Search results for: terrain classification

Authors: Hong-Nam Choi, Hyeong-Wook Song, Sungwan Hong, Hong-Kyu Kim

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In Korea, elements that decide the quality of residential environment are not only diverse, but show deviation as well. However, people do not consider these elements and instead, they try to settle the uniformed style of residential environment, which focuses on the construction development of apartment housing and business based plans. Recently, block-unit redevelopment is becoming the standout alternative plan of standardize redevelopment projects, but constructions become inefficient because of indefinite planning criteria. In conclusion, the following research is about analyzing and categorizing the development method and legal ground of redevelopment project district, plan determinant and applicable standard. The purpose of this study is to become a basis in compatible analysis of planning standards that will happen in the future.

Keywords: shape restrictions, improvement of regulation, diversity of residential environment, classification of redevelopment project, planning criteria of redevelopment, special architectural district (SAD)

Procedia PDF Downloads 484

Authors: Artemis Louppis, Michalis Constantinou, Ioanna Kosma, Federica Blando, Michael Kontominas, Anastasia Badeka

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The aim of the present study was to differentiate yellow prickly pear according to geographical origin based on the combination of mineral content, physicochemical parameters, vitamins and antioxidants. A total of 240 yellow prickly pear samples from Cyprus, Spain, Italy and Greece were analyzed for pH, titratable acidity, electrical conductivity, protein, moisture, ash, fat, antioxidant activity, individual antioxidants, sugars and vitamins by UPLC-MS/MS as well as minerals by ICP-MS. Statistical treatment of the data included multivariate analysis of variance followed by linear discriminant analysis. Based on results, a correct classification of 66.7% was achieved using the cross validation by mineral content while 86.1% was achieved using the cross validation method by combination of all analytical parameters.

Keywords: geographical differentiation, prickly pear, chemometrics, analytical techniques

Procedia PDF Downloads 143

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 255

Authors: Raquel Ramos López, Anissa El-Khattabi, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

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An increasing number of mobile devices with integrated cameras has meant that most digital video comes from these devices. These digital videos can be made anytime, anywhere and for different purposes. They can also be shared on the Internet in a short period of time and may sometimes contain recordings of illegal acts. The need to reliably trace the origin becomes evident when these videos are used for forensic purposes. This work proposes an algorithm to identify the brand and model of mobile device which generated the video. Its procedure is as follows: after obtaining the relevant video information, a classification algorithm based on sensor noise and Wavelet Transform performs the aforementioned identification process. We also present experimental results that support the validity of the techniques used and show promising results.

Keywords: digital video, forensics analysis, key frame, mobile device, PRNU, sensor noise, source identification

Procedia PDF Downloads 428

Authors: Nicholas Anderson, Steven Petersen, Tom Bates, Val Anderson

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Under the multiple-use management regime established in the United States for federally owned lands, government agencies have come under pressure from commercial apiaries to grant permits for the summer pasturing of honeybees on government lands. Federal agencies have struggled to integrate honeybees into their management plans and have little information to make regulations that resolve how many colonies should be allowed in a single location and at what distance sets of hives should be placed. Many conservation groups have voiced their concerns regarding the introduction of honeybees to these natural lands, as they may outcompete and displace native pollinating species. Assessing the quality of an area in regard to its floral resources, pollen, and nectar can be important when attempting to create regulations for the integration of commercial honeybee operations into a native ecosystem. Areas with greater floral resources may be able to support larger numbers of honeybee colonies, while poorer resource areas may be less resilient to introduced disturbances. Attempts are made in this study to determine flower cover using high resolution drone imagery to help assess the floral resource availability to pollinators in high elevation, tall forb communities. This knowledge will help in determining the potential that different areas may have for honeybee pasturing and honey production. Roughly 700 images were captured at 23m above ground level using a drone equipped with a Sony QX1 RGB 20-megapixel camera. These images were stitched together using Pix4D, resulting in a 60m diameter high-resolution mosaic of a tall forb meadow. Using the program ENVI, a supervised maximum likelihood classification was conducted to calculate the percentage of total flower cover and flower cover by color (blue, white, and yellow). A complete vegetation inventory was taken on site, and the major flowers contributing to each color class were noted. An accuracy assessment was performed on the classification yielding an 89% overall accuracy and a Kappa Statistic of 0.855. With this level of accuracy, drones provide an affordable and time efficient method for the assessment of floral cover in large areas. The proximal step of this project will now be to determine the average pollen and nectar loads carried by each flower species. The addition of this knowledge will result in a quantifiable method of measuring pollen and nectar resources of entire landscapes. This information will not only help land managers determine stocking rates for honeybees on public lands but also has applications in the agricultural setting, aiding producers in the determination of the number of honeybee colonies necessary for proper pollination of fruit and nut crops.

