Search results for: forest height mapping

Authors: Abdelghani Qadem, Zohair Qadem, Mohamed Lasri

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At the level of the Moroccan Sais Plateau, groundwater constitutes strategic natural resources for agricultural, industrial, and domestic use. Today, due to climate change and population growth, the pressure on groundwater has increased considerably. This contribution aims to delineate and map potential areas for groundwater storage in the area in question using GIS and remote sensing. The methodology adopted is based on the identification of the thematic layers used to assess the potential recharge of the aquifer. The mapping of potential areas for groundwater storage is developed through the method of modeling and weighted overlay using the spatial analysis tool on the Geographic Information System. The results obtained can be used for the planning of future artificial recharge projects in the study area in order to ensure the good sustainable use of this underground gift.

Keywords: Morocco, climate change, groundwater, mapping, recharge

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Authors: Ji-Suk Kim, Dong-Pil Kim, Kee-Rae Gang, Yoon Ho Choi

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This study was conducted to investigate the characteristics of butterfly communities according to the habitat characteristics of Korean veins. The survey sites were 12 mountains located in the vein, and 12~30 quadrats (200 in total) were set. The species richness and biodiversity were different according to land use type. Two types of land use (forest and graveyard) showed lower species diversity index values ​​than other land use types. The species abundance was low in the forest and graveyards, and grasslands, forest tops, cultivated areas and urban areas showed relatively high species richness. The altitude was not statistically significant with the number of species of butterflies and biodiversity index. The degree of canopy closure showed a negative correlation. As a result of interspecific correlation analysis, it was confirmed that there was a very high correlation (R2=0.746) between Lycaena phlaeas and Pseudozizeeria maha argia, Choaspes benjaminii japonica and Argyronome ruslana.

Keywords: land use type, species diversity index, correlation, canopy closure

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Authors: Dua Hişam, Serhat İkizoğlu

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Identifying the problem behind balance disorder is one of the most interesting topics in the medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three machine learning (ML) models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest Classifier (RF) was the most accurate model.

Keywords: vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting

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Authors: Anshu Siwach, Qianlai Zhuang, Ratul Baishya

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Context: This study focuses on the influence of moss cover and seasonality on soil microbial biomass and enzymatic activity in different Central Himalayan temperate forest types. Soil microbial biomass and enzymes are key indicators of microbial communities in soil and provide information on soil properties, microbial status, and organic matter dynamics. The activity of microorganisms in the soil varies depending on the vegetation type and environmental conditions. Therefore, this study aims to assess the effects of moss cover, seasons, and different forest types on soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN), and soil enzymatic activity in the Central Himalayas, Uttarakhand, India. Research Aim: The aim of this study is to evaluate the levels of SMBC, SMBN, and soil enzymatic activity in different temperate forest types under the influence of two ground covers (soil with and without moss cover) during the rainy and winter seasons. Question Addressed: This study addresses the following questions: 1. How does the presence of moss cover and seasonality affect soil microbial biomass and enzymatic activity? 2. What is the influence of different forest types on SMBC, SMBN, and enzymatic activity? Methodology: Soil samples were collected from different forest types during the rainy and winter seasons. The study utilizes the chloroform-fumigation extraction method to determine SMBC and SMBN. Standard methodologies are followed to measure enzymatic activities, including dehydrogenase, acid phosphatase, aryl sulfatase, β-glucosidase, phenol oxidase, and urease. Findings: The study reveals significant variations in SMBC, SMBN, and enzymatic activity under different ground covers, within the rainy and winter seasons, and among the forest types. Moss cover positively influences SMBC and enzymatic activity during the rainy season, while soil without moss cover shows higher values during the winter season. Quercus-dominated forests, as well as Cupressus torulosa forests, exhibit higher levels of SMBC and enzymatic activity, while Pinus roxburghii forests show lower levels. Theoretical Importance: The findings highlight the importance of considering mosses in forest management plans to improve soil microbial diversity, enzymatic activity, soil quality, and health. Additionally, this research contributes to understanding the role of lower plants, such as mosses, in influencing ecosystem dynamics. Conclusion: The study concludes that moss cover during the rainy season significantly influences soil microbial biomass and enzymatic activity. Quercus and Cupressus torulosa dominated forests demonstrate higher levels of SMBC and enzymatic activity, indicating the importance of these forest types in sustaining soil microbial diversity and soil health. Including mosses in forest management plans can improve soil quality and overall ecosystem dynamics.

