Search results for: CSLBP features

Authors: Chanchai Supaartagorn

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E-retailing is the sale of goods online that takes place over the Internet. The Internet has shrunk the entire World. The world e-retailing is growing at an exponential rate in the Americas, Europe, and Asia. However, e-retailing costs require expensive investment, such as hardware, software, and security systems. Cloud computing technology is internet-based computing for the management and delivery of applications and services. Cloud-based e-retailing application models allow enterprises to lower their costs with their effective implementation of e-retailing activities. In this paper, we describe the concept of cloud computing and present the architecture of cloud computing, combining the features of e-retailing. In addition, we propose a strategy for implementing cloud computing with e-retailing. Finally, we explain the benefits from the architecture.

Keywords: architecture, cloud computing, e-retailing, internet-based

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Authors: Shilpa Avarebeel

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Background: India is one of the seven identified countries in South-East Asia region, regularly reporting dengue infection and may soon transform into a major niche for dengue epidemics. Objective: To study the clinical profile of dengue in our setting with special reference to respiratory complication. Study design: Descriptive and exploratory study, for one year in 2014. All patients confirmed as dengue infection were followed and their clinical profile, along with outcome was determined. Study proforma was designed based on the objective of the study and it was pretested and used after modification. Data was analyzed using statistical software SPSS-Version 16. Data were expressed as mean ±S .D for parametric variables and actual frequencies or percentage for non-parametric data. Comparison between groups was done using students’ t-test for independent groups, Chie square test, one-way ANOVA test, Karl Pearson’s correlation test. Statistical significance is taken at P < 0.05. Results: Study included 134 dengue positive cases. 81% had dengue fever, 18% had dengue hemorrhagic fever, and one had dengue shock syndrome. Most of the cases reported were during the month of June. Maximum number of cases was in the age group of 26-35 years. Average duration of hospital stay was less than seven days. Fever and myalgia was present in all the 134 patients, 16 had bleeding manifestation. 38 had respiratory symptoms, 24 had breathlessness, and 14 had breathlessness and dry cough. On clinical examination of patients with respiratory symptoms, all twenty-eight had hypoxia features, twenty-four had signs of pleural effusion, and four had ARDS features. Chest x-ray confirmed the same. Among the patients with respiratory symptoms, the mean platelet count was 26,537 c/cmm. There was no statistical significant difference in the platelet count in those with ARDS and other dengue complications. Average four units of platelets were transfused to all those who had ARDS in view of bleeding tendency. Mechanical ventilator support was provided for ARDS patients. Those with pleural effusion and pulmonary oedema were given NIV (non-invasive ventilation) support along with supportive care. However, steroids were given to patients with ARDS and 10 patients with signs of respiratory distress. 100%. Mortality was seen in patients with ARDS. Conclusion: Dengue has to be checked for those presenting with fever and breathlessness. Supportive treatments remain the cornerstone of treatment. Platelet transfusion has to be given only by clinical judgment. Steroids have no role except in early ARDS, which is controversial. Early NIV support helps in speedy recovery of dengue patients with respiratory distress.

Keywords: adult respiratory distress syndrome, dengue fever, non-invasive ventilation, pulmonary complication

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Authors: Mekdelawit Teferi Alamirew

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As a practical tool, the Geographical information system (GIS) was used for data integration, collection, management, analysis, and output presentation in pavement mangement systems . There are many GIS techniques to improve the maintenance activities like Dynamic segmentation and weighted overlay analysis which considers Multi Criteria Decision Making process. The results indicated that the developed MPI model works sufficiently and yields adequate output for providing accurate decisions. Hence considering multi criteria to prioritize the pavement sections for maintenance, as a result of the fact that GIS maps can express position, extent, and severity of pavement distress features more effectively than manual approaches, lastly the paper also offers digitized distress maps that can help agencies in their decision-making processes.

