Search results for: CNTs forest
708 The Material Behavior in Curved Glulam Beam of Jabon Timber
Authors: Erma Desmaliana, Saptahari Sugiri
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Limited availability of solid timber in large dimensions becomes a problem. The demands of timbers in Indonesia is more increasing compared to its supply from natural forest. It is associated with the issues of global warming and environmental preservation. The uses of timbers from HTI (Industrial Planting Forest) and HTR (Society Planting Forest), such as Jabon, is an alternative source that required to solve these problems. Having shorter lifespan is the benefit of HTI/HTR timbers, although they are relatively smaller in dimension and lower in strength. Engineering Wood Product (EWP) such as glulam (glue-laminated) timber, is required to overcome their losses. Glulam is fabricated by gluing the wooden planks that having a thickness of 20 to 45 mm with an adhesive material and a certain pressure. Glulam can be made a curved beam, is one of the advantages, thus making it strength is greater than a straight beam. This paper is aimed to know the material behavior of curved glue-laminated beam of Jabon timber. Preliminary methods was to gain physical and mechanical properties, and glue spread strength of Jabon timber, which following the ASTM D-143 standard test method. Dimension of beams were 50 mm wide, 760 mm span, 50 mm thick, and 50 mm rise. Each layer of Jabon has a thickness of 5 mm and is glued with polyurethane. Cold press will be applied to beam laminated specimens for more than 5 hours. The curved glue-laminated beams specimens will be tested about the bending behavior. This experiments aims to obtain the increasing of load carrying capacity and stiffness of curved glulam beam.Keywords: curved glulam beam, HTR&HTI, load carrying, strength
Procedia PDF Downloads 291707 Changes in Forest Cover Regulate Streamflow in Central Nigerian Gallery Forests
Authors: Rahila Yilangai, Sonali Saha, Amartya Saha, Augustine Ezealor
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Gallery forests in sub-Saharan Africa are drastically disappearing due to intensive anthropogenic activities thus reducing ecosystem services, one of which is water provisioning. The role played by forest cover in regulating streamflow and water yield is not well understood, especially in West Africa. This pioneering 2-year study investigated the interrelationships between plant cover and hydrology in protected and unprotected gallery forests. Rainfall, streamflow, and evapotranspiration (ET) measurements/estimates over 2015-2016 were obtained to form a water balance for both catchments. In addition, transpiration in the protected gallery forest with high vegetation cover was calculated from stomatal conductance readings of selected species chosen from plot level data of plant diversity and abundance. Results showed that annual streamflow was significantly higher in the unprotected site than the protected site, even when normalized by catchment area. However, streamflow commenced earlier and lasted longer in the protected site than the degraded unprotected site, suggesting regulation by the greater tree density in the protected site. Streamflow correlated strongly with rainfall with the highest peak in August. As expected, transpiration measurements were less than potential evapotranspiration estimates, while rainfall exceeded ET in the water cycle. The water balance partitioning suggests that the lower vegetation cover in the unprotected catchment leads to a larger runoff in the rainy season and less infiltration, thereby leading to streams drying up earlier, than in the protected catchment. This baseline information is important in understanding the contribution of plants in water cycle regulation, for modeling integrative water management in applied research and natural resource management in sustaining water resources with changing the land cover and climate uncertainties in this data-poor region.Keywords: evapotranspiration, gallery forest, rainfall, streamflow, transpiration
Procedia PDF Downloads 164706 Economic Development and New Challenges: Biomass Energy and Sustainability
Authors: Fabricia G. F. S. Rossato, Ieda G. Hidalgo, Andres Susseta, Felipe Casale, Leticia H. Nakamiti
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This research was conducted to show the useful source of biomass energy provided from forest waste and the black liquor from the pulping process. This energy source could be able to assist and improve its area environment in a sustainable way. The research will demonstrate the challenges from producing the biomass energy and the implantation of the pulp industry in the city of Três Lagoas, MS. – Brazil. Planted forest’s potential, energy production in the pulp industries and its consequence of impacts on the local region environmental was also studied and examined. The present study is classified as descriptive purposes as it exposes the characteristics of a given population and the means such as bibliographical and documentary. All the data and information collected and demonstrate in this study was carefully analyzed and provided from reliable sources such as official government agencies.Keywords: Brazil, pulp industry, renewable energy, Três Lagoas
Procedia PDF Downloads 319705 Multifunctional Epoxy/Carbon Laminates Containing Carbon Nanotubes-Confined Paraffin for Thermal Energy Storage
Authors: Giulia Fredi, Andrea Dorigato, Luca Fambri, Alessandro Pegoretti
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Thermal energy storage (TES) is the storage of heat for later use, thus filling the gap between energy request and supply. The most widely used materials for TES are the organic solid-liquid phase change materials (PCMs), such as paraffin. These materials store/release a high amount of latent heat thanks to their high specific melting enthalpy, operate in a narrow temperature range and have a tunable working temperature. However, they suffer from a low thermal conductivity and need to be confined to prevent leakage. These two issues can be tackled by confining PCMs with carbon nanotubes (CNTs). TES applications include the buildings industry, solar thermal energy collection and thermal management of electronics. In most cases, TES systems are an additional component to be added to the main structure, but if weight and volume savings are key issues, it would be advantageous to embed the TES functionality directly in the structure. Such multifunctional materials could be employed in the automotive industry, where the diffusion of lightweight structures could