Search results for: edge application framework

Authors: Anil Kumar, Rajnish Kaur, Mateusz Czyzycki, Alessandro Migilori, Andreas Germanos Karydas, Sanjiv Puri

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The radiative decay of Li(i=1-3) sub-shell vacancies produced through photoionization results in production of the characteristic emission spectrum comprising several X-ray lines, whereas non-radiative vacancy decay results in Auger electron spectrum. Accurate reliable data on the Li(i=1-3) sub-shell X-ray production (XRP) cross sections is of considerable importance for investigation of atomic inner-shell ionization processes as well as for quantitative elemental analysis of different types of samples employing the energy dispersive X-ray fluorescence (EDXRF) analysis technique. At incident photon energies in vicinity of the absorption edge energies of an element, the many body effects including the electron correlation, core relaxation, inter-channel coupling and post-collision interactions become significant in the photoionization of atomic inner-shells. Further, in case of compounds, the characteristic emission spectrum of the specific element is expected to get influenced by the chemical environment (coordination number, oxidation state, nature of ligand/functional groups attached to central atom, etc.). These chemical effects on L X-ray fluorescence parameters have been investigated by performing the measurements at incident photon energies much higher than the Li(i=1-3) sub-shell absorption edge energies using EDXRF spectrometers. In the present work, the cross sections for production of the Lk(k= γ2,3, γ4) X-rays have been measured for some compounds of 66Dy, namely, Dy2O3, Dy2(CO3)3, Dy2(SO4)3.8H2O, DyI2 and Dy metal by tuning the incident photon energies few eV above the L1 absorption-edge energy in order to investigate the influence of chemical effects on these cross sections in presence of the many body effects which become significant at photon energies close to the absorption-edge energies. The present measurements have been performed under vacuum at the IAEA end-station of the X-ray fluorescence beam line (10.1L) of ELETTRA synchrotron radiation facility (Trieste, Italy) using self-supporting pressed pellet targets (1.3 cm diameter, nominal thicknesses ~ 176 mg/cm2) of 66Dy compounds (procured from Sigma Aldrich) and a metallic foil of 66Dy (nominal thickness ~ 3.9 mg/cm2, procured from Good Fellow, UK). The present measured cross sections have been compared with theoretical values calculated using the Dirac-Hartree-Slater(DHS) model based fluorescence and Coster-Kronig yields, Dirac-Fock(DF) model based X-ray emission rates and two sets of L1 sub-shell photoionization cross sections based on the non-relativistic Hartree-Fock-Slater(HFS) model and those deduced from the self-consistent Dirac-Hartree-Fock(DHF) model based total photoionization cross sections. The present measured XRP cross sections for 66Dy as well as for its compounds for the L2,3 and L4 X-rays, are found to be higher by ~14-36% than the two calculated set values. It is worth to be mentioned that L2,3 and L4 X-ray lines are originated by filling up of the L1 sub-shell vacancies by the outer sub-shell (N2,3 and O2,3) electrons which are much more sensitive to the chemical environment around the central atom. The present observed differences between measured and theoretical values are expected due to combined influence of the many-body effects and the chemical effects.

Keywords: chemical effects, L X-ray production cross sections, Many body effects, Synchrotron radiation

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Authors: Enze Zhang

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One of the most challenging steps in implementing virtual water content (VWC) analysis of crops is to get properly the total volume of consumptive water use (CWU) and, therefore, the choice of a reliable crop CWU estimation method. In practice, lots of previous researches obtaining CWU of crops follow a classical procedure for calculating crop evapotranspiration which is determined by multiplying reference evapotranspiration by appropriate coefficient, such as crop coefficient and water stress coefficients. However, this manner of calculation requires lots of field experimental data at point scale and more seriously, when current growing conditions differ from the standard conditions, may easily produce deviation between the calculated CWU and the actual CWU. Since evapotranspiration caused by crop planting always plays a vital role in surface water-energy balance in an agricultural region, this study decided to alternatively estimates crop evapotranspiration by Budyko framework. After brief introduce the development process of Budyko framework. We choose a modified Budyko framework under unsteady-state to better evaluated the actual CWU and apply it in an agricultural irrigation area in North China Plain which rely on underground water for irrigation. With the agricultural statistic data, this calculated CWU was further converted into VWC and its subdivision of crops at the annual scale. Results show that all the average values of VWC, VWC_blue and VWC_green show a downward trend with increased agricultural production and improved acreage. By comparison with the previous research, VWC calculated by Budyko framework agree well with part of the previous research and for some other research the value is greater. Our research also suggests that this methodology and findings may be reliable and convenient for investigation of virtual water throughout various agriculture regions of the world.

