Search results for: pattern recognition approach

Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.

Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma

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Authors: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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Authors: M. Radunovic

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Region of Southeastern Europe has a substantial energy resource potential and is witnessing an increasing rate of power and energy project investments. This comes as a result of countries harmonizing their legal framework and market regulations to conform the ones of European Union, enabling direct private investments. Funding in the power and energy market in this region originates from various resources and investment entities, including commercial and institutional ones. Risk anticipation and assessment is crucial to project success, especially given the long exploitation period of project in power and energy domain, as well as the wide range of stakeholders involved. This paper analyzes the possibility of combined application of tools used in total quality management and international financing institutions for project planning, execution and evaluation, with the goal of anticipating, assessing and minimizing the risks that might occur in the development and execution phase of a power and energy project in the market of southeastern Europe. History of successful project management and investments both in the industry and institutional sector provides sufficient experience, guidance and internationally adopted tools to provide proper project assessment for investments in power and energy. Business environment of southeastern Europe provides immense potential for developing power and engineering projects of various magnitudes, depending on stakeholders’ interest. Diversification on investment sources provides assurance that there is interest and commitment to invest in this market. Global economic and political developments will be intensifying the pace of investments in the upcoming period. The proposed approach accounts for key parameters that contribute to the sustainability and profitability of a project which include technological, educational, social and economic gaps between the southeastern European region and western Europe, market trends in equipment design and production on a global level, environment friendly approach to renewable energy sources as well as conventional power generation systems, and finally the effect of the One Belt One Road Initiative led by People’s Republic of China to the power and energy market of this region in the upcoming period on a long term scale. Analysis will outline the key benefits of the approach as well as the accompanying constraints. Parallel to this it will provide an overview of dominant threats and opportunities in present and future business environment and their influence to the proposed application. Through concrete examples, full potential of this approach will be presented along with necessary improvements that need to be implemented. Number of power and engineering projects being developed in southeastern Europe will be increasing in the upcoming period. Proper risk analysis will lead to minimizing project failures. The proposed successful combination of reliable project planning tools from different investment areas can prove to be beneficial in the future power and engineering investments, and guarantee their sustainability and profitability.

Keywords: capital investments, lean six sigma, logical framework approach, logical framework matrix, one belt one road initiative, project management tools, quality function deployment, Southeastern Europe, total quality management

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Authors: A. Alli-Oluwafuyi, A. Amin, S. M. Fii, S. O. Amusa, A. Imam, N. T. Asogwa, W. I. Abdulmajeed, F. Olaseinde, B. V. Owoyele

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Chronic stress or prolonged glucocorticoid administration impairs higher cognitive functions in rodents and humans. However, the mechanisms are not fully clear. Insulin and receptors are expressed in the brain and are involved in cognition. Insulin resistance accompanies Alzheimer’s disease and associated cognitive decline. The goal of this study was to evaluate the effects of sub-chronic administration of a glucocorticoid, dexamethasone (DEX) on behavior and biochemical changes in prefrontal cortex (PFC). Male Wistar rats were administered DEX (2, 4 & 8 mg/kg, IP) or saline for seven consecutive days and behavior was assessed in the following paradigms: “Y” maze, elevated plus maze, Morris’ water maze and novel object recognition (NOR) tests. Insulin, lactate dehydrogenase (LDH) and Superoxide Dismutase (SOD) activity were evaluated in homogenates of the prefrontal cortex. DEX-treated rats exhibited impaired prefrontal cortex function manifesting as reduced locomotion, impaired novel object exploration and impaired short- and long-term spatial memory compared to normal controls (p < 0.05). These effects were not consistently dose-dependent. These behavioral alterations were accompanied by a decrease in insulin concentration observed in PFC of 4 mg/kg DEX-treated rats compared to control (10μIU/mg vs. 50μIU/mg; p < 0.05) but not 2mg/kg. Furthermore, we report a modification of brain stress markers LDH and SOD (p > 0.05). These results indicate that prolonged activation of GCs disrupt prefrontal cortex function which may be related to insulin impairment. These effects may not be attributable to a non-specific elevation of oxidative stress in the brain. Future studies would evaluate mechanisms of GR-induced insulin loss.

