Search results for: Bayesian approach
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14149

Search results for: Bayesian approach

11629 The Data-Driven Localized Wave Solution of the Fokas-Lenells Equation Using Physics-Informed Neural Network

Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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11628 An Approach of Node Model TCnNet: Trellis Coded Nanonetworks on Graphene Composite Substrate

Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

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Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

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11627 DNA Nano Wires: A Charge Transfer Approach

Authors: S. Behnia, S. Fathizadeh, A. Akhshani

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In the recent decades, DNA has increasingly interested in the potential technological applications that not directly related to the coding for functional proteins that is the expressed in form of genetic information. One of the most interesting applications of DNA is related to the construction of nanostructures of high complexity, design of functional nanostructures in nanoelectronical devices, nanosensors and nanocercuits. In this field, DNA is of fundamental interest to the development of DNA-based molecular technologies, as it possesses ideal structural and molecular recognition properties for use in self-assembling nanodevices with a definite molecular architecture. Also, the robust, one-dimensional flexible structure of DNA can be used to design electronic devices, serving as a wire, transistor switch, or rectifier depending on its electronic properties. In order to understand the mechanism of the charge transport along DNA sequences, numerous studies have been carried out. In this regard, conductivity properties of DNA molecule could be investigated in a simple, but chemically specific approach that is intimately related to the Su-Schrieffer-Heeger (SSH) model. In SSH model, the non-diagonal matrix element dependence on intersite displacements is considered. In this approach, the coupling between the charge and lattice deformation is along the helix. This model is a tight-binding linear nanoscale chain established to describe conductivity phenomena in doped polyethylene. It is based on the assumption of a classical harmonic interaction between sites, which is linearly coupled to a tight-binding Hamiltonian. In this work, the Hamiltonian and corresponding motion equations are nonlinear and have high sensitivity to initial conditions. Then, we have tried to move toward the nonlinear dynamics and phase space analysis. Nonlinear dynamics and chaos theory, regardless of any approximation, could open new horizons to understand the conductivity mechanism in DNA. For a detailed study, we have tried to study the current flowing in DNA and investigated the characteristic I-V diagram. As a result, It is shown that there are the (quasi-) ohmic areas in I-V diagram. On the other hand, the regions with a negative differential resistance (NDR) are detectable in diagram.

Keywords: DNA conductivity, Landauer resistance, negative di erential resistance, Chaos theory, mean Lyapunov exponent

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11626 Production of Metal Powder Using Twin Arc Spraying Process for Additive Manufacturing

Authors: D. Chen, H. Daoud, C. Kreiner, U. Glatzel

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Additive Manufacturing (AM) provides promising opportunities to optimize and to produce tooling by integrating near-contour tempering channels for more efficient cooling. To enhance the properties of the produced tooling using additive manufacturing, prototypes should be produced in short periods. Thereby, this requires a small amount of tailored powders, which either has a high production cost or is commercially unavailable. Hence, in this study, an arc spray atomization approach to produce a tailored metal powder at a lower cost and even in small quantities, in comparison to the conventional powder production methods, was proposed. This approach involves converting commercially available metal wire into powder by modifying the wire arc spraying process. The influences of spray medium and gas pressure on the powder properties were investigated. As a result, particles with smooth surface and lower porosity were obtained, when nonoxidizing gases are used for thermal spraying. The particle size decreased with increasing of the gas pressure, and the particles sizes are in the range from 10 to 70 µm, which is desirable for selective laser melting (SLM). A comparison of microstructure and mechanical behavior of SLM generated parts using arc sprayed powders (alloy: X5CrNiCuNb 16-4) and commercial powder (alloy: X5CrNiCuNb 16-4) was also conducted.

Keywords: additive manufacturing, arc spraying, powder production, selective laser melting

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11625 Evaluation of Water Management Options to Improve the Crop Yield and Water Productivity for Semi-Arid Watershed in Southern India Using AquaCrop Model

