Search results for: forest disturbance

Authors: Chakkrit Poonpakdee, Jing-Hua Tzen, Ya-Zhen Huang, Yao-Tung Lin

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Potassium (K) is a known macro nutrient and essential element for plant growth. Single leaching and modified sequential extraction schemes have been developed to estimate the relative phase associations of soil samples. The sequential extraction process is a step in analyzing the partitioning of metals affected by environmental conditions, but it is not a tool for estimation of K bioavailability. While, traditional single leaching method has been used to classify K speciation for a long time, it depend on its availability to the plants and use for potash fertilizer recommendation rate. Clay mineral in soil is a factor for controlling soil fertility. The change of the micro-structure of clay minerals during various environment (i.e. swelling or shrinking) is characterized using Transmission X-Ray Microscopy (TXM). The objective of this study are to 1) compare the distribution of K speciation between single leaching and sequential extraction process 2) determined clay particle flocculation structure before/after suspension with K+ using TXM. Four tropical soil samples: farming without K fertilizer (10 years), long term applied K fertilizer (10 years; 168-240 kg K2O ha-1 year-1), red soil (450-500 kg K2O ha-1 year-1) and forest soil were selected. The results showed that the amount of K speciation by single leaching method were high in mineral K, HNO3 K, Non-exchangeable K, NH4OAc K, exchangeable K and water soluble K respectively. Sequential extraction process indicated that most K speciations in soil were associated with residual, organic matter, Fe or Mn oxide and exchangeable fractions and K associate fraction with carbonate was not detected in tropical soil samples. In farming long term applied K fertilizer and red soil were higher exchangeable K than farming long term without K fertilizer and forest soil. The results indicated that one way to increase the available K (water soluble K and exchangeable K) should apply K fertilizer and organic fertilizer for providing available K. The two-dimension of TXM image of clay particles suspension with K+ shows that the aggregation structure of clay mineral closed-void cellular networks. The porous cellular structure of soil aggregates in 1 M KCl solution had large and very larger empty voids than in 0.025 M KCl and deionized water respectively. TXM nanotomography is a new technique can be useful in the field as a tool for better understanding of clay mineral micro-structure.

Keywords: potassium, sequential extraction process, clay mineral, TXM

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Authors: Aleksandr A. Gajour, Vladimir G. Merzlikin, Vladimir I. Veselov

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This paper refers to the analysis of the characteristics of industrial and lifestyle facilities heat- energy objects as a part of the thermal envelope of Earth's surface for inclusion in any database of economic forecasting. The idealized model of the Earth's surface is discussed. This model gives the opportunity to obtain the energy equivalent for each element of terrain and world ocean. Energy efficiency criterion of comfortable human existence is introduced. Dynamics of changes of this criterion offers the possibility to simulate the possible technogenic catastrophes with the spontaneous industrial development of the certain Earth areas. Calculated model with the confirmed forecast of the Gulf Stream freezing in the polar regions in 2011 due to the heat-energy balance disturbance for the oceanic subsurface oil polluted layer is given. Two opposing trends of human development under limited and unlimited amount of heat-energy resources are analyzed.

Keywords: Earth's surface, heat-energy consumption, energy criteria, technogenic catastrophes

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Authors: Badr M. Alshammari, T. Guesmi

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In this paper, the concept of a non-dominated sorting multi-objective particle swarm optimization with local search (NSPSO-LS) is presented for the optimal design of multimachine power system stabilizers (PSSs). The controller design is formulated as an optimization problem in order to shift the system electromechanical modes in a pre-specified region in the s-plan. A composite set of objective functions comprising the damping factor and the damping ratio of the undamped and lightly damped electromechanical modes is considered. The performance of the proposed optimization algorithm is verified for the 3-machine 9-bus system. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and superiority of the NSPSO-LS algorithm in tuning PSSs over a wide range of loading conditions and large disturbance compared to the classic PSO technique and genetic algorithms.

