Search results for: label relation
2919 Scene Classification Using Hierarchy Neural Network, Directed Acyclic Graph Structure, and Label Relations
Authors: Po-Jen Chen, Jian-Jiun Ding, Hung-Wei Hsu, Chien-Yao Wang, Jia-Ching Wang
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A more accurate scene classification algorithm using label relations and the hierarchy neural network was developed in this work. In many classification algorithms, it is assumed that the labels are mutually exclusive. This assumption is true in some specific problems, however, for scene classification, the assumption is not reasonable. Because there are a variety of objects with a photo image, it is more practical to assign multiple labels for an image. In this paper, two label relations, which are exclusive relation and hierarchical relation, were adopted in the classification process to achieve more accurate multiple label classification results. Moreover, the hierarchy neural network (hierarchy NN) is applied to classify the image and the directed acyclic graph structure is used for predicting a more reasonable result which obey exclusive and hierarchical relations. Simulations show that, with these techniques, a much more accurate scene classification result can be achieved.Keywords: convolutional neural network, label relation, hierarchy neural network, scene classification
Procedia PDF Downloads 4522918 A New Approach for Improving Accuracy of Multi Label Stream Data
Authors: Kunal Shah, Swati Patel
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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer
Procedia PDF Downloads 5772917 An Improvement of Multi-Label Image Classification Method Based on Histogram of Oriented Gradient
Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart
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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients
Procedia PDF Downloads 3692916 Effective Nutrition Label Use on Smartphones
Authors: Vladimir Kulyukin, Tanwir Zaman, Sarat Kiran Andhavarapu
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Research on nutrition label use identifies four factors that impede comprehension and retention of nutrition information by consumers: label’s location on the package, presentation of information within the label, label’s surface size, and surrounding visual clutter. In this paper, a system is presented that makes nutrition label use more effective for nutrition information comprehension and retention. The system’s front end is a smartphone application. The system’s back end is a four node Linux cluster for image recognition and data storage. Image frames captured on the smartphone are sent to the back end for skewed or aligned barcode recognition. When barcodes are recognized, corresponding nutrition labels are retrieved from a cloud database and presented to the user on the smartphone’s touchscreen. Each displayed nutrition label is positioned centrally on the touchscreen with no surrounding visual clutter. Wikipedia links to important nutrition terms are embedded to improve comprehension and retention of nutrition information. Standard touch gestures (e.g., zoom in/out) available on mainstream smartphones are used to manipulate the label’s surface size. The nutrition label database currently includes 200,000 nutrition labels compiled from public web sites by a custom crawler. Stress test experiments with the node cluster are presented. Implications for proactive nutrition management and food policy are discussed.Keywords: mobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning
Procedia PDF Downloads 3652915 The Influence of Noise on Aerial Image Semantic Segmentation
Authors: Pengchao Wei, Xiangzhong Fang
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Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise
Procedia PDF Downloads 2112914 Association of Dietary Intake with the Nutrition Knowledge, Food Label Use, and Food Preferences of Adults in San Jose del Monte City, Bulacan, Philippines
Authors: Barby Jennette A. Florano
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Dietary intake has been associated with the health and wellbeing of adults, and lifestyle related diseases. The aim of this study was to investigate whether nutrition knowledge, food label use, and food preference are associated with the dietary intake in a sample of San Jose Del Monte City, Bulacan (SJDM) adults. A sample of 148 adults, with a mean age of 20 years, completed a validated questionnaire related to their demographic, dietary intake, nutrition knowledge, food label use and food preference. Data were analyzed using Pearson correlation and there was no association between dietary intake and nutrition knowledge. However, there were positive relationships between dietary intake and food label use (r=0.1276, p<0.10), and dietary intake and food preference (r=0.1070, p<0.10). SJDM adults who use food label and have extensive food preference had better diet quality. This finding magnifies the role of nutrition education as a potential tool in health campaigns to promote healthy eating patterns and reading food labels among students and adults. Results of this study can give information for the design of future nutrition education intervention studies to assess the efficacy of nutrition knowledge and food label use among a similar sample population.Keywords: dietary intake, nutrition knowledge, food preference, food label use