Authors: V. S. Manivasagam, R. Nagarajan

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Modeling the soil, water and crop growth interactions are attaining major importance, considering the future climate change and water availability for agriculture to meet the growing food demand. Progress in understanding the crop growth response during water stress period through crop modeling approach provides an opportunity for improving and sustaining the future agriculture water use efficiency. An attempt has been made to evaluate the potential use of crop modeling approach for assessing the minimal supplementary irrigation requirement for crop growth during water limited condition and its practical significance in sustainable improvement of crop yield and water productivity. Among the numerous crop models, water driven-AquaCrop model has been chosen for the present study considering the modeling approach and water stress impact on yield simulation. The study has been evaluated in rainfed maize grown area of semi-arid Shanmuganadi watershed (a tributary of the Cauvery river system) located in southern India during the rabi cropping season (October-February). In addition to actual rainfed maize growth simulation, irrigated maize scenarios were simulated for assessing the supplementary irrigation requirement during water shortage condition for the period 2012-2015. The simulation results for rainfed maize have shown that the average maize yield of 0.5-2 t ha-1 was observed during deficit monsoon season (<350 mm) whereas 5.3 t ha-1 was noticed during sufficient monsoonal period (>350 mm). Scenario results for irrigated maize simulation during deficit monsoonal period has revealed that 150-200 mm of supplementary irrigation has ensured the 5.8 t ha-1 of irrigated maize yield. Thus, study results clearly portrayed that minimal application of supplementary irrigation during the critical growth period along with the deficit rainfall has increased the crop water productivity from 1.07 to 2.59 kg m-3 for major soil types. Overall, AquaCrop is found to be very effective for the sustainable irrigation assessment considering the model simplicity and minimal inputs requirement.

Keywords: AquaCrop, crop modeling, rainfed maize, water stress

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11624 A Soft Computing Approach Monitoring of Heavy Metals in Soil and Vegetables in the Republic of Macedonia

Authors: Vesna Karapetkovska Hristova, M. Ayaz Ahmad, Julijana Tomovska, Biljana Bogdanova Popov, Blagojce Najdovski

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The average total concentrations of heavy metals; (cadmium [Cd], copper [Cu], nickel [Ni], lead [Pb], and zinc [Zn]) were analyzed in soil and vegetables samples collected from the different region of Macedonia during the years 2010-2012. Basic soil properties such as pH, organic matter and clay content were also included in the study. The average concentrations of Cd, Cu, Ni, Pb, Zn in the A horizon (0-30 cm) of agricultural soils were as follows, respectively: 0.25, 5.3, 6.9, 15.2, 26.3 mg kg-1 of soil. We have found that neural networking model can be considered as a tool for prediction and spatial analysis of the processes controlling the metal transfer within the soil-and vegetables. The predictive ability of such models is well over 80% as compared to 20% for typical regression models. A radial basic function network reflects good predicting accuracy and correlation coefficients between soil properties and metal content in vegetables much better than the back-propagation method. Neural Networking / soft computing can support the decision-making processes at different levels, including agro ecology, to improve crop management based on monitoring data and risk assessment of metal transfer from soils to vegetables.

Keywords: soft computing approach, total concentrations, heavy metals, agricultural soils

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11623 Integrating Renewable Energy Forecasting Systems with HEMS and Developing It with a Bottom-Up Approach

Authors: Punit Gandhi, J. C. Brezet, Tim Gorter, Uchechi Obinna

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This paper introduces how weather forecasting could help in more efficient energy management for smart homes with the use of Home Energy Management Systems (HEMS). The paper also focuses on educating consumers and helping them make more informed decisions while using the HEMS. A combined approach of technical and user perspective has been selected to develop a novel HEMS-product-service combination in a more comprehensive manner. The current HEMS switches on/off the energy intensive appliances based on the fluctuating electricity tariffs, but with weather forecasting, it is possible to shift the time of use of energy intensive appliances to maximum electricity production from the renewable energy system installed in the house. Also, it is possible to estimate the heating/cooling load of the house for the day ahead demand. Hence, relevant insight is gained in the expected energy production and consumption load for the next day, facilitating better (more efficient, peak shaved, cheaper, etc.) energy management practices for smart homes. In literature, on the user perspective, it has been observed that consumers lose interest in using HEMS after three to four months. Therefore, to further help in better energy management practices, the new system had to be designed in a way that consumers would sustain their interaction with the system on a structural basis. It is hypothesized that, if consumers feel more comfortable with using such system, it would lead to a prolonged usage, including more energy savings and hence financial savings. To test the hypothesis, a survey for the HEMS is conducted, to which 59 valid responses were recorded. Analysis of the survey helped in designing a system which imparts better information about the energy production and consumption to the consumers. It is also found from the survey that, consumers like a variety of options and they do not like a constant reminder of what they should do. Hence, the final system is designed to encourage consumers to make an informed decision about their energy usage with a wide variety of behavioral options available. It is envisaged that the new system will be tested in several pioneering smart energy grid projects in both the Netherlands and India, with a continued ‘design thinking’ approach, combining the technical and user perspective, as the basis for further improvements.

