Search results for: traditional similarity transformation model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21744

Search results for: traditional similarity transformation model

20844 Virtual Reality Technology for Employee Training in High-Risk Industries: Benefits and Advancements

Authors: Yeganeh Jabbari, Sepideh Khalatabad

Abstract:

This study explores the development of virtual reality (VR) technology for training applications, specifically its the potential benefits of VR technology for employee training and its ability to simulate real-world scenarios in a safe and controlled environment are highlighted, along with the associated cost and time savings. The adoption of VR technology in high-risk industrial organizations such as the oil and gas industry is discussed, with a focus on its ability to improve worker performance. Additionally, the use of VR technology in activities such as simulation and data visualization in the oil and gas industry is explored, leading to enhanced safety measures and collaboration between teams. The integration of advanced technologies such as robotics is mentioned as a way to further promote efficiency and sustainability. Also, the study mentions that the digital transformation of the oil and gas industry is revolutionizing operations and promoting safety, efficiency, and sustainability through the use of VR technology.

Keywords: virtual reality training, virtual reality benefits, high-risk industries, digital transformation

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20843 Life Cycle Datasets for the Ornamental Stone Sector

Authors: Isabella Bianco, Gian Andrea Blengini

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The environmental impact related to ornamental stones (such as marbles and granites) is largely debated. Starting from the industrial revolution, continuous improvements of machineries led to a higher exploitation of this natural resource and to a more international interaction between markets. As a consequence, the environmental impact of the extraction and processing of stones has increased. Nevertheless, if compared with other building materials, ornamental stones are generally more durable, natural, and recyclable. From the scientific point of view, studies on stone life cycle sustainability have been carried out, but these are often partial or not very significant because of the high percentage of approximations and assumptions in calculations. This is due to the lack, in life cycle databases (e.g. Ecoinvent, Thinkstep, and ELCD), of datasets about the specific technologies employed in the stone production chain. For example, databases do not contain information about diamond wires, chains or explosives, materials commonly used in quarries and transformation plants. The project presented in this paper aims to populate the life cycle databases with specific data of specific stone processes. To this goal, the methodology follows the standardized approach of Life Cycle Assessment (LCA), according to the requirements of UNI 14040-14044 and to the International Reference Life Cycle Data System (ILCD) Handbook guidelines of the European Commission. The study analyses the processes of the entire production chain (from-cradle-to-gate system boundaries), including the extraction of benches, the cutting of blocks into slabs/tiles and the surface finishing. Primary data have been collected in Italian quarries and transformation plants which use technologies representative of the current state-of-the-art. Since the technologies vary according to the hardness of the stone, the case studies comprehend both soft stones (marbles) and hard stones (gneiss). In particular, data about energy, materials and emissions were collected in marble basins of Carrara and in Beola and Serizzo basins located in the province of Verbano Cusio Ossola. Data were then elaborated through an appropriate software to build a life cycle model. The model was realized setting free parameters that allow an easy adaptation to specific productions. Through this model, the study aims to boost the direct participation of stone companies and encourage the use of LCA tool to assess and improve the stone sector environmental sustainability. At the same time, the realization of accurate Life Cycle Inventory data aims at making available, to researchers and stone experts, ILCD compliant datasets of the most significant processes and technologies related to the ornamental stone sector.

Keywords: life cycle assessment, LCA datasets, ornamental stone, stone environmental impact

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20842 Effects of High-Intensity Interval Training versus Traditional Rehabilitation Exercises on Functional Outcomes in Patients with Knee Osteoarthritis: A Randomized Controlled Trial

Authors: Ahmed Torad

Abstract:

Background: Knee osteoarthritis (OA) is a prevalent musculoskeletal condition characterized by pain and functional impairment. While various rehabilitation approaches have been employed, the effectiveness of high-intensity interval training (HIIT) compared to traditional rehabilitation exercises remains unclear. Objective: This randomized controlled trial aimed to compare the effects of HIIT and traditional rehabilitation exercises on pain reduction, functional improvement, and quality of life in individuals with knee OA. Methods: A total of 120 participants diagnosed with knee OA were randomly allocated into two groups: the HIIT group (n=60) and the traditional rehabilitation group (n=60). The HIIT group participated in a 12-week supervised program consisting of high-intensity interval exercises, while the traditional rehabilitation group followed a conventional physiotherapy regimen. Outcome measures included visual analog scale (VAS) pain scores, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the Short Form-36 Health Survey (SF-36) at baseline and after the intervention period. Results: Both groups showed significant improvements in pain scores, functional outcomes (WOMAC), and quality of life (SF-36) after 12 weeks of intervention. However, the HIIT group demonstrated superior pain reduction (p<0.001), functional improvement (p<0.001), and physical health-related quality of life (p=0.002) compared to the traditional rehabilitation group. No significant differences were observed in mental health-related quality of life between the two groups. Conclusion: High-intensity interval training appears to be a more effective rehabilitation approach than traditional exercises for individuals with knee osteoarthritis, resulting in greater pain reduction, improved function, and enhanced physical health-related quality of life. These findings suggest that HIIT may represent a promising intervention strategy for managing knee OA and enhancing the overall well-being of affected individuals.