Keywords: moss cover, seasons, soil enzymes, soil microbial biomass, temperate forest types

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Authors: Laxuman Thakuri

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Despite the large number of in-depth case studies focused on policy analysis, institutional arrangement, and collective action of common property resource management; how the local institutions take the pricing decision of forest products in community forest management and what kinds of effects produce it, the answers of these questions are largely silent among the policy-makers and researchers alike. The study examined how the local institutions take the pricing decision of forest products in the lowland community forestry of Nepal and how the decisions affect to equitable distribution of benefits and livelihood improvement which are also objectives of Nepalese community forestry. The study assumes that forest products pricing decisions have multiple effects on equitable distribution and livelihood improvement in the areas having heterogeneous socio-economic conditions. The dissertation was carried out at four community forests of lowland, Nepal that has characteristics of high value species, matured-experience of community forest management and better record-keeping system of forest products production, pricing and distribution. The questionnaire survey, individual to group discussions and direct field observation were applied for data collection from the field, and Lorenz curve, gini-coefficient, χ²-text, and SWOT (Strong, Weak, Opportunity, and Threat) analysis were performed for data analysis and results interpretation. The dissertation demonstrates that the low pricing strategy of high-value forest products was supposed crucial to increase the access of socio-economically weak households, and to and control over the important forest products such as timber, but found counter productive as the strategy increased the access of socio-economically better-off households at higher rate. In addition, the strategy contradicts to collect a large-scale community fund and carry out livelihood improvement activities as per the community forestry objectives. The crucial part of the study is despite the fact of low pricing strategy; the timber alone contributed large part of community fund collection. The results revealed close relation between pricing decisions and livelihood objectives. The action research result shows that positive price discrimination can slightly reduce the prevailing inequality and increase the fund. However, it lacks to harness the full price of forest products and collects a large-scale community fund. For broader outcomes of common property resource management in terms of resource sustainability, equity, and livelihood opportunity, the study suggests local institutions to harness the full price of resource products with respect to the local market.

Keywords: community, equitable, forest, livelihood, socioeconomic, Nepal

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Authors: Ratun Rahman, Rafid Islam, Akin Ahmed, Kamrul Hasan, Hasan Mahmud

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Malware is becoming more prevalent, and several threat categories have risen dramatically in recent years. This paper provides a bird's-eye view of the world of malware analysis. The efficiency of five different machine learning methods (Naive Bayes, K-Nearest Neighbor, Decision Tree, Random Forest, and TensorFlow Decision Forest) combined with features picked from the retrieval of Android permissions to categorize applications as harmful or benign is investigated in this study. The test set consists of 1,168 samples (among these android applications, 602 are malware and 566 are benign applications), each consisting of 948 features (permissions). Using the permission-based dataset, the machine learning algorithms then produce accuracy rates above 80%, except the Naive Bayes Algorithm with 65% accuracy. Of the considered algorithms TensorFlow Decision Forest performed the best with an accuracy of 90%.

Keywords: android malware detection, machine learning, malware, malware analysis

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Authors: W. Promprom, W. Chatan

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Leguminosae is a large plant family and its members are important for local people utilization in the Northeast of Thailand. This research aimed to survey medicinal plants in this family in Kantharalak Community forest. The plant collection and exploration were made from October 2017 to September 2018. Folk medicinal uses were studied by interviewing villagers and folk medicine healers living around the community forest by asking about local names, using parts, preparation and properties. The results showed that 65 species belonging to 40 genera were found. Among these, 30 species were medicinal plant. The most used plant parts were leaf. Decoction and drinking were mostly preparation method and administration mode used. All medicinal plants could be categorized into 17 diseases/symptoms. Most plant (56.66%) were used for fever. The voucher specimens were deposited in Department of Biology, Faculty of Science, Mahasarakham University, Thailand. Therefore, the data from this study might be widely used by the local area and further scientific study.

Keywords: ethnobotany, ethnophamacology, medicinal plant, taxonomy, utilization

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Authors: Sikiru Ademola Adewale, Joe Thomas, Bolanle Hafiz Matti, Tosin Ige

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This project demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were shown to demonstrate model generality over the video temporal dimension. Predicted captions were shown to generalize over video action, even in instances where the video scene changed dramatically. Model architecture changes are discussed to improve sentence grammar and correctness.