Keywords: weather forecasting, smart grid, renewable energy forecasting, user defined HEMS

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11622 Revolutionizing Gaming Setup Design: Utilizing Generative and Iterative Methods to Prop and Environment Design, Transforming the Landscape of Game Development Through Automation and Innovation

Authors: Rashmi Malik, Videep Mishra

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The practice of generative design has become a transformative approach for an efficient way of generating multiple iterations for any design project. The conventional way of modeling the game elements is very time-consuming and requires skilled artists to design. A 3D modeling tool like 3D S Max, Blender, etc., is used traditionally to create the game library, which will take its stipulated time to model. The study is focused on using the generative design tool to increase the efficiency in game development at the stage of prop and environment generation. This will involve procedural level and customized regulated or randomized assets generation. The paper will present the system design approach using generative tools like Grasshopper (visual scripting) and other scripting tools to automate the process of game library modeling. The script will enable the generation of multiple products from the single script, thus creating a system that lets designers /artists customize props and environments. The main goal is to measure the efficacy of the automated system generated to create a wide variety of game elements, further reducing the need for manual content creation and integrating it into the workflow of AAA and Indie Games.

Keywords: iterative game design, generative design, gaming asset automation, generative game design

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11621 Biosurfactant: A Greener Approach for Enhanced Concrete Rheology and Strength

Authors: Olivia Anak Rayeg, Clotilda Binti Petrus, Arnel Reanturco Ascotia, Ang Chung Huap, Caroline Marajan, Rudy Tawie Joseph Sipi

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Concrete is essential for global infrastructure, yet enhancing its rheology and strength in an environmentally sustainable manner remains a significant challenge. Conventional chemical admixtures often pose environmental and health risks. This study explores the use of a phospholipid biosurfactant, derived from Rhizopus oryzae, as an environmentally friendly admixture in concrete. Various concentrations of the biosurfactant were integrated into fresh concrete, partially replacing the water content. The inclusion of the biosurfactant markedly enhanced the workability of the concrete, as demonstrated by Vertical Slump, Slump Flow, and T50 tests. After a 28-day curing period, the concrete's mechanical properties were assessed through compressive strength and bonding tests. Results revealed that substituting up to 10% of the water with the biosurfactant not only improved workability but also significantly increased both compressive and flexural strength. These findings highlight the potential of phospholipid biosurfactant as a biodegradable and non-toxic alternative to traditional admixtures, enhancing both structural integrity and sustainability in concrete. This approach reduces environmental impact and production costs, marking a significant advancement in sustainable construction technology.

Keywords: concrete rheology, green admixture, fungal biosurfactant, phospholipids, rhizopus oryzae

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11620 Interdisciplinary Integrated Physical Education Program Using a Philosophical Approach

Authors: Ellie Abdi, Susana Juniu

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The purpose of this presentation is to describe an interdisciplinary teaching program that integrates physical education concepts using a philosophical approach. The presentation includes a review of: a) the philosophy of American education, b) the philosophy of sports and physical education, c) the interdisciplinary physical education program, d) professional development programs, (e) the Success of this physical education program, f) future of physical education. This unique interdisciplinary program has been implemented in an urban school physical education discipline in East Orange, New Jersey for over 10 years. During the program the students realize that the bodies go through different experiences. The body becomes a place where a child can recognize in an enjoyable way to express and perceive particular feelings or mental states. Children may distinguish themselves to have high abilities in the social or other domains but low abilities in the field of athletics. The goal of this program for the individuals is to discover new skills, develop and demonstrate age appropriate mastery level at different tasks, therefore the program consists of 9 to 12 sports, including many game. Each successful experience increases the awareness ability. Engaging in sports and physical activities are social movements involving groups of children in situations such as teams, friends, and recreational settings, which serve as a primary socializing agent for teaching interpersonal skills. As a result of this presentation the audience will reflect and explore how to structure a physical education program to integrate interdisciplinary subjects with philosophical concepts.