complicate the thermal management of the cockpit environment or of other temperature sensitive components. This work aims to produce epoxy/carbon structural laminates containing CNT-stabilized paraffin. CNTs were added to molten paraffin in a fraction of 10 wt%, as this was the minimum amount at which no leakage was detected above the melting temperature (45°C). The paraffin/CNT blend was cryogenically milled to obtain particles with an average size of 50 µm. They were added in various percentages (20, 30 and 40 wt%) to an epoxy/hardener formulation, which was used as a matrix to produce laminates through a wet layup technique, by stacking five plies of a plain carbon fiber fabric. The samples were characterized microstructurally, thermally and mechanically. Differential scanning calorimetry (DSC) tests showed that the paraffin kept its ability to melt and crystallize also in the laminates, and the melting enthalpy was almost proportional to the paraffin weight fraction. These thermal properties were retained after fifty heating/cooling cycles. Laser flash analysis showed that the thermal conductivity through the thickness increased with an increase of the PCM, due to the presence of CNTs. The ability of the developed laminates to contribute to the thermal management was also assessed by monitoring their cooling rates through a thermal camera. Three-point bending tests showed that the flexural modulus was only slightly impaired by the presence of the paraffin/CNT particles, while a more sensible decrease of the stress and strain at break and the interlaminar shear strength was detected. Optical and scanning electron microscope images revealed that these could be attributed to the preferential location of the PCM in the interlaminar region. These results demonstrated the feasibility of multifunctional structural TES composites and highlighted that the PCM size and distribution affect the mechanical properties. In this perspective, this group is working on the encapsulation of paraffin in a sol-gel derived organosilica shell. Submicron spheres have been produced, and the current activity focuses on the optimization of the synthesis parameters to increase the emulsion efficiency.Keywords: carbon fibers, carbon nanotubes, lightweight materials, multifunctional composites, thermal energy storage
Procedia PDF Downloads 157704 Predicting Costs in Construction Projects with Machine Learning: A Detailed Study Based on Activity-Level Data
Authors: Soheila Sadeghi
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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.Keywords: cost prediction, machine learning, project management, random forest, neural networks
Procedia PDF Downloads 36703 Characterization of Forest Fire Fuel in Shivalik Himalayas Using Hyperspectral Remote Sensing
Authors: Neha Devi, P. K. Joshi
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Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. One of the most significant forms of global disturbance, impacting community dynamics, biogeochemical cycles and local and regional climate across a wide range of ecosystems ranging from boreal forests to tropical rainforest is wildfire Assessment of fire danger is a function of forest type, fuelwood stock volume, moisture content, degree of senescence and fire management strategy adopted in the ground. Remote sensing has potential of reduction the uncertainty in mapping fuels. Hyperspectral remote sensing is emerging to be a very promising technology for wildfire fuels characterization. Fine spectral information also facilitates mapping of biophysical and chemical information that is directly related to the quality of forest fire fuels including above ground live biomass, canopy moisture, etc. We used Hyperion imagery acquired in February, 2016 and analysed four fuel characteristics using Hyperion sensor data on-board EO-1 satellite, acquired over the Shiwalik Himalayas covering the area of Champawat, Uttarakhand state. The main objective of this study was to present an overview of methodologies for mapping fuel properties using hyperspectral remote sensing data. Fuel characteristics analysed include fuel biomass, fuel moisture, and fuel condition and fuel type. Fuel moisture and fuel biomass were assessed through the expression of the liquid water bands. Fuel condition and type was assessed using green vegetation, non-photosynthetic vegetation and soil as Endmember for spectral mixture analysis. Linear Spectral Unmixing, a partial spectral unmixing algorithm, was used to identify the spectral abundance of green vegetation, non-photosynthetic vegetation and soil.Keywords: forest fire fuel, Hyperion, hyperspectral, linear spectral unmixing, spectral mixture analysis
Procedia PDF Downloads 154702 Effect of Acid-Basic Treatments of Lingocellulosic Material Forest Wastes Wild Carob on Ethyl Violet Dye Adsorption
Authors: Abdallah Bouguettoucha, Derradji Chebli, Tariq Yahyaoui, Hichem Attout
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The effect of acid -basic treatment of lingocellulosic material (forest wastes wild carob) on Ethyl violet adsorption was investigated. It was found that surface chemistry plays an important role in Ethyl violet (EV) adsorption. HCl treatment produces more active acidic surface groups such as carboxylic and lactone, resulting in an increase in the adsorption of EV dye. The adsorption efficiency was higher for treated of lingocellulosic material with HCl than for treated with KOH. Maximum biosorption capacity was 170 and 130 mg/g, for treated of lingocellulosic material with HCl than for treated with KOH at pH 6 respectively. It was also found that the time to reach equilibrium takes less than 25 min for both treated materials. The adsorption of basic dye (i.e., ethyl violet or basic violet 4) was carried out by varying some process parameters, such as initial concentration, pH and temperature. The adsorption process can be well described by means of a pseudo-second-order reaction model showing that boundary layer resistance was not the rate-limiting step, as confirmed by intraparticle diffusion since the linear plot of Qt versus t^0.5 did not pass through the origin. In addition, experimental data were accurately expressed by the Sips equation if compared with the Langmuir and Freundlich isotherms. The values of ΔG° and ΔH° confirmed that the adsorption of EV on acid-basic treated forest wast wild carob was spontaneous and endothermic in nature. The positive values of ΔS° suggested an irregular increase of the randomness at the treated lingocellulosic material -solution interface during the adsorption process.Keywords: adsorption, isotherm models, thermodynamic parameters, wild carob
