Search results for: special style and features

Authors: Bohuslava Juhasova, Igor Halenar, Martin Juhas

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The wireless communication is one of the widely used methods of data transfer at the present days. The benefit of this communication method is the partial independence of the infrastructure and the possibility of mobility. In some special applications it is the only way how to connect. This paper presents some problems in the implementation of a sensor network connection for measuring environmental parameters in the area of manufacturing plants.

Keywords: network, communication, reliability, sensors

Procedia PDF Downloads 646

Authors: Engin Eroğlu, Oktay Yıldız, Necmi Aksoy, Akif Keten, Mehmet Kıvanç Ak, Şeref Keskin, Elif Atmaca, Sertaç Kaya

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Nowadays, green spaces in urban areas are under threat and decreasing their percentages in the urban areas because of increasing population, urbanization, migration, and some cultural changes in quality. An important element of the natural landscape water and water-related natural ecosystems are exposed to corruption due to these pressures. A landscape has owned many different types of elements or units, a more dominant structure than other landscapes as good or bad perceptible extent different direction and variable reveals a unique structure and character of the landscape. Whereas landscapes deal with two main groups as urban and rural according to their location on the world, especially intersection areas of urban and rural named semi-urban or semi-rural present variety landscape features. The main components of the landscape are defined as patch-matrix-corridor. The corridors include quite various vegetation types such as riparian, wetland and the others. In urban areas, natural water corridors are an important elements of the diversity of the riparian vegetation cover. In particular, water corridors attract attention with a natural diversity and lack of fragmentation, degradation and artificial results. Thanks to these features, without a doubt, water corridors are the important component of all cities in the world. These corridors not only divide the city into two separate sides, but also assured the ecological connectivity between the two sides of the city. The main objective of this study is to determine the vegetation and habitat features of urban stream corridor according to environmental interactions. Within this context, this study will be realized that 'Asar Suyu' is an important component of the city of Düzce. Moreover, the riparian zone touched contiguous area borders of the city and overlaid the urban development limits of the city, determining of characteristics of the corridor will be carried out as floristic and habitat analysis. Consequently, vegetation structure and habitat features which play an important role between riparian zone vegetation covers and environmental interaction will be determined. This study includes first results of The Scientific and Technological Research Council of Turkey (TUBITAK-116O596; 'Determining of Landscape Character of Urban Water Corridors as Visual and Ecological; A Case Study of Asar Suyu in Duzce').

Keywords: corridor, Duzce, landscape ecology, riparian vegetation

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Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo

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SMPL-X was a powerful parametric human body model that included male, neutral, and female models, with significant gender differences between these three models. During the process of 3D human body reconstruction, the correct selection of standard templates was crucial for obtaining accurate results. To address this issue, we developed an efficient gender classification algorithm to automatically select the appropriate template for 3D human body reconstruction. The key to this gender classification algorithm was the precise analysis of human body features. By using the SMPL-X model, the algorithm could detect and identify gender features of the human body, thereby determining which standard template should be used. The accuracy of this algorithm made the 3D reconstruction process more accurate and reliable, as it could adjust model parameters based on individual gender differences. SMPL-X and the related gender classification algorithm have brought important advancements to the field of 3D human body reconstruction. By accurately selecting standard templates, they have improved the accuracy of reconstruction and have broad potential in various application fields. These technologies continue to drive the development of the 3D reconstruction field, providing us with more realistic and accurate human body models.

Keywords: gender classification, joint detection, SMPL-X, 3D reconstruction

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Authors: Kavita Goel, Donald Winchester