Keywords: pavement, flexible, maintenance, index

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Authors: Uswah Ahmad Khan, Muhammad Moazam Fraz, Humayoon Shafique Satti, Qasim Aziz

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Approximately 10-14% of the global population experiences a functional disorder known as irritable bowel syndrome (IBS). The disorder is defined by persistent abdominal pain and an irregular bowel pattern. IBS significantly impairs work productivity and disrupts patients' daily lives and activities. Although IBS is widespread, there is still an incomplete understanding of its underlying pathophysiology. This study aims to help characterize the phenotype of IBS patients by differentiating the comorbidities found in IBS patients from those in non-IBS patients using machine learning algorithms. In this study, we extracted samples coding for IBS from the UK BioBank cohort and randomly selected patients without a code for IBS to create a total sample size of 18,000. We selected the codes for comorbidities of these cases from 2 years before and after their IBS diagnosis and compared them to the comorbidities in the non-IBS cohort. Machine learning models, including Decision Trees, Gradient Boosting, Support Vector Machine (SVM), AdaBoost, Logistic Regression, and XGBoost, were employed to assess their accuracy in predicting IBS. The most accurate model was then chosen to identify the features associated with IBS. In our case, we used XGBoost feature importance as a feature selection method. We applied different models to the top 10% of features, which numbered 50. Gradient Boosting, Logistic Regression and XGBoost algorithms yielded a diagnosis of IBS with an optimal accuracy of 71.08%, 71.427%, and 71.53%, respectively. Among the comorbidities most closely associated with IBS included gut diseases (Haemorrhoids, diverticular diseases), atopic conditions(asthma), and psychiatric comorbidities (depressive episodes or disorder, anxiety). This finding emphasizes the need for a comprehensive approach when evaluating the phenotype of IBS, suggesting the possibility of identifying new subsets of IBS rather than relying solely on the conventional classification based on stool type. Additionally, our study demonstrates the potential of machine learning algorithms in predicting the development of IBS based on comorbidities, which may enhance diagnosis and facilitate better management of modifiable risk factors for IBS. Further research is necessary to confirm our findings and establish cause and effect. Alternative feature selection methods and even larger and more diverse datasets may lead to more accurate classification models. Despite these limitations, our findings highlight the effectiveness of Logistic Regression and XGBoost in predicting IBS diagnosis.

Keywords: comorbidities, disease association, irritable bowel syndrome (IBS), predictive analytics

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Authors: Lei Zhou, Chao Li, Ruiqi Ren, Dan Li, Yali Wang, Daxin Ni, Zijian Feng, Qun Li

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Background: Since the first human infection with avian influenza A(H7N9) case was reported in China on 31 March 2013, five epidemics have been observed in China through February 2013 and September 2017. Though the overall mortality rate of H7N9 has remained as high as around 40% throughout the five epidemics, the specific mortality rate in Mainland China varied by provinces. We conducted a descriptive analysis of mortality rates of H7N9 cases to explore the various severity features of the disease and then to provide clues of further analyses of potential factors associated with the severity of the disease. Methods: The data for analysis originated from the National Notifiable Infectious Disease Report and Surveillance System (NNIDRSS). The surveillance system and identification procedure for H7N9 infection have not changed in China since 2013. The definition of a confirmed H7N9 case is as same as previous reports. Mortality rates of H7N9 cases are described and compared by time and location of reporting, age and sex, and genetic features of H7N9 virus strains. Results: The overall mortality rate, the male and female specific overall rates of H7N9 is 39.6% (608/1533), 40.3% (432/1072) and 38.2% (176/461), respectively. There was no significant difference between the mortality rates of male and female. The age-specific mortality rates are significantly varied by age groups (χ²=38.16, p < 0.001). The mortality of H7N9 cases in the age group between 20 and 60 (33.17%) and age group of over 60 (51.16%) is much higher than that in the age group of under 20 (5.00%). Considering the time of reporting, the mortality rates of cases which were reported in the first (40.57%) and fourth (42.51%) quarters of each year are significantly higher than the mortality of cases which were reported in the second (36.02%) and third (27.27%) quarters (χ²=75.18, p < 0.001). The geographic specific mortality rates vary too. The mortality rates of H7N9 cases reported from the Northeast China (66.67%) and Westeast China (56.52%) are significantly higher than that of H7N9 cases reported from the remained area of mainland China. The mortality rate of H7N9 cases reported from the Central China is the lowest (34.38%). The mortality rates of H7N9 cases reported from rural (37.76%) and urban (38.96%) areas are similar. The mortality rate of H7N9 cases infected with the highly pathogenic avian influenza A(H7N9) virus (48.15%) is higher than the rate of H7N9 cases infected with the low pathogenic avian influenza A(H7N9) virus (37.57%), but the difference is not statistically significant. Preliminary analyses showed that age and some clinical complications such as respiratory failure, heart failure, and septic shock could be potential risk factors associated with the death of H7N9 cases. Conclusions: The mortality rates of H7N9 cases varied by age, sex, time of reporting and geographical location in mainland China. Further in-depth analyses and field investigations of the factors associated with the severity of H7N9 cases need to be considered.