Keywords: virtual water content, Budyko framework, consumptive water use, crop evapotranspiration

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Authors: Robert L. Burdett, Bayan Bevrani

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Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways, these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

Keywords: capacity analysis, capacity expansion, railways, track sub division, track duplication

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Authors: O. O. Oguntoye

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Product consumption constitutes an important consideration for sustainable development. Seeing how product consumption could be highly unsustainable, coupled with how existing policies on corporate responsibility do not particularly address the consumption aspect of product lifecycle, conducting this research became necessary. The research makes an attempt to provide a framework by which to gauge corporate responsibility of product suppliers in terms of their commitment towards the sustainable consumption of their products. Through an exploration of relevant literature, independently established ideas with which to assess a given product supplier were galvanised into a four-criterion framework. The criteria are: (1) Embeddedness of consumption as a factor in corporate sustainability policy, (2) Level of understanding of consumption behaviour, (3) Breadth of behaviour-influencing strategies adopted, and (4) Inclusiveness for all main dimensions of sustainability. This resulting framework was then applied in a case study involving a UK-based furniture supplier where interviews and content analysis of corporate documents were used as the mode for primary data collection. From the case study, it was found that the supplier had performed to different levels across the four themes of the assessment. Two major areas for improvement were however identified – one is for the furniture supplier to focus more proactively on understanding consumption behaviour and, two is for it to widen the scope of its current strategies for enhancing sustainable consumption of supplied furniture. As a generalisation, the framework presented here makes it possible for companies to reflect with a sense of guidance, how they have demonstrated commitment towards sustainable consumption through their values, culture, and operations. It also provides a foundation for developing standardized assessment which the current widely used frameworks such as the GRI, the Global Compact, and others do not cover. While these popularly used frameworks mainly focus on sustainability of companies within the production and supply chain management contexts (i.e. mostly ‘upstream’), the framework here provides an extension by bringing the ‘downstream’ or consumer bit into light.

Keywords: corporate sustainability, design for sustainable consumption, extended producer responsibility, sustainable consumer behaviour

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Authors: Zahid Ullah, Atlas Khan

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The rapid advancements in data collection, storage, and processing capabilities have led to an explosion of data in various domains. In this era of big data, mathematical sciences play a crucial role in uncovering valuable insights and driving informed decision-making through data analytics. The purpose of this abstract is to present the latest advances in mathematical sciences and their application in harnessing the power of data analytics. This abstract highlights the interdisciplinary nature of data analytics, showcasing how mathematics intersects with statistics, computer science, and other related fields to develop cutting-edge methodologies. It explores key mathematical techniques such as optimization, mathematical modeling, network analysis, and computational algorithms that underpin effective data analysis and interpretation. The abstract emphasizes the role of mathematical sciences in addressing real-world challenges across different sectors, including finance, healthcare, engineering, social sciences, and beyond. It showcases how mathematical models and statistical methods extract meaningful insights from complex datasets, facilitating evidence-based decision-making and driving innovation. Furthermore, the abstract emphasizes the importance of collaboration and knowledge exchange among researchers, practitioners, and industry professionals. It recognizes the value of interdisciplinary collaborations and the need to bridge the gap between academia and industry to ensure the practical application of mathematical advancements in data analytics. The abstract highlights the significance of ongoing research in mathematical sciences and its impact on data analytics. It emphasizes the need for continued exploration and innovation in mathematical methodologies to tackle emerging challenges in the era of big data and digital transformation. In summary, this abstract sheds light on the advances in mathematical sciences and their pivotal role in unveiling the power of data analytics. It calls for interdisciplinary collaboration, knowledge exchange, and ongoing research to further unlock the potential of mathematical methodologies in addressing complex problems and driving data-driven decision-making in various domains.

