Search results for: statistical features

Authors: Yassine Jamoussi, Ameni Youssfi, Henda Ben Ghezala

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With the growing interest in social networking, the interaction of social actors evolved to a source of knowledge in which it becomes possible to perform context aware-reasoning. The information extraction from social networking especially Twitter and Facebook is one of the problems in this area. To extract text from social networking, we need several lexical features and large scale word clustering. We attempt to expand existing tokenizer and to develop our own tagger in order to support the incorrect words currently in existence in Facebook and Twitter. Our goal in this work is to benefit from the lexical features developed for Twitter and online conversational text in previous works, and to develop an extraction model for constructing a huge knowledge based on actions

Keywords: social networking, information extraction, part-of-speech tagging, natural language processing

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Authors: Atefeh Heydari, Mohammadali Tavakoli, Naomie Salim

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In recent years, we have witnessed that online reviews are the most important source of customers’ opinion. They are progressively more used by individuals and organisations to make purchase and business decisions. Unfortunately, for the reason of profit or fame, frauds produce deceptive reviews to hoodwink potential customers. Their activities mislead not only potential customers to make appropriate purchasing decisions and organisations to reshape their business, but also opinion mining techniques by preventing them from reaching accurate results. Spam reviews could be divided into two main groups, i.e. multiple and singleton spam reviews. Detecting a singleton spam review that is the only review written by a user ID is extremely challenging due to lack of clue for detection purposes. Singleton spam reviews are very harmful and various features and proofs used in multiple spam reviews detection are not applicable in this case. Current research aims to propose a novel supervised technique to detect singleton spam reviews. To achieve this, various features are proposed in this study and are to be combined with the most appropriate features extracted from literature and employed in a classifier. In order to compare the performance of different classifiers, SVM and naive Bayes classification algorithms were used for model building. The results revealed that SVM was more accurate than naive Bayes and our proposed technique is capable to detect singleton spam reviews effectively.

Keywords: classification algorithms, Naïve Bayes, opinion review spam detection, singleton review spam detection, support vector machine

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Authors: Eunice H. Li

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This paper discusses and analyses a small portion of the literature that has been reviewed for research work in Distance Education (DE) pedagogies that I am currently undertaking. It begins by presenting a brief overview of Taylor's (2001) five-generation models of Distance Education. The focus of the discussion will be on the 5th generation, Intelligent Flexible Learning Model. For this generation, educational and other institutions make portal access and interactive multi-media (IMM) an integral part of their operations. The paper then takes a brief look at current trends in technologies – for example smart-watch wearable technology such as Apple Watch. The emergent trends in technologies carry many new features. These are compared to former DE generational features. Also compared is the time span that has elapsed between the generations that are referred to in Taylor's model. This paper is a work in progress. The paper therefore welcome new insights, comparisons and critique of the issues discussed.

Keywords: distance education, e-learning technologies, pedagogy, generational models

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Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

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Authors: Jian-Jun Shu

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The statistical properties of CRMs are explored by estimating similar-word set occurrence distribution. It is observed that CRMs tend to have a fat-tail distribution for similar-word set occurrence. Thus, the fat-tail test with two fatness coefficients is proposed to distinguish CRMs from non-CRMs, especially from exons. For the first fatness coefficient, the separation accuracy between CRMs and exons is increased as compared with the existing content-based CRM prediction method – fluffy-tail test. For the second fatness coefficient, the computing time is reduced as compared with fluffy-tail test, making it very suitable for long sequences and large data-base analysis in the post-genome time. Moreover, these indexes may be used to predict the CRMs which have not yet been observed experimentally. This can serve as a valuable filtering process for experiment.

