Search results for: forest residue
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 251

Search results for: forest residue

161 The Influence of the Types of Smoke Powder and Storage Duration on Sensory Quality of Balinese Beef and Buffalo Meatballs

Authors: E. Abustam, M. I. Said, M. Yusuf, H. M. Ali

Abstract:

This study aims to examine the sensory quality of meatballs made from Balinese beef and buffalo meat after the addition of smoke powder prior to storage at the temperatures of 2- 5°C for 7 days. This study used meat from Longissimus dorsi muscle of male Balinese cattle aged 3 years and of male buffalo aged 5 years as the main raw materials, and smoke powder as a binder and preservative in making meatballs. The study was based on completely randomized design (CRD) of factorial pattern of 2 x 3 x 2 where factors 1, 2 and 3 included the types of meat (cattle and buffalo), types of smoke powder (oven dried, freeze dried and spray dried) with a level of 2% of the weight of the meat (w/w), and storage duration (0 and 7 days) with three replications, respectively. The parameters measured were the meatball sensory quality (scores of tenderness, firmness, chewing residue, and intensity of flavor). The results of this study show that each type of meat has produced different sensory characteristics. The meatballs made from buffalo meat have higher tenderness and elasticity scores than the Balinese beef. Meanwhile, the buffalo meatballs have a lower residue mastication score than the Balinese beef. Each type of smoke powders has produced a relatively similar sensory quality of meatballs. It can be concluded that the smoke powder of 2% of the weight of the meat (w/w) could maintain the sensory quality of the meatballs for 7 days of storage.

Keywords: Balinese beef meatballs, buffalo meatballs, sensory quality, smoke powder.

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160 Environmental Analysis of Springs in Urban Areas–A Methodological Proposal

Authors: Milton Pavezzi Netto, Gustavo D'Almeida Scarpinella, Ricardo Siloto da Silva

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The springs located in urban areas are the outpouring of surface water, which can serve as water supply, effluent receptors and important local macro-drainage elements. With unplanned occupation, non-compliance with environmental legislation and the importance of these water bodies, it is vital to analyze the springs within urban areas, considering the Brazilian forest code. This paper submits an analysis and discussion methodology proposal of environmental compliance functions of urban springs, by means of G.I.S. - Geographic Information System analysis - and in situ analysis. The case study included two springs which exhibit a history of occupation along its length, with different degrees of impact. The proposed method is effective and easy to apply, representing a powerful tool for analyzing the environmental conditions of springs in urban areas.

Keywords: Springs, urban area, Brazilian forest code.

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159 The Environmental Conservation Behavior of the Applied Health Science Students of Green and Clean University

Authors: Nareelux Suwannobol, Plernpit Promrak, Kiattisak Batsungnoen

Abstract:

The aim of this study was to investigate the environmental conservation behavior of the Applied Health Science students of Suranaree University of Technology, a green and clean university. The sample group was 184 Applied Health Science students (medical, nursing, and public health). A questionnaire was used to collect information. The result of the study found that the students had more negative than positive behaviors towards energy, water, and forest conservation. This result can be used as basic information for designing long-term behavior modification activities or research projects on environmental conservation. Thus Applied Health Science students will be encouraged to be conscious and also be a good example of environmental conservation behavior.

Keywords: Energy conservation behavior, Water conservationbehavior, Forest conservation behavior, Green and clean University.

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158 Multivariate Analysis of Spectroscopic Data for Agriculture Applications

Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

Abstract:

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.

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157 Comparison of Multivariate Adaptive Regression Splines and Random Forest Regression in Predicting Forced Expiratory Volume in One Second

Authors: P. V. Pramila, V. Mahesh

Abstract:

Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients resulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects) with the aforementioned input features. It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, as well as yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV1, Multivariate Adaptive Regression Splines Pulmonary Function Test, Random Forest.

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156 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.

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155 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.