Keywords: mathematical sciences, data analytics, advances, unveiling

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Authors: L. Ngowi, N. H. Mvungi

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This paper critically examines the evolution of socio-technical systems theory, its practices, and challenges in system design and development. It examines concepts put forward by researchers focusing on the application of the theory in software engineering. There are various methods developed that use socio-technical concepts based on systems engineering without remarkable success. The main constraint is the large amount of data and inefficient techniques used in the application of the concepts in system engineering for developing time-bound systems and within a limited/controlled budget. This paper critically examines each of the methods, highlight bottlenecks and suggest the way forward. Since socio-technical systems theory only explains what to do, but not how doing it, hence engineers are not using the concept to save time, costs and reduce risks associated with new frameworks. Hence, a new framework, which can be considered as a practical approach is proposed that borrows concepts from soft systems method, agile systems development and object-oriented analysis and design to bridge the gap between theory and practice. The approach will enable the development of systems using socio-technical systems theory to attract/enable the system engineers/software developers to use socio-technical systems theory in building worthwhile information systems to avoid fragilities and hostilities in the work environment.

Keywords: socio-technical systems, human centered design, software engineering, cognitive engineering, soft systems, systems engineering

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Authors: Rui Teixeira, Alan O’Connor, Maria Nogal

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The statistical theory of extreme events is progressively a topic of growing interest in all the fields of science and engineering. The changes currently experienced by the world, economic and environmental, emphasized the importance of dealing with extreme occurrences with improved accuracy. When it comes to the design of offshore structures, particularly offshore wind turbines, the importance of efficiently characterizing extreme events is of major relevance. Extreme events are commonly characterized by extreme values theory. As an alternative, the accurate modeling of the tails of statistical distributions and the characterization of the low occurrence events can be achieved with the application of the Peak-Over-Threshold (POT) methodology. The POT methodology allows for a more refined fit of the statistical distribution by truncating the data with a minimum value of a predefined threshold u. For mathematically approximating the tail of the empirical statistical distribution the Generalised Pareto is widely used. Although, in the case of the exceedances of significant wave data (H_s) the 2 parameters Weibull and the Exponential distribution, which is a specific case of the Generalised Pareto distribution, are frequently used as an alternative. The Generalized Pareto, despite the existence of practical cases where it is applied, is not completely recognized as the adequate solution to model exceedances over a certain threshold u. References that set the Generalised Pareto distribution as a secondary solution in the case of significant wave data can be identified in the literature. In this framework, the current study intends to tackle the discussion of the application of statistical models to characterize exceedances of wave data. Comparison of the application of the Generalised Pareto, the 2 parameters Weibull and the Exponential distribution are presented for different values of the threshold u. Real wave data obtained in four buoys along the Irish coast was used in the comparative analysis. Results show that the application of the statistical distributions to characterize significant wave data needs to be addressed carefully and in each particular case one of the statistical models mentioned fits better the data than the others. Depending on the value of the threshold u different results are obtained. Other variables of the fit, as the number of points and the estimation of the model parameters, are analyzed and the respective conclusions were drawn. Some guidelines on the application of the POT method are presented. Modeling the tail of the distributions shows to be, for the present case, a highly non-linear task and, due to its growing importance, should be addressed carefully for an efficient estimation of very low occurrence events.

