Search results for: network resources

Authors: Yu-Chen Chien, Sheng-Jung Ou, Shang-Ling Hsu

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Many aboriginal tribes in the early modern began to actively promote tribal tourism. The tribe uses rich ecological environment and unique folk culture successfully attract crowds. In addition to the tribe in the construction level to consider the cultural heritage and living needs, in order to improve tribal tourism for the tribe to bring the benefits of all levels, as well as to avoid the tourism industry is too prosperous brought negative tourism impact. How to successfully create the conditions of mutual benefit of residents and tourists is an important issue common to many tribes. Hualien Turuku Hongye Tribe in Taiwan around the tourist resources are very rich. It is famous for its Hongye hot springs and Ruisui hot springs. Hongye tribe to develop tribal tourism is bound to use its own has three advantages: Truku culture, in the agricultural products experience and marketing, and the surrounding hot springs industry tourism benefits. Tribal Development Association in the past to promote these three advantages for tribal tourism. But due to the impact of many levels led to the tribes in the promotion of tourism on the ineffective. At present, in addition to the Hongye Tribal Development Association in promoting tribal tourism, local residents to promote cultural heritage workshop also gradually rise. Its purpose is to link local cultural resources, agricultural specialty resources, spa tourism industry, the revitalization of the internal development of the tribes at all levels. Each tribe to promote tribal tourism due to geographical environment, resource types have a different set of practices and patterns. This study explores the tourist opportunities and resource points of Hongye tribes, and tribal tourism has been to promote the operation practices and benefits. To understand the difficulties encountered in the implementation of tribal tourism and the impact of all levels. Reference successful development of domestic and foreign tourism tribal tribe case. Develop a questionnaire and using the questionnaire survey to understand tribal residents for the tribal tribes to promote tribal tourism views. Finally, it puts forward some suggestions and strategies to promote the tribal tourism in Hongye tribe.

Keywords: cultural tourism, tourism impact, aboriginal tribe, Hongye Tribe

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Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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Authors: Ali Kadivar, Kaveh Niayesh

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The integration of green energy resources is a major focus, and the role of Medium Voltage Direct Current (MVDC) systems is exponentially expanding. However, the protection of MVDC systems against DC faults is a challenge that can have consequences on reliable and safe grid operation. This challenge reveals the need for MVDC circuit breakers (MVDC CB), which are in infancies of their improvement. Therefore will be a lack of MVDC CBs standards, including thresholds for acceptable power losses and operation speed. To establish a baseline for comparison purposes, a benchmark system for testing future MVDC CBs is vital. The literatures just give the timing sequence of each switch and the emphasis is on the topology, without in-depth study on the control algorithm of DCCB, as the circuit breaker control system is not yet systematic. A digital testing benchmark is designed for the Proof-of-concept of simulation studies using software models. It can validate studies based on real-time digital simulators and Transient Network Analyzer (TNA) models. The proposed experimental setup utilizes data accusation from the accurate sensors installed on the tested MVDC CB and through general purpose input/outputs (GPIO) from the microcontroller and PC Prototype studies in the laboratory-based models utilizing Hardware-in-the-Loop (HIL) equipment connected to real-time digital simulators is achieved. The improved control algorithm of the circuit breaker can reduce the peak fault current and avoid arc resignation, helping the coordination of DCCB in relay protection. Moreover, several research gaps are identified regarding case studies and evaluation approaches.

Keywords: DC circuit breaker, hardware-in-the-loop, real time digital simulation, testing benchmark

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Authors: Natalia Strobel, Jan Kratzer

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In this paper, we test whether different types of research and development (R&D) alliances positively impact the radical innovation performance of firms. We differentiate between the R&D alliances without extern R&D orders and embeddedness in knowledge source network. We test the differences between the domestically diversified R&D alliances and R&D alliances diversified abroad. Moreover, we test how non-price competition influences the impact of domestically diversified R&D alliances, and R&D alliance diversified abroad on radical innovation performance. Our empirical analysis is based on the comprehensive Swiss innovation panel, which allowed us to study 3520 firms between the years between 1996 and 2011 in 3 years intervals. We analyzed the data with a linear estimation with Swamy-Aurora transformation using plm package in R software. Our results show as hypothesized a positive impact of R&D alliances diversity abroad as well as domestically on radical innovation performance. The effect of non-price interaction is in contrast to our hypothesis, not significant. This suggests that diversity of R&D alliances is highly advantageous independent of non-price competition.

