Search results for: settlement architecture cluster

Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom, Sawanath Treesathon

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As there are several countries which import agriculture product from Thailand, those countries demand Thailand to establish the traceability system. The traceability system is the tool to reduce the risk in the supply chain in a very effective way as it will help the stakeholder in the supply chain to identify the defect point which will reduce the cost of operation in the supply chain. This research is aimed to design the traceability system for Tubtimjun roseapple for exporting to China, and it is the qualitative research. The data was collected from the expert in the tuntimjun roseapple and fruit exporting industry, and the data was used to design the traceability system. The design of the tubtimjun roseapple traceability system was followed the theory of supply chain which starts from the upstream of the supply chain to the downstream of the supply chain to support the process and condition of the exporting which included the database designing, system architecture, user interface design and information technology of the traceability system.

Keywords: design information, technology system, traceability, tubtimjun roseapple

Procedia PDF Downloads 170

Authors: A. Rezazadeh, N. Omidvar, H. Eini-Zinab

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Food insecurity (FI) influences may result in poor physical and mental health outcomes. Minor ethnic group may experience higher level of FI, and this situation may be related with higher depression prevalence. The aim of this study was to determine the association of depression with food security status in major (Azeri) and minor (Kurdish) ethnicity living in Urmia, West Azerbaijan, north of Iran. In this cross-sectional study, 723 participants (427 women and 296 men) aged 20–64 years old, from two ethnic groups (445 Azeri and 278 Kurdish), were selected through a multi stage cluster systematic sampling. Depression rate was assessed by “Beck” short form questionnaire (validated in Iranians) through interviews. Household FI status (HFIS) was measured using adapted HFI access scale through face-to-face interviews at homes. Multinomial logistic regression was used to estimate odds ratios (OR) of depression across HFIS. Higher percent of Kurds had moderate and severe depression in comparison with Azeri group (73 [17.3%] vs. 86 [27.9%]). There were not any significant differences between the two ethnicities in mild depression. Also, of all the subjects, moderate-to-sever FI was more prevalent in Kurds (28.5%), compared to Azeri group (17.3%) [P < 0.01]. Kurdish ethnic group living in food security or mild FI households had lower chance to have symptom of severe depression in comparison to those with sever FI (OR=0.097; 95% CI: 0.02-0.47). However, there was no significant association between depression and HFI in Azeri group. Findings revealed that the severity of HFI was related with severity depression in minor studied ethnic groups. However, in Azeri ethnicity as a major group, other confounders may have influence on the relation with depression and FI, that were not studied in the present study.

Keywords: depression, ethnicity, food security status, Iran

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Authors: Francesca Scalisi, Cesare Sposito

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The building construction industry consumes a large amount of resources and energy, both during construction (embodied energy) and during the operational phase (operating energy). This paper presents a review of the literature on low carbon and low embodied energy materials in buildings. The embodied energy comprises the energy consumed during the extraction, processing, transportation, construction, and demolition of building materials. While designing a nearly zero energy building, it is necessary to choose and use materials, components, and technologies that allow to reduce the consumption of energy and also to reduce the emissions in the atmosphere during all the Life Cycle Assessment phases. The appropriate choice of building materials can contribute decisively to reduce the energy consumption of the building sector. The increasing worries for the environmental impact of construction materials are witnessed by a lot of studies. The mentioned worries have brought again the attention towards natural materials. The use of more sustainable construction materials and construction techniques represent a major contribution to the eco-efficiency of the construction industry and thus to a more sustainable development.

Keywords: embodied energy, embodied carbon, life cycle assessment, architecture, sustainability, material construction

