Search results for: Random Forest

Authors: Priyanka Sharma, Ranjita Das, Mohan C. Kalita, Debajit Thakur

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Background: Actinomycetes are the richest source of novel bioactive secondary metabolites such as antibiotics, enzymes and other therapeutically useful metabolites with diverse biological activities. The present study aims at the antimicrobial potential and genetic diversity of culturable Actinomycetes isolated from protected forest ecosystems of Assam which includes Kaziranga National Park (26°30˝-26°45˝N and 93°08˝-93°36˝E), Pobitora Wildlife Sanctuary (26º12˝-26º16˝N and 91º58˝-92º05˝E) and Gibbon Wildlife Sanctuary (26˚40˝-26˚45˝N and 94˚20˝-94˚25˝E) which are located in the North-eastern part of India. Northeast India is a part of the Indo-Burma mega biodiversity hotspot and most of the protected forests of this region are still unexplored for the isolation of effective antibiotic-producing Actinomycetes. Thus, there is tremendous possibility that these virgin forests could be a potential storehouse of novel microorganisms, particularly Actinomycetes, exhibiting diverse biological properties. Methodology: Soil samples were collected from different ecological niches of the protected forest ecosystems of Assam and Actinomycetes were isolated by serial dilution spread plate technique using five selective isolation media. Preliminary screening of Actinomycetes for an antimicrobial activity was done by spot inoculation method and the secondary screening by disc diffusion method against several test pathogens, including multidrug resistant Staphylococcus aureus (MRSA). The strains were further screened for the presence of antibiotic synthetic genes such as type I polyketide synthases (PKS-I), type II polyketide synthases (PKS-II) and non-ribosomal peptide synthetases (NRPS) genes. Genetic diversity of the Actinomycetes producing antimicrobial metabolites was analyzed through 16S rDNA-RFLP using Hinf1 restriction endonuclease. Results: Based on the phenotypic characterization, a total of 172 morphologically distinct Actinomycetes were isolated and screened for antimicrobial activity by spot inoculation method on agar medium. Among the strains tested, 102 (59.3%) strains showed activity against Gram-positive bacteria, 98 (56.97%) against Gram-negative bacteria, 92 (53.48%) against Candida albicans MTCC 227 and 130 (75.58%) strains showed activity against at least one of the test pathogens. Twelve Actinomycetes exhibited broad spectrum antimicrobial activity in the secondary screening. The taxonomic identification of these twelve strains by 16S rDNA sequencing revealed that Streptomyces was found to be the predominant genus. The PKS-I, PKS-II and NRPS genes detection indicated diverse bioactive products of these twelve Actinomycetes. Genetic diversity by 16S rDNA-RFLP indicated that Streptomyces was the dominant genus amongst the antimicrobial metabolite producing Actinomycetes. Conclusion: These findings imply that Actinomycetes from the protected forest ecosystems of Assam, India, are a potential source of bioactive secondary metabolites. These areas are as yet poorly studied and represent diverse and largely unscreened ecosystem for the isolation of potent Actinomycetes producing antimicrobial secondary metabolites. Detailed characterization of the bioactive Actinomycetes as well as purification and structure elucidation of the bioactive compounds from the potent Actinomycetes is the subject of ongoing investigation. Thus, to exploit Actinomycetes from such unexplored forest ecosystems is a way to develop bioactive products.

Keywords: Actinomycetes, antimicrobial activity, forest ecosystems, RFLP

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Authors: David Delpine Leila, Demnyo Sunita Femi, Musa David Garkida, Elisha Emmanuel Barde, Emmanuel Allahnanan, Yani Julius Philip

