Search results for: international classification of functioning

Authors: A. V. Popa, C. Barna, V. Mihalache

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Being the largest port at the Black Sea and functioning as a civil and military nodal point between Europe and Asia, Constantza Port has become a potential target on the terrorist international agenda. The authors use qualitative research based on both face-to-face and online semi-structured interviews with relevant stakeholders (top decision-makers in the Romanian Naval Authority, Romanian Maritime Training Centre, National Company "Maritime Ports Administration" and military staff) in order to detect potential vulnerabilities which might be exploited by terrorists in the case of Constantza Port. Likewise, this will enable bringing together the experts’ opinions on potential mitigation measures. Subsequently, this paper formulates various counter-terrorism policies to enhance the robustness of Constantza Port under potential terror attacks and connects them with the attributions in the field of critical infrastructure protection conferred by the law to the lead national authority for preventing and countering terrorism, namely the Romanian Intelligence Service. Extending the national counterterrorism efforts to an international level, the authors propose the establishment – among the experts of the NATO member states of the Wider Black Sea Region – of a platform for the exchange of know-how and best practices in the field of critical infrastructure protection.

Keywords: Constantza Port, counter-terrorism policies, critical infrastructure protection, security, Wider Black Sea Region

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Authors: Khitem Amiri, Mohamed Farah

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Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

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Authors: I. A. Farhat, M. Bin Hasan

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A developed approach for the protection of power transmission lines using Support Vector Machines (SVM) technique is presented. In this paper, the SVM technique is utilized for the classification and isolation of faults in power transmission lines. Accurate fault classification and location results are obtained for all possible types of short circuit faults. As in distance protection, the approach utilizes the voltage and current post-fault samples as inputs. The main advantage of the method introduced here is that the method could easily be extended to any power transmission line.

Keywords: fault detection, classification, diagnosis, power transmission line protection, support vector machines (SVM)

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Authors: Ermal Xhelilaj

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International practice has revealed that many maritime conflicts have been initiated as a direct result of coastal states’ disagreements over maritime boundaries and other related maritime issues. These disagreements embrace relevant problematic matters reflecting international conflicts, which in order to prevent further escalation into international crises or even armed conflicts have to be legally resolved. The most challenging cases in international system involve regional or bilateral disputes regarding maritime boundaries delimitations between states, which may result in the activation of respective armed forces, considered crucial elements for the protection of territorial sovereignty. Taken under considerations the legal issues that Law of the Sea Convention (1982) reflects, including the legal provisions over disputes settlements, the importance of analyzing this paramount issue might be considered relevant at present. Therefore, this study will be focused in discussing legal and practical issues that concern the resolution of international maritime disputes seen from international relations point of view, by initially analyzing UN Convention on the Law of the Sea (UNCLOS 1982) relevant legal provisions, further discussing several notable cases over maritime boundaries delimitations as well as concluding with some recommendations related to this issue. The author is of the opinion that although the boundaries delimitation’s legal regime of UNCLOS reflects important standards for dispute settlements, yet considering the complex situation that represents this issue, relevant amendments might be necessary to be undertaken by international maritime organizations in order to further clarify the aforementioned legal matter.

Keywords: Law of the Sea, maritime conflicts, dispute settlements, international relations

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.

Keywords: statistical downscaling, global climate model, climate change, uncertainty

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Authors: Tudor Barbu

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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

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Authors: Madhuri S. Ghate, Rahul P. Chavhan, Shriya S. Nahar

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Learning objective: •To describe Magnetic Resonance Imaging (MRI) imaging appearances of typical and atypical uterine fibroids with emphasis on differentiating it from other similar conditions. •To classify uterine fibroids according to International Federation of Gynecology and Obstetrics (FIGO) Sub-classifications system and emphasis on its clinical significance. •To show cases with atypical imaging appearances atypical fibroids Material and methods: MRI of Pelvis had been performed in symptomatic women of child bearing age group on 1.5T and 3T MRI using T1, T2, STIR, FAT SAT, DWI sequences. Contrast was administered when degeneration was suspected. Imaging appearances of Atypical fibroids and various degenerations in fibroids were studied. Fibroids were classified using FIGO Sub-classification system. Its impact on surgical decision making and clinical outcome were also studied qualitatively. Results: Intramural fibroids were most common (14 patients), subserosal 7 patients, submucosal 5 patients . 6 patients were having multiple fibroids. 7 were having atypical fibroids. (1 hyaline degeneration, 1 cystic degeneration, 1 fatty, 1 necrosis and hemorrhage, 1 red degeneration, 1 calcification, 1 unusual large bilobed growth). Fibroids were classified using FIGO system. In uterus conservative surgeries, the lesser was the degree of myometrial invasion of fibroid, better was the fertility outcome. Conclusion: Relationship of fibroid with mucosal and serosal layers is important in the management of symptomatic fibroid cases. Risk to fertility involved in uterus conservative surgeries in women of child bearing age group depends on the extent of myometrial invasion of fibroids. FIGO system provides better insight into the degree of myometrial invasion. Knowledge about the atypical appearances of fibroids is important to avoid diagnostic confusion and untoward treatment.

