Search results for: radial distribution networks

Authors: N. Boutra, N. Ravot, J. Benoit, O. Picon

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Submarine power cables used for offshore wind farms electric energy distribution and transmission are subject to numerous threats. Some of the risks are associated with transport, installation and operating in harsh marine environment. This paper describes the feasibility of an electromagnetic low frequency sensing technique for submarine power cable failure prediction. The impact of a structural damage shape and material variability on the induced electric field is evaluated. The analysis is performed by modeling the cable using the finite element method, we use sensitivity analysis in order to identify the main damage characteristics affecting electric field variation. Lastly, we discuss the results obtained.

Keywords: electromagnetism, finite element method, sensitivity analysis, submarine power cables

Procedia PDF Downloads 333

Authors: Mustafa M. Donma, Orkide Donma

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The examination of both serum lipid fractions and body’s lipid composition are quite informative during the evaluation of obesity stages. Within this context, alterations in lipid parameters are commonly observed. The variations in the fat distribution of the body are also noteworthy. Total cholesterol (TC), triglycerides (TRG), low density lipoprotein-cholesterol (LDL-C), high density lipoprotein-cholesterol (HDL-C) are considered as the basic lipid fractions. Fat deposited in trunk and extremities may give considerable amount of information and different messages during discrete health states. Ratios are also derived from distinct fat distribution in these areas. Trunk-to-leg fat ratio (TLFR) and trunk-to-appendicular fat ratio (TAFR) are the most recently introduced ratios. In this study, lipid fractions and TLFR, as well as TAFR, were evaluated, and the distinctions among healthy, obese (OB), and morbid obese (MO) groups were investigated. Three groups [normal body mass index (N-BMI), OB, MO] were constituted from a population aged 6 to 18 years. Ages and sexes of the groups were matched. The study protocol was approved by the Non-interventional Ethics Committee of Tekirdag Namik Kemal University. Written informed consent forms were obtained from the parents of the participants. Anthropometric measurements (height, weight, waist circumference, hip circumference, head circumference, neck circumference) were obtained and recorded during the physical examination. Body mass index values were calculated. Total, trunk, leg, and arm fat mass values were obtained by TANITA Bioelectrical Impedance Analysis. These values were used to calculate TLFR and TAFR. Systolic (SBP) and diastolic blood pressures (DBP) were measured. Routine biochemical tests including TC, TRG, LDL-C, HDL-C, and insulin were performed. Data were evaluated using SPSS software. p value smaller than 0.05 was accepted as statistically significant. There was no difference among the age values and gender ratios of the groups. Any statistically significant difference was not observed in terms of DBP, TLFR as well as serum lipid fractions. Higher SBP values were measured both in OB and MO children than those with N-BMI. TAFR showed a significant difference between N-BMI and OB groups. Statistically significant increases were detected between insulin values of N-BMI group and OB as well as MO groups. There were bivariate correlations between LDL and TLFR (r=0.396; p=0.037) as well as TAFR values (r=0.413; p=0.029) in MO group. When adjusted for SBP and DBP, partial correlations were calculated as (r=0.421; p=0.032) and (r=0.438; p=0.025) for LDL-TLFR as well as LDL-TAFR, respectively. Much stronger partial correlations were obtained for the same couples (r=0.475; p=0.019 and r=0.473; p=0.020, respectively) upon controlling for TRG and HDL-C. Much stronger partial correlations observed in MO children emphasize the potential transition from morbid obesity to metabolic syndrome. These findings have concluded that LDL-C may be suggested as a discriminating parameter between OB and MO children.

Keywords: children, lipid parameters, obesity, trunk-to-leg fat ratio, trunk-to-appendicular fat ratio

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Authors: Kostas Philippopoulos, Chris G. Tzanis, Despina Deligiorgi

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Climate change adaptation requires the exploitation of renewable energy sources such as wind. However, climate variability can affect the regional wind energy potential and consequently the available wind power production. The goal of the research project is to examine the impact of atmospheric circulation on wind energy production over Greece. In the context of synoptic climatology, the proposed novel methodology employs Self-Organizing Maps for grouping and classifying the atmospheric circulation and nationally-aggregated capacity factor time series for a 30-year period. The results indicate the critical effect of atmospheric circulation on the national aggregated wind energy production values and therefore address the issue of optimum distribution of wind farms for a specific region.

