Search results for: soft biometric technology

Authors: Nathenal Thomas Lambamo

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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

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Authors: Layla Mujahed

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COVID-19 is an exam for all the city’s systems. It shows many gaps in the systems such as healthcare, economic, social, and environment. This pandemic is paving for a new era, an era of technology and it has changed people’s lives, such as physical, and emotional changes, and converting communication into digitalized. The effect of COVID-19 has covered all urban city parts. COVID-19 will not be the last pandemic our cities will face. For that, more researches focus on enhancing the quality of the urban environment. This pandemic encourages a rethinking of the environment’s role, especially in cities. Cities are trying to provide the best suitable strategies and regulations to prevent the spread of COVID-19, and an example of that is Amman city. Amman has a high increment in the number of COVID-19 infected people, while it has controlled the situation for months. For that, this paper studies the relation between COVID-19 and urban environmental studies cases about cities around the world, and learns from their models to face COVID-19. In Amman, people’s behavior has changed towards public transportation and public green spaces. N­ew governmental regulations focus on increasing people’s mental awareness, supporting local businesses, and enhancing neighborhood planning that can help Amman to face any future pandemics.

Keywords: COVID-19, urban environment, urban planning, urban resilience

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Authors: Allison Futter

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Lifetime use of electronic cigarettes (EC) in college students has been estimated at around 50%; recent research shows Mobile Health (mHealth) technology is a promising tool to help address this public health issue, yet the majority of EC cessation mHealth tools found on smartphone app stores lack empirical support of their effectiveness. The Smiling Instead of Smoking (SiS) app is a positive psychology-based smartphone app for nondaily smokers. Due to previous success with brief, self-administered positive psychology exercises for cigarette cessation, this study examined the SiS App’s feasibility and effectiveness for EC cessation. Sixteen undergraduates used the SiS app for 3 weeks: one week before their quit date and 2 weeks after. As hypothesized, participants had significant declines in their craving and maintained pre-cessation levels of positive affect. There were no significant changes in dependency or self-efficacy. In the one-month follow-up survey, 38% of participants reported being abstinent. The app had an almost 4-star rating for its features (e.g., functionality, aesthetics, information, etc.) and participants reported moderate satisfaction with its use. Participants used the app, on average, 10 out of the 21 days of the prescribed app use. This study highlights the promise of mHealth support and positive psychology for EC cessation, adding to the understanding of possible ways to support EC quit attempts.

Keywords: e-cigarette cessation, mHealth, positive psychology, smartphone app

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Authors: Vanessa Cho, Janet Hsiao, Nigel King, Robert Anthonappa

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Background: The personal protective equipment (PPE) requirements for health care workers (HCWs) have changed significantly during the COVID-19 pandemic. Aim: To ascertain, using eye-tracking technology, what children notice the most when seeing HCWs in various PPE. Design: A Tobii nano pro-eye-tracking camera tracked 156 children's visual attention while they viewed photographs of HCWs in various PPEs. Eye Movement analysis with Hidden Markov Models (EMHMM) was employed to analyse 624 recordings using two approaches, namely (i) data-driven where children's fixation determined the regions of interest (ROIs), and (ii) fixed ROIs where the investigators predefined the ROIs. Results: Two significant eye movement patterns, namely distributed(85.2%) and selective(14.7%), were identified(P<0.05). Most children fixated primarily on the face regardless of the different PPEs. Children fixated equally on all PPE images in the distributed pattern, while a strong preference for unmasked faces was evident in the selective pattern (P<0.01). Conclusion: Children as young as 2.5 years used a top-down visual search behaviour and demonstrated their face processing ability. Most children did not show a strong visual preference for a specific PPE, while a minority preferred PPE with distinct facial features, namely without masks and loupes.