Procedia PDF Downloads 269701 Multivariate Analysis of Spectroscopic Data for Agriculture Applications
Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman
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In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.Keywords: Brown rot disease, NIR spectroscopy, potato, random forest
Procedia PDF Downloads 183700 Satellite LiDAR-Based Digital Terrain Model Correction using Gaussian Process Regression
Authors: Keisuke Takahata, Hiroshi Suetsugu
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Forest height is an important parameter for forest biomass estimation, and precise elevation data is essential for accurate forest height estimation. There are several globally or nationally available digital elevation models (DEMs) like SRTM and ASTER. However, its accuracy is reported to be low particularly in mountainous areas where there are closed canopy or steep slope. Recently, space-borne LiDAR, such as the Global Ecosystem Dynamics Investigation (GEDI), have started to provide sparse but accurate ground elevation and canopy height estimates. Several studies have reported the high degree of accuracy in their elevation products on their exact footprints, while it is not clear how this sparse information can be used for wider area. In this study, we developed a digital terrain model correction algorithm by spatially interpolating the difference between existing DEMs and GEDI elevation products by using Gaussian Process (GP) regression model. The result shows that our GP-based methodology can reduce the mean bias of the elevation data from 3.7m to 0.3m when we use airborne LiDAR-derived elevation information as ground truth. Our algorithm is also capable of quantifying the elevation data uncertainty, which is critical requirement for biomass inventory. Upcoming satellite-LiDAR missions, like MOLI (Multi-footprint Observation Lidar and Imager), are expected to contribute to the more accurate digital terrain model generation.Keywords: digital terrain model, satellite LiDAR, gaussian processes, uncertainty quantification
Procedia PDF Downloads 171699 Effect of Mangrove Forests in Coastal Flood and Erosion
Authors: Majid Samiee Zenoozian
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This paper studies the susceptibility of local settlements in the gulf of Oman mangrove forest zone to flooding and progressesconsiderate of acuities and reactions to historical and present coastal flooding.it is indirect thaterosionsproduced in coastal zones by the change of mangrove undergrowthsubsequent from the enduring influence of persons since the late 19th century. Confronted with the increasing impact of climate change on climate ambitiousalarms such as flooding and biodiversity damage, handling the relationship between mangroves and their atmosphere has become authoritative for their defense. Coastal flood dangers are increasing quickly. We offer high resolution approximations of the financial value of mangroves forests for flood risk discount. We progress a probabilistic, process-based estimate of the properties of mangroves on avoidanceharms to people and property. More significantly, it also establishes how the incessantsqualor of this significant ecosystem has the potential to unfavorably influence the future cyclone persuadeddangers in the area.Keywords: mangrove forest, coastal, flood, erosion
Procedia PDF Downloads 105698 Monitoring Three-Dimensional Models of Tree and Forest by Using Digital Close-Range Photogrammetry
Authors: S. Y. Cicekli
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In this study, tree-dimensional model of tree was created by using terrestrial close range photogrammetry. For this close range photos were taken. Photomodeler Pro 5 software was used for camera calibration and create three-dimensional model of trees. In first test, three-dimensional model of a tree was created, in the second test three-dimensional model of three trees were created. This study aim is creating three-dimensional model of trees and indicate the use of close-range photogrammetry in forestry. At the end of the study, three-dimensional model of tree and three trees were created. This study showed that usability of close-range photogrammetry for monitoring tree and forests three-dimensional model.Keywords: close- range photogrammetry, forest, tree, three-dimensional model
Procedia PDF Downloads 381697 Application of Multilayer Perceptron and Markov Chain Analysis Based Hybrid-Approach for Predicting and Monitoring the Pattern of LULC Using Random Forest Classification in Jhelum District, Punjab, Pakistan
Authors: Basit Aftab, Zhichao Wang, Feng Zhongke
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Land Use and Land Cover Change (LULCC) is a critical environmental issue that has significant effects on biodiversity, ecosystem services, and climate change. This study examines the spatiotemporal dynamics of land use and land cover (LULC) across a three-decade period (1992–2022) in a district area. The goal is to support sustainable land management and urban planning by utilizing the combination of remote sensing, GIS data, and observations from Landsat satellites 5 and 8 to provide precise predictions of the trajectory of urban sprawl. In order to forecast the LULCC patterns, this study suggests a hybrid strategy that combines the Random Forest method with Multilayer Perceptron (MLP) and Markov Chain analysis. To predict the dynamics of LULC change for the year 2035, a hybrid technique based on multilayer Perceptron and Markov Chain Model Analysis (MLP-MCA) was employed. The area of developed land has increased significantly, while the amount of bare land, vegetation, and forest cover have all decreased. This is because the principal land types have changed due to population growth and economic expansion. The study also discovered that between 1998 and 2023, the built-up area increased by 468 km² as a result of the replacement of natural resources. It is estimated that 25.04% of the study area's urbanization will be increased by 2035. The performance of the model was confirmed with an overall accuracy of 90% and a kappa coefficient of around 0.89. It is important to use advanced predictive models to guide sustainable urban development strategies. It provides valuable insights for policymakers, land managers, and researchers to support sustainable land use planning, conservation efforts, and climate change mitigation strategies.Keywords: land use land cover, Markov chain model, multi-layer perceptron, random forest, sustainable land, remote sensing.
