Search results for: rise time

Authors: Hiroshi Abe, Minoru Nakayama

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The frontal area in the brain is known to be involved in behavioral judgement. Because a Kanji character can be discriminated visually and linguistically from other characters, in Kanji character discrimination, we hypothesized that frontal event-related potential (ERP) waveforms reflect two discrimination processes in separate time periods: one based on visual analysis and the other based on lexcical access. To examine this hypothesis, we recorded ERPs while performing a Kanji lexical decision task. In this task, either a known Kanji character, an unknown Kanji character or a symbol was presented and the subject had to report if the presented character was a known Kanji character for the subject or not. The same response was required for unknown Kanji trials and symbol trials. As a preprocessing of signals, we examined the performance of a method using independent component analysis for artifact rejection and found it was effective. Therefore we used it. In the ERP results, there were two time periods in which the frontal ERP wavefoms were significantly different betweeen the unknown Kanji trials and the symbol trials: around 170ms and around 300ms after stimulus onset. This result supported our hypothesis. In addition, the result suggests that Kanji character lexical access may be fully completed by around 260ms after stimulus onset.

Keywords: Character discrimination, Event-related Potential, IndependentComponent Analysis, Kanji, Lexical access.

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

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This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: Stochastic models, ARIMA, extreme streamflow, Karkheh River.

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Authors: D. Lepe-Cervantes, E. Leon-Becerril, J. Gomez-Romero, O. Garcia-Depraect, A. Lopez-Lopez

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In this study, raw coffee wastewater (CWW) was used as a complex substrate for anaerobic digestion. The inoculum adaptation stage, microbial diversity analysis and biomethane potential (BMP) tests were performed. A fast inoculum adaptation stage was used by the replacement of vinasse to CWW in an anaerobic sequential batch reactor (AnSBR) operated at mesophilic conditions. Illumina MiSeq sequencing was used to analyze the microbial diversity. While, BMP tests using inoculum adapted to CWW were carried out at different inoculum to substrate (I/S) ratios (2:1, 3:1 and 4:1, on a VS basis). Results show that the adaptability percentage was increased gradually until it reaches the highest theoretical value in a short time of 10 d; with a methane yield of 359.10 NmL CH₄/g COD-removed; Methanobacterium beijingense was the most abundant microbial (75%) and the greatest specific methane production was achieved at I/S ratio 4:1, whereas the lowest was obtained at 2:1, with BMP values of 320 NmL CH₄/g VS and 151 NmL CH₄/g VS, respectively. In conclusion, gradual replacement of substrate was a feasible method to adapt the inoculum in a short time even using complex raw substrates, whereas in the BMP tests, the specific methane production was proportional to the initial amount of inoculum.

Keywords: Fast inoculum adaptation, coffee wastewater, biomethane potential test, anaerobic digestion.

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Authors: Zoran Veršić, Josip Galić, Marin Binički, Lucija Stepinac

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With the current increase in CO2 emissions and global warming, the sustainability of both existing and new solutions must be assessed on a wide scale. As the implementation of closed cavity façades (CCF) is on the rise, various factors must be included in the analysis of new types of CCF. This paper aims to cover the relevant factors included in the sustainability assessment of new types of CCF. Several mathematical models are being used to describe the physical behavior of CCF. Depending on the type of CCF, they cover the main factors which affect the durability of the façade: thermal behavior of various elements in the façade, stress and deflection of the glass panels, pressure and the moisture control in the cavity. CCF itself represents a complex system in which all mentioned factors must be considered mutually. Still, the façade is only an envelope of a more complex system, the building. Choice of the façade dictates the heat loss and the heat gain, thermal comfort of inner space, natural lighting, and ventilation. Annual energy consumption for heating, cooling, lighting, and maintenance costs will present the operational advantages or disadvantages of the chosen façade system in economic and environmental aspects. Still, the only operational viewpoint is not all-inclusive. As the building codes constantly demand higher energy efficiency as well as transfer to renewable energy sources, the ratio of embodied and lifetime operational energy footprint of buildings is changing. With the drop in operational energy CO2 emissions, embodied energy emissions present a larger and larger share in the lifecycle emissions of the building. Taking all into account, the sustainability assessment of a façade, as well as other major building elements, should include all mentioned factors during the lifecycle of an element. The challenge of such an approach is a timescale. Depending on the climatic conditions on the building site, the expected lifetime of a glazed façade can exceed 25 years. In such a timespan, some of the factors can be estimated more precisely than the others. However, the ones depending on the socio-economic conditions are more likely to be harder to predict than the natural ones like the climatic load. This work recognizes and summarizes the relevant factors needed for the assessment of a new type of CCF, considering the entire lifetime of a façade element in an environmental aspect.