Keywords: extreme events, offshore structures, peak-over-threshold, significant wave data

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Lufungula Osembe

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The field of education has witnessed advances in technology and digital transformation. The methods of teaching have undergone significant changes in recent years, resulting in effects on various areas such as pedagogies, curriculum design, personalized teaching, gamification, data analytics, cloud-based learning applications, artificial intelligence tools, advanced plug-ins in LMS, and the emergence of multimedia creation and design. The field of education has not been immune to the changes brought about by digital innovation in recent years, similar to other fields such as engineering, health, science, and technology. There is a need to look at the variables/elements that digital innovation brings to education and develop a framework for higher institutions of learning to assess their readiness to create a viable environment for digital innovation to be successfully adopted. Given the potential benefits of digital innovation in education, it is essential to develop a framework that can assist academics and policymakers in higher institutions of learning to evaluate the effectiveness of adopting and adapting to the evolving landscape of digital innovation in education. The primary research question addressed in this study is to establish the preparedness of higher institutions of learning to adopt and adapt to the evolving landscape of digital innovation. This study follows a Design Science Research (DSR) paradigm to develop a framework for academics and policymakers in higher institutions of learning to evaluate the readiness of their institutions to adopt digital innovation in education. The Design Science Research paradigm is proposed to aid in developing a readiness framework for digital innovation in education. This study intends to follow the Design Science Research (DSR) methodology, which includes problem awareness, suggestion, development, evaluation, and conclusion. One of the major contributions of this study will be the development of the framework for digital innovation in education. Given the various opportunities offered by digital innovation in recent years, the need to create a readiness framework for digital innovation will play a crucial role in guiding academics and policymakers in their quest to align with emerging technologies facilitated by digital innovation in education.

Keywords: digital innovation, DSR, education, opportunities, research

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Authors: Driss Kettani

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In this paper, we shed light on “Digital Divide 2.0,” which we see as COVID-19’s Version of the Digital Divide! We believe that “Fighting” against Digital Divide 2.0 necessitates for a Country to be seriously advanced in the Global Digital Transformation that is, naturally, a complex, delicate, costly and long-term Process. We build an argument supporting our assumption and, from there, we present the foundations of a computational framework to guide and streamline Digital Transformation at all levels.

Keywords: digital divide 2.0, digital transformation, ICTs for development, computational outcomes assessment

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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Authors: Ignatio Madanhire, Charles Mbohwa

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This study looks at the best model of aggregate planning activity in an industrial entity and uses the trial and error method on spreadsheets to solve aggregate production planning problems. Also linear programming model is introduced to optimize the aggregate production planning problem. Application of the models in a furniture production firm is evaluated to demonstrate that practical and beneficial solutions can be obtained from the models. Finally some benchmarking of other furniture manufacturing industries was undertaken to assess relevance and level of use in other furniture firms

Keywords: aggregate production planning, trial and error, linear programming, furniture industry

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Authors: Masoud Baghalian, Musa Arshad

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In order to investigate the effect of foliar application of calcium chloride on the resistance of fruits such as Red and Golden Lebanese apple varieties to blue mold, a split plot experiment in time and space, based on accidental blocks, with three replications under foliar application were done (Control, one in a thousand, two in thousands) and the results of the variance analysis showed that there is a significant difference between the levels of foliar and variety at 5% level and between time, there is significant difference in interaction of variety × time and three way interaction of foliar×variety×time, at 1% level. The highest resistance to the blue mold disease in foliar application was observed at two in thousands calcium (calcium chloride) level.

Keywords: apple, blue mold, foliar calcium, resistance

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Authors: Jie Zhao, Meng Su

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Image recognition, as one of the most critical technologies in computer vision, works to help machine-like robotics understand a scene, that is, if deployed appropriately, will trigger the revolution in remote sensing and industry automation. With the developments of AI technologies, there are many prevailing and sophisticated neural networks as technologies developed for image recognition. However, computer vision platforms as hardware, supporting neural networks for image recognition, as crucial as the neural network technologies, need to be more congruently addressed as the research subjects. In contrast, different computer vision platforms are deterministic to leverage the performance of different neural networks for recognition. In this paper, three different computer vision platforms – Jetson Nano(with 4GB), a standalone laptop(with RTX 3000s, using CUDA), and Google Colab (web-based, using GPU) are explored and four prominent neural network architectures (including AlexNet, VGG(16/19), GoogleNet, and ResNet(18/34/50)), are investigated. In the context of pairwise usage between different computer vision platforms and distinctive neural networks, with the merits of recognition accuracy and time efficiency, the performances are evaluated. In the case study using public imageNets, our findings provide a nuanced perspective on optimizing image recognition tasks across Edge-AI platforms, offering guidance on selecting appropriate neural network structures to maximize performance under hardware constraints.

