Search results for: focal loss

Authors: Yuan-Ching Lin, Sin-Yu Chen, Pei-Yu Wu

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This study reports the improvement in the wear performance of A6061 aluminum alloy clad with mixed powders of titanium carbide (TiC), copper (Cu) and aluminum (Al) using the gas tungsten arc welding (GTAW) method. The wear performance of the A6061 clad layers was evaluated by performing pin-on-disc mode wear test. Experimental results clearly indicate an enhancement in the hardness of the clad layer by about two times that of the A6061 substrate without cladding. Wear test demonstrated a significant improvement in the wear performance of the clad layer when compared with the A6061 substrate without cladding. Moreover, the interface between the clad layer and the A6061 substrate exhibited superior metallurgical bonding. Due to this bonding, the clad layer did not spall during the wear test; as such, massive wear loss was prevented. Additionally, massive oxidized particulate debris was generated on the worn surface during the wear test; this resulted in three-body abrasive wear and reduced the wear behavior of the clad surface.

Keywords: GTAW、A6061 aluminum alloy, 、surface modification, tribological study, TiC powder cladding

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Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee

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Water pipe network is installed underground and once equipped; it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using Matlab. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.

Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform

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Authors: Murat Çolak, Elifnaz Tanyıldızı

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Today, human mobility with globalization has increased the interaction between countries significantly; although this contact has advanced societies in terms of civilization, it has also increased the likelihood of pandemics. The coronavirus (COVID-19) pandemic, which caused the most loss of life among them, turned into a global epidemic by covering the whole world in a short time. While there was an explosion in demand in some businesses around the world, some businesses temporarily stopped or had to stop their activities. The businesses affected by the crisis had to adapt to the new legal regulations but had to make changes in matters such as their working styles, human resources practices, and policies. One of the measures taken into account is the reduction of the workforce. The current COVID-19 crisis has posed serious challenges for many organizations and has generated an unprecedented wave of termination notices. This study examined examples of companies affected by the pandemic process and changed their working policies after the pandemic. This study aims to reveal the impact of the global COVID-19 pandemic on human resources policies and employees and how these situations will affect businesses in the future.

Keywords: human resource management, crisis management, COVID-19, business function

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Authors: Lama Yaseen, Nourah Al-Hosain

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A Multi-modal system in urban mobility is an essential framework for an optimized urban transport network. Many cities are still heavily dependent on vehicle transportation, dominantly using conventional fuel-based cars for daily travel. With the reliance on motorized vehicles in large cities such as Riyadh, the capital city of Saudi Arabia, traffic congestion is eminent, which ultimately results in an increase in road emissions and loss of time. Saudi Arabia plans to undergo a massive transformation in mobility infrastructure and urban greening projects, including introducing public transport and other massive urban greening infrastructures that enable alternative mobility options. This paper uses a Geographic Information System (GIS) approach that analyzes the accessibility of current and planned public transport stations and how they intertwine with massive urban greening projects that may play a role as an enabler of micro-mobility and walk-ability options in the city.

Keywords: urban development, urban mobility, sustainable mobility, Middle East

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Authors: Rubens P. Costa, Marcelo A. Leigui de Oliveira

