Search results for: multi sensor image fusion

Authors: Nashwa Elyamany

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In visual cultures, namely that of the United States, media representations are such influential and pervasive reflections of societal norms and expectations to the extent that they impact the manner in which both genders view themselves. Health and fitness magazines fall within the realm of visual culture. Since the main goal of communication is to ensure proper dissemination of information in order for the target audience to grasp the intended messages, it becomes imperative that magazine publishers, editors, advertisers and image producers use different modes of communication within their reach to convey messages to their readers and viewers. A rapid waxing flow of multimodality floods popular discourse, particularly health and fitness magazine cover pages. The use of well-crafted cover lines and visual images is imbued with agendas, consumerist ideologies and properties capable of effectively conveying implicit and explicit meaning to potential readers and viewers. In essence, the primary goal of this thesis is to interrogate the multi-semiotic operations and manifestations of hegemonic masculinity and femininity in male and female body culture, particularly on the cover pages of the twin American magazines Men's Health and Women's Health using corpora that spanned from 2011 to the mid of 2016. The researcher explores the semiotic resources that contribute to shaping and legitimizing a new form of postmodern, consumerist, gendered discourse that positions the reader-viewer ideologically. Methodologically, the researcher carries out analysis on the macro and micro levels. On the macro level, the researcher takes on a critical stance to illuminate the ideological nature of the multimodal ensemble of the cover pages, and, on the micro level, seeks to put forward new theoretical and methodological routes through which the semiotic choices well invested on the media texts can be more objectively scrutinized. On the macro level, a 'themes' analysis is initially conducted to isolate the overarching themes that dominate the fitness discourse on the cover pages under study. It is argued that variation in terms of frequencies of such themes is indicative, broadly speaking, of which facets of hegemonic masculinity and femininity are infused in the fitness discourse on the cover pages. On the micro level, this research work encompasses three sub-levels of analysis. The researcher follows an SF-MMDA approach, drawing on a trio of analytical frameworks: Halliday's SFG for the verbal analysis; Kress & van Leeuween's VG for the visual analysis; and CMT in relation to Sperber & Wilson's RT for the pragma-cognitive analysis of multimodal metaphors and metonymies. The data is presented in terms of detailed descriptions in conjunction with frequency tables, ANOVA with alpha=0.05 and MANOVA in the multiple phases of analysis. Insights and findings from this multi-faceted, social-semiotic analysis are interpreted in light of Cultivation Theory, Self-objectification Theory and the literature to date. Implications for future research include the implementation of a multi-dimensional approach whereby linguistic and visual analytical models are deployed with special regards to cultural variation.

Keywords: gender, hegemony, magazine cover page, multimodal discourse analysis, multimodal metaphor, multimodal metonymy, systemic functional grammar, visual grammar

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Authors: Haifeng Shi, Kun Song, Yili Zhao

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In China, with the extensive promotion of the ‘aging in place’ pension policy as the background, most of the elders will choose to remain in their current homes and communities, finding out of preference or necessity that they will need to remodel their homes to fit their changing needs. This generation elder born in the 1960s to 1970s almost live in the same form of housing-condominium built from 1982 to 2012. Based on the survey of existing multi-family housing, especially in Tianjin, it is found that the current ‘double two-thirds principles’ is becoming the threshold for modification to existing house, particularly in the project of elevators addition to existing condominium (built from 1982 to 2016 without elevators below 6 floors according to the previous building code). Firstly, this article concludes the local policies of elevator addition nationwide, most of which has determined the importance and necessity of the community-based self-organization principle in the operation of the elevator addition. Secondly, by comparing the three existing community management systems (owners' congress, property management system and community committee) in instances, find that the community-based ‘two-thirds’ principle is not conducive to implement for multi-owned property renovation in the community or common accessibility modification in the building. However, analysis the property and other community management related laws, pointing out the shortcomings of the existing community-based ‘two-thirds’ decision-making norms. The analyzation showed that the unit-based and ‘100% principle’ method is more capable of common accessibility in the condominium in China. Differing from existing laws, the unit-based principle will be effective for the process of decision-making and ‘100% principle’ will protect closely profit-related householders for condominium modification in the multi-owned area. These three aspects of the analysis suggest that the establishment of the unit-based self-organization mechanism is a preferred and inevitable method to solve the problem of elevators addition to the existing condominium in China.

