Search results for: mobility features

Authors: Eder Amayuelas, Begoña Bazán, M. Karmele Urtiaga, Gotzone Barandika, María I. Arriortua

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Metal Organic Frameworks (MOFs) have attracted great interest in recent years, taking a lead role in the field of catalysis, drug delivery, sensors and absorption. In the past decade, promising results have been reported specifically in the field of adsorption, based on the topology and chemical features of this type of porous material. Thus, its application in industry and environment for the adsorption of pollutants is presented as a response to an increasingly important need. In this area, organic dyes are nowadays widely used in many industries including medicine, textile, leather, printing and plastics. The consequence of this fact is that dyes are present as emerging pollutants in soils and water where they remain for long periods of time due to their high stability, with a potential risk of toxicity in wildlife and in humans. On the other hand, the presence of iodine in soils, water and gas as a nuclear activity pollutant product or its extended use as a germicide is still a problem in many countries, which indicates the imperative need for its removal. In this context, this work presents the characterization as an adsorbent of the activated compound αMOP@Ei2-1 obtained from the already reported [Cu₂₄(m-BDC)₂₄(DMF)₂₀(H₂O)₄]•24DMF•40H₂O (MOP@Ei2-1), where m-BDC is the 1,3-benzenedicarboxylic ligand and DMF is N,N′-dimethylformamide. The structure of MOP@Ei2-1 consists of Cu24 clusters arranged in such a way that 12 paddle-wheels are connected through m-BDC ligands. The clusters exhibit an internal cavity where crystallization molecules of DMF and water are located. Adsorption of dyes and iodine as pollutant examples has been carried out, focusing attention on the kinetics of the rapid process.

Keywords: adsorption, organic dyes, iodine, metal organic frameworks

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Authors: Christelle Rabbat, Carole Vouebou, Sary Awad, Alan Jean-Marie

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Hydrogen has been proven to be a viable alternative to standard fuels as it is easy to produce and only generates water vapour and zero carbon emissions. However, despite the hydrogen benefits, the widespread adoption of hydrogen fuel cell vehicles and internal combustion engine vehicles is impeded by several challenges. The lack of refueling infrastructures remains one of the main hindering factors due to the high costs associated with their design, construction, and operation. Besides, the lack of hydrogen vehicles on the road diminishes the economic viability of investing in refueling infrastructure. Simultaneously, the absence of accessible refueling stations discourages consumers from adopting hydrogen vehicles, perpetuating a cycle of limited market uptake. To address these challenges, the implementation of adequate policies incentivizing the use of hydrogen vehicles and the reduction of the investment and operation costs of hydrogen refueling stations (HRS) are essential to put both investors and customers at ease. Even though the transition to hydrogen cars has been rather slow, public transportation companies have shown a keen interest in this highly promising fuel. Besides, their hydrogen demand is easier to predict and regulate than personal vehicles. Due to the reduced complexity of designing a suitable hydrogen supply chain for public vehicles, this sub-sector could be a great starting point to facilitate the adoption of hydrogen vehicles. Consequently, this study will focus on designing a chain of on-site green HRS for the public transportation network in Nantes Metropole leveraging the latest relevant technological advances aiming to reduce the costs while ensuring reliability, safety, and ease of access. To reduce the cost of HRS and encourage their widespread adoption, a network of 7 H35-T40 HRS has been designed, replacing the conventional J-T valves with turbo-expanders. Each station in the network has a daily capacity of 1,920 kg. Thus, the HRS network can produce up to 12.5 tH2 per day. The detailed cost analysis has revealed a CAPEX per station of 16.6 M euros leading to a network CAPEX of 116.2 M euros. The proposed station siting prioritized Nantes metropole’s 5 bus depots and included 2 city-centre locations. Thanks to the turbo-expander technology, the cooling capacity of the proposed HRS is 19% lower than that of a conventional station equipped with J-T valves, resulting in significant CAPEX savings estimated at 708,560 € per station, thus nearly 5 million euros for the whole HRS network. Besides, the turbo-expander power generation ranges from 7.7 to 112 kW. Thus, the power produced can be used within the station or sold as electricity to the main grid, which would, in turn, maximize the station’s profit. Despite the substantial initial investment required, the environmental benefits, cost savings, and energy efficiencies realized through the transition to hydrogen fuel cell buses and the deployment of HRS equipped with turbo-expanders offer considerable advantages for both TAN and Nantes Metropole. These initiatives underscore their enduring commitment to fostering green mobility and combatting climate change in the long term.

Keywords: green hydrogen, refueling stations, turbo-expander, heavy-duty vehicles

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Authors: Bashir Ahmad Amiri, Nsenda Lukumwena

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The developing economies are experiencing an unprecedented rate of urbanization, mainly the urbanization of poverty which is leading to sprawling of slums and informal settlement. Kabul, being the capital and primate city of Afghanistan is grossly encountered to the informal settlement where the majority of the people consider to be informal. Despite all efforts to upgrade and minimize the growth of these settlements, they are growing rapidly. Various interventions have been taken by the government and some international organizations from physical upgrading to urban renewal, but none of them have succeeded to solve the issue of informal settlement. The magnitude of the urbanization and the complexity of informal settlement in Kabul city, and the institutional and capital constraint of the government calls for integration and optimization of currently practiced strategies. This paper provides an overview of informal settlement formation and the conventional upgrading strategies in Kabul city to identify the dominant/successful practices and rationalize the conventional upgrading modes. For this purpose, Hothkhel has been selected as the case study, since it represents the same situation of major informal settlements of the city. Considering the existing potential and features of the Hothkhel and proposed land use by master plan this paper intends to find a suitable upgrading mode for the study area and finally to scale up the model for the city level upgrading. The result highlights that the informal settlements of Kabul city have high (re)development capacity for accepting the additional room without converting the available agricultural area to built-up. The result also indicates that the integrated multi-sector upgrading has the scale-up potential to increase the reach of beneficiaries and to ensure an inclusive and efficient urbanization.

