Search results for: green infrastructure network

Authors: Paolo Biancone, Silvana Secinaro, Davide Calandra

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This study explores the integration of Islamic finance principles with environmental, social, and governance (ESG) criteria, focusing on the contribution of Islamic financial instruments to achieving sustainable development goals (SDGs). Through a systematic literature review (SLR) and bibliometric analysis of 66 documents from 2019 to 2024, the research addresses critical gaps by examining the alignment between Islamic finance and ESG, identifying emerging trends, and assessing operational challenges and opportunities. Findings indicate that Islamic finance, mainly through instruments such as green sukuk and Islamic microfinance, demonstrates substantial alignment with ESG objectives, anchored in its ethical principles of risk-sharing, fairness, and avoidance of harmful investments. Nevertheless, scalability and regulatory structures pose significant challenges to broader ESG adoption within Islamic finance. This study offers theoretical and practical implications, proposing that Islamic finance provides a solid framework to address sustainability shortcomings in conventional finance. Furthermore, it highlights future research directions, emphasizing the need for empirical studies on the long-term impact of Islamic financial products on sustainability outcomes and exploring the role of fintech in ESG integration.

Keywords: Islamic finance, ESG, SDGs, bibliometric analysis, Shariah-compliant investments

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Authors: Rufat Nuriyev

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Located in the eastern part of the Republic of Azerbaijan and on the western shore of the Caspian Sea, Gobustan National Reserve was inscribed as Gobustan Rock Art Cultural Landscape into the World Heritage List in 2007. Gobustan is an outstanding rock art landscape, where over 6000 rock engravings were found and registered, since the end of Upper Paleolithic up to the Middle Ages. Being a rock art center, the Gobustan seeks to stimulate public awareness and disseminate knowledge of prehistoric art to enrich educational, cultural and artistic communities regionally, nationally and internationally. Due to the Decree of the President of the Republic of Azerbaijan and the “Action Plan” , planned actions started to realize. Some of them implemented before of stipulated date. For the attraction of visitors and improvement of service quality in the museum-reserve, various activities are organized. The building of a new museum center at the foot of the Beyukdash Mountain has been completed in 2011. Main aims of the new museum building and exhibition was to provide better understanding of the importance of this monument for local community, Azerbaijanian culture and the world. In the Petroglyph Museum at Gobustan, digital and traditional media are closely integrated to reveal the complexity of historical, cultural and artistic meaning of prehistoric rock carvings of Gobustan. Alongside with electronic devices, the visitor gets opportunity of direct contact with artifacts and ancient rock carvings.

Keywords: Azerbaijan, Gobustan, rock art, museum

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Authors: Kiamran Radjabli

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State Estimator became an intrinsic part of Energy Management Systems (EMS). The SCADA measurements received from the field are processed by the State Estimator in order to accurately determine the actual operating state of the power systems and provide that information to other real-time network applications. All EMS vendors offer a State Estimator functionality in their baseline products. However, setting up and ensuring that State Estimator consistently produces a reliable solution often consumes a substantial engineering effort. This paper provides generic recommendations and describes a simple practical approach to efficient tuning of State Estimator, based on the working experience with major EMS software platforms and consulting projects in many electrical utilities of the USA.

Keywords: convergence, monitoring, state estimator, performance, troubleshooting, tuning, power systems

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Authors: L. Godinho, N. Teixeira

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Nowadays, massification of Internet access represents one of the major challenges to the traditional powers of the State, among which the power to control its external image. The virtual world has also sparked the interest of social sciences which consider it a new field of study, an immense open text where sense is expressed. In this paper, that immense text has been accessed to so as to understand the perception Internet users from all over the world have of Portugal. Ours is a quantitative and qualitative approach, as we have resorted to buzz, thematic and category analysis. The results confirm the predominance of sea stereotype in others' vision of the Portuguese people, and evidence that national image has adapted to network communication through processes of individuation and paganization.