Procedia PDF Downloads 18696 Co-management Organizations: A Way to Facilitate Sustainable Management of the Sundarbans Mangrove Forests of Bangladesh
Authors: Md. Wasiul Islam, Md. Jamius Shams Sowrov
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The Sundarbans is the largest single tract of mangrove forest in the world. This is located in the southwest corner of Bangladesh. This is a unique ecosystem which is a great breeding and nursing ground for a great biodiversity. It supports the livelihood of about 3.5 million coastal dwellers and also protects the coastal belt and inland areas from various natural calamities. Historically, the management of the Sundarbans was controlled by the Bangladesh Forest Department following top-down approach without the involvement of local communities. Such fence and fining-based blue-print approach was not effective to protect the forest which caused Sundarbans to degrade severely in the recent past. Fifty percent of the total tree cover has been lost in the last 30 years. Therefore, local multi-stakeholder based bottom-up co-management approach was introduced at some of the parts of the Sundarbans in 2006 to improve the biodiversity status by enhancing the protection level of the forest. Various co-management organizations were introduced under co-management approach where the local community people could actively involve in various activities related to the management and welfare of the Sundarbans including the decision-making process to achieve the goal. From this backdrop, the objective of the study was to assess the performance of co-management organizations to facilitate sustainable management of the Sundarbans mangrove forests. The qualitative study followed face-to-face interview to collect data using two sets of semi-structured questionnaires. A total of 40 respondents participated in the research that was from eight villagers under two forest ranges. 32 representatives from the local communities as well as 8 official representatives involved in co-management approach were interviewed using snowball sampling technique. The study shows that the co-management approach improved governance system of the Sundarbans through active participation of the local community people and their interactions with the officials via the platform of co-management organizations. It facilitated accountability and transparency system to some extent through following some formal and informal rules and regulations. It also improved the power structure of the management process by fostering local empowerment process particularly the women. Moreover, people were able to learn from their interactions with and within the co-management organizations as well as interventions improved environmental awareness and promoted social learning. The respondents considered good governance as the most important factor for achieving the goal of sustainable management and biodiversity conservation of the Sundarbans. The success of co-management planning process also depends on the active and functional participation of different stakeholders including the local communities where co-management organizations were considered as the most functional platform. However, the governance system was also facing various challenges which resulted in barriers to the sustainable management of the Sundarbans mangrove forest. But still there were some members involved in illegal forest operations and created obstacles against sustainable management of the Sundarbans. Respondents recommended greater patronization from the government, financial and logistic incentives for alternative income generation opportunities with effective participatory monitoring and evaluation system to improve sustainable management of the Sundarbans.Keywords: Bangladesh, co-management approach, co-management organizations, governance, Sundarbans, sustainable management
Procedia PDF Downloads 168695 A Delphi Study of Factors Affecting the Forest Biorefinery Development in the Pulp and Paper Industry: The Case of Bio-Based Products
Authors: Natasha Gabriella, Josef-Peter Schöggl, Alfred Posch
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Being a mature industry, pulp and paper industry (PPI) possess strength points coming from its existing infrastructure, technology know-how, and abundant availability of biomass. However, the declining trend of the wood-based products sales sends a clear signal to the industry to transform its business model in order to increase its profitability. With the emerging global attention on bio-based economy and circular economy, coupled with the low price of fossil feedstock, the PPI starts to integrate biorefinery as a value-added business model to keep the industry’s competitiveness. Nonetheless, biorefinery as an innovation exposes the PPI with some barriers, of which the uncertainty of the promising product becomes one of the major hurdles. This study aims to assess factors that affect the diffusion and development of forest biorefinery in the PPI, including drivers, barriers, advantages, disadvantages, as well as the most promising bio-based products of forest biorefinery. The study examines the identified factors according to the layer of business environment, being the macro-environment, industry, and strategic group level. Besides, an overview of future state of the identified factors is elaborated as to map necessary improvements for implementing forest biorefinery. A two-phase Delphi method is used to collect the empirical data for the study, comprising of an online-based survey and interviews. Delphi method is an effective communication tools to elicit ideas from a group of experts to further reach a consensus of forecasting future trends. Collaborating a total of 50 experts in the panel, the study reveals that influential factors are found in every layers of business of the PPI. The politic dimension is apparent to have a significant influence for tackling the economy barrier while reinforcing the environmental and social benefits in the macro-environment. In the industry level, the biomass availability appears to be a strength point of the PPI while the knowledge gap on technology and market seem to be barriers. Consequently, cooperation with academia and the chemical industry has to be improved. Human resources issue is indicated as one important premise behind the preceding barrier, along with the indication of the PPI’s resistance towards biorefinery implementation as an innovation. Further, cellulose-based products are acknowledged for near-term product development whereas lignin-based products are emphasized to gain importance in the long-term future.Keywords: forest biorefinery, pulp and paper, bio-based product, Delphi method
Procedia PDF Downloads 267694 Stock Price Prediction with 'Earnings' Conference Call Sentiment
Authors: Sungzoon Cho, Hye Jin Lee, Sungwhan Jeon, Dongyoung Min, Sungwon Lyu
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Major public corporations worldwide use conference calls to report their quarterly earnings. These 'earnings' conference calls allow for questions from stock analysts. We investigated if it is possible to identify sentiment from the call script and use it to predict stock price movement. We analyzed call scripts from six companies, two each from Korea, China and Indonesia during six years 2011Q1 – 2017Q2. Random forest with Frequency-based sentiment scores using Loughran MacDonald Dictionary did better than control model with only financial indicators. When the stock prices went up 20 days from earnings release, our model predicted correctly 77% of time. When the model predicted 'up,' actual stock prices went up 65% of time. This preliminary result encourages us to investigate advanced sentiment scoring methodologies such as topic modeling, auto-encoder, and word2vec variants.Keywords: earnings call script, random forest, sentiment analysis, stock price prediction
