Search results for: GLCM texture features

Authors: Nengi A. H. Ejiobih

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Conflict is one of the defining features of human societies. Often, the use or misuse of language in interaction is the genesis of conflict. As such, it is expected that when people use language they do so in socially determined ways and with almost predictable social effects. The objective of this paper was to examine the interest at work as manifested in language choice and collocations in conflict discourse. It also scrutinized the implications of linguistic features in conflict discourse as it concerns ideology and power relations in political discourse in Nigeria. The methodology used for this paper is an approach from Critical discourse analysis because of its multidisciplinary model of analysis, linguistic features and its implications were analysed. The datum used is a text from the Sunday Sun Newspaper in Nigeria, West Africa titled Akunyili Memo: State of the Nation. Some of the findings include; different ideologies are inherent in conflict discourse, there is the presence of power relations being produced, exercised, maintained and produced throughout the discourse and the use of pronouns in conflict discourse is valuable because it is used to initiate and maintain relationships in social context. This paper has provided evidence that, taking into consideration the nature of the social actions and the way these activities are translated into languages, the meanings people convey by their words are identified by their immediate social, political and historical conditions.

Keywords: conflicts, discourse, language, linguistic features, social context

Procedia PDF Downloads 455

Authors: M. Ibrahim Ali, M. El Dawi, M. A. Mohamed Ali

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In this study, the use of magnetic gradient survey, and the geoelectrical ground methods used together to explore archaeological features in Nuri’s pyramids area. Research methods used and the procedures and methodologies have taken full right during the study. The magnetic survey method was used to search for archaeological features using (Geoscan Fluxgate Gradiometer (FM36)). The study area was divided into a number of squares (networks) exactly equal (20 * 20 meters). These squares were collected at the end of the study to give a major network for each region. Networks also divided to take the sample using nets typically equal to (0.25 * 0.50 meter), in order to give a more specific archaeological features with some small bipolar anomalies that caused by buildings built from fired bricks. This definition is important to monitor many of the archaeological features such as rooms and others. This main network gives us an integrated map displayed for easy presentation, and it also allows for all the operations required using (Geoscan Geoplot software). The parallel traverse is the main way to take readings of the magnetic survey, to get out the high-quality data. The study area is very rich in old buildings that vary from small to very large. According to the proportion of the sand dunes and the loose soil, most of these buildings are not visible from the surface. Because of the proportion of the sandy dry soil, there is no connection between the ground surface and the electrodes. We tried to get electrical readings by adding salty water to the soil, but, unfortunately, we failed to confirm the magnetic readings with electrical readings as previously planned.

Keywords: archaeological features, independent grids, magnetic gradient, Nuri pyramid

Procedia PDF Downloads 463

Authors: Mayank Raj, V. G. Narendra

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Ever since the DARPA challenge on autonomous vehicles in 2005, there has been a lot of buzz about ‘Autonomous Vehicles’ amongst the major tech giants such as Google, Uber, and Tesla. Numerous approaches have been adopted to solve this problem, which can have a long-lasting impact on mankind. In this paper, we have used Deep Learning techniques and TensorFlow framework with the goal of building a neural network model to predict (speed, acceleration, steering angle, and brake) features needed for navigation of autonomous vehicles. The Deep Neural Network has been trained on images and sensor data obtained from the comma.ai dataset. A heatmap was used to check for correlation among the features, and finally, four important features were selected. This was a multivariate regression problem. The final model had five convolutional layers, followed by five dense layers. Finally, the calculated values were tested against the labeled data, where the mean squared error was used as a performance metric.

Keywords: autonomous vehicles, deep learning, computer vision, artificial intelligence