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The comprehension of features on the energy spectra, the chemical compositions, and the origins of Ultra-High Energy Cosmic Rays (UHECRs) - mainly atomic nuclei with energies above ~1.0 EeV (exa-electron volts) - are intrinsically linked to the problem of determining the magnitude of their deflections in cosmic magnetic fields on cosmological scales. In addition, as they propagate from the source to the observer, modifications are expected in their original energy spectra, anisotropy, and the chemical compositions due to interactions with low energy photons and matter. This means that any consistent interpretation of the nature and origin of UHECRs has to include the detailed knowledge of their propagation in a three-dimensional environment, taking into account the magnetic deflections and energy losses. The parameter space range for the magnetic fields in the universe is very large because the field strength and especially their orientation have big uncertainties. Particularly, the strength and morphology of the Extragalactic Magnetic Fields (EGMFs) remain largely unknown, because of the intrinsic difficulty of observing them. Monte Carlo simulations of charged particles traveling through a simulated magnetized universe is the straightforward way to study the influence of extragalactic magnetic fields on UHECRs propagation. However, this brings two major difficulties: an accurate numerical modeling of charged particles diffusion in magnetic fields, and an accurate numerical modeling of the magnetized Universe. Since magnetic fields do not cause energy losses, it is important to impose that the particle tracking method conserve the particle’s total energy and that the energy changes are results of the interactions with background photons only. Hence, special attention should be paid to computational effects. Additionally, because of the number of particles necessary to obtain a relevant statistical sample, the particle tracking method must be computationally efficient. In this work, we present an analysis of the propagation of ultra-high energy charged particles in the intergalactic medium. The EGMFs are considered to be coherent within cells of 1 Mpc (mega parsec) diameter, wherein they have uniform intensities of 1 nG (nano Gauss). Moreover, each cell has its field orientation randomly chosen, and a border region is defined such that at distances beyond 95% of the cell radius from the cell center smooth transitions have been applied in order to avoid discontinuities. The smooth transitions are simulated by weighting the magnetic field orientation by the particle's distance to the two nearby cells. The energy losses have been treated in the continuous approximation parameterizing the mean energy loss per unit path length by the energy loss length. We have shown, for a particle with the typical energy of interest the integration method performance in the relative error of Larmor radius, without energy losses and the relative error of energy. Additionally, we plotted the distance amplification from rectilinear propagation as a function of the traveled distance, particle's magnetic rigidity, without energy losses, and particle's energy, with energy losses, to study the influence of particle's species on these calculations. The results clearly show when it is necessary to use a full three-dimensional simulation.

Keywords: cosmic rays propagation, extragalactic magnetic fields, magnetic deflections, ultra-high energy

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Authors: D. Kumar, S. Kumar, A. G. Memon, R. A. Memon, K. Harijan

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A considerable amount of energy is usually lost due to compression of insulation in Heating, ventilation, and air conditioning (HVAC) duct. In this paper, the economic impact of compression of insulation is estimated. Relevant mathematical models were used to estimate the optimal thickness at the points of compression. Furthermore, the payback period is calculated for the optimal thickness at the critical parts of supply air duct (SAD) and return air duct (RAD) considering natural gas (NG) and liquefied petroleum gas (LPG) as fuels for chillier operation. The mathematical model is developed using preliminary data obtained for an HVAC system of a pharmaceutical company. The higher heat gain and cooling loss, due to compression of thermal insulation, is estimated using relevant heat transfer equations. The results reveal that maximum energy savings (ES) in SAD is 34.5 and 40%, while in RAD is 22.9% and 29% for NG and LPG, respectively. Moreover, the minimum payback period (PP) for SAD is 2 and 1.6years, while in RAD is 4.3 and 2.7years for NG and LPG, respectively. The optimum insulation thickness (OIT) corresponding to maximum ES and minimum PP is estimated to be 35 and 42mm for SAD, while 30 and 38mm for RAD in case of NG and LPG, respectively.

Keywords: optimum insulation thickness, life cycle cost analysis, payback period, HVAC system

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Authors: Leveque Benjamin, Rabaud Suzanne, Anest Hugo, Catalan Caroline, Neveux Guillaume

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Human products consumption is one of the main drivers of biodiversity loss. However, few pertinent ecological indicators regarding product life cycle impact on species and ecosystems have been built. Life cycle assessment (LCA) methodologies are well under way to conceive standardized methods to assess this impact, by taking already partially into account three of the Millennium Ecosystem Assessment pressures (land use, pollutions, climate change). Coupling LCA and ecological data and methods is an emerging challenge to develop a product biodiversity footprint. This approach was tested on three case studies from food processing, textile, and cosmetic industries. It allowed first to improve the environmental relevance of the Potential Disappeared Fraction of species, end-point indicator typically used in life cycle analysis methods, and second to introduce new indicators on overexploitation and invasive species. This type of footprint is a major step in helping companies to identify their impacts on biodiversity and to propose potential improvements.

