Search results for: tree cover
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2039

Search results for: tree cover

1859 Conceptual Methods of Mitigating Matured Urban Tree Roots Surviving in Conflicts Growth within Built Environment: A Review

Authors: Mohd Suhaizan Shamsuddin

Abstract:

Urbanization exacerbates the environment quality and pressures of matured urban trees' growth and development in changing environment. The growth of struggled matured urban tree-roots by spreading within the existences of infrastructures, resulting in large damage to the structured and declined growth. Many physiological growths declined or damages by the present and installations of infrastructures within and nearby root zone. Afford to remain both matured urban tree and infrastructures as a service provider causes damage and death, respectively. Inasmuch, spending more expenditure on fixing both or removing matured urban trees as risky to the future environment as the mitigation methods to reduce the problems are unconcerned. This paper aims to explain mitigation method practices of reducing the encountered problems of matured urban tree-roots settling and infrastructures while modified urban soil to sustain at an optimum level. Three categories capturing encountered conflicts growth of matured urban tree-roots growth within and nearby infrastructures by mitigating the problems of limited soil spaces, poor soil structures and soil space barrier installations and maintenance. The limited soil space encountered many conflicts and identified six methods that mitigate the survival tree-roots, such as soil volume/mounding, soil replacement/amendment for the radial trench, soil spacing-root bridge, root tunneling, walkway/pavement rising/diverted, and suspended pavement. The limited soil spaces are mitigation affords of inadequate soil-roots and spreading root settling and modification of construction soil media since the barrier existed and installed in root trails or zones. This is the reason for enabling tree-roots spreading and finds adequate sources (nutrients, water uptake and oxygen), spaces and functioning to stability stand of root anchorage since the matured tree grows larger. The poor soil structures were identified as three methods to mitigate soil materials' problems, and fewer soil voids comprise skeletal soil, structural soil, and soil cell. Mitigation of poor soil structure is altering the existing and introducing new structures by modifying the quantities and materials ratio allowing more voids beneath for roots spreading by considering the above structure of foot and vehicle traffics functioning or load-bearing. The soil space barrier installations and maintenance recognized to sustain both infrastructures and tree-roots grown in limited spaces and its benefits, the root barrier installations and root pruning are recommended. In conclusion, these recommended methods attempt to mitigate the present problems encountered at a particular place and problems among tree-roots and infrastructures exist. The combined method is the best way to alleviates the conflicts since the recognized conflicts are between tree-roots and man-made while the urban soil is modified. These presenting methods are most considered to sustain the matured urban trees' lifespan growth in the urban environment.

Keywords: urban tree-roots, limited soil spaces, poor soil structures, soil space barrier and maintenance

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1858 Effect of Superabsorbent for the Improvement of Car Seat's Thermal Comfort

Authors: Funda Buyuk Mazari, Adnan Mazari, Antonin Havelka, Jakub Wiener, Jawad Naeem

Abstract:

The use of super absorbent polymers (SAP) for moisture absorption and comfort is still unexplored. In this research the efficiency of different SAP fibrous webs are determined under different moisture percentage to examine the sorption and desorption efficiency. The SAP fibrous web with low thickness and high moisture absorption are tested with multilayer sandwich structure of car seat cover to determine the moisture absorption through cover material. Sweating guarded hot plate (SGHP) from company Atlas is used to determine the moisture permeability of different car seat cover with superabsorbent layer closed with impermeable polyurethane foam. It is observed that the SAP fibrous layers are very effective in absorbing and desorbing water vapor under extreme high and low moisture percentages respectively. In extreme humid condition (95 %RH) the 20g of SAP layer absorbs nearly 3g of water vapor per hour and reaches the maximum absorption capacity in 6 hours.

Keywords: car seat, comfort, SAF, superabsorbent

Procedia PDF Downloads 432
1857 Frequent-Pattern Tree Algorithm Application to S&P and Equity Indexes

Authors: E. Younsi, H. Andriamboavonjy, A. David, S. Dokou, B. Lemrabet

Abstract:

Software and time optimization are very important factors in financial markets, which are competitive fields, and emergence of new computer tools further stresses the challenge. In this context, any improvement of technical indicators which generate a buy or sell signal is a major issue. Thus, many tools have been created to make them more effective. This worry about efficiency has been leading in present paper to seek best (and most innovative) way giving largest improvement in these indicators. The approach consists in attaching a signature to frequent market configurations by application of frequent patterns extraction method which is here most appropriate to optimize investment strategies. The goal of proposed trading algorithm is to find most accurate signatures using back testing procedure applied to technical indicators for improving their performance. The problem is then to determine the signatures which, combined with an indicator, outperform this indicator alone. To do this, the FP-Tree algorithm has been preferred, as it appears to be the most efficient algorithm to perform this task.

