Search results for: interactive cultural learning

Authors: Maria Diogo, Patrícia Diogo

Abstract:

The stone is a constituent part of the geological structure of the Territory, introducing himself as a subject that has always interconnected human and environment in the development of a discourse of meanings and symbols that reflect elements realized in different cultures and experiences. This action meant that the first settlements and their areas of influence gained importance in the field of humanization and spatial organization of the territory, not only for the appropriation that its inhabitants did, but mainly because the community regardless of their economic or social condition, used it as living space and cultural integration. These factors become decisive in the characterization of the landscape area in the northwest of Portugal, because the stone is a material that appears not only in the natural landscape, but is also a strong element in humanized landscape, becoming this relation the main characterization of the study area.

Keywords: Landscape, Men, Stone, Territory.

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Authors: E. Podhovnik

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Cultures play a role in business communication and in research. At the example of language in international business, this paper addresses the issue of how the research cultures of management research and linguistics as well as cultures as such can be linked. After looking at existing research on language in international business, this paper approaches communication in international business from a linguistic angle and attempts to explain communication issues in businesses based on linguistic research. Thus the paper makes a step into cross-disciplinary research combining management research with linguistics.

Keywords: Language in international business, sociolinguistics, ethnopragmatics, cultural scripts.

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Authors: Nadeem Akhtar, Shan Bo

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This article illustrates that how non similar culture become a cause of constant anxiety among international students in China. For that, a survey was carried out among international students of Wuhan University, China. The association among non similar culture, non familiarity of Chinese culture, self finance students and food problem is looked at through a regression line, and in the light of empirical results, a model is anticipated which elucidates these results. Some suggestions were directed at the end which will help to mitigate the anxiety among prospective students in Chinese universities.

Keywords: Anxiety, international students, non similar culture, Wuhan University

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Authors: Ashly Joseph

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Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies.

Keywords: Machine Learning, Natural Learning Processing, Denial-of-Service attacks, Sentiment Analysis, Cloud computing.

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Authors: Fatima Muhammad Shitu

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In language learning, second language learners as well as Native speakers commit errors in their attempt to achieve competence in the target language. The realm of collocation has to do with meaning relation between lexical items. In all human language, there is a kind of ‘natural order’ in which words are arranged or relate to one another in sentences so much so that when a word occurs in a given context, the related or naturally co-occurring word will automatically come to the mind. It becomes an error, therefore, if students inappropriately pair or arrange such ‘naturally’ co–occurring lexical items in a text. It has been observed that most of the second language learners in this research group commit collocation errors. A study of this kind is very significant as it gives insight into the kinds of errors committed by learners. This will help the language teacher to be able to identify the sources and causes of such errors as well as correct them thereby guiding, helping and leading the learners towards achieving some level of competence in the language. The aim of the study is to understand the nature of these errors as stumbling blocks to effective essay writing. The objective of the study is to identify the errors, analyze their structural compositions so as to determine whether there are similarities between students in this regard and to find out whether there are patterns to these kinds of errors which will enable the researcher to understand their sources and causes. As a descriptive research, the researcher samples some nine hundred essays collected from three hundred undergraduate learners of English as a second language in the Federal College of Education, Kano, North- West Nigeria, i.e. three essays per each student. The essays which were given on three different lecture times were of similar thematic preoccupations (i.e. same topics) and length (i.e. same number of words). The essays were written during the lecture hour at three different lecture occasions. The errors were identified in a systematic manner whereby errors so identified were recorded only once even if they occur severally in students’ essays. The data was collated using percentages in which the identified numbers of occurrences were converted accordingly in percentages. The findings from the study indicate that there are similarities as well as regular and repeated errors which provided a pattern. Based on the pattern identified, the conclusion is that students’ collocation errors are attributable to poor teaching and learning which resulted in wrong generalization of rules.

Keywords: Collocations, errors, collocation errors, second language learning.