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154 A Detailed Timber Harvest Simulator Coupled with 3-D Visualization

Authors: Jürgen Roßmann, Gerrit Alves

Abstract:

In today-s world, the efficient utilization of wood resources comes more and more to the mind of forest owners. It is a very complex challenge to ensure an efficient harvest of the wood resources. This is one of the scopes the project “Virtual Forest II" addresses. Its core is a database with data about forests containing approximately 260 million trees located in North Rhine-Westphalia (NRW). Based on this data, tree growth simulations and wood mobilization simulations can be conducted. This paper focuses on the latter. It describes a discrete-event-simulation with an attached 3-D real time visualization which simulates timber harvest using trees from the database with different crop resources. This simulation can be displayed in 3-D to show the progress of the wood crop. All the data gathered during the simulation is presented as a detailed summary afterwards. This summary includes cost-benefit calculations and can be compared to those of previous runs to optimize the financial outcome of the timber harvest by exchanging crop resources or modifying their parameters.

Keywords: Timber harvest, simulation, 3-D, optimization.

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153 Forest Growth Simulation: Tropical Rain Forest Stand Table Projection

Authors: Yasmin Yahya, Roslan Ismail, Samreth Vanna, Khorn Saret

Abstract:

The study on the tree growth for four species groups of commercial timber in Koh Kong province, Cambodia-s tropical rainforest is described. The simulation for these four groups had been successfully developed in the 5-year interval through year-60. Data were obtained from twenty permanent sample plots in the duration of thirteen years. The aim for this study was to develop stand table simulation system of tree growth by the species group. There were five steps involved in the development of the tree growth simulation: aggregate the tree species into meaningful groups by using cluster analysis; allocate the trees in the diameter classes by the species group; observe the diameter movement of the species group. The diameter growth rate, mortality rate and recruitment rate were calculated by using some mathematical formula. Simulation equation had been created by combining those parameters. Result showed the dissimilarity of the diameter growth among species groups.

Keywords: cluster analysis, diameter growth, simulation

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152 Land Use Change Detection Using Remote Sensing and GIS

Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi

Abstract:

In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.

Keywords: HARAZ Basin, Change Detection, Land-use, Satellite Data.

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151 A Study on Local Wisdom towards Career Building of People in Kamchanoad Community

Authors: Phusit Phukamchanoad, Thananya Santithammakul, Suwaree Yordchim, Pennapa Palapin

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This research gathered local wisdom towards career building of people in Kamchanoad Community, Baan Muang sub-district, Baan Dung district, Udon Thani province. Data was collected through in-depth interviews with village headmen, community board, teachers, monks, Kamchanoad forest managers and revered elderly aged over 60 years old. All of these 30 interviewees have resided in Kamchanoad Community for more than 40. Descriptive data analysis result revealed that the most prominent local wisdom of Kamchanoad community is their beliefs and religion. Most people in the community have strongly maintained local tradition, the festival of appeasing Chao Pu Sri Suttho on the middle of the 6th month of Thai lunar calendar which falls on the same day with Vesak Day. 100 percent of the people in this community are Buddhist. They believe that Naga, an entity or being, taking the form of a serpent, named “Sri Suttho” lives in Kamchanoad forest. The local people worship the serpent and ask for blessings. Another local wisdom of this community is Sinh fabric weaving.

Keywords: Local Wisdom, Careers, Kamchanoad Community.

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150 Towards Integrating Statistical Color Features for Human Skin Detection

Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: Color space, neural network, random forest, skin detection, statistical feature.

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149 Volatile Organochlorine Compounds Emitted by Temperate Coniferous Forests

Authors: Jana Doležalová, Josef Holík, Zdeněk Wimmer, Sándor T. Forczek

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Chlorine is one of the most abundant elements in nature, which undergoes a complex biogeochemical cycle. Chlorine bound in some substances is partly responsible for atmospheric ozone depletion and contamination of some ecosystems. As due to international regulations anthropogenic burden of volatile organochlorines (VOCls) in atmosphere decreases, natural sources (plants, soil, abiotic formation) are expected to dominate VOCl production in the near future. Examples of plant VOCl production are methyl chloride, and bromide emission from (sub)tropical ferns, chloroform, 1,1,1-trichloroethane and tetrachloromethane emission from temperate forest fern and moss. Temperate forests are found to emit in addition to the previous compounds tetrachloroethene, and brominated volatile compounds. VOCls can be taken up and further metabolized in plants. The aim of this work is to identify and quantitatively analyze the formed VOCls in temperate forest ecosystems by a cryofocusing/GC-ECD detection method, hence filling a gap of knowledge in the biogeochemical cycle of chlorine.

