Search results for: forest soil

Authors: Dan Li, Hao Tang

Abstract:

The idea of “public bonds” was foreign to Qing China because it went against the traditional political ideology that supported that the emperor had absolute ownership over the nation. When a new fiscal crisis emerged out of the First Sino-Japanese War in 1894, the Qing rulers had no better option than to issue domestic bonds. This article documents the processes of issuance, distribution, and reimbursement for a total of three bonds issued by the Qing. These processes reveal how a well-established Western fiscal instrument could be extremely awkward and difficult to implant in China—a culturally, politically, and institutionally different society. Our paper sheds light on why Qing China failed to rise as a modern fiscal state.

Keywords: public bond, Qing China, fiscal crisis, fiscal state, the first Sino-Japanese war

Procedia PDF Downloads 130

Authors: Revoti Prasad Bora, Nikita Katyal

Abstract:

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

Procedia PDF Downloads 162

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

Procedia PDF Downloads 86

Authors: Pamir Gogoi, Ratree Wayland

Abstract:

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

Procedia PDF Downloads 77

Authors: Kavita Bodke

Abstract:

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

Procedia PDF Downloads 23

Authors: Raymond Xu, Cindy Jingru Wang

Abstract:

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 230

Authors: Aree Thongpukdee, Chockpisit Thepsithar, Chuthalak Thammaso

Abstract:

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 296

Authors: Muhammad Ali

Abstract:

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 107

Authors: Walid Moudani

Abstract:

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 399

Authors: M. S. Baazzim, M. S. Al-Saud, M. A. El-Kady

Abstract:

In this paper, steady-state ampacity (current carrying capacity) evaluation of underground power cable system by using analytical and numerical methods for different conditions (depth of cable, spacing between phases, soil thermal resistivity, ambient temperature, wind speed), for two system voltage level were used 132 and 380 kV. The analytical method or traditional method that was used is based on the thermal analysis method developed by Neher-McGrath and further enhanced by International Electrotechnical Commission (IEC) and published in standard IEC 60287. The numerical method that was used is finite element method and it was recourse commercial software based on finite element method.

Keywords: cable ampacity, finite element method, underground cable, thermal rating

Procedia PDF Downloads 365

Authors: K. E. Daryani, H. Mohamad

Abstract:

Uncertainties in the geo-structure analysis and design have a significant impact on the safety of slopes. Traditionally, uncertainties in the geotechnical design are addressed by incorporating a conservative factor of safety in the analytical model. In this paper, a risk-based approach is adopted to assess the influence of the geotechnical variable uncertainties on the stability of infinite slopes in cohesionless soils using the “partial factor of safety on shear strength” approach as stated in Eurocode 7. Analyses conducted using Monte Carlo simulation show that the same partial factor can have very different levels of risk depending on the degree of uncertainty of the mean values of the soil friction angle and void ratio.

Keywords: Safety, Probability of Failure, Reliability, Infinite Slopes, Sand.

Procedia PDF Downloads 564

Authors: Gatot Dwi Hendro, Hayyan ul Haq

Abstract:

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 474

Authors: Seyed Ali Mohammad, Modarres Sanavy, Hamed Keshavarz, Ali Mokhtassi-Bidgoli

Abstract:

One of the biggest challenges for the current and future generations is to produce sufficient food for the world population with the existing limited available water resources. Peppermint is a specialty crop used for food and medicinal purposes. Its main component is menthol. It is used predominantly for oral hygiene, pharmaceuticals, and foods. Although drought stress is considered as a negative factor in agriculture, being responsible for severe yield losses; medicinal plants grown under semi-arid conditions usually produce higher concentrations of active substances than same species grown under moderate climates. Nitrogen (N) fertilizer management is central to the profitability and sustainability of forage crop production. Sub-optimal N supply will result in poor yields, and excess N application can lead to nitrate leaching and environmental pollution. In order to determine the response of peppermint to drought stress and different fertilizer treatments, a field experiment with peppermint was conducted in a sandy loam soil at a site of the Tarbiat Modares University, Agriculture Faculty, Tehran, Iran. The experiment used a complete randomized block design, with six rates of fertilizer strategies (F1: control, F2: Urea, F3: 75% urea + 25% vermicompost, F4: 50% urea + 50% vermicompost, F5: 25% urea + 75% vermicompost and F6: vermicompost) and three irrigation regime (S1: 45%, S2: 60% and S3: 75% FC) with three replication. The traits such as nitrogen, chlorophyll, carotenoids, anthocyanin, flavonoid and fresh biomass were studied. The results showed that the treatments had a significant effect on the studied traits as drought stress reduced photosynthetic pigment concentration. Also, drought stress reduced fresh yield of peppermint. Non stress condition had the greater amount of chlorophyll and fresh yield more than other irrigation treatments. The highest concentration of chlorophyll and the fresh biomass was obtained in F2 fertilizing treatments. Sever water stress (S1) produced decreased photosynthetic pigment content fresh yield of peppermint. Supply of N could improve photosynthetic capacity by enhancing photosynthetic pigment content. Perhaps application of vermicompost significantly improved the organic carbon, available N, P and K content in soil over urea fertilization alone. To get sustainable production of peppermint, application of vermicompost along with N through synthetic fertilizer is recommended for light textured sandy loam soils.

Keywords: fresh yield, peppermint, synthetic nitrogen, vermicompost, water stress

Procedia PDF Downloads 207

Authors: Sagir M. Yusuf, Chris Baber

Abstract:

In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

Procedia PDF Downloads 108

Authors: Subrat Roy

Abstract:

This paper describes the findings of a study carried out for evaluating the performance of cell-filled pavement for low volume roads. Details of laboratory investigations and the methodology adopted for construction of cell-filled pavement are presented. The aim of this study is to evaluate the structural behaviour of cement concrete filled cell pavement laid over three different types of subbases (water bound macadam, soil-cement and moorum). A formwork of cells of a thin plastic sheet was used to construct the cell-filled pavements to form flexible, interlocked block pavements. Surface deflections were measured using falling weight deflectometer and benkelman beam methods. Resilient moduli of pavement layers were estimated from the measured deflections. A comparison of deflections obtained from both the methodology is also presented.

Keywords: cell-filled pavement, WBM, FWD, Moorum

Procedia PDF Downloads 290

Authors: Reshmi Vijayan

Abstract:

Alkaline protease is one of the most important enzymes in the biological world. Microbial production of alkaline protease is getting more attention from researchers due to its unique properties and substantial activity. Microorganisms are the most common sources of commercial enzymes due to their physiological and biochemical properties. The study was conducted on Ayiramthenghu mangrove sediments to isolate protease producing bacteria. All the isolates were screened for proteolytic activity on a skim milk agar plate at 37˚C for 48hrs. Protease activities were determined by the formation of a clear zone around the colonies on Skim milk agar medium. The activity of the enzyme was measured by the tyrosine standard curve, and it was found to be 0.186285 U/ml/min.

Keywords: protease, protease assay, skim milk agar medium, mangrove ecosystem

Procedia PDF Downloads 83

Authors: Abdullahi Jibrin, Aishetu Abdulkadir

Abstract:

The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

Procedia PDF Downloads 434

Authors: Rino Gubiani, Gianfranco Pergher

Abstract:

The work focused on the statistical analysis of accidents in the forestry sector (2000-2020) in Friuli-Venezia Giulia region, located in the North-East of Italy. The aim of the work was to analyse the evolution of the casualties throughout time and to evaluate possible improvements in the sector. It was shown that even nowadays the rate of accidents in forestry work is higher compared with all the other sectors, including agriculture; moreover, it was highlighted that some accidents remained present throughout the whole analysed range, such as slipping on the soil, being hit by trees and falling down from the plants. The results showed that an increase in forestry exploitation could even increase the total number of accidents, if advanced technological machines, such as cable cranes, would not implemented, given the fact that there is also a significant number of old people (above 50 years old) working in the sector.