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Authors: Yusri Yusof, Stephen Newman, Aydin Nassehi, Keith Case

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The changing economic climate has made global manufacturing a growing reality over the last decade, forcing companies from east and west and all over the world to collaborate beyond geographic boundaries in the design, manufacture and assemble of products. The ISO10303 and ISO14649 Standards (STEP and STEP-NC) have been developed to introduce interoperability into manufacturing enterprises so as to meet the challenge of responding to production on demand. This paper describes and illustrates a STEP compliant CAD/CAPP/CAM System for the manufacture of rotational parts on CNC turning centers. The information models to support the proposed system together with the data models defined in the ISO14649 standard used to create the NC programs are also described. A structured view of a STEP compliant CAD/CAPP/CAM system framework supporting the next generation of intelligent CNC controllers for turn/mill component manufacture is provided. Finally a proposed computational environment for a STEP-NC compliant system for turning operations (SCSTO) is described. SCSTO is the experimental part of the research supported by the specification of information models and constructed using a structured methodology and object-oriented methods. SCSTO was developed to generate a Part 21 file based on machining features to support the interactive generation of process plans utilizing feature extraction. A case study component has been developed to prove the concept for using the milling and turning parts of ISO14649 to provide a turn-mill CAD/CAPP/CAM environment.

Keywords:

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Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi

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This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Keywords: Decision Support System, Neural Network, Flood Level

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Authors: Ali Sarosh, Dong Yun-Feng, Muhammad Umer

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Fully reusable spaceplanes do not exist as yet. This implies that design-qualification for optimized highly-integrated forebody-inlet configuration of booster-stage vehicle cannot be based on archival data of other spaceplanes. Therefore, this paper proposes a novel TIPSO-SVM expert system methodology. A non-trivial problem related to optimization and classification of hypersonic forebody-inlet configuration in conjunction with mass-model of the two-stage-to-orbit (TSTO) vehicle is solved. The hybrid-heuristic machine learning methodology is based on two-step improved particle swarm optimizer (TIPSO) algorithm and two-step support vector machine (SVM) data classification method. The efficacy of method is tested by first evolving an optimal configuration for hypersonic compression system using TIPSO algorithm; thereafter, classifying the results using two-step SVM method. In the first step extensive but non-classified mass-model training data for multiple optimized configurations is segregated and pre-classified for learning of SVM algorithm. In second step the TIPSO optimized mass-model data is classified using the SVM classification. Results showed remarkable improvement in configuration and mass-model along with sizing parameters.

Keywords: TIPSO-SVM expert system, TIPSO algorithm, two-step SVM method, aerothermodynamics, mass-modeling, TSTO vehicle.

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Authors: Sri Ranjini Mei Hua, Vivian Hsueh-hua Chen

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The African Diaspora in Singapore (and larger Asia) is a topic that has received little scholarly attention and research. This exploratory study will analyze the changing identity of Africans throughout the process of cultural adaptation in Singapore. For the focus of this study, “black Africans" will be defined as any black Africans from sub-Saharan Africa who have lived in Singapore for at least six months. The dialectic relationship between Singaporean conceptions of black African identity and African self-consciousness will be analyzed from the perspective of black Africans so as to evaluate the impact of intercultural discourse on the evolution of the African identity in Singapore.

Keywords: African, Diaspora, identity negotiation, interculturalcommunication

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Authors: S.I Sulaiman, T.K Abdul Rahman, I. Musirin, S. Shaari

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This paper presents performance analysis of the Evolutionary Programming-Artificial Neural Network (EPANN) based technique to optimize the architecture and training parameters of a one-hidden layer feedforward ANN model for the prediction of energy output from a grid connected photovoltaic system. The ANN utilizes solar radiation and ambient temperature as its inputs while the output is the total watt-hour energy produced from the grid-connected PV system. EP is used to optimize the regression performance of the ANN model by determining the optimum values for the number of nodes in the hidden layer as well as the optimal momentum rate and learning rate for the training. The EPANN model is tested using two types of transfer function for the hidden layer, namely the tangent sigmoid and logarithmic sigmoid. The best transfer function, neural topology and learning parameters were selected based on the highest regression performance obtained during the ANN training and testing process. It is observed that the best transfer function configuration for the prediction model is [logarithmic sigmoid, purely linear].

Keywords: Artificial neural network (ANN), Correlation coefficient (R), Evolutionary programming-ANN (EPANN), Photovoltaic (PV), logarithmic sigmoid and tangent sigmoid.

