Search results for: Arabic data mining

Authors: Gholamhassan Kakha, Mohsen Jami, Daniel Alex Merino Natorce

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Sustainable development refers to the creation of a balance between the development and the environment too; it consists of three key principles namely environment, society and economy. These three parameters are related to each other and the imbalance occurs in each will lead to the disparity of the other parts. Mining is one of the most important tools of the economic growth and social welfare in many countries. Meanwhile, assessment of the environmental impacts has directed to the attention of planners toward the natural environment of the areas surrounded by mines and allowing for monitoring and controlling of the current situation by the designers. In this look upon, a semi-quantitative model using a matrix method is presented for assessing the environmental impacts in the BOOG Granite Mine located in Sistan and Balouchestan, one of the provinces of Iran for determining the effective factors and environmental components. For accomplishing this purpose, the initial data are collected by the experts at the next stage; the effect of the factors affects each environmental component is determined by specifying the qualitative viewpoints. Based on the results, factors including air quality, ecology, human health and safety along with the environmental damages resulted from mining activities in that area. Finally, the results gained from the assessment of the environmental impact are used to evaluate the sustainability by using Philips mathematical model. The results show that the sustainability of this area is weak, so environmental preventive measures are recommended to reduce the environmental damages to its components.

Keywords: sustainable development, environmental impacts' assessment, BOOG granite, Philips mathematical model

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Authors: Tuba Zahra, Aakash Parekh

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Hyperspectral remote sensing refers to imaging of objects or materials in narrow conspicuous spectral bands. Hyperspectral images (HSI) enable the extraction of spectral signatures for objects or materials observed. These images contain information about the reflectance of each pixel across the electromagnetic spectrum. It enables the acquisition of data simultaneously in hundreds of spectral bands with narrow bandwidths and can provide detailed contiguous spectral curves that traditional multispectral sensors cannot offer. The contiguous, narrow bandwidth of hyperspectral data facilitates the detailed surveying of Earth's surface features. This would otherwise not be possible with the relatively coarse bandwidths acquired by other types of imaging sensors. Hyperspectral imaging provides significantly higher spectral and spatial resolution. There are several use cases that represent the commercial applications of hyperspectral remote sensing. Each use case represents just one of the ways that hyperspectral satellite imagery can support operational efficiency in the respective vertical. There are some use cases that are specific to VNIR bands, while others are specific to SWIR bands. This paper discusses the different commercially viable use cases that are significant for HSI application areas, such as agriculture, mining, oil and gas, defense, environment, and climate, to name a few. Theoretically, there is n number of use cases for each of the application areas, but an attempt has been made to streamline the use cases depending upon economic feasibility and commercial viability and present a review of literature from this perspective. Some of the specific use cases with respect to agriculture are crop species (sub variety) detection, soil health mapping, pre-symptomatic crop disease detection, invasive species detection, crop condition optimization, yield estimation, and supply chain monitoring at scale. Similarly, each of the industry verticals has a specific commercially viable use case that is discussed in the paper in detail.

Keywords: agriculture, mining, oil and gas, defense, environment and climate, hyperspectral, VNIR, SWIR

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Authors: Kemal Polat

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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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Authors: Carine Cridelich, Pablo Juesas Cano, Emmanuel Ramasso, Noureddine Zerhouni, Bernd Weiler

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Safety is one of the most important considerations when buying a new car. While active safety aims at avoiding accidents, passive safety systems such as airbags and seat belts protect the occupant in case of an accident. In addition to legal regulations, organizations like Euro NCAP provide consumers with an independent assessment of the safety performance of cars and drive the development of safety systems in automobile industry. Those ratings are mainly based on injury assessment reference values derived from physical parameters measured in dummies during a car crash test. The components and sub-systems of a safety system are designed to achieve the required restraint performance. Sled tests and other types of tests are then carried out by car makers and their suppliers to confirm the protection level of the safety system. A Knowledge Discovery in Databases (KDD) process is proposed in order to minimize the number of tests. The KDD process is based on the data emerging from sled tests according to Euro NCAP specifications. About 30 parameters of the passive safety systems from different data sources (crash data, dummy protocol) are first analysed together with experts opinions. A procedure is proposed to manage missing data and validated on real data sets. Finally, a procedure is developed to estimate a set of rough initial parameters of the passive system before testing aiming at reducing the number of tests.