Keywords: safety, forestry work, accidents, risk analysis, casualties, statistical analysis

Procedia PDF Downloads 123

Authors: Milind Chaudhari, Suhail Balasinor

Abstract:

Due to massive deforestation and an ever-increasing population, the organic content of the soil is depleting at a much faster rate. Due to this, there is a big chance that the entire food production in the world will drop by 40% in the next two decades. Vertical farming can help in aiding food production by leveraging big data and cloud computing to ensure plants are grown naturally by providing the optimum nutrients sunlight by analyzing millions of data points. This paper outlines the most important parameters in vertical farming and how a combination of big data and AI helps in calculating and analyzing these millions of data points. Finally, the paper outlines how different organizations are controlling the indoor environment by leveraging big data in enhancing food quantity and quality.

Keywords: big data, IoT, vertical farming, indoor farming

Procedia PDF Downloads 162

Authors: S. Niamkaeo, O. Robert, O. Chaowalit

Abstract:

In this investigation, we focus on discovering spatial relationship of drug smuggling along the northern border of Thailand. Thailand is no longer a drug production site, but Thailand is still one of the major drug trafficking hubs due to its topographic characteristics facilitating drug smuggling from neighboring countries. Our study areas cover three districts (Mae-jan, Mae-fahluang, and Mae-sai) in Chiangrai city and four districts (Chiangdao, Mae-eye, Chaiprakarn, and Wienghang) in Chiangmai city where drug smuggling of methamphetamine crystal and amphetamine occurs mostly. The data on drug smuggling incidents from 2011 to 2017 was collected from several national and local published news. Geo-spatial drug smuggling database was prepared. Decision tree algorithm was applied in order to discover the spatial relationship of factors related to drug smuggling, which was converted into rules using rule-based system. The factors including land use type, smuggling route, season and distance within 500 meters from check points were found that they were related to drug smuggling in terms of rules-based relationship. It was illustrated that drug smuggling was occurred mostly in forest area in winter. Drug smuggling exhibited was discovered mainly along topographic road where check points were not reachable. This spatial relationship of drug smuggling could support the Thai Office of Narcotics Control Board in surveillance drug smuggling.

Keywords: decision tree, drug smuggling, Geographic Information System, GIS knowledge discovery, rule-based system

Procedia PDF Downloads 159

Authors: Mohamed Bekhit Gad Khalil

Abstract:

This dam is the oldest dam in history. It was built by the ancient Egyptian around (2650 B.C) control flooding. It is believed to have been built between the third and fourth dynasties .It contains the oldest dam in history. Many studies have been conducted for the dam. This report was prepared under my supervision and in cooperation with the Ministry of Tourism and Antiquities. The dam was re-documented and photographed again. The dam on the northern side Consists of irregularly shaped stones of varying sizes used randomly. Sand and soil fill the gaps between the stones. creating layers to form the body of the dam. The eastern. side of the dam Consists of a series of regular shaped stones that have been cut and constructed into a stepped pyramid-like structure with width of (15,7) meters and height of (10) meters. The surface has significant erosion and wear on the stones due to weather Conditions. which has resulted in deep cavities in most of the stone blocks forming the surface.