Keywords: COVID-19, PPE, dentistry, pediatric

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Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

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Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

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Authors: Siti Indati Mustapa, Hussain Ali Bekhet

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Global CO2 emission and increasing fuel consumption to meet energy demand requirement has become a threat in recent decades. Effort to reduce the CO2 emission is now a matter of priority in most countries of the world including Malaysia. Transportation has been identified as the most intensive sector of carbon-based fuels and achievement of the voluntary target to meet 40% carbon intensity reduction set at the 15th Conference of the Parties (COP15) means that the emission from the transport sector must be reduced accordingly. This posed a great challenge to Malaysia and effort has to be made to embrace suitable and appropriate energy policy for sustainable energy and emission reduction of this sector. The focus of this paper is to analyse the trends of Malaysia’s energy consumption and emission of four different transport sub-sectors (road, rail, aviation and maritime). Underlying factors influencing the growth of energy consumption and emission trends are discussed. Besides, technology status towards energy efficiency in transportation sub-sectors is presented. By reviewing the existing policies and trends of energy used, the paper highlights prospective policy options towards achieving emission reduction in the transportation sector.

Keywords: CO2 emissions, transportation sector, fuel consumption, energy policy, Malaysia

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Authors: Robert Jacobsen

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Flood inundation maps (FIMs) are an essential tool in communicating flood threat scenarios to the public as well as in floodplain governance. With an increasing demand for online raster FIMs, the FIM State-of-the-Practice (SOP) is rapidly advancing to meet the dual requirements for high-resolution and high-accuracy—or High-Definition. Importantly, today’s technology also enables the resolution of problems of local—neighborhood-scale—bias errors that often occur in FIMs, even with the use of SOP two-dimensional flood modeling. To facilitate the development of HD-FIMs, a new GIS method--Raster Adjustment with Scenario Profiles, RASPTM—is described for adjusting kernel raster FIMs to match refined scenario profiles. With RASPTM, flood professionals can prepare HD-FIMs for a wide range of scenarios with available kernel rasters, including kernel rasters prepared from vector FIMs. The paper provides detailed procedures for RASPTM, along with an example of applying RASPTM to prepare an HD-FIM for the August 2016 Flood in Louisiana using both an SOP kernel raster and a kernel raster derived from an older vector-based flood insurance rate map. The accuracy of the HD-FIMs achieved with the application of RASPTM to the two kernel rasters is evaluated.

Keywords: hydrology, mapping, high-definition, inundation

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Authors: Muhammad Rizwan Tabassum, Ao Xia, Jerry D. Murphy

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The purpose of this work is to provide a comprehensive overview of seaweed as the alternative feedstock for biofuel production and key conversion technologies. Resource depletion and climate change are the driving forces to hunt for renewable sources of energy. Macroalgae can be preferred over land based crops for biofuel production because they are not in competition with food crops for arable land, high growth rates and low lignin contents which require less energy-intensive pre-treatments. However, some disadvantages, such as high moisture content, seasonal variation in chemical composition and process inhibition limit its economic feasibility. Seaweed can be converted into gaseous and liquid fuel by different conversion technologies, but biogas via anaerobic digestion from seaweed is attracting increased attention due to its dual benefit of an economic source of bio-fuel and environment-friendly technology. Biodiesel and bioethanol conversion technologies from seaweed are still under development. A selection of high yielding seaweed species, optimal harvesting season and process optimization make them economically feasible for the alternative source of renewable and sustainable feedstock for biofuel in future.

Keywords: anaerobic digestion, biofuel, bio-methane, conversion technologies, seaweed

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Authors: A. N. Dagang, E. I. Ismail, Z. Zakaria

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This paper presents the analysis on the performance of monopole antenna with fluorescent tubes. In this research, the simulation and experimental approach is conducted. The fluorescent tube with different length and size is designed using Computer Simulation Technology (CST) software and the characteristics of antenna parameter are simulated throughout the software. CST was used to simulate antenna parameters such as return loss, resonant frequency, gain and directivity. Vector Network Analyzer (VNA) was used to measure the return loss of plasma antenna in order to validate the simulation results. In the simulation and experiment, the supply frequency is set starting from 1 GHz to 10 GHz. The results show that the return loss of plasma antenna changes when size of fluorescent tubes is varied, correspond to the different plasma properties. It shows that different values of plasma properties such as plasma frequency and collision frequency gives difference result of return loss, gain and directivity. For the gain, the values range from 2.14 dB to 2.36 dB. The return loss of plasma antenna offers higher value range from -22.187 dB to -32.903 dB. The higher the values of plasma frequency and collision frequency, the higher return loss can be obtained. The values obtained are comparative to the conventional type of metal antenna.