Procedia PDF Downloads 343

Authors: Marriette Sakah, Christoph Kuhn, Samuel Gyamfi

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Global electricity demand of households in 2005 is estimated to double by 2025 and nearly double again in 2030. The residential sector promises considerable demand growth through infrastructural and equipment investments, the majority of which is projected to occur in developing countries. This lays bare the urgency for enhanced efficiency in all energy systems combined with exploitation of local potential for renewable energy systems. This study explores options for reducing energy consumption, particularly in residential buildings and providing robust, decentralized and renewable energy supply for African cities. The potential of energy efficiency measures and the potential of harnessing local resources for renewable energy supply are quantitatively assessed. The scale of research specifically addresses the city level, which is regulated by local authorities. Local authorities can actively promote the transition to a renewable-based energy supply system by promoting energy efficiency and the use of alternative renewable fuels in existing buildings, and particularly in planning and development of new settlement areas through the use of incentives, regulations, and demonstration projects. They can also support a more sustainable development by shaping local land use and development patterns in such ways that reduce per capita energy consumption and are benign to the environment. The subject of the current case study, Tema, is Ghana´s main industrial hub, a port city and home to 77,000 families. Residential buildings in Tema consumed 112 GWh of electricity in 2013 or 1.45 MWh per household. If average household electricity demand were to decline at an annual rate of just 2 %, by 2035 Tema would consume only 134 GWh of electricity despite an expected increase in the number of households by 84 %. The work is based on a ground survey of the city’s residential sector. The results show that efficient technologies and decentralized renewable energy systems have great potential for meeting the rapidly growing energy demand of cities in developing countries.

Keywords: energy efficiency, energy saving potential, renewable energy integration, residential buildings, urban Africa

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Authors: Marwa Ben Khalifa, Zeineb Ben Salem, Wissem Frikha

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The purpose of the present work is to study the consolidation behavior of highly compressible Tunis soft soil “TSS” by means of prefabricated vertical drains (PVD’s) associated to preloading based on laboratory and field investigations. In the first hand, the field performance of PVD’s on the layer of Tunis soft soil was analysed based on the case study of the construction of embankments of “Radès la Goulette” bridge project. PVD’s Geosynthetics drains types were installed with triangular grid pattern until 10 m depth associated with step-by-step surcharge. The monitoring of the soil settlement during preloading stage for Radès La Goulette Bridge project was provided by an instrumentation composed by various type of tassometer installed in the soil. The distribution of water pressure was monitored through piezocone penetration. In the second hand, a laboratory reduced tests are performed on TSS subjected also to preloading and improved with PVD's Mebradrain 88 (Mb88) type. A specific test apparatus was designed and manufactured to study the consolidation. Two series of consolidation tests were performed on TSS specimens. The first series included consolidation tests for soil improved by one central drain. In thesecond series, a triangular mesh of three geodrains was used. The evolution of degree of consolidation and measured settlements versus time derived from laboratory tests and field data were presented and discussed. The obtained results have shown that PVD’s have considerably accelerated the consolidation of Tunis soft soil by shortening the drainage path. The model with mesh of three drains gives results more comparative to field one. A longer consolidation time is observed for the cell improved by a single central drain. A comparison with theoretical analysis, basically that of Barron (1948) and Carillo (1942), was presented. It’s found that these theories overestimate the degree of consolidation in the presence of PVD.

Keywords: tunis soft soil, prefabricated vertical drains, acceleration of consolidation, dissipation of excess pore water pressures, radès bridge project, barron and carillo’s theories

Procedia PDF Downloads 127

Authors: Madushani Rodrigo, Banuka Athuraliya

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

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

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Authors: Sarita Agarwal, Deepika Delsa Dean

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Like the task of transferring photo images to artistic images, image-to-image translation aims to translate the data to the imitated data which belongs to the target domain. Neural Style Transfer and CycleGAN are two well-known deep learning architectures used for photo image-to-art image transfer. However, studies involving these two models concentrate on one-to-one domain translation, not one-to-multi domains translation. Our study tries to investigate deep learning architectures, which can be controlled to yield multiple artistic style translation only by adding a conditional vector. We have expanded CycleGAN and constructed Conditional CycleGAN for 5 kinds of categories translation. Our study found that the architecture inserting conditional vector into the middle layer of the Generator could output multiple artistic images.

Keywords: genetic counseling, FMR1 gene, fragile x-associated primary ovarian insufficiency, premutation

Procedia PDF Downloads 131

Authors: Chander Kant, Arun Kumar

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Biometric systems automatically recognize an individual based on his/her physiological and behavioral characteristics. There are also some traits like weight, age, height etc. that may not provide reliable user recognition because of there common and temporary nature. These traits are called soft bio metric traits. Although soft bio metric traits are lack of permanence to uniquely and reliably identify an individual, yet they provide some beneficial evidence about the user identity and may improve the system performance. Here in this paper, we have proposed an approach for integrating the soft bio metrics with fingerprint and face to improve the performance of personal authentication system. In our approach we have proposed a combined architecture of three different sensors to elevate the system performance. The approach includes, soft bio metrics, fingerprint and face traits. We have also proven the efficiency of proposed system regarding FAR (False Acceptance Ratio) and total response time, with the help of MUBI (Multimodal Bio metrics Integration) software.

