Search results for: forest tourism

Authors: Kavita Bodke

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

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

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Authors: Raymond Xu, Cindy Jingru Wang

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

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

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Authors: Aree Thongpukdee, Chockpisit Thepsithar, Chuthalak Thammaso

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

Keywords: vegetable plants, ethnobotanical survey, Kalasin, Thailand

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Authors: Muhammad Ali

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

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

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Authors: Walid Moudani

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

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

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Authors: Weera Weerasophon

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The purpose of this research was to study Tourists’s satisfaction strategies case of Tourists who attended and shopped in Chatuchak weekend market (Bangkok) in order to improve service operation of Chatuchak weekend market to serve tourists’ need to impress them. The researcher used the marketing mix as a main factor that affect to tourist satisfaction. This research was emphasized as quantitative research as 400 of questionnaires were used for collecting the data from international tourists around Chatuchak weekend market that questionnaires divided in to 3 parts as a personal information part, satisfaction of marketing/services and facilities and suggestion part. After collecting all the data that would be processed in statistic program of SPSS to use for analyze the data later on. The result is described that most of international tourists satisfied Chatuchak weekend market in the level of 4 as more satisfaction for example friendly staff, Chatuchak information, price of product, facilities and service by the way, the environment of Chatuchak weekend market is the most satisfaction level.

Keywords: Chatuchak, satisfaction, Thailand tourism, marketing mix, tourists

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Authors: Gatot Dwi Hendro, Hayyan ul Haq

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

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

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Authors: Sagir M. Yusuf, Chris Baber

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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

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Authors: Yu Hung Chiang, Hei Chia Wang

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Nowadays, tourism has become a part of life. Before reserving hotels, customers need some information, which the most important source is online reviews, about hotels to help them make decisions. Due to the dramatic growing of online reviews, it is impossible for tourists to read all reviews manually. Therefore, designing an automatic review analysis system, which summarizes reviews, is necessary for them. The main purpose of the system is to understand the opinion of reviews, which may be positive or negative. In other words, the system would analyze whether the customers who visited the hotel like it or not. Using sentiment analysis methods will help the system achieve the purpose. In sentiment analysis methods, the targets of opinion (here they are called the feature) should be recognized to clarify the polarity of the opinion because polarity of the opinion may be ambiguous. Hence, the study proposes an unsupervised method using Part-Of-Speech pattern and multi-lexicons sentiment analysis to summarize all reviews. We expect this method can help customers search what they want information as well as make decisions efficiently.

Keywords: text mining, sentiment analysis, product feature extraction, multi-lexicons

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Authors: Abdullahi Jibrin, Aishetu Abdulkadir

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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

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Authors: Somesh Kumar Sharma, Sunanad Gupta

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The contribution of aviation to society and economy is undisputedly significant. The aviation industry drives economic and social progress by contributing prominently to tourism, commerce and improved quality of life. Identifying the amount of fuel consumed by an aircraft while moving in both airspace and ground networks is critical to air transport economics. Aviation fuel is a major operating cost parameter of the aviation industry and at the same time it is prone to various constraints. This article aims to develop a model for fuel consumption of aviation product. The paper tailors the information for the fuel consumption optimization in terms of information development, information evaluation and information refinement. The information is evaluated and refined using statistical package R and Factor Analysis which is further validated with neural networking. The study explores three primary dimensions which are finally summarized into 23 influencing variables in contrast to 96 variables available in literature. The 23 variables explored in this study should be considered as highly influencing variables for fuel consumption which will contribute significantly towards fuel optimization.

Keywords: fuel consumption, civil aviation industry, neural networking, optimization

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Authors: Vajiheh Javani

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Hosting sport event result in both economic and socio-psychological impacts on host communities. Economic impacts, which are considered by many scholars and the social impacts of tourism based on hosting sports events have also been somehow investigated. But, investigating perceived social impacts based on host community perceptions has been paid not with little attention enough. Therefore, this study aims to study the beneficiary social impact of hosting sport event from residents’ perceptions. The participations for this research were 50 residents of Tabriz city who were recruited by judgment sampling method. focused group interviews were used for gathering the data. Then thematic analysis was utilized for interview analysis. Extracted perceived beneficiary social impacts include (1) economic benefits; (2) community pride; (3) community development. This study highlighted the perceived social beneficiary impacts and could contribute to a better understanding of how local residents of the studied community view the impacts associated with a sport event.

