Search results for: local area network

Authors: D. Diaz, C. Guevara, P. Rey

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This paper contains information about designing, shielding and protocols building in order to avoid ionizing radiation in X-Rays imaging areas as generated by X-Ray, mammography equipment, computed tomography equipment and digital subtraction angiography equipment, according to global standards. Furthermore, tools and elements about infrastructure to improve protection over patients, physicians and staff involved in a diagnostic imaging area are presented. In addition, technical parameters about each machine and the architecture designs and maps are described.

Keywords: imaging area, X-ray, shielding, dose

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Authors: Emmanuel D. Buedi, K. O. Boateng, Griffith S. Klogo

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Electrical distribution networks are prone to power quality disturbances originating from the complexity of the distribution network, mode of distribution (overhead or underground) and types of loads used by customers. Data on the types of disturbances present and frequency of occurrence is needed for economic evaluation and hence finding solution to the problem. Utility companies have resorted to using secondary power quality devices such as smart meters to help gather the required data. Even though this approach is easier to adopt, data gathered from these devices may not serve the required purpose, since the installation of these devices in the electrical network usually does not conform to available PQM placement methods. This paper presents a design of a PQM that is capable of integrating into an existing DAS infrastructure to take advantage of available placement methodologies. The monitoring component of the design is implemented and installed to monitor an existing LV network. Data from the monitor is analyzed and presented. A portion of the LV network of the Electricity Company of Ghana is modeled in MATLAB-Simulink and analyzed under various earth fault conditions. The results presented show the ability of the PQM to detect and analyze PQ disturbance such as voltage sag and overvoltage. By adopting a placement methodology and installing these nodes, utilities are assured of accurate and reliable information with respect to the quality of power delivered to consumers.

Keywords: power quality, remote monitoring, distributed automation system, economic evaluation, LV network

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Authors: Auntika Thipjumnong

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This research study aimed to investigate the production process and the market target of Kraseasin’s woven cloth including the customers’ behaviors towards the local woven products. The suggestions of a better process of production were recommended in this study. This survey research was conducted by using a questionnaire and interview, which were considered as the practical instruments to collect the data. The 200 Kraseasin’s woven makers and consumers were subjects by using a purposive sampling. Percentages, means and standard deviation were used to analyze data. The findings revealed that only 22 local woven members owned their 18 manual weavers in producing the raw materials like cotton or fiber. The main products were flowery woven cloth e.g. pikul, puangchompoo, pakakrong and ban mai roo roiy, and the others were rainy, glass wall, dice glass ball and yok dok etc. At the present, all local woven products were applied to be modernized but the strong point of those products were keeping the quality standard and firming textures, not thickness. The main objective of producing these local woven products was to earn and increase their extra incomes. Moreover, there were two dominant sales: Firstly, the makers sold their own products by themselves in their community and malls; and secondly, they would weave their products by customers’ orders. The prices’ allocation was on the difficulties in producing process. The government officials and non-government officials in local were normally customers. However the drawback of producing this local product was lack of raw material and this brought about the higher investment. The community’s customers were now lacking of interest in wearing these local products, even though they maintained their quality standard. The factors in customers’ purchasing decision were product (M = 3.93), price (M = 3.74), distribution (M = 3.73) and promotion (M = 3.97) for marketing mix well-known. Suggestion was a designing pattern of products had to be matched to the customers’ needs.

Keywords: marketing, consumer behavior, cloth products weaves, Songkhla Thailand

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Authors: Ayman Othman, Tallat Ali