Keywords: knee osteoarthritis, high-intensity interval training, traditional rehabilitation exercises, randomized controlled trial, pain reduction, functional improvement, quality of life

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20841 A Composite Beam Element Based on Global-Local Superposition Theory for Prediction of Delamination in Composite Laminates

Authors: Charles Mota Possatti Júnior, André Schwanz de Lima, Maurício Vicente Donadon, Alfredo Rocha de Faria

Abstract:

An interlaminar damage model is combined with a beam element formulation based on global-local superposition to assess delamination in composite laminates. The variations in the mechanical properties in the laminate, generated by the presence of delamination, are calculated as a function of the displacements in the interface layers. The global-local superposition of displacement fields ensures the zig-zag behaviour of stresses and displacement, and the number of degrees of freedom (DOFs) is independent of the number of layers. The displacements and stresses are calculated as a function of DOFs commonly used in traditional beam elements. Finally, the finite element(FE) formulation is extended to handle cases of different thicknesses, and then the FE model predictions are compared with results obtained from analytical solutions and commercial finite element codes.

Keywords: delamination, global-local superposition theory, single beam element, zig-zag, interlaminar damage model

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20840 The Functional-Engineered Product-Service System Model: An Extensive Review towards a Unified Approach

Authors: Nicolas Haber

Abstract:

The study addresses the design process of integrated product-service offerings as a measure of answering environmental sustainability concerns by replacing stand-alone physical artefacts with comprehensive solutions relying on functional results rather than conventional product sales. However, views regarding this transformation are dissimilar and differentiated: The study discusses the importance and requirements of product-service systems before analysing the theoretical studies accomplished in the extent of their design and development processes. Based on this, a framework, built on a design science approach, is proposed, where the distinct approaches from the literature are merged towards a unified structure serving as a generic methodology to designing product-service systems. Each stage of this model is then developed to present a holistic design proposal called the Functional Engineered Product-Service System (FEPSS) model. Product-service systems are portrayed as customisable solutions tailored to specific settings and defined circumstances. Moreover, the approaches adopted to guide the design process are diversified. A thorough analysis of the design strategies and development processes however, allowed the extraction of a design backbone, valid to varied situations and contexts whether they are product-oriented, use-oriented or result-oriented. The goal is to guide manufacturers towards an eased adoption of these integrated offerings, given their inherited environmental benefits, by proposing a robust all-purpose design process.

Keywords: functional product, integrated product-service offerings, product-service systems, sustainable design

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20839 An Intelligent Prediction Method for Annular Pressure Driven by Mechanism and Data

Authors: Zhaopeng Zhu, Xianzhi Song, Gensheng Li, Shuo Zhu, Shiming Duan, Xuezhe Yao

Abstract:

Accurate calculation of wellbore pressure is of great significance to prevent wellbore risk during drilling. The traditional mechanism model needs a lot of iterative solving procedures in the calculation process, which reduces the calculation efficiency and is difficult to meet the demand of dynamic control of wellbore pressure. In recent years, many scholars have introduced artificial intelligence algorithms into wellbore pressure calculation, which significantly improves the calculation efficiency and accuracy of wellbore pressure. However, due to the ‘black box’ property of intelligent algorithm, the existing intelligent calculation model of wellbore pressure is difficult to play a role outside the scope of training data and overreacts to data noise, often resulting in abnormal calculation results. In this study, the multi-phase flow mechanism is embedded into the objective function of the neural network model as a constraint condition, and an intelligent prediction model of wellbore pressure under the constraint condition is established based on more than 400,000 sets of pressure measurement while drilling (MPD) data. The constraint of the multi-phase flow mechanism makes the prediction results of the neural network model more consistent with the distribution law of wellbore pressure, which overcomes the black-box attribute of the neural network model to some extent. The main performance is that the accuracy of the independent test data set is further improved, and the abnormal calculation values basically disappear. This method is a prediction method driven by MPD data and multi-phase flow mechanism, and it is the main way to predict wellbore pressure accurately and efficiently in the future.