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In a world of information overload and work complexities, academics often struggle to create an online instructional environment enabling efficient and effective student learning. Research has established that students’ learning styles are different, some learn faster when taught using audio and visual methods. Attributes like prior knowledge and mental effort affect their learning. ‘Cognitive load theory’, opines learners have limited processing capacity. Cognitive load depends on the learner’s prior knowledge, the complexity of content and tasks, and instructional environment. Hence, the proper allocation of cognitive resources is critical for students’ learning. Consequently, a lecturer needs to understand the limits and strengths of the human learning processes, various learning styles of students, and accommodate these requirements while designing online assessments. As acknowledged in the cognitive load theory literature, visual and auditory explanations of worked examples potentially lead to a reduction of cognitive load (effort) and increased facilitation of learning when compared to conventional sequential text problem solving. This will help learner to utilize both subcomponents of their working memory. Instructional design changes were introduced at the case site for the delivery of the postgraduate business subjects. To make effective use of auditory and visual modalities, video recorded lectures, and key concept webinars were delivered to students. Videos were prepared to free up student limited working memory from irrelevant mental effort as all elements in a visual screening can be viewed simultaneously, processed quickly, and facilitates greater psychological processing efficiency. Most case study students in the postgraduate programs are adults, working full-time at higher management levels, and studying part-time. Their learning style and needs are different from other tertiary students. The purpose of the audio and visual interventions was to lower the students cognitive load and provide an online environment supportive to their efficient learning. These changes were expected to impact the student’s learning experience, their academic performance and retention favourably. This paper posits that these changes to instruction design facilitates students to integrate new knowledge into their long-term memory. A mixed methods case study methodology was used in this investigation. Primary data were collected from interviews and survey(s) of students and academics. Secondary data were collected from the organisation’s databases and reports. Some evidence was found that the academic performance of students does improve when new instructional design changes are introduced although not statistically significant. However, the overall grade distribution of student’s academic performance has changed and skewed higher which shows deeper understanding of the content. It was identified from feedback received from students that recorded webinars served as better learning aids than material with text alone, especially with more complex content. The recorded webinars on the subject content and assessments provides flexibility to students to access this material any time from repositories, many times, and this enhances students learning style. Visual and audio information enters student’s working memory more effectively. Also as each assessment included the application of the concepts, conceptual knowledge interacted with the pre-existing schema in the long-term memory and lowered student’s cognitive load.

Keywords: cognitive load theory, learning style, instructional environment, working memory

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Authors: Shishay T. Kidanu

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The study area is located in Southwestern Missouri and is mainly underlain by Mississippian Age limestone which is highly susceptible to karst processes. The area is known for the presence of various karst features like caves, springs and more importantly Sinkholes. Sinkholes are one of the most common karst features and the primary hazard in karst areas. Investigating the subsurface structure and development mechanism of existing sinkholes enables to understand their long-term impact and chance of reactivation and also helps to provide effective mitigation measures. In this study ERT (Electrical Resistivity Tomography), MASW (Multichannel Analysis of Surface Waves) and borehole control data have been used to image the subsurface structure and investigate the development mechanism of a sinkhole in Southwestern Missouri. The study shows that the main process responsible for the development of the sinkhole is the downward piping of fine grained soils. Furthermore, the study reveals that the sinkhole developed along a north-south oriented vertical joint set characterized by a vertical zone of water seepage and associated fine grained soil piping into preexisting fractures.

Keywords: ERT, Karst, MASW, sinkhole

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Aminur Rahman

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The Unique feature of BROTHERS Furniture sofa stands in ergonomic Design, skilled hand work and art work. Present world market is passing through a contentious competitive situation that is rapidly and dramatic. Competitive strategy concerns how to create competitive advantage in upholstery businesses. In order to competitive advantage in upholstery sofa market, Design and develop a sofa that have to ergonomic features. Design an ergonomic upholstery sofa knowing and understanding the appropriate seat depth, seat height, angle between Seat & back, back height which is concurrent market demand, world class sofa has to incorporate ergonomic factors. The study the relationships between human, seat and context variables comfort and discomfort. We must have conduct market survey among users whose are need and use sofa. Health & safety factors should be examined from a variety of angle. An attractive design and meet customer requirements, ergonomically fit should be considered for sofa development. This paper will explain how to design & develop sofa’s as per standard specifications which have ergonomic features for users all over the world.