Procedia PDF Downloads 134

Authors: Benjamin Beltzung, Marie Pelé, Julien P. Renoult, Cédric Sueur

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To this day, it is not known if drawing is specifically human behavior or if this behavior finds its origins in ancestor species. An interesting window to enlighten this question is to analyze the drawing behavior in genetically close to human species, such as non-human primate species. A good candidate for this approach is the orangutan, who shares 97% of our genes and exhibits multiple human-like behaviors. Focusing on figurative aspects may not be suitable for orangutans’ drawings, which may appear as scribbles but may have meaning. A manual feature selection would lead to an anthropocentric bias, as the features selected by humans may not match with those relevant for orangutans. In the present study, we used deep learning to analyze the drawings of a female orangutan named Molly († in 2011), who has produced 1,299 drawings in her last five years as part of a behavioral enrichment program at the Tama Zoo in Japan. We investigate multiple ways to decipher Molly’s drawings. First, we demonstrate the existence of differences between seasons by training a deep learning model to classify Molly’s drawings according to the seasons. Then, to understand and interpret these seasonal differences, we analyze how the information spreads within the network, from shallow to deep layers, where early layers encode simple local features and deep layers encode more complex and global information. More precisely, we investigate the impact of feature complexity on classification accuracy through features extraction fed to a Support Vector Machine. Last, we leverage style transfer to dissociate features associated with drawing style from those describing the representational content and analyze the relative importance of these two types of features in explaining seasonal variation. Content features were relevant for the classification, showing the presence of meaning in these non-figurative drawings and the ability of deep learning to decipher these differences. The style of the drawings was also relevant, as style features encoded enough information to have a classification better than random. The accuracy of style features was higher for deeper layers, demonstrating and highlighting the variation of style between seasons in Molly’s drawings. Through this study, we demonstrate how deep learning can help at finding meanings in non-figurative drawings and interpret these differences.

Keywords: cognition, deep learning, drawing behavior, interpretability

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Authors: Ismail Baniadam, Nafisa Tadayyon, Javid Fereidoni

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This study aimed to investigate medical students’ attitudes toward some teachers’ talking features regarding their gender in the Iranian context. To do so, 60 male and 60 female medical students of Urmia University of Medical Sciences (UMSU) participated in the research. A researcher made Likert-type questionnaire which was initially piloted and was used to gather the data. Comparing the four different factors regarding the features of teacher talk, it was revealed that visual and extra-linguistic information factor, Lexical and syntactic familiarity, Speed of speech, and the use of Persian language had the highest to the lowest mean score, respectively. It was also indicated that female students rather than male students were significantly more in favor of speed of speech and lexical and syntactic familiarity.

Keywords: attitude, gender, medical student, teacher talk

Procedia PDF Downloads 155

Authors: Banafsheh Aghamohammadi, Masoud Honarvar, Babak Ghiassi Tarzi

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Usage of different components has been considered to improve the quality and nutritional properties of cakes in recent years. The effects of applying some sweeteners, instead of sugar, have been evaluated in cakes and many bread formulas up to now; but there has not been any research about the usage of by-products of sugar factories such as Wash and Green-A Syrups in cake formulas. In this research, the effects of substituting 25%, 50%, 75% and 100% of sugar with Wash and Green-A Syrups on some dough and cake properties, such as pH, viscosity, density, volume, weight loss, moisture, water activity, texture, staling, color and sensory evaluations, are studied. The results of these experiments showed that the pH values were not significantly different among any of the all cake batters and also most of the cake samples. Although differences among viscosity and specific gravity of all treatments were both significant and insignificant, these two parameters resulted in higher volume in all samples than the blank one. The differences in weight loss, moisture content and water activity of samples were insignificant. Evaluating of texture showed that the softness of most of samples is increased and the staling is decreased. Crumb color and sensory evaluations of samples were also affected by the replacement of sucrose with Wash and Green-A Syrups. According to the results, we can increase the shelf life and improve the quality and nutritional values of cake by using these kinds of syrups in the formulation.