Keywords: ministry of tourism and antiquities, excavations, registration, documentation

Procedia PDF Downloads 23

Authors: Vishaal Subramanian, Annuatha Vinod Kumar, Santosh Kumar Budankayala, M. Senthil Kumar

Abstract:

This paper discusses the aerodynamic and structural design, simulation and optimization of a mini-High Altitude Long Endurance (HALE) UAV. The applications of this mini HALE UAV vary from aerial topological surveys, quick first aid supply, emergency medical blood transport, search and relief activates to border patrol, surveillance and estimation of forest fire progression. Although classified as a mini UAV according to UVS International, our design is an amalgamation of the features of ‘mini’ and ‘HALE’ categories, combining the light weight of the ‘mini’ and the high altitude ceiling and endurance of the HALE. Designed with the idea of implementation in India, it is in strict compliance with the UAS rules proposed by the office of the Director General of Civil Aviation. The plane can be completely automated or have partial override control and is equipped with an Infra-Red camera and a multi coloured camera with on-board storage or live telemetry, GPS system with Geo Fencing and fail safe measures. An additional of 1.5 kg payload can be attached to three major hard points on the aircraft and can comprise of delicate equipment or releasable payloads. The paper details the design, optimization process and the simulations performed using various software such as Design Foil, XFLR5, Solidworks and Ansys.

Keywords: aircraft, endurance, HALE, high altitude, long range, UAV, unmanned aerial vehicle

Procedia PDF Downloads 387

Authors: Meri Khakhutaishvili, Indira Djaparidze, Maia Vanidze, Aleko Kalandia

Abstract:

Cultivation of blueberry in Georgia started in 21st century. There are more than 20 species of blueberry cultivated in this region from all other the world. The species are mostly planted on acidic soil, previously occupied by tea plantations. Many of the plantations have pretty good yield. It is known that changing the location of a plant to a new soil or climate effects chemical compositions of the plant. However, even though these plants are brought from other countries, no research has been conducted to fully examine the blueberry fruit cultivated in Georgia. Shota Rustaveli National Science Foundation Grant FR/335/10-160/14, gave us an opportunity to continue our previous works and conduct research on several berries, among them of course the chemical composition of stored Blueberry. We were able to conduct the first study that included examining qualitative and quantitative features of bioactive compounds in Georgian Blueberry. This experiments were held in the ‘West Georgia Regional Chromatography center’ (Grant AP/96/13) of our university, that is equipped with modern equipment like HPLC UV-Vis, RI-detector, HPLC-conductivity detector, UPLC-MS-detector. Biochemical analysis was conducted using different physico-chemical and instrumental methods. Separation-identification and quantitative analysis were conducted using UPLC-MS (Waters Acquity QDa detector), HPLC (Waters Brceze 1525, UV-Vis 2489 detectors), pH-meters (Mettler Toledo). Refractrometer -Misco , Spectrometer –Cuvette Changer (Mettler Toledo UV5A), C18 Cartridge Solid Phase Extraction (SPE) Waters Sep-Pak C18 (500 mg), Chemicals – stability radical- 2,2-Diphenil-1-picrilhydrazyl (Aldrich-germany), Acetonitrile, Methanol, Acetic Acid (Merck-Germany), AlCl3, Folin Ciocalteu reagent (preparation), Standarts –Callic acid, Quercetin. Carbohydrate HPLC-RI analysis used systems acetonitrile-water (80-20). UPLC-MS analysis used systems- solvent A- Water +1 % acetic acid და solvent -B Methanol +1% acetic acid). It was concluded that the amount of sugars was in range of 5-9 %, mostly glucose and fructose. Also, the amount of organic acids was 0.2-1.2% most of which was malic and citric acid. Anthocians were also present in the sample 200-550mg/100g. We were able to identify up to 15 different compounds, most of which were products of delphinidine and cyanide. All species have high antioxidant level(DPPH). By rapidly freezing the sample and then keeping it in specific conditions allowed us to keep the sample for 12 months.

Keywords: antioxidants, bioactive, blueberry, storage

Procedia PDF Downloads 196

Authors: Arezoo Sadrinezhad, Kallol Sett, S. I. Hariharan

Abstract:

In this paper, a probabilistic framework based on Fokker-Planck-Kolmogorov (FPK) approach has been applied to simulate triaxial cyclic constitutive behavior of uncertain soils. The framework builds upon previous work of the writers, and it has been extended for cyclic probabilistic simulation of triaxial undrained behavior of soils. von Mises elastic-perfectly plastic material model is considered. It is shown that by using probabilistic framework, some of the most important aspects of soil behavior under cyclic loading can be captured even with a simple elastic-perfectly plastic constitutive model.