Keywords: honeybee, flower, pollinator, remote sensing

Procedia PDF Downloads 141

Authors: R. Gupta, P. Jain, S. Das

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One way to approach construction scheduling optimization problem is to focus on the individual aspects of planning, which can be broadly classified as time scheduling, crew and resource management, and cost control. During the last four decades, construction planning has seen a lot of research, but to date, no paper had attempted to summarize the literature available under important heads. This paper addresses each of aspects separately, and presents the findings of an in-depth literature of the various planning techniques. For techniques dealing with time scheduling, the authors have adopted a rough chronological documentation. For crew and resource management, classification has been done on the basis of the different steps involved in the resource planning process. For cost control, techniques dealing with both estimation of costs and the subsequent optimization of costs have been dealt with separately.

Keywords: construction planning techniques, time scheduling, resource planning, cost control

Procedia PDF Downloads 487

Authors: Yuan-lin Liu, Ye Li, Tian Xia

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There are some shortcomings in Chinese existing taxi management modes. This paper suggests to establish the third-party comprehensive information management platform and put forward an evaluation model based on credit. Four indicators are used to evaluate the drivers’ credit, they are passengers’ evaluation score, driving behavior evaluation, drivers’ average bad record number, and personal credit score. A weighted clustering method is used to achieve credit level evaluation for taxi drivers. The management of taxi industry is based on the credit level, while the grade of the drivers is accorded to their credit rating. Credit rating determines the cost, income levels, the market access, useful period of license and the level of wage and bonus, as well as violation fine. These methods can make the credit evaluation effective. In conclusion, more credit data will help to set up a more accurate and detailed classification standard library.

Keywords: credit, mobile internet, e-hailing taxi, management mode, weighted cluster

Procedia PDF Downloads 325

Authors: Narin Salehiyan, Ramin Ghasemi Shayan

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The largest genus of plant viruses, the potyvirus, is responsible for significant crop losses. Potyviruses are aphid sent in a nonpersistent way, and some of them are likewise seed communicated. As significant microorganisms, potyviruses are substantially more examined than other plant infections having a place with different genera, and their review covers numerous parts of plant virology, like utilitarian portrayal of viral proteins, sub-atomic communication with hosts and vectors, structure, scientific classification, development, the study of disease transmission, and determination. Biotechnological utilizations of potyviruses are likewise being investigated. During this last ten years, significant advances have been made in the comprehension of the sub-atomic science of these infections and the elements of their different proteins. Potyvirus multiplication, movement, and transmission, as well as potyvirus/plant compatible interactions, including pathogenicity and symptom determinants, are updated following a general overview of the family Potyviridae and the potyviral proteins. it end the survey giving data on biotechnological uses of potyviruses.