Keywords: national image, internet, self-communication, perception

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Authors: Padma Chutoo, Elena Kulinskaya, Ilyas Bakbergenuly, Nicholas Steel, Dmitri Pchejetski

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Transient ischaemic attacks (TIAs) are warning signs for future strokes. TIA patients are at increased risk of stroke and cardio-vascular events after a first episode. A majority of studies on TIA focused on the occurrence of these ancillary events after a TIA. Long-term mortality after TIA received only limited attention. We undertook this study to determine the long-term hazards of all-cause mortality following a first episode of a TIA using anonymised electronic health records (EHRs). We used a retrospective case-control study using electronic primary health care records from The Health Improvement Network (THIN) database. Patients born prior to or in year 1960, resident in England, with a first diagnosis of TIA between January 1986 and January 2017 were matched to three controls on age, sex and general medical practice. The primary outcome was all-cause mortality. The hazards of all-cause mortality were estimated using a time-varying Weibull-Cox survival model which included both scale and shape effects and a random frailty effect of GP practice. 20,633 cases and 58,634 controls were included. Cases aged 39 to 60 years at the first TIA event had the highest hazard ratio (HR) of mortality compared to matched controls (HR = 3.04, 95% CI (2.91 - 3.18)). The HRs for cases aged 61-70 years, 71-76 years and 77+ years were 1.98 (1.55 - 2.30), 1.79 (1.20 - 2.07) and 1.52 (1.15 - 1.97) compared to matched controls. Aspirin provided long-term survival benefits to cases. Cases aged 39-60 years on aspirin had HR of 0.93 (0.84 - 1.00), 0.90 (0.82 - 0.98) and 0.88 (0.80 - 0.96) at 5 years, 10 years and 15 years, respectively, compared to cases in the same age group who were not on antiplatelets. Similar beneficial effects of aspirin were observed in other age groups. There were no significant survival benefits with other antiplatelet options. No survival benefits of antiplatelet drugs were observed in controls. Our study highlights the excess long-term risk of death of TIA patients and cautions that TIA should not be treated as a benign condition. The study further recommends aspirin as the better option for secondary prevention for TIA patients compared to clopidogrel recommended by NICE guidelines. Management of risk factors and treatment strategies should be important challenges to reduce the burden of disease.

Keywords: dual antiplatelet therapy (DAPT), General Practice, Multiple Imputation, The Health Improvement Network(THIN), hazard ratio (HR), Weibull-Cox model

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Amjad F. Alharbi, Bashayer A. Alotaibi, Fahd S. Alotaibi

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The emergence of Internet of Things (IoT) technology provides capabilities for a huge number of smart devices, services and people to be communicate with each other for exchanging data and information over existing network. While as IoT is progressing, it provides many opportunities for new ways of communications as well it introduces many security and privacy threats and challenges which need to be considered for the future of IoT development. In this survey paper, an IoT security issues as threats and current challenges are summarized. The security architecture for IoT are presented from four main layers. Based on these layers, the IoT security requirements are presented to insure security in the whole system. Furthermore, some researches initiatives related to IoT security are discussed as well as the future direction for IoT security are highlighted.

Keywords: Internet of Things (IoT), IoT security challenges, IoT security requirements, IoT security architecture

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Authors: Sunita Singh, Rajani Srivastava

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For natural resource management and in other applications about earth observation revolutionary remote sensing technology plays a significant role. One of such application in monitoring and classification of crop types at spatial and temporal scale, as it provides latest, most precise and cost-effective information. Present study emphasizes the use of three different vegetation indices of Rapid Eye imagery on crop type classification. It also analyzed the effect of each indices on classification accuracy. Rapid Eye imagery is highly demanded and preferred for agricultural and forestry sectors as it has red-edge and NIR bands. The three indices used in this study were: the Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) and all of these incorporated the Red Edge band. The study area is Varanasi district of Uttar Pradesh, India and Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Classification was performed with these three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 85% was obtained using three vegetation indices. The study concluded that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the Rapid Eye imagery can get satisfactory results of classification accuracy without original bands.