Keywords: elasto-plasticity, uncertainty, soils, fokker-planck equation, fourier spectral method, finite difference method

Procedia PDF Downloads 360

Authors: Ruichong Zhang

Abstract:

This study proposes a recording-based approach to characterize and quantify earthquake-induced site nonlinearity, exemplified as soil nonlinearity and/or liquefaction. Alternative to Fourier spectral analysis (FSA), the paper introduces time-frequency analysis of earthquake ground motion recordings with the aid of so-called Hilbert-Huang transform (HHT), and offers justification for the HHT in addressing the nonlinear features shown in the recordings. With the use of the 2001 Nisqually earthquake recordings, this study shows that the proposed approach is effective in characterizing site nonlinearity and quantifying the influences in seismic ground responses.

Keywords: site nonlinearity, site amplification, site damping, Hilbert-Huang Transform (HHT), liquefaction, 2001 Nisqually Earthquake

Procedia PDF Downloads 475

Authors: Sheikh Samsuzzhan Alam

Abstract:

The present study investigates the selection of variogram model in analyzing spatial variations of environmental variables with the trend. Sometimes, the autofitted theoretical variogram does not really capture the true nature of the empirical semivariogram. So proper exploration and analysis are needed to select the best variogram model. For this study, an open source data collected from California Soil Resource Lab1 is used to explain the problems when fitting a theoretical variogram. Five most commonly used variogram models: Linear, Gaussian, Exponential, Matern, and Spherical were fitted to the experimental semivariogram. Ordinary kriging methods were considered to evaluate the accuracy of the selected variograms through cross-validation. This study is beneficial for selecting an appropriate theoretical variogram model for environmental variables.

Keywords: anisotropy, cross-validation, environmental variables, kriging, variogram models

Procedia PDF Downloads 320

Authors: Nuria Vargas, Frances Rodriguez

Abstract:

Neotropical medium cities have opportunities to develop in a good manner. Xalapa City (Veracruz capital, Mexico) and its metropolitan region, near to the Gulf of Mexico, has already <1 million inhabitants, a medium city size, but it’s growing rapidly as several cities in Latin America. Inside a landscape where it had been a forest cloud and coffee land, emerges the city with an irregular topography. The rapid grow of the urbanization and the loss of vegetation has result in a change on the climate parameters. Frequently warms spells, floods and landslides had been impacted last 2 decades, also a higher incidence of dengue and diarrhea is mentioned in the region. Therefore, the analysis of hydrometeorological events is crucial to understand the role they play in its problem. The urbanization and others radiative forces has created a modulation that can explain the decadal climate changes on the Xalapa region. The Atlantic Multidecadal Oscillation directly influences the temperature and precipitation of the region, even more than climate change does. The total effect of these drivers can create a significant context that origin more risk. However, the most policies frequently consider only the climate change as a principal factor, but other drivers are important to consider and evaluate for the implementation of actions that improve our ambient and cities, in a context of climate change. Medium-sized cities could create better conditions for future citizens, preventing with urban planning that considers possible risks associated with weather and climate.