Keywords: alexNet, VGG, googleNet, resNet, Jetson nano, CUDA, COCO-NET, cifar10, imageNet large scale visual recognition challenge (ILSVRC), google colab

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Authors: Abdulrahman S. Alqahtani

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The revolution of computing and networks could revolutionise terrorism in the same way that it has brought about changes in other aspects of life. The modern technological era has faced countries with a new set of security challenges. There are many states and potential adversaries who have the potential and capacity in cyberspace, which makes them able to carry out cyber-attacks in the future. Some of them are currently conducting surveillance, gathering and analysis of technical information, and mapping of networks and nodes and infrastructure of opponents, which may be exploited in future conflicts. This poster presents the results of the quantitative study (survey) to test the validity of the proposed theoretical framework for the cyber terrorist threats. This theoretical framework will help to in-depth understand these new digital terrorist threats. It may also be a practical guide for managers and technicians in critical infrastructure, to understand and assess the threats they face. It might also be the foundation for building a national strategy to counter cyberterrorism. In the beginning, it provides basic information about the data. To purify the data, reliability and exploratory factor analysis, as well as confirmatory factor analysis (CFA) were performed. Then, Structural Equation Modelling (SEM) was utilised to test the final model of the theory and to assess the overall goodness-of-fit between the proposed model and the collected data set.

Keywords: cyberterrorism, critical infrastructure, , national security, theoretical framework, terrorism

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Authors: M. Dhana Lakshmi, S. Sakthivel Murugan

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As light passes from source to observer in the water medium, it is scattered by the suspended particulate matter. This scattering effect will plague the captured images with non-uniform illumination, blurring details, halo artefacts, weak edges, etc. To overcome this, pixel normalization with an Amended Unsharp Mask (AUM) filter is proposed to enhance the degraded image. To validate the robustness of the proposed technique irrespective of atmospheric light, the considered datasets are collected on dual locations. For those images, the maxima and minima pixel intensity value is computed and normalized; then the AUM filter is applied to strengthen the blurred edges. Finally, the enhanced image is obtained with good illumination and contrast. Thus, the proposed technique removes the effect of scattering called de-hazing and restores the perceptual information with enhanced edge detail. Both qualitative and quantitative analyses are done on considering the standard non-reference metric called underwater image sharpness measure (UISM), and underwater image quality measure (UIQM) is used to measure color, sharpness, and contrast for both of the location images. It is observed that the proposed technique has shown overwhelming performance compared to other deep-based enhancement networks and traditional techniques in an adaptive manner.

Keywords: underwater drone imagery, pixel normalization, thresholding, masking, unsharp mask filter

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Authors: H. Cha, J. Kim, D. Kim, J. Shin, K. Lee

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Since 1980's, the rapid economic growth resulted in so many aged apartment buildings in South Korea. Nevertheless, there is insufficient maintenance practice of buildings. In this study, to facilitate the building maintenance the authors classified the building defects into three levels according to their level of performance and developed a mobile application tool based on each level's appropriate feedback. The feedback structure consisted of 'Maintenance manual phase', 'Online feedback phase', 'Repair work phase of the specialty contractors'. In order to implement each phase the authors devised the necessary database for each phase and created a prototype system that can develop on its own. The authors expect that the building users can easily maintain their buildings by using this application.

Keywords: building defect, maintenance practice, mobile application, system algorithm

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Authors: Veljko Jeremic, Milica Kostic Stankovic, Aleksandar Markovic, Milan Martic

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Evaluating the efficiency of decision making units has been frequently elaborated on in numerous publications. In this paper, the theoretical framework for a novel method of Distance Based Analysis (DBA) is presented. In addition, the method is performed on a sample of the ARWU’s top 54 Universities of the United States, the findings of which clearly demonstrate that the best ranked Universities are far from also being the most efficient.

