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  • Open Access English
    Authors: 
    Meysam Alizamir; Ozgur Kisi; Ali Najah Ahmed; Cihan Mert; Chow Ming Fai; Sungwon Kim; Nam-Won Kim; Ahmed El-Shafie;
    Publisher: Public Library of Science

    Soil temperature has a vital importance in biological, physical and chemical processes of terrestrial ecosystem and its modeling at different depths is very important for land-atmosphere interactions. The study compares four machine learning techniques, extreme learning machine (ELM), artificial neural networks (ANN), classification and regression trees (CART) and group method of data handling (GMDH) in estimating monthly soil temperatures at four different depths. Various combinations of climatic variables are utilized as input to the developed models. The models’ outcomes are also compared with multi-linear regression based on Nash-Sutcliffe efficiency, root mean square error, and coefficient of determination statistics. ELM is found to be generally performs better than the other four alternatives in estimating soil temperatures. A decrease in performance of the models is observed by an increase in soil depth. It is found that soil temperatures at three depths (5, 10 and 50 cm) could be mapped utilizing only air temperature data as input while solar radiation and wind speed information are also required for estimating soil temperature at the depth of 100 cm.

  • Open Access
    Authors: 
    Aaron A. Dutton; Andrea V. Macciò; Jonas Frings; Liang Wang; G. S. Stinson; Camilla Penzo; Xi Kang;
    Publisher: Oxford University Press (OUP)
    Project: EC | MW-DISK (321035)

    We compare the half-light circular velocities, V_{1/2}, of dwarf galaxies in the Local Group to the predicted circular velocity curves of galaxies in the NIHAO suite of LCDM simulations. We use a subset of 34 simulations in which the central galaxy has a stellar luminosity in the range 0.5 x 10^5 < L_V < 2 x 10^8 L_{sun}. The NIHAO galaxy simulations reproduce the relation between stellar mass and halo mass from abundance matching, as well as the observed half-light size vs luminosity relation. The corresponding dissipationless simulations over-predict the V_{1/2}, recovering the problem known as too big to fail (TBTF). By contrast, the NIHAO simulations have expanded dark matter haloes, and provide an excellent match to the distribution of V_{1/2} for galaxies with L_V > 2 x 10^6 L_{sun}. For lower luminosities our simulations predict very little halo response, and tend to over predict the observed circular velocities. In the context of LCDM, this could signal the increased stochasticity of star formation in haloes below M_{halo} \sim 10^{10} M_{sun}, or the role of environmental effects. Thus, haloes that are "too big to fail", do not fail LCDM, but haloes that are "too small to pass" (the galaxy formation threshold) provide a future test of LCDM. 6 pages, 3 figures, accepted to MNRAS letters

  • Open Access
    Authors: 
    Nighat Perveen; Sabir Bin Muzaffar; Mohammad Ali Al-Deeb;
    Publisher: MDPI AG

    Simple Summary The Middle East and North Africa represent a hyper arid region of the world. Humans in these regions have historically kept domestic livestock usually under harsh environmental circumstances. With recent human development, especially in the Middle East, the livestock industry has increased. Livestock is affected by ticks and tick-borne diseases on which there has been relatively few studies in this region. This review paper aims to (i) examine the diversity of ticks infesting livestock, (ii) assess the variety of pathogens in animals and humans, and (iii) to identify gaps in our understanding of tick biology and tick-borne disease transmission in the region. We found 55 tick species on livestock including camels, cows, goats and sheep, belonging to eight genera. Fifteen tick-borne pathogens were reported from livestock in the region. We highlight the magnitude of the tick problem in the region and evaluate the control efforts currently in place. We suggest that disease control and prevention could be achieved effectively through collaborative work among all stakeholders such as funding international research projects and establishing joint control programs to combat cross-border movement of ticks. Abstract Ticks are important vectors of an array of viral, bacterial and protozoan pathogens resulting in a wide range of animal and human diseases. There is limited information in the literature about tick species in the Middle East and North Africa (MENA) countries, even though they have suitable climate and vegetation for ticks and their hosts. We reviewed the occurrence of tick species and the pathogens they transmit from the MENA on published papers from 1901–2020. We found taxonomic records of 55 tick species infesting livestock representing the following eight genera: Ornithodoros, Otobius, Amblyomma, Dermacentor, Haemaphysalis, Hyalomma, Ixodes, and Rhipicephalus. In addition, 15 pathogens were recorded causing diseases of significance, with Crimean–Congo hemorrhagic fever, theileriosis, babesiosis and anaplasmosis being widely distributed diseases in the region. In recent decades, there has been increasing trends in disease occurrence and movement associated with global movement of humans and global trade of animals. We suggest that disease control and prevention could be achieved effectively through good integration between public health, veterinary medicine and animal management, and ecological approaches. We recommend further research in the areas of tick ecology and tick born-disease transmission. Furthermore, we suggest evaluation and improvement of disease control policies in the region.