Procedia PDF Downloads 288693 Classification for Obstructive Sleep Apnea Syndrome Based on Random Forest
Authors: Cheng-Yu Tsai, Wen-Te Liu, Shin-Mei Hsu, Yin-Tzu Lin, Chi Wu
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Background: Obstructive Sleep apnea syndrome (OSAS) is a common respiratory disorder during sleep. In addition, Body parameters were identified high predictive importance for OSAS severity. However, the effects of body parameters on OSAS severity remain unclear. Objective: In this study, the objective is to establish a prediction model for OSAS by using body parameters and investigate the effects of body parameters in OSAS. Methodologies: Severity was quantified as the polysomnography and the mean hourly number of greater than 3% dips in oxygen saturation during examination in a hospital in New Taipei City (Taiwan). Four levels of OSAS severity were classified by the apnea and hypopnea index (AHI) with American Academy of Sleep Medicine (AASM) guideline. Body parameters, including neck circumference, waist size, and body mass index (BMI) were obtained from questionnaire. Next, dividing the collecting subjects into two groups: training and testing groups. The training group was used to establish the random forest (RF) to predicting, and test group was used to evaluated the accuracy of classification. Results: There were 3330 subjects recruited in this study, whom had been done polysomnography for evaluating severity for OSAS. A RF of 1000 trees achieved correctly classified 79.94 % of test cases. When further evaluated on the test cohort, RF showed the waist and BMI as the high import factors in OSAS. Conclusion It is possible to provide patient with prescreening by body parameters which can pre-evaluate the health risks.Keywords: apnea and hypopnea index, Body parameters, obstructive sleep apnea syndrome, Random Forest
Procedia PDF Downloads 148692 Mayan Culture and Attitudes towards Sustainability
Authors: Sarah Ryu
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Agricultural methods and ecological approaches employed by the pre-colonial Mayans may provide valuable insights into forest management and viable alternatives for resource sustainability in the face of major deforestation across Central and South America.Using a combination of observation data collected from the modern indigenous inhabitants near Mixco in Guatemala and historical data, this study was able to create a holistic picture of how the Maya maintained their ecosystems. Surveys and observations were conducted in the field, over a period of twelve weeks across two years. Geographic and archaeological data for this area was provided by Guatemalan organizations such as the Universidad de San Carlos de Guatemala. Observations of current indigenous populations around Mixco showed that they adhered to traditional Mayan methods of agriculture, such as terrace construction and arboriculture. Rather than planting one cash crop as was done by the Spanish, indigenous peoples practice agroforestry, cultivating forests that would provide trees for construction material, wild plant foods, habitat for game, and medicinal herbs. The emphasis on biodiversity prevented deforestation and created a sustainable balance between human consumption and forest regrowth. Historical data provided by MayaSim showed that the Mayans successfully maintained their ecosystems from about 800BCE to 700CE. When the Mayans practiced natural resource conservation and cultivated a harmonious relationship with the forest around them, they were able to thrive and prosper alongside nature. Having lasted over a thousand years, the Mayan empire provides a valuable lesson in sustainability and human attitudes towards the environment.Keywords: biodiversity, forestry, mayan, sustainability
Procedia PDF Downloads 173691 Improved Computational Efficiency of Machine Learning Algorithm Based on Evaluation Metrics to Control the Spread of Coronavirus in the UK
Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick
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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest
Procedia PDF Downloads 116690 Antagonist Study of Fungi Isolated from the Burned Forests of Region of Mila, Algeria
Authors: Abdelaziz Wided, Khiat Nawel, Khiat Inssaf
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The present study was initiated to: Determine burned forest-inhabiting fungi in Zouagha, Terri Beinène, Mila and study the antagonistic activity of Trichoderma sp against Fusarium sp, Penicillium sp, Rhizoctonia sp, Alternaria sp. 18 fungal strains were isolated from Soil samples taken from the forest Zouagha (Burned) in the region Mila representing 6 genera: Trichoderma sp et Fusarium sp, Penicillium sp, Rhizoctonia sp, Alternaria sp, Rhizopus sp. The tests of dual culture method on culture medium (PDA) against Trichoderma sp et Fusarium sp, Penicillium sp, Rhizoctonia sp, Alternaria sp revealed that: Trichoderma sp could reduce l mycelium grouth of Fusarium sp23.13%, Penicillium sp33.13%, Rhizoctoniasp33.75 %and Alternaria sp 38.31% in comparaison with the witness after 6 days at room temperature. The strains of Fusarium sp ,Penicillium sp, Rhizoctonia sp et Alternaria sp showed differences sensibility to the antagoniste.Keywords: isolation, identification, molds, burned soil of zouagha, antagonism, trichoderma sp
Procedia PDF Downloads 245689 Wet Spun Graphene Fibers With Silver Nanoparticles For Flexible Electronic Applications
Authors: Syed W. Hasan, Zhiqun Tian
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Wet spinning provides a facile and economic route to fabricate graphene nanofibers (GFs) on mass scale. Nevertheless, the pristine GFs exhibit significantly low electrical and mechanical properties owing to stacked graphene sheets and weak inter-atomic bonding. In this report, we present highly conductive Ag-decorated-GFs (Ag/GFs). The SEM micrographs show Ag nanoparticles (NPs) (dia ~10 nm) are homogeneously distributed throughout the cross-section of the fiber. The Ag NPs provide a conductive network for the electrons flow raising the conductivity to 1.8(10^4) S/m which is 4 times higher than the pristine GFs. Our results surpass the conductivities of graphene fibers doped with CNTs, Nanocarbon, fullerene, and Cu. The chemical and structural attributes of Ag/GFs are further elucidated through XPS, AFM and Raman spectroscopy.Keywords: Ag nanoparticles, Conductive fibers, Graphene, Wet spinning
Procedia PDF Downloads 134688 Economics of Sugandhakokila (Cinnamomum Glaucescens (Nees) Dury) in Dang District of Nepal: A Value Chain Perspective
Authors: Keshav Raj Acharya, Prabina Sharma