Keywords: evaluating efficiency, distance based analysis, ranking of universities, ARWU

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Authors: Mohamed Sharof Mostafa, Atefeh Ahmadi

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Most of traditional single modality psychotherapy and counselling approaches to clients’ problems are based on the application of one therapy in all sessions. Modern developments in these sciences focus on eclectic and integrative interventions to consider all dimensions of an issue and all characteristics of the clients. This paper presents and overview eclectic therapy and its pros and cons. In addition, multiple intelligence theory and its application in eclectic therapy approaches are mentioned.

Keywords: eclectic therapy, client, multiple intelligence theory, dimensions

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Authors: S. A. A. Nabeela Nasreen, S. Sundarrajan, S. A. Syed Nizar, Seeram Ramakrishna

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Metal-organic frameworks (MOFs) have attracted considerable interest due to its diverse pore size tunability, fascinating topologies and extensive uses in fields such as catalysis, membrane separation, chemical sensing, etc. Zeolitic imidazolate frameworks (ZIFs) are a class of MOF with porous crystals containing extended three-dimensional structures of tetrahedral metal ions (e.g., Zn) bridged by Imidazolate (Im). Selected ZIFs are used to separate solvent/solvent mixtures. A layer by layer formation of the nanocomposite of Zinc oxide (ZnO) and ZIF on a ceramic support using a solvothermal method was engaged and tested for target solvent/solvent separation. Metal oxide layer was characterized by XRD, SEM, and TEM to confirm the smooth and continuous coating for the separation process. The chemical composition of ZIF films was studied by using X-Ray absorption near-edge structure (XANES) spectroscopy. The obtained ceramic tube with metal oxide and ZIF layer coating were tested for its packing density, thickness, distribution of seed layers and variation of permeation rate of solvent mixture (isopropyl alcohol (IPA)/methyl isobutyl ketone (MIBK). Pervaporation technique was used for the separation to achieve a high permeation rate with separation ratio of > 99.5% of the solvent mixture.

Keywords: metal oxide, membrane, pervaporation, solvothermal, ZIF

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Ahmad Helman Hamdani, Diana Putri Hamdiana

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The Sajau coal measures of Berau Basin, northeastern Kalimantan were deposited within a range of facies associations spanning a spectrum of settings from fluvial to marine. The transitional to terrestrial coal measures are dominated by siliciclastics, but they also contain three laterally extensive marine bands (mudstone). These bands act as marker horizons that enable correlation between fully marine and terrestrial facies. Examination of this range of facies and their sedimentology has enabled the development of a high-resolution sequence stratigraphic framework. Set against the established backdrop of third-order Sajau transgression, nine fourth-order sequences are recognized. Results show that, in the composite sequences, peat accumulation predominantly correlates in transitional areas with early transgressive sequence sets (TSS) and highstand sequence set (HSS), while in more landward areas it correlates with the middle TSS to late highstand sequence sets (HSS). Differences in peat accumulation regimes within the sequence stratigraphic framework are attributed to variations in subsidence and background siliciclastic input rates in different depositional settings, with these combining to produce differences in the rate of accommodation change. The preservation of coal resources in the middle to late HSS in this area was most likely related to the rise of the regional base level throughout the Sajau.