Keywords: cake, green-A syrup, quality tests, sensory evaluation, wash syrup

Procedia PDF Downloads 155

Authors: Olivier Chaigneau, Damianos Oikonomidis, Marie-Cecile Delmas

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GAMBAS (Galileo Advanced features for the Maritime domain: Breakthrough Applications for Safety and security) is a project funded by the European Space Program Agency (EUSPA) aiming at identifying the search-and-rescue and ship security alert system needs for maritime users (including operators and fishing stakeholders) and developing operational concepts to answer these needs. The general objective of the GAMBAS project is to support the deployment of Galileo exclusive features in the maritime domain in order to improve safety and security at sea, detection of illegal activities and associated surveillance means, resilience to natural and human-induced emergency situations, and develop, integrate, demonstrate, standardize and disseminate these new associated capabilities. The project aims to demonstrate: improvement of the SAR (Search And Rescue) and SSAS (Ship Security Alert System) detection and response to maritime distress through the integration of new features into the beacon for SSAS in terms of cost optimization, user-friendly aspects, integration of Galileo and OS NMA (Open Service Navigation Message Authentication) reception for improved authenticated localization performance and reliability, and at sea triggering capabilities, optimization of the responsiveness of RCCs (Rescue Co-ordination Centre) towards the distress situations affecting vessels, the adaptation of the MCCs (Mission Control Center) and MEOLUT (Medium Earth Orbit Local User Terminal) to the data distribution of SSAS alerts.

Keywords: Galileo new advanced features, maritime, safety, security

Procedia PDF Downloads 76

Authors: Qazi Mahdia Ghyas

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Electronic Government Procurement (e-GP) has implemented in Bangladesh to ensure the good Governance. e-GP has transformed Bangladesh's procurement process electronically. But, to our best knowledge, there is no study to understand the key features of e-GP in Bangladesh. So, this study tries to identify the features of performance improvement after implementing an e-GP system that will help for further improvements. Data was collected from the PROMIS Overall Report (Central Procurement Technical Unit website) for the financial year from Q1 _July- Sep 2015-16 to Q4 _Apr- Jun 2021-22. This study did component factor analysis on KPIs and found nineteen KPIs that are statistically significant and represent time savings, efficiency, accountability, anti-corruption and compliance key features in procurement activities of e-GP. Based on the analysis, some practical measures have been recommended for better improvement of e-GP. This study has some limitations. Because of having multicollinearity issues, all the 42 KPIs (except 19) did not show a good fit for component factor analysis.

Keywords: public procurement, electronic government procurement, KPI, performance evaluation

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Authors: Malarvizhi Selvaraj, Paul Fergus, Andy Shaw

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Uterine contractions produced during labour have the potential to damage the foetus by diminishing the maternal blood flow to the placenta. In order to observe this phenomenon labour and delivery are routinely monitored using cardiotocography monitors. An obstetrician usually makes the diagnosis of foetus hypoxia by interpreting cardiotocography recordings. However, cardiotocography capture and interpretation is time-consuming and subjective, often lead to misclassification that causes damage to the foetus and unnecessary caesarean section. Both of these have a high impact on the foetus and the cost to the national healthcare services. Automatic detection of foetal heart rate may be an objective solution to help to reduce unnecessary medical interventions, as reported in several studies. This paper aim is to provide a system for better identification and interpretation of abnormalities of the fetal heart rate using RStudio. An open dataset of 552 Intrapartum recordings has been filtered with 0.034 Hz filters in an attempt to remove noise while keeping as much of the discriminative data as possible. Features were chosen following an extensive literature review, which concluded with FIGO features such as acceleration, deceleration, mean, variance and standard derivation. The five features were extracted from 552 recordings. Using these features, recordings will be classified either normal or abnormal. If the recording is abnormal, it has got more chances of hypoxia.

Keywords: cardiotocography, foetus, intrapartum, hypoxia

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Authors: Amin Nezarat, Naeime Seifadini

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Trip mode selection is a behavioral characteristic of passengers with immense importance for travel demand analysis, transportation planning, and traffic management. Identification of trip mode distribution will allow transportation authorities to adopt appropriate strategies to reduce travel time, traffic and air pollution. The majority of existing trip mode inference models operate based on human selected features and traditional machine learning algorithms. However, human selected features are sensitive to changes in traffic and environmental conditions and susceptible to personal biases, which can make them inefficient. One way to overcome these problems is to use neural networks capable of extracting high-level features from raw input. In this study, the convolutional neural network (CNN) architecture is used to predict the trip mode distribution based on raw GPS trajectory data. The key innovation of this paper is the design of the layout of the input layer of CNN as well as normalization operation, in a way that is not only compatible with the CNN architecture but can also represent the fundamental features of motion including speed, acceleration, jerk, and Bearing rate. The highest prediction accuracy achieved with the proposed configuration for the convolutional neural network with batch normalization is 85.26%.