Keywords: degeneration, FIGO sub-classification, MRI pelvis, uterine fibroids

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Authors: Seane Mabitsela

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The Territory of Namibia was entrusted to South Africa as a Mandate under the League of Nations Covenant. After the dissolution of the League of Nations and the commencement of United Nations operations, South Africa's conception of its legal obligations under the mandate varied from those of other members of the United Nations. Because of that, the General Assembly requested the International Court of Justice for an Advisory Opinion on the international obligations of South Africa arising therefrom. The International Court of Justice declared that South West Africa was still a mandatory territory under the Covenant of the League of Nations. It also held that South Africa continued to transmit petitions from inhabitants of the territory, the supervisory functions to be exercised by the United Nations, to which the annual reports and the petitions were to be submitted. Subject to this judgement, the question of South West Africa remained a dispute relating to the mandate brought before the International Court of Justice against South Africa. The International Court of Justice and South Africa dispute reflected the nature of the Namibian inhabitants’ appeal for recognition at the United Nations.

Keywords: International Court of Justice, Namibia, petitions, United Nations

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Authors: Sanaa Rashed Abdallah, Yasser F. Hassan

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The paper will introduce an approach where a rough sets, gene expression programming and rough neural networks are used cooperatively for learning and classification support. The Objective of gene expression programming rough neural networks (GEP-RNN) approach is to obtain new classified data with minimum error in training and testing process. Starting point of gene expression programming rough neural networks (GEP-RNN) approach is an information system and the output from this approach is a structure of rough neural networks which is including the weights and thresholds with minimum classification error.

Keywords: rough sets, gene expression programming, rough neural networks, classification

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Authors: Hasan Vural

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Turkey is a favorable country to produce a great variety of agricultural products because of her different geographic and climatic conditions which have been used to divide the country into four main and seven sub regions. This classification into seven regions traditionally has been used in order to data collection and publication especially related with agricultural production. Afterwards, nine agricultural regions were considered. Recently, the governmental body which is responsible of data collection and dissemination (Turkish Institute of Statistics-TIS) has used 12 classes which include 11 sub regions and Istanbul province. This study aims to evaluate these classification efforts based on the acreage of ten main crops in a ten years time period (1996-2005). The panel data grouped in 11 subregions has been evaluated by cluster and multivariate statistical methods. It was concluded that from the agricultural production point of view, it will be rather meaningful to consider three main and eight sub-agricultural regions throughout the country.

Keywords: agricultural region, factorial analysis, cluster analysis,

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Authors: I. Gusti A. A. Rai Asmiwyati, Robert J. Corner, Ashraf M. Dewan

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Change on land use/cover (LULC) dominantly affects spatial structure and function. It can have such impacts by disrupting social culture practice and disturbing physical elements. Thus, it has become essential to understand of the dynamics in time and space of LULC as it can be used as a critical input for developing sustainable LULC. This study was an attempt to map and monitor the LULC change in Bali Indonesia from 2003 to 2013. Using object based classification to improve the accuracy, and change detection, multi temporal land use/cover data were extracted from a set of ASTER satellite image. The overall accuracies of the classification maps of 2003 and 2013 were 86.99% and 80.36%, respectively. Built up area and paddy field were the dominant type of land use/cover in both years. Patch increase dominantly in 2003 illustrated the rapid paddy field fragmentation and the huge occurring transformation. This approach is new for the case of diverse urban features of Bali that has been growing fast and increased the classification accuracy than the manual pixel based classification.

