Search results for: sensor network design
14948 Roughness Discrimination Using Bioinspired Tactile Sensors
Authors: Zhengkun Yi
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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination
Procedia PDF Downloads 31214947 Nelder-Mead Parametric Optimization of Elastic Metamaterials with Artificial Neural Network Surrogate Model
Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao
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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization
Procedia PDF Downloads 12814946 Classification of Generative Adversarial Network Generated Multivariate Time Series Data Featuring Transformer-Based Deep Learning Architecture
Authors: Thrivikraman Aswathi, S. Advaith
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As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.Keywords: GAN, transformer, classification, multivariate time series
Procedia PDF Downloads 13014945 Colors and Interiority - A Study on the Relationship of Colors and Interior Spaces
Authors: Mahwish Ghulam Rasool
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The design of a space is a complex process that involves multiple stages, from conceptualization, identifying design problems to understanding the context, materiality, and functionality of the space. Out of all the design elements, color is one of the most dominant and expressive factors that affect the spatial dynamics of the interior space. Color affects aesthetic comfort in space and has a lasting impact on human perception and psychology. Using color as a tool for creating spatial experiences is a new paradigm. Color semantics in spaces are not only used for surface treatment or aesthetics, but it also has more powerful functional characteristics. As interior spaces are evolving and becoming experiential with each decade, designers are looking for new processes to enhance the spatial and experiential quality of interior spaces. The relationship between color and interior typologies is a relatively new paradigm. This paper discusses the role of colors in interior spaces from various perspectives, exploring their impact on the formation of interior typologies and the use of colors in space design. The paper analyzes interior typologies worldwide, from residential to commercial interior spaces, where color semantics plays a prominent role in the design. The paper also emphasizes the design process and the creation of design language, unveiling the possibilities of applying colors in interior spaces that can be in harmony with the building context, space functionality, or in opposition to the existing building envelope or environment. The paper aims to contribute to the field of interior design education and practices. By using experimental and various research methodologies for investigation, it aims to fill the gap in the literature regarding color semantics and the relationship between interior typologies.Keywords: color psychology, color semantics, interior environments, interior typologies
Procedia PDF Downloads 8714944 A Methodological Approach to the Betterment of the Retail Store's Interior Design: The Example of Dereboyu Street, Nicosia
Authors: Nazanin Reza Nejad, Kamil Guley
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Shopping is one of the most entertaining activities of daily life. In parallel to this, the successful settings of the stores impress the customers and made it more appealing for the users. The design of the atmosphere is the language of the interior space, and this design directly affects users’ emotions and perceptions. One of the goals of interior design is to increase the quality of the designed space. A well-designed venue satisfies the user and ensures happiness and safety. Thus, customers are turned into frequent users of the store. Spaces without the right designs negatively influence the user. The accurate interior design of the stores becomes crucial at this point. This study aims to act as a guideline for the betterment of the interior design of a newly designed or already existing clothing store located on the shopping streets of the cities. In light of the relevant literature review, the most important point in interior store design is the design and ambiance factors and how these factors are used in the interior space of the stores. Within the scope of this study, 27 clothing stores located on Dereboyu, the largest shopping street in Nicosia, the capital of North Cyprus, were examined. The examined stores were grouped as brand stores and non-brand stores which sell products from different production sites. The observation regarding the interiors of the selected stores was analyzed through qualitative and quantitative research methods. The arrangements of the sub-functions in the stores were analyzed through various reading methods over the plan schemes and recorded images. The sub-functions of all examined stores are compared against the ambiance and design factors in the literature, and results were interpreted accordingly. At the end of the study, the differences among stores that belong to a brand with an identity and stores which have not yet established an identity were identified and compared. The results of the comparisons were used to offer implications for the betterment of the interior design on a future or already existing store on the street. Thus, the study was concluded to be a guideline for people interested in interior store design.Keywords: atmosphere, ambiance factors, clothing store, identity, interior design