Procedia PDF Downloads 832913 An Algorithm for the Map Labeling Problem with Two Kinds of Priorities
Authors: Noboru Abe, Yoshinori Amai, Toshinori Nakatake, Sumio Masuda, Kazuaki Yamaguchi
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We consider the problem of placing labels of the points on a plane. For each point, its position, the size of its label and a priority are given. Moreover, several candidates of its label positions are prespecified, and each of such label positions is assigned a priority. The objective of our problem is to maximize the total sum of priorities of placed labels and their points. By refining a labeling algorithm that can use these priorities, we propose a new heuristic algorithm which is more suitable for treating the assigned priorities.Keywords: map labeling, greedy algorithm, heuristic algorithm, priority
Procedia PDF Downloads 4252912 Deep learning with Noisy Labels : Learning True Labels as Discrete Latent Variable
Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack
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In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32
Procedia PDF Downloads 1172911 Learning from Small Amount of Medical Data with Noisy Labels: A Meta-Learning Approach
Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak
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Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity
Procedia PDF Downloads 1512910 Semantic Differences between Bug Labeling of Different Repositories via Machine Learning
Authors: Pooja Khanal, Huaming Zhang
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Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.Keywords: bug classification, bug labels, GitHub issues, semantic differences
Procedia PDF Downloads 1912909 Grammar as a Logic of Labeling: A Computer Model
Authors: Jacques Lamarche, Juhani Dickinson
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This paper introduces a computational model of a Grammar as Logic of Labeling (GLL), where the lexical primitives of morphosyntax are phonological matrixes, the form of words, understood as labels that apply to realities (or targets) assumed to be outside of grammar altogether. The hypothesis is that even though a lexical label relates to its target arbitrarily, this label in a complex (constituent) label is part of a labeling pattern which, depending on its value (i.e., N, V, Adj, etc.), imposes language-specific restrictions on what it targets outside of grammar (in the world/semantics or in cognitive knowledge). Lexical forms categorized as nouns, verbs, adjectives, etc., are effectively targets of labeling patterns in use. The paper illustrates GLL through a computer model of basic patterns in English NPs. A constituent label is a binary object that encodes: i) alignment of input forms so that labels occurring at different points in time are understood as applying at once; ii) endocentric structuring - every grammatical constituent has a head label that determines the target of the constituent, and a limiter label (the non-head) that restricts this target. The N or A values are restricted to limiter label, the two differing in terms of alignment with a head. Consider the head initial DP ‘the dog’: the label ‘dog’ gets an N value because it is a limiter that is evenly aligned with the head ‘the’, restricting application of the DP. Adapting a traditional analysis of ‘the’ to GLL – apply label to something familiar – the DP targets and identifies one reality familiar to participants by applying to it the label ‘dog’ (singular). Consider next the DP ‘the large dog’: ‘large dog’ is nominal by even alignment with ‘the’, as before, and since ‘dog’ is the head of (head final) ‘large dog’, it is also nominal. The label ‘large’, however, is adjectival by narrow alignment with the head ‘dog’: it doesn’t target the head but targets a property of what dog applies to (a property or value of attribute). In other words, the internal composition of constituents determines that a form targets a property or a reality: ‘large’ and ‘dog’ happen to be valid targets to realize this constituent. In the presentation, the computer model of the analysis derives the 8 possible sequences of grammatical values with three labels after the determiner (the x y z): 1- D [ N [ N N ]]; 2- D [ A [ N N ] ]; 3- D [ N [ A N ] ]; 4- D [ A [ A N ] ]; 5- D [ [ N N ] N ]; 5- D [ [ A N ] N ]; 6- D [ [ N A ] N ] 7- [ [ N A ] N ] 8- D [ [ Adv A ] N ]. This approach that suggests that a computer model of these grammatical patterns could be used to construct ontologies/knowledge using speakers’ judgments about the validity of lexical meaning in grammatical patterns.Keywords: syntactic theory, computational linguistics, logic and grammar, semantics, knowledge and grammar
Procedia PDF Downloads 302908 Label Survey in Romania: A Study on How Consumers Use Food Labeling
Authors: Gabriela Iordachescu, Mariana Cretu Stuparu, Mirela Praisler, Camelia Busila, Doina Voinescu, Camelia Vizireanu