Keywords: Assessment, closed cavity façade, life cycle, sustainability.

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Authors: R. Guliyev

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The enhanced need for food items is receiving more importance due to a gradual increase in the world population and, in this scenario, fertilizers play a very important role in agriculture. In this study, the production of the normal superphosphate was investigated with a continuous chamber method by adding potassium chloride to a mixture of Hibin apatite and Kingisepp phosphorite. In the experiments, the following parameters were selected: The concentration of sulfuric acid (54–66% (w/w)), the stoichiometric norm of sulfuric acid (100, 107, 110, 114% (w/w)), the ratio of apatite/phosphorite in the mixture of phosphate (95/5, 90/10, 85/15, 80/20, 75/25, 70/30, 65/35,60/40, 55/45, 50/50 (w/w)), potassium chloride/the mixture of phosphate (1/50, 2/50, 3/50,4/50, 5/50 (w/w)), and the reaction time (2–8 min). It was observed that by adding potassium chloride to a low-grade phosphorite and using it to substitute a fraction of high-grade apatite in the normal superphosphate production not only resulted in a high-quality product but also eliminated the waiting period for the maturation of superphosphate in the storage. The objective of this study was to produce a normal superphosphate fertilizer by using a continuous chamber method in order to accelerate the production process and to reduce the environmental pollution caused by fluoride gases by eliminating the maturation time in the storage.

Keywords: Continuous chamber method, environmental pollution, fluoride gases.

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Authors: Mansour N. Jadid

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This paper describes the implementation of a GIS to provide decision support for successfully monitoring the movements and storage of materials, hence ensuring that finished products travel from the point of origin to the destination construction site through the supply-chain management (SCM) system. This system ensures the efficient operation of suppliers, manufacturers, and distributors by determining the shortest path from the point of origin to the final destination to reduce construction costs, minimize time, and enhance productivity. These systems are essential to the construction industry because they reduce costs and save time, thereby improve productivity and effectiveness. This study describes a typical supply-chain model and a geographical information system (GIS)-based SCM that focuses on implementing an electronic document management system, which maps the application framework to integrate geodetic support with the supply-chain system. This process provides guidance for locating the nearest suppliers to fill the information needs of project members in different locations. Moreover, this study illustrates the use of a GIS-based SCM as a collaborative tool in innovative methods for implementing Web mapping services, as well as aspects of their integration by generating an interactive GIS for the construction industry platform.

Keywords: Construction, coordinate, engineering, GIS, management, map.

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Authors: Samit Ari, Goutam Saha

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Artificial Neural Network (ANN) has been extensively used for classification of heart sounds for its discriminative training ability and easy implementation. However, it suffers from overparameterization if the number of nodes is not chosen properly. In such cases, when the dataset has redundancy within it, ANN is trained along with this redundant information that results in poor validation. Also a larger network means more computational expense resulting more hardware and time related cost. Therefore, an optimum design of neural network is needed towards real-time detection of pathological patterns, if any from heart sound signal. The aims of this work are to (i) select a set of input features that are effective for identification of heart sound signals and (ii) make certain optimum selection of nodes in the hidden layer for a more effective ANN structure. Here, we present an optimization technique that involves Singular Value Decomposition (SVD) and QR factorization with column pivoting (QRcp) methodology to optimize empirically chosen over-parameterized ANN structure. Input nodes present in ANN structure is optimized by SVD followed by QRcp while only SVD is required to prune undesirable hidden nodes. The result is presented for classifying 12 common pathological cases and normal heart sound.

Keywords: ANN, Classification of heart diseases, murmurs, optimization, Phonocardiogram, QRcp, SVD.