Keywords: wind energy, atmospheric circulation, capacity factor, self-organizing maps

Procedia PDF Downloads 142

Authors: Awal Liman Sale

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The world is fast becoming a global village; and a necessary tool for this process is communication, of which telecommunication is a key player. The quantum development is very rapid as one innovation replaces another in a matter of weeks. Interconnected phone calls across the different Nigerian Telecom service providers are mostly difficult to connect and often diverted, incurring unnecessary charges on the customers. This compels the consumers to register and use multiple subscriber information modules (SIM) so that they can switch to another if one fails. This study aims to identify and prioritize the key factors in selecting telecom service providers by subscribers in Nigeria using the Analytical Hierarchy Process (AHP) in order to match the factors with the GSM network providers and create a hierarchical structure. Opinions of 400 random subscribers of different service providers will be sought using the questionnaire. In general, four components and ten sub-components will be examined in this study. After determining the weight of these components, the importance of each in choosing the service will be prioritized in Nigeria.

Keywords: analytical hierarchy process, global village, Nigerian telecommunication, subscriber information modules

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Authors: Fabiana Franceschi, Martha Cobo, Manuel Figueredo

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Bogotá, the capital of Colombia, is its largest city and one of the most polluted in Latin America due to the fast economic growth over the last ten years. Bogotá has been affected by high pollution events which led to the high concentration of PM10 and NO2, exceeding the local 24-hour legal limits (100 and 150 g/m3 each). The most important pollutants in the city are PM10 and PM2.5 (which are associated with respiratory and cardiovascular problems) and it is known that their concentrations in the atmosphere depend on the local meteorological factors. Therefore, it is necessary to establish a relationship between the meteorological variables and the concentrations of the atmospheric pollutants such as PM10, PM2.5, CO, SO2, NO2 and O3. This study aims to determine the interrelations between meteorological variables and air pollutants in Bogotá, using data mining techniques. Data from 13 monitoring stations were collected from the Bogotá Air Quality Monitoring Network within the period 2010-2015. The Principal Component Analysis (PCA) algorithm was applied to obtain primary relations between all the parameters, and afterwards, the K-means clustering technique was implemented to corroborate those relations found previously and to find patterns in the data. PCA was also used on a per shift basis (morning, afternoon, night and early morning) to validate possible variation of the previous trends and a per year basis to verify that the identified trends have remained throughout the study time. Results demonstrated that wind speed, wind direction, temperature, and NO2 are the most influencing factors on PM10 concentrations. Furthermore, it was confirmed that high humidity episodes increased PM2,5 levels. It was also found that there are direct proportional relationships between O3 levels and wind speed and radiation, while there is an inverse relationship between O3 levels and humidity. Concentrations of SO2 increases with the presence of PM10 and decreases with the wind speed and wind direction. They proved as well that there is a decreasing trend of pollutant concentrations over the last five years. Also, in rainy periods (March-June and September-December) some trends regarding precipitations were stronger. Results obtained with K-means demonstrated that it was possible to find patterns on the data, and they also showed similar conditions and data distribution among Carvajal, Tunal and Puente Aranda stations, and also between Parque Simon Bolivar and las Ferias. It was verified that the aforementioned trends prevailed during the study period by applying the same technique per year. It was concluded that PCA algorithm is useful to establish preliminary relationships among variables, and K-means clustering to find patterns in the data and understanding its distribution. The discovery of patterns in the data allows using these clusters as an input to an Artificial Neural Network prediction model.

Keywords: air pollution, air quality modelling, data mining, particulate matter

Procedia PDF Downloads 243

Authors: G. M. Komba

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The Internet Gateway (IGW) has extra ability than a simple Mesh Router (MR) and the responsibility to route mostly the all traffic from Mesh Clients (MCs) to the Internet backbone however, IGWs are more expensive. Choosing strategic locations for the Internet Gateways (IGWs) best location in Backbone Wireless Mesh (BWM) precarious to the Wireless Mesh Network (WMN) and the location of IGW can improve a quantity of performance related problem. In this paper, we propose a novel algorithm, namely New Gateway Location Algorithm (NGLA), which aims to achieve four objectives, decreasing the network cost effective, minimizing delay, optimizing the throughput capacity, Different from existing algorithms, the NGLA increasingly recognizes IGWs, allocates mesh routers (MRs) to identify IGWs and promises to find a feasible IGW location and install minimum as possible number of IGWs while regularly conserving the all Quality of Service (QoS) requests. Simulation results showing that the NGLA outperforms other different algorithms by comparing the number of IGWs with a large margin and it placed 40% less IGWs and 80% gain of throughput. Furthermore the NGLA is easy to implement and could be employed for BWM.