Keywords: biodiversity, companies, footprint, life cycle assessment, products

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Authors: Vitali Kremez

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The researcher monitored an organized ransomware campaign in order to gain significant visibility into the tactics, techniques, and procedures employed by a campaign boss operating a ransomware scheme out of Russia. As the Russian hacking community lowered the access requirements for unsophisticated Russian cybercriminals to engage in ransomware campaigns, corporations and individuals face a commensurately greater challenge of effectively protecting their data and operations from being held ransom. This report discusses two notorious ransomware campaigns. Though the loss of data can be devastating, the findings demonstrate that sending ransom payments does not always help obtain data. Key learnings: 1. From the ransomware affiliate perspective, such campaigns have significantly lowered the barriers for entry for low-tier cybercriminals. 2. Ransomware revenue amounts are not as glamorous and fruitful as they are often publicly reported. Average ransomware crime bosses make only $90K per year on average. 3. Data gathered indicates that sending ransom payments does not always help obtain data. 4. The talk provides the complete payout structure and Bitcoin laundering operation related to the ransomware-as-a-service campaign.

Keywords: bitcoin, cybercrime, ransomware, Russia

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Authors: Priya Arora, Jaspreet K. Rajput

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Superparamagnetism has accelerated the research and use of more economical and ecological magnetically separable catalysts due to their more efficient isolation by response to an applied magnetic field. Magnetite nanomaterials coated by SiO2 shell have received a great deal of focus in the last decades as it provides high stability and also easy further surface functionalization depending upon the application. In this protocol, Fe3O4 magnetic nanoparticles have been synthesized by co-precipitation combined with sonication method. Further, Fe3O4 superparamagnetic nanoparticles have been functionalized by various moieties to serve as efficient catalysts for multicomponent reactions. The functionalized nanoparticles were characterized by techniques like Fourier transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), scanning electron microscopy (SEM), vibrating sample magnetometer (VSM), thermogravimetric analysis (TGA), Brunauer-Emmett-Teller (BET) surface area analysis. The as prepared nanocatalysts can be reused for several times without any significant loss in its activity. The utilization of magnetic nanoparticles as catalysts for this reaction is one approach i.e. green, inexpensive, facile and widely applicable.

Keywords: functionalized, magnetite, multicomponent reactions, superparamagnetic

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Authors: Kudakwashe Diana Nyamugure

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Engine design has evolved to suit new industry standards of smaller compact designs that operate at high temperatures and even higher stress loads. Research has proven that the interaction of the bearing surface and the lubrication film is affected by the bearing's surface texture, geometry, and dimensional tolerances. The challenge now for the automotive manufacturing industry is to understand which processes can be applied on bearing surfaces to reduce the 65% energy loss in engines, 15% of which is caused by friction. This paper will discuss a post grinding process known as microfinishing which optimises the characteristics of a manufactured surface such as roughness, profile, and waviness. Microfinishing is becoming an increasing trend within the automotive industry and has so far been applied on high performance and mass production crank or cam bearing surfaces in bid of friction reduction and extended engine service life. In the near future, microfinishing will be applied to more engine components because of the stringent environmental regulations demands on fuel consumption, reliability, power, and service life of engine components.

Keywords: bearings, tribology, friction reduction, energy efficiency

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Authors: Abdulkadir Adamu Shehu

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Company’s reputation is an elusive asset. The reputation gained by companies must be preserved for sustainability of the company. However, the construction project is still suffering from declination of character due to the factors that affect their reputation. The problem led to the loss of projects, abandoning of the projects and many more. This contributed to negative impact on the contractors in the construction industry. As for today, previous studies have not investigated in this regards yet. For that reason, this paper examines the factors which could promote contractor’s reputation in the construction industry in Nigeria. To achieve this aim, 140 questionnaires were distributed to the Nigerian contractors. Based on the 67% response rate, descriptive analysis and analysis of variance (ANOVA) were the tools applied for the data obtained to be analysed. The result shows that, good communication system and improve quality of output of products are the most significant variables that can promote contractor’s reputation. The homogenous analyses indicate that there are significant different perceptions of respondents in term of the significant effects. The research concluded that contractor’s reputation in construction industry must be maintained and further research was suggested to focus on the qualitative method to have in-depth knowledge on contractor’s reputation in the construction industry.