Keywords: plasma antenna, fluorescent tube, CST, plasma parameters

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Authors: Anant Mehrotra, Krish Phagwani

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Democratic voting is vital for any country, but current methods like ballot papers or EVMs have drawbacks, including transparency issues, low voter turnout, and security concerns. Blockchain technology offers a potential solution by providing a secure, decentralized, and transparent platform for e-voting. With features like immutability, security, and anonymity, blockchain combined with smart contracts can enhance trust and prevent vote tampering. This paper explores an Ethereum-based e-voting application using Solidity, showcasing a web app that prevents duplicate voting through a token-based system, while also discussing the advantages and limitations of blockchain in digital voting. Voting is a crucial component of democratic decision-making, yet current methods, like paper ballots, remain outdated and inefficient. This paper reviews blockchain-based voting systems, highlighting strategies and guidelines to create a comprehensive electronic voting system that leverages cryptographic techniques, such as zero-knowledge proofs, to enhance privacy. It addresses limitations of existing e-voting solutions, including cost, identity management, and scalability, and provides key insights for organizations looking to design their own blockchain-based voting systems.

Keywords: electronic voting, smart contracts, blockchain nased voting, security

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Authors: Thanunthon Bowornsakulwong, Charukorn Charukarn, Franck Courtes, Panit Kitsubun, Lalintip Horcharoen

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Vero cell is a continuous cell line that is widely used for the production of viral vaccines. However, due to its adherent characteristic, scaling up strategy in large-scale production remains complicated and thus limited. Consequently, suspension-like Vero cell culture processes based on microcarriers have been introduced and employed while also providing increased surface area per volume unit. However, harvesting Vero cells from microcarriers is a huge challenge due to difficulties in cells detaching, lower recovery yield, time-consuming and dissociation agent carry-over. To overcome these problems, we developed a dissociation-association platform technology for detaching and re-attaching cells during subculturing from microcarriers to microcarriers, which will be conveniently applied to seed trains strategies in large scale bioreactors. Herein, Hillex-2 was used to culture Vero cells in serum-containing media using spinner flasks as a scale-down model. The overall confluency of cells on microcarriers was observed using inverted microscope, and the sample cells were daily detached in order to obtain the kinetics data. The metabolites consumption and by-products formation were determined by Nova Biomedical BioprofileFlex.

Keywords: dissociation-reassociation, microcarrier, scale up, Vero cell

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Authors: Rodrigo Buaiz Boabaid

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Tokenization of Blue Bonds is an emerging Green Finance tool that has the potential to scale Blue Carbon Projects to fight climate change. This innovative solution has a huge potential to democratize the green finance market and catalyze innovations in the climate change finance sector. Switzerland has emerged as a leader in the Green Finance space and is well-positioned to drive the adoption of Tokenization of Blue & Green Bonds. This unique approach has the potential to unlock new sources of capital and enable global investors to participate in the financing of sustainable blue carbon projects. By leveraging the power of blockchain technology, Tokenization of Blue Bonds can provide greater transparency, efficiency, and security in the investment process while also reducing transaction costs. Investments are in line with the highest regulations and designed according to the stringent legal framework and compliance standards set by Switzerland. The potential benefits of Tokenization of Blue Bonds are significant and could transform the way that sustainable projects are financed. By unlocking new sources of capital, this approach has the potential to accelerate the deployment of Blue Carbon projects and create new opportunities for investors to participate in the fight against climate change.

Keywords: blue bonds, blue carbon, tokenization, green finance

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Authors: Salihu Takuma

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Neem seed oil has high contents of unsaturated fatty acids which can be converted to epoxy fatty acids. The vegetable oil – based epoxy material are sustainable, renewable and biodegradable materials replacing petrochemical – based epoxy materials in some applications. Polystyrene is highly brittle with limited mechanical applications. Raw neem seed oil was obtained from National Research Institute for Chemical Technology (NARICT), Zaria, Nigeria. The oil was epoxidized at 60 0C for three (3) hours using formic acid generated in situ. The epoxidized oil was characterized using Fourier Transform Infrared spectroscopy (FTIR). The disappearance of C = C stretching peak around 3011.7 cm-1and formation of a new absorption peak around 943 cm-1 indicate the success of epoxidation. The epoxidized oil was blended with pure polystyrene in different weight percent compositions using solution casting in chloroform. The tensile properties of the blends demonstrated that the addition of 5 wt % ENO to PS led to an increase in elongation at break, but a decrease in tensile strength and modulus. This is in accordance with the common rule that plasticizers can decrease the tensile strength of the polymer.