Keywords: quantitative analysis, back-testing, computational models, apriori algorithm, pattern recognition, data mining, FP-tree

Procedia PDF Downloads 335
1856 Hierarchical Tree Long Short-Term Memory for Sentence Representations

Authors: Xiuying Wang, Changliang Li, Bo Xu

Abstract:

A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

Procedia PDF Downloads 328
1855 Forecasting Unusual Infection of Patient Used by Irregular Weighted Point Set

Authors: Seema Vaidya

Abstract:

Mining association rule is a key issue in data mining. In any case, the standard models ignore the distinction among the exchanges, and the weighted association rule mining does not transform on databases with just binary attributes. This paper proposes a novel continuous example and executes a tree (FP-tree) structure, which is an increased prefix-tree structure for securing compacted, discriminating data about examples, and makes a fit FP-tree-based mining system, FP enhanced capacity algorithm is used, for mining the complete game plan of examples by illustration incessant development. Here, this paper handles the motivation behind making remarkable and weighted item sets, i.e. rare weighted item set mining issue. The two novel brightness measures are proposed for figuring the infrequent weighted item set mining issue. Also, the algorithm are handled which perform IWI which is more insignificant IWI mining. Moreover we utilized the rare item set for choice based structure. The general issue of the start of reliable definite rules is troublesome for the grounds that hypothetically no inciting technique with no other person can promise the rightness of influenced theories. In this way, this framework expects the disorder with the uncommon signs. Usage study demonstrates that proposed algorithm upgrades the structure which is successful and versatile for mining both long and short diagnostics rules. Structure upgrades aftereffects of foreseeing rare diseases of patient.

Keywords: association rule, data mining, IWI mining, infrequent item set, frequent pattern growth

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1854 Heart Attack Prediction Using Several Machine Learning Methods

Authors: Suzan Anwar, Utkarsh Goyal

Abstract:

Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

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1853 Environmental Degradation of Natural Resources in Broghil National Park in the High Mountains of Pakistan – Empirical Evidence From Local Community and Geoinformatics

Authors: Siddique Ullah Baig, Alisha Manzoor

Abstract:

The remotest, mountainous, and icy Broghil Valley is a high-profile protected area as a national park, which hosts one of the highest altitude permanent human settlements on the earth. This park hosts a distributed but diverse range of habitats. Due to a lack of infrastructures, higher altitudes, and harsh environmental conditions, poverty-stricken inhabitants mostly rely on its resources, causing ecological dis-balance. This study aims to investigate the environmental degradation of natural resources of the park based on empirical evidence from stakeholders and geoinformatics. The result shows that one-fourth of the park is a gently undulating basin dotted with water bodies / grass, and agricultural land and three fourth is entirely rugged with steep mountains and glaciers. There are virtually no forests as the arid cold tundra climate and high altitude prevent tree growth. Rapid three-decadal land cover changes have led to ecological disequilibrium of the park, narrowing the traditional diverse food base, decreasing the resilience of biodiversity and local livelihoods as crop-land has shifted towards fallow, alpine-grass to peat-land and snow/glacial ice area to bare-soil/rocks. The local community believes in exploiting whatever vegetation or organic material is available for use as food, fodder, and fuel. The permanent presence of the community and limited cost-effective options in the park will be a challenge forever to maintain undisturbed natural processes as the objective of a national park.

Keywords: Broghil National Park, natural resources, environmental degradation, land cover

Procedia PDF Downloads 38
1852 Comparison between Radiocarbon and Dendrochronology Ages Obtained on a 700 Years Tree-Ring Sequence from Northern Romania

Authors: G. Sava, I. Popa, T. Sava, A. Ion, M. Ilie, C. Manailescu, A. Robu

Abstract:

At the RoAMS laboratory in Bucharest we have looked for a head-to-head meeting between AMS radiocarbon dating and dendrochronology dating, aiming to point out and explain any differences or similarities that might appear between their output results. As a subject of this investigation, we have fixed our attention on a sequence of tree rings spanning on a period of 700 years, starting with 1000 AD. The samples were collected from the northern Romanian territory within Moldavia region, and were provided by the ‘Marin Dracea - National Institute for Research and Development in Forestry’. All the 23 single ring wood samples were radiocarbon dated using alpha-cellulose extraction, followed by graphitization in an AGE3 installation. A wiggle matching procedure was applied to reduce the radiocarbon uncertainties for the calibrated ages. The results showed a good agreement on 3 out of 4 wood cores, the age-shifting of one of the wood cores being interpreted as an uncertain dendrochronology matching, which was further corrected.