Keywords: informal settlement, upgrading strategies, Kabul city, urban expansion, integrated multi-sector, scale-up

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Authors: A. Bahmanpour, I. Eames, C. Klettner, A. Dimakopoulos

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We develop a new set of diagnostic tools to analyze inundation into a model district using three-dimensional CFD simulations, with a view to generating a database against which to test simpler models. A three-dimensional model of Oregon city with different-sized groups of building next to the coastline is used to run calculations of the movement of a long period wave on the shore. The initial and boundary conditions of the off-shore water are set using a nonlinear inverse method based on Eulerian spatial information matching experimental Eulerian time series measurements of water height. The water movement is followed in time, and this enables the pressure distribution on every surface of each building to be followed in a temporal manner. The three-dimensional numerical data set is validated against published experimental work. In the first instance, we use the dataset as a basis to understand the success of reduced models - including 2D shallow water model and reduced 1D models - to predict water heights, flow velocity and forces. This is because models based on the shallow water equations are known to underestimate drag forces after the initial surge of water. The second component is to identify critical flow features, such as hydraulic jumps and choked states, which are flow regions where dissipation occurs and drag forces are large. Finally, we describe how future tsunami inundation models should be modified to account for the complex effects of buildings through drag and blocking.Financial support from UCL and HR Wallingford is greatly appreciated. The authors would like to thank Professor Daniel Cox and Dr. Hyoungsu Park for providing the data on the Seaside Oregon experiment.

Keywords: computational fluid dynamics, extreme events, loading, tsunami

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Authors: Zerihun Yohannes Amare, Belayneh Birku Geremew, Nigatu Melise Kebede, Sisaynew Getahun Amera

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In Ethiopia, agricultural production is predominantly rainfed. The El Niño Southern Oscillation (ENSO) is the driver of climate variability, which affects the agricultural production system in the country. This paper aims to study trends, variability of rainfall, and impacts of El Niño Southern Oscillation (ENSO) on rainfall amount. The study was carried out in Ethiopia's Western Amhara National Regional State, which features a variety of seasons that characterize the nation. Monthly rainfall data were collected from fifteen meteorological stations of Western Amhara. Selected El Niño and La Niña years were also extracted from National Oceanic and Atmospheric Administration (NOAA) from 1986 to 2015. Once the data quality was checked and inspected, the monthly rainfall data of the selected stations were arranged in Microsoft Excel Spreadsheet and analyzed using XLSTAT software. The coefficient of variation and the Mann-Kendall non-parametric statistical test was employed to analyze trends and variability of rainfall and temperature. The long-term recorded annual rainfall data indicated that there was an increasing trend from 1986 to 2015 insignificantly. The rainfall variability was less (Coefficient of Variation, CV = 8.6%); also, the mean monthly rainfall of Western Amhara decreased during El Niño years and increased during La Niña years, especially in the rainy season (JJAS) over 30 years. This finding will be useful to suggest possible adaptation strategies and efficient use of resources during planning and implementation.

Keywords: rainfall, Mann-Kendall test, El Niño, La Niña, Western Amhara, Ethiopia

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Chi-Ching Lee, Po-Jung Huang, Kuo-Yang Huang, Petrus Tang

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Background: Recent advances in high-throughput research technologies such as new-generation sequencing and multi-dimensional liquid chromatography makes it possible to dissect the complete transcriptome and proteome in a single run for the first time. However, it is almost impossible for many laboratories to handle and analysis these “BIG” data without the support from a bioinformatics team. We aimed to provide a web-based analysis platform for users with only limited knowledge on bio-computing to study the functional genomics and proteomics. Method: We use NCI-60 as an example dataset to demonstrate the power of the web-based analysis platform and data delivering system: C-eXpress takes a simple text file that contain the standard NCBI gene or protein ID and expression levels (rpkm or fold) as input file to generate a distribution map of gene/protein expression levels in a heatmap diagram organized by color gradients. The diagram is hyper-linked to a dynamic html table that allows the users to filter the datasets based on various gene features. A dynamic summary chart is generated automatically after each filtering process. Results: We implemented an integrated database that contain pre-defined annotations such as gene/protein properties (ID, name, length, MW, pI); pathways based on KEGG and GO biological process; subcellular localization based on GO cellular component; functional classification based on GO molecular function, kinase, peptidase and transporter. Multiple ways of sorting of column and rows is also provided for comparative analysis and visualization of multiple samples.