Keywords: biodegradable, elongation at break, epoxidation, epoxy fatty acids, sustainable, tensile strength and modulus

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Authors: Azlina Binti Abu Bakar, Fahmi Zaidi Bin Abdul Razak, Wan Salihin Wong Abdullah

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Psychographic is a psychological study of values, attitudes, interests and it is used mostly in prediction, opinion research and social research. This study predicts the influence of performance expectancy, effort expectancy, social influence and facilitating condition on e-government acceptance among Malaysian citizens. The survey responses of 543 e-government users have been validated and analyzed by means of covariance-based Structural Equation Modeling. The findings indicate that e-government acceptance among Malaysian citizens are mainly influenced by performance expectancy (β = 0.66, t = 11.53, p < 0.01) and social influence (β = 0.20, t = 4.23, p < 0.01). Surprisingly, there is no significant effect of facilitating condition and effort expectancy on e-government continuance intention (β = 0.01, t = 0.27, p > 0.05; β = -0.01, t = -0.40, p > 0.05). This study offers government and vendors a frame of reference to analyze citizen’s situation before initiating new innovations. In case of Malaysian e-government technology, adoption strategies should be built around fostering level of citizens’ technological expectation and social influence on e-government usage.

Keywords: continuance intention, Malaysian citizen, media psychology, structural equation modeling

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Authors: A. Moualdia, D. J. Boudana, O. Bouchhida, A. Medjber

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Wind energy has many advantages, it does not pollute and it is an inexhaustible source. However, the cost of this energy is still too high to compete with traditional fossil fuels, especially on sites less windy. The performance of a wind turbine depends on three parameters: the power of wind, the power curve of the turbine and the generator's ability to respond to wind fluctuations. This paper presents a control chain conversion based on a double-fed asynchronous machine and flow-oriented. The supply system comprises of two identical converters, one connected to the rotor and the other one connected to the network via a filter. The architecture of the device is up by three commands are necessary for the operation of the turbine control extraction of maximum power of the wind to control itself (MPPT) control of the rotor side converter controlling the electromagnetic torque and stator reactive power and control of the grid side converter by controlling the DC bus voltage and active power and reactive power exchanged with the network. The proposed control has been validated in both modes of operation of the three-bladed wind 7.5 kW, using Matlab/Simulink. The results of simulation control technology study provide good dynamic performance and static.

Keywords: D.F.I.G, variable wind speed, hypersynchrone, energy quality, hyposynchrone

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Authors: Mahshid TalebianKiakalayeh

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As AI technologies can be used by both civilians and soldiers, it is vital to consider the consequences emanating from AI military as well as civilian use. Indeed, many of the same technologies can have a dual-use. This paper will explore the military uses of AI and assess its compliance with international legal norms. AI developments not only have changed the capacity of the military to conduct complex operations but have also increased legal concerns. The existence of a potential legal vacuum in legal principles on the military use of AI indicates the necessity of more study on compliance with International Humanitarian Law (IHL), the branch of international law which governs the conduct of hostilities. While capabilities of new means of military AI continue to advance at incredible rates, this body of law is seeking to limit the methods of warfare protecting civilian persons who are not participating in an armed conflict. Implementing AI in the military realm would result in potential issues, including ethical and legal challenges. For instance, when intelligence can perform any warfare task without any human involvement, a range of humanitarian debates will be raised as to whether this technology might distinguish between military and civilian targets or not. This is mainly because AI in fully military systems would not seem to carry legal and ethical judgment, which can interfere with IHL principles. The paper will take, as a case study, Canada’s compliance with IHL in the area of AI and the related legal issues that are likely to arise as this country continues to develop military uses of AI.