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Authors: Yan Yu, Wang Yu, Chen Xintong, Liu Yi, Zhang Yanzhong, Wang Yanji, Chen Xingyu, Zhang Miaocheng, Tong Yi

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Neuromorphic computing based on spiking neural networks (SNNs) has emerged as a promising avenue for building the next generation of intelligent computing systems. Owing to their high-density integration, low power, and outstanding nonlinearity, memristors have attracted emerging attention on achieving SNNs. However, fabricating a low-power and robust memristor-based spiking neuron without extra electrical components is still a challenge for brain-inspired systems. In this work, we demonstrate a TiO2-based threshold switching (TS) memristor to emulate a leaky integrate-and-fire (LIF) neuron without auxiliary circuits, used to realize single layer fully connected (FC) SNNs. Moreover, our TiO2-based resistive switching (RS) memristors realize spiking-time-dependent-plasticity (STDP), originating from the Ag diffusion-based filamentary mechanism. This work demonstrates that TiO2-based memristors may provide an efficient method to construct hardware neuromorphic computing systems.

Keywords: Leaky integrate-and-fire, memristor, spiking neural networks, spiking-time-dependent-plasticity.

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Authors: Ma Shidong, He Yuncheng, Wang Zhong, Yang Guoqing

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In this paper, enhanced ground proximity warning simulation and validation system is designed and implemented. First, based on square grid and sub-grid structure, the global digital terrain database is designed and constructed. Terrain data searching is implemented through querying the latitude and longitude bands and separated zones of global terrain database with the current aircraft position. A combination of dynamic scheduling and hierarchical scheduling is adopted to schedule the terrain data, and the terrain data can be read and delete dynamically in the memory. Secondly, according to the scope, distance, approach speed information etc. to the dangerous terrain in front, and using security profiles calculating method, collision threat detection is executed in real-time, and provides caution and warning alarm. According to this scheme, the implementation of the enhanced ground proximity warning simulation system is realized. Simulations are carried out to verify a good real-time in terrain display and alarm trigger, and the results show simulation system is realized correctly, reasonably and stable.

Keywords: enhanced ground proximity warning system, digital terrain, look-ahead terrain alarm, terrain display, simulation and validation

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Authors: Rana M. Zeina, Laila AL-Ayadhi, Shahid Bashir

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The association between sensory problems and cognitive abilities has been studied in individuals with Autism Spectrum Disorders (ASDs). In this study, we used a Neuropsychological Test to evaluate memory and attention in ASDs children with sensory problems compared to the ASDs children without sensory problems. Four visual memory tests of Cambridge Neuropsychological Test Automated Battery (CANTAB) including Big/little circle (BLC), Simple Reaction Time (SRT) Intra /Extra dimensional set shift (IED), Spatial recognition memory (SRM), were administered to 14 ASDs children with sensory problems compared to 13 ASDs without sensory problems aged 3 to 12 with IQ of above 70. ASDs individuals with sensory problems performed worse than the ASDs group without sensory problems on comprehension, learning, reversal and simple reaction time tasks, and no significant difference between the two groups was recorded in terms of the visual memory and visual comprehension tasks. The findings of this study suggest that ASDs children with sensory problems are facing deficits in learning, comprehension, reversal, and speed of response to a stimulus.

Keywords: Visual memory, Attention, Autism Spectrum Disorders (ASDs).

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Authors: Miloš Marjanović, Jaroslav Burian, Ja kub Miřijovský, Jan Harbula

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This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.

Keywords: Change detection, image classification, land cover, Landsat images, Olomouc city, urbanization.

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Authors: Ritu Vijay, Rekha Govil

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The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.

Keywords: ANN, RBF, Tidal Data.

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Authors: Vikas Tewari, K.R. Pardasani

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Calcium is very important for communication among the neurons. It is vital in a number of cell processes such as secretion, cell movement, cell differentiation. To reduce the system of reactiondiffusion equations of [Ca2+] into a single equation, two theories have been proposed one is excess buffer approximation (EBA) other is rapid buffer approximation (RBA). The RBA is more realistic than the EBA as it considers both the mobile and stationary endogenous buffers. It is valid near the mouth of the channel. In this work we have studied the effects of different types of buffers on calcium diffusion under RBA. The novel thing studied is the effect of sodium ions on calcium diffusion. The model has been made realistic by considering factors such as variable [Ca2+], [Na+] sources, sodium-calcium exchange protein(NCX), Sarcolemmal Calcium ATPase pump. The proposed mathematical leads to a system of partial differential equations which has been solved numerically to study the relationships between different parameters such as buffer concentration, buffer disassociation rate, calcium permeability. We have used Forward Time Centred Space (FTCS) approach to solve the system of partial differential equations.