Keywords: decoder, encoder, many-to-many mapping, video captioning, 2-gram BLEU

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Authors: Yeliz Sarı Nayim, B. Niyami Nayim

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Biotopes such as forest areas rich in biodiversity, wetlands, hedgerows and woodlands play important ecological roles in agricultural landscapes. Of these semi-natural areas and features, hedgerows are the most common landscape elements. Their most significant features are that they serve as a barrier between the agricultural lands, serve as shelter, add aesthetical value to the landscape and contribute significantly to the wildlife and biodiversity. Hedgerows surrounding agricultural landscapes also provide an important habitat for pollinators which are important for agricultural production. This study looks into the identification of hedgerows in agricultural lands in the Mugada rural area within Bartın province, Turkey. From field data and-and satellite images, it is clear that in this area, especially around rural settlements, large forest areas have been cleared for settlement and agriculture. A network of hedgerows is also apparent, which might potentially play an important role in the otherwise open agricultural landscape. We found that these hedgerows serve as an ecological and biological corridor, linking forest ecosystems. Forest patches of different sizes and creating a habitat network across the landscape. Some examples of this will be presented. The overall conclusion from the study is that ecologically, biologically and aesthetically important hedge biotopes should be maintained in the long term in agricultural landscapes such as this. Some suggestions are given for how they could be managed sustainably into the future.

Keywords: agricultural biotopes, Hedgerows, landscape ecology, Turkey

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: Khaing Su Su Than, Hibino Yo

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Seismic evaluation is needed upon the buildings in Myanmar. Microtremor measurement was conducted in the main cities, Mandalay and Yangon. In order to evaluate the seismic properties of buildings currently under construction, seismic information was gathered for six buildings in Yangon city and four buildings in Mandalay city. The investigated buildings vary from 12m-80 m in height, and mostly public residence structures. The predominant period obtained from frequency results of the investigated buildings were given by horizontal to vertical spectral ratio (HVSR) for each building. The fundamental period results have been calculated in the form of Fourier amplitude spectra of translation along with the main structure. Based on that, the height (H)-period(T) relationship was observed as T=0.012H-0.017H in the buildings of Yangon and, observed the relationship as T=0.014H-0.019H in the buildings of Mandalay. The results showed that the relationship between height and natural period was slightly under the relationship T=0.02H that is used for Japanese reinforced concrete buildings, which indicated that the results depend on the properties and characteristics of materials used.

Keywords: HVSR, height-period relationship, microtremor, Myanmar earthquake, reinforced concrete structures

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Authors: K. V. F. Fatokun, P. A. Eniayeju

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This study concerns the effects of concept mapping-guided discovery integrated teaching approach on the learning style and achievement of chemistry students. The sample comprised 162 senior secondary school (SS 2) students drawn from two science schools in Nasarawa State which have equivalent mean scores of 9.68 and 9.49 in their pre-test. Five instruments were developed and validated while the sixth was purely adopted by the investigator for the study, Four null hypotheses were tested at α = 0.05 level of significance. Chi square analysis showed that there is a significant shift in students’ learning style from accommodating and diverging to converging and assimilating when exposed to concept mapping- guided discovery approach. Also t-test and ANOVA that those in experimental group achieve and retain content learnt better. Results of the Scheffe’s test for multiple comparisons showed that boys in the experimental group performed better than girls. It is therefore concluded that the concept mapping-guided discovery integrated approach should be used in secondary schools to successfully teach electrochemistry. It is strongly recommended that chemistry teachers should be encouraged to adopt this method for teaching difficult concepts.

Keywords: integrated teaching approach, concept mapping-guided discovery, achievement, retention, learning styles and interest

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Authors: S. Benkraouda, Z. Djelloul-Khedda, B. Yagoubi

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we present a method for early detection of forest fires from a thermal infrared satellite image, using the image matrix of the probability of belonging. The principle of the method is to compare a theoretical mathematical model to an experimental model. We considered that each line of the image matrix, as an embodiment of a non-stationary random process. Since the distribution of pixels in the satellite image is statistically dependent, we divided these lines into small stationary and ergodic intervals to characterize the image by an adequate mathematical model. A standard deviation was chosen to generate random variables, so each interval behaves naturally like white Gaussian noise. The latter has been selected as the mathematical model that represents a set of very majority pixels, which we can be considered as the image background. Before modeling the image, we made a few pretreatments, then the parameters of the theoretical Gaussian model were extracted from the modeled image, these settings will be used to calculate the probability of each interval of the modeled image to belong to the theoretical Gaussian model. The high intensities pixels are regarded as foreign elements to it, so they will have a low probability, and the pixels that belong to the background image will have a high probability. Finally, we did present the reverse of the matrix of probabilities of these intervals for a better fire detection.