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Sugandhakokila (Cinnamomum glaucescens Nees. Dury) is a large evergreen native tree species; mostly confined naturally in mid-hills of Rapti Zone of Nepal. The species is identified as prioritized for agro-technology development as well as for research and development by a department of plant resources. This species is band for export outside the country without processing by the government of Nepal to encourage the value addition within the country. The present study was carried out in Chillikot village of Dang district to find out the economic contribution of C. glaucescens in the local economy and to document the major conservation threats for this species. Participatory Rural Appraisal (PRA) tools such as Household survey, key informants interviews and focus group discussions were carried out to collect the data. The present study reveals that about 1.7 million Nepalese rupees (NPR) have been contributed annually in the local economy of 29 households from the collection of C. glaucescens berries in the study area. The average annual income of each family was around NPR 67,165.38 (US$ 569.19) from the sale of the berries which contributes about 53% of the total household income. Six different value chain actors are involved in C. glaucescens business. Maximum profit margin was taken by collector followed by producer, exporter and processor. The profit margin was found minimum to regional and village traders. The total profit margin for producers was NPR 138.86/kg, and regional traders have gained NPR 17/kg. However, there is a possibility to increase the profit of producers by NPR 8.00 more for each kg of berries through the initiation of community forest user group and village cooperatives in the area. Open access resource, infestation by an insect to over matured trees and browsing by goats were identified as major conservation threats for this species. Handing over the national forest as a community forest, linking the producers with the processor through organized market channel and replacing the old tree through new plantation has been recommended for future.Keywords: community forest, conservation threats, C. glaucescens, value chain analysis
Procedia PDF Downloads 133687 A Homogenized Mechanical Model of Carbon Nanotubes/Polymer Composite with Interface Debonding
Authors: Wenya Shu, Ilinca Stanciulescu
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Carbon nanotubes (CNTs) possess attractive properties, such as high stiffness and strength, and high thermal and electrical conductivities, making them promising filler in multifunctional nanocomposites. Although CNTs can be efficient reinforcements, the expected level of mechanical performance of CNT-polymers is not often reached in practice due to the poor mechanical behavior of the CNT-polymer interfaces. It is believed that the interactions of CNT and polymer mainly result from the Van der Waals force. The interface debonding is a fracture and delamination phenomenon. Thus, the cohesive zone modeling (CZM) is deemed to give good capture of the interface behavior. The detailed, cohesive zone modeling provides an option to consider the CNT-matrix interactions, but brings difficulties in mesh generation and also leads to high computational costs. Homogenized models that smear the fibers in the ground matrix and treat the material as homogeneous are studied in many researches to simplify simulations. But based on the perfect interface assumption, the traditional homogenized model obtained by mixing rules severely overestimates the stiffness of the composite, even comparing with the result of the CZM with artificially very strong interface. A mechanical model that can take into account the interface debonding and achieve comparable accuracy to the CZM is thus essential. The present study first investigates the CNT-matrix interactions by employing cohesive zone modeling. Three different coupled CZM laws, i.e., bilinear, exponential and polynomial, are considered. These studies indicate that the shapes of the CZM constitutive laws chosen do not influence significantly the simulations of interface debonding. Assuming a bilinear traction-separation relationship, the debonding process of single CNT in the matrix is divided into three phases and described by differential equations. The analytical solutions corresponding to these phases are derived. A homogenized model is then developed by introducing a parameter characterizing interface sliding into the mixing theory. The proposed mechanical model is implemented in FEAP8.5 as a user material. The accuracy and limitations of the model are discussed through several numerical examples. The CZM simulations in this study reveal important factors in the modeling of CNT-matrix interactions. The analytical solutions and proposed homogenized model provide alternative methods to efficiently investigate the mechanical behaviors of CNT/polymer composites.Keywords: carbon nanotube, cohesive zone modeling, homogenized model, interface debonding
Procedia PDF Downloads 125686 Land Use, Land Cover Changes and Woody Vegetation Status of Tsimur Saint Gebriel Monastery, in Tigray Region, Northern Ethiopia
Authors: Abraha Hatsey, Nesibu Yahya, Abeje Eshete
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Ethiopian Orthodox Tewahido Church has a long tradition of conserving the Church vegetation and is an area treated as a refugee camp for many endangered indigenous tree species in Northern Ethiopia. Though around 36,000 churches exist in Ethiopia, only a few churches have been studied so far. Thus, this study assessed the land use land cover change of 3km buffer (1986-2018) and the woody species diversity and regeneration status of Tsimur St. Gebriel monastery in Tigray region, Northern Ethiopia. For vegetation study, systematic sampling was used with 100m spacing between plots and between transects. Plot size was 20m*20m for the main plot and 2 subplots (5m*5m each) for the regeneration study. Tree height, diameter at breast height(DBH) and crown area were measured in the main plot for all trees with DBH ≥ 5cm. In the subplots, all seedlings and saplings were counted with DBH < 5cm. The data was analyzed on excel and Pass biodiversity software for diversity and evenness analysis. The major land cover classes identified include bare land, farmland, forest, shrubland and wetland. The extents of forest and shrubland were declined considerably due to bare land and agricultural land expansions within the 3km buffer, indicating an increasing pressure on the church forest. Regarding the vegetation status, A total of 19 species belonging to 13 families were recorded in the monastery. The diversity (H’) and evenness recorded were 2.4 and 0.5, respectively. The tree density (DBH ≥ 5cm) was 336/ha and a crown cover of 65%. Olea europaea was the dominant (6.4m2/ha out of 10.5m2 total basal area) and a frequent species (100%) with good regeneration in the monastery. The rest of the species are less frequent and are mostly confined to water sources with good site conditions. Juniperus procera (overharvested) and the other indigenous species were with few trees left and with no/very poor regeneration status. The species having poor density, frequency and regeneration (Junperus procera, Nuxia congesta Fersen and Jasminium abyssinica) need prior conservation and enrichment planting. The indigenous species could also serve as a potential seed source for the reproduction and restoration of nearby degraded landscapes. The buffer study also demonstrated expansion of agriculture and bare land, which could be a threat to the forest of the isolated monastery. Hence, restoring the buffer zone is the only guarantee for the healthy existence of the church forest.Keywords: church forests, regeneration, land use change, vegetation status