Keywords: Wireless Mesh Network, Gateway Location Algorithm, Quality of Service, BWM

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Authors: M. Bertsiou, E. Feloni, E. Baltas

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The proper management of the water supply and electricity is the key issue, especially in small islands, where sustainability has been combined with the autonomy and covering of water needs and the fast development in potential sectors of economy. In this research work a hybrid system in Fournoi island (Icaria), a small island of Aegean, has been evaluated in order to produce hydropower and cover water demands, as it can provide solutions to acute problems, such as the water scarcity or the instability of local power grids. The meaning and the utility of hybrid system and the cooperation with a desalination plant has also been considered. This kind of project has not yet been widely applied, so the consideration will give us valuable information about the storage of water and the controlled distribution of the generated clean energy. This process leads to the conclusions about the functioning of the system and the profitability of this project, covering the demand for water and electricity.

Keywords: hybrid system, water, electricity, island

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Authors: Ridvan Yamanoglu, Erdinc Efendi, Ismail Daoud

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In this study, Ti-5Al-2.5Fe alloy was prepared by powder metallurgy. The elemental titanium, aluminum, and iron powders were mechanically alloyed for 10 h in a vacuum atmosphere. A stainless steel jar and stainless steel balls were used for mechanical alloying. The alloyed powders were then sintered by vacuum hot pressing at 950 °C for a soaking time of 30 minutes. Pure titanium was also sintered at the same conditions for comparison of mechanical properties and microstructural behavior. The samples were investigated by scanning electron microscopy, XRD analysis, and optical microscopy. Results showed that, after mechanical alloying, a homogeneous distribution of the elements was obtained, and desired a-b structure was determined. Ti-5Al-2.5Fe alloy was successfully produced, and the alloy showed enhanced mechanical properties compared to the commercial pure titanium.

Keywords: Ti5Al-2.5Fe, mechanical alloying, hot pressing, sintering

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Authors: Hireni Mankodi

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The textile preforms for thermoplastic composite play a key role in providing the mechanical properties and gives the idea about preparing combination of yarn from Glass, Basalt, Carbon as reinforcement and PP, PET, Nylon as thermoplastic matrix at yarn stage for preforms to improve the quality and performance of laminates. The main objectives of this work are to develop the hybrid yarn using different yarn manufacturing process and prepare different performs using hybrid yarns. It has been observed that the glass/pp combination give homogeneous distribution in yarn. The proportion varied to optimize the glass/pp composition. The different preform has been prepared with combination of hybrid yarn, PP, glass combination. Further studies will investigate the effect of glass content in fabric, effect of weave, warps and filling density, number of layer plays significant role in deciding mechanical properties of thermoplastic laminates.

Keywords: thermoplastic, preform, laminates, hybrid yarn, glass

Procedia PDF Downloads 566

Authors: M. Taouzari, A. Sardi, J. El Aoufi, Ahmed Mouhsen

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The purpose of this work is to design a reader antenna fed by 90° hybrid coupler that would ensure a tag which is detected regardless of its orientation for the radio frequency identification system covering the UHF and ISM bands frequencies. Based on this idea, the proposed work is dividing in two parts, first part is about study and design hybrid coupler using the resonators planar called T-and Pi networks operating in commercial bands. In the second part, the proposed antenna fed by the hybrid coupler is designed on FR4 substrate with dielectric permittivity 4.4, thickness dielectric 1.6mm and loss tangent 0.025. The T-slot is inserted in patch of the proposed antenna fed by the hybrid coupler is first designed, optimized and simulated using electromagnetic simulator ADS and then simulated in a full wave simulation software CST Microwave Studio. The simulated antenna by the both softwares achieves the expected performances in terms of matching, pattern radiation, phase shifting, gain and size.