Keywords: wiggle matching, tree-ring radiocarbon dating, dendrochronology, AMS radiocarbon dating, radiocarbon dating in Romania

Procedia PDF Downloads 159
1851 Valuing Public Urban Street Trees and Their Environmental Spillover Benefits

Authors: Sofia F. Franco, Jacob Macdonald

Abstract:

This paper estimates the value of urban public street trees and their complementary and substitution value with other broader urban amenities and dis-amenities via the residential housing market. We estimate a lower bound value on a city’s tree amenities under instrumental variable and geographic regression discontinuity approaches with an application to Lisbon, Portugal. For completeness, we also explore how urban trees and in particular public street trees impact house prices across the city. Finally, we jointly analyze the planting and maintenance costs and benefits of urban street trees. The estimated value of all public trees in Lisbon is €8.84M. When considering specifically trees planted alongside roads and in public squares, the value is €6.06M or €126.64 per tree. This value is conditional on the distribution of trees in terms of their broader density, with higher effects coming from the overall greening of larger areas of the city compared to the greening of the direct neighborhood. Detrimental impacts are found when the number of trees is higher near street canyons, where they may exacerbate the stagnation of air pollution from traffic. Urban street trees also have important spillover benefits due to pollution mitigation around €6.21 million, or an additional €129.93 per tree. There are added benefits of €26.32 and €28.58 per tree in terms of flooding and heat mitigation, respectively. With significant resources and policies aimed at urban greening, the value obtained is shown to be important for discussions on the benefits of urban trees as compared to mitigation and abatement costs undertaken by a municipality.

Keywords: urban public goods, urban street trees, spatial boundary discontinuities, geospatial and remote sensing methods

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1850 Hydrological Modelling of Geological Behaviours in Environmental Planning for Urban Areas

Authors: Sheetal Sharma

Abstract:

Runoff,decreasing water levels and recharge in urban areas have been a complex issue now a days pointing defective urban design and increasing demography as cause. Very less has been discussed or analysed for water sensitive Urban Master Plans or local area plans. Land use planning deals with land transformation from natural areas into developed ones, which lead to changes in natural environment. Elaborated knowledge of relationship between the existing patterns of land use-land cover and recharge with respect to prevailing soil below is less as compared to speed of development. The parameters of incompatibility between urban functions and the functions of the natural environment are becoming various. Changes in land patterns due to built up, pavements, roads and similar land cover affects surface water flow seriously. It also changes permeability and absorption characteristics of the soil. Urban planners need to know natural processes along with modern means and best technologies available,as there is a huge gap between basic knowledge of natural processes and its requirement for balanced development planning leading to minimum impact on water recharge. The present paper analyzes the variations in land use land cover and their impacts on surface flows and sub-surface recharge in study area. The methodology adopted was to analyse the changes in land use and land cover using GIS and Civil 3d auto cad. The variations were used in  computer modeling using Storm-water Management Model to find out the runoff for various soil groups and resulting recharge observing water levels in POW data for last 40 years of the study area. Results were anlayzed again to find best correlations for sustainable recharge in urban areas.

Keywords: geology, runoff, urban planning, land use-land cover

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1849 Transcendental Birth of the Column from the Full Jar Expressed at the Notre Dame of Paris and Saint Germain-des-Pres

Authors: Kang Woobang

Abstract:

The base of the column is not only a support but also the embodiment of profound symbolism full of cosmic energy. Finding the full jars from which various energy emanate at the Notre Dame of Paris and Saint-Germain-des-Pres in France, the author was so shocked. As the column is cosmic tree, from the Full Jar full with cosmic energy emerges the cosmic tree composed of shaft and capital.