Keywords: construction industry, contractor’s reputation, effects of delay, Nigeria

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Authors: A. Hassannia, S. Ramezani

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The technology of superconductivity has developed in many power system devices such as transmission cable, transformer, current limiter, motor and generator. Superconducting wires can carry high density current without loss, which is the capability that is used to design the compact, lightweight and more efficient electrical machines. Superconducting motors have found applications in marine and air propulsion systems as well as superconducting generators are considered in low power hydraulic and wind generators. This paper presents a rim-driven superconducting synchronous generator for hydraulic power plant. The rim-driven concept improves the performance of hydro turbine. Furthermore, high magnetic field that is produced by superconducting windings allows replacing the rotor core. As a consequent, the volume and weight of the machine is decreased significantly. In this paper, a 1 MW coreless rim-driven superconducting synchronous generator is designed. Main performance characteristics of the proposed machine are then evaluated using finite elements method and compared to an ordinary similar size synchronous generator.

Keywords: coreless machine, electrical machine design, hydraulic generator, rim-driven machine, superconducting generator

Procedia PDF Downloads 174

Authors: Peng Wang, Tigang Jiang

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The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

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Authors: Naghmeh M. Bandari, Javad Dargahi, Muthukumaran Packirisamy

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Robot-assisted minimally invasive surgery (RMIS) has been widely performed around the world during the last two decades. RMIS demonstrates significant advantages over conventional surgery, e.g., improving the accuracy and dexterity of a surgeon, providing 3D vision, motion scaling, hand-eye coordination, decreasing tremor, and reducing x-ray exposure for surgeons. Despite benefits, surgeons cannot touch the surgical site and perceive tactile information. This happens due to the remote control of robots. The literature survey identified the lack of force feedback as the riskiest limitation in the existing technology. Without the perception of tool-tissue contact force, the surgeon might apply an excessive force causing tissue laceration or insufficient force causing tissue slippage. The primary use of force sensors has been to measure the tool-tissue interaction force in real-time in-situ. Design of a tactile sensor is subjected to a set of design requirements, e.g., biocompatibility, electrical-passivity, MRI-compatibility, miniaturization, ability to measure static and dynamic force. In this study, a planar optical fiber-based sensor was proposed to mount at the surgical grasper. It was developed based on the light intensity modulation principle. The deflectable part of the sensor was a beam modeled as a cantilever Euler-Bernoulli beam on rigid substrates. A semi-cylindrical indenter was attached to the bottom surface the beam at the mid-span. An optical fiber was secured at both ends on the same rigid substrates. The indenter was in contact with the fiber. External force on the sensor caused deflection in the beam and optical fiber simultaneously. The micro-bending of the optical fiber would consequently result in light power loss. The sensor was simulated and studied using finite element methods. A laser light beam with 800nm wavelength and 5mW power was used as the input to the optical fiber. The output power was measured using a photodetector. The voltage from photodetector was calibrated to the external force for a chirp input (0.1-5Hz). The range, resolution, and hysteresis of the sensor were studied under monotonic and harmonic external forces of 0-2.0N with 0 and 5Hz, respectively. The results confirmed the validity of proposed sensing principle. Also, the sensor demonstrated an acceptable linearity (R2 > 0.9). A minimum external force was observed below which no power loss was detectable. It is postulated that this phenomenon is attributed to the critical angle of the optical fiber to observe total internal reflection. The experimental results were of negligible hysteresis (R2 > 0.9) and in fair agreement with the simulations. In conclusion, the suggested planar sensor is assessed to be a cost-effective solution, feasible, and easy to use the sensor for being miniaturized and integrated at the tip of robotic graspers. Geometrical and optical factors affecting the minimum sensible force and the working range of the sensor should be studied and optimized. This design is intrinsically scalable and meets all the design requirements. Therefore, it has a significant potential of industrialization and mass production.