Keywords: socio-psychological impacts, sport event, community development, hosting

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Authors: A. Bouzekri, H. Benmassaud

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Aurès region is one of the arid and semi-arid areas that have suffered climate crises and overexploitation of natural resources they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and its spatiotemporal changes in the Aurès between 1987 and 2013, for this work, we adopted a method of analysis based on the exploitation of the images satellite Landsat TM 1987 and Landsat OLI 2013, from the supervised classification likelihood coupled with field surveys of the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover maps from 1987 and 2013, one can extract a spatial map change of different land cover units. The results show that between 1987 and 2013 vegetation has suffered negative changes are the significant degradation of forests and steppe rangelands, and sandy soils and bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013 allows us to understand the extensive or regressive orientation of vegetation and soil, this map shows that dense forests give his place to clear forests and steppe vegetation develops from a degraded forest vegetation and bare, sandy soils earn big steppe surfaces that explain its remarkable extension. The analysis of remote sensing data highlights the profound changes in our environment over time and quantitative monitoring of the risk of desertification.

Keywords: remote sensing, spatiotemporal, land use, Aurès

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

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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

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

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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

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Authors: Nuria Vargas, Frances Rodriguez

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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

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

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

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

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Authors: Diane H. Dotson, Shari L. Rodriguez

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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

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Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: Ma. Karen Jimeno, Erika Kate Co, Ma. Claudia Alexis Frani, Shane Rosshel Guzman, Marie Jaye Constance Selga

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Home sharing continues to gain traction in the Philippines at the expense of traditional lodging options, to which the hospitality industry has reacted in stages. This study aims to describe the social and economic impact of home sharing in Metro Manila from the perspective of hosts. A cross-sectional survey questionnaire consisting of five-point Likert items was administered to 120 hosts in Metro Manila. Kruskal-Wallis test, together with Dunn’s pairwise comparison, was used in the analysis of data. Results show that there is a significant difference in the median scores between increased awareness of Filipino food/heritage and the pursuit of enjoyable life in terms of social impact. Economic-wise, the respondents, did not perceive that their businesses as an additional source of income for the local government. These findings can be used for further exploratory studies and formulation of sustainable business policies conducive for the entrepreneurs and the hospitality industry alike.

Keywords: bed-and-breakfast, home sharing, marketing, tourism

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Authors: F. O. Oboite, P. G. Comeau

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Advance regeneration is present in many lodgepole pine stands in Alberta. When the overstory pine canopy is killed by Mountain Pine Beetle (MPB) the growth of this advance is likely to increase. Understanding the growth response of these understory tree species is needed to improve mid-term timber supply projections and management decisions. To quantify the growth (diameter, height, height/diameter ratio) responses of black spruce and white spruce to lodgepole pine mortality, sample trees of black and white spruce advance regeneration were selected from 7 lodgepole pine dominated stands (5 attacked; 2 control) in the Foothills Region of western Alberta. Measurements were collected 7-8 years after MPB attack across a wide range of spruce height and stand densities. Analysis was done using mixed model linear regression. Result indicates that there was an increase in both diameter and height growth after MPB attack; however, this increase in growth was delayed for about four years. Both spruce species had similar height response and their height/diameter ratio decreased after release, partly as a result of increased understory light associated with loss of needles in the pine canopy. In addition, the diameter and height growth responses of both spruce species were strongly related to density, prerelease growth and initial size.

Keywords: mountain pine beetle, forest regeneration, lodgepole pine, growth response

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Authors: Dina M. Ezz El-Din

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A variety of sources on Ancient Egypt provides us with knowledge about its agricultural and eating habits. This wealth of information testifies that the ancient Egyptians disposed of a wide variety of food choices. Egyptian agricultural diet was complemented by livestock breeding (Cows, sheep, geese, ducks, quail, pigeons, pelicans, etc). Moreover, the ancient Egyptians planted and harvested large amounts of cereals and vegetables (onions, leeks, lettuces, garlic). They had a varied and well-balanced diet throughout their history. Like in modern times, their eating habits not only changed from one region to the other, but also these also differed according to social classes. The present research is a descriptive-analytical study that tackles eating habits and culinary experience of the ancient Egyptians in an attempt to revive and preserve Egyptians’ food heritage. It focuses on different meals that were prepared and consumed in different occasions, and the habits that can be traced in Egypt in modern times. It also suggests means of bringing to life the ancient Egyptians’ food experience through restaurants and other tourism activities.