Keywords: interdisciplinary disciplines, philosophical concepts, physical education, interdisciplinary teaching program

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11619 Genetic Identification of Crop Cultivars Using Barcode System

Authors: Kesavan Markkandan, Ha Young Park, Seung-Il Yoo, Sin-Gi Park, Junhyung Park

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For genetic identification of crop cultivars, insertions/deletions (InDel) markers have been preferred currently because they are easy to use, PCR based, co-dominant and relatively abundant. However, new InDels need to be developed for genetic studies of new varieties due to the difference of allele frequencies in InDels among the population groups. These new varieties are evolved with low levels of genetic diversity in specific genome loci with high recombination rate. In this study, we described soybean barcode system approach based on InDel makers, each of which is specific to a variation block (VB), where the genomes split by all assumed recombination sites. Firstly, VBs in crop cultivars were mined for transferability to VB-specific InDel markers. Secondly, putative InDels in the VB regions were identified for the development of barcode system by analyzing particular cultivar’s whole genome data. Thirdly, common VB-specific InDels from all cultivars were selected by gel electrophoresis, which were converted as 2D barcode types according to comparing amplicon polymorphisms in the five cultivars to the reference cultivar. Finally, the polymorphism of the selected markers was assessed with other cultivars, and the barcode system that allows a clear distinction among those cultivars is described. The same approach can be applicable for other commercial crops. Hence, VB-based genetic identification not only minimize the molecular markers but also useful for assessing cultivars and for marker-assisted breeding in other crop species.

Keywords: variation block, polymorphism, InDel marker, genetic identification

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11618 Participatory Air Quality Monitoring in African Cities: Empowering Communities, Enhancing Accountability, and Ensuring Sustainable Environments

Authors: Wabinyai Fidel Raja, Gideon Lubisa

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Air pollution is becoming a growing concern in Africa due to rapid industrialization and urbanization, leading to implications for public health and the environment. Establishing a comprehensive air quality monitoring network is crucial to combat this issue. However, conventional methods of monitoring are insufficient in African cities due to the high cost of setup and maintenance. To address this, low-cost sensors (LCS) can be deployed in various urban areas through the use of participatory air quality network siting (PAQNS). PAQNS involves stakeholders from the community, local government, and private sector working together to determine the most appropriate locations for air quality monitoring stations. This approach improves the accuracy and representativeness of air quality monitoring data, engages and empowers community members, and reflects the actual exposure of the population. Implementing PAQNS in African cities can build trust, promote accountability, and increase transparency in the air quality management process. However, challenges to implementing this approach must be addressed. Nonetheless, improving air quality is essential for protecting public health and promoting a sustainable environment. Implementing participatory and data-informed air quality monitoring can take a significant step toward achieving these important goals in African cities and beyond.

Keywords: low-cost sensors, participatory air quality network siting, air pollution, air quality management

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11617 Exploring the Influence of Culture on Dietary Practices and Ethnic Inequality in Health among Migrant Nigerians in the UK

Authors: Babatunde Johnson

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The rate of diseases and death from preventable diseases among ethnic minority groups is high when compared with the wider white population in the UK. This can be due in part to the diet consumed and various cultural reasons. Changes in dietary practices and the health of ethnic minority groups can be caused by the adoption of food practices of the host culture after migration (acculturation) and generational differences among migrants. However, understanding how and why these changes occur is limited due to the challenges of data collection in research. This research utilizes the interpretive phenomenological approach, coupled with Bourdieu’s theory used as the conceptual framework, and seeks an in-depth understanding of how adult immigrant Nigerians in the UK interpret their experience of the influence of ethnic and prevailing cultures on their dietary practice. Recruiting participants from a close-knit community, such as the Nigerian population in the UK, can be complex and problematic and is determined by the accessibility to the community. Although complex, the researcher leveraged the principles of Patient and Public Involvement (PPI) in gaining access to participants within the Nigerian community. This study emphasizes the need for a culturally tailored and community-centered approach to interventions geared toward the reduction of ethnic health inequality in the UK other than the existing practice, which focuses on better healthy eating through the improvement of skills and knowledge about food groups.

Keywords: culture, dietary practice, ethnic minority, health inequality

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11616 Analysis of Bed Load Sediment Transport Mataram-Babarsari Irrigation Canal

Authors: Agatha Padma Laksitaningtyas, Sumiyati Gunawan

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Mataram Irrigation Canal has 31,2 km length, is the main irrigation canal in Special Region Province of Yogyakarta, connecting Progo River on the west side and Opak River on the east side. It has an important role as the main water carrier distribution for various purposes such as agriculture, fishery, and plantation which should be free from sediment material. Bed Load Sediment is the basic sediment that will make the sediment process on the irrigation canal. Sediment process is a simultaneous event that can make deposition sediment at the base of irrigation canal and can make the height of elevation water change, it will affect the availability of water to be used for irrigation functions. To predict the amount of drowning sediments in the irrigation canal using two methods: Meyer-Peter and Muller’s Method which is an energy approach method and Einstein Method which is a probabilistic approach. Speed measurement using floating method and using current meters. The channel geometry is measured directly in the field. The basic sediment of the channel is taken in the field by taking three samples from three different points. The result of the research shows that by using the formula Meyer -Peter Muller get the result of 60,75799 kg/s, whereas with Einsten’s Method get result of 13,06461 kg/s. the results may serve as a reference for dredging the sediments on the channel so as not to disrupt the flow of water in irrigation canal.

