Search results for: detecting face

Authors: Nuray Okcum, Jenny Sharples

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While the scrutinization towards marginalized groups throughout the globe has been existent for decades, prejudice towards Muslims in Western countries has been increasing dramatically. The vicious attacks across the globe by perpetrators who identify with Islam as well as popular political discourse by politicians in Western countries claiming and portraying Muslims as being dangerous, oppressed, or lacking the ability to assimilate into the community, adds to the exclusion and lack of belonging Muslims living in Western countries experience. The early stages of adulthood which have recently been conceptualized as emerging adulthood is a critical and socially ambiguous transition. For a young Muslim emerging into adulthood in a Western country, a variety of different challenges and demands that can exceed their coping abilities can arise. While in search for their identity and in a bid to structure themselves with their past childhood experiences together with their newly forming values, the emerging adult may attempt to direct or change the way in which they are viewed by others. This can be done to gain approval from others and to feel a sense of belonging. A change in the emerging adult’s interpersonal interactions and relationships, the way in which they view themselves and others, their sense of belonging, and their identity, also occurs during this developmental stage. To explore the manner in which Muslims emerging into adulthood carve their identity, their experiences, and representation of their Muslim identity, social identification, and their sense of belonging in Australia, an interpretative phenomenological methodology was utilized. This allowed participants to offer their own subjective experiences. A total of eight emerging adults took part in the study whilst four adults who work with emerging adults took part. Adult participants who work with emerging adults took part in the study to bring forth their insight and experiences. Common experiences were organized into themes. Themes included identifying as a Muslim, social identification, and belonging. Identification included visual identification and name, discrimination and resilience. Findings clearly indicated that Muslims emerging into adulthood in Australia do face various hurdles while they try to retain and represent their religious identity. Despite the unique challenges that they face, they still feel a sense of belonging and identity as being Australian.

Keywords: Muslim, Islam, emerging adulthood, Australia

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Authors: Jesmin Akter, Chang Hyuk Ahn, Ilho Kim, Fumitake Nishimura, Jaiyeop Lee

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This study aimed to compare two pre-treatment and two RNA extraction methods, namely PEG, and Nano bubble, Viral RNA Soil, and Mini Kit, in terms of their efficiency in detecting SARS-CoV-2 and PMMoV in influent and 1st sedimentation samples from a wastewater treatment plant. The extracted RNA samples were quantified and evaluated for purity, yield, and integrity. The results indicated that the nanobubble PEG method provided the highest yield of RNA, while the QIAamp Viral RNA Mini Kit produced the purest RNA samples. In terms of sensitivity and specificity, all these methods were able to detect SARS-CoV-2 and PMMoV in both influent and 1st sedimentation samples. However, the nanobubble PEG method showed slightly higher sensitivity compared to the other methods. These findings suggest that the choice of RNA extraction method should depend on the downstream application and the quality of the RNA required. The study also highlights the potential of wastewater-based epidemiology as an effective and non-invasive method for monitoring the spread of infectious diseases in a community.

Keywords: influent, PMMoV, SARS-CoV-2, wastewater based epidemiology

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Authors: Yassa Nacera, Badji Abderrezak, Saidoune Abdelmalek, Houassine Hamza

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Several kinds of faults can occur in a permanent magnet synchronous machine (PMSM) systems: bearing faults, electrically short/open faults, eccentricity faults, and demagnetization faults. Demagnetization fault means that the strengths of permanent magnets (PM) in PMSM decrease, and it causes low output torque, which is undesirable for EVs. The fault is caused by physical damage, high-temperature stress, inverse magnetic field, and aging. Motor current signature analysis (MCSA) is a conventional motor fault detection method based on the extraction of signal features from stator current. a simulation model of the PMSM under partial demagnetization and uniform demagnetization fault was established, and different degrees of demagnetization fault were simulated. The harmonic analyses using the Fast Fourier Transform (FFT) show that the fault diagnosis method based on the harmonic wave analysis is only suitable for partial demagnetization fault of the PMSM and does not apply to uniform demagnetization fault of the PMSM.

Keywords: permanent magnet, diagnosis, demagnetization, modelling

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Authors: Gabriela Quintana Vigiola

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Social sustainability is an issue scarcely addressed by different authors, being one of its key factors the psychosocial processes of sense of place, sense of community and appropriation. In Caracas’s barrios (Venezuela) these were developed through sharing the construction of the place and different struggles that brought the neighbours together. However, one of the main problems they face is criminal violence, hence being its social sustainability threatened and affected by it. This matter can be addressed by acknowledging communities’ sense of place and engaging in cultural events.