Keywords: FAR, minutiae point, multimodal bio metrics, primary bio metric, soft bio metric

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Authors: Aneek Kuila, Yaron Paz

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MIP 177 LT and HT are two-phase transformable metal organic frameworks consisting of a Ti12O15 oxocluster and a tetracarboxylate ligand that exhibits robust chemical stability and improved photoactivity. LT to HT only shows the changes in dimensionality from 0D to 1D without any change in the overall chemical structure. In terms of chemical and photoactivity MIP 177 LT is found to perform better than the MIP 177HT. Step-scan Fourier transform absorption difference time-resolved spectroscopy has been used to collect mid-IR time-resolved infrared spectra of the transient electronic excited states of a nano-porous metal–organic framework MIP 177-LT and HT with 2.5 ns time resolution. Analyzing the time-resolved vibrational data after 355nm LASER excitation reveals the presence of the temporal changes of ν (O-Ti-O) of Ti-O metal cluster and ν (-COO) of the ligand concluding the fact that these moieties are the ultimate acceptors of the excited charges which are localized over those regions on the nanosecond timescale. A direct negative correlation between the differential absorbance (Δ Absorbance) reveals the charge transfer relation among these two moieties. A longer-lived transient signal up to 180ns for MIP 177 LT compared to the 100 ns of MIP 177 HT shows the extended lifetime of the reactive charges over the surface that exerts in their effectivity. An ultrafast change of bidentate to monodentate bridging in the -COO-Ti-O ligand-metal coordination environment was observed after the photoexcitation of MIP 177 LT which remains and lives with for seconds after photoexcitation is halted. This phenomenon is very unique to MIP 177 LT but not observed with HT. This in-situ change in the coordination denticity during the photoexcitation was not observed previously which can rationalize the reason behind the ability of MIP 177 LT to accumulate electrons during continuous photoexcitation leading to a superior photocatalytic activity.

Keywords: time resolved FTIR, metal organic framework, denticity, photoacatalysis

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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Authors: Radka Sefcu, Vaclava Antuskova, Ivana Turkova

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A growing market with modern artworks of a high price leads to the creation and selling of artwork counterfeits. Material analysis is an important part of the process of assessment of authenticity. Knowledge of materials and techniques used by original authors is also necessary. The contribution presents possibilities of non-invasive methods of structural analysis in research on paintings. It was proved that unambiguous identification of many art materials is feasible without sampling. The combination of Raman spectroscopy with FTIR-external reflection enabled the identification of pigments and binders on selected artworks of prominent Czech painters from the first half of the 20th century – Josef Čapek, Emil Filla, Václav Špála and Jan Zrzavý. Raman spectroscopy confirmed the presence of a wide range of white pigments - lead white, zinc white, titanium white, barium white and also Freeman's white as a special white pigment of painting. Good results were obtained for red, blue and most of the yellow areas. Identification of green pigments was often impossible due to strong fluorescence. Oil was confirmed as a binding medium on most of the analyzed artworks via FTIR - external reflection. Collected data present the valuable background for the determination of art materials characteristic for each painter (his palette) and its development over time. Obtained results will further serve as comparative material for the authentication of artworks. This work has been financially supported by the project of the Ministry of the Interior of the Czech Republic: The Development of a Strategic Cluster for Effective Instrumental Technological Methods of Forensic Authentication of Modern Artworks (VJ01010004).

Keywords: non-invasive analysis, Raman spectroscopy, FTIR-external reflection, forgeries

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Authors: Xiaohui Zhao, Shahan Mafuz

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Context-aware technologies provide system applications with the awareness of environmental conditions, customer behaviour, object movements, etc. Further, with such capability system applications can be smart to adapt intelligently their responses to the changing conditions. Concerning business operations, this promises businesses that their business processes can run more intelligently, adaptively and flexibly, and thereby either improve customer experience, enhance reliability of service delivery, or lower operational cost, to make the business more competitive and sustainable. Aiming at realizing such context-aware business process management, this paper firstly explores its potential benefit and then identifies some gaps between the current business process management support and the expected. In addition, some preliminary solutions are also discussed with context definition, rule-based process execution, run-time process evolution, etc. A framework is also presented to give a conceptual architecture of context-aware business process management system to guide system implementation.