Keywords: KDD process, passive safety systems, sled test, dummy injury assessment reference values, frontal impact

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: Karin Eines, Riki Tesler

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Introduction: The Mamanet Cachibol League (MCL) is a community-based model developed in Israel to promote physical activity (PA) and amateur team sports among women. team sports are not just groups in the context of specific sport activity but also incorporated into a person’s sense of self and become influencing factor on sport-related behavior among the players. While in the non-Arabic sector, sport venues are available for the local authority population, the Arabic sector authorities face limited access sport facilities, with 168 sport venues and authorities with no venues at all. Within the Arab community, women participation in sports has traditionally been limited and, even more so for participation in team sports. Aims: The purpose of the study was to explore attributes of women MCL activity via: (1) assess differences between participants in the MCL and non-participants among Arab women regarding well-being level; (2) to examine among MCL participants the relationship between health maintenance characteristics and the likelihood of participating in the MCL; and (3) Use qualitative approach to shed light over the question why Arabic women participate in MCL and continue their engagement in PA. Methods: An explanatory sequential mixed-method design was employed to gain a deeper understanding of the advantages and motivations among women participating in community-based team sports. A cross-sectional survey was conducted among Israeli Arab women aged 25–59. Demographic characteristics, well-being (SRH and psychosomatic symptoms), eating habits, and social support were analyzed using two-way analyses of covariance and multiple regression models with a sequential entry of the variables. Quantitative results were further explored in qualitative in-depth interviews among 30 of the MCL participants, which shed light on additional reasons for participation in PA. Results: MCL participants reported better self-reported health (p < 0.001) and lower rates of psychosomatic symptoms (p < 0.001) compared to non-participants. Participation in MCL was also related to higher levels of well-being and healthy eating habits. Women who participated also experienced a profound sense of belonging, leading to enhanced social interactions and positivity in their personal and professional lives. They were dedicated to the group and felt empowered by the reciprocal commitment. The group promoted equality, making the women feel valued and respected, resulting in community admiration. Their involvement positively impacted their families, justifying their time commitment.

Keywords: wellbeing, obesity, community based sports, healthy eating habits, arab women

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Authors: Amna Javed, Hisashi Masuda, Youji Kohda

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This study examines the value analysis in Islamic and conventional banking services in Pakistan. Many scholars have focused on co-creation of values in services but mainly economic values not non-economic. As Islamic banking is based on Islamic principles that are more concerned with non-economic values (well-being, partnership, fairness, trust worthy, and justice) than economic values as money in terms of interest. This study is important to know the providers point of view about the co-created values, because, it may be more sustainable and appropriate for today’s unpredictable socioeconomic environment. Data were collected from 4 banks (2 Islamic and 2 conventional banks). Text mining technique is applied for data analysis, and values with 100% occurrences in Islamic banking are chosen. The results reflect that Islamic banking is more centric towards non-economic values than economic values and it promotes team work and partnership concept by applying Islamic spirit and trust worthiness concept.

Keywords: economic values, Islamic banking, non-economic values, value system

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Authors: Hing Hao Chan, Thomas Richard, Masood Mostofi

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The mining industry relies on an estimate of rock strength at several stages of a mine life cycle: mining (excavating, blasting, tunnelling) and processing (crushing and grinding), both very energy-intensive activities. An effective comminution design that can yield significant dividends often requires a reliable estimate of the material rock strength. Common laboratory tests such as rod, ball mill, and uniaxial compressive strength share common shortcomings such as time, sample preparation, bias in plug selection cost, repeatability, and sample amount to ensure reliable estimates. In this paper, the authors present a methodology to derive an estimate of the rock strength from drilling data recorded while coring with a diamond core head. The work presented in this paper builds on a phenomenological model of the bit-rock interface proposed by Franca et al. (2015) and is inspired by the now well-established use of the scratch test with PDC (Polycrystalline Diamond Compact) cutter to derive the rock uniaxial compressive strength. The first part of the paper introduces the phenomenological model of the bit-rock interface for a diamond core head that relates the forces acting on the drill bit (torque, axial thrust) to the bit kinematic variables (rate of penetration and angular velocity) and introduces the intrinsic specific energy or the energy required to drill a unit volume of rock for an ideally sharp drilling tool (meaning ideally sharp diamonds and no contact between the bit matrix and rock debris) that is found well correlated to the rock uniaxial compressive strength for PDC and roller cone bits. The second part describes the laboratory drill rig, the experimental procedure that is tailored to minimize the effect of diamond polishing over the duration of the experiments, and the step-by-step methodology to derive the intrinsic specific energy from the recorded data. The third section presents the results and shows that the intrinsic specific energy correlates well to the uniaxial compressive strength for the 11 tested rock materials (7 sedimentary and 4 igneous rocks). The last section discusses best drilling practices and a method to estimate the rock strength from field drilling data considering the compliance of the drill string and frictional losses along the borehole. The approach is illustrated with a case study from drilling data recorded while drilling an exploration well in Australia.