Keywords: ergonomics, angle between seat & back, standard dimension, seat comfort

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: Aistis ZekevicIus

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Biopolitical theory, which was first developed by Michel Foucault, takes into consideration the administration of life by implying a style of government based on the regulation of populations as its subject. The intensification of the #BlackLivesMatter movement and popular outcries against racial discrimination in the US health system have prompted us to reconsider the relationship between biopolitics and race in the face of the COVID-19 pandemic. Based on works by Foucault, Achille Mbembe and Nicholas Mirzoeff that transcend the boundaries of poststructuralism, critical theory and postcolonial studies, the paper suggests that the global pandemic has highlighted new aspects of the interplay between biopower and race by encouraging the search for scapegoats, deepening the structural racial inequality, and thus producing necropolitical regimes of exclusion.

Keywords: biopolitics, biopower, necropolitics, pandemic, race

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Authors: Celine Jaspers

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The Belgian legal system is slowly evolving to mandatory mediation to promote ADR. One of the reasons for this evolution is the lack of use of alternative methods in relation to their possible benefits. Especially in divorce cases, ADR can play a beneficial role in resolving disputes, since the emotional component is very much present. When children are involved, a solution provided by the parent may be more adapted to the child’s best interest than a court order. In the first part, the lack of use of voluntary ADR and the evolution toward mandatory ADR in Belgium will be indicated by sources of legislation, jurisprudence and social-scientific sources, with special attention to divorce cases. One of the reasons is lack of knowledge on ADR, despite the continuing efforts of the Belgian legislator to promote ADR. One of the last acts of ADR-promotion, was the implementation of an Act in 2018 which gives the judge the possibility to refer parties to mediation if at least one party wants to during the judicial procedure. This referral is subject to some conditions. The parties will be sent to a private mediator, recognized by the Federal Mediation Commission, to try to resolve their conflict. This means that at least one party can be mandated to try mediation (indicated as “semi-mandatory mediation”). The main goal is to establish the factors and elements that Belgium has to take into account in their further development of mandatory ADR, with consideration of the human rights perspective and the EU perspective. Furthermore it is also essential to detect some dangerous pitfalls other systems have encountered with their process design. Therefore, the second part, the comparative component, will discuss the existing framework in California, USA to establish the necessary elements, possible pitfalls and considerations the Belgian legislator can take into account when further developing the framework of mandatory ADR. The contrasting and functional method will be used to create key elements and possible pitfalls, to help Belgium improve its existing framework. The existing mandatory system in California has been in place since 1981 and is still up and running, and can thus provide valuable lessons and considerations for the Belgian system. Thirdly, the key elements from a human rights perspective and from a European Union perspective (e.g. the right to access to a judge, the right to privacy) will be discussed too, since the basic human rights and European legislation and jurisprudence play a significant part in Belgian legislation as well. The main sources for this part will be the international and European treaties, legislation, jurisprudence and soft law. In the last and concluding part, the paper will list the most important elements of a mandatory ADR-system design with special attention to the dangers of these elements (e.g. to include or exclude domestic violence cases in the mandatory ADR-framework and the consequences thereof), and with special attention for the necessary the international and European rights, prohibitions and guidelines.

Keywords: Belgium, divorce, framework, mandatory ADR

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Authors: Thuy Hanh Nguyen Thi

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By the method of deep reading and text analysis, this article will analyze the use and creation of dialects as a way of demonstrating Yan Lianke's creative stance. This article indicates that this is the writer’s narrative strategy in a fight against aphasia, a language disorder of Chinese people and culture, demonstrating a sense of return to folklore and marks his own linguistic style. In terms of verbal text, the dialect in the Yan Lianke’s novels manifested through the use of words, sentences and dialects. There are two types of dialects that exist in Yan Lianke’s novels: the current dialect system and the particular dialect system of Pa Lau world created by the writer himself in order to enrich the vocabulary of Han Chinese.

