Search results for: regional features

Authors: Tasawar Ashraf

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The paper argues that the European Union’s securitized recourse to migration management which is lacking on the principle of solidarity has enhanced the sufferings of the asylum seekers by influencing the asylum policies of the non-EU states in the Eastern Mediterranean. The research critically analyses the development of the Turkish Asylum Policy and advocates that due to extraordinary burden of refugees and conceivable chances of getting EU membership, Turkey is developing its asylum policy essentially on the footprints of the EU. Such political and economic domination of the EU are resulting in the development of broader securitized migration zone in the EU and MENA region. Therefore, this paper critically analyses two interconnected issues, i.e., securitization of the migration in the EU and MENA region and the deficiency of the principle of solidarity and burden sharing in the European Agenda on Migration and how it reflects on Turkish asylum policy. This paper suggests that the EU must adopt a more generous resettle scheme ensuring the division of the refugee burden on all member and regional states by considering different political, social, and economic factors. Only such corporation can increase the pool of refugee hosting states by collaborating with the regional states to develop their asylum systems in accordance with international law.

Keywords: European Agenda on Migration (EAM), EU, Middle East and North Africa (MENA), Treaty on the Functioning of the European Union (TFEU)

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Authors: Ebrahim Rahmani, Siyamak Moazeni

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According to the Iraq's first constitutional law (approved 2005), Iraq is an independent with sovereignty and its governmental structure is parliamentary democratic republic and federal. Even in reforms in 2009, this article of law did not changed at all. But considering the existence of this emphasis and clarity which is mentioned in the law, different and sometimes contradictory interpretations and positions are expressed about federalism in the way that we can say, considering the importance of the matter, federalism is a focus point to create and expansion of the cold war among leaders of different groups of the country. Iraq's today political and security position has granted the suitable opportunity to Iraq's Kurdistan in appearing of the recent security crisis to increase its share from the central political power or to achieve to its independent dream. The federalism the weakest point of Iraq's territorial integrity in a way that if different groups do not come to a consensus about it and do not think about a mechanism which is accepted by all of them, this can effect on and Iraq's political stability and security. Iraq's Kurdistan follows the option of disintegration and separation under the shadow of political and security changes, even with existence of some Iraqi groups' hopes regarding the improvement of situation after parliament election and also considering Masoud Barezani's power will for separation from Iraq as well as regarding special international changes and disintegration of Karime from Ukraine and ISIS crises; concerns have been created among regional and international powers and interior players. In this article, a paradox due constitutional law about federalism, Iraq's central government view and its politicians to the matter and the regional effect of this action on region's geopolitics are reviewed as well.

Keywords: constitutional law, federalism, decomposition, Iraq's Kurdistan

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: Vilem Paril, Dominika Tothova

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This paper discusses the value theory in cultural heritage and the value theory in environmental economics. Two economic views of the value theory are compared within the field of cultural heritage maintenance and within the field of the environment. The main aims are to find common features in these two differently structured theories under the layer of differently defined terms as well as really differing features of these two approaches, to clear the confusion which stems from different terminology as in fact these terms capture the same aspects of reality and to show possible inspiration these two perspectives can offer one another. Another aim is to present these two value systems in one value framework. First, important moments of the value theory from the economic perspective are presented, leading to the marginal revolution of (not only) the Austrian School. Then the theory of value within cultural heritage and environmental economics are explored. Finally, individual approaches are compared and their potential mutual inspiration searched for.