Procedia PDF Downloads 20214943 Topology Optimization of Structures with Web-Openings
Authors: D. K. Lee, S. M. Shin, J. H. Lee
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Topology optimization technique utilizes constant element densities as design parameters. Finally, optimal distribution contours of the material densities between voids (0) and solids (1) in design domain represent the determination of topology. It means that regions with element density values become occupied by solids in design domain, while there are only void phases in regions where no density values exist. Therefore the void regions of topology optimization results provide design information to decide appropriate depositions of web-opening in structure. Contrary to the basic objective of the topology optimization technique which is to obtain optimal topology of structures, this present study proposes a new idea that topology optimization results can be also utilized for decision of proper web-opening’s position. Numerical examples of linear elastostatic structures demonstrate efficiency of methodological design processes using topology optimization in order to determinate the proper deposition of web-openings.Keywords: topology optimization, web-opening, structure, element density, material
Procedia PDF Downloads 47214942 Using Dynamic Bayesian Networks to Characterize and Predict Job Placement
Authors: Xupin Zhang, Maria Caterina Bramati, Enrest Fokoue
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Understanding the career placement of graduates from the university is crucial for both the qualities of education and ultimate satisfaction of students. In this research, we adapt the capabilities of dynamic Bayesian networks to characterize and predict students’ job placement using data from various universities. We also provide elements of the estimation of the indicator (score) of the strength of the network. The research focuses on overall findings as well as specific student groups including international and STEM students and their insight on the career path and what changes need to be made. The derived Bayesian network has the potential to be used as a tool for simulating the career path for students and ultimately helps universities in both academic advising and career counseling.Keywords: dynamic bayesian networks, indicator estimation, job placement, social networks
Procedia PDF Downloads 37914941 The Effect of Mathematical Modeling of Damping on the Seismic Energy Demands
Authors: Selamawit Dires, Solomon Tesfamariam, Thomas Tannert
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Modern earthquake engineering and design encompass performance-based design philosophy. The main objective in performance-based design is to achieve a system performing precisely to meet the design objectives so to reduce unintended seismic risks and associated losses. Energy-based earthquake-resistant design is one of the design methodologies that can be implemented in performance-based earthquake engineering. In energy-based design, the seismic demand is usually described as the ratio of the hysteretic to input energy. Once the hysteretic energy is known as a percentage of the input energy, it is distributed among energy-dissipating components of a structure. The hysteretic to input energy ratio is highly dependent on the inherent damping of a structural system. In numerical analysis, damping can be modeled as stiffness-proportional, mass-proportional, or a linear combination of stiffness and mass. In this study, the effect of mathematical modeling of damping on the estimation of seismic energy demands is investigated by considering elastic-perfectly-plastic single-degree-of-freedom systems representing short to long period structures. Furthermore, the seismicity of Vancouver, Canada, is used in the nonlinear time history analysis. According to the preliminary results, the input energy demand is not sensitive to the type of damping models deployed. Hence, consistent results are achieved regardless of the damping models utilized in the numerical analyses. On the other hand, the hysteretic to input energy ratios vary significantly for the different damping models.Keywords: damping, energy-based seismic design, hysteretic energy, input energy
Procedia PDF Downloads 16814940 Task Based Functional Connectivity within Reward Network in Food Image Viewing Paradigm Using Functional MRI
Authors: Preetham Shankapal, Jill King, Kori Murray, Corby Martin, Paula Giselman, Jason Hicks, Owen Carmicheal