Keywords: bed load, sediment, irrigation, Mataram canal

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11615 Land Cover Remote Sensing Classification Advanced Neural Networks Supervised Learning

Authors: Eiman Kattan

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This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

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11614 Parametric Modeling for Survival Data with Competing Risks Using the Generalized Gompertz Distribution

Authors: Noora Al-Shanfari, M. Mazharul Islam

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The cumulative incidence function (CIF) is a fundamental approach for analyzing survival data in the presence of competing risks, which estimates the marginal probability for each competing event. Parametric modeling of CIF has the advantage of fitting various shapes of CIF and estimates the impact of covariates with maximum efficiency. To calculate the total CIF's covariate influence using a parametric model., it is essential to parametrize the baseline of the CIF. As the CIF is an improper function by nature, it is necessary to utilize an improper distribution when applying parametric models. The Gompertz distribution, which is an improper distribution, is limited in its applicability as it only accounts for monotone hazard shapes. The generalized Gompertz distribution, however, can adapt to a wider range of hazard shapes, including unimodal, bathtub, and monotonic increasing or decreasing hazard shapes. In this paper, the generalized Gompertz distribution is used to parametrize the baseline of the CIF, and the parameters of the proposed model are estimated using the maximum likelihood approach. The proposed model is compared with the existing Gompertz model using the Akaike information criterion. Appropriate statistical test procedures and model-fitting criteria will be used to test the adequacy of the model. Both models are applied to the ‘colon’ dataset, which is available in the “biostat3” package in R.

Keywords: competing risks, cumulative incidence function, improper distribution, parametric modeling, survival analysis

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11613 Clustered Regularly Interspaced Short Palindromic Repeat/cas9-Based Lateral Flow and Fluorescence Diagnostics for Rapid Pathogen Detection

Authors: Mark Osborn

Abstract:

Clustered, regularly interspaced short palindromic repeat (CRISPR/Cas) proteins can be designed to bind specified DNA and RNA sequences and hold great promise for the accurate detection of nucleic acids for diagnostics. Commercially available reagents were integrated into a CRISPR/Cas9-based lateral flow assay that can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences with single-base specificity. This approach requires minimal equipment and represents a simplified platform for field-based deployment. A rapid, multiplex fluorescence CRISPR/Cas9 nuclease cleavage assay capable of detecting and differentiating SARS-CoV-2, influenza A and B, and respiratory syncytial virus in a single reaction was also developed. These findings provide proof of principle for CRISPR/Cas9 point-of-care diagnosis that can detect specific SARS-CoV-2 strain(s). Further, Cas9 cleavage allows for a scalable fluorescent platform for identifying respiratory viral pathogens with overlapping symptomology. Collectively, this approach is a facile platform for diagnostics with broad application to user-defined sequence interrogation and detection.

Keywords: CRISPR/Cas9, lateral flow assay, SARS-Co-V2, single-nucleotide resolution

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11612 Plethora of Drivers Transforming Colonial Cities: The Case of Allahabad

Authors: Akanksha Gupta, Vishal Dubey

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In the Neoliberal era, there has been a much-talked discourse about urban issues that arise from a narrow approach of the single rationality of market-driven planning in Indian cities. More to this, India's urban planning is already jeopardized by the captious shortage of infrastructure, a cluster of incoherent governing bodies and implementation mechanism, leading cities to lie in the plethora of urban challenges. In this context, Allahabad (now known as Prayagraj) a city in North India is not an exception. Once known as the most planned splendid Colonial city of the British regime in India collapsed phenomenally because of the incompetent approach of planning machinery, straightforward market-driven accession and lack of attention on urban equity and sustainability. Particularly Civil Lines a Colonial neighbourhood, reached to the zenith of the glorified legacy of the Colonial era, transformed into filthy and congested urban form. Contextually this study contemplates and assesses the chronological episodes of major changes in land management reforms and policies under the ad hoc approach of political economy and land use planning which radically degraded the living environment in the present context. This study would empirically showcase the selected sample area detailing some of the major consequences in terms of gradual change in urban morphology, land use, and function. Here the method of study is primarily a qualitative study implying oral history and other historical methods to exhibit the idiom of planning conundrum. This subsequently reflects the repercussions translated into major issues like unclear land titles, encroachment, and unauthorized development and mushrooming of informal and squatter settlements. In nutshell, the study seeks to distinct out the limitations of the land reform and land management policies, which impacted the general degradation to the beautiful setting of Colonial neighbourhood. The Colonial legacy of Civil Lines now exists in the traces of history- memories of people, who once took pride in its serenity have now witnessed the transformation bit by bit till neo-liberal market forces completely swallow it.

