Search results for: forest biodiversity

Authors: Laurenn Borges de Macedo, Fabiane Salles Ferro, Tiago Hendrigo de Almeida, Gérson Moreira de Lima, André Luiz Christoforo, Francisco Antonio Rocco Lahr

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The growth of the furniture manufacturing industry is one of the fundamental factors contributing to the growth of the particleboard industry. The use of recycled products into particleboards can contribute to the forest conservation, in addition to achieve a high quality sustainable product with low-cost production. This work investigates the effect of bi-oriented polypropylene (BOPP) waste particles and sealing product on the physical and mechanical properties of Eucalyptus sp. particleboards fabricated with a castor oil based polyurethane resin. Among the factors, only the seal coating was statistically significant. The wood panels of Treatment 2 were classified as H1, based on the internal bond strength and elastic modulus results data required by ANSI A208.1:1999. The bending strength data did not reach the minimum values recommended by NBR 14810:2006 and ANSI A208.1:1999. The thickness swelling data for 2h immersed in water achieved the standard requirement levels. High-density panels were achieved revealing their potential use in variety of particleboard applications.

Keywords: BOPP, mechanical properties, particleboards, physical properties

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Authors: Elkington Sibusiso Mnguni

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In South Africa, mining has been a key economic sector since the discovery of gold in 1886 in the Witwatersrand region, where the city of Johannesburg is located. However, some mines have since been decommissioned, and the continuous pumping of acid mine drainage (AMD) also stopped causing the AMD to rise towards the ground surface. This posed a serious environmental risk to the groundwater resources and river systems in the region. This paper documents the development and extent of the environmental damage as well as the measures implemented by the government to alleviate such damage. The study will add to the body of knowledge on the subject of AMD treatment to prevent environmental degradation. The method used to gather and collate relevant data and information was the desktop study. The key findings include the social and environmental impact of the AMD, which include the pollution of water sources for domestic use leading to skin and other health problems and the loss of biodiversity in some areas. It was also found that the technical intervention of constructing a plant to pump and treat the AMD using the high-density sludge technology was the most effective short-term solution available while a long-term solution was being explored. Some successes and challenges experienced during the implementation of the project are also highlighted. The study will be a useful record of the current status of the AMD treatment interventions in the region.

Keywords: acid mine drainage, groundwater resources, pollution, river systems, technical intervention, high density sludge

Procedia PDF Downloads 186

Authors: James Taylor

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This paper considers the political, geo-philosophical musings of Deleuze and Guattari on spatialisation, place and movement in relation to the religious nomad (wandering ascetics and reclusive forest monks) inhabiting the borderlands of Thailand. A nomadic science involves improvised ascetic practices between the molar lines striated by modern state apparatuses. The wandering ascetics, inhabiting a frontier political ecology, stand in contrast to the appropriating, sedentary metaphysics and sanctifying arborescence of statism and its corollary place-making, embedded in rootedness and territorialisation. It is argued that the religious nomads, residing on the endo-exteriorities of the state, came to represent a rhizomatic and politico-ontological threat to centre-nation and its apparatus of capture. The paper also theorises transitions and movement at the borderlands in the context of the state’s monastic reforms. These reforms, and its pervasive royal science, problematised the interstitial zones of the early ascetic wanderers in their radical cross-cutting networks and lines, moving within and across demarcated frontiers. Indeed, the ascetic wanderers and their allegorical war machine were seen as a source of wild, free-floating charisma and mystical power, eventually appropriated by the centre-nation in it’s becoming unitary and fixed.