Keywords: forest fire, forest fire detection, satellite image, normal distribution, theoretical gaussian model, thermal infrared matrix image

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Authors: Karl D. Humm

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The United Nations’ Community-based REDD+ (Reducing Emissions from Deforestation and forest Degradation) (CBR+) is a programme that directly finances grassroots climate change mitigation strategies that uplift Indigenous Peoples (IPs) and other marginalised groups. A pilot for it in six countries was developed in response to criticism of the REDD+ programme for excluding IPs from dialogues about climate change mitigation strategies affecting their lands and livelihoods. Despite the pilot’s conclusion in 2017, no complete report has yet been produced on the results of CBR+. To fill this gap, this study investigated the experiences with involving IPs in the CBR+ programmes and local projects across all six pilot countries. A literature review of official UN reports and academic articles identified challenges and successes with IP participation in REDD+ which became the basis for a framework guiding data collection. A mixed methods approach was used to collect and analyse qualitative and quantitative data from CBR+ documents and written interviews with CBR+ National Coordinators in each country for a cross-country comparative analysis. The study found that the most frequent challenges were lack of organisational capacity, illegal forest activities, and historically-based contentious relationships in IP and forest-dependent communities. Successful programmes included IPs and incorporated respect and recognition of IPs as major stakeholders in managing sustainable forests. Findings are summarized and shared with a set of recommendations for improvement of future projects.

Keywords: climate change, forests, indigenous peoples, REDD+

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Authors: Chakraborty Sudipta, A. R. Kambekar, Sarma Arnab

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Sea-level rise being one of the most important impacts of anthropogenic induced climate change resulting from global warming and melting of icebergs at Arctic and Antarctic, the investigations done by various researchers both on Indian Coast and elsewhere during the last decade has been reviewed in this paper. The paper aims to ascertain the propensity of consistency of different suggested methods to predict the near-accurate future sea level rise along the coast of Mumbai. Case studies at East Coast, Southern Tip and West and South West coast of India have been reviewed. Coastal Vulnerability Index of several important international places has been compared, which matched with Intergovernmental Panel on Climate Change forecasts. The application of Geographic Information System mapping, use of remote sensing technology, both Multi Spectral Scanner and Thematic Mapping data from Landsat classified through Iterative Self-Organizing Data Analysis Technique for arriving at high, moderate and low Coastal Vulnerability Index at various important coastal cities have been observed. Instead of data driven, hindcast based forecast for Significant Wave Height, additional impact of sea level rise has been suggested. Efficacy and limitations of numerical methods vis-à-vis Artificial Neural Network has been assessed, importance of Root Mean Square error on numerical results is mentioned. Comparing between various computerized methods on forecast results obtained from MIKE 21 has been opined to be more reliable than Delft 3D model.

Keywords: climate change, Coastal Vulnerability Index, global warming, sea level rise

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Authors: Linhang Zhu, Hongyu Zhu, Jiahe Liu

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This paper investigated a method of indoor real-time positioning and mapping based on the Manhattan world assumption. In indoor environments, relying solely on feature matching techniques or other geometric algorithms for sensor pose estimation inevitably resulted in cumulative errors, posing a significant challenge to indoor positioning. To address this issue, we adopt the Manhattan world hypothesis to optimize the camera pose algorithm based on feature matching, which improves the accuracy of camera pose estimation. A special processing method was applied to image data frames that conformed to the Manhattan world assumption. When similar data frames appeared subsequently, this could be used to eliminate drift in sensor pose estimation, thereby reducing cumulative errors in estimation and optimizing mapping and positioning. Through experimental verification, it is found that our method achieves high-precision real-time positioning in indoor environments and successfully generates maps of indoor environments. This provides effective technical support for applications such as indoor navigation and robot control.