Keywords: Caracas’ barrios, cultural engagement, developing countries, social sustainability

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Authors: Chueh Chang, Chia-jung Hsieh, Fu-yu Yu, Yu-Hwa Lin

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Background:The majority of women diagnosed with breast cancer undergo treatment involving surgery and radiotherapy or chemotherapy, or both. With these major advances in breast cancer management, many patients still have to deal with short or long-term side effects and psychological distress related to the disease and treatment, which have a substantial impact on their quality of life. The Laughing Qigong Program (LQP) is an interactive laughter program that combines the physical and physiological benefits of laughter with the mental benefits of Chinese qigong. Purpose: In order to improve the quality of life for breast cancer women in the community as well as echoing the WHO 2004 “Promoting Mental Health” for every one. This study focused on how to promote the positive mental health for women of breast cancer through the “laughter program” in Taiwan. During the presentation, how to practice Laughing Qigong will be demonstrated. Method: Using nonequivalent pretest-posttest design, ix-one breast cancer patients were volunteered to enroll in this study from the Taiwan Breast Cancer Alliance (TBCA). Thirty patients were assigned to the experimental group and the other 31 patients were assigned to the control group. The women who were assigned to the experimental group received laughter program one hour per session, once a week, totally 12 sessions. All subjects were tested before and after the intervention on the following: Self-Esteem scale (RSE), Face Scale (FS), Anxiety and pain experience were measured as psychological markers; saliva cortisol (CS) as an immunological marker; blood pressure (BP), heart rate (HR),and heart rate variability (HRV) as physiological markers of the body’s response to stress. Results: After comparing the experimental and control groups, the results revealed that those breast cancer women with “laughing program” their sense of humor were improved, less uncomfortable on self report physical conditions, more positive attitudes toward stress management by using laughter, and had emotional improvement according to the face scale.

Keywords: mental health promotion, breast cancer, laughing Qigong, women

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Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

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Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

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It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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Authors: G. K. Viswanadh, B. Rajasekhar, G. Venkata Ramana

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Water distribution networks play a vital role in ensuring a reliable supply of clean water to urban areas. However, they face several challenges, including pressure control, pump speed optimization, and burst event detection. This paper combines insights from two studies to address these critical issues in Water distribution networks, focusing on the specific context of Kapra Municipality, India. The first part of this research concentrates on optimizing pressure control and pump speed in complex Water distribution networks. It utilizes the EPANET- MATLAB Toolkit to integrate EPANET functionalities into the MATLAB environment, offering a comprehensive approach to network analysis. By optimizing Pressure Reduce Valves (PRVs) and variable speed pumps (VSPs), this study achieves remarkable results. In the Benchmark Water Distribution System (WDS), the proposed PRV optimization algorithm reduces average leakage by 20.64%, surpassing the previous achievement of 16.07%. When applied to the South-Central and East zone WDS of Kapra Municipality, it identifies PRV locations that were previously missed by existing algorithms, resulting in average leakage reductions of 22.04% and 10.47%. These reductions translate to significant daily Water savings, enhancing Water supply reliability and reducing energy consumption. The second part of this research addresses the pressing issue of burst event detection and localization within the Water Distribution System. Burst events are a major contributor to Water losses and repair expenses. The study employs wireless sensor technology to monitor pressure and flow rate in real time, enabling the detection of pipeline abnormalities, particularly burst events. The methodology relies on transient analysis of pressure signals, utilizing Cumulative Sum and Wavelet analysis techniques to robustly identify burst occurrences. To enhance precision, burst event localization is achieved through meticulous analysis of time differentials in the arrival of negative pressure waveforms across distinct pressure sensing points, aided by nodal matrix analysis. To evaluate the effectiveness of this methodology, a PVC Water pipeline test bed is employed, demonstrating the algorithm's success in detecting pipeline burst events at flow rates of 2-3 l/s. Remarkably, the algorithm achieves a localization error of merely 3 meters, outperforming previously established algorithms. This research presents a significant advancement in efficient burst event detection and localization within Water pipelines, holding the potential to markedly curtail Water losses and the concomitant financial implications. In conclusion, this combined research addresses critical challenges in Water distribution networks, offering solutions for optimizing pressure control, pump speed, burst event detection, and localization. These findings contribute to the enhancement of Water Distribution System, resulting in improved Water supply reliability, reduced Water losses, and substantial cost savings. The integrated approach presented in this paper holds promise for municipalities and utilities seeking to improve the efficiency and sustainability of their Water distribution networks.