Keywords: dexamethasone, insulin, memory, prefrontal cortex

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Authors: Suchismita Dattagupta

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Social rules and guidelines specify how a body should be clothed and how it should look. The social rules have made the body a space for expression, oppression and sexual 'commodification'. Being a malleable aspect of the human body, hair has always been worn in a number of ways and this characteristic of hair has made it an essential vehicle for conveying symbolic meaning. Hair, particularly women’s hair has always been considered to be associated with richness and beauty, apart from being associated with sexual power. Society has always had a preoccupation with hair bordering on obsession and has projected its moral and political supremacy by controlling and influencing how an individual wears their hair. Irrespective of the gender of the individual, society has tried to control an individual’s hair to express its control. However, with time, there has been a marked change in the way hair has been used by the individual. Hair has always been the focus of scholarly studies; not just aesthetically, but also in the cultural and social context. The fascination with hair rises from the fact that it is the only part of the human body that is always on display. Fetishization of hair is common in literature and goes ahead to reveal the character’s social and moral status. Modern authors for children and young adults have turned this concept on its head to point out how characters are breaking away from the mould and establishing their personal, moral and social boundaries. This paper will trace the change in hair symbolism in literature for children and young adults to understand how it has changed over the course of the time and what light it throws on the changing pattern of women’s position in society.

Keywords: gender, hair, social symbols, society, women's role

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Authors: Haifeng Wang, Haili Zhang

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Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

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Authors: Tesfaw Belayneh Abebe

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Integrating low-altitude earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs) within a non-terrestrial network (NTN) with the assistance of reconfigurable intelligent surfaces (RIS), we investigate the problem of how to enhance throughput through integrated LEO satellites and UAVs with the assistance of RIS. We propose a method to jointly optimize the associations with the LEO satellite, the 3D trajectory of the UAV, and the phase shifts of the RIS to maximize communication throughput for RIS-assisted integrated LEO satellite and UAV-enabled wireless communications, which is challenging due to the time-varying changes in the position of the LEO satellite, the high mobility of UAVs, an enormous number of possible control actions, and also the large number of RIS elements. Utilizing a multi-agent double deep Q-network (MADDQN), our approach dynamically adjusts LEO satellite association, UAV positioning, and RIS phase shifts. Simulation results demonstrate that our method significantly outperforms baseline strategies in maximizing throughput. Lastly, thanks to the integrated network and the RIS, the proposed scheme achieves up to 65.66x higher peak throughput and 25.09x higher worst-case throughput.

Keywords: integrating low-altitude earth orbit (LEO) satellites, unmanned aerial vehicles (UAVs) within a non-terrestrial network (NTN), reconfigurable intelligent surfaces (RIS), multi-agent double deep Q-network (MADDQN)

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Authors: Mostafa Mjahed

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Tilt Rotor UAVs (Unmanned Aerial Vehicles) are naturally unstable and difficult to maneuver. The purpose of this paper is to design controllers for the stabilization and trajectory tracking of this type of UAV. To this end, artificial intelligence methods have been exploited. First, the dynamics of this UAV was modeled using the Lagrange-Euler method. The conventional method based on Proportional, Integral and Derivative (PID) control was applied by decoupling the different flight modes. To improve stability and trajectory tracking of the Tilt Rotor, the fuzzy approach and the technique of multilayer neural networks (NN) has been used. Thus, Fuzzy Proportional Integral and Derivative (FPID) and Neural Network-based Proportional Integral and Derivative controllers (NNPID) have been developed. The meta-heuristic approach based on Particle Swarm Optimization (PSO) method allowed adjusting the setting parameters of NNPID controller, giving us an improved NNPID-PSO controller. Simulation results under the Matlab environment show the efficiency of the approaches adopted. Besides, the Tilt Rotor UAV has become stable and follows different types of trajectories with acceptable precision. The Fuzzy, NN and NN-PSO-based approaches demonstrated their robustness because the presence of the disturbances did not alter the stability or the trajectory tracking of the Tilt Rotor UAV.

Keywords: neural network, fuzzy logic, PSO, PID, trajectory tracking, tilt-rotor UAV

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Authors: Jalil Qoulizadeh, Hasan Sadeghi

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Brain waves are electrical wave patterns that are produced in the human brain. Knowing these waves and activating them can have a positive effect on brain function and ultimately create an ideal life. The brain has the ability to produce waves from 0.1 to above 65 Hz. (The Beta One device produces exactly these waves) This is because it is said that the waves produced by the Beta One device exactly match the waves produced by the brain. The function and method of this device is based on the magnetic stimulation of the brain. The technology used in the design and producƟon of this device works in a way to strengthen and improve the frequencies of brain waves with a pre-defined algorithm according to the type of requested function, so that the person can access the expected functions in life activities. to perform better. The effect of this field on neurons and their stimulation: In order to evaluate the effect of this field created by the device, on the neurons, the main tests are by conducting electroencephalography before and after stimulation and comparing these two baselines by qEEG or quantitative electroencephalography method using paired t-test in 39 subjects. It confirms the significant effect of this field on the change of electrical activity recorded after 30 minutes of stimulation in all subjects. The Beta One device is able to induce the appropriate pattern of the expected functions in a soft and effective way to the brain in a healthy and effective way (exactly in accordance with the harmony of brain waves), the process of brain activities first to a normal state and then to a powerful one. Production of inexpensive neuroscience equipment (compared to existing rTMS equipment) Magnetic brain stimulation for clinics - homes - factories and companies - professional sports clubs.