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Activation of reward and satiety networks in the brain while processing palatable food cues, as well as functional connectivity during rest has been studied using functional Magnetic Resonance Imaging of the brain in various obesity phenotypes. However, functional connectivity within the reward and satiety network during food cue processing is understudied. 14 obese individuals underwent two fMRI scans during viewing of Macronutrient Picture System images. Each scan included two blocks of images of High Sugar/High Fat (HSHF), High Carbohydrate/High Fat (HCHF), Low Sugar/Low Fat (LSLF) and also non-food images. Seed voxels within seven food reward relevant ROIs: Insula, putamen and cingulate, precentral, parahippocampal, medial frontal and superior temporal gyri were isolated based on a prior meta-analysis. Beta series correlation for task-related functional connectivity between these seed voxels and the rest of the brain was computed. Voxel-level differences in functional connectivity were calculated between: first and the second scan; individuals who saw novel (N=7) vs. Repeated (N=7) images in the second scan; and between the HC/HF, HSHF blocks vs LSLF and non-food blocks. Computations and analysis showed that during food image viewing, reward network ROIs showed significant functional connectivity with each other and with other regions responsible for attentional and motor control, including inferior parietal lobe and precentral gyrus. These functional connectivity values were heightened among individuals who viewed novel HS/HF images in the second scan. In the second scan session, functional connectivity was reduced within the reward network but increased within attention, memory and recognition regions, suggesting habituation to reward properties and increased recollection of previously viewed images. In conclusion it can be inferred that Functional Connectivity within reward network and between reward and other brain regions, varies by important experimental conditions during food photography viewing, including habituation to shown foods.Keywords: fMRI, functional connectivity, task-based, beta series correlation
Procedia PDF Downloads 27014939 Cultural Reflection within Contemporary Residential Interior in India
Authors: Icy Vinod Sanghvi
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In the light of rising modernism within the residential design industry, a significant growth of the western concepts of maximalism or minimalism is observed in the Indian housings. Although dynamism in design styles is natural due to the constant emergence of new innovations, it is imperative that local houses reflect cultural identity. This paper highlights the importance of ‘Indian Modernism’, and how to incorporate the same in residential design. Thus, helping the Indian culture to flourish and become a significant part of housing design in the future. A literature review was conducted to analyze and derive effective methods to build cultural value whilst catering to the urban and contemporary design industry. Alongside, a questionnaire survey was conducted to observe how the local houses are designed and to understand the preferences of people with regards to the design styles incorporated in their homes. In addition, their opinions on the excessive use of contemporary styles in home designs was recorded. The results of the same provided a better understanding of the local audience, their demands, and their willingness to adapt to contemporary designs. Studying color, materials, ornamentation, symbolism, detail, and structure offers an in-depth understanding of the essence of traditional Indian homes. These variables further provided effective solutions for design ideation and mockups for efficient traditional yet contemporary spaces. Design interventions like these can build a revolutionary set of practices that involve creating a balance between contemporary and traditional styles. The emergence of this synergy will not only make contemporary homes communicative but also allow India to compete within the global residential architecture industry with a strong foundation of its rich heritage.Keywords: balance, contemporary design, cultural identity, Indian modernism
Procedia PDF Downloads 13914938 Off Design Modelling of 650MW Combined Cycle Gas Turbine Power Plant Integrated with a Retrofitted Inlet Fogging System
Authors: Osarobo Omorogieva Ighodaro, Josephus Otejere
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This paper contains the modelling and simulation of GT13E2 combined cycle gas turbine with the aid of the software EBSILON PROFESSIONAL. The design mode was modeled using guaranteed performance data from the power plant, in the off design, temperature variation of ambient air and fogging (spray water at inlet to compressor) was simulated. The fogging was simulated under two different modes; constant fuel consumption and constant turbine exhaust temperature .The model results were validated using actual operating data by applying error percentage analysis. The validation results obtained ranged from -0.0038% to 0% in design condition while the results varied from -0.9202% to 10.24% The model shows that fogging decreases compressor inlet temperature which in turn decreases the power required to drive the compressor hence improving the simple cycle efficiency and hence increasing power generated.Keywords: inlet fogging, off design, combined cycle, modelling
Procedia PDF Downloads 3914937 An Ergonomic Handle Design for Instruments in Laparoscopic Surgery
Authors: Ramon Sancibrian, Carlos Redondo-Figuero, Maria C. Gutierrez-Diez, Esther G. Sarabia, Maria A. Benito-Gonzalez, Jose C. Manuel-Palazuelos