Keywords: bit-rock interaction, drilling experiment, impregnated diamond drilling, uniaxial compressive strength

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Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

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In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: churn prediction, data mining, decision-theoretic rough set, feature selection

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Authors: Antonio De Lisa

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The aim of this contribution is to describe a Sufi ceremony personally observed and recorded in Istanbul. It is part of research on the semiotics of religion that has been going on for some time. Over the centuries, Sufism has produced remarkable literature, elaborated mainly in the context of Arabic literature and Persian literature, but has also found expression in many other languages (Turkish, Indian, Malayo-Indonesian, etc.). Among the genres cultivated are: devotional books (prayers, meditation, spiritual exercises, etc.); the hagiographic texts, containing the biographies and sentences of the best-known Sufis; the texts that illustrate the abodes or stations of the spiritual path; finally, the theoretical treatises on various topics, often of an apologetic nature. Another typical expression of Sufism is in the literature in verse, which includes first-rate poets of both Arabic (Ibn al-Farid, Ibn 'Arabi) and Persian (Farid al-Din al-Attar, Rumi, Hafez, Gohar Shahi) expression. To observe an authentic Sufi ceremony, we contacted the Silivrikapı Mevlana Cultural Center in Istanbul. The ceremony we will talk about is a characteristic of the brotherhood called Mevleviyye (Mawlawiyya), so called from Mawlānā ('our lord', in Turkish: Mevlānā) Jalāl al-Dīn Muḥammad Rūmī (13th century) better known as the brotherhood of the Whirling Dervishes, founded in Konya. The characteristic of the order is to pray about one's love for Allah with music and dance in a ritual that has the name of Semà. The dance is a swirling movement in a group, representing a mystical journey of the spiritual ascent of man through the mind and love for the 'perfect'. Turning towards the truth, the follower of the group ascends towards love, passing beyond the World and Nothingness. After asceticism, he returns to the common world to communicate his own experience.

Keywords: semiotics of religion, sufi, rumi, islamic philosophy

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: Anam Alam, Rahim Jamaluddin Kanji

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With the rapid growth of event in everywhere, event extraction has now become an important matter to retrieve the information from the unstructured data. One of the challenging problems is to extract the event from it. An event is an observable occurrence of interaction among entities. The paper investigates the effectiveness of event extraction capabilities of three software tools that are Wandora, Nitro and SPSS. We performed standard text mining techniques of these tools on the data sets of (i) Afghan War Diaries (AWD collection), (ii) MUC4 and (iii) WebKB. Information retrieval measures such as precision and recall which are computed under extensive set of experiments for Event Extraction. The experimental study analyzes the difference between events extracted by the software and human. This approach helps to construct an algorithm that will be applied for different machine learning methods.

Keywords: event extraction, Wandora, nitro, SPSS, event analysis, extraction method, AFG, Afghan War Diaries, MUC4, 4 universities, dataset, algorithm, precision, recall, evaluation

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Authors: Mace Bentley, Zhuojun Duan, Tobias Gerken, Dudley Bonsal, Henry Way, Endre Szakal, Mia Pham, Hunter Donaldson, Chelsea Lang, Hayden Abbott, Leah Wilcynzski