Keywords: R&D alliances, partner diversity, knowledge source diversity, non-price competition, absorptive capacity

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Authors: Pramod Somvanshi, Manu Tomar, K. V. Venkatesh

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Insulin and glucagon are responsible for homeostasis of key plasma metabolites like glucose, amino acids and fatty acids in the blood plasma. These hormones act antagonistically to each other during the secretion and signaling stages. In the present work, we analyze the effect of macronutrients on the response from integrated insulin and glucagon signaling pathways. The insulin and glucagon pathways are connected by DAG (a calcium signaling component which is part of the glucagon signaling module) which activates PKC and inhibits IRS (insulin signaling component) constituting a crosstalk. AKT (insulin signaling component) inhibits cAMP (glucagon signaling component) through PDE3 forming the other crosstalk between the two signaling pathways. Physiological level of anabolism and catabolism is captured through a metric quantified by the activity levels of AKT and PKA in their phosphorylated states, which represent the insulin and glucagon signaling endpoints, respectively. Under resting and starving conditions, the phosphorylation metric represents homeostasis indicating a balance between the anabolic and catabolic activities in the tissues. The steady state analysis of the integrated network demonstrates the presence of a bistable response in the phosphorylation metric with respect to input plasma glucose levels. This indicates that two steady state conditions (one in the homeostatic zone and other in the anabolic zone) are possible for a given glucose concentration depending on the ON or OFF path. When glucose levels rise above normal, during post-meal conditions, the bistability is observed in the anabolic space denoting the dominance of the glycogenesis in liver. For glucose concentrations lower than the physiological levels, while exercising, metabolic response lies in the catabolic space denoting the prevalence of glycogenolysis in liver. The non-linear positive feedback of AKT on IRS in insulin signaling module of the network is the main cause of the bistable response. The span of bistability in the phosphorylation metric increases as plasma fatty acid and amino acid levels rise and eventually the response turns monostable and catabolic representing diabetic conditions. In the case of high fat or protein diet, fatty acids and amino acids have an inhibitory effect on the insulin signaling pathway by increasing the serine phosphorylation of IRS protein via the activation of PKC and S6K, respectively. Similar analysis was also performed with respect to input amino acid and fatty acid levels. This emergent property of bistability in the integrated network helps us understand why it becomes extremely difficult to treat obesity and diabetes when blood glucose level rises beyond a certain value.

Keywords: bistability, diabetes, feedback and crosstalk, obesity

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Authors: John Narh

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There is high rate of deforestation in Ghana due to agricultural expansion, illegal mining and illegal logging. While it is attempting to address the illegalities, Ghana has also initiated a reforestation program known as the Modified Taungya System (MTS). Within the MTS framework, farmers are allocated degraded forestland and provided with tree seedlings to practice agroforestry until the trees form canopy. Yet, the political, ecological and economic models that inform the selection of tree species, the motivations of participating farmers as well as the factors that accounts for differential access to the land and performance of farmers engaged in the program lie underexplored. Using a sequential explanatory mixed methods approach in five forest-fringe communities in the Eastern Region of Ghana, the study reveals that economic factors and Ghana’s commitment to international conventions on the environment underpin the selection of tree species for the MTS program. Social network and access to remittances play critical roles in having access to, and enhances poor farmers’ chances in the program respectively. Farmers are more motivated by the access to degraded forestland to cultivate food crops than having a share in the trees that they plant. As such, in communities where participating farmers are not informed about their benefit in the tree that they plant, the program is largely unsuccessful.

Keywords: translocality, deforestation, forest management, social network

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Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

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This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

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Authors: Mehaiguene Madjid, Meddi Mohamed

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The results of applying the model WEAP 21 or 'Water Evaluation and Planning System' in Upper and Middle Cheliff are presented in cartographic and graphic forms by considering two scenarios: -Reference scenario 1961-1990, -Climate change scenarios (low and high) for 2020 and 2050. These scenarios are presented together in the results and compared them to know the impact on aquatic systems and water resources. For the low scenario for 2050, a decrease in the rate of runoff / infiltration will be 81.4 to 3.7 Hm3 between 2010 and 2050. While for the high scenario for 2050, the reduction will be 87.2 to 78.9 Hm3 between 2010 and 2050. Comparing the two scenarios, shows that the water supplied will increase by 216.7 Hm3 to 596 Hm3 up to 2050 if we do not take account of climate change. Whereas, if climate change will decrease step by step: from 2010 to 2026: for the climate change scenario (high scenario) by 2050, water supplied from 346 Hm3 to 361 Hm3. That of the reference scenario (1961-1990) will increase to 379.7 Hm3 in 2050. This is caused by the increased demand (increased population, irrigated area, etc ). The balance water management basin is positive for the different Horizons and different situations. If we do not take account of climate change will be the outflow of 5881.4 Hm3. This excess at the basin can be used as part of a transfer for example.

