Search results for: regional features
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5436

Search results for: regional features

4506 Delineation of Subsurface Tectonic Structures Using Gravity, Magnetic and Geological Data, in the Sarir-Hameimat Arm of the Sirt Basin, NE Libya

Authors: Mohamed Abdalla Saleem, Hana Ellafi

Abstract:

The study area is located in the eastern part of the Sirt Basin, in the Sarir-Hameimat arm of the basin, south of Amal High. The area covers the northern part of the Hamemat Trough and the Rakb High. All of these tectonic elements are part of the major and common tectonics that were created when the old Sirt Arch collapsed, and most of them are trending NW-SE. This study has been conducted to investigate the subsurface structures and the sedimentology characterization of the area and attempt to define its development tectonically and stratigraphically. About 7600 land gravity measurements, 22500 gridded magnetic data, and petrographic core data from some wells were used to investigate the subsurface structural features both vertically and laterally. A third-order separation of the regional trends from the original Bouguer gravity data has been chosen. The residual gravity map reveals a significant number of high anomalies distributed in the area, separated by a group of thick sediment centers. The reduction to the pole magnetic map also shows nearly the same major trends and anomalies in the area. Applying the further interpretation filters reveals that these high anomalies are sourced from different depth levels; some are deep-rooted, and others are intruded igneous bodies within the sediment layers. The petrographic sedimentology study for some wells in the area confirmed the presence of these igneous bodies and defined their composition as most likely to be gabbro hosted by marine shale layers. Depth investigation of these anomalies by the average depth spectrum shows that the average basement depth is about 7.7 km, while the top of the intrusions is about 2.65 km, and some near-surface magnetic sources are about 1.86 km. The depth values of the magnetic anomalies and their location were estimated specifically using the 3D Euler deconvolution technique. The obtained results suggest that the maximum depth of the sources is about 4938m. The total horizontal gradient of the magnetic data shows that the trends are mostly extending NW-SE, others are NE-SW, and a third group has an N-S extension. This variety in trend direction shows that the area experienced different tectonic regimes throughout its geological history.

Keywords: sirt basin, tectonics, gravity, magnetic

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4505 Aeromagnetic Data Interpretation and Source Body Evaluation Using Standard Euler Deconvolution Technique in Obudu Area, Southeastern Nigeria

Authors: Chidiebere C. Agoha, Chukwuebuka N. Onwubuariri, Collins U.amasike, Tochukwu I. Mgbeojedo, Joy O. Njoku, Lawson J. Osaki, Ifeyinwa J. Ofoh, Francis B. Akiang, Dominic N. Anuforo

Abstract:

In order to interpret the airborne magnetic data and evaluate the approximate location, depth, and geometry of the magnetic sources within Obudu area using the standard Euler deconvolution method, very high-resolution aeromagnetic data over the area was acquired, processed digitally and analyzed using Oasis Montaj 8.5 software. Data analysis and enhancement techniques, including reduction to the equator, horizontal derivative, first and second vertical derivatives, upward continuation and regional-residual separation, were carried out for the purpose of detailed data Interpretation. Standard Euler deconvolution for structural indices of 0, 1, 2, and 3 was also carried out and respective maps were obtained using the Euler deconvolution algorithm. Results show that the total magnetic intensity ranges from -122.9nT to 147.0nT, regional intensity varies between -106.9nT to 137.0nT, while residual intensity ranges between -51.5nT to 44.9nT clearly indicating the masking effect of deep-seated structures over surface and shallow subsurface magnetic materials. Results also indicated that the positive residual anomalies have an NE-SW orientation, which coincides with the trend of major geologic structures in the area. Euler deconvolution for all the considered structural indices has depth to magnetic sources ranging from the surface to more than 2000m. Interpretation of the various structural indices revealed the locations and depths of the source bodies and the existence of geologic models, including sills, dykes, pipes, and spherical structures. This area is characterized by intrusive and very shallow basement materials and represents an excellent prospect for solid mineral exploration and development.