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Birds are among the key components of the earth’s biodiversity and the most diverse and evolutionarily successful groups of animals. The weaverbirds are a large family of birds found mostly in Africa, with a few species found in southern Asia and the West Indian Ocean islands. This study assessed the diversity and abundance of weaver birds and their allies within and around Ngel-Nyaki Forest Reserve in Yelwa, Sardauna Local Government Area of Taraba State, Nigeria. A total of 602 weaver birds and allies’ bird species were recorded using the Point Count Line Transect. The data collected during the research period were analyzed using simple percentages, and diversity was calculated using the Shannon Wiener Diversity Index. The fenced (ungrazed area) was more abundant with 351 individuals while the unfenced (grazed area) was less abundant with 251 individuals recorded. In the fenced (ungrazed area), Yellow Bishop (Euplectes capensis) had the highest abundance of (102; 29.01%), followed by Village Weaver (Ploceus cucullatus) (80; 22.79%), then Vieillot's Black Weaver (Ploceus nigerrimus) (40; 11.42%), Red-collard Widowbird (Ploceus ardens) (6; 1.71%), Dark-backed Weaver (5; 1.42%) and the least was Hartlaub Marsh Widowbird (1; 0.28%) while in the unfenced (grazed area), the Village weaver (Ploceus cucullatus) (85; 33.86%) was the most abundant, followed by Spectacled Weaver (Ploceus ocularis) (36; 14.34%), then Yellow Bishop (Euplectes capensis) (30; 11.95%), Baglefecht Weaver (Ploceus baglafecht) (23; 9.16%), Bannerman’s Weaver (Ploceus bannermani) (17; 6.77%) and the least was Yellow-mantled Widowbird (Euplectes macroura) (5; 1.99%). In terms of diversity, there were more weaver bird species in the fenced area with a Shannon Wiener Diversity Index of (Hˈ 2.03417) than in the unfenced area with a Shannon Wiener Diversity Index of (Hˈ 1.862671). The Shannon Wiener Diversity Index in both fenced and unfenced areas is significant. There was more abundance of bird species in the fenced area than in the unfenced area of the Forest Reserve. Thorough research should be conducted on the abundance and diversity of weavers and their allies because we were only able to access 4 km2 out of 46 km2 of land available, according to the Annual Report of Ngel-Nyaki Forest Reserve of 2020. It shows that there are many species of weaver birds and their allies, such as the Black-billed Weaver (Ploceus melanogaster) and the Red-billed Quelea (Quelea quelea), which are available within the reserve.

Keywords: abundance, diversity, weaver birds, allies, Ngel-Nyaki

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Authors: Nursel Koyuncu, Nihal Ata Tutkun

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Frailty model is a survival model that takes into account the unobserved heterogeneity for exploring the relationship between the survival of an individual and several covariates. In the recent years, proposed survival models become more complex and this feature causes convergence problems especially in large data sets. Therefore selection of sample from these big data sets is very important for estimation of parameters. In sampling literature, some authors have defined new sampling schemes to predict the parameters correctly. For this aim, we try to see the effect of sampling design in semi-parametric frailty model. We conducted a simulation study in R programme to estimate the parameters of semi-parametric frailty model for different sample sizes, censoring rates under classical simple random sampling and ranked set sampling schemes. In the simulation study, we used data set recording 17260 male Civil Servants aged 40–64 years with complete 10-year follow-up as population. Time to death from coronary heart disease is treated as a survival-time and age, systolic blood pressure are used as covariates. We select the 1000 samples from population using different sampling schemes and estimate the parameters. From the simulation study, we concluded that ranked set sampling design performs better than simple random sampling for each scenario.

Keywords: frailty model, ranked set sampling, efficiency, simple random sampling

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Authors: Adeyemi A. Ajisebiolola

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This study examined people’s responses to demand and consumption of herbal medicines in Nigeria. It also assessed people’s evaluation of the effectiveness of the existing medicines on the treatment of ailments and encouraging forest products utilization for greener future in terms of healthcare delivery. Two Local Government Areas, namely Ido and Ibadan Northwest were adopted for the study; Ido is characterized by rural populace and Ibadan Northwest by urban populace. Out of 500 questionnaires randomly administered to the households in the two local government areas of study, 481 (96.2%) were recovered. Statistical analysis employed showed that people were beginning to understand the importance of herbal medicines in Nigeria as majority of the households use herbal medicines to treat various ailments. Among the major problems encountered by the respondents are lack of precise dosage and adequate preservation methods. It was recommended that Forestry Research Institutes in Nigeria should be deeply involved in the findings on medicinal plants, package them into products and make them available to the society for sustainable healthcare management and greener future of the nation.