Keywords: balance water, management basin, climate change scenario, Upper and Middle Cheliff

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Authors: Michael Ray Brunt

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China has been the site of some of the most significant earthquakes in history; however, earthquake monitoring has long been the provenance of universities and research institutions. The China Digital Seismographic Network was initiated in 1983 and improved significantly during 1992-1993. Data from the CDSN is widely used by government and research institutions, and, generally, this data is not readily accessible to middle and high school students. An educational seismic network in China is needed to provide collaboration and research opportunities for students and engaging students around the country in scientific understanding of earthquake hazards and risks while promoting community awareness. In 2022, the Tsinghua International School (THIS) Seismology Team, made up of enthusiastic students and facilitated by two experienced teachers, was established. As a group, the team’s objective is to install seismographs in schools throughout China, thus creating an educational seismic network that shares data from the THIS Educational Seismic Network (THIS-ESN) and facilitates collaboration. The THIS-ESN initiative will enhance education and outreach in China about earthquake risks and hazards, introduce seismology to a wider audience, stimulate interest in research among students, and develop students’ programming, data collection and analysis skills. It will also encourage and inspire young minds to pursue science, technology, engineering, the arts, and math (STEAM) career fields. The THIS-ESN utilizes small, low-cost RaspberryShake seismographs as a powerful tool linked into a global network, giving schools and the public access to real-time seismic data from across China, increasing earthquake monitoring capabilities in the perspective areas and adding to the available data sets regionally and worldwide helping create a denser seismic network. The RaspberryShake seismograph is compatible with free seismic data viewing platforms such as SWARM, RaspberryShake web programs and mobile apps are designed specifically towards teaching seismology and seismic data interpretation, providing opportunities to enhance understanding. The RaspberryShake is powered by an operating system embedded in the Raspberry Pi, which makes it an easy platform to teach students basic computer communication concepts by utilizing processing tools to investigate, plot, and manipulate data. THIS Seismology Team believes strongly in creating opportunities for committed students to become part of the seismological community by engaging in analysis of real-time scientific data with tangible outcomes. Students will feel proud of the important work they are doing to understand the world around them and become advocates spreading their knowledge back into their homes and communities, helping to improve overall community resilience. We trust that, in studying the results seismograph stations yield, students will not only grasp how subjects like physics and computer science apply in real life, and by spreading information, we hope students across the country can appreciate how and why earthquakes bear on their lives, develop practical skills in STEAM, and engage in the global seismic monitoring effort. By providing such an opportunity to schools across the country, we are confident that we will be an agent of change for society.

Keywords: collaboration, outreach, education, seismology, earthquakes, public awareness, research opportunities

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Authors: Robson C. Santos, David D. Oliveira, Matheus M. Reis, Gerson G. Cunha, Marcos A. C. Moreira

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The project demonstrates the construction of a solar power generation, integrated inverter equipment to a "Grid-Tie" by converting direct current generated by solar panels, into alternating current, the same parameters of frequency and voltage concessionaire distribution network. The energy generated is quantified by smart metering module that transmits the information in specified periods of time to a microcontroller via GSM modem. The modem provides the measured data on the internet, using networks and cellular antennas. The monitoring, fault detection and maintenance are performed by a supervisory station. Employed board types, best inverter selection and studies about control equipment and devices have been described. The article covers and explores the global trend of implementing smart distribution electrical energy networks and the incentive to use solar renewable energy. There is the possibility of the excess energy produced by the system be purchased by the local power utility. This project was implemented in residences in the rural community of the municipality of Cabo Frio/RJ. Data could be seen through daily measurements during the month of November 2013.

Keywords: rural residence, supervisory, smart grid, solar energy

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Authors: Jasmine H. Gagnon

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The present study examined how grandiose narcissists make adaptive trade-offs between mating investment, parenting investment, and somatic investment relative to individuals without narcissistic personalities. A sample of 509 males and females between the ages of 24 and 35 years old (49.31% female) completed a personality inventory assessing Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness to Experience. In a Latent Profile Analysis (LPA), personality inventory scores were used to classify participants into latent groups. The model of best fit identified one grandiose narcissist group and three groups with non-narcissistic personalities. Covariate analyses revealed that individuals with narcissistic traits made significantly more significant somatic investments in comparison to two of the three non-narcissistic latent groups. No other significant differences between the narcissistic and non-pathological groups were found. Thus, grandiose narcissists trade off parenting and mating investments to make more significant somatic investments. That is, they expend a larger portion of their energetic resources on maintaining their physical health and careers and similar quantities of energetic resources on maintaining relationships with their offspring and potential romantic partners as individuals without narcissistic personalities.