Keywords: Euler deconvolution, horizontal derivative, Obudu, structural indices

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4504 Analyzing the Impacts of Sustainable Tourism Development on Residents’ Well-Being Based on Stakeholder Perception: Evidence from a Coastal-Hinterland Region

Authors: Elham Falatoonitoosi, Vikki Schaffer, Don Kerr

Abstract:

Over-development for tourism and its consequences on residents’ well-being turn into a critical issue in tourism destinations. Learning about undesirable impacts of tourism has led many people to seek more sustainable and responsible tourism. The main objective of this research is to understand how and to what extent sustainable tourism development enhances locals’ well-being regarding stakeholder perception. The research was conducted in a coastal-hinterland tourism region through two sequential phases. At the first phase, a unique set of 19 sustainable tourism indicators resulted from a triplex model was used to examine the sustainability effects on the main factors of residents’ well-being including equity and living condition, life satisfaction, health condition, and education quality. The triplex model including i) systematic literature search, ii) convergent interviewing, and iii) DEMATEL aimed to develop sustainability indicators, specify them for a particular destination, and identify the dominant sustainability issues acting as key predictors in sustainable development. At the second phase, a hierarchical multiple regression was used to examine the relationship between sustainable development and local residents’ well-being. A number of 167 participants from five different groups of stakeholders perceived the importance level of each sustainability indicators regarding well-being factors on 5-point Likert scale. Results from the first phase indicated that sustainability training, government support, tourism sociocultural effects, tourism revenue, and climate change are the top dominant sustainability issues in the regional sustainable development. Results from the second phase showed that sustainable development considerably improves the overall residents’ well-being and has positive relationships with all well-being factors except life satisfaction. It explains that it was difficult for stakeholders to recognize a link between sustainable development and their overall life satisfaction and happiness. Among well-being’s factors, health condition was influenced the most by sustainability indicators that indicate stakeholders believed sustainability development can promote public health, health sector performance, quality of drinking water, and sanitation. For the future research, it is highly recommended to analysis the effects of sustainable tourism development on the other features of a tourism destination’s well-being including residents sociocultural empowerment, local economic growth, and attractiveness of the destination.

Keywords: residents' well-being, stakeholder perception, sustainability indicators, sustainable tourism

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4503 Environmental Interactions in Riparian Vegetation Cover in an Urban Stream Corridor: A Case Study of Duzce Asar Suyu

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

Abstract:

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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4502 3D Reconstruction of Human Body Based on Gender Classification

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

Abstract:

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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4501 Application of Electrical Resistivity Tomography to Image the Subsurface Structure of a Sinkhole, a Case Study in Southwestern Missouri

Authors: Shishay T. Kidanu

Abstract:

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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4500 Intelligent Rheumatoid Arthritis Identification System Based Image Processing and Neural Classifier

Authors: Abdulkader Helwan

Abstract:

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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4499 BROTHERS: World-class Ergonomic Sofa Development

Authors: Aminur Rahman

Abstract:

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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4498 Early Detection of Breast Cancer in Digital Mammograms Based on Image Processing and Artificial Intelligence

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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4497 Trends of Municipal Council Members in Practicing His Role on Municipality's Main Municipal Activities in the Kingdom of Saudi Arabia

Authors: Ameer Alalwan

Abstract:

Summary: The aim of this research is to identify trends of municipal council member in practicing his administrative control, decision-making, and counsultive role on municipalities' main municipal activities in the kingdom of Saudi Arabia. This research is conducted after the implementation of the new municipal system resolution no. (M\61) in 1435 in the work of municipal councils for the third session. To achieve the goal of this research, a questionnaire has been designed to obtain the opinion of municipal councils on this matter. This questionnaire has been tested for reliability and validity. The results of this research show that in general performance of municipal council is moderate after the implementation of the new municipal system resolution no. (M\61) in 1435 in the work of municipal councils for the third session. Also, extend that municipal council member practice his roles on the main municipality activities is moderate and weak. In addition, results show that municipal council member practice big role in decision-making, and moderate role in administrative control, and weaker role in giving opinion on municipality main issues. Furthermore, the results show that there is a significant difference between municipal council member's responses by the change of their Personal characteristics. Educated and appointed municipal council members practicing their role more than others do. In addition, municipal council presidents, and vice presidents, and in regional and sub-regional municipalities practice their role more than others do. Finally, this research in general recommened that muincialty council member must be empowered, so that he can practice his role on muicipality main activities. In addition, research suggest, granting municipal council member the authority, resources needed, training and appointment of qualified members, so that they will be able to practice their roles. Furthermore, this research suggest for the time being maintain certain percent of municipal council's appointed until this experience mature in the kingdom.