Keywords: pressure reduce valve, complex networks, variable speed pump, wavelet transform, burst detection, CUSUM (Cumulative Sum), water pipeline monitoring

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Authors: Elnaz Lashgari, Emel Demircan

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Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: electromyography, manifold learning, ISOMAP, Laplacian Eigenmaps, locally linear embedding

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Authors: Shanorfizah Mohd Safar, Shaizatulaqma Kamalul Ariffin

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Internationalization of halal small and medium-sized enterprises (SMEs) is necessary for SMEs to become more involved in regional trade and business cooperation. By internationalization, SMEs' profit can increase, and market expansion of SMEs is basic for rising economies of countries to contend all around in the halal industry globally. There are several modes of internationalization; exporting is one of the first steps for internationalization with less capital needed. The study examines the influential factors of export performance amongst halal SMEs in Malaysia. Specifically, this study examines the positive and significant relationships amongst human capital, managerial capability, Halal Assurance Management System (HAMS), digital transformation, government support, and networking capability on halal SMEs' export performance toward SMEs' competitive advantage. In addition, this study will examine innovation capabilities as a moderator in the relationship between independence variables and competitive advantage. Competitive advantage is the most compelling perspective that drives the export performance of halal SMEs in Malaysia. A quantitative method will be used: an online questionnaire survey distributed through emails and face-to-face toward selected halal-certificated SMEs registered in JAKIM, MATRADE website and SME Corp Malaysia website. Nevertheless, whether the halal SMEs practice global business, they will still be the potential respondents. The data were examined and obtained using the statistical software Smart PLS. The analysis used is reliability, correlation, and regression analysis to meet the research objectives. This study contributes significantly to the theory by integrating Resource Based View (RBV) theory, Technology–Organization–Environment (TOE) framework and Networking theory. In addition, this research extends the RBV by extending a variable, the Halal Assurance Management System. This study also examines a moderating role of innovation capabilities in the framework and competitive advantage as a mediator. This research aims to analyze the factors that will impact the internationalization of halal SMEs.

Keywords: internationalization, halal SMEs, competitive advantage, export performance

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Authors: A. Casale, J. Alessi, C. N. Bianchi, G. Bozzini, M. Brunoldi, V. Cappanera, P. Corvisiero, G. Fanciulli, D. Grosso, N. Magnoli, A. Mandich, C. Melchiorre, C. Morri, P. Povero, N. Stasi, M. Taiuti, G. Viano, M. Wurtz

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This work describes a real-time algorithm for detecting, tracking and classifying single motorboats, developed using the acoustic data recorded by a hydrophone array within the framework of EU LIFE + project ARION (LIFE09NAT/IT/000190). The project aims to improve the conservation status of bottlenose dolphins through a real-time simultaneous monitoring of their population and surface ship traffic. A Passive Acoustic Monitoring (PAM) system is installed on two autonomous permanent marine buoys, located close to the boundaries of the Marine Protected Area (MPA) of Portofino (Ligurian Sea- Italy). Detecting surface ships is also a necessity in many other sensible areas, such as wind farms, oil platforms, and harbours. A PAM system could be an effective alternative to the usual monitoring systems, as radar or active sonar, for localizing unauthorized ship presence or illegal activities, with the advantage of not revealing its presence. Each ARION buoy consists of a particular type of structure, named meda elastica (elastic beacon) composed of a main pole, about 30-meter length, emerging for 7 meters, anchored to a mooring of 30 tons at 90 m depth by an anti-twist steel wire. Each buoy is equipped with a floating element and a hydrophone tetrahedron array, whose raw data are send via a Wi-Fi bridge to a ground station where real-time analysis is performed. Bottlenose dolphin detection algorithm and ship monitoring algorithm are operating in parallel and in real time. Three modules were developed and commissioned for ship monitoring. The first is the detection algorithm, based on Time Difference Of Arrival (TDOA) measurements, i.e., the evaluation of angular direction of the target respect to each buoy and the triangulation for obtaining the target position. The second is the tracking algorithm, based on a Kalman filter, i.e., the estimate of the real course and speed of the target through a predictor filter. At last, the classification algorithm is based on the DEMON method, i.e., the extraction of the acoustic signature of single vessels. The following results were obtained; the detection algorithm succeeded in evaluating the bearing angle with respect to each buoy and the position of the target, with an uncertainty of 2 degrees and a maximum range of 2.5 km. The tracking algorithm succeeded in reconstructing the real vessel courses and estimating the speed with an accuracy of 20% respect to the Automatic Identification System (AIS) signals. The classification algorithm succeeded in isolating the acoustic signature of single vessels, demonstrating its temporal stability and the consistency of both buoys results. As reference, the results were compared with the Hilbert transform of single channel signals. The algorithm for tracking multiple targets is ready to be developed, thanks to the modularity of the single ship algorithm: the classification module will enumerate and identify all targets present in the study area; for each of them, the detection module and the tracking module will be applied to monitor their course.