Keywords: narcissism, grandiose narcissism, HEXACO, trade-offs, mating, parenting, somatic, dark triad

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled DNI field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: artificial neural networks, resilient propagation, solar radiation, time series forecasting

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Muhammad Atif, Cang Yan

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The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

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Authors: Lisa Kasmer

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Teachers’ instructional decisions shape the structure and content of mathematics lessons and influence the mathematics that students are given the opportunity to learn. Therefore, it is important to better understand how teachers make instructional decisions and thus find new ways to help practicing and future teachers give their students a more effective and robust learning experience. Understanding the relationship between teachers’ instructional decisions and their goals, resources, and orientations (beliefs) is important given the heightened focus on geometric transformations in the middle school mathematics curriculum. This work is significant as the development and support of current and future teachers need more effective ways to teach geometry to their students. The following research questions frame this study: (1) As middle school mathematics teachers plan and enact instruction related to teaching transformations, what thinking processes do they engage in to make decisions about teaching transformations with or without a coordinate system and (2) How do the goals, resources and orientations of these teachers impact their instructional decisions and reveal about their understanding of teaching transformations? Teachers and students alike struggle with understanding transformations; many teachers skip or hurriedly teach transformations at the end of the school year. However, transformations are an important mathematical topic as this topic supports students’ understanding of geometric and spatial reasoning. Geometric transformations are a foundational concept in mathematics, not only for understanding congruence and similarity but for proofs, algebraic functions, and calculus etc. Geometric transformations also underpin the secondary mathematics curriculum, as features of transformations transfer to other areas of mathematics. Teachers’ instructional decisions in terms of goals, orientations, and resources that support these instructional decisions were analyzed using open-coding. Open-coding is recognized as an initial first step in qualitative analysis, where comparisons are made, and preliminary categories are considered. Initial codes and categories from current research on teachers’ thinking processes that are related to the decisions they make while planning and reflecting on the lessons were also noted. Surfacing ideas and additional themes common across teachers while seeking patterns, were compared and analyzed. Finally, attributes of teachers’ goals, orientations and resources were identified in order to begin to build a picture of the reasoning behind their instructional decisions. These categories became the basis for the organization and conceptualization of the data. Preliminary results suggest that teachers often rely on their own orientations about teaching geometric transformations. These beliefs are underpinned by the teachers’ own mathematical knowledge related to teaching transformations. When a teacher does not have a robust understanding of transformations, they are limited by this lack of knowledge. These shortcomings impact students’ opportunities to learn, and thus disadvantage their own understanding of transformations. Teachers’ goals are also limited by their paucity of knowledge regarding transformations, as these goals do not fully represent the range of comprehension a teacher needs to teach this topic well.

Keywords: coordinate plane, geometric transformations, instructional decisions, middle school mathematics

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Authors: Merab Khokhobaia

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The research of Georgian tourism policy challenges is important, as the tourism can play an increasing role for the economic growth and improvement of standard of living of the country even with scanty resources, at the expense of improved creative approaches. It is also important to make correct decisions at macroeconomic level, which will be accordingly reflected in the successful functioning of the travel companies and finally, in the improvement of economic indicators of the country. In order to correctly orient sectoral policy, it is important to precisely determine its role in the economy. Development of travel industry has been considered as one of the priorities in Georgia; the country has unique cultural heritage and traditions, as well as plenty of natural resources, which are a significant precondition for the development of tourism. Despite the factors mentioned above, the existing resources are not completely utilized and exploited. This work represents a study of subjective, as well as objective reasons of ineffective functioning of the sector. During the years of transformation experienced by Georgia, the role of travel industry in economic development of the country represented the subject of continual discussions. Such assessments were often biased and they did not rest on specific calculations. This topic became especially popular on the ground of market economy, because reliable statistical data have a particular significance in the designing of tourism policy. In order to deeply study the aforementioned issue, this paper analyzes monetary, as well as non-monetary indicators. The research widely included the tourism indicators system; we analyzed the flaws in reporting of the results of tourism sector in Georgia. Existing defects are identified and recommendations for their improvement are offered. For stable development tourism, similarly to other economic sectors, needs a well-designed policy from the perspective of national, as well as local, regional development. The tourism policy must be drawn up in order to efficiently achieve our goals, which were established in short-term and long-term dynamics on the national or regional scale of specific country. The article focuses on the role and responsibility of the state institutes in planning and implementation of the tourism policy. The government has various tools and levers, which may positively influence the processes. These levers are especially important in terms of international, as well as internal tourism development. Within the framework of this research, the regulatory documents, which are in force in relation to this industry, were also analyzed. The main attention is turned to their modernization and necessity of their compliance with European standards. It is a current issue to direct the efforts of state policy on support of business by implementing infrastructural projects, as well as by development of human resources, which may be possible by supporting the relevant higher and vocational studying-educational programs.