Keywords: demand and consumption, forest products, herbal medicines, Nigeria

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Authors: Halil Ibrahim Demir, Tarık Cakar, Ibrahim Cil, Muharrem Dugenci, Caner Erden

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Conventionally, process planning, scheduling, and due-date assignment functions are performed separately and sequentially. The interdependence of these functions requires integration. Although integrated process planning and scheduling, and scheduling with due date assignment problems are popular research topics, only a few works address the integration of these three functions. This work focuses on the integration of process planning, WMS scheduling, and WPPW due date assignment. Another novelty of this work is the use of a weighted due date assignment. In the literature, due dates are generally assigned without considering the importance of customers. However, in this study, more important customers get closer due dates. Typically, only tardiness is punished, but the JIT philosophy punishes both earliness and tardiness. In this study, all weighted earliness, tardiness, and due date related costs are penalized. As no customer desires distant due dates, such distant due dates should be penalized. In this study, various levels of integration of these three functions are tested and genetic search and random search are compared both with each other and with ordinary solutions. Higher integration levels are superior, while search is always useful. Genetic searches outperformed random searches.

Keywords: process planning, weighted scheduling, weighted due-date assignment, genetic algorithm, random search

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Authors: Azita Ramezani, Atousa Ramezani

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In the ever-escalating landscape of windows malware the necessity for pioneering defense strategies turns into undeniable this study introduces an avant-garde approach fusing the capabilities of clustering random forests and support vector machines SVM to combat the intricate web of cyber threats our fusion model triumphs with a staggering accuracy of 98.67 and an equally formidable f1 score of 98.68 a testament to its effectiveness in the realm of windows malware defense by deciphering the intricate patterns within malicious code our model not only raises the bar for detection precision but also redefines the paradigm of cybersecurity preparedness this breakthrough underscores the potential embedded in the fusion of diverse analytical methodologies and signals a paradigm shift in fortifying against the relentless evolution of windows malicious threats as we traverse through the dynamic cybersecurity terrain this research serves as a beacon illuminating the path toward a resilient future where innovative fusion models stand at the forefront of cyber threat defense.

Keywords: fusion models, cyber threat defense, windows malware, clustering, random forests, support vector machines (SVM), accuracy, f1-score, cybersecurity, malicious code detection

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Authors: Pantana Tor-Ngern

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In the global water cycle, tree water use (Tr) largely contributes to evapotranspiration which is the total amount of water evaporated from terrestrial ecosystems to the atmosphere, regulating climates. Tree water use responds to environmental factors, including atmospheric humidity and sunlight (represented by vapor pressure deficit or VPD and photosynthetically active radiation or PAR, respectively) and soil moisture. In forests, Tr responses to such factors depend on species and their spatial and temporal variations. Tropical forests in Southeast Asia (SEA) have experienced land-use conversion from abandoned agricultural practices, resulting in patches of forests at different stages including old-growth and secondary forests. Because the inherent structures, such as canopy height and tree density, significantly vary among forests at different stages and can strongly affect their respective microclimate, Tr and its responses to changing environmental conditions in successional forests may differ. Daily and seasonal variations in the environmental factors may exert significant impacts on the respective Tr patterns. Extrapolating Tr data from short periods of days to longer periods of seasons or years can be complex and is important for estimating long-term ecosystem water use which often includes normal and abnormal climatic conditions. Thus, this study aims to investigate the diurnal variation of Tr, using measured sap flux density (JS) data, with changes in VPD in eight evergreen tree species in an old-growth forest (hereafter OF; >200 years old) and a young forest (hereafter YF, <10 years old) in Khao Yai National Park, Thailand. The studied species included Sysygium syzygoides, Aquilaria crassna, Cinnamomum subavenium, Nephelium melliferum, Altingia excelsa in OF, and Syzygium nervosum and Adinandra integerrima in YF. Only Sysygium antisepticum was found in both forest stages. Specifically, hysteresis, which indicates the asymmetrical changes of JS in response to changing VPD across daily timescale, was examined in these species. Results showed no hysteresis in all species in OF, except Altingia excelsa which exhibited a 3-hour delayed JS response to VPD. In contrast, JS of all species in YF displayed one-hour delayed responses to VPD. The OF species that showed no hysteresis indicated their well-coupling of their canopies with the atmosphere, facilitating the gas exchange which is essential for tree growth. The delayed responses in Altingia excelsa in OF and all species in YF were associated with higher JS in the morning than that in the afternoon. This implies that these species were sensitive to drying air, closing stomata relatively rapidly compared to the decreasing atmospheric humidity (VPD). Such behavior is often observed in trees growing in dry environments. This study suggests that detailed investigation of JS at sub-daily timescales is imperative for better understanding of mechanistic responses of trees to the changing climate, which will benefit the improvement of earth system models.