Keywords: GNDVI, NDRE, NDVI, rapid eye, vegetation indices

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Authors: Yogi Wibisono Budhi, Ferry Iskandar, Veinardi Suendo, Muhammad Fakhrudin, Neng Tresna Umi Culsum

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Oil palm empty fruit bunch (OPEFB), an abundant agro-waste in Indonesia, is being studied as raw material of Cellulose Nanocrystals (CNC) synthesis. Instead of conventional acid mineral, phosphotungstic acid (H₃PW₁₂O₄₀, HPW) was used to hydrolyze cellulose due to recycling ability and easy handling. Before hydrolysis process, dried EFB was treated by 4% NaOH solution at 90oC for 2 hours and then bleached using 2% NaClO₂ solution at 80oC for 3 hours to remove hemicellulose and lignin. Hydrolysis reaction parameters such as temperature, acid concentration, and reaction time were optimized with fixed solid-liquid ratio of 1:40. Response surface method was used for experimental design to determine the optimum condition of each parameter. HPW was extracted from the mixed solution and recycled with diethyl ether. CNC was separated from the solution by centrifuging and washing with distilled water and ethanol to remove degraded sugars and unreacted celluloses. In this study, pulp from dried EFB produced 44.8% yield of CNC. Dynamic Light Scattering (DLS) analysis showed that most of CNC equivalent diameter was 140 nm. Crystallinity index was observed at 73.3% using X-ray Diffraction (XRD) analysis. Thus, a green established process for the preparation of CNC was achieved.

Keywords: acid hydrolysis, cellulose nanocrystals, oil palm empty fruit bunch, phosphotungstic acid

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Authors: Dongjae Kang, Sokho Son, Jinmee Kim

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Cloud service brokering is a new service paradigm that provides interoperability and portability of application across multiple Cloud providers. In this paper, we designed cloud service brokerage system, any broker, supporting integrated service provisioning and SLA based service life cycle management. For the system design, we introduce the system concept and whole architecture, details of main components and use cases of primary operations in the system. These features ease the Cloud service provider and customer’s concern and support new Cloud service open market to increase cloud service profit and prompt Cloud service echo system in cloud computing related area.

Keywords: cloud service brokerage, multiple Clouds, Integrated service provisioning, SLA, network service

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Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Nazakat Ismailzada, Carol Jones

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Tomato drilling moth Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) is the main pest of tomato plants in many countries. The larvae of tomato leaves, the stems inside, in the end buds, they opened the gallery in green and ripe fruit. In this way the harmful products can be fed with all parts of the tomato plant can cause damage to 80-100%. Pest harms all above ground parts of the tomato plant. After the seedlings are planted in areas and during blossoming holder traps with tomato moth’s rubber capsule inside should be placed in the area by using five-tomato moth’s feremon per ha. Then there should be carried out observations in the fields in every three days regularly. During the researches, it was showed that in field condition Carogen 20 SC besides high-level biological efficiency also has low ecological load for environment, and should be used against tomato moth in farms. Therefore it was showed that in field condition Carogen 20 SC besides high-level biological efficiency also has low ecological load for environment, and should be used against tomato moth in farms with insecticide expenditure norm 320 qr\ha. In farms should be used plant rotation, plant fields should be plowed on the 25-30 sm depth, before sowing seeds should be proceeded by insecticides. As element of integrated plant protection activities, should be used pheromones trap. In tomato plant fields as an insecticide should be used AGROSAN 240 SC and Carogen 20 SP.

Keywords: lepidoptera, Tuta absoluta, chemical control, integrated pest management

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Authors: Ahlem Dhahri, Waleed Omri, Audrey Becuwe, Abdelwahed Omri

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In industrial processes, decision-making ranges across different scales, from process control to supply chain management. The purchasing decision-making process in the supply chain is presently gaining more attention as a critical contributor to the company's strategic success. Given the scarcity of thorough summaries in the prior studies, this bibliometric analysis aims to adopt a meticulous approach to achieve quantitative knowledge on the constantly evolving subject of purchasing decision-making in supply chain management. Through bibliometric analysis, we examine a sample of 358 peer-reviewed articles from the Scopus database. VOSviewer and Gephi software were employed to analyze, combine, and visualize the data. Data analytic techniques, including citation network, page-rank analysis, co-citation, and publication trends, have been used to identify influential works and outline the discipline's intellectual structure. The outcomes of this descriptive analysis highlight the most prominent articles, authors, journals, and countries based on their citations and publications. The findings from the research illustrate an increase in the number of publications, exhibiting a slightly growing trend in this field. Co-citation analysis coupled with content analysis of the most cited articles identified five research themes mentioned as follows integrating sustainability into the supplier selection process, supplier selection under disruption risks assessment and mitigation strategies, Fuzzy MCDM approaches for supplier evaluation and selection, purchasing decision in vendor problems, decision-making techniques in supplier selection and order lot sizing problems. With the help of a graphic timeline, this exhaustive map of the field illustrates a visual representation of the evolution of publications that demonstrate a gradual shift from research interest in vendor selection problems to integrating sustainability in the supplier selection process. These clusters offer insights into a wide variety of purchasing methods and conceptual frameworks that have emerged; however, they have not been validated empirically. The findings suggest that future research would emerge with a greater depth of practical and empirical analysis to enrich the theories. These outcomes provide a powerful road map for further study in this area.