Keywords: force sensor, minimally invasive surgery, optical sensor, robotic surgery, tactile sensor

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: Abdul Manan

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Dielectric Resonators (DRs) have revolutionized the microwave wireless communication industry globally. There are three directions for research in ceramics for application in telecommunication industry Three key properties of ceramic dielectrics that determine their functionality at microwave and millimetrewave frequencies include relative permittivity (εr), unloaded quality factor Qu- the inverse of the dielectric loss (tanδ) and temperature coefficient of resonant frequency (τf). Each direction requires specific properties. These dielectric properties are affected by a number of factors. These includes tolerance factor, onset of structural phase transitions, dark core formation, processing conditions, raw materials and impurities, order/disorder behavior, compositional ordering, porosity, humidity, grain size, orientation of the crystallites, and grain boundaries. The data related to these factors is scattered. The main purpose of this review is to bring these together and present the effects of these factors on the microwave dielectric properties. Control of these factors is important for improvement in the microwave properties. This review would be very helpful to the novice researchers and technologists in the field.

Keywords: order disorder, sintering, defect, porosity, grain boundaries

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Authors: Muhammad Nurrizka Ramadhan

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Today,Demand for wood increase in rapid rate. Wood is widely used for many things range from building materials to furniture materials. This makes the forest area in Indonesia dropped dramatically, it is estimated that the area of Indonesiaan forest in 2020 will be only about 16 million hectares. The more forest in Indonesia loss, people are required to look for another material to subtitute wood for the furniture. Jepara, a city with the largest furniture industry in Indonesia, requires a large supply of wood, it can reach 300.000 – 500.000 cubic meters per year. Most of the furniture in Jepara use teak, mahogany, and rosewood. Though teak wood is a rare species that must be protected. Today the availability of bamboo in Indonesia is very big. With cheap price, and the period of rapid growth makes bamboo can be used as a substitute for wood for the furniture industry in the future. By making use bamboo to make wood bamboo composite to replace the use of wood for furniture material. This paper is about the use of bamboo as a substitute for wood bamboo composite for the furniture industry. Expected in future, wood can be replaced by a wood bamboo composite.

Keywords: bamboo, composite, furniture, wood

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Authors: Adnan Mazari, Engin Akcagun, Antonin Havelka, Funda Buyuk Mazari, Pavel Kejzlar

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This article experimentally investigates various physical properties of special fire retardant sewing threads under different sewing speeds. The aramid threads are common for sewing the fire-fighter clothing due to high strength and high melting temperature. 3 types of aramid threads with different linear densities are used for sewing at different speed of 2000 to 4000 r/min. The needle temperature is measured at different speeds of sewing and tensile properties of threads are measured before and after the sewing process respectively. The results shows that the friction and abrasion during the sewing process causes a significant loss to the tensile properties of the threads and needle temperature rises to nearly 300^oC at 4000 r/min of machine speed. The Scanning electron microscope images are taken before and after the sewing process and shows no melting spots but significant damage to the yarn. It is also found that machine speed of 2000r/min is ideal for sewing firefighter clothing for higher tensile properties and production.

Keywords: Kevlar, needle temperautre, nomex, sewing

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Authors: J. S. S. Neto, R. A. A. Lima, D. K. K. Cavalcanti, J. P. B. Souza, R. A. A. Aguiar, M. D. Banea

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In the last decade, investments in sustainable processes and products have gained space in several segments, such as in the civil, automobile, textile and other industries. In addition to increasing concern about the development of environmentally friendly materials that reduce, energy costs and reduces environmental impact in the production of these products, as well as reducing CO2 emissions. Natural fibers offer a great alternative to replace synthetic fibers, totally or partially, because of their low cost and their renewable source. The purpose of this research is to study the effect of surface chemical treatment on the thermal properties of hybrid fiber reinforced natural fibers (NFRC), jute + ramie, jute + sisal, jute + curauá, and jute fiber in polymer matrices. Two types of chemical treatment: alkalinization and silanization were employed, besides the condition without treatment. Differential scanning calorimetry (DSC), thermogravimetry (TG) and dynamic-mechanical analysis (DMA) were performed to explore the thermal stability and weight loss in the natural fiber reinforced composite as a function of chemical treatment.