Keywords: sap flow, tropical forest, forest succession, thermal dissipcation probe

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Authors: Azize Serap Tuncer

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Turkey is one of the most outstanding figures among the Mediterranean countries from the natural and historical point at view. It is relatively rich country as regards the flora and vegetation. But at the same time as a result of improper and unplanned usage of the land for centuries, its forests and fertile soils have been exposed to great damages. While rapid and uncontrolled urbanization has important effects on the environment, urban development legislations, have become very unsufficient for the protection of these areas. Some of them have been completely eradicated, and some others have lost their fertility. Besides Turkey has a high main land with a rough surface and its soils areas exposed to heavy erosion. On the other hand as a developing country, it is not willing to endanger the goals of industrialization and avoid foreign direct investment by implementing strict environmental policies. Although this kind of pressure on forestland resources threatens the stability of forest land and land use management, in recent years, there has been an obvious increase in public concern about environmental problems like over global warming, environmental pollution, deforestation and their potential effects on natural resources. To protect the ecological balance and prevention of naturel resources from the unplanned intervention of human-beıng is only possible establishing conservation areas wıth co-operation at the national and the internatıonal levels. This study was carried out to evaluate the relation between urbanization and forestry policies in Turkey. While it elaborates the normative arrangements resulting in power conflicts, it also addresses which shortages and discrepancies are responsible for the said conflicts. The present urban reconstruction and transformation practices and their aesthetic and functional aspects were studied with some examples in a country level and evaluated within the assistance of literature researches, analyses, and observations. Atatürk Forest Farm and ODTU Forest examples were negotiated as two famous cases. Obtained findings were supported by charts and photos.

Keywords: deforestration, environmental policies, metropolitan, pollution, urbanization

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Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

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Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

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Authors: Jaehong Yu, Seoung Bum Kim

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Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

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Authors: Vu H. N. Khue, Marian Pavelka, Georg Jocher, Jiří Dušek, Le T. Son, Bui T. An, Ho Q. Bang, Pham Q. Huong

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Agriculture is an important economic sector of Vietnam, the most popular of which is wet rice cultivation. These activities are also known as the main contributor to the national greenhouse gas. In order to understand more about greenhouse gas exchange in these activities and to investigate the factors influencing carbon cycling and sequestration in these types of ecosystems, since 2019, the first eddy covariance station has been installed in a paddy field in Long An province, Mekong Delta. The station was equipped with state-of-the-art equipment for CO₂ and CH₄ gas exchange and micrometeorology measurements. In this study, data from the station was processed following the ICOS recommendations (Integrated Carbon Observation System) standards for CO₂, while CH₄ was manually processed and gap-filled using a random forest model from methane-gapfill-ml, a machine learning package, as there is no standard method for CH₄ flux gap-filling yet. Finally, the carbon equivalent (Ce) balance based on CO₂ and CH₄ fluxes was estimated. The results show that in 2020, even though a new water management practice - alternate wetting and drying - was applied to reduce methane emissions, the paddy field released 928 g Cₑ.m⁻².yr⁻¹, and in 2021, it was reduced to 707 g Cₑ.m⁻².yr⁻¹. On a provincial level, rice cultivation activities in Long An, with a total area of 498,293 ha, released 4.6 million tons of Cₑ in 2020 and 3.5 million tons of Cₑ in 2021.

Keywords: eddy covariance, greenhouse gas, methane, rice cultivation, Mekong Delta

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Authors: Nguyen Chan Hung, Mai Ngoc Anh, Nguyen Xuan Ha, Tran Xuan Duc, Dang Bao Lam, Nguyen Hoang Viet

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This paper presents a design and implementation of a navigation controller for a humanoid mobile robot platform to operate in indoor office environments. In order to fulfil the requirement of recognizing and approaching human to provide service while avoiding random obstacles, a behavior-based fuzzy logic controller was designed to simultaneously coordinate multiple behaviors. Experiments in real office environment showed that the fuzzy controller deals well with complex scenarios without colliding with random objects and human.