Keywords: rapid buffer approximation, sodium-calcium exchangeprotein, Sarcolemmal Calcium ATPase pump, buffer disassociationrate, forward time centred space.

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Authors: T. Teo, S. W. Lye, Y. F. Li, Z. Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that using a developed channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available brain computer interface (BCI) 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring, ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: Neurophysiology, monitoring, EEG, outliers, electroencephalography.

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Authors: D.Y. Su, C.C. Liu, C.M. Chiang, W. Wang

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This study aims to discuss the effect of illumination and the color temperature of the lighting source under the office lighting environment on human psychological and physiological responses. In this study, 21 healthy participants were selected, and the Ryodoraku measurement system was utilized to measure their skin resistance change.The findings indicated that the effect of the color temperature of the lighting source on human physiological responses is significant within 90 min after turning the lights on; while after 90 min the effect of illumination on human physiological responses is higher than that of the color temperature. Moreover, the cardiovascular, digestive and endocrine systems are prone to be affected by the indoor lighting environment. During the long-term exposure to high intensity of illumination and high color temperature (2000Lux -6500K), the effect on the psychological responses turned moderate after the human visual system adopted to the lighting environment. However, the effect of the Ryodoraku value on human physiological responses was more significant with the increase of perceptive time. The effect of long time exposure to a lighting environment on the physiological responses is greater than its effect on the psychological responses. This conclusion is different from the traditional public viewpoint that the effect on the psychological responses is greater.

Keywords: Autonomic nervous system, Human responses, Office Lighting Environment, Ryodoraku, Meridian

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Authors: Majid Amidpour, Parisa Karimi, Marzieh Joda

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For the last few years, release of burned undesirable by-products has become a challenging issue in oil industries. Flaring, as one of the main sources of air contamination, involves detrimental and long-lasting effects on human health and is considered a substantial reason for energy losses worldwide. This research involves studying the implications of two main flare gas recovery methods at three oil refineries, all in Iran as the case I, case II, and case III in which the production capacities are increasing respectively. In the proposed methods, flare gases are converted into more valuable products, before combustion by the flare networks. The first approach involves collecting, compressing and converting the flare gas to smokeless fuel which can be used in the fuel gas system of the refineries. The other scenario includes utilizing the flare gas as a feed into liquefied petroleum gas (LPG) production unit already established in the refineries. The processes of these scenarios are simulated, and the capital investment is calculated for each procedure. The cumulative profits of the scenarios are evaluated using Net Present Value method. Furthermore, the sensitivity analysis based on total propane and butane mole fraction is carried out to make a rational comparison for LPG production approach, and the results are illustrated for different mole fractions of propane and butane. As the mole fraction of propane and butane contained in LPG differs in summer and winter seasons, the results corresponding to LPG scenario are demonstrated for each season. The results of the simulations show that cumulative profit in fuel gas production scenario and LPG production rate increase with the capacity of the refineries. Moreover, the investment return time in LPG production method experiences a decline, followed by a rising trend with an increase in C₃ and C₄ content. The minimum value of time return occurs at propane and butane sum concentration values of 0.7, 0.6, and 0.7 in case I, II, and III, respectively. Based on comparison of the time of investment return and cumulative profit, fuel gas production is the superior scenario for three case studies.

Keywords: Flare gas reduction, liquefied petroleum gas, fuel gas, net present value method, sensitivity analysis.