Keywords: land use/cover, urban, Bali, ASTER

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Authors: Shivani Yadav

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The paper will first elaborate on the concept of soft power as formulated by Joseph Nye, who argues that soft power is as important as hard power in international politics as it replaces coercion with non-coercive forms of co-optation and attraction. The central tenet of the paper is to extrapolate the continued relevance of soft power in international relations in the 21st century. It is argued that the relevance of soft power, in concurrence with hard power, is on the rise in the international system. This is found to be emanating out of two factors. First, the state-centric practice of international relations has expanded to allow other actors to participate in policymaking. This has led to the resources for power generation to become varied, largely move away from the control of governments, and to produce both hard and soft power attributes. Second, as the currency of coercive power seems to be devaluing in global politics, the role of intangible factors like soft power is getting more important in policymaking. The paper will then go on to elaborate on the critiques of the formulation of soft power from various perspectives, as well as the defenses to these critiques presented by soft power proponents. The paper will reflect on the continued relevance of soft power in international politics by giving the example of India, and how soft power has continued to serve its policy objectives over the years. It is observed that even as India is recognized as a rising superpower today, yet it has made a continuous effort in cultivating its soft power resources, which have proven to be its assets in furthering its foreign policy interests. In conclusion, the paper makes the point that soft power, in conjunction with hard power, will shape international politics in the coming times.

Keywords: foreign policy, India’s soft power, international politics, smart power, soft power

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Authors: Baohua Yu

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In line with wider tends in the expansion of international student mobility, the number of international higher degree research students has grown at a significant rate in recent years. In particular, Australia has become a hub for attracting international higher degree research students from around the world. However, research has identified that international higher degree research students often encounter a wide range of academic and socio-cultural challenges in adapting to their new environment. Moreover, this can have a significant bearing on their levels of satisfaction with their studies. This paper outlines the findings of a mixed method study exploring the experiences and perceptions of international higher degree research students in Australia. Findings revealed that IRHD students’ overall and academic satisfaction in Australia were highly related to each other, and they were strongly influenced by their learning and research, moderately influenced by co-national support and intercultural contact ability. Socio-cultural satisfaction seemed to belong to a different domain from academic satisfaction because it was explained by a different set of variables such as living and adaptation and intercultural contact ability. In addition, the most important issues in terms of satisfaction were not directly related to academic studies. Instead, factors such as integration into the community, interacting with other students, relationships with supervisors, and the provision of adequate desk space were often given the greatest weight. Implications for how university policy can better support international doctoral students are discussed.

Keywords: international higher degree research students, academic adaptation, socio-cultural adaptation, student satisfaction

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Authors: Lei Zhang

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The carbon cycle greatly influences global change, and the land cover changes contribute to the status and rate of the carbon budget in ecosystems. This paper proposes a land cover classification system for mapping land cover, the national ecological environment assessment, and estimating carbon storage in ecosystems. The classification system consists of basic land cover classes at levels Ⅰ and Ⅱ and auxiliary features at level III. The basic 38 classes characterizing land cover features are derived from 19 criteria referring to composition, structure, pattern, phenology, etc. The basic classes reflect the status of carbon storage in ecosystems. The auxiliary classes at level III complement the attributes of higher levels by 9 criteria. The 5 environmental criteria of temperature, moisture, landform, aspect and slope mainly reflect the potential and intensity of carbon storage in ecosystems. The disturbance of vegetation succession caused by land use type influences the vegetation carbon budget. The other 3 vegetation cover criteria, growth period, and species characteristics further refine the vegetation types. The hierarchical structure of the land cover map (the classes of levels Ⅰ and Ⅱ) is independent of the products of level III, which is helpful for land cover product management and applications. The classification system has been adopted in the Chinese national land cover database for the carbon budget in ecosystems at a 30 m scale.

Keywords: classification system, land cover, ecosystem, carbon storage, object based

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Authors: Hannah Bigelow, Marcus D. Gottlieb, Michelle Ogrodnik, Jeffrey, D. Graham, Barbara Fenesi