Keywords: cultural heritage, environmental economics, existence value, value theory

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Authors: Seung-Seok Bak, Chang-Mu Jung

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An enough amount supply of industrial complexes is an important national policy in South Korea, which is highly dependent on foreign trade. A development process of the industrial complex can distinguish between the planning stage and the construction stage. The planning stage consists of the process of consulting with many stakeholders on the contents of the development of industrial complex, feasibility study, compliance with the Regional policies, and so on. The industrial complex planning stage, including licensing procedure, usually takes about three years in South Korea. The government determined that the appropriate supply of industrial complexes have been delayed, due to the long licensing period and drafted a law to shorten the license period in 2008. The law was expected to shorten the period of licensing, which was about three years, to six months. This paper attempts to show that the shortening of the licensing period does not positively affect the appropriate supply of industrial complexes. To do this, we used Interrupted Time Series Designs. As a result, it was found that the supply of industrial complexes was influenced more by other factors such as actual industrial complex demand of private sector and macro-level economic variables. In addition, the specific provisions of the law conflict with local policy and cause some problems such as damage to nature and agricultural land, traffic congestion.

Keywords: development of industrial complexes, industrial complexes, interrupted time series designs, simplification of licensing procedures for industrial complexes, time series regression

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Authors: M. Leonora D. Guerrero

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The study attempted to uncover the most and least frequent phonological variation evident in the speech patterns of grade 1 teachers in select public elementary schools in the Philippines. It also determined the lectal description of the participants based on Tayao’s consonant charts for American and Philippine English. Descriptive method was utilized. A total of 24 grade 1 teachers participated in the study. The instrument used was word list. Each column in the word list is represented by words with the target consonant phonemes: labiodental fricatives f/ and /v/ and lingua-alveolar fricative /z/. These phonemes were in the initial, medial, and final positions, respectively. Findings of the study revealed that the most frequent variation happened when the participants read words with /z/ in the final position while the least frequent variation happened when the participants read words with /z/ in the initial position. The study likewise proved that the grade 1 teachers exhibited the segmental features of both the mesolect and basilect. Based on these results, it is suggested that teachers of English in the Philippines must aspire to manifest the features of the mesolect, if not, the acrolect since it is expected of the academicians not to be displaying the phonological features of the acrolects since this variety is only used by the 'uneducated.' This is especially so with grade 1 teachers who are often mimicked by their students who classify their speech as the 'standard.'

Keywords: consonant phonemes, lectal description, Philippine English, phonological variation

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Authors: Weikang Peng

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The innovation corridor is an important spatial carrier to promote regional collaborative innovation, and its development process is the spatial re-organization process of regional innovation resources. This paper takes the Nanjing-Zhenjiang G312 Industrial Innovation Corridor, which involves seven municipal districts in Jiangsu Province, as empirical evidence. Based on multi-source spatial big data in 2010, 2016, and 2022, this paper applies triangulated irregular network (TIN), head/tail breaks, regional innovation ecosystem (RIE) niche fitness evaluation model, and social network analysis to carry out empirical research on the spatial organization and functional structural evolution characteristics of innovation corridors and their correlation with the structural evolution of collaborative innovation network. The results show, first, the development of innovation patches in the corridor has fractal characteristics in time and space and tends to be multi-center and cluster layout along the Nanjing Bypass Highway and National Highway G312. Second, there are large differences in the spatial distribution pattern of niche fitness in the corridor in various dimensions, and the niche fitness of innovation patches along the highway has increased significantly. Third, the scale of the collaborative innovation network in the corridor is expanding fast. The core of the network is shifting from the main urban area to the periphery of the city along the highway, with small-world and hierarchical levels, and the core-edge network structure is highlighted. With the development of the Innovation Corridor, the main collaborative mode in the corridor is changing from collaboration within innovation patches to collaboration between innovation patches, and innovation patches with high ecological suitability tend to be the active areas of collaborative innovation. Overall, polycentric spatial layout, graded functional structure, diversified innovation clusters, and differentiated environmental support play an important role in effectively constructing collaborative innovation linkages and the stable expansion of the scale of collaborative innovation within the innovation corridor.

