness, maintain and increase its market share, the company is in the necessity even the obligation to develop its tangible and intangible investments. SMEs are generally closed companies with special and critical financial situation, limited resources and difficulty to access the capital markets; their shareholders are always living in a conflict between their independence and their need to increase capital that leads to the entry of new shareholder. The capital structure was always considered the core of research in corporate finance; moreover, the financial crisis and its repercussions on the credit’s availability, especially for SMEs make SME financing a hot topic. On the other hand, financial theories do not provide answers to capital structure’s questions; they offer tools and mode of financing that are more accessible to larger companies. Yet, SME’s capital structure can’t be independent of their governance structure. The classic financial theory supposes independence between the investment decision and the financing decision. Thus, investment determines the volume of funding, but not the split between internal or external funds. In this context, we find interesting to study the hypothesis that SMEs respond positively to the financial theories applied to large firms and to check if they are constrained by conventional solutions used by large companies. In this context, this research focuses on the analysis of the resource’s structure of SME in parallel with their investments’ structure, in order to highlight a link between their assets and liabilities structure. We founded our conceptual model based on two main theoretical frameworks: the Pecking order theory, and the Trade Off theory taking into consideration the SME’s characteristics. Our data were generated from DIANE database. Five hypotheses were tested via a panel regression to understand the type of dependence between the financing methods of 3,244 French SMEs and the development of their investment over a period of 10 years (2007-2016). The results show dependence between equity and internal financing in case of intangible investments development. Moreover, this type of business is constraint to financial debts since the guarantees provided are not sufficient to meet the banks' requirements. However, for tangible investments development, SMEs count sequentially on internal financing, bank borrowing, and new shares issuance or hybrid financing. This is compliant to the Pecking Order Theory. We, therefore, conclude that unlisted SMEs incur more financial debts to finance their tangible investments more than their intangible. However, they always prefer internal financing as a first choice. This seems to be confirmed by the assumption that the profitability of the company is negatively related to the increase of the financial debt. Thus, the Pecking Order Theory predictions seem to be the most plausible. Consequently, SMEs primarily rely on self-financing and then go, into debt as a priority to finance their financial deficit.

Keywords: capital structure, investments, life cycle, pecking order theory, trade off theory

Procedia PDF Downloads 88

Authors: Maria C. Proença, Maria T. Rebelo, Marília Antunes, Maria J. Alves, Hugo Osório, Sofia Cunha, REVIVE team

Abstract:

The environment of the mosquitoes complex Culex pipiens sl. in Portugal mainland is evaluated based in its abundance, using a data set georeferenced, collected during seven years (2006-2012) from May to October. The suitability of the different regions can be delineated using the relative abundance areas; the suitablility index is directly proportional to disease transmission risk and allows focusing mitigation measures in order to avoid outbreaks of vector-borne diseases. The interest in the Culex pipiens complex is justified by its medical importance: the females bite all warm-blooded vertebrates and are involved in the circulation of several arbovirus of concern to human health, like West Nile virus, iridoviruses, rheoviruses and parvoviruses. The abundance of Culex pipiens mosquitoes were documented systematically all over the territory by the local health services, in a long duration program running since 2006. The environmental factors used to characterize the vector habitat are land use/land cover, distance to cartographed water bodies, altitude and latitude. Focus will be on the mosquito females, which gonotrophic cycle mate-bloodmeal-oviposition is responsible for the virus transmission; its abundance is the key for the planning of non-aggressive prophylactic countermeasures that may eradicate the transmission risk and simultaneously avoid chemical ambient degradation. Meteorological parameters such as: air relative humidity, air temperature (minima, maxima and mean daily temperatures) and daily total rainfall were gathered from the weather stations network for the same dates and crossed with the standardized females’ abundance in a geographic information system (GIS). Mean capture and percentage of above average captures related to each variable are used as criteria to compute a threshold for each meteorological parameter; the difference of the mean capture above/below the threshold was statistically assessed. The meteorological parameters measured at the net of weather stations all over the country are averaged by month and interpolated to produce raster maps that can be segmented according to the meaningful thresholds for each parameter. The intersection of the maps of all the parameters obtained for each month show the evolution of the suitable meteorological conditions through the mosquito season, considered as May to October, although the first and last month are less relevant. In parallel, mean and above average captures were related to the physiographic parameters – the land use/land cover classes most relevant in each month, the altitudes preferred and the most frequent distance to water bodies, a factor closely related with the mosquito biology. The maps produced with these results were crossed with the meteorological maps previously segmented, in order to get an index of suitability for the complex Culex pipiens evaluated all over the country, and its evolution from the beginning to the end of the mosquitoes season.