Keywords: civil lines, land reforms, policies, urban challenges

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11611 Microfinance for the Marginalised: The Impact of the Rojiroti Approach in India

Authors: Gil Yaron, Rebecca Gordon, John Best, Sunil Choudhary

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There have been a number of studies examining the impact of microfinance; however, the magnitude of impact varies across regions, and there has been mixed evidence due to the differences in the nature of interventions, context and the way in which microfinance is implemented. The Rojiroti approach to microfinance involves the creation of women's self-help groups (SHGs), rotated loans from savings and subsequent credit from a Bihar-based NGO. Rojiroti serves customers who are significantly poorer and more marginalised than those typically served by microfinance in India. In the data analysed, more than 90 percent of members are from scheduled caste and tribes (62 percent) or other disadvantaged castes. This paper analyses the impact of Rojiroti microfinance using panel data on 740 new SHG members and 340 women in matched control sites at baseline and after 18 months. We consider changes in assets, children's education, women's mobility and domestic violence among other indicators. These results show significant gains for Rojiroti borrowers relative to control sites for important, but not all, variables. Comparison with more longstanding SHGs (at least 36 months) helps to explain how the borrowing patterns of poor and marginalised SHG members evolve. The context of this intervention is also important; in this case, innovative microfinance is provided too much poorer and marginalised women than is typically the case, and so the results seen are in contrast to numerous studies that show little or no effect of microfinance on the lives of their clients.

Keywords: microfinance, gender, impact, pro-poor

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11610 LTE Modelling of a DC Arc Ignition on Cold Electrodes

Authors: O. Ojeda Mena, Y. Cressault, P. Teulet, J. P. Gonnet, D. F. N. Santos, MD. Cunha, M. S. Benilov

Abstract:

The assumption of plasma in local thermal equilibrium (LTE) is commonly used to perform electric arc simulations for industrial applications. This assumption allows to model the arc using a set of magneto-hydromagnetic equations that can be solved with a computational fluid dynamic code. However, the LTE description is only valid in the arc column, whereas in the regions close to the electrodes the plasma deviates from the LTE state. The importance of these near-electrode regions is non-trivial since they define the energy and current transfer between the arc and the electrodes. Therefore, any accurate modelling of the arc must include a good description of the arc-electrode phenomena. Due to the modelling complexity and computational cost of solving the near-electrode layers, a simplified description of the arc-electrode interaction was developed in a previous work to study a steady high-pressure arc discharge, where the near-electrode regions are introduced at the interface between arc and electrode as boundary conditions. The present work proposes a similar approach to simulate the arc ignition in a free-burning arc configuration following an LTE description of the plasma. To obtain the transient evolution of the arc characteristics, appropriate boundary conditions for both the near-cathode and the near-anode regions are used based on recent publications. The arc-cathode interaction is modeled using a non-linear surface heating approach considering the secondary electron emission. On the other hand, the interaction between the arc and the anode is taken into account by means of the heating voltage approach. From the numerical modelling, three main stages can be identified during the arc ignition. Initially, a glow discharge is observed, where the cold non-thermionic cathode is uniformly heated at its surface and the near-cathode voltage drop is in the order of a few hundred volts. Next, a spot with high temperature is formed at the cathode tip followed by a sudden decrease of the near-cathode voltage drop, marking the glow-to-arc discharge transition. During this stage, the LTE plasma also presents an important increase of the temperature in the region adjacent to the hot spot. Finally, the near-cathode voltage drop stabilizes at a few volts and both the electrode and plasma temperatures reach the steady solution. The results after some seconds are similar to those presented for thermionic cathodes.