Keywords: Deleuze and Guattari, religious nomad, centre-nation, borderlands, Buddhism

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Authors: Kitda Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Mueang district, Samut Songkram province for ecotourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: 1. The identity of Amphur (District) Mueang, Samut Songkram province. This establishment was near the Mouth of Maekong River for normal people and tourists, consisting of rest accommodations. There are restaurants where food and drinks are served, rich mangrove forests, Hoy Lod (Razor Clam) and mangrove trees. Don Hoy Lod, is characterized by muddy beaches, is a coastal wetland for Ramsar Site. It is at 1099th ranging where the greatest number of Hoy Lod (Razor Clam) can be seen from March to May each year. 2. The communication of the identity of Amphur Mueang, Samut Songkram province which the researcher could find and design to present in English materials can be summed up in 4 items: 1) The history of Amphur Mueang, Samut Songkram province 2) Wat Phet Samut Worrawihan 3) The Learning source of Ecotourism: Don Hoy Lod and Mangrove forest 4) How to keep Amphur Mueang, Samut Songkram province for ecotourism.

Keywords: foreigner tourists, signified, semiotics, ecotourism

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Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

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Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

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Authors: Yanto Santosa, Catharina Yudea

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The rapid growth of oil palm industry in Indonesia raised many negative accusations from various parties, who said that oil palm plantation is damaging the environment and biodiversity, including birds. Since research on oil palm plantation impacts on bird diversity is still limited, this study needs to be developed in order to gain further learning and understanding. Data on bird diversity were collected in March 2018 in KJNP Estate, Riau Province using strip transect method on five different land cover types (young, intermediate, and old growth of oil palm plantation, high conservation value area, and crops field or the baseline). The observations were conducted simultaneously, with three repetitions. The result shows that the baseline has 19 species of birds and land cover after the oil palm plantation has 39 species. HCV (high conservation value) area has the highest increase in diversity value. Oil palm plantation has changed the composition of bird species. The highest similarity index is shown by young growth oil palm land cover with total score 0.65, meanwhile the lowest similarity index with total score 0.43 is shown by HCV area. Overall, the existence of oil palm plantation made a positive impact by increasing bird species diversity, with total 23 species gained and 3 species lost.

Keywords: bird diversity, crops field, impact of oil palm plantation, KJNP estate

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Authors: Alexander Rincón Ruiz

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This article is based on an exhaustive review and interdisciplinary effort spanning three years. It involved interviews, dialogues, discussion panels, and collective work on various visions of bio-economy in Colombia. The dialogue included government institutions, universities, local communities, activist groups, research institutes, the productive sector, and politicians, integrating perspectives such as Latin American environmental thought, complexity theory, modern visions, local worldviews (Afro-Colombian, indigenous, peasant), decoloniality, political ecology, ecological economics, and environmental economies. This work highlighted the need to redefine the traditional bio-economy concept, typically focused on markets and biotechnology, and to revisit the original idea of a bio-economy as an ‘economy for life’. In a country as diverse as Colombia—both biophysically and in its varied relationships with the territory—this redefinition is crucial. It emphasizes alternative logics of well-being related to resilience, care, and cooperation, reflecting Indigenous, Afro-Colombian, and peasant worldviews. This article is significant for proposing, for the first time, a viable approach to diverse and alternative economies for life tailored to the Colombian context. It represents not only academic work but also a political commitment to inclusion and plurality, aligning with the Colombian context and potentially extendable to other regions.

Keywords: ecological economics, decoloniality, complexity, Biodiversity

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Authors: Abduselam Faris, Rijalu Negash, Zera Kedir

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This study was initiated to identify constraints and opportunities of the wood production value chain in Southwest Ethiopia. About 385 wood trees growing farmers were randomly interviewed. Similarly, about 30 small-scale wood processors, 30 retailers, 15 local collectors and 5 wholesalers were purposively included in the study. The results of the study indicated that 98.96 % of the smallholder farmers that engaged in the production of wood trees which is used for wood were male-headed, with an average age of 46.88 years. The main activity that the household engaged was agriculture (crop and livestock) which accounts for about 61.56% of the sample respondents. Through value chain mapping of actors, the major value chain participant and supporting actors were identified. On average, the tree-growing farmers generated gross income of 9385.926 Ethiopian birr during the survey year. Among the critical constraints identified along the wood production value chain was limited supply of credit, poor market information dissemination, high interference of brokers, and shortage of machines, inadequate working area and electricity. The availability of forest resources is the leading opportunity in the wood production value chain. Reinforcing the linkage among wood production value chain actors, providing skill training for small-scale processors, and developing suitable policy for wood tree wise use is key recommendations forward.