Keywords: business process adaptation, business process evolution, business process modelling, and context awareness

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Authors: Muzammil Dar

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The confluence of trans-national interests and divergent approaches followed by multiple actors has surrounded the Indo-Pacific region with myriad of strategic complexes- Geo-Political, Geo-economic, and security. This paper has thus made a humble attempt to understand the Indo-Pacific strategic predicament from Asia-Pacific perspective. The portmanteau of Indo-Pacific strategic gamble has multiple actors from global powers to regional actors. On the indo-pacific waters, not only flow trade relations, but the tides of conflicts and controversies are striking these actors against each other. The alliance formation and infrastructure building has built-in threat perceptions from rivals vice-versa. The assertiveness of China as a reality and India’s ideological doctrine of peace and friendship, as well as American rebalancing against China, could be seen as clear and bright on the Indo-Pacific strategic portmanteau. ASEAN and Japan, too, have oscillating posturing in the strategic dilemma. The aim and objective of the paper are to sketch out the prospectus and prejudices of Indo-pacific strategic complex.

Keywords: Indo Pacific, Asia Pacific, security and growth for all in the region, SAGAR, ASEAN China

Procedia PDF Downloads 153

Authors: Raninder Kaur Dhillon, Mayur Jethwa, Hardeep Singh Rai

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Information technology has made a pivotal progress across disparate disciplines, one of which is AEC (Architecture, Engineering and Construction) industry. CAD is a form of computer-aided building modulation that architects, engineers and contractors use to create and view two- and three-dimensional models. The AEC industry also uses building information modeling (BIM), a newer computerized modeling system that can create four-dimensional models; this software can greatly increase productivity in the AEC industry. BIM models generate open source IFC (Industry Foundation Classes) files which aim for interoperability for exchanging information throughout the project lifecycle among various disciplines. The methods developed in previous studies require either an IFC schema or MVD and software applications, such as an IFC model server or a Building Information Modeling (BIM) authoring tool, to extract a partial or complete IFC instance model. This paper proposes an efficient algorithm for extracting a partial and total model from an Industry Foundation Classes (IFC) instance model without an IFC schema or a complete IFC model view definition (MVD).

Keywords: BIM, CAD, IFC, MVD

Procedia PDF Downloads 300

Authors: M. Mohan, J. P. Roise, G. P. Catts

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Despite living in an era where conservation zones are de-facto the central element in any sustainable wildlife management strategy, we still find ourselves grappling with several pareto-optimal situations regarding resource allocation and area distribution for the same. In this paper, a multi-objective decision making (MODM) model is presented to answer the question of whether or not we can establish mutual relationships between these contradicting objectives. For our study, we considered a Red-cockaded woodpecker (Picoides borealis) habitat conservation scenario in the coastal plain of North Carolina, USA. Red-cockaded woodpecker (RCW) is a non-migratory territorial bird that excavates cavities in living pine trees for roosting and nesting. The RCW groups nest in an aggregation of cavity trees called ‘cluster’ and for our model we use the number of clusters to be established as a measure of evaluating the size of conservation zone required. The case study is formulated as a linear programming problem and the objective function optimises the Red-cockaded woodpecker clusters, carbon retention rate, biofuel, public safety and Net Present Value (NPV) of the forest. We studied the variation of individual objectives with respect to the amount of area available and plotted a two dimensional dynamic graph after establishing interrelations between the objectives. We further explore the concept of interdependency by integrating the MODM model with GIS, and derive a raster file representing carbon distribution from the existing forest dataset. Model results demonstrate the applicability of interdependency from both linear and spatial perspectives, and suggest that this approach holds immense potential for enhancing environmental investment decision making in future.