Keywords: stimulation, brain, waves, betaOne

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Authors: Ma Chaoyang

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This article starts from the perspective of environmental justice theory and analyzes the accessibility and regional equity of park green spaces in the central urban area of Chengdu in 2022 based on the improved Gaussian 2SFCA analysis method and Gini coefficient method. Then, according to the relevant analysis model, it further explores the correlation between the spatial distribution of park green spaces and the socio-economic conditions of residents in order to provide a reference for the construction and research of Chengdu's park city under the guidance of fairness and justice. The results show that: (1) Overall, the spatial distribution of parks and green spaces in Chengdu shows a significantly uneven distribution of extreme core edge, with a certain degree of unfairness; that is, there is an environmental injustice pattern. (2) The spatial layout of urban parks and green spaces is subject to strong guiding interference from the socio-economic level; that is, there is a high correlation between housing prices and the tendency of parks. (3) Green space resources Gini coefficient analysis shows that residents of the three modes of transportation in the study area have unequal opportunities to enjoy park and green space services, and the degree of unfairness in walking is much greater than that in cycling and cycling.

Keywords: parks and green spaces, environmental justice, two step mobile search method, Gini coefficient, spatial distribution

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Authors: Julian Mehler, Marcus Fischer, Martin Hartmann, Peter S. Schulz

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During the last two decades, the synthesis of metal-organic frameworks (MOFs) has gained ever increasing attention. Based on their pore size and shape as well as host-guest interactions, they are of interest for numerous fields related to porous materials, like catalysis and gas separation. Usually, MOF-synthesis takes place in an organic solvent between room temperature and approximately 220 °C, with mixtures of polyfunctional organic linker molecules and metal precursors as substrates. Reaction temperatures above the boiling point of the solvent, i.e. solvothermal reactions, are run in autoclaves or sealed glass vessels under autogenous pressures. A relatively new approach for the synthesis of MOFs is the so-called ionothermal synthesis route. It applies an ionic liquid as a solvent, which can serve as a structure-directing template and/or a charge-compensating agent in the final coordination polymer structure. Furthermore, this method often allows for less harsh reaction conditions than the solvothermal route. Here a variation of the ionothermal approach is reported, where the ionic liquid also serves as an organic linker source. By using 1-ethyl-3-methylimidazolium terephthalates ([EMIM][Hbdc] and [EMIM]₂[bdc]), the one-step synthesis of MIL-53(Al)/Boehemite composites with interesting features is possible. The resulting material is already formed at moderate temperatures (90-130 °C) and is stabilized in the usually unfavored ht-phase. Additionally, in contrast to already published procedures for MIL-53(Al) synthesis, no further activation at high temperatures is mandatory. A full characterization of this novel composite material is provided, including XRD, SS-NMR, El-Al., SEM as well as sorption measurements and its interesting features are compared to MIL-53(Al) samples produced by the classical solvothermal route. Furthermore, the syntheses of the applied ionic liquids and salts is discussed. The influence of the degree of ionicity of the linker source [EMIM]x[H(2-x)bdc] on the crystal structure and the achievable synthesis temperature are investigated and give insight into the role of the IL during synthesis. Aside from the synthesis of MIL-53 from EMIM terephthalates, the use of the phosphonium cation in this approach is discussed as well. Additionally, the employment of ILs in the preparation of other MOFs is presented briefly. This includes the ZIF-4 framework from the respective imidazolate ILs and chiral camphorate based frameworks from their imidazolium precursors.