Keywords: value chain analysis, wood production, southwest Ethiopia, constraints and opportunities

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Authors: Pisit Poolprasert, Auttpol Nakwa, Keerati Tanruean, Ezra Mongkolchaichana, Ezra Mongkolchaichana, Sinlapachai Senarat, Mark Tunmore

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This present preliminary study aimed to observe the butterfly species diversity in two selected subdistricts i.e., Mae Klong and Umphang of Umphang district, Tak province, northern Thailand, during May to September 2018. A survey method using sweep net was employed along line transects between 10.00-12.00 a.m. and 13.00-15.00 p.m. A total of 337 butterflies representing 37 species, 26 genera in five families were encountered. The family Nymphalidae held the highest species richness (15 species), followed by Papilionidae (9 species) and Pieridae (6 speices), respectively. Herein, four uncommon species, namely Junonia iphita iphita, Tanaecia julii odilina, Penthema darlisa melema, and Papilio alcmenor alcmenor, were discovered in this time. The Shannon diversity (H’) for all samples obtained from the pooled data set of this observation valued 2.563 with relatively high values of Evenness (J’= 0.710) and Simpson index and (D = 0.829). For similarity index (Ss), the assemblage recorded of butterfly species between Mae Klang-Umphang shared about 0.629, implying that the environmental conditions in both surveyed zones were alike. Additionally, the accumulation curve in both locations of the butterfly was still increasing gradually when the collection ended, indicating that the lepidopteran species would be raised if we continue to survey more in next month. Nevertheless, to gain more butterfly taxa, observing different plant communities covering every season and using several survey techniques should be considered for further investigation.

Keywords: butterfly, biodiversity, tak province, thailand

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Authors: Julie Ann L. Gadin, Andrearose C. Igano, Carl Joseph S. Ignacio, Christopher C. Bacungan

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Corn production has become an important and pervasive industry in the Visayas for many years. Its role as a substitute commodity to rice heightens demand for health-particular consumers. Unfortunately, the corn industry is confronted with several challenges, such as weak institutions. Considering these issues, the paper examined the factors that influence corn production in the three administrative regions in the Visayas, namely, Western Visayas, Central Visayas, and Eastern Visayas. The data used was retrieved from a variety of publicly available data sources such as the Philippine Statistics Authority, the Department of Agriculture, the Philippine Crop Insurance Corporation, and the International Disaster Database. Utilizing a dataset from 2002 to 2019, the indicators were tested using three multiple linear regression (MLR) models. Results showed that the land area harvested (p=0.02), and the value of corn production (p=0.00) are statistically significant variables that influence corn production in the Visayas. Given these findings, it is suggested that the policy of forest conversion and sustainable land management should be effective in enabling farmworkers to obtain land to grow corn crops, especially in rural regions. Furthermore, the Biofuels Act of 2006, the Livestock Industry Restructuring and Rationalization Act, and supported policy, Senate Bill No. 225, or an Act Establishing the Philippine Corn Research Institute and Appropriating Funds, should be enforced inclusively in order to improve the demand for the corn-allied industries which may lead to an increase in the value and volume of corn production in the Visayas.

Keywords: corn, industry, production, MLR, Visayas

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Authors: Srikantan L. Jayasri, James Gan

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The changes in Singapore’s land use, natural preference of long-tailed macaques (Macaca fascicularis) to live in forest edges and their adaptability has led to interface between humans and macaques. Studies have shown that two-third of human-macaque interactions in Singapore were related to human food. We aimed to assess differences among macaques groups in their dependence on human food and interaction with humans as indicators of the level of interface. Field observations using instantaneous scan sampling and all occurrence ad-lib sampling were carried out for 23 macaque groups over 28 days recording 71.5 hours of observations. Data on macaque behaviour, demography, frequency, and nature of human-macaque interactions were collected. None of the groups were found to completely rely on human food source. Of the 23 groups, 40% of them were directly or indirectly provisioned by humans. One-third of the groups observed engaged in some form of interactions with the humans. Three groups that were directly fed by humans contributed to 83% of the total human-macaque interactions observed during the study. Our study indicated that interactions between humans and macaques exist in specific groups and in those fed by humans regularly. Although feeding monkeys is illegal in Singapore, such incidents seem to persist in specific locations. We emphasize the importance of group and location-specific assessment of the existing human-wildlife interactions. Conflict management strategies developed should be location specific to address the cause of interactions.