Keywords: multi-objective optimization, particle swarm optimization, power system stabilizer, low frequency oscillations

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Authors: O. P. Tripathi, P. L. Verma

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Coronal Mass Ejections (CMEs) are mostly reached on Earth from 1 to 5 days from the Sun. As a consequence, slow CMEs are accelerated toward the speed of solar wind and fast CMEs are decelerated toward the speed of the solar wind. Coronal mass ejections (CMEs) are bursts of solar material i.e. clouds of plasma and magnetic fields that shoot off the sun’s surface. Other solar events include solar wind streams that come from the coronal holes on the Sun and solar energetic particles that are primarily released by CMEs. We have studied geomagnetic storms (DST ≤ - 80nT) during 1997-2012 with halo and partial halo coronal mass ejections and found that 73.28% CMEs (halo and partial halo coronal mass ejections) are associated with geomagnetic storms. The association rate of halo and partial halo coronal mass ejections are found 67.06% and 32.94% with geomagnetic storms respectively. We have also determined positive co-relation between magnitude of geomagnetic storms and speed of coronal mass ejection with correlation co-efficient 0.23.

Keywords: geomagnetic storms, coronal mass ejections (CMEs), disturbance storm time (Dst), interplanetary magnetic field (IMF)

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Authors: Javad Abdi, Azam Famil Khalili

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Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Hritik Bhattarai

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Land use and land cover play a crucial role in preserving and managing Earth's natural resources. Various factors, such as economic, demographic, social, cultural, technological, and environmental processes, contribute to changes in land use and land cover (LULC). Rupandehi District is significantly influenced by a combination of driving forces, including its geographical location, rapid population growth, economic opportunities, globalization, tourism activities, and political events. Urbanization and urban growth in the region have been occurring in an unplanned manner, with internal migration and natural population growth being the primary contributors. Internal migration, particularly from neighboring districts in the higher and lower Himalayan regions, has been high, leading to increased population growth and density. This study utilizes geospatial technology, specifically geographic information system (GIS), to analyze and illustrate the land cover and land use changes in the Rupandehi district for the years 2009 and 2019, using freely available Landsat images. The identified land cover categories include built-up area, cropland, Das-Gaja, forest, grassland, other woodland, riverbed, and water. The statistical analysis of the data over the 10-year period (2009-2019) reveals significant percentage changes in LULC. Notably, Das-Gaja shows a minimal change of 99.9%, while water and forest exhibit increases of 34.5% and 98.6%, respectively. Riverbed and built-up areas experience changes of 95.3% and 39.6%, respectively. Cropland and grassland, however, show concerning decreases of 102.6% and 140.0%, respectively. Other woodland also indicates a change of 50.6%. The most noteworthy trends are the substantial increase in water areas and built-up areas, leading to the degradation of agricultural and open spaces. This emphasizes the urgent need for effective urban planning activities to ensure the development of a sustainable city. While Das-Gaja seems unaffected, the decreasing trends in cropland and grassland, accompanied by the increasing built-up areas, are unsatisfactory. It is imperative for relevant authorities to be aware of these trends and implement proactive measures for sustainable urban development.

Keywords: land use and land cover, geospatial, urbanization, geographic information system, sustainable urban development

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Authors: Sarah Okende

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It is universally recognized that the forests of the Congo Basin remain a common good and a complex ecosystem, and insufficiently known. Historically and throughout the world, forests have been valued for the multiple products and benefits they provide. In addition to their major role in the conservation of global biodiversity and in the fight against climate change, these forests also have an essential role in the regional and global ecology. This is particularly the case of the Luki Biosphere Reserve, a highly diversified evergreen Guinean-Congolese rainforest. Despite the efforts of sustainable management of the said reserve, the understanding of the place occupied by the soil under the influence of the latter does not seem to be an interesting subject for the general public or even scientists. The Luki biosphere reserve is located in the west of the DRC, more precisely in the south-east of Mayombe Congolais, in the province of Bas-Congo. The vegetation of the Luki Biosphere Reserve is very heterogeneous and diversified. It ranges from grassy formations to semi-evergreen dense humid forests, passing through edaphic formations on hydromorphic soils (aquatic and semi-aquatic vegetation; messicole and segetal vegetation; gascaricole vegetation; young secondary forests with Musanga cercropioides, Xylopia aethiopica, Corynanthe paniculata; mature secondary forests with Terminalia superba and Hymenostegia floribunda; primary forest with Prioria balsamifera; climax forests with Gilbertiodendron dewevrei, and Gilletiodendron kisantuense). Field observations and reading of previous and up-to-date work carried out in the Luki biosphere reserve are the methodological approaches for this study, the aim of which is to show the impact of soil types in determining the varieties of vegetation. The results obtained prove that the four different types of soil present (purplish red soils, developing on amphibolites; red soils, developed on gneisses; yellow soils occurring on gneisses and quartzites; and alluvial soils, developed on recent alluvium) have a major influence apart from other environmental factors on the determination of different facies of the vegetation of the Luki Biosphere Reserve. In conclusion, the Luki Biosphere Reserve is characterized by a wide variety of biotopes determined by the nature of the soil, the relief, the microclimates, the action of man, or the hydrography. Overall management (soil, biodiversity) in the Luki Biosphere Reserve is important for maintaining the ecological balance.