Keywords: conservation, interdependency, multi-objective decision making, red-cockaded woodpecker

Procedia PDF Downloads 337

Authors: Atefeh Omidkhah Kharashtomi, Rasoul Hedayat Nejad, Saeed Bakhtiyari

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Circulation paths and indoor connection network of the building play an important role both in the daily operation of the building and during evacuation in emergency situations. The degree of legibility of the paths for navigation inside the building has a deep connection with the perceptive and cognitive system of human, and the way the surrounding environment is being perceived. Human perception of the space is based on the sensory systems in a three-dimensional environment, and non-linearly, so it is necessary to avoid reducing its representations in architectural design as a two-dimensional and linear issue. Today, the advances in the field of virtual reality (VR) technology have led to various applications, and architecture and building science can benefit greatly from these capabilities. Especially in cases where the design solution requires a detailed and complete understanding of the human perception of the environment and the behavioral response, special attention to VR technologies could be a priority. Way-finding in the indoor circulation network is a proper example for such application. Success in way-finding could be achieved if human perception of the route and the behavioral reaction have been considered in advance and reflected in the architectural design. This paper discusses the VR technology applications for the way-finding improvements in indoor engineering of the building. In a systematic review, with a database consisting of numerous studies, firstly, four categories for VR applications for circulation way-finding have been identified: 1) data collection of key parameters, 2) comparison of the effect of each parameter in virtual environment versus real world (in order to improve the design), 3) comparing experiment results in the application of different VR devices/ methods with each other or with the results of building simulation, and 4) training and planning. Since the costs of technical equipment and knowledge required to use VR tools lead to the limitation of its use for all design projects, priority buildings for the use of VR during design are introduced based on case-studies analysis. The results indicate that VR technology provides opportunities for designers to solve complex buildings design challenges in an effective and efficient manner. Then environmental parameters and the architecture of the circulation routes (indicators such as route configuration, topology, signs, structural and non-structural components, etc.) and the characteristics of each (metrics such as dimensions, proportions, color, transparency, texture, etc.) are classified for the VR way-finding experiments. Then, according to human behavior and reaction in the movement-related issues, the necessity of scenario-based and experiment design for using VR technology to improve the design and receive feedback from the test participants has been described. The parameters related to the scenario design are presented in a flowchart in the form of test design, data determination and interpretation, recording results, analysis, errors, validation and reporting. Also, the experiment environment design is discussed for equipment selection according to the scenario, parameters under study as well as creating the sense of illusion in the terms of place illusion, plausibility and illusion of body ownership.

Keywords: virtual reality (VR), way-finding, indoor, circulation, design

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Authors: Esther Yemisi Akinjiola

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Mathematics has been regarded as the backbone of science and technological development, without which no nation can achieve any sustainable growth and development. Mathematics is a useful tool to simplify science by quantification of phenomena; hence physics and chemistry cannot be done without Calculus and Statistics. Mathematics is used in physical science to calculate the measurement of objects and their characteristics, as well as to show the relationship between different functions and properties. Mathematics is the building block for everything in our daily lives, including the use of mobile devices, architecture design, ancient arts, engineering sports, and. among others. Therefore the study of Mathematics is made compulsory at primary, basic, and secondary school levels. Thus, this paper discusses the concepts of Mathematics, science, and their relationships. Also, it discusses Mathematics contents needed to study science-oriented courses such as physics education, chemistry education, and biology education in the tertiary institution. The paper concluded that without adequate knowledge of Mathematics, it will be difficult, if not impossible, for science education students to cope in their field of study.

Keywords: mathematical knowledge, prerequisite, science education, tertiary institution

Procedia PDF Downloads 91

Authors: Arun Prasad Jaganathan

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In today's dynamic industrial world, traditional task allocation methods often fall short in adapting to evolving operational conditions. This paper introduces an AI-enabled task assistance and management system designed to overcome the limitations of conventional approaches. By using artificial intelligence (AI) and machine learning (ML), the system intelligently interprets user instructions, analyzes tasks, and allocates resources based on real-time data and environmental factors. Additionally, geolocation tracking enables proactive identification of potential delays, ensuring timely interventions. With its transparent reporting mechanisms, the system provides stakeholders with clear insights into task progress, fostering accountability and informed decision-making. The paper presents a comprehensive overview of the system architecture, algorithm, and implementation, highlighting its potential to revolutionize task management across diverse industries.