Keywords: ionic liquids, ionothermal synthesis, material synthesis, MIL-53, MOFs

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Authors: P. G. Siddheshwar, R. K. Vanishree, C. Kanchana

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A local nonlinear stability analysis using a eight-mode expansion is performed in arriving at the coupled amplitude equations for Rayleigh-Bénard-Brinkman convection (RBBC) in the presence of LTNE effects. Streamlines and isotherms are obtained in the two-dimensional unsteady finite-amplitude convection regime. The parameters’ influence on heat transport is found to be more pronounced at small time than at long times. Results of the Rayleigh-Bénard convection is obtained as a particular case of the present study. Additional modes are shown not to significantly influence the heat transport thus leading us to infer that five minimal modes are sufficient to make a study of RBBC. The present problem that uses rolls as a pattern of manifestation of instability is a needed first step in the direction of making a very general non-local study of two-dimensional unsteady convection. The results may be useful in determining the preferred range of parameters’ values while making rheometric measurements in fluids to ascertain fluid properties such as viscosity. The results of LTE are obtained as a limiting case of the results of LTNE obtained in the paper.

Keywords: coupled Ginzburg–Landau model, local thermal non-equilibrium (LTNE), local thermal equilibrium (LTE), Rayleigh–Bénard-Brinkman convection

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Authors: Ki-Yeo Kim

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Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined genomic expression achieved better performance in the discrimination of different conditions than in a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

Keywords: oral squamous cell carcinoma, combined biomarker, microarray dataset, correlated genes

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Authors: Chaiwat Tantarangsee

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The purposes of this study are 1) to study the frequent English writing errors of students registering the course: Reading and Writing English for Academic Purposes II, and 2) to find out the results of writing error correction by using coded indirect corrective feedback and writing error treatments. Samples include 28 2nd year English Major students, Faculty of Education, Suan Sunandha Rajabhat University. Tool for experimental study includes the lesson plan of the course; Reading and Writing English for Academic Purposes II, and tool for data collection includes 4 writing tests of short texts. The research findings disclose that frequent English writing errors found in this course comprise 7 types of grammatical errors, namely Fragment sentence, Subject-verb agreement, Wrong form of verb tense, Singular or plural noun endings, Run-ons sentence, Wrong form of verb pattern and Lack of parallel structure. Moreover, it is found that the results of writing error correction by using coded indirect corrective feedback and error treatment reveal the overall reduction of the frequent English writing errors and the increase of students’ achievement in the writing of short texts with the significance at .05.

Keywords: coded indirect corrective feedback, error correction, error treatment, English writing

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Authors: Hanen Khaldi

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This paper aims to study the impact of international migration on human security in the Southeastern region of Asia, especially after Asian Financial Crisis 1997-98. International migration has impacts on many dimensions of security: the state security (sovereignty and autonomy); international relationships security (conflicts, terrorism, etc); and immigrants security. The paper aims to improve our comprehension of the impact of international migration on immigrant security in the region of Southeast Asia, particularly “vulnerable workers’’ whose number is growing very fast in the region. The literature review carried out on this matter led us to ask the following two question: 1) Did the creation of ASEAN Community matter on the evolution of immigrants in the region? And How governments try to resolve the gap between economic objectifs and security of immigrants in the region? To answer these two questions, the paper is subdivided in three parts: Firstly, we will show how the creation of the ASEAN Community, especially ASEAN Economic Community, had a significant impact on the pattern of evolution of immigration in this region. Secondly, we will paint a portrait illustrating the vulnerability of immigrants in Southeast Asia, particularly unskilled workers. Finally, using the theories of regional integration, we will assess how governments try to ensure the security and safety of the immigrants. Overall, our analysis illustrate the significant change of the official discourse of the leaders of the ASEAN member states, now more conciliator and especially more open to cooperation, as well as the proliferation of meetings and initiatives between these countries to control mobility flows in the region, and the ensure immigrants security.

Keywords: migrant workers, human security, human rights

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Authors: Mariya Salihu Ingawa, Sani Suleiman Isah

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The assessment of Integrated Information System (IIS) in organisation is an important initiative to enable the Information System (IS) managers, as well as top management to understand the success status of their investment in IS integration efforts. However, without a proper assessment, an organisation will not know its IIS status, which may affect their judgment on what action should be taken onwards. Current research on IIS assessment is lacking and those related literature on IIS assessment focus more on assessing the technical aspect of IIS. It is argued that assessing technical aspect alone is inadequate since organisational and strategic aspects in IIS should also be considered. Current methods, techniques and tools used by vendors for IIS assessment also are lack of comprehensive measures to fully assess the Integrated Information System in term of technical, organisational and strategic domains. The purpose of this study is to establish critical success factors for measuring success of an Integrated Information System. These factors are used as the basis for constructing an approach to comprehensively assess IIS in an organisation. A comprehensive list of success factors for IIS assessment, established from literature, was initially presented. An expert surveys using both manual and online methods were conducted to verify the factors. Based on the factors, an instrument for IIS assessment was constructed. The results from a case study indicate that through comprehensive assessment approach, not only the level of success been known, but also reveals the contributing factors. This research contributes to the field of Information Systems specifically in the area of Integrated Information System assessment.

