Search results for: text classification

Authors: Abdullah M. Alzahrani

Abstract:

The karyotypes of Khalas (KH), Sukkary (SK), Sheeshi (SS), Shibeebi (SB) and Sillije (SJ) date palm cultivars were investigated. Data showed no variation in chromosome number, 2n = 36, 34 autosomes in addition to XX in females and XY in males. Mean autosomes length ranged from 3.85-9.93 μm and 3.71-2.73 μm for X and Y chromosomes, respectively. The formula of female date palm karyotype was 8m + 4sm +2st + 4t, and submedian Y chromosome. Relative chromosome length ranged from 3.3- 9.38 μm. SS cultivar showed high asymmetry levels by scoring low values of Syi (45.51), TF (42.8) and high values for A1 (0.53), A (0.41) and AI (0.29). Syi developed an inverse relation with A1 and A while A exhibited a direct correlation with A1. Cultivars SK, SB and SJ score medium values of Syi, A1, AI and A. KH cultivar exhibited high symmetry by scoring highest values of Syi (53.68), TF (51.81) and lowest values of A1 (0.44), A (0.34) and AI (0.18). Higher DI value was obtained in SB cultivar (1.34) followed by SJ (1.15) and low DI scores of 0.99, 0.86 and 0.71 were detected in KH, SS and SK, respectively. Stebbins classification assorted SS as 3B and the other cultivars as 2B, insuring the evolution and asymmetry of SS compared to the other karyotypes. Scatter diagram of Syi-A1 couple has the advantage of revealing high degree of sensitivity to present karyotype interrelationships, followed by AI-A and CVCL-CVCI couples.

Keywords: Karyotype, date palm, Khalas, Sukkary, Sheeshi

Procedia PDF Downloads 348

Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang

Abstract:

This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.

Keywords: decision tree, data mining, customers, life insurance pay package

Procedia PDF Downloads 412

Authors: Mohadese Sookhtesaraii, Abed Taghavi, Kosar Sookhtesaraii

Abstract:

Pottery is always attended by human beings for its application functions. By passing time and human development and writing progressing, writing was started to do on pottery dishes. Some of important issues in making thise dishes, in addition to their application, are their names and obviosely their relationship between their function and their names. These names are different based on their appearances and the kind of their using. So by meaning these words in dictionary, naming these dishes are classified. In poetry works there are so many names of these dishes which are showing their importance and their using. More using of some of these dishes name in poem and writing works is caused the select these dishes. For better and precise analysing the form of pottery it emphasis on the meaning which are in dictionary and the names that are existed in poems and writters works. On the other hand, on the dishes there are written poet more than text, that it can study their beautiful aspect. Seperate from their meanings. Dishes name like Chamaneh, Satgini, was clearly named for drinking in dictionary. while using Khonb was applied for storing. So dishes applying can be the basis of classifying. The size and capacity of these dishes is also caused the differences in naming the dishes. Such as Khom, Khonb which are same in farm but. They are different in capacity and size. Meaning are written on these dishe was studied. In addition to preying phrase, they had loving meaning or inviting to drink and enjoying and shorting the human life.

Keywords: pialeh, sajegni, khomre, pottery

Procedia PDF Downloads 49

Authors: K. Kanja, M. Mweemba, K. Malungwa

Abstract:

Due to the rampant population growth coupled with retrenchments currently going on in the Copper mines in Zambia, a number of people are resorting to land clearing for agriculture, illegal settlements as well as charcoal production among other vices. This study aims at assessing the rate of expansion of agricultural fields and illegal settlements in protected areas using remote sensing and Geographic Information System. Zambia’s Mwekera National Forest Reserve was used as a case study. Iterative Self-Organizing Data Analysis Technique (ISODATA), as well as maximum likelihood, supervised classification on four Landsat images as well as an accuracy assessment of the classifications was performed. Over the period under observation, results indicate annual percentage changes to be -0.03, -0.49 and 1.26 for agriculture, forests and settlement respectively indicating a higher conversion of forests into human settlements and agriculture.