Keywords: full picher or jar, transcendental or supernatural birth from yonggi, yonggimun, yonggissak

Procedia PDF Downloads 389
1848 Historical Tree Height Growth Associated with Climate Change in Western North America

Authors: Yassine Messaoud, Gordon Nigh, Faouzi Messaoud, Han Chen

Abstract:

The effect of climate change on tree growth in boreal and temperate forests has received increased interest in the context of global warming. However, most studies were conducted in small areas and with a limited number of tree species. Here, we examined the height growth responses of seventeen tree species to climate change in Western North America. 37009 stands from forest inventory databases in Canada and USA with varying establishment date were selected. Dominant and co-dominant trees from each stand were sampled to determine top tree height at 50 years breast height age. Height was related to historical mean annual and summer temperatures, annual and summer Palmer Drought Severity Index, tree establishment date, slope, aspect, soil fertility as determined by the rate of carbon organic matter decomposition (carbon/nitrogen), geographic locations (latitude, longitude, and elevation), species range (coastal, interior, and both ranges), shade tolerance and leaf form (needle leaves, deciduous needle leaves, and broadleaves). Climate change had mostly a positive effect on tree height growth. The results explained 62.4% of the height growth variance. Since 1880, height growth increase was greater for coastal, high shade tolerant, and broadleaf species. Height growth increased more on steep slopes and high soil fertility soils. Greater height growth was mostly observed at the leading range and upward. Conversely, some species showed the opposite pattern probably due to the increase of drought (coastal Mediterranean area), precipitation and cloudiness (Alaska and British Columbia) and peculiarity (higher latitudes-lower elevations and vice versa) of western North America topography. This study highlights the role of the species ecological amplitude and traits, and geographic locations as the main factors determining the growth response and its magnitude to the recent global climate change.

Keywords: Height growth, global climate change, species range, species characteristics, species ecological amplitude, geographic locations, western North America

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1847 Land Cover Mapping Using Sentinel-2, Landsat-8 Satellite Images, and Google Earth Engine: A Study Case of the Beterou Catchment

Authors: Ella Sèdé Maforikan

Abstract:

Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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1846 Exploiting JPEG2000 into Reversible Information

Authors: Te-Jen Chang, I-Hui Pan, Kuang-Hsiung Tan, Shan-Jen Cheng, Chien-Wu Lan, Chih-Chan Hu

Abstract:

With the event of multimedia age in order to protect data not to be tampered, damaged, and faked, information hiding technologies are proposed. Information hiding means important secret information is hidden into cover multimedia and then camouflaged media is produced. This camouflaged media has the characteristic of natural protection. Under the undoubted situation, important secret information is transmitted out.Reversible information hiding technologies for high capacity is proposed in this paper. The gray images are as cover media in this technology. We compress gray images and compare with the original image to produce the estimated differences. By using the estimated differences, expression information hiding is used, and higher information capacity can be achieved. According to experimental results, the proposed technology can be approved. For these experiments, the whole capacity of information payload and image quality can be satisfied.

Keywords: cover media, camouflaged media, reversible information hiding, gray image

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1845 Remote Sensing Approach to Predict the Impacts of Land Use/Land Cover Change on Urban Thermal Comfort Using Machine Learning Algorithms

Authors: Ahmad E. Aldousaria, Abdulla Al Kafy

Abstract:

Urbanization is an incessant process that involves the transformation of land use/land cover (LULC), resulting in a reduction of cool land covers and thermal comfort zones (TCZs). This study explores the directional shrinkage of TCZs in Kuwait using Landsat satellite data from 1991 – 2021 to predict the future LULC and TCZ distribution for 2026 and 2031 using cellular automata (CA) and artificial neural network (ANN) algorithms. Analysis revealed a rapid urban expansion (40 %) in SE, NE, and NW directions and TCZ shrinkage in N – NW and SW directions with 25 % of the very uncomfortable area. The predicted result showed an urban area increase from 44 % in 2021 to 47 % and 52 % in 2026 and 2031, respectively, where uncomfortable zones were found to be concentrated around urban areas and bare lands in N – NE and N – NW directions. This study proposes an effective and sustainable framework to control TCZ shrinkage, including zero soil policies, planned landscape design, manmade water bodies, and rooftop gardens. This study will help urban planners and policymakers to make Kuwait an eco–friendly, functional, and sustainable country.