Keywords: dual band antenna, RFID, hybrid coupler, polarization, radiation pattern

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Authors: O. D. Arbeláez-Echeverri, E. Restrepo-Parra, J. C. Riano-Rojas

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A two dimensional geometric model of Bit Patterned Media is proposed, the model is based on the crystal structure of the materials commonly used to produce the nano islands in bit patterned materials and the possible defects that may arise from the interaction between the nano islands and the matrix material. The dynamic magnetic properties of the material are then computed using time aware integration methods for the multi spin Hamiltonian. The Hamiltonian takes into account both the spatial and topological disorder of the sample as well as the high perpendicular anisotropy that is pursued when building bit patterned media. The main finding of the research was the possibility of replicating the results of previous experiments on similar materials and the ability of computing the switching field distribution given the geometry of the material and the parameters required by the model.

Keywords: nanostructures, Monte Carlo, pattern media, magnetic properties

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Authors: Azar Khodabakhshi, Elham Bolandnazar

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Agriculture as the most important food manufacturing sector is not only the energy consumer, but also is known as energy supplier. Using energy is considered as a helpful parameter for analyzing and evaluating the agricultural sustainability. In this study, the pattern of energy consumption of strawberry greenhouses of Jiroft in Kerman province of Iran was surveyed. The total input energy required in the strawberries production was calculated as 113314.71 MJ /ha. Electricity with 38.34% contribution of the total energy was considered as the most energy consumer in strawberry production. In this study, Neuro Fuzzy networks was used for function modeling in the production of strawberries. Results showed that the best model for predicting the strawberries function had a correlation coefficient, root mean square error (RMSE) and mean absolute percentage error (MAPE) equal to 0.9849, 0.0154 kg/ha and 0.11% respectively. Regards to these results, it can be said that Neuro Fuzzy method can be well predicted and modeled the strawberry crop function.

Keywords: crop yield, energy, neuro-fuzzy method, strawberry

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Authors: A. Pourahmad, Sh. Gharipour

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The present work describes the preparation and characterization of nanosized SiO₂@PbS core-shell particles by using a simple wet chemical route. This method utilizes silica spheres formation followed by successive ionic layer adsorption and reaction method assisted lead sulphide shell layer formation. The final product was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), UV–vis spectroscopic, infrared spectroscopy (IR) and transmission electron microscopy (TEM) experiments. The morphological studies revealed the uniformity in size distribution with core size of 250 nm and shell thickness of 18 nm. The electron microscopic images also indicate the irregular morphology of lead sulphide shell layer. The structural studies indicate the face-centered cubic system of PbS shell with no other trace for impurities in the crystal structure.

Keywords: core-shell, nanostructure, semiconductor, optical property, XRD

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Authors: Walid Fantazi

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The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

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Authors: Rania Alshikhe, Vinita Jindal

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Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

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Authors: Ibrahim Djelloul Berkane

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A survey was conducted to assess the presence of the virus in Citrus tristeza one of the main citrus regions of Algeria, namely the Chlef region, using the technique of Direct Tissue Print Immunoprinting Assay (DTBIA) and the Double Sandwich ELISA antibodies. A nursery citrus, lumber yards, and commercial orchards, which are the main varieties cultivated citrus were subjected to samples collected samples for laboratory analysis. 0.91% of the plants tested orchards were infected with CTV, while no positive case was detected at the nursery the yard, however, it is reported that an alarming rate of 10,5% of orchards tested at the common Chettia were infected with tristeza virus. The investigation was launched to identify the vector species tristeza revealed the presence of a vector is important Aphis gossypii.

Keywords: aphis, chlef, citrus, DAS-ELISA, DTBIA, tristeza

Procedia PDF Downloads 279

Authors: Ali Abdrhman M. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The single step parallel contour extraction (SSPCE) method is used to create the edge map as a key image from the different Gray level/Binary image. Performing the X-OR operation between the key image and each bit plane of the original image for image pixel values change purpose. The Arnold transform used to changes the locations of image pixels as image scrambling process. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Gary level image and completely reconstructed without any distortion. Also shown that the analyzed algorithm have extremely large security against some attacks like salt & pepper and JPEG compression. Its proof that the Gray level image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression-salt- peppers attacks, bitplanes decomposition, Arnold transform, lossless image encryption

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Authors: Leila Rashidian, Mina Rajabali

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Industrialization has made progress and comfort for human beings in many aspects. It is not only achievement for the global environment but also factor for destruction and disruption of the Earth's climate. In this study, we used LARS.WG model and down scaling of general circulation climate model HADCM-3 daily precipitation amounts, minimum and maximum temperature and daily sunshine hours. These data are provided by the meteorological organization for Caspian Sea coastal station such as Anzali, Manjil, Rasht, Lahijan and Astara since their establishment is from 1982 until 2010. According to the IPCC scenarios, including series A1b, A2, B1, we tried to simulate data from 2010 to 2040. The rainfall pattern has changed. So we have a rainfall distribution inappropriate in different months.