Keywords: geographic information system, land cover change, Landsat TM and ETM+, Mwekera forest reserve, remote sensing

Procedia PDF Downloads 128

Authors: Burcu Oralhan, Zeki Oralhan, Nilsun Sariyer, Kumru Uyar

Abstract:

Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every business. Customer Relationship Management is an approach to focus on customer relationship development, retention and increase on customer satisfaction. In this study, we made an application of a data mining methods in telecommunication customer relationship management side. This study aims to determine the customers profile who likely to leave the system, develop marketing strategies, and customized campaigns for customers. Data are clustered by applying classification techniques for used to determine the churners. As a result of this study, we will obtain knowledge from international telecommunication industry. We will contribute to the understanding and development of this subject in Customer Relationship Management.

Keywords: customer churn analysis, customer relationship management, data mining, telecommunication industry

Procedia PDF Downloads 294

Authors: Vita Kalnberzina, Lauren Miller Anderson

Abstract:

The aim of the paper is to report on the results of the telecollaboration project results carried out between the students of the University of Latvia, National Louis University in the US, and Austral University in Chili during the Intercultural Communication course. The objectives of the study are 1) to compare different forms of student telecollaboration and virtual exchange, 2) to collect and analyse the student feedback on the telecollaboration project, 3) to evaluate the products (films) produced during the telecollaboration project. The methods of research used are as follows: Survey of the student feedback after the project, video text analysis of the films produced by the students, and interview of the students participating in the project. We would like to compare the results of a three-year collaboration project, where we tried out synchronous telecollaboration and asynchronous collaboration. The different variables that were observed were the impact of the different time zones, different language proficiency levels of students, and different curricula developed for collaboration. The main findings suggest that the effort spent by students to organize meetings in different time zones and to get to know each other diminishes the quality of the product developed and thus reduces the students' feeling of accomplishment. Therefore, we would like to propose that asynchronous collaboration where the national teams work on a film project specifically developed by the students of one university for the students of another university ends up with a better quality film, which in its turn appeals more to the students of the other university and creates a deeper intercultural bond between the collaborating students.

Keywords: telecollaboration, intercultural communication, synchronous collaboration, asynchronous collaboration

Procedia PDF Downloads 79

Authors: McClain Thiel

Abstract:

Object detection and localization has historically required two or more sensors due to the loss of information from 3D to 2D space, however, most surveillance systems currently in use in the real world only have one sensor per location. Generally, this consists of a single low-resolution camera positioned above the area under observation (mall, jewelry store, traffic camera). This is not sufficient for robust 3D tracking for applications such as security or more recent relevance, contract tracing. This paper proposes a lightweight system for 3D person tracking that requires no additional hardware, based on compressed object detection convolutional-nets, facial landmark detection, and projective geometry. This approach involves classifying the target into a demographic category and then making assumptions about the relative locations of facial landmarks from the demographic information, and from there using simple projective geometry and known constants to find the target's location in 3D space. Preliminary testing, although severely lacking, suggests reasonable success in 3D tracking under ideal conditions.

Keywords: monocular distancing, computer vision, facial analysis, 3D localization

Procedia PDF Downloads 118

Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi

Abstract:

In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.

Keywords: Haraz basin, change detection, land-use, satellite data

Procedia PDF Downloads 398

Authors: Tooba Sabir, Namra Sabir, Mohammad Amjad Sabir

Abstract:

The human-environment relationship has been projected since the beginning of literary tradition i.e. pastoral tradition, however, the interest of critics, writers and poets, in this view, has been developed, since the last couple of decades because of the increasing scope of environmental studies and growing environmental issues. One such novel, that projects human-environment relationship, is ‘The Alchemist.’ It is Paulo Coelho’s one of the most read novels. It holds a central theme that the universe conspires to help a person achieve his destiny, projecting anthropocentrism and human domination by centralizing human and devaluing the intrinsic worth of ecosystem. However, ecocritical analysis of the text reveals that the novel contains, at several instances, ecocentrism as well e.g. ‘everything on earth is being continuously transformed because earth is alive.’ This portrays ecosphere as living and dynamic entity rather than a mere instrument for human to achieve his destiny. The idea that the universe shares the same language projects unity of nature showing the relationship between human and non-human aspects of the environment as one being and not separate or superior to one another. It depicts human as a part of the environment and not the lord of the world. Therefore, it can be concluded that the novel oscillates between both the ecocentric and the anthropocentric phenomena. It is not suggested, however, that one phenomenon should be valued over the other but that the complexities of both the phenomena should be recognized, acknowledged and valued in order to encourage the interactions between literature and environment.

Keywords: anthropocentrism, ecocentrism, ecocritical analysis, human-environment relationship

Procedia PDF Downloads 295

Authors: Hadeer M. Sayed, Hesham E. El Deeb, Shereen A. Taie

Abstract:

In the big data era, we are facing a diversity of datasets from different sources in different domains that describe a single life event. These datasets consist of multiple modalities, each of which has a different representation, distribution, scale, and density. Multimodal fusion is the concept of integrating information from multiple modalities in a joint representation with the goal of predicting an outcome through a classification task or regression task. In this paper, multimodal fusion techniques are classified into two main classes: model-agnostic techniques and model-based approaches. It provides a comprehensive study of recent research in each class and outlines the benefits and limitations of each of them. Furthermore, the audiovisual speech recognition task is expressed as a case study of multimodal data fusion approaches, and the open issues through the limitations of the current studies are presented. This paper can be considered a powerful guide for interested researchers in the field of multimodal data fusion and audiovisual speech recognition particularly.

Keywords: multimodal data, data fusion, audio-visual speech recognition, neural networks

Procedia PDF Downloads 91

Authors: Hilary Modir, Kyle Dutton, Michelle Swab, Shabnam Asghari

Abstract:

Since its emergence, the cutaneous manifestations of COVID-19 have been documented in the literature. However, the majority are case reports with significant limitations in appraisal quality, thus leaving the role of dermatological manifestations of COVID-19 erroneously underexplored. The primary aim of this review was to systematically examine clinical patterns of dermatological manifestations as reported in the literature. This study was designed as a systematic review of case reports. The inclusion criteria consisted of all published reports and articles regarding COVID-19 in English, from September 1st, 2019, until June 22nd, 2020. The population consisted of confirmed cases of COVID-19 with associated cutaneous signs and symptoms. Exclusion criteria included research in planning stages, protocols, book reviews, news articles, review studies, and policy analyses. With the collaboration of a librarian, a search strategy was created consisting of a mixture of keyword terms and controlled vocabulary. Electronic databases searched were MEDLINE via PubMed, EMBASE, CINAHL, Web of Science, LILACS, PsycINFO, WHO Global Literature on Coronavirus Disease, Cochrane Library, Campbell Collaboration, Prospero, WHO International Clinical Trials Registry Platform, Australian and New Zealand Clinical Trials Registry, U.S. Institutes of Health Ongoing Trials Register, AAD Registry, OSF preprints, SSRN, MedRxiV and BioRxiV. The study selection featured an initial pre-screening of titles and abstracts by one independent reviewer. Results were verified by re-examining a random sample of 1% of excluded articles. Eligible studies progressed for full-text review by two calibrated independent reviewers. Covidence was used to store and extract data, such as citation information and findings pertaining to COVID-19 and cutaneous signs and symptoms. Data analysis and summarization methodology reflect the framework proposed by PRISMA and recommendations set out by Cochrane and Joanna Brigg’s Institute for conducting systematic reviews. The Oxford Centre for Evidence-Based Medicine’s level of evidence was used to appraise the quality of individual studies. The literature search revealed a total of 1221 articles. After the abstract and full-text screening, only 95 studies met the eligibility criteria, proceeding to data extraction. Studies were divided into 58% case reports and 42% series. A total of 833 manifestations were reported in 723 confirmed COVID-19 cases. The most frequent lesions were 23% maculopapular, 15% urticarial and 13% pseudo-chilblains, with 46% of lesions reporting pruritus, 16% erythema, 14% pain, 12% burning sensation, and 4% edema. The most common lesion locations were 20% trunk, 19.5% lower limbs, and 17.7% upper limbs. The time to resolution of lesions was between one and twenty-one days. In conclusion, over half of the reported cutaneous presentations in COVID-19 positive patients were maculopapular, urticarial and pseudo-chilblains, with the majority of lesions distributed to the extremities and trunk. As this review’s sample size only contained COVID-19 confirmed cases with skin presentations, it becomes difficult to deduce the direct relationship between skin findings and COVID-19. However, it can be correlated that acute onset of skin lesions, such as chilblains-like, may be associated with or may warrant consideration of COVID-19 as part of the differential diagnosis.