Keywords: Yan Lianke , aphasia, dialect, Pa Lou world

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Authors: Brian Tung, Yam Wing Siu, Tsun Se Cheong

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Purpose: This research aims to explore how personal and environmental factors, especially the socio-economic changes and behavioral changes fostered by the COVID-19 outbreak pandemic, affect the financial vulnerability of a specific segment of people in financial distress. Innovative research methodology of machine learning will be applied to data collected from over 300 local individuals in Hong Kong seeking counseling or similar services in recent years. Results: First, machine learning has found that too much exposure to digital services and information on digitized services may lead to adverse effects on respondents’ financial vulnerability. Second, the improvement in financial literacy level provides benefits to the financially vulnerable group, especially those respondents who have started with a lower level. Third, serious addiction to digital technology can lead to worsened debt servicing ability. Machine learning also has found a strong correlation between debt servicing situations and income-seeking behavior as well as spending behavior. In addition, if the vulnerable groups are able to make appropriate investments, they can reduce the probability of incurring financial distress. Finally, being too active in borrowing and repayment can result in a higher likelihood of over-indebtedness. Conclusion: Findings can be employed in formulating a better counseling strategy for professionals. Debt counseling services can be more preventive in nature. For example, according to the findings, with a low level of financial literacy, the respondents are prone to overspending and unable to react properly to the e-marketing promotion messages pop-up from digital services or even falling into financial/investment scams. In addition, people with low levels of financial knowledge will benefit from financial education. Therefore, financial education programs could include tech-savvy matters as special features.

Keywords: personal finance, digitization of the economy, COVID-19 pandemic, addiction to digital technology, financial vulnerability

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Authors: Roberta Gentry

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A mixed methods study that examined candidate’s perceptions of the use of computerized simulation as an effective tool to learn classroom management will be presented. The development, implementation, and assessment of the simulation and candidate data on the feasibility of the approach in comparison to other methods will be presented.

Keywords: behavior management, simulations, teacher preparation, teacher education

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Authors: Cita Ayeni

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Following countless violations of Human Rights in Nigeria by the various arms and agencies of government; from the Military to the Federal Police and other law enforcement agencies, Nigeria has been riddled with several reports of acts by these agencies against the citizens, ranging from illegal arrest and imprisonment, torture, disappearing, and extrajudicial killings, just to mention a few. This paper, focuses on SARS (Special Anti-Robbery Squad), a division of the Nigeria Police Force, and its reported threats to the people’s security, particularly the Nigerian youths, with continuous violence, extortion, illegal arrest and imprisonment, terror, and extrajudicial activities resulting in maiming and in most cases death, thus infringing on the human rights of the people it’s sworn to protect. This research further analyses how the activities of SARS has over the years instigated fear on the average Nigerian youth, preventing the free participation in daily life, education, job, and individual development, in turn impeding the realization of their full potentials for growth and participation in collective national development. This research analyzes the executive order by the then Acting President (Vice-President) of Nigeria, directing the overhauling of SARS, and its implementation by the Federal Police Force in determining if it’s enough to prevent or put a stop to the continuous Human Rights abuse and threat to the security of the individual citizen. Concluding that although the order by the Acting President was given with an intent to halt the various violations by SARS, and the Inspector General of Police’s (IGP) subsequent action by releasing a statement following the order, the bureaucracy in Nigeria, with a history of incompetency and a return to 'business as usual' after a reduced public outcry, it’s most likely that there will not be adequate follow up put in place and these violations would be slowly 'swept under the rug' with SARS officials not held accountable. It is recommended therefore that the Federal Government through the NPF, following the reforms made, in collaboration with the mentioned Independent Human Rights and civil societies organizations should periodically produce unbiased and publicly accessible reports on the implementation of these reforms and progress made. This will go a long way in assuring the public of actual fulfillment of the restructuring, reduce fear by the youths and restore some public faith in the government.