Keywords: statistical approach, transcription factor binding sites, cis-regulatory modules, DNA sequences

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Authors: Abbas Ghahremani

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One of the most fundamental management issues in organizations and companies is the recruiting of efficient staff and compiling exact and perfect criteria for testing the applicants,which is guided and practiced by the manager of human resources of the organization. Obviously, each part of the organization seeks special features and abilities in the people apart from common features among all the staff in all units,which are called principal duties and abilities,and we will study them more. This article is trying to find out how we can identify the most efficient people among the applicants of employment by using proper methods of testing appropriate for the needs of different of employment by using proper methods of testing appropriate for the needs of different units of the organization and recruit efficient staff. Acceptable method for recruiting is to closely identify their characters from various aspects such as ability to communicate, flexibility, stress management, risk acceptance, tolerance, vision to future, familiarity with the art, amount of creativity and different thinking and by raising proper questions related with the above named features and presenting a questionnaire, evaluate them from various aspect in order to gain the proper result. According to the above explanations, it can be concluded which aspects of abilities and characteristics of a person must be evaluated in order to reduce any mistake in recruitment and approach an ideal result and ultimately gain an organized system according to the standards and avoid waste of energy for unprofessional personnel which is a marginal issue in the organizations.

Keywords: human resources management, staff recuiting, employment factors, efficient staff

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Authors: Bruno Trstenjak, Dzenana Donko

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Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.

Keywords: case based reasoning, classification, expert's knowledge, hybrid model

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Authors: Sheena Christabel Pravin, M. Palanivelan

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Speech disfluencies are common in spontaneous speech. The primary purpose of this study was to distinguish linguistic disfluencies from stuttering disfluencies in bilingual Tamil–English (TE) speaking children. The secondary purpose was to determine whether their disfluencies are mediated by native language dominance and/or on an early onset of developmental stuttering at childhood. A detailed study was carried out to identify the prosodic and acoustic features that uniquely represent the disfluent regions of speech. This paper focuses on statistical modeling of repetitions, prolongations, pauses and interjections in the speech corpus encompassing bilingual spontaneous utterances from school going children – English and Tamil. Two classifiers including Hidden Markov Models (HMM) and the Multilayer Perceptron (MLP), which is a class of feed-forward artificial neural network, were compared in the classification of disfluencies. The results of the classifiers document the patterns of disfluency in spontaneous speech samples of school-aged children to distinguish between Children Who Stutter (CWS) and Children with Language Impairment CLI). The ability of the models in classifying the disfluencies was measured in terms of F-measure, Recall, and Precision.

Keywords: bi-lingual, children who stutter, children with language impairment, hidden markov models, multi-layer perceptron, linguistic disfluencies, stuttering disfluencies

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

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

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

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

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Authors: Asad Abbas, Muhammad Fezan Afzal, Muhammad Latif Anjum, Muhammad Azmat

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The Internet of Things (IoT) is used to link up real objects that use the internet to interact. IoT applications allow handling and operating the equipment in accordance with environmental needs, such as transportation and healthcare. IoT devices are linked together via a number of agents that act as a middleman for communications. The operation of a heat sensor differs indoors and outside because agent applications work with environmental variables. In this article, we suggest using Software Product Line (SPL) to model IoT agents and applications' features on an XML-based basis. The contextual diversity within the same domain of application can be handled, and the reusability of features is increased by XML-based feature modelling. For the purpose of managing contextual variability, we have embraced XML for modelling IoT applications, agents, and internet-connected devices.

Keywords: IoT agents, IoT applications, software product line, feature model, XML

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Authors: Avantika Verma

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Diabetic retinopathy (DR) and Central serous retinopathy (CSR) are 2 distinct entities, with difference in age of presentation, eitiopathogenesis and clinical features, but when occurring together, can be a diagnostic dilemma and requires careful evaluation. Case study of 3 patients with long standing diabetes (>15yrs) and features of Central serous retinopathy was done at Bangalore West Lions Superspeciality Eye Hospital, Bangalore, India in 2013. Even though diabetic retinopathy and CSR have different pathologies, they can coexist. The reason for coexistence could be the following: A patient with CSR as a young adult could develop DR in later years. Stress could be the contributing factor in older patient with diabetes.Stress could be a common factor for both, as it is one of the important factors in the pathogenesis of Maturity Onset Diabetes Miletus (MODY). In any situation, a careful evaluation is necessary to differentiate the cause of fundus picture, as treatment differs for the two diseases.