Keywords: COVID-19, cutaneous manifestations, cutaneous signs, general dermatology, medical dermatology, Sars-Cov-2, skin and infectious disease, skin findings, skin manifestations

Procedia PDF Downloads 167

Authors: Christian Nwaoha

Abstract:

This study investigates taboo expressions and classifications in Igbo discourse, their socio-cultural factors affecting their usage. The study classifies Linguistic taboo expressions by their discourse into five categories: morality-related taboo, veneration-related, decorum-related, religion-related and fear-related taboo expressions. This study argues that while religion-related and decorum-related taboos are unmentioned and have no euphemistic synonyms is because they are closely tied to various Igbo deities and objects, while morality, veneration, and fear-related have permissible alternatives. A descriptive research design was adopted and the data collection was by questionnaire and oral interview. The result of the research proves that aside of the categories of taboos in Igbo, socially, the styles of discourse have some levels of gender, age and class-connected taboos, which for instance, in gender-connected taboos, women in Igbo are forbidden to use style of discourse that are connected with genital organs in social gathering comprising men and women. The same has to do with class-connected where much younger men can use some certain expressions that are taboo, but in much older men gathering such expressions would be tagged forbidden in the context. The study further reveals that there are occasions in which these taboos can be used with reasons. The research concludes that using these taboos in literary text can enhance clear understanding of Igbo taboos to the users and learners of Igbo language.

Keywords: taboo expressions, classifications, Igbo, socio-cultural factors, discourse

Procedia PDF Downloads 216

Authors: S. M. Azad, H. Ghodsi Pour, F. Roshannafasa

Abstract:

In recent years ‘technology management and policymaking’ is one of the most important problems in management science. In this field, different generations of innovation and technology management are presented which the earliest one is Innovation System (IS) approach. In a general classification, innovation systems are divided in to 4 approaches: Technical, sectoral, regional, and national. There are many researches in relation to each of these approaches in different academic fields. Every approach has some benefits. If two or more approaches hybrid, their benefits would be combined. In addition, according to the sectoral structure of the governance model in Iran, in many sectors such as information technology, the combination of three other approaches with sectoral approach is essential. Hence, in this paper, combining two IS approaches (technical and sectoral) and using system dynamics, a generic model is presented for a sample of software industry. As a complimentary point, this article is introducing a new hybrid approach called Techno-Sectoral Innovation System. This TSIS model is accomplished by Changing concepts of the ‘functions’ which came from Technological IS literature and using them into sectoral system as measurable indicators.