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Authors: Shaza Melies, Abeer Refky, Nihad Mansoor

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Multimodality involves the communication between verbal and visual components in various discourses. A painting represents a form of communication between the artist and the viewer in terms of colors, shades, objects, and the title. This paper aims to present how multimodality can be used to decode the verbal and visual dimensions a painting holds. For that purpose, this study uses Kress and van Leeuwen’s theoretical framework of visual grammar for the analysis of the multimodal semiotic resources of selected paintings of Salvador Dali. This study investigates the visual decoding of the selected paintings of Salvador Dali and analyzing their social and political meanings using Kress and van Leeuwen’s framework of visual grammar. The paper attempts to answer the following questions: 1. How far can multimodality decode the verbal and non-verbal meanings of surrealistic art? 2. How can Kress and van Leeuwen’s theoretical framework of visual grammar be applied to analyze Dali’s paintings? 3. To what extent is Kress and van Leeuwen’s theoretical framework of visual grammar apt to deliver political and social messages of Dali? The paper reached the following findings: the framework’s descriptive tools (representational, interactive, and compositional meanings) can be used to analyze the paintings’ title and their visual elements. Social and political messages were delivered by appropriate usage of color, gesture, vectors, modality, and the way social actors were represented.

Keywords: Multimodality, multimodal analysis, paintings analysis, Salvador Dali, visual grammar.

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Authors: Jutharat Sunprasert, Ekapong Hirunsirisawat, Narongrit Waraporn, Somporn Peansukmanee

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Metal Ship and Robotic Car is one of the hands-on activities in the course, the Fundamental of Engineering that can be divided into three parts. The first part, the metal ships, was made by using engineering drawings, physics and mathematics knowledge. The second part is where the students learned how to construct a robotic car and control it using computer programming. In the last part, the students had to combine the workings of these two objects in the final testing. This aim of study was to investigate the effectiveness of hands-on activity by integrating Science, Technology, Engineering and Mathematics (STEM) concepts to develop scientific and engineering skills. The results showed that the majority of students felt this hands-on activity lead to an increased confidence level in the integration of STEM. Moreover, 48% of all students engaged well with the STEM concepts. Students could obtain the knowledge of STEM through hands-on activities with the topics science and mathematics, engineering drawing, engineering workshop and computer programming; most students agree and strongly agree with this learning process. This indicated that the hands-on activity: “Metal Ship and Robotic Car” is a useful tool to integrate each aspect of STEM. Furthermore, hands-on activities positively influence a student’s interest which leads to increased learning achievement and also in developing scientific and engineering skills.

Keywords: Hands-on activity, STEM education, computer programming, metal work.

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Authors: Bohuslava Juhasova, Martin Juhas, Renata Masarova, Zuzana Sutova

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The article deals with the tool in Matlab GUI form that is designed to analyse a mechatronic system sensitivity and tolerance. In the analysed mechatronic system, a torque is transferred from the drive to the load through a coupling containing flexible elements. Different methods of control system design are used. The classic form of the feedback control is proposed using Naslin method, modulus optimum criterion and inverse dynamics method. The cascade form of the control is proposed based on combination of modulus optimum criterion and symmetric optimum criterion. The sensitivity is analysed on the basis of absolute and relative sensitivity of system function to the change of chosen parameter value of the mechatronic system, as well as the control subsystem. The tolerance is analysed in the form of determining the range of allowed relative changes of selected system parameters in the field of system stability. The tool allows to analyse an influence of torsion stiffness, torsion damping, inertia moments of the motor and the load and controller(s) parameters. The sensitivity and tolerance are monitored in terms of the impact of parameter change on the response in the form of system step response and system frequency-response logarithmic characteristics. The Symbolic Math Toolbox for expression of the final shape of analysed system functions was used. The sensitivity and tolerance are graphically represented as 2D graph of sensitivity or tolerance of the system function and 3D/2D static/interactive graph of step/frequency response.

Keywords: Mechatronic systems, Matlab GUI, sensitivity, tolerance.

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: Situation-awareness, Smart home, IoT, Machine learning, Classifier.

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Authors: Han Guan Chew, Keith Yong Ngee Ng, Shan-Wei Fan

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In Singapore, talent retention is one of the most persistent and real issue companies have to grapple with due to the tight labour market. Being resource-scarce, Singapore depends solely on its talented pool of high quality human resource to sustain its competitive advantage in the global economy. But the complex and multifaceted nature of turnover phenomenon makes the prescription of effective talent retention strategies in such a competitive labour market very challenging, especially when it comes to monetary incentives, companies struggle to answer the question of “How much is enough?” By examining the interactive effects of perceived alternative employment opportunities, annual salary and satisfaction with compensation on the turnover intention of 102 Singapore Professionals, Managers, Executives and Technicians (PMET) through correlation analyses and multiple regressions, important insights into the psyche of the Singapore talent pool can be drawn. It is found that annual salary influence turnover intention indirectly through mediation and moderation effects on PMET’s satisfaction on compensation. PMET are also found to be heavily swayed by better external opportunities. This implies that talent retention strategies should not adopt a purely monetary based blanket approach but rather a comprehensive and holistic one that considers the dynamics of prevailing market conditions.