Keywords: municipal council, municipal council member, municipality, decision-making role

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4496 Water Security and Transboundary Issues for Food Security of Ethiopia. The Case of Nile River

Authors: Kebron Asnake

Abstract:

Water security and transboundary issues are critical concerns for countries, particularly in regions where shared water resources are significant. This Research focuses on exploring the challenges and opportunities related to water security and transboundary issues in Ethiopia, using the case of the Nile River. Ethiopia, as a riparian country of the Nile River, faces complex water security issues due to its dependence on this transboundary water resource. This abstract aims to analyze the various factors that affect water security in Ethiopia, including population growth, climate change, and competing water demands. The Study examines the challenges linked to transboundary water management of the Nile River. It delves into the complexities of negotiating water allocations and addressing potential conflicts among the downstream riparian countries. The paper also discusses the role of international agreements and cooperation in promoting sustainable water resource management. Additionally, the paper highlights the opportunities for collaboration and sustainable development that arise from transboundary water management. It explores the potential for joint investments in water infrastructure, hydropower generation, and irrigation systems that can contribute to regional economic growth and water security. Furthermore, the study emphasizes the need for integrated water management approaches in Ethiopia to ensure the equitable and sustainable use of the Nile River's waters. It highlights the importance of involving stakeholders from diverse sectors, including agriculture, energy, and environmental conservation, in decision-making processes. By presenting the case of the Nile River in Ethiopia, this Abstract contributes to the understanding of water security and transboundary issues. It underscores the significance of regional cooperation and informed policy-making to address the challenges and opportunities presented by transboundary water resources. The paper serves as a foundation for further research and policy in water management in Ethiopia and other regions facing similar challenges.

Keywords: water, health, agriculture, medicine

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4495 Deep Learning Approaches for Accurate Detection of Epileptic Seizures from Electroencephalogram Data

Authors: Ramzi Rihane, Yassine Benayed

Abstract:

Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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4494 Regional Anesthesia: A Vantage Point for Management of Normal Pressure Hydrocephalus

Authors: Kunal K. S., Shwetashri K. R., Keerthan G., Ajinkya R.

Abstract:

Background: Normal pressure hydrocephalus is a condition caused by abnormal accumulation of cerebrospinal fluid (CSF) within the brain resulting in enlarged cerebral ventricles due to a disruption of CSF formation, absorption, or flow. Over the course of time, ventriculoperitoneal shunt under general anesthesia has become a standard of care. Yet only a finite number of centers have started the inclusion of regional anesthesia techniques for the such patient cohort. Stem Case: We report a case of a 75-year-old male with underlying aortic sclerosis and cardiomyopathy who presented with complaints of confusion, forgetfulness, and difficulty in walking. Neuro-imaging studies revealed disproportionally enlarged subarachnoid space hydrocephalus (DESH). The baseline blood pressure was 116/67 mmHg with a heart rate of 106 beats/min and SpO2 of 96% on room air. The patient underwent smooth induction followed by sonographically guided superficial cervical plexus block and transverse abdominis plane block. Intraoperative pain indices were monitored with Analgesia nociceptive index monitor (ANI, MdolorisTM) and surgical plethysmographic index (SPI, GE Healthcare, Helsinki, FinlandTM). These remained stable during the application of the block and the entire surgical duration. No significant hemodynamic response was observed during the tunneling of the skin by the surgeon. The patient underwent a smooth recovery and emergence. Conclusion: Our decision to incorporate peripheral nerve blockade in conjunction with general anesthesia resulted in opioid-sparing anesthesia and decreased post-operative analgesic requirement by the patient. This blockade was successful in suppressing intraoperative stress responses. Our patient recovered adequately and underwent an uncomplicated post-operative stay.

