Search results for: trans-european transport network

Authors: Josif Figueroa, Kush Bubbar, Greg Young-Morris

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The reliability evaluation of composite generation and bulk transmission systems is crucial for ensuring a reliable supply of electrical energy to significant system load points. However, evaluating adequacy indices using probabilistic methods like sequential Monte Carlo Simulation can be computationally expensive. Despite this, it is necessary when time-varying and interdependent resources, such as renewables and energy storage systems, are involved. Recent advances in solving power network optimization problems and parallel computing have improved runtime performance while maintaining solution accuracy. This work introduces CompositeSystems, an open-source Composite System Reliability Evaluation tool developed in Julia™, to address the current deficiencies of commercial and non-commercial tools. This work introduces its design, validation, and effectiveness, which includes analyzing two different formulations of the Optimal Power Flow problem. The simulations demonstrate excellent agreement with existing published studies while improving replicability and reproducibility. Overall, the proposed tool can provide valuable insights into the performance of transmission systems, making it an important addition to the existing toolbox for power system planning.

Keywords: open-source software, composite system reliability, optimization methods, Monte Carlo methods, optimal power flow

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Authors: Benhui Fan, Fahmi Bedoui, Jinbo Bai

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Incorporated carbon nanotube-BaTiO₃ hybrids (H-CNT-BT) with core-shell structure, a better dispersion of CNTs can be achieved in a semi-crystalline polymeric matrix, polyvinylidene fluoride (PVDF). Carried by BT particles, CNTs are easy to mutually connect which helps to obtain an extremely low percolation threshold (fc). After thermal treatments, the dielectric constants (ε’) of samples further increase which depends on the conditions of thermal treatments such as annealing temperatures, annealing durations and cooling ways. Thus, in order to study more comprehensively about the influence of thermal treatments on composite’s dielectric behaviors, in situ synchrotron X-ray is used to detect re-crystalline behavior of PVDF. Results of wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS) show that after the thermal treatment, the content of β polymorph (the polymorph with the highest ε’ among all the polymorphs of PVDF’s crystalline structure) has increased nearly double times at the interfacial region of CNT-PVDF, and the thickness of amorphous layers (La) in PVDF’s long periods (Lp) has shrunk around 10 Å. The evolution of CNT’s network possibly occurs in the procedure of La shrinkage, where the strong interfacial polarization may be aroused and increases ε’ at low frequency. Moreover, an increase in the thickness of crystalline lamella may also arouse more orientational polarization and improve ε’ at high frequency.

Keywords: dielectric properties, thermal treatments, carbon nanotubes, crystalline structure

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: Jake Gonzalez, Tommy Dang

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This paper proposes a temporal graph approach to visualize and analyze the evolution of gene relationships and nomenclature over time. An interactive web-based tool implements this temporal graph, enabling researchers to traverse a timeline and observe coupled dynamics in network topology and naming conventions. Analysis of a real human genomic dataset reveals the emergence of densely interconnected functional modules over time, representing groups of genes involved in key biological processes. For example, the antimicrobial peptide DEFA1A3 shows increased connections to related alpha-defensins involved in infection response. Tracking degree and betweenness centrality shifts over timeline iterations also quantitatively highlight the reprioritization of certain genes’ topological importance as knowledge advances. Examination of the CNR1 gene encoding the cannabinoid receptor CB1 demonstrates changing synonymous relationships and consolidating naming patterns over time, reflecting its unique functional role discovery. The integrated framework interconnecting these topological and nomenclature dynamics provides richer contextual insights compared to isolated analysis methods. Overall, this temporal graph approach enables a more holistic study of knowledge evolution to elucidate complex biology.

Keywords: temporal graph, gene relationships, nomenclature evolution, interactive visualization, biological insights

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Authors: Ayna Yusubova, Bart Clarysse

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This paper explores role of research institutes in creation of support ecosystem for new technology-based ventures. Previous literature introduced research institutes as part of business and knowledge ecosystem, very few studies are available that consider a research institute as an ecosystem that support high-tech startups at every stage of development. Based on a resource-based view and a stage-based model of high-tech startups growth, this study aims to analyze how a research institute builds a startup support ecosystem by attracting different stakeholders in order to help startups to overcome resource. This paper is based on an in-depth case study of public research institute that focus on development of entrepreneurial ecosystem in a developed region. Analysis shows that the idea generation stage of high-tech startups that related to the invention and development of product or technology for commercialization is associated with a lack of critical knowledge resources. Second, at growth phase that related to market entrance, high-tech startups face challenges associated with the development of their business network. Accordingly, the study shows the support ecosystem that research institute creates helps high-tech startups overcome resource gaps in order to achieve a successful transition from one phase of growth to the next.