Procedia PDF Downloads 197685 Biodiversity and Climate Change: Consequences for Norway Spruce Mountain Forests in Slovakia
Authors: Jozef Mindas, Jaroslav Skvarenina, Jana Skvareninova
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Study of the effects of climate change on Norway Spruce (Picea abies) forests has mainly focused on the diversity of tree species diversity of tree species as a result of the ability of species to tolerate temperature and moisture changes as well as some effects of disturbance regime changes. The tree species’ diversity changes in spruce forests due to climate change have been analyzed via gap model. Forest gap model is a dynamic model for calculation basic characteristics of individual forest trees. Input ecological data for model calculations have been taken from the permanent research plots located in primeval forests in mountainous regions in Slovakia. The results of regional scenarios of the climatic change for the territory of Slovakia have been used, from which the values are according to the CGCM3.1 (global) model, KNMI and MPI (regional) models. Model results for conditions of the climate change scenarios suggest a shift of the upper forest limit to the region of the present subalpine zone, in supramontane zone. N. spruce representation will decrease at the expense of beech and precious broadleaved species (Acer sp., Sorbus sp., Fraxinus sp.). The most significant tree species diversity changes have been identified for the upper tree line and current belt of dwarf pine (Pinus mugo) occurrence. The results have been also discussed in relation to most important disturbances (wind storms, snow and ice storms) and phenological changes which consequences are little known. Special discussion is focused on biomass production changes in relation to carbon storage diversity in different carbon pools.Keywords: biodiversity, climate change, Norway spruce forests, gap model
Procedia PDF Downloads 279684 Land Cover, Land Surface Temperature, and Urban Heat Island Effects in Tropical Sub Saharan City of Accra
Authors: Eric Mensah
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The effects of rapid urbanisation of tropical sub-Saharan developing cities on local and global climate are of great concern due to the negative impacts of Urban Heat Island (UHI) effects. The importance of urban parks, vegetative cover and forest reserves in these tropical cities have been undervalued with a rapid degradation and loss of these vegetative covers to urban developments which continue to cause an increase in daily mean temperatures and changes to local climatic conditions. Using Landsat data of the same months and period intervals, the spatial variations of land cover changes, temperature, and vegetation were examined to determine how vegetation improves local temperature and the effects of urbanisation on daily mean temperatures over the past 12 years. The remote sensing techniques of maximum likelihood supervised classification, land surface temperature retrieval technique, and normalised differential vegetation index techniques were used to analyse and create the land use land cover (LULC), land surface temperature (LST), and vegetation and non-vegetation cover maps respectively. Results from the study showed an increase in daily mean temperature by 0.80 °C as a result of rapid increase in urban area by 46.13 sq. km and loss of vegetative cover by 46.24 sq. km between 2005 and 2017. The LST map also shows the existence of UHI within the urban areas of Accra, the potential mitigating effects offered by the existence of forest and vegetative cover as demonstrated by the existence of cool islands around the Achimota ecological forest and University of Ghana botanical gardens areas.Keywords: land surface temperature, climate, remote sensing, urbanisation
Procedia PDF Downloads 316683 Determination of Soil Loss by Erosion in Different Land Covers Categories and Slope Classes in Bovilla Watershed, Tirana, Albania
Authors: Valmir Baloshi, Fran Gjoka, Nehat Çollaku, Elvin Toromani
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As a sediment production mechanism, soil erosion is the main environmental threat to the Bovilla watershed, including the decline of water quality of the Bovilla reservoir that provides drinking water to Tirana city (the capital of Albania). Therefore, an experiment with 25 erosion plots for soil erosion monitoring has been set up since June 2017. The aim was to determine the soil loss on plot and watershed scale in Bovilla watershed (Tirana region) for implementation of soil and water protection measures or payments for ecosystem services (PES) programs. The results of erosion monitoring for the period June 2017 - May 2018 showed that the highest values of surface runoff were noted in bare land of 38829.91 liters on slope of 74% and the lowest values in forest land of 12840.6 liters on slope of 64% while the highest values of soil loss were found in bare land of 595.15 t/ha on slope of 62% and lowest values in forest land of 18.99 t/ha on slope of 64%. These values are much higher than the average rate of soil loss in the European Union (2.46 ton/ha/year). In the same sloping class, the soil loss was reduced from orchard or bare land to the forest land, and in the same category of land use, the soil loss increased with increasing land slope. It is necessary to conduct chemical analyses of sediments to determine the amount of chemical elements leached out of the soil and end up in the reservoir of Bovilla. It is concluded that PES programs should be implemented for rehabilitation of sub-watersheds Ranxe, Vilez and Zall-Bastar of the Bovilla watershed with valuable conservation practices.Keywords: ANOVA, Bovilla, land cover, slope, soil loss, watershed management
Procedia PDF Downloads 156682 Breast Cancer Detection Using Machine Learning Algorithms
Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra
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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer
Procedia PDF Downloads 45681 Assessment of the Landscaped Biodiversity in the National Park of Tlemcen (Algeria) Using Per-Object Analysis of Landsat Imagery
Authors: Bencherif Kada