Keywords: chemical treatment, hybrid composite, jute, thermal

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Authors: V. Sobotková, B. Šarapatka, M. Dumbrovský, J. Uhrová, M. Bednář

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The paper deals with the influence of implemented conservation measures on the quality of surface water resources. Recently, a new process of complex land consolidation in the Czech Republic has provided a unique opportunity to improve the quality of the environment and sustainability of crop production by means of better soil and water conservation. The most important degradation factor in our study area in the Hubenov drinking water reservoir catchment basin was water erosion together with loss of organic matter. Hubenov Reservoir water resources were monitored for twenty years (1990–2010) to collect water quality data for nitrate nitrogen (N-NO3-), total P, and undissolved substances. Results obtained from measurements taken before and after land consolidation indicated a decrease in the linear trend of N-NO3- and total P concentrations, this was achieved through implementation of conservation measures limiting soil degradation in the Hubenov reservoir catchment area.

Keywords: complex land consolidation, degradation, land use, soil and water conservation, surface water resources

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Authors: Navneet Kaur, S. D. Tiwari

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Ferritin is a protein which present in the blood of mammals. It maintains the need of iron inside the body. It has an antiferromagnetic iron core, 7-8 nm in size, which is encapsulated inside a protein cage. The thickness of this protein shell is about 2-3 nm. This protein shell reduces the interaction among particles and make ferritin a model superparamagnet. The major composition of ferritin core is mineral ferrihydrite. The molecular formula of ferritin core is (FeOOH)8[FeOOPO3H2]. In this study, we discuss the phase transition of ferritin. We characterized ferritin using x-ray diffractometer, transmission electron micrograph, thermogravimetric analyzer and vibrating sample magnetometer. It is found that ferritin core is amorphous in nature with average particle size of 8 nm. The thermogravimetric and differential thermogravimetric analysis curves shows mass loss at different temperatures. We heated ferritin at these temperatures. It is found that ferritin core starts decomposing after 390^o C. At 1020^o C, the ferritin core is finally converted to alpha phase of iron oxide. Magnetization behavior of final sample clearly shows the iron oxyhydroxide core is completely converted to alpha iron oxide.

Keywords: Antiferromagnetic, Ferritin, Phase, Superparamagnetic

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Authors: Fang Bin Guo, Emma Roberts, Haibin Du, Yonggang Wang, Yu Chen, Xiuli Ge

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This paper explores the findings so far from a major externally-funded project which operates internationally in China, Germany and the UK. The research team is working in the context of the redevelopment of post-industrial sites in China and how these might be platforms for creative enterprises and thereby, the economy and welfare to flourish. Results from the project are anticipated to inform urban design policies in China and possibly farther afield. The research has utilised ethnographic studies and participatory design methods to investigate alternative strategies for sustainable urban renewal of China’s post-industrial areas. Additionally, it has undertaken comparative studies of successful examples of European and Chinese urban regeneration cases. The international cross-disciplinary team has been seeking different opportunities for developing relevant creative industries whilst retaining cultural and industrial heritage. This paper will explore the research conducted so far by the team and offer initial findings. Findings point out the development challenges of cities respecting the protection of local culture/heritages, history of the industries and transformation of the local economies. The preliminary results and pilot analysis of the current research have demonstrated that local government policyholders, business investors/developers and creative industry practitioners are the three major stakeholders that will impact city revitalisations. These groups are expected to work together with asynchronous vision in order for redevelopments to be successful. Meanwhile, local geography, history, culture, politics, economy and ethnography have been identified as important factors that impact on project design and development during urban transformations. Data is being processed from the team’s research conducted across the focal Western and Chinese cities. This has provided theoretical guidance and practical support to the development of significant experimental projects. Many were re-examined with a more international perspective, and adjustments have been based on the conclusions of the research. The observations and research are already generating design solutions in terms of ascertaining essential site components, layouts, visual design and practical facilities for regenerated sites. Two significant projects undertaken by this project team have been nominated by the central Chinese government as the most successful exemplars. They have been listed as outstanding national industry heritage projects; in particular, one of them was nominated by ArchDaily as Building of the Year 2019, and so this project outcome has made a substantial contribution to research and innovation. In summary, this paper will outline the funded project, discuss the work conducted so far, and pinpoint the initial discoveries. It will detail the future steps and indicate how these will impact on national and local governments in China, designers, local citizens and building users.

Keywords: cultural & industrial heritages, ethnographic research, participatory design, regeneration of post-industrial sites, sustainable

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Mohsen Mazidi, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, Mohamamd Rastegar

Abstract:

To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.