Keywords: behavior control, fuzzy logic, humanoid robot, mobile robot

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Authors: R. Ruslee, H. Gollee

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Functional electrical stimulation (FES) is a commonly used technique in rehabilitation and often associated with rapid muscle fatigue which becomes the limiting factor in its applications. The objective of this study is to investigate the effects on the onset of fatigue of conventional synchronous stimulation, as well as asynchronous stimulation that mimic voluntary muscle activation targeting different motor units which are activated sequentially or randomly via multiple pairs of stimulation electrodes. We investigate three different approaches with various electrode configurations, as well as different patterns of stimulation applied to the gastrocnemius muscle: Conventional Synchronous Stimulation (CSS), Asynchronous Sequential Stimulation (ASS) and Asynchronous Random Stimulation (ARS). Stimulation was applied repeatedly for 300 ms followed by 700 ms of no-stimulation with 40 Hz effective frequency for all protocols. Ten able-bodied volunteers (28±3 years old) participated in this study. As fatigue indicators, we focused on the analysis of Normalized Fatigue Index (NFI), Fatigue Time Interval (FTI) and pre-post Twitch-Tetanus Ratio (ΔTTR). The results demonstrated that ASS and ARS give higher NFI and longer FTI confirming less fatigue for asynchronous stimulation. In addition, ASS and ARS resulted in higher ΔTTR than conventional CSS. In this study, we proposed a randomly distributed stimulation method for the application of FES and investigated its suitability for reducing muscle fatigue compared to previously applied methods. The results validated that asynchronous stimulation reduces fatigue, and indicates that random stimulation may improve fatigue resistance in some conditions.

Keywords: asynchronous stimulation, electrode configuration, functional electrical stimulation (FES), muscle fatigue, pattern stimulation, random stimulation, sequential stimulation, synchronous stimulation

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Authors: Samir Benzegane, Said Sadoudi, Mustapha Djeddou

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In this paper, we present a software development of video streaming encryption for Device-to-Device (D2D) communications by using Hyperchaos-based Random Number Generator (HRNG) implemented in C#. The software implements and uses the proposed HRNG to generate key stream for encrypting and decrypting real-time video data. The used HRNG consists of Hyperchaos Lorenz system which produces four signal outputs taken as encryption keys. The generated keys are characterized by high quality randomness which is confirmed by passing standard NIST statistical tests. Security analysis of the proposed encryption scheme confirms its robustness against different attacks.

Keywords: hyperchaos Lorenz system, hyperchaos-based random number generator, D2D communications, C#

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Authors: Ahmed Guerine, Ali El Hafidi, Bruno Martin, Philippe Leclaire

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In this paper, we propose a method for the dynamic response of multi-storey structures with uncertain-but-bounded parameters. The effectiveness of the proposed method is demonstrated by a numerical example of three-storey structures. This equation is integrated numerically using Newmark’s method. The numerical results are obtained by the proposed method. The simulation accounting the interval analysis method results are compared with a probabilistic approach results. The interval analysis method provides a mean curve that is between an upper and lower bound obtained from the probabilistic approach.

Keywords: multi-storey structure, dynamic response, interval analysis method, random parameters

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Authors: Obaidul Fattah Tanvir, Zinat Ara Afroze

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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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Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

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Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

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Authors: Harold M. Carag, April Charmaine D. Camacho, Girlie Nora A. Abrigo, Florencia G. Palis, Ma. Larissa Lelu P. Gata