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The aim of the study was to evaluate the consumers’ degree of confidence in food labeling, how they use and understand the label and respectively food labeling elements. The label is a bridge between producers, suppliers, and consumers. It has to offer enough information in terms of public health and food safety, statement of ingredients, nutritional information, warnings and advisory statements, producing date and shelf-life, instructions for storage and preparation (if required). The survey was conducted on 500 consumers group in Romania, aged 15+, males and females, from urban and rural areas and with different graduation levels. The questionnaire was distributed face to face and online. It had single or multiple choices questions and label images for the efficiency and best understanding of the question. The law 1169/2011 applied to food products from 13 of December 2016 improved and adapted the requirements for labeling in a clear manner. The questions were divided on following topics: interest and general trust in labeling, use and understanding of label elements, understanding of the ingredient list and safety information, nutrition information, advisory statements, serving sizes, best before/use by meanings, intelligent labeling, and demographic data. Three choice selection exercises were also included. In this case, the consumers had to choose between two similar products and evaluate which label element is most important in product choice. The data were analysed using MINITAB 17 and PCA analysis. Most of the respondents trust the food label, taking into account some elements especially when they buy the first time the product. They usually check the sugar content and type of sugar, saturated fat and use the mandatory label elements and nutrition information panel. Also, the consumers pay attention to advisory statements, especially if one of the items is relevant to them or the family. Intelligent labeling is a challenging option. In addition, the paper underlines that the consumer is more careful and selective with the food consumption and the label is the main helper for these.Keywords: consumers, food safety information, labeling, labeling nutritional information
Procedia PDF Downloads 2082907 A Fully Automated New-Fangled VESTAL to Label Vertebrae and Intervertebral Discs
Authors: R. Srinivas, K. V. Ramana
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This paper presents a novel method called VESTAL to label vertebrae and inter vertebral discs. Each vertebra has certain statistical features properties. To label vertebrae and discs, a new equation to model the path of spinal cord is derived using statistical properties of the spinal canal. VESTAL uses this equation for labeling vertebrae and discs. For each vertebrae and inter vertebral discs both posterior, interior width, height are measured. The calculated values are compared with real values which are measured using venires calipers and the comparison produced 95% efficiency and accurate results. The VESTAL is applied on 50 patients 350 MR images and obtained 100% accuracy in labeling.Keywords: spine, vertebrae, inter vertebral disc, labeling, statistics, texture, disc
Procedia PDF Downloads 3582906 Establishment of Thuja Label: Development Prospects for the Marketing Practices of the Handicraft of Essaouira's Marquetry
Authors: Fatima El Kandoussi, Lamiae El Hdiddioui, Mustapha Bouragba
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The woodwork of thuja in Essaouira is one of the main crafts in Morocco. Certainly, marquetry reflects both cultural and artistic identity of the city, considering the talent and ancestral knowledge of craftsman working in marquetry. Yet, the production units encounter a considerable number of difficulties among which insufficiencies within marketing practices. Consequently, it is obvious that major improvements are needed, and supportive solutions must be provided in order to improve the Essaouira’s marquetry, as a symbol of the entire province. Thus, the establishment of Thuja Label is a necessary measure that would be the key to ensuring sustainability of this vital craft. The main purpose of this paper is to study marketing practices’ current state of the production units in the marquetry of Essaouira, therefore to recommend remedial actions likely to raise them up to the required functional level.Keywords: craft, marketing practices, marquetry, thuja label
Procedia PDF Downloads 1892905 Non-Fungible Token (NFT) - Used in the Music Industry for Independent Artists without a Music Recording Label
Authors: Bartholomew Badar
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An NFT is a digital certificate with rights to own an asset, including various valuable digital goods such as art pieces, music items, collectibles, etc. The market for NFTs started developing in 2017 and has lately seen increased growth as crypto-currencies and the blockchain market continue to gain popularity. This study aims to understand potential uses for NFTs concerning the music industry and record labels. Independent artists struggle to distribute and sell their music without the help of a record label. The NFT marketplace could be a great tool to eliminate this problem. The research objective is to identify possibilities for independent artists to own their music rights and share value with an audience. We see a trend of new-school music artists trying to enter the music NFT market by creating visualizers, beats, cover art, etc. To analyze various existing music NFT assets and determine whether or not independent artists could monetize their music without a record label is the main focus of this scholarly paper.Keywords: blockchain, crypto-currency, music, artist, NFT