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In this paper, the design and evaluation of a handle for laparoscopic surgery is presented. The design of the handle is based on ergonomic principles and tries to avoid awkward postures for surgeons. The handle combines the so-called power-grip and accurate-grip in order to provide strength and accuracy in the performance of surgery. The handle is tested using both objective and subjective approaches. The objective approach uses motion capture techniques to obtain the angles of forearm, arm, wrist and hand. The muscular effort is obtained with electromyography electrodes. On the other hand, a subjective survey has been carried out using questionnaires. Results confirm that the handle is preferred by the majority of the surgeons.Keywords: laparoscopic surgery, ergonomics, mechanical design, biomechanics
Procedia PDF Downloads 50214936 Optimizing Design Parameters for Efficient Saturated Steam Production in Fire Tube Boilers: A Cost-Effective Approach
Authors: Yoftahe Nigussie Worku
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This research focuses on advancing fire tube boiler technology by systematically optimizing design parameters to achieve efficient saturated steam production. The main objective is to design a high-performance boiler with a production capacity of 2000kg/h at a 12-bar design pressure while minimizing costs. The methodology employs iterative analysis, utilizing relevant formulas, and considers material selection and production methods. The study successfully results in a boiler operating at 85.25% efficiency, with a fuel consumption rate of 140.37kg/hr and a heat output of 1610kW. Theoretical importance lies in balancing efficiency, safety considerations, and cost minimization. The research addresses key questions on parameter optimization, material choices, and safety-efficiency balance, contributing valuable insights to fire tube boiler design.Keywords: safety consideration, efficiency, production methods, material selection
Procedia PDF Downloads 6614935 Non-Linear Dynamic Analyses of Grouted Pile-Sleeve Connection
Authors: Mogens Saberi
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The focus of this article is to present the experience gained from the design of a grouted pile-sleeve connection and to present simple design expressions which can be used in the preliminary design phase of such connections. The grout pile-sleeve connection serves as a connection between an offshore jacket foundation and pre-installed piles located in the seabed. The jacket foundation supports a wind turbine generator resulting in significant dynamic loads on the connection. The connection is designed with shear keys in order to optimize the overall design but little experience is currently available in the use of shear keys in such connections. It is found that the consequence of introducing shear keys in the design is a very complex stress distribution which requires special attention due to significant fatigue loads. An optimal geometrical shape of the shear keys is introduced in order to avoid large stress concentration factors and a relatively easy fabrication. The connection is analysed in ANSYS Mechanical where the grout is modelled by a non-linear material model which allows for cracking of the grout material and captures the elastic-plastic behaviour of the grout material. Special types of finite elements are used in the interface between the pile sleeve and the grout material to model the slip surface between the grout material and the steel. Based on the performed finite element modelling simple design expressions are introduced.Keywords: fatigue design, non-linear finite element modelling, structural dynamics, simple design expressions
Procedia PDF Downloads 38414934 A Multi-Output Network with U-Net Enhanced Class Activation Map and Robust Classification Performance for Medical Imaging Analysis
Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin
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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis
Procedia PDF Downloads 20314933 Unsupervised Neural Architecture for Saliency Detection
Authors: Natalia Efremova, Sergey Tarasenko
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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment
Procedia PDF Downloads 34814932 Synthesis of Highly Sensitive Molecular Imprinted Sensor for Selective Determination of Doxycycline in Honey Samples
Authors: Nadia El Alami El Hassani, Soukaina Motia, Benachir Bouchikhi, Nezha El Bari
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Doxycycline (DXy) is a cycline antibiotic, most frequently prescribed to treat bacterial infections in veterinary medicine. However, its broad antimicrobial activity and low cost, lead to an intensive use, which can seriously affect human health. Therefore, its spread in the food products has to be monitored. The scope of this work was to synthetize a sensitive and very selective molecularly imprinted polymer (MIP) for DXy detection in honey samples. Firstly, the synthesis of this biosensor was performed by casting a layer of carboxylate polyvinyl chloride (PVC-COOH) on the working surface of a gold screen-printed electrode (Au-SPE) in order to bind covalently the analyte under mild conditions. Secondly, DXy as a template molecule was bounded to the activated carboxylic groups, and the formation of MIP was performed by a biocompatible polymer by the mean of polyacrylamide matrix. Then, DXy was detected by measurements of differential pulse voltammetry (DPV). A non-imprinted polymer (NIP) prepared in the same conditions and without the use of template molecule was also performed. We have noticed that the elaborated biosensor exhibits a high sensitivity and a linear behavior between the regenerated current and the logarithmic concentrations of DXy from 0.1 pg.mL−1 to 1000 pg.mL−1. This technic was successfully applied to determine DXy residues in honey samples with a limit of detection (LOD) of 0.1 pg.mL−1 and an excellent selectivity when compared to the results of oxytetracycline (OXy) as analogous interfering compound. The proposed method is cheap, sensitive, selective, simple, and is applied successfully to detect DXy in honey with the recoveries of 87% and 95%. Considering these advantages, this system provides a further perspective for food quality control in industrial fields.Keywords: doxycycline, electrochemical sensor, food control, gold nanoparticles, honey, molecular imprinted polymer