Keywords: Employee Turnover, High Performers, Knowledge Workers, Perceived Alternative Employment Opportunities Salary, Satisfaction on Compensation, Singapore PMET, Talent Retention.

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Authors: Ryuji Yamazaki, Masahiro Kochi, Weiran Zhu, Hiroko Kase

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In care for older adults, behavioral and psychological symptoms of dementia (BPSD) like agitation and aggression are distressing for patients and their caretakers, often resulting in premature institutionalization with increased costs of care. To improve mood and mitigate symptoms, as a non-pharmaceutical approach, emotion-oriented therapy like reminiscence work is adopted in face-to-face communication. Telecommunication support is expected to be provided by robotic media as a bridge for digital divide for those with dementia and facilitate social interaction both verbally and nonverbally. The purpose of this case study is to explore the conditions in which robotic media can effectively attract attention from older adults with dementia and promote their well-being. As a pilot study, we introduced the pillow-phone Hugvie^®, a huggable humanly shaped communication medium to five residents with dementia at a care facility, to investigate how the following conditions work for the elderly when they use the medium; 1) no sound, 2) radio, non-interactive, 3) daily conversation, and 4) reminiscence work. As a result, under condition 4, reminiscence work, the five participants kept concentration in interacting with the medium for a longer duration than other conditions. In condition 4, they also showed larger amount of utterances than under other conditions. These results indicate that providing topics related to personal histories through robotic media could affect communication positively and should, therefore, be further investigated. In addition, the issue of ethical implications by using persuasive technology that affects emotions and behaviors of older adults is also discussed.

Keywords: BPSD, reminiscence, tactile telecommunication, utterances.

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Authors: Alper Akın, İbrahim Aydoğdu

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This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the displacement limitations, the inter-story drift and the other structural constraints are derived from LRFD-AISC specification. In this study, a hybrid algorithm by using teachinglearning based optimization (TLBO) and harmony search (HS) algorithms is employed to solve the stated optimum design problem. These algorithms are two of the recent additions to metaheuristic techniques of numerical optimization and have been an efficient tool for solving discrete programming problems. Using these two algorithms in collaboration creates a more powerful tool and mitigates each other’s weaknesses. To demonstrate the powerful performance of presented hybrid algorithm, the optimum design of a large scale steel building is presented and the results are compared to the previously obtained results available in the literature.

Keywords: Optimum structural design, hybrid techniques, teaching-learning based optimization, harmony search algorithm, minimum weight, steel space frame.

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Authors: Chong-Yang Qiao

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Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.

Keywords: Mobile augmented reality, remote collaboration, user experience, cognitive model.

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Authors: Maryam Vafadar, Alireza Behrad, Saeed Akbari

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Nowadays, with the emerging of the new applications like robot control in image processing, artificial vision for visual servoing is a rapidly growing discipline and Human-machine interaction plays a significant role for controlling the robot. This paper presents a new algorithm based on spatio-temporal volumes for visual servoing aims to control robots. In this algorithm, after applying necessary pre-processing on video frames, a spatio-temporal volume is constructed for each gesture and feature vector is extracted. These volumes are then analyzed for matching in two consecutive stages. For hand gesture recognition and classification we tested different classifiers including k-Nearest neighbor, learning vector quantization and back propagation neural networks. We tested the proposed algorithm with the collected data set and results showed the correct gesture recognition rate of 99.58 percent. We also tested the algorithm with noisy images and algorithm showed the correct recognition rate of 97.92 percent in noisy images.

Keywords: Back propagation neural network, Feature vector, Hand gesture recognition, k-Nearest Neighbor, Learning vector quantization neural network, Robot control, Spatio-temporal volume, Visual servoing

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Authors: Farideh Alizadeh, Mohd Nasir Hashim

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Present research investigates eclecticism in Iranian theatre on the basis of eclectic theory. Eclectic theatre is a new theory in postmodernism. The theory appeared during 60th – 70th century in some theatres such as “Conference of the Birds”. Special theatrical forms have been developed in many geographical- cultural areas of the world and are indigenous to that area. These forms, as compared with original forms, are considered to be traditional while being comprehensive, the form is considered to be national. Kaboudan and Sfandiar theatre has been influenced by elements of traditional form of Iran.

Keywords: Eclectic theatre, theatrical forms, tradition, play.

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: Breast cancer, health diagnosis, Machine Learning, biomarker classification, Neural Network.