Keywords: multiphase flow mechanism, pressure while drilling data, wellbore pressure, mechanism constraints, combined drive

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20838 Service Business Model Canvas: A Boundary Object Operating as a Business Development Tool

Authors: Taru Hakanen, Mervi Murtonen

Abstract:

This study aims to increase understanding of the transition of business models in servitization. The significance of service in all business has increased dramatically during the past decades. Service-dominant logic (SDL) describes this change in the economy and questions the goods-dominant logic on which business has primarily been based in the past. A business model canvas is one of the most cited and used tools in defining end developing business models. The starting point of this paper lies in the notion that the traditional business model canvas is inherently goods-oriented and best suits for product-based business. However, the basic differences between goods and services necessitate changes in business model representations when proceeding in servitization. Therefore, new knowledge is needed on how the conception of business model and the business model canvas as its representation should be altered in servitized firms in order to better serve business developers and inter-firm co-creation. That is to say, compared to products, services are intangible and they are co-produced between the supplier and the customer. Value is always co-created in interaction between a supplier and a customer, and customer experience primarily depends on how well the interaction succeeds between the actors. The role of service experience is even stronger in service business compared to product business, as services are co-produced with the customer. This paper provides business model developers with a service business model canvas, which takes into account the intangible, interactive, and relational nature of service. The study employs a design science approach that contributes to theory development via design artifacts. This study utilizes qualitative data gathered in workshops with ten companies from various industries. In particular, key differences between Goods-dominant logic (GDL) and SDL-based business models are identified when an industrial firm proceeds in servitization. As the result of the study, an updated version of the business model canvas is provided based on service-dominant logic. The service business model canvas ensures a stronger customer focus and includes aspects salient for services, such as interaction between companies, service co-production, and customer experience. It can be used for the analysis and development of a current service business model of a company or for designing a new business model. It facilitates customer-focused new service design and service development. It aids in the identification of development needs, and facilitates the creation of a common view of the business model. Therefore, the service business model canvas can be regarded as a boundary object, which facilitates the creation of a common understanding of the business model between several actors involved. The study contributes to the business model and service business development disciplines by providing a managerial tool for practitioners in service development. It also provides research insight into how servitization challenges companies’ business models.

Keywords: boundary object, business model canvas, managerial tool, service-dominant logic

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20837 Nano Liquid Thin Film Flow over an Unsteady Stretching Sheet

Authors: Prashant G. Metri

Abstract:

A numerical model is developed to study nano liquid film flow over an unsteady stretching sheet in the presence of hydromagnetic have been investigated. Similarity transformations are used to convert unsteady boundary layer equations to a system of non-linear ordinary differential equations. The resulting non-linear ordinary differential equations are solved numerically using Runge-Kutta-Fehlberg and Newton-Raphson schemes. A relationship between film thickness β and the unsteadiness parameter S is found, the effect of unsteadiness parameter S, and the hydromagnetic parameter S, on the velocity and temperature distributions are presented. The present analysis shows that the combined effect of magnetic field and viscous dissipation has a significant influence in controlling the dynamics of the considered problem. Comparison with known results for certain particular cases is in excellent agreement.

Keywords: boundary layer flow, nanoliquid, thin film, unsteady stretching sheet

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20836 Ethno-Botanical of Seaweeds and Sea Grass in Eastern Indonesia

Authors: Siegfried Berhimpon, Jein Dangeubun, Sandra Baulu, Rene Ch. Kepel

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In Indonesia, macro-alga is known as seaweeds or rumput laut and sea grass or lamun, and have been used as vegetables and medicine since long time ago. This studies have been done, to collect data about utilization of seaweed and sea grass as food or medicine in Eastern Indonesia. Six regencies in two provinces have been chosen as sampling areas i.e. South-East Maluku, West-East Maluku, and Aru in province of Maluku; and Sangihe, Sitaro, and Minahasa in province of North Sulawesi. The results shown that in the pass, seaweeds and sea grass have been widely used as food and medicine, and there are similarity between one area and other areas in species and in the way to prepare or to cook the food. Ten species of alga and 2 species of sea grass were consumed as vegetables and desert, and one species of sea grass was used for traditional medicine. Nowadays, because of easier to get terrestrial vegetables, the people in the coastal area rarely consumed marine vegetables, and if there are no attempt to promote and to socialize the custom, the habits trend to disappear. Environmental degradation was another caused has been identified. Seaweed contained high content of Iodine and dietary fiber, therefore, this food can overcomes the problem of iodine deficiency, and to supply an exotic high-fiber foods. In addition, by consuming seaweeds, marine culture industry will be developed, especially in the number of species seaweeds to be cultivated.