Keywords: climate change, Lars.WG, HADCM3, Gillan province, climatic parameters, A2 scenario

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Authors: Azene Zenebe

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Deep learning is a subset of machine learning which incorporates techniques for the construction of artificial neural networks and found to be useful for modeling complex problems with large dataset. Deep learning requires a very high power computational and longer time for training. By aggregating computing power, high performance computer (HPC) has emerged as an approach to resolving advanced problems and performing data-driven research activities. Cyber threat intelligence (CIT) is actionable information or insight an organization or individual uses to understand the threats that have, will, or are currently targeting the organization. Results of review of literature will be presented along with results of experimental study that compares the performance of tree-based and function-base machine learning including deep learning algorithms using secondary dataset collected from darknet.

Keywords: deep-learning, cyber security, cyber threat modeling, tree-based machine learning, function-based machine learning, data science

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: Mohaddeseh Ahmadnezhad, Shahrbano Oryan, Mahmoud Bahmani, Mohammadd Sayad Bourani

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Changes in abundance and size of skin ionocytes were investigated in two larval stage of Caspian sea zander, Sander lucioperca, before and after yolk sac absorption, at 96h after transfer from fresh water (FW; <0.5‰) to 7‰ (estuary) and 12‰ (Caspian sea water=CW) salinity. Survival rate in the stage of after yolk sac absorption were more than larval pre-absorbed yolk sac in condition of salinity (p<0.05). Ionocyte abundance increased significantly in 7 and 12‰ salinity (p<0.05), but not about ionocyte size. The results of this study suggest that development of skin Ionocyte osmoregulatory function and osmoregulation capability of Caspian Sea zander larvae increased with growth of the larvae.

Keywords: Caspian Sea, larvae, Sander lucioperca, salinity, skin ionocyte

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Authors: Xiaohan Bookman, Xiaoyan Zhu

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Margin-Based Principle has been proposed for a long time, it has been proved that this principle could reduce the structural risk and improve the performance in both theoretical and practical aspects. Meanwhile, feed-forward neural network is a traditional classifier, which is very hot at present with a deeper architecture. However, the training algorithm of feed-forward neural network is developed and generated from Widrow-Hoff Principle that means to minimize the squared error. In this paper, we propose a new training algorithm for feed-forward neural networks based on Margin-Based Principle, which could effectively promote the accuracy and generalization ability of neural network classifiers with less labeled samples and flexible network. We have conducted experiments on four UCI open data sets and achieved good results as expected. In conclusion, our model could handle more sparse labeled and more high-dimension data set in a high accuracy while modification from old ANN method to our method is easy and almost free of work.

Keywords: Max-Margin Principle, Feed-Forward Neural Network, classifier, structural risk

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Authors: Claudio Burguez, María Castelló, Mikaela Pisani, Marcos Umpiérrez

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BIOFEEDBACK exhibition offers a unique experience for each visitor, combining art, neuroscience, and technology in an interactive way. Using a headband that captures the bioelectric activity of the brain, the visitors are able to generate sound and images in a sequence loop, making them an integral part of the artwork. Through this interactive exhibit, visitors gain a deeper appreciation of the beauty and complexity of the brain. As a special takeaway, visitors will receive an NFT as a present, allowing them to continue their engagement with the exhibition beyond the physical space. We used the EEG Biofeedback technique following a closed-loop neuroscience approach, transforming EEG data captured by a Muse S headband in real-time into audiovisual stimulation. PureData is used for sound generation and Generative Adversarial Networks (GANs) for image generation. Thirty participants have experienced the exhibition. For some individuals, it was easier to focus than others. Participants who said they could focus during the exhibit stated that at one point, they felt that they could control the sound, while images were more abstract, and they did not feel that they were able to control them.