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Air pollution has the potential to modify the lifespan and intensity of thunderstorms and the properties of lightning. Using data mining and geovisualization, we investigate how background climate and weather conditions shape variability in urban air pollution and how this, in turn, shapes thunderstorms as measured by the intensity, distribution, and frequency of cloud-to-ground lightning. A spatiotemporal analysis was conducted in order to identify thunderstorms using high-resolution lightning detection network data. Over seven million lightning flashes were used to identify more than 196,000 thunderstorms that occurred between 2006 - 2020 in the Washington, DC Metropolitan Region. Each lightning flash in the dataset was grouped into thunderstorm events by means of a temporal and spatial clustering algorithm. Once the thunderstorm event database was constructed, hourly wind direction, wind speed, and atmospheric thermodynamic data were added to the initiation and dissipation times and locations for the 196,000 identified thunderstorms. Hourly aerosol and air quality data for the thunderstorm initiation times and locations were also incorporated into the dataset. Developing thunderstorm climatologies using a lightning tracking algorithm and lightning detection network data was found to be useful for visualizing the spatial and temporal distribution of urban augmented thunderstorms in the region.

Keywords: lightning, urbanization, thunderstorms, climatology

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Authors: Ahmed Ishtiaq, Maeeda Khalid, Umair Sajjad

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In the fast-moving world, information is the key to success. If information is easily available, then it makes work easy. The Internet is the biggest collection and source of information nowadays, and with every single day, the data on internet increases, and it becomes difficult to find required data. Everyone wants to make his/her website at the top of search results. This can be possible when you have applied some techniques of SEO inside your application or outside your application, which are two types of SEO, onsite and offsite SEO. SEO is an abbreviation of Search Engine Optimization, and it is a set of techniques, methods to increase users of a website on World Wide Web or to rank up your website in search engine indexing. In this paper, we have compared different techniques of Onpage and Offpage SEO, and we have suggested many things that should be changed inside webpage, outside web page and mentioned some most powerful and search engine considerable elements and techniques in both types of SEO in order to gain high ranking on Search Engine.

Keywords: auto-suggestion, search engine optimization, SEO, query, web mining, web crawler

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Authors: B. Keawaram, P. Dumrongchai

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The volume of overburden and coal excavations in open-pit mine is generally determined by conventional survey such as total station. This study aimed to evaluate the accuracy of terrestrial laser scanner (TLS) used to measure overburden and coal excavations, and to compare TLS survey data sets with the data of the total station. Results revealed that, the reference points measured with the total station showed 0.2 mm precision for both horizontal and vertical coordinates. When using TLS on the same points, the standard deviations of 4.93 cm and 0.53 cm for horizontal and vertical coordinates, respectively, were achieved. For volume measurements covering the mining areas of 79,844 m², TLS yielded the mean difference of about 1% and the surface error margin of 6 cm at the 95% confidence level when compared to the volume obtained by total station.

Keywords: mine, survey, terrestrial laser scanner, total station

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Authors: Jumel Christian P. Nicha, Severino G. Salmo III

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This study investigated the concentration of heavy metals (HM) in mangrove sediments of Lake Uacon, Zambales, Philippines. The relationship among the studied HM (Cr, Ni, Pb, Cu, Cd, Fe) and the mangrove vegetation and sediment characteristics were assessed. Fourteen sampling plots were designated across the lake (10 vegetated and 4 un-vegetated) based on distance from the mining effluents. In each plot, three sediment cores were collected at 20 cm depth. Among the dominant mangrove species recorded were (in order of dominance): Sonneratia alba, Rhizophora stylosa, Avicennia marina, Excoecaria agallocha and Bruguiera gymnorrhiza. Sediment samples were digested with aqua regia, and the HM concentrations were quantified using Atomic Absorption Spectroscopy (AAS). Results showed that HM concentrations were higher in the vegetated plots as compared to the un-vegetated sites. Vegetated sites had high Ni (mean: 881.71 mg/kg) and Cr (mean: 776.36 mg/kg) that exceeded the threshold values (cf. by the United States Environmental Protection Agency; USEPA). Fe, Pb, Cu and Cd had a mean concentration of 2597.92 mg/kg, 40.94 mg/kg, 36.81 mg/kg and 2.22 mg/kg respectively. Vegetation variables were not significantly correlated with HM concentration. However, the HM concentration was significantly correlated with sediment variables particularly pH, redox, particle size, nitrogen, phosphorus, moisture and organic matter contents. The Pollution Load Index (PLI) indicated moderate to high pollution in the lake. Risk assessment and management should be designed in order to mitigate the ecological risk posed by HM. The need of a regular monitoring scheme for lake and mangrove rehabilitation programs and management should be designed.