Keywords: bibliometric analysis, citation analysis, co-citation, Gephi, network analysis, purchasing, SCM, VOSviewer

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Authors: Jana Gebhartova, Tomas Duda, Ivan Benes

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World is characterized by constantly emerging new links, increasing complexity and speed of processes in the society. The globalized world needs (except political and financial mechanisms and institutions) functional supply chains. Transport and supply chains can be interrupted in case of natural disasters, conflicts and civil disorders, sudden demand shocks, export/import restrictions, terrorism. Long-term interruption of crucial services for human existence can results in breakdown of the whole society. If global supply chains can be interrupted, the ability to survive a crisis situation depends on local self-sufficiency, it means ensuring water, food and energy. In the world of 21st century, new way of thinking (based on the concept of resilience) is needed. Planning for self-sufficiency and resilience must be part of the agenda of local governments. The paper presents first results of research project VF20112015518 “Security of population – crisis management” that deals with issue of critical infrastructure, ensuring regional self-sufficiency in crisis situations and issues related to population protection and water, energy and food security. The project is being solved within Security Research of Ministry of the Interior of the Czech Republic in 2011-2015.

Keywords: crisis management, resilience, indicators of self-sufficiency, continuity of supplies

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Authors: Mohammadreza Hedyehzadeh, Mahdi Yousefi

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Colon cancer is one of the most common cancer, which predicted to increase its prevalence due to the bad eating habits of peoples. Nowadays, due to the busyness of people, the use of fast foods is increasing, and therefore, diagnosis of this disease and its treatment are of particular importance. To determine the best treatment approach for each specific colon cancer patients, the oncologist should be known the stage of the tumor. The most common method to determine the tumor stage is TNM staging system. In this system, M indicates the presence of metastasis, N indicates the extent of spread to the lymph nodes, and T indicates the size of the tumor. It is clear that in order to determine all three of these parameters, an imaging method must be used, and the gold standard imaging protocols for this purpose are CT and PET/CT. In CT imaging, due to the use of X-rays, the risk of cancer and the absorbed dose of the patient is high, while in the PET/CT method, there is a lack of access to the device due to its high cost. Therefore, in this study, we aimed to estimate the tumor size and the extent of its spread to the lymph nodes using MR images. More than 1300 MR images collected from the TCIA portal, and in the first step (pre-processing), histogram equalization to improve image qualities and resizing to get the same image size was done. Two expert radiologists, which work more than 21 years on colon cancer cases, segmented the images and extracted the tumor region from the images. The next step is feature extraction from segmented images and then classify the data into three classes: T0N0، T3N1 و T3N2. In this article, the VGG-16 convolutional neural network has been used to perform both of the above-mentioned tasks, i.e., feature extraction and classification. This network has 13 convolution layers for feature extraction and three fully connected layers with the softmax activation function for classification. In order to validate the proposed method, the 10-fold cross validation method used in such a way that the data was randomly divided into three parts: training (70% of data), validation (10% of data) and the rest for testing. It is repeated 10 times, each time, the accuracy, sensitivity and specificity of the model are calculated and the average of ten repetitions is reported as the result. The accuracy, specificity and sensitivity of the proposed method for testing dataset was 89/09%, 95/8% and 96/4%. Compared to previous studies, using a safe imaging technique (MRI) and non-use of predefined hand-crafted imaging features to determine the stage of colon cancer patients are some of the study advantages.

