Search results for: forest fire detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4710

Search results for: forest fire detection

2250 Low-Cost, Portable Optical Sensor with Regression Algorithm Models for Accurate Monitoring of Nitrites in Environments

Authors: David X. Dong, Qingming Zhang, Meng Lu

Abstract:

Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.

Keywords: optical sensor, regression model, nitrites, water quality

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2249 Emotion Recognition in Video and Images in the Wild

Authors: Faizan Tariq, Moayid Ali Zaidi

Abstract:

Facial emotion recognition algorithms are expanding rapidly now a day. People are using different algorithms with different combinations to generate best results. There are six basic emotions which are being studied in this area. Author tried to recognize the facial expressions using object detector algorithms instead of traditional algorithms. Two object detection algorithms were chosen which are Faster R-CNN and YOLO. For pre-processing we used image rotation and batch normalization. The dataset I have chosen for the experiments is Static Facial Expression in Wild (SFEW). Our approach worked well but there is still a lot of room to improve it, which will be a future direction.

Keywords: face recognition, emotion recognition, deep learning, CNN

Procedia PDF Downloads 185
2248 Urban Search, Rescue and Rapid Field Assessment of Damaged and Collapsed Building Structures

Authors: Abid I. Abu-Tair, Gavin M. Wilde, John M. Kinuthia

Abstract:

Urban Search and Rescue (USAR) is a functional capability that has been developed to allow the United Kingdom Fire and Rescue Service to deal with ‘major incidents’ primarily involving structural collapse. The nature of the work undertaken by USAR means that staying out of a damaged or collapsed building structure is not usually an option for search and rescue personnel. As a result, there is always a risk that they could become victims. For this paper, a systematic and investigative review using desk research was undertaken to explore the role which structural engineering can play in assisting search and rescue personnel to conduct structural assessments when in the field. The focus is on how search and rescue personnel can assess damaged and collapsed building structures, not just in terms of the structural damage that may be countered, but also in relation to structural stability. Natural disasters, accidental emergencies, acts of terrorism and other extreme events can vary significantly in nature and ferocity, and can cause a wide variety of damage to building structures. It is not possible or, even realistic, to provide search and rescue personnel with definitive guidelines and procedures to assess damaged and collapsed building structures as there are too many variables to consider. However, understanding what implications damage may have upon the structural stability of a building structure will enable search and rescue personnel to judge better and quantify the risk from a life-safety standpoint. It is intended that this will allow search and rescue personnel to make informed decisions and ensure every effort is made to mitigate risk so that they do not become victims.

Keywords: damaged and collapsed building structures, life safety, quantifying risk, search and rescue personnel, structural assessments in the field

Procedia PDF Downloads 391
2247 Fault-Tolerant Control Study and Classification: Case Study of a Hydraulic-Press Model Simulated in Real-Time

Authors: Jorge Rodriguez-Guerra, Carlos Calleja, Aron Pujana, Iker Elorza, Ana Maria Macarulla

Abstract:

Society demands more reliable manufacturing processes capable of producing high quality products in shorter production cycles. New control algorithms have been studied to satisfy this paradigm, in which Fault-Tolerant Control (FTC) plays a significant role. It is suitable to detect, isolate and adapt a system when a harmful or faulty situation appears. In this paper, a general overview about FTC characteristics are exposed; highlighting the properties a system must ensure to be considered faultless. In addition, a research to identify which are the main FTC techniques and a classification based on their characteristics is presented in two main groups: Active Fault-Tolerant Controllers (AFTCs) and Passive Fault-Tolerant Controllers (PFTCs). AFTC encompasses the techniques capable of re-configuring the process control algorithm after the fault has been detected, while PFTC comprehends the algorithms robust enough to bypass the fault without further modifications. The mentioned re-configuration requires two stages, one focused on detection, isolation and identification of the fault source and the other one in charge of re-designing the control algorithm by two approaches: fault accommodation and control re-design. From the algorithms studied, one has been selected and applied to a case study based on an industrial hydraulic-press. The developed model has been embedded under a real-time validation platform, which allows testing the FTC algorithms and analyse how the system will respond when a fault arises in similar conditions as a machine will have on factory. One AFTC approach has been picked up as the methodology the system will follow in the fault recovery process. In a first instance, the fault will be detected, isolated and identified by means of a neural network. In a second instance, the control algorithm will be re-configured to overcome the fault and continue working without human interaction.

Keywords: fault-tolerant control, electro-hydraulic actuator, fault detection and isolation, control re-design, real-time

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2246 Development of Wide Bandgap Semiconductor Based Particle Detector

Authors: Rupa Jeena, Pankaj Chetry, Pradeep Sarin

Abstract:

The study of fundamental particles and the forces governing them has always remained an attractive field of theoretical study to pursue. With the advancement and development of new technologies and instruments, it is possible now to perform particle physics experiments on a large scale for the validation of theoretical predictions. These experiments are generally carried out in a highly intense beam environment. This, in turn, requires the development of a detector prototype possessing properties like radiation tolerance, thermal stability, and fast timing response. Semiconductors like Silicon, Germanium, Diamond, and Gallium Nitride (GaN) have been widely used for particle detection applications. Silicon and germanium being narrow bandgap semiconductors, require pre-cooling to suppress the effect of noise by thermally generated intrinsic charge carriers. The application of diamond in large-scale experiments is rare owing to its high cost of fabrication, while GaN is one of the most extensively explored potential candidates. But we are aiming to introduce another wide bandgap semiconductor in this active area of research by considering all the requirements. We have made an attempt by utilizing the wide bandgap of rutile Titanium dioxide (TiO2) and other properties to use it for particle detection purposes. The thermal evaporation-oxidation (in PID furnace) technique is used for the deposition of the film, and the Metal Semiconductor Metal (MSM) electrical contacts are made using Titanium+Gold (Ti+Au) (20/80nm). The characterization comprising X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM), Ultraviolet (UV)-Visible spectroscopy, and Laser Raman Spectroscopy (LRS) has been performed on the film to get detailed information about surface morphology. On the other hand, electrical characterizations like Current Voltage (IV) measurement in dark and light and test with laser are performed to have a better understanding of the working of the detector prototype. All these preliminary tests of the detector will be presented.