Keywords: predicting, deep learning, neural network, urban trip

Procedia PDF Downloads 112

Authors: Donludee Jaisut, Norihisa Kato, Thanutchaporn Kumrungsee, Kiyoshi Kawai, Somkiat Prachayawarakorn, Patchalee Tungtrakul

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Jasmine Rice is a principle food of Thai people. However, glycemic index of jasmine rice is in high level, risk of type II diabetes after consuming. Burdock root is a good source of non-starch polysaccharides such as inulin. Inulin acts as prebiotic and helps reduce blood-sugar level. The purpose of this research was to reduce digestion rate of jasmine rice by coating burdock root extract on rice surface, using top-spay fluidized bed coating technique. Coating experiments were performed by spraying burdock root solution onto Jasmine rice kernels (Khao Dawk Mali-105; KDML), which had an initial moisture content of 11.6% wet basis, suspended in the fluidized bed. The experimental conditions were: solution spray rates of 31.7 mL/min, atomization pressure of 1.5 bar, spray time of 10 min, time of drying after spraying of 30 s, superficial air velocity of 3.2 m/s and drying temperatures of 60°C. The coated rice quality was evaluated in terms of the moisture content, texture, whiteness and digestion rate. The results showed that initial and final moisture contents of samples were the same in concentration 8% (v/v) and 10% (v/v). The texture was insignificantly changed from that of uncoated sample. The whiteness values were varied on concentration of burdock root extract. Coated samples were slower digested.

Keywords: burdock root, digestion, drying, rice

Procedia PDF Downloads 272

Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: data mining, Korean linguistic feature, literary fiction, relationship extraction

Procedia PDF Downloads 355

Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

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Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

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Authors: Soumyajit Koley, Kuladeep Rajamudili, Supriyo Ganguly

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In recent years, iron-based shape-memory alloys have been emerging as an inexpensive alternative to costly Ni-Ti alloy and thus considered suitable for many different applications in civil structures. Fe-17Mn-10Cr-5Si-4Ni-0.5V-0.5C alloy contains 37 wt.% of total solute elements. Such complex multi-component metallurgical system often leads to severe solute segregation and solidification cracking. Wire-arc additive manufacturing (WAAM) of Fe-17Mn-10Cr-5Si-4Ni-0.5V-0.5C alloy was attempted using a cold-wire fed plasma arc torch attached to a 6-axis robot. Self-standing walls were manufactured. However, multiple vertical cracks were observed after deposition of around 15 layers. Microstructural characterization revealed open surfaces of dendrites inside the crack, confirming these cracks as solidification cracks. Machine hammer peening (MHP) process was adopted on each layer to cold work the newly deposited alloy. Effect of MHP traverse speed were varied systematically to attain a window of operation where cracking was completely stopped. Microstructural and textural analysis were carried out further to correlate the peening process to microstructure.MHP helped in many ways. Firstly, a compressive residual stress was induced on each layer which countered the tensile residual stress evolved from solidification process; thus, reducing net tensile stress on the wall along its length. Secondly, significant local plastic deformation from MHP followed by the thermal cycle induced by deposition of next layer resulted into a recovered and recrystallized equiaxed microstructure instead of long columnar grains along the vertical direction. This microstructural change increased the total crack propagation length and thus, the overall toughness. Thirdly, the inter-layer peening significantly reduced the strong cubic {001} crystallographic texture formed along the build direction. Cubic {001} texture promotes easy separation of planes and easy crack propagation. Thus reduction of cubic texture alleviates the chance of cracking.

Keywords: Iron-based shape-memory alloy, wire-arc additive manufacturing, solidification cracking, inter-layer cold working, machine hammer peening

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Authors: Kadir Akkuş, Burcu A. Hamat, Kaan Ciloglu

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Additive Manufacturing (AM) is the respectable improvement of this century in the field of manufacturing and regarded as a breakthrough that represents the third industrial revolution by the leading authorities such as Wohlers Associates Inc., The Economist, and MIT Technology Review. Thanks to the stacking and unifying methodology of AM, design of lighter but stiffer parts with really more complex shapes and geometrical features, which were not possible by traditional subtractive manufacturing methods, became achievable. Through analysis of the AM process must be performed and mechanical properties of manufactured test parts must be studied to provide input for design. Furthermore, process capabilities, constraints, limitations and challenges regarding AM must be examined so that the design must be compatible with the process to be able to take all the advantages of the AM. In this paper, capabilities and limitations of AM will be investigated through a test part including unique features and manufactured from Ti-6Al-4V by employing Electron Beam Melting (EBM) technology by comparing to the test parts introduced in literature.