Keywords: central serous retinopathy, diabetic retinopathy, existence, stress

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Authors: P. V. Pramila , V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest

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Authors: Rasim M. Alguliyev, Alovsat G. Aliyev, Roza O. Shahverdiyeva

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The paper investigated the role and position of high techno-parks, which is one of the priorities of Azerbaijan. The main objectives, functions and features of the establishment of high-techno parks, as well as organization of the activity of the structural elements, which are the parking complex and their interactions were analyzed. The development, organization and management of high techno-parks were studied. The key features and functions of innovative structures’ management were explained. The need for a comprehensive management system for the development of high-techno parks was emphasized and the major problems were analyzed. In addition, the methods were proposed for the development of information systems supporting decision making in systematic and sustainable management of the parks.

Keywords: innovative development, innovation processes, innovation economy, innovation infrastructure, high technology park, efficient management, management decisions, information insurance

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Authors: Maria Istvanova

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The purpose of the comparative study of the affricate consonants in Chinese and Slovak is to increase the awareness of the main distinguishing features between these two languages taking into consideration this particular group of consonants. This study determines the main difficulties of the Slovak learners in the process of acquiring correct pronunciation of affricate initial consonants in Chinese based on the understanding of the distinguishing features of Chinese and Slovak affricates in combination with the experimental measuring of VOT values. The software tool Praat is used for the analysis of the recorded language samples. The language samples contain recordings of a Chinese native speaker and Slovak students of Chinese with different language proficiency levels. Based on the results of the analysis in Praat, the study identifies erroneous pronunciation and provide clarification of its cause.

Keywords: Chinese, comparative study, initial consonants, pronunciation, Slovak

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Authors: Mohammad Reza Ostad Ali Naghi Kashani, Esfanji Elia

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Nowadays, the amounts of companies which tend to have an Enterprise Resource Planning (ERP) application are increasing particularly in developing countries like Iran. ERP projects are expensive, time consuming, and complex, in addition the failure rate is high among these projects. It is important to know whether these projects could meet their goals or not. Furthermore, the area which should be improved should be identified. In this paper we made a framework to evaluate ERP projects success implementation. First, based on literature review we made a framework based on BSC model, financial, customer, processes, learning and knowledge, because of the importance of change management it was added to model. Then an organization was divided in three layers. We choose corporate, managerial, and operational levels. Then to find criteria to assess each aspect, we use Delphi method in two rounds. And for the second round we made a questionnaire and did some statistical tasks on them. Based on the statistical results some of them are accepted and others are rejected.

Keywords: ERP, BSC, ERP project evaluation, IT projects

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Authors: Sello Mokwena, Monyepao Thabang

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In this study, we propose a comprehensive approach to address the challenges in person re-identification models. By combining a centroid tracking algorithm with a Siamese convolutional neural network model, our method excels in detecting, tracking, and capturing robust person features across non-overlapping camera views. The algorithm efficiently identifies individuals in the camera network, while the neural network extracts fine-grained global features for precise cross-image comparisons. The approach's effectiveness is further accentuated by leveraging the camera network topology for guidance. Our empirical analysis on benchmark datasets highlights its competitive performance, particularly evident when background subtraction techniques are selectively applied, underscoring its potential in advancing person re-identification techniques.

Keywords: camera network, convolutional neural network topology, person tracking, person re-identification, siamese

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Authors: Hasliza A. Rahim, Fareq Malek, Nur A. M. Affendi, Azuwa Ali, Norshafinash Saudin, Latifah Mohamed

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This paper presents the experimental investigation of on-body channel fading at 2.45 GHz considering two effects of the user body movement; stationary and mobile. A pair of body-worn antennas was utilized in this measurement campaign. A statistical analysis was performed by comparing the measured on-body path loss to five well-known distributions; lognormal, normal, Nakagami, Weibull and Rayleigh. The results showed that the average path loss of moving arm varied higher than the path loss in sitting position for upper-arm-to-left-chest link, up to 3.5 dB. The analysis also concluded that the Nakagami distribution provided the best fit for most of on-body static link path loss in standing still and sitting position, while the arm movement can be best described by log-normal distribution.