Keywords: particle detector, rutile titanium dioxide, thermal evaporation, wide bandgap semiconductors

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2245 Development of Geo-computational Model for Analysis of Lassa Fever Dynamics and Lassa Fever Outbreak Prediction

Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

Abstract:

Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

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2244 Biodiversity Indices for Macrobenthic Community structures of Mangrove Forests, Khamir Port, Iran

Authors: Mousa Keshavarz, Abdul-Reza Dabbagh, Maryam Soyuf Jahromi

Abstract:

The diversity of mangrove macrobenthos assemblages at mudflat and mangrove ecosystems of Port Khamir, Iran were investigated for one year. During this period, we measured physicochemical properties of water temperature, salinity, pH, DO and the density and distribution of the macrobenthos. We sampled a total of 9 transects, at three different topographic levels along the intertidal zone at three stations. Assemblages at class level were compared. The five most diverse and abundant classes were Foraminifers (54%), Gastropods (23%), Polychaetes (10%), Bivalves (8%) & Crustaceans (5%), respectively. Overall densities were 1869 ± 424 ind/m2 (26%) in spring, 2544 ± 383 ind/m2(36%) in summer, 1482 ± 323 ind/m2 (21%) in autumn and 1207 ± 80 ind/m2 (17%) in winter. Along the intertidal zone, the overall relative density of individuals at high, intermediate, and low topographic levels was 40, 30, and 30% respectively. Biodiversity indices were used to compare different classes: Gastropoda (Shannon index: 0.33) and Foraminifera (Simpson index: 0.28) calculated the highest scores. It was also calculated other bio-indices. With the exception of bivalves, filter feeders were associated with coarser sediments at higher intertidal levels, while deposit feeders were associated with finer sediments at lower levels. Salinity was the most important factor acting on community structure, while DO and pH had little influence.

Keywords: macrobenthos, biodiversity, mangrove forest, Khamir Port

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2243 Juniperus thurefera Multiplication Tests by Cauttigs in Aures, Algeria

Authors: N. Khater, S. A. Menina, H. Benbouza

Abstract:

Juniperus thurefera is an endemic cupressacée constitutes a forest cover in the mountains of Aures (Algeria). It is a heritage and important ecological richness but continues to decline, highly endangered species in danger of extinction, these populations show significant originality due to climatic conditions of the environment, because of its strength and extraordinary vitality, made a powerful but fragile and unique ecosystem in which natural regeneration by seed is almost absent in Algeria. Because of the quality of seeds that are either dormant or affected at the tree and the ground level by a large number of pests and parasites, which will lead to the total disappearance of this species and consequently leading to the biodiversity. View the ecological and socio- economic interest presented by this case, it deserves to be preserved and produced in large quantities in this respect. The present work aims to try to regenerate the Juniperus thurefera via vegetative propagation. We studied the potential of cuttings to form adventitious roots and buds. Cuttings were taken from young subjects from 5 to 20 years treated with indole butyric acid (AIB) and planted out-inside perlite under atomizer whose temperature and light are controlled. Results indicated that the percentage of developing buds on cuttings is better than the rooting ones.

Keywords: Juniperus thurefera, indole butyric acid, cutting, buds, rooting

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2242 Detection of Temporal Change of Fishery and Island Activities by DNB and SAR on the South China Sea

Authors: I. Asanuma, T. Yamaguchi, J. Park, K. J. Mackin

Abstract:

Fishery lights on the surface could be detected by the Day and Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi-NPP). The DNB covers the spectral range of 500 to 900 nm and realized a higher sensitivity. The DNB has a difficulty of identification of fishing lights from lunar lights reflected by clouds, which affects observations for the half of the month. Fishery lights and lights of the surface are identified from lunar lights reflected by clouds by a method using the DNB and the infrared band, where the detection limits are defined as a function of the brightness temperature with a difference from the maximum temperature for each level of DNB radiance and with the contrast of DNB radiance against the background radiance. Fishery boats or structures on islands could be detected by the Synthetic Aperture Radar (SAR) on the polar orbit satellites using the reflected microwave by the surface reflecting targets. The SAR has a difficulty of tradeoff between spatial resolution and coverage while detecting the small targets like fishery boats. A distribution of fishery boats and island activities were detected by the scan-SAR narrow mode of Radarsat-2, which covers 300 km by 300 km with various combinations of polarizations. The fishing boats were detected as a single pixel of highly scattering targets with the scan-SAR narrow mode of which spatial resolution is 30 m. As the look angle dependent scattering signals exhibits the significant differences, the standard deviations of scattered signals for each look angles were taken into account as a threshold to identify the signal from fishing boats and structures on the island from background noise. It was difficult to validate the detected targets by DNB with SAR data because of time lag of observations for 6 hours between midnight by DNB and morning or evening by SAR. The temporal changes of island activities were detected as a change of mean intensity of DNB for circular area for a certain scale of activities. The increase of DNB mean intensity was corresponding to the beginning of dredging and the change of intensity indicated the ending of reclamation and following constructions of facilities.