Keywords: colon cancer, VGG-16, magnetic resonance imaging, tumor size, lymph node metastasis

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Authors: Gulfam Haider, sana danish

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Convolutional Neural Networks (CNNs) have emerged as powerful tools for image classification, and the choice of optimizers profoundly affects their performance. The study of optimizers and their adaptations remains a topic of significant importance in machine learning research. While numerous studies have explored and advocated for various optimizers, the efficacy of these optimization techniques is still subject to scrutiny. This work aims to address the challenges surrounding the effectiveness of optimizers by conducting a comprehensive analysis and evaluation. The primary focus of this investigation lies in examining the performance of different optimizers when employed in conjunction with the popular activation function, Rectified Linear Unit (ReLU). By incorporating ReLU, known for its favorable properties in prior research, the aim is to bolster the effectiveness of the optimizers under scrutiny. Specifically, we evaluate the adjustment of these optimizers with both the original Softmax activation function and the modified ReLU activation function, carefully assessing their impact on overall performance. To achieve this, a series of experiments are conducted using a well-established benchmark dataset for image classification tasks, namely the Canadian Institute for Advanced Research dataset (CIFAR-10). The selected optimizers for investigation encompass a range of prominent algorithms, including Adam, Root Mean Squared Propagation (RMSprop), Adaptive Learning Rate Method (Adadelta), Adaptive Gradient Algorithm (Adagrad), and Stochastic Gradient Descent (SGD). The performance analysis encompasses a comprehensive evaluation of the classification accuracy, convergence speed, and robustness of the CNN models trained with each optimizer. Through rigorous experimentation and meticulous assessment, we discern the strengths and weaknesses of the different optimization techniques, providing valuable insights into their suitability for image classification tasks. By conducting this in-depth study, we contribute to the existing body of knowledge surrounding optimizers in CNNs, shedding light on their performance characteristics for image classification. The findings gleaned from this research serve to guide researchers and practitioners in making informed decisions when selecting optimizers and activation functions, thus advancing the state-of-the-art in the field of image classification with convolutional neural networks.

Keywords: deep neural network, optimizers, RMsprop, ReLU, stochastic gradient descent

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Authors: Jürgen Keil, Frank Walther

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This article presents two innovative solutions for vertical vibration mitigation barriers including experimental and numerical investigations on the completed barriers. There is a continuing growth of exposure to noise and vibration in people´s daily lives due to the quest for more mobility and flexibility. In previous times neglected, immissions caused by vibrations can lead, for example, to secondary noise or damage in the adjacent buildings. Also people can feel very affected by vibrations. But unlike in new construction, in existing infrastructure and buildings action can be taken almost only on the transmission path of those vibrations. In the following two solutions were shown how vibrations on the transmission path can be mitigated. These are the jet grouting method and a new installation method (patent pending) by means of a prefabricated hollow box which is filled with vibration reducing mats and driven down to depth, are presented. The essential results of the numerical and experimental investigations on the completed wave barriers are included as well. This article is based on the results of a field test with the participation of Keller Holding, which was executed in the context of the European research project RIVAS (Railway Induced Vibration Abatement Solutions), and on a thesis done at the Technical University of Dresden with the involvement of BAUGRUND DRESDEN Ingenieurgesellschaft mbH and the Keller Holding GmbH.

Keywords: jet grouting, rail way lines, vertical vibration mitigation, vibration reducing mats

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Authors: Le Zhao, Alain Nogaret

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We have built universal Central Pattern Generator (CPG) hardware by interconnecting Hodgkin-Huxley neurons with reciprocally inhibitory synapses. We investigate the dynamics of neuron oscillations as a function of the time delay between current steps applied to individual neurons. We demonstrate stimulus dependent switching between spiking polyrhythms and map the phase portraits of the neuron oscillations to reveal the basins of attraction of the system. We experimentally study the dependence of the attraction basins on the network parameters: the neuron response time and the strength of inhibitory connections.

Keywords: central pattern generator, winnerless competition principle, artificial neural networks, synapses

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Authors: R. S. Al Abri, M. H. Albadi, M. H. Al Abri, U. K. Al Rasbi, M. H. Al Hasni, S. M. Al Shidi

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This paper presents an analysis study on the impacts of the changes of the capacitor banks, the loss of a transformer, and the installation of distributed generation on the voltage total harmonic distortion and harmonic resonance. The study is applied in a real system in Oman, Sohar Industrial Port–C Substation Network. Frequency scan method and Fourier series analysis method are used with the help of EDSA software. Moreover, the results are compared with limits specified by national Oman distribution code.