Keywords: innovation corridor development, spatial structure, niche fitness evaluation model, head/tail breaks, innovation network

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Authors: S. S. Salehi, A. Shamloo

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Poor ability of cartilage tissue when experiencing a damage leads scientists to use tissue engineering as a reliable and effective method for regenerating or replacing damaged tissues. An artificial tissue should have some features such as biocompatibility, biodegradation and, enough mechanical properties like the original tissue. In this work, a composite hydrogel is prepared by using natural and synthetic materials that has high porosity. Mechanical properties of different combinations of polymers such as modulus of elasticity were tested, and a hydrogel with good mechanical properties was selected. Bone marrow derived mesenchymal stem cells were also seeded into the pores of the sponge, and the results showed the adhesion and proliferation of cells within the hydrogel after one month. In comparison with previous works, this study offers a new and efficient procedure for the fabrication of cartilage like tissue and further cartilage repair.

Keywords: cartilage tissue engineering, hydrogel, mechanical strength, mesenchymal stem cell

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Authors: Tingyu Zhang

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This paper utilizes the Super-SBM model to assess water resources green efficiency (WRGE) among provinces in China and investigate its spatial and temporal features, based on the characteristic framework of “economy-environment-society.” The social network analysis is employed to examine the network pattern and spatial interaction of WRGE. Further, the quadratic assignment procedure method is utilized for examining the influencing factors of the spatial association of WRGE regarding “relationship.” The study reveals that: (1) the spatial distribution of WRGE demonstrates a distribution pattern of Eastern>Western>Central; (2) a remarkable spatial association exists among provinces; however, no strict hierarchical structure is observed. The internal structure of the WRGE network is characterized by the feature of "Eastern strong and Western weak". The block model analysis discovers that the members of the “net spillover” and “two-way spillover” blocks are mostly in the eastern and central provinces; “broker” block, which plays an intermediary role, is mostly in the central provinces; and members of the “net beneficiary” block are mostly in the western region. (3) Differences in economic development, degree of urbanization, water use environment, and water management have significant impacts on the spatial connection of WRGE. This study is dedicated to the realization of regional linkages and synergistic enhancement of WRGE, which provides a meaningful basis for building a harmonious society of human and water coexistence.

Keywords: water resources green efficiency, super-SBM model, social network analysis, quadratic assignment procedure

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Authors: Yilei Yu

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Modernism, emerging in the Western world of the 20th century, attempted to create a universal international style, which pulled the architectural and social systems created by classicism back to an initial pure state. However, out of the introspection of the Modernism, Regionalism attempted to restore a humanistic environment and create flexible buildings during the 1950s. Meanwhile, as the first generation of architects came back, the wind of the Regionalism blew to Taiwan. However, with the increasing of political influence and the tightening of free creative space, from the second half of the 1950s to the 1980s, the "real" Regional Architecture, which should have taken roots in Taiwan, becomes the "fake" Regional Architecture filled with the oriental charm. Through the Comparative Method, which includes description, interpretation, juxtaposition, and comparison, this study analyses the difference of the style of the Modernist Chinese Architecture between the period before the 1980s and the after. The paper aims at exploring the development of Regionalism Architecture in Taiwan, which includes three parts. First, the burgeoning period of the "modernist Chinese architecture" in Taiwan was the beginning of the Chinese Nationalist Party's coming to Taiwan to consolidate political power. The architecture of the "Ming and Qing Dynasty Palace Revival Style" dominated the architectural circles in Taiwan. These superficial "regional buildings" have nearly no combination with the local customs of Taiwan, which is difficult to evoke the social identity. Second, in the late 1970s, the second generation of architects headed by Baode Han began focusing on the research and preservation of traditional Taiwanese architecture, and creating buildings combined the terroirs of Taiwan through the imitation of styles. However, some scholars have expressed regret that very few regionalist architectural works that appeared in the 1980s can respond specifically to regional conditions and forms of construction. Instead, most of them are vocabulary-led representations. Third, during the 1990s, by the end of the period of martial law, community building gradually emerged, which made the object of Taiwan's architectural concern gradually extended to the folk and ethnic groups. In the Yilan area, there are many architects who care about the local environment, such as the Field office Architects. Compared with the hollow regionality of the passionate national spirits that emerged during the martial law period, the local practice of the architect team in Yilan can better link the real local environmental life and reflect the true regionality. In conclusion, with the local practice case of the huge construction team in Yilan area, this paper focuses on the Spatial Practice by the Field office Architects to explore the spatial representation of the space and the practical enlightenment in the process of modernist Chinese architecture development in Taiwan.