Keywords: primates, Southeast Asia, wildlife management, Singapore

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Authors: Ramesh Subramani, Mathivanan Narayanasamy, William Aalbersberg

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It is well accepted by last 35 years of research and on-going programmes that marine environment harbours abundant and unique biodiversity, which is currently playing as an important source in bioprospecting. It has become apparent that marine microorganisms are lead in the biodiscovery. Among marine organisms, actinobacteria are a target phylum for discovering novel antibiotics against increasing the multi-drug resistant human pathogens because of these taxa representing for novel genera and species. Marine actinomycetes are a proven source of new antibiotic leads and novel enzymes with important industrial applications. A total of 183 streptomycete and 25 non-streptomycete strains were isolated from different marine samples collected from north-eastern part of the Indian Ocean. Among them, 111 isolates displayed antibacterial activity against human pathogens and 151 exhibited antifungal activity against phytopathogens. Importantly, most of them produced various extracellular enzymes and 58 of them produced exopolysaccharides. Totally eight small bioactive compounds and a thermostable alkaline protease have been purified from a selected strain, Streptomyces fungicidicus. Besides, our on-going studies on non-streptomycete strains (rare actinomycetes) are most likely promising resource for new and unique compounds against current emerging drug-resistant pathogens. We have just recognised the chemical diversity in marine microorganisms. Therefore it is worthwhile to continue the exploration of marine microorganisms for new drug leads, novel enzymes and other bioprospecting research.

Keywords: bioactive compounds, industrial enzymes, marine actinobacteria, microbial metabolites, marine natural products

Procedia PDF Downloads 279

Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Minakshi Jain, I. P. Singh

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The mountain system makes the one fifth of the world’s landscape and is the home to the 600 million people. Though hills and mountains contain about 10 percent of the total population of the country, yet almost half of the country’s population living in or adjacent to the mountain areas depend directly or indirectly on the resources of the hills. Mountain environments are essential to the survival of the global ecosystems, as they sustain the economy of India through its perennial river system and precious forest wealth. Hill areas, with distinct climate, diverse vegetation and valuable flora & fauna are distinguished primarily by unique eco-system, rich both in bio-diversity and visual resources. These areas have special significance in terms of environment and economy. Still the irony is that these mountain ecosystems are fragile and highly susceptible to disturbance, with a low ability to rebound and heal after damage. Hills are home to endangered species, biological diversity and an essential part of the ecosystem. They are extremely sensitive to any human related development. Natural systems are the most ignored in the hills. The way the cities and towns have encroached them today has the serious repercussions on the climate. Amidst immense resources and constraints of nature, the town had a fantastic diversity of cultural and ethnic characteristics nurtured through ages along river basin and valley strung across the length and breadth of this Himalayan setting.

Keywords: eco-system, bio-diversity, urban sprawl, vernacular landscape

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Authors: Rachel Thomas Tharmabalan

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The growing unease over the matter of food security in the world is the result of a maturing realization that the genetic base of most human caloric intake from plants is dangerously narrow. Malaysia’s tropical rainforests have the potential to contribute to diet diversification and provide a source of nutrient-rich food as the Orang Asli communities in Malaysia have relied almost entirely on the jungle for food, fodder, medicine and fuel antithetical to what is happening today. This segregation of the Orang Asli from traditional lands and resources leads to severe loss of knowledge of biodiversity. In order to preserve these wild edibles, four different types of vegetables that are frequently consumed by the Orang Asli which consists of Rebu, Meranti, Saya and Pama were selected. These vegetables were then analysed to determine its proximate and mineral content to help ascertain claims and reaffirm the impact it can play in ensuring food and nutrition security, in addition to combating chronic diseases. From the results obtained, the Meranti had the highest crude fiber, iron and calcium content. Other minerals such as potassium, magnesium and copper were also found in varying content. These wild edibles could also contribute to education and bring awareness to younger generations as well as urban populations to start consuming more of these in their daily life as it could prevent various chronic diseases in Malaysia.