Keywords: additive manufacturing, DfAM, EBM, test artifact, Ti-6Al-4V

Procedia PDF Downloads 88

Authors: Bhalke D. G., Bormane D. S., Kharate G. K.

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This paper presents classification of musical instrument using machine learning techniques. The classification has been carried out using temporal, spectral, cepstral and wavelet features. Detail feature analysis is carried out using separate and combined features. Further, instrument model has been developed using K-Nearest Neighbor and Support Vector Machine (SVM). Benchmarked McGill university database has been used to test the performance of the system. Experimental result shows that SVM performs better as compared to KNN classifier.

Keywords: feature extraction, SVM, KNN, musical instruments

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Authors: Tasleem Zafar, Jiwan Sidhu

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Introduction: Chickpea flour is known to offer many benefits to diabetic persons, especially in maintaining their blood sugar levels in the acceptable range. Under this project we have studied the chemical composition and antioxidant capacity of white flour (WF), whole wheat flour (WWF) and chickpea flour (BF), in addition to the effect of replacement of WF and WWF with BF on the rheological characteristics of these flour blends, with the ultimate objective of producing acceptable quality flat as well as pan-bread for the diabetic consumers. Methods: WF and WWF were replaced with BF ranging from 0 to 40%, to investigate its effect on the rheological properties and functionality of blended flour dough using farinograph, viscoamylograph, mixograph and falling number apparatus as per the AACC standard methods. Texture Profile Analysis (TPA) was carried on the WF, WWF, and their blends with BF using Stable Micro System Texture Analyzer. Effect of certain additives, such as freeze-dried amla fruit powder (Phyllanthus emblica L.), guar gum, and xanthan gum on the dough rheological properties were also studied. Results: Freeze-dried amla fruit powder was found to be very rich in ascorbic acid and other phenolics having higher antioxidant activity. A decreased farinograph water absorption, increased dough development time, higher mixing tolerance index (i.e., weakening of dough), decreased resistance to extension, lower ratio numbers were obtained when the replacement with BF was increased from 0 to 40%. The BF gave lower peak viscosity, lower paste breakdown, and lower setback values when compared with WF. The falling number values were significantly lower in WWF (meaning higher α-amylase activity) than both the WF and BF. Texture Profile Analysis (TPA) carried on the WF, WWF, and their blends with BF showed significant variations in hardness and compressibility values, dough becoming less hard and less compressible when the replacement of WF and WWF with BF was increased from 0 to 40%. Conclusions: To overcome the deleterious effects of adding BF to WF and WWF on the rheological properties will be an interesting challenge when good quality pan bread and Arabic flatbread have to be commercially produced in a bakery. Use of freeze-dried amla fruit powder, guar gum, and xanthan gum did show some promise to improve the mixing characteristics of WF, WWF, and their blends with BF, and these additives are expected to be useful in producing an acceptable quality flat as well as pan-bread on a commercial scale.

Keywords: wheat flour, chickpea flour, amla fruit, rheology

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

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Authors: Nunyong Fuengkajornfung, Pattama Hirunyophat, Tidarat Sanphom

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The objectives of this research were: To study of the recipe standard of Thai steamed dumpling, to study the ratio of modified starch in Thai steamed dumpling, to study chemical elements analyzing and Escherichia coli in Thai steamed dumpling. The experimental processes were designed in two stages as follows: To study the recipe standard of Thai steamed dumpling and to study the ratio of rice flour: modify starch by three levels 90:10, 73:30, and 50:50. The evaluation test used 9 Points Hedonic Scale method by the sensory evaluation test such as color, smell, taste, texture and overall liking. An experimental by Randomized Complete Block Design (RCBD). The statistics used in data analyses were means, standard deviation, one-way ANOVA and Duncan’s New Multiple Range Test. Regression equation, at a statistically significant level of .05. The results showed that the recipe standard was studied from three recipes by the sensory evaluation test such as color, odor, taste, spicy, texture and total acceptance. The result showed that the recipe standard of second was suitably to development. The ratio of rice flour: modified starch had 3 levels 90:10, 73:30, and 50:50 which the process condition of 50:50 had well scores (like moderately to like very much; used 9 Points Hedonic Scale method for the sensory test). Chemical elements analyzing, it showed that moisture 58.63%, fat 5.45%, protein 4.35%, carbohydrate 30.45%, and Ash 1.12%. The Escherichia coli is not found in lab testing.