Keywords: day night band, SAR, fishery, South China Sea

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2241 A Techno-Economic Simulation Model to Reveal the Relevance of Construction Process Impact Factors for External Thermal Insulation Composite System (ETICS)

Authors: Virgo Sulakatko

Abstract:

The reduction of energy consumption of the built environment has been one of the topics tackled by European Commission during the last decade. Increased energy efficiency requirements have increased the renovation rate of apartment buildings covered with External Thermal Insulation Composite System (ETICS). Due to fast and optimized application process, a large extent of quality assurance is depending on the specific activities of artisans and are often not controlled. The on-site degradation factors (DF) have the technical influence to the façade and cause future costs to the owner. Besides the thermal conductivity, the building envelope needs to ensure the mechanical resistance and stability, fire-, noise-, corrosion and weather protection, and long-term durability. As the shortcomings of the construction phase become problematic after some years, the common value of the renovation is reduced. Previous work on the subject has identified and rated the relevance of DF to the technical requirements and developed a method to reveal the economic value of repair works. The future costs can be traded off to increased the quality assurance during the construction process. The proposed framework is describing the joint simulation of the technical importance and economic value of the on-site DFs of ETICS. The model is providing new knowledge to improve the resource allocation during the construction process by enabling to identify and diminish the most relevant degradation factors and increase economic value to the owner.

Keywords: ETICS, construction technology, construction management, life cycle costing

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2240 Modern Detection and Description Methods for Natural Plants Recognition

Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

Abstract:

Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT

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2239 Study of the Microflora of Cedar Forests with Different Degrees of Decline in the National Park Belezma (Batna, Algeria)

Authors: Cherak Imen, Sellami Mehdi

Abstract:

The Atlas cedar, Cedrus atlantica, is endemic to the mountains of North Africa. This is one of the most valuable softwood, both economically, ecologically, aesthetically and culturally. In Algeria, the cedar forests currently have worrying symptoms of decline which therefore require special monitoring. Fungal endophytes are involved in various diseases of the Atlas cedar. They attack all organs on which they cause many symptoms. These microflora live in complex interaction with plants. In this study, we identified a total of 09 mycotaxons collected needles Cedarwood at three stations with different degrees of decline (Talmet, Boumerzoug and Tuggurt) in the National Park Belezma (Batna, Algeria). The study conducted on a total of 12 trees were identified 08 mycoendophytes in Talmet station, 04 species in the Boumerzoug station and 03 in Tuggurt station. The total species richness mycoendophytes depending on the types of cedar forests showed that the largest diversity was recorded at the cedar forest healthy, Alternaria is the most common type in all stations. This work should be completed by further detailed studies to identify other endophyte species and better know its interactions with the Atlas cedar.

Keywords: Cedrus atlantica, endophytic fungi, microflora, mycotaxons, mycoendophyte

Procedia PDF Downloads 344
2238 Effect of External Radiative Heat Flux on Combustion Characteristics of Rigid Polyurethane Foam under Piloted-Ignition and Radiative Auto-Ignition Modes

Authors: Jia-Jia He, Lin Jiang, Jin-Hua Sun

Abstract:

Rigid polyurethane foam (RPU) has been extensively applied in building insulation system, yet with high flammability for being easily ignited by high temperature spark or radiative heat flux from other flaming materials or surrounding building facade. Using a cone calorimeter by Fire Testing Technology and thermal couple tree, this study systematically investigated the effect of radiative heat flux on the ignition time and characteristic temperature distribution during RPU combustion under different heat fluxes gradient (12, 15, 20, 25, 30, 35, 40, 45, and 50 kW/m²) with spark ignition/ignition by radiation. The ignition time decreases proportionally with increase of external heat flux, meanwhile increasing the external heat flux raises the peak heat release rate and impresses on the vertical temperature distribution greatly. The critical ignition heat flux is found to be 15 and 25 kW/m² for spark ignition and radiative ignition, respectively. Based on previous experienced ignition formula, a methodology to predict ignition times in both modes has been developed theoretically. By analyzing the heat transfer mechanism around the sample surroundings, both radiation from cone calorimeter and convection flow are considered and calculated theoretically. The experimental ignition times agree well with the theoretical ones in both radiative and convective conditions; however, the observed critical ignition heat flux is higher than the calculated one under piloted-ignition mode because the heat loss process, especially in lower heat flux radiation, is not considered in this developed methodology.

Keywords: rigid polyurethane foam, cone calorimeter, ignition time, external heat flux

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2237 3D Label-Free Bioimaging of Native Tissue with Selective Plane Illumination Optical Microscopy

Authors: Jing Zhang, Yvonne Reinwald, Nick Poulson, Alicia El Haj, Chung See, Mike Somekh, Melissa Mather

Abstract:

Biomedical imaging of native tissue using light offers the potential to obtain excellent structural and functional information in a non-invasive manner with good temporal resolution. Image contrast can be derived from intrinsic absorption, fluorescence, or scatter, or through the use of extrinsic contrast. A major challenge in applying optical microscopy to in vivo tissue imaging is the effects of light attenuation which limits light penetration depth and achievable imaging resolution. Recently Selective Plane Illumination Microscopy (SPIM) has been used to map the 3D distribution of fluorophores dispersed in biological structures. In this approach, a focused sheet of light is used to illuminate the sample from the side to excite fluorophores within the sample of interest. Images are formed based on detection of fluorescence emission orthogonal to the illumination axis. By scanning the sample along the detection axis and acquiring a stack of images, 3D volumes can be obtained. The combination of rapid image acquisition speeds with the low photon dose to samples optical sectioning provides SPIM is an attractive approach for imaging biological samples in 3D. To date all implementations of SPIM rely on the use of fluorescence reporters be that endogenous or exogenous. This approach has the disadvantage that in the case of exogenous probes the specimens are altered from their native stage rendering them unsuitable for in vivo studies and in general fluorescence emission is weak and transient. Here we present for the first time to our knowledge a label-free implementation of SPIM that has downstream applications in the clinical setting. The experimental set up used in this work incorporates both label-free and fluorescent illumination arms in addition to a high specification camera that can be partitioned for simultaneous imaging of both fluorescent emission and scattered light from intrinsic sources of optical contrast in the sample being studied. This work first involved calibration of the imaging system and validation of the label-free method with well characterised fluorescent microbeads embedded in agarose gel. 3D constructs of mammalian cells cultured in agarose gel with varying cell concentrations were then imaged. A time course study to track cell proliferation in the 3D construct was also carried out and finally a native tissue sample was imaged. For each sample multiple images were obtained by scanning the sample along the axis of detection and 3D maps reconstructed. The results obtained validated label-free SPIM as a viable approach for imaging cells in a 3D gel construct and native tissue. This technique has the potential use in a near-patient environment that can provide results quickly and be implemented in an easy to use manner to provide more information with improved spatial resolution and depth penetration than current approaches.

Keywords: bioimaging, optics, selective plane illumination microscopy, tissue imaging

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2236 Vaccination Coverage and Its Associated Factors in India: An ML Approach to Understand the Hierarchy and Inter-Connections

Authors: Anandita Mitro, Archana Srivastava, Bidisha Banerjee

Abstract:

The present paper attempts to analyze the hierarchy and interconnection of factors responsible for the uptake of BCG vaccination in India. The study uses National Family Health Survey (NFHS-5) data which was conducted during 2019-21. The univariate logistic regression method is used to understand the univariate effects while the interconnection effects have been studied using the Categorical Inference Tree (CIT) which is a non-parametric Machine Learning (ML) model. The hierarchy of the factors is further established using Conditional Inference Forest which is an extension of the CIT approach. The results suggest that BCG vaccination coverage was influenced more by system-level factors and awareness than education or socio-economic status. Factors such as place of delivery, antenatal care, and postnatal care were crucial, with variations based on delivery location. Region-specific differences were also observed which could be explained by the factors. Awareness of the disease was less impactful along with the factor of wealth and urban or rural residence, although awareness did appear to substitute for inadequate ANC. Thus, from the policy point of view, it is revealed that certain subpopulations have less prevalence of vaccination which implies that there is a need for population-specific policy action to achieve a hundred percent coverage.

Keywords: vaccination, NFHS, machine learning, public health

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2235 Detection of Phoneme [S] Mispronounciation for Sigmatism Diagnosis in Adults

Authors: Michal Krecichwost, Zauzanna Miodonska, Pawel Badura

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The diagnosis of sigmatism is mostly based on the observation of articulatory organs. It is, however, not always possible to precisely observe the vocal apparatus, in particular in the oral cavity of the patient. Speech processing can allow to objectify the therapy and simplify the verification of its progress. In the described study the methodology for classification of incorrectly pronounced phoneme [s] is proposed. The recordings come from adults. They were registered with the speech recorder at the sampling rate of 44.1 kHz and the resolution of 16 bit. The database of pathological and normative speech has been collected for the study including reference assessments provided by the speech therapy experts. Ten adult subjects were asked to simulate a certain type of stigmatism under the speech therapy expert supervision. In the recordings, the analyzed phone [s] was surrounded by vowels, viz: ASA, ESE, ISI, SPA, USU, YSY. Thirteen MFCC (mel-frequency cepstral coefficients) and RMS (root mean square) values are calculated within each frame being a part of the analyzed phoneme. Additionally, 3 fricative formants along with corresponding amplitudes are determined for the entire segment. In order to aggregate the information within the segment, the average value of each MFCC coefficient is calculated. All features of other types are aggregated by means of their 75th percentile. The proposed method of features aggregation reduces the size of the feature vector used in the classification. Binary SVM (support vector machine) classifier is employed at the phoneme recognition stage. The first group consists of pathological phones, while the other of the normative ones. The proposed feature vector yields classification sensitivity and specificity measures above 90% level in case of individual logo phones. The employment of a fricative formants-based information improves the sole-MFCC classification results average of 5 percentage points. The study shows that the employment of specific parameters for the selected phones improves the efficiency of pathology detection referred to the traditional methods of speech signal parameterization.

Keywords: computer-aided pronunciation evaluation, sibilants, sigmatism diagnosis, speech processing

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2234 A Hybrid Data Mining Algorithm Based System for Intelligent Defence Mission Readiness and Maintenance Scheduling

Authors: Shivam Dwivedi, Sumit Prakash Gupta, Durga Toshniwal

Abstract:

It is a challenging task in today’s date to keep defence forces in the highest state of combat readiness with budgetary constraints. A huge amount of time and money is squandered in the unnecessary and expensive traditional maintenance activities. To overcome this limitation Defence Intelligent Mission Readiness and Maintenance Scheduling System has been proposed, which ameliorates the maintenance system by diagnosing the condition and predicting the maintenance requirements. Based on new data mining algorithms, this system intelligently optimises mission readiness for imminent operations and maintenance scheduling in repair echelons. With modified data mining algorithms such as Weighted Feature Ranking Genetic Algorithm and SVM-Random Forest Linear ensemble, it improves the reliability, availability and safety, alongside reducing maintenance cost and Equipment Out of Action (EOA) time. The results clearly conclude that the introduced algorithms have an edge over the conventional data mining algorithms. The system utilizing the intelligent condition-based maintenance approach improves the operational and maintenance decision strategy of the defence force.