Keywords: power quality, capacitor bank, voltage total harmonics distortion, harmonic resonance, frequency scan

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Authors: Min Chen, Hui Lin

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VGEs are a kind of typical web- and computer-based geographic environment, with aims of merging geographic knowledge, computer technology, virtual reality technology, network technology, and geographic information technology, to provide a digital mirror of physical geographic environments to allow users to ‘feel it in person’ by a means for augmenting the senses and to ‘know it beyond reality’ through geographic phenomena simulation and collaborative geographic experiments. Many achievements have appeared in this field, but further evolution should be explored. With the exploration of the conception of VGEs, and some examples, this article illustrated the role of VGEs and their contribution to currently GIScience. Based on the above analysis, questions are proposed for discussing about the future way of VGEs.

Keywords: virtual geographic environments (VGEs), GIScience, virtual reality, geographic information systems

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Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

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The paper is focused on the operational model for transport the single wagon consignments on railway network by using two different models of train formation. The paper gives an overview of possibilities of improving the quality of transport services. Paper deals with two models used in problematic of train formatting - time continuously and time discrete. By applying these models in practice, the transport company can guarantee a higher quality of service and expect increasing of transport performance. The models are also applicable into others transport networks. The models supplement a theoretical problem of train formation by new ways of looking to affecting the organization of wagon flows.

Keywords: train formation, wagon flows, marshalling yard, railway technology

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Authors: Narendra Akhadkar, Philippe Delcambre

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In power protection and control products, assembly process variations due to the individual parts manufactured from single or multi-cavity tooling is a major problem. The dimensional and geometrical variations on the individual parts, in the form of manufacturing tolerances and assembly tolerances, are sources of clearance in the kinematic joints, polarization effect in the joints, and tolerance stack-up. All these variations adversely affect the quality of product, functionality, cost, and time-to-market. Variation simulation analysis may be used in the early product design stage to predict such uncertainties. Usually, variations exist in both manufacturing processes and materials. In the tolerance analysis, the effect of the dimensional and geometrical variations of the individual parts on the functional characteristics (conditions) of the final assembled products are studied. A functional characteristic of the product may be affected by a set of interrelated dimensions (functional parameters) that usually form a geometrical closure in a 3D chain. In power protection and control products, the prerequisite is: when a fault occurs in the electrical network, the product must respond quickly to react and break the circuit to clear the fault. Usually, the response time is in milliseconds. Any failure in clearing the fault may result in severe damage to the equipment or network, and human safety is at stake. In this article, we have investigated two important functional characteristics that are associated with the robust performance of the product. It is demonstrated that the experimental data obtained at the Schneider Electric Laboratory prove the very good prediction capabilities of the variation simulation performed using CETOL (tolerance analysis software) in an industrial context. Especially, this study allows design engineers to better understand the critical parts in the product that needs to be manufactured with good, capable tolerances. On the contrary, some parts are not critical for the functional characteristics (conditions) of the product and may lead to some reduction of the manufacturing cost, ensuring robust performance. The capable tolerancing is one of the most important aspects in product and manufacturing process design. In the case of miniature circuit breaker (MCB), the product's quality and its robustness are mainly impacted by two aspects: (1) allocation of design tolerances between the components of a mechanical assembly and (2) manufacturing tolerances in the intermediate machining steps of component fabrication.

Keywords: geometrical variation, product robustness, tolerance analysis, variation simulation

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Authors: Veronique Jubera, Guillaume Salek, Manuel Gaudon, Alain Garcia, Alain Demourgues

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Luminescence of transition metal and rare earth elements cover ultraviolet to far infrared wavelengths. Applications of phosphors are numerous. One can cite lighting, sensing, laser, energy, medical or military applications. But regarding each domain, specific criteria are required and they can be achieved with a strong control of the chemical composition. Emission of doped materials can be tailored with modifications of the local environment of the cations. For instance, the increase of the crystal field effect shifts the divalent manganese radiative transitions from the green to the red color. External factor as heat-treatment can induce changes of the doping element location or modify the unit cell crystalline symmetry. By controlling carefully the synthesis route, it is possible to initiate emission shift and to establish the thermal history of a compound. We propose to demonstrate through the luminescence of divalent manganese and trivalent rare earth doped oxide, that it is possible to follow the thermal history of a material. After optimization of the synthesis route, structural and optical properties are discussed. Finally, thermal calibration graphs are successfully established on these doped compounds. This makes these materials promising probe for thermal sensing.