Keywords: integrated information system, expert surveys, organisation, assessment

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Authors: Ken Hampshire, Thomas Mazzuchi, Shahram Sarkani

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As a subset of metaheuristics, nature-inspired optimization algorithms such as particle swarm optimization (PSO) have shown promise both in solving intractable problems and in their extensibility to novel problem formulations due to their general approach requiring few assumptions. Unfortunately, single instantiations of algorithms require detailed tuning of parameters and cannot be proven to be best suited to a particular illustrative problem on account of the “no free lunch” (NFL) theorem. Using these algorithms in real-world problems requires exquisite knowledge of the many techniques and is not conducive to reconciling the various approaches to given classes of problems. This research aims to present a unified view of PSO-based approaches from the perspective of relevant systems engineering problems, with the express purpose of then eliciting the best solution for any problem formulation in an ensemble learning bucket of models approach. The central hypothesis of the research is that extending the PSO algorithms found in the literature to real-world optimization problems requires a general ensemble-based method for all problem formulations but a specific implementation and solution for any instance. The main results are a problem-based literature survey and a general method to find more globally optimal solutions for any systems engineering optimization problem.

Keywords: particle swarm optimization, nature-inspired optimization, metaheuristics, systems engineering, ensemble learning

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Authors: Thaiurie Govender, Shannon Verne

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The Fourth Industrial Revolution has ushered in an era where technology significantly impacts various aspects of life, including higher education. Blended learning, which combines synchronous and asynchronous learning, has gained popularity as a pedagogical approach. However, its effective implementation is a challenge, particularly in the context of the COVID-19 pandemic and technological obstacles faced in South Africa. This study focused on lecturers' teaching and learning practices to implement blended learning, aiming to understand the teaching and learning strategies used with the integration of digital tools to facilitate the blended learning approach within a private higher educational institution in South Africa. Using heutagogy and constructivism theoretical frameworks, the study aimed to uncover insights into the lecturer’s teaching and learning practices to overcome challenges in designing and facilitating blended learning modules. Through a qualitative analysis, the themes of student engagement, teaching and learning strategies, digital tools, and feedback emerged, highlighting the complexities and opportunities in a blended learning classroom. The findings emphasize the importance of tailoring methods to students' needs and subject matter, aligning with constructivist principles. Recommendations include promoting professional development opportunities, addressing infrastructure issues, and fostering a supportive learning environment.

Keywords: blended learning, digital tools, higher education, teaching strategies

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Authors: Samuel Quashie

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PhDs in Construction Management often designs their methods based on those established in social sciences using theoretical models, to collect, gather and analysis data to answer research questions. Work aim is to apply qualitative and quantitative as a data analysis method, and as part of the theoretical framework - descriptive theory. To improve the ability to replicate the contribution to knowledge the research. Using practical triangulation approach, which covers, interviews and observations, literature review and (archival) document studies, project-based case studies, questionnaires surveys and review of integrated systems used in, construction and construction related industries. The clarification of organisational context and management delivery that influences organizational performance and quality of product and measures are achieved. Results illustrate improved reliability in this research approach when interpreting real world phenomena; cumulative results of research can be applied with confidence under similar environments. Assisted validity of the PhD research outcomes and strengthens the confidence to apply cumulative results of research under similar conditions in the Built Environment research systems, which have been criticised for the lack of reliability in approaches when interpreting real world phenomena.

Keywords: case studies, descriptive theory, theoretical framework, qualitative and quantitative research

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: cyber security, intrusion prevention, optimal policy, Q-learning

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Authors: Shreya Saxena, Felix Miller-Molloy, Phillipa Bowen, Greg Fellows, Elizabeth Bowen