Keywords: artificial intelligence, military use, international humanitarian law, the Canadian perspective

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Authors: S. Kampeephat, P. Krachodnok, R. Wongsan

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The conventional rectangular horn has been used for microwave antenna a long time. Its gain can be increased by enlarging the construction of horn to flare exponentially. This paper presents a study of the shaped woodpile Electromagnetic Band Gap (EBG) to improve its gain for conventional horn without construction enlargement. The gain enhancement synthesis method for shaped woodpile EBG that has to transfer the electromagnetic fields from aperture of a horn antenna through woodpile EBG is presented by using the variety of shaped woodpile EBGs such as planar, triangular, quadratic, circular, gaussian, cosine, and squared cosine structures. The proposed technique has the advantages of low profile, low cost for fabrication and light weight. The antenna characteristics such as reflection coefficient (S11), radiation patterns and gain are simulated by utilized A Computer Simulation Technology (CST) software. With the proposed concept, an antenna prototype was fabricated and experimented. The S11 and radiation patterns obtained from measurements show a good impedance matching and a gain enhancement of the proposed antenna. The gain at dominant frequency of 10 GHz is 25.6 dB, application for X- and Ku-Band Radar, that higher than the gain of the basic rectangular horn antenna around 8 dB with adding only one appropriated EBG structures.

Keywords: conventional rectangular horn antenna, electromagnetic band gap, gain enhancement, X- and Ku-band radar

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Authors: María R. Contreras, Diana Endara

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Cyanide leaching is the most used technology for gold mining industry, which produces large amounts of effluents requiring treatment. In Ecuador the development of gold mining industry has increased, causing significant environmental impacts due to the highly use of cyanide, it is estimated that 10 gr of extracted gold generates 7000 liters of water contaminated with 300mg/L of free cyanide. The most common methods used nowadays are the treatment with peroxodisulfuric acid, ozonation, H₂O₂ and other reactants which are expensive and present disadvantages. Several methods have been developed to treat this contaminant such as heterogeneous catalysts. Layered double hydroxides (LDHs) have received much attention due to their wide applications like a catalysis support. Therefore, in this study, Mg-Al/ LDH was synthetized by coprecipitation method and then platinum was impregned on it, in order to enhance its catalytic activity. Two methods of impregnation were used, the first one, called incipient wet impregnation and the second one was developed by continuous agitation of LDH in contact with chloroplatinic acid solution for 24 h. The support impregnated was analyzed by X-ray diffraction, FTIR and SEM. Finally, the oxidation of cyanide ion was performed by preparing synthetic solutions of sodium cyanide (NaCN) with an initial concentration of 500 mg/L at pH 10,5 and air flow of 180 NL/h. After 8 hours of treatment, an 80% of oxidation of ion cyanide was achieved.

Keywords: catalysis, cyanide, LDHs, mining

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Authors: Meng-Hao Chen, Jeng-Der Huang, Chia-Ray Chen

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With the new space mission need of high power dissipation, low thermal inertia and cyclical operation unit, such as high power amplifier (HPA) for synthetic aperture radar (SAR) satellite, the development of phase change material (PCM) technology seems to be a proper solution. Generally, the expected benefit of PCM solution is to eliminate temperature variation and maintain the stability of electronic units by using the latent heat during phase change process. It can also result in advantages of decreased radiator area and heater power. However, the PCMs have a drawback of low thermal conductivity that leads to large temperature gradient between the heat source and PCM. This paper thus presents both experimental and simplified numerical investigations on configuration design of PCM’s container. A comparison was carried out between the container with and without internal pin-fins structure. The results showed the benefit of pin-fins that act as the heat transfer enhancer to improve the temperature uniformity during phase transition. Furthermore, thermal testing and measurements were presented for four PCM candidates (i.e. n-octadecane, n-eicosane, glycerin and gallium). The solidification and supercooling behaviors on different PCMs were compared with available literature data and discussed in this study

Keywords: phase change material (PCM), thermal control, solidification, supercooling