Keywords: soil, biodiversity, forest, Luki, rainforest

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Authors: Jeremy Johnson, Craig Nitschke, Luke Kelly

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Fire regimes, climate and topographic gradients interact to influence ecosystem structure and function across fire-prone, montane landscapes worldwide. Biota have developed a range of adaptations to historic fire regime thresholds, which allow them to persist in these environments. In south-eastern Australia, a signal of fire regime changes is emerging across these landscapes, and anthropogenic climate change is likely to be one of the main drivers of an increase in burnt area and more frequent wildfire over the last 25 years. This shift has the potential to modify vegetation structure and composition at broad scales, which may lead to landscape patterns to which biota are not adapted, increasing the likelihood of local extirpation of some mammal species. This study aimed to address concerns related to the influence of abrupt changes in fire regimes on mammal populations in montane landscapes. It first examined the impact of climate, topography, and vegetation on fire patterns and then explored the consequences of these changes on mammal populations and their habitats. Field studies were undertaken across diverse vegetation, fire severity and fire frequency gradients, utilising camera trapping and passive acoustic monitoring methodologies and the collection of fine-scale vegetation data. Results show that drought is a primary contributor to fire regime shifts at the landscape scale, while topographic factors have a variable influence on wildfire occurrence at finer scales. Frequent, high severity wildfire influenced forest structure and composition at broad spatial scales, and at fine scales, it reduced occurrence of hollow-bearing trees and promoted coarse woody debris. Mammals responded differently to shifts in forest structure and composition depending on their habitat requirements. This study highlights the complex interplay between fire regimes, environmental gradients, and biotic adaptations across temporal and spatial scales. It emphasizes the importance of understanding complex interactions to effectively manage fire-prone ecosystems in the face of climate change.

Keywords: fire, ecology, biodiversity, landscape ecology

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: M. S. Sarkar, J. A. Johnson, S. Sen, G. K. Saha, K. Ramesh

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There is growing recognition of several important roles played by tigers for maintaining sustainable biodiversity at diverse ecosystems in South and South-East Asia. Only <3200 individuals are left in the wild because of poaching and habitat loss. Thus, restoring wild population is an emerging as well as important conservation initiative, but such efforts still remain challenging due to their elusive and solitary behavior. After careful translocation of few individuals, how reintroduced individuals colonize into suitable habitat and achieve stable stage population through reproduction is vital information for forest managers and policy makers of its 13 distribution range countries. Four wild and two captive radio collared tigers were reintroduced at Panna Tiger Reserve, Madhya-pradesh, India during 2009-2014. We critically examined their settlement behavior and population growth over the period. Results from long term telemetry data showed that male explored larger areas rapidly in short time span, while females explored small area in long time period and with significant high rate of movement in both sexes during exploratory period. Significant difference in home range sizes of tigers were observed in exploratory and settlement period. Though all reintroduced tigers preferred densely vegetated undisturbed forest patches within the core area of tiger reserve, a niche based k select analysis showed that individual variation in habitat selection was prominent among reintroduced tigers. Total 18 litter of >42 known cubs were born with low mortality rate, high maternity rate, high observed growth rate and short generation time in both the sexes. The population achieved its carrying capacity in a very short time span, marking success of this current tiger conservation programme. Our study information could provide significant insights on the tiger biology of translocated tigers with implication for future conservation strategies that consider translocation based recovery in their range countries.