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A pavement maintenance management system (PMMS) was developed for the city of Aswan as a model of a small city to provide the road maintenance department in Aswan city with the capabilities for comprehensive planning of the maintenance activities needed to put the internal pavement network into desired physical condition in view of maintenance budget constraints. The developed system consists of three main stages. First is the inventory & condition survey stage where the internal pavement network of Aswan city was inventoried and its actual conditions were rated in segments of 100 meters length. Second is the analysis stage where pavement condition index (PCI) was calculated and the most appropriate maintenance actions were assigned for each segment. The total maintenance budget was also estimated and a parameter based ranking criteria were developed to prioritize maintenance activities when the available maintenance budget is not sufficient. Finally comes the packaging stage where approved maintenance budget is packed into maintenance projects for field implementation. System results indicate that, the system output maintenance budget is very reasonable and the system output maintenance programs agree to a great extent with the actual maintenance needs of the network. Condition survey of Aswan city road network showed that roughness is the most dominate distress. In general, the road network can be considered in a fairly reasonable condition, however, the developed PMMS needs to be officially adapted to maintain the road network in a desirable condition and to prevent further deterioration.

Keywords: pavement, maintenance, management, system, distresses, survey, ranking

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Authors: Masood Ahmad, Ataul Aziz Ikram, Ishtiaq Wahid

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Wireless sensor network (WSN) is the interconnection of mobile wireless nodes with limited energy and memory. These networks can be deployed formany critical applications like military operations, rescue management, fire detection and so on. In flat routing structure, every node plays an equal role of sensor and router. The topology may change very frequently due to the mobile nature of nodes in WSNs. The topology maintenance may produce more overhead messages. To avoid topology maintenance overhead messages, an optimized cluster based mobile wireless sensor network using memetic algorithm is proposed in this paper. The nodes in this network are first divided into clusters. The cluster leaders then transmit data to that base station. The network is validated through extensive simulation study. The results show that the proposed technique has superior results compared to existing techniques.

Keywords: WSN, routing, cluster based, meme, memetic algorithm

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Authors: Khader S. Al-Aidmat, Venus W. Samawi

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Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

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Authors: Katharina Eberhardt, Florian Klaus Kaiser, Frank Schultmann

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Last-mile distribution is one of the most critical parts of a disaster relief operation. Various uncertainties, such as infrastructure conditions, resource availability, and fluctuating beneficiary demand, render last-mile distribution challenging in disaster relief operations. The need to balance critical performance criteria like response time, meeting demand and cost-effectiveness further complicates the task. The occurrence of disasters cannot be controlled, and the magnitude is often challenging to assess. In summary, these uncertainties create a need for additional flexibility, agility, and preparedness in logistics operations. As a result, strategic planning and efficient network design are critical for an effective and efficient response. Furthermore, the increasing frequency of disasters and the rising cost of logistical operations amplify the need to provide robust and resilient solutions in this area. Therefore, we formulate a scenario-based bi-objective optimization model that integrates pre-positioning, allocation, and distribution of relief supplies extending the general form of a covering location problem. The proposed model aims to minimize underlying logistics costs while maximizing demand coverage. Using a set of disruption scenarios, the model allows decision-makers to identify optimal network solutions to address the risk of disruptions. We provide an empirical case study of the public authorities’ emergency food storage strategy in Germany to illustrate the potential applicability of the model and provide implications for decision-makers in a real-world setting. Also, we conduct a sensitivity analysis focusing on the impact of varying stockpile capacities, single-site outages, and limited transportation capacities on the objective value. The results show that the stockpiling strategy needs to be consistent with the optimal number of depots and inventory based on minimizing costs and maximizing demand satisfaction. The strategy has the potential for optimization, as network coverage is insufficient and relies on very high transportation and personnel capacity levels. As such, the model provides decision support for public authorities to determine an efficient stockpiling strategy and distribution network and provides recommendations for increased resilience. However, certain factors have yet to be considered in this study and should be addressed in future works, such as additional network constraints and heuristic algorithms.