Keywords: innovation system, technology, techno-sectoral system, functional indicators, system dynamics

Procedia PDF Downloads 420

Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

Abstract:

Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

Procedia PDF Downloads 141

Authors: C. -L. Huang, J. -H. Ho

Abstract:

Social media has become more and more important in our life. Many enterprises promote their services and products to fans via the social media. The positive or negative sentiment of feedbacks from fans is very important for enterprises to improve their products, services, and promotion activities. The purpose of this paper is to understand the sentiment of the fan’s responses by analyzing the responses posted by fans on Facebook. The entity and aspect of fan’s responses were analyzed based on a predefined ontology. The ontology for cell phone sentiment analysis consists of aspect categories on the top level as follows: overall, shape, hardware, brand, price, and service. Each category consists of several sub-categories. All aspects for a fan’s response were found based on the ontology, and their corresponding sentimental terms were found using lexicon-based approach. The sentimental scores for aspects of fan responses were obtained by summarizing the sentimental terms in responses. The frequency of 'like' was also weighted in the sentimental score calculation. Three famous cell phone fan pages on Facebook were selected as demonstration cases to evaluate performances of the proposed methodology. Human judgment by several domain experts was also built for performance comparison. The performances of proposed approach were as good as those of human judgment on precision, recall and F1-measure.

Keywords: opinion mining, ontology, sentiment analysis, text mining

Procedia PDF Downloads 218

Authors: Anam Nawaz

Abstract:

The present study is an attempt to compare the translations of Faiz’s poetry made by native and non-native translators, to determine the role of the translator in terms of preserving the cultural ethos of the original text. Peter Newmark and Katharine Reiss’s approaches to translation criticism have been used to provide a theoretical framework for the study. This study also emphasizes those cultural and semantic aspects of the original which are translated more convincingly by a native translator, and contrasting those features which the non-natives can tackle more ably. The research also highlights the linguistic sockets, ignored by the interpreters in the translation process. The analysis showed that both native and non-native translators have made an admirable effort to stay as close to the original as possible. The natives with their advantage of belonging to the same culture have excelled in preserving the original subject matter, whereas the non-native renderings have been presented in a much rhythmic and poetic manner with an excellent choice of words. Though none of the four translators has been successfully able to recreate Faiz’s magic, however V. G. Kiernan and Sarvat Rahman’s translations can be regarded as the closest to the original. Whereas V. G. Kiernan with his outstanding command over English mesmerizes the readers, Sarvat Rahman’s profound understanding of cultural ties helps establish her translations as a brilliant example of faithful re-renderings.

Keywords: comparative translations, linguistic and cultural constraints, native translators, non-native translators, poetry and translation, Faiz Ahmad Faiz

Procedia PDF Downloads 241

Authors: Anna Kesoyan

Abstract:

The present paper deals with the syntax-related problems of translation from English into Armenian. Although Syntax is a part of grammar, syntax-related problems of translation are studied separately during the process of translation. Translation from one language to another is widely accepted as a challenging problem. This becomes even more challenging when the source and target languages are widely different in structure and style, as is the case with English and Armenian. Syntax-related problems of translation from English into Armenian are mainly connected with the syntactical structures of these languages, and particularly, with the word order of the sentence. The word order of the sentence of the Armenian language, which is a synthetic language, is usually characterized as “rather free”, and the word order of the English language, which is an analytical language, is characterized “fixed”. The following research examines the main translation means, particularly, syntactical transformations as the translator has to take real steps while trying to solve certain syntax-related problems. Most of the means of translation are based on the transformation of grammatical components of the sentence, without changing the main information of the text. There are several transformations that occur during translation such as word order of the sentence, transformations of certain grammatical constructions like Infinitive participial construction, Nominative with the Infinitive and Elliptical constructions which have been covered in the following research.