  • Open Access
    Authors: 
    Emilia Papakonstantinou; Ioanna Kechribari; Panayota Mitrou; E Trakakis; D. Vassiliadi; Ekavi N. Georgousopoulou; A Zampelas; Meropi D. Kontogianni; George Dimitriadis;
    Publisher: Springer Science and Business Media LLC

    Effect of meal frequency on glucose and insulin levels in women with polycystic ovary syndrome: a randomised trial

  • Open Access
    Authors: 
    Yagnesh Bapodra; Udayakumar Rajamanickam;
    Publisher: IOP Publishing

    Abstract This paper discusses about the Hybrid Electric Vehicle (HEV) and the simulation on the Parallel Hybrid Electric Vehicle Drivetrain. The concept and the classification of the HEV is discussed here and the simulation and analysis of a drivetrain for Parallel Electric Hybrid Engine (PHEV) was formulated on MATLAB Simulink. The methodology of simulation was to accelerate or decelerate the vehicle independently with the electric motor with engine running at constant speed. And the parameters such as electric motor and engine power were compared and observed. And research on CO2 emission and fuel consumption was made between the PHEV and Conventional Vehicle (ICE Vehicle). And the conclusion was made according to the research and the simulation that the development of HEV will have a great potential in fuel economy improvement.

  • Open Access
    Authors: 
    Hong Zhang; Kumar Anupam; Athanasios Skarpas; Cor Kasbergen; Sandra Erkens;
    Publisher: SAGE Publications
    Country: Netherlands

    In the Netherlands, more than 80% of the highways are surfaced by porous asphalt (PA) mixes. The benefits of using PA mixes include, among others, the reduction of noise and the improvement of skid resistance. However, pavements with PA mixes are known to have a shorter lifetime and higher maintenance costs as compared with traditional dense asphalt mixes. Raveling is one of the most prominent distresses that occur on PA mix pavements. To analyze the raveling distress of a PA mix pavement, the stress and strain fields at the component level are required. Computational models based on finite element methods (FEM), discrete element methods (DEM), or both, can be used to compute local stress and strain fields. However, they require the development of large FEM meshes and large-scale computational facilities. As an alternative, the homogenization technique provides a way to calculate the stress and strain fields at the component level without the need for much computation power. This study aims to propose a new approach to analyze the raveling distress of a PA mix pavement by using the homogenization technique. To demonstrate the application of the proposed approach, a real field-like example was presented. In the real field-like example, the Mori–Tanaka model was used as a homogenization technique. The commonly available pavement analysis tool 3D-MOVE was used to compute the response of the analyzed pavement. In general, it was concluded that the homogenization technique could be a reliable and effective way to analyze the raveling distress of a PA mix pavement.

  • Publication . Conference object . Preprint . Article . 2019 . Embargo End Date: 01 Jan 2019
    Open Access
    Authors: 
    Breton Minnehan; Andreas Savakis;
    Publisher: arXiv

    We propose a data-driven approach for deep convolutional neural network compression that achieves high accuracy with high throughput and low memory requirements. Current network compression methods either find a low-rank factorization of the features that requires more memory, or select only a subset of features by pruning entire filter channels. We propose the Cascaded Projection (CaP) compression method that projects the output and input filter channels of successive layers to a unified low dimensional space based on a low-rank projection. We optimize the projection to minimize classification loss and the difference between the next layer's features in the compressed and uncompressed networks. To solve this non-convex optimization problem we propose a new optimization method of a proxy matrix using backpropagation and Stochastic Gradient Descent (SGD) with geometric constraints. Our cascaded projection approach leads to improvements in all critical areas of network compression: high accuracy, low memory consumption, low parameter count and high processing speed. The proposed CaP method demonstrates state-of-the-art results compressing VGG16 and ResNet networks with over 4x reduction in the number of computations and excellent performance in top-5 accuracy on the ImageNet dataset before and after fine-tuning.