Keywords: cancer, visualization, database, functional annotation

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Authors: Taher M. Abou-deif, Esmail M. El-Bialy, Essam E. Khalil

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The paper is devoted to numerically investigating the influence of the air supply outlets geometry on human comfort inside living looms. A computational fluid dynamics model is developed to examine the air flow characteristics of a room with different supply air diffusers. The work focuses on air flow patterns, thermal behavior in the room with few number of occupants. As an input to the full-scale 3-D room model, a 2-D air supply diffuser model that supplies direction and magnitude of air flow into the room is developed. Air distribution effect on thermal comfort parameters was investigated depending on changing the air supply diffusers type, angles and velocity. Air supply diffusers locations and numbers were also investigated. The pre-processor Gambit is used to create the geometric model with parametric features. Commercially available simulation software “Fluent 6.3” is incorporated to solve the differential equations governing the conservation of mass, three momentum and energy in the processing of air flow distribution. Turbulence effects of the flow are represented by the well-developed two equation turbulence model. In this work, the so-called standard k-ε turbulence model, one of the most widespread turbulence models for industrial applications, was utilized. Basic parameters included in this work are air dry bulb temperature, air velocity, relative humidity and turbulence parameters are used for numerical predictions of indoor air distribution and thermal comfort. The thermal comfort predictions through this work were based on ADPI (Air Diffusion Performance Index),the PMV (Predicted Mean Vote) model and the PPD (Percentage People Dissatisfied) model, the PMV and PPD were estimated using Fanger’s model.

Keywords: thermal comfort, Fanger's model, ADPI, energy effeciency

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Authors: Xu Yifei, Le Yining, Yang Qingluan, Tu Yanjie

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Objective: This study aims to investigate the distribution features of Traditional Chinese Medicine (TCM) syndromes and syndrome elements in Epstein-Barr virus-associated diseases and then explores the relations between TCM syndromes or syndrome elements and laboratory indicators of Epstein-Barr virus-associated diseases. Methods: A cross-sectional study of 70 patients with EBV infection was described. We assessed the diagnostic information and laboratory indicators of these patients from Huashan Hospital Affiliated to Fudan University between November 2017 and July 2019. The disease diagnosis and syndrome differentiation were based on the diagnostic criteria of EBV-associated diseases and the theory of TCM respectively. Confidence correlation analysis, logistic regression analysis, cluster analysis, and the Sankey diagram were used to analyze the correlation between the data. Results: The differentiation of the 4 primary TCM syndromes in the collected patients was correlated with the indexes of immune function, liver function, inflammation, and anemia, especially the relationship between Qifen syndrome and high lactic acid dehydrogenase level. The common 11 TCM syndrome elements were associated with the increased CD3+ T cell rate, low hemoglobin level, high procalcitonin level, high lactic acid dehydrogenase level, and low albumin level. Conclusion: The changes in immune function indexes, procalcitonin, and liver function-related indexes in patients with EBV-associated diseases were consistent with the evolution law of TCM syndromes. This study provides a reference for judging the pathological stages of these kinds of diseases, predicting their prognosis, and guiding subsequent treatment strategies based on TCM syndrome type.

Keywords: EBV-associated diseases, traditional Chinese medicine syndrome, syndrome element, diagnostics

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Authors: Samir El-Gendy, Doaa Zaghloul

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The current study dealt with the gross and microscopic anatomy of the integument of male ostrich in addition to the histological features of different areas of skin by light and SEM. The ostrich skin is characterized by prominent feather follicles and bristles. The number of feather follicles was determined per cm2 in different regions. The integument of ostrich had many modifications which appeared as callosities and scales, nail and toe pads. They were sternal, pubic and Achilles tendon callosities. The vacuolated epidermal cells were seen mainly in the skin of legs and to a lesser extent in the skin of back and Achilles areas. Higher lipogenic potential was expressed by epidermis from glabrous areas of ostrich skin. The dermal papillae were found in the skin of feathered area of neck and back and this was not a common finding in bird's skin which may give resistance against shearing forces in these regions of ostrich skin. The thickness of the keratin layer of ostrich varied, being thick and characteristically loose in the skin at legs, very thin and wavy at neck, while at Achilles skin area, scale and toe pad were thick and more compact, with the thickest very dense and wavy keratin layer at the nail. The dermis consisted of superficial layer of dense irregular connective tissue characterized by presence of many vacuoles of different sizes just under the basal lamina of the epithelium of epidermis and deep layer of dense regular connective tissue. This result suggested presence of fat droplets in this layer which may be to overcome the lack of good barrier of cutaneous water loss in epidermis.

Keywords: ostrich, light microscopy, scanning electron microscopy, integument, skin modifications

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Authors: Skander Ben Mami

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Despite its particular patterns and historical importance, the remote region of the Pamir Hindu Kush still lacks public recognition, as well as scientific substance, because of the abundance of classical state-centred geopolitical studies, the resilience of (inter)national narratives, and the political utility of the concepts of 'Central Asia' and 'South Asia'. However, this specific region of about 100 million inhabitants and located at the criss-cross of four geopolitical areas (Indian, Iranian, Chinese and Russian) over a territory of half a million square kilometres features a string of patterns that set it apart from the neighbouring areas of the Fergana, the Gansu and Punjab. Moreover, the Pamir Hindu Kush undergoes a series of parallel social and economic transformations that deserve scrutiny for their strong effect on the people’s lifestyle, particularly in three major urban centres (Aksu in China, Bukhara in Uzbekistan and Islamabad in Pakistan) and their immediate rural surroundings. While the involvement of various public and private stakeholders (States, NGOs, civil movements, private firms…) has undeniably resulted in positive elements (economic growth, connectivity, higher school attendance), it has in the same time generated a collection of negative effects (radicalizing, inequalities, pollution, territorial divide) that need to be addressed to strengthen regional and international security. This paper underscores the region’s strategical importance as the major hotbed and engine of insecurity and violence in Asia, notably in the context of Afghanistan’s enduring violence. It introduces the inner structures of the region, the different sources of violence as well as the governments’ responses to address it.