Keywords: land cover change, thermal environment, green cover loss, machine learning, remote sensing

Procedia PDF Downloads 200
1844 Hybrid Anomaly Detection Using Decision Tree and Support Vector Machine

Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

Abstract:

Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: decision tree, feature selection, intrusion detection system, support vector machine

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1843 Interannual Variations in Snowfall and Continuous Snow Cover Duration in Pelso, Central Finland, Linked to Teleconnection Patterns, 1944-2010

Authors: M. Irannezhad, E. H. N. Gashti, S. Mohammadighavam, M. Zarrini, B. Kløve

Abstract:

Climate warming would increase rainfall by shifting precipitation falling form from snow to rain, and would accelerate snow cover disappearing by increasing snowpack. Using temperature and precipitation data in the temperature-index snowmelt model, we evaluated variability of snowfall and continuous snow cover duration(CSCD) during 1944-2010 over Pelso, central Finland. MannKendall non-parametric test determined that annual precipitation increased by 2.69 (mm/year, p<0.05) during the study period, but no clear trend in annual temperature. Both annual rainfall and snowfall increased by 1.67 and 0.78 (mm/year, p<0.05), respectively. CSCD was generally about 205 days from 14 October to 6 May. No clear trend was found in CSCD over Pelso. Spearman’s rank correlation showed most significant relationships of annual snowfall with the East Atlantic (EA) pattern, and CSCD with the East Atlantic/West Russia (EA/WR) pattern. Increased precipitation with no warming temperature caused the rainfall and snowfall to increase, while no effects on CSCD.

Keywords: variations, snowfall, snow cover duration, temperature-index snowmelt model, teleconnection patterns

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1842 Assessment of Land Use and Land Cover Change in Lake Ol Bolossat Catchment, Nyandarua County, Kenya

Authors: John Wangui, Charles Gachene, Stephen Mureithi, Boniface Kiteme

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Land use changes caused by demographic, natural variability, economic, technological and policy factors affect the goods and services derived from an ecosystem. In the past few decades, Lake Ol Bolossat catchment in Nyandarua County Kenya has been facing challenges of land cover changes threatening its capacity to perform ecosystems functions and adversely affecting communities and ecosystems downstream. This study assessed land cover changes in the catchment for a period of twenty eight years (from 1986 to 2014). Analysis of three Landsat images i.e. L5 TM 1986, L5 TM 1995 and L8 OLI/TIRS 2014 was done using ERDAS 9.2 software. The results show that dense forest, cropland and area under water increased by 27%, 29% and 3% respectively. On the other hand, open forest, dense grassland, open grassland, bushland and shrubland decreased by 3%, 3%, 11%, 26% and 1% respectively during the period under assessment. The lake was noted to have increased due to siltation caused by soil erosion causing a reduction in Lake’s depth and consequently causing temporary flooding of the wetland. The study concludes that the catchment is under high demographic pressure which would lead to resource use conflicts and therefore formulation of mitigation measures is highly recommended.

Keywords: land cover, land use change, land degradation, Nyandarua, Remote sensing

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1841 Comparative Analysis of the Impact of Urbanization on Land Surface Temperature in the United Arab Emirates

Authors: A. O. Abulibdeh

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The aim of this study is to investigate and compare the changes in the Land Surface Temperature (LST) as a function of urbanization, particularly land use/land cover changes, in three cities in the UAE, mainly Abu Dhabi, Dubai, and Al Ain. The scale of this assessment will be at the macro- and micro-levels. At the macro-level, a comparative assessment will take place to compare between the four cities in the UAE. At the micro-level, the study will compare between the effects of different land use/land cover on the LST. This will provide a clear and quantitative city-specific information related to the relationship between urbanization and local spatial intra-urban LST variation in three cities in the UAE. The main objectives of this study are 1) to investigate the development of LST on the macro- and micro-level between and in three cities in the UAE over two decades time period, 2) to examine the impact of different types of land use/land cover on the spatial distribution of LST. Because these three cities are facing harsh arid climate, it is hypothesized that (1) urbanization is affecting and connected to the spatial changes in LST; (2) different land use/land cover have different impact on the LST; and (3) changes in spatial configuration of land use and vegetation concentration over time would control urban microclimate on a city scale and control macroclimate on the country scale. This study will be carried out over a 20-year period (1996-2016) and throughout the whole year. The study will compare between two distinct periods with different thermal characteristics which are the cool/cold period from November to March and warm/hot period between April and October. The best practice research method for this topic is to use remote sensing data to target different aspects of natural and anthropogenic systems impacts. The project will follow classical remote sensing and mapping techniques to investigate the impact of urbanization, mainly changes in land use/land cover, on LST. The investigation in this study will be performed in two stages. Stage one remote sensing data will be used to investigate the impact of urbanization on LST on a macroclimate level where the LST and Urban Heat Island (UHI) will be compared in the three cities using data from the past two decades. Stage two will investigate the impact on microclimate scale by investigating the LST and UHI using a particular land use/land cover type. In both stages, an LST and urban land cover maps will be generated over the study area. The outcome of this study should represent an important contribution to recent urban climate studies, particularly in the UAE. Based on the aim and objectives of this study, the expected outcomes are as follow: i) to determine the increase or decrease of LST as a result of urbanization in these four cities, ii) to determine the effect of different land uses/land covers on increasing or decreasing the LST.