Keywords: humanitarian logistics, bi-objective optimization, pre-positioning, last mile distribution, decision support, disaster relief networks

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Authors: Emel Bayraktar, Gulengun Turk

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Introduction and Objective: Safe administration of medicines is one of the main responsibilities of nurses. Intramuscular drug administration is among the most common methods used by nurses among all drug applications. This study was carried out in order to determine determine the effect of education given on injection in ventrogluteal area on the level of knowledge of nurses on this subject. Methods: The sample of the study consisted of 20 nurses who agreed to participate in the study between 01 October and 31 December 2019. The research is a pretest-posttest comparative, quasi-experimental type pilot study. The nurses were given a 4-hour training prepared on injection into the ventrogluteal area. The training consisted of two hours of theoretical and two hours of laboratory practice. Before the training and 4 weeks after the training, a questionnaire form containing questions about their knowledge and practices regarding the injection of the ventrogluteal region was applied to the nurses. Results: The average age of the nurses is 26.55 ± 7.60, 35% (n = 7) of them are undergraduate and 30% (n = 6) of them work in intensive care units. Before the training, 35% (n = 7) of the nurses stated that the most frequently used intramuscular injection site was the ventrogluteal area, and 75% (n = 15) stated that the safest area was the rectus femoris muscle. After the training, 55% (n = 11) of the nurses stated that they most frequently used the ventrogluteal area and 100% (n = 20) of them stated that the ventrogluteal area was the safest area. The average score the nurses got from the premises before the training is 14.15 ± 6.63 (min = 0, max = 20), the total score is 184. The average score obtained after the training was determined as 18.69 ± 2.35 (min = 12, max = 20), and the total score was 243. Conclusion: As a result of the research, it was determined that the training given on the injection of ventrogluteal area increased the knowledge level of the nurses. It is recommended to organize in-service trainings for all nurses on the injection of ventrogluteal area.

Keywords: safe injection, knowledge level, nurse, intramuscular injection, ventrogluteal area

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Authors: Daniele Contini, Antonio Donateo, Andrea Gambaro, Athanasios Argiriou, Dimitrios Melas, Daniela Cesari, Anastasia Poupkou, Athanasios Karagiannidis, Apostolos Tsakis, Eva Merico, Rita Cesari, Adelaide Dinoi

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Emissions of atmospheric pollutants from ships and harbour activities are a growing concern at International level given their potential impacts on air quality and climate. These close-to-land emissions have potential impact on local communities in terms of air quality and health. Recent studies show that the impact of maritime traffic to atmospheric particulate matter concentrations in several coastal urban areas is comparable with the impact of road traffic of a medium size town. However, several different approaches have been used for these estimates making difficult a direct comparison of results. In this work an integrated approach based on emission inventories and dedicated measurement campaigns has been applied to give a comparable estimate of the impact of maritime traffic to PM2.5 and particle number concentrations in three major harbours of the Adriatic/Ionian Seas. The influences of local meteorology and of the logistic layout of the harbours are discussed.

Keywords: ship emissions, PM2.5, particle number concentrations, impact of shipping to atmospheric aerosol

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Authors: Roven Tumaneng, Angelica Kristina Monzon, Ralph Sedricke Lapuz, Jose Don De Alban, Jennica Paula Masigan, Joanne Rae Pales, Laila Monera Pornel, Dennis Tablazon, Rizza Karen Veridiano, Jackie Lou Wenceslao, Edmund Leo Rico, Neil Aldrin Mallari

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Most protected area management plans in the Philippines, particularly the smaller and more remote islands suffer from insufficient baseline data, which should provide the bases for formulating measureable conservation targets and appropriate management interventions for these protected areas. Attempts to synthesize available data particularly on cultural and socio-economic characteristic of local peoples within and outside protected areas also suffer from the lack of comprehensive and detailed inventories, which should be considered in designing adaptive management interventions to be used for those protected areas. Mt Guiting-guiting Natural Park (MGGNP) located in Sibuyan Island is one of the poorly studied protected areas in the Philippines. In this study, we determined the highly biologically important areas of the protected area using Maximum Entropy approach (MaxEnt) from environmental predictors (i.e., topographic, bioclimatic,land cover, and soil image layers) derived from global remotely sensed data and point occurrence data of species of birds and trees recorded during field surveys on the island. A total of 23 trigger species of birds and trees was modeled and stacked to generate species richness maps for biological high conservation value areas (HCVAs). Forest habitat change was delineated using dual-polarised L-band ALOS-PALSAR mosaic data at 25 meter spatial resolution, taken at two acquisition years 2007 and 2009 to provide information on forest cover ad habitat change in the island between year 2007 and 2009. Determining the livelihood guilds were also conducted using the data gathered from171 household interviews, from which demographic and livelihood variables were extracted (i.e., age, gender, number of household members, educational attainment, years of residency, distance from forest edge, main occupation, alternative sources of food and resources during scarcity months, and sources of these alternative resources).Using Principal Component Analysis (PCA) and Kruskal-Wallis test, the diversity and patterns of forest resource use by people in the island were determined with particular focus on the economic activities that directly and indirectly affect the population of key species as well as to identify levels of forest resource use by people in different areas of the park.Results showed that there are gaps in the area occupied by the natural park, as evidenced by the mismatch of the proposed HCVAs and the existing perimeters of the park. We found out that subsistence forest gathering was the possible main driver for forest degradation out of the eight livelihood guilds that were identified in the park. Determining the high conservation areas and identifyingthe anthropogenic factors that influence the species richness and abundance of key species in the different management zone of MGGNP would provide guidance for the design of a protected area management plan and future monitoring programs. However, through intensive communication and consultation with government stakeholders and local communities our results led to setting conservation targets in local development plans and serve as a basis for the reposition of the boundaries and reconfiguration of the management zones of MGGNP.

Keywords: conservation gaps, livelihood guilds, MaxEnt, protected area

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Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

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Authors: D. Pazder

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The main assumption of the study is to examine the coherence between two aspects of spatial planning important in Poland. The first one is the need to realize a participatory planning paradigm, and the second is a global trend of the pro-ecological orientation of city development. The aim of the research is the verification of the possibility of finding the right balance between economic and socio-spatial dimensions of urban redefinition, especially within public green areas. The significance of the examination lies in the fact that there are a huge anthropopressure and overinvestment in downtown areas of big Polish cities. The methodology used in the research of a case study was the three-layered comparative analyses of spatial planning documents, participatory planning undertakings, soft and hard actions concerning a given area in the period of 2008-2020. The main findings are that there is a lack of satisfactory cooperation between the municipality and local communities, a connection between soft actions and investment in green public space, inhabitants are of high ecological consciousness but not so concerned about spatial planning legislation. The conclusion is that it is needed to provide real participation in spatial planning processes so as to take advantage of local communities’ activity and to combine more top-down and bottom-up actions so as to integrate people and educate them on how to act in favor of a common good in democratic citizenship.

Keywords: placemaking, participatory planning, anesthetization, public greenery

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Authors: Imam Muthohar, Budi Hartono, Sigit Priyanto, Hardiansyah Hardiansyah

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The eruption of Merapi Volcano in Yogyakarta, Indonesia in 2010 caused many casualties due to minimum preparedness in facing disaster. Increasing population capacity and evacuating to safe places become very important to minimize casualties. Regional government through the Regional Disaster Management Agency has divided disaster-prone areas into three parts, namely ring 1 at a distance of 10 km, ring 2 at a distance of 15 km and ring 3 at a distance of 20 km from the center of Mount Merapi. The success of the evacuation is fully supported by road network infrastructure as a way to rescue in an emergency. This research attempts to model evacuation process based on the rise of refugees in ring 1, expanded to ring 2 and finally expanded to ring 3. The model was developed using SATURN (Simulation and Assignment of Traffic to Urban Road Networks) program version 11.3. 12W, involving 140 centroid, 449 buffer nodes, and 851 links across Yogyakarta Special Region, which was aimed at making a preliminary identification of road networks considered vulnerable to disaster. An assumption made to identify vulnerability was the improvement of road network performance in the form of flow and travel times on the coverage of ring 1, ring 2, ring 3, Sleman outside the ring, Yogyakarta City, Bantul, Kulon Progo, and Gunung Kidul. The research results indicated that the performance increase in the road networks existing in the area of ring 2, ring 3, and Sleman outside the ring. The road network in ring 1 started to increase when the evacuation was expanded to ring 2 and ring 3. Meanwhile, the performance of road networks in Yogyakarta City, Bantul, Kulon Progo, and Gunung Kidul during the evacuation period simultaneously decreased in when the evacuation areas were expanded. The results of preliminary identification of the vulnerability have determined that the road networks existing in ring 1, ring 2, ring 3 and Sleman outside the ring were considered vulnerable to the evacuation of Mount Merapi eruption. Therefore, it is necessary to pay a great deal of attention in order to face the disasters that potentially occur at anytime.

Keywords: model, evacuation, SATURN, vulnerability

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Authors: Matias Hargreaves, Martin Del Valle, Diego Rodriguez, Riveros Jose Luis

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Trough years, all kind of social development projects have tried to solve social problems such as hunger, poverty, malnutrition, food insecurity, among others, with poor success. Both private and state initiatives have invested resources in several countries and communities. Nevertheless, most of these initiatives are scientific or external developers-centered, with a lack of local participation. This compromises the sustainability of any intervention and also leads to a poor empowerment of local community. The participatory approach aims to rescue and enhance the local knowledge since it recognizes that this kind of problems are better known by native actors. The objective of the study was to describe the role played by the community empowerment on food security improvement in the NGO “O Viveiro” (15°43'37.77"S; 32°46'27.53"E) and Barrio Broma village (15°43'58.78"S; 32°46'7.27"E) in Chitima, Mozambique. A center for training in goat livestock and orchard was build. A community orchard was co-constructed between foreign technicians and local actors. The prototype was installed in February, 2016 by the technician team and local community with 16 m2 as a nursery garden. Two orchard workshops were conducted in order to design a sustainable productive model which mixes both local and technological approaches. Two goat meat workshops were conducted in order to describe local methods and train the community to conduce their own techniques with high sanitary and productive standards. Technician team stayed in Mozambique until May, 2016. The quorum for the orchard workshops was 20 and 14 persons respectively, which represents 100% and 70%of the total requested quorum (20). For the goat meat workshops were 4 and 5 persons, which representa80% and 100% of the total requested quorum (5). Until August, 2016, the orchard is 3.219 m2 and it grows several vegetables as beans, chili pepper, garlic, onion, tomatoes, lettuce, sweet potato, yuca potato, cabbage, eggplant, papaya trees, mango, and cassava. The process of increasing in size and diversification of vegetables grown was led entirely by the local community. In connection with this, the local community started to harvest and began to sell the vegetable products at the local market. At the meat goat workshops, local participants rescued a local knowledge by describing and practicing a traditional way to process goat meat by drying it outdoors and then doing a smoked treatment. This information might contribute to describe the level of empowerment of this community, and thus give evidence of acceptance of foreign intervention for improving their own proceedings and traditions.

Keywords: children malnutrition, food security, Local community, participatory approach

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Authors: Tomas Berhanu Bekele

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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.

Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression

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Authors: Jianlun Zhang, Christine Lim

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Local food is one of the most attractive elements to tourists. The role of local cuisine in destination branding is very important because it is the distinctive identity that helps tourists remember the destination. The objectives of this study are: (1) Test the direct relation between the cognitive image of destination food and tourists’ intention to eat local food. (2) Examine the mediating effect of tourists’ desire to try destination food on the relationship between the cognitive image of local food and tourists’ intention to eat destination food. (3) Study the moderating effect of tourists’ perceived difficulties in finding local food on the relationship between tourists’ desire to try destination food and tourists’ intention to eat local food. To achieve the goals of this study, Macanese cuisine is selected as the destination food. Macau is located in Southeastern China and is a former colonial city of Portugal. The taste and texture of Macanese cuisine are unique because it is a fusion of cuisine from many countries and regions of mainland China. As people travel to seek authentically exotic experience, it is important to investigate if the food image of Macau leaves a good impression on tourists and motivate them to try local cuisine. A total of 449 Chinese tourists were involved in this study. To analyze the data collected, partial least square-structural equation modelling (PLS-SEM) technique is employed. Results suggest that the cognitive image of Macanese cuisine has a direct effect on tourists’ intention to eat Macanese cuisine. Tourists’ desire to try Macanese cuisine mediates the cognitive image-intention relationship. Tourists’ perceived difficulty of finding Macanese cuisine moderates the desire-intention relationship. The lower tourists’ perceived difficulty in finding Macanese cuisine is, the stronger the desire-intention relationship it will be. There are several practical implications of this study. First, the government tourism website can develop an authentic storyline about the evolvement of local cuisine, which provides an opportunity for tourists to taste the history of the destination and create a novel experience for them. Second, the government should consider the development of food events, restaurants, and hawker businesses. Third, to lower tourists’ perceived difficulty in finding local cuisine, there should be locations of restaurants and hawker stalls with clear instructions for finding them on the websites of the government tourism office, popular tourism sites, and public transportation stations in the destination. Fourth, in the post-COVID-19 era, travel risk will be a major concern for tourists. Therefore, when promoting local food, the government tourism website should post images that show food safety and hygiene.

Keywords: cognitive image of destination food, desire to try destination food, intention to eat food in the destination, perceived difficulties of finding local cuisine, PLS-SEM

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Authors: Arwa Alzughaibi

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Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

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Authors: Yijun Shao, Yan Cheng, Rashmee U. Shah, Charlene R. Weir, Bruce E. Bray, Qing Zeng-Treitler

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Deep neural network (DNN) models are being explored in the clinical domain, following the recent success in other domains such as image recognition. For clinical adoption, outcome prediction models require explanation, but due to the multiple non-linear inner transformations, DNN models are viewed by many as a black box. In this study, we developed a deep neural network model for predicting 1-year mortality of patients who underwent major cardio vascular procedures (MCVPs), using temporal image representation of past medical history as input. The dataset was obtained from the electronic medical data warehouse administered by Veteran Affairs Information and Computing Infrastructure (VINCI). We identified 21,355 veterans who had their first MCVP in 2014. Features for prediction included demographics, diagnoses, procedures, medication orders, hospitalizations, and frailty measures extracted from clinical notes. Temporal variables were created based on the patient history data in the 2-year window prior to the index MCVP. A temporal image was created based on these variables for each individual patient. To generate the explanation for the DNN model, we defined a new concept called impact score, based on the presence/value of clinical conditions’ impact on the predicted outcome. Like (log) odds ratio reported by the logistic regression (LR) model, impact scores are continuous variables intended to shed light on the black box model. For comparison, a logistic regression model was fitted on the same dataset. In our cohort, about 6.8% of patients died within one year. The prediction of the DNN model achieved an area under the curve (AUC) of 78.5% while the LR model achieved an AUC of 74.6%. A strong but not perfect correlation was found between the aggregated impact scores and the log odds ratios (Spearman’s rho = 0.74), which helped validate our explanation.

Keywords: deep neural network, temporal data, prediction, frailty, logistic regression model

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Authors: Somia Bouzid, Messaoud Ramdani

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The success of any diagnosis strategy critically depends on the sensors measuring process variables. This paper presents a detection and diagnosis sensor faults method based on a Bottleneck Neural Network (BNN). The BNN approach is used as a statistical process control tool for drinking water distribution (DWD) systems to detect and isolate the sensor faults. Variable reconstruction approach is very useful for sensor fault isolation, this method is validated in simulation on a nonlinear system: actual drinking water distribution system. Several results are presented.

Keywords: fault detection, localization, PCA, NLPCA, auto-associative neural network

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Authors: Marina Bubalo, Davor Romić, Stjepan Husnjak, Helena Bakić

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Even though European Council Directive 91/676/EEC known as Nitrates Directive was adopted in 1991, the issue of water quality preservation in areas of intensive agricultural production still persist all over Europe. High nitrate nitrogen concentrations in surface and groundwater originating from diffuse sources are one of the most important environmental problems in modern intensive agriculture. The fate of nitrogen in soil, surface and groundwater in agricultural area is mostly affected by anthropogenic activity (i.e. agricultural practice) and hydrological and climatological conditions. The aim of this study was to identify impact of land use, soil type, soil vulnerability to pollutant percolation, and natural aquifer vulnerability to nitrate occurrence in surface and groundwater within an intensive agricultural area. The study was set in Varaždin County (northern Croatia), which is under significant influence of the large rivers Drava and Mura and due to that entire area is dominated by alluvial soil with shallow active profile mainly on gravel base. Negative agricultural impact on water quality in this area is evident therefore the half of selected county is a part of delineated nitrate vulnerable zones (NVZ). Data on water quality were collected from 7 surface and 8 groundwater monitoring stations in the County. Also, recent study of the area implied detailed inventory of agricultural production and fertilizers use with the aim to produce new agricultural land use database as one of dominant parameters. The analysis of this database done using ArcGIS 10.1 showed that 52,7% of total County area is agricultural land and 59,2% of agricultural land is used for intensive agricultural production. On the other hand, 56% of soil within the county is classified as soil vulnerable to pollutant percolation. The situation is similar with natural aquifer vulnerability; northern part of the county ranges from high to very high aquifer vulnerability. Statistical analysis of water quality data is done using SPSS 13.0. Cluster analysis group both surface and groundwater stations in two groups according to nitrate nitrogen concentrations. Mean nitrate nitrogen concentration in surface water – group 1 ranges from 4,2 to 5,5 mg/l and in surface water – group 2 from 24 to 42 mg/l. The results are similar, but evidently higher, in groundwater samples; mean nitrate nitrogen concentration in group 1 ranges from 3,9 to 17 mg/l and in group 2 from 36 to 96 mg/l. ANOVA analysis confirmed statistical significance between stations that are classified in the same group. The previously listed parameters (land use, soil type, etc.) were used in factorial correspondence analysis (FCA) to detect importance of each stated parameter in local water quality. Since stated parameters mostly cannot be altered, there is obvious necessity for more precise and more adapted land management in such conditions.

Keywords: agricultural area, nitrate, factorial correspondence analysis, water quality

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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: Khaled Nagaty, Heba Nagaty, Gerard McKee

Abstract:

A signature is a behavioral biometric that is used for authenticating users in most financial and legal transactions. Signatures can be easily forged by skilled forgers. Therefore, it is essential to verify whether a signature is genuine or forged. The aim of any signature verification algorithm is to accommodate the differences between signatures of the same person and increase the ability to discriminate between signatures of different persons. This work presented in this paper proposes an automatic signature verification system to indicate whether a signature is genuine or not. The system comprises four phases: (1) The pre-processing phase in which image scaling, binarization, image rotation, dilation, thinning, and connecting ridge breaks are applied. (2) The feature extraction phase in which global and local features are extracted. The local features are minutiae points, curvature orientation, and curve plateau. The global features are signature area, signature aspect ratio, and Hu moments. (3) The post-processing phase, in which false minutiae are removed. (4) The classification phase in which features are enhanced before feeding it into the classifier. k-nearest neighbors and support vector machines are used. The classifier was trained on a benchmark dataset to compare the performance of the proposed offline signature verification system against the state-of-the-art. The accuracy of the proposed system is 92.3%.

Keywords: signature, ridge breaks, minutiae, orientation

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Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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Authors: Sun Jiaojiao, Fu Jiayan

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At present, in China, the research about the urban sustainability construction is still in the exploratory stage. The ecological problems of the coastal area are more sensitive and complicated. In the background of global warming with serious ecological damage, this paper deeply researches on the main characteristics of urban sustainability and measures how to build urban sustainability. Through combination with regional environmental and economic ability along the coastal area, we put forward the system planning framework, construction strategy and the evaluation index system in order to seek the way of building urban sustainability along coastal area in China.

Keywords: urban sustainability, coastal areas, construction strategy, evaluation index system

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Authors: Dhruba Khatri

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Despite the short history of community based forest management, the community forestry program of Nepal has produced substantial positive effects to organize the local people at a local level institution called Community Forest User Group and manage the local forest resources in the line of poverty reduction since its inception in 1970s. Moreover, each CFUG has collected a community fund from the sale of forest products and non-forestry sources as well and the fund has played a vital role to improve the livelihood of user households living in and around the forests. The specific study sites were selected based on the criteria of i) community forests having dominancy of Sal forests, and ii) forests having 3-5 years experience of community forest management. The price rates of forest products fixed by the CFUGs and the distribution records were collected from the respective community forests. Nonetheless, the relation between pricing strategy and community fund collection revealed that the small change in price of forest products could greatly affect in community fund collection and carry out of forest management, community development, and income generation activities in the line of poverty reduction at local level.

Keywords: benefit sharing, community forest, equitable, Nepal

Procedia PDF Downloads 374

Authors: Mekha Mathew, Varun P Gopi

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Wireless Capsule Endoscopy (WCE) has become a great device in Gastrointestinal (GI) tract diagnosis, which can examine the entire GI tract, especially the small intestine without invasiveness and sedation. Bleeding in the digestive tract is a symptom of a disease rather than a disease itself. Hence the detection of bleeding is important in diagnosing many diseases. In this paper we proposes a novel method for distinguishing bleeding regions from normal regions based on Contourlet transform and Local Binary Pattern (LBP). Experiments show that this method provides a high accuracy rate of 96.38% in CIE XYZ colour space for k-Nearest Neighbour (k-NN) classifier.

Keywords: Wireless Capsule Endoscopy, local binary pattern, k-NN classifier, contourlet transform

Procedia PDF Downloads 479

Authors: Fangwei Zhu, Wei Tian, Linzhuo Wang, Miao Yu

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Megaproject has long been a critical issue in project governance, for its low success rate and large impact on society. Although the extant literature on megaproject governance is vast, to our best knowledge, the lacking of a thorough literature review makes it hard for us to gain a holistic view on current scenario of megaproject governance. The study conducts a systematic literature review process to analyze the existing literatures on megaproject governance. The finding indicates that mega project governance needs to be handled at network level and forming a network level governance provides a holistic framework for governing megaproject towards sustainable development of the projects. Theoretical and practical implications, as well as future studies and limitations, were discussed.

Keywords: megaproject, governance, literature review, network

Procedia PDF Downloads 190

Authors: Mokrane Selma

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The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network

Procedia PDF Downloads 143

Authors: Nasrin Bakhshizadeh, Ashkan Forootan

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A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

Procedia PDF Downloads 135

Authors: Francis Wargirai

Abstract:

Since gaining independence in 1975, Papua New Guinea`s core challenge has been the consolidation of democracy against a backdrop of enormous social, political and territorial diversity. Consequently, the government has implemented several political reforms including decentralization. Constitutional planners believed that national unity, would be better achieved by sharing state power over centralization. They anticipated that this would institutionalize a democratic civic culture by providing opportunities to groups and individuals to make political decisions within their jurisdiction. This would then eventually lead to confidence and participation in the larger entity of the state. In retrospect, civil society and community based groups are largely underrated and have had minimal influence on decisions at the local level, consequently contributing to nepotism, patronism and cynicism. By applying an elitist approach to analyze how national political leaders exert their influence and power within the local government system and local communities, this paper argues that decentralization has fragmented local communities. With an absence of political party roots and deeply divided ethnic groups, national political leaders have used divide and rule tactics resulting in mistrust among citizens. Through their influence and power within local governments to dictate projects and services to certain areas, this has resulted in skepticism and divisions among civil society along different cultural cleavages. This has been a contributing factor to anomalies in democratic consolidation and democratic political culture in Papua New Guinea.

Keywords: civic culture, cultural cleavages, decentralization, democratic consolidation

Procedia PDF Downloads 167