Keywords: food and nutrition security, Orang Asli, underutilized plants, wild edible food systems

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Authors: Ansong Richard Omari, Yosei Oikawa, Yoshiharu Fujii, Dorothea Sonoko Bellingrath-Kimura

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Renewed interest in soil management aimed at improving the productive capacity of Sub Saharan Africa (SSA) soils has called for the need to analyse the long term effect of different fertilization systems on soil. This study was conducted in two agroecological zones (i.e., Guinea Savannah (GS) and Deciduous forest (DF)) of Ghana to evaluate the impacts of long term (> 5 years) fertilization schemes on soil chemical and microbial properties. Soil samples under four different fertilization schemes (inorganic, inorganic and organic, organic, and no fertilization) were collected from 20 farmers` field in both agroecological zones. Soil analyses were conducted using standard procedures. All average soil quality parameters except extractable C, potential mineralizable nitrogen and CEC were significantly higher in DF sites compared to GS. Inorganic fertilization proved superior in soil chemical and microbial biomass especially in GS zone. In GS, soil deterioration index (DI) revealed that soil quality deteriorated significantly (−26%) under only organic fertilization system whereas soil improvement was observed under inorganic and no fertilization sites. In DF, either inorganic or organic and inorganic fertilization showed significant positive effects on soil quality. The high soil chemical composition and enhanced microbial biomass in DF were associated with the high rate of inorganic fertilization.

Keywords: deterioration index, fertilization scheme, microbial biomass, tropical agroecological zone

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Authors: Y. Sarı Nayim, B. N. Nayim

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This research proposal includes the defining and evaluation of the semi-natural and cultural ecosystems at Bartın University main campus in Turkey in terms of landscape mosaics. The ecosystem mosaic of the main campus was divided into zones based on ecological classification technique. Based on the results from the study, it was found that 6 different ecosystem mosaics should be used as a base in the planning and design of the existing and future landscape planning of Kutlubeyyazıcılar campus. The first landscape zone involves the 'social areas'. These areas include yards, dining areas, recreational areas and lawn areas. The second landscape zone is 'main vehicle and pedestrian areas'. These areas include vehicle access to the campus landscape, moving in the campus with vehicles, parking and pedestrian walk ways. The third zone is 'landscape areas with high visual landscape quality'. These areas will be the places where attractive structural and plant landscape elements will be used. Fourth zone will be 'landscapes of building borders and their surroundings.' The fifth and important zone that should be survived in the future is 'Actual semi-natural forest and bush areas'. And the last zone is 'water landscape' which brings ecological value to landscape areas. While determining the most convenient areas in the planning and design of the campus, these landscape mosaics should be taken into consideration. This zoning will ensure that the campus landscape is protected and living spaces in the campus apart from the areas where human activities are carried out will be used properly.

Keywords: campus landscape planning and design, landscape ecology, landscape mosaics, Bartın

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Authors: Revoti Prasad Bora, Nikita Katyal

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Promotion is a key element in the retail business. Thus, analysis of promotions to quantify their effectiveness in terms of Revenue and/or Margin is an essential activity in the retail industry. However, measuring the sales/revenue uplift is based on estimations, as the actual sales/revenue without the promotion is not present. Further, the presence of Halo and Cannibalization in a multiple parallel promotions’ scenario complicates the problem. Calculating Baseline by considering inter-brand/competitor items or using Halo and Cannibalization's impact on Revenue calculations by considering Baseline as an interpretation of items’ unit sales in neighboring nonpromotional weeks individually may not capture the overall Revenue uplift in the case of multiple parallel promotions. Hence, this paper proposes a Machine Learning based method for calculating the Revenue uplift by considering the Halo and Cannibalization impact on the Baseline and the Revenue. In the first section of the proposed methodology, Baseline of an item is calculated by incorporating the impact of the promotions on its related items. In the later section, the Revenue of an item is calculated by considering both Halo and Cannibalization impacts. Hence, this methodology enables correct calculation of the overall Revenue uplift due a given promotion.