Keywords: Thai snack in Rattanakosin era, Thai steamed dumpling, modify starch, recipe standard

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Authors: Dona Abdulwassi, Dhaee Dahlawi, Yara Zainy, Leen Joharji

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The relationship between Netflix and artificial intelligence is discussed in this paper. Netflix uses the most effective and efficient approaches to apply artificial intelligence, machine learning, and data science. Netflix employs the personalization tool for their users, recommending or suggesting shows based on what those users have already watched. The researchers conducted an experiment to learn more about how Netflix is used and how AI affects the user experience. The main conclusions of this study are that Netflix has a wide range of AI features, most users are happy with their Netflix subscriptions, and the majority prefer Netflix to alternative apps.

Keywords: easy accessibility, recommends, accuracy, privacy

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Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

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Authors: Guoliang Lu, Changhou Lu, Xueyong Li

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In action recognition, previous studies have demonstrated the effectiveness of using multiple features to improve the recognition performance. We focus on two practical issues: i) most studies use a direct way of concatenating/accumulating multi features to evaluate the similarity between two actions. This way could be too strong since each kind of feature can include different dimensions, quantities, etc; ii) in many studies, the employed classification methods lack of a flexible and effective mechanism to add new feature(s) into classification. In this paper, we explore an unified scheme based on recently-proposed multi-dimensional dynamic time warping (MD-DTW). Experiments demonstrated the scheme's effectiveness of combining multi-feature and the flexibility of adding new feature(s) to increase the recognition performance. In addition, the explored scheme also provides us an open architecture for using new advanced classification methods in the future to enhance action recognition.

Keywords: action recognition, multi features, dynamic time warping, feature combination

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Authors: Manendra Singh Parihar, Sandip Ghosh Chowdhury

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Austenitic stainless steels are widely used and give a good combination of properties. When this steel is plastically deformed, a phase transformation of the metastable Face Centred Cubic Austenite to the stable Body Centred Cubic (α’) or to the Hexagonal close packed (ԑ) martensite may occur, leading to the enhancement in the mechanical properties like strength. The work was based on variant selection and corresponding texture analysis for the strain induced martensitic transformation during deformation of the parent austenite FCC phase to form the product HCP and the BCC martensite phases separately, obeying their respective orientation relationships. The automated method for reconstruction of the parent phase orientation using the EBSD data of the product phase orientation is done using the MATLAB and TSL-OIM software. The method of triplets was used which involves the formation of a triplet of neighboring product grains having a common variant and linking them using a misorientation-based criterion. This led to the proper reconstruction of the pre-transformation phase orientation data and thus to its microstructure and texture. The computational speed of current method is better compared to the previously used methods of reconstruction. The reconstruction of austenite from ԑ and α’ martensite was carried out for multiple samples and their IPF images, pole figures, inverse pole figures and ODFs were compared. Similar type of results was observed for all samples. The comparison gives the idea for estimating the correct sequence of the transformation i.e. γ → ε → α’ or γ → α’, during deformation of AISI 304 austenitic stainless steel.

