Search results for: urban road network

Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

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Site response has a profound effect on earthquake damages. Seismic interaction of urban tunnels with surface structures could also affect seismic site response. Here, we use FLAC 2D to investigate the interaction of a single tunnel and twin tunnels-surface structures on the site response. Soil stratification and properties are selected based on Line. No 7 of the Tehran subway. The effect of surface structure is considered in two ways: Equivalent surcharge and geometrical modeling of the structure. Comparison of the results shows that consideration of the structure geometry