Keywords: aging in place, condominium, modification, multi own

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Authors: Alireza Naseri, Susan L. Holdt, Charlotte Jacobsen

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In 2014, the global amount of carrageenan production was 60,000 ton with a value of US$ 626 million. From this number, it can be estimated that the total dried seaweed consumption for this production was at least 300,000 ton/year. The protein content of these types of seaweed is 5 – 25%. If just half of this total amount of protein could be extracted, 18,000 ton/year of a high-value protein product would be obtained. The overall aim of this study was to develop a technology that will ensure further utilization of the seaweed that is used only as raw materials for carrageenan production as single extraction at present. More specifically, proteins should be extracted from the seaweed either before or after extraction of carrageenan with focus on maintaining the quality of carrageenan as a main product. Different mechanical, chemical and enzymatic technologies were evaluated. The optimized process was implemented in lab scale and based on its results; the new experiments were done a pilot and larger scale. In order to calculate the efficiency of the new upstream multi-extraction process, protein content was tested before and after extraction. After this step, the extraction of carrageenan was done and carrageenan content and the effect of extraction on yield were evaluated. The functionality and quality of carrageenan were measured based on rheological parameters. The results showed that by using the new multi-extraction process (submitted patent); it is possible to extract almost 50% of total protein without any negative impact on the carrageenan quality. Moreover, compared to the routine carrageenan extraction process, the new multi-extraction process could increase the yield of carrageenan and the rheological properties such as gel strength in the final carrageenan had a promising improvement. The extracted protein has initially been screened as a plant protein source in typical food applications. Further work will be carried out in order to improve properties such as color, solubility, and taste.

Keywords: carrageenan, extraction, protein, seaweed

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Authors: Mohsen Tehranizadeh, Mahboobe Forghani

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The impact of higher modes on the seismic response of dual structural system consist of concrete moment-resisting frame and with RC shear walls is investigated against near-field earthquakes in this paper. a 20 stories reinforced concrete shear wall-special moment frame structure is designed in accordance with ASCE7 requirements and The nonlinear model of the structure was performed on OpenSees platform. Nonlinear time history dynamic analysis with 3 near-field records are performed on them. In order to further understand the structural collapse behavior in the near field, the response of the structure at the moment of collapse especially the formation of plastic hinges is explored. The results revealed that the amplification of moment at top of the wall due to higher modes, the plastic hinge can form in the upper part of wall, even when designed and detailed for plastic hinging at the base only (according to ACI code).on the other hand, shear forces in excess of capacity design values can develop due to the contribution of the higher modes of vibration to dynamic response due to the near field can cause brittle shear or sliding failure modes. The past investigation on shear walls clearly shows the dual-hinge design concept is effective at reducing the effects of the second mode of response. An advantage of the concept is that, when combined with capacity design, it can result in relaxation of special reinforcing detailing in large portions of the wall. In this study, to investigate the implications of multi-design approach, 4 models with varies arrangement of hinge plastics at the base and height of the shear wall are considered. results base on time history analysis showed that the dual or multi plastic hinges approach can be useful in order to control the high moment and shear demand of higher mode effect.

Keywords: higher mode effect, Near-field earthquake, nonlinear time history analysis, multi plastic hinge design

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Authors: Tomasz Wejrzanowski, Łukasz Kaczmarek, Michał Maksimczuk

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High-resolution X-ray computed microtomography (µCT) is a non-destructive technique commonly used to determine the internal structure of reservoir rock sample. This study concerns µCT analysis of Silurian and Ordovician shales and mudstones from a borehole in the Baltic Basin, north of Poland. The spatial resolution of the µCT images obtained was 27 µm, which enabled the authors to create accurate 3-D visualizations and to calculate the ratio of pores and fractures volume to the total sample volume. A total of 1024 µCT slices were used to create a 3-D volume of sample structure geometry. These µCT slices were processed to obtain a clearly visible image and the volume ratio. A copper X-ray source filter was used to reduce image artifacts. Due to accurate technical settings of µCT it was possible to obtain high-resolution 3-D µCT images of low X-ray transparency samples. The presented results confirm the utility of µCT implementations in geoscience and show that µCT has still promising applications for reservoir exploration and characterization.

Keywords: fractures, material density, pores, structure

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Authors: Hong Kai, Zhong Jun Jie, Chen Lin Qi, Wang Chen Guang

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There are inefficient global scheduling parallelism and local scheduling parallelism prone to processor starvation in current scheduling algorithms. Regarding this issue, this paper proposed a load-aware queue partitioning scheduling strategy by first allocating the queues according to the number of processor cores, calculating the load factor to specify the load queue capacity, and it assigned the awaiting nodes to the appropriate perceptual queues through the precursor nodes and the communication computation overhead. At the same time, real-time computation of the load factor could effectively prevent the processor from being starved for a long time. Experimental comparison with two classical algorithms shows that there is a certain improvement in both performance metrics of scheduling length and task speedup ratio.