Keywords: new technology-based firms, ecosystems, resources, business incubators, research instutes

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Authors: Sangeeta Tripathi, Muna Al Shahri

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This research article presents the changing role and status of women in Oman. Transformation of women’s status started with the regime of His Majesty Sultan Qaboos Bin Said in 1970. It is always desired by the Sultan to enable women in all the ways for the balance growth of the country. Forbidding full face veil for women in public offices is one of the best efforts for their empowerment. Women education is also increasing rapidly. They are getting friendly with new information communication technology and using different social media applications such as WhatsApp, Instagram and Facebook for interaction and economic growth. Though there are some traditional and tribal boundaries, women are infused with courage and enjoying fair treatment and equal opportunities in different career positions. The study will try to explore changing mindset of young Omani women towards these traditional tribal boundaries, cultural heritage, business and career: ‘How are young Omani women making balance between work and social prestige?’, ‘How are they preserving their cultural values, embracing new technologies and approaching social network to enhance their economic power.’ This paper will discover their hurdles while using internet for their new entrepreneur. It will also examine the prospects of online business in Oman. The mixed research methodology is applied to find out the result.

Keywords: advertising, business, entrepreneurship, tribal barrier

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Authors: Norhan El Dallal

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The MENA region is a challenging, rapid urbanizing region, with a special profile; culturally, socially, economically and environmentally. Despite the diversity between different countries of the MENA region they all share similar urban challenges where extensive interventions are crucial. A climate sensitive region as the MENA region requires special attention for development, adaptation and mitigation. Integrating climatic and environmental parameters into the planning process to create a responsive urban form is the aim of this research in which “Parametric Urbanism” as a trend serves as a tool to reach a more sustainable urban morphology. An attempt to parameterize the relation between the climate and the urban form in a detailed manner is the main objective of the thesis. The aim is relating the different passive approaches suitable for the MENA region with the design guidelines of each and every part of the planning phase. Various conceptual scenarios for the network pattern and block subdivision generation based on computational models are the next steps after the parameterization. These theoretical models could be applied on different climatic zones of the dense communities of the MENA region to achieve an energy efficient neighborhood or city with respect to the urban form, morphology, and urban planning pattern. A final criticism of the theoretical model is to be conducted showing the feasibility of the proposed solutions economically. Finally some push and pull policies are to be proposed to help integrate these solutions into the planning process.

Keywords: parametric urbanism, climate responsive, urban form, urban and regional studies

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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Authors: Yountaik Leem, Sang Ho Lee

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In this paper, different goals and the ways to reach smart cities shown in many countries during planning and implementation processes will be discussed. Each country dealt with technologies which have been embedded into space as development of ICTs (information and communication technologies) for their own purposes and by their own ways. For example, European countries tried to adapt technologies to reduce greenhouse gas emission to overcome global warming while US-based global companies focused on the way of life using ICTs such as EasyLiving of Microsoft™ and CoolTown of Hewlett-Packard™ during last decade of 20th century. In the North-East Asian countries, urban space with ICTs were developed in large scale on the viewpoint of capitalism. Ubiquitous city, first introduced in Korea which named after Marc Weiser’s concept of ubiquitous computing pursued new urban development with advanced technologies and high-tech infrastructure including wired and wireless network. Japan has developed smart cities as comprehensive and technology intensive cities which will lead other industries of the nation in the future. Not only the goals and strategies but also new directions to which smart cities are oriented also suggested at the end of the paper. Like a Finnish smart community whose slogan is ‘one more hour a day for citizens,’ recent trend is forwarding everyday lives and cultures of human beings, not capital gains nor physical urban spaces.

Keywords: smart cities, urban strategy, future direction, comparative study

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Authors: Rongbo Shen, Jianhua Yao, Kezhou Yan, Kuan Tian, Cheng Jiang, Ke Zhou

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This study proposes a generative adversarial networks (GAN) framework to perform synthetic sampling in feature space, i.e., feature augmentation, to address the class imbalance problem in medical image analysis. A feature extraction network is first trained to convert images into feature space. Then the GAN framework incorporates adversarial learning to train a feature generator for the minority class through playing a minimax game with a discriminator. The feature generator then generates features for minority class from arbitrary latent distributions to balance the data between the majority class and the minority class. Additionally, a data cleaning technique, i.e., Tomek link, is employed to clean up undesirable conflicting features introduced from the feature augmentation and thus establish well-defined class clusters for the training. The experiment section evaluates the proposed method on two medical image analysis tasks, i.e., mass classification on mammogram and cancer metastasis classification on histopathological images. Experimental results suggest that the proposed method obtains superior or comparable performance over the state-of-the-art counterparts. Compared to all counterparts, our proposed method improves more than 1.5 percentage of accuracy.