  • Open Access
    Authors: 
    Christos Mourlas; George Markou; Manolis Papadrakakis;
    Publisher: Elsevier BV

    Abstract Many constitutive models have been proposed in order to capture the realistic behavior of reinforced concrete structures under static loading conditions. Few of these numerical models manage to extend to dynamic problems. This is due to the fact that these models present increased computational demand and inability to simulate realistically the different types of mechanical behavior of reinforced concrete members. The purpose of this paper is to propose a computationally efficient constitutive method in order to simulate accurately the behavior of a wide range of reinforced concrete structural members under dynamic loading conditions. The proposed material model is based on the Markou and Papadrakakis [1] model which was an extension of the Kotsovos and Pavlovic [2] work. A solution strategy which describes the behavior of concrete during the dynamic loading is presented. The proposed algorithm describes the cyclic behavior of concrete which is dominated by the development of microcracking, macrocracking and brittle failure. It uses the implicit integration method of Newmark in order to solve the equation of motion. The concrete domain is simulated by 8- and 20-noded hexahedral elements, which treat cracking with the smeared crack approach. The steel reinforcement is embedded inside the hexahedral meshing and modeled by truss and beam elements. Accurate nonlinear dynamic analysis of reinforced concrete structures is very helpful in estimating the behavior of a concrete structures during an earthquake. Many concrete buildings have been designed according to the old seismic codes. Thus, an accurate and realistic modeling to assess their strength and their ability to carry the expected seismic forces is very important. The validity of the proposed method is demonstrated by comparing the numerical response with the corresponding experimental results of reinforced concrete members.

  • Open Access English
    Authors: 
    Jinsong Wu; Richard T. Watson; Raffaele Bolla; Athanassios Manikas; Mounir Hamdi; Jaafar M. H. Elmirghani;
    Publisher: IEEE
    Country: United Kingdom

    The papers in this special section focus on green communications, computing, and systems engineering. Computing technologies are used extensively in network systems, such as cloud computing and grid computing, and the Internet is the most well-known and widely used network infrastructure for computing. Networked software and hardware applications, especially wireless and mobile ones, have been made remarkable and fast increasing impacts on society development and human lives. They touch a great number of the human population in the world through ubiquitous mobile phones and devices. Computing and communications are indispensable components in many diverse systems. All these systems have energy issues. Their increasing spread, particularly with the emergence of the Internet of Things, is a great challenge to a world seeking to reduce its reliance on fossil fuels and address global climate changes. At the same time, although energy concerns are one of the dominant “green” topics, the green issues could be more generally defined as those making the world and the components of man-made systems both sustainable and friendly in an environmental, economic, social, and/or technical sense. In this sense, the word “green,” includes not only the sustainability objectives but also the “most positive and friendly” characteristics concerning human environments and societies.

  • Open Access
    Authors: 
    Haneen Alsuradi; Jerald Yoo;
    Publisher: Springer Science and Business Media LLC

    AbstractThe healthcare system is undergoing a noticeable transformation from a reactive, post-disease treatment to a preventive, predictive continuous healthcare. The key enabler for such a system is a pervasive wearable platform. Several technologies have been suggested and implemented as a wearable platform, but these technologies either lack reliability, manufacturing practicability or pervasiveness. We propose a screen-printed circuit board on bio-degradable hydrocolloid dressings, which are medically used and approved, as a platform for wearable biomedical sensors to overcome the aforementioned problems. We experimentally characterize and prepare the surface of the hydrocolloid and demonstrate high-quality screen-printed passive elements and interconnects on its surface using conductive silver paste. We also propose appropriate models of the thick-film screen-printed passives, validated through measurements and FEM simulations. We further elucidate on the usage of the hydrocolloid dressing by prototyping a Wireless Power Transfer (WPT) sensor and a humidity sensor using printed spiral inductors and interdigital capacitors, respectively.