Keywords: load-aware, scheduling algorithm, perceptual queue, heterogeneous multi-core

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Authors: Berfin Yildiz

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These days, increasing global warming effects, limited amount of energy resources, etc., necessitates the awareness that must be present in every profession group. The architecture and construction sectors are responsible for both the embodied and operational energy of the materials. This responsibility has led designers to seek alternative solutions for energy-efficient material selection. The choice of energy-efficient material requires consideration of the entire life cycle, including the building's production, use, and disposal energy. The aim of this study is to investigate the method of material selection of external thermal insulation composite systems (ETICS). Embodied and in-use energy values of material alternatives were used for the evaluation in this study. The operational energy is calculated according to the u-value calculation method defined in the TS 825 (Thermal Insulation Requirements) standard for Turkey, and the embodied energy is calculated based on the manufacturer's Energy Performance Declaration (EPD). ETICS consists of a wall, adhesive, insulation, lining, mechanical, mesh, and exterior finishing materials. In this study, lining, mechanical, and mesh materials were ignored because EPD documents could not be obtained. The material selection problem is designed as a hypothetical volume area (5x5x3m) and defined as a multi-objective discrete optimization problem for external thermal insulation composite systems. Defining the problem as a discrete optimization problem is important in order to choose between materials of various thicknesses and sizes. Since production and use energy values, which are determined as optimization objectives in the study, are often conflicting values, material selection is defined as a multi-objective optimization problem, and it is aimed to obtain many solution alternatives by using Hypervolume (HypE) algorithm. The enrollment process started with 100 individuals and continued for 50 generations. According to the obtained results, it was observed that autoclaved aerated concrete and Ponce block as wall material, glass wool, as insulation material gave better results.

Keywords: embodied energy, multi-objective discrete optimization, performative design, thermal insulation

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Authors: Belouadah Rabah, Guyomar Daneil, Guiffard Benoit

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The magnetoelectric (ME) materials has dielectric polarization induced by the magnetic field or induced magnetization under an electric field. A strong ME effect requires the simultaneous presence of magnetic moments and electric dipoles. In the last decades, extensive research has been conducted on the ME effect in single phase and composite materials. This article reported the results obtained with two samples, the first is mono layer of PVDF bi-stretched and the second is the multi layer PVDF bi-stretched with the Polyurethane filled with micro particles magnetic Fe3O4 (PU+2% Fe3O4). Compare with non ME material like Alumine, a large ME polarization coefficient for the two samples was obtained. The piezoelectric properties of the PVDF and elastic proprieties of Pu+2% Fe3O4 give a big linear ME coefficient of the multi layer PVDF/(Pu+2% Fe3O4) than in the monolayer of PVDF.

Keywords: magnetoelectric effect, polymers, magnetic particles, composites, films

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Authors: L. Lakhdari, B. Bouchiba, M. Bechar

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The multi-level inverters present an important novelty in the field of energy control with high voltage and power. The major advantage of all multi-level inverters is the improvement and spectral quality of its generated output signals. In recent years, various pulse width modulation techniques have been developed. From these technics we have: Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM). This work presents a detailed analysis of the comparative advantage of space vector pulse width modulation (SVPWM) and the standard SPWM technique for Three Level Diode Clamped Inverter fed Induction Motor. The comparison is based on the evaluation of harmonic distortion THD.

Keywords: induction motor, multilevel inverters, SVPWM, SPWM, THD

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Authors: Heshalini Rajagopal, Li Sze Chow, Raveendran Paramesran

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Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modality. Subjective assessment of the image quality is regarded as the gold standard to evaluate MR images. In this study, a database of 210 MR images which contains ten reference images and 200 distorted images is presented. The reference images were distorted with four types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur and DCT compression. The 210 images were assessed by ten subjects. The subjective scores were presented in Difference Mean Opinion Score (DMOS). The DMOS values were compared with four FR-IQA metrics. We have used Pearson Linear Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) to validate the DMOS values. The high correlation values of PLCC and SROCC shows that the DMOS values are close to the objective FR-IQA metrics.