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In the forest management practice, landscape and Mediterranean forest are never posed as linked objects. But sustainable forestry requires the valorization of the forest landscape, and this aim involves assessing the spatial distribution of biodiversity by mapping forest landscaped units and subunits and by monitoring the environmental trends. This contribution aims to highlight, through object-oriented classifications, the landscaped biodiversity of the National Park of Tlemcen (Algeria). The methodology used is based on ground data and on the basic processing units of object-oriented classification, that are segments, so-called image-objects, representing a relatively homogenous units on the ground. The classification of Landsat Enhanced Thematic Mapper plus (ETM+) imagery is performed on image objects and not on pixels. Advantages of object-oriented classification are to make full use of meaningful statistic and texture calculation, uncorrelated shape information (e.g., length-to-width ratio, direction, and area of an object, etc.), and topological features (neighbor, super-object, etc.), and the close relation between real-world objects and image objects. The results show that per object classification using the k-nearest neighbor’s method is more efficient than per pixel one. It permits to simplify of the content of the image while preserving spectrally and spatially homogeneous types of land covers such as Aleppo pine stands, cork oak groves, mixed groves of cork oak, holm oak, and zen oak, mixed groves of holm oak and thuja, water plan, dense and open shrub-lands of oaks, vegetable crops or orchard, herbaceous plants, and bare soils. Texture attributes seem to provide no useful information, while spatial attributes of shape and compactness seem to be performant for all the dominant features, such as pure stands of Aleppo pine and/or cork oak and bare soils. Landscaped sub-units are individualized while conserving the spatial information. Continuously dominant dense stands over a large area were formed into a single class, such as dense, fragmented stands with clear stands. Low shrublands formations and high wooded shrublands are well individualized but with some confusion with enclaves for the former. Overall, a visual evaluation of the classification shows that the classification reflects the actual spatial state of the study area at the landscape level.Keywords: forest, oaks, remote sensing, diversity, shrublands
Procedia PDF Downloads 112680 An Analysis of LoRa Networks for Rainforest Monitoring
Authors: Rafael Castilho Carvalho, Edjair de Souza Mota
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As the largest contributor to the biogeochemical functioning of the Earth system, the Amazon Rainforest has the greatest biodiversity on the planet, harboring about 15% of all the world's flora. Recognition and preservation are the focus of research that seeks to mitigate drastic changes, especially anthropic ones, which irreversibly affect this biome. Functional and low-cost monitoring alternatives to reduce these impacts are a priority, such as those using technologies such as Low Power Wide Area Networks (LPWAN). Promising, reliable, secure and with low energy consumption, LPWAN can connect thousands of IoT devices, and in particular, LoRa is considered one of the most successful solutions to facilitate forest monitoring applications. Despite this, the forest environment, in particular the Amazon Rainforest, is a challenge for these technologies, requiring work to identify and validate the use of technology in a real environment. To investigate the feasibility of deploying LPWAN in remote water quality monitoring of rivers in the Amazon Region, a LoRa-based test bed consisting of a Lora transmitter and a LoRa receiver was set up, both parts were implemented with Arduino and the LoRa chip SX1276. The experiment was carried out at the Federal University of Amazonas, which contains one of the largest urban forests in Brazil. There are several springs inside the forest, and the main goal is to collect water quality parameters and transmit the data through the forest in real time to the gateway at the uni. In all, there are nine water quality parameters of interest. Even with a high collection frequency, the amount of information that must be sent to the gateway is small. However, for this application, the battery of the transmitter device is a concern since, in the real application, the device must run without maintenance for long periods of time. With these constraints in mind, parameters such as Spreading Factor (SF) and Coding Rate (CR), different antenna heights, and distances were tuned to better the connectivity quality, measured with RSSI and loss rate. A handheld spectrum analyzer RF Explorer was used to get the RSSI values. Distances exceeding 200 m have soon proven difficult to establish communication due to the dense foliage and high humidity. The optimal combinations of SF-CR values were 8-5 and 9-5, showing the lowest packet loss rates, 5% and 17%, respectively, with a signal strength of approximately -120 dBm, these being the best settings for this study so far. The rains and climate changes imposed limitations on the equipment, and more tests are already being conducted. Subsequently, the range of the LoRa configuration must be extended using a mesh topology, especially because at least three different collection points in the same water body are required.Keywords: IoT, LPWAN, LoRa, coverage, loss rate, forest
Procedia PDF Downloads 77679 Modification of Carbon-Based Gas Sensors for Boosting Selectivity
Authors: D. Zhao, Y. Wang, G. Chen
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Gas sensors that utilize carbonaceous materials as sensing media offer numerous advantages, making them the preferred choice for constructing chemical sensors over those using other sensing materials. Carbonaceous materials, particularly nano-sized ones like carbon nanotubes (CNTs), provide these sensors with high sensitivity. Additionally, carbon-based sensors possess other advantageous properties that enhance their performance, including high stability, low power consumption for operation, and cost-effectiveness in their construction. These properties make carbon-based sensors ideal for a wide range of applications, especially in miniaturized devices created through MEMS or NEMS technologies. To capitalize on these properties, a group of chemoresistance-type carbon-based gas sensors was developed and tested against various volatile organic compounds (VOCs) and volatile inorganic compounds (VICs). The results demonstrated exceptional sensitivity to both VOCs and VICs, along with the sensor’s long-term stability. However, this broad sensitivity also led to poor selectivity towards specific gases. This project aims at addressing the selectivity issue by modifying the carbon-based sensing materials and enhancing the sensor's specificity to individual gas. Multiple groups of sensors were manufactured and modified using proprietary techniques. To assess their performance, we conducted experiments on representative sensors from each group to detect a range of VOCs and VICs. The VOCs tested included acetone, dimethyl ether, ethanol, formaldehyde, methane, and propane. The VICs comprised carbon monoxide (CO), carbon dioxide (CO2), hydrogen (H2), nitric oxide (NO), and nitrogen dioxide (NO2). The concentrations of the sample gases were all set at 50 parts per million (ppm). Nitrogen (N2) was used as the carrier gas throughout the experiments. The results of the gas sensing experiments are as follows. In Group 1, the sensors exhibited selectivity toward CO2, acetone, NO, and NO2, with NO2 showing the highest response. Group 2 primarily responded to NO2. Group 3 displayed responses to nitrogen oxides, i.e., both NO and NO2, with NO2 slightly surpassing NO in sensitivity. Group 4 demonstrated the highest sensitivity among all the groups toward NO and NO2, with NO2 being more sensitive than NO. In conclusion, by incorporating several modifications using carbon nanotubes (CNTs), sensors can be designed to respond well to NOx gases with great selectivity and without interference from other gases. Because the response levels to NO and NO2 from each group are different, the individual concentration of NO and NO2 can be deduced.Keywords: gas sensors, carbon, CNT, MEMS/NEMS, VOC, VIC, high selectivity, modification of sensing materials
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