Keywords: virology, poty, virus, genome, genetic

Procedia PDF Downloads 73

Authors: Ke Zhang, Yongli Zhu

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Due to rapid load growths in today’s highly electrified societies and the requirement for green energy sources, large-scale wind farm power transmission system is constantly developing. This system is a typical multi-terminal power supply system, whose structure of the network topology of transmission lines is complex. What’s more, it locates in the complex terrain of mountains and grasslands, thus increasing the possibility of transmission line faults and finding the fault location with difficulty after the faults and resulting in an extremely serious phenomenon of abandoning the wind. In order to solve these problems, a fault location method for multi-terminal transmission line based on wind farm characteristics and improved single-ended traveling wave positioning method is proposed. Through studying the zero sequence current characteristics by using the characteristics of the grounding transformer(GT) in the existing large-scale wind farms, it is obtained that the criterion for judging the fault interval of the multi-terminal transmission line. When a ground short-circuit fault occurs, there is only zero sequence current on the path between GT and the fault point. Therefore, the interval where the fault point exists is obtained by determining the path of the zero sequence current. After determining the fault interval, The location of the short-circuit fault point is calculated by the traveling wave method. However, this article uses an improved traveling wave method. It makes the positioning accuracy more accurate by combining the single-ended traveling wave method with double-ended electrical data. What’s more, a method of calculating the traveling wave velocity is deduced according to the above improvements (it is the actual wave velocity in theory). The improvement of the traveling wave velocity calculation method further improves the positioning accuracy. Compared with the traditional positioning method, the average positioning error of this method is reduced by 30%.This method overcomes the shortcomings of the traditional method in poor fault location of wind farm transmission lines. In addition, it is more accurate than the traditional fixed wave velocity method in the calculation of the traveling wave velocity. It can calculate the wave velocity in real time according to the scene and solve the traveling wave velocity can’t be updated with the environment and real-time update. The method is verified in PSCAD/EMTDC.

Keywords: grounding transformer, multi-terminal transmission line, short circuit fault location, traveling wave velocity, wind farm

Procedia PDF Downloads 263

Authors: J. Tamosaitiene

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The article focuses on the identification and classification of key risk management criteria that represent the most important sustainability aspects of the construction industry. The construction sector is one of the most important sectors in Lithuania. Nowadays, the assessment of the risk level of a construction project is especially important for the quality of construction projects, the growth of enterprises and the sector. To establish the most important criteria for successful growth of the sector, a questionnaire for experts was developed. The analytic hierarchy process (AHP), the expert judgement method and other multicriteria decision making (MCDM) methods were used to develop the hybrid model. The results were used to develop an integrated knowledge system for the measurement of a risk level particular to construction projects. The article presents a practical case that details the developed system, sustainable aspects, and risk assessment.

Keywords: risk, system, model, construction

Procedia PDF Downloads 167

Authors: Leila Torkaman, Nasser Ghassembaglou

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Significant quota of Municipal Electrical Energy consumption is related to Decentralized Air Conditioning which is mostly provided by evaporative coolers. So the aim is to optimize design of air conditioners to increase their efficiencies. To achieve this goal, results of practical standardized tests for 40 evaporative coolers in different types collected and simultaneously results for same coolers based on one of EER (Energy Efficiency Ratio) modeling styles are figured out. By comparing experimental results of different coolers standardized tests with modeling results, preciseness of used model is assessed and after comparing gained preciseness with international standards based on EER for cooling capacity, aeration and also electrical energy consumption, energy label from A (most effective) to G (less effective) is classified. finally needed methods to optimize energy consumption and cooler's classification are provided.

Keywords: cooler, EER, energy label, optimization

Procedia PDF Downloads 344

Authors: Nadia el Atlas, Mohammed el Aroussi, Mohammed Wahbi

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In this paper a novel technique of mass characterization based on robust features-fusion is presented. The proposed method consists of mainly four stages: (a) the first phase involves segmenting the masses using edge information’s. (b) The second phase is to calculate and fuse the most relevant morphological features. (c) The last phase is the classification step which allows us to classify the images into benign and malignant masses. In this step we have implemented Support Vectors Machines (SVM) and Artificial Neural Networks (ANN), which were evaluated with the following performance criteria: confusion matrix, accuracy, sensitivity, specificity, receiver operating characteristic ROC, and error histogram. The effectiveness of this new approach was evaluated by a recently developed database: INBREAST database. The fusion of the most appropriate morphological features provided very good results. The SVM gives accuracy to within 64.3%. Whereas the ANN classifier gives better results with an accuracy of 97.5%.