Keywords: Manhattan world hypothesis, real-time positioning and mapping, feature matching, loopback detection

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Authors: K. Kanja, M. Mweemba, K. Malungwa

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Due to the rampant population growth coupled with retrenchments currently going on in the Copper mines in Zambia, a number of people are resorting to land clearing for agriculture, illegal settlements as well as charcoal production among other vices. This study aims at assessing the rate of expansion of agricultural fields and illegal settlements in protected areas using remote sensing and Geographic Information System. Zambia’s Mwekera National Forest Reserve was used as a case study. Iterative Self-Organizing Data Analysis Technique (ISODATA), as well as maximum likelihood, supervised classification on four Landsat images as well as an accuracy assessment of the classifications was performed. Over the period under observation, results indicate annual percentage changes to be -0.03, -0.49 and 1.26 for agriculture, forests and settlement respectively indicating a higher conversion of forests into human settlements and agriculture.

Keywords: geographic information system, land cover change, Landsat TM and ETM+, Mwekera forest reserve, remote sensing

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Authors: Nina Philipova

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The influence of the geometric parameters of trapezoidal labyrinth channel on the pressure losses along the labyrinth length is investigated in this work. The impact of the dentate height is studied at fixed values of the dentate angle and the dentate spacing. The objective of the work presented in this paper is to derive a mathematical model of the pressure losses along the labyrinth length depending on the dentate height. The numerical simulations of the water flow movement are performed by using Commercial codes ANSYS GAMBIT and FLUENT. Dripper inlet pressure is set up to be 1 bar. As a result, the mathematical model of the pressure losses is determined as a second-order polynomial by means Commercial code STATISTIKA. Bi-objective optimization is performed by using the mean algebraic function of utility. The optimum value of the dentate height is defined at fixed values of the dentate angle and the dentate spacing. The derived model of the pressure losses and the optimum value of the dentate height are used as a basis for a more successful emitter design.

Keywords: drip irrigation, labyrinth channel hydrodynamics, numerical simulations, Reynolds stress model

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Authors: Cassandra A. Skinner, Linda R. Chamberlain

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The nonprofit and public sectors are increasingly turning to Geographic Information Systems for data visualizations which can better inform programmatic and policy decisions. Additionally, the private and nonprofit sectors are turning to systems mapping to better understand the ecosystems within which they operate. This study explores the potential which combining these data visualization methods—a method which is called geographic systems mapping—to create an exhaustive and comprehensive understanding of a social problem’s ecosystem may have in social innovation efforts. Researchers with Grand Valley State University collaborated with Talent 2025 of West Michigan to conduct a mixed-methods research study to paint a comprehensive picture of the workforce development ecosystem in West Michigan. Using semi-structured interviewing, observation, secondary research, and quantitative analysis, data were compiled on workforce development organizations’ locations, programming, metrics for success, partnerships, funding sources, and service language. To best visualize and disseminate the data, a geographic system map was created which identifies programmatic, operational, and geographic gaps in workforce development services of West Michigan. By combining geographic and systems mapping methods, the geographic system map provides insight into the cross-sector relationships, collaboration, and competition which exists among and between workforce development organizations. These insights identify opportunities for and constraints around cross-sectoral social innovation in the West Michigan workforce development ecosystem. This paper will discuss the process utilized to prepare the geographic systems map, explain the results and outcomes, and demonstrate how geographic systems mapping illuminated the needs of the community and opportunities for social innovation. As complicated social problems like unemployment often require cross-sectoral and multi-stakeholder solutions, there is potential for geographic systems mapping to be a tool which informs, enables, and inspires these solutions.

Keywords: cross-sector collaboration, data visualization, geographic systems mapping, social innovation, workforce development

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Authors: Luis C. Parra

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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: M. Alkhalidi, S. Neelamani, Z. Al-Zaqah

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This paper investigates the interaction of single and twin offshore rubble mound breakwaters with regular and random water waves through physical modeling to assess their reflection, transmission and energy dissipation characteristics. Various combinations of wave heights and wave periods were utilized in a series of experiments, along with three different water depths. The single and twin permeable breakwater models were both constructed with one layer of rubbles. Both models had the same total volume; however, the single breakwater was of trapezoidal type while the twin breakwaters were of triangular type. Physical modeling experiments were carried out in the wave flume of the coastal engineering laboratory of Kuwait Institute for Scientific Research (KISR). Measurements of the six wave probes which were fixed in the two-dimensional wave flume were collected and used to determine the generated incident wave heights, as well as the reflected and transmitted wave heights resulting from the wave-breakwater interaction. The possible factors affecting the wave attenuation efficiency of the breakwater models are the relative water depth (d/L), wave steepness (H/L), relative wave height ((h-d)/Hi), relative height of the breakwater (h/d), and relative clear spacing between the twin breakwaters (S/h). The results indicated that the single and double breakwaters show different responds to the change in their relative height as well as the relative wave height which demonstrates that the effect of the relative water depth on wave reflection, transmission, and energy dissipation is highly influenced by the change in the relative breakwater height, the relative wave height and the relative breakwater spacing. In general, within the range of the relative water depth tested in this study, and under both regular and random waves, it is found that the single breakwater allows for lower wave transmission and shows higher energy dissipation effect than both of the tested twin breakwaters, and hence has the best overall performance.