Procedia PDF Downloads 1712904 A Supervised Face Parts Labeling Framework
Authors: Khalil Khan, Ikram Syed, Muhammad Ehsan Mazhar, Iran Uddin, Nasir Ahmad
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Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method (FPL) which divides a given image into its constitutes parts is proposed in this paper. A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. The testing phase is performed with two semantic segmentation methods, i.e., pixel and super-pixel based segmentation. In pixel-based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixel only – as a result, the same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel based methods is 97.68 % and 93.45% respectively.Keywords: face labeling, semantic segmentation, classification, face segmentation
Procedia PDF Downloads 2502903 Exo-III Assisted Amplification Strategy through Target Recycling of Hg²⁺ Detection in Water: A GNP Based Label-Free Colorimetry Employing T-Rich Hairpin-Loop Metallobase
Authors: Abdul Ghaffar Memon, Xiao Hong Zhou, Yunpeng Xing, Ruoyu Wang, Miao He
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Due to deleterious environmental and health effects of the Hg²⁺ ions, various online, detection methods apart from the traditional analytical tools have been developed by researchers. Biosensors especially, label, label-free, colorimetric and optical sensors have advanced with sensitive detection. However, there remains a gap of ultrasensitive quantification as noise interact significantly especially in the AuNP based label-free colorimetry. This study reported an amplification strategy using Exo-III enzyme for target recycling of Hg²⁺ ions in a T-rich hairpin loop metallobase label-free colorimetric nanosensor with an improved sensitivity using unmodified gold nanoparticles (uGNPs) as an indicator. The two T-rich metallobase hairpin loop structures as 5’- CTT TCA TAC ATA GAA AAT GTA TGT TTG -3 (HgS1), and 5’- GGC TTT GAG CGC TAA GAA A TA GCG CTC TTT G -3’ (HgS2) were tested in the study. The thermodynamic properties of HgS1 and HgS2 were calculated using online tools (http://biophysics.idtdna.com/cgi-bin/meltCalculator.cgi). The lab scale synthesized uGNPs were utilized in the analysis. The DNA sequence had T-rich bases on both tails end, which in the presence of Hg²⁺ forms a T-Hg²⁺-T mismatch, promoting the formation of dsDNA. Later, the Exo-III incubation enable the enzyme to cleave stepwise mononucleotides from the 3’ end until the structure become single-stranded. These ssDNA fragments then adsorb on the surface of AuNPs in their presence and protect AuNPs from the induced salt aggregation. The visible change in color from blue (aggregation stage in the absence of Hg²⁺) and pink (dispersion state in the presence of Hg²⁺ and adsorption of ssDNA fragments) can be observed and analyzed through UV spectrometry. An ultrasensitive quantitative nanosensor employing Exo-III assisted target recycling of mercury ions through label-free colorimetry with nanomolar detection using uGNPs have been achieved and is further under the optimization to achieve picomolar range by avoiding the influence of the environmental matrix. The proposed strategy will supplement in the direction of uGNP based ultrasensitive, rapid, onsite, label-free colorimetric detection.Keywords: colorimetric, Exo-III, gold nanoparticles, Hg²⁺ detection, label-free, signal amplification
Procedia PDF Downloads 3062902 Label Free Detection of Small Molecules Using Surface-Enhanced Raman Spectroscopy with Gold Nanoparticles Synthesized with Various Capping Agents
Authors: Zahra Khan
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Surface-Enhanced Raman Spectroscopy (SERS) has received increased attention in recent years, focusing on biological and medical applications due to its great sensitivity as well as molecular specificity. In the context of biological samples, there are generally two methodologies for SERS based applications: label-free detection and the use of SERS tags. The necessity of tagging can make the process slower and limits the use for real life. Label-free detection offers the advantage that it reports direct spectroscopic evidence associated with the target molecule rather than the label. Reproducible, highly monodisperse gold nanoparticles (Au NPs) were synthesized using a relatively facile seed-mediated growth method. Different capping agents (TRIS, citrate, and CTAB) were used during synthesis, and characterization was performed. They were then mixed with different analyte solutions before drop-casting onto a glass slide prior to Raman measurements to see which NPs displayed the highest SERS activity as well as their stability. A host of different analytes were tested, both non-biomolecules and biomolecules, which were all successfully detected using this method at concentrations as low as 10-3M with salicylic acid reaching a detection limit in the nanomolar range. SERS was also performed on samples with a mixture of analytes present, whereby peaks from both target molecules were distinctly observed. This is a fast and effective rapid way of testing samples and offers potential applications in the biomedical field as a tool for diagnostic and treatment purposes.Keywords: gold nanoparticles, label free, seed-mediated growth, SERS