Keywords: desh, NPH, VP shunt, cervical plexus block, transversus abdominis plane block

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4493 A New Approach of Preprocessing with SVM Optimization Based on PSO for Bearing Fault Diagnosis

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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4492 Development of the Squamate Egg Tooth on the Basis of Grass Snake Natrix natrix Studies

Authors: Mateusz Hermyt, Pawel Kaczmarek, Weronika Rupik

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The egg tooth is a crucial structure during hatching of lizards and snakes. In contrast to birds, turtles, crocodiles, and monotremes, egg tooth of squamate reptiles is a true tooth sharing common features of structure and development with all the other teeth of vertebrates. The egg tooth; however, due to its function, exhibits structural differences in relation to regular teeth. External morphology seems to be important in the context of phylogenetic relationships within Squamata but up to date, there is scarce information concerning structure and development of the egg tooth at the submicroscopical level. In presented studies detailed analysis of the egg tooth development in grass snake has been performed with the usage of light (including fluorescent), transmission and scanning electron microscopy. Grass snake embryo’s heads have been used in our studies. Grass snake is common snake species occurring in most of Europe including Poland. The grass snake is characterized by the presence of single unpaired egg tooth (as in most squamates) in contrast to geckos and dibamids possessing paired egg teeth. Studies show changes occurring on the external morphology, tissue and cellular levels of differentiating egg tooth. The egg tooth during its development changes its curvature. Initially, faces directly downward and in the course of its differentiation, it gradually changes to rostro-ventral orientation. Additionally, it forms conical dentinal protrusions on the sides. Histological analysis showed that egg tooth development occurs in similar steps in relation to regular teeth. It undergoes initiation, bud, cap and bell morphological stages. Analyses focused on describing morphological changes in hard tissues (mainly dentin and predentin) of egg tooth and in cells which enamel organ consists of. It included: outer enamel epithelium, stratum intermedium, inner enamel epithelium, odontoblasts, and cells of dental pulp. All specimens used in the study were captured according to the Polish regulations concerning the protection of wild species. Permission was granted by the Local Ethics Commission in Katowice (41/2010; 87/2015) and the Regional Directorate for Environmental Protection in Katowice (WPN.6401.257.2015.DC).

Keywords: hatching, organogenesis, reptile, Squamata

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4491 An Event Relationship Extraction Method Incorporating Deep Feedback Recurrent Neural Network and Bidirectional Long Short-Term Memory

Authors: Yin Yuanling

Abstract:

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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4490 Comprehensive Analysis of Electrohysterography Signal Features in Term and Preterm Labor

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

Abstract:

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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4489 Soft Power Contestation in South Asia: Analyzing Bollywood and Chinese Cinema as Strategic Tools in the India-China Rivalry and Their Impact on Cultural Diplomacy and Regional Identity

Authors: Julia Mathew

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This paper explores the use of Bollywood and Chinese movies as soft power instruments within the larger context of India-China contention in South Asia. As India and China compete for influence in South Asia, they have increasingly relied on cultural diplomacy, using cinema to change perceptions, promote goodwill, and build cultural linkages. Bollywood, with its long-standing popularity and cultural resonance, has been a powerful instrument for projecting Indian ideals and identity throughout South Asia. In contrast, China has made concerted attempts in recent years to promote its own films, showing Chinese culture and values in a positive manner to offset Bollywood’s effect. This study examines the ways in which Chinese and Bollywood films influence public opinion and appeal to South Asian audiences while also supporting their respective countries’ soft power goals. To learn about this, we take a mixed-methods approach that incorporates content analysis of popular Bollywood and Chinese films released in South Asia, focussing on issues such as cultural identity, nationalism, and social values. In addition, we use sentiment analysis and surveys to map how these two cinematic traditions are received in various South Asian countries. This study takes into account government activities and cultural policies that promote each country’s cinema industry as a diplomatic instrument. The present study uses case studies from Nepal, Sri Lanka, Bangladesh, and Bhutan to demonstrate the subtle ways in which Bollywood and Chinese movies influence regional attitudes. For example, in Nepal and Bangladesh, Bollywood’s deep cultural ties have historically given India an advantage, but China’s growing economic relations and media presence have presented Chinese cinema as an alternative cultural influence. In contrast, Sri Lanka exemplifies a complicated relationship in which Bollywood’s cultural attraction is strong, but Chinese state-backed media diplomacy is making inroads, altering the cultural landscape. Due to limited cultural interchange and Bhutan’s historical alignment with India, Chinese cinema has a small presence in the country. The findings highlight cinema’s significance as a soft power tool in India and China’s regional ambitions. Bollywood’s emotional resonance and cultural familiarity have long bolstered India’s prominence, but Chinese cinema’s expansion reflects China’s desire to shift cultural narratives in its favour. This paper closes by presenting insights into the broader implications of cultural diplomacy within the India-China competition, arguing that as India and China continue to compete for influence in South Asia, film will play an increasingly crucial role in defining the soft power environment.