Keywords: special anti-robbery squad, youths in Nigeria, overhaul, insecurities, human rights violations

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Authors: Tawfik Thelaidjia, Salah Chenikher

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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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Authors: Shutchapol Chopvitayakun

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Internship program is a compulsory course of many undergraduate programs in Thailand. It gives opportunities to a lot of senior students as interns to practice their working skills in the real organizations and also gives chances for interns to face real-world working problems. Interns also learn how to solve those problems by direct and indirect experiences. This program in many schools is a well-structured course with a contract or agreement made with real business organizations. Moreover, this program also offers opportunities for interns to get jobs after completing it from where the internship program takes place. Interns also learn how to work as a team and how to associate with other colleagues, trainers, and superiors of each organization in term of social hierarchy, self-responsibility, and self-disciplinary. This research focuses on senior students of Suan Sunandha Rajabhat University, Thailand whose studying major is information technology program. They practiced their working skills or took internship programs in the real business sector or real operating organizations in 2015-2016. Interns are categorized in to two types: normal program and special program. For special program, students study in weekday evening from Monday to Friday or Weekend and most of them work full-time or part-time job. For normal program, students study in weekday working hours and most of them do not work. The differences of these characters and the outcomes of internship performance were studied and analyzed in this research. This work applied some statistical analytics to find out whether the internship performance of each intern type has different performances statistically or not.

Keywords: internship, intern, senior student, information technology program

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Authors: Rajkumar Ghosh

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The study focuses on the tectonics of out-of-sequence thrusting (OOST) in the NW region of the Himalaya, particularly in Himachal Pradesh. The research aims to identify the features and nature of OOST in the field and the associated rock types and lithological boundaries in the field of NW Himalaya, Himachal Pradesh, India. The research employs fieldwork and micro-structure observations, correlations, and analyses to identify and analyze the OOST features and associated rock types. The study reveals the presence of three OOSTs, namely Jhakri Thrust (JT), Sarahan Thrust (ST), and Chaura Thrust (CT), which consist of several branches, some of which are still active. The thrust system exhibits varying internal geometry, including box folds, boudins, scar folds, crenulation cleavages, kink folds, and tension gashes. The CT, which is concealed beneath Jutogh Thrust sheet, represents a steepened downward thrust, while the JT has a western dip and is south-westward verging. The research provides crucial information on the tectonics of OOST in the NW region of the Himalaya, particularly in Himachal Pradesh, which is crucial in understanding the regional geological evolution and associated hazards. The data were collected through fieldwork and micro-structure observations, correlations, and analyses of rock samples. The data were analyzed using tectonic and geochronological techniques to identify the nature and characteristics of OOST. The research addressed the question of identifying Higher Himalayan OOST in the field of NW Himalaya, Himachal Pradesh, India, and the associated rock types and lithological boundaries. The study concludes that there is minimal documentation and a lack of suitable exposure of rocks to generalize the features of OOST in the field in NW Higher Himalaya, Himachal Pradesh. The study recommends more extensive mapping and fieldwork to improve understanding of OOST in the region.

Keywords: out-of-sequence thrust (OOST), main central thrust (MCT), jhakri thrust (JT), sarahan thrust (ST), chaura thrust (CT), higher himalaya (HH)

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Zhihui Liu, Dongmei Hao, Qian Qiu, Yang An, Lin Yang, Song Zhang, Yimin Yang, Xuwen Li, Dingchang Zheng

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Premature birth, defined as birth before 37 completed weeks of gestation is a leading cause of neonatal morbidity and mortality and has long-term adverse consequences for health. It has recently been reported that the worldwide preterm birth rate is around 10%. The existing measurement techniques for diagnosing preterm delivery include tocodynamometer, ultrasound and fetal fibronectin. However, they are subjective, or suffer from high measurement variability and inaccurate diagnosis and prediction of preterm labor. Electrohysterography (EHG) method based on recording of uterine electrical activity by electrodes attached to maternal abdomen, is a promising method to assess uterine activity and diagnose preterm labor. The purpose of this study is to analyze the difference of EHG signal features between term labor and preterm labor. Free access database was used with 300 signals acquired in two groups of pregnant women who delivered at term (262 cases) and preterm (38 cases). Among them, EHG signals from 38 term labor and 38 preterm labor were preprocessed with band-pass Butterworth filters of 0.08–4Hz. Then, EHG signal features were extracted, which comprised classical time domain description including root mean square and zero-crossing number, spectral parameters including peak frequency, mean frequency and median frequency, wavelet packet coefficients, autoregression (AR) model coefficients, and nonlinear measures including maximal Lyapunov exponent, sample entropy and correlation dimension. Their statistical significance for recognition of two groups of recordings was provided. The results showed that mean frequency of preterm labor was significantly smaller than term labor (p < 0.05). 5 coefficients of AR model showed significant difference between term labor and preterm labor. The maximal Lyapunov exponent of early preterm (time of recording < the 26th week of gestation) was significantly smaller than early term. The sample entropy of late preterm (time of recording > the 26th week of gestation) was significantly smaller than late term. There was no significant difference for other features between the term labor and preterm labor groups. Any future work regarding classification should therefore focus on using multiple techniques, with the mean frequency, AR coefficients, maximal Lyapunov exponent and the sample entropy being among the prime candidates. Even if these methods are not yet useful for clinical practice, they do bring the most promising indicators for the preterm labor.