Keywords: art, audiovisual, biofeedback, EEG, NFT, neuroscience, technology

Procedia PDF Downloads 57

Authors: G. Rosaz, V. Semblanet, S. Calatroni, A. Sublet, M. Taborelli

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We report in this paper the design and qualification of a cylindrical unbalanced magnetron source. The dedicated magnetic assemblies were simulated using a finite element model. A hall-effect magnetic probe was then used to characterize those assemblies and compared to the theoretical magnetic profiles. These show a good agreement between the expected and actual values. The qualification of the different magnetic assemblies was then performed by measuring the ion flux density reaching the surface of the sample to be coated using a commercial retarding field energy analyzer. The strongest unbalanced configuration shows an increase from 0.016 A.cm^-2 to 0.074 A.cm^-2 of the ion flux density reaching the sample surface compared to the standard balanced configuration for a pressure 5.10^-3 mbar and a plasma source power of 300 W.

Keywords: ion energy distribution function, magnetron sputtering, niobium, unbalanced, SRF cavities, thin film

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Authors: Hemant Kumar Pathak

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In 1994, Matthews (S.G. Matthews, Partial metric topology, in: Proc. 8th Summer Conference on General Topology and Applications, in: Ann. New York Acad. Sci., vol. 728, 1994, pp. 183-197) introduced the concept of a partial metric as a part of the study of denotational semantics of data flow networks. He gave a modified version of the Banach contraction principle, more suitable in this context. In fact, (complete) partial metric spaces constitute a suitable framework to model several distinguished examples of the theory of computation and also to model metric spaces via domain theory. In this paper, we introduce the concept of almost partial Hausdorff metric. We prove a fixed point theorem for multi-valued mappings on partial metric space using the concept of almost partial Hausdorff metric and prove an analogous to the well-known Nadler’s fixed point theorem. In the sequel, we derive a homotopy result as an application of our main result.

Keywords: fixed point, partial metric space, homotopy, physical sciences

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Authors: Zhifang Liao, Yanbing Li, Li Xu, Yan Zhang, Xiaoping Fan, Jinsong Wu

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Pull Request (PR) is the primary method for code contributions from the external contributors in Github. PR review is an essential part of open source software developments for maintaining the quality of software. Matching a new PR of an appropriate integrator will make the PR review more effective. However, PR and integrator matching are now organized manually in Github. To reduce this cost, we presented an AIPM model to predict highly relevant integrator of incoming PRs. AIPM uses topic model to extract topics from the PRs, and builds a one-to-one correspondence between topics and integrators. Then, AIPM finds the most suitable integrator according to the maximum entry of the topic-document distribution. On average, AIPM can reach a precision of 60%, and even in some projects, can reach a precision of 80%.

Keywords: pull Request, integrator matching, Github, open source project, topic model

Procedia PDF Downloads 280

Authors: Olubunmi Kolawole

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This study explored how certain organizational antecedents like work environment, and individual antecedents (e.g. job level and tenure) could affect employees empowerment in the hospitality industry. A total of 200 valid responses from a survey conducted in 10 hotels in Lagos Nigeria were received. Data were analyzed using frequency distribution and percentage analysis. Findings suggest that leadership, work environment, as well as tenure and level in the organization are reliable predictors of employees empowerment in Nigeria's hotel sector. Empowerment is a major factor which determines how employees feel about themselves and their jobs. The study concluded that organizations need to learn that an empowered employee will put in superior performance which would positively impact on the organization.

Keywords: employee empowerment, hospitality industry, individual-level antecedents, leadership, organizational antecedents

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Authors: Dessy Arumsari, Ais Assana Athqiya, Mulyaminingrum

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Healthcare in remote areas is one of the major concerns in Indonesia. Building hospitals in a nation of 18.000 islands with a larger-than-life bureaucracy and problems with corruption, a critical shortage of qualified medical professionals and well-heeled patients resigned to traveling abroad for health care is a hard feat to accomplish. To assuring that all populations have access to appropriate and cost-effective care, a new solution to tackle this problem is with the presence of RV Car Clinic. This car has a concept such as a walking hospital that provides health facilities inside it. All of the health professionals who work in RV Car Clinic will do the rotation for a year in order to the equitable distribution of health workers. We need to advocate the policy makers to help realize RV Car Clinic in remote areas. Health services can be disseminated by the present of RV Car Clinic. Summarily, the local communities can get cost effectively because RV Car Clinic will come to their place and serve the health services.

Keywords: health policy, health professional, remote areas, RV Car Clinic

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Authors: Serhat Tüzün, Tufan Demirel

Abstract:

Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

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