Keywords: land use/land cover, global warming, land surface temperature, remote sensing

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1840 EnumTree: An Enumerative Biclustering Algorithm for DNA Microarray Data

Authors: Haifa Ben Saber, Mourad Elloumi

Abstract:

In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of constant rows with a group of columns. This kind of clustering is called biclustering. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed. We introduce a new algorithm called, Enumerative tree (EnumTree) for biclustering of binary microarray data. is an algorithm adopting the approach of enumerating biclusters. This algorithm extracts all biclusters consistent good quality. The main idea of ​​EnumLat is the construction of a new tree structure to represent adequately different biclusters discovered during the process of enumeration. This algorithm adopts the strategy of all biclusters at a time. The performance of the proposed algorithm is assessed using both synthetic and real DNA micryarray data, our algorithm outperforms other biclustering algorithms for binary microarray data. Biclusters with different numbers of rows. Moreover, we test the biological significance using a gene annotation web tool to show that our proposed method is able to produce biologically relevent biclusters.

Keywords: DNA microarray, biclustering, gene expression data, tree, datamining.

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1839 The Best Prediction Data Mining Model for Breast Cancer Probability in Women Residents in Kabul

Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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1838 Variations in Wood Traits across Major Gymnosperm and Angiosperm Tree Species and the Driving Factors in China

Authors: Meixia Zhang, Chengjun Ji, Wenxuan Han

Abstract:

Many wood traits are important functional attributes for tree species, connected with resource competition among species, community dynamics, and ecosystem functions. Large variations in these traits exist among taxonomic categories, but variation in these traits between gymnosperms and angiosperms is still poorly documented. This paper explores the systematic differences in 12 traits between the two tree categories and the potential effects of environmental factors and life form. Based on a database of wood traits for major gymnosperm and angiosperm tree species across China, the values of 12 wood traits and their driving factors in gymnosperms vs. angiosperms were compared. The results are summarized below: i) Means of wood traits were all significantly lower in gymnosperms than in angiosperms. ii) Air-dried density (ADD) and tangential shrinkage coefficient (TSC) reflect the basic information of wood traits for gymnosperms, while ADD and radial shrinkage coefficient (RSC) represent those for angiosperms, providing higher explanation power when used as the evaluation index of wood traits. iii) For both gymnosperm and angiosperm species, life form exhibits the largest explanation rate for large-scale spatial patterns of ADD, TSC (RSC), climatic factors the next, and edaphic factors have the least effect, suggesting that life form is the dominant factor controlling spatial patterns of wood traits. Variations in the magnitude and key traits between gymnosperms and angiosperms and the same dominant factors might indicate the evolutionary divergence and convergence in key functional traits among woody plants.

Keywords: allometry, functional traits, phylogeny, shrinkage coefficient, wood density

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1837 FRP Bars Spacing Effect on Numerical Thermal Deformations in Concrete Beams under High Temperatures

Authors: A. Zaidi, F. Khelifi, R. Masmoudi, M. Bouhicha

Abstract:

5 In order to eradicate the degradation of reinforced concrete structures due to the steel corrosion, professionals in constructions suggest using fiber reinforced polymers (FRP) for their excellent properties. Nevertheless, high temperatures may affect the bond between FRP bar and concrete, and consequently the serviceability of FRP-reinforced concrete structures. This paper presents a nonlinear numerical investigation using ADINA software to investigate the effect of the spacing between glass FRP (GFRP) bars embedded in concrete on circumferential thermal deformations and the distribution of radial thermal cracks in reinforced concrete beams submitted to high temperature variations up to 60 °C for asymmetrical problems. The thermal deformations predicted from nonlinear finite elements model, at the FRP bar/concrete interface and at the external surface of concrete cover, were established as a function of the ratio of concrete cover thickness to FRP bar diameter (c/db) and the ratio of spacing between FRP bars in concrete to FRP bar diameter (e/db). Numerical results show that the circumferential thermal deformations at the external surface of concrete cover are linear until cracking thermal load varied from 32 to 55 °C corresponding to the ratio of e/db varied from 1.3 to 2.3, respectively. However, for ratios e/db >2.3 and c/db >1.6, the thermal deformations at the external surface of concrete cover exhibit linear behavior without any cracks observed on the specified surface. The numerical results are compared to those obtained from analytical models validated by experimental tests.

Keywords: concrete beam, FRP bars, spacing effect, thermal deformation

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1836 Analysis of Land Use, Land Cover Changes in Damaturu, Nigeria: Using Satellite Images

Authors: Isa Muhammad Zumo, Musa Lawan

Abstract:

This study analyzes the land use/land cover changes in Damaturu metropolis from 1986 to 2005. LandSat TM Images of 1986, 1999, and 2005 were used. Built-up lands, agric lands, water body and other lands were created as themes within ILWIS 3.4 software. The images were displayed in False Colour Composite (FCC) for a better visualization and identification of the themes created. Training sample sets were collected based on the ground truth data during field the checks. Statistical data were then extracted from the classified sample set. Area in hectares for each theme was calculated for each year and the result for each land use/land cover types for each study year was compared. From the result, it was found out that built-up areas have a considerable increase from 37.71 hectares in 1986 to 1062.72 hectares in 2005. It has an annual increase rate of approximately 0.34%. The results also reveal that there is a decrease of 5829.66 hectares of other lands (vacant lands) from 1986 to 2005.

Keywords: land use, changes, analysis, environmental pollution

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1835 Hybrid Thresholding Lifting Dual Tree Complex Wavelet Transform with Wiener Filter for Quality Assurance of Medical Image

Authors: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

Abstract:

The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

Procedia PDF Downloads 135
1834 Breeding Biology of the House Crow Corvus splendens at Hazara University, Garden Campus, Mansehra, Pakistan

Authors: Muhammad Awais

Abstract:

Study on the nesting biology of the House Crow Corvus splendens was conducted at Hazara University, Garden Campus (125 acres), Mansehra during the 2013 breeding season (June to September). Details about nest locations, tree characteristics, nest and egg characteristics were recorded. Mean nest density of House Crow was 2.4 nests/ acre. Mean tree and nest height were 14.8±6.30 and 11.8±5.42m. Mean tree canopy spread 9.5±2.48m. Mean maximum and minimum nest diameters were 42.3±2.08 and 39.0±1.73cm respectively while maximum and minimum diameters of nest cup were 15.6±1.52 and 13.3±1.15cm respectively. Nest depth and nest cup depth were measured 19.3±2.08 and 8.3±1.15cm respectively. Mean nest weight was 1.4±0.24 kg. Mean clutch size was 4.0 (ranged 1–6). Mean egg length was 38.6±0.69mm, breadth 26.0±0.69mm, egg volume 13.3±0.83cm3 and egg shape index 1.42±0.83. Mean egg weight was 12.3±0.70g. Egg and nest success was calculated 55.1% and 69.0%. Hatchlings and fledglings produced per nest were 2.20 and 1.44 respectively. Main reasons for reproductive failures were unhatched eggs, poor nest construction, bad weather conditions and observer’s disturbance.

Keywords: breeding, Corvus splendens, fledglings, Hazara university, house crow, Mansehra, populus orientalis

Procedia PDF Downloads 378
1833 Object Oriented Fault Tree Analysis Methodology

Authors: Yi Xiong, Tao Kong

Abstract:

Traditional safety, risk and reliability analysis approaches are problem-oriented, which make it great workload when analyzing complicated and huge system, besides, too much repetitive work would to do if the analyzed system composed by many similar components. It is pressing need an object and function oriented approach to maintain high consistency with problem domain. A new approach is proposed to overcome these shortcomings of traditional approaches, the concepts: class, abstract, inheritance, polymorphism and encapsulation are introduced into FTA and establish the professional class library that the abstractions of physical objects in real word, four areas relevant information also be proposed as the establish help guide. The interaction between classes is completed by the inside or external methods that mapping the attributes to base events through fully search the knowledge base, which forms good encapsulation. The object oriented fault tree analysis system that analyze and evaluate the system safety and reliability according to the original appearance of the problem is set up, where could mapped directly from the class and object to the problem domain of the fault tree analysis. All the system failure situations can be analyzed through this bottom-up fault tree construction approach. Under this approach architecture, FTA approach is developed, which avoids the human influence of the analyst on analysis results. It reveals the inherent safety problems of analyzed system itself and provides a new way of thinking and development for safety analysis. So that object oriented technology in the field of safety applications and development, safety theory is conducive to innovation.