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD, as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches, such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: Autism spectrum disorder, clustering, optimization, unsupervised machine learning.

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Authors: Chris Fersterer, Col Fay, Tobias Danielmeier, Kat Achterberg, Scott Willis

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New Zealand, an island nation, has an extensive coastline peppered with small communities of iconic buildings known as Bachs. Post WWII, these modest buildings were constructed by their owners as retreats and generally were small, low cost, often using recycled material and often they fell below current acceptable building standards. In the latter part of the 20^th century, real estate prices in many of these communities remained low and these areas became permanent residences for people attracted to this affordable lifestyle choice. The Blueskin Resilient Communities Trust (BRCT) is an organisation that recognises the vulnerability of communities in low lying settlements as now being prone to increased flood threat brought about by climate change and sea level rise. Some of the inhabitants of Blueskin Bay, Otago, NZ have already found their properties to be un-insurable because of increased frequency of flood events and property values have slumped accordingly. Territorial authorities also acknowledge this increased risk and have created additional compliance measures for new buildings that are less than 2 m above tidal peaks. Community resilience becomes an additional concern where inhabitants are attracted to a lifestyle associated with a specific location and its people when this lifestyle is unable to be met in a suburban or city context. Traditional models of social housing fail to provide the sense of community connectedness and identity enjoyed by the current residents of Blueskin Bay. BRCT have partnered with the Otago Polytechnic Design School to design a new form of community housing that can react to this environmental change. It is a longitudinal project incorporating participatory approaches as a means of getting people ‘on board’, to understand complex systems and co-develop solutions. In the first period, they are seeking industry support and funding to develop a transportable and fully self-contained housing model that exploits current technologies. BRCT also hope that the building will become an educational tool to highlight climate change issues facing us today. This paper uses the Climate Safe House (CSH) as a case study for education in architectural sustainability through experiential learning offered as part of the Otago Polytechnics Bachelor of Design. Students engage with the project with research methodologies, including site surveys, resident interviews, data sourced from government agencies and physical modelling. The process involves collaboration across design disciplines including product and interior design but also includes connections with industry, both within the education institution and stakeholder industries introduced through BRCT. This project offers a rich learning environment where students become engaged through project based learning within a community of practice, including architecture, construction, energy and other related fields. The design outcomes are expressed in a series of public exhibitions and forums where community input is sought in a truly participatory process.

Keywords: Community resilience, problem based learning, project based learning, case study.

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and electrocardiogram (ECG)-based systems are unquestionably the best choice due to their appealing inherent characteristics. The Convolutional Neural Networks (CNNs) are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the caliber of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest False Acceptance Rate (FAR)  of 0.04% and the highest False Rejection Rate (FRR)  of 5%, the best performing network achieved an identification accuracy of 99.94%. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable, but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, dense networks, identification rate, train/test split ratio.

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Authors: Samedin Mehmeti

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The rationale behind this study is considering combating and preventing the phenomenon of trafficking in human beings from a multidisciplinary perspective that involves many layers of the society. Trafficking in human beings is an abhorrent phenomenon highly affecting negatively the victims and their families in both human and material aspect, sometimes causing irreversible damages. The longer term effects of this phenomenon, in countries with a weak economic development and extremely young and dynamic population, such as Kosovo, without proper measures to prevented and control can cause tremendous damages in the society. Given the fact that a complete eradication of this phenomenon is almost impossible, efforts should be concentrated at least on the prevention and controlling aspects. Treating trafficking in human beings based on traditional police tactics, methods and proceedings cannot bring satisfactory results. There is no doubt that a multi-disciplinary approach is an irreplaceable requirement, in other words, a combination of authentic and functional proactive and reactive methods, techniques and tactics. Obviously, police must exercise its role in preventing and combating trafficking in human beings, a role sanctioned by the law, however, police role and contribution cannot by any means considered complete if all segments of the society are not included in these efforts. Naturally, civil society should have an important share in these collaborative and interactive efforts especially in preventive activities such as: awareness on trafficking risks and damages, proactive engagement in drafting appropriate legislation and strategies, law enforcement monitoring and direct or indirect involvement in protective and supporting activities which benefit the victims of trafficking etc.

Keywords: Civil society, cooperation, police, trafficking in human beings.