Keywords: regionalism, modernism, Chinese architecture, political landscape, spatial representation

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Authors: Kaewmart Pongakkasira

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This study investigated how different levels of pixelation affect face detection in natural scenes. Eye movements and reaction times, while observers searched for faces in natural scenes rendered in different ranges of pixels, were recorded. Detection performance for coarse visual detail at lower pixel size (3 x 3) was better than with very blurred detail carried by higher pixel size (9 x 9). The result is consistent with the notion that face detection relies on gross detail information of face-shape template, containing crude shape structure and features. In contrast, detection was impaired when face shape and features are obscured. However, it was considered that the degradation of scenic information might also contribute to the effect. In the next experiment, a more direct measurement of the effect of pixelation on face detection, only the embedded face photographs, but not the scene background, will be filtered.

Keywords: eye movements, face detection, face-shape information, pixelation

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Authors: Elżbieta Antczak

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Cities offer important opportunities for economic development and for expanding access to basic services, including health care and education, for large numbers of people. Moreover, green areas (as an integral part of sustainable urban development) present a major opportunity for improving urban environments, quality of lives and livelihoods. This paper examines, using spatial concentration and spatial taxonomic measures, regional diversification of greenery in the cities of Poland. The analysis includes location quotients, Lorenz curve, Locational Gini Index, and the synthetic index of greenery and spatial statistics tools: (1) To verify the occurrence of strong concentration or dispersion of the phenomenon in time and space depending on the variable category, and, (2) To study if the level of greenery depends on the spatial autocorrelation. The data includes the greatest Polish cities, categories of the urban greenery (parks, lawns, street greenery, and green areas on housing estates, cemeteries, and forests) and the time span 2004-2015. According to the obtained estimations, most of cites in Poland are already taking measures to become greener. However, in the country there are still many barriers to well-balanced urban greenery development (e.g. uncontrolled urban sprawl, poor management as well as lack of spatial urban planning systems).

Keywords: greenery, urban areas, regional spatial diversification and concentration, spatial taxonomic measure

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Authors: Anikó Kaluzsa

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The article's author aims to introduce and analyze those microbiological safety hazards which indicate the presence of secondary contamination in the water supply system. Since drinking water belongs to primary foods and is the basic condition of life, special attention should be paid on its quality. There are such indicators among the microbiological features can be found in water, which are clear evidence of the presence of water contamination, and based on this there is no need to perform other diagnostics, because they prove properly the contamination of the given water supply section. Laboratory analysis can help - both technologically and temporally – to identify contamination, but it does matter how long takes the removal and if the disinfection process takes place in time. The identification of the factors that often occur in the same places or the chance of their occurrence is greater than the average, facilitates our work. The pathogen microbiological risk assessment by the help of several features determines the most likely occurring microbiological features in the Carpathian basin. From among all the microbiological indicators, that are recommended targets for routine inspection by the World Health Organization, there is a paramount importance of the appearance of Escherichia coli in the water network, as its presence indicates the potential ubietiy of enteric pathogens or other contaminants in the water network. In addition, the author presents the steps of microbiological risk assessment analyzing those pathogenic micro-organisms registered to be the most critical.