Keywords: geography, security, terrorism, urbanisation

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

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Authors: Heruanda Alviana Giska Barabah, Hilda Rasnia Hapsari

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Acoustic phenomena create an acoustic interpretation condition that describes the characteristics of the environment. In urban areas, the tendency of heterogeneous and simultaneous human activity form a soundscape that is different from other regions, one of the characteristics of urban areas that developing the soundscape is the presence of vertical model houses or residential building. Activities both within the building and surrounding environment are able to make the soundscape with certain characteristics. The acoustics comfort of residential building becomes an important aspect, those demand lead the building features become more diverse. Initial steps in mapping acoustic conditions in a soundscape are important, this is the method to determine uncomfortable condition. Noise generated by road traffic, railway, and plane is an important consideration, especially for urban people, therefore the proper design of the building becomes very important as an effort to bring appropriate acoustics comfort. In this paper the authors developed noise mapping on the location of the residential building. Mapping done by taking some point referring to the noise source. The mapping result become the basis for modeling the acoustics wave interacted with the building model. Material selection is done based on literature study and modeling simulation using Insul by considering the absorption coefficient and Sound Transmission Class. The analysis of acoustics rays is ray tracing method using Comsol simulator software that can show the movement of acoustics rays and their interaction with a boundary. The result of this study can be used to consider boundary material in residential building as well as consideration for improving the acoustic quality in the acoustics zones that are formed.

Keywords: residential building, noise, absorption coefficient, sound transmission class, ray tracing

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Authors: Oyebade K. Oyedotun

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The cardiotocogram is a technical recording of the heartbeat rate and uterine contractions of a fetus during pregnancy. During pregnancy, several complications can occur to both the mother and the fetus; hence it is very crucial that medical experts are able to find technical means to check the healthiness of the mother and especially the fetus. It is very important that the fetus develops as expected in stages during the pregnancy period; however, the task of monitoring the health status of the fetus is not that which is easily achieved as the fetus is not wholly physically available to medical experts for inspection. Hence, doctors have to resort to some other tests that can give an indication of the status of the fetus. One of such diagnostic test is to obtain cardiotocograms of the fetus. From the analysis of the cardiotocograms, medical experts can determine the status of the fetus, and therefore necessary medical interventions. Generally, medical experts classify examined cardiotocograms into ‘normal’, ‘suspect’, or ‘pathological’. This work presents an artificial neural network based decision support system which can filter cardiotocograms data, producing the corresponding statuses of the fetuses. The capability of artificial neural network to explore the cardiotocogram data and learn features that distinguish one class from the others has been exploited in this research. In this research, feedforward and radial basis neural networks were trained on a publicly available database to classify the processed cardiotocogram data into one of the three classes: ‘normal’, ‘suspect’, or ‘pathological’. Classification accuracies of 87.8% and 89.2% were achieved during the test phase of the trained network for the feedforward and radial basis neural networks respectively. It is the hope that while the system described in this work may not be a complete replacement for a medical expert in fetus status evaluation, it can significantly reinforce the confidence in medical diagnosis reached by experts.

Keywords: decision support, cardiotocogram, classification, neural networks

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Authors: Surabhi Agrawal Kohli, Sunita Gupta, Esha Khanuja, Parul Garg, P. Gupta

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Background: Adenomyosis is a common gynaecological condition that affects the menstruating women. Uterine enlargement, dysmenorrhoea, and menorrhagia are regarded as the cardinal clinical symptoms of adenomyosis. Classically it was thought, compared with ultrasonography, when adenomyosis is suspected, MRI enables more accurate diagnosis of the disease. Materials and Methods: 172 subjects were enrolled after an informed consent that had complaints of HMB, dyspareunia, dysmenorrhea, and chronic pelvic pain. Detailed history of the enrolled subjects was taken, followed by a clinical examination. These patients were then subjected to TVS where myometrial echo texture, presence of myometrial cysts, blurring of endomyometrial junction was noted. MRI was followed which noted the presence of junctional zone thickness and myometrial cysts. After hysterectomy, histopathological diagnosis was obtained. Results: 78 participants were analysed. The mean age was 44.2 years. 43.5% had parity of 4 or more. heavy menstrual bleeding (HMB) was present in 97.8% and dysmenorrhea in 93.48 % of HPE positive patient. Transvaginal sonography (TVS) and MRI had a sensitivity of 89.13% and 80.43%, specificity of 90.62% and 84.37%, positive likelihood ratio of 9.51 and 5.15, negative likelihood ratio of 0.12 and 0.23, positive predictive value of 93.18% and 88.1%, negative predictive value of 85.29% and 75% and a diagnostic accuracy of 89.74% and 82.5%. Comparison of sensitivity (p=0.289) and specificity (p=0.625) showed no statistically significant difference between TVS and MRI. Conclusion: Prevalence of 30.23%. HMB with dysmenorrhoea and chronic pelvic pain helps in diagnosis. TVS (Endomyometrial junction blurring) is both sensitive and specific in diagnosing adenomyosis without need for additional diagnostic tool. Both TVS and MRI are equally efficient, however because of certain additional advantages of TVS over MRI, it may be used as the first choice of imaging. MRI may be used additionally in difficult cases as well as in patients with existing co-pathologies.