Keywords: regional development, tourism industry, tourism policy, transition

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Bayesian network, classification, expert knowledge, structure learning, surface water analysis

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Authors: Jinwooung Kim, Jae-Hwan Jung, Seong-Jun Kim, Sung-Ah Kim

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Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.

Keywords: building envelope, machine learning, perforated metal, multi-factor optimization, façade

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Authors: Samaneh Poormohammadi, Farid Golkar, Vahideh Khatibi Sarabi

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Climate change and consecutive droughts have increased the importance of using rainwater harvesting methods. One of the methods of rainwater harvesting and, in other words, the management of atmospheric water resources is the use of weather modification technologies. Weather modification (also known as weather control) is the act of intentionally manipulating or altering the weather. The most common form of weather modification is cloud seeding, which increases rain or snow, usually for the purpose of increasing the local water supply. Cloud seeding operations in Iran have been married since 1999 in central Iran with the aim of harvesting rainwater and reducing the effects of drought. In this research, we analyze the results of cloud seeding operations in the Simindashtplain in northern Iran. Rainwater harvesting with the help of cloud seeding technology has been evaluated through its effects on surface water and underground water. For this purpose, two different methods have been used to estimate runoff. The first method is the US Soil Conservation Service (SCS) curve number method. Another method, known as the reasoning method, has also been used. In order to determine the infiltration rate of underground water, the balance reports of the comprehensive water plan of the country have been used. In this regard, the study areas located in the target area of each province have been extracted by drawing maps of the influence coefficients of each area in the GIS software. It should be mentioned that the infiltration coefficients were taken from the balance sheet reports of the country's comprehensive water plan. Then, based on the area of each study area, the weighted average of the infiltration coefficient of the study areas located in the target area of each province is considered as the infiltration coefficient of that province. Results show that the amount of water extracted from the rain with the help of cloud seeding projects in Simindasht is as follows: an increase in runoff 63.9 million cubic meters (with SCS equation) or 51.2 million cubic meters (with logical equation) and an increase in ground water resources: 40.5 million cubic meters.

Keywords: rainwater harvesting, ground water, atmospheric water resources, weather modification, cloud seeding

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Authors: Guenther Schuh, Christina Koenig, Nico Schoen, Markus Wellensiek

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Identification and selection of appropriate product and manufacturing technologies are key factors for competitiveness and market success of technology-based companies. Therefore many companies perform technology intelligence (TI) activities to ensure the identification of evolving technologies at the right time. Technology monitoring is one of the three base activities of TI, besides scanning and scouting. As the technological progress is accelerating, more and more technologies are being developed. Against the background of limited resources it is therefore necessary to focus TI activities. In this paper, we propose a concept for defining appropriate search fields for technology monitoring. This limitation of search space leads to more concentrated monitoring activities. The concept will be introduced and demonstrated through an anonymized case study conducted within an industry project at the Fraunhofer Institute for Production Technology. The described concept provides a customized monitoring approach, which is suitable for use in technology-oriented companies especially those that have not yet defined an explicit technology strategy. It is shown in this paper that the definition of search fields and search tasks are suitable methods to define topics of interest and thus to direct monitoring activities. Current as well as planned product, production and material technologies as well as existing skills, capabilities and resources form the basis of the described derivation of relevant search areas. To further improve the concept of technology monitoring the proposed concept should be extended during future research e.g. by the definition of relevant monitoring parameters.

Keywords: monitoring radar, search field, technology intelligence, technology monitoring

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Authors: Pouya Taraghi, Yong Li, Nader Yoosef-Ghodsi, Muntaseer Kainat, Samer Adeeb

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Buried pipelines play a crucial role in the transportation of energy products such as oil, gas, and various chemical fluids, ensuring their efficient and safe distribution. However, these pipelines are often susceptible to ground movements caused by geohazards like landslides, fault movements, lateral spreading, and more. Such ground movements can lead to strain-induced failures in pipes, resulting in leaks or explosions, leading to fires, financial losses, environmental contamination, and even loss of human life. Therefore, it is essential to study how buried pipelines respond when traversing geohazard-prone areas to assess the potential impact of ground movement on pipeline design. As such, this study introduces an approach called the Physics-Informed Neural Network (PINN) to predict the strain demand in inelastic pipes subjected to permanent ground displacement (PGD). This method uses a deep learning framework that does not require training data and makes it feasible to consider more realistic assumptions regarding existing nonlinearities. It leverages the underlying physics described by differential equations to approximate the solution. The study analyzes various scenarios involving different geohazard types, PGD values, and crossing angles, comparing the predictions with results obtained from finite element methods. The findings demonstrate a good agreement between the results of the proposed method and the finite element method, highlighting its potential as a simulation-free, data-free, and meshless alternative. This study paves the way for further advancements, such as the simulation-free reliability assessment of pipes subjected to PGD, as part of ongoing research that leverages the proposed method.