Keywords: breast cancer, mammography, CAD system, features, fusion

Procedia PDF Downloads 599

Authors: Chaima Babi, Said Gadri

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The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

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Authors: Petra Hurbišová, Monika Davidová

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The article deals with the readiness of military professionals for challenging situations. It discusses higher requirements on the psychical endurance of military professionals arising from the specific nature of the military occupation, which is typical for being very difficult to maintain regularity, which is in accordance with the hygiene of work alternated by relaxation. The soldier must be able to serve in the long term and constantly intense performance that goes beyond human tolerance to stress situations. A challenging situation is always associated with overcoming difficulties, obstacles and complicated circumstances or using unusual methods, ways and means to achieve the desired (expected) objectives, performing a given task or satisfying an important need. This paper describes the categories of challenging situations, their classification and characteristics. Attention is also paid to the formation of personality in challenging situations, coping with stress in challenging situations, Phases of solutions of stressful situations, resistance to challenging life situations and its factors. Finally, the article is focused on increasing the readiness of military professionals for challenging situations.

Keywords: coping, challenging situations, stress, stressful situations, military professionals, resilience

Procedia PDF Downloads 316

Authors: M. Aouimeur

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The environmental risks of a dam and particularly the security in the Valley downstream of it,, is a very complex problem. Integrated management and risk-sharing become more and more indispensable. The definition of "vulnerability “concept can provide assistance to controlling the efficiency of protective measures and the characterization of each valley relatively to the floods's risk. Security can be enhanced through the integrated land management. The social sciences may be associated to the operational systems of civil protection, in particular warning networks. The passage of extreme floods in the site of the dam causes the rupture of this structure and important damages downstream the dam. The river bed could be damaged by erosion if it is not well protected. Also, we may encounter some scouring and flooding problems in the downstream area of the dam. Therefore, the protection of the dam is crucial. It must have an energy dissipator in a specific place. The basin of dissipation plays a very important role for the security of the dam and the protection of the environment against floods downstream the dam. It allows to dissipate the potential energy created by the dam with the passage of the extreme flood on the weir and regularize in a natural manner and with more security the discharge or elevation of the water plan on the crest of the weir, also it permits to reduce the speed of the flow downstream the dam, in order to obtain an identical speed to the river bed. The problem of the dimensioning of a classic dissipation basin is in the determination of the necessary parameters for the dimensioning of this structure. This communication presents a simple graphical method, that is fast and complete, and a methodology which determines the main features of the hydraulic jump, necessary parameters for sizing the classic dissipation basin. This graphical method takes into account the constraints imposed by the reality of the terrain or the practice such as the one related to the topography of the site, the preservation of the environment equilibrium and the technical and economic side.This methodology is to impose the loss of head DH dissipated by the hydraulic jump as a hypothesis (free design) to determine all the others parameters of classical dissipation basin. We can impose the loss of head DH dissipated by the hydraulic jump that is equal to a selected value or to a certain percentage of the upstream total head created by the dam. With the parameter DH+ =(DH/k),(k: critical depth),the elaborate graphical representation allows to find the other parameters, the multiplication of these parameters by k gives the main characteristics of the hydraulic jump, necessary parameters for the dimensioning of classic dissipation basin.This solution is often preferred for sizing the dissipation basins of small concrete dams. The results verification and their comparison to practical data, confirm the validity and reliability of the elaborate graphical method.