Keywords: suitability index, Culex pipiens, habitat evolution, GIS model

Procedia PDF Downloads 553

Authors: Diamant Irene, Dar Tamar

Abstract:

Burnout, conceptualized within the framework of stress research, is to a large extent a result of a threat on resources of time or a feeling of time shortage. In reaction to numerous tasks, deadlines, high output, management of different duties encompassing work-home conflicts, many individuals experience ‘time pressure’. Time pressure is characterized as the perception of a lack of available time in relation to the amount of workload. It can be a result of local objective constraints, but it can also be a chronic attribute in coping with life. As such, time pressure is associated in the literature with general stress experience and can therefore be a direct, contributory burnout factor. The present study examines the relation of chronic time pressure – feeling of time shortage and of being rushed, with another central aspect in subjective temporal experience - time perspective. Time perspective is a stable personal disposition, capturing the extent to which people subjectively remember the past, live the present and\or anticipate the future. Based on Hobfoll’s Conservation of Resources Theory, it was hypothesized that individuals with chronic time pressure would experience a permanent threat on their time resources resulting in relatively increased burnout. In addition, it was hypothesized that different time perspective profiles, based on Zimbardo’s typology of five dimensions – Past Positive, Past Negative, Present Hedonistic, Present Fatalistic, and Future, would be related to different magnitudes of chronic time pressure and of burnout. We expected that individuals with ‘Past Negative’ or ‘Present Fatalist’ time perspectives would experience more burnout, with chronic time pressure being a moderator variable. Conversely, individuals with a ‘Present Hedonistic’ - with little concern with the future consequences of actions, would experience less chronic time pressure and less burnout. Another temporal experience angle examined in this study is the difference between the actual distribution of time (as in a typical day) versus desired distribution of time (such as would have been distributed optimally during a day). It was hypothesized that there would be a positive correlation between the gap between these time distributions and chronic time pressure and burnout. Data was collected through an online self-reporting survey distributed on social networks, with 240 participants (aged 21-65) recruited through convenience and snowball sampling methods from various organizational sectors. The results of the present study support the hypotheses and constitute a basis for future debate regarding the elements of burnout in the modern work environment, with an emphasis on subjective temporal experience. Our findings point to the importance of chronic and stable temporal experiences, as time pressure and time perspective, in occupational experience. The findings are also discussed with a view to the development of practical methods of burnout prevention.

Keywords: conservation of resources, burnout, time pressure, time perspective

Procedia PDF Downloads 149

Authors: Adeola Adenikinju, Olusanya E. Olubusoye, Lateef O. Akinpelu, Dilinna L. Nwobi

Abstract:

Since the enactment of the Fiscal Responsibility Act (2007), the Federal Government of Nigeria (FGN) has made public its fiscal budget and the subsequent implementation report. A critical review of these documents shows significant variations in the five macroeconomic variables which are inputs in each Presidential budget; oil Production target (mbpd), oil price ($), Foreign exchange rate(N/$), and Gross Domestic Product growth rate (%) and inflation rate (%). This results in underperformance of the Federal budget expected output in terms of non-oil and oil revenue aggregates. This paper evaluates first the existing variance between budgeted and actuals, then the relationship and causality between the determinants of Federal fiscal budget assumptions, and finally the determinants of FGN’s Gross Oil Revenue. The paper employed the use of descriptive statistics, the Autoregressive distributed lag (ARDL) model, and a Profit oil probabilistic model to achieve these objectives. This model permits for both the static and dynamic effect(s) of the independent variable(s) on the dependent variable, unlike a static model that accounts for static or fixed effect(s) only. It offers a technique for checking the existence of a long-run relationship between variables, unlike other tests of cointegration, such as the Engle-Granger and Johansen tests, which consider only non-stationary series that are integrated of the same order. Finally, even with small sample size, the ARDL model is known to generate a valid result, for it is the dependent variable and is the explanatory variable. The results showed that there is a long-run relationship between oil revenue as a proxy for budget performance and its determinants; oil price, produced oil quantity, and foreign exchange rate. There is a short-run relationship between oil revenue and its determinants; oil price, produced oil quantity, and foreign exchange rate. There is a long-run relationship between non-oil revenue and its determinants; inflation rate, GDP growth rate, and foreign exchange rate. The grangers’ causality test results show that there is a mono-directional causality between oil revenue and its determinants. The Federal budget assumptions only explain 68% of oil revenue and 62% of non-oil revenue. There is a mono-directional causality between non-oil revenue and its determinants. The Profit oil Model describes production sharing contracts, joint ventures, and modified carrying arrangements as the greatest contributors to FGN’s gross oil revenue. This provides empirical justification for the selected macroeconomic variables used in the Federal budget design and performance evaluation. The research recommends other variables, debt and money supply, be included in the Federal budget design to explain the Federal budget revenue performance further.