Keywords: reintroduction, tiger, home range, demography

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Ç. Erdoğan, T. Turan

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Pediatric cancer patients experience multiple distressing, challenges, physical symptom such as fatigue, pain, sleep disturbance, and balance impairment that continue years after treatment completion. In recent years, yoga is often used in children with cancer to cope with these symptoms. Yoga practice is defined as a unique physical activity that combines physical practice, breath work and mindfulness/meditation. Yoga is an increasingly popular mind-body practice also characterized as a mindfulness mode of exercise. This study aimed to evaluate the impact of yoga intervention of children with cancer. This article planned searching the literature in this field. It has been determined that individualized yoga is feasible and provides benefits for inpatient children, improves health-related quality of life, physical activity levels, physical fitness. After yoga program, children anxiety score decreases significantly. Additionally, individualized yoga is feasible for inpatient children receiving intensive chemotherapy. As a result, yoga is an alternative and complementary medicine that can be safely used in children with cancer.

Keywords: cancer treatment, children, nursing, yoga

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Authors: Kelum N. Manamendra-Arachchi, Kalangi Rodrigo

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Bones, teeth, and shells have been acknowledged over the last two centuries as evidence of chronology, Palaeo-environment, and human activity. Faunal traces are valid evidence of past situations because they have properties that have not changed over long periods of time. Sri Lanka has been known as an Island, which has a diverse variation of prehistoric occupation among ecological zones. Defining the Paleoecology of the past societies has been an archaeological thought developed in the 1960s. It is mainly concerned with the reconstruction from available geological and biological evidence of past biota, populations, communities, landscapes, environments, and ecosystems. Sri Lanka has dealt with this subject and considerable research has been already undertaken. The fossil and material record of Sri Lanka’s Wet Zone tropical forests continues from c. 38,000–34,000 ybp. This early and persistent human fossil, technical, and cultural florescence, as well as a collection of well-preserved tropical-forest rock shelters with associated ' on-site ' Palaeoenvironmental records, makes Sri Lanka a central and unusual case study to determine the extent and strength of early human tropical forest encounters. Excavations carried out in prehistoric caves in the low country wet zone has shown that in the last 50,000 years, the temperature in the lowland rainforests has not exceeded 5 degrees. Based on Semnopithecus Priam (Gray Langur) remains unearned from wet zone prehistoric caves, it has been argued that periods of momentous climate changes during the LGM and Terminal Pleistocene/Early Holocene boundary, with a recognizable preference for semi-open ‘Intermediate’ rainforest or edges. Continuous Genus Acavus and Oligospira occupation along with uninterrupted horizontal pervasive of Canarium sp. (‘kekuna’ nut) have proven that temperatures in the lowland rain forests have not changed by at least 5 oC over the last 50,000 years. Site Catchment or Territorial analysis cannot be no longer defensible, due to time-distance based factors as well as optimal foraging theory failed as a consequences of prehistoric people were aware of the decrease in cost-benefit ratio and located sites, and generally played out a settlement strategy that minimized the ratio of energy expanded to energy produced.

Keywords: palaeo-environment, prehistory, palaeo-ecology, zooarchaeology

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Authors: Radha Rajamma, Susheela Palanisamy

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The use of chemical fertilizers and pesticides has posed a serious threat to the environment, cause disturbance to the soil ecosystem, pollute the water causing serious health problems. The indigenous practices such as herbal spray, phyto-alternatives, etc. offer harmless alternatives in integrated pest management. The use of plant materials has become an integral part of insect pest management because of their cheap and non-toxic nature. Hence an investigation has been made to determine the bio-efficacy of vermiwash and two leaf extracts, Azadirachta indica and Vitex negundo against mealy bug, Paracoccus marginatus. The results on the effect of vermitechnologies on the activity of mealy bug indicated the effectiveness of vermiwash foliar application in suppressing the pest activity. Accumulative mortality of mealy bug increased gradually with the increase of exposure intervals. The combined treatment of vermiwash with Azadirachta indica reported the highest mortality percentage of 96% followed by the individual treatment of leaf extracts. Hence vermiwash was proved to be the most effective in enhancing the potency of mealy bug and decreased LC50 of the target insect.