Keywords: medical resonance (MR) images, difference mean opinion score (DMOS), full reference image quality assessment (FR-IQA)

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

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Authors: Saurav Kumar Suman, P. Karthigayani

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In this paper the height of the tree is estimated and forest types is classified from the multi temporal RISAT-1 Horizontal-Horizontal (HH) and Horizontal-Vertical (HV) Polarised Satellite Aperture Radar (SAR) data. The novelty of the proposed project is combined use of the Back-scattering Coefficients (Sigma Naught) and the Coherence. It uses Water Cloud Model (WCM). The approaches use two main steps. (a) Extraction of the different forest parameter data from the Product.xml, BAND-META file and from Grid-xxx.txt file come with the HH & HV polarized data from the ISRO (Indian Space Research Centre). These file contains the required parameter during height estimation. (b) Calculation of the Vegetation and Ground Backscattering, Coherence and other Forest Parameters. (c) Classification of Forest Types using the ENVI 5.0 Tool and ROI (Region of Interest) calculation.

Keywords: RISAT-1, classification, forest, SAR data

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Authors: Manish Kumar Rajak, Sanjay Gupta

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Mobile ad hoc networks (MANETs) are infrastructure less and intercommunicate using single-hop and multi-hop paths. Network based congestion avoidance which involves managing the queues in the network devices is an integral part of any network. QoS: A set of service requirements that are met by the network while transferring a packet stream from a source to a destination. Especially in MANETs, packet loss results in increased overheads. This paper presents a new algorithm to avoid congestion using one or more queue on nodes and corresponding flow rate decided in advance for each node. When any node attains an initial value of queue then it sends this status to its downstream nodes which in turn uses the pre-decided flow rate of packet transfer to its upstream nodes. The flow rate on each node is adjusted according to the status received from its upstream nodes. This proposed algorithm uses the existing infrastructure to inform to other nodes about its current queue status.

Keywords: mesh networks, MANET, packet count, threshold, throughput

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Authors: S. Burgalat, L. Teilhac, A. Brand, E. Chastel, M. Jumeline

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The paper presents actual benefits and drawbacks of a multidirectional autonomous hovercraft conceived with limited resources and designed for indoor exploration. Recent developments in the field have led to the apparition of very powerful automotive systems capable of very high calculation and exploration in complex unknown environments. They usually propose very complex algorithms, high precision/cost sensors and sometimes have heavy calculation consumption with complex data fusion. These systems are usually powerful but have a certain price, and the benefits may not be worth the cost, especially considering their hardware limitations and their power consumption. The present approach is to build a compromise between cost, power consumption and results preciseness.

Keywords: hovercraft, indoor exploration, autonomous, multidirectional, wireless control

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Authors: Tegan H. Emerson, Colin C. Olson, George Stantchev, Jason A. Edelberg, Michael Wilson

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Detecting small targets at range is difficult because there is not enough spatial information present in an image sub-region containing the target to use correlation-based methods to differentiate it from dynamic confusers present in the scene. Moreover, this lack of spatial information also disqualifies the use of most state-of-the-art deep learning image-based classifiers. Here, we use characteristics of target tracks extracted from video sequences as data from which to derive distinguishing topological features that help robustly differentiate targets of interest from confusers. In particular, we calculate persistent homology from time-delayed embeddings of dynamic statistics calculated from motion tracks extracted from a wide field-of-view video stream. In short, we use topological methods to extract features related to target motion dynamics that are useful for classification and disambiguation and show that small targets can be detected at range with high probability.

Keywords: motion tracks, persistence images, time-delay embedding, topological data analysis

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Authors: Tingting Huang, Sha Li, Geoffrey Griffiths, Martin Lukac, Jianning Zhu

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Territorial landscapes have experienced a gradual loss of their typical characteristics during long-term human activities. In order to protect the integrity of regional landscapes, it is necessary to characterize, evaluate and protect them in a graded manner. The study takes Fujian, China, as an example and classifies the landscape characters of the site at the regional scale, middle scale, and detailed scale. A multi-scale approach combining parametric and holistic approaches is used to classify and partition the landscape character types (LCTs) and landscape character areas (LCAs) at different scales, and a multi-element landscape assessment approach is adopted to explore the conservation strategies of the landscape character. Firstly, multiple fields and multiple elements of geography, nature and humanities were selected as the basis of assessment according to the scales. Secondly, the study takes a parametric approach to the classification and partitioning of landscape character, Principal Component Analysis, and two-stage cluster analysis (K-means and GMM) in MATLAB software to obtain LCTs, combines with Canny Operator Edge Detection Algorithm to obtain landscape character contours and corrects LCTs and LCAs by field survey and manual identification methods. Finally, the study adopts the Landscape Sensitivity Assessment method to perform landscape character conservation analysis and formulates five strategies for different LCAs: conservation, enhancement, restoration, creation, and combination. This multi-scale identification approach can efficiently integrate multiple types of landscape character elements, reduce the difficulty of broad-scale operations in the process of landscape character conservation, and provide a basis for landscape character conservation strategies. Based on the natural background and the restoration of regional characteristics, the results of landscape character assessment are scientific and objective and can provide a strong reference in regional and national scale territorial spatial planning.