Keywords: ARDL, budget performance, oil price, oil quantity, oil revenue

Procedia PDF Downloads 148

Authors: Triveni Gogoi, Rima Chatterjee

Abstract:

Shear wave velocity (Vs) estimation is an important approach in the seismic exploration and characterization of a hydrocarbon reservoir. There are varying methods for prediction of S-wave velocity, if recorded S-wave log is not available. But all the available methods for Vs prediction are empirical mathematical models. Shear wave velocity can be estimated using P-wave velocity by applying Castagna’s equation, which is the most common approach. The constants used in Castagna’s equation vary for different lithologies and geological set-ups. In this study, multiple regression analysis has been used for estimation of S-wave velocity. The EMERGE module from Hampson-Russel software has been used here for generation of S-wave log. Both single attribute and multi attributes analysis have been carried out for generation of synthetic S-wave log in Upper Assam basin. Upper Assam basin situated in North Eastern India is one of the most important petroleum provinces of India. The present study was carried out using four wells of the study area. Out of these wells, S-wave velocity was available for three wells. The main objective of the present study is a prediction of shear wave velocities for wells where S-wave velocity information is not available. The three wells having S-wave velocity were first used to test the reliability of the method and the generated S-wave log was compared with actual S-wave log. Single attribute analysis has been carried out for these three wells within the depth range 1700-2100m, which corresponds to Barail group of Oligocene age. The Barail Group is the main target zone in this study, which is the primary producing reservoir of the basin. A system generated list of attributes with varying degrees of correlation appeared and the attribute with the highest correlation was concerned for the single attribute analysis. Crossplot between the attributes shows the variation of points from line of best fit. The final result of the analysis was compared with the available S-wave log, which shows a good visual fit with a correlation of 72%. Next multi-attribute analysis has been carried out for the same data using all the wells within the same analysis window. A high correlation of 85% has been observed between the output log from the analysis and the recorded S-wave. The almost perfect fit between the synthetic S-wave and the recorded S-wave log validates the reliability of the method. For further authentication, the generated S-wave data from the wells have been tied to the seismic and correlated them. Synthetic share wave log has been generated for the well M2 where S-wave is not available and it shows a good correlation with the seismic. Neutron porosity, density, AI and P-wave velocity are proved to be the most significant variables in this statistical method for S-wave generation. Multilinear regression method thus can be considered as a reliable technique for generation of shear wave velocity log in this study.

Keywords: Castagna's equation, multi linear regression, multi attribute analysis, shear wave logs

Procedia PDF Downloads 201

Authors: Hemant Upadhyay, Tarun Kumar Kundu

Abstract:

It is utmost important for a blast furnace operator to understand the mechanisms governing the liquid flow, accumulation, drainage and heat transfer between various phases in blast furnace hearth for a stable and efficient blast furnace operation. Abnormal drainage behavior may lead to high liquid build up in the hearth. Operational problems such as pressurization, low wind intake, and lower material descent rates, normally be encountered if the liquid levels in the hearth exceed a critical limit when Hearth coke and Deadman start to float. Similarly, hot metal temperature is an important parameter to be controlled in the BF operation; it should be kept at an optimal level to obtain desired product quality and a stable BF performance. It is not possible to carry out any direct measurement of above due to the hostile conditions in the hearth with chemically aggressive hot liquids. The objective here is to develop a mathematical model to simulate the variation in hot metal / slag accumulation and temperature during the tapping of the blast furnace based on the computed drainage rate, production rate, mass balance, heat transfer between metal and slag, metal and solids, slag and solids as well as among the various zones of metal and slag itself. For modeling purpose, the BF hearth is considered as a pressurized vessel, filled with solid coke particles. Liquids trickle down in hearth from top and accumulate in voids between the coke particles which are assumed thermally saturated. A set of generic mass balance equations gives the amount of metal and slag intake in hearth. A small drainage (tap hole) is situated at the bottom of the hearth and flow rate of liquids from tap hole is computed taking in account the amount of both the phases accumulated their level in hearth, pressure from gases in the furnace and erosion behaviors of tap hole itself. Heat transfer equations provide the exchange of heat between various layers of liquid metal and slag, and heat loss to cooling system through refractories. Based on all that information a dynamic simulation is carried out which provides real time information of liquids accumulation in hearth before and during tapping, drainage rate and its variation, predicts critical event timings during tapping and expected tapping temperature of metal and slag on preset time intervals. The model is in use at JSPL, India BF-II and its output is regularly cross-checked with actual tapping data, which are in good agreement.

Keywords: blast furnace, hearth, deadman, hotmetal

Procedia PDF Downloads 168

Authors: Gaurav Kumar Sinha

Abstract:

In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

Procedia PDF Downloads 44

Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

Abstract:

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

Procedia PDF Downloads 10

Authors: Nicholas McNamara, John Brookes, Michael Williams, Manish Mathew, Elizabeth Brookes, Tristan Yan, Paul Bannon

Abstract:

Objective: Pericardial effusions are an uncommon but potentially fatal complication after cardiac surgery. The goal of this study was to describe the incidence and risk factors associated with the development of pericardial effusion requiring drainage after coronary artery bypass graft surgery (CABG). Methods: A retrospective analysis was undertaken using prospectively collected data. All adult patients who underwent CABG at our institution between 1st January 2017 and 31st December 2018 were included. Pericardial effusion was diagnosed using transthoracic echocardiography (TTE) performed for clinical suspicion of pre-tamponade or tamponade. Drainage was undertaken if considered clinically necessary and performed via a sub-xiphoid incision, pericardiocentesis, or via re-sternotomy at the discretion of the treating surgeon. Patient demographics, operative characteristics, anticoagulant exposure, and postoperative outcomes were examined to identify those variables associated with the development of pericardial effusion requiring drainage. Tests of association were performed using the Fischer exact test for dichotomous variables and the Student t-test for continuous variables. Logistic regression models were used to determine univariate predictors of pericardial effusion requiring drainage. Results: Between January 1st, 2017, and December 31st, 2018, a total of 408 patients underwent CABG at our institution, and eight (1.9%) required drainage of pericardial effusion. There was no difference in age, gender, or the proportion of patients on preoperative therapeutic heparin between the study and control groups. Univariate analysis identified preoperative atrial arrhythmia (37.5% vs 8.8%, p = 0.03), reduced left ventricular ejection fraction (47% vs 56%, p = 0.04), longer cardiopulmonary bypass (130 vs 84 min, p < 0.01) and cross-clamp (107 vs 62 min, p < 0.01) times, higher drain output in the first four postoperative hours (420 vs 213 mL, p <0.01), postoperative atrial fibrillation (100% vs 32%, p < 0.01), and pleural effusion requiring drainage (87.5% vs 12.5%, p < 0.01) to be associated with development of pericardial effusion requiring drainage. Conclusion: In this study, the incidence of pericardial effusion requiring drainage was 1.9%. Several factors, mainly related to preoperative or postoperative arrhythmia, length of surgery, and pleural effusion requiring drainage, were identified to be associated with developing clinically significant pericardial effusions. High clinical suspicion and low threshold for transthoracic echo are pertinent to ensure this potentially lethal condition is not missed.