Keywords: emission, thermal sensing, transition metal, rare eath element

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Authors: Mimoun Melliti

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In the wake of the global pandemic, educational systems worldwide faced unprecedented challenges and had to swiftly adapt to new conditions. This necessitated a fundamental shift in assessment processes, as traditional in-person exams became impractical. The present paper aims to investigate how educational systems have adapted to the new conditions imposed by the outbreak of the pandemic. This paper serves as a case study documenting the various decisions, conditions, experiments, and outcomes associated with transitioning the assessment processes of a higher education institution to a fully online format. The participants of this study consisted of 4666 students from health, engineering, science, and humanities disciplines, who were enrolled in general English (Eng101/104) and English for specific purposes (Eng102/113) courses at a preparatory year institution in Saudi Arabia. The findings of this study indicate that online assessment can be effectively implemented given the fulfillment of specific requirements. These prerequisites encompass the presence of competent staff, administrative flexibility, and the availability of necessary infrastructure and technological support. The significance of this case study lies in its comprehensive description of the various steps and measures undertaken to adapt to the "new normal" situation. Furthermore, it evaluates the impact of these measures and offers detailed recommendations for potential similar future scenarios.

Keywords: hybrid learning, testing, adaptive teaching, EFL

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Authors: Raiya Kishwar Ashraf

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The National University, the largest public educational institution in Bangladesh, recently made it mandatory for all students to study a course in Bangladesh‘s history of the 1971 Liberation War. This introduction was accompanied by massive political, financial and academic movement that allocated resources towards achieving greater awareness of the country‘s spirit, goals of liberation and patriotism among the youth. This study argues that the infrastructure and political economy around the course heavily politicizes the education system and more specifically the teaching and learning the process. By conducting a qualitative study in three affiliated colleges under the National University, this study aimed to explore the extent to which politicization affected higher education curriculum, especially history education in Bangladesh. The findings revealed significant levels of politicization and structural constraints present in the process that restricts the teacher and student engagement with course materials. The results of this study are useful for curriculum designers and higher education teachers and staffs who wish to develop content and deliver education that promotes critical inquiry among students. The findings further shed light on the importance of identifying and addressing political influences in education curriculum and programme development.

Keywords: Bangladesh higher education, critical thinking, curriculum politicization, history curriculum, National University, teaching-learning method

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Authors: A. Bouamrane, M. T. Bouziane, K. Boutebba, Y. Djebbar

Abstract:

This paper aims to develop a decision support tool to provide solutions to the problems of sewer networks management/maintenance in order to assist the manager to sort sections upon priority of intervention by taking account of the technical, economic, social and environmental standards as well as the managers’ strategy. This solution uses the Analytic Network Process (ANP) developed by Thomas Saaty, coupled with a set of tools for modelling and collecting integrated data from a geographic information system (GIS). It provides to the decision maker a tool adapted to the reality on the ground and effective in usage compared to the means and objectives of the manager.

Keywords: multi-criteria decision support, maintenance, Geographic Information System, modelling

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Authors: Arshad Munir, Naseem Akhtar

Abstract:

The determination of the Sufi is to effort towards unity. His main purpose is to bring humanity, separated as it is into so many different units, closer together in the deeper understanding of life. His mission is to bring about brotherhood among races, nations and faiths and to respect one another's faith, scripture and teacher. Sufi is to confer sympathy on these lives, to impart love, compassion and kindheartedness on all creations. The Sufi message is the resonance of the same Divine message which has always come and will always come to inform humanity. It is the continuation of all the pronounced religions which have come at several times and it is amalgamation of them all, which was the wish of all the prophets. Pakistan, who came into being in the name of Islam unfortunately, have linked with terrorism. It is a disgrace that in contemporary day Pakistan, mullahism and the recent cancer of Talibanisation are gradually eating into what had kept us integral as a society. Terrorism has grown-up to develop a prime safety pressure to the area. The terrorism has deadly caused decrease in overseas and local investment, exports, physical infrastructure, and wealth stock ultimately leading to damage of the socio-economic status of Pakistan. Main reasons are ignorance about the actual teaching of Islam both by Muslim and non-Muslim, exploitation by the religious and political influential, sectarianism and extremism, lack of tolerance and broadmindedness and reaction and retortion by the sufferer. The key treatment and therapy of the abovementioned illnesses exist in the messages of Sufism.