Keywords: class imbalance, synthetic sampling, feature augmentation, generative adversarial networks, data cleaning

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Authors: Simon Arunga, Teddy Kwaga, Rita Kageni, Michael Gichangi, Nyawira Mwangi, Fred Kagwa, Rogers Mwavu, Amos Baryashaba, Luis F. Nakayama, Katharine Morley, Michael Morley, Leo A. Celi, Jessica Haberer, Celestino Obua

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Purpose: The main aim for creating the Multimodal Database of Retinal Images for Africa (MoDRIA) was to provide a publicly available repository of retinal images for responsible researchers to conduct algorithm development in a bid to curb the challenges of ophthalmic artificial intelligence (AI) in Africa. Methods: Data and retina images were ethically sourced from sites in Uganda and Kenya. Data on medical history, visual acuity, ocular examination, blood pressure, and blood sugar were collected. Retina images were captured using fundus cameras (Foru3-nethra and Canon CR-Mark-1). Images were stored on a secure online database. Results: The database consists of 7,859 retinal images in portable network graphics format from 1,988 participants. Images from patients with human immunodeficiency virus were 18.9%, 18.2% of images were from hypertensive patients, 12.8% from diabetic patients, and the rest from normal’ participants. Conclusion: Publicly available data repositories are a valuable asset in the development of AI technology. Therefore, is a need for the expansion of MoDRIA so as to provide larger datasets that are more representative of Sub-Saharan data.

Keywords: retina images, MoDRIA, image repository, African database

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Authors: Armando Cartenì

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Within the design of sustainable transportation engineering, the problem of reducing particulate matter (PM) concentrations in railways metro system was not much discussed. It is well known that PM levels in railways metro system are mainly produced by mechanical friction at the rail-wheel-brake interactions and by the PM re-suspension caused by the turbulence generated by the train passage, which causes dangerous problems for passenger health. Starting from these considerations, the aim of this research was twofold: i) to investigate the particulate matter concentrations in a ‘traditional’ railways metro system; ii) to investigate the particulate matter concentrations of a ‘high quality’ metro system equipped with design devices useful for reducing PM concentrations: platform screen doors, rubber-tyred and an advanced ventilation system. Two measurement surveys were performed: one in the ‘traditional’ metro system of Naples (Italy) and onother in the ‘high quality’ rubber-tyred metro system of Turin (Italy). Experimental results regarding the ‘traditional’ metro system of Naples, show that the average PM10 concentrations measured in the underground station platforms are very high and range between 172 and 262 µg/m3 whilst the average PM2,5 concentrations range between 45 and 60 µg/m3, with dangerous problems for passenger health. By contrast the measurements results regarding the ‘high quality’ metro system of Turin show that: i) the average PM10 (PM2.5) concentrations measured in the underground station platform is 22.7 µg/m3 (16.0 µg/m3) with a standard deviation of 9.6 µg/m3 (7.6 µg/m3); ii) the indoor concentrations (both for PM10 and for PM2.5) are statistically lower from those measured in outdoors (with a ratio equal to 0.9-0.8), meaning that the indoor air quality is greater than those in urban ambient; iii) that PM concentrations in underground stations are correlated to the trains passage; iv) the inside trains concentrations (both for PM10 and for PM2.5) are statistically lower from those measured at station platform (with a ratio equal to 0.7-0.8), meaning that inside trains the use of air conditioning system could promote a greater circulation that clean the air. The comparison among the two case studies allow to conclude that the metro system designed with PM reduction devices allow to reduce PM concentration up to 11 times against a ‘traditional’ one. From these results, it is possible to conclude that PM concentrations measured in a ‘high quality’ metro system are significantly lower than the ones measured in a ‘traditional’ railway metro systems. This result allows possessing the bases for the design of useful devices for retrofitting metro systems all around the world.

Keywords: air quality, pollutant emission, quality in public transport, underground railway, external cost reduction, transportation planning

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Authors: Imran Ullah Imran

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Language contact is a familiar concept in the present global world. Across the globe, languages get mixed up at different levels. Borrowing, code-switching are some of the means through which languages interact. This study examines Pashto-English contact at word and syllable levels. By recording the speech of 30 Pashto native speakers, selected via 'social network' sampling, the study located a number of Pashto-English compound words, which is a unique contact of its kind. In data analysis, tokens were categorized on the basis of their pattern and morphological structure. The study shows that Pashto-English Bilingual Compound words (BCWs) are very prevalent in the Pashto language. The study also found that the BCWs in Pashto are completely productive and have their own meanings. It also shows that the dominant pattern of hybrid words in Pashto is the conjugation of an independent English root word followed by a Pashto inflectional morpheme, which contributes to the core semantic content of the construction. The BCWs construction shows that how both the languages are closer to each other. Pashto-English contact results into bilingual compound and hybrid words, which forms a considerable number of tokens in the present-day spoken Pashto. On the basis of these findings, the study assumes that the same phenomenon may increase with the passage of time that would, in turn, result in the formation of more bilingual compound or hybrid words.