Keywords: condition based maintenance, data mining, defence maintenance, ensemble, genetic algorithms, maintenance scheduling, mission capability

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2233 Evaluation of Ecological Resilience in Mountain-plain Transition Zones: A Case Study of Dujiangyan City, Chengdu

Authors: Zhu Zhizheng, Huang Yong, Li Tong

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In the context of land and space development and resource environmental protection. Due to its special geographical location, mountain-plain transition zones are limited by many factors such as topography, mountain forest protection, etc., and their ecology is also more sensitive, with the characteristics of disaster susceptibility and resource gradient. Taking Dujiangyan City, Chengdu as an example, this paper establishes resilience evaluation indicators on the basis of ecological suitability evaluation through the analysis of current situation data and relevant policies: water conservation evaluation, soil and water conservation evaluation, biodiversity evaluation, soil erosion sensitivity evaluation, etc. Based on GIS spatial analysis, the ecological suitability and resilience evaluation results of Dujiangyan city were obtained by disjunction operation. The ecological resilience level of Dujiangyan city was divided into three categories: high, medium and low, with an area ratio of 50.81%, 16.4% and 32.79%, respectively. This paper can provide ideas for solving the contradiction between man and land in the mountain-plain transition zones, and also provide a certain basis for the construction of regional ecological protection and the delineation of three zones and three lines.

Keywords: urban and rural planning, ecological resilience, dujiangyan city, mountain-plain transition zones

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2232 Dielectric Properties of Mineral Oil Blended with Soyabean Oil for Power Transformers: A Laboratory Investigation

Authors: Deepa S N, Srinivasan a D, Veeramanju K T

Abstract:

The power transformer is a critical equipment in the transmission and distribution network that must be managed to ensure uninterrupted power service. The liquid insulation is essential for the proper functioning of the transformer, as it serves as both coolant and insulating medium, which influences the transformer’s durability. Further, the insulating state of a power transformer has a significant impact on its reliability. Mineral oil derived from petroleum crude oil has been employed as liquid dielectrics for decades due to its superior functional characteristics, however as a resource for the same are getting depleted over the years. Research is undertaken across the globe to identify a viable substitute for mineral oil. Further, alternate insulating oils are being investigated for better environmental impact, biodegradability and economics. Several combinations of vegetable oil derived natural esters are being inspected by researchers across the globe in these domains. In this work, mineral oil is blended with soyabean oil with various proportions and dielectric properties such as dielectric breakdown voltage, relative permittivity, dissipation factor, viscosity, flash and fire point have been investigated according to international standards. A quantitative comparison is made among various samples and is observed that the blended oil sample of equal proportion of mineral oil and soyabean oil, MO50+SO50 exhibits superior dielectric properties such as breakdown voltage of 65kV, dissipation factor of 0.0044, relative permittivity of 3.1680 that are closer to the range of values recommended for power transformer applications. Also, Breakdown voltage values of all the investigated oil samples obeyed the Weibull and Normal probability distribution.

Keywords: blended oil, dielectric breakdown, liquid insulation, power transformer

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2231 A Survey of Domain Name System Tunneling Attacks: Detection and Prevention

Authors: Lawrence Williams

Abstract:

As the mechanism which converts domains to internet protocol (IP) addresses, Domain Name System (DNS) is an essential part of internet usage. It was not designed securely and can be subject to attacks. DNS attacks have become more frequent and sophisticated and the need for detecting and preventing them becomes more important for the modern network. DNS tunnelling attacks are one type of attack that are primarily used for distributed denial-of-service (DDoS) attacks and data exfiltration. Discussion of different techniques to detect and prevent DNS tunneling attacks is done. The methods, models, experiments, and data for each technique are discussed. A proposal about feasibility is made. Future research on these topics is proposed.

Keywords: DNS, tunneling, exfiltration, botnet

Procedia PDF Downloads 72
2230 Rapid Detection of the Etiology of Infection as Bacterial or Viral Using Infrared Spectroscopy of White Blood Cells

Authors: Uraib Sharaha, Guy Beck, Joseph Kapelushnik, Adam H. Agbaria, Itshak Lapidot, Shaul Mordechai, Ahmad Salman, Mahmoud Huleihel

Abstract:

Infectious diseases cause a significant burden on the public health and the economic stability of societies all over the world for several centuries. A reliable detection of the causative agent of infection is not possible based on clinical features, since some of these infections have similar symptoms, including fever, sneezing, inflammation, vomiting, diarrhea, and fatigue. Moreover, physicians usually encounter difficulties in distinguishing between viral and bacterial infections based on symptoms. Therefore, there is an ongoing need for sensitive, specific, and rapid methods for identification of the etiology of the infection. This intricate issue perplex doctors and researchers since it has serious repercussions. In this study, we evaluated the potential of the mid-infrared spectroscopic method for rapid and reliable identification of bacterial and viral infections based on simple peripheral blood samples. Fourier transform infrared (FTIR) spectroscopy is considered a successful diagnostic method in the biological and medical fields. Many studies confirmed the great potential of the combination of FTIR spectroscopy and machine learning as a powerful diagnostic tool in medicine since it is a very sensitive method, which can detect and monitor the molecular and biochemical changes in biological samples. We believed that this method would play a major role in improving the health situation, raising the level of health in the community, and reducing the economic burdens in the health sector resulting from the indiscriminate use of antibiotics. We collected peripheral blood samples from young 364 patients, of which 93 were controls, 126 had bacterial infections, and 145 had viral infections, with ages lower than18 years old, limited to those who were diagnosed with fever-producing illness. Our preliminary results showed that it is possible to determine the infectious agent with high success rates of 82% for sensitivity and 80% for specificity, based on the WBC data.