Procedia PDF Downloads 31614931 Network and Sentiment Analysis of U.S. Congressional Tweets
Authors: Chaitanya Kanakamedala, Hansa Pradhan, Carter Gilbert
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Social media platforms, such as Twitter, are excellent datasets for understanding human interactions and sentiments. This report explores social dynamics among US Congressional members through a network analysis applied to a dataset of tweets spanning 2008 to 2017 from the ’US Congressional Tweets Dataset’. In this report, we preform network analysis where connections between users (edges) are established based on a similarity threshold: two tweets are connected if the tweets they post are similar. By utilizing the Natural Language Toolkit (NLTK) and NetworkX, we quantified tweet similarity and constructed a graph comprising various interconnected components. Each component represents a cluster of users with closely aligned content. We then preform sentiment analysis on each cluster to explore the prevalent emotions and opinions within these groups. Our findings reveal that despite the initial expectation of distinct ideological divisions typically aligning with party lines, the analysis exposed a high degree of topical convergence across tweets from different political affiliations. The analysis preformed in this report not only highlights the potential of social media as a tool for political communication but also suggests a complex layer of interaction that transcends traditional partisan boundaries, reflecting a complicated landscape of politics in the digital age.Keywords: natural language processing, sentiment analysis, centrality analysis, topic modeling
Procedia PDF Downloads 3314930 Design of Two-Channel Quadrature Mirror Filter Banks Using a Transformation Approach
Authors: Ju-Hong Lee, Yi-Lin Shieh
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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
Procedia PDF Downloads 22514929 Participatory Air Quality Monitoring in African Cities: Empowering Communities, Enhancing Accountability, and Ensuring Sustainable Environments
Authors: Wabinyai Fidel Raja, Gideon Lubisa
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Air pollution is becoming a growing concern in Africa due to rapid industrialization and urbanization, leading to implications for public health and the environment. Establishing a comprehensive air quality monitoring network is crucial to combat this issue. However, conventional methods of monitoring are insufficient in African cities due to the high cost of setup and maintenance. To address this, low-cost sensors (LCS) can be deployed in various urban areas through the use of participatory air quality network siting (PAQNS). PAQNS involves stakeholders from the community, local government, and private sector working together to determine the most appropriate locations for air quality monitoring stations. This approach improves the accuracy and representativeness of air quality monitoring data, engages and empowers community members, and reflects the actual exposure of the population. Implementing PAQNS in African cities can build trust, promote accountability, and increase transparency in the air quality management process. However, challenges to implementing this approach must be addressed. Nonetheless, improving air quality is essential for protecting public health and promoting a sustainable environment. Implementing participatory and data-informed air quality monitoring can take a significant step toward achieving these important goals in African cities and beyond.Keywords: low-cost sensors, participatory air quality network siting, air pollution, air quality management
Procedia PDF Downloads 9214928 Improved Safety Science: Utilizing a Design Hierarchy
Authors: Ulrica Pettersson
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Collection of information on incidents is regularly done through pre-printed incident report forms. These tend to be incomplete and frequently lack essential information. ne consequence is that reports with inadequate information, that do not fulfil analysts’ requirements, are transferred into the analysis process. To improve an incident reporting form, theory in design science, witness psychology and interview and questionnaire research has been used. Previously three experiments have been conducted to evaluate the form and shown significant improved results. The form has proved to capture knowledge, regardless of the incidents’ character or context. The aim in this paper is to describe how design science, in more detail a design hierarchy can be used to construct a collection form for improvements in safety science.