Keywords: dimensioning, energy dissipation basin, hydraulic jump, protection of the environment

Procedia PDF Downloads 583

Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

Procedia PDF Downloads 151

Authors: Thang V. Kieu, Long P. Nguyen

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Kernelized Correlation Filter (KCF) based trackers have gained a lot of attention recently because of their accuracy and fast calculation speed. However, this algorithm is not robust in cases where the object is lost by a sudden change of direction, being obscured or going out of view. In order to improve KCF performance in long-term tracking, this paper proposes an anomaly detection method for target loss warning by analyzing the response map of each frame, and a classification algorithm for reliable target re-locating mechanism by using Random fern. Being tested with Visual Tracker Benchmark and Visual Object Tracking datasets, the experimental results indicated that the precision and success rate of the proposed algorithm were 2.92 and 2.61 times higher than that of the original KCF algorithm, respectively. Moreover, the proposed tracker handles occlusion better than many state-of-the-art long-term tracking methods while running at 60 frames per second.

Keywords: correlation filter, long-term tracking, random fern, real-time tracking

Procedia PDF Downloads 138

Authors: Musaab Riyadh, Norwati Mustapha, Dina Riyadh

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Trajectory similarity can be defined as the cost of transforming one trajectory into another based on certain similarity method. It is the core of numerous mining tasks such as clustering, classification, and indexing. Various approaches have been suggested to measure similarity based on the geometric and dynamic properties of trajectory, the overlapping between trajectory segments, and the confined area between entire trajectories. In this article, an evaluation of these approaches has been done based on computational cost, usage memory, accuracy, and the amount of data which is needed in advance to determine its suitability to stream mining applications. The evaluation results show that the stream mining applications support similarity methods which have low computational cost and memory, single scan on data, and free of mathematical complexity due to the high-speed generation of data.

Keywords: global distance measure, local distance measure, semantic trajectory, spatial dimension, stream data mining

Procedia PDF Downloads 396

Authors: Mikhail Zimin, Svetlana Zimina, Maxim Zimin

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Without question, the basic method of prevention of human and material losses is the provision for adequate strength of constructions. At the same time, seismic load has a stochastic character. So, at all times, there is little danger of earthquake forces exceeding the selected design load. This risk is very low, but the consequences of such events may be extremely serious. Very dangerous are also occasional mistakes in seismic zoning, soil conditions changing before temblors, and failure to take into account hazardous natural phenomena caused by earthquakes. Besides, it is known that temblors detrimentally affect the environmental situation in regions where they occur, resulting in panic and worsening various disease courses. It may lead to mistakes of personnel of hazardous production facilities like the production and distribution of gas and oil, which may provoke severe accidents. In addition, gas and oil pipelines often have long mileage and cross many perilous zones by contrast with buildings. This situation increases the risk of heavy accidents. In such cases, complex monitoring of potential earthquake localities would be relevant. Even though the number of successful real-time forecasts of earthquakes is not great, it is well in excess, such as may be under random guessing. Experimental performed time-lapse study and analysis consist of searching seismic, biological, meteorological, and light earthquake precursors, processing such data with the help of fuzzy sets, collecting weather information, utilizing a database of terrain, and computing risk of slope processes under the temblor in a given setting. Works were done in a real-time environment and broadly acceptable results took place. Observations from already in-place seismic recording systems are used. Furthermore, a look back study of precursors of known earthquakes is done. Situations before Ashkhabad, Tashkent, and Haicheng seismic events are analyzed. Fairish findings are obtained. Results of earthquake forecasts can be used for predicting dangerous natural phenomena caused by temblors such as avalanches and mudslides. They may also be utilized for prophylaxis of some diseases and their complications. Relevant software is worked out too. It should be emphasized that such control does not require serious financial expenses and can be performed by a small group of professionals. Thus, complex monitoring of potential earthquake localities, including short-term earthquake forecasts and analysis of possible hazardous consequences of temblors, may further the safety of pipeline facilities.