Keywords: heavy metals, mangrove vegetation, mining, Philippines, sediment

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Authors: K. P. Sandesh, M. H. Suman

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Text processing plays an important role in information retrieval, data-mining, and web search. Measuring the similarity between the documents is an important operation in the text processing field. In this project, a new similarity measure is proposed. To compute the similarity between two documents with respect to a feature the proposed measure takes the following three cases into account: (1) The feature appears in both documents; (2) The feature appears in only one document and; (3) The feature appears in none of the documents. The proposed measure is extended to gauge the similarity between two sets of documents. The effectiveness of our measure is evaluated on several real-world data sets for text classification and clustering problems, especially in banking and health sectors. The results show that the performance obtained by the proposed measure is better than that achieved by the other measures.

Keywords: document classification, document clustering, entropy, accuracy, classifiers, clustering algorithms

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Authors: Mohamed R. Mhereeg

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The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). Microsoft's .NET windows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, implementation, multi-agent, SOA, autonomous, WCF

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Authors: Ntloana Hlabishi Peter

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The availability of public transportation modes and qualitative infrastructure is a burning issue that affects urban sustainability. Public transportation is indispensable in providing adequate transportation means to people at an affordable price, and it promotes public transport reliance. Burgersfort town has a critical condition on the urban public transportation infrastructure which affects the bus and taxi public transport modes and the existing infrastructure. The municipality is regarded as one of the mining towns in Limpopo Province considering the availability of mining activities and proposal on establishment of a Special Economic Zone (SEZ). The study aim is to assess the efficacy of current public transportation infrastructure and to propose relevant recommendations that will unlock the possibility of future supportable public transportation systems. The Key Informant Interview (KII) was used to acquire data on the views from commuters and stakeholders involved. There KII incorporated three relevant questions in relation to services rendered in public transportation. Relevant literature relating to public transportation modes and infrastructure revealed the imperatives of public transportation infrastructure, and relevant legislation was reviewed concerning public transport infrastructure. The finding revealed poor conditions on the public transportation ranks and also inadequate parking space for public transportation modes. The study reveals that 100% of people interviewed were not satisfied with the condition of public transportation infrastructure and 100% are not satisfied with the services offered by public transportation sectors. The findings revealed that the municipality is the main player who can upgrade the existing conditions of public transportation. The study recommended that an intermodal transportation facility must be established to resolve the emerging challenges.

Keywords: public transportation, modes, infrastructure, urban sustainability

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Authors: Inas Hussein

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Communication in the modern world is increasingly becoming multimodal due to globalization and the digital space we live in which have remarkably affected how people communicate. Accordingly, Multimodal Discourse Analysis (MDA) is an emerging paradigm in discourse studies with the underlying assumption that other semiotic resources such as images, colours, scientific symbolism, gestures, actions, music and sound, etc. combine with language in order to  communicate meaning. One of the effective multimodal media that combines both verbal and non-verbal elements to create meaning is political cartoons. Furthermore, since political and social issues are mirrored in political cartoons, these are regarded as potential objects of discourse analysis since they not only reflect the thoughts of the public but they also have the power to influence them. The aim of this paper is to analyze some selected cartoons on the recognition of Jerusalem as Israel's capital by the American President, Donald Trump, adopting a multimodal approach. More specifically, the present research examines how the various semiotic tools and resources utilized by the cartoonists function in projecting the intended meaning. Ten political cartoons, among a surge of editorial cartoons highlighted by the Anti-Defamation League (ADL) - an international Jewish non-governmental organization based in the United States - as publications in different Arabic-language newspapers in Egypt, Saudi Arabia, UAE, Oman, Iran and UK, were purposively selected for semiotic analysis. These editorial cartoons, all published during 6^th–18^th December 2017, invariably suggest one theme: Jewish and Israeli domination of the United States. The data were analyzed using the framework of Visual Social Semiotics. In accordance with this methodological framework, the selected visual compositions were analyzed in terms of three aspects of meaning: representational, interactive and compositional. In analyzing the selected cartoons, an interpretative approach is being adopted. This approach prioritizes depth to breadth and enables insightful analyses of the chosen cartoons. The findings of the study reveal that semiotic resources are key elements of political cartoons due to the inherent political communication they convey. It is proved that adequate interpretation of the three aspects of meaning is a prerequisite for understanding the intended meaning of political cartoons. It is recommended that further research should be conducted to provide more insightful analyses of political cartoons from a multimodal perspective.