Keywords: artificial intelligence, machine learning, task allocation, operational efficiency, resource optimization

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Authors: N. F. F. Ebecken, G. C. Pereira

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Although networks provide a powerful approach to the study of a wide variety of ecological systems, their formulation usually does not include various types of interactions, interactions that vary in space and time, and interconnected systems such as networks. The emerging field of 'multilayer networks' provides a natural framework for extending ecological systems analysis to include these multiple layers of complexity as it specifically allows for differentiation and modeling of intralayer and interlayer connectivity. The structure provides a set of concepts and tools that can be adapted and applied to the ecology, facilitating research in high dimensionality, heterogeneous systems in nature. Here, ecological multilayer networks are formally defined based on a review of prior and related approaches, illustrates their application and potential with existing data analyzes, and discusses limitations, challenges, and future applications. The integration of multilayer network theory into ecology offers a largely untapped potential to further address ecological complexity, to finally provide new theoretical and empirical insights into the architecture and dynamics of ecological systems.

Keywords: ecological networks, multilayered networks, sea ecology, Brazilian Coastal Area

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Authors: Chuluundorj Begz

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This paper presents the dynamic, psycho-cognitive approach to study of human verbal thinking on the basis of typologically different languages /as a Mongolian, English and Russian/. Topological equivalence in verbal communication serves as a basis of Universality of mental structures and therefore deep structures. Mechanism of verbal thinking consisted at the deep level of basic concepts, rules for integration and classification, neural networks of vocabulary. In neuro cognitive study of language, neural architecture and neuro psychological mechanism of verbal cognition are basis of a vector-based modeling. Verbal perception and interpretation of the infinite set of meanings and propositions in mental continuum can be modeled by applying tensor methods. Euclidean and non-Euclidean spaces are applied for a description of human semantic vocabulary and high order structures.

Keywords: Euclidean spaces, isomorphism and homomorphism, mental lexicon, mental mapping, semantic memory, verbal cognition, vector space

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Authors: Khadijat Olabisi Abdulwahab, Mohammad Azad Malik, Paul O'Brien, Grigore Timco, Floriana Tuna

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The synthesis of spinel ferrite nanoparticles with a narrow size distribution is very crucial in their numerous applications including information storage, hyperthermia treatment, drug delivery, contrast agent in magnetic resonance imaging, catalysis, sensors, and environmental remediation. Ferrites have the general formula MFe₂O₄ (M = Fe, Co, Mn, Ni, Zn e.t.c) and possess remarkable electrical and magnetic properties which depend on the cations, method of preparation, size and their site occupancies. To the best of our knowledge, there are no reports on the use of a single source precursor to synthesise quaternary ferrite nanoparticles. Here in, we demonstrated the use of trimetallic iron pivalate cluster [CrCoFeO(O₂CᵗBu)₆(HO₂CᵗBu)₃] as a single source precursor to synthesise monodisperse cobalt chromium ferrite (FeCoCrO₄) nanoparticles by the hot injection thermolysis method. The precursor was thermolysed in oleylamine, oleic acid, with diphenyl ether as solvent at 260 °C. The effect of reaction time on the stoichiometry, phases or morphology of the nanoparticles was studied. The p-XRD patterns of the nanoparticles obtained after one hour was pure phase of cubic iron cobalt chromium ferrite (FeCoCrO₄). TEM showed that a more monodispersed spherical ferrite nanoparticles were obtained after one hour. Magnetic measurements revealed that the ferrite particles are superparamagnetic at room temperature. The nanoparticles were characterised by Powder X-ray Diffraction (p-XRD), Transmission Electron Microscopy (TEM), Energy Dispersive Spectroscopy (EDS) and Super Conducting Quantum Interference Device (SQUID).

Keywords: cobalt chromium ferrite, colloidal, hot injection thermolysis, monodisperse, reaction time, single source precursor, quaternary ferrite nanoparticles

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Authors: Yo-Sheng Lin, Jen-How Lee, Chien-Chin Wang

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A 60-GHz receiver front-end using standard 90-nm CMOS technology is reported. The receiver front-end comprises a wideband low-noise amplifier (LNA), and a double-balanced Gilbert cell mixer with a current-reused RF single-to-differential (STD) converter, an LO Marchand balun and a baseband amplifier. The receiver front-end consumes 34.4 mW and achieves LO-RF isolation of 60.7 dB, LO-IF isolation of 45.3 dB and RF-IF isolation of 41.9 dB at RF of 60 GHz and LO of 59.9 GHz. At IF of 0.1 GHz, the receiver front-end achieves maximum conversion gain (CG) of 26.1 dB at RF of 64 GHz and CG of 25.2 dB at RF of 60 GHz. The corresponding 3-dB bandwidth of RF is 7.3 GHz (58.4 GHz to 65.7 GHz). The measured minimum noise figure was 5.6 dB at 64 GHz, one of the best results ever reported for a 60 GHz CMOS receiver front-end. In addition, the measured input 1-dB compression point and input third-order inter-modulation point are -33.1 dBm and -23.3 dBm, respectively, at 60 GHz. These results demonstrate the proposed receiver front-end architecture is very promising for 60 GHz direct-conversion transceiver applications.