Keywords: risk, earthquake, monitoring, forecast, precursor

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Authors: Farshideh Einsele, Hassan Foroosh

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In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using wellknown geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: camera-based OCR, feature extraction, document, image processing, grocery products

Procedia PDF Downloads 406

Authors: Omonov Jahongir Mahmatkulovic

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Purpose: To study the significance of D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen coagulation parameters (Fg) in predicting the course, severity and prognosis of COVID-19. Source and method of research: From September 15, 2021, to November 5, 2021, 93 patients aged 25 to 60 with suspected COVID-19, who are under inpatient treatment at the multidisciplinary clinic of the Tashkent Medical Academy, were retrospectively examined. DD, PT, APTT, and Fg were studied in dynamics and studied changes. Results: Coagulation disorders occurred in the early stages of COVID-19 infection with an increase in DD in 54 (58%) patients and an increase in Fg in 93 (100%) patients. DD and Fg levels are associated with the clinical classification. Of the 33 patients who died, 21 had an increase in DD in the first laboratory study, 27 had an increase in DD in the second and third laboratory studies, and 15 had an increase in PT in the third test. The results of the ROC analysis of mortality showed that the AUC DD was three times 0.721, 0.801, and 0.844, respectively; PT was 0.703, 0.845, and 0.972. (P<0:01). Conclusion”: Coagulation dysfunction is more common in patients with severe and critical conditions. DD and PT can be used as important predictors of mortality from COVID-19.

Keywords: Covid19, DD, PT, Coagulogram analysis, APTT

Procedia PDF Downloads 107

Authors: Kamel Laidi, Khelifa Benmansour, Ouahid Bouchhida

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Neural networks-based approach for 2-cells serial converter has been developed and implemented. The approach is based on a behavioural description of the different operating modes of the converter. Each operating mode represents a well-defined configuration, and for which is matched an operating zone satisfying given invariance conditions, depending on the capacitors' voltages and the load current of the converter. For each mode, a control vector whose components are the control signals to be applied to the converter switches has been associated. Therefore, the problem is reduced to a classification task of the different operating modes of the converter. The artificial neural nets-based approach, which constitutes a powerful tool for this kind of task, has been adopted and implemented. The application to a 2-cells chopper has allowed ensuring efficient and robust control of the load current and a high capacitors voltages balancing.

Keywords: neural nets, control, multicellular converters, 2-cells chopper

Procedia PDF Downloads 834

Authors: Emad A. Mohammed

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Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

Procedia PDF Downloads 144

Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

Procedia PDF Downloads 93

Authors: Vesna Pungercar, Florian Musso

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Identifying materials that can substitute rare or expensive natural resources is one of the key challenges for improving resource efficiency in the building sector. With a growing world population and rising living standards, more and more salt is produced as waste through seawater desalination and potash mining processes. Unfortunately, most of the salt is directly disposed of into nature, where it causes environmental pollution. On the other hand, salt is affordable, is used therapeutically in various respiratory treatments, and can store humidity and heat. It was, therefore, necessary to determine salt materials already in use in building construction and their hygrothermal properties. This research aims to identify salt materials from different scientific branches and historically, to investigate their properties and prioritize the most promising salt materials for indoor applications in a thermal envelope. This was realized through literature review and classification of salt materials into three groups (raw salt materials, composite salt materials, and processed salt materials). The outcome of this research shows that salt has already been used as a building material for centuries and has a potential for future applications due to its hygrothermal properties in a thermal envelope.

Keywords: salt, building material, hygrothermal properties, environment

Procedia PDF Downloads 169

Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh

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The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.

Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features

Procedia PDF Downloads 526

Authors: Levent Basayigit, Mert Dedeoglu, Fadime Ozogul

Abstract:

In this study, an application was carried out to determine the Volcanic Soils by using remote sensing.  The study area was located on the Golcuk formation in Isparta-Turkey. The thermal bands of Landsat 7 image were used for processing. The implementation of the climate model that was based on the water index was used in ERDAS Imagine software together with pixel based image classification. Soil Moisture Index (SMI) was modeled by using the surface temperature (Ts) which was obtained from thermal bands and vegetation index (NDVI) derived from Landsat 7. Surface moisture values were grouped and classified by using scoring system. Thematic layers were compared together with the field studies. Consequently, different moisture levels for volcanic soils were indicator for determination and separation. Those thermal wavelengths are preferable bands for separation of volcanic soils using moisture and temperature models.