Keywords: parameterization, multi-scale, landscape character identify, landscape character assessment

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Authors: Lae-Jeong Park

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The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: pedestrian detection, color segmentation, false positive, feature extraction

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Authors: Babatunde Olumide Olawale, Oyebode Olumide Oyediran

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The security safe is a place or building where classified document and precious items are kept. To prevent unauthorised persons from gaining access to this safe a lot of technologies had been used. But frequent reports of an unauthorised person gaining access into security safes with the aim of removing document and items from the safes are pointers to the fact that there is still security gap in the recent technologies used as access control for the security safe. In this paper we try to solve this problem by developing a multimodal biometric system for physical access control into a security safe using face and voice recognition. The safe is accessed by the combination of face and speech pattern recognition and also in that sequential order. User authentication is achieved through the use of camera/sensor unit and a microphone unit both attached to the door of the safe. The user face was captured by the camera/sensor while the speech was captured by the use of the microphone unit. The Scale Invariance Feature Transform (SIFT) algorithm was used to train images to form templates for the face recognition system while the Mel-Frequency Cepitral Coefficients (MFCC) algorithm was used to train the speech recognition system to recognise authorise user’s speech. Both algorithms were hosted in two separate web based servers and for automatic analysis of our work; our developed system was simulated in a MATLAB environment. The results obtained shows that the developed system was able to give access to authorise users while declining unauthorised person access to the security safe.

Keywords: access control, multimodal biometrics, pattern recognition, security safe

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Authors: Boris Djartov, Sanaz Mostaghim

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This paper presents a number-based dominance method. The main idea is how to fragment the many attributes of the problem into subsets suitable for the well-established concept of Pareto dominance. Although other similar methods can be found in the literature, they focus on comparing the solutions one objective at a time, while the focus of this method is to compare entire subsets of the objective vector. Given the nature of the method, it is computationally costlier than other methods and thus, it is geared more towards selecting an option from a finite set of alternatives, where each solution is defined by multiple objectives. The need for this method was motivated by dynamic alternate airport selection (DAAS). In DAAS, pilots, while en route to their destination, can find themselves in a situation where they need to select a new landing airport. In such a predicament, they need to consider multiple alternatives with many different characteristics, such as wind conditions, available landing distance, the fuel needed to reach it, etc. Hence, this method is primarily aimed at human decision-makers. Many methods within the field of multi-objective and many-objective decision-making rely on the decision maker to initially provide the algorithm with preference points and weight vectors; however, this method aims to omit this very difficult step, especially when the number of objectives is so large. The proposed method will be compared to Favour (1 − k)-Dom and L-dominance (LD) methods. The test will be conducted using well-established test problems from the literature, such as the DTLZ problems. The proposed method is expected to outperform the currently available methods in the literature and hopefully provide future decision-makers and pilots with support when dealing with many-objective optimization problems.

Keywords: multi-objective decision-making, many-objective decision-making, multi-objective optimization, many-objective optimization

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Authors: Zaid Almahmoud, Rana Mahmoud

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To mitigate the environmental impacts of throwing away plastic waste, there has been a recent interest in manufacturing and producing biodegradable plastics. Here, we study a new class of biodegradable plastics which are mixed with external natural additives, including catalytic additives that lead to a successful degradation of the resulting material. To recommend the best alternative among multiple materials, we propose a multi-objective AI model that evaluates the material against multiple objectives given the material properties. As a proof of concept, the AI model was implemented in an expert system and evaluated using multiple materials. Our findings showed that Polyethylene Terephalate is potentially the best biodegradable plastic substitute based on its material properties. Therefore, it is recommended that governments shift the attention to the use of Polyethylene Terephalate in the manufacturing of bottles to gain a great environmental and sustainable benefits.

Keywords: plastic bottles, expert systems, multi-objective model, biodegradable substitutes

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Authors: Raphael Rehmet, Armin Lohrengel, Prof Dr-Ing

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In terms of making machines more silent and convenient, it is necessary to analyze the transmission path of mechanical vibrations and structure-bone noise. A typical solution for the elimination of structure-bone noise would be to simply add stiffeners or additional masses to change the transmission behavior and, thereby, avoid the propagation of vibrations. Another solution could be to use materials with a different damping behavior, such as elastomers, to isolate the machine dynamically. This research approach investigates the damping behavior of additive printed components made from structural steel or titanium, which have been manufactured in the “Laser Powder Bed Fusion“-process. By using the design flexibility which this process comes with, it will be investigated how a local impedance difference will affect the transmission behavior of the specimens.