Keywords: CMOS, 60 GHz, direct-conversion transceiver, LNA, down-conversion mixer, marchand balun, current-reused

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Authors: D. Calogine, O. Chau, S. Dotti, O. Ramiarinjanahary, P. Rasoavonjy, F. Tovondahiniriko

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Mafate is a natural circus in the north-western part of Reunion Island, without an electrical grid and road network. A micro-grid concept is being experimented in this area, composed of a photovoltaic production combined with electrochemical batteries, in order to meet the local population for self-consumption of electricity demands. This work develops a discrete model as well as a stochastic model in order to reach an optimal equilibrium between production and consumptions for a cluster of houses. The management of the energy power leads to a large linearized programming system, where the time interval of interest is 24 hours The experimental data are solar production, storage energy, and the parameters of the different electrical devices and batteries. The unknown variables to evaluate are the consumptions of the various electrical services, the energy drawn from and stored in the batteries, and the inhabitants’ planning wishes. The objective is to fit the solar production to the electrical consumption of the inhabitants, with an optimal use of the energies in the batteries by satisfying as widely as possible the users' planning requirements. In the discrete model, the different parameters and solutions of the linear programming system are deterministic scalars. Whereas in the stochastic approach, the data parameters and the linear programming solutions become random variables, then the distributions of which could be imposed or established by estimation from samples of real observations or from samples of optimal discrete equilibrium solutions.

Keywords: photovoltaic production, power consumption, battery storage resources, random variables, stochastic modeling, estimations of probability distributions, mixed integer linear programming, smart micro-grid, self-consumption of electricity.

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Authors: Praveena Sridhar, Nihar Devathi, Parikshit Chakraborty

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As the software product changes versions across releases, there are changes to the API’s and features and the upgrades become necessary. Hence, it becomes imperative to get the impact of upgrading the dependent components. This tool finds out API changes across two versions and their impact on other API’s followed by execution of the automated regression suites relevant to updates and their impacted areas. This tool has 4 layer architecture, each layer with its own unique pre-assigned capability which it does and sends the required information to next layer. This are the 4 layers. 1) Comparator: Compares the two versions of API. 2) Analyzer: Analyses the API doc and gives the modified class and its dependencies along with implemented interface details. 3) Impact Filter: Find the impact of the modified class on the other API methods. 4) Auto Executer: Based on the output given by Impact Filter, Executor will run the API regression Suite. Tool reads the java doc and extracts the required information of classes, interfaces and enumerations. The extracted information is saved into a data structure which shows the class details and its dependencies along with interfaces and enumerations that are listed in the java doc.

Keywords: automation impact regression, java doc, executor, analyzer, layers

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Authors: Khader S. Al-Aidmat, Venus W. Samawi

Abstract:

Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

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Authors: Kim Young-Jin, Kim Byung-Kon

Abstract:

Although more efforts to expand the application of BIM (Building Information Modeling) technologies have be pursued in recent years than ever, it’s true that there have been various challenges in doing so, including a lack or absence of relevant institutions, lots of costs required to build BIM-related infrastructure, incompatible processes, etc. This, in turn, has led to a more prolonged delay in the expansion of their application than expected at an early stage. Especially, attempts to save costs for building BIM-related infrastructure and provide various BIM services compatible with domestic processes include studies to link between BIM and cloud computing technologies. Also in this study, the author attempted to develop a cloud BIM service operation model through analyzing the level of BIM applications for the construction sector and deriving relevant service areas, and find how to link BIM services to the cloud operation model, as through archiving BIM data and creating a revenue structure so that the BIM services may grow spontaneously, considering a demand for cloud resources.