Keywords: strain demand, inelastic pipe, permanent ground displacement, machine learning, physics-informed neural network

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Authors: Szu-Hua Wang, Yi-Wen Chen

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Urban ecosystems are complex coupled human-environment systems. They contain abundant natural resources for producing natural assets and attract urban assets to consume natural resources for urban development. Urban ecosystems provide several ecosystem services, including provisioning services, regulating services, cultural services, and supporting services. Rapid global climate change makes urban ecosystems and their ecosystem services encountering various natural disasters. Lots of natural disasters have occurred around the world under the constant changes in the frequency and intensity of extreme weather events in the past two decades. In Taiwan, hydrological disasters have been paid more attention due to the potential high sensitivity of Taiwan’s cities to climate change, and it impacts. However, climate change not only causes extreme weather events directly but also affects the interactions among human, ecosystem services and their dynamic feedback processes indirectly. Therefore, this study adopts a systematic method, solar energy synthesis, based on the concept of the eco-energy analysis. The Taipei area, the most densely populated area in Taiwan, is selected as the study area. The changes of ecosystem services between 2015 and Typhoon Soudelor have been compared in order to investigate the impacts of extreme precipitation events on ecosystem services. The results show that the forest areas are the largest contributions of energy to ecosystem services in the Taipei area generally. Different soil textures of different subsystem have various upper limits of water contents or substances. The major contribution of ecosystem services of the study area is natural hazard regulation provided by the surface water resources areas. During the period of Typhoon Soudelor, the freshwater supply in the forest areas had become the main contribution. Erosion control services were the main ecosystem service affected by Typhoon Soudelor. The second and third main ecosystem services were hydrologic regulation and food supply. Due to the interactions among ecosystem services, fresh water supply, water purification, and waste treatment had been affected severely.

Keywords: ecosystem, extreme precipitation events, ecosystem services, solar energy synthesis

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Authors: Dominique Parrish

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Globally, higher education institutions are responsible for the quality assurance and accreditation of their educational programmes (Courses). The primary purpose of these activities is to ensure that the educational standards of the governing higher education authority are met and the quality of the education provided to students is assured. Despite policies and frameworks being established in many countries, to improve the veracity and accountability of quality assurance and accreditation processes, there are reportedly still mistakes, gaps and deficiencies in these processes. An analysis of Australian universities’ quality assurance and accreditation processes noted that significant improvements were needed in managing these processes and ensuring that review recommendations were implemented. It has also been suggested that the following principles are critical for higher education quality assurance and accreditation to be effective and sustainable: academic standards and performance outcomes must be defined, attainable and monitored; those involved in providing the higher education must assume responsibility for the associated quality assurance and accreditation; potential academic risks must be identified and management solutions developed; and the expectations of the public, governments and students should be considered and incorporated into Course enhancements. This phenomenological study, which was conducted in a Faculty of Science, Medicine and Health in an Australian university, sought to systematically and iteratively develop an effective quality assurance and accreditation process that integrated the evidence-based principles of success and promoted meaningful and sustainable change. Qualitative evaluative feedback was gathered, over a period of eleven months (January - November 2014), from faculty staff engaged in the quality assurance and accreditation of forty-eight undergraduate and postgraduate Courses. Reflexive analysis was used to analyse the data and inform ongoing modifications and developments to the assurance and accreditation process as well as the associated supporting resources. The study resulted in the development of a formal quality assurance and accreditation process together with a suite of targeted resources that were identified as critical for success. The research findings also provided some insights into the institutional enablers that were antecedents to successful quality assurance and accreditation processes as well as meaningful change in the educational practices of academics. While longitudinal data will be collected to further assess the value of the assurance and accreditation process on educational quality, early indicators are that there has been a change in the pedagogical perspectives and activities of academic staff and growing momentum to explore opportunities to further enhance and develop Courses. This presentation will explain the formal quality assurance and accreditation process as well as the component parts, which resulted from this study. The targeted resources that were developed will be described, the pertinent factors that contributed to the success of the process will be discussed and early indicators of sustainable academic change as well as suggestions for future research will be outlined.