Keywords: adenomyosis, heavy menstrual bleeding, MRI, TVS

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Authors: Sahani Rathnasiri, Pritee Ray, Sardar M. N. Isalm, Carlos A. Vega-Mejia

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This study develops a cooperative game theory-based cost-sharing contract model for a business to consumer (B2C) e-commerce supply chain to minimize the overall supply chain costs and the individual costs within an information asymmetry scenario. The objective of this study is to address the issues of strategic interactions among the key players of the e-commerce supply chain operation, which impedes the optimal operational outcomes. Game theory has been included in the field of supply chain management to resolve strategic decision-making issues; however, most of the studies are limited only to two-echelons of the supply chains. Multi-echelon supply chain optimizations based on game-theoretic models are less explored in the previous literature. This study adopts a cooperative game model to focus on the common payoff of operations and addresses the issues of information asymmetry and coordination of a three-echelon e-commerce supply chain. The cost-sharing contract model integrates operational features such as production, inventory management and distribution with the contract related constraints. The outcomes of the model highlight the importance of maintaining lower operational costs by all players to obtain benefits from the cost-sharing contract. Further, the cost-sharing contract ensures true cost revelation, and hence eliminates the information asymmetry issues among the players. Comparing the results of the contract model with the de-centralized e-commerce supply chain operation further emphasizes that the cost-sharing contract derives Pareto-improved outcomes and minimizes the costs of overall e-commerce supply chain operation.

Keywords: cooperative game theory, cost-sharing contract, e-commerce supply chain, information asymmetry

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Authors: Andrew Gryguć, Seyed Behzad Behravesh, Hamid Jahed, Mary Wells, Wojciech Macek, Bruce Williams

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This extended abstract investigates the influence of the multiaxial loading on the fatigue behavior of forged magnesium through quantitative analysis of its fracture surface topography and mesoscopic cracking orientation. Fatigue tests were performed on hollow tubular sample geometries extracted from closed-die forged AZ80 Mg components, with three different multiaxial strain paths (axial/shear), proportional, 45° out of phase, and 90° out of phase. Regardless of the strain path, fatigue cracks are initiated at the outer surface of the specimen where the combined stress state is largest. Depending on the salient mode of deformation, distinctive features in the fracture surface manifested themselves with different topographic amplitudes, surface roughness, and mesoscopic cracking orientation in the vicinity of the initiation site. The dominant crack propagation path was in the circumferential direction of the hollow tubular specimen (i.e., cracking transverse to the sample axis, with little to no branching), which is congruent with previous findings of low to moderate shear strain energy density (SED) multiaxial loading. For proportional loading, the initiation zone surface morphology was largely flat and striated, whereas, at phase angles of 45° and 90°, the initiation surface became more faceted and inclined. Overall, both a qualitative and quantitative link was developed between the fracture surface morphology and the level of non-proportionality in the loading providing useful insight into the fracture mechanics of forged magnesium as a relevant focus for future study.

Keywords: fatigue, fracture, magnesium, forging, fractography, anisotropy, strain energy density, asymmetry, multiaxial fatigue

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Authors: Shashank Gupta, Iteash Agarwal, Vijayalaxmi Mogiligidda, Rajesh Kumar Krishnan, Sruthi Chennuri, Deepika Aggarwal, Anwesha Hoodati, Sheroy Cooper, Ranjan, Mohammad Bilal Sheik, Bhavya K. M., Manasa Hegde, M. Naveen Krishna, Amit Kumar Chauhan, Mallikarjun Korrapati, Sumit Singh, J. B. Singh, Sunil Sud, Sunil Gupta, Sidhartha Pant, Sankar, Neha Agrawal, Ashish Ranjan, Piyush Mohapatra, Roopak T., Arsh Ahmad, Nanjunda M., Dilip Singh

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Major research interests on quantum key distribution (QKD) are primarily focussed on increasing 1. point-to-point transmission distance (1000 Km), 2. secure key rate (Mbps), 3. security of quantum layer (device-independence). It is great to push the boundaries on these fronts, but these isolated approaches are neither scalable nor cost-effective due to the requirements of specialised hardware and different infrastructure. Current and future QKD network requires addressing different sets of challenges apart from distance, key rate, and quantum security. In this regard, we present ChaQra -a sub-quantum network with core features as 1) Crypto agility (integration in the already deployed telecommunication fibres), 2) Software defined networking (SDN paradigm for routing different nodes), 3) reliability (addressing denial-of-service with hybrid quantum safe cryptography), 4) upgradability (modules upgradation based on scientific and technological advancements), 5) Beyond QKD (using QKD network for distributed computing, multi-party computation etc). Our results demonstrate a clear path to create and accelerate quantum secure Indian subcontinent under the national quantum mission.