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A technology impact assessment on the use of microbial inoculants in the reforestation and rehabilitation of forest ancestral lands of the Magbukün Aytas in Morong, Bataan was conducted. This two-year rainforestation technology aimed to determine the optimum condition for the improvement of seedling survival rate in the nursery and in the field to hasten the process of forest regeneration of Magbukün Ayta’s ancestral land. A combination of qualitative methods (key informant interviews, focus groups and participant observation), participated by the farmers who were directly involved in the project, community men and women, the council of elders and the project staff, was employed to complete this impact assessment. The recorded data were transcribed, and the accounts were broadly categorized on the following aspects: social (gender, institutional, anthropological), economic and environmental. The Australian Center for International Agricultural Research (ACIAR) framework was primarily used for the impact analysis while the Harvard Analytical Framework was specifically used for the gender impact analysis. Through this technology, a wildling nursery with more than one thousand seedlings was successfully established and served as a good area for the healthy growth of seedlings that would be planted in the forest. Results showed that this technology affected positively and negatively the various gender roles present in the community although household work remained to be the women’s responsibility. The technology introduced directly added up to the workload done by the men and women (preparing and applying fertilizer, making pots etc.) but this, in turn, provided ways to increase their sources of livelihood. The gender roles that were already present were further strengthened after the project and men remained to be in control. The technology or project in turn also benefited from the already present roles since they no longer have to assign things to them, the execution of the various roles was smoothly executed. In the anthropological aspect, their assigned task to manage the nursery was an easy responsibility because of their deep connection to the environment and their fear and beliefs on ‘engkato’ and ‘anito’ was helpful in guarding the forest. As the cultural value of these trees increases, their mindset of safeguarding the forest also heightens. Meanwhile, the welfare of the whole tribe is the ultimate determinant of the swift entry of projects. The past institutions brought ephemeral reliefs on the subsistence of the Magbukün Aytas. These were good ‘conditioning’ factors for the adoption of the technology of the project. As an attempt to turn away from the dependent of harmful chemical, the project’s way of introducing organic inputs was slowly gaining popularity in the community. Economically, the project was able to provide additional income to the farmers. However, the slow mode of payment dismayed other farmers and abandoned their roles. Lastly, major environmental effects weren’t that much observed after the application of the technology. The minor effects concentrated more on the improved conditions of the soil and water in the community. Because of the introduced technology, soil conditions became more favorable specifically for the species that were planted. The organic fertilizers used were in turn not harmful for the residents living in Sitio Kanawan. There were no human diseases caused by the technology. The conservation of the biodiversity of the forest is clearly the most evident long-term result of the project.

Keywords: ancestral lands, impact assessment, microbial inculants, reforestation

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Authors: Agoston Restas

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Introduction: This paper describes many initiatives and shows also practical examples which happened recently using Unmanned Aerial Systems (UAS) to support disaster management. Since the operation of manned aircraft at disasters is usually not only expensive but often impossible to use as well, in many cases managers fail to use the aerial activity. UAS can be an alternative moreover cost-effective solution for supporting disaster management. Methods: This article uses thematic division of UAS applications; it is based on two key elements, one of them is the time flow of managing disasters, other is its tactical requirements. Logically UAS can be used like pre-disaster activity, activity immediately after the occurrence of a disaster and the activity after the primary disaster elimination. Paper faces different disasters, like dangerous material releases, floods, earthquakes, forest fires and human-induced disasters. Research used function analysis, practical experiments, mathematical formulas, economic analysis and also expert estimation. Author gathered international examples and used own experiences in this field as well. Results and discussion: An earthquake is a rapid escalating disaster, where, many times, there is no other way for a rapid damage assessment than aerial reconnaissance. For special rescue teams, the UAS application can help much in a rapid location selection, where enough place remained to survive for victims. Floods are typical for a slow onset disaster. In contrast, managing floods is a very complex and difficult task. It requires continuous monitoring of dykes, flooded and threatened areas. UAS can help managers largely keeping an area under observation. Forest fires are disasters, where the tactical application of UAS is already well developed. It can be used for fire detection, intervention monitoring and also for post-fire monitoring. In case of nuclear accident or hazardous material leakage, UAS is also a very effective or can be the only one tool for supporting disaster management. Paper shows some efforts using UAS to avoid human-induced disasters in low-income countries as part of health cooperation.

Keywords: disaster management, floods, forest fires, Unmanned Aerial Systems

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Jian Yang, Atsushi Yagi

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Tree-grass coexistence system is of great importance for forest ecology. Mathematical models are being proposed to study the dynamics of tree-grass coexistence and the stability of the systems. However, few of the models concentrates on spatial dynamics of the tree-grass coexistence. In this study, we modified an age-structured continuous-space population model for forests, obtaining an age-structured continuous-space population model for the tree-grass competition model. In the model, for thermal competitions, adult trees can out-compete grass, and grass can out-compete seedlings. We mathematically studied the model to make sure tree-grass coexistence solutions exist. Numerical experiments demonstrated that a fraction of area that trees or grass occupies can affect whether the coexistence is stable or not. We also tried regulating the mortality of adult trees with other parameters and the fraction of area trees and grass occupies were fixed; results show that the mortality of adult trees is also a factor affecting the stability of the tree-grass coexistence in this model.