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Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders affecting approximately 6% of children worldwide. ADHD is characterized by a combination of persistent deficits including impaired inhibitory control, working memory and task-switching. Many children with ADHD also have comorbid mental health issues such as anxiety and depression. There are several treatment options to manage ADHD impairments, including drug and behavioural management therapy, but they all have drawbacks, such as worsening mood disturbances or being inaccessible to certain demographics. Both physical exercise and mindfulness meditation serve as alternative options to potentially help mitigate ADHD symptoms. Although there is extensive support for the benefits of long-term physical exercise or mindfulness meditation programs, there is insufficient research investigating how acute bouts (i.e., single, short bouts) can help children with ADHD. Thus, the current study aimed to understand how single, short bouts of exercise and mindfulness meditation impacts executive functioning and psycho-emotional well-being in children with ADHD, as well as to directly compare the efficacy of these two interventions. The study used a a pre- post-test, within-subjects design to assess the effects of a 10-minute bout of moderate intensity exercise versus a 10-minute bout of mindfulness meditation (versus 10 minutes of a reading control) on the executive functioning and psycho-emotional well-being of 16 children and youth with ADHD aged 10-14 (male=11; White=80%). Participants completed all three interventions: 10 minutes of exercise, 10 minutes of mindfulness meditation, and 10 minutes of reading (control). Executive functioning (inhibitory control, working memory, task-switching) and psycho-emotional well-being (mood, self-efficacy) were assessed before and after each intervention. Mindfulness meditation promoted executive functioning, while exercise enhanced positive mood and self-efficacy. Critically, this work demonstrates that a single, short bout of mindfulness meditation session can promote inhibitory control among children with ADHD. This is especially important for children with ADHD as inhibitory control deficits are among the most pervasive challenges that they face. Furthermore, the current study provides preliminary evidence for the benefit of acute exercise for promoting positive mood and general self-efficacy for children and youth with ADHD. These results may increase the accessibility of acute exercise for children with ADHD, providing guardians and teachers a feasible option to incorporate just 10 minutes of exercise to assist children emotionally. In summary, this research supports the use of acute exercise and mindfulness meditation on varying aspects of executive functioning and psycho-emotional well-being in children and youth with ADHD. This work offers important insight into how behavioural interventions could be personalized according to a child’s needs.

Keywords: attention-deficit hyperactivity disorder (ADHD), acute exercise, mindfulness meditation, executive functioning, psycho-emotional well-being

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Authors: Anne Giles

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Humans naturally wish they could forget traumatic experiences. To help prevent future harm, however, the human brain has evolved to retain data about experiences of threat, alarm, or violation. When given compassionate support and assistance with thinking helpfully and realistically about traumatic events, most people can adjust to experiencing hardships, albeit with residual sad, unfortunate memories. Persistent, recurrent, intrusive memories, difficulty sleeping, emotion dysregulation, and avoidance of reminders, however, may be symptoms of Post-traumatic Stress Disorder (PTSD). Brain scans show that PTSD affects brain functioning. We currently have no physical means of restoring the system of brain structures and functions involved with PTSD. Medications may ease some symptoms but not others. However, forms of "talk therapy" with cognitive components have been found by researchers to reduce, even resolve, a broad spectrum of trauma symptoms. Many cultures have taboos against talking about hardships. Individuals may present themselves to mental health care professionals with severe, disabling trauma symptoms but, because of cultural norms, be unable to speak about them. In China, for example, relationship expectations may include the belief, "Bad things happening in the family should stay in the family (jiāchǒu bùkě wàiyán 家丑不可外扬)." The concept of "family (jiā 家)" may include partnerships, close and extended families, communities, companies, and the nation itself. In contrast to many trauma therapies, Cognitive Processing Therapy (CPT) for Post-traumatic Stress Disorder asks its participants to focus not on "what" happened but on "why" they think the trauma(s) occurred. The question "why" activates and exercises cognitive functioning. Brain scans of individuals with PTSD reveal executive functioning portions of the brain inadequately active, with emotion centers overly active. CPT conceptualizes PTSD as a network of cognitive distortions that keep an individual "stuck" in this under-functioning and over-functioning dynamic. Through asking participants forms of the question "why," plus offering a protocol for examining answers and relinquishing unhelpful beliefs, CPT assists individuals in consciously reactivating the cognitive, executive functions of their brains, thus restoring normal functioning and reducing distressing trauma symptoms. The culturally sensitive components of CPT that allow people to "talk about it without talking about it" may offer the possibility for worldwide relief from symptoms of trauma.