Keywords: Halo, Cannibalization, promotion, Baseline, temporary price reduction, retail, elasticity, cross price elasticity, machine learning, random forest, linear regression

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

Abstract:

In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Pamir Gogoi, Ratree Wayland

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This study investigates the acoustic measures of breathiness when coarticulated with nasality. The acoustic correlates of breathiness and nasality that has already been well established after years of empirical research. Some of these acoustic parameters - like low frequency peaks and wider bandwidths- are common for both nasal and breathy voice. Therefore, it is likely that these parameters interact when a sound is coarticulated with breathiness and nasality. This leads to the hypothesis that the acoustic parameters, which usually act as robust cues in differentiating between breathy and modal voice, might not be reliable cues for differentiating between breathy and modal voice when breathiness is coarticulated with nasality. The effect of nasality on the perception of breathiness has been explored in earlier studies using synthesized speech. The results showed that perceptually, nasality and breathiness do interact. The current study investigates if a similar pattern is observed in natural speech. The study is conducted on Marathi, an Indo-Aryan language which has a three-way contrast between nasality and breathiness. That is, there is a phonemic distinction between nasals, breathy voice and breathy-nasals. Voice quality parameters like – H1-H2 (Difference between the amplitude of first and second harmonic), H1-A3 (Difference between the amplitude of first harmonic and third formant, CPP (Cepstral Peak Prominence), HNR (Harmonics to Noise ratio) and B1 (Bandwidth of first formant) were extracted. Statistical models like linear mixed effects regression and Random Forest classifiers show that measures that capture the noise component in the signal- like CPP and HNR- can classify breathy voice from modal voice better than spectral measures when breathy voice is coarticulated with nasality.

Keywords: breathiness, marathi, nasality, voice quality

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Authors: Kavita Bodke

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Structural health monitoring (SHM) is experiencing growth, necessitating the development of distinct methodologies to address its expanding scope effectively. In this study, we developed automatic structure damage identification, which incorporates three unique types of a building’s structural integrity. The first pertains to the presence of fractures within the structure, the second relates to the issue of dampness within the structure, and the third involves corrosion inside the structure. This study employs image classification techniques to discern between intact and impaired structures within structural data. The aim of this research is to find automatic damage detection with the probability of each damage class being present in one image. Based on this probability, we know which class has a higher probability or is more affected than the other classes. Utilizing photographs captured by a mobile camera serves as the input for an image classification system. Image classification was employed in our study to perform multi-class and multi-label classification. The objective was to categorize structural data based on the presence of cracks, moisture, and corrosion. In the context of multi-class image classification, our study employed three distinct methodologies: Random Forest, Multilayer Perceptron, and CNN. For the task of multi-label image classification, the models employed were Rasnet, Xceptionet, and Inception.

Keywords: SHM, CNN, deep learning, multi-class classification, multi-label classification