Keywords: electrohysterogram, feature, preterm labor, term labor

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Authors: Joseph Uzuazomaro Oju

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The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

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Authors: Raghad Dwaik

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It is well known in language acquisition literature that a mere understanding of a reading text is not enough to help students build proficiency in comprehension. Students should rather follow understanding by attempting to express what has been understood by pushing their competence to the limit. Learners' attempt to push their competence was given the term "comprehensible output" by Swain (1985). Teachers in large classes, however, find it sometimes difficult to give all students a chance to communicate their views or to share their ideas during the short class time. In most cases, students who are outgoing dominate class discussion and get more opportunities for practice which leads to ignoring the shy students totally while helping the good ones become better. This paper presents the idea of using Google Classroom features of posting and commenting to allow students who hesitate to participate in class discussions about a reading text to write their views on the wall of a Google Classroom and share them later after they have received feedback and comments from classmates. Such attempts lead to developing their proficiency through additional practice in comprehensible output and to enhancing their confidence in themselves and their views. It was found that virtual classroom interaction would help students maintain vocabulary, use more complex structures and focus on meaning besides form.

Keywords: learning groups, reading TESOL, Google Classroom, comprehensible output

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Authors: Woei-Shyan Lee, Hao-Chien Kao

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The impact deformation and fracture behaviour of cobalt-based Haynes 188 superalloy are investigated by means of a split Hopkinson pressure bar. Impact tests are performed at strain rates ranging from 1×103 s-1 to 5×103 s-1 and temperatures between 25°C and 800°C. The experimental results indicate that the flow response and fracture characteristics of cobalt-based Haynes 188 superalloy are significantly dependent on the strain rate and temperature. The flow stress, work hardening rate and strain rate sensitivity all increase with increasing strain rate or decreasing temperature. It is shown that the impact response of the Haynes 188 specimens is adequately described by the Zerilli-Armstrong fcc model. The fracture analysis results indicate that the Haynes 188 specimens fail predominantly as the result of intensive localised shearing. Furthermore, it is shown that the flow localisation effect leads to the formation of adiabatic shear bands. The fracture surfaces of the deformed Haynes 188 specimens are characterised by dimple- and / or cleavage-like structure with knobby features. The knobby features are thought to be the result of a rise in the local temperature to a value greater than the melting point.

Keywords: Haynes 188 alloy, impact, strain rate and temperature effect, adiabatic shearing

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Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

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Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