Advanced search in
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
18,404 Research products, page 1 of 1,841
  • Open Access English
    Authors: 
    Meysam Alizamir; Ozgur Kisi; Ali Najah Ahmed; Cihan Mert; Chow Ming Fai; Sungwon Kim; Nam-Won Kim; Ahmed El-Shafie;
    Publisher: Public Library of Science

    Soil temperature has a vital importance in biological, physical and chemical processes of terrestrial ecosystem and its modeling at different depths is very important for land-atmosphere interactions. The study compares four machine learning techniques, extreme learning machine (ELM), artificial neural networks (ANN), classification and regression trees (CART) and group method of data handling (GMDH) in estimating monthly soil temperatures at four different depths. Various combinations of climatic variables are utilized as input to the developed models. The models’ outcomes are also compared with multi-linear regression based on Nash-Sutcliffe efficiency, root mean square error, and coefficient of determination statistics. ELM is found to be generally performs better than the other four alternatives in estimating soil temperatures. A decrease in performance of the models is observed by an increase in soil depth. It is found that soil temperatures at three depths (5, 10 and 50 cm) could be mapped utilizing only air temperature data as input while solar radiation and wind speed information are also required for estimating soil temperature at the depth of 100 cm.

  • Open Access
    Authors: 
    Aaron A. Dutton; Andrea V. Macciò; Jonas Frings; Liang Wang; G. S. Stinson; Camilla Penzo; Xi Kang;
    Publisher: Oxford University Press (OUP)
    Project: EC | MW-DISK (321035)

    We compare the half-light circular velocities, V_{1/2}, of dwarf galaxies in the Local Group to the predicted circular velocity curves of galaxies in the NIHAO suite of LCDM simulations. We use a subset of 34 simulations in which the central galaxy has a stellar luminosity in the range 0.5 x 10^5 < L_V < 2 x 10^8 L_{sun}. The NIHAO galaxy simulations reproduce the relation between stellar mass and halo mass from abundance matching, as well as the observed half-light size vs luminosity relation. The corresponding dissipationless simulations over-predict the V_{1/2}, recovering the problem known as too big to fail (TBTF). By contrast, the NIHAO simulations have expanded dark matter haloes, and provide an excellent match to the distribution of V_{1/2} for galaxies with L_V > 2 x 10^6 L_{sun}. For lower luminosities our simulations predict very little halo response, and tend to over predict the observed circular velocities. In the context of LCDM, this could signal the increased stochasticity of star formation in haloes below M_{halo} \sim 10^{10} M_{sun}, or the role of environmental effects. Thus, haloes that are "too big to fail", do not fail LCDM, but haloes that are "too small to pass" (the galaxy formation threshold) provide a future test of LCDM. 6 pages, 3 figures, accepted to MNRAS letters

  • Open Access
    Authors: 
    Nighat Perveen; Sabir Bin Muzaffar; Mohammad Ali Al-Deeb;
    Publisher: MDPI AG

    Simple Summary The Middle East and North Africa represent a hyper arid region of the world. Humans in these regions have historically kept domestic livestock usually under harsh environmental circumstances. With recent human development, especially in the Middle East, the livestock industry has increased. Livestock is affected by ticks and tick-borne diseases on which there has been relatively few studies in this region. This review paper aims to (i) examine the diversity of ticks infesting livestock, (ii) assess the variety of pathogens in animals and humans, and (iii) to identify gaps in our understanding of tick biology and tick-borne disease transmission in the region. We found 55 tick species on livestock including camels, cows, goats and sheep, belonging to eight genera. Fifteen tick-borne pathogens were reported from livestock in the region. We highlight the magnitude of the tick problem in the region and evaluate the control efforts currently in place. We suggest that disease control and prevention could be achieved effectively through collaborative work among all stakeholders such as funding international research projects and establishing joint control programs to combat cross-border movement of ticks. Abstract Ticks are important vectors of an array of viral, bacterial and protozoan pathogens resulting in a wide range of animal and human diseases. There is limited information in the literature about tick species in the Middle East and North Africa (MENA) countries, even though they have suitable climate and vegetation for ticks and their hosts. We reviewed the occurrence of tick species and the pathogens they transmit from the MENA on published papers from 1901–2020. We found taxonomic records of 55 tick species infesting livestock representing the following eight genera: Ornithodoros, Otobius, Amblyomma, Dermacentor, Haemaphysalis, Hyalomma, Ixodes, and Rhipicephalus. In addition, 15 pathogens were recorded causing diseases of significance, with Crimean–Congo hemorrhagic fever, theileriosis, babesiosis and anaplasmosis being widely distributed diseases in the region. In recent decades, there has been increasing trends in disease occurrence and movement associated with global movement of humans and global trade of animals. We suggest that disease control and prevention could be achieved effectively through good integration between public health, veterinary medicine and animal management, and ecological approaches. We recommend further research in the areas of tick ecology and tick born-disease transmission. Furthermore, we suggest evaluation and improvement of disease control policies in the region.