Keywords: loss, plug-in hybrid electric vehicle (PHEV), PHEV parking lot, V2G

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Authors: Vinay Kumar K. S., Shravani V., Spoorthi G., Udith K. S., Divya T. M., Venkatesha M.

Abstract:

In this work, the mathematical modeling, design and analysis of a 2×2 microstrip patch antenna array (MSPA) antenna configuration is presented. Array utilizes a tiny strip antenna module with two vertical slots for 5G applications at an operating frequency of 5.3 GHz. The proposed array of antennas where the phased array antenna systems (PAAS) are used ubiquitously everywhere, from defense radar applications to commercial applications like 5G/6G. Microstrip patch antennae with slot arrays for linear polarisation parallel and perpendicular to the axis, respectively, are fed through transverse slots in the side wall of the circular waveguide and fed through longitudinal slots in the small wall of the rectangular waveguide. The microstrip patch antenna is developed using Ansys HFSS (High-Frequency Structure Simulator), this simulation tool. The maximum gain of 6.14 dB is achieved at 5.3 GHz for a single MSPA. For 2×2 array structure, a gain of 7.713 dB at 5.3 GHz is observed. Such antennas find many applications in 5G devices and technology.

Keywords: Ansys HFSS, gain, return loss, slot array, microstrip patch antenna, 5G antenna

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Authors: B. Philip, J. Littlewood, R. Radford, N. Evans, T. Whyman, D. P. Jones

Abstract:

UK buildings and energy infrastructures are heavily dependent on natural gas, a large proportion of which is used for domestic space heating. However, approximately half of the gas consumed in the UK is imported. Improving energy security and reducing carbon emissions are major government drivers for reducing gas dependency. In order to do so there needs to be a wholesale shift in the energy provision to householders without impacting on thermal comfort levels, convenience or cost of supply to the end user. Heat pumps are seen as a potential alternative in modern well insulated homes, however, can the same be said of older homes? A large proportion of housing stock in Britain was built prior to 1919. The age of the buildings bears testimony to the quality of construction; however, their thermal performance falls far below the minimum currently set by UK building standards. In recent years significant sums of money have been invested to improve energy efficiency and combat fuel poverty in some of the most deprived areas of Wales. Increasing energy efficiency of older properties remains a significant challenge, which cannot be achieved through insulation and air-tightness interventions alone, particularly when alterations to historically important architectural features of the building are not permitted. This paper investigates the energy demand of pre-1919 dwellings in a former Welsh mining village, the feasibility of meeting that demand using water from the disused mine workings to supply a district heat network and potential barriers to success of the scheme. The use of renewable solar energy generation and storage technologies, both thermal and electrical, to reduce the load and offset increased electricity demand, are considered. A wholistic surveying approach to provide a more accurate assessment of total household heat demand is proposed. Several surveying techniques, including condition surveys, air permeability, heat loss calculations, and thermography were employed to provide a clear picture of energy demand. Additional insulation can bring unforeseen consequences which are detrimental to the fabric of the building, potentially leading to accelerated dilapidation of the asset being ‘protected’. Increasing ventilation should be considered in parallel, to compensate for the associated reduction in uncontrolled infiltration. The effectiveness of thermal performance improvements are demonstrated and the detrimental effects of incorrect material choice and poor installation are highlighted. The findings show estimated heat demand to be in close correlation to household energy bills. Major areas of heat loss were identified such that improvements to building thermal performance could be targeted. The findings demonstrate that the use of heat pumps in older buildings is viable, provided sufficient improvement to thermal performance is possible. Addition of passive solar thermal and photovoltaic generation can help reduce the load and running cost for the householder. The results were used to predict future heat demand following energy efficiency improvements, thereby informing the size of heat pumps required.