Keywords: coronary artery bypass, pericardial effusion, pericardiocentesis, tamponade, sub-xiphoid drainage

Procedia PDF Downloads 149

Authors: Ja-Keoung Koo, Kensuke Nakamura, Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Byung-Woo Hong

Abstract:

The machine learning techniques based on a convolutional neural network (CNN) have been actively developed and successfully applied to a variety of image analysis tasks including reconstruction, noise reduction, resolution enhancement, segmentation, motion estimation, object recognition. The classical visual information processing that ranges from low level tasks to high level ones has been widely developed in the deep learning framework. It is generally considered as a challenging problem to derive visual interpretation from high dimensional imagery data. A CNN is a class of feed-forward artificial neural network that usually consists of deep layers the connections of which are established by a series of non-linear operations. The CNN architecture is known to be shift invariant due to its shared weights and translation invariance characteristics. However, it is often computationally intractable to optimize the network in particular with a large number of convolution layers due to a large number of unknowns to be optimized with respect to the training set that is generally required to be large enough to effectively generalize the model under consideration. It is also necessary to limit the size of convolution kernels due to the computational expense despite of the recent development of effective parallel processing machinery, which leads to the use of the constantly small size of the convolution kernels throughout the deep CNN architecture. However, it is often desired to consider different scales in the analysis of visual features at different layers in the network. Thus, we propose a CNN model where different sizes of the convolution kernels are applied at each layer based on the random projection. We apply random filters with varying sizes and associate the filter responses with scalar weights that correspond to the standard deviation of the random filters. We are allowed to use large number of random filters with the cost of one scalar unknown for each filter. The computational cost in the back-propagation procedure does not increase with the larger size of the filters even though the additional computational cost is required in the computation of convolution in the feed-forward procedure. The use of random kernels with varying sizes allows to effectively analyze image features at multiple scales leading to a better generalization. The robustness and effectiveness of the proposed CNN based on random kernels are demonstrated by numerical experiments where the quantitative comparison of the well-known CNN architectures and our models that simply replace the convolution kernels with the random filters is performed. The experimental results indicate that our model achieves better performance with less number of unknown weights. The proposed algorithm has a high potential in the application of a variety of visual tasks based on the CNN framework. Acknowledgement—This work was supported by the MISP (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by IITP, and NRF-2014R1A2A1A11051941, NRF2017R1A2B4006023.

Keywords: deep learning, convolutional neural network, random kernel, random projection, dimensionality reduction, object recognition

Procedia PDF Downloads 262

Authors: Fredrick Forster, Gareth Ward, Matthew Tubby, Pamela Lithgow, Anne Nortcliffe

Abstract:

This paper presents the results from a research study of random adult participants accessing one of four different commercially available Virtual Reality (VR) Head Mounted Displays (HMDs) and completing a post user experience reflection questionnaire. The research sort to understand how inclusive commercially available VR HMDs are and identify any associated barriers that could impact the widespread adoption of the devices, specifically in Higher Education (HE). In the UK, education providers are legally required under the Equality Act 2010 to ensure all education facilities are inclusive and reasonable adjustments can be applied appropriately. The research specifically aimed to identify the considerations that academics and learning technologists need to make when adopting the use of commercial VR HMDs in HE classrooms, namely cybersickness, user comfort, Interpupillary Distance, inclusiveness, and user perceptions of VR. The research approach was designed to build upon previously published research on user reflections on presence, usability, and overall HMD comfort, using quantitative and qualitative research methods by way of a questionnaire. The quantitative data included the recording of physical characteristics such as the distance between eye pupils, known as Interpupillary Distance (IPD). VR HMDs require each user’s IPD measurement to enable the focusing of the VR HMDs virtual camera output to the right position in front of the eyes of the user. In addition, the questionnaire captured users’ qualitative reflections and evaluations of the broader accessibility characteristics of the VR HMDs. The initial research activity was accomplished by enabling a random sample of visitors, staff, and students at Canterbury Christ Church University, Kent to use a VR HMD for a set period of time and asking them to complete the post user experience questionnaire. The study identified that there is little correlation between users who experience cyber sickness and car sickness. Also, users with a smaller IPD than average (typically associated with females) were able to use the VR HMDs successfully; however, users with a larger than average IPD reported an impeded experience. This indicates that there is reduced inclusiveness for the tested VR HMDs for users with a higher-than-average IPD which is typically associated with males of certain ethnicities. As action education research, these initial findings will be used to refine the research method and conduct further investigations with the aim to provide verification and validation of the accessibility of current commercial VR HMDs. The conference presentation will report on the research results of the initial study and subsequent follow up studies with a larger variety of adult volunteers.