Keywords: variant selection, reconstruction, EBSD, austenitic stainless steel, martensitic transformation

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Authors: Abdul Malik Dawlatzai, Shafiqullah Rahmani

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Splash erosion in field has affected by factors; slope, rain intensity, soil properties, and plant cover. And also, soil erosion affects not only farmland productivity but also water quality downstream. There are a number of potential soil conservation practices, but many of these are complicated and relatively expensive, such as buffer strips, agro-forestry, counter banking, catchment canal, terracing, surface mulching, reduced tillage, etc. However, mitigation soil and water loss in agricultural land, particularly in arid and semi-arid climatic conditions, is indispensable for environmental protection and agricultural production. The objective of this study is to evaluate the effects of adding gypsum mineral on mitigating splash erosion caused by rain drop. The research was conducted in soil laboratory Badam Bagh Agricultural Researching Farm, Kabul, Afghanistan. The stainless steel cores were used, and constant water pressure was controlled by a Mariotte’s bottle with kinetic energy of raindrops 2.36 x 10⁻⁵J. Gypsum mineral was applied at a rate of 5 and 10 t ha⁻¹ and using a sandy loam and loam soil textures. The result was showed an average soil loss from sandy loam soil texture; control was 8.22%, 4.31% and 4.06% similar from loam soil texture, control was 7.26%, 2.89%, and 2.72% respectively. The application of gypsum mineral significantly (P < 0.05) reduced dispersion of soil particles caused by the impact of raindrops compared to control. Therefore, it was concluded that the addition of gypsum was effective as a measure for mitigating splash erosion.

Keywords: gypsum, soil loss, splash erosion, Afghanistan

Procedia PDF Downloads 108

Authors: Majid Javanmard

Abstract:

Edible mushrooms are those agricultural products which contain high quantity of protein and can have special role in human diet. So search for methods to increase their shelf life is important. One of these strategies can be use of active packaging for absorb the ethylene which has been studied in present study. In this study, initially, production of impregnating zeolite with potassium permanganate has been studied with zeolite clinoptiolite available in iran. After that, these ethylene scavengers were placed in the package of edible mushrooms and then transferred to the refrigerator with temperature 4c for a period of 20 days. Each 5 days, several experiments accomplished on edible mushrooms such as weight loss, moisture content, color, texture, bacterial experiments and sensory evaluation. After production of impregnating zeolite with potassium permanganate (with a concentration of %2.5, %5, %7.5, %10 and %12.5) by zeolite type clinoptiolite (with mesh 35 and 60), samples have been analyzed with gas chromatography and titration with sodium oxalate. The results showed that zeolite by concentration of %5, %7.5 and %10 potassium permanganate and mesh 60 have a higher efficiency. Results from the experiments on edible mushrooms proved that impregnated zeolite with potassium permanganate have a meaningful influence in prevent the weight loss, decrease of moisture content and L-value, increase of a-value and overall color change (ΔE) and decrease of firmness texture of mushrooms. In addition, these absorbents can influence on decrease microbial load (mesophilic bacteria) rather than control. Generally, concluded that the impregnated zeolite with 10% permanganate potassium has a high efficiency on increase the shelf life of fresh edible mushrooms.

Keywords: active packaging, ethylene scavenger, zeolite clinoptiolite, permanganate potassium, shelf life

Procedia PDF Downloads 391

Authors: Al Mutawa A. Amir, Liaqat Ali, Faisal Ali

Abstract:

After the World War II, the world economy was disrupted and changed due to oil and its prices. The research in this paper presents the basic statistical features and economic characteristics of the Gulf economy. The main features of the Gulf economies and its heavy dependence on oil exports, its dualism between modern and traditional sectors and its rapidly increasing affluences are particularly emphasized.  In this context, the research in this paper discussed the problems of growth versus development and has attempted to draw the implications for the future economic development of this area.

Keywords: oil prices, GCC, economic growth, gulf oil

Procedia PDF Downloads 317

Authors: Osayande Pascal Omondiagbe, Sherlock a Licorish

Abstract:

Stack Overflow is a popular community question and answer portal which is used by practitioners to solve technology-related challenges during software development. Previous studies have shown that this forum is becoming a substitute for official software programming languages documentation. While tools have looked to aid developers by presenting interfaces to explore Stack Overflow, developers often face challenges searching through many possible answers to their questions, and this extends the development time. To this end, researchers have provided ways of predicting acceptable Stack Overflow answers by using various modeling techniques. However, less interest is dedicated to examining the performance and quality of typically used modeling methods, and especially in relation to models’ and features’ complexity. Such insights could be of practical significance to the many practitioners that use Stack Overflow. This study examines the performance and quality of various modeling methods that are used for predicting acceptable answers on Stack Overflow, drawn from 2014, 2015 and 2016. Our findings reveal significant differences in models’ performance and quality given the type of features and complexity of models used. Researchers examining classifiers’ performance and quality and features’ complexity may leverage these findings in selecting suitable techniques when developing prediction models.