Keywords: Multimodal Discourse Analysis (MDA), multimodal text, political cartoons, visual modality

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Authors: Roshani S. Golhar, Neerajkumar S. Sathawane, Snehal Dongre

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Background and objectives: As the, cardiovascular illnesses increasing and becoming cause of mortality worldwide, killing around lot of people each year. Arrhythmia is a type of cardiac illness characterized by a change in the linearity of the heartbeat. The goal of this study is to develop novel deep learning algorithms for successfully interpreting arrhythmia using a single second segment. Because the ECG signal indicates unique electrical heart activity across time, considerable changes between time intervals are detected. Such variances, as well as the limited number of learning data available for each arrhythmia, make standard learning methods difficult, and so impede its exaggeration. Conclusions: The proposed method was able to outperform several state-of-the-art methods. Also proposed technique is an effective and convenient approach to deep learning for heartbeat interpretation, that could be probably used in real-time healthcare monitoring systems

Keywords: electrocardiogram, ECG classification, neural networks, convolutional neural networks, portable document format

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Authors: Javier Donoso-Bravo, Camila Cortés-Zambrano

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In this paper, we analyze socioterritorial inequalities in the region of Valparaiso (Chile) using secondary data to account for these inequalities drawing on economic, social, educational, and environmental dimensions regarding the thirty-six municipalities of the region. We looked over a wide-ranging set of secondary data from public sources regarding economic activities, poverty, employment, income, years of education, post-secondary education access, green areas, access to potable water, and others. We found sharp socioterritorial inequalities especially based on the economic performance in each territory. Analysis show, on the one hand, the existence of a dual and unorganized development model in some territories with a strong economic activity -especially in the areas of finance, real estate, mining, and vineyards- but, at the same time, with poor social indicators. On the other hand, most of the territories show a dispersed model with very little dynamic economic activities and very poor social development. Finally, we discuss how socioterritorial inequalities in the region of Valparaiso reflect the level of globalization of the economic activities carried on in every territory.

Keywords: socioterritorial inequalities, development model, Chile, secondary data, Region of Valparaiso

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Authors: Andriana Mkrtchyan, Vahe Khlghatyan

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The choice of a profession is one of the most important decisions people make throughout their life. With the development of modern science, technologies, and all the spheres existing in the modern world, more and more professions are being arisen that complicate even more the process of choosing. Hence, there is a need for a guiding platform to help people to choose a profession and the right career path based on their interests, skills, and personality. This review aims at analyzing existing methods of comparing PDF format documents and suggests that a 3-stage approach is implemented for the comparison, that is – 1. text extraction from PDF format documents, 2. comparison of the extracted text via NLP algorithms, 3. comparison representation using special shape and color psychology methodology.

Keywords: color psychology, data acquisition/extraction, data augmentation, disambiguation, natural language processing, outlier detection, semantic similarity, text-mining, user evaluation, visual search

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Laicheng Cao, Xiangqian Su, Youxiao Wu

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Feature selection is one of the important problems in network security, pattern recognition, data mining and other fields. In order to remove redundant features, effectively improve the detection speed of intrusion detection system, proposes a new feature selection method, which is based on the invasive weed optimization (IWO) algorithm and tabu search algorithm(TS). Use IWO as a global search, tabu search algorithm for local search, to improve the results of IWO algorithm. The experimental results show that the feature selection method can effectively remove the redundant features of network data information in feature selection, reduction time, and to guarantee accurate detection rate, effectively improve the speed of detection system.