Keywords: acoustic-noise, bottlenose-dolphin, hydrophone, motorboat

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Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

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Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

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Authors: Cristian Viespe, Dana Miu

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Surface acoustic wave (SAW) sensors with nanoparticles (NPs) of various dimensions and concentrations embedded in different types of polymer sensing films for detecting volatile organic compounds (VOCs) were studied. The sensors were ‘delay line’ type with a center frequency of 69.4 MHz on ST-X quartz substrates. NPs with different diameters of 7 nm or 13 nm were obtained by laser ablation with lasers having 5 ns or 10 ps pulse durations, respectively. The influence of NPs dimensions and concentrations on sensor properties such as frequency shift, sensitivity, noise and response time were investigated. To the best of our knowledge, the influence of NP dimensions on SAW sensor properties with has not been investigated. The frequency shift and sensitivity increased with increasing NP concentration in the polymer for a given NP dimension and with decreasing NP diameter for a given concentration. The best performances were obtained for the smallest NPs used. The SAW sensor with NPs of 7 nm had a limit of detection (LOD) of 65 ppm (almost five times better than the sensor with polymer alone), and a response time of about 9 s for ethanol.

Keywords: surface acoustic wave sensor, nanoparticles, volatile organic compounds, laser ablation

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Authors: Mahdi Sepehrmanesh

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This essay explores Gerald Vizenor's innovative concepts of the tragedy of absence and the comedy of presence as frameworks for understanding and challenging dominant narratives about Native American identity and history. Vizenor's work critiques the notion of irrevocable cultural loss and rigid definitions of Indigenous identity based on blood quantum and stereotypical practices. Through subversive humor, trickster figures, and storytelling, Vizenor asserts the active presence and continuance of Native peoples, advocating for a dynamic, self-determined understanding of Native identity. The essay examines Vizenor's use of postmodern techniques, including his engagement with simulation and hyperreality, to disrupt colonial discourses and create new spaces for Indigenous expression. It explores the concept of "crossblood" identities as a means of resisting essentialist notions of Native authenticity and embracing the complexities of contemporary Indigenous experiences. Vizenor's ideas of survivance and transmotion are analyzed as strategies for cultural resilience and adaptation in the face of ongoing colonial pressures. The interplay between absence and presence in Vizenor's work is discussed, particularly through the lens of shadow survivance and the power of storytelling. The essay also delves into Vizenor's critique of terminal creed and his promotion of natural reason as an alternative epistemology to Western rationalism. While acknowledging the significant influence of Vizenor's work on Native American literature and theory, the essay also addresses critiques of his approach, including concerns about the accessibility of his writing and its political effectiveness. Despite these debates, the essay argues that Vizenor's concepts offer a powerful vision of Indigenous futurity that is rooted in tradition yet open to change, inspiring hope and agency in the face of oppression. By examining Vizenor's multifaceted approach to Native American identity and presence, this essay contributes to ongoing discussions about Indigenous representation, cultural continuity, and resistance to colonial narratives in literature and beyond.

Keywords: gerald vizenor, identity native american literature, survivance, trickster discourse, identity

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Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

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A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

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Authors: Mike Chia-Yu Huang

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China’s port facility construction projects in the Indian Ocean (IO) region, Gwadar Port and Djibouti Port projects in particular, have led to a heated debate among both Chinese and Western strategists over whether the country has literally been carrying out its “string of pearls” strategy, an alleged Chinese plan to challenge America’s military predominance in South Asia. Even though the Chinese government repeatedly denied the existence of such a strategy and highlighted the civilian/commercial nature of its port projects, it has significantly enhanced its strategic cooperation with littoral countries in the IO region since the “One Belt One Road” initiative was introduced by Chinese President Xi Jinping in 2013. Whether China does have a plan to expand its sphere of military influence westward concerns the balance of power in the IO region. If the answer is positive, the security environment there will be changed drastically. This paper argues that rather than simply copying the U.S. model of developing overseas military bases along the IO periphery, Beijing has been deliberating a more sophisticated plan for its physical presence there: creating a new set of “overseas strategic pivots.” These “pivots,” semi-military and semi-commercial in nature, are designed to help Beijing sustain its anti-piracy operations in the Gulf of Aden and serve as forward stations for the transportation of China’s imported energy and merchandise. They can support the Chinese Navy’s operations overseas but are not supposed to undertake face-to-face combat missions. This upgraded Chinese scheme can be identified as “string of pearls” strategy 2.0. Moreover, it is expected to help China deepen its roots in the IO region, implying that Beijing has to a large extent scratched its old diplomatic philosophy which highlighted the merits of non-interference and nonalignment. While a full-scale maritime confrontation between China and the U.S.-India security alliance is unlikely to be witnessed in the near future, an ambitious Chinese plan to step into the global maritime domain has been evidently shown.