Keywords: Landsat 7, soil moisture index, temperature models, volcanic soils

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Authors: Wahab Ali, Oyebade K. Oyedotun, Adnan Khashman

Abstract:

Breast cancer remains a threat to the woman’s world in view of survival rates, it early diagnosis and mortality statistics. So far, research has shown that many survivors of breast cancer cases are in the ones with early diagnosis. Breast cancer is usually categorized into stages which indicates its severity and corresponding survival rates for patients. Investigations show that the farther into the stages before diagnosis the lesser the chance of survival; hence the early diagnosis of breast cancer becomes imperative, and consequently the application of novel technologies to achieving this. Over the year, mammograms have used in the diagnosis of breast cancer, but the inconclusive deductions made from such scans lead to either false negative cases where cancer patients may be left untreated or false positive where unnecessary biopsies are carried out. This paper presents the application of artificial neural networks in the prediction of severity of breast tumour (whether benign or malignant) using mammography reports and other factors that are related to breast cancer.

Keywords: breast cancer, intelligent classification, neural networks, mammography

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Authors: Aleksandra Jonas, Aleksandra Gronowska, Maciej Ścigacz, Szymon Jadczak

Abstract:

Exact Data is a smart tool which helps with meaningful marketing content creation. It helps marketers achieve this by analyzing the text of an advertisement before and after its publication on social media sites like Facebook or Instagram. In our research we focus on four areas of natural language processing (NLP): grammar correction, sentiment analysis, irony detection and advertisement interpretation. Our research has identified a considerable lack of NLP tools for the Polish language, which specifically aid online marketers. In light of this, our research team has set out to create a robust and versatile NLP tool for the Polish language. The primary objective of our research is to develop a tool that can perform a range of language processing tasks in this language, such as sentiment analysis, text classification, text correction and text interpretation. Our team has been working diligently to create a tool that is accurate, reliable, and adaptable to the specific linguistic features of Polish, and that can provide valuable insights for a wide range of marketers needs. In addition to the Polish language version, we are also developing an English version of the tool, which will enable us to expand the reach and impact of our research to a wider audience. Another area of focus in our research involves tackling the challenge of the limited availability of linguistically diverse corpora for non-English languages, which presents a significant barrier in the development of NLP applications. One approach we have been pursuing is the translation of existing English corpora, which would enable us to use the wealth of linguistic resources available in English for other languages. Furthermore, we are looking into other methods, such as gathering language samples from social media platforms. By analyzing the language used in social media posts, we can collect a wide range of data that reflects the unique linguistic characteristics of specific regions and communities, which can then be used to enhance the accuracy and performance of NLP algorithms for non-English languages. In doing so, we hope to broaden the scope and capabilities of NLP applications. Our research focuses on several key NLP techniques including sentiment analysis, text classification, text interpretation and text correction. To ensure that we can achieve the best possible performance for these techniques, we are evaluating and comparing different approaches and strategies for implementing them. We are exploring a range of different methods, including transformers and convolutional neural networks (CNNs), to determine which ones are most effective for different types of NLP tasks. By analyzing the strengths and weaknesses of each approach, we can identify the most effective techniques for specific use cases, and further enhance the performance of our tool. Our research aims to create a tool, which can provide a comprehensive analysis of advertising effectiveness, allowing marketers to identify areas for improvement and optimize their advertising strategies. The results of this study suggest that a smart tool for advertisement analysis can provide valuable insights for businesses seeking to create effective advertising campaigns.

Keywords: NLP, AI, IT, language, marketing, analysis

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