Keywords: ethno-botany, seaweed, sea grass, exotic food

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20835 The Estimation of Bird Diversity Loss and Gain as an Impact of Oil Palm Plantation: Study Case in KJNP Estate Riau Province

Authors: Yanto Santosa, Catharina Yudea

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The rapid growth of oil palm industry in Indonesia raised many negative accusations from various parties, who said that oil palm plantation is damaging the environment and biodiversity, including birds. Since research on oil palm plantation impacts on bird diversity is still limited, this study needs to be developed in order to gain further learning and understanding. Data on bird diversity were collected in March 2018 in KJNP Estate, Riau Province using strip transect method on five different land cover types (young, intermediate, and old growth of oil palm plantation, high conservation value area, and crops field or the baseline). The observations were conducted simultaneously, with three repetitions. The result shows that the baseline has 19 species of birds and land cover after the oil palm plantation has 39 species. HCV (high conservation value) area has the highest increase in diversity value. Oil palm plantation has changed the composition of bird species. The highest similarity index is shown by young growth oil palm land cover with total score 0.65, meanwhile the lowest similarity index with total score 0.43 is shown by HCV area. Overall, the existence of oil palm plantation made a positive impact by increasing bird species diversity, with total 23 species gained and 3 species lost.

Keywords: bird diversity, crops field, impact of oil palm plantation, KJNP estate

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20834 Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion

Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

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Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: basketball, deep learning, feature extraction, single-camera, tracking

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20833 Isolation of a Bacterial Community with High Removal Efficiencies of the Insecticide Bendiocarb

Authors: Eusebio A. Jiménez-Arévalo, Deifilia Ahuatzi-Chacón, Juvencio Galíndez-Mayer, Cleotilde Juárez-Ramírez, Nora Ruiz-Ordaz

Abstract:

Bendiocarb is a known toxic xenobiotic that presents acute and chronic risks for freshwater invertebrates and estuarine and marine biota; thus, the treatment of water contaminated with the insecticide is of concern. In this paper, a bacterial community with the capacity to grow in bendiocarb as its sole carbon and nitrogen source was isolated by enrichment techniques in batch culture, from samples of a composting plant located in the northeast of Mexico City. Eight cultivable bacteria were isolated from the microbial community, by PCR amplification of 16 rDNA; Pseudoxanthomonas spadix (NC_016147.2, 98%), Ochrobacterium anthropi (NC_009668.1, 97%), Staphylococcus capitis (NZ_CP007601.1, 99%), Bosea thiooxidans. (NZ_LMAR01000067.1, 99%), Pseudomonas denitrificans. (NC_020829.1, 99%), Agromyces sp. (NZ_LMKQ01000001.1, 98%), Bacillus thuringiensis. (NC_022873.1, 97%), Pseudomonas alkylphenolia (NZ_CP009048.1, 98%). NCBI accession numbers and percentage of similarity are indicated in parentheses. These bacteria were regarded as the isolated species for having the best similarity matches. The ability to degrade bendiocarb by the immobilized bacterial community in a packed bed biofilm reactor, using as support volcanic stone fragments (tezontle), was evaluated. The reactor system was operated in batch using mineral salts medium and 30 mg/L of bendiocarb as carbon and nitrogen source. With this system, an overall removal efficiency (ηbend) rounding 90%, was reached.

Keywords: bendiocarb, biodegradation, biofilm reactor, carbamate insecticide

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20832 Effect of Heating Rate on Microstructural Developments in Cold Heading Quality Steel Used for Automotive Applications

Authors: Shahid Hussain Abro, F. Mufadi, A. Boodi

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Microstructural study and phase transformation in steels is a basic and important step during the design of structural steel. There are huge efforts and study has been done so far on phase transformations, due to so many steel grades available commercially the phase development in steel has different consequences. In the present work an effort has been made to study the effect of heating rate on microstructural features of cold heading quality steel. The SEM, optical microscopy, and heat treatment techniques have been applied to observe the microstructural features in the experimental steel. It was observed that heating rate has the strong influence on phase transformation of CHQ steel under investigation. Heating rate increases the austenite formation kinetics with respect to holding time, and this austenite has been transformed to martensite upon cooling. Heating rate also plays a vital role on nucleation sites of austenite formation in the experimental steel.

Keywords: CHQ steel, austenite formation, heating rate, nucleation

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20831 Sorting Maize Haploids from Hybrids Using Single-Kernel Near-Infrared Spectroscopy