Procedia PDF Downloads 1202901 A Meta Regression Analysis to Detect Price Premium Threshold for Eco-Labeled Seafood
Authors: Cristina Giosuè, Federica Biondo, Sergio Vitale
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In the last years, the consumers' awareness for environmental concerns has been increasing, and seafood eco-labels are considered as a possible instrument to improve both seafood markets and sustainable fishing management. In this direction, the aim of this study was to carry out a meta-analysis on consumers’ willingness to pay (WTP) for eco-labeled wild seafood, by a meta-regression. Therefore, only papers published on ISI journals were searched on “Web of Knowledge” and “SciVerse Scopus” platforms, using the combinations of the following key words: seafood, ecolabel, eco-label, willingness, WTP and premium. The dataset was built considering: paper’s and survey’s codes, year of publication, first author’s nationality, species’ taxa and family, sample size, survey’s continent and country, data collection (where and how), gender and age of consumers, brand and ΔWTP. From analysis the interest on eco labeled seafood emerged clearly, in particular in developed countries. In general, consumers declared greater willingness to pay than that actually applied for eco-label products, with difference related to taxa and brand.Keywords: eco label, meta regression, seafood, willingness to pay
Procedia PDF Downloads 1162900 Assessment of Highly Sensitive Dielectric Modulated GaN-FinFET for Label-Free Biosensing Applications
Authors: Ajay Kumar, Neha Gupta
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This work presents the sensitivity assessment of Gallium Nitride (GaN) material-based FinFET by dielectric modulation in the nanocavity gap for label-free biosensing applications. The significant deflection is observed in the electrical characteristics such as drain current (ID), transconductance (gm), surface potential, energy band profile, electric field, sub-threshold slope (SS), and threshold voltage (Vth) in the presence of biomolecules owing to GaN material. Further, the device sensitivity is evaluated to identify the effectiveness of the proposed biosensor and its capability to detect the biomolecules with high precision or accuracy. Higher sensitivity is observed for Gelatin (k=12) in terms of on-current (SION), threshold voltage (SVth), and switching ratio (SSR) by 104.88%, 82.12%, and 119.73%, respectively. This work is performed using a powerful tool 3D Sentaurus TCAD using a well-calibrated structure. All the results pave the way for GaN-FinFET as a viable candidate for label-free dielectric modulated biosensor applications.Keywords: biosensor, biomolecules, FinFET, sensitivity
Procedia PDF Downloads 1952899 Automatic Extraction of Arbitrarily Shaped Buildings from VHR Satellite Imagery
Authors: Evans Belly, Imdad Rizvi, M. M. Kadam
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Satellite imagery is one of the emerging technologies which are extensively utilized in various applications such as detection/extraction of man-made structures, monitoring of sensitive areas, creating graphic maps etc. The main approach here is the automated detection of buildings from very high resolution (VHR) optical satellite images. Initially, the shadow, the building and the non-building regions (roads, vegetation etc.) are investigated wherein building extraction is mainly focused. Once all the landscape is collected a trimming process is done so as to eliminate the landscapes that may occur due to non-building objects. Finally the label method is used to extract the building regions. The label method may be altered for efficient building extraction. The images used for the analysis are the ones which are extracted from the sensors having resolution less than 1 meter (VHR). This method provides an efficient way to produce good results. The additional overhead of mid processing is eliminated without compromising the quality of the output to ease the processing steps required and time consumed.Keywords: building detection, shadow detection, landscape generation, label, partitioning, very high resolution (VHR) satellite imagery
Procedia PDF Downloads 3082898 Causal Relation Identification Using Convolutional Neural Networks and Knowledge Based Features
Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi
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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation
Procedia PDF Downloads 7172897 Investigation of Various Physical and Physiological Properties of Ethiopian Elite Men Distances Runners
Authors: Getaye Fisseha Gelaw