Keywords: code-mixing, bilingual compound words, pashto-english contact, hybrid words, inflectional lexical morpheme

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Authors: Muhammad Hassan, Kemal Celebi

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Developing a highly efficient electrochromic energy storage device with sufficient color fluctuation and significant electrochemical performance is highly desirable for practical energy-saving applications. Here, to achieve a highly stable material with a large electrochemical storage capacity, a W₁₈O₄₉ NW/Ti₃C₂Tₓ composite has been fabricated and deposited on a pre-assembled Ag and W₁₈O₄₉ NW conductive network by Langmuir-Blodgett technique. The resulting hybrid electrode composed of 15 layers of W₁₈O₄₉ NW/Ti₃C₂Tₓ exhibits an areal capacitance of 125 mF/cm², with a fast and reversible switching response. An optical modulation of 98.2% can be maintained at a current density of 5 mAcm⁻². Using this electrode, we fabricated a bifunctional symmetric electrochromic supercapacitor device having an energy density of 10.26 μWh/cm² and a power density of 0.605 mW/cm², with high capacity retention and full columbic efficiency over 4000 charge-discharge cycles. Meanwhile, the device displays remarkable electrochromic characteristics, including fast switching time (5 s for coloring and 7 s for bleaching) and a significant coloration efficiency of 116 cm²/C with good optical modulation stability. In addition, the device exhibits remarkable mechanical flexibility and fast switching while being stable over 100 bending cycles, which is promising for real-world applications.

Keywords: MXene, nanowires, supercapacitor, ion diffusion, electrochromic, coloration efficiency

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Authors: S. Rodosik, J. P. Poirot-Crouvezier, Y. Bultel

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With the expansion of the hydrogen economy, Proton Exchange Membrane Fuel Cell (PEMFC) systems are often presented as promising energy converters suitable for transport applications. However, reaching a durability of 5000 h recommended by the U.S. Department of Energy and decreasing system cost are still major hurdles to their development. In order to increase the system efficiency and simplify the system without affecting the fuel cell lifetime, an architecture called alternative fuel feeding has been developed. It consists in a fuel cell stack divided into two parts, alternatively fed, implemented on a 5-kW system for real scale testing. The operation strategy can be considered close to Dead End Anode (DEA) with specific modifications to avoid water and nitrogen accumulation in the cells. The two half-stacks are connected in series to enable each stack to be alternatively fed. Water and nitrogen accumulated can be shifted from one half-stack to the other one according to the alternative feeding frequency. Thanks to the homogenization of water vapor along the stack, water management was improved. The operating conditions obtained at system scale are close to recirculation without the need of a pump or an ejector. In a first part, a performance comparison with the DEA strategy has been performed. At high temperature and low pressure (80°C, 1.2 bar), performance of alternative fuel feeding was higher, and the system efficiency increased. In a second part, in order to highlight the benefits of the architecture on the fuel cell lifetime, two durability tests, lasting up to 1000h, have been conducted. A test on the 5-kW system has been compared to a reference test performed on a test bench with a shorter stack, conducted with well-controlled operating parameters and flow-through hydrogen strategy. The durability test is based upon the Fuel Cell Dynamic Load Cycle (FC-DLC) protocol but adapted to the system limitations: without OCV steps and a maximum current density of 0.4 A/cm². In situ local measurements with a segmented S++® plate performed all along the tests, showed a more homogeneous distribution of the current density with alternative fuel feeding than in flow-through strategy. Tests performed in this work enabled the understanding of this architecture advantages and drawbacks. Alternative fuel feeding architecture appeared to be a promising solution to ensure the humidification function at the anode side with a simplified fuel cell system.

Keywords: automotive conditions, durability, fuel cell system, proton exchange membrane fuel cell, stack architecture

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Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.

Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma

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Authors: Mauricio Quintero Angel, Alexander Pereira, Selene Alarcón