Keywords: arc-electrode interaction, thermal plasmas, electric arc simulation, cold electrodes

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11609 Algorithms Inspired from Human Behavior Applied to Optimization of a Complex Process

Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

Abstract:

Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

Procedia PDF Downloads 109
11608 Filtering Intrusion Detection Alarms Using Ant Clustering Approach

Authors: Ghodhbani Salah, Jemili Farah

Abstract:

With the growth of cyber attacks, information safety has become an important issue all over the world. Many firms rely on security technologies such as intrusion detection systems (IDSs) to manage information technology security risks. IDSs are considered to be the last line of defense to secure a network and play a very important role in detecting large number of attacks. However the main problem with today’s most popular commercial IDSs is generating high volume of alerts and huge number of false positives. This drawback has become the main motivation for many research papers in IDS area. Hence, in this paper we present a data mining technique to assist network administrators to analyze and reduce false positive alarms that are produced by an IDS and increase detection accuracy. Our data mining technique is unsupervised clustering method based on hybrid ANT algorithm. This algorithm discovers clusters of intruders’ behavior without prior knowledge of a possible number of classes, then we apply K-means algorithm to improve the convergence of the ANT clustering. Experimental results on real dataset show that our proposed approach is efficient with high detection rate and low false alarm rate.

Keywords: intrusion detection system, alarm filtering, ANT class, ant clustering, intruders’ behaviors, false alarms

Procedia PDF Downloads 406
11607 Applied Mathematical Approach on “Baut” Special High Performance Metal Aggregate by Formulation and Equations

Authors: J. R. Bhalla, Gautam, Gurcharan Singh, Sanjeev Naval

Abstract:

Mathematics is everywhere behind the every things on the earth as well as in the universe. Predynastic Egyptians of the 5th millennium BC pictorially represented geometric designs. Now a day’s we can made and apply an equation on a complex geometry through applied mathematics. Here we work and focus on to create a formula which apply in the field of civil engineering in new concrete technology. In this paper our target is to make a formula which is applied on “BAUT” Metal Aggregate. In this paper our approach is to make formulation and equation on special “BAUT” Metal Aggregate by Applied Mathematical Study Case 1. BASIC PHYSICAL FORMULATION 2. ADVANCE EQUATION which shows the mechanical performance of special metal aggregates for concrete technology. In case 1. Basic physical formulation shows the surface area and volume manually and in case 2. Advance equation shows the mechanical performance has been discussed, the metal aggregates which had outstandingly qualities to resist shear, tension and compression forces. In this paper coarse metal aggregates is 20 mm which used for making high performance concrete (H.P.C).

Keywords: applied mathematical study case, special metal aggregates, concrete technology, basic physical formulation, advance equation

Procedia PDF Downloads 375
11606 Transformation of Antitrust Policy against Collusion in Russia and Transition Economies

Authors: Andrey Makarov

Abstract:

This article will focus on the development of antitrust policy in transition economies in the context of preventing explicit and tacit collusion. Experience of BRICS, CIS (Ukraine, Kazakhstan) and CEE countries (Bulgaria, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, Czech Republic, Estonia) in the creation of antitrust institutions was analyzed, including both legislation and enforcement practice. Most of these countries in the early 90th were forced to develop completely new legislation in the field of protection of competition and it is important to compare different ways of building antitrust institutions and policy results. The article proposes a special approach to evaluation of preventing collusion mechanisms. This approach takes into account such enforcement problems as: classification problems (tacit vs explicit collusion, vertical vs horizontal agreements), flexibility of prohibitions (the balance between “per se” vs “rule of reason” approaches de jure and in practice), design of sanctions, private enforcement challenge, leniency program mechanisms, the role of antitrust authorities etc. The analysis is conducted using both official data, published by competition authorities, and expert assessments. The paper will show how the integration process within the EU predetermined some aspects of the development of antitrust policy in CEE countries, including the trend of the use of "rule of reason" approach. Simultaneously was analyzed the experience of CEE countries in special mechanisms of government intervention. CIS countries in the development of antitrust policy followed more or less original ways, without such a great impact from the European Union, more attention will be given to Russian experience in this field, including the analysis of judicial decisions in antitrust cases. Main problems and challenges for transition economies in this field will be shown, including: Legal uncertainty problem; Problem of rigidity of prohibitions; Enforcement priorities of the regulator; Interaction of administrative and criminal law, limited effectiveness of criminal sanctions in the antitrust field; The effectiveness of leniency program design; Private enforcement challenge.

Keywords: collusion, antitrust policy, leniency program, transition economies, Russia, CEE

Procedia PDF Downloads 447
11605 Extreme Value Modelling of Ghana Stock Exchange Indices

Authors: Kwabena Asare, Ezekiel N. N. Nortey, Felix O. Mettle

Abstract:

Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana Stock Exchange All-Shares indices (2000-2010) by applying the Extreme Value Theory to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before EVT method was applied. The Peak Over Threshold (POT) approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model’s goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the Value at Risk (VaR) and Expected Shortfall (ES) risk measures at some high quantiles, based on the fitted GPD model.