Keywords: data collection, design science, incident reports, safety science
Procedia PDF Downloads 22314927 Exploration of an Environmentally Friendly Form of City Development Combined with a River: An Example of a Four-Dimensional Analysis Based on the Expansion of the City of Jinan across the Yellow River
Authors: Zhaocheng Shang
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In order to study the topic of cities crossing rivers, a Four-Dimensional Analysis Method consisting of timeline, X-axis, Y-axis, and Z-axis is proposed. Policies, plans, and their implications are summarized and researched along with the timeline. The X-axis is the direction which is parallel to the river. The research area was chosen because of its important connection function. It is proposed that more surface water network should be built because of the ecological orientation of the research area. And the analysis of groundwater makes it for sure that the proposal is feasible. After the blue water network is settled, the green landscape network which is surrounded by it could be planned. The direction which is transversal to the river (Y-axis) should run through the transportation axis so that the urban texture could stretch in an ecological way. Therefore, it is suggested that the work of the planning bureau and river bureau should be coordinated. The Z-axis research is on the section view of the river, especially on the Yellow River’s special feature of being a perched river. Based on water control safety demands, river parks could be constructed on the embankment buffer zone, whereas many kinds of ornamental trees could be used to build the buffer zone. City Crossing River is a typical case where we make use of landscaping to build a symbiotic relationship between the urban landscape architecture and the environment. The local environment should be respected in the process of city expansion. The planning order of "Benefit- Flood Control Safety" should be replaced by "Flood Control Safety - Landscape Architecture- People - Benefit".Keywords: blue-green landscape network, city crossing river, four-dimensional analysis method, planning order
Procedia PDF Downloads 15914926 Research of Applicable Ground Reinforcement Method in Double-Deck Tunnel Junction
Authors: SKhan Park, Seok Jin Lee, Jong Sun Kim, Jun Ho Lee, Bong Chan Kim
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Because of the large economic losses caused by traffic congestion in metropolitan areas, various studies on the underground network design and construction techniques has been performed various studies in the developed countries. In Korea, it has performed a study to develop a versatile double-deck of deep tunnel model. This paper is an introduction to develop a ground reinforcement method to enable the safe tunnel construction in the weakened pillar section like as junction of tunnel. Applicable ground reinforcement method in the weakened section is proposed and it is expected to verify the method by the field application tests.Keywords: double-deck tunnel, ground reinforcement, tunnel construction, weakened pillar section
Procedia PDF Downloads 40914925 Review: Wavelet New Tool for Path Loss Prediction
Authors: Danladi Ali, Abdullahi Mukaila
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In this work, GSM signal strength (power) was monitored in an indoor environment. Samples of the GSM signal strength was measured on mobile equipment (ME). One-dimensional multilevel wavelet is used to predict the fading phenomenon of the GSM signal measured and neural network clustering to determine the average power received in the study area. The wavelet prediction revealed that the GSM signal is attenuated due to the fast fading phenomenon which fades about 7 times faster than the radio wavelength while the neural network clustering determined that -75dBm appeared more frequently followed by -85dBm. The work revealed that significant part of the signal measured is dominated by weak signal and the signal followed more of Rayleigh than Gaussian distribution. This confirmed the wavelet prediction.Keywords: decomposition, clustering, propagation, model, wavelet, signal strength and spectral efficiency
Procedia PDF Downloads 44814924 An Improved Cuckoo Search Algorithm for Voltage Stability Enhancement in Power Transmission Networks
Authors: Reza Sirjani, Nobosse Tafem Bolan
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Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability
Procedia PDF Downloads 55214923 Improving the Gain of a Multiband Antenna by Adding an Artificial Magnetic Conductor Metasurface
Authors: Amira Bousselmi