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One of the elements of greatest importance in agricultural production is the harvesting; an activity associated to different occupational health risks such as harvesting in high altitudes, the transport of heavy materials and the application of excessive muscle strain that leads to muscular-bone disorders. Therefore, there is an urgent necessity to improve and validate interventions to reduce exposition and risk to harvesters. This article has the objective of describing the co-development under the ergonomic analysis framework of an assisted manual harvesting tool for peach palm oriented to reduce the risk of death and accidents as it avoid the harvest in heights. The peach palm is a palm tree that is cultivated in Colombia, Perú, Brasil, Costa Rica, among others and that reaches heights of over 20 m, with stipes covered with spines. The fruits are drupes of variable size. For the harvesting of peach palm, in Colombia farmers use the “Marota” or “Climber”, a tool in a closed X shape built in wood, that has two supports adjusted at the stipe, that elevate alternately until reaching a point high enough to grab the bunch that is brought down using a rope. An activity of high risk since it is done at a high altitude without any type of protection and safety measures. The Marota is alternated with a rod, which as variable height between 5 and 12 Meters with a harness system at one end to hold the bunch that is lowered with the whole system (bamboo bunch). The rod is used from the ground or from the Marota in height. As an alternative to traditional tools, the Bajachonta was co-developed with farmers, a tool that employs a traditional bamboo hook system with modifications, to be able to hold it with a rope that passes through a pulley. Once the bunch is hitched, the hook system is detached and this stays attached to the peduncle of the palm tree, afterwards through a pulling force being exerted towards the ground by tensioning the rope, the bunch comes loose to be taken down using a rope and the pulley system to the ground, reducing the risk and efforts in the operation. The bajachonta was evaluated in tree productive zones of Colombia, with innovative farmers, were the adoption is highly probable, with some modifications to improve its efficiency and effectiveness, keeping in mind that the farmers perceive in it an advantage in the reduction of death and accidents by not having to harvest in heights.

Keywords: assisted harvesting, ergonomics, harvesting in high altitudes, participative design, peach palm

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Authors: Peyman Soltani, Mohammad Sadegh Amin Din

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The relation between religion and education has been considered for a long time. Approaching education through religion and sovereignty has been a kind of idealism in past centuries` educational systems and no opposition between religion and education has been felt. The doctrine of human education and training is mentioned in the Qur’an, as the most important reason of Prophet Mohammad ` first revelation, Verse 129 of Chapter Baqara, Verse 164 of Chapter Aali-ʻimraan and verse 2 of Chapter Jumʻah have addressed this issue. During Middle age, temples and mosques were engaged in children education. Religious materials have played an important role in the content of educational courses. In this era, the main goal of education was to study the religious books and behaving in society accordingly. Also in this training period, the European countries were considerably influenced by religion. Children in these countries were trained in churches and monasteries. Training and religion are closely connected with each other. It should be noted that experience and religious knowledge is a heart and emotional issue with no-imposition, therefore, the educational space should be designed in such a way that students, themselves, shift to experiencing some religious feelings. The important factors in Islamic Educational system are as follow: - Religious-based - Strengthening national identity - Authenticity of learner role 4- Importance of teacher` authority role. These factors are explained in Conceptual and intertwined network and in practical process, training each of them, proportional to student needs and conditions, can be the beginning of a course of religious education for students, and can strengthen other elements.

Keywords: education and training, Islamic educational system, the Qur'an, religious knowledge

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Aime P. Lampad-Dela Pena, Rhodora V. Azanza, Cesar L. Villanoy, Ephrime B. Metillo, Aletta T. Yniguez

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Phytoplankton community changes in relation to environmental parameters were compared between and within, the three interconnected basins. Phytoplankton samples were collected from thirteen stations of Baler Bay and Casiguran Sound, Aurora last May 2013 by filtering 10 L buckets of surface water and 5 L Niskin samples at 20 meters and at 30 to 40 meters depths through a 20um sieve. Duplicate samples per station were preserved, counted, and identified up to genus level, in order to determine the horizontal and vertical spatial variation of different phytoplankton functional groups during the summer ebb and flood flow. Baler Bay, Outer and Inner Casiguran Sound had a total of 89 genera from four phytoplankton groups: Diatom (62), Dinoflagellate (25), Silicoflagellate (1) and Cyanobacteria (1). Non-toxic diatom Chaetoceros spp. bloom (averaged 2.0 x 105 to 2.73 x 106 cells L⁻¹) co-existed with Bacteriastrum spp. at surface waters in Inner and Outer Casiguran. Pseudonitzschia spp. (1.73 x 106 cells L⁻¹) bloomed at bottom waters of the innermost embayment near Casiguran mangrove estuary. Cyanobacteria Trichodesmium spp. significantly increased during ebb tide at the mid-water layers (20 meters depth) in the three basins (ranged from 6, 900 to 15, 125 filaments L⁻¹), forming another bloom. Gonyaulax spp. - dominated dinoflagellate did not significantly change with depth across the three basins. Overall, diatoms and dinoflagellates community assemblages significantly changed between sites (p < 0.001) while diatoms and cyanobacteria varied within Casiguran outer and inner sites (p < 0.001) only. Tidal fluctuations significantly affected dinoflagellates and diatom groups (p < 0.001) in inner and baler sites. Chlorophyll significantly varied between (KW, p < 0.001) and within each basins (KW, p < 0.05), no tidal influence, with the highest value at inner Casiguran and at deeper waters indicating deep chlorophyll maxima. Aurora’s distinct shelf morphology favoring counterclockwise circulation pattern, advective transport, and continuous stratification of the water column could basically affect the phytoplankton assemblages and water quality of Baler Bay and Casiguran inner and outer basins. Observed spatial phytoplankton community changes with multi-species diatom and cyanobacteria bloom at different water layers of the three inter-connected embayments would be vital for any environmental management initiatives in Aurora.