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Authors: Jorge Rodriguez-Guerra, Carlos Calleja, Aron Pujana, Iker Elorza, Ana Maria Macarulla

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Society demands more reliable manufacturing processes capable of producing high quality products in shorter production cycles. New control algorithms have been studied to satisfy this paradigm, in which Fault-Tolerant Control (FTC) plays a significant role. It is suitable to detect, isolate and adapt a system when a harmful or faulty situation appears. In this paper, a general overview about FTC characteristics are exposed; highlighting the properties a system must ensure to be considered faultless. In addition, a research to identify which are the main FTC techniques and a classification based on their characteristics is presented in two main groups: Active Fault-Tolerant Controllers (AFTCs) and Passive Fault-Tolerant Controllers (PFTCs). AFTC encompasses the techniques capable of re-configuring the process control algorithm after the fault has been detected, while PFTC comprehends the algorithms robust enough to bypass the fault without further modifications. The mentioned re-configuration requires two stages, one focused on detection, isolation and identification of the fault source and the other one in charge of re-designing the control algorithm by two approaches: fault accommodation and control re-design. From the algorithms studied, one has been selected and applied to a case study based on an industrial hydraulic-press. The developed model has been embedded under a real-time validation platform, which allows testing the FTC algorithms and analyse how the system will respond when a fault arises in similar conditions as a machine will have on factory. One AFTC approach has been picked up as the methodology the system will follow in the fault recovery process. In a first instance, the fault will be detected, isolated and identified by means of a neural network. In a second instance, the control algorithm will be re-configured to overcome the fault and continue working without human interaction.

Keywords: Fault-tolerant control, electro-hydraulic actuator, fault detection and isolation, control re-design, real-time.

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Authors: Armin Samarghandi, Amirreza Jafari, Mohamad Ghiasi

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Since individuals spend the majority of their time indoors, this immediately affects their productivity and health. An essential factor in occupational health and public health is the influence of indoor environmental quality (IEQ) in buildings on occupant welfare and productivity. Since then, empirical data have been equivocal, indicating either that the studies are inaccurate or that the research has just scratched the surface of green buildings in offices, accommodation, and hospital settings and not taken the aforementioned holistically. This study compared three green-certified buildings — a residential green building, a green hospital, and a green school — with conventional structures in Tehran, Iran by means of a questionnaire spread among those utilizing these buildings, and assessing their productivity and health rate as opposed to the time they resided, worked in conventional buildings. The results demonstrated higher scores pertaining to productivity, physical and mental wellness as a consequence of better indoor environmental quality (IEQ), natural lighting, design, and sustainability of these building against non-green buildings. In addition, ancillary matters — environmental, financial, intellectual, emotional, social, spiritual dimensions of participants — were indirectly evaluated, and the same results are produced.

Keywords: Green building, Iran, productivity, physical and mental health, Tehran.

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Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: Behavior, big data, hierarchical Hidden Markov Model, intelligent object.

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Authors: Jian Shi, Baoguo Yu, Haonan Jia, Meng Liu, Ping Huang

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Adapting to the flexibility of war, a large number of guided weapons launch from aircraft. Therefore, the inertial navigation system loaded in the weapon needs to undergo an alignment process in the air. This article proposes the following methods to the problem of inaccurate modeling of the system under large misalignment angles, the accuracy reduction of filtering caused by outliers, and the noise changes in GPS signals: first, considering the large misalignment errors of Strapdown Inertial Navigation System (SINS)/GPS, a more accurate model is made rather than to make a small-angle approximation, and the Unscented Kalman Filter (UKF) algorithms are used to estimate the state; then, taking into account the impact of GPS noise changes on the fine alignment algorithm, the innovation adaptive filtering algorithm is introduced to estimate the GPS’s noise in real-time; at the same time, in order to improve the anti-interference ability of the air fine alignment algorithm, a robust filtering algorithm based on outlier detection is combined with the air fine alignment algorithm to improve the robustness of the algorithm. The algorithm can improve the alignment accuracy and robustness under interference conditions, which is verified by simulation.

Keywords: Air alignment, fine alignment, inertial navigation system, integrated navigation system, UKF.

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Authors: P. Pinyaphong, S. Phutrakul

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Palm oil could be converted to cocoa butter equivalent by lipase-catalyzed interesterification. The objective of this research was to investigate the structure modification of palm oil to cocoa butter equivalent using Carica papaya lipase –catalyzed interesterification. The study showed that the compositions of cocoa butter equivalent were affected by acyl donor sources, substrate ratio, initial water of enzyme, reaction time, reaction temperature and the amount of enzyme. Among three acyl donors tested (methyl stearate, ethyl stearate and stearic acid), methyl stearate appeared to be the best acyl donor for incorporation to palm oil structure. The best reaction conditions for cocoa butter equivalent production were : substrate ratio (palm oil : methyl stearate, mol/mol) at 1 : 4, water activity of enzyme at 0.11, reaction time at 4 h, reaction temperature at 45 ° C and 18% by weight of the enzyme. The chemical and physical properties of cocoa butter equivalent were 9.75 ± 0.41% free fatty acid, 44.89 ± 0.84 iodine number, 193.19 ± 0.78 sponification value and melting point at 37-39 °C.