Keywords: 3D-printed, acoustics, dynamics, impedance

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: Ying-Chang Yu, Yuan-Lung Lo

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Building ventilation performance is an important indicator of indoor comfort. However, in addition to the geometry of the building or the proportion of the opening, the ventilation performance is also very much related to the actual wind pressure of the building. There are more and more contemporary building designs built with multi-layer exterior envelope. Due to ventilation and view observatory requirement, the porous outer layer of the building is commonly adopted and has a significant wind damping effect, causing the phenomenon of actual wind pressure loss. However, the relationship between the wind damping effect and the actual wind pressure is not linear. This effect can make the indoor ventilation of the building rationalized to reasonable range under the condition of high wind pressure, and also maintain a good amount of ventilation performance under the condition of low wind pressure. In this study, wind tunnel experiments were carried out to simulate the different wind pressures flow through the porous outer layer, and observe the actual wind pressure strength engage with the window layer to find the decreasing relationship between the damping effect of the porous shell and the wind pressure. Experiment specimen scale was designed to be 1:50 for testing real-world building conditions; the study found that the porous enclosure has protective shielding without affecting low-pressure ventilation. Current study observed the porous skin may damp more wind energy to ease the wind pressure under high-speed wind. Differential wind speed may drop the pressure into similar pressure level by using porous skin. The actual mechanism and value of this phenomenon will need further study in the future.

Keywords: multi-layer facade, porous media, wind damping, wind tunnel test, building ventilation

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Authors: P. Senthilraja, C. Rukumani Khandhan, M. Palaniappan, S. L. Rama, P. Sai Sushimitha, R. Madhan, J. Vinumathi, N. Vijayarangan

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Nowadays, the logistics achieve a vast improvement in efficient delivery of goods. The technology improvement also helps to improve its development, but still the owners of transport vehicles face problems, i.e., fuel theft in vehicles by the drivers or by an unknown person. There is no proper solution to overcome the problems. This scheme is to determine the amount of fuel that has been stolen and also to determine the position of the vehicle at a particular time using the technologies like GPS, GSM, ultrasonic fuel level sensor and numeric lock system. The ultrasonic sensor uses the ultrasonic waves to calculate the height of the tank up to which the fuel is available. Based on height it is possible to calculate the amount of fuel. The Global Positioning System (GPS) is a satellite-based navigation system. The scientific community uses GPS for its precision timing capability and position information. The GSM provides the periodic information about the fuel level. A numeric lock system has been provided for fuel tank opening lever. A password is provided to access the fuel tank lever and this is authenticated only by the driver and the owner. Once the fuel tank is opened an alert is sent to owner through a SMS including the timing details. Third party monitoring software is a user interface that updates the information automatically into the database which helps to retrieve the data as and when required. Third party monitoring software provides vehicle’s information to the owner and also shows the status of the vehicle. The techniques that are to be proposed will provide an efficient output. This project helps to overcome the theft and hence to put forth fuel economy.

Keywords: fuel theft, third party monitoring software, bioinformatics, biomedicine

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Authors: Katri K. Cornelissen, Lise Gulli Brokjob, Kristofor McCarty, Jiri Gumancik, Martin J. Tovee, Piers L. Cornelissen

Abstract:

Recent research has shown that body size estimation of healthy women is driven by independent attitudinal and perceptual components. The attitudinal component represents psychological concerns about body, coupled to low self-esteem and a tendency towards depressive symptomatology, leading to over-estimation of body size, independent of the Body Mass Index (BMI) someone actually has. The perceptual component is a normal bias known as contraction bias, which, for bodies is dependent on actual BMI. Women with a BMI less than the population norm tend to overestimate their size, while women with a BMI greater than the population norm tend to underestimate their size. Women whose BMI is close to the population mean are most accurate. This is indexed by a regression of estimated BMI on actual BMI with a slope less than one. It is well established that body dissatisfaction, i.e. an attitudinal distortion, leads to body size overestimation in eating disordered individuals. However, debate persists as to whether women with eating disorders may also suffer a perceptual body distortion. Therefore, the current study was set to ask whether women with eating disorders exhibit the normal contraction bias when they estimate their own body size. If they do not, this would suggest differences in the way that women with eating disorders process the perceptual aspects of body shape and size in comparison to healthy controls. 100 healthy controls and 33 women with a history of eating disorders were recruited. Critically, it was ensured that both groups of participants represented comparable and adequate ranges of actual BMI (e.g. ~18 to ~40). Of those with eating disorders, 19 had a history of anorexia nervosa, 6 bulimia nervosa, and 8 OSFED. 87.5% of the women with a history of eating disorders self-reported that they were either recovered or recovering, and 89.7% of them self-reported that they had had one or more instances of relapse. The mean time lapsed since first diagnosis was 5 years and on average participants had experienced two relapses. Participants were asked to fill number of psychometric measures (EDE-Q, BSQ, RSE, BDI) to establish the attitudinal component of their body image as well as their tendency to internalize socio-cultural body ideals. Additionally, participants completed a method of adjustment psychophysical task, using photorealistic avatars calibrated for BMI, in order to provide an estimate of their own body size and shape. The data from the healthy controls replicate previous findings, revealing independent contributions to body size estimation from both attitudinal and perceptual (i.e. contraction bias) body image components, as described above. For the eating disorder group, once the adequacy of their actual BMI ranges was established, a regression of estimated BMI on actual BMI had a slope greater than 1, significantly different to that from controls. This suggests that (some) eating disordered individuals process the perceptual aspects of body image differently from healthy controls. It therefore is necessary to develop interventions which are specific to the perceptual processing of body shape and size for the management of (some) individuals with eating disorders.

Keywords: body image distortion, perception, recovery, relapse, BMI, eating disorders

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Authors: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong

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This paper and its companions (Part II, Part III) will concentrate on optimizing a class of supply chain problems known as Multi- Commodities Consumer Supply Chain (MCCSC) problem. MCCSC problem belongs to production-distribution (P-D) planning category. It aims to determine facilities location, consumers’ allocation, and facilities configuration to minimize total cost (CT) of the entire network. These facilities can be manufacturer units (MUs), distribution centres (DCs), and retailers/end-users (REs) but not limited to them. To address this problem, three major tasks should be undertaken. At the first place, a mixed integer non-linear programming (MINP) mathematical model is developed. Then, system’s behaviors under different conditions will be observed using a simulation modeling tool. Finally, the most optimum solution (minimum CT) of the system will be obtained using a multi-objective optimization technique. Due to the large size of the problem, and the uncertainties in finding the most optimum solution, integration of modeling and simulation methodologies is proposed followed by developing new approach known as GASG. It is a genetic algorithm on the basis of granular simulation which is the subject of the methodology of this research. In part II, MCCSC is simulated using discrete-event simulation (DES) device within an integrated environment of SimEvents and Simulink of MATLAB® software package followed by a comprehensive case study to examine the given strategy. Also, the effect of genetic operators on the obtained optimal/near optimal solution by the simulation model will be discussed in part III.

Keywords: supply chain, genetic algorithm, optimization, simulation, discrete event system

Procedia PDF Downloads 300

Authors: Kristin Thooft

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— Increasing pressure to manage healthcare costs has resulted in shifting care towards ambulatory settings and is driving a focus on cost transparency. There are few nurse staffing to workload models developed for ambulatory settings, less for multi-specialty clinics. Of the existing models, few have been evaluated against outcomes to understand any impact. This evaluation took place after the AWARD model for nurse staffing to workload was implemented in a multi-specialty clinic at a regional healthcare system in the Midwest. The multi-specialty clinic houses 26 medical and surgical specialty practices. The AWARD model was implemented in two specialty practices in October 2020. Donabedian’s Structure-Process-Outcome (SPO) model was used to evaluate outcomes based on changes to the structure and processes of care provided. The AWARD model defined and quantified the processes, recommended changes in the structure of day-to-day nurse staffing. Cost of care per patient visit, total visits, a total nurse performed visits used as structural and process measures, influencing the outcomes of cost of care and access to care. Independent t-tests were used to compare the difference in variables pre-and post-implementation. The SPO model was useful as an evaluation tool, providing a simple framework that is understood by a diverse care team. No statistically significant changes in the cost of care, total visits, or nurse visits were observed, but there were differences. Cost of care increased and access to care decreased. Two weeks into the post-implementation period, the multi-specialty clinic paused all non-critical patient visits due to a second surge of the COVID-19 pandemic. Clinic nursing staff was re-allocated to support the inpatient areas. This negatively impacted the ability of the Nurse Manager to utilize the AWARD model to plan daily staffing fully. The SPO framework could be used for the ongoing assessment of nurse staffing performance. Additional variables could be measured, giving a complete picture of the impact of nurse staffing. Going forward, there must be a continued focus on the outcomes of care and the value of nursing