Keywords: Azadirachta indica, Paracoccus marginatus, vermiwash, Vitex negundo

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Authors: Melis Inalpulat, Levent Genc

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Land Use Land Cover (LULC) changes due to human activities and natural causes have become a major environmental concern. Assessment of temporal remote sensing data provides information about LULC impacts on environment. Land Surface Temperature (LST) is one of the important components for modeling environmental changes in climatological, hydrological, and agricultural studies. In this study, LULC changes (September 7, 1984 and July 8, 2014) especially in agricultural lands together with population changes (1985-2014) and LST status were investigated using remotely sensed and census data in South Marmara Watershed, Turkey. LULC changes were determined using Landsat TM and Landsat OLI data acquired in 1984 and 2014 summers. Six-band TM and OLI images were classified using supervised classification method to prepare LULC map including five classes including Forest (F), Grazing Land (G), Agricultural Land (A), Water Surface (W), and Residential Area-Bare Soil (R-B) classes. The LST image was also derived from thermal bands of the same dates. LULC classification results showed that forest areas, agricultural lands, water surfaces and residential area-bare soils were increased as 65751 ha, 20163 ha, 1924 ha and 20462 ha respectively. In comparison, a dramatic decrement occurred in grazing land (107985 ha) within three decades. The population increased % 29 between years 1984-2014 in whole study area. Along with the natural causes, migration also caused this increase since the study area has an important employment potential. LULC was transformed among the classes due to the expansion in residential, commercial and industrial areas as well as political decisions. In the study, results showed that agricultural lands around the settlement areas transformed to residential areas in 30 years. The LST images showed that mean temperatures were ranged between 26-32 °C in 1984 and 27-33 °C in 2014. Minimum temperature of agricultural lands was increased 3 °C and reached to 23 °C. In contrast, maximum temperature of A class decreased to 41 °C from 44 °C. Considering temperatures of the 2014 R-B class and 1984 status of same areas, it was seen that mean, min and max temperatures increased by 2 °C. As a result, the dynamism of population, LULC and LST resulted in increasing mean and maximum surface temperatures, living spaces/industrial areas and agricultural lands.

Keywords: census data, landsat, land surface temperature (LST), land use land cover (LULC)

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Authors: Masoomeh Alsadat Mirshafaei

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The present study aims to explore the effect of an 8-week aerobic training regimen combined with cinnamon extract on serum irisin and leptin levels in insulin-resistant rats. Additionally, this research leverages various machine learning (ML) and deep learning (DL) algorithms to model the complex interdependencies between exercise, nutrition, and metabolic markers, offering a groundbreaking approach to obesity and diabetes research. Forty-eight Wistar rats were selected and randomly divided into four groups: control, training, cinnamon, and training cinnamon. The training protocol was conducted over 8 weeks, with sessions 5 days a week at 75-80% VO2 max. The cinnamon and training-cinnamon groups were injected with 200 ml/kg/day of cinnamon extract. Data analysis included serum data, dietary intake, exercise intensity, and metabolic response variables, with blood samples collected 72 hours after the final training session. The dataset was analyzed using one-way ANOVA (P<0.05) and fed into various ML and DL models, including Support Vector Machines (SVM), Random Forest (RF), and Convolutional Neural Networks (CNN). Traditional statistical methods indicated that aerobic training, with and without cinnamon extract, significantly increased serum irisin and decreased leptin levels. Among the algorithms, the CNN model provided superior performance in identifying specific interactions between cinnamon extract concentration and exercise intensity, optimizing the increase in irisin and the decrease in leptin. The CNN model achieved an accuracy of 92%, outperforming the SVM (85%) and RF (88%) models in predicting the optimal conditions for metabolic marker improvements. The study demonstrated that advanced ML and DL techniques could uncover nuanced relationships and potential cellular responses to exercise and dietary supplements, which is not evident through traditional methods. These findings advocate for the integration of advanced analytical techniques in nutritional science and exercise physiology, paving the way for personalized health interventions in managing obesity and diabetes.