Keywords: H7N9 virus, Avian Influenza, mortality, China

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Authors: Abdelhalem Shahen

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The world is now experiencing a digital revolution and greatly accelerated technological developments, in addition to the transition from the economy in its traditional form to the digital economy, which has resulted in the emergence of new tools that are appropriate to those developments, and from this, this paper attempts to explore the economic characteristics of the bitcoin currency that circulated recently. Due to the many advantages that distinguish it from money in its traditional forms, which have a range of economic effects. The study found that Bitcoin is among the technological innovations, which contain a set of characteristics that are worth studying, those that make it the focus of attention, such as the digital currency, the peer-to-peer property, Lower and Faster Transaction Costs, transparency, decentralized control, privacy, and Double-Spending, as well as security and Cryptographic, and finally mining.

Keywords: Digital Economics, Digital Currencies, Bitcoin, Features of Bitcoin

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Authors: Shael Brown, Reza Farivar

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Persistence diagrams capture valuable topological features of datasets that other methods cannot uncover. Still, their adoption in data pipelines has been limited due to the lack of publicly available tools in R (and python) for analyzing groups of them with machine learning and statistical inference. In an easy-to-use and scalable R package called TDApplied, we implement several applied analysis methods tailored to groups of persistence diagrams. The two main contributions of our package are comprehensiveness (most functions do not have implementations elsewhere) and speed (shown through benchmarking against other R packages). We demonstrate applications of the tools on simulated data to illustrate how easily practical analyses of any dataset can be enhanced with topological information.

Keywords: machine learning, persistence diagrams, R, statistical inference

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Authors: John Morales, Eduardo Orduña

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Currently the Principal Component Analysis (PCA) theory has been used to develop algorithms regarding to Electric Power Systems (EPS). In this context, this paper presents a practical tutorial of this technique detailed their concept, on-line and off-line mathematical foundations, which are necessary and desirables in EPS algorithms. Thus, features of their eigenvectors which are very useful to real-time process are explained, showing how it is possible to select these parameters through a direct optimization. On the other hand, in this work in order to show the application of PCA to off-line and on-line signals, an example step to step using Matlab commands is presented. Finally, a list of different approaches using PCA is presented, and some works which could be analyzed using this tutorial are presented.

Keywords: practical guide; on-line; off-line, algorithms, faults

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Authors: Ehsan Khademi, Mahdi Jalili

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Despite the special features of bipartite networks, they are common in many systems. Real-world bipartite networks may show community structure, similar to what one can find in one-mode networks. However, the interpretation of the community structure in bipartite networks is different as compared to one-mode networks. In this manuscript, we compare a number of available methods that are frequently used to discover community structure of bipartite networks. These networks are categorized into two broad classes. One class is the methods that, first, transfer the network into a one-mode network, and then apply community detection algorithms. The other class is the algorithms that have been developed specifically for bipartite networks. These algorithms are applied on a model network with prescribed community structure.

Keywords: community detection, bipartite networks, co-clustering, modularity, network projection, complex networks

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Authors: N. M. Thao, I. Dolguntseva, M. Leijon

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Flow blockages referring to the increase in flow are considered as a vital equipment for marine current energy conversion. However, the shape of these devices will result in extracted energy under the operation. The present work investigates the effect of two configurations of a grating, convergent and divergent that located upstream, to the water flow velocity. Computational Fluid Dynamic simulation studies the flow characteristics by using the ANSYS Fluent solver for these specified arrangements of the grating. The results indicate that distinct features of flow velocity between “convergent” and “divergent” grating placements are up to in confined conditions. Furthermore, the velocity in case of granting is higher than that of the divergent grating.