Keywords: random waves, regular waves, relative water depth, relative wave height, single breakwater, twin breakwater, wave steepness

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Authors: Shengbiao Wu, Weihua Cao, Min Wu, Can Liu

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This paper presents an intelligent tuning method of microwave filter based on complex neural network and improved space mapping. The tuning process consists of two stages: the initial tuning and the fine tuning. At the beginning of the tuning, the return loss of the filter is transferred to the passband via the error of phase. During the fine tuning, the phase shift caused by the transmission line and the higher order mode is removed by the curve fitting. Then, an Cauchy method based on the admittance parameter (Y-parameter) is used to extract the coupling matrix. The influence of the resonant cavity loss is eliminated during the parameter extraction process. By using processed data pairs (the amount of screw variation and the variation of the coupling matrix), a tuning model is established by the complex neural network. In view of the improved space mapping algorithm, the mapping relationship between the actual model and the ideal model is established, and the amplitude and direction of the tuning is constantly updated. Finally, the tuning experiment of the eight order coaxial cavity filter shows that the proposed method has a good effect in tuning time and tuning precision.

Keywords: microwave filter, scattering parameter, coupling matrix, intelligent tuning

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Authors: Wei-Na Li, Mei-Lan Piao, Nam Kim

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We proposed a novel computer-generated hologram (CGH) achieved scheme, wherein the CGH is generated from a point cloud which is transformed by a mapping relationship of a series of elemental images captured from a real three-dimensional (3D) object by using a lens array. This scheme is composed of three procedures: mapping from elemental images to point cloud, hologram generation, and hologram display. A mapping method is figured out to achieve a virtual volume date (point cloud) from a series of elemental images. This mapping method consists of two steps. Firstly, the coordinate (x, y) pairs and its appearing number are calculated from the series of sub-images, which are generated from the elemental images. Secondly, a series of corresponding coordinates (x, y, z) are calculated from the elemental images. Then a hologram is generated from the volume data that is calculated by the previous two steps. Eventually, a spatial light modulator (SLM) and a green laser beam are utilized to display this hologram and reconstruct the original 3D object. In this paper, in order to show a more auto stereoscopic display of a real 3D object, we successfully obtained the actual depth data of every discrete point of the real 3D object, and overcame the inherent drawbacks of the depth camera by obtaining point cloud from the elemental images.

Keywords: elemental image, point cloud, computer-generated hologram (CGH), autostereoscopic display

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Authors: Rahim Ada, Ahmet Tamkoç

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The research was conducted in the “Randomized Complete Block Design” with three replications in research field of Agricultural Faculty, Selcuk University, Konya, Turkey. In study, a total of 9 Cephalaria syriaca promised lines (9, 37, 38, 42, Beyaz 4, 5 Beyaz, 13 Beyaz, 27 Beyaz, Başaklar 2), which were taken from Sivas population, and 1 population were evaluated in two growing seasons (2012-13 and 2013-14). According to the results, the highest plant height, first branch height, first head height, number of branches per plant, number of head per plant, head diameter,1000 seed weight, seed yield, oil content and oil yield were obtained respectively from Başaklar 2 (68.37 cm), Başaklar 2 (37.80 cm), Başaklar 2 (54.83 cm), 37 (7.73 number/plant), 42 (18.03 number/plant), 9 (10.30 mm), Başaklar 2 (19.33 g), 27 Beyaz (1254.2 kg ha-1), Başaklar 2 (28.77%), and 27 Beyaz (357.9 kg ha-1).