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Authors: Lloyd A. Taylor

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An increase in the prevalence of Attention Deficit-Hyperactivity Disorder (ADHD) highlights the need to consider factors that may be exacerbating symptom presentation. Traditional diagnostic criteria provide a little framework for healthcare providers to consider as they attempt to diagnose and treat children with behavioral problems. In fact, aside from exclusion criteria, limited alternative considerations are available, and approaches fail to consider the impact of outside factors that could increase or decrease the likelihood of appropriate diagnosis and success of interventions. This paper will consider specific systems-based factors that influence behavior and intervention successes that, when not considered, could account for the upsurge of diagnoses. These include understanding (1) challenges in the healthcare system, (2) the influence and impact of educators and the educational system, (3) technology use, and (4) patient and parental attitudes about the diagnosis of ADHD. These factors must be considered both individually and as a whole when considering both the increase in diagnoses and the subsequent increases in prescriptions for psychostimulant medication. A theoretical model based on a risk management approach will be presented. Finally, data will be presented that demonstrates pediatric provider satisfaction with this approach to diagnoses and treatment of ADHD as it relates to practice trends.

Keywords: ADHD, diagnostic criteria, risk management model, pediatricians

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Authors: Ting Gao, Mingyue He

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Reconfigurable intelligent surfaces (RISs) are expected to be an important part of next-generation wireless communication networks due to their potential to reduce the hardware cost and energy consumption of millimeter Wave (mmWave) massive multiple-input multiple-output (MIMO) technology. However, owing to the lack of signal processing abilities of the RIS, the perfect channel state information (CSI) in RIS-assisted communication systems is difficult to acquire. In this paper, the uplink channel estimation for mmWave systems with a hybrid active/passive RIS architecture is studied. Specifically, a deep learning-based estimation scheme is proposed to estimate the channel between the RIS and the user. In particular, the sparse structure of the mmWave channel is exploited to formulate the channel estimation as a sparse reconstruction problem. To this end, the proposed approach is derived to obtain the distribution of non-zero entries in a sparse channel. After that, the channel is reconstructed by utilizing the least-squares (LS) algorithm and compressed sensing (CS) theory. The simulation results demonstrate that the proposed channel estimation scheme is superior to existing solutions even in low signal-to-noise ratio (SNR) environments.

Keywords: channel estimation, reconfigurable intelligent surface, wireless communication, deep learning

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Authors: Voss Harrigan, Korey Carter, Mohammad Reza Shaeri

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Detrimental effects of lunar dust on space hardware, spacesuits, and astronauts’ health have been already identified during Apollo missions. Developing effective dust mitigation technologies is critically important for successful space exploration and related missions in NASA applications. In this study, an electrostatic cleaning system (ECS) integrated with a negatively ionized Thunderon brush was developed to mitigate small-sized lunar dust particles with diameters ranging from 0.04 µm to 35 µm, and the mean and median size of 7 µm and 5 µm, respectively. It was found that the frequency pulses of the negative ion generator caused particles to stick to the Thunderon bristles and repel between the pulses. The brush was used manually to ensure that particles were removed from areas where the ECS failed to mitigate the lunar simulant. The acquired data demonstrated that the developed system removed over 91-96% of the lunar dust particles. The present study was performed as a proof-of-concept to enhance the cleaning performance of ECSs by integrating a brushing process. Suggestions were made to further improve the performance of the developed technology through future research.

Keywords: lunar dust mitigation, electrostatic cleaning system, Brushing, Thunderon brush, cleaning rate

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Authors: Christopher Muhawe, Masooda Bashir

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With increased Internet Communication Technology(ICT), the virtual world has become the new normal. At the same time, there is an unprecedented collection of massive amounts of data by both private and public entities. Unfortunately, this increase in data collection has been in tandem with an increase in data misuse and data breach. Regrettably, the majority of data breach and data misuse claims have been unsuccessful in the United States courts for the failure of proof of direct injury to physical or economic interests. The requirement to express data privacy harms from an economic or physical stance negates the fact that not all data harms are physical or economic in nature. The challenge is compounded by the fact that data breach harms and risks do not attach immediately. This research will use a descriptive and normative approach to show that not all data harms can be expressed in economic or physical terms. Expressing privacy harms purely from an economic or physical harm perspective negates the fact that data insecurity may result into harms which run counter the functions of privacy in our lives. The promotion of liberty, selfhood, autonomy, promotion of human social relations and the furtherance of the existence of a free society. There is no economic value that can be placed on these functions of privacy. The proposed approach addresses data harms from a psychological and social perspective.