Keywords: FTA, knowledge base, object-oriented technology, reliability analysis

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1832 Decision Tree Model for the Recommendation of Digital and Alternate Payment Methods for SMEs

Authors: Arturo J. Anci Alméstar, Jose D. Fernandez Huapaya, David Mauricio

Abstract:

Companies make erroneous decisions by not evaluating the inherent difficulties of entering electronic commerce without a prior review of current digital and alternate means of payment. For this reason, it is very important for businesses to have reliable, complete and integrated information on the means of current digital and alternate payments that allow decisions to be made about which of these to use. However, there is no such consolidated information or criteria that companies use to make decisions about the means of payment according to their needs. In this paper, we propose a decision tree model based on a taxonomy that presents us with a categorization of digital and alternative means of payment, as well as the visualization of the flow of information at a high level from the company to obtain a recommendation. This will allow the company to make the most appropriate decision about the implementation of the digital means of payment or alternative ideal for their needs, which allows a reduction in costs and complexity of the payment process. Likewise, the efficiency of the proposed model was evaluated through a satisfaction survey presented to company personnel, confirming the satisfactory quality level of the recommendations obtained by the model.

Keywords: digital payment medium, decision tree, decision making, digital payments taxonomy

Procedia PDF Downloads 153
1831 Predicting Growth of Eucalyptus Marginata in a Mediterranean Climate Using an Individual-Based Modelling Approach

Authors: S.K. Bhandari, E. Veneklaas, L. McCaw, R. Mazanec, K. Whitford, M. Renton

Abstract:

Eucalyptus marginata, E. diversicolor and Corymbia calophylla form widespread forests in south-west Western Australia (SWWA). These forests have economic and ecological importance, and therefore, tree growth and sustainable management are of high priority. This paper aimed to analyse and model the growth of these species at both stand and individual levels, but this presentation will focus on predicting the growth of E. Marginata at the individual tree level. More specifically, the study wanted to investigate how well individual E. marginata tree growth could be predicted by considering the diameter and height of the tree at the start of the growth period, and whether this prediction could be improved by also accounting for the competition from neighbouring trees in different ways. The study also wanted to investigate how many neighbouring trees or what neighbourhood distance needed to be considered when accounting for competition. To achieve this aim, the Pearson correlation coefficient was examined among competition indices (CIs), between CIs and dbh growth, and selected the competition index that can best predict the diameter growth of individual trees of E. marginata forest managed under different thinning regimes at Inglehope in SWWA. Furthermore, individual tree growth models were developed using simple linear regression, multiple linear regression, and linear mixed effect modelling approaches. Individual tree growth models were developed for thinned and unthinned stand separately. The developed models were validated using two approaches. In the first approach, models were validated using a subset of data that was not used in model fitting. In the second approach, the model of the one growth period was validated with the data of another growth period. Tree size (diameter and height) was a significant predictor of growth. This prediction was improved when the competition was included in the model. The fit statistic (coefficient of determination) of the model ranged from 0.31 to 0.68. The model with spatial competition indices validated as being more accurate than with non-spatial indices. The model prediction can be optimized if 10 to 15 competitors (by number) or competitors within ~10 m (by distance) from the base of the subject tree are included in the model, which can reduce the time and cost of collecting the information about the competitors. As competition from neighbours was a significant predictor with a negative effect on growth, it is recommended including neighbourhood competition when predicting growth and considering thinning treatments to minimize the effect of competition on growth. These model approaches are likely to be useful tools for the conservations and sustainable management of forests of E. marginata in SWWA. As a next step in optimizing the number and distance of competitors, further studies in larger size plots and with a larger number of plots than those used in the present study are recommended.

Keywords: competition, growth, model, thinning

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1830 Using 3D Satellite Imagery to Generate a High Precision Canopy Height Model

Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

Abstract:

Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

Procedia PDF Downloads 92