Keywords: population-structured models, stabilities of ecosystems, thermal competitions, tree-grass coexistence systems

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Authors: Adijat Olubukola Olateju

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Women empowerment is an essential developmental tool in every economy especially in less developed countries; as it helps to enhance women's socio-economic well-being. Some empirical evidence has shown that microcredit has been an effective tool in enhancing women empowerment, especially in developing countries. This paper therefore, investigates the impact of microcredit programme on women empowerment in Lagos State, Nigeria. The study used Cowries Microfinance Bank (CMB) as a case study bank, and a total of 359 women entrepreneurs were selected by simple random sampling technique from the list of Cowries Microfinance Bank. Selection bias which could arise from non-random selection of participants or non-random placement of programme, was adjusted for by dividing the data into participant women entrepreneurs and non-participant women entrepreneurs. The data were analyzed with a Propensity Score Matching (PSM) technique. The result of the Average Treatment Effect on the Treated (ATT) obtained from the PSM indicates that the credit programme has a significant effect on the empowerment of women in the study area. It is therefore, recommended that microfinance banks should be encouraged to give loan to women and for more impact of the loan to be felt by the beneficiaries the loan programme should be complemented with other programmes such as training, grant, and periodic monitoring of programme should be encouraged.

Keywords: empowerment, microcredit, socio-economic wellbeing, development

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Authors: J. Julius Adebayo

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The objective of this paper is to assess the agro-climatic condition of Ibadan in the rain forest ecological zone of Nigeria, using rainfall pattern and temperature between 1978-2018. Data on rainfall and temperature in Ibadan, Oyo State for a period of 40 years were obtained from Meteorological Section of Forestry Research Institute of Nigeria, Ibadan and Oyo State Meteorology Centre. Time series analysis was employed to analyze the data. The trend revealed that rainfall is decreasing slowly and temperature is averagely increasing year after year. The model for rainfall and temperature are Yₜ = 1454.11-8*t and Yₜ = 31.5995 + 2.54 E-02*t respectively, where t is the time. On this basis, a forecast of 20 years (2019-2038) was generated, and the results showed a further downward trend on rainfall and upward trend in temperature, this indicates persistence rainfall shortage and very hot weather for agricultural practices in the southwest rain forest ecological zone. Suggestions on possible solutions to avert climate change crisis and also promote climate-smart agriculture for sustainable food and nutrition security were also discussed.

Keywords: climate change, rainfall pattern, temperature, time series analysis, food and nutrition security

Procedia PDF Downloads 145

Authors: Samira Cherid, Samir Bentata, Feyza Zahira Meghoufel, Yamina Sefir, Sabria Terkhi, Fatima Bendahma, Bouabdellah Bouadjemi, Ali Zitouni

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Using the transfer-matrix technique and the Kronig Penney model, we numerically and analytically investigate the effect of short-range correlated disorder in random dimer model (RDM) on transmission properties of light in one dimension photonic crystals made of three different materials. Such systems consist of two different structures randomly distributed along the growth direction, with the additional constraint that one kind of these layers appears in pairs. It is shown that the one-dimensional random dimer photonic crystals support two types of extended modes. By shifting of the dimer resonance toward the host fundamental stationary resonance state, we demonstrate the existence of the ballistic response in these systems.

Keywords: photonic crystals, disorder, correlation, transmission

Procedia PDF Downloads 478

Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: Halil Ibrahim Demir, Abdullah Hulusi Kokcam, Fuat Simsir, Özer Uygun

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Traditionally, three important manufacturing functions which are process planning, scheduling and due-date assignment are performed sequentially and separately. Although there are numerous works on the integration of process planning and scheduling and plenty of works focusing on scheduling with due date assignment, there are only a few works on integrated process planning, scheduling and due-date assignment. Although due-dates are determined without taking into account of weights of the customers in the literature, here weighted due-date assignment is employed to get better performance. Jobs are scheduled according to weighted earliest due date dispatching rule and due dates are determined according to some popular due date assignment methods by taking into account of the weights of each job. Simulated Annealing, Evolutionary Strategies, Random Search, hybrid of Random Search and Simulated Annealing, and hybrid of Random Search and Evolutionary Strategies, are applied as solution techniques. Three important manufacturing functions are integrated step-by-step and higher integration levels are found better. Search meta-heuristics are found to be very useful while improving performance measure.