Keywords: quantum network, quantum key distribution, quantum security, quantum information

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: G. M. B. P. Abeysekara, W. A. D. C. Wijerathna

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Terminal choice from the multiple terminals region is not a simple decision and it is very complex, because shipping lines should consider on influential factors for the terminal choice at once according to their requirement. Therefore, terminal choice is a multiple criterion decision making (MCDM) situation under a specially designed decision hierarchy. Identification of perspective of shipping lines regarding terminal choice is vital important for the decision makers regarding container terminals. Thus this study is evaluated perception on main and feeder shipping lines’ regarding port of Colombo container terminals, and ranked terminals according to shipping lines preference. Analytic Hierarchy Process (AHP) model is adapted to this study, since it has features similar to the MCDM, it is weighted every influential factor by using pair wise comparisons, and consistency of the decision makers’ judgments are checked to evaluate trustworthiness of gathered data. And rating method is used to rank the terminals within Port of Colombo by assigning particular preference values with respect to the criteria and sub criteria. According to the findings of this study, main lines’ mainly concern on water depth of approach channel, depth of berth, handling charges and handling equipment facilities. And feeder lines’ main concerns were handling equipment facilities, loading and discharging efficiency, depth of berth and handling charges. Findings of the study suggested concentrating regarding the emphasized areas in order to enhance the competitiveness of terminals, and to increase number of vessel callings at the Port of Colombo. Application of above finding of the terminals within Port of Colombo lead to a far better competition among terminals and would uplift the overall level of services.

Keywords: AHP, Main and feeder shipping lines, criteria, sub criteria

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Authors: Terryann Clark, Kabir Dasgupta, Sonia Lewycka, Gail Pacheco, Alexander Plum

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This paper focused on two main research aims using data from the Growing Up in New Zealand (GUINZ) birth cohort: 1. To examine ethnic differences in life-course trajectories in the use and experience of healthcare services in early childhood years (namely immunisation, dental checks and use of General Practitioners (GPs)) 2. To quantify the contribution of relevant explanatory factors to ethnic differences. Current policy in New Zealand indicates there should be, in terms of associated direct costs, equitable access by ethnicity for healthcare services. However, empirical evidence points to persistent ethnic gaps in several domains. For example, the data highlighted that Māori have the lowest immunisation rates, across a number of time points in early childhood – despite having a higher antenatal intention to immunise relative to NZ European. Further to that, NZ European are much more likely to have their first-choice lead maternity caregiver (LMC) and use child dental services compared to all ethnicities. Method: This research explored the underlying mechanisms behind ethnic differences in the use and experience of child healthcare services. First, a multivariate regression analysis was used to adjust raw ethnic gaps in child health care utilisation by relevant covariates. This included a range of factors, encompassing mobility, socio-economic status, mother and child characteristics, household characteristics and other social aspects. Second, a decomposition analysis was used to assess the proportion of each ethnic gap that can be explained, as well as the main drivers behind the explained component. The analysis for both econometric approaches was repeated for each data time point available, which included antenatal, 9 months, 2 years and 4 years post-birth. Results: The following findings emerged: There is consistent evidence that Asian and Pacific peoples have a higher likelihood of child immunisation relative to NZ Europeans and Māori. This was evident at all time points except one. Pacific peoples had a lower rate relative to NZ European for receiving all first-year immunisations on time. For a number of potential individual and household predictors of healthcare service utilisation, the association is time-variant across early childhood. For example, socio-economic status appears highly relevant for timely immunisations in a child’s first year, but is then insignificant for the 15 month immunisations and those at age 4. Social factors play a key role. This included discouragement or encouragement regarding child immunisation. When broken down by source, discouragement by family has the largest marginal effect, followed by health professionals; whereas for encouragement, medical professionals have the largest positive influence. Perceived ethnically motivated discrimination by a health professional was significant with respect to both reducing the likelihood of achieving first choice LMC, and also satisfaction levels with child’s GP. Some ethnic gaps were largely unexplained, despite the wealth of factors employed as independent variables in our analysis. This included understanding why Pacific mothers are much less likely to achieve their first choice LMC compared to NZ Europeans; and also the ethnic gaps for both Māori and Pacific peoples relative to NZ Europeans concerning dental service use.

Keywords: child health, cohort analysis, ethnic disparities, primary healthcare

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Authors: K. N. Dinesh Babu, P. K. Gargava

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Energization of a transformer results in sudden flow of current which is an effect of core magnetization. This current will be dominated by the presence of second harmonic, which in turn is used to segregate fault and inrush current, thus guaranteeing proper operation of the relay. This additional security in the relay sometimes obstructs or delays differential protection in a specific scenario, when the 2^nd harmonic content was present during a genuine fault. This kind of scenario can result in isolation of the transformer by Buchholz and pressure release valve (PRV) protection, which is acted when fault creates more damage in transformer. Such delays involve a huge impact on the insulation failure, and chances of repairing or rectifying fault of problem at site become very dismal. Sometimes this delay can cause fire in the transformer, and this situation becomes havoc for a sub-station. Such occurrences have been observed in field also when differential relay operation was delayed by 10-15 ms by second harmonic blocking in some specific conditions. These incidences have led to the need for an alternative solution to eradicate such unwarranted delay in operation in future. Modern numerical relay, called as intelligent electronic device (IED), is embedded with advanced protection features which permit higher flexibility and better provisions for tuning of protection logic and settings. Such flexibility in transformer protection IEDs, enables incorporation of alternative methods such as dynamic switching of second harmonic feature for blocking the differential protection with additional security. The analysis and precautionary measures carried out in this case, have been simulated and discussed in this paper to ensure that similar solutions can be adopted to inhibit analogous issues in future.