Keywords: aerobic training, cinnamon extract, insulin resistance, irisin, leptin, convolutional neural networks, exercise physiology, support vector machines, random forest

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Authors: Phuc D. Nguyen, Kristy L. Hansen, Branko Zajamsek

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The existence of special characteristics of wind farm noise such as amplitude modulation (AM) contributes significantly to annoyance, which could ultimately result in sleep disturbance and other adverse health effects for residents living near wind farms. In order to detect and quantify this phenomenon, several methods have been developed which can be separated into three types: time-domain, frequency-domain and hybrid methods. However, due to a lack of systematic validation of these methods, it is still difficult to select the best method for identifying AM. Furthermore, previous comparisons between AM methods have been predominantly qualitative or based on synthesised signals, which are not representative of the actual noise. In this study, a comparison between methods for detecting and quantifying AM has been carried out. The results are based on analysis of real noise data which were measured at a wind farm in South Australia. In order to evaluate the performance of these methods in terms of detecting AM, an approach has been developed to select the most successful method of AM detection. This approach uses a receiver operating characteristic (ROC) curve which is based on detection of AM in audio files by experts.

Keywords: amplitude modulation, wind farm noise, ROC curve

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Authors: Dahiru Muhammad, Muhammad Danladi, Muhammad Yahaya, Adamu Garba

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This paper put forward the potentialities of biomass for energy as divers means of sustainable economic development. The paper explains, in brief, the ways or methods that are used to generate energy from biomass, such as combustion, pyrolysis, anaerobic, and gasification, and also how biomass for energy can enhance the sustainable economic development of a Nation. Currently, the nation depends on fossil fuels as a sources of generating its energy which is finite and deflectable with time, while on the other hand, biomass is an alternative and endless product which consists of forest biomass, agricultural residues, and energy crops. Finally, recommendations and conclusion were made on the role of biomass for energy in improving sustainable economic development.

Keywords: biomass, energy, sustainability, economic

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Authors: Seyed Jamal Haddadi, M. Reza Mehranpour, Roya Sadat Mortazavi, Zahra Sadat Mortazavi

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Principal aim of this research is trajectory tracking, attitude and position control scheme in real flight mode by an Octorotor helicopter. For more stability, in this Unmanned Aerial Vehicle (UAV), number of motors is increased to eight motors which end of each arm installed two coaxial counter rotating motors. Dynamic model of this Octorotor includes of motion equation for translation and rotation. Utilized controller is proportional-integral-derivative (PID) control loop. The proposed controller is designed such that to be able to attenuate an effect of external wind disturbance and guarantee stability in this condition. The trajectory is determined by a Global Positioning System (GPS). Also an ARM CortexM4 is used as microprocessor. Electronic board of this UAV designed as able to records all of the sensors data, similar to an aircraft black box in external memory. Finally after auto landing of Octorotor, flight data is shown in MATLAB software and Experimental results of the proposed controller show the effectiveness of our approach on the Autonomous Quadrotor in real conditions.

Keywords: octorotor, design, PID controller, autonomous, trajectory tracking

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Authors: Mahmoud Samkan

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In this paper, the design and assessment of new coordination between Power System Stabilizers (PSSs) and Static Var Compensator (SVC) in a multimachine power system via statistical method are proposed. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is handled as an optimization problem. The Bacterial Swarming Optimization (BSO), which synergistically couples the Bacterial Foraging (BF) with the Particle Swarm Optimization (PSO), is employed to seek for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is enhanced. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is executed to validate the robustness of coordinated controller versus uncoordinated one.