Keywords: data breach and misuse, economic harms, privacy harms, psychological harms

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Authors: Hemadri Raut

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The city is a blend of the possible interactions of the built form, open spaces and their spatial organization layout in a geographical area to obtain an integrated pattern and environment with building facades being a dominant figure in the body of a city. Façades of each city have their own inherent properties responsive to the human behaviour, weather conditions, safety factors, material availability and composition along with the necessary aesthetics in coordination with adjacent building facades. Cities experience a huge transformation in the culture, lifestyle; socioeconomic conditions and technology nowadays because of the increasing population, urban sprawl, industrialization, contemporary architectural style, post-disaster consequences, war reconstructions, etc. This leads to the loss of the actual identity and architectural character of the city which in turn induces chaos and turbulence in the city. This paper attempts to identify and learn from the traditional elements that would make us more aware of the unique identity of the local communities in a city. It further studies the architectural style, color, shape, and design techniques through the case studies of contextual cities. The work focuses on the observation and transformation of the image of the city through these considerations in the designing of the facades to achieve the reconciliation of the people with urban spaces.

Keywords: building facades, city, community, heritage, identity, transformation, urban

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Authors: Virpi Oksman

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Drones are new phenomenon in public spaces. Adoption of this kind of new technologies requires public acceptance. Drones and other unmanned aerial systems may have various impacts on people’s living environments, and the public is exposed to possible disadvantages of drones. Public acceptance may be expressed as positive or negative attitude by majority of the citizens towards the new technology or service or as rapid adoption of it in everyday life. In various parts of the globe, in cities and in rural areas, drones as emerging technologies are perceived quite differently. Public acceptance studies of drones have been conducted mostly in highly urbanized environments like in Singapore and in European cities. This paper presents results of a Nordic survey study (N=1000) conducted in Sweden and in Finland. The survey aims at understanding the level of acceptance of different uses of drones in public spaces and the main concerns and benefits related to emerging UAM technologies. The study shows that even though the general attitude towards drones is quite positive, privacy and safety, and noise levels are the main concerns by Nordic citizens. Also, for what purpose and by whom the drones are operated affects the acceptability significantly. The study concludes, that there is need for regulations that safeguard public interests. In addition, considering privacy in design, and quiet environmentally friendly drones support public acceptance of drones.

Keywords: public acceptance, privacy, safety, survey

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Authors: Muhammad Fiaz, Muhammad Saqlain, Bernard M. Y. Cheung, S. M. Saqlan Naqvi, Ghazala Kaukab Raja

Abstract:

Background: Association of C allele of rs662799 SNP of APOA5 gene with metabolic syndrome (MetS) has been reported in different populations around the world. A case control study was conducted to explore the relationship of rs662799 variants (T/C) with the MetS and the associated risk phenotypes in a population of Pakistani origin. Methods: MetS was defined according to the IDF criteria. Blood samples were collected from the Pakistan Institute of Medical Sciences, Islamabad, Pakistan for biochemical profiling and DNA extraction. Genotyping of rs662799 was performed using mass ARRAY, iPEX Gold technology. A total of 712 unrelated case and control subjects were genotyped. Data were analyzed using Plink software and SPSS 16.0. Results: The risk allele C of rs662799 showed highly significant association with MetS (OR=1.5, Ρ=0.002). Among risk phenotypes, dyslipidemia, and obesity showed strong association with SNP (OR=1.49, p=0.03; OR =1.46, p=0.01) respectively in models adjusted for age and gender. Conclusion: The rs662799C allele is a significant risk marker for MetS in the local Pakistani population studied. The effect of the SNP is more on dyslipidemia than the other components of the MetS.