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

Procedia PDF Downloads 259

Authors: Aree Thongpukdee, Chockpisit Thepsithar, Chuthalak Thammaso

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Use of plants grown in local area for edible has a long tradition in different culture. The indigenous knowledge such as usage of plants as vegetables by local people is risk to disappear when no records are done. In order to conserve and transfer this valuable heritage to the new generation, ethnobotanical study should be investigated and documented. The survey of vegetable plants traditionally used was carried out in the year 2012. Information was accumulated via questionnaires and oral interviewing from 100 people living in 36 villages of 9 districts in Amphoe Huai Mek, Kalasin, Thailand. Local plant names, utilized parts and preparation methods of the plants were recorded. Each mentioned plant species were collected and voucher specimens were prepared. A total of 55 vegetable plant species belonging to 34 families and 54 genera were identified. The plant habits were tree, shrub, herb, climber, and shrubby fern at 21.82%, 18.18%, 38.18%, 20.00% and 1.82% respectively. The most encountered vegetable plant families were Leguminosae (20%), Cucurbitaceae (7.27%), Apiaceae (5.45%), whereas families with 3.64% uses were Araceae, Bignoniaceae, Lamiaceae, Passifloraceae, Piperaceae and Solanaceae. The most common consumptions were fresh or brief boiled young shoot or young leaf as side dishes of ‘jaeo, laab, namprik, pon’ or curries. Most locally known vegetables included 45% of the studied plants which grow along road side, backyard garden, hedgerow, open forest and rice field.

Keywords: vegetable plants, ethnobotanical survey, Kalasin, Thailand

Procedia PDF Downloads 318

Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

Procedia PDF Downloads 126

Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

Procedia PDF Downloads 411

Authors: Gatot Dwi Hendro, Hayyan ul Haq

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This work aims to explore the strategy in embodying the ecological validity in creating the sustainability of public policy, particularly in strengthening the green economy in Indonesia. This green economy plays an important role in supporting the national development in Indonesia, as it is a part of the national policy that posits the primary priority in Indonesian governance. The green economy refers to the national development covering strategic natural resources, such as mining, gold, oil, coal, forest, water, marine, and the other supporting infrastructure for products and distribution, such as fabrics, roads, bridges, and so forth. Thus, all activities in those national development should consider the sustainability. This sustainability requires the strong commitment of the national and regional government, as well as the local governments to put the ecology as the main requirement for issuing any policy, such as licence in mining production, and developing and building new production and supporting infrastructures for optimising the national resources. For that reason this work will focus on the strategy how to embody the ecological values and norms in the public policy. In detail, this work will offer the method, i.e. legal techniques, in visualising and embodying the norms and public policy that valid ecologically. This ecological validity is required in order to maintain and sustain our collective life.

Keywords: ecological validity, sustainable development, coherence, Indonesian Pancasila values, environment, marine

Procedia PDF Downloads 487

Authors: Anny Lucrece Nlend Nkott, Ludovic Temple

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The appearance in 2012 of the CRISPR-CaS9 genome editing technique marks a turning point in the field of genetics. This technique would make it possible to create new varieties quickly and cheaply. Although some consider CRISPR-CaS9 to be revolutionary, others consider it a potential societal threat. To document the controversy, we explain the socioeconomic conditions under which this technique could be accepted for the creation of a rainfed rice variety in Madagascar. The methodological framework is based on 38 individual and semistructured interviews, a multistakeholder forum with 27 participants, and a survey of 148 rice producers. Results reveal that the acceptability of genome editing requires (i) strengthening the seed system through the operationalization of regulatory structures and the upgrading of stakeholders' knowledge of genetically modified organisms, (ii) assessing the effects of the edited variety on biodiversity and soil nitrogen dynamics, and (iii) strengthening the technical and human capacities of the biosafety body. Structural mechanisms for regulating the seed system are necessary to ensure safe experimentation of genome editing techniques. Organizational innovation also appears to be necessary. The study documents how collective learning between communities of scientists and nonscientists is a component of systemic processes of varietal innovation. This study was carried out with the financial support of the GENERICE project (Generation and Deployment of Genome-Edited, Nitrogen-use-Efficient Rice Varieties), funded by the Agropolis Foundation.