Keywords: Chinese navy, Djibouti, Gwadar, Indian Ocean, string of pearls strategy

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Authors: Shuo Li, Yannick Coffinier, Chann Lagadec, Fabrizio Cleri, Katsuhiko Nishiguchi, Akira Fujiwara, Soo Hyeon Kim, Nicolas Clément

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The need for single cell detection and analysis techniques has increased in the past decades because of the heterogeneity of individual living cells, which increases the complexity of the pathogenesis of malignant tumors. In the search for early cancer detection, high-precision medicine and therapy, the technologies most used today for sensitive detection of target analytes and monitoring the variation of these species are mainly including two types. One is based on the identification of molecular differences at the single-cell level, such as flow cytometry, fluorescence-activated cell sorting, next generation proteomics, lipidomic studies, another is based on capturing or detecting single tumor cells from fresh or fixed primary tumors and metastatic tissues, and rare circulating tumors cells (CTCs) from blood or bone marrow, for example, dielectrophoresis technique, microfluidic based microposts chip, electrochemical (EC) approach. Compared to other methods, EC sensors have the merits of easy operation, high sensitivity, and portability. However, despite various demonstrations of low limits of detection (LOD), including aptamer sensors, arrayed EC sensors for detecting single-cell have not been demonstrated. In this work, a new technique based on 20-nm-thick nanopillars array to support cells and keep them at ideal recognition distance for redox-labeled aptamers grafted on the surface. The key advantages of this technology are not only to suppress the false positive signal arising from the pressure exerted by all (including non-target) cells pushing on the aptamers by downward force but also to stabilize the aptamer at the ideal hairpin configuration thanks to a confinement effect. With the first implementation of this technique, a LOD of 13 cells (with5.4 μL of cell suspension) was estimated. In further, the nanosupported cell technology using redox-labeled aptasensors has been pushed forward and fully integrated into a single-cell electrochemical aptasensor array. To reach this goal, the LOD has been reduced by more than one order of magnitude by suppressing parasitic capacitive electrochemical signals by minimizing the sensor area and localizing the cells. Statistical analysis at the single-cell level is demonstrated for the recognition of cancer cells. The future of this technology is discussed, and the potential for scaling over millions of electrodes, thus pushing further integration at sub-cellular level, is highlighted. Despite several demonstrations of electrochemical devices with LOD of 1 cell/mL, the implementation of single-cell bioelectrochemical sensor arrays has remained elusive due to their challenging implementation at a large scale. Here, the introduced nanopillar array technology combined with redox-labeled aptamers targeting epithelial cell adhesion molecule (EpCAM) is perfectly suited for such implementation. Combining nanopillar arrays with microwells determined for single cell trapping directly on the sensor surface, single target cells are successfully detected and analyzed. This first implementation of a single-cell electrochemical aptasensor array based on Brownian-fluctuating redox species opens new opportunities for large-scale implementation and statistical analysis of early cancer diagnosis and cancer therapy in clinical settings.

Keywords: bioelectrochemistry, aptasensors, single-cell, nanopillars

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Authors: Avinash Malladhi

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Forensic accounting is a specialized field that involves the application of accounting principles, investigative skills, and legal knowledge to detect and prevent fraud. With the rise of big data and technological advancements, artificial intelligence (AI) and machine learning (ML) algorithms have emerged as powerful tools for forensic accountants to enhance their fraud detection capabilities. In this paper, we review and analyze various AI/ML algorithms that are commonly used in forensic accounting, including supervised and unsupervised learning, deep learning, natural language processing Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Decision Trees, and Random Forests. We discuss their underlying principles, strengths, and limitations and provide empirical evidence from existing research studies demonstrating their effectiveness in detecting financial fraud. We also highlight potential ethical considerations and challenges associated with using AI/ML in forensic accounting. Furthermore, we highlight the benefits of these technologies in improving fraud detection and prevention in forensic accounting.