Keywords: metabolic syndrome, APOA5, rs662799, dyslipidemia, obesity

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Authors: Weiwei Cui, Dejian Lin, Leigang Zhang, Yao Wang, Zheng Sun, Lianfeng Li

Abstract:

Built-in test (BIT) is an important technology in testability field, and it is widely used in state monitoring and fault diagnosis. With the improvement of modern equipment performance and complexity, the scope of BIT becomes larger, and it leads to the emergence of false alarm problem. The false alarm makes the health assessment unstable, and it reduces the effectiveness of BIT. The conventional false alarm suppression methods such as repeated test and majority voting cannot meet the requirement for a complicated system, and the intelligence algorithms such as artificial neural networks (ANN) are widely studied and used. However, false alarm has a very low frequency and small sample, yet a method based on ANN requires a large size of training sample. To recognize the false alarm, we propose a method based on multi-classification support vector machine (SVM) in this paper. Firstly, we divide the state of a system into three states: healthy, false-alarm, and faulty. Then we use multi-classification with '1 vs 1' policy to train and recognize the state of a system. Finally, an example of fault injection system is taken to verify the effectiveness of the proposed method by comparing ANN. The result shows that the method is reasonable and effective.

Keywords: false alarm, fault diagnosis, SVM, k-means, BIT

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Authors: Milica Z. Karadzic, Lidija R. Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Z. Kovacevic, Anamarija I. Mandic, Katarina Penov-Gasi, Andrea R. Nikolic, Aleksandar M. Okljesa

Abstract:

In this study, a set of 29 newly synthesized steroid derivatives were investigated using reversed-phase high-performance liquid chromatography (RP-HPLC) as a first step in preselection of drug candidates. This analysis presents an experimental determination of chromatographic lipophilicity, and it was conducted to obtain physicochemical characterization of these molecules. As the most widely used bonded phases in RP-HPLC, octadecyl (C18) and octyl (C8) were used. Binary mixtures of water and acetonitrile or methanol were used as mobile phases. Obtained results were expressed as retention factor values logk and they were correlated with logP values. The results showed that both columns provide good estimations of the chromatographic lipophilicity of the molecules included in this study. This analysis was conducted in order to characterize newly synthesized steroid derivatives for further investigation regarding their antiproliferative and antimicrobial activity. This article is based upon work from COST Action (CM1306), supported by COST (European Cooperation in Science and Technology).

Keywords: antiproliferative activity, chromatographic lipophilicity, liquid chromatography, steroids

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Authors: Chao Wu

Abstract:

Thioredoxin reductase 2 is a mitochondrial enzyme that belongs to the cellular defense against oxidative stress. We deleted mitochondrial Txnrd2 in a KrasG12D-driven pancreatic tumor model. Despite an initial increase in precursor lesions, tumor incidence decreased significantly. We isolated cancer cell lines from these genetically engineered mice and observed an impaired proliferation and colony formation. Reactive Oxygen Species, as determined by DCF fluorescence, were increased. We detected a higher mitochondrial copy number in Txnrd2-deficient cells (KTP). However, measurement of mitochondrial bioenergetics showed no impairment of mitochondrial function and comparable O₂-consumption and extracellular acidification rates. In addition, the mitochondrial complex composition was affected in Txnrd2 deleted cell lines. To gain better insight into the role of Txnrd2, we deleted Txnrd2 in clones from parental KrasG12D cell lines using Crispr/Cas9 technology. The deletion was confirmed by western blot and activity assay. Interestingly, and in line with previous RNA expression analysis, we saw changes in EMT markers in Txnrd2 deleted cell lines and control cell lines. This might help us explain the reduced tumor incidence in KrasG12D; Txnrd2∆panc mice.

Keywords: PDAC, TXNRD2, epithelial-to-mesenchymal-transition, ROS

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Authors: Muhammad Muhammad Suleiman

Abstract:

Cloud Computing is a versatile concept that refers to a service that allows users to outsource their data without having to worry about local storage issues. However, the most pressing issues to be addressed are maintaining a secure and reliable data repository rather than relying on untrustworthy service providers. In this study, we look at how stenography approaches and collaboration with Digital Watermarking can greatly improve the system's effectiveness and data security when used for Cloud Computing. The main requirement of such frameworks, where data is transferred or exchanged between servers and users, is safe data management in cloud environments. Steganography is the cloud is among the most effective methods for safe communication. Steganography is a method of writing coded messages in such a way that only the sender and recipient can safely interpret and display the information hidden in the communication channel. This study presents a new text steganography method for hiding a loaded hidden English text file in a cover English text file to ensure data protection in cloud computing. Data protection, data hiding capability, and time were all improved using the proposed technique.

Keywords: cloud computing, steganography, information hiding, cloud storage, security

Procedia PDF Downloads 192