Keywords: virtual reality, education technology, inclusive technology, higher education

Procedia PDF Downloads 41

Authors: Nursultan Turdakyn, Alisher Medeubayev, Didar Meiramov, Zhibek Bekezhankyzy, Desmond Adair, Gulnur Kalimuldina

Abstract:

In recent years the development of sustainable energy sources is getting extensive research interest due to the ever-growing demand for energy. As an alternative energy source to power small electronic devices, ambient energy harvesting from vibration or human body motion is considered a potential candidate. Despite the enormous progress in the field of battery research in terms of safety, lifecycle and energy density in about three decades, it has not reached the level to conveniently power wearable electronic devices such as smartwatches, bands, hearing aids, etc. For this reason, the development of self-charging power units with excellent flexibility and integrated energy harvesting and storage is crucial. Self-powering is a key idea that makes it possible for the system to operate sustainably, which is now getting more acceptance in many fields in the area of sensor networks, the internet of things (IoT) and implantable in-vivo medical devices. For solving this energy harvesting issue, the self-powering nanogenerators (NGS) were proposed and proved their high effectiveness. Usually, sustainable power is delivered through energy harvesting and storage devices by connecting them to the power management circuit; as for energy storage, the Li-ion battery (LIB) is one of the most effective technologies. Through the movement of Li ions under the driving of an externally applied voltage source, the electrochemical reactions generate the anode and cathode, storing the electrical energy as the chemical energy. In this paper, we present a simultaneous process of converting the mechanical energy into chemical energy in a way that NG and LIB are combined as an all-in-one power system. The electrospinning method was used as an initial step for the development of such a system with a β-PVDF separator. The obtained film showed promising voltage output at different stress frequencies. X-ray diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) analysis showed a high percentage of β phase of PVDF polymer material. Moreover, it was found that the addition of 1 wt.% of BTO (Barium Titanate) results in higher quality fibers. When comparing pure PVDF solution with 20 wt.% content and the one with BTO added the latter was more viscous. Hence, the sample was electrospun uniformly without any beads. Lastly, to test the sensor application of such film, a particular testing device has been developed. With this device, the force of a finger tap can be applied at different frequencies so that electrical signal generation is validated.

Keywords: electrospinning, nanogenerators, piezoelectric PVDF, self-charging li-ion batteries

Procedia PDF Downloads 141

Authors: Esra Sengul, R. G. Aktas, M. E. Sitar, H. Isan

Abstract:

Hepatocellular carcinoma (HCC) is a hepatocellular tumor commonly found on the surface of the chronic liver. HepG2 is the most commonly used cell type in HCC studies. The main proteins remaining in the blood serum after separation of plasma fibrinogen are albumin and globulin. The fact that the albumin showed hepatocellular damage and reflect the synthesis capacity of the liver was the main reason for our use. Alpha-Fetoprotein (AFP) is an albumin-like structural embryonic globulin found in the embryonic cortex, cord blood, and fetal liver. It has been used as a marker in the follow-up of tumor growth in various malign tumors and in the efficacy of surgical-medical treatments, so it is a good protein to look at with albumins. We have seen the morphological changes of dimethyl sulfoxide (DMSO) on HepG2 and decided to investigate its biochemical effects. We examined the effects of DMSO, which is used in cell cultures, on albumin, AFP and total protein at low doses. Material Method: Cell Culture: Medium was prepared in cell culture using Dulbecco's Modified Eagle Media (DMEM), Fetal Bovine Serum Dulbecco's (FBS), Phosphate Buffered Saline and trypsin maintained at -20 ° C. Fixation of Cells: HepG2 cells, which have been appropriately developed at the end of the first week, were fixed with acetone. We stored our cells in PBS at + 4 ° C until the fixation was completed. Area Calculation: The areas of the cells are calculated in the ImageJ (IJ). Microscope examination: The examination was performed with a Zeiss Inverted Microscope. Daytime photographs were taken at 40x, 100x 200x and 400x. Biochemical Tests: Protein (Total): Serum sample was analyzed by a spectrophotometric method in autoanalyzer. Albumin: Serum sample was analyzed by a spectrophotometric method in autoanalyzer. Alpha-fetoprotein: Serum sample was analyzed by ECLIA method. Results: When liver cancer cells were cultured in medium with 1% DMSO for 4 weeks, a significant difference was observed when compared with the control group. As a result, we have seen that DMSO can be used as an important agent in the treatment of liver cancer. Cell areas were reduced in the DMSO group compared to the control group and the confluency ratio increased. The ability to form spheroids was also significantly higher in the DMSO group. Alpha-fetoprotein was lower than the values of an ordinary liver cancer patient and the total protein amount increased to the reference range of the normal individual. Because the albumin sample was below the specimen value, the numerical results could not be obtained on biochemical examinations. We interpret all these results as making DMSO a caretaking aid. Since each one was not enough alone we used 3 parameters and the results were positive when we refer to the values of a normal healthy individual in parallel. We hope to extend the study further by adding new parameters and genetic analyzes, by increasing the number of samples, and by using DMSO as an adjunct agent in the treatment of liver cancer.