Authors: Paul R Armstrong

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Doubled haploids (DHs) have become an important breeding tool for creating maize inbred lines, although several bottlenecks in the DH production process limit wider development, application, and adoption of the technique. DH kernels are typically sorted manually and represent about 10% of the seeds in a much larger pool where the remaining 90% are hybrid siblings. This introduces time constraints on DH production and manual sorting is often not accurate. Automated sorting based on the chemical composition of the kernel can be effective, but devices, namely NMR, have not achieved the sorting speed to be a cost-effective replacement to manual sorting. This study evaluated a single kernel near-infrared reflectance spectroscopy (skNIR) platform to accurately identify DH kernels based on oil content. The skNIR platform is a higher-throughput device, approximately 3 seeds/s, that uses spectra to predict oil content of each kernel from maize crosses intentionally developed to create larger than normal oil differences, 1.5%-2%, between DH and hybrid kernels. Spectra from the skNIR were used to construct a partial least squares regression (PLS) model for oil and for a categorical reference model of 1 (DH kernel) or 2 (hybrid kernel) and then used to sort several crosses to evaluate performance. Two approaches were used for sorting. The first used a general PLS model developed from all crosses to predict oil content and then used for sorting each induction cross, the second was the development of a specific model from a single induction cross where approximately fifty DH and one hundred hybrid kernels used. This second approach used a categorical reference value of 1 and 2, instead of oil content, for the PLS model and kernels selected for the calibration set were manually referenced based on traditional commercial methods using coloration of the tip cap and germ areas. The generalized PLS oil model statistics were R2 = 0.94 and RMSE = .93% for kernels spanning an oil content of 2.7% to 19.3%. Sorting by this model resulted in extracting 55% to 85% of haploid kernels from the four induction crosses. Using the second method of generating a model for each cross yielded model statistics ranging from R2s = 0.96 to 0.98 and RMSEs from 0.08 to 0.10. Sorting in this case resulted in 100% correct classification but required models that were cross. In summary, the first generalized model oil method could be used to sort a significant number of kernels from a kernel pool but was not close to the accuracy of developing a sorting model from a single cross. The penalty for the second method is that a PLS model would need to be developed for each individual cross. In conclusion both methods could find useful application in the sorting of DH from hybrid kernels.

Keywords: NIR, haploids, maize, sorting

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20830 AI/ML Atmospheric Parameters Retrieval Using the “Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN)”

Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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20829 Privacy Preserving Data Publishing Based on Sensitivity in Context of Big Data Using Hive

Authors: P. Srinivasa Rao, K. Venkatesh Sharma, G. Sadhya Devi, V. Nagesh

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Privacy Preserving Data Publication is the main concern in present days because the data being published through the internet has been increasing day by day. This huge amount of data was named as Big Data by its size. This project deals the privacy preservation in the context of Big Data using a data warehousing solution called hive. We implemented Nearest Similarity Based Clustering (NSB) with Bottom-up generalization to achieve (v,l)-anonymity. (v,l)-Anonymity deals with the sensitivity vulnerabilities and ensures the individual privacy. We also calculate the sensitivity levels by simple comparison method using the index values, by classifying the different levels of sensitivity. The experiments were carried out on the hive environment to verify the efficiency of algorithms with Big Data. This framework also supports the execution of existing algorithms without any changes. The model in the paper outperforms than existing models.

Keywords: sensitivity, sensitive level, clustering, Privacy Preserving Data Publication (PPDP), bottom-up generalization, Big Data

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20828 From Abraham to Average Man: Game Theoretic Analysis of Divine Social Relationships

Authors: Elizabeth Latham

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Billions of people worldwide profess some feeling of psychological or spiritual connection with the divine. The majority of them attribute this personal connection to the God of the Christian Bible. The objective of this research was to discover what could be known about the exact social nature of these relationships and to see if they mimic the interactions recounted in the bible; if a worldwide majority believes that the Christian Bible is a true account of God’s interactions with mankind, it is reasonable to assume that the interactions between God and the aforementioned people would be similar to the ones in the bible. This analysis required the employment of an unusual method of biblical analysis: Game Theory. Because the research focused on documented social interaction between God and man in scripture, it was important to go beyond text-analysis methods. We used stories from the New Revised Standard Version of the bible to set up “games” using economics-style matrices featuring each player’s motivations and possible courses of action, modeled after interactions in the Old and New Testaments between the Judeo-Christian God and some mortal person. We examined all relevant interactions for the objectives held by each party and their strategies for obtaining them. These findings were then compared to similar “games” created based on interviews with people subscribing to different levels of Christianity who ranged from barely-practicing to clergymen. The range was broad so as to look for a correlation between scriptural knowledge and game-similarity to the bible. Each interview described a personal experience someone believed they had with God and matrices were developed to describe each one as social interaction: a “game” to be analyzed quantitively. The data showed that in most cases, the social features of God-man interactions in the modern lives of people were like those present in the “games” between God and man in the bible. This similarity was referred to in the study as “biblical faith” and it alone was a fascinating finding with many implications. The even more notable finding, however, was that the amount of game-similarity present did not correlate with the amount of scriptural knowledge. Each participant was also surveyed on family background, political stances, general education, scriptural knowledge, and those who had biblical faith were not necessarily the ones that knew the bible best. Instead, there was a high degree of correlation between biblical faith and family religious observance. It seems that to have a biblical psychological relationship with God, it is more important to have a religious family than to have studied scripture, a surprising insight with massive implications on the practice and preservation of religion.