Keywords: cultural heritage, ancient Egyptian food, eating habits, preserving food traditions

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Authors: Dwi Yulian Fahruddin Shah, Mochammad Luthfy Rizaldy Dwi Putra, Tommy Adi Rachmawan, Mona Annisa Matondang, Nadya Sylvia, Hilmy Ramzy Rinaldy

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Gili island is one of the island in Indonesia which is located in Probolinggo city, East Java. Gili Island has some potential culture as local wisdom that can be used as tourism commodity because it can be used as attractive ecotourism. With the ecotourism that utilize local wisdom of Indonesian’s culture that located in Gili can introduce the richness of Indonesian culture in the world that will increase foreign exchange. One of the cultural potential as local wisdom in Gili island are Petik Laut and Onjem. It are a culture in Gili island that can’t be found in other island in Indonesia. Not just that but also it are a cultural identity that is owned by Gili island which has fill the criteria to be used as local wisdom that can be used as ecotourism that can bring Indonesian culture to the world so that the tourists of the world will visit to Indonesia, especially to Gili island to see Petik Laut and Onjem culture directly.

Keywords: Gili island, petik laut and onjem culture, ecotourism, indonesia’s culture

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Authors: Madhavi S. Apte, Milind Bhitre

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In pharmaceutical research and new drug development, medicinal plants have important roles. Similarly, Indian dhak tree belonging to family Fabaceae has been widely used in the traditional Indian medical system of ‘Ayurveda’ for the treatment of a variety of ailments. Hence the cell viability study was undertaken to evaluate and compare the activity of extracts of various parts like flower, bark, leaf, seed by conducting MTT assay method along with other pharmacognostical studies. The methanolic extracts of bark, flowers, leaves, and seeds were used for the study. The cell viability MTT assay was performed using the standard operating procedures. The extracts were dissolved in DMSO and serially diluted with complete medium to get the concentrations range of test concentration. DMSO concentration was kept < 0.1% in all the samples. HUVEC cells maintained in appropriate conditions were seeded in 96 well plates and treated with different concentrations of the test samples and incubated at 37°C, 5% CO₂ for 96 hours. MTT reagent was added to the wells and incubated for 4 hours; the dark blue formazan product formed by the cells was dissolved in DMSO under a safety cabinet and read at 550nm. Percentage inhibitions were calculated and plotted with the concentrations used to calculate the IC50 values. The bark, flower, leaves and seed extracts have shown the cytotoxicity activity and can be further studied for antiangiogenesis activity.

Keywords: pharmacognosy, Cell viability, MTT assay, anti-angiogenesis

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Authors: Teresa Wanjiru Mbatia

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On 7th June 2011, the government Minister of Roads in Kenya announced the proposed construction of a major highway known as a southern bypass to run on the northern border of the Nairobi National Park. The following day on 8th June 2011, the chairperson of the Friends of Nairobi National Park (FONNAP) posted a protest statement on their website, with the heading, ‘Nairobi Park is Not a cake’ alerting its members and conservation groups, with the aim of getting support to the campaign against the government’s intention to hive off a section of the park for road construction. This was the first and earliest statement that led to a series of other events that culminated in conservationists and some other members of the public campaign against the government’s plan to hive off sections of the park to build road and railway infrastructure in or around the park. Together with other non-state actors, mostly non-governmental organisations in conservation/environment and tourism businesses, FoNNAP issued a series of other statements on social, print and electronic media to battle against road and railway construction. This paper examined the strategies, outcomes and interests of actors involved in opposing/proposing the development of transport infrastructure in and around the Nairobi National Park. Specifically, the objectives were to analyse the: (1) Arguments put forward by the eco-warriors to protest infrastructure development; (2) Background and interests of the eco-warriors; (3) Needs/interests and opinions of ordinary common citizens on transport infrastructural development, particularly in and around the urban nature reserve and (4) Final outcomes of the eco-politics surrounding infrastructure development in and around Nairobi National Park. The methodological approach used was environmental history and the social construction of nature. The study collected combined qualitative data using four main approaches, the grounded theory approach, narratives, case studies and a phenomenological approach. The information collected was analysed using critical discourse analysis. The major findings of the study were that under the guise of “public participation,” influential non-state actors have the capacity to perpetuate social-spatial inequalities in the form of curtailing the majority from accessing common public goods. A case in point in this study is how the efforts of powerful conservationists, environmentalists, and tourism businesspersons managed to stall the construction of much-needed road and railway infrastructure severally through litigations in lengthy environmental court processes involving injunctions and stop orders to the government bodies in charge. Moreover, powerful non-state actors were found to have formed informal and sometimes formal coalitions with politicians with selfish interests, which serves to deepen the exclusionary practices and the common good. The study concludes that mostly composed of certain types of elites (NGOs, business communities, politicians and privileged social-cultural groups), non-state actors have used participatory policies to advance their own interests at the expense of the majority whom they claim to represent. These practices are traced to the historically unjust social, political, and economic forces involved in the production of space in Nairobi.