Keywords: chloroform, cryofocusing-GC-ECD, ozonedepletion, volatile organochlorines

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148 A Supplier-Manufacturer Relationship Model for Teak Forest Carbon Sequestration and Teak Log Demand Fulfillment with Sustainability Consideration

Authors: Ririn Dewi Cahyani, Muh. Hisjam, Wahyudi Sutopo, Kuncoro Harto Widodo

Abstract:

Availability of raw materials is important for Indonesia as a furniture exporting country. Teak log as raw materials is supplied to the furniture industry by Perum Perhutani (PP). PP needs to involve carbon trading for nature conservation. PP also has an obligation in the Corporate Social Responsibility program. PP and furniture industry also must prosecute the regulations related to ecological issues and labor rights. This study has the objective to create the relationship model between supplier and manufacturer to fulfill teak log demand that involving teak forest carbon sequestration. A model is formulated as Goal Programming to get the favorable solution for teak log procurement and support carbon sequestration that considering economical, ecological, and social aspects of both supplier and manufacturer. The results show that the proposed model can be used to determine the teak log quantity involving carbon trading to achieve the seven goals to be satisfied the sustainability considerations.

Keywords: Availability of teak log, support carbon sequestration, goal programming, sustainability consideration.

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147 Res2ValHUM: Creation of Resource Management Tool and Microbial Consortia Isolation and Identification

Authors: A. Ribeiro, N. Valério, C. Vilarinho, J. Araujo, J. Carvalho

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Res2ValHUM project involves institutions from the Spanish Autonomous Region of Galicia and the north of Portugal (districts of Porto and Braga) and has as overall objectives of promotion of composting as an process for the correct managing of organic waste, valorization of compost in different fields or applications for the constitution of products with high added value, reducing of raw materials losses, and reduction of the amount of waste throw in landfills. Three main actions were designed to achieve the objectives: development of a management tool to improve collection and residue channeling for composting, sensibilization of the population for composting and characterization of the chemical and biological properties of compost and humic and fulvic substances to envisage high-value applications of compost. Here we present the cooperative activity of Galician and northern Portuguese institutions to valorize organic waste in both regions with common socio-economic characteristics and residue management problems. Results from the creation of the resource manage tool proved the existence of a large number of agricultural wastes that could be valorized. In the North of Portugal, the wastes from maize, oats, potato, apple, grape pomace, rye, and olive pomace can be highlighted. In the Autonomous Region of Galicia the wastes from maize, wheat, potato, apple, and chestnuts can be emphasized. Regarding the isolation and identification of microbial consortia from compost samples, results proved microorganisms belong mainly to the genus Bacillus spp. Among all the species identified in compost samples, Bacillus licheniformis can be highlighted in the production of humic and fulvic acids.

Keywords: Agricultural wastes, Bacillus licheniformis, Bacillus spp., Humic-acids, Fulvic-acids.

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146 Role of Community Youths in Conservation of Forests and Protected Areas of Bangladesh

Authors: Obaidul Fattah Tanvir, Zinat Ara Afroze

Abstract:

Community living adjacent to forests and Protected Areas, especially in South Asian countries, have a common practice in extracting resources for their living and livelihoods. This extraction of resources, because the way it is done, destroys the biophysical features of the area. Deforestation, wildlife poaching, illegal logging, unauthorized hill cutting etc. are some of the serious issues of concern for the sustainability of the natural resources that has a direct impact on environment and climate as a whole. To ensure community involvement in conservation initiatives of the state, community based forest management, commonly known as Comanagement, has been in practice in 6 South Asian countries. These are -India, Nepal, Sri Lanka, Pakistan, Bhutan and Bangladesh. Involving community in forestry management was initiated first in Bangladesh in 1979 and reached as an effective co-management approach through a several paradigm shifts. This idea of Comanagement has been institutionalized through a Government Order (GO) by the Ministry of Environment and Forests, Government of Bangladesh on November 23, 2009. This GO clearly defines the structure and functions of Co-management and its different bodies. Bangladesh Forest Department has been working in association with community to conserve and manage the Forests and Protected areas of Bangladesh following this legal document. Demographically young people constitute the largest segment of population in Bangladesh. This group, if properly sensitized, can produce valuable impacts on the conservation initiatives, both by community and government. This study traced the major factors that motivate community youths to work effectively with different tiers of comanagement organizations in conservation of forests and Protected Areas of Bangladesh. For the purpose of this study, 3 FGDs were conducted with 30 youths from the community living around the Protected Areas of Cox’s bazar, South East corner of Bangladesh, who are actively involved in Co-management organizations. KII were conducted with 5 key officials of Forest Department stationed at Cox’s Bazar. 2 FGDs were conducted with the representatives of 7 Co-management organizations working in Cox’s Bazar region and approaches of different community outreach activities conducted for forest conservation by 3 private organizations and Projects have been reviewed. Also secondary literatures were reviewed for the history and evolution of Co-management in Bangladesh and six South Asian countries. This study found that innovative community outreach activities that are financed by public and private sectors involving youths and community as a whole have played a pivotal role in conservation of forests and Protected Areas of the region. This approach can be replicated in other regions of Bangladesh as well as other countries of South Asia where Co-Management exists in practice.

Keywords: Community, co-management, conservation, forests, protected areas, youth.

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145 Production of Biodiesel from Different Edible Oils

Authors: Amir Shafeeq, Ayyaz Muhammad, Noman Hassan, Rofice Dickson

Abstract:

Different vegetable oil based biodiesel (FAMES) were prepared by alkaline transesterification using refined oils as well as waste frying oil (WFO). Methanol and sodium hydroxide are used as catalyst under similar reaction conditions. To ensure the quality of biodiesel produced, a series of different ASTM Standard tests were carried out. In this context, various testwere done including viscosity, carbon residue, specific gravity, corrosion test, flash point, cloud point and pour point. Results revealed that characteristics of biodiesel depend on the feedstock and it is far better than petroleum diesel.

Keywords: Biodiesel, Edible oils, Separation.

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144 3D Human Reconstruction over Cloud Based Image Data via AI and Machine Learning

Authors: Kaushik Sathupadi, Sandesh Achar

Abstract:

Human action recognition (HAR) modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view Football datasets. Our HAR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH Multi-view Football datasets, respectively.

Keywords: Computer vision, human motion analysis, random forest, machine learning.

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143 Assessment of Tourist and Community Perception with Regard to Tourism Sustainability Indicators: A Case Study of Sinharaja World Heritage Rainforest, Sri Lanka

Authors: L. P. K. Liyanage, N. R. P. Withana, A. L. Sandika

Abstract:

The purpose of this study was to determine tourist and community perception-based sustainable tourism indicators as well as Human Pressure Index (HPI) and Tourist Activity Index (TAI). Study was carried out in Sinharaja forest which is considered as one of the major eco-tourism destination in Sri Lanka. Data were gathered using a pre-tested semi-structured questionnaire as well as records from Forest department. Convenient sampling technique was applied. For the majority of issues, the responses were obtained on multi-point Likert-type scales. Visual portrayal was used for display analyzed data. The study revealed that the host community of the Kudawa gets many benefits from tourism. Also, tourism has caused negative impacts upon the environment and community. The study further revealed the need of proper waste management and involvement of local cultural events for the tourism business in the Kudawa conservation center. The TAI, which accounted to be 1.27 and monthly evolution of HPI revealed that congestion can be occurred in the Sinharaja rainforest during peak season. The results provide useful information to any party involved with tourism planning anywhere, since such attempts would be more effective once the people’s perceptions on these aspects are taken into account.

Keywords: Kudawa conservation center, Sinharaja world heritage rainforest, sustainability indicators.