Keywords: Carica papaya lipase, cocoa butter equivalent, interesterification, palm oil.

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Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: Travel characteristics analysis, transportation choice, travel sharing rate, neural network model, traffic resource allocation.

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Authors: Md. Ashikur Rahman Khan, M. M. Rahman, K. Kadirgama, M.A. Maleque, Rosli A. Bakar

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Conventionally the selection of parameters depends intensely on the operator-s experience or conservative technological data provided by the EDM equipment manufacturers that assign inconsistent machining performance. The parameter settings given by the manufacturers are only relevant with common steel grades. A single parameter change influences the process in a complex way. Hence, the present research proposes artificial neural network (ANN) models for the prediction of surface roughness on first commenced Ti-15-3 alloy in electrical discharge machining (EDM) process. The proposed models use peak current, pulse on time, pulse off time and servo voltage as input parameters. Multilayer perceptron (MLP) with three hidden layer feedforward networks are applied. An assessment is carried out with the models of distinct hidden layer. Training of the models is performed with data from an extensive series of experiments utilizing copper electrode as positive polarity. The predictions based on the above developed models have been verified with another set of experiments and are found to be in good agreement with the experimental results. Beside this they can be exercised as precious tools for the process planning for EDM.

Keywords: Ti-15l-3, surface roughness, copper, positive polarity, multi-layered perceptron.

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Authors: D. Sivakumar

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Textile industry processes are among the most environmentally unfriendly industrial processes; because, they produce color wastewater that is heavily polluted the environment. Therefore, textile industry wastewater has to be treated before being discharged into the environment. In this study, experiments were conducted for different process parameters like nutrient dosage and dilution ratio against the pH and contact time to remove COD and color in a textile industrial wastewater using aquatic macrophytes Lemna minor L. The experimental results showed that the maximum percentage reduction of COD and color in a textile industry wastewater by Lemna minor L. was obtained at an optimum nutrient dosage of 50g, dilution ratio of 8, pH of 8 and contact time of 4 days. Similarly, the results of validation experiments showed that the experiments were able to reproduce the obtained optimum process parameters. The maximum removal percentage of color in an aqueous solution (86.35%) is higher than the removal of color in a textile industry wastewater (82.85). Further, the first order kinetic model was fitted well with the experimental data of this present study. Finally, this study concluded that Lemna minor L. may be used for removing all types of parameters in any type of textile industry wastewater.

Keywords: Aquatic Macrophyte, Process Parameters, Textile Industry Wastewater.

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Authors: Najmeh Bolbolamiri, Maryam Setayesh Sanai, Ahmad Mirabadi

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This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.

Keywords: stator currents monitoring, railway points, point failures, fault detection and diagnosis, Kolmogorov-Smirnov test, time-domain analysis.

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Authors: Renata Martins Pacheco, João Claro

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Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Keywords: Management Mediterranean-climate regions, policy, wildfire.

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: Crime prediction, machine learning, public safety, smart city.

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Authors: A. A. M. Azoddein, R. M. Yunus, N. M. Sulaiman, A. B. Bustary, K. Sabar

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Microbes have been used to solve environmental problems for many years. The role of microorganism to sequester, precipitate or alter the oxidation state of various heavy metals has been extensively studied. Treatment using microorganism interacts with toxic metal are very diverse. The purpose of this research is to remove the mercury using Pseudomonas putida (P. putida), pure culture ATTC 49128 at optimum growth parameters such as techniques of culture, acclimatization time and speed of incubator shaker. Thus, in this study, the optimum growth parameters of P. putida were obtained to achieve the maximum of mercury removal. Based on the optimum parameters of P. putida for specific growth rate, the removal of two different mercury concentration, 1 ppm and 4 ppm were studied. From mercury nitrate solution, a mercuryresistant bacterial strain which is able to reduce from ionic mercury to metallic mercury was used to reduce ionic mercury. The overall levels of mercury removal in this study were between 80% and 89%. The information obtained in this study is of fundamental for understanding of the survival of P. putida ATTC 49128 in mercury solution. Thus, microbial mercury removal is a potential bioremediation for wastewater especially in petrochemical industries in Malaysia.