Keywords: AI, machine learning, forensic accounting & fraud detection, anti money laundering, Benford's law, fraud triangle theory

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Authors: Amer Ali, Jessica Cecchinelli, Antonis Charalambous

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Cycling is one of the most environmentally friendly, economic and healthy modes of transport but it needs more efficient cycle infrastructure and more effective safety measures. This paper represents an investigation into the performance and operation of the London Cycle Hire Scheme which started to operate in July 2010 using 5,000 cycles and 315 docking stations and currently has more than 10,000 cycles and over 700 docking stations across London which are available 24/7, 365 days a year. The study, which was conducted during the second half of 2014, consists of two parts; namely, the longitudinal review of the hire scheme between its introduction in 2010 and November 2014, and a field survey in November 2014 in the form of face-face interviews of the users of the cycle scheme to ascertain the existing limitations and difficulties experienced by those users and how it could be improved in terms of capability and safety. The study also includes a correlation between the usage of the cycle scheme and the corresponding weather conditions. The main findings are that on average the number of users (hiring frequency) had increased from just over two millions hires in 2010 to just less than ten millions in 2014. The field survey showed that 80% of the users are satisfied with the performance of the scheme whilst 50% of the users raised concern about the safety level of using the available cycle routes and infrastructure. The study also revealed that a high percentage of the cycle trips were relatively short (less than 30 minutes). Although the weather condition had some effect on cycling, the cost of using the cycle scheme and the main events in London had more effect on the number of cycle hires. The key conclusions are that despite the safety concern and the lack of infrastructure for continuous routes there was an encouraging number of people who opted for cycling as a clean, affordable, and healthy mode of transport. There is a need to expand the scheme by providing more cycles and docking stations and to support that by more well-designed and maintained cycle routes. More details about the development of London Cycle Hire Scheme during the last five years, its performance and the key issues revealed by the surveyed users will be reported in the full version of the paper.

Keywords: cycling mode of transport, london cycle hire scheme, safety, environmental and health benefits, user satisfaction

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Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

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Authors: Agastya Pratap Singh

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This review paper examines the emerging applications of generative adversarial networks (GANs) in the fields of image recognition and anomaly detection. With the rapid growth of digital image data, the need for efficient and accurate methodologies to identify and classify images has become increasingly critical. GANs, known for their ability to generate realistic data, have gained significant attention for their potential to enhance traditional image recognition systems and improve anomaly detection performance. The paper systematically analyzes various GAN architectures and their modifications tailored for image recognition tasks, highlighting their strengths and limitations. Additionally, it delves into the effectiveness of GANs in detecting anomalies in diverse datasets, including medical imaging, industrial inspection, and surveillance. The review also discusses the challenges faced in training GANs, such as mode collapse and stability issues, and presents recent advancements aimed at overcoming these obstacles.

Keywords: generative adversarial networks, image recognition, anomaly detection, synthetic data generation, deep learning, computer vision, unsupervised learning, pattern recognition, model evaluation, machine learning applications

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Authors: Hema Vanita Kesevan

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The global spread of Covid-19 virus in early 2020 has led to major changes in many walks of life, including the education system. Traditional face to face lessons that were carried out for years has been replaced by online learning. Although online learning has been used before the pandemic, it has not been the only source of teaching and learning. This drastic change has brought significant impact to the process of teaching and learning in many classrooms around the world. Likewise, in country like Malaysia that that has been promoting online learning but has not utilize it fully due to many restrictions in terms of technology, accessibility, and online literacy, the sudden change to full online platform learning in all educational sector has definitely caused Issues in terms of its adaptation and usage. Although many studies have been conducted to explore the efficiency and impact of online learning during the pandemic, studies focusing on the same are limited in Malaysian classroom context, especially in English language classrooms. Thus, this study seeks to explore on the efficacy and effectiveness of online learning tools in ESL classroom contexts during the pandemic. The aim of this study is to understand the educator's and student's perceptions on the implementation of online learning tools in the teaching and learning process and the types of online learning tools that were used to assist the teaching and learning process during the pandemic. Particularly, this study focused to explore the types of online learning tools used in Malaysian schools and university during the online teaching and learning process and further explores how the various types of tools used impacted the students' participation in the lessons conducted. The participants of this study are secondary school students, teachers, and university students. Data will be collected in terms of survey questionnaire and interviews. The survey data intends to obtain information on the types of online learning used in ESL teaching and learning practices during the pandemic, how the various types of online tools influence students' participation during lessons. The interview data from the teachers serves to provide information about the selection of online learning tools, challenges of using it to conduct online lessons, and other arising issues. A mixed method design will be used to analysed the data obtained. The questionnaire will be analysed quantitatively using descriptive analysis meanwhile, the interview data will be analysed qualitatively.