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Background: Complex fluid balance abnormalities are well-established post-neurosurgery and traumatic brain injury (TBI). The triple-phase response requires fluid management strategies reactive to urine output and sodium homeostasis as patients shift between Diabetes Insipidus (DI) and Syndrome of Inappropriate ADH (SIADH). It was observed, at a tertiary paediatric center, a relatively high prevalence of the above complications within a cohort of paediatric post-neurosurgical and TBI patients. An audit of the clinical practice against set institutional guidelines was undertaken and analyzed to understand why this was occurring. Based on those results, new guidelines were developed with structured educational packages for the specialist teams involved. This was then reaudited, and the findings were compared. Methods: Two independent audits were conducted across two time periods, pre and post guideline change. Primary data was collected retrospectively, including both qualitative and quantitative data sets from the CQUIN neurosurgical database and electronic medical records. All paediatric patients post posterior fossa (PFT) or supratentorial surgery or with a TBI were included. A literature review of evidence-based practice, initial audit data, and stakeholder feedback was used to develop new clinical guidelines and nursing standard operation procedures. Compliance against these newly developed guidelines was re-assessed and a thematic, trend-based analysis of the two sets of results was conducted. Results: Audit-1 January2017-June2018, n=80; Audit-2 January2020-June2021, n=30 (reduced operative capacity due to COVID-19 pandemic). Overall, improvements in the monitoring of both fluid balance and electrolyte trends were demonstrated; 51% vs. 77% and 78% vs. 94%, respectively. The number of clear fluid management plans documented postoperatively also increased (odds ratio of 4), leading to earlier recognition and management of evolving fluid-balance abnormalities. The local paediatric endocrine team was involved in the care of all complex cases and notified sooner for those considered to be developing DI or SIADH (14% to 35%). However, significant Na fluctuations (>12mmol in 24 hours) remained similar – 5 vs six patients – found to be due to complex pituitary hypothalamic pathology – and the recommended adaptive fluid management strategy was still not always used. Qualitative data regarding useability and understanding of fluid-balance abnormalities and the revised guidelines were obtained from health professionals via surveys and discussion in the specialist teams providing care. The feedback highlighted the new guidelines provided a more consistent approach to the post-operative care of these patients and was a better platform for communication amongst the different specialist teams involved. The potential limitation to our study would be the small sample size on which to conduct formal analyses; however, this reflects the population that we were investigating, which we cannot control. Conclusion: The revised clinical guidelines, based on audited data, evidence-based literature review and stakeholder consultations, have demonstrated an improvement in understanding of the neuro-endocrine complications that are possible, as well as increased compliance to post-operative monitoring of fluid balance and electrolytes in this cohort of patients. Emphasis has been placed on preventative rather than treatment of DI and SIADH. Consequently, this has positively impacted patient safety for the center and highlighted the importance of educational awareness and multi-disciplinary team working.

Keywords: post-operative, fluid-balance management, neuro-endocrine complications, paediatric

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Authors: Zia Ullah, Muhammad Asim, Shi Sujuan, Rayyan Khan, Aaqib Shaheen, LIU Haobao

Abstract:

The plant-specific auxin efflux proteins PIN-FORMED (PIN) have been well depicted in many plant species for their essential roles in regulating the transport of auxins in several phases of plant growth. Little is known about the various functions of the PIN family genes in the Nicotiana tabacum (N. tabacum) species during plant growth. To define the expression pattern of the NtPIN1a gene under abiotic stresses and hormone treatment, transgenic tobacco with promoterNtPIN1a::GUS construct was employed. Comprehensive computational analyses of the NtPIN1a promoter confirmed the existence of common core promoter elements including CAAT-box, TATA-box, hormone, and abiotic stress-responsive elements such as ABRE, P-box, MYC, MYB, ARE, and GC-motifs. The transgenic plants with the promoter of NtPIN1a displayed a promising expression of β-glucuronidase (GUS) in germinating seeds, root tips, shoot-apex, and developing leaves under optimal conditions. While the differential expression of GUS in moderate salt, drought, low potassium stresses, and externally high auxin level at two different time points, suggested NtPIN1a played a key role in growth processes and the plants’ response to abiotic stresses. This analysis provides a foundation for more in-depth discoveries of the biological functions of NtPIN1a in Nicotiana species and this promoter may be employed in genetic engineering of other crops for enhanced stress tolerance.

Keywords: tobacco, nicotiana tabacum, pin, promoter, GUS, abiotic stresses, auxin

Procedia PDF Downloads 102

Authors: S. P. Chintan, A. M. Khoja, M. Modi, R. K. Chopra, S. Garde, D. Jain, O. Kajale

Abstract:

Pulmonary Hypertension is a rare but debilitating disease that affects individuals of all ages and walks of life. As recent as 15 years ago, a patient diagnosed with PH was given an average survival rate of 2.8 years. Recent advances in treatment options have allowed patients to improve quality o and quantity of life. Initial screening for PH is through echocardiography with final diagnosis confirmed through right heart catheterization. PH is now considered to have five major classifications with subgroups among each. The mild to moderate PH is common in chronic lung diseases like Chronic obstructive pulmonary diseases and Interstitial lung disease. But very severe PH is noted in few cases. In COPD patients, PH is associated with an increased risk of severe exacerbations and a reduced life expectancy. Similarly, in patients with ILD, the presence of PH correlates with a poor prognosis. Early diagnosis is essential to slow disease progression. We report here five cases of severe PH (Out of Proportion) of which four cases were of COPD and another one of IPF (UIP pattern). There echocardiography showed gross RA/RV dilatation, interventricular septum bulging to the left and mPAP of more than 100 mmHg in all the five cases. These patients were put on LTOT, pulmonary rehabilitation, combination pharmacotherapy of vasodilators and diuretics in continuation to the treatment of underlying disease. As these patients have grave prognosis close monitoring and follow up is required. Physicians associated with respiratory care and treating chronic lung disease should have knowledge in the diagnosis and management of patients with PH.

Keywords: COPD, pulmonary hypertension, chronic lung disease, India

Procedia PDF Downloads 361

Authors: Ghada A. Gamea, Nabila A. Yaseen, Ahmed A. Othman, Ahmed S. Tawfik

Abstract:

Infection with Toxoplasma gondii can cause serious complications in pregnant women, leading to abortion, stillbirth, and congenital anomalies in the fetus. Definitive diagnosis of T. gondii acute infection is therefore critical for the clinical management of a mother and her fetus. This study was conducted on 250 pregnant females in the first trimester who were inpatients or outpatients at Obstetrics and Gynaecology Department at Tanta University Hospital. Screening of the selected females was done for the detection of immunoglobulin (IgG and IgM), and all subjects were submitted to history taking through a questionnaire including personal data, risk factors for Toxoplasma, complaint and history of the present illness. Thirty-eight samples, including 18 IgM +ve and 20 IgM-ve cases were further investigated by the avidity and IgE ELISA tests. The seroprevalence of toxoplasmosis in pregnant women was (42.8%) based on the presence of IgG antibodies in their sera. Contact with cats and consumption of raw or undercooked meat are important risk factors that were associated with toxoplasmosis in pregnant women. By serology, it could be observed that in the IgM +ve group, only one case (5.6%) showed an acute pattern by using the avidity test, though 10 (55.6%) cases were found to be acute by the IgE assay. On the other hand, in the IgM –ve group, 3 (15%) showed low avidity, but none of them was positive by using the IgE assay. In conclusion, there is no single serological test that can be used to confirm whether T. gondii infection is recent or was acquired in the distant past. A panel of tests for detection of toxoplasmosis will certainly have higher discriminatory power than any test alone.

Keywords: diagnosis, serology, seroprevalence, toxoplasmosis

Procedia PDF Downloads 157

Authors: Ogunwole Cecilia Oluwakemi, Timothy Ayomitunde Aderemi

Abstract:

Provision of sufficient food and elimination of abject poverty have usually been the conventional benefits of agriculture in any society. Meanwhile, despite the fact that Nigeria is an agrarian society, food insecurity and poverty have become the issues of concern among both scholars and policymakers in the recent times. Against this backdrop, this study examined the nexus among agriculture, food security, and poverty reduction in Nigeria from 1990 to 2019 within the framework of the Cointegration and Granger Causality approach. Data was collected from the Central Bank of Nigeria Statistical Bulletin and the World Development Indicators, respectively. The following are the major results that emanated from the study. A long run equilibrium relationship exists among agricultural value added, food production index, and GDP per capita in Nigeria. Similarly, there is a unidirectional causality which flows from food production index to poverty reduction in Nigeria. In the same vein, one way causality flows from poverty reduction to agricultural value added in Nigeria. Consequently, this study makes the following recommendation for the policymakers in Nigeria, and other African countries by extension, that agricultural value added and food production are the important variables that cannot be undermined when poverty reduction occupies the central focus of the policymakers. Therefore, any time these policymakers want to reduce poverty, policies that drive agricultural value added and food production should be embarked upon. Therefore, this study will contribute to the literature by establishing the type of linkage that exists between agriculture, food security, and poverty reduction in Nigeria.