Keywords: sequence stratigraphy, coal, Pliocene, Berau basin

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Authors: L. R. Shobin, S. Manivannan

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One dimensional silver nanowires and nanoparticles gained more interest in developing transparent conducting films, catalysis, biological and chemical sensors. Silver nanostructures can be synthesized by varying reaction conditions such as the precursor concentration, molar ratio of the surfactant, injection speed of silver ions, etc. in the polyol process. However, the reaction proceeds for greater than 2 hours for the formation of silver nanowires. The introduction of etchant in the medium promotes the growth of silver nanowires from silver nanoparticles along the [100] direction. Rapid growth of silver nanowires is accomplished using the Cl- ions from NaCl and polyvinyl pyrrolidone (PVP) as surfactant. The role of Cl- ion was investigated in the growth of the nanostructured silver. Silver nanoparticles (<100 nm) were harvested from glycerol medium in the absence of Cl- ions. Trace amount of Cl- ions (2.5 mM -NaCl) produced the edge joined nanowires of length upto 2 μm and width ranging from 40 to 65 nm. Formation and rapid growth (within 25 minutes) of long, uniform silver nanowires (upto 5 μm) with good yield were realized in the presence of 5 mM NaCl at 200ºC. The growth of nanostructures was monitored by UV-vis-NIR spectroscopy. Scanning and transmission electron microscopes reveal the morphology of the silver nano harvests. The role of temperature in the reduction of silver ions, growth mechanism for nanoparticles, edge joined and straight nanowires will be discussed.

Keywords: silver nanowires, glycerol mediated polyol process, scanning electron microscopy, UV-Vis- NIR spectroscopy, transmission electron microscopy

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Authors: Tina Pujara

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Urban and regional research in the new emerging inter-disciplinary field of happiness is seemingly limited. However, it is progressively being recognized that there is enormous potential for social and behavioral scientists to add a spatial dimension to it. In fact, the happiness of communities can be notably influenced by the design and maintenance of the neighborhoods they inhabit. The probable key reasons being that places can facilitate human social connections and relationships. While it is increasingly being acknowledged that some neighborhood designs appear better suited for social connectedness than others, the plausible reasons for places to deter these characteristics and perhaps their influence on happiness are outwardly unknown. In addition, an explicit step wise methodology to assess neighborhood designs for happiness (of their communities) is not known to exist. This paper is an attempt towards developing such a methodological framework. The paper presents the development of a methodological framework for assessing neighborhood designs for happiness, with a particular focus on the outdoor shared spaces in neighborhoods. The developed methodological framework of investigation follows a mixed method approach and draws upon four different sources of information. The framework proposes an empirical examination of the contribution of neighborhood factors, particularly outdoor shared spaces, to individual happiness. One of the main tools proposed for this empirical examination is Jan Gehl’s Public Space Public Life (PSPL) Survey. The developed framework, as presented in the paper, is a contribution towards the development of a consolidated methodology for assessing neighborhood designs for happiness, which can further serve as a unique tool to inform urban designers, architects and other decision makers.

Keywords: happiness, methodology, neighbourhood design, outdoor shared spaces

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Authors: Marylene S. Eder

Abstract:

Existing location based alarm applications has inability to give information to user’s particular direction to a specified place of destination and does not display a particular scenic spot from its current location going to the destination. With this problem, a location based alarm mobile reminder was developed. The application is implemented on Android based smart phones to provide services like providing routing information, helping to find nearby hotels, restaurants and scenic spots and offer many advantages to the mobile users to retrieve the information about their current location and process that data to get more useful information near to their location. It reminds the user about the location when the user enters some predefined location. All the user needs to have is the mobile phone with android platform with version 4.0 and above, and then the user can select the destination and find the destination on the application. The main objective of the project is to develop a location based application that provides tourists with real time information for scenic spots and provides alarm to a specified place of destination. This mobile application service will act as assistance for the frequent travelers to visit new places around the City.

Keywords: location based alarm, mobile application, mobile reminder, tourist’s spots

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Authors: Shaima Almalhan, Lubna Shukri, Miriam Talal, Safaa Teskieh

Abstract:

Since artificial intelligence is a rapidly evolving topic that has had a significant impact on technical growth and innovation, this paper examines people's awareness, use, and engagement with the Google Translate application. To see how familiar aware users are with the app and its features, quantitative and qualitative research was conducted. The findings revealed that consumers have a high level of confidence in the application and how far people they benefit from this sort of innovation and how convenient it makes communication.