  • Open Access
    Authors: 
    Emilia Papakonstantinou; Ioanna Kechribari; Panayota Mitrou; E Trakakis; D. Vassiliadi; Ekavi N. Georgousopoulou; A Zampelas; Meropi D. Kontogianni; George Dimitriadis;
    Publisher: Springer Science and Business Media LLC

    Effect of meal frequency on glucose and insulin levels in women with polycystic ovary syndrome: a randomised trial

  • Open Access
    Authors: 
    Yagnesh Bapodra; Udayakumar Rajamanickam;
    Publisher: IOP Publishing

    Abstract This paper discusses about the Hybrid Electric Vehicle (HEV) and the simulation on the Parallel Hybrid Electric Vehicle Drivetrain. The concept and the classification of the HEV is discussed here and the simulation and analysis of a drivetrain for Parallel Electric Hybrid Engine (PHEV) was formulated on MATLAB Simulink. The methodology of simulation was to accelerate or decelerate the vehicle independently with the electric motor with engine running at constant speed. And the parameters such as electric motor and engine power were compared and observed. And research on CO2 emission and fuel consumption was made between the PHEV and Conventional Vehicle (ICE Vehicle). And the conclusion was made according to the research and the simulation that the development of HEV will have a great potential in fuel economy improvement.

  • Open Access
    Authors: 
    Hong Zhang; Kumar Anupam; Athanasios Skarpas; Cor Kasbergen; Sandra Erkens;
    Publisher: SAGE Publications
    Country: Netherlands

    In the Netherlands, more than 80% of the highways are surfaced by porous asphalt (PA) mixes. The benefits of using PA mixes include, among others, the reduction of noise and the improvement of skid resistance. However, pavements with PA mixes are known to have a shorter lifetime and higher maintenance costs as compared with traditional dense asphalt mixes. Raveling is one of the most prominent distresses that occur on PA mix pavements. To analyze the raveling distress of a PA mix pavement, the stress and strain fields at the component level are required. Computational models based on finite element methods (FEM), discrete element methods (DEM), or both, can be used to compute local stress and strain fields. However, they require the development of large FEM meshes and large-scale computational facilities. As an alternative, the homogenization technique provides a way to calculate the stress and strain fields at the component level without the need for much computation power. This study aims to propose a new approach to analyze the raveling distress of a PA mix pavement by using the homogenization technique. To demonstrate the application of the proposed approach, a real field-like example was presented. In the real field-like example, the Mori–Tanaka model was used as a homogenization technique. The commonly available pavement analysis tool 3D-MOVE was used to compute the response of the analyzed pavement. In general, it was concluded that the homogenization technique could be a reliable and effective way to analyze the raveling distress of a PA mix pavement.

  • Publication . Conference object . Preprint . Article . 2019 . Embargo End Date: 01 Jan 2019
    Open Access
    Authors: 
    Breton Minnehan; Andreas Savakis;
    Publisher: arXiv

    We propose a data-driven approach for deep convolutional neural network compression that achieves high accuracy with high throughput and low memory requirements. Current network compression methods either find a low-rank factorization of the features that requires more memory, or select only a subset of features by pruning entire filter channels. We propose the Cascaded Projection (CaP) compression method that projects the output and input filter channels of successive layers to a unified low dimensional space based on a low-rank projection. We optimize the projection to minimize classification loss and the difference between the next layer's features in the compressed and uncompressed networks. To solve this non-convex optimization problem we propose a new optimization method of a proxy matrix using backpropagation and Stochastic Gradient Descent (SGD) with geometric constraints. Our cascaded projection approach leads to improvements in all critical areas of network compression: high accuracy, low memory consumption, low parameter count and high processing speed. The proposed CaP method demonstrates state-of-the-art results compressing VGG16 and ResNet networks with over 4x reduction in the number of computations and excellent performance in top-5 accuracy on the ImageNet dataset before and after fine-tuning.