Keywords: SVC, PSSs, multimachine power system, coordinated design, bacteria swarm optimization, statistical assessment

Procedia PDF Downloads 378

Authors: Dahiru Muhammad, Muhammad Danladi, Adamu Garba, Muhammad Yahaya

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This paper put forward the potentialities of biomass for energy as divers means of sustainable economic development. The paper explains in brief the ways or methods that are used to generate energy from biomass, such as combustion, pyrolysis, anaerobic, and gasification, and also how biomass for energy can enhance the sustainable economic development of a Nation. Currently, the nation depends on fossil fuels as a sources of generating its energy which is finite and deflectable with time, while on the other hand, biomass is an alternative and endless product which consists of a forest biomass, agricultural residues, and energy crops. Finally, recommendations and conclusion were made on the role of biomass for energy in improving sustainable economic development.

Keywords: biomass, energy, sustainable, economic, development

Procedia PDF Downloads 129

Authors: Muhammad Awais

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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 407

Authors: Nancy Daly

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Migrant youth who have experienced traumatic events in their home countries or in their passage to the United States may require interventions or formal services to support varying levels and types of needs. The manner in which such youth are engaged and evaluated, as well as the framework of evaluation, can impact their educational services and placement. Evidenced-based trauma-informed practices that engage and support migrant youth serve as an important bridge to stabilization; however, ensuring long-term growth may require a range of integrated services, including special education and mental health services. Special education evaluations which consider the eligibility of Emotional Disturbance for migrant youth must carefully weigh issues of mental health needs against the exclusionary criteria of lack of access to education, limited language skills, as well as other environmental factors. Case studies of recently arrived migrant youth reveal both commonalities and differences in types and levels of need which underscores the importance of adept evaluation and case management to ensure the provision of services that support growth and resiliency.

Keywords: migrant youth, trauma-informed care, mental health services, special education

Procedia PDF Downloads 126

Authors: Bryan Clark B. Hernandez, Eugene C. Herrera, Kazuo Nadaoka

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Mangrove forests thriving in intertidal zones in tropical and subtropical regions of the world offer a range of ecosystem services including carbon storage and sequestration. They can regulate the detrimental effects of climate change due to carbon releases two to four times greater than that of mature tropical rainforests. Moreover, they are effective natural defenses against storm surges and tsunamis. However, their proliferation depends significantly on the prevailing hydroperiod at the coast. In the Philippines, these coastal ecosystems have been severely threatened with a 50% decline in areal extent observed from 1918 to 2010. The highest decline occurred in 1950 - 1972 when national policies encouraged the development of fisheries and aquaculture. With the intensive land use conversion upstream, changes in the freshwater-saltwater envelope at the coast may considerably impact mangrove growth conditions. This study investigates a developing urban watershed in Kalibo, Aklan province with a 220-hectare mangrove forest replanted for over 30 years from coastal mudflats. Since then, the mangrove forest was sustainably conserved and declared as protected areas. Hybrid land cover classification technique was used to classify Landsat images for years, 1990, 2010, and 2017. Digital elevation model utilized was Interferometric Synthetic Aperture Radar (IFSAR) with a 5-meter resolution to delineate the watersheds. Using numerical modelling techniques, the hydrologic and hydraulic analysis of the influence of land cover change to flow and sediment dynamics was simulated. While significant land cover change occurred upland, thereby increasing runoff and sediment loads, the mangrove forests abundance adjacent to the coasts for the urban watershed, was somehow sustained. However, significant alteration of the coastline was observed in Kalibo through the years, probably due to the massive land-use conversion upstream and significant replanting of mangroves downstream. Understanding the hydrologic-hydraulic response of these watersheds to change land cover is essential to helping local government and stakeholders facilitate better management of these mangrove ecosystems.

Keywords: coastal mangroves, hydrologic model, land cover change, Philippines

Procedia PDF Downloads 123

Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper

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In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l₂-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.

Keywords: linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control

Procedia PDF Downloads 395

Authors: O. P. Popoola, O. A. Alawode, M. O. Olayiwola, A. M. Oladele

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This research work is based on using discriminant analysis to forecast crime rate in Nigeria between 1996 and 2008. The work is interested in how gender (male and female) relates to offences committed against the government, against other properties, disturbance in public places, murder/robbery offences and other offences. The data used was collected from the National Bureau of Statistics (NBS). SPSS, the statistical package was used to analyse the data. Time plot was plotted on all the 29 offences gotten from the raw data. Eigenvalues and Multivariate tests, Wilks’ Lambda, standardized canonical discriminant function coefficients and the predicted classifications were estimated. The research shows that the distribution of the scores from each function is standardized to have a mean O and a standard deviation of 1. The magnitudes of the coefficients indicate how strongly the discriminating variable affects the score. In the predicted group membership, 172 cases that were predicted to commit crime against Government group, 66 were correctly predicted and 106 were incorrectly predicted. After going through the predicted classifications, we found out that most groups numbers that were correctly predicted were less than those that were incorrectly predicted.