Keywords: Cephalaria syriaca, yield, oil, population

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Authors: Ibrahim Ilker Ozyigit, Ertugrul Filiz, Seda Birbilener, Semsettin Kulac, Zeki Severoglu

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In this study, we have performed genetic diversity analysis of Tilia tomentosa genotypes by using randomly amplified polymorphic DNA (RAPD) primers. A total of 28 genotypes, including 25 members from the urban ecosystem and 3 genotypes from forest ecosystem as outgroup were used. 8 RAPD primers produced a total of 53 bands, of which 48 (90.6 %) were polymorphic. Percentage of polymorphic loci (P), observed number of alleles (Na), effective number of alleles (Ne), Nei's (1973) gene diversity (h), and Shannon's information index (I) were found as 94.29 %, 1.94, 1.60, 0.34, and 0.50, respectively. The unweighted pair-group method with arithmetic average (UPGMA) cluster analysis revealed that two major groups were observed. The genotypes of urban and forest ecosystems showed a high genetic similarity between 28% and 92% and these genotypes did not separate from each other in UPGMA tree. Also, urban and forest genotypes clustered together in principal component analysis (PCA).

Keywords: Tilia tomentosa, genetic diversity, urban ecosystem, RAPD, UPGMA

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Authors: Y. Cochet, A. Achim, Tom Flatman, J-C. Domec, J. Ogée, L. Wingate, Ram Oren

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It is accepted that atmospheric CO2 concentration will increase in the future. For the past 30 years, researchers have used FACE (Free-Air Carbon Dioxide Enrichment) facilities to study the development of terrestrial ecosystems under elevated CO2 (eCO2). Forest responses to eCO2 are likely to impact timber industries with potential feedbacks towards the atmosphere. The main objectives of this study were to examine whether eCO2 alone or in combination with N-fertilization alter wood properties and to identify changes in wood anatomy related to water transport. Wood disks were sampled at breast height from mature loblolly pine trees (Pinus taeda L.) harvested at the Duke FACE site (NC, USA). By measuring ring width and intra-ring changes in density (X-ray densitometry) and tracheid size (lumen and cell wall thickness) from pith to bark, the following hypotheses were tested: 1) eCO2 and N-fertilization interact positively to increase significantly above-ground primary productivity; 2) eCO2 and N-fertilization lead to a decrease in density; 3) eCO2 and N-fertilization increase lumen diameter and decrease cell wall thickness, thus affecting water transport capacity. Our results revealed a boost in earlywood tracheid production induced by eCO2 lasting a few years. The following decrease seemed to be buffered by N-fertilization. X-ray profiles did not show a marked decrease in wood density under eCO2 or N-fertilization, although there were changes in cell anatomical properties such as a reduction in cell-wall thickness and an increase in lumen diameter. If such effects of eCO2 are confirmed, forest management strategies for example N-fertilization should be redesigned.

Keywords: wood density, Duke FACE (free-air carbon dioxide enrichment), N fertilization, tree ring

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Authors: Menuka Maharjan

Abstract:

In the name of food security, agriculture intensification through conventional farming is being implemented in Nepal. Government focus on increasing agriculture production completely ignores soil as well human health. This leads to create serious soil degradation, i.e., reduction of soil fertility and microbial activity and health hazard in the country. On this note, organic farming is sustainable agriculture approach which can address challenge of sustaining food security while protecting the environment. This creates a win-win situation both for people and the environment. However, people have limited knowledge on significance of organic farming for environment conservation and food security especially developing countries like Nepal. Thus, the objective of the study was to assess the impacts of organic farming on soil fertility and microbial activity compared to conventional farming and forest in Chitwan, Nepal. Total soil organic carbon (C) was highest in organic farming (24 mg C g⁻¹ soil) followed by conventional farming (15 mg C g⁻¹ soil) and forest (9 mg C g⁻¹ soil) in the topsoil layer (0-10 cm depth). A similar trend was found for total nitrogen (N) content in all three land uses with organic farming soil possessing the highest total N content in both 0-10 cm and 10-20 cm depth. Microbial biomass C and N were also highest under organic farming, especially in the topsoil layer (350 and 46 mg g⁻¹ soil, respectively). Similarly, microbial biomass phosphorus (P) was higher (3.6 and 1.0 mg P kg⁻¹ at 0-10 and 10-20 cm depth, respectively) in organic farming compared to conventional farming and forest at both depths. However, conventional farming and forest soils had similar microbial biomass (C, N, and P) content. After conversion of forest, the P stock significantly increased by 373% and 170% in soil under organic farming at 0-10 and 10-20 cm depth, respectively. In conventional farming, the P stock increased by 64% and 36% at 0-10 cm and 10-20 cm depth, respectively, compared to forest. Overall, organic farming practices, i.e., crop rotation, residue input and farmyard manure application, significantly alters soil fertility and microbial activity. Organic farming system is emerging as a sustainable land use system which can address the issues of food security and environment conservation by increasing sustainable agriculture production and carbon sequestration, respectively, supporting to achieve goals of sustainable development.