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This article presents a PIFA antenna designed for geolocation applications (GNSS) operating on 1.278 GHz, 2.8 GHz, 5.7 GHz and 10 GHz. To improve the performance of the antenna, an artificial magnetic conductor structure (AMC) was used. Adding the antenna with AMC resulted in a measured gain of 4.78 dBi. The results of simulations and measurements are presented. CST Microwave Studio is used to design and compare antenna performance. An antenna design methodology, design and characterization of the AMC surface are described as well as the simulated and measured performances of the AMC antenna are then discussed. Finally, in Section V, there is a conclusion.Keywords: antenna multiband, global navigation system, AMC, Galeleo
Procedia PDF Downloads 7714922 Land Cover Remote Sensing Classification Advanced Neural Networks Supervised Learning
Authors: Eiman Kattan
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This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.Keywords: conventional neural network, remote sensing, land cover, land use
Procedia PDF Downloads 37014921 Optimization of Media for Enhanced Fermentative Production of Mycophenolic Acid by Penicillium brevicompactum
Authors: Shraddha Digole, Swarali Hingse, Uday Annapure
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Mycophenolic acid (MPA) is an immunosuppressant; produced by Penicillium Sp. Box-Behnken statistical experimental design was employed to optimize the condition of Penicillium brevicompactum NRRL 2011 for mycophenolic acid (MPA) production. Initially optimization of various physicochemical parameters and media components was carried out using one factor at a time approach and significant factors were screened by Taguchi L-16 orthogonal array design. Taguchi design indicated that glucose, KH2PO4 and MgSO4 had significant effect on MPA production. These variables were selected for further optimization studies using Box-Behnken design. Optimised fermentation condition, glucose (60 g/L), glycine (28 g/L), L-leucine (1.5g/L), KH2PO4 (3g/L), MgSO4.7H2O (1.5g/L), increased the production of MPA from 170 mg/L to 1032.54 mg/L. Analysis of variance (ANOVA) showed a high value of coefficient of determination R2 (0.9965), indicating a good agreement between experimental and predicted values and proves validity of the statistical model.Keywords: Box-Behnken design, fermentation, mycophenolic acid, Penicillium brevicompactum
Procedia PDF Downloads 45214920 Rapid Design Approach for Electric Long-Range Drones
Authors: Adrian Sauer, Lorenz Einberger, Florian Hilpert
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The advancements and technical innovations in the field of electric unmanned aviation over the past years opened the third dimension in areas like surveillance, logistics, and mobility for a wide range of private and commercial users. Researchers and companies are faced with the task of integrating their technology into airborne platforms. Especially start-ups and researchers require unmanned aerial vehicles (UAV), which can be quickly developed for specific use cases without spending significant time and money. This paper shows a design approach for the rapid development of a lightweight automatic separate-lift-thrust (SLT) electric vertical take-off and landing (eVTOL) UAV prototype, which is able to fulfill basic transportation as well as surveillance missions. The design approach does not require expensive or time-consuming design loop software. Thereby developers can easily understand, adapt, and adjust the presented method for their own project. The approach is mainly focused on crucial design aspects such as aerofoil, tuning, and powertrain.Keywords: aerofoil, drones, rapid prototyping, powertrain
Procedia PDF Downloads 7114919 Exploring De-Fi through 3 Case Studies: Transparency, Social Impact, and Regulation
Authors: Dhaksha Vivekanandan
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DeFi is a network that avoids reliance on financial intermediaries through its peer-to-peer financial network. DeFi operates outside of government control; hence it is important for us to understand its impacts. This study employs a literature review to understand DeFi and its emergence, as well as its implications on transparency, social impact, and regulation. Further, 3 case studies are analysed within the context of these categories. DeFi’s provision of increased transparency poses environmental and storage costs and can lead to user privacy being endangered. DeFi allows for the provision of entrepreneurial incentives and protection against monetary censorship and capital control. Despite DeFi's transparency issues and volatility costs, it has huge potential to reduce poverty; however, regulation surrounding DeFi still requires further tightening by governments.Keywords: DeFi, transparency, regulation, social impact
Procedia PDF Downloads 84