Keywords: discriminant analysis, DA, multivariate analysis of variance, MANOVA, canonical correlation, and Wilks’ Lambda

Procedia PDF Downloads 471

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

Procedia PDF Downloads 81

Authors: Kalangi Rodrigo

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Sri Lanka has been known as an island which has a diverse variety of prehistoric occupation among ecological zones. Defining the paleoecology of the past societies has been an archaeological thought developed in the 1960s. It is mainly concerned with the reconstruction from available geological and biological evidence of past biota, populations, communities, landscapes, environments, and ecosystems. Sri Lanka has dealt with this subject, and considerable research has been already undertaken. The fossil and material record of Sri Lanka’s Wet Zone tropical forests continues from c. 38,000–34,000 ybp. This early and persistent human fossil, technical, and cultural florescence, as well as a collection of well-preserved tropical-forest rock shelters with associated 'on-site' palaeoenvironmental records, makes Sri Lanka a central and unusual case study to determine the extent and strength of early human tropical forest encounters. Excavations carried out in prehistoric caves in the low country wet zone has shown that in the last 50,000 years, the temperature in the lowland rainforests has not exceeded 5°C. When taking Batadombalena alone, the entire seven layers have yielded an uninterrupted occupation of Acavus sp and Canerium zeylanicum, a plant that grows in the middle of the rainforest. Acavus, which is highly sensitive to rainforest ecosystems, has been well documented in many of the lowland caves, confirming that the wetland rainforest environment has remained intact at least for the last 50,000 years. If the dry and arid conditions in the upper hills regions affected the wet zone, the Tufted Gray Lunger (semnopithecus priam), must also meet with the prehistoric caves in the wet zone thrown over dry climate. However, the bones in the low country wet zone do not find any of the fragments belonging to Turfed Gray Lunger, and prehistoric human consumption is bestowed with purple-faced leaf monkey (Trachypithecus vetulus) and Toque Macaque (Macaca Sinica). The skeletal remains of Lyriocephalus scutatus, a full-time resident in rain forests, have also been recorded among lowland caves. But, in zoological terms, these remains may be the remains of the Barking deer (Muntiacus muntjak), which is currently found in the wet zone. For further investigations, the mtDNA test of genetic diversity (Bottleneck effect) and pollen study from lowland caves should determine whether the wet zone climate has persisted over the last 50,000 years, or whether the dry weather affected in the mountainous region has invaded the wet zone.

Keywords: paleoecology, prehistory, zooarchaeology, reconstruction, palaeo-climate

Procedia PDF Downloads 141

Authors: R. P. Leite, M. A. S. Diamante, F. R. Gadelha, L. H. G. Ribeiro, H. Dolder

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Although industrial processes are the major contributor to increase cadmium environmental concentration, phosphate fertilizers have significantly increased its percentage in soil, making food and tobacco the main source of cadmium exposure to humans. Worldwide population surveys have shown a consistent link between environmental exposure to cadmium and several idiopathic pathologies among non-occupationally exposed subjects. Epidemiological investigations and animal experiments paralleling human chronic exposure to environmental cadmium are, therefore of major importance for establishing a relationship between cadmium and several pathologies of unspecific etiology. In the present study, Wistar rats were randomly divided into three different groups and subjected to increasing cadmium doses ranging between low to moderate environmentally realistic doses. At the end of the treatment, the testis was dissected and subjected to biochemical and histological analyses. Our data show a significant disturbance in the cellular oxidative status for all cadmium-treated group, accompanied by morphological changes in blood vessel lumen.

Keywords: cadmium, blood vessel, environmental realistic doses, oxidative stress

Procedia PDF Downloads 489