Keywords: intrusion detection, feature selection, iwo, tabu search

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Authors: Rabab Makki

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Bone mineral density and bone metabolism are affected by various factors such as genetic, endocrine, mechanical and nutritional. Our understanding of nutritional influences on bone health is limited because most studies have focused on calcium. This study investigated the dietary factors which are likely t contribute to Osteoporosis in Saudi post-menopausal women, and correlated it with BMD. This is a case controlled study involved 36 postmenopausal Saudi females selected from the Orthopedics and osteoporosis outpatient clinics, and 25 postmenopausal Saudi females as controls from the primary clinic of Military Hospital in Riyadh. The women were diagnosed as osteoporotic based on the BMD measurement at any site (left femur neck, right femur neck, left total hip or right total hip or spine). Both the controls and the Osteoporotics were over 50 years of age and BMI between 31-34 kg/m2 had 2nd degree obesity, and were not free from other problems such as diabetes, hypertension, etc. Subjects (osteoporotics and controls) were interviewed to called data on demographic characterstics, medical history, dietary intake anthropometry (height and weight) bone mineral density. Blood samples were collected from subjects (Osteoporotics and controls). Analysis of serum calcium, vitamin D, phosphate were done at the main laboratory at Military Hospital Riyadh, by the laboratory technician while BMD was determined at the department of Nuclear Medicine by an expert technician and results were interpreted by radiologist.Data on frequency of consumption of animal food (meat, eggs, poultry and fish) and diary foods (milk, yogurt, cheese) of osteoporotic was less than control. In spite of the low intake there was no association with BMD.In general, the vegetables and fruits were consumed less by the osteoporotics than control. The only fruit which had shown a significant positive correlation is banana with right and left hip BMD total probably due to high potassium and minerals content which likely to prevent bone resorption. Mataziz vegetables combination of wheat showed a significant positive correlation with the same site (total right and left hip). Both osteoporotics abd controls were consuming table sugar. (But the sweet intake showed a significant negative correlation with left neck femur BMD, suggesting sucrose increase urinary calcium loss. Both osteoporotic and controls were consuming Arabic coffee. A negative significant correlation between intake of Arabic coffee and BMD of right neck femur of osteoporosis patient was observed. It could be suggested that increased intake of fruits and vegetables, might promote bone density while high intake of coffee and sugars might affect bone density, no significant correlation was observed between BMD at any site and diary product. We can say the major risk factors are inadequate nutrition. Further studies are needed among Saudi population to confirm these results.

Keywords: osteoporosi, Saudia Arabia, Riyadh Armed Forces, postmenopausal women

Procedia PDF Downloads 390

Authors: Raja Lahiani

Abstract:

'Locksley Hall' is a poem that Lord Alfred Tennyson (1809-1892) published in 1842. It is believed to be his first attempt to face as a poet some of the most painful of his experiences, as it is a study of his rising out of sickness into health, conquering his selfish sorrow by faith and hope. So far, in Victorian scholarship as in modern criticism, 'Locksley Hall' has been studied and approached as a canonical Victorian English poem. The aim of this project is to prove that some strategies of translation were used in this poem in such a way as to guarantee its assimilation into the English canon and hence efface to a large extent its Arabic roots. In its relationship with its source text, 'Locksley Hall' is at the same time mimetic and imitative. As part of the terminology used in translation studies, ‘imitation’ means almost the exact opposite of what it means in ordinary English. By adopting an imitative procedure, a translator would do something totally different from the original author, wandering far and freely from the words and sense of the original text. An imitation is thus aimed at an audience which wants the work of the particular translator rather than the work of the original poet. Hallam Tennyson, the poet’s biographer, asserts that 'Locksley Hall' is a simple invention of place, incidents, and people, though he notes that he remembers the poet claiming that Sir William Jones’ prose translation of the Mu‘allaqat (pre-Islamic poems) gave him the idea of the poem. A comparative work would prove that 'Locksley Hall' mirrors a great deal of Tennyson’s biography and hence is not a simple invention of details as asserted by his biographer. It would be challenging to prove that 'Locksley Hall' shares so many details with the Mu‘allaqat, as declared by Tennyson himself, that it needs to be studied as an imitation of the Mu‘allaqat of Imru’ al-Qays and ‘Antara in addition to its being a poem in its own right. Thus, the main aim of this work is to unveil the imitative and mimetic strategies used by Tennyson in his composition of 'Locksley Hall.' It is equally important that this project researches the acculturating assimilative tools used by the poet to root his poem in its Victorian English literary, cultural and spatiotemporal settings. This work adopts a comparative methodology. Comparison is done at different levels. The poem will be contextualized in its Victorian English literary framework. Alien details related to structure, socio-spatial setting, imagery and sound effects shall be compared to Arabic poems from the Mu‘allaqat collection. This would determine whether the poem is a translation, an adaption, an imitation or a genuine work. The ultimate objective of the project is to unveil in this canonical poem a new dimension that has for long been either marginalized or ignored. By proving that 'Locksley Hall' is an imitation of classical Arabic poetry, the project aspires to consolidate its literary value and open up new gates of accessing it.