Keywords: process planning, weighted scheduling, weighted due-date assignment, simulated annealing, evolutionary strategies, hybrid searches

Procedia PDF Downloads 462

Authors: Li Zhou, Yanmei Fang

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With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

Procedia PDF Downloads 428

Authors: Mario Isaza-Ruget, Claudia C. Colmenares-Mejia, Nancy Yomayusa, Camilo A. González, Andres Cely, Jossie Murcia

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Quantification of risks associated with complications development from chronic kidney disease (CKD) through accurate survival models can help with patient management. A retrospective cohort that included patients diagnosed with CKD from a primary care program and followed up between 2013 and 2018 was carried out. Time-dependent and static covariates associated with demographic, clinical, and laboratory factors were included. Deep Learning (DL) survival analyzes were developed for three CKD outcomes: CKD stage progression, >25% decrease in Estimated Glomerular Filtration Rate (eGFR), and Renal Replacement Therapy (RRT). Models were evaluated and compared with Random Survival Forest (RSF) based on concordance index (C-index) metric. 2.143 patients were included. Two models were developed for each outcome, Deep Neural Network (DNN) model reported C-index=0.9867 for CKD stage progression; C-index=0.9905 for reduction in eGFR; C-index=0.9867 for RRT. Regarding the RSF model, C-index=0.6650 was reached for CKD stage progression; decreased eGFR C-index=0.6759; RRT C-index=0.8926. DNN models applied in survival analysis context with considerations of longitudinal covariates at the start of follow-up can predict renal stage progression, a significant decrease in eGFR and RRT. The success of these survival models lies in the appropriate definition of survival times and the analysis of covariates, especially those that vary over time.

Keywords: artificial intelligence, chronic kidney disease, deep neural networks, survival analysis

Procedia PDF Downloads 136

Authors: Carolina Morales, Ricardo Castro-Huerta, Enrique A. Mundaca

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The edaphic fauna is the main factor involved in the transformation of nutrients and soil decomposition processes. Edaphic organisms are highly sensitive to soil disturbances, which normally causes changes in the composition and abundance of such organisms. Fire is known to be a disturbing factor since it affects the physical, chemical and biological properties of the soil and the whole ecosystem. During the summer (December-March) of 2017, Chile suffered the major fire events recorded in its modern history, which affected a vast area and a number of ecosystem types. The objective of this study was first to use remote sensing satellite images and GIS (Geographic Information Systems) to assess and identify levels of fire severity in disturbed areas and to compare the responses of the soil mesofauna diversity among such areas. We identified four areas (treatments) with an ascending level of severity, namely: mild, medium, high severity, and free of fire. A non-affected patch of forest was established as a control. Three samples from each treatment were collected in the form of a soil cube (10x10x10 cm). Edaphic mesofauna was obtained from each sample through the Berlese-Tullgren funnel method. Collected specimens were quantified and identified, using the RTU (Recognisable Taxonomic Unit) criterion. Diversity was analysed using inferential statistics to compare Simpson and Shannon-Wiener indexes across treatments. As predicted, the unburned forest patch (control) exhibited higher diversity values than the treatments. Significantly higher diversity values were recorded in those treatments subjected to lower fire severity. We conclude that remote sensing zoning is an adequate tool to identify different levels of fire severity and that an edaphic mesofauna is a group of organisms that qualify as good bioindicators for monitoring soil recovery after fire events.

Keywords: bioindicator, Chile, fire severity level, soil

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Authors: Mahmoud I. Syam

Abstract:

Stratified double median ranked set sampling (SDMRSS) method is suggested for estimating the population mean. The SDMRSS is compared with the simple random sampling (SRS), stratified simple random sampling (SSRS), and stratified ranked set sampling (SRSS). It is shown that SDMRSS estimator is an unbiased of the population mean and more efficient than SRS, SSRS, and SRSS. Also, by SDMRSS, we can increase the efficiency of mean estimator for specific value of the sample size. SDMRSS is applied on real life examples, and the results of the example agreed the theoretical results.

Keywords: efficiency, double ranked set sampling, median ranked set sampling, ranked set sampling, stratified

Procedia PDF Downloads 247