Keywords: bible, Christianity, game theory, social psychology

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20827 The Effects of Stand Density, Standards and Species Composition on Biomass Production in Traditional Coppices

Authors: Marek Mejstřík, Radim Matula, Martin Šrámek

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Traditional coppices and coppice-with-standards were widely used throughout Europe and Asia for centuries but were largely abandoned in the second half of the 19th century, especially in central and northwestern Europe. In the last decades, there has been a renewed interest in traditional coppicing for nature conservation and most often, for rapid woody biomass production. However, there is little information on biomass productivity of traditional coppices and what affects it. Here, we focused on the effects of stand density, standards and tree species composition on sprout biomass production in newly restored coppices in the Czech Republic. We measured sprouts and calculated sprout biomass 7 years after the harvest from 2013 resprouting stumps in two 4 ha experimental plots. Each plot was divided into 64 subplots with different densities of standards and sprouting stumps. Total sprout biomass declined with increasing density of standards, but the effect of standards differed significantly among studied species. Whereas increasing density of standards decreased sprout biomass in Quercus petraea and Carpinus betulus, it did not affect sprout biomass productivity in Acer campestre and Tilia cordata. Sprout biomass on stand-level increased linearly with an increasing number of sprouting stumps and we observed no leveling of this relationship even in the highest densities of stumps. We also found a significant shift in tree species composition with the steeply declining relative abundance of Quercus in favor of other studied tree species.

Keywords: traditional coppice, coppice with standards, sprout biomass, forest management

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20826 Songwriting in the Postdigital Age: Using TikTok and Instagram as Online Informal Learning Technologies

Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

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In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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20825 The Analysis of Application of Green Bonds in New Energy Vehicles in China: From Evolutionary Game Theory

Authors: Jing Zhang

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Sustainable development in the new energy vehicles field is the requirement of the net zero aim. Green bonds are accepted as a practical financial tool to boost the transformation of relevant enterprises. The paper analyzes the interactions among governments, enterprises of new energy vehicles, and financial institutions by an evolutionary game theory model and offers advice to stakeholders in China. The decision-making subjects of green behavior are affected by experiences, interests, perception ability, and risk preference, so it is difficult for them to be completely rational. Based on the bounded rationality hypothesis, this paper applies prospect theory in the evolutionary game analysis framework and analyses the costs of government regulation of enterprises adopting green bonds. The influence of the perceived value of revenue prospect and the probability and risk transfer coefficient of the government's active regulation on the decision-making agent's strategy is verified by numerical simulation. Finally, according to the research conclusions, policy suggestions are given to promote green bonds.

Keywords: green bonds, new energy vehicles, sustainable development, evolutionary Game Theory model

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20824 Balancing and Synchronization Control of a Two Wheel Inverted Pendulum Vehicle

Authors: Shiuh-Jer Huang, Shin-Ham Lee, Sheam-Chyun Lin

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A two wheel inverted pendulum (TWIP) vehicle is built with two hub DC motors for motion control evaluation. Arduino Nano micro-processor is chosen as the control kernel for this electric test plant. Accelerometer and gyroscope sensors are built in to measure the tilt angle and angular velocity of the inverted pendulum vehicle. Since the TWIP has significantly hub motor dead zone and nonlinear system dynamics characteristics, the vehicle system is difficult to control by traditional model based controller. The intelligent model-free fuzzy sliding mode controller (FSMC) was employed as the main control algorithm. Then, intelligent controllers are designed for TWIP balance control, and two wheels synchronization control purposes.

Keywords: balance control, synchronization control, two-wheel inverted pendulum, TWIP

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20823 Visual Thing Recognition with Binary Scale-Invariant Feature Transform and Support Vector Machine Classifiers Using Color Information

Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

Abstract:

The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: color moments, visual thing recognition system, SIFT, color SIFT

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20822 Inferring Influenza Epidemics in the Presence of Stratified Immunity

Authors: Hsiang-Yu Yuan, Marc Baguelin, Kin O. Kwok, Nimalan Arinaminpathy, Edwin Leeuwen, Steven Riley

Abstract:

Traditional syndromic surveillance for influenza has substantial public health value in characterizing epidemics. Because the relationship between syndromic incidence and the true infection events can vary from one population to another and from one year to another, recent studies rely on combining serological test results with syndromic data from traditional surveillance into epidemic models to make inference on epidemiological processes of influenza. However, despite the widespread availability of serological data, epidemic models have thus far not explicitly represented antibody titre levels and their correspondence with immunity. Most studies use dichotomized data with a threshold (Typically, a titre of 1:40 was used) to define individuals as likely recently infected and likely immune and further estimate the cumulative incidence. Underestimation of Influenza attack rate could be resulted from the dichotomized data. In order to improve the use of serosurveillance data, here, a refinement of the concept of the stratified immunity within an epidemic model for influenza transmission was proposed, such that all individual antibody titre levels were enumerated explicitly and mapped onto a variable scale of susceptibility in different age groups. Haemagglutination inhibition titres from 523 individuals and 465 individuals during pre- and post-pandemic phase of the 2009 pandemic in Hong Kong were collected. The model was fitted to serological data in age-structured population using Bayesian framework and was able to reproduce key features of the epidemics. The effects of age-specific antibody boosting and protection were explored in greater detail. RB was defined to be the effective reproductive number in the presence of stratified immunity and its temporal dynamics was compared to the traditional epidemic model using use dichotomized seropositivity data. Deviance Information Criterion (DIC) was used to measure the fitness of the model to serological data with different mechanisms of the serological response. The results demonstrated that the differential antibody response with age was present (ΔDIC = -7.0). The age-specific mixing patterns with children specific transmissibility, rather than pre-existing immunity, was most likely to explain the high serological attack rates in children and low serological attack rates in elderly (ΔDIC = -38.5). Our results suggested that the disease dynamics and herd immunity of a population could be described more accurately for influenza when the distribution of immunity was explicitly represented, rather than relying only on the dichotomous states 'susceptible' and 'immune' defined by the threshold titre (1:40) (ΔDIC = -11.5). During the outbreak, RB declined slowly from 1.22[1.16-1.28] in the first four months after 1st May. RB dropped rapidly below to 1 during September and October, which was consistent to the observed epidemic peak time in the late September. One of the most important challenges for infectious disease control is to monitor disease transmissibility in real time with statistics such as the effective reproduction number. Once early estimates of antibody boosting and protection are obtained, disease dynamics can be reconstructed, which are valuable for infectious disease prevention and control.

Keywords: effective reproductive number, epidemic model, influenza epidemic dynamics, stratified immunity

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20821 On the Study of All Waterloo Automaton Semilattices

Authors: Mikhail Abramyan, Boris Melnikov

Abstract:

The aim is to study the set of subsets of grids of the Waterloo automaton and the set of covering automata defined by the grid subsets. The study was carried out using the library for working with nondeterministic finite automata NFALib implemented by one of the authors (M. Abramyan) in C#. The results are regularities obtained when considering semilattices of covering automata for the Waterloo automaton. A complete description of the obtained semilattices from the point of view of equivalence of the covering automata to the original Waterloo automaton is given, the criterion of equivalence of the covering automaton to the Waterloo automaton in terms of properties of the subset of grids defining the covering automaton is formulated. The relevance of the subject area under consideration is due to the need to research a set of regular languages and, in particular, a description of their various subclasses. Also relevant are the problems that may arise in some subclasses. This will give, among other things, the possibility of describing new algorithms for the equivalent transformation of nondeterministic finite automata.

Keywords: nondeterministic finite automata, universal automaton, grid, covering automaton, equivalent transformation algorithms, the Waterloo automaton

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20820 LanE-change Path Planning of Autonomous Driving Using Model-Based Optimization, Deep Reinforcement Learning and 5G Vehicle-to-Vehicle Communications

Authors: William Li

Abstract:

Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

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20819 Redefinition of Village Landscape with Ruins-Taking Cunwei Village in Nanping City, Fujian Province as Example

Authors: Siyu Bu, Jie Wang, Yajing Jiang

Abstract:

Nowadays, villages still occupying 94.7% of the national territorial area (almost nine million square kilometers) of China. Some of them are meeting urbanization and grow as satellite; however, others are witnessing more and more citizens swarming into with nostalgia, seek enjoyment from the beautiful green countryside. In villages, new types of house come and we see billions of old houses lay unused, or even be dying at every second, which cause a lot of 'bad palaces', decadent and dangerous. In this context, there are lots of tries for gearing villages in China. This article deconstructs the traditional village house to excavate its’ landscape potential for future. By research in CunWei Village, Nanping City, Fujian Province, China, a method of reconstruction of old houses comes out: the wreckage will be a strong landscape, showing the great beauty of nature. It will be a better use of the old material as well as the space pattern. It was supposed to gain a juxtaposition of traditional village life and modern social life by offering possibilities of multiple event, replacing the bad space to attractive one by strengthen the old structures without destroy traditional patterns. Furthermore , this method acts as an exploring for building redefinition of village landscape that fit Chinese villages, using local nature resource and traditional construction logic.