Keywords: artificial intelligence, google translate, speech recognition, language translation, camera translation, speech to text, text to speech

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Authors: Athirat Intajorn

Abstract:

According to the ASEAN free trade areas (AFTA), Thailand has applied the AFTA agreement for reducing tariffs and reflecting changes in business processes. The reflection of changes in agribusiness processes, in particular, has accumulated as production costs for producers. Palm Oil industry has become an important industry to Thailand economic. Thailand currently ranks the 3rd in the world for Crude Palm Oil CPO. Therefore, the scope of this paper presents a research framework to investigate the supply chain management practices in Thailand palm oil industry. This research is limit to literature review. And the proposed framework identifies the criteria of supply chain management for Thailand palm oil industry in order for linkage among entities within logistics management involving plantation, mill, collection port, refinery and cookie from the data utilization. The Supply Chain Management Practices in Thailand Palm Oil Industry framework has a somewhat different view due to the high complexity of agribusiness logistics management.

Keywords: supply chain management, practice, palm oil industry, Thailand palm oil industry

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Authors: Mazharuddin Syed Ahmed

Abstract:

This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

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Authors: Subarna Ferdous, Mitsuru Ikeda

Abstract:

For the shrimp companies to remain relevant to its local and international consumers, they must offer new shrimp product and services. It must work actively not just to create value for the consumer, but to involve the consumer in co-creating value for shrimp product innovation in the market. In this theoretical work, we conceptualize the business concept of value co-creation in the context of shrimp products, and propose a framework of value co-creation for shrimp product innovation in shrimp industries. With guidance on value co-creation in in shrimp industry, and shrimp value chain actors mapped to the co-creation cycle, companies can use the framework to offer new shrimp product to consumer communities. Although customer co-creation is known approach in the world, it is not commonly used by the companies in Bangladesh. This paper makes an original contribution by conceptualizing co-creation and set the examples of best co-creation practices in food sector. The results of the study provide management with guidelines for successful co-creation projects with an innovation- and market-oriented approach. The framework also provides a basis for further research in this area.

Keywords: bangladesh, shrimp industry, value co-creation, shrimp product

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Authors: Cajethan U. Ugwuoke

Abstract:

Agriculture is taught in secondary schools to develop skills in students which will empower them to contribute to national economic development. Unfortunately, our educational system emphasizes the application of conventional teaching methods in delivering instructions, which fails to produce students competent enough to carry out agricultural production. This study was therefore aimed at examining the application of digital technologies as tools for transformative instructional delivery. Four specific purposes, research questions and hypotheses guided the study. The study adopted a descriptive survey research design where 80 subjects representing 64 teachers of agriculture and 16 principals in the Udenu local government area of Enugu State, Nigeria, participated in the study. A structured questionnaire was used to collect data. The assumption of normality was ascertained by subjecting the data collected to a normality test. Data collected were later subjected to mean, Pearson product-moment correlation, ANOVA and t-test to answer the research questions and test the hypotheses at a 5% significant level. The result shows that the application of digital technologies helps to reduce learners’ boredom (3.52.75), improves learners’ performance (3.63.51), and is used as a visual aid for learners (3.56.61), among others. There was a positive, strong and significant relationship between the application of digital technologies and effective instructional delivery (+.895, p=.001<.05, F=17.73), competency of teachers to the application of digital technologies and effective instructional delivery (+998, p=.001<0.5, F=16263.45), and frequency of the application of digital technologies and effective instructional delivery (+.999, p=.001<.05, F=31436.14). There was no evidence of autocorrelation and multicollinearity in the regression models between the application of digital technologies and effective instructional delivery (2.03, Tolerance=1.00, VIF=1.00), competency of teachers in the application of digital technologies and effective instructional delivery (2.38, Tolerance=1.00, VIF=1.00) and frequency of the application of digital technologies and effective instructional delivery (2.00, Tolerance=1.00, VIF=1.00). Digital technologies should be therefore applied in teaching to facilitate effective instructional delivery in agriculture.

Keywords: agricultural science, digital technologies, instructional delivery, learning

Procedia PDF Downloads 53