Keywords: academic standards, quality assurance and accreditation, phenomenological study, process, resources

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

Procedia PDF Downloads 150

Authors: Christo Nicholls

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The National Electricity Grid (NEG) in South Africa has been under strain for the last five years. This overburden of the NEG led Eskom (the State-Owned Entity responsible for the NEG) to implement a blunt methodology to assist them in reducing the maximum demand (MD) on the NEG, when required, called Loadshedding. The challenge of this methodology is that not only does it lead to immense technical issues with the distribution network equipment, e.g., transformers, due to the frequent abrupt off and on switching, it also has a broader negative fiscal impact on the distributors, as their key consumers (commercial & industrial) are now grid defecting due to the lack of Electricity Security Provision (ESP). This paper provides a pragmatic alternative methodology utilizing specific functionalities embedded within direct-connect single and three-phase Advanced Meter Infrastructure (AMI) Solutions deployed within the distribution network, in conjunction with a Multi-Agent Systems Based AI implementation focused on Automated Negotiation Peer-2-Peer trading. The results of this research clearly illustrate, not only does methodology provide a factual percentage contribution towards the NEG MD at the point of consideration, it also allows the distributor to leverage the real-time MD data from key consumers to activate complex, yet impact-measurable Demand Response (DR) programs.

Keywords: AI, AMI, demand response, multi-agent

Procedia PDF Downloads 98

Authors: Maria Jose Ramos Villagra

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Since the boom of tourism in the late 80s and 90s, Costa Rica is considered as one of the leading countries for tourism. The size and geography of its territory, its low population density, and its image of being one of the most stable Latin American democracies make Costa Rica an attractive and safe target for foreign investors. Land ownership by foreign investors has increased as the natural resources in rural communities have been exhausted. When nature becomes an instrument to increase profit, it loses its communal value contributing to local communities losing their sovereignty and access to basic resources. The rural regions in proximity to the most tourist areas are often the most marginalized. The purpose of this research is to use the case of the rural community Sardinal and its struggle to protect its aquifer to investigate the economic and cultural consequences of the tourism boom in Costa Rican rural communities. The process of reclaiming the access to and the preservation of the aquifer enabled individuals to redefine their political views and their political power. The case of Sardinal broke the stereotypes about rural individuals and their ability to politically educate themselves and organize. Sardinal´s conflict brought to light the necessity of questioning the role of modern tourism as part of Costa Rica’s national identity, and as a tool for development

Keywords: Costa Rica, tourism, rural development, economy, ecotourism, environment, water, Sardinal

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Authors: Lauren B. Birney

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The BOP-CCERS (Billion Oyster Project- Curriculum and Community Enterprise for Restoration Science) Near-Peer Mentoring Program provides the long-term (five-year) support network to motivate and guide students toward restoration science-based CTE pathways. Students are selected from middle schools with actively participating BOP-CCERS teachers. Teachers will nominate students from grades 6-8 to join cohorts of between 10 and 15 students each. Cohorts are comprised primarily of students from the same school in order to facilitate mentors' travel logistics as well as to sustain connections with students and their families. Each cohort is matched with an exceptional undergraduate or graduate student, either a BOP research associate or STEM mentor recruited from collaborating City University of New York (CUNY) partner programs. In rare cases, an exceptional high school junior or senior may be matched with a cohort in addition to a research associate or graduate student. In no case is a high school student or minor be placed individually with a cohort. Mentors meet with students at least once per month and provide at least one offsite field visit per month, either to a local STEM Hub or research lab. Keeping with its five-year trajectory, the near-peer mentoring program will seek to retain students in the same cohort with the same mentor for the full duration of middle school and for at least two additional years of high school. Upon reaching the final quarter of 8th grade, the mentor will develop a meeting plan for each individual mentee. The mentee and the mentor will be required to meet individually or in small groups once per month. Once per quarter, individual meetings will be substituted for full cohort professional outings. The mentor will organize the entire cohort on a field visit or educational workshop with a museum or aquarium partner. In addition to the mentor-mentee relationship, each participating student will also be asked to conduct and present his or her own BOP field research. This research is ideally carried out with the support of the students’ regular high school STEM subject teacher; however, in cases where the teacher or school does not permit independent study, the student will be asked to conduct the research on an extracurricular basis. Near-peer mentoring affects students’ social identities and helps them to connect to role models from similar groups, ultimately giving them a sense of belonging. Qualitative and quantitative analytics were performed throughout the study. Interviews and focus groups also ensued. Additionally, an external evaluator was utilized to ensure project efficacy, efficiency, and effectiveness throughout the entire project. The BOP-CCERS Near Peer Mentoring program is a peer support network in which high school students with interest or experience in BOP (Billion Oyster Project) topics and activities (such as classroom oyster tanks, STEM Hubs, or digital platform research) provide mentorship and support for middle school or high school freshmen mentees. Peer mentoring not only empowers those students being taught but also increases the content knowledge and engagement of mentors. This support provides the necessary resources, structure, and tools to assist students in finding success.