Keywords: soft power, China, India, Bollywood, Chinese cinema

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4488 Detecting Manipulated Media Using Deep Capsule Network

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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4487 Activation of Google Classroom Features to Engage Introvert Students in Comprehensible Output

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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4486 Impact Deformation and Fracture Behaviour of Cobalt-Based Haynes 188 Superalloy

Authors: Woei-Shyan Lee, Hao-Chien Kao

Abstract:

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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4485 DTI Connectome Changes in the Acute Phase of Aneurysmal Subarachnoid Hemorrhage Improve Outcome Classification

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

Abstract:

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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4484 Deep Learning Based-Object-classes Semantic Classification of Arabic Texts

Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

Abstract:

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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4483 Metagenomics Features of The Gut Microbiota in Metabolic Syndrome

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

Abstract:

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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4482 An Assessment on Socio-Economic Impacts of Smallholder Eucalyptus Tree Plantation in the Case of Northwest Ethiopia

Authors: Mersha Tewodros Getnet, Mengistu Ketema, Bamlaku Alemu, Girma Demilew

Abstract:

The availability of forest products determines the possibilities for forest-based livelihood options. Plantation forest is a widespread economic activity in highland areas of the Amhara regional state, owing primarily to degradation and limited access to natural forests. As a result, tree plantation has become one of the rural livelihood options in the area. Therefore, given the increasing importance of smallholder plantations in highland areas of Amhara Regional States, the aim of this research was to evaluate the extent of smallholder plantations and their socio-economic impact. To address the abovementioned research, a sequential embedded mixed research design was employed. This qualitative and quantitative information was gathered from both primary and secondary sources. Primary data were collected from 385 sample households, which were chosen using a three-stage, multi-stage sampling method based on the Cochran sample size formula. Both descriptive and inferential statistics were used to analyze the data. Smallholder eucalyptus plantations in the study area were discovered to be common, and they are now part of the livelihood portfolio for meeting both household wood consumption and generating cash income. According to the PSM model's ATT results, income from selling farm forest products certainly contributes more to total household income, farm expenditure per cultivated land, and education spending than non-planter households. As a result, the government must strengthen plantation practices by prioritizing specific intervention areas while implementing measures to counteract the plantation's inequality-increasing effect through a variety of means, including progressive taxation.

Keywords: smallholder plantation, Eucalyptus, propensity score matching, average treatment effect and income

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4481 A Comparative Study of Regional Climate Models and Global Coupled Models over Uttarakhand

Authors: Sudip Kumar Kundu, Charu Singh

Abstract:

As a great physiographic divide, the Himalayas affecting a large system of water and air circulation which helps to determine the climatic condition in the Indian subcontinent to the south and mid-Asian highlands to the north. It creates obstacles by defending chill continental air from north side into India in winter and also defends rain-bearing southwesterly monsoon to give up maximum precipitation in that area in monsoon season. Nowadays extreme weather conditions such as heavy precipitation, cloudburst, flash flood, landslide and extreme avalanches are the regular happening incidents in the region of North Western Himalayan (NWH). The present study has been planned to investigate the suitable model(s) to find out the rainfall pattern over that region. For this investigation, selected models from Coordinated Regional Climate Downscaling Experiment (CORDEX) and Coupled Model Intercomparison Project Phase 5 (CMIP5) has been utilized in a consistent framework for the period of 1976 to 2000 (historical). The ability of these driving models from CORDEX domain and CMIP5 has been examined according to their capability of the spatial distribution as well as time series plot of rainfall over NWH in the rainy season and compared with the ground-based Indian Meteorological Department (IMD) gridded rainfall data set. It is noted from the analysis that the models like MIROC5 and MPI-ESM-LR from the both CORDEX and CMIP5 provide the best spatial distribution of rainfall over NWH region. But the driving models from CORDEX underestimates the daily rainfall amount as compared to CMIP5 driving models as it is unable to capture daily rainfall data properly when it has been plotted for time series (TS) individually for the state of Uttarakhand (UK) and Himachal Pradesh (HP). So finally it can be said that the driving models from CMIP5 are better than CORDEX domain models to investigate the rainfall pattern over NWH region.