Keywords: drinking water, E. coli, microbiological indicators, risk assessment, water safety plan

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Authors: Rafik Djemili, Hocine Bourouba, M. C. Amara Korba

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In this paper, we present a method in order to classify EEG signals for Brain-Computer Interfaces (BCI). EEG signals are first processed by means of spectral estimation methods to derive reliable features before classification step. Spectral estimation methods used are standard periodogram and the periodogram calculated by the Welch method; both methods are compared with Logarithm of Band Power (logBP) features. In the method proposed, we apply Linear Discriminant Analysis (LDA) followed by Support Vector Machine (SVM). Classification accuracy reached could be as high as 85%, which proves the effectiveness of classification of EEG signals based BCI using spectral methods.

Keywords: brain-computer interface, motor imagery, electroencephalogram, linear discriminant analysis, support vector machine

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Authors: Xiao Chen, Xiaoying Kong, Min Xu

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This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.

Keywords: vehicle classification, signal processing, road traffic model, magnetic sensing

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Authors: Etibar Guliyev

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The breakdown of the Soviet Union in 1991 has led to a considerable rise in the religious self-consciousness of Muslim population of the Central Asia. Additionally, huge amount of money spent by various states further facilitated the spread of religious ideas. According to some sources, Saudi Arabia spent 87 billion dollars to propagate Wahhabism abroad during two decades, whereas the Communist Party of the Soviet Union spent just over 7 billion dollars to spread its ideology worldwide between 1921 and 1991. As the result, today once a remote area from international politics has turned into third major source of recruitment of fighters for global terrorist organizations. In order to illustrate to scope of the involvement of the Central Asian residents in international terrorist networks it is enough to mention the name of Colonel Gulmorod Khalimov, the former head of the Tajik special police forces who served as ISIS war minister between 2016 and 2017. The importance of the topic stems from the fact that the above-mentioned republics with a territory of 4 million square km and the population of around 80 million people borders Russia, Iran Afghanistan and China. Moreover, the fact that political and military activities motivated with religious feelings in those countries have implications not only for domestic but also for regional and global political relations and all of them has root in politics of religions adds value to the research. This research aims to provide an in-depth analyses of the marked features of the state policies to regulate religious activities and approach this question both from individual, domestic, regional and global levels of analyses. The research will enable us to better understand what implications have the state of religious freedom in post-Soviet Muslim republics for international relations and the rise of global jihadi terrorism. The paper tries to find a linkage between the mentioned terror attacks and underground rise of religious extremism in Central Asia. This research is based on multiple research methods, mainly on qualitative one. The process tracing method is also employed to review religious policies implemented from 1918-1991 and after the collapse of the Soviet Union in a chronological way. In terms of the quantitative method, it chiefly will be used in a bid to process various statistics disseminated in academic and official sources. The research mostly explored constructivist, securitization and social movement theories. Findings of the research suggests that the endemic problems peculiar to authoritarian regimes of Central Asia such as crackdown on the expression of religious believe and any kind of opposition, economic decline, instrumental use of religion and corruption and tribalism further accelerated the recruitment problem. Paper also concludes that the Central Asian states in some cases misused counter-terrorism campaign as a pretext to further restrict freedom of faith in their respective countries.

Keywords: identity, political Islam, religious extremism, security, terrorism

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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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: Argyro Maria Skourmalla

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Internationalization and management of linguistic diversity in Higher Education (HE) have gained much attention in research in the last few years. Internationalization policies in HE aims at promoting the dual role of Higher Education Institutions (HEIs), civilization and competitiveness. In the context of the European Union, the European Education Area initiative aims at “inclusive national education and training systems” through networking and exchange between HEIs. However, the use of English as a ‘lingua academica’ in the place of the official, national, and regional/minority languages raises questions regarding linguistic diversity, linguistic rights and concerns that have to do with the scientific weakening of these languages. In fact, the European Civil Society Platform for Multilingualism, in the Declaration for Multilingualism in Higher Education, draws attention to the use of English at the expense of other regional/national languages and the impact of English-only language policy on an epistemological level. The above issues were brought up during semi-structured interviews with lecturing staff coming from three multilingual Universities in Europe. Lecturers shared their experiences and the practices they use to manage linguistic diversity in these three Universities. Findings show that even though different languages are used in teaching across disciplines, English -or ‘Globish’ as mentioned during an interview- is widely used in research. Despite English being accepted as the “lingua academica,” issues regarding loss of identity come up