Keywords: feature selection, modeling and prediction, neural network, random forest, stack overflow

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Authors: J. S. Kim

Abstract:

This paper presents a 0.13-µm Complementary Metal-Oxide Semiconductor (CMOS) vector modulator for beamforming system. The vector modulator features a 360° phase and gain range of -10 dB to 10 dB with a root mean square phase and amplitude error of only 2.2° and 0.45 dB, respectively. These features make it a suitable for wireless backhaul system in the 5 GHz industrial, scientific, and medical (ISM) bands. It draws a current of 20.4 mA from a 1.2 V supply. The total chip size is 1.87x1.34 mm².

Keywords: CMOS, vector modulator, beamforming, 802.11ac

Procedia PDF Downloads 188

Authors: Mohammed Abaoli, Omer Kara

Abstract:

The current research has investigated the soil quality status under dryland vegetation of Yabello district, Southern Ethiopia in which we should identify the nature and extent of salinity problem of the area for further research bases. About 48 soil samples were taken from 0-30, 31-60, 61-90 and 91-120 cm soil depths by opening 12 representative soil profile pits at 1.5 m depth. Soil color, texture, bulk density, Soil Organic Carbon (SOC), Cation Exchange Capacity (CEC), Na, K, Mg, Ca, CaCO₃, gypsum (CaSO₄), pH, Sodium Adsorption Ratio (SAR), Exchangeable Sodium Percentage (ESP) were analyzed. The dominant soil texture was silty-clay-loam.  Bulk density varied from 1.1 to 1.31 g/cm³. High SOC content was observed in 0-30 cm. The soil pH ranged from 7.1 to 8.6. The electrical conductivity shows indirect relationship with soil depth while CaCO₃ and CaSO₄ concentrations were observed in a direct relationship with depth. About 41% are non-saline, 38.31% saline, 15.23% saline-sodic and 5.46% sodic soils. Na concentration in saline soils was greater than Ca and Mg in all the soil depths. Ca and Mg contents were higher above 60 cm soil depth in non-saline soils. The concentrations of SO₂^-4 and HCO^-3 were observed to be higher at the most lower depth than upper. SAR value tends to be higher at lower depths in saline and saline-sodic soils, but decreases at lower depth of the non-saline soils. The distribution of ESP above 60 cm depth was in an increasing order in saline and saline-sodic soils. The result of the research has shown the direction to which extent of salinity we should consider for the Commiphora plant species we want to grow on the area. 

Keywords: commiphora species, dryland vegetation, ecological significance, soil quality, salinity problem

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Authors: G. K. Awari, Vishwajeet V. Ambade, S. W. Rajurkar

Abstract:

The field of additive manufacturing is growing, and discoveries are being made. 3D printing machines are also being developed to accommodate a wider range of 3D printing materials, including plastics, metals (metal AM powders), composites, filaments, and other materials. There are numerous printing materials available for industrial additive manufacturing. Such materials have their unique characteristics, advantages, and disadvantages. In order to avoid errors in additive manufacturing, key elements such as 3D printing material type, texture, cost, printing technique and procedure, and so on must be examined. It can be complex to select the best material for a particular job. Polylactic acid (PLA) is made from sugar cane or cornstarch, both of which are renewable resources. "Black plastic" is another name for it. Because it is safe to use and print, it is frequently used in primary and secondary schools. This is also how FDM screen printing is done. PLA is simple to print because of its low warping impact. It's also possible to print it on a cold surface. When opposed to ABS, it allows for sharper edges and features to be printed. This material comes in a wide range of colours. Polylactic acid (PLA) is the most common material used in fused deposition modelling (FDM). PLA can be used to print a wide range of components, including medical implants, household items, and mechanical parts. The mechanical behaviour of the printed item is affected by variations in infill patterns that are subjected to compressive tests in the current investigation to examine their behaviour under compressive stresses.

Keywords: fused deposition modelling, polylactic acid, infill density, infill pattern, compressive strength

Procedia PDF Downloads 55