Keywords: extreme value theory, expected shortfall, generalized pareto distribution, peak over threshold, value at risk

Procedia PDF Downloads 559
11604 Decay Analysis of 118Xe* Nucleus Formed in 28Si Induced Reaction

Authors: Manoj K. Sharma, Neha Grover

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Dynamical cluster decay model (DCM) is applied to study the decay mechanism of 118Xe* nucleus in reference to recent data on 28Si + 90Zr → 118Xe* reaction, as an extension of our previous work on the dynamics of 112Xe* nucleus. It is relevant to mention here that DCM is based on collective clusterization approach, where emission probability of different decay paths such as evaporation residue (ER), intermediate mass fragments (IMF) and fission etc. is worked out on parallel scale. Calculations have been done over a wide range of center of mass energies with Ec.m. = 65 - 92 MeV. The evaporation residue (ER) cross-sections of 118Xe* compound nucleus are fitted in reference to available data, using spherical and quadrupole (β2) deformed choice of decaying fragments within the optimum orientations approach. It may be noted that our calculated cross-sections find decent agreement with experimental data and hence provide an opportunity to analyze the exclusive role of deformations in view of fragmentation behavior of 118Xe* nucleus. The possible contribution of IMF fragments is worked out and an extensive effort is being made to analyze the role of excitation energy, angular momentum, diffuseness parameter and level density parameter to have better understanding of the decay patterns governed in the dynamics of 28Si + 90Zr → 118Xe* reaction.

Keywords: cross-sections, deformations, fragmentation, angular momentum

Procedia PDF Downloads 321
11603 Computer-Aided Classification of Liver Lesions Using Contrasting Features Difference

Authors: Hussein Alahmer, Amr Ahmed

Abstract:

Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

Procedia PDF Downloads 327
11602 Integrated Risk Management as a Framework for Organisational Success

Authors: Olakunle Felix Adekunle

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Risk management is recognised as an essential tool to tackle the inevitable uncertainty associated with business and projects at all levels. But it frequently fails to meet expectations, with projects continuing to run late, over budget or under performing, and business is not gaining the expected benefits. The evident disconnect which often occurs between strategic vision and tactical project delivery typically arises from poorly defined project objectives and inadequate attention to the proactive management of risks that could affect those objectives. One of the main failings in the traditional approach to risk management arises from a narrow focus on the downside, restricted to the technical or operational field, addressing tactical threats to processes, performance or people. This shortcoming can be overcome by widening the scope of risk management to encompass both strategic risks and upside opportunities, creating an integrated approach which can bridge the gap between strategy and tactics. Integrated risk management addresses risk across a variety of levels in the organisation, including strategy and tactics, and covering both opportunity and threat. Effective implementation of integrated risk management can produce a number of benefits to the organisation which are not available from the typical limited-scope risk process. This paper explores how to expand risk management to deliver strategic advantage while retaining its use as a tactical tool.

Keywords: risk management, success, organization, strategy, project, tactis, vision

Procedia PDF Downloads 399
11601 Explorative Approach to the Evolving Administrative Landscape of South Africa

Authors: Z. I Jeeva

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The establishment of municipalities in South Africa has been a long and difficult process; 25 years later, it still appears to be evolving. In 1994, the new democratic government undertook to restructure the country’s racially segregated administrative structure by integrating areas to form cohesive municipal entities that would allow for the more efficient administration management of the regions. It planned to achieve this within a short seven-year period from 1993 to 2000, which was to be divided into three phases, namely, the pre-interim phase from 1994 to1995, the interim phase from 1996 to 1999, and the post-interim phase from 2000 onwards. However, the extensive integrated municipal approach was easier to pen on paper than to implement in practice. This paper seeks to explore the South African spatial reform process from 1993 to 2020, by analyzing policy documents and literature in order to determine how exactly the government attempted to achieve this. The study found that the spatial restructuring process was particularly complex since the democratic government inherited an unequal society located on a fragmented spatial landscape of which there was limited knowledge with many unresolved issues. Furthermore, the study found that there is a lack of literature on the topic from an urban planning perspective and calls for further research to ensure the formation of more efficient administrative regions.

Keywords: categorization, demarcation, municipalities, racial integration, spatial reform

Procedia PDF Downloads 111
11600 Predictive Modeling of Student Behavior in Virtual Reality: A Machine Learning Approach

Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

Abstract:

In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

Procedia PDF Downloads 145