Keywords: agriculture, value added, food production, GDP per capita, Nigeria

Procedia PDF Downloads 204

Authors: Shirl H. Terrell

Abstract:

In the telling of mythologies, stories of cultural and religious histories, the creative arts provide an archetypal lens through which the personal and collective unconscious are viewed, thus revealing mysteries of the unknown psyche. To that end, the author of this paper, using the hermeneutic approach, proves that Carlisle Floyd’s (1955) English language opera Susannah illuminates humanity’s instinctual nature and behaviors through music, libretto, and drama. While impressive musical works such as Wagner’s Ring Cycle and Webber’s Phantom of the Opera have received extensive Jungian analyses, critics and scholars often ignore lesser esteemed works, such as Susannah, notwithstanding the fact that they have been consistently performed on the theater circuit. Such pieces, when given notice, allow viewers to grasp the soul-making depth and timeless quality of productions which may otherwise go unrecognized as culturally or psychologically significant. Although Susannah has sometimes been described as unsophisticated and simple in scope, the author demonstrates why Floyd’s 'little' opera, set in New Hope Valley, Appalachia, a cultural region in the Eastern United States known for its prevailing myths and distortions of isolation, temperament, and the judgmentally conservative behavior of its inhabitants, belongs to opera’s hallmark works. Its approach to powerful underlying archetypal themes, which give rise to the poignant and haunting depictions of the darker and destructive side of the human soul, the Shadow, provides crucial significance to the work. The Shadow’s manifestation in the form of the scapegoating complex is central to the plot of Susannah; the church’s meting out of rules, judgment, and reparation for sins point to the foreboding aspects of human behavior that evoke their intrinsic nature. The scapegoating complex is highlighted in an eight-step process gleaned from the works of Kenneth Burke and Rene Girard. In summary, through depth psychological terms and mythological motifs, the author provides an insightful approach to perceiving instinctual behaviors as they play out in an American opera that has been staged over eight-hundred times, yet, unfortunately, remains in the shadows. Susannah’s timelessness is now.

Keywords: archetypes, mythology, opera, scapegoating, Shadow, Susannah

Procedia PDF Downloads 153

Authors: Desplanches Maxime

Abstract:

Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

Procedia PDF Downloads 74

Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

Abstract:

Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

Procedia PDF Downloads 121

Authors: Muhammad Alif Bin Razali, Cheng-Gang Xie, Wai Lam Loh

Abstract:

A venturi device is commonly used as an integral part of a multiphase flowmeter (MPFM) in real-time oil-gas production monitoring. For an accurate determination of individual phase fraction and flowrate, a gas-liquid flow ideally needs to be well mixed in the venturi measurement section. Partial flow mixing is achieved by installing a venturi vertically downstream of the blind-tee pipework that ‘homogenizes’ the incoming horizontal gas-liquid flow. In order to study in-depth the flow-mixing effect of the blind-tee, gas-liquid flows are captured at blind-tee and venturi sections by using a high-speed video camera and a purpose-built transparent test rig, over a wide range of superficial liquid velocities (0.3 to 2.4m/s) and gas volume fractions (10 to 95%). Electrical capacitance sensors are built to measure the instantaneous holdup (of oil-gas flows) at the venturi inlet and throat. Flow regimes and flow (a)symmetry are investigated based on analyzing the statistical features of capacitance sensors’ holdup time-series data and of the high-speed video time-stacked images. The perceived homogenization effect of the blind-tee on the incoming intermittent horizontal flow regimes is found to be relatively small across the tested flow conditions. A horizontal (blind-tee) to vertical (venturi) flow-pattern transition map is proposed based on gas and liquid mass fluxes (weighted by the Baker parameters).

Keywords: blind-tee, flow visualization, gas-liquid two-phase flow, MPFM

Procedia PDF Downloads 132

Authors: William J. Crowther, Conor Marsh

Abstract:

Object-based flow simulation allows fast computation of arbitrarily complex aerodynamic models made up of simple objects with limited flow interactions. The proposed approach is universally applicable to objects made from arbitrarily scaled ellipsoid primitives at arbitrary aerodynamic attitude and angular rate. The use of a component-based aerodynamic modelling approach increases efficiency by allowing selective inclusion of different physics models at run-time and allows extensibility through the development of new models. Insight into the numerical stability of the model under first order fixed-time step integration schemes is provided by stability analysis of the drag component. The compute cost of model components and functions is evaluated and compared against numerical benchmarks. Model static outputs are verified against theoretical expectations and dynamic behaviour using falling plate data from the literature. The model is applied to a range of case studies to demonstrate the efficacy of its application in extensibility, ease of use, and low computational cost. Dynamically complex multi-body systems can be implemented in a transparent and efficient manner, and we successfully demonstrate large scenes with hundreds of objects interacting with diverse flow fields.

Keywords: aerodynamics, real-time simulation, low-order model, flight dynamics

Procedia PDF Downloads 109