Keywords: hepatocellular carcinoma, HepG2, dimethyl sulfoxide, cell culture, ELISA

Procedia PDF Downloads 118

Authors: Rahul Jain, Jagdish Chander, Anish Gupta

Abstract:

Introduction: Laparoscopic common bile duct exploration (LCBDE) allows cholecystectomy and the removal of common bile duct (CBD) stones to be performed during the same sitting, thereby decreasing hospital stay. CBD exploration through choledochotomy can be closed primarily with an absorbable suture material, but can lead to biliary leakage postoperatively. In this study we tried to find a solution to further lower the incidence of bile leakage by using fibrin glue to reinforce the sutures put on choledochotomy suture line. It has haemostatic and sealing action, through strengthening the last step of the physiological coagulation and biostimulation, which favours the formation of new tissue matrix. Methodology: This study was conducted at a tertiary care teaching hospital in New Delhi, India, from 2011 to 2013. 20 patients with CBD stones documented on MRCP with CBD diameter of 9 mm or more were included in this study. Patients were randomized into two groups namely Group A in which choledochotomy was closed with polyglactin 4-0 suture and suture line reinforced with fibrin glue, and Group ‘B’ in which choledochotomy was closed with polyglactin 4-0 suture alone. Both the groups were evaluated and compared on clinical parameters such as operative time, drain content, drain output, no. of days drain was required, blood loss & transfusion requirements, length of postoperative hospital stay and conversion to open surgery. Results: The operative time for Group A ranged from 60 to 210 min (mean 131.50 min) and Group B 65 to 300 min (mean 140 minutes). The blood loss in group A ranged from 10 to 120 ml (mean 51.50 ml), in group B it ranged from 10 to 200 ml (mean 53.50 ml). In Group A, there was no case of bile leak but there was bile leak in 2 cases in Group B, minimum 0 and maximum 900 ml with a mean of 97 ml and p value of 0.147 with no statistically significant difference in bile leak in test and control groups. The minimum and maximum serous drainage in Group A was nil & 80 ml (mean 11 ml) and in Group B was nil & 270 ml (mean 72.50 ml). The p value came as 0.028 which is statistically significant. Thus serous leakage in Group A was significantly less than in Group B. The drains in Group A were removed from 2 to 4 days (mean: 3 days) while in Group B from 2 to 9 days (mean: 3.9 days). The patients in Group A stayed in hospital post operatively from 3 to 8 days (mean: 5.30) while in Group B it ranged from 3 to 10 days with a mean of 5 days. Conclusion: Fibrin glue application on CBD decreases bile leakage but in statistically insignificant manner. Fibrin glue application on CBD can significantly decrease post operative serous drainage after LCBDE. Fibrin glue application on CBD is safe and easy technique without any significant adverse effects and can help less experienced surgeons performing LCBDE.

Keywords: bile leak, fibrin glue, LCBDE, serous leak

Procedia PDF Downloads 192

Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

Abstract:

Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

Procedia PDF Downloads 49