Keywords: infectious diseases, (FTIR) spectroscopy, viral infections, bacterial infections.

Procedia PDF Downloads 133
2229 A Short Dermatoscopy Training Increases Diagnostic Performance in Medical Students

Authors: Magdalena Chrabąszcz, Teresa Wolniewicz, Cezary Maciejewski, Joanna Czuwara

Abstract:

BACKGROUND: Dermoscopy is a clinical tool known to improve the early detection of melanoma and other malignancies of the skin. Over the past few years melanoma has grown into a disease of socio-economic importance due to the increasing incidence and persistently high mortality rates. Early diagnosis remains the best method to reduce melanoma and non-melanoma skin cancer– related mortality and morbidity. Dermoscopy is a noninvasive technique that consists of viewing pigmented skin lesions through a hand-held lens. This simple procedure increases melanoma diagnostic accuracy by up to 35%. Dermoscopy is currently the standard for clinical differential diagnosis of cutaneous melanoma and for qualifying lesion for the excision biopsy. Like any clinical tool, training is required for effective use. The introduction of small and handy dermoscopes contributed significantly to the switch of dermatoscopy toward a first-level useful tool. Non-dermatologist physicians are well positioned for opportunistic melanoma detection; however, education in the skin cancer examination is limited during medical school and traditionally lecture-based. AIM: The aim of this randomized study was to determine whether the adjunct of dermoscopy to the standard fourth year medical curriculum improves the ability of medical students to distinguish between benign and malignant lesions and assess acceptability and satisfaction with the intervention. METHODS: We performed a prospective study in 2 cohorts of fourth-year medical students at Medical University of Warsaw. Groups having dermatology course, were randomly assigned to:  cohort A: with limited access to dermatoscopy from their teacher only – 1 dermatoscope for 15 people  Cohort B: with a full access to use dermatoscopy during their clinical classes:1 dermatoscope for 4 people available constantly plus 15-minute dermoscopy tutorial. Students in both study arms got an image-based test of 10 lesions to assess ability to differentiate benign from malignant lesions and postintervention survey collecting minimal background information, attitudes about the skin cancer examination and course satisfaction. RESULTS: The cohort B had higher scores than the cohort A in recognition of nonmelanocytic (P < 0.05) and melanocytic (P <0.05) lesions. Medical students who have a possibility to use dermatoscope by themselves have also a higher satisfaction rates after the dermatology course than the group with limited access to this diagnostic tool. Moreover according to our results they were more motivated to learn dermatoscopy and use it in their future everyday clinical practice. LIMITATIONS: There were limited participants. Further study of the application on clinical practice is still needed. CONCLUSION: Although the use of dermatoscope in dermatology as a specialty is widely accepted, sufficiently validated clinical tools for the examination of potentially malignant skin lesions are lacking in general practice. Introducing medical students to dermoscopy in their fourth year curricula of medical school may improve their ability to differentiate benign from malignant lesions. It can can also encourage students to use dermatoscopy in their future practice which can significantly improve early recognition of malignant lesions and thus decrease melanoma mortality.

Keywords: dermatoscopy, early detection of melanoma, medical education, skin cancer

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2228 Development of a Bead Based Fully Automated Mutiplex Tool to Simultaneously Diagnose FIV, FeLV and FIP/FCoV

Authors: Andreas Latz, Daniela Heinz, Fatima Hashemi, Melek Baygül

Abstract:

Introduction: Feline leukemia virus (FeLV), feline immunodeficiency virus (FIV), and feline coronavirus (FCoV) are serious infectious diseases affecting cats worldwide. Transmission of these viruses occurs primarily through close contact with infected cats (via saliva, nasal secretions, faeces, etc.). FeLV, FIV, and FCoV infections can occur in combination and are expressed in similar clinical symptoms. Diagnosis can therefore be challenging: Symptoms are variable and often non-specific. Sick cats show very similar clinical symptoms: apathy, anorexia, fever, immunodeficiency syndrome, anemia, etc. Sample volume for small companion animals for diagnostic purposes can be challenging to collect. In addition, multiplex diagnosis of diseases can contribute to an easier, cheaper, and faster workflow in the lab as well as to the better differential diagnosis of diseases. For this reason, we wanted to develop a new diagnostic tool that utilizes less sample volume, reagents, and consumables than multiplesingleplex ELISA assays Methods: The Multiplier from Dynextechonogies (USA) has been used as platform to develop a Multiplex diagnostic tool for the detection of antibodies against FIV and FCoV/FIP and antigens for FeLV. Multiplex diagnostics. The Dynex®Multiplier®is a fully automated chemiluminescence immunoassay analyzer that significantly simplifies laboratory workflow. The Multiplier®ease-of-use reduces pre-analytical steps by combining the power of efficiently multiplexing multiple assays with the simplicity of automated microplate processing. Plastic beads have been coated with antigens for FIV and FCoV/FIP, as well as antibodies for FeLV. Feline blood samples are incubated with the beads. Read out of results is performed via chemiluminescence Results: Bead coating was optimized for each individual antigen or capture antibody and then combined in the multiplex diagnostic tool. HRP: Antibody conjugates for FIV and FCoV antibodies, as well as detection antibodies for FeLV antigen, have been adjusted and mixed. 3 individual prototyple batches of the assay have been produced. We analyzed for each disease 50 well defined positive and negative samples. Results show an excellent diagnostic performance of the simultaneous detection of antibodies or antigens against these feline diseases in a fully automated system. A 100% concordance with singleplex methods like ELISA or IFA can be observed. Intra- and Inter-Assays showed a high precision of the test with CV values below 10% for each individual bead. Accelerated stability testing indicate a shelf life of at least 1 year. Conclusion: The new tool can be used for multiplex diagnostics of the most important feline infectious diseases. Only a very small sample volume is required. Fully automation results in a very convenient and fast method for diagnosing animal diseases.With its large specimen capacity to process over 576 samples per 8-hours shift and provide up to 3,456 results, very high laboratory productivity and reagent savings can be achieved.