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The purpose of this study was to investigate the key physical and physiological characteristics of 16 elite male Ethiopian national team distance runners, who have an average age of 28.1±4.3 years, a height of 175.0 ±5.6 cm, a weight of 59.1 ±3.9 kg, a BMI of 19.6 ±1.5, and training age of 10.1 ±5.1 yrs. The average weekly distance is 196.3±13.8 km, the average 10,000m time is 27:14±0.5 min sec, the average half marathon time is 59:30±0.6 min sec, the average marathon time is 2hr 03min 39sec±0.02. In addition, the average Cooper test (12-minute run test) is 4525.4±139.7 meters, and the average VO2 max is 90.8±3.1ml/kg/m. All athletes have a high profile and compete on the international label, and according to the World Athletics athletes' ranking system in 2021, 56.3% of the 16 participants were platinum label status, while the remaining 43.7 % were gold label status-completed an incremental treadmill test for the assessment of VO2peak, submaximal running, lactate threshold and test during which they ran continuously at 21 km/h. The laboratory determined VO2peak was 91.4 ± 1.7 mL/kg/min with anaerobic threshold of 74.2±1.6 mL/min/Kg and VO2max 81%. The speed at the AT is 15.9 ±0.6 Kmh and the altitude is 4,0%. The respiratory compensation RC point was reached at 88.7±1.1 mL/min/Kg and 97% of VO2 max. On RCP, the speed is 17.6 ±0.4 km/h and the altitude/slope are 5.5% percent, and the speed at Maximum effort is 19.5 ±1.5 and the elevation is 6.0%. The data also suggest that Ethiopian distance top athletes have considerably higher VO2 max values than those found in earlier research.Keywords: long-distance running, Ethiopians, VO2 max, world athletics, anthropometric
Procedia PDF Downloads 1212896 Evaluation of Stable Isotope in Life History and Mating Behaviour of Mediterranean Fruit Fly Ceratitis capitata (Diptera: Tephidae) in Laboratory Conditions
Authors: Hasan AL-Khshemawee, Manjree Agarwal, Xin Du, Yonglin Ren
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The possibility use of stable isotopes to study Medfly mating and life history were investigated in these experiments. 13C6 glucose was incorporated in the diet of the Mediterranean fruit fly Ceratitis capitata (Diptera: Tephidae). Treatments included labelling and unlabelled of either the media or adult sugar water. The measured started from egg hatching till the adults have died. After mating, the adults were analysed for 13C6 glucose ratio using Liquid chromatography-mass spectrometry LC-MS in two periods of time immediately and after three days of mating. Results showed that stable isotopes were used successfully for labelling Medfly in laboratory conditions, and there were significant differences between labelled and unlabelled treatment in eggs hatching, larval development, pupae emergence, survival of adults and mating behaviour. Labelling during larval development and combined labelling of larvae and adults resulted in detectable values. The label glucose in larvae stage did not effect on mating behaviour, however, the label glucose in adults’ stage was affected by mating behaviour. We recommended that it is possible to label adults of Mediterranean fruit fly C. capitata and detected the label after mating. This method offers good tools to study mating behaviour in Medfly and other types of insects and could be providing useful tools in genetic studies, sterile insect technique (SIT) or agricultural pest management. Also, we recommended using this technique in the field.Keywords: stable isotope, sterile insect technique (SIT), medfly, mating behaviour
Procedia PDF Downloads 2492895 Proposals for the Thermal Regulation of Buildings in Algeria: A New Energy Label for Social Housing
Authors: Marco Morini, Nicolandrea Calabrese, Dario Chello
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Despite the international commitment of Algeria towards the development of energy efficiency and renewable energy in the country, the internal energy demand has been continuously growing during the last decade due to the substantial increase of population and of living conditions, which in turn has led to an unprecedented expansion of the residential building sector. The thermal building regulation is the technical document that establishes the calculation framework for the thermal performance of buildings in Algeria, setting up minimum obligatory targets for the thermal performance of new buildings. An update of this regulation is due in the coming years, and this paper discusses some proposals in this regard, with the aim to improve the energy efficiency of the building sector, particularly with regard to social housing. In particular, it proposes a methodology for drafting an energy performance label of new Algerian residential buildings, moving from the results of the thermal compliance verification and sizing of technical systems as defined in the RTB. Such an energy performance label – whose calculation method is briefly described in the paper – aims to raise citizens' awareness of the benefits of energy efficiency. It can represent the first step in a process of integrating technical installations into the calculation of the energy performance of buildings in Algeria.Keywords: building, energy certification, energy efficiency, social housing, international cooperation, Mediterranean region
Procedia PDF Downloads 1382894 A Dataset of Program Educational Objectives Mapped to ABET Outcomes: Data Cleansing, Exploratory Data Analysis and Modeling
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
Procedia PDF Downloads 1642893 Formalizing the Sense Relation of Hyponymy from Logical Point of View: A Study of Mathematical Linguistics in Farsi
Authors: Maryam Ramezankhani
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The present research tries to study the possibility of formalizing the sense relation of hyponymy. It applied mathematical tools and also uses mathematical logic concepts especially those from propositional logic. In order to do so, firstly, it goes over the definitions of hyponymy presented in linguistic dictionaries and semantic textbooks. Then, it introduces a formal translation of the sense relation of hyponymy. Lastly, it examines the efficiency of the suggested formula by some examples of natural language.Keywords: sense relations, hyponymy, formalizing, words’ sense relation, formalizing sense relations