Keywords: aurora fronting Philippines Rise, intermonsoon, multi-species diatom bloom, spatial variability

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Authors: Zs. Csanádi, A. Szabó Nagy, J. Szabó, J. Erdős

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Atmospheric aerosols have several important environmental impacts and health effects in point of air quality. Monitoring the PM10-bound polycyclic aromatic hydrocarbons (PAHs) could have important environmental significance and health protection aspects. Benzo(a)pyrene (BaP) is the most relevant indicator of these PAH compounds. In Hungary, the Hungarian Air Quality Network provides air quality monitoring data for several air pollutants including BaP, but these data show only the annual mean concentrations and maximum values. Seasonal variation of BaP concentrations comparing the heating and non-heating periods could have important role and difference as well. For this reason, the main objective of this study was to assess the annual concentration and seasonal variation of BaP associated with PM10 in the ambient air of Northwestern Hungary seven different sampling sites (six urban and one rural) in the sampling period of 2008–2013. A total of 1475 PM10 aerosol samples were collected in the different sampling sites and analyzed for BaP by gas chromatography method. The BaP concentrations ranged from undetected to 8 ng/m3 with the mean value range of 0.50-0.96 ng/m3 referring to all sampling sites. Relatively higher concentrations of BaP were detected in samples collected in each sampling site in the heating seasons compared with non-heating periods. The annual mean BaP concentrations were comparable with the published data of the other Hungarian sites.

Keywords: air quality, benzo(a)pyrene, PAHs, polycyclic aromatic hydrocarbons

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Authors: Ahlyum Mun, Ji-Young Moon, Moon-Seok Yoon, Dong-Jin Baek, Doo-Seok Seo, Oun-Kyong Moon

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There is a growing public concern over the standards of farm animal welfare, with higher standards of food safety. In addition, the recent low incidence of Avian Influenza in laying hens among certificated farms is receiving attention. In this study, we introduce animal welfare systems covering the rearing, transport and slaughter of farm animals in South Korea. The concepts of animal welfare farm certification are based on ensuring the five freedoms of animal. The animal welfare is also achieved by observing the condition of environment including shelter and resting area, feeding and water and the care for the animal health. The certification of farm animal welfare is handled by the Animal Protection & Welfare Division of Animal and Plant Quarantine Agency (APQA). Following the full amendment of Animal Protection Law in 2011, animal welfare farm certification program has been implemented since 2012. The certification system has expanded to cover laying hen, swine, broiler, beef cattle and dairy cow, goat and duck farms. Livestock farmers who want to be certified must apply for certification at the APQA. Upon receipt of the application, the APQA notifies the applicant of the detailed schedule of the on-site examination after reviewing the document and conducts the on-site inspection according to the evaluation criteria of the welfare standard. If the on-site audit results meet the certification criteria, APQA issues a certificate. The production process of certified farms is inspected at least once a year for follow-up management. As of 2017, a total of 145 farms have been certified (95 laying hen farms, 12 swine farms, 30 broiler farms and 8 dairy cow farms). In addition, animal welfare transportation vehicles and slaughterhouses have been designated since 2013 and currently 6 slaughterhouses have been certified. Animal Protection Law has been amended so that animal welfare certification marks can be affixed only to livestock products produced by animal welfare farms, transported through animal welfare vehicles and slaughtered at animal welfare slaughterhouses. The whole process including rearing–transportation- slaughtering completes the farm animal welfare system. APQA established its second 5-year animal welfare plan (2014-2019) that includes setting a minimum standard of animal welfare applicable to all livestock farms, transportation vehicles and slaughterhouses. In accordance with this plan, we will promote the farm animal welfare policy in order to truly advance the Korean livestock industry.