Keywords: Multiplex, FIV, FeLV, FCoV, FIP

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2227 An Application for Risk of Crime Prediction Using Machine Learning

Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

Abstract:

The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

Procedia PDF Downloads 108
2226 Failure Analysis of the Gasoline Engines Injection System

Authors: Jozef Jurcik, Miroslav Gutten, Milan Sebok, Daniel Korenciak, Jerzy Roj

Abstract:

The paper presents the research results of electronic fuel injection system, which can be used for diagnostics of automotive systems. In the paper is described the construction and operation of a typical fuel injection system and analyzed its electronic part. It has also been proposed method for the detection of the injector malfunction, based on the analysis of differential current or voltage characteristics. In order to detect the fault state, it is needed to use self-learning process, by the use of an appropriate self-learning algorithm.

Keywords: electronic fuel injector, diagnostics, measurement, testing device

Procedia PDF Downloads 549
2225 Laser - Ultrasonic Method for the Measurement of Residual Stresses in Metals

Authors: Alexander A. Karabutov, Natalia B. Podymova, Elena B. Cherepetskaya

Abstract:

The theoretical analysis is carried out to get the relation between the ultrasonic wave velocity and the value of residual stresses. The laser-ultrasonic method is developed to evaluate the residual stresses and subsurface defects in metals. The method is based on the laser thermooptical excitation of longitudinal ultrasonic wave sand their detection by a broadband piezoelectric detector. A laser pulse with the time duration of 8 ns of the full width at half of maximum and with the energy of 300 µJ is absorbed in a thin layer of the special generator that is inclined relative to the object under study. The non-uniform heating of the generator causes the formation of a broadband powerful pulse of longitudinal ultrasonic waves. It is shown that the temporal profile of this pulse is the convolution of the temporal envelope of the laser pulse and the profile of the in-depth distribution of the heat sources. The ultrasonic waves reach the surface of the object through the prism that serves as an acoustic duct. At the interface ‚laser-ultrasonic transducer-object‘ the conversion of the most part of the longitudinal wave energy takes place into the shear, subsurface longitudinal and Rayleigh waves. They spread within the subsurface layer of the studied object and are detected by the piezoelectric detector. The electrical signal that corresponds to the detected acoustic signal is acquired by an analog-to-digital converter and when is mathematically processed and visualized with a personal computer. The distance between the generator and the piezodetector as well as the spread times of acoustic waves in the acoustic ducts are the characteristic parameters of the laser-ultrasonic transducer and are determined using the calibration samples. There lative precision of the measurement of the velocity of longitudinal ultrasonic waves is 0.05% that corresponds to approximately ±3 m/s for the steels of conventional quality. This precision allows one to determine the mechanical stress in the steel samples with the minimal detection threshold of approximately 22.7 MPa. The results are presented for the measured dependencies of the velocity of longitudinal ultrasonic waves in the samples on the values of the applied compression stress in the range of 20-100 MPa.

Keywords: laser-ultrasonic method, longitudinal ultrasonic waves, metals, residual stresses

Procedia PDF Downloads 321
2224 Effect of Fuel Injection Discharge Curve and Injection Pressure on Upgrading Power and Combustion Parameters in HD Diesel Engine with CFD Simulation

Authors: Saeed Chamehsara, Seyed Mostafa Mirsalim, Mehdi Tajdari

Abstract:

In this study, the effect of fuel injection discharge curve and injection pressure simultaneously for upgrading power of heavy duty diesel engine by simulation of combustion process in AVL-Fire software are discussed. Hence, the fuel injection discharge curve was changed from semi-triangular to rectangular which is usual in common rail fuel injection system. Injection pressure with respect to amount of injected fuel and nozzle hole diameter are changed. Injection pressure is calculated by an experimental equation which is for heavy duty diesel engines with common rail fuel injection system. Upgrading power for 1000 and 2000 bar injection pressure are discussed. For 1000 bar injection pressure with 188 mg injected fuel and 3 mm nozzle hole diameter in compare with first state which is semi-triangular discharge curve with 139 mg injected fuel and 3 mm nozzle hole diameter, upgrading power is about 19% whereas the special change has not been observed in cylinder pressure. On the other hand, both the NOX emission and the Soot emission decreased about 30% and 6% respectively. Compared with first state, for 2000 bar injection pressure that injected fuel and nozzle diameter are 196 mg and 2.6 mm respectively, upgrading power is about 22% whereas cylinder pressure has been fixed and NOX emission and the Soot emissions are decreased 36% and 20%, respectively.