Keywords: natural variability, urbanization, atlantic multidecadal oscillation, land use changes

Procedia PDF Downloads 54

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

Abstract:

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

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

Procedia PDF Downloads 124

Authors: Cinzia Federico, Gaetano Giudice, Salvatore Inguaggiato, Marco Liuzzo, Maria Pedone, Fabio Vita, Christoph Kern, Leonardo La Pica, Giovannella Pecoraino, Lorenzo Calderone, Vincenzo Francofonte

Abstract:

The periods of increased fumarolic activity at La Fossa volcano have been characterized, since early 80's, by changes in the gas chemistry and in the output rate of fumaroles. Excepting the direct measurements of the steam output from fumaroles performed from 1983 to 1995, the mass output of the single gas species has been recently measured, with various methods, only sporadically or for short periods. Since 2008, a scanning DOAS system is operating in the Palizzi area for the remote measurement of the in-plume SO₂ flux. On these grounds, the need of a cross-comparison of different methods for the in situ measurement of the output rate of different gas species is envisaged. In 2015, two field campaigns have been carried out, aimed at: 1. The mapping of the concentration of CO₂, H₂S and SO₂ in the fumarolic plume at 1 m from the surface, by using specific open-path diode tunable lasers (GasFinder Boreal Europe Ltd.) and an Active DOAS for SO₂, respectively; these measurements, coupled to simultaneous ultrasonic wind speed and meteorological data, have been elaborated to obtain the dispersion map and the output rate of single species in the overall fumarolic field; 2. The mapping of the concentrations of CO₂, H₂S, SO₂, H₂O in the fumarolic plume at 0.5 m from the soil, by using an integrated system, including IR spectrometers and specific electrochemical sensors; this has provided the concentration ratios of the analysed gas species and their distribution in the fumarolic field; 3. The in-fumarole sampling of vapour and measurement of the steam output, to validate the remote measurements. The dispersion map of CO₂, obtained from the tunable laser measurements, shows a maximum CO₂ concentration at 1m from the soil of 1000 ppmv along the rim, and 1800 ppmv in the inner slopes. As observed, the largest contribution derives from a wide fumarole of the inner-slope, despite its present outlet temperature of 230°C, almost 200°C lower than those measured at the rim fumaroles. Actually, fumaroles in the inner slopes are among those emitting the largest amount of magmatic vapour and, during the 1989-1991 crisis, reached the temperature of 690°C. The estimated CO₂ and H₂S fluxes are 400 t/d and 4.4 t/d, respectively. The coeval SO₂ flux, measured by the scanning DOAS system, is 9±1 t/d. The steam output, recomputed from CO₂ flux measurements, is about 2000 t/d. The various direct and remote methods (as described at points 1-3) have produced coherent results, which encourage to the use of daily and automatic DOAS SO₂ data, coupled with periodic in-plume measurements of different acidic gases, to obtain the total mass rates.

Keywords: DOAS, fumaroles, plume, tunable laser

Procedia PDF Downloads 386

Authors: Diane H. Dotson, Shari L. Rodriguez

Abstract:

Habitat for predators is on the decline worldwide, which often brings humans and predators into conflict over remaining shared space and common resources. While the direct impacts of human predator conflict on humans (i.e., attacks on livestock or humans resulting in injury or death) are well documented, the indirect impacts of conflict on humans (i.e., downstream effects such as fear, stress, opportunity costs, PTSD) have not been addressed. We interviewed 437 people living in 54 villages on the periphery of Kanha National Park, India, to assess the amount and severity of direct and indirect impacts of predator conflict. ​While 58% of livestock owners believed that predator attacks on livestock guards occurred frequently and 62% of those who collect forest products believed that predator attacks on those collecting occurred frequently, less than 20% of all participants knew of someone who had experienced an attack. Data related to indirect impacts suggest that such impacts are common; 76% of participants indicated they were afraid a predator will physically injure them. Livestock owners reported that livestock guarding took time away from their primary job (61%) and getting enough sleep (73%), and believed that it increased their vulnerability to illnesses (80%). These results suggest that the perceptions of risk of predator attack are likely inflated, yet the costs of human predator impacts may be substantially higher than previously estimated, particularly related to human well-being, making the implementation of appropriate and effective conservation and conflict mitigation strategies and policies increasingly urgent.

Keywords: direct impacts, indirect impacts, human-predator conflict, India

Procedia PDF Downloads 146