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142 GIS-based Non-point Sources of Pollution Simulation in Cameron Highlands, Malaysia

Authors: M. Eisakhani, A. Pauzi, O. Karim, A. Malakahmad, S.R. Mohamed Kutty, M. H. Isa

Abstract:

Cameron Highlands is a mountainous area subjected to torrential tropical showers. It extracts 5.8 million liters of water per day for drinking supply from its rivers at several intake points. The water quality of rivers in Cameron Highlands, however, has deteriorated significantly due to land clearing for agriculture, excessive usage of pesticides and fertilizers as well as construction activities in rapidly developing urban areas. On the other hand, these pollution sources known as non-point pollution sources are diverse and hard to identify and therefore they are difficult to estimate. Hence, Geographical Information Systems (GIS) was used to provide an extensive approach to evaluate landuse and other mapping characteristics to explain the spatial distribution of non-point sources of contamination in Cameron Highlands. The method to assess pollution sources has been developed by using Cameron Highlands Master Plan (2006-2010) for integrating GIS, databases, as well as pollution loads in the area of study. The results show highest annual runoff is created by forest, 3.56 × 108 m3/yr followed by urban development, 1.46 × 108 m3/yr. Furthermore, urban development causes highest BOD load (1.31 × 106 kgBOD/yr) while agricultural activities and forest contribute the highest annual loads for phosphorus (6.91 × 104 kgP/yr) and nitrogen (2.50 × 105 kgN/yr), respectively. Therefore, best management practices (BMPs) are suggested to be applied to reduce pollution level in the area.

Keywords: Cameron Highlands, Land use, Non-point Sources of Pollution

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141 Ensemble Approach for Predicting Student's Academic Performance

Authors: L. A. Muhammad, M. S. Argungu

Abstract:

Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

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140 Development of Bicomponent Fibre to Combat Insects

Authors: M. Bischoff, F. Schmidt, J. Herrmann, J. Mattheß, G. Seide, T. Gries

Abstract:

Crop yields have not increased as dramatically as the demand for food. One method to counteract this is to use pesticides to keep away predators, e.g. several forms of insecticide are available to fight insects. These insecticides and pesticides are both controversial as their application and their residue in the food product can also harm humans. In this study an alternative method to combat insects is studied. A physical insect-killing effect of SiO2 particles is used. The particles are applied on fibres to avoid erosion in the fields, which would occur when applied separately. The development of such SiO2 functionalized PP fibres is shown.

Keywords: Agriculture, environment, insects, protection, silica, textile.

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139 An Evaluation of Land Use Control in Hokkaido, Japan

Authors: Kayoko Yamamoto

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This study focuses on an evaluation of Hokkaido which is the northernmost and largest prefecture by surface area in Japan and particularly on two points: the rivalry between all kinds of land use such as urban land and agricultural and forestry land in various cities and their surrounding areas and the possibilities for forestry biomass in areas other than those mentioned above and grasps which areas require examination of the nature of land use control and guidance through conducting land use analysis at the district level using GIS (Geographic Information Systems). The results of analysis in this study demonstrated that it is essential to divide the whole of Hokkaido into two areas: those within delineated city planning areas and those outside of delineated city planning areas and to conduct an evaluation of each land use control. In delineated urban areas, particularly urban areas, it is essential to re-examine land use from the point of view of compact cities or smart cities along with conducting an evaluation of land use control that focuses on issues of rivalry between all kinds of land use such as urban land and agricultural and forestry land. In areas outside of delineated urban areas, it is desirable to aim to build a specific community recycling range based on forest biomass utilization by conducting an evaluation of land use control concerning the possibilities for forest biomass focusing particularly on forests within and outside of city planning areas.