Keywords: differential protection, intelligent electronic device (IED), 2nd harmonic inhibit, inrush inhibit

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Authors: Ivana Cabarkapa, Zorica Tomicic, Olivera Duragic

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Antimicrobial resistance represents one of the major challenges facing humanity in the last decades. Increasing antibiotic-resistant pathogens indicates the need for the development of alternative antibacterial drugs and new treatment strategies. One of the innovative emerging treatments in overcoming multidrug-resistant pathogens certainly represents the inhibition anti-quorum sensing system. For most of the food-borne pathogens, the expression of the virulence depends on their capability communication with other members of the population by means of quorum sensing (QS). QS represents a specific way of bacterial intercellular communication, which enabled owing to their ability to detect and to respond to cell population density by gene regulation. QS mechanisms are responsible for controls the pathogenesis, virulence luminescence, motility, sporulation and biofilm formation of many organisms by regulating gene expression. Therefore, research in this field is being an attractive target for the development of new natural antibacterial agents. Anti-QS compounds are known to have the ability to prohibit bacterial pathogenicity. Considering the importance of quorum sensing during bacterial pathogenesis, this research has been focused on evaluation anti - QS properties of four essential oils (EOs) Origanum heracleoticum, Origanum vulgare, Thymus vulgare, and Thymus serpyllum, using biomonitor strain of Chromobacterium violaceum CV026. Tests conducted on Luria Bertani agar supplemented with N hexanol DL homoserine lacton (HHL) 10µl/50ml of agar. The anti-QS potential of the EOs was assayed in a range of concentrations of 200 – 0.39 µl/ml using the disc diffusion method. EOs of Th. vulgaris and T. serpyllum were exhibited anti-QS activity indicated by a non- pigmented ring with a dilution-dependent manner. The lowest dilution of EOs T. vulgaris and T. serpyllum in which they exhibited visually detectable inhibition of violacein synthesis was 6.25 µl/ml for both tested EOs. EOs of O. heracleoticum and O. vulgare were displayed different active principles, i.e., antimicrobial activity indicated by the inner clear ring and anti-QS activity indicated by the outer non-pigmented ring, in a concentration-dependent manner. The lowest dilution of EOs of O. heracleoticum and O. vulgare in which exhibited visually detectable inhibition of violacein synthesis was 1.56 and 3.25 µl/ml, respectively. Considering that, the main constituents of the tested EOs represented by monoterpenes (carvacrol, thymol, γ-terpinene, and p-cymene), anti - QS properties of tested EOs can be mainly attributed to their activity. In particular, from the scientific literature, carvacrol and thymol show a sub-inhibitory effect against foodborne pathogens. Previous studies indicated that sub-lethal concentrations of carvacrol reduced the mobility of bacteria due to the ability of interference using QS mechanism between the bacterial cells, and thereby reducing the ability of biofilm formation The precise mechanism by which carvacrol inhibits biofilm formation is still not fully understood. Our results indicated that EOs displayed different active principles, i.e., antimicrobial activity indicated by the inner clear ring and anti-QS activity indicated by an outer non- pigmented ring with visually detectable inhibition of violacein. Preliminary results suggest that EOs represent a promising alternative for effective control of the emergence and spread of resistant pathogens.

Keywords: anti-quorum sensing activity, Chromobacterium violaceum, essential oils, violacein

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Authors: Ling Xu, Giuseppe Loprencipe, Antonio D'Andrea

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Asphalt pavement with recycled and sustainable materials has become the most commonly adopted strategy for road construction, including reclaimed asphalt pavement (RAP) and crumb rubber (CR) from waste tires. However, the adhesion and cohesion characteristics of rubberized reclaimed asphalt pavement were still ambiguous, resulting in deteriorated adhesion behavior and life performance. This research investigated the effect of bonding characteristics on rutting resistance and moisture susceptibility of rubberized reclaimed asphalt pavement in terms of two RAP sources with different oxidation levels and two tire rubber with different particle sizes. Firstly, the binder bond strength (BBS) test and bonding failure distinguishment were conducted to analyze the surface behaviors of binder-aggregate interaction. Then, the compatibility and penetration grade of rubberized RAP binder were evaluated by rotational viscosity test and penetration test, respectively. Hamburg wheel track (HWT) test with high-temperature viscoelastic deformation analysis was adopted, which illustrated the rutting resistance. Additionally, a water boiling test was employed to evaluate the moisture susceptibility of the mixture and the texture features were characterized with the statistical parameters of image colors. Finally, the colloid structure model of rubberized RAP binder with surface interaction was proposed, and statistical analysis was established to release the correlation among various indexes. This study concluded that the gel-phase colloid structure and molecular diffusion of the free light fraction would affect the surface interpretation with aggregate, determining the bonding characteristic of rubberized RAP asphalt.

Keywords: bonding characteristics, reclaimed asphalt pavement, rubberized asphalt, sustainable material

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: S. Abdi Goudazri, R. Ziaie Moayed, A. Nazeri

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Loose soils normally are of weak bearing capacity due to their structural nature. Being exposed to heavy traffic loads, they would fail in most cases. To tackle the aforementioned issue, geotechnical engineers have come up with different approaches; one of which is making use of geosynthetic-reinforced soil-aggregate systems. As these polymeric reinforcements have highlighted economic and environmentally-friendly features, they have become widespread in practice during the last decades. The present research investigates the efficiency of four different types of these reinforcements in increasing the bearing capacity of two-layered soil sections using a series California Bearing Ratio (CBR) test. The studied sections are comprised of a 10 cm-thick layer of no. 161 Firouzkooh sand (weak subgrade) and a 10 cm-thick layer of compacted aggregate materials (base course) classified as SP and GW according to the United Soil Classification System (USCS), respectively. The aggregate layer was compacted to the relative density (Dr) of 95% at the optimum water content (Wopt) of 6.5%. The applied reinforcements were including two kinds of geocomposites (type A and B), a geotextile, and a geogrid that were embedded at the interface of the lower and the upper layers of the soil-aggregate system. As the standard CBR mold was not appropriate in height for this study, the mold used for soaked CBR tests were utilized. To make a comparison between the results of stress-settlement behavior in the studied specimens, CBR values pertinent to the penetrations of 2.5 mm and 5 mm were considered. The obtained results demonstrated 21% and 24.5% increments in the amount of CBR value in the presence of geocomposite type A and geogrid, respectively. On the other hand, the effect of both geotextile and geocomposite type B on CBR values was generally insignificant in this research.