Procedia PDF Downloads 2322892 Solving Definition and Relation Problems in English Navigation Terminology
Authors: Ayşe Yurdakul, Eckehard Schnieder
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Because of the growing multidisciplinarity and multilinguality, communication problems in different technical fields grows more and more. Therefore, each technical field has its own specific language, terminology which is characterised by the different definition of terms. In addition to definition problems, there are also relation problems between terms. Among these problems of relation, there are the synonymy, antonymy, hypernymy/hyponymy, ambiguity, risk of confusion, and translation problems etc. Thus, the terminology management system iglos of the Institute for Traffic Safety and Automation Engineering of the Technische Universität Braunschweig has the target to solve these problems by a methodological standardisation of term definitions with the aid of the iglos sign model and iglos relation types. The focus of this paper should be on solving definition and relation problems between terms in English navigation terminology.Keywords: iglos, iglos sign model, methodological resolutions, navigation terminology, common language, technical language, positioning, definition problems, relation problems
Procedia PDF Downloads 3232891 Environmental Assessment of Roll-to-Roll Printed Smart Label
Authors: M. Torres, A. Moulay, M. Zhuldybina, M. Rozel, N. D. Trinh, C. Bois
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Printed electronics are a fast-growing market as their applications cover a large range of industrial needs, their production cost is low, and the additive printing techniques consume less materials than subtractive manufacturing methods used in traditional electronics. With the growing demand for printed electronics, there are concerns about their harmful and irreversible contribution to the environment. Indeed, it is estimated that 80% of the environmental load of a product is determined by the choices made at the conception stage. Therefore, examination through a life cycle approach at the developing stage of a novel product is the best way to identify potential environmental issues and make proactive decisions. Life cycle analysis (LCA) is a comprehensive scientific method to assess the environmental impacts of a product in its different stages of life: extraction of raw materials, manufacture and distribution, use, and end-of-life. Impacts and major hotspots are identified and evaluated through a broad range of environmental impact categories of the ReCiPe (H) middle point method. At the conception stage, the LCA is a tool that provides an environmental point of view on the choice of materials and processes and weights-in on the balance between performance materials and eco-friendly materials. Using the life cycle approach, the current work aims to provide a cradle-to-grave life cycle assessment of a roll-to-roll hybrid printed smart label designed for the food cold chain. Furthermore, this presentation will present the environmental impact of metallic conductive inks, a comparison with promising conductive polymers, evaluation of energy vs. performance of industrial printing processes, a full assessment of the impact from the smart label applied on a cellulosic-based substrate during the recycling process and the possible recovery of precious metals and rare earth elements.Keywords: Eco-design, label, life cycle assessment, printed electronics
Procedia PDF Downloads 1572890 Signal Amplification Using Graphene Oxide in Label Free Biosensor for Pathogen Detection
Authors: Agampodi Promoda Perera, Yong Shin, Mi Kyoung Park
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The successful detection of pathogenic bacteria in blood provides important information for early detection, diagnosis and the prevention and treatment of infectious diseases. Silicon microring resonators are refractive-index-based optical biosensors that provide highly sensitive, label-free, real-time multiplexed detection of biomolecules. We demonstrate the technique of using GO (graphene oxide) to enhance the signal output of the silicon microring optical sensor. The activated carboxylic groups in GO molecules bind directly to single stranded DNA with an amino modified 5’ end. This conjugation amplifies the shift in resonant wavelength in a real-time manner. We designed a capture probe for strain Staphylococcus aureus of 21 bp and a longer complementary target sequence of 70 bp. The mismatched target sequence we used was of Streptococcus agalactiae of 70 bp. GO is added after the complementary binding of the probe and target. GO conjugates to the unbound single stranded segment of the target and increase the wavelength shift on the silicon microring resonator. Furthermore, our results show that GO could successfully differentiate between the mismatched DNA sequences from the complementary DNA sequence. Therefore, the proposed concept could effectively enhance sensitivity of pathogen detection sensors.Keywords: label free biosensor, pathogenic bacteria, graphene oxide, diagnosis
Procedia PDF Downloads 462