Keywords: Land Use Control, Urbanization, Forestry Biomass, Geographic Information Systems (GIS), Hokkaido

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138 Geochemical and Mineralogical Characteristics of Soils in Areas Affected by the Fires on August 2021 at the Ilia Prefecture, Greece

Authors: D. Panagiotaras, P. Avramidis, D. Papoulis, D. Koulougliotis, D. C. Christodoulopoulos, D. Lekka, D. Nifora, D. Drouvari, A. Skalioti

Abstract:

This study delineates the geochemical, mineralogical and sedimentological characteristics of soils collected from woodland and forest areas affected by the fires of August 2021 at the Pelopio region, Ancient Olympia Municipality, Ilia prefecture, Greece. The mineralogical composition of the samples consists of quartz, calcite, feldspars (albite, oligoclase, anorthite) and clay minerals mostly smectite, kaolinite, and illite. Quartz ranges from 38% to 57% with an average of 48%, calcite ranges from 2% to 25% with an average of 14%, feldspars ranges from 7% to 26% with an average of 17% and clays ranges from 4% to 43% with an average of 21%. Sedimentological analyses classify most of the samples as loam to silt loam. Sand percentage ranges from 14.76% to 71.11% with an average of 35.01%, silt ranges from 21.68% to 62.34% with an average of 44.96%. Geochemical analyses of the soil samples applied for total organic carbon (TOC), total nitrogen (TN), total phosphorous (TP), Cu, Zn, Mn and Fe. TOC ranges from 0.28-0.83%, TN from 0.09-0.48 mg/g, TP from 0.02-0.26 mg/g, Cu from 10-21 ppm, Zn from 15-34 ppm, Mn from 612-1204 ppm, Fe from 9528-27500 ppm. The pH ranges from 7.5 to 9.07 with an average of 8.74, while the values of electrical conductivity (EC) range from 0.05-0.12 mS/cm, with an average of 0.07 mS/cm. Statistical analysis of the data shows a positive correlation between clays and Zn, Mn, Fe. TOC and TN show a strong positive correlation, while Fe shows a strong negative correlation with calcite. 

Keywords: Soils, geochemistry, mineralogy, sedimentology, woodland, forest.

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137 Wildfires Assessed by Remote Sense Images and Burned Land Monitoring

Authors: M. C. Proença

Abstract:

The tools described in this paper enable the location of burned areas where took place the annihilation of natural habitats and establishes a baseline for major changes in forest ecosystems during recovery. Moreover, the result allows the follow up of the surface fuel loading, allowing the evaluation and guidance of restoration measures to remote areas by phased time planning. This case study implements the evaluation of burned areas that suffered successive wildfires in Portugal mainland during the summer of 2017, killing more than 60 people. The goal is to show that this evaluation can be done with remote sense data free of charges in a simple laptop, with open-source software, describing the not-so-simple methodology step by step, to make it accessible for local workers in the areas attained, where the availability of information is essential for the immediate planning of mitigation measures, such as restoring road access, allocate funds for the recovery of human dwellings and assess further needs for restoration of the ecological system. Wildfires also devastate forest ecosystems having a direct impact on vegetation cover and killing or driving away the animal population, besides loss of all crops in rural areas that are essential as local resources. The economic interests are also attained, as the pinewood burned becomes useless for the noblest applications, so its value decreases, and resin extraction ends for several years.

Keywords: Image processing, remote sensing, wildfires, burned areas, SENTINEL-2.

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136 Optimizing the Number of Bits/Stage in 10-Bit, 50Ms/Sec Pipelined A/D Converter Considering Area, Speed, Power and Linearity

Authors: P. Prasad Rao, K. Lal Kishore

Abstract:

Pipeline ADCs are becoming popular at high speeds and with high resolution. This paper discusses the options of number of bits/stage conversion techniques in pipelined ADCs and their effect on Area, Speed, Power Dissipation and Linearity. The basic building blocks like op-amp, Sample and Hold Circuit, sub converter, DAC, Residue Amplifier used in every stage is assumed to be identical. The sub converters use flash architectures. The design is implemented using 0.18

Keywords: 1.5 bits/stage, Conversion Frequency, Redundancy Switched Capacitor Sample and Hold Circuit

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135 A Machine Learning Approach for Earthquake Prediction in Various Zones Based on Solar Activity

Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Mujeeb Ur Rehman, Saifur Rahman Sabuj

Abstract:

This paper examines relationships between solar activity and earthquakes, it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity, and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to effect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth

.