Keywords: Covid 19, online learning tools, ESL classroom, effectiveness, efficacy

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Authors: Katherine van Kampen, Reva Qiu, Patricia Farrugia

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Orthopedic surgery has fallen behind when it comes to gender diversity despite medical school classes reaching gender parity. Studies have shown that orthopedic surgery would require 117 years to reach gender parity with the trainee population, the longest time than any other specialty, including neurosurgery, urology, and otolaryngology. The barriers that face women in orthopedic surgery have been well researched, with contributing factors being on-going stereotypes of the field, lack of women mentors, and gender roles outside of the hospital. Furthermore, women in orthopedic surgery face barriers to achieve promotion, publications, and leadership roles leading to a “leaky pipeline,” resulting in less and less women in key academic roles in the field. It is a complex topic with barriers and challenges faced in medical school, residency, and throughout employment. Our scoping review seeks to understand these challenges across a temporal timeline and to further characterize such barriers and the driving factors behind them. To this date, authors did not find a scoping review that seeks to look broadly at factors impacting the decreased amount of women entering orthopedics and the factors that cause women to hit a “glass ceiling”, the idea that women will not achieve the same success as men despite the same qualifications, upon entering the field. This scoping review is the first of its kind to attempt to summarize the large body of research focusing on women in orthopedic surgery from the preconceptions in medical school impacting their desire to pursue orthopedics all the way to employment, including challenges to academic success and financial success. Literature databases will be searched with the following key terms: women, gender inequity, workforce, orthopedics, and citations will be hand searched and collected. Articles included will discuss gender inequality within orthopedics with non-english, patient related articles excluded. Full-text review will seek to characterize the specific barriers faced by women across medical school, residency, and employment. Themes that are expected to be highlighted are workforce data, women in orthopedic leadership, medical student perspectives on the specialty, and gender bias and discrimination in the field.

Keywords: orthopedics, gender equity, workforce, women in surgery

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Authors: Neha Toppo

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Method and strategies of teaching instruction highly influence learning of students. In second language teaching, number of ways and methods has been suggested by different scholars and researchers through times. The present article deals with the role of teaching instruction in developing compositional ability of students in writing. It focuses on the secondary level students of rural areas, whose exposure to English language is limited and they face challenges even in simple compositions. The students till high school suffer with their disability in writing formal letter, application, essay, paragraph etc. They face problem in note making, writing answers in examination using their own words and depend fully on rote learning. It becomes difficult for them to give language to their own ideas. Teaching writing composition deserves special attention as writing is an integral part of language learning and students at this level are expected to have sound compositional ability for it is useful in numerous domains. Effective method of instruction could help students to learn expression of self, correct selection of vocabulary and grammar, contextual writing, composition of formal and informal writing. It is not limited to school but continues to be important in various other fields outside the school such as in newspaper and magazine, official work, legislative work, material writing, academic writing, personal writing, etc. The study is based on the experimental method, which hypothesize that guided instruction will be more effective in teaching writing compositions than usual instruction in which students are left to compose by their own without any help. In the test, students of one section are asked to write an essay on the given topic without guidance and another section are asked to write the same but with the assistance of guided instruction in which students have been provided with a few vocabulary and sentence structure. This process is repeated in few more schools to get generalize data. The study shows the difference on students’ performance using both the instructions; guided and unguided. The conclusion of the study is followed by the finding that writing skill of the students is quite poor but with the help of guided instruction they perform better. The students are in need of better teaching instruction to develop their writing skills.

Keywords: composition, essay, guided instruction, writing skill

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Authors: Eid Alharbi, Yaser Miaji

Abstract:

The quality level for fresh fruits is very important for the fruit industries. In presents study, an automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics, NIR, fruit quality, spectroscopic technology, mechatronic design

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Authors: R. Majidzadeh Heravi, M. Sankian, H. Kermanshahi, M. R. Nassiri, A. Heravi Moussavi, S. A. Lari, A. R. Varasteh

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The use of probiotics engineered to express specific enzymes has been the subject of considerable attention in poultry industry because of increased nutrient availability and reduced cost of enzyme supplementation. Phytase enzyme is commonly added to poultry feed to improve digestibility and availability of phosphorus from plant sources. To construct a probiotic with potential of phytate degradation, phytase gene (appA) from E. coli was cloned and transformed into two probiotic bacteria Lactobacillus salivarius and Lactococcus lactis. L. salivarous showed plasmid instability, unable to express the gene. The expression of appA gene in L. lactis was analyzed by detecting specific RNA and zymography assay. Phytase enzyme was isolated from cellular extracts of recombinant L. lactis, showing a 46 kDa band upon the SDS-PAGE analysis. Zymogram also confirmed the phytase activity of the 46 kDa band corresponding to the enzyme. An enzyme activity of 4.9U/ml was obtained in cell extracts of L. lactis. The growth of native and recombinant L. lactis was similar in the presence of two concentrations of ox bile.