Keywords: global warming, rainfall, CMIP5, CORDEX, NWH

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4480 Types of Neurons in the Spinal Trigeminal Nucleus of the Camel Brain: Golgi Study

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

Abstract:

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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4479 Inhibition of Variant Surface Glycoproteins Translation to Define the Essential Features of the Variant Surface Glycoprotein in Trypanosoma brucei

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

Procedia PDF Downloads 150
4478 Content Based Video Retrieval System Using Principal Object Analysis

Authors: Van Thinh Bui, Anh Tuan Tran, Quoc Viet Ngo, The Bao Pham

Abstract:

Video retrieval is a searching problem on videos or clips based on content in which they are relatively close to an input image or video. The application of this retrieval consists of selecting video in a folder or recognizing a human in security camera. However, some recent approaches have been in challenging problem due to the diversity of video types, frame transitions and camera positions. Besides, that an appropriate measures is selected for the problem is a question. In order to overcome all obstacles, we propose a content-based video retrieval system in some main steps resulting in a good performance. From a main video, we process extracting keyframes and principal objects using Segmentation of Aggregating Superpixels (SAS) algorithm. After that, Speeded Up Robust Features (SURF) are selected from those principal objects. Then, the model “Bag-of-words” in accompanied by SVM classification are applied to obtain the retrieval result. Our system is performed on over 300 videos in diversity from music, history, movie, sports, and natural scene to TV program show. The performance is evaluated in promising comparison to the other approaches.

Keywords: video retrieval, principal objects, keyframe, segmentation of aggregating superpixels, speeded up robust features, bag-of-words, SVM

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4477 Engaging the Terrorism Problematique in Africa: Discursive and Non-Discursive Approaches to Counter Terrorism

Authors: Cecil Blake, Tolu Kayode-Adedeji, Innocent Chiluwa, Charles Iruonagbe

Abstract:

National, regional and international security threats have dominated the twenty-first century thus far. Insurgencies that utilize “terrorism” as their primary strategy pose the most serious threat to global security. States in turn adopt terrorist strategies to resist and even defeat insurgents who invoke the legitimacy of statehood to justify their action. In short, the era is dominated by the use of terror tactics by state and non-state actors. Globally, there is a powerful network of groups involved in insurgencies using Islam as the bastion for their cause. In Africa, there are Boko Haram, Al Shabaab and Al Qaeda in the Maghreb representing Islamic groups utilizing terror strategies and tactics to prosecute their wars. The task at hand is to discover and to use multiple ways of handling the present security threats, including novel approaches to policy formulation, implementation, monitoring and evaluation that would pay significant attention to the important role of culture and communication strategies germane for discursive means of conflict resolution. In other to achieve this, the proposed research would address inter alia, root causes of insurgences that predicate their mission on Islamic tenets particularly in Africa; discursive and non-discursive counter-terrorism approaches fashioned by African governments, continental supra-national and regional organizations, recruitment strategies by major non-sate actors in Africa that rely solely on terrorist strategies and tactics and sources of finances for the groups under study. A major anticipated outcome of this research is a contribution to answers that would lead to the much needed stability required for development in African countries experiencing insurgencies carried out by the use of patterned terror strategies and tactics. The nature of the research requires the use of triangulation as the methodological tool.

Keywords: counter-terrorism, discourse, Nigeria, security, terrorism

Procedia PDF Downloads 486