Keywords: animal welfare, farm animal, certification system, South Korea

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Authors: Gregory Kelly, Gary Chai, Sittampalam Manoharan, Deborah Delaney

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A Structural Number (SN) can be calculated for a road pavement from the properties and thicknesses of the surface, base course, sub-base, and subgrade. Historically, the cost of collecting structural data has been very high. Data were initially collected using Benkelman Beams and now by Falling Weight Deflectometer (FWD). The structural strength of pavements weakens over time due to environmental and traffic loading factors, but due to a lack of data, no structural deterioration curve for pavements has been implemented in a Pavement Management System (PMS). International Roughness Index (IRI) is a measure of the road longitudinal profile and has been used as a proxy for a pavement’s structural integrity. This paper offers two conceptual methods to develop Pavement Structural Deterioration Curves (PSDC). Firstly, structural data are grouped in sets by design Equivalent Standard Axles (ESA). An ‘Initial’ SN (ISN), Intermediate SN’s (SNI) and a Terminal SN (TSN), are used to develop the curves. Using FWD data, the ISN is the SN after the pavement is rehabilitated (Financial Accounting ‘Modern Equivalent’). Intermediate SNIs, are SNs other than the ISN and TSN. The TSN was defined as the SN of the pavement when it was approved for pavement rehabilitation. The second method is to use Traffic Speed Deflectometer data (TSD). The road network already divided into road blocks, is grouped by traffic loading. For each traffic loading group, road blocks that have had a recent pavement rehabilitation, are used to calculate the ISN and those planned for pavement rehabilitation to calculate the TSN. The remaining SNs are used to complete the age-based or if available, historical traffic loading-based SNI’s.

Keywords: conceptual, pavement structural number, pavement structural deterioration curve, pavement management system

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Authors: Matias Micheletto, Rodrigo Santos, Sergio F. Ochoa

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In developing countries, the most roads in rural areas are dirt road. They require frequent maintenance since are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the main-tenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like in Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision

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Authors: Mohamed Mahmoud Hasan, Hoda M. O. Mokhtar

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With the gigantic increment in portable applications use and the spread of positioning and location-aware technologies that we are seeing today, new procedures and methodologies for location-based strategies are required. Location recommendation is one of the highly demanded location-aware applications uniquely with the wide accessibility of social network applications that are location-aware including Facebook check-ins, Foursquare, and others. In this paper, we aim to present a new methodology for location recommendation. The proposed approach coordinates customary spatial traits alongside other essential components including shortest distance, and user interests. We also present another idea namely, "activity trajectory" that represents trajectory that fulfills the set of activities that the user is intrigued to do. The approach dispatched acquaints the related distance value to select trajectory(ies) with minimum cost value (distance) and spatial-area to prune unneeded directions. The proposed calculation utilizes the idea of movement direction to prescribe most comparable N-trajectory(ies) that matches the client's required action design with least voyaging separation. To upgrade the execution of the proposed approach, parallel handling is applied through the employment of a MapReduce based approach. Experiments taking into account genuine information sets were built up and tested for assessing the proposed approach. The exhibited tests indicate how the proposed approach beets different strategies giving better precision and run time.

Keywords: location based recommendation, map-reduce, recommendation system, trajectory search

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Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

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The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

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Authors: Germans Natuhwera, Peter Ellis, Acuda Wilson, Anne Merriman, Martha Rabwoni

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Objective: The aim of the study was to diagnose the socio-economic burden and impact of a diagnosis of cervical cancer (CC) in rural women in the context of low-resourced country Uganda, using a phenomenological enquiry. Methods: This was a multi-site phenomenological inquiry, conducted at three hospice settings; Mobile Hospice Mbarara in southwestern, Little Hospice Hoima in Western, and Hospice Africa Uganda Kampala in central Uganda. A purposive sample of women with a histologically confirmed diagnosis of CC was recruited. Data was collected using open-ended audio-recorded interviews conducted in the native languages of participants. Interviews were transcribed verbatim in English, and Braun and Clarke’s (2019) framework of thematic analysis was used. Results: 13 women with a mean age of 49.2 and age range 29-71 participated in the study. All participants were of low socioeconomic status. The majority (84.6%) had advanced disease at diagnosis. A fuller reading of transcripts produced four major themes clustered under; (1) socioeconomic characteristics of women, (2) impact of CC on women’s relationships, (3) disrupted and impaired activities of daily living (ADLs), and (4) economic disruptions. Conclusions: A diagnosis of CC introduces significant socio-economic disruptions in a woman’s and her family’s life. CC causes disability, impairs the woman and her family’s productivity hence exacerbating levels of poverty in the home. High and expensive out-of-pocket expenditure on treatment, investigations, and transport costs further compound the socio-economic burden. Decentralizing cancer care services to regional centers, scaling up screening services, subsidizing costs of cancer care services, or making cervical cancer care treatment free of charge, strengthening monitoring mechanisms in public facilities to curb the vice of healthcare workers soliciting bribes from patients, increased mass awareness campaigns about cancer, training more healthcare professionals in cancer investigation and management, and palliative care, and introducing an introductory course on gynecologic cancers into all health training institutions are recommended.