Keywords: construction IT, BIM (building information modeling), cloud computing, BIM service based cloud computing

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Authors: Zuzana Fišerová, Marie Paseková

Abstract:

Debt relief (also labelled personal bankruptcy) is a bankruptcy settlement method which was implemented into Czech legislation by the Insolvency Act (Act No. 182/2006 Coll. on Insolvency and its Resolution) on 1 January 2008. The need to implement the institute of personal bankruptcy arose from the excessive over-indebtedness of many inhabitants of the Czech Republic after the crisis that arose around 2008 and 2009. The contribution analyses the development in the manner in which households approach personal bankruptcy and assesses and surveys the differences between indebtedness among men and women. The first section analyses the development in numbers of filed personal bankruptcy petitions and the successfulness thereof; it likewise analyses the impact of other economic influences (regional differences, unemployment etc.). The differences between debtors in dependency to gender are also surveyed. A survey of insolvency proceedings for 664 persons whose insolvency proceedings were commenced in 2008 was conducted, whilst the data were acquired from the publicly accessible insolvency register. The hypothesis on the equality of the average debt level of men and women was tested when comparing indebtedness in dependency to debtor gender. At a significance level of 0.05, the test confirmed that the mean value of debt level for women is lower than the mean value of debt level for men. Through analysis of further results, it was found that the average level of debt among women was CZK 537 thousand, while the average level of creditor satisfaction reached 46.2%. Men in the monitored sample had an average level of reported receivables of CZK 652 thousand, satisfaction of their creditors reached 58.8%. The main changes in the institute of personal bankruptcy are then evaluated in the closing discussion, and the impacts of these changes for households are assessed. The development of legislation in the Czech Republic and practice are shifting towards broader usage of personal bankruptcy, especially insofar as it can now also be used by entrepreneurs. Furthermore, the amendment of the Insolvency Act has enabled married couples to apply for joint debt relief, which has improved the position of the marriage partner with lower income and who would not get permission for debt relief on his/her own (mostly women are at issue). In current practice, the condition of adequate income is also solved by the fact that another person (usually a family member) undertakes to donate a certain monthly sum throughout the duration of the debt relief. Personal bankruptcy can thus be completed also by individuals to whom it would previously have been denied by the court.

Keywords: debtor, households, insolvency act, over-indebtedness, personal bankruptcy

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Authors: Zaki Ahmad Khan, Jamshed Siddiqui, Abdus Samad

Abstract:

The Scheduling and mapping of tasks on a set of processors is considered as a critical problem in parallel and distributed computing system. This paper deals with the problem of dynamic scheduling on a special type of multiprocessor architecture known as Linear Crossed Cube (LCQ) network. This proposed multiprocessor is a hybrid network which combines the features of both linear type of architectures as well as cube based architectures. Two standard dynamic scheduling schemes namely Minimum Distance Scheduling (MDS) and Two Round Scheduling (TRS) schemes are implemented on the LCQ network. Parallel tasks are mapped and the imbalance of load is evaluated on different set of processors in LCQ network. The simulations results are evaluated and effort is made by means of through analysis of the results to obtain the best solution for the given network in term of load imbalance left and execution time. The other performance matrices like speedup and efficiency are also evaluated with the given dynamic algorithms.

Keywords: dynamic algorithm, load imbalance, mapping, task scheduling

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Authors: Pavan K. Rallabandi, Kailash C. Patidar

Abstract:

In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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Authors: Eduardo Remirez, Luis Moreno

Abstract:

The rapid growth of the private satellite launchers sector is leading the space race. Hence, with the privatization of the sector, all the companies are racing for a more efficient and reliant way to set satellites in orbit. Having detected the current needs for power management in the launcher vehicle industry, the Modular Power Bus is proposed as a technology to revolutionize power management in current and future Launcher Vehicles. The MPBus Project is committed to develop a new power bus architecture combining ejectable batteries with the main bus through intelligent nodes. These nodes are able to communicate between them and a battery controller using an improved, data over DC line technology, expected to reduce the total weight in two main areas: improving the use of the batteries and reducing the total weight due to harness. This would result in less weight for each launch stage increasing the operational satellite payload and reducing cost. These features make the system suitable for a number of launchers.

Keywords: modular power bus, Launcher vehicles, ejectable batteries, intelligent nodes

Procedia PDF Downloads 480