Keywords: on-body channel communications, fading characteristics, statistical model, body movement

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Authors: Kanda Runapongsa Saikaew, Chaluemwut Noyunsan

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Nowadays social media information, such as news, links, images, or VDOs, is shared extensively. However, the effectiveness of disseminating information through social media lacks in quality: less fact checking, more biases, and several rumors. Many researchers have investigated about credibility on Twitter, but there is no the research report about credibility information on Facebook. This paper proposes features for measuring credibility on Facebook information. We developed the system for credibility on Facebook. First, we have developed FB credibility evaluator for measuring credibility of each post by manual human’s labelling. We then collected the training data for creating a model using Support Vector Machine (SVM). Secondly, we developed a chrome extension of FB credibility for Facebook users to evaluate the credibility of each post. Based on the usage analysis of our FB credibility chrome extension, about 81% of users’ responses agree with suggested credibility automatically computed by the proposed system.

Keywords: facebook, social media, credibility measurement, internet

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Authors: Gabriela-Andreea Despescu, Mădălina Mavrodin, Gheorghe Lăzăroiu, S. Nacu, R. Băstinaş

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The Monitoring of Surface Water Bodies (Rivers) from Tisa Catchment Area - Maramureş County in 2014. This study is focused on the monitoring and evaluation of river’s water bodies from Maramureş County, using the methodology associated with the EU Water Framework Directive 60/2000. Thus, in the first part are defined the theoretical terms of monitoring activities related to the water bodies’ quality and the specific features of those we can find in the studied area. There are presented the water bodies’ features, quality indicators and the monitoring frequencies for the rivers situated in the Tisa catchment area. The results have shown the actual ecological and chemical state of those water bodies, in relation with the standard values mentioned through the Water Framework Directive.

Keywords: monitoring, surveillance, water bodies, quality

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Authors: Lota Largavista

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This study entitled, ‘The Organizational Structure, Development Features, and Metadiscoursal Elements in the Expository Writing of Freshman College Writers’ aimed to examine essays written by college students. It seeks to examine the organizational structure and development features of the essays and describe their defining characteristics, the linguistic elements at both macrostructural and microstructural discourse levels and the types of textual and interpersonal metadiscourse markers that are employed in order to negotiate meanings with their prospective readers. The different frameworks used to analyze the essays include Toulmin’s ( 1984) model for argument structure, Olson’s ( 2003) three-part essay structure; Halliday and Matthiesen (2004) in Herriman (2011) notions of thematic structure, Danes (1974) thematic progression or method of development, Halliday’s (2004) concept of grammatical and lexical cohesion ;Hyland’s (2005) metadiscourse strategies; and Chung and Nation’s( 2003) four-step scale for technical vocabulary. This descriptive study analyzes qualitatively and quantitatively how freshman students generally express their written compositions. Coding of units is done to determine what linguistic features are present in the essays. Findings revealed that students’ expository essays observe a three-part structure having all three moves, the Introduction, the Body and the Conclusion. Stance assertion, stance support, and emerging moves/strategies are found to be employed in the essays. Students have more marked themes on the essays and also prefer constant theme progression as their method of development. The analysis of salient linguistic elements reveals frequently used cohesive devices and metadiscoursal strategies. Based on the findings, an instructional learning plan is being proposed. This plan is characterized by a genre approach that focuses on expository and linguistic conventions.

Keywords: metadiscourse, organization, theme progression, structure

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Authors: Fernando Miguel Campos, Fernando Jesus Aguiar Campos, Pedro Filipe Campos

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A large amount of software products offer a wide range and number of features. This is called featurities or creeping featurism and tends to rise with each release of the product. Feautiris often adds unnecessary complexity to software, leading to longer learning curves and overall confusing the users and degrading their experience. We take a look to a new design approach tendency that has been coming up, the so-called “What You Get Is What You Need” concept that argues that products should be very focused, simple and with minimalistic interfaces in order to help users conduct their tasks in distraction-free ambiances. This is not as simple to implement as it might sound and the developers need to cut down features. Our contribution illustrates and evaluates this design method through a novel distraction-free diagramming tool named Delineato Pro for Mac OS X in which the user is confronted with an empty canvas when launching the software and where tools only show up when really needed.