Keywords: Lactobacillus salivarus, Lactococcuslactis, recombinant, phytase, poultry

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Authors: Farah Naja, Mohamad Alameddine

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Background: The difficulty of compliance to therapeutic and lifestyle management of type 2 diabetes mellitus (T2DM) encourages patients to use complementary and alternative medicine (CAM) therapies. Little is known about the prevalence and mode of CAM use among diabetics in the Eastern Mediterranean Region in general and Lebanon in particular. Objective: To assess the prevalence and modes of CAM use among patients with T2DM residing in Beirut, Lebanon. Methods: A cross-sectional survey of T2DM patients was conducted on patients recruited from two major referral centers - a public hospital and a private academic medical center in Beirut. In a face-to-face interview, participants completed a survey questionnaire comprised of three sections: socio-demographic, diabetes characteristics and types and modes of CAM use. Descriptive statistics, univariate and multivariate logistic regression analyses were utilized to assess the prevalence, mode and correlates of CAM use in the study population. The main outcome in this study (CAM use) was defined as using CAM at least once since diagnosis with T2DM. Results: A total of 333 T2DM patients completed the survey (response rate: 94.6%). Prevalence of CAM use in the study population was 38%, 95% CI (33.1-43.5). After adjustment, CAM use was significantly associated with a “married” status, a longer duration of T2DM, the presence of disease complications, and a positive family history of the disease. Folk foods and herbs were the most commonly used CAM followed by natural health products. One in five patients used CAM as an alternative to conventional treatment. Only 7 % of CAM users disclosed the CAM use to their treating physician. Health care practitioners were the least cited (7%) as influencing the choice of CAM among users. Conclusion: The use of CAM therapies among T2DM patients in Lebanon is prevalent. Decision makers and care providers must fully understand the potential risks and benefits of CAM therapies to appropriately advise their patients. Attention must be dedicated to educating T2DM patients on the importance of disclosing CAM use to their physicians especially patients with a family history of diabetes, and those using conventional therapy for a long time.

Keywords: nutritional supplements, type 2 diabetes mellitus, complementary and alternative medicine (CAM), conventional therapy

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Authors: Reza Hedayati, Meysam Jahanbakhshi

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In this work, Fracture Mechanics is used to predict crack propagation in the adhesive joining aluminum and composite plates. Three types of loadings and two types of glass-epoxy composite sequences: [0/90]2s and [0/45/-45/90]s are considered for the composite plate. Therefore, 2*3=6 cases are considered and their results are compared. The debonding initiation load, complete debonding load, crack face profile and load-displacement diagram have been compared for the six cases.

Keywords: adhesive joint, debonding, fracture, LEFM, APDL

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Authors: M. R. Bhuiyan, S. M. M. Hossain, M. Z. Islam

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Autism Spectrum Disorder (ASD) is the fastest growing serious developmental disorder characterized by social deficits, communicative difficulties, and repetitive behaviors. ASD is an emerging public health issue globally which is associated with huge financial burden to the family, community and the nation. The aim of this study was to assess the financial burden of family for the children with Autism spectrum Disorder. This cross-sectional study was carried out from July 2015 to June 2016 among 154 children with ASD to assess the financial burden of family. Data were collected by face-to-face interview with semi-structured questionnaire following systematic random sampling technique. Majority (73.4%) children were male and mean (±SD) age was 6.66 ± 2.97 years. Most (88.8%) of the children were from urban areas with average monthly family income Tk. 41785.71±23936.45. Average monthly direct cost of the children was Tk.17656.49 ± 9984.35, while indirect cost was Tk. 13462.90 ± 9713.54 and total treatment cost was Tk. 23076.62 ± 15341.09. Special education cost (Tk. 4871.00), cost of therapy (Tk. 4124.07) and travel cost (Tk. 3988.31) were the major types of direct cost, while loss of income (Tk.14570.18) was the chief indirect cost incurred by the families. The study found that majority (59.8%) of the children attended special schools were incurred Tk.20001-78700 as total treatment cost, which were statistically significant (p<0.001). Again, families with higher monthly family income incurred higher treatment cost (r=0.526, p<0.05). Difference between mean direct and indirect cost was found significant (t=4.190, df=61, p<0.001). According to the analysis of variance, mean difference of father’s educational status among direct cost (F=10.337, p<0.001) and total treatment cost (F=7.841, p<0.001), which were statistically significant. The study revealed that maximum children with ASD were under five years, three-fourth were male. According to monthly family income, maximum family were in middle class. The study recommends cost effective interventions and financial safety-net measures to reduce the financial burden of families for the children with ASD.

Keywords: autism spectrum disorder, financial burden, direct cost, indirect cost, special education

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Authors: Rei-Heng Cheng, Wen-Pinn Fang

Abstract:

A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.

Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks

Procedia PDF Downloads 387