Keywords: cognitive processing therapy (CPT), cultural norms, post-traumatic stress disorder (PTSD), trauma recovery

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Authors: Seongryong Kang, Woonjin Kim, Sungjoo Lee

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Under the environment of fierce competition and globalized economy, international technology collaboration has gained increasing attention as a way to improve innovation efficiency. While international technology transfer helps a firm to acquire necessary technology in a short period of time, it also has a risk; embedding external technology from overseas partners may cause a transaction cost due to the regional, cultural and language barriers, which tend to offset the benefits of such transfer. Though a number of previous studies have focused on the effects of technology in-transfer on firm performance, few have conducted in the context of international technology transfer. To fill this gap, this study aims to investigate the impact of international technology in-transfer on firm performance – both innovation and financial performance, with a particular emphasis on the diversity and intensity of such transfer. To do this, we adopted technology balance payment (TBP) data of Korean firms from 2010 to 2011, where an intermediate regression analysis was used to identify the intermediate effects of absorptive capacity. The analysis results indicate that i) the diversity and intensity of international technology transfer influence innovation performance by improving R&D capability positively; and ii) the diversity has a positive impact but the intensity has a negative impact on financial performance through the intermediation of R&D intensity. The research findings are expected to provide meaningful implications for establishing global technology strategy and developing policy programs to facilitate technology transfer.

Keywords: diversity, intensity, international technology acquisition, performance, technology transfer

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Authors: Tatyana Kim

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This paper seeks to explore the academic and sociocultural adaptation experiences of international students studying in Kazakhstan. Using multiple case study design, the research will be undertaken at two private Kazakhstani universities having a relatively large and diverse body of international students. Thus, 20 full-time undergraduate international students from the sampled universities will be interviewed to identify factors that impede or, vice versa, facilitate their academic and sociocultural adaptation in Kazakhstan, as well as to reveal how universities support these students in the process of their adaptation. To investigate the issue more deeply, it was decided to explore the university administrators’ viewpoint of the issue. Thus, six university administrators who are in charge of recruiting and supporting international students and, thus, are particularly knowledgeable about their experiences, have been recruited for this study. Identification of both students’ and administrators’ perspectives on the matter may help reveal miscommunication, if any, and gain greater insight into the phenomenon. The data will be collected between November 5, 2019, and December 10, 2019. Preliminary findings will be presented at the conference. Lysgaard’s U-curve adjustment theory (1955) will be employed as a guiding framework to discuss and interpret the findings.

Keywords: academic adaptation, adaptation, higher education, international students, sociocultural adaptation

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Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

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Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection

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Authors: Manoela Cabo da Silva, Elton Fernandes, Ricardo Pacheco, Heloisa Pires

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This study examined cointegration and causal relationships between economic growth and regular domestic and international passenger air transport in Brazil. Total passengers embarked and disembarked were used as a proxy for air transport activity and gross domestic product (GDP) as a proxy for economic development. The test spanned the period from 2000 to 2015 for domestic passenger traffic and from 1995 to 2015 for international traffic. The results confirm the hypothesis that there is cointegration between passenger traffic series and economic development, showing a bi-directional Granger causal relationship between domestic traffic and economic development and unidirectional influence by economic growth on international passenger air transport demand. Variance decomposition of the series showed that domestic air transport was far more important than international transport to promoting economic development in Brazil.

Keywords: air passenger transport, cointegration, economic growth, GDP, Granger causality

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Authors: Joseph George, Anne Kotteswara Roa

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Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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Authors: Ali Arabkheradmand, Enayat A. Shabani, Shabnam Ranjbar Nikkhoo

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Historical and ancestral bonds of the countries in the Middle East have led to similarities in culture and context of their societies. In addition, economic resources, such as the oil industry, have generally been an integrative point in the region. Higher education of a country is influenced by different national and international factors and regarding the mentioned bonds, it is inviting to study the development of the countries of the Middle East in higher education and draw some practical implications which can be used in the educational policy-making of the region. This review includes a data analysis on the population of international students in the countries of the Middle East. As its second objective, a review study on the successful countries, that is those which host the highest number of international students and the strategies they have developed to reach this state among the countries of the region has been conducted. Suggestions are made as to the strategies in higher education systems of these countries which could prove useful and practical in the development of internationalization of higher education in the region, specifically with regard to the recruitment of international students.