Keywords: juxtaposition, replace, village, ruins

Procedia PDF Downloads 235
20818 The Return of the Witches: A Class That Motivates the Analysis of Gender Bias in Engineer

Authors: Veronica Botero, Karen Ortiz

Abstract:

The Faculty of Mines, of the National University of Colombia, Medellín Campus, is a faculty that has 136 years of history and represents one of the most important study centers in the country in the field of engineering and scientific research, as well as a reference at a global, national, and Latin American level in this matter. Despite being a faculty with so many years of history and having trained a large number of graduates under the traditional mechanistic and androcentric paradigm, which reproduces the logic of the traditional scientific method and the differentiated and severe look between subject-object of research among other binarisms, has also been the place where professors and students have become aware of the need to transform this paradigm into engineering, and focus on the sustainability of diversity and the well-being of the natural and social systems that inhabit the territories and has opened possibilities for the implementation of classes that address feminist pedagogical theories and practices. The class: The return of the witches, is an initiative that constitutes an important training exercise that provides students with the study of feminisms, the importance of closing gender gaps and critical readings on the traditional paradigm of engineering. The objective of this article is to present a systematization of the experience of design, implementation and development of this elective class, describing the tensions that arose at the time when a subject of this style was created and proposed in the Department of Geosciences and Environment, from the Faculty of Mines in 2022; the reactions of the groups of students who have taken it and their perceptions and opinions about ecofeminism as proposals for critical analysis and practices in relation to the environment and, above all, how their readings of the world have changed after having studied this subject for a semester. The pedagogical journey and the feminist methodologies that have been designed and adjusted over two years of work will be explained based on the sharing of situated knowledge of the students and the two teachers who teach the course, who pose challenges to the dominant ideology in engineering since one of them is trained in human sciences and feminist studies and the other, although trained in civil engineering and geosciences, is a woman with diverse sexual orientation and is the first professor to have assumed the position of dean in the 135 years of history of the Faculty. The transformations in the life experience of the students are revealing since they affirm that the training process is forceful and powerful to outline a much more qualified and critical professional profile that contributes to the transformation of gender gaps in the country. This class is therefore a challenge in this Faculty of Engineering that still presents a dominant ideology on gender that has not been questioned or challenged before.

Keywords: feminisms, gender equality, gender bias, engineering for life Manifiesto.

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20817 Design of Two-Channel Quadrature Mirror Filter Banks Using a Transformation Approach

Authors: Ju-Hong Lee, Yi-Lin Shieh

Abstract:

Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.

Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm

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20816 Magneto-Hydrodynamic Mixed Convective Fluid Flow through Two Parallel Vertical Plates Channel with Hall, Chemical Reaction, and Thermal Radiation Effects

Authors: Okuyade Ighoroje Wilson Ata

Abstract:

Magneto-hydrodynamic mixed convective chemically reacting fluid flow through two parallel vertical plates channel with Hall, radiation, and chemical reaction effects are examined. The fluid is assumed to be chemically reactive, electrically conducting, magnetically susceptible, viscous, incompressible, and Newtonian; the plates are porous, electrically conductive, and heated to a high-temperature regime to generate thermal rays. The flow system is highly interactive, such that cross/double diffusion is present. The governing equations are partial differential equations transformed into ordinary differential equations using similarity transformation and solved by the method of Homotopy Perturbation. Expressions for the concentration, temperature, velocity, Nusselt number, Sherwood number, and Wall shear stress are obtained, computed, and presented graphically and tabularly. The analysis of results shows, amongst others, that an increase in the Raleigh number increases the main velocity and temperature but decreases the concentration. More so, an increase in chemical reaction rate increases the main velocity, temperature, rate of heat transfer from the terminal plate, the rate of mass transfer from the induced plate, and Wall shear stress on both the induced and terminal plates, decreasing the concentration, and the mass transfer rate from the terminal plate. Some of the obtained results are benchmarked with those of existing literature and are in consonance.

Keywords: chemical reaction, hall effect, magneto-hydrodynamic, radiation, vertical plates channel

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20815 Equivalent Circuit Model for the Eddy Current Damping with Frequency-Dependence

Authors: Zhiguo Shi, Cheng Ning Loong, Jiazeng Shan, Weichao Wu

Abstract:

This study proposes an equivalent circuit model to simulate the eddy current damping force with shaking table tests and finite element modeling. The model is firstly proposed and applied to a simple eddy current damper, which is modelled in ANSYS, indicating that the proposed model can simulate the eddy current damping force under different types of excitations. Then, a non-contact and friction-free eddy current damper is designed and tested, and the proposed model can reproduce the experimental observations. The excellent agreement between the simulated results and the experimental data validates the accuracy and reliability of the equivalent circuit model. Furthermore, a more complicated model is performed in ANSYS to verify the feasibility of the equivalent circuit model in complex eddy current damper, and the higher-order fractional model and viscous model are adopted for comparison.

Keywords: equivalent circuit model, eddy current damping, finite element model, shake table test

Procedia PDF Downloads 173