  • Open Access
    Authors: 
    Christos Mourlas; George Markou; Manolis Papadrakakis;
    Publisher: Elsevier BV

    Abstract Many constitutive models have been proposed in order to capture the realistic behavior of reinforced concrete structures under static loading conditions. Few of these numerical models manage to extend to dynamic problems. This is due to the fact that these models present increased computational demand and inability to simulate realistically the different types of mechanical behavior of reinforced concrete members. The purpose of this paper is to propose a computationally efficient constitutive method in order to simulate accurately the behavior of a wide range of reinforced concrete structural members under dynamic loading conditions. The proposed material model is based on the Markou and Papadrakakis [1] model which was an extension of the Kotsovos and Pavlovic [2] work. A solution strategy which describes the behavior of concrete during the dynamic loading is presented. The proposed algorithm describes the cyclic behavior of concrete which is dominated by the development of microcracking, macrocracking and brittle failure. It uses the implicit integration method of Newmark in order to solve the equation of motion. The concrete domain is simulated by 8- and 20-noded hexahedral elements, which treat cracking with the smeared crack approach. The steel reinforcement is embedded inside the hexahedral meshing and modeled by truss and beam elements. Accurate nonlinear dynamic analysis of reinforced concrete structures is very helpful in estimating the behavior of a concrete structures during an earthquake. Many concrete buildings have been designed according to the old seismic codes. Thus, an accurate and realistic modeling to assess their strength and their ability to carry the expected seismic forces is very important. The validity of the proposed method is demonstrated by comparing the numerical response with the corresponding experimental results of reinforced concrete members.

  • Open Access English
    Authors: 
    Jinsong Wu; Richard T. Watson; Raffaele Bolla; Athanassios Manikas; Mounir Hamdi; Jaafar M. H. Elmirghani;
    Publisher: IEEE
    Country: United Kingdom

    The papers in this special section focus on green communications, computing, and systems engineering. Computing technologies are used extensively in network systems, such as cloud computing and grid computing, and the Internet is the most well-known and widely used network infrastructure for computing. Networked software and hardware applications, especially wireless and mobile ones, have been made remarkable and fast increasing impacts on society development and human lives. They touch a great number of the human population in the world through ubiquitous mobile phones and devices. Computing and communications are indispensable components in many diverse systems. All these systems have energy issues. Their increasing spread, particularly with the emergence of the Internet of Things, is a great challenge to a world seeking to reduce its reliance on fossil fuels and address global climate changes. At the same time, although energy concerns are one of the dominant “green” topics, the green issues could be more generally defined as those making the world and the components of man-made systems both sustainable and friendly in an environmental, economic, social, and/or technical sense. In this sense, the word “green,” includes not only the sustainability objectives but also the “most positive and friendly” characteristics concerning human environments and societies.

  • Open Access
    Authors: 
    Haneen Alsuradi; Jerald Yoo;
    Publisher: Springer Science and Business Media LLC

    AbstractThe healthcare system is undergoing a noticeable transformation from a reactive, post-disease treatment to a preventive, predictive continuous healthcare. The key enabler for such a system is a pervasive wearable platform. Several technologies have been suggested and implemented as a wearable platform, but these technologies either lack reliability, manufacturing practicability or pervasiveness. We propose a screen-printed circuit board on bio-degradable hydrocolloid dressings, which are medically used and approved, as a platform for wearable biomedical sensors to overcome the aforementioned problems. We experimentally characterize and prepare the surface of the hydrocolloid and demonstrate high-quality screen-printed passive elements and interconnects on its surface using conductive silver paste. We also propose appropriate models of the thick-film screen-printed passives, validated through measurements and FEM simulations. We further elucidate on the usage of the hydrocolloid dressing by prototyping a Wireless Power Transfer (WPT) sensor and a humidity sensor using printed spiral inductors and interdigital capacitors, respectively.

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