Keywords: eco-politics, exclusion, infrastructure, Nairobi national park, non-state actors, protests

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Authors: Nuchanat Handumrongkul Danaya Darnsawasdi, Anantachai Aeka

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To be a model for performing oral presentations by the tour guides, this research has been conducted. In order to develop French language teaching and studying for tourism, its purpose is to analyze the content used by tour guides. The study employed audio recordings of these presentations as an interview method in authentic situations, having four guides as respondents and information providers. The data was analyzed through content analysis. The results found that the tour guides described eight important items by giving more importance to details at Wat Phra Kaew or the Temple of the Emerald Buddha than at the palaces. They preferred the buildings upon the upper terrace, Buddhist cosmology, the decoration techniques, the royal chapel, the mural paintings, Thai offerings to Buddha images, palaces with architectural features and functions including royal ceremonies and others. This information represents the Thai characteristics of each building and other related content. The findings were used as a manual for guides for how to describe a tourist attraction, especially the temple and other related cultural topics of interest.

Keywords: guide, guide presentation, Grand Palace, Buddhist cosmology

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Authors: Hela Ben Maallem

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Applications based on virtual reality offer many benefits to the heritage and tourism sector. Digital heritage mediation is a constantly emerging field that aims to reconstruct the history of heritage items and sites, while at the same time highlighting the identity of a community or region and encouraging public engagement. This research focuses on the analysis of a virtual reality application used in a heritage digital mediation project. The modality introduced is examined through a case study of Djerba View VR application. The aim of this study is to understand the nature and potential uses of this immersive technology and to focus on the study of the possibilities of this medium. The goal of this article is to analyze how 3D reconstruction and immersive storytelling can offer an immersive, interactive and engaging user experience, while meeting the expectations and needs of visitors in a context of technological transition and user-centred design.

Keywords: digital heritage mediation, technological transition, virtual reality, 3D reconstruction, immersive storytelling, user experience, user centered design, interactivity, immersion

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Authors: Florin Leon, Silvia Curteanu

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

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

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Authors: Lei Qin

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As shared accommodation has become one of the most important market developments in the tourism industry, numerous contributions have emerged on travelers’ motivations to choose shared accommodation. A debated question, however, resides in the heterogeneity of travelers based on motivations. This paper aims to reconcile opposing perspectives by comparing motivation segmentation at two distinct phases of innovation adoption of this new hospitality option: (i) before the first travel – potential users showing interest (n=420) and (ii) after the first travel – users (n=420). Interestingly, we find that travelers (including pre-and-post adopters) have a stronger agreement in experiential motivations than practical motivations. However, the heterogeneity of motivations among travelers is significantly higher in users, increasing from two to six clusters, which means travelers cluster into more and distinct motivation groups after adoption. Rather than invalidating specific assumptions used in the literature in terms of motivation heterogeneity, this paper reconciles opposing findings by putting them along with one another in the process of innovation adoption. A subsequent tourists’ segmentation based on motivations were conducted according to their innovation adoption stages.

Keywords: motivation, pre-and-post adoption, shared accommodation, segmentation

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Authors: Tovondahiniriko Fanjirindratovo, Olga Ramiarinjanahary, Paulisimone Rasoavonjy

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The sunshine duration, which is the sum of all the moments when the solar beam radiation is up to a minimal value, is an important parameter for climatology, tourism, agriculture and solar energy. Its measure is usually given by a pyrheliometer installed on a two-axis solar tracker. Due to the high cost of this device and the availability of global radiation on a horizontal surface, on the other hand, several studies have been done to make a correlation between global radiation and sunshine duration. Most of these studies are fitted for the northern hemisphere using a pyrheliometric database. The aim of the present work is to list and assess all the existing methods and apply them to Reunion Island, a tropical region in the southern hemisphere. Using a database of ten years, global, diffuse and beam radiation for a horizontal surface are employed in order to evaluate the uncertainty of existing algorithms for a tropical region. The methodology is based on indirect comparison because the solar beam radiation is not measured but calculated by the beam radiation on a horizontal surface and the sun elevation angle.

Keywords: Carpentras method, data fitting, global radiation, sunshine duration, Slob and Monna algorithm, step algorithm

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