Keywords: heat demand, heat pump, renewable energy, retrofit

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Authors: Ather Saeed, Arif Khan, Jeffrey Gosper

Abstract:

Sensor devices are prone to errors and sudden node failures, which are difficult to detect in a timely manner when deployed in real-time, hazardous, large-scale harsh environments and in medical emergencies. Therefore, the loss of data can be life-threatening when the sensed phenomenon is not disseminated due to sudden node failure, battery depletion or temporary malfunctioning. We introduce a set of partial differential equations for localizing faults, similar to Green’s and Maxwell’s equations used in Electrostatics and Electromagnetism. We introduce a node organization and clustering scheme for self-stabilizing sensor networks. Green’s theorem is applied to regions where the curve is closed and continuously differentiable to ensure network connectivity. Experimental results show that the proposed GTFD (Green’s Theorem fault-detection and Self-stabilization) protocol not only detects faulty nodes but also accurately generates network stability graphs where urgent intervention is required for dynamically self-stabilizing the network.

Keywords: Green’s Theorem, self-stabilization, fault-localization, RSSI, WSN, clustering

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Authors: Balamurugan Baladhandapani, Ganesh Renganathan, V. R. Sanal Kumar

Abstract:

In this paper a comprehensive review on various factory layouts has been carried out for designing a lucrative process layout for medium scale industries. Industry data base reveals that the end product rejection rate is on the order of 10% amounting large profit loss. In order to avoid these rejection rates and to increase the quality product production an intermediate non-destructive testing facility (INDTF) has been recommended for increasing the overall profit. We observed through detailed case studies that while introducing INDTF to medium scale industries the expensive production process can be avoided to the defective products well before its final shape. Additionally, the defective products identified during the intermediate stage can be effectively utilized for other applications or recycling; thereby the overall wastage of the raw materials can be reduced and profit can be increased. We concluded that the prudent design of a factory layout through critical path method facilitating with INDTF will warrant profitable outcome.

Keywords: intermediate non-destructive testing, medium scale industries, process layout design

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Authors: Rajinder Kumar Gupta, Rajni Kant Agrawal, Jaganniwas

Abstract:

One of the most frightening phenomena of nature is the occurrence of earthquake as it has terrible and disastrous effects. Many earthquakes occur every day worldwide. There is need to have knowledge regarding the trends in earthquake occurrence worldwide. The recoding and interpretation of data obtained from the establishment of the worldwide system of seismological stations made this possible. From the analysis of recorded earthquake data, the earthquake parameters and source parameters can be computed and the earthquake catalogues can be prepared. These catalogues provide information on origin, time, epicenter locations (in term of latitude and longitudes) focal depths, magnitude and other related details of the recorded earthquakes. Theses catalogues are used for seismic hazard estimation. Manual interpretation and analysis of these data is tedious and time consuming. A geographical information system is a computer based system designed to store, analyzes and display geographic information. The implementation of integrated GIS technology provides an approach which permits rapid evaluation of complex inventor database under a variety of earthquake scenario and allows the user to interactively view results almost immediately. GIS technology provides a powerful tool for displaying outputs and permit to users to see graphical distribution of impacts of different earthquake scenarios and assumptions. An endeavor has been made in present study to compile the earthquake data for the whole world in visual Basic on ARC GIS Plate form so that it can be used easily for further analysis to be carried out by earthquake engineers. The basic data on time of occurrence, location and size of earthquake has been compiled for further querying based on various parameters. A preliminary analysis tool is also provided in the user interface to interpret the earthquake recurrence in region. The user interface also includes the seismic hazard information already worked out under GHSAP program. The seismic hazard in terms of probability of exceedance in definite return periods is provided for the world. The seismic zones of the Indian region are included in the user interface from IS 1893-2002 code on earthquake resistant design of buildings. The City wise satellite images has been inserted in Map and based on actual data the following information could be extracted in real time: • Analysis of soil parameters and its effect • Microzonation information • Seismic hazard and strong ground motion • Soil liquefaction and its effect in surrounding area • Impacts of liquefaction on buildings and infrastructure • Occurrence of earthquake in future and effect on existing soil • Propagation of earth vibration due of occurrence of Earthquake GIS based earthquake information system has been prepared for whole world in Visual Basic on ARC GIS Plate form and further extended micro level based on actual soil parameters. Individual tools has been developed for liquefaction, earthquake frequency etc. All information could be used for development of infrastructure i.e. multi story structure, Irrigation Dam & Its components, Hydro-power etc in real time for present and future.

Keywords: GIS based earthquake information system, microzonation, analysis and real time information about liquefaction, infrastructure development

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 90