Keywords: comparative literature, imitation, Locksley Hall, Lord Alfred Tennyson, translation, Victorian poetry

Procedia PDF Downloads 183

Authors: Penina Orenstein

Abstract:

In today’s world, particularly with COVID-19 a constant worldwide threat, organizations need greater visibility over their supply chains more than ever before, in order to find areas for improvement and greater efficiency, reduce the chances of disruption and stay competitive. The concept of supply chain mapping is one where every process and route is mapped in detail between each vendor and supplier. The simplest method of mapping involves sourcing publicly available data including news and financial information concerning relationships between suppliers. An additional layer of information would be disclosed by large, direct suppliers about their production and logistics sites. While this method has the advantage of not requiring any input from suppliers, it also doesn’t allow for much transparency beyond the first supplier tier and may generate irrelevant data—noise—that must be filtered out to find the actionable data. The primary goal of this research is to build data maps of supply chains by focusing on a layered approach. Using these maps, the secondary goal is to address the question as to whether the supply chain is re-engineered to make improvements, for example, to lower the carbon footprint. Using a drill-down approach, the end result is a comprehensive map detailing the linkages between tier-one, tier-two, and tier-three suppliers super-imposed on a geographical map. The driving force behind this idea is to be able to trace individual parts to the exact site where they’re manufactured. In this way, companies can ensure sustainability practices from the production of raw materials through the finished goods. The approach allows companies to identify and anticipate vulnerabilities in their supply chain. It unlocks predictive analytics capabilities and enables them to act proactively. The research is particularly compelling because it unites network science theory with empirical data and presents the results in a visual, intuitive manner.

Keywords: data mining, supply chain, empirical research, data mapping

Procedia PDF Downloads 158

Authors: K. Sathishkumar, V. Thiagarasu

Abstract:

Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

Procedia PDF Downloads 308

Authors: Anyimc, C. J. Aneke, J. O. Orji, O. Nworie, U. C. C. Egbule

Abstract:

The microbial examination and antimicrobial susceptibility profile of microorganism isolated from the salt mining site in Ebonyi state were evaluated in the present study using a standard microbiological technique. A total of 300 samples were randomly collected in three sample groups (A, B, and C) of 100 each. Isolation, Identification and characterization of organization present on the soil samples were determined by culturing, gram-staining and biochemical technique. The result showed the following organisms were isolated with their frequency as follow: Bacillus species (37.3%) and Staphylococcus species(23.5%) had the highest frequency in the whole Sample group A and B while Klebsiella specie (15.7%), Pseudomonas species(13.7%), and Erwinia species (9.8%) had the least. Rhizopus species (42.0%) and Aspergillus species (26.0%) were the highest fungi isolated, followed by Penicillum species (20.0%) while Mucor species (4.0%), and Fusarium species (8.0%) recorded the least. Sample group C showed high microbial population of all the microbial isolates when compared to sample group A and B. Disc diffusion method was used to determine the susceptibility of isolated bacteria to various antibiotics (oxfloxacin, pefloxacin, ciprorex, augumentin, gentamycin, ciproflox, septrin, ampicillin), while agar well diffusion method was used to determine the susceptibility of isolated fungi to some antifungal drugs (metronidazole, ketoconazole, itraconazole fluconazole). The antibacterial activity of the antibiotics used showed that ciproflux has the best inhibitory effect on all the test bacteria. Ketoconazole showed the highest inhibitory effect on the fungal isolates, followed by itraconazole, while metronidazole and fluconazole showed the least inhibitory effect on the entire test fungal isolates. Hence, the multiple drug resistance of most isolates to appropriate drugs of choice are of great public health concern and cells for periodic monitoring of antibiograms to detect possible changing patterns. Microbes isolated in the salt mining site can also be used as a source of gene(s) that can increase salt tolerance in different crop species through genetic engineering.

Keywords: microorganisms, antibacterial, antifungal, resistance, salt mining site, Ebonyi State

Procedia PDF Downloads 294