Keywords: diagramming, HCI, usability, user interface

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Authors: Anano Tenieshvili, Teona Lodia

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Social anxiety disorder (SAD) is one of the most common mental health problems not only in adults but also in adolescents. Individuals with SAD exhibit difficulties in interpersonal relationships, understanding emotions, and regulating them as well. For social and emotional adaptation, it is crucial to identify, understand, accept and manage emotions correctly. Researchers actively learn those factors that contribute to the development and maintenance of this condition. Therefore, the main purpose of this study is to acquire knowledge about the association between social anxiety and individual characteristics, such as theory of mind (ToM), verbal irony comprehension, and personal traits. 112 adolescents aged from 12 to 18 were selected for this research. 15 of them are diagnosed with Social anxiety disorder. Statistical analysis was performed on the entire sample, and furthermore, two groups, adolescents with and without social anxiety disorder, were compared separately. Social anxiety and personal traits were assessed by questionnaires. Theory of mind and comprehension of verbal irony were measured using tests. Statistical analysis indicated a positive relationship between social anxiety and comprehension of ironic criticism. Moreover, social anxiety was significantly positively correlated with neuroticism and isolation tendency, whereas it was negatively related to extraversion and frustration tolerance. On top of that, statistical analysis revealed a positive relationship between ToM and verbal irony comprehension. However, the relationship between social anxiety and ToM was not statistically significant. In conclusion, the current research expands knowledge about social anxiety and supports the results of some previous studies.

Keywords: personal traits, social anxiety, theory of mind, verbal irony comprehension

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Authors: Anano Tenieshvili, Teona Lodia

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Social anxiety disorder (SAD) is one of the most common mental health problems not only in adults but also in adolescents. Individuals with SAD exhibit difficulties in interpersonal relationships, understanding emotions and regulating them as well. For social and emotional adaptation, it is crucial to identify, understand, accept and manage emotions correctly. Researchers actively learn those factors that contribute to the development and maintenance of this condition. Therefore, the main purpose of this study is to acquire knowledge about the association between social anxiety and individual characteristics, such as the theory of mind (ToM), verbal irony comprehension and personal traits. 112 adolescents aged from 12 to 18 were selected for this research. 15 of them are diagnosed with Social anxiety disorder. Statistical analysis was performed on the entire sample and furthermore, two groups, adolescents with and without a social anxiety disorder, were compared separately. Social anxiety and personal traits were assessed by questionnaires. Theory of mind and comprehension of verbal irony was measured using tests. Statistical analysis indicated a positive relationship between social anxiety and comprehension of ironic criticism. Moreover, social anxiety was significantly positively correlated with neuroticism and isolation tendency, whereas it was negatively related to extraversion and frustration tolerance. On top of that, statistical analysis revealed a positive relationship between ToM and verbal irony comprehension. However, the relationship between social anxiety and ToM was not statistically significant. In conclusion, the current research expands knowledge about social anxiety and supports the results of some previous studies.

Keywords: personal traits, social anxiety, theory of mind, verbal irony comprehension

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Authors: Reda A. H. Mahmoud

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This paper investigates the pragmatic meaning of prosodic focus through four accentuation moods of blaming utterances in Egyptian Arabic. Prosodic focus results in various pragmatic meanings when the speaker utters the same blaming expression in different emotional moods: the angry, the mocking, the frustrated, and the informative moods. The main objective of this study is to interpret the meanings of these four accentuation moods in relation to their illocutionary forces and pre-locutionary effects, the integrated features of prosodic focus (e.g., tone movement distributions, pitch accents, lengthening of vowels, deaccentuation of certain syllables/words, and tempo), and the consonance between the former prosodic features and certain lexico-grammatical components to communicate the intentions of the speaker. The data on blaming utterances has been collected via elicitation and pre-recorded material, and the selection of blaming utterances is based on the criteria of lexical and prosodic regularity to be processed and verified by three computer programs, Praat, Speech Analyzer, and Spectrogram Freeware. A dual pragmatic approach is established to interpret expressive blaming utterance and their lexico-grammatical distributions into intonational focus structure units. The pragmatic component of this approach explains the variable psychological attitudes through the expressions of blaming and their effects whereas the analysis of prosodic focus structure is used to describe the intonational contours of blaming utterances and other prosodic features. The study concludes that every accentuation mood has its different prosodic configuration which influences the listener’s interpretation of the pragmatic meanings of blaming utterances.