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Authors: George E. Tsekouras, Evi Sampanikou

Abstract:

We compare three categorical data clustering algorithms with respect to the problem of classifying cultural data related to the aesthetic judgment of comics artists. Such a classification is very important in Comics Art theory since the determination of any classes of similarities in such kind of data will provide to art-historians very fruitful information of Comics Art-s evolution. To establish this, we use a categorical data set and we study it by employing three categorical data clustering algorithms. The performances of these algorithms are compared each other, while interpretations of the clustering results are also given.

Keywords: Aesthetic judgment, comics artists, cluster analysis, categorical data.

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Authors: Gamze Fahriye Pehlivan, Tulay Canitez

Abstract:

The traditional Turkish houses becoming unusable are a result of the deterioration of the balanced interaction between users and house (human and house) continuing during the history. Especially depending upon the change in social structure, the houses becoming neglected do not meet the desires of the users and do not have the meaning but the shelter are becoming unusable and are being destroyed. A conservation policy should be developed and renovations should be made in order to pass the traditional houses carrying the quality of a cultural and historical document presenting the social structure, the lifestyle and the traditions of its own age to the next generations and to keep them alive.

Keywords: House, social structural change, social structural, traditional Turkish houses.

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Authors: Aaron A. R. Nwabude

Abstract:

The research investigates the “impact of VLE on mathematical concepts acquisition of the special education needs (SENs) students at KS4 secondary education sector" in England. The overall aim of the study is to establish possible areas of difficulties to approach for above or below knowledge standard requirements for KS4 students in the acquisition and validation of basic mathematical concepts. A teaching period, in which virtual learning environment (Fronter) was used to emphasise different mathematical perception and symbolic representation was carried out and task based survey conducted to 20 special education needs students [14 actually took part]. The result shows that students were able to process information and consider images, objects and numbers within the VLE at early stages of acquisition process. They were also able to carry out perceptual tasks but with limiting process of different quotient, thus they need teacher-s guidance to connect them to symbolic representations and sometimes coach them through. The pilot study further indicates that VLE curriculum approaches for students were minutely aligned with mathematics teaching which does not emphasise the integration of VLE into the existing curriculum and current teaching practice. There was also poor alignment of vision regarding the use of VLE in realisation of the objectives of teaching mathematics by the management. On the part of teacher training, not much was done to develop teacher-s skills in the technical and pedagogical aspects of VLE that is in-use at the school. The classroom observation confirmed teaching practice will find a reliance on VLE as an enhancer of mathematical skills, providing interaction and personalisation of learning to SEN students.

Keywords: VLE, Mathematical Concepts Acquisition, PilotStudy, SENs, KS4, Education, Teacher

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Authors: Anupama Pande, Vishik Goel

Abstract:

A complex valued neural network is a neural network, which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in image and vision processing. In Neural networks, radial basis functions are often used for interpolation in multidimensional space. A Radial Basis function is a function, which has built into it a distance criterion with respect to a centre. Radial basis functions have often been applied in the area of neural networks where they may be used as a replacement for the sigmoid hidden layer transfer characteristic in multi-layer perceptron. This paper aims to present exhaustive results of using RBF units in a complex-valued neural network model that uses the back-propagation algorithm (called 'Complex-BP') for learning. Our experiments results demonstrate the effectiveness of a Radial basis function in a complex valued neural network in image recognition over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error on a neural network model with RBF units. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Radial BasisFunction, Image recognition.

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Authors: Aimen Mohamed Almaloul

Abstract:

The main focus of this study is investigating the interference of Arabic in the use of English prepositions by Libyan university students. Prepositions in the tests used in the study were categorized, according to their relation to Arabic, into similar Arabic and English prepositions (SAEP), dissimilar Arabic and English prepositions (DAEP), Arabic prepositions with no English counterparts (APEC), and English prepositions with no Arabic counterparts (EPAC).

The subjects of the study were the first year university students of the English department, Sabrata Faculty of Arts, Azzawia University; both males and females, and they were 100 students. The basic tool for data collection was a test of English prepositions; students are instructed to fill in the blanks with the correct prepositions and to put a zero (0) if no preposition was needed. The test was then handed to the subjects of the study.

The test was then scored and quantitative as well as qualitative results were obtained. Quantitative results indicated the number, percentages and rank order of errors in each of the categories and qualitative results indicated the nature and significance of those errors and their possible sources. Based on the obtained results the researcher could detect that students made more errors in the EPAC category than the other three categories and these errors could be attributed to the lack of knowledge of the different meanings of English prepositions. This lack of knowledge forced the students to adopt what is called the strategy of transfer.

Keywords: Foreign language acquisition, foreign language learning, interference system, interlanguage system, mother tongue interference.

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