Keywords: Pseudomonas putida, growth kinetic, biosorption, mercury, petrochemical wastewater.

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Authors: Davide D’Aria, Paolo Falcone, Luigi Maggi, Aldo Cero, Giovanni Amoroso

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The paper presents a methodology for real-time structural health monitoring and geophysical applications. The key elements of the system are a high performance MIMO RADAR sensor, an optical camera and a dedicated set of software algorithms encompassing interferometry, tomography and photogrammetry. The MIMO Radar sensor proposed in this work, provides an extremely high sensitivity to displacements making the system able to react to tiny deformations (up to tens of microns) with a time scale which spans from milliseconds to hours. The MIMO feature of the system makes the system capable of providing a set of two-dimensional images of the observed scene, each mapped on the azimuth-range directions with noticeably resolution in both the dimensions and with an outstanding repetition rate. The back-scattered energy, which is distributed in the 3D space, is projected on a 2D plane, where each pixel has as coordinates the Line-Of-Sight distance and the cross-range azimuthal angle. At the same time, the high performing processing unit allows to sense the observed scene with remarkable refresh periods (up to milliseconds), thus opening the way for combined static and dynamic structural health monitoring. Thanks to the smart TX/RX antenna array layout, the MIMO data can be processed through a tomographic approach to reconstruct the three-dimensional map of the observed scene. This 3D point cloud is then accurately mapped on a 2D digital optical image through photogrammetric techniques, allowing for easy and straightforward interpretations of the measurements. Once the three-dimensional image is reconstructed, a 'repeat-pass' interferometric approach is exploited to provide the user of the system with high frequency three-dimensional motion/vibration estimation of each point of the reconstructed image. At this stage, the methodology leverages consolidated atmospheric correction algorithms to provide reliable displacement and vibration measurements.

Keywords: Interferometry, MIMO RADAR, SAR, tomography.

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Authors: Morgan Cheng, Wilson Ho, Max Yiu, Dragon Tsui, Wylog Wong, Yasir A. Naveed, C. S. Loong, Richard Kwan, K. C. Lam, Hannah Lo, C. L. Wong

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Hong Kong is known worldwide for high density living and the ability to thrive under trying circumstances. The 7.5 million residents of this busy metropolis live primarily in high-rise buildings which are built and demolished incessantly. Hong Kong residents are therefore affected continuously by numerous construction activities. In 2020, the Hong Kong Environmental Protection Department (EPD) commissioned a feasibility study on the management of construction noise, including those associated with renovation of domestic premises. A key component of the study focused on the review of practices concerning the management and control of construction noise in metropolitans in other parts of the world. To benefit from international best practices, this extensive review aimed at identifying possible areas of improvement in Hong Kong. The study first referred to the United Nations “The World’s Cities in 2016” Report and examined the top 100 cities therein. The 20 most suitable cities were then chosen for further review. Upon further screening, 12 cities with more relevant management practices were selected for further scrutiny. These 12 cities include: Asia – Tokyo, Seoul, Taipei, Guangzhou, Singapore; Europe – City of Westminster (London), Berlin; North America – Toronto, New York City, San Francisco; Oceania – Sydney, Melbourne. Subsequently, three cities, namely Sydney, City of Westminster, and New York City, were selected for in-depth review. These three were chosen primarily because of the maturity, success, and effectiveness of their construction noise management and control measures, as well as their similarity to Hong Kong in certain key aspects. One of the more important findings of the review is the importance of early focus on potential noise issues, with the objective of designing the noise away wherever practicable. The study examined the similar yet different construction noise early focus mechanisms of these three cities. This paper describes this landmark, worldwide and extensive review on international best construction noise management and control practices at the source, along the noise transmission path and at the receiver end. The methodology, approach, and key findings are presented succinctly in this paper. By sharing the findings with the acoustics professionals worldwide, it is hoped that more advanced and mature construction noise management practices can be developed to attain urban sustainability.

Keywords: construction noise, international best practices, noise control and noise management

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