Keywords: pragmatics, pragmatic interpretation, prosody, prosodic focus

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Authors: Beema Akbar, Varun P. Gopi, V. Suresh Babu

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Colon cancer causes the deaths of about half a million people every year. The common method of its detection is histopathological tissue analysis, it leads to tiredness and workload to the pathologist. A novel method is proposed that combines both structural and statistical pattern recognition used for the detection of colon cancer. This paper presents a comparison among the different classifiers such as Multilayer Perception (MLP), Sequential Minimal Optimization (SMO), Bayesian Logistic Regression (BLR) and k-star by using classification accuracy and error rate based on the percentage split method. The result shows that the best algorithm in WEKA is MLP classifier with an accuracy of 83.333% and kappa statistics is 0.625. The MLP classifier which has a lower error rate, will be preferred as more powerful classification capability.

Keywords: colon cancer, histopathological image, structural and statistical pattern recognition, multilayer perception

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Authors: Shahzad A. Mughal, Ameer A. P. Ghaloo, Faisal Laghari, Mohsin A. Mirza

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Job satisfaction and level of job stressors among employees of a university are considered as essential factors responsible for institutional success. Job satisfaction is usually believed as a single baseline variable for the evaluation of a university human resource area. The objectives of this study were to assess the level of job satisfaction and influence of job stressors among university teachers and their association with long term physical health of the employees in government sector universities in Pakistan. A cross-sectional study was conducted on university employees including faculty members and administrative staff of three government sector universities in Sindh province of Pakistan who have completed at least ten years of their job. The study period was six months. All the employees were randomly selected. The job satisfaction scale Questionnaire with yes and no options, together with questions regarding demographic factors, job stress or other working factors and physical health issues were administered in questionnaires. These questionnaires were handed out to 100 faculty members of both genders with permanent job and 50 non faculty staff of grade 17 and above with permanent employment status. Students’ T test and one way ANOVA was applied to categorical variables and Pearson’s correlation analysis was performed to evaluate the correlations between study variables. 121 successful responses were obtained (effective respondent rate 80.6%). The average score of overall job satisfaction was 65.6%. Statistical analysis revealed that the job satisfaction and work related stressors had negative impact on overall health status of the employees with resultant less efficacy and mental stress. The positive relation was perceived by employees for organizational support and high income with job satisfaction. Demographic features such as age and female gender were also linked to the level of job satisfaction and health related issues. The total variation among all responses regarding correlation between job satisfaction job stressors and health related issues was 55%. A study was conducted on University employees of government sector Universities in Pakistan, regarding association of job satisfaction and job stressors with long term physical health of the employees. Study revealed a moderate level of job satisfaction among the employees of all universities included in this study. Attitude and personal relations with heads of the departments and institution along with salary packages were considered as biggest job stressors related correlated directly with physical health. Demographic features and gender were associated factors for job satisfaction. Organizational support was the strongest factor for job satisfaction and results pointed out that by improving support level from University may improve the quality of job satisfaction and overall health of employees.

Keywords: job satisfaction, organizational support, physical health, university employees

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Authors: A. Luli, A. Santona

Abstract:

It is rare for individuals that are involved in a relationship to think about the possibility of having procreation problems in the near present or in the future. However, infertility is a condition that affects millions of people all around the world. Often, infertile individuals have to deal with experiences of psychological, relational and social problems. In these cases, they have to review their choices and take into consideration, if it is necessary, new ones. Different studies have examined the different decisions that infertile individuals have to go through dealing with infertility and its treatment, but none of them is focused on the decision-making style used by infertile individuals to solve their problem and on the factors that influences it. The aim of this paper is to define the style of decision-making used by infertile persons to give a solution to the ‘problem’ and the potential predictive role of the attachment and of the dyadic adjustment. The total sample is composed by 251 participants, divided in two groups: the experimental group composed by 114 participants, 62 males and 52 females, age between 25 and 59 years, and the control group composed by 137 participants, 65 males and 72 females, age between 22 and 49 years. The battery of instruments used is composed by: the General Decision Making Style (GDMS), the Experiences in Close Relationships Questionnaire Revised (ECR-R), Dyadic Adjustment Scale (DAS), and the Symptom Checklist-90-R (SCL-90-R). The results from the analysis of the samples showed a prevalence of the rational decision-making style for both males and females. No significant statistical difference was found between the experimental and control group. Also the analyses showed a significant statistical relationship between the decision making styles and the adult attachment styles for both males and females. In this case, only for males, there was a significant statistical difference between the experimental and the control group. Another significant statistical relationship was founded between the decision making styles and the adjustment scales for both males and females. Also in this case, the difference between the two groups was founded to be significant only of males. These results contribute to enrich the literature on the subject of decision-making styles in infertile individuals, showing also the predictive role of the attachment styles and the adjustment, confirming in this was the few results in the literature.

Keywords: adjustment, attachment, decision-making style, infertility

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Authors: Md Tasbirul Islam, Pablo Dias, Nazmul Huda

Abstract:

E-waste/Waste electrical and electronic equipment (WEEE) is one of the fastest growing waste streams across the globe. This paper aims to compare the e-waste management system in Switzerland and Australia in terms of four features - legislative initiatives, disposal practice, collection and financial mechanisms. The qualitative content analysis is employed as a research method in the study. Data were collected from various published academic research papers, industry reports, and web sources. In addition, a questionnaire survey is conducted in Australia to understand the public awareness and opinions on the features. The results of the study provide valuable insights to policymakers in Australia developing better e-waste management system in conjunction with the public consensus, and the state-of-the-art operational strategies currently being practiced in Switzerland.

Keywords: E-waste management, WEEE, awareness, pro-environmental behavior, Australia, Switzerland

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Authors: Kiknadze T, Tevdorashvili G, Muzashvili T, Gachechiladze M, Burkadze G

Abstract:

Uterine leiomyomas decrease the quality of life by causing significant morbidity among women of reproductive age. Histologically various types of leiomyoma's can be differentiated. We have analysed th histopathological, proliferation, apoptotic, and hormonal profile in different types of leiomyomas. Study included altogether140 cases distributed into the following groups: group I-normal myometrium (20cases), group II-classic leiomyoma (69 cases), group III-cellular leiomyoma (15 cases), group IV-bizarre cell/atypical leiomyoma (22cases), group V-smooth muscle tumors of uncertain malignancy potential (STUMP) (8 cases) and group VI-leiomyosarcoma (6 cases). Together with classic histopathological features such as nuclear atypia, cellularity, presence of mitoses, vasculature and necrosis, immunohistochemical phenotype using antibodies against Ki67,Cas3, ER, and PR were analysed. The results of our study showed that leiomyomas are charterised with variable histopathological and immunohistocthemical phenotype. Histopathological parameters mainly correlate with the degree of malignancy except for two bizarre/atypical leiomyoma and STUMP, where two distinct subgroups could be identified. In bizarre/ atipycal leiomyoma, 31% of cases are characterized with the features of classic leiomyoma, whilst the rest of the cases reveal more atipycal phenotype. In STUMP 37.5 % of cases are characterized with the features of atipycal leiomyomas. The result of the immunohistochemical study also reveald that half of bizarre/atipycal leiomyomas are characterized with the low proliferation index, high apoptotic index, and high ER and PR index, whilst another half is characterized with high proliferation index, low apoptotic index, and low ER and PR index. Similarly, part of the STUMP cases are characterized with low proliferation index, high Er, and PR index and whilst part of the cases are characterized whith high proliferation index, low apoptotic index and low ER and PR index. The results of the histopathological and immunohistochemical study indicate that these two entities represent the heterogenous group of diseases, which might be the explanation of their different prognosis. Presented histopathological and immunohistochemical features should be considered in the diagnosis of myometrial smooth muscle tumors.

Keywords: proliferation, apoptosis, bizarre cell, leiomyosarcoma., leiomyoma

Procedia PDF Downloads 91