Keywords: CRISPR-CaS9, varietal innovation, seed system, innovation system

Procedia PDF Downloads 155

Authors: Fani Sakellariadou

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The Blue Economy includes all marine-based and marine-related activities. They correspond to established, emerging as well as unborn ocean-based industries. Seabed mining is an emerging marine-based activity; its operations depend particularly on cutting-edge science and technology. The 21st century will face a crisis in resources as a consequence of the world’s population growth and the rising standard of living. The natural capital stored in the global ocean is decisive for it to provide a wide range of sustainable ecosystem services. Seabed mineral deposits were identified as having a high potential for critical elements and base metals. They have a crucial role in the fast evolution of green technologies. The major categories of marine mineral deposits are deep-sea deposits, including cobalt-rich ferromanganese crusts, polymetallic nodules, phosphorites, and deep-sea muds, as well as shallow-water deposits including marine placers. Seabed mining operations may take place within continental shelf areas of nation-states. In international waters, the International Seabed Authority (ISA) has entered into 15-year contracts for deep-seabed exploration with 21 contractors. These contracts are for polymetallic nodules (18 contracts), polymetallic sulfides (7 contracts), and cobalt-rich ferromanganese crusts (5 contracts). Exploration areas are located in the Clarion-Clipperton Zone, the Indian Ocean, the Mid Atlantic Ridge, the South Atlantic Ocean, and the Pacific Ocean. Potential environmental impacts of deep-sea mining include habitat alteration, sediment disturbance, plume discharge, toxic compounds release, light and noise generation, and air emissions. They could cause burial and smothering of benthic species, health problems for marine species, biodiversity loss, reduced photosynthetic mechanism, behavior change and masking acoustic communication for mammals and fish, heavy metals bioaccumulation up the food web, decrease of the content of dissolved oxygen, and climate change. An important concern related to deep-sea mining is our knowledge gap regarding deep-sea bio-communities. The ecological consequences that will be caused in the remote, unique, fragile, and little-understood deep-sea ecosystems and inhabitants are still largely unknown. The blue economy conceptualizes oceans as developing spaces supplying socio-economic benefits for current and future generations but also protecting, supporting, and restoring biodiversity and ecological productivity. In that sense, people should apply holistic management and make an assessment of marine mining impacts on ecosystem services, including the categories of provisioning, regulating, supporting, and cultural services. The variety in environmental parameters, the range in sea depth, the diversity in the characteristics of marine species, and the possible proximity to other existing maritime industries cause a span of marine mining impact the ability of ecosystems to support people and nature. In conclusion, the use of the untapped potential of the global ocean demands a liable and sustainable attitude. Moreover, there is a need to change our lifestyle and move beyond the philosophy of single-use. Living in a throw-away society based on a linear approach to resource consumption, humans are putting too much pressure on the natural environment. Applying modern, sustainable and eco-friendly approaches according to the principle of circular economy, a substantial amount of natural resource savings will be achieved. Acknowledgement: This work is part of the MAREE project, financially supported by the Division VI of IUPAC. This work has been partly supported by the University of Piraeus Research Center.

Keywords: blue economy, deep-sea mining, ecosystem services, environmental impacts

Procedia PDF Downloads 85

Authors: Hany Mustafa, Mahmoud Roushdi, Khaled Kheireldin

Abstract:

Rainfall variability is an important feature of semi-arid climates. Climate change is very likely to increase the frequency, magnitude, and variability of extreme weather events such as droughts, floods, and storms. The Blue Nile Basin is facing extreme climate change-related events such as floods and droughts and its possible impacts on ecosystem, livelihood, agriculture, livestock, and biodiversity are expected. Rainfall variability is a threat to food production in the Blue Nile Basin countries. This study investigates the long-term variations and trends of seasonal and annual precipitation over the Blue Nile Basin for 102-year period (1901-2002). Six statistical trend analysis of precipitation was performed with nonparametric Mann-Kendall test and Sen's slope estimator. On the other hands, four statistical absolute homogeneity tests: Standard Normal Homogeneity Test, Buishand Range test, Pettitt test and the Von Neumann ratio test were applied to test the homogeneity of the rainfall data, using XLSTAT software, which results of p-valueless than alpha=0.05, were significant. The percentages of significant trends obtained for each parameter in the different seasons are presented. The study recommends adaptation strategies to be streamlined to relevant policies, enhancing local farmers’ adaptive capacity for facing future climate change effects.

Keywords: Blue Nile basin, climate change, Mann-Kendall test, trend analysis

Procedia PDF Downloads 552