Keywords: marine current energy, converter, turbine granting, RANS simulation, water flow velocity

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Authors: Tingting Zou

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This paper firstly presents an overview of the situation of Xinjiang and Hotan, and describes the current status and features of Uyghur students’ English education. Then it summarizes the research on the theories of Third Language Acquisition and Foreign Language Learning Motivation at home and abroad. Further, through the data collected by the questionnaire, the paper points out the three main problems and causes of Uyghur students’ English learning in Hotan, Xinjiang. Finally, the paper draws a conclusion and puts forward some suggestions on how to improve their English learning quality based on the theory of Foreign Language Learning Motivation.

Keywords: countermeasures and difficulties, English learning, Hotan Xinjiang, Uyghur students

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Sanaa I. Abu Alasal, Madleen M. Esbeih, Eman R. Fayyad, Rami S. Gharaibeh, Mostafa Z. Ali, Ahmed A. Freewan, Monther M. Jamhawi

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This research proposes a novel reconstruction protocol for restoring missing surfaces and low-quality edges and shapes in photos of artifacts at historical sites. The protocol starts with the extraction of a cloud of points. This extraction process is based on four subordinate algorithms, which differ in the robustness and amount of resultant. Moreover, they use different -but complementary- accuracy to some related features and to the way they build a quality mesh. The performance of our proposed protocol is compared with other state-of-the-art algorithms and toolkits. The statistical analysis shows that our algorithm significantly outperforms its rivals in the resultant quality of its object files used to reconstruct the desired model.

Keywords: meshes, point clouds, surface reconstruction protocols, 3D reconstruction

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Authors: S. Ait Ali Yahia

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One of the main features of the Maghreb is its linguistic richness. The multilingualism is a fact which always marked the Maghreb since the beginning of the history up to know. Since the arrival of the Phoenicians, followed by the Carthaginians, Romans, and Arabs, etc, there was a social group in the Maghreb which controlled two kinds of idioms. The libyc one remained, despite everything, the local language used by the major part of the population. This language had a support of written transmission attested by many inscriptions. Among all the forms of the Maghreb writing, this alphabet, however, continues to cause a certain number of questions about the origin and the date of its appearance. The archaeological, linguistic and historical data remain insufficient to answer these questions. This did not prevent the researchers from giving an opinion. In order to answer these questions we will expose here the various assumptions adopted by various authors who are founded on more or less explicit arguments. We will also speak about the various forms taken by the libyc writing during antiquity.

Keywords: the alphabet libyc, Eastern libyc, Western libyc, multilingualism

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Authors: David A. Wallace, Salakjit J. Nilboworn

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Secure and reliable transmission and distribution of electrical power is crucial in today’s ever-increasing demand for electricity. Traditional methods of protecting the electrical grid have relied on relaying systems receiving voltage and current inputs from inductive instruments transformers (IT). This method has provided robust and stable performance throughout the years. Today with the advent of new non-conventional transformers (NCIT) and sensors, the electrical landscape is changing. These new systems have to ability to provide the same electrical performance as traditional instrument transformers with the added features of data acquisition, communication, smaller footprint, lower cost and resistance to GMD/GIC events.

Keywords: non-conventional instrument transformers, digital substations, smart grids, micro-grids

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Authors: S. Tehsin, S. Kausar

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The ultimate aim of machine intelligence is to explore and materialize the human capabilities, one of which is the ability to detect various text objects within one or more images displayed on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However, it needs to technologically testify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed. Subsequent examination bears testimony to the fact that the features extracted proved instrumental to text detection.

Keywords: biologically inspired vision, content based retrieval, document analysis, text extraction

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Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

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Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

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Authors: Gauranga Das

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People in cities have prosperity but there is immense pollution, chaos in the mind, anxiety and turbulence. People in the villages experience pristine pure environment but they also experience poverty. There is a need to find out ways by which the cities and the villages can complement each other through their strengths and take care of each other’s weaknesses. In order to do this, the case study of Govardhan Ecovillage has been explored in this paper. All its environment, social and economic initiatives along with eco-tourism and wellness features are being analyzed. The analysis shows that Govardhan Ecovillage is successfully able to harmonize its different initiatives and provide a package which has created a win-win solution for the city people and also the villagers. Such kind of Eco-tourism initiatives should be supported and replicated in other places in the world to benefit everyone.

Keywords: sustainability, ecotourism, ecology, rural development, wellness, biodiversity

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Authors: Maria Antonietta Marongiu

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Propositional information in discourse is made coherent, intelligible, and persuasive through metadiscourse. The linguistic and rhetorical choices that writers/speakers make to organize and negotiate content matter are intended to help relate a text to its context. Besides, they help the audience to connect to and interpret a text according to the values of a specific discourse community. Based on these assumptions, this work aims to analyse the use of metadiscourse in the spoken performance of teachers in online EFL, ESP, and subject-teacher courses taught in English to non-native learners in higher education. In point of fact, the global spread of Covid 19 has forced universities to transition their in-class courses to online delivery. This has inevitably placed on the instructor a heavier interactional responsibility compared to in-class courses. Accordingly, online delivery needs greater structuring as regards establishing the reader/listener’s resources for text understanding and negotiating. Indeed, in online as well as in in-class courses, lessons are social acts which take place in contexts where interlocutors, as members of a community, affect the ways ideas are presented and understood. Following Hyland’s Interactional Model of Metadiscourse (2005), this study intends to investigate Teacher Talk in online academic courses during the Covid 19 lock-down in Italy. The selected corpus includes the transcripts of online EFL and ESP courses and subject-teachers online courses taught in English. The objective of the investigation is, firstly, to ascertain the presence of metadiscourse in the form of interactive devices (to guide the listener through the text) and interactional features (to involve the listener in the subject). Previous research on metadiscourse in academic discourse, in college students' presentations in EAP (English for Academic Purposes) lessons, as well as in online teaching methodology courses and MOOC (Massive Open Online Courses) has shown that instructors use a vast array of metadiscoursal features intended to express the speakers’ intentions and standing with respect to discourse. Besides, they tend to use directions to orient their listeners and logical connectors referring to the structure of the text. Accordingly, the purpose of the investigation is also to find out whether metadiscourse is used as a rhetorical strategy by instructors to control, evaluate and negotiate the impact of the ongoing talk, and eventually to signal their attitudes towards the content and the audience. Thus, the use of metadiscourse can contribute to the informative and persuasive impact of discourse, and to the effectiveness of online communication, especially in learning contexts.

Keywords: discourse analysis, metadiscourse, online EFL and ESP teaching, rhetoric

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Authors: Ki-Jin Kim, Suk-Hui LEE, Sanghoon Park, K. H. Ahn

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A high power, low loss asymmetric single pole double through(SPDT) antenna switch for LTE-A Front-End Module(FEM) is presented in this paper by using CMOS technology. For the usage of LTE-A applications, low loss and high linearity are the key features which are very challenging works under CMOS process. To enhance insertion loss(IL) and power handling capability, this paper adopts asymmetric Transmitter (TX) and RX (Receiver) structure, floating body technique, multi-stacked structure, and feed forward capacitor technique. The designed SPDT switch shows TX IL 0.34 dB, RX IL 0.73 dB, P1dB 38.9 dBm at 0.9 GHz and TX IL 0.37 dB, RX IL 0.95 dB, P1dB 39.1 dBm at 2.5 GHz respectively.

Keywords: CMOS switch, SPDT switch, high power CMOS switch, LTE-A FEM

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Authors: Jonas Kahlert

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Blockchain technology has gained importance and momentum in the energy sector. Yet, there is no structured analysis of how specific features of the blockchain technology can create value in the energy sector. We employ a qualitative analysis on insights gained from the current literature and expert interviews. Along the four most prevalent use cases of blockchain technology in the energy sector, we discuss the potential of blockchain technology to support a transition to a more affordable, sustainable and reliable energy system. We show that in its current state, blockchain and adjacent technologies are not a necessity but a sufficiency towards this transition. We also show how current limitations of the blockchain and adjacent technologies can be even counterproductive. Finally, we discuss implications for policy makers and managers.

Keywords: blockchain technology, affordance theory, energy trilemma, sustainability

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Authors: Murad Aydin Şanda, Mustafa Küçüködük

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The flora and it’s plants ethnobotanical features of Oyukludag were investigated between 2003 and 2006 years; 780 herbarium specimens belonging to 448 taxa, 292 genera and 62 families were collected and identified from the area. The families which have the most taxa in research area are Compositae (Asteraceae) 78 (17%), Leguminosae (Fabaceae) 58 (13%), Cruciferae (Brassicaceae) 34 (8%), Labiatae (Lamiaceae) 33 (7%), Gramineae (Poaceae) 29 (6%), Caryophyllaceae 19 (4%), Umbelliferae (Apiaceae) 18 (4%), Boraginaceae 17 (4%), Liliaceae 16 (4%). The number of cultivated plants are 17. The research area is in the district of Konya and is in the C4 square according to the Grid System. The phytogeographic elements are represented in the study area as follows; Iranian-Turanian (18%), Mediterranean (17%) and Euro-Siberian (2%). The phytogeographic regions of 268 (60%) taxa are either multi-regional or unknown. The number of endemic taxa is 56 (12%).

Keywords: flora, Oyukludag, Yellibel, Karaman, Turkey

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Authors: Mohammed Nadir Djedid, Abdallah Chouarfia

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Transparency of the system and its integration into the natural environment of the user are some of the important features of pervasive computing. But these characteristics that are considered as the strongest points of pervasive systems are also their weak points in terms of the user’s privacy. The privacy in pervasive systems involves more than the confidentiality of communications and concealing the identity of virtual users. The physical presence and behavior of the user in the pervasive space cannot be completely hidden and can reveal the secret of his/her identity and affect his/her privacy. This paper shows that the application of major techniques for protecting the user’s privacy still insufficient. A new solution named Shadow Protocol is proposed, which allows the users to authenticate and interact with the surrounding devices within an ubiquitous computing environment while preserving their privacy.

Keywords: pervasive systems, identification, authentication, privacy

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

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

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

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Authors: Bharatendra Rai

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Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.

Keywords: degradation signal, drill-bit breakage, random forest, multinomial logistic regression

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Authors: Hangsik Shin

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The purpose of this research is to restore the feature location of under-sampled photoplethysmogram using spline interpolation and to investigate feasibility for feature shape restoration. We obtained 10 kHz-sampled photoplethysmogram and decimated it to generate under-sampled dataset. Decimated dataset has 5 kHz, 2.5 k Hz, 1 kHz, 500 Hz, 250 Hz, 25 Hz and 10 Hz sampling frequency. To investigate the restoration performance, we interpolated under-sampled signals with 10 kHz, then compared feature locations with feature locations of 10 kHz sampled photoplethysmogram. Features were upper and lower peak of photplethysmography waveform. Result showed that time differences were dramatically decreased by interpolation. Location error was lesser than 1 ms in both feature types. In 10 Hz sampled cases, location error was also deceased a lot, however, they were still over 10 ms.

Keywords: peak detection, photoplethysmography, sampling, signal reconstruction

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Authors: Railly Hugo, Igor Aguilar-Alonso

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Software visualization is a powerful tool for understanding complex software systems. However, current visualization tools often lack features or are difficult to use, limiting their effectiveness. In this paper, we present next-viz, a proposed web-based visualization tool that addresses these challenges. We provide a literature review of existing software visualization techniques and tools and describe the architecture of next-viz in detail. Our proposed tool incorporates state-of-the-art visualization techniques and is designed to be user-friendly and intuitive. We believe next-viz has the potential to advance the field of software visualization significantly.

Keywords: software visualization, literature review, tool proposal, next-viz, web-based, architecture, visualization techniques, user-friendly, intuitive

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Authors: G. P. Gunasinghe, Lilani Ruhunage, N. P. Ratnayake, G. V. I. Samaradivakara, H. M. R. Premasiri, A. S. Ratnayake, Nimila Dushantha, W. A. P. Weerakoon, K. B. A. Silva

Abstract:

Sri Lanka is affected by different natural disasters such as tsunami, landslides, lightning, and riverine flood. Out of them, riverine floods act as a major disaster in the country. Different strategies are applied to control the impacts of flood hazards, and the expansion of river mouth is considered as one of the main activities for flood mitigation and disaster reduction. However, due to this expansion process, natural sand barriers including sand spits, barrier islands, and tidal planes are destroyed or subjected to change. This, in turn, can change the hydrodynamics and sediment dynamics of the area leading to other damages to the natural coastal features. The removal of a considerable portion of naturally formed sand barrier at Kaluganga River outlet (Calido Beach), Sri Lanka to control flooding event at Kaluthara urban area on May 2017, has become a serious issue in the area causing complete collapse of river mouth barrier spit bar system leading to rapid coastal erosion Kaluganga river outlet area and saltwater intrusion into the Kaluganga River. The present investigation is focused on assessing effects due to the removal of a considerable portion of naturally formed sand barrier at Kaluganga river mouth. For this study, the beach profiles, the bathymetric surveys, and Google Earth historical satellite images, before and after the flood event were collected and analyzed. Furthermore, a beach boundary survey was also carried out in October 2018 to support the satellite image data. The results of Google Earth satellite images and beach boundary survey data analyzed show a chronological breakdown of the sand barrier at the river outlet. The comparisons of pre and post-disaster bathymetric maps and beach profiles analysis revealed a noticeable deepening of the sea bed at the nearshore zone as well. Such deepening in the nearshore zone can cause the sea waves to break very near to the coastline. This might also lead to generate new diffraction patterns resulting in differential coastal accretion and erosion scenarios. Unless immediate mitigatory measures were not taken, the impacts may cause severe problems to the sensitive Kaluganag river mouth system.

Keywords: bathymetry, beach profiles, coastal features, river outlet, sand barrier, Sri Lanka

Procedia PDF Downloads 119

Authors: Behrooz Ghasemi, Bahram Sharijian

Abstract:

Al2O3/Mo nanocomposite powders were successfully synthesized by mechanical milling through mechanochemical reaction between MoO3 and Al. The structural evolutions of powder particles during mechanical milling were studied by X-ray diffractometry (XRD), energy dispersive X-ray spectroscopy(EDX) and scanning electron microscopy (SEM). Results show that Al2O3-Mo was completely obtained after 5 hr of milling. The crystallite sizes of Al2O3 and Mo after milling for 20 hr were about 45 nm and 23 nm, respectively. With longer milling time, the intensities of Al2O3 and Mo peaks decreased and became broad due to the decrease in crystallite size. Morphological features of powders were influenced by the milling time. The resulting Al2O3- Mo nanocomposite powder exhibited an average particle size of 200 nm after 20 hr of milling. Also nanocomposite powder after 10 hr milling had relatively equiaxed shape with uniformly distributed Mo phase in Al2O3 matrix.

Keywords: Al2O3/Mo, nanocomposites, mechanochemical, mechanical milling

Procedia PDF Downloads 348

Authors: Stefan Peters, Phillip Roetman

Abstract:

The global loss of biodiversity is threatening the benefits nature provides to human populations and has become a more pressing issue than climate change and requires immediate attention. While there have been successful global agreements for environmental protection, such as the Montreal Protocol, these are rare, and we cannot rely on them solely. Thus, it is crucial to take national and local actions to support biodiversity. Australia is one of the 17 countries in the world with a high level of biodiversity, and its cities are vital habitats for endangered species, with more of them found in urban areas than in non-urban ones. However, the protection of biodiversity in metropolitan Adelaide has been inadequate, with over 130 species disappearing since European colonization in 1836. In this research project we conceptualized, developed and implemented a framework for wildlife Habitat Hotspots and Habitat Corridor modelling in an urban context using geographic data and GIS modelling and analysis. We used detailed topographic and other geographic data provided by a local council, including spatial and attributive properties of trees, parcels, water features, vegetated areas, roads, verges, traffic, and census data. Weighted factors considered in our raster-based Habitat Hotspot model include parcel size, parcel shape, population density, canopy cover, habitat quality and proximity to habitats and water features. Weighted factors considered in our raster-based Habitat Corridor model include habitat potential (resulting from the Habitat Hotspot model), verge size, road hierarchy, road widths, human density, and presence of remnant indigenous vegetation species. We developed a GIS model, using Python scripting and ArcGIS-Pro Model-Builder, to establish an automated reproducible and adjustable geoprocessing workflow, adaptable to any study area of interest. Our habitat hotspot and corridor modelling framework allow to determine and map existing habitat hotspots and wildlife habitat corridors. Our research had been applied to the study case of Burnside, a local council in Adelaide, Australia, which encompass an area of 30 km2. We applied end-user expertise-based category weightings to refine our models and optimize the use of our habitat map outputs towards informing local strategic decision-making.

Keywords: biodiversity, GIS modeling, habitat hotspot, wildlife corridor

Procedia PDF Downloads 89