Keywords: sufism, love, Pakistan, terrorism

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Authors: F. Benkaci-Ali, R. Mékaoui, G. Scholl, G. Eppe

Abstract:

The new methods as accelerated steam distillation assisted by microwave (ASDAM) is a combination of microwave heating and steam distillation, performed at atmospheric pressure at very short extraction time. Isolation and concentration of volatile compounds are performed by a single stage. (ASDAM) has been compared with (ASDAM) with cryogrinding of seeds (CG) and a conventional technique, hydrodistillation assisted by microwave (HDAM), hydro-distillation (HD) for the extraction of essential oil from aromatic herb as caraway and cumin seeds. The essential oils extracted by (ASDAM) for 1 min were quantitatively (yield) and qualitatively (aromatic profile) no similar to those obtained by ASDAM-CG (1 min) and HD (for 3 h). The accelerated microwave extraction with cryogrinding inhibits numerous enzymatic reactions as hydrolysis of oils. Microwave radiations constitute the adequate mean for the extraction operations from the yields and high content in major component majority point view, and allow to minimise considerably the energy consumption, but especially heating time too, which is one of essential parameters of artifacts formation. The ASDAM and ASDAM-CG are green techniques and yields an essential oil with higher amounts of more valuable oxygenated compounds comparable to the biosynthesis compounds, and allows substantial savings of costs, in terms of time, energy and plant material.

Keywords: microwave, steam distillation, caraway, cumin, cryogrinding, GC-MS, GCxGC-MS

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Authors: René Čechmánek, Vladan Prachař, Ludvík Lederer, Jiří Loskot

Abstract:

Thin-walled elements with a matrix set on a base of high-valuable Portland cement with dispersed reinforcement from alkali-resistant glass fibres are used in a range of applications as claddings of buildings and infrastructure constructions as well as various architectural elements of residential buildings. Even if their elementary thickness and therefore total weight is quite low, architects and building companies demand on even further decreasing of the bulk density of these fibre-cement elements for the reason of loading elimination of connected superstructures and easier assembling in demand conditions. By the means of various kinds of light-weight aggregates it is possible to achieve light-weighing of thin-walled fibre-cement composite elements. From the range of possible fillers with different material properties granulated expanded glass worked the best. By the means of laboratory testing an effect of two fillers based on expanded glass on the fibre reinforced cement composite was verified. Practical applicability was tested in the production of commonly manufactured glass fibre reinforced concrete elements, such as channels for electrical cable deposition, products for urban equipment and especially various cladding elements. Even if these are not structural elements, it is necessary to evaluate also strength characteristics and resistance to environment for their durability in certain applications.

Keywords: fibre-cement composite, granulated expanded glass, light-weighing

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Authors: Milton Jusu, Moses Koroma

Abstract:

Efforts by the Ministry of Fisheries and Marine Resources and its development partners to introduce “modern” aquaculture in Sierra Leone since the 1970s have not been successful. A number of reasons have been hypothesized, including the suggestion that the market infrastructure and demand for farmed fish were inadequate to stimulate large-scale and widespread aquaculture production in the country. We have assessed the size, structure, networks and opportunities in fish markets using a combination of Participatory Rural Appraisals (PRAs) and questionnaire surveys conducted in a sample of 29 markets (urban, weekly, wholesale and retail) and two hundred traders. The study showed that the local fish markets were dynamic, with very high variations in demand and supply. The markets sampled supplied between 135.2 and 9947.6 tonnes/year. Mean prices for fresh fish varied between US$1.12 and US$3.89/kg depending on species, with smoked catfish and shrimps commanding prices as high as US$7.4/kg. It is unlikely that marine capture fisheries can increase their current production levels, and these may, in fact, already be over-exploited and declining. Marine fish supplies are particularly low between July and September. More careful attention to the timing of harvests (rainy season, not dry season) and to species (catfish, not tilapia) (could help in the successful adoption of aquaculture.

Keywords: fisheries and aquaculture, fish market, marine fish supplies, harvests

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