Keywords: higher education, internationalization, linguistic diversity, teaching, research, English

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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: Joel F. Campbell, Bing Lin, Michael Obland, Susan Kooi, Tai-Fang Fan, Byron Meadows, Edward Browell, Wayne Erxleben, Doug McGregor, Jeremy Dobler, Sandip Pal, Christopher O'Dell, Ken Davis

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The Active Sensing of CO₂ Emissions over Nights, Days, and Seasons (ASCENDS) CarbonHawk Experiment Simulator (ACES) is a NASA Langley Research Center instrument funded by NASA’s Science Mission Directorate that seeks to advance technologies critical to measuring atmospheric column carbon dioxide (CO₂ ) mixing ratios in support of the NASA ASCENDS mission. The ACES instrument, an Intensity-Modulated Continuous-Wave (IM-CW) lidar, was designed for high-altitude aircraft operations and can be directly applied to space instrumentation to meet the ASCENDS mission requirements. The ACES design demonstrates advanced technologies critical for developing an airborne simulator and spaceborne instrument with lower platform consumption of size, mass, and power, and with improved performance. The Atmospheric Carbon and Transport – America (ACT-America) is an Earth Venture Suborbital -2 (EVS-2) mission sponsored by the Earth Science Division of NASA’s Science Mission Directorate. A major objective is to enhance knowledge of the sources/sinks and transport of atmospheric CO₂ through the application of remote and in situ airborne measurements of CO₂ and other atmospheric properties on spatial and temporal scales. ACT-America consists of five campaigns to measure regional carbon and evaluate transport under various meteorological conditions in three regional areas of the Continental United States. Regional CO₂ distributions of the lower atmosphere were observed from the C-130 aircraft by the Harris Corp. Multi-Frequency Fiber Laser Lidar (MFLL) and the ACES lidar. The airborne lidars provide unique data that complement the more traditional in situ sensors. This presentation shows the applications of CO₂ lidars in support of these science needs.

Keywords: CO₂ measurement, IMCW, CW lidar, laser spectroscopy

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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: 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

Abstract:

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

Abstract:

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

Procedia PDF Downloads 228

Authors: Yazid Abdullahi Abubakar, Jay Mitra

Abstract:

This paper is concerned with entrepreneurial high-impact firms, which are firms that generate ‘both’ disproportionate levels of employment and sales growth, and have high levels of innovative activity. It investigates differences in factors influencing high-impact growth between indigenous and foreign firms. The study is based on an analysis of data from United Kingdom (UK) Innovation Scoreboard on 865 firms, which were divided into high-impact firms (those achieving positive growth in both sales and employment) and low-impact firms (negative or no growth in sales or employment); in order to identifying the critical differences in regional, sectorial and size related factors that facilitate knowledge spillovers and high-impact growth between indigenous and foreign firms. The findings suggest that: 1) Firms’ access to regional knowledge spillovers (from businesses and higher education institutions) is more significantly associated with high-impact growth of UK firms in comparison to foreign firms, 2) Because high-tech sectors have greater use of knowledge spillovers (compared to low-tech sectors), high-tech sectors are more associated with high-impact growth, but the relationship is stronger for UK firms compared to foreign firms, 3) Because small firms have greater need for knowledge spillovers (relative to large firms), there is a negative relationship between firm size and high-impact growth, but the negative relationship is greater for UK firms in comparison to foreign firms.

Keywords: entrepreneurship, high-growth, indigenous firms, foreign firms, small firms, large firms

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Authors: P. V. Pramila , V. Mahesh

Abstract:

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

Procedia PDF Downloads 310