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Authors: Veronica Onyemauwa

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This research work examines the socio-ethical issues embedded in resource management and wealth creation in Nigeria, using Akwa Ibom State as a case study. The work is poised to proffer answers to the problematic questions raised, “why is the wealth of Akwa Ibom State not prudently managed, and wastages curbed in order to cater for the satisfaction of the indigent citizens, as Jesus Christ did in the feeding of five thousand people (John 6:12) ? Could ethical and responsible resource management not solve the paradox of poverty stricken people of Akwa Ibom in a rich economy? What ought to be done to better the lot of Akwa Ibomites? The research adopts phenomenological and sociological research methodology with primary and secondary sources of information to explore the socio-ethical issues embedded in resource management and wealth creation in Akwa Ibom State. Findings revealed that, reckless exploitation and mismanagement of the rich natural and human resources of Akwa Ibom State have spelt doom to the economic progress and survival of Akwa Ibomites in particular and Nigerians in general. Hence, hunger and poverty remain adversaries to majority of the people. Again, the culture of diversion of funds and squandermania institutionalized within the confine of Akwa Ibom State government, deter investment in economic enterprises, job and wealth creation that would have yielded economic dividends for Akwa Ibomites. These and many other unwholesome practices are responsible for the present deplorable condition of Akwa Ibom State in particular and Nigerian society in general. As a way out of this economic quagmire, it is imperative that, every unwholesome practice within the State be tackled more proactively and innovatively in the interest of the masses through responsible resource management and wealth creation. It is believed that, an effective leadership, a statesman with vision and commitment would transform the abundant resources to achieve meaningful development, create wealth and reduce poverty. Ethical leadership is required in all the tiers of government and public organizations to transform resources into more wealth. Thus, this paper advocates for ethics of virtue: a paradigm shift from exploitative leadership style to productive leadership style; change from atomistic human relation to corporative human relation; change from being subsistence to abundant in other to maximize the available resources in the State. To do otherwise is unethical and lack moral justification.

Keywords: corrective, mismanagement, resources, virtue ethics

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Authors: Sergio Alejandro Cuevas, Catherine Etchebest, Fernando Luis Barroso Da Silva

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The flavivirus genus has several organisms responsible for generating various diseases in humans. Special in Brazil, Zika (ZIKV), Dengue (DENV) and Yellow Fever (YFV) viruses have raised great health concerns due to the high number of cases affecting the area during the last years. Diagnostic is still a difficult issue since the clinical symptoms are highly similar. The understanding of their common structural/dynamical and biomolecular interactions features and differences might suggest alternative strategies towards differential serological diagnostics and therapeutic intervention. Due to their immunogenicity, the primary focus of this study was on the ZIKV, DENV and YFV non-structural proteins 1 (NS1) protein. By means of computational studies, we calculated the main physical chemical properties of this protein from different strains that are directly responsible for the biomolecular interactions and, therefore, can be related to the differential infectivity of the strains. We also mapped the electrostatic differences at both the sequence and structural levels for the strains from Uganda to Brazil that could suggest possible molecular mechanisms for the increase of the virulence of ZIKV. It is interesting to note that despite the small changes in the protein sequence due to the high sequence identity among the studied strains, the electrostatic properties are strongly impacted by the pH which also impact on their biomolecular interactions with partners and, consequently, the molecular viral biology. African and Asian strains are distinguishable. Exploring the interfaces used by NS1 to self-associate in different oligomeric states, and to interact with membranes and the antibody, we could map the strategy used by the ZIKV during its evolutionary process. This indicates possible molecular mechanisms that can explain the different immunological response. By the comparison with the known antibody structure available for the West Nile virus, we demonstrated that the antibody would have difficulties to neutralize the NS1 from the Brazilian strain. The present study also opens up perspectives to computationally design high specificity antibodies.

Keywords: zika, biomolecular interactions, electrostatic interactions, molecular mechanisms

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Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

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We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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Authors: Anna D. Kotrova, Alexandr N. Shishkin, Elena I. Ermolenko

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The aim. To study the quantitative and qualitative colon bacteria ratio from patients with metabolic syndrome. Materials and methods. Fecal samples from patients of 2 groups were identified and analyzed: the first group was formed by patients with metabolic syndrome, the second one - by healthy individuals. The metagenomics method was used with the analysis of 16S rRNA gene sequences. The libraries of the variable sites (V3 and V4) gene 16S RNA were analyzed using the MiSeq device (Illumina). To prepare the libraries was used the standard recommended by Illumina, a method based on two rounds of PCR. Results. At the phylum level in the microbiota of patients with metabolic syndrome compared to healthy individuals, the proportion of Tenericutes was reduced, the proportion of Actinobacteria was increased. At the genus level, in the group with metabolic syndrome, relative to the second group was increased the proportion of Lachnospira. Conclusion. Changes in the colon bacteria ratio in the gut microbiota of patients with metabolic syndrome were found both at the type and the genus level. In the metabolic syndrome group, there is a decrease in the proportion of bacteria that do not have a cell wall. To confirm the revealed microbiota features in patients with metabolic syndrome, further study with a larger number of samples is required.