Keywords: CFD simulation, HD diesel engine, upgrading power, injection pressure, fuel injection discharge curve, combustion process

Procedia PDF Downloads 520
2223 Detection of Triclosan in Water Based on Nanostructured Thin Films

Authors: G. Magalhães-Mota, C. Magro, S. Sério, E. Mateus, P. A. Ribeiro, A. B. Ribeiro, M. Raposo

Abstract:

Triclosan [5-chloro-2-(2,4-dichlorophenoxy) phenol], belonging to the class of Pharmaceuticals and Personal Care Products (PPCPs), is a broad-spectrum antimicrobial agent and bactericide. Because of its antimicrobial efficacy, it is widely used in personal health and skin care products, such as soaps, detergents, hand cleansers, cosmetics, toothpastes, etc. However, it has been considered to disrupt the endocrine system, for instance, thyroid hormone homeostasis and possibly the reproductive system. Considering the widespread use of triclosan, it is expected that environmental and food safety problems regarding triclosan will increase dramatically. Triclosan has been found in river water samples in both North America and Europe and is likely widely distributed wherever triclosan-containing products are used. Although significant amounts are removed in sewage plants, considerable quantities remain in the sewage effluent, initiating widespread environmental contamination. Triclosan undergoes bioconversion to methyl-triclosan, which has been demonstrated to bio accumulate in fish. In addition, triclosan has been found in human urine samples from persons with no known industrial exposure and in significant amounts in samples of mother's milk, demonstrating its presence in humans. The action of sunlight in river water is known to turn triclosan into dioxin derivatives and raises the possibility of pharmacological dangers not envisioned when the compound was originally utilized. The aim of this work is to detect low concentrations of triclosan in an aqueous complex matrix through the use of a sensor array system, following the electronic tongue concept based on impedance spectroscopy. To achieve this goal, we selected the appropriate molecules to the sensor so that there is a high affinity for triclosan and whose sensitivity ensures the detection of concentrations of at least nano-molar. Thin films of organic molecules and oxides have been produced by the layer-by-layer (LbL) technique and sputtered onto glass solid supports already covered by gold interdigitated electrodes. By submerging the films in complex aqueous solutions with different concentrations of triclosan, resistance and capacitance values were obtained at different frequencies. The preliminary results showed that an array of interdigitated electrodes sensor coated or uncoated with different LbL and films, can be used to detect TCS traces in aqueous solutions in a wide range concentration, from 10⁻¹² to 10⁻⁶ M. The PCA method was applied to the measured data, in order to differentiate the solutions with different concentrations of TCS. Moreover, was also possible to trace a curve, the plot of the logarithm of resistance versus the logarithm of concentration, which allowed us to fit the plotted data points with a decreasing straight line with a slope of 0.022 ± 0.006 which corresponds to the best sensitivity of our sensor. To find the sensor resolution near of the smallest concentration (Cs) used, 1pM, the minimum measured value which can be measured with resolution is 0.006, so the ∆logC =0.006/0.022=0.273, and, therefore, C-Cs~0.9 pM. This leads to a sensor resolution of 0.9 pM for the smallest concentration used, 1pM. This attained detection limit is lower than the values obtained in the literature.

Keywords: triclosan, layer-by-layer, impedance spectroscopy, electronic tongue

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2222 The Innovation of English Materials to Communicate the Identity of Bangpoo, Samut Prakan Province, for Ecotourism

Authors: Kitda Praraththajariya

Abstract:

The main purpose of this research was to study how to communicate the identity of the Mueang district, SamutSongkram 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, SamutSongkram 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 AmphurMueang, SamutSongkram province which the researcher could find and design to present in English materials can be summed up in 4 items: 1) The history of AmphurMueang, SamutSongkram province 2) WatPhetSamutWorrawihan 3) The Learning source of Ecotourism: Don Hoy Lod and Mangrove forest 4) How to keep AmphurMueang, SamutSongkram province for ecotourism.

Keywords: foreigner tourists, signified, semiotics, ecotourism

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2221 Traditional Management Systems and the Conservation of Cultural and Natural Heritage: Multiple Case Studies in Zimbabwe

Authors: Nyasha Agnes Gurira, Petronella Katekwe

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Traditional management systems (TMS) are a vital source of knowledge for conserving cultural and natural heritage. TMS’s are renowned for their ability to preserve both tangible and intangible manifestations of heritage. They are a construct of the intricate relationship that exists between heritage and host communities, where communities are recognized as owners of heritage and so, set up management mechanisms to ensure its adequate conservation. Multiple heritage condition surveys were conducted to assess the effectiveness of using TMS in the conservation of both natural and cultural heritage. Surveys were done at Nharira Hills, Mahwemasimike, Dzimbahwe, Manjowe Rock art sites and Norumedzo forest which are heritage places in Zimbabwe. It assessed the state of conservation of the five case studies and assessed the role that host communities play in the management of these heritage places. It was revealed that TMS’s are effective in the conservation of natural heritage, however in relation to heritage forms with cultural manifestations, there are major disparities. These range from differences in appreciation and perception of value within communities leading to vandalism, over emphasis in the conservation of the intangible element as opposed to the tangible. This leaves the tangible element at risk. Despite these issues, TMS are a reliable knowledge base which enables more holistic conservation approaches for cultural and natural heritage.

Keywords: communities, cultural intangible, tangible heritage, traditional management systems, natural

Procedia PDF Downloads 550