Keywords: elliptical constructions, nominative with the infinitive constructions, fixed and free word order, syntactic structures

Procedia PDF Downloads 430

Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

Abstract:

In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

Procedia PDF Downloads 202

Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

Abstract:

In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method Web-App auto-generated twin data structure replication. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi" has been developed. A special login form has been developed with a special instance of data validation; this verification process secures the web application from its early stages. The system has been tested and validated, up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database

Procedia PDF Downloads 129

Authors: Donna L. Roberts

Abstract:

Beyond the fundamental question of what is (and what isn’t) art, one then moves to the question of what about art, or a specific artwork, matters. If there is an agreement that something is art, the next step is to answer the obvious, ‘So what? What does it mean?’ In answering these questions, one must decide how to focus the proverbial microscope –i.e., what level of perspective is relevant as a point of view for this analysis- the artwork itself, the artist’s intention, the viewer’s interpretation, the artwork’s reflection of the larger artistic movement, the social, political, and historical context of art? One must determine what product and what contexts are meaningful when experiencing and interpreting art. Is beauty really in the eye of the beholder? Or is it more important what the creator was trying to say than what the critic or observer heard? The fact that so many artists –from Rembrandt to Van Gogh to Picasso- include among their works at least one self-portrait seems to scream their point –I matter. But, Is a piece more impactful because of the persona behind it? Or does that persona impose limits and close one’s mind to the possibilities of interpretation? In the popular art text visual culture, Richard Howells argues against a biographical focus on the artist in the analysis of art. Similarly, abstract expressionist Mark Rothko, along with several of his contemporaries of the genre, often did not title his paintings for the express purpose of not imposing a specific meaning or interpretation on the piece. And yet, he once said, ‘The people who weep before my pictures are having the same religious experience I had when I painted them,’ thus alluding to a desire for a shared connection and revelation. This research analyzes the arguments for differing levels of interpretation and points of view when considering a work of art and/or the artist who created it.

Keywords: art analysis, art interpretation, art theory, artistic perspective

Procedia PDF Downloads 128

Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya

Abstract:

Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.

Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms

Procedia PDF Downloads 80

Authors: Vishnu Goyal, Basant Agarwal

Abstract:

Sentiment analysis research provides methods for identifying the people’s opinion written in blogs, reviews, social networking websites etc. Sentiment analysis is to understand what opinion people have about any given entity, object or thing. Sentiment analysis research can be broadly categorised into three types of approaches i.e. semantic orientation, machine learning and lexicon based approaches. Feature selection methods improve the performance of the machine learning algorithms by eliminating the irrelevant features. Information gain feature selection method has been considered best method for sentiment analysis; however, it has the drawback of selection of threshold. Therefore, in this paper, we propose a hybrid feature selection methods comprising of information gain and proposed feature selection method. Initially, features are selected using Information Gain (IG) and further more noisy features are eliminated using the proposed feature selection method. Experimental results show the efficiency of the proposed feature selection methods.

Keywords: feature selection, sentiment analysis, hybrid feature selection

Procedia PDF Downloads 310

Authors: Ayesha Hasan

Abstract:

This study offers unique perspectives and analyses of peace and conflict journalism through interpretative repertoire, media frames, and critical discourse analyses. Two major English publications in Pakistan, representing both long and short-form journalism, are investigated to uncover how the Afghan refugee repatriation from Pakistan in 2016-17 has been framed in Pakistani English media. Peace journalism focuses on concepts such as peace initiatives and peace building, finding common ground, and preventing further conflict. This study applies Jake Lynch’s Coding Criteria to guide the critical discourse analysis and Lee and Maslog’s Peace Journalism Quotient to examine the extent of peace journalism in each text. This study finds that peace journalism is missing in Pakistani English press, but represented, to an extent, in long-form print and online coverage. Two new alternative frames are also proposed. This study gives an in-depth understanding of if and how journalists in Pakistan are covering conflicts and framing stories that can be identified as peace journalism. This study represents significant contributions to the remarkably limited scholarship on peace and conflict journalism in Pakistan and extends Shabbir Hussain’s work on critical pragmatic perspectives on peace journalism in Pakistan.

Keywords: Afghan refugee repatriation, Critical discourse analysis, Media framing , Peace and conflict journalism

Procedia PDF Downloads 187

Authors: Vineetha Bettaiah, Heggere S. Ranganath

Abstract:

This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.

Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation

Procedia PDF Downloads 261

Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

Abstract:

Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

Procedia PDF Downloads 131

Authors: May Ziade

Abstract:

Postgraduate studies in English language and literature at the University of Sydney provided opportunity for research into one of the most significant singer/songwriters of our time, Bob Dylan, and his masterpiece from the mid-1960s, ‘Desolation Row’. With a title alluding to Jack Kerouac’s Desolation Angels as well as John Steinbeck’s Cannery Row, ‘Desolation Row’ is Bob Dylan’s magnum opus. Recorded on August 4 1965, it takes pride of place as the last track on the revolutionary 1965 album of rock poetics, Highway 61 Revisited. From its inception, its epic proportions (ten long verses) and rich and baffling imagery got our attention - it amused, fascinated and beguiled. The song’s surreal and dreamlike landscape and its cast of characters, drawn from history, fiction, mythology, theology, and popular culture, lured us in and begged interpretation. What were they doing there? Where is Desolation Row? Do they want to escape from or go to ‘Desolation Row’? What was Dylan writing about and what were his influences? Through literary analysis and historical research, this paper will examine the song’s lyrics, the mid-60s context and Dylan’s vast influences to make sense, offer explanations and make connections. In particular, research findings place the Beat poets and oeuvre as a significant literary influence but it is a rich, multilayered text that straddles traditions and emerges as a paradox – a paradox that has endured and endeared itself to many. As it turns 50 this year, what better way to acknowledge this momentous occasion than at an international English language conference.

Keywords: analysis, Bob Dylan, beat context, desolation row

Procedia PDF Downloads 475

Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

Abstract:

Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

Procedia PDF Downloads 441

Authors: Nor-Edine Abriak, Mahfoud Benzerzour, Mouhamadou Amar, Abdeljalil Zri

Abstract:

In this work, firstly we have studied the potential of raw sediments and sediments treated with lime or cement for use in a foundation layer and the base layer of a roadway. Secondly, we have examined mineral changes caused by the addition of lime or cement in order to explain the mechanical performance of stabilized sediments. After determining the amount of lime and cement required stabilizing the sediments, the compaction characteristics and Immediate Bearing Capacity (IBI) were studied using the Modified Proctor method. Then, the evolution of the three parameters, which are optimum water content, maximum dry density and IBI, were determined. Mechanical performances can be evaluated through resistance to compression, resistance under traction and the elasticity modulus. The resistances of the formulations treated with ROLAC®645 increase with the amount of ROLAC®645. Traction resistance and the elastic modulus were used to evaluate the potential of the formulations as road construction materials using the classification diagram. The results show that all the other formulations with ROLAC®645 can be used in subgrades and foundation layers for roads.

Keywords: sediment, lime, cement, roadway

Procedia PDF Downloads 250

Authors: Vivek Ganesh

Abstract:

Tropical cyclones are some of the most damaging events. They occur in yearly cycles and affect the coastal population with three dangerous effects: heavy rain, strong wind and storm surge. In order to estimate the area and the population affected by a cyclone, all the three types of physical impacts must be taken into account. Storm surge is an abnormal rise of water above the astronomical tides, generated by strong winds and drop in the atmospheric pressure. The main aim of the study is to identify the impact by comparing three different months data. The technique used here is NDVI classification technique for change detection and other techniques like storm surge modelling for finding the tide height. Current study emphasize on recent very severe cyclonic storm Hud Hud of category 3 hurricane which had developed on 8 October 2014 and hit the coast on 12 October 2014 which caused significant changes on land and coast of Visakhapatnam, Andhra Pradesh. In the present study, we have used Remote Sensing and GIS tools for investigating and quantifying the changes in vegetation and settlement.

Keywords: inundation map, NDVI map, storm tide map, track map

Procedia PDF Downloads 250

Authors: Smah Almotiri

Abstract:

One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

Procedia PDF Downloads 163