Keywords: internationalization of higher education, international student recruitment, Middle East countries, educational policy making

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Authors: Sanela Slavkovic, Congor Nad, Spela Golubovic

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Background: The diagnosis of multiple sclerosis (MS) is a major life challenge and has repercussions on all aspects of the daily functioning of those attained by it – personal activities, social participation, and quality of life. Regular follow-up of only the neurological status is not informative enough so that it could provide data on the sort of support and rehabilitation that is required. Objective: The aim of this study was to establish the current level of functioning of persons attained by MS and the factors that influence it. Methods: The study was conducted in Serbia, on a sample of 108 persons with relapse-remitting form of MS, aged 20 to 53 (mean 39.86 years; SD 8.20 years). All participants were fully ambulatory. Methods applied in the study include Expanded Disability Status Scale-EDSS and World Health Organization Disability Assessment Schedule, WHODAS 2.0 (36-item version, self-administered). Results: Participants were found to experience the most problems in the domains of Participation, Mobility, Life activities and Cognition. The least difficulties were found in the domain of Self-care. Symptom duration was the only control variable with a significant partial contribution to the prediction of the WHODAS scale score (β=0.30, p < 0.05). The total EDSS score correlated with the total WHODAS 2.0 score (r=0.34, p=0.00). Statistically significant differences in the domain of EDSS 0-5.5 were found within categories (0-1.5; 2-3.5; 4-5.5). The more pronounced a participant’s EDSS score was, although not indicative of large changes in the neurological status, the more apparent the changes in the functional domain, i.e. in all areas covered by WHODAS 2.0. Pyramidal (β=0.34, p < 0.05) and Bowel and bladder (β=0.24, p < 0.05) functional systems were found to have a significant partial contribution to the prediction of the WHODAS score. Conclusion: Measuring functioning and disability is important in the follow-up of persons suffering from MS in order to plan rehabilitation and define areas in which additional support is needed.

Keywords: disability, functionality, multiple sclerosis, rehabilitation

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Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

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The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Refilwe Moeletsi

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Dimension stone quarrying around Brits and Belfast areas started in the early 1930s and has been growing rapidly since then. Environmental impacts associated with these quarries have not been documented, and hence this study aims at detecting any change in the environment that might have been caused by these activities. Landsat images that were used to assess land use/land cover changes in Brits quarries from 1998 - 2015. A supervised classification using maximum likelihood classifier was applied to classify each image into different land use/land cover types. Classification accuracy was assessed using Google Earth™ as a source of reference data. Post-classification change detection method was used to determine changes. The results revealed significant increase in granite quarries and corresponding decrease in vegetation cover within the study region.

Keywords: remote sensing, GIS, change detection, granite quarries

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Authors: Fedorova Elena

Abstract:

In this article, we draw a distinction between two important functions of public policy in private international law. The first function is widely recognized and relates to the prevention of application of foreign laws and enforcement of foreign court judgments whenever their effects are incompatible with the domestic legal system of the forum. This effectively protects sovereign rights of the forum state as it allows to resist against the undesirable effects of foreign law-making and law-enforcement policies. The second function is less obvious, but not less important. As the internal private legal relationships, international private relationships are usually governed by rules of public policy, to which the parties can not derogate by mutual agreement. Thefore, for international private law relations public policy has a different function than previously mentioned: in this case, the public policy acts as a defense against unacceptable effects of the party autonomy. Thus, this second function of public policy consists in the limitation of the party autonomy wich effects would be unacceptable for the local legal system. In the frame of this second function the author will analyse two types of public policy which can limit the party autonomy: « substantial » public policy (which regulates the substance of international legal relationship) and « conflictual » public policy (which regulates the party autonomy to choose the law applicable for the substance of relationship). The author provides an analysis of these functions of the public policy in the field of international contract law because of the important role of the principle of party autonomy for international contract relations.

Keywords: public policy, general theory of private international law, substantial public policy, conflictual public policy

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Authors: Akbar

Abstract:

Pros and cons of the capital punishment in Indonesia have been out of the date. The discourse of capital punishment has no relevance to the theory of punishment and theories of cultural relativism. In fact, the provisions of exceptions to the right to life by administering the death penalty against the perpetrators of serious crimes in Indonesia is a narrow perspective that does not pay attention to the development of the punishment of the crime. This thing is aggravated by an error to understand the natural right and legal right where the prohibition of those rights is result from a failure to distinguish the characteristic of the rights and to remember the raison d’être of law. To parse the irrational above, this paper will try to analyze normatively the error referring to the complementary theory between the sources of international law and the sources of municipal law of Indonesia. Both sources of the law above should be understood in the mutually reinforcing relationship enforceability because of false perceptions against those will create the disintegration between international law and municipal law of Indonesia. This disintegration is explicit not only contrary to the integrative theory of international law but also integrative theory of municipal law of Indonesia.

Keywords: capital punishment, municipal law, right to life, international law, the raison d’être of law, complementary theory, integrative theory

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Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

Abstract:

In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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Authors: Nidhal K. Azawi, John M. Gauch

Abstract:

Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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