Keywords: organic farming, soil fertility, micobial biomas, food security

Procedia PDF Downloads 151

Authors: Felix Damilola Ajibade, Opeyemi O. Enoch, Taiwo Paul Fajusigbe

Abstract:

This paper is centered on conducting an inquiry into the stability of the F* iterative algorithm to the fixed point of a strongly pseudo-contractive mapping in the framework of uniformly convex Banach spaces. To achieve the desired result, certain existing inequalities in convex Banach spaces were utilized, as well as the stability criteria of Harder and Hicks. Other necessary conditions for the stability of the F* algorithm on strong pseudo-contractive mapping were also obtained. Through a numerical approach, we prove that the F* iterative algorithm is H-stable for strongly pseudo-contractive mapping. Finally, the solution of the mixed-type Volterra-Fredholm functional non-linear integral equation is estimated using our results.

Keywords: stability, F* -iterative algorithm, pseudo-contractive mappings, uniformly convex Banach space, mixed-type Volterra-Fredholm integral equation

Procedia PDF Downloads 78

Authors: Arzyana Sunkar, Yanto Santosa

Abstract:

The expansions of independent smallholdings in Indonesia are feared to increase the negative ecological impacts of oil palm plantation on biodiversity. Hence, research is required to identify the conservation importance of independent smallholder oil palm plantations on biodiversity. This paper discussed the role of independent smallholdings in the conservation of biodiversity in oil palm plantations and to compare it with High Conservation Value Forest as a conservation standard of RSPO. The research was conducted from March to April 2016. Data on biodiversity were collected on 16 plantations and 8 private oil palm plantations in the Districts of Kampar, Pelalawan, Kuantan, Singingi and Siak of Riau Province, Indonesia. In addition, data on community environmental perceptions of both smallholder plantation and High Conservation Value (HCV) Forest were also collected. Species that were observed were birds and earthworms. Data on birds were collected using transect method, while identification of earthworm was determine by taking some soil samples and counting the number of individual earthworm found for each worm species. The research used direct interview with oil palm owners and community members, as well as direct observation to examine the environmental conditions of each plantation. In general, field observation and measurement have found that birds species richness was higher in the forested HCV Forest. Nevertheless, if compared to non-forested HCV, bird’s species richness was higher in the independent smallholdings. On the other hand, different results were observed for earthworm, where the density was higher in the independent smallholdings than in the HCV. It can be concluded from this research that managing independent smallholder oil palm plantations and forested HCV forest could enhance biodiversity conservation. The results of this study justified the importance of retaining forested area to safeguard biodiversity in oil palm plantation.

Keywords: biodiversity conservation, high conservation value forest, independent smallholdings, oil palm plantations

Procedia PDF Downloads 199

Authors: Sampriti Panda

Abstract:

Earning one’s own livelihood is the most basic and inseparable activity for survival and existence of humankind. In any kind of situation and in every type of geographical terrain, human does adopt various strategies and ways of earning their own livelihood. Since time immemorial, anthropocentrism has been the saga of livelihood where environment is out casted and exploited to any limit so that mankind can survive. With the passage of time, humans regained their consciousness and realized that the time has arrived now to shift to sustainable livelihood and stop being self centered. This paper tries to focus on the very central issue and the hotpot of discussion in the present era which revolves around sustainable livelihood. The aim of the paper is to find out how the tribal communities which are primarily forest based are the best example of sustainable livelihood since their existence. The paper also tries to throw light on the burning issue of the so-called term ‘development’ affecting the traditional ways of livelihood opted by the forest based tribal communities. The data presented in the paper are primary and have been collected using various techniques and methodology like observation, interviews, life histories, case studies and other techniques used in a self conducted fieldwork among the Juangs, who are one of the PVTGs of Odisha.

Keywords: forest, livelihood, sustainability, tribe

Procedia PDF Downloads 193