Keywords: ambulatory, clinic, evaluation, outcomes, staffing, staffing model, staffing to workload

Procedia PDF Downloads 162

Authors: Asim Alsharif, Christophe Pinna, Hassan Ghadbeigi

Abstract:

The development of next-generation advanced high strength steels (AHSS) used in the automotive industry requires a better understanding of local deformation and damage development at the scale of their microstructures. This work is focused on dual-phase DP1000 steels and involves micro-mechanical tensile testing inside a scanning electron microscope (SEM) combined with digital image correlation (DIC) to quantify the heterogeneity of deformation in both ferrite and martensite and its evolution up to fracture. Natural features of the microstructure are used for the correlation carried out using Davis LaVision software. Strain localization is observed in both phases with tensile strain values up to 130% and 110% recorded in ferrite and martensite respectively just before final fracture. Damage initiation sites have been observed during deformation in martensite but could not be correlated to local strain values. A finite element (FE) model of the microstructure has then been developed using Abaqus to map stress distributions over representative areas of the microstructure by forcing the model to deform as in the experiment using DIC-measured displacement maps as boundary conditions. A MATLAB code has been developed to automatically mesh the microstructure from SEM images and to map displacement vectors from DIC onto the FE mesh. Results show a correlation of damage initiation at the interface between ferrite and martensite with local principal stress values of about 1700MPa in the martensite phase. Damage in ferrite is now being investigated, and results are expected to bring new insight into damage development in DP steels.

Keywords: advanced high strength steels, digital image correlation, finite element modelling, micro-mechanical testing

Procedia PDF Downloads 128

Authors: Dongwon Lee, Sunmyeng Kim

Abstract:

Underwater acoustic networks (UANs) have become a very active research area in recent years. Compared with wireless networks, UANs are characterized by the limited bandwidth, long propagation delay and high channel dynamic in acoustic modems, which pose challenges to the design of medium access control (MAC) protocol. The characteristics severely affect network performance. In this paper, we study a MS-MAC (Multi-Sender MAC) protocol in order to improve network performance. The proposed protocol exploits temporal reuse by learning the propagation delays to neighboring nodes. A source node locally calculates the transmission schedules of its neighboring nodes and itself based on the propagation delays to avoid collisions. Performance evaluation is conducted using simulation, and confirms that the proposed protocol significantly outperforms the previous protocol in terms of throughput.

Keywords: acoustic channel, MAC, temporal reuse, UAN

Procedia PDF Downloads 331

Authors: Iris Vogeler, Rogerio Cichota, Armin Werner

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Dairy farms are under pressure to increase productivity while reducing environmental impacts. Effective fertiliser management practices are critical to achieve this. Determination of optimum nitrogen (N) fertilisation rates which maximise pasture growth and minimise N losses is challenging due to variability in plant requirements and likely near-future supply of N by the soil. Remote sensing can be used for mapping N nutrition status of plants and to rapidly assess the spatial variability within a field. An algorithm is, however, lacking which relates the N status of the plants to the expected yield response to additions of N. The aim of this simulation study was to develop a multi-variate model for determining N fertilisation rate for a target percentage of the maximum achievable yield based on the pasture N concentration (ii) use of an algorithm for guiding fertilisation rates, and (iii) evaluation of the model regarding pasture yield and N losses, including N leaching, denitrification and volatilisation. A simulation study was carried out using the Agricultural Production Systems Simulator (APSIM). The simulations were done for an irrigated ryegrass pasture in the Canterbury region of New Zealand. A multi-variate model was developed and used to determine monthly required N fertilisation rates based on pasture N content prior to fertilisation and targets of 50, 75, 90 and 100% of the potential monthly yield. These monthly optimised fertilisation rules were evaluated by running APSIM for a ten-year period to provide yield and N loss estimates from both nonurine and urine affected areas. Comparison with typical fertilisation rates of 150 and 400 kg N/ha/year was also done. Assessment of pasture yield and leaching from fertiliser and urine patches indicated a large reduction in N losses when N fertilisation rates were controlled by the multi-variate model. However, the reduction in leaching losses was much smaller when taking into account the effects of urine patches. The proposed approach based on biophysical modelling to develop a multi-variate model for determining optimum N fertilisation rates dependent on pasture N content is very promising. Further analysis, under different environmental conditions and validation is required before the approach can be used to help adjust fertiliser management practices to temporal and spatial N demand based on the nitrogen status of the pasture.

Keywords: APSIM modelling, optimum N fertilization rate, pasture N content, ryegrass pasture, three dimensional surface response function.

Procedia PDF Downloads 118