Keywords: K-Nearest Neighbour, Support Vector Regression, Random Forest Regression, Long Short-Term Memory Network, earthquakes, solar activity, sunspot number, solar wind, solar flares.

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134 Characterization of an Almond Shell Composite Based on PHBH

Authors: J. Ivorra-Martinez, L. Quiles-Carrillo, J. Gomez-Caturla, T. Boronat, R. Balart

Abstract:

The utilization of almond crop by-products to obtain Poly(3-hydroxybutyrat-co-3-hydroxyhexanoat) (PHBH)-based composites was carried out by using an extrusion process followed by an injection to obtain test samples. To improve the properties of the resulting composite, the incorporation of Oligomer Lactic Acid (OLA 8) as a coupling agent and plasticizer was additionally considered. A characterization process was carried out by the measurement of mechanical properties, thermal properties, surface morphology, and water absorption ability. The use of the almond residue allows obtaining composites based on PHBH with a higher environmental interest and lower cost.

Keywords: Almond shell, PHBH, composite, polymer.

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133 Evaluation of the Impact of Dataset Characteristics for Classification Problems in Biological Applications

Authors: Kanthida Kusonmano, Michael Netzer, Bernhard Pfeifer, Christian Baumgartner, Klaus R. Liedl, Armin Graber

Abstract:

Availability of high dimensional biological datasets such as from gene expression, proteomic, and metabolic experiments can be leveraged for the diagnosis and prognosis of diseases. Many classification methods in this area have been studied to predict disease states and separate between predefined classes such as patients with a special disease versus healthy controls. However, most of the existing research only focuses on a specific dataset. There is a lack of generic comparison between classifiers, which might provide a guideline for biologists or bioinformaticians to select the proper algorithm for new datasets. In this study, we compare the performance of popular classifiers, which are Support Vector Machine (SVM), Logistic Regression, k-Nearest Neighbor (k-NN), Naive Bayes, Decision Tree, and Random Forest based on mock datasets. We mimic common biological scenarios simulating various proportions of real discriminating biomarkers and different effect sizes thereof. The result shows that SVM performs quite stable and reaches a higher AUC compared to other methods. This may be explained due to the ability of SVM to minimize the probability of error. Moreover, Decision Tree with its good applicability for diagnosis and prognosis shows good performance in our experimental setup. Logistic Regression and Random Forest, however, strongly depend on the ratio of discriminators and perform better when having a higher number of discriminators.

Keywords: Classification, High dimensional data, Machine learning

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132 A Robust and Efficient Segmentation Method Applied for Cardiac Left Ventricle with Abnormal Shapes

Authors: Peifei Zhu, Zisheng Li, Yasuki Kakishita, Mayumi Suzuki, Tomoaki Chono

Abstract:

Segmentation of left ventricle (LV) from cardiac ultrasound images provides a quantitative functional analysis of the heart to diagnose disease. Active Shape Model (ASM) is widely used for LV segmentation, but it suffers from the drawback that initialization of the shape model is not sufficiently close to the target, especially when dealing with abnormal shapes in disease. In this work, a two-step framework is improved to achieve a fast and efficient LV segmentation. First, a robust and efficient detection based on Hough forest localizes cardiac feature points. Such feature points are used to predict the initial fitting of the LV shape model. Second, ASM is applied to further fit the LV shape model to the cardiac ultrasound image. With the robust initialization, ASM is able to achieve more accurate segmentation. The performance of the proposed method is evaluated on a dataset of 810 cardiac ultrasound images that are mostly abnormal shapes. This proposed method is compared with several combinations of ASM and existing initialization methods. Our experiment results demonstrate that accuracy of the proposed method for feature point detection for initialization was 40% higher than the existing methods. Moreover, the proposed method significantly reduces the number of necessary ASM fitting loops and thus speeds up the whole segmentation process. Therefore, the proposed method is able to achieve more accurate and efficient segmentation results and is applicable to unusual shapes of heart with cardiac diseases, such as left atrial enlargement.

Keywords: Hough forest, active shape model, segmentation, cardiac left ventricle.

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