Keywords: activities of daily living, cervical cancer, out-of-pocket, expenditure, phenomenology, socioeconomic

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Authors: Weera Weerasophon

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This research paper is to study the development of a management model for promoting sustainable tourism of Rajabhat universities in Thailand. Mixed Method Research is applied under the said topic. The researcher has developed a management model to promote sustainable tourism. The objectives of the research are 1) to study the readiness in management sustainable tourism of Rajabhat universities in Thailand 2) to develop a management model for promoting sustainable tourism of those universities. The process of this research is organized in two steps according to the objectives. The results of the research are as in the following: 1. Rajabhat universities have the readiness in management for promoting sustainable tourism. The universities can be developed to be sustainable tourist attraction under the admistrators who have vision and realize the importance of tourism, eager to promote sustainable tourism of the universities by specifying obvious policy plans and management. 2. The management model for promoting sustainable tourism of Rajabhat universities is consisted of the main following factors : 2.1 Master plan and policy, 2.2 Rajabhat universities organization management and personnel administration, 2.3 Assignment and authority, leadership, 2.4 Join network, 2.5 Assurance of quality and controlling, 2.6 Budget management, 2.7 Human Resources management, 2.8 Alliance and co-ordination, 2.9 Tool of marketing. There are also other communal factors for promoting sustainable tourism. They are: local communities, local communities, tourism activities, government and private sectors, communicative technology system, history, tourist attractive, art and culture, internal and external environment including local wisdom heritage. The management model for promoting sustainable tourism can be concluded from these main and communal factors mentioned above.

Keywords: tourism, sustainable tourism, management, Rajabhat University

Procedia PDF Downloads 414

Authors: Surbhi Kaura, Sachin Kandhari, Shahiduz Zafar

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Chronic stroke, characterized by persistent motor deficits, often necessitates comprehensive rehabilitation interventions to improve functional outcomes and mitigate long-term dependency. Luna neurorobotic devices, integrated with EMG feedback systems, provide an innovative platform for facilitating neuroplasticity and functional improvement in stroke survivors. This retrospective study aims to investigate the impact of EMG-based Luna neurorobotic interventions on the strengthening of the affected side in chronic stroke patients. In rehabilitation, active patient participation significantly activates the sensorimotor network during motor control, unlike passive movement. Stroke is a debilitating condition that, when not effectively treated, can result in significant deficits and lifelong dependency. Common issues like neglecting the use of limbs can lead to weakness in chronic stroke cases. In rehabilitation, active patient participation significantly activates the sensorimotor network during motor control, unlike passive movement. This study aims to assess how electromyographic triggering (EMG-triggered) robotic treatments affect walking, ankle muscle force after an ischemic stroke, and the coactivation of agonist and antagonist muscles, which contributes to neuroplasticity with the assistance of biofeedback using robotics. Methods: The study utilized robotic techniques based on electromyography (EMG) for daily rehabilitation in long-term stroke patients, offering feedback and monitoring progress. Each patient received one session per day for two weeks, with the intervention group undergoing 45 minutes of robot-assisted training and exercise at the hospital, while the control group performed exercises at home. Eight participants with impaired motor function and gait after stroke were involved in the study. EMG-based biofeedback exercises were administered through the LUNA neuro-robotic machine, progressing from trigger and release mode to trigger and hold, and later transitioning to dynamic mode. Assessments were conducted at baseline and after two weeks, including the Timed Up and Go (TUG) test, a 10-meter walk test (10m), Berg Balance Scale (BBG), and gait parameters like cadence, step length, upper limb strength measured by EMG threshold in microvolts, and force in Newton meters. Results: The study utilized a scale to assess motor strength and balance, illustrating the benefits of EMG-biofeedback following LUNA robotic therapy. In the analysis of the left hemiparetic group, an increase in strength post-rehabilitation was observed. The pre-TUG mean value was 72.4, which decreased to 42.4 ± 0.03880133 seconds post-rehabilitation, with a significant difference indicated by a p-value below 0.05, reflecting a reduced task completion time. Similarly, in the force-based task, the pre-knee dynamic force in Newton meters was 18.2NM, which increased to 31.26NM during knee extension post-rehabilitation. The post-student t-test showed a p-value of 0.026, signifying a significant difference. This indicated an increase in the strength of knee extensor muscles after LUNA robotic rehabilitation. Lastly, at baseline, the EMG value for ankle dorsiflexion was 5.11 (µV), which increased to 43.4 ± 0.06 µV post-rehabilitation, signifying an increase in the threshold and the patient's ability to generate more motor units during left ankle dorsiflexion. Conclusion: This study aimed to evaluate the impact of EMG and dynamic force-based rehabilitation devices on walking and strength of the affected side in chronic stroke patients without nominal data comparisons among stroke patients. Additionally, it provides insights into the inclusion of EMG-triggered neurorehabilitation robots in the daily rehabilitation of patients.

Keywords: neurorehabilitation, robotic therapy, stroke, strength, paralysis

Procedia PDF Downloads 62