Keywords: geosynthetics, geogrid, geotextile, CBR test, increasing bearing capacity

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Authors: Maryam Karimi, Rouzbeh Nazari

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Introduction: Understanding thermal distribution in the micro-urban climate has now been necessary for urban planners or designers due to the impact of complex micro-scale features of Urban Heat Island (UHI) on the built environment and public health. Hence, understanding the interrelation between urban components and thermal pattern can assist planners in the proper addition of vegetation to build-environment, which can minimize the UHI impact. To characterize the need for urban green infrastructure (UGI) through better urban planning, this study proposes the use of RayMan model to measure the impact of air quality and increased temperature based on urban morphology in the selected metropolitan cities. This project will measure the impact of build environment for urban and regional planning using human biometeorological evaluations (Tmrt). Methods: We utilized the RayMan model to estimate the Tmrt in an urban environment incorporating location and height of buildings and trees as a supplemental tool in urban planning and street design. The estimated Tmrt value will be compared with existing surface and air temperature data to find the actual temperature felt by pedestrians. Results: Our current results suggest a strong relationship between sky-view factor (SVF) and increased surface temperature in megacities based on current urban morphology. Conclusion: This study will help with Quantifying the impacts of the built environment and surface properties on surrounding temperature, identifying priority urban neighborhoods by analyzing Tmrt and air quality data at the pedestrian level, and characterizing the need for urban green infrastructure cooling potential.

Keywords: built environment, urban planning, urban cooling, extreme heat

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Authors: Taslim Khan, Ray Hua Horng, Rajendra Singh

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This study presents a comprehensive analysis of the design, fabrication, and performance evaluation of a solar-blind Schottky photodetector based on ZnGa₂O₄ grown via MOCVD, utilizing Ni/Au as the Schottky electrode. ZnGa₂O₄, with its wide bandgap of 5.2 eV, is well-suited for high-performance solar-blind photodetection applications. The photodetector demonstrates an impressive responsivity of 280 A/W, indicating its exceptional sensitivity within the solar-blind ultraviolet band. One of the device's notable attributes is its high rejection ratio of 10⁵, which effectively filters out unwanted background signals, enhancing its reliability in various environments. The photodetector also boasts a photodetector responsivity contrast ratio (PDCR) of 10⁷, showcasing its ability to detect even minor changes in incident UV light. Additionally, the device features an outstanding detective of 10¹⁸ Jones, underscoring its capability to precisely detect faint UV signals. It exhibits a fast response time of 80 ms and an ON/OFF ratio of 10⁵, making it suitable for real-time UV sensing applications. The noise-equivalent power (NEP) of 10^-17 W/Hz further highlights its efficiency in detecting low-intensity UV signals. The photodetector also achieves a high forward-to-backward current rejection ratio of 10⁶, ensuring high selectivity. Furthermore, the device maintains an extremely low dark current of approximately 0.1 pA. These findings position the ZnGa₂O₄-based Schottky photodetector as a leading candidate for solar-blind UV detection applications. It offers a compelling combination of sensitivity, selectivity, and operational efficiency, making it a highly promising tool for environments requiring precise and reliable UV detection.

Keywords: wideband gap, solar blind photodetector, MOCVD, zinc gallate

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Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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Authors: Jonas Hamann, Siavash Saki, Tobias Hagen

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Discretization of urban areas is a crucial aspect in many spatial analyses. The process of discretization of space into subspaces without overlaps and gaps is called tessellation. It helps understanding spatial space and provides a framework for analyzing geospatial data. Tessellation methods can be divided into two groups: regular tessellations and irregular tessellations. While regular tessellation methods, like squares-grids or hexagons-grids, are suitable for addressing pure geometry problems, they cannot take the unique characteristics of different subareas into account. However, irregular tessellation methods allow the border between the subareas to be defined more realistically based on urban features like a road network or Points of Interest (POI). Even though Python is one of the most used programming languages when it comes to spatial analysis, there is currently no library that combines different tessellation methods to enable users and researchers to compare different techniques. To close this gap, we are proposing TessPy, an open-source Python package, which combines all above-mentioned tessellation methods and makes them easily accessible to everyone. The core functions of TessPy represent the five different tessellation methods: squares, hexagons, adaptive squares, Voronoi polygons, and city blocks. By using regular methods, users can set the resolution of the tessellation which defines the finesse of the discretization and the desired number of tiles. Irregular tessellation methods allow users to define which spatial data to consider (e.g., amenity, building, office) and how fine the tessellation should be. The spatial data used is open-source and provided by OpenStreetMap. This data can be easily extracted and used for further analyses. Besides the methodology of the different techniques, the state-of-the-art, including examples and future work, will be discussed. All dependencies can be installed using conda or pip; however, the former is more recommended.

Keywords: geospatial data science, geospatial data analysis, tessellations, urban studies

Procedia PDF Downloads 128