Keywords: STEM education, environmental science, citizen science, near peer mentoring

Procedia PDF Downloads 76

Authors: Mohamed Elshal, Hazim El-Mounayri, Omar El-Mounayri

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Emergency department (ED) is considered as a complex system of interacting entities: patients, human resources, software and hardware systems, interfaces, and other systems. This paper represents a research for implementing a detailed Systems Engineering (SE) approach in a mid-size hospital in central Indiana. This methodology will be applied by “The Initiative for Product Lifecycle Innovation (IPLI)” institution at Indiana University to study and solve the crowding problem with the aim of increasing throughput of patients and enhance their treatment experience; therefore, the nature of crowding problem needs to be investigated with all other problems that leads to it. The presented SE methods are workflow analysis and systems modeling where SE tools such as Microsoft Visio are used to construct a group of system-level diagrams that demonstrate: patient’s workflow, documentation and communication flow, data systems, human resources workflow and requirements, leadership involved, and integration between ER different systems. Finally, the ultimate goal will be managing the process through implementation of an executable model using commercialized software tools, which will identify bottlenecks, improve documentation flow, and help make the process faster.

Keywords: systems modeling, ED operation, workflow modeling, systems analysis

Procedia PDF Downloads 167

Authors: April Hueimin Lu, Liangj-Ju Yao, Jun-Tin Lin, Susan Siru Liu

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This paper discusses the application of aerial survey technology and 3D laser scanning technology in the surveying and mapping work of the settlements and slate houses of the old Taiwanese aborigines. The relics of old Taiwanese aborigines with thousands of history are widely distributed in the deep mountains of Taiwan, with a vast area and inconvenient transportation. When constructing the basic data of cultural assets, it is necessary to apply new technology to carry out efficient and accurate settlement mapping work. In this paper, taking the old Paiwan as an example, the aerial survey of the settlement of about 5 hectares and the 3D laser scanning of a slate house were carried out. The obtained orthophoto image was used as an important basis for drawing the settlement map. This 3D landscape data of topography and buildings derived from the aerial survey is important for subsequent preservation planning as well as building 3D scan provides a more detailed record of architectural forms and materials. The 3D settlement data from the aerial survey can be further applied to the 3D virtual model and animation of the settlement for virtual presentation. The information from the 3D scanning of the slate house can also be used for further digital archives and data queries through network resources. The results of this study show that, in large-scale settlement surveys, aerial surveying technology is used to construct the topography of settlements with buildings and spatial information of landscape, as well as the application of 3D scanning for small-scale records of individual buildings. This application of 3D technology, greatly increasing the efficiency and accuracy of survey and mapping work of aboriginal settlements, is much helpful for further preservation planning and rejuvenation of aboriginal cultural heritage.

Keywords: aerial survey, 3D scanning, aboriginal settlement, settlement architecture cluster, ecological landscape area, old Paiwan settlements, slat house, photogrammetry, SfM, MVS), Point cloud, SIFT, DSM, 3D model

Procedia PDF Downloads 142

Authors: Parul Bhalla, Sarvesh Palria

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Wetlands are areas of land that are either temporarily or permanently covered by water. Wetlands exhibit enormous diversity according to their genesis, geographical location, water regime and chemistry, dominant plants and soil or sediment characteristics. The spatial and temporal characteristics of wetland in terms of turbidity and aquatic vegetation could serve as guiding tool, in conservation prioritization of wetlands. The aquatic vegetation in the wetland is an indicator of the trophic status of the wetland which has a bearing on the water quality, the turbidity level in any wetland is indicative of the quality of the water in it. To conserve and manage wetland resources, it is important to have inventory of wetland and its catchment. Fateh Sagar wetland in Udaipur city is the one of the important wetland for tourism industry and other economic activities in the region. Realizing the importance of the wetland, the present study has been taken up with the specific objective of delineation and characterization of Fateh Sagar wetland in terms of turbidity and aquatic vegetation, using high resolution satellite data such as Cartosat and LISS IV multi-temporal data, which will efficiently bring out the changes in water spread and quality parameters. The catchment of wetland has been also characterized for various features. The study leads in to takes necessary steps to conserve the wetland and its resources.

Keywords: aquatic vegetation, catchment, turbidity status, wetland

Procedia PDF Downloads 382