Keywords: gut microbiota, metabolic syndrome, metagenomics, tenericutes

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Authors: Mirko Klaric

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In different countries, sub-municipal units have different organizational and political positions. In some countries, the role of sub-municipal units is important; in others, it is marginal. That depends on the organization of the local government system in different countries, and the political role of local self-government units, their size, public authorities, and the possibility for managing various local public tasks. This paper attempts to analyze the sub-municipal government as an organizational form of local governance participation of citizens in the local community with a comparative perspective. Secondly, it presents elements that generally format sub-municipal government as a tool for strengthening of democratization processes in local government units. Those elements are crucial for the understanding of the dynamic in relation to local government vs. sub-municipal government. Special focus is put on the sub-municipal government in South-Eastern European countries, which have a common history and institutional framework, with this main question: how can sub-municipal government contribute to strengthening democratic processes in these countries. In centralized countries, the sub-municipal government usually has a reduced role, which relates to managing public tasks connected with local community needs. The purpose of this comparative research methodology is used for analyzing the present organization and role of sub-municipal government in local government systems in Croatia and other significant countries in Europe, with a special focus on the states in South-Eastern Europe and Croatia. Comparative analyses attempt to show that local government systems with bigger local government units have more significant sub-municipal government. On the other hand, local government systems with small local government units don’t have a strong sub-municipal government. Finally, this paper aims to present ideas on how the sub-municipal government can improve decentralization and contribute to better development of the local community and the whole of society.

Keywords: public administration, local government, sub-municipal government, decentralization

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Authors: Qasim A. El Dwairi, Saleh M. Banihani, Ayat S. Banihani, Ziad M. Bataineh

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Neurons in the spinal trigeminal nucleus of the camel were studied by Golgi impregnation. Neurons were classified based on differences in size and shape of their cell bodies, density of their dendritic trees, morphology and distribution of their appendages. In the spinal trigeminal nucleus of the camel, at least twelve types of neurons were identified. These neurons include, stalked, islets, octubus-like, lobulated, boat-like, pyramidal, multipolar, round, oval and elongated neurons. They have large number of different forms of appendages not only for their dendrites but also for their cell bodies. Neurons with unique large dilatations especially at their dendritic branching points were found. The morphological features of these neurons were described and compared with their counterparts in other species. Finding of large number of neuronal types with different size and shapes and large number of different forms of appendages for cell bodies and dendrites together with the presence of cells with unique features such as large dilated parts for dendrites may indicate to a very complex information processing for pain and temperature at the level of the spinal trigeminal nucleus in the camel that traditionally live in a very hard environment (the desert).

Keywords: camel, golgi, neurons , spinal trigeminal nucleus

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Authors: Isobel Hambleton, Mark Carrington

Abstract:

Trypanosoma brucei, the causal agent of a range of diseases in humans and livestock, evades the mammalian immune system through a population survival strategy based on the expression of a series of antigenically distinct variant surface glycoproteins (VSGs). RNAi mediated knockdown of the active VSG gene triggers a precytokinesis cell cycle arrest. To determine whether this phenotype is the result of reduced VSG transcript or depleted VSG protein, we used morpholino antisense oligonucleotides to block translation of VSG mRNA. The same precytokinesis cell cycle arrest was observed, suggesting that VSG protein abundance is monitored closely throughout the cell cycle. An inducible expression system has been developed to test various GPI-anchored proteins for their ability to rescue this cell cycle arrest. This system has been used to demonstrate that wild-type VSG expressed from a T7 promoter rescues this phenotype. This indicates that VSG expression from one of the specialised bloodstream expression sites (BES) is not essential for cell division. The same approach has been used to define the minimum essential features of a VSG necessary for function.

Keywords: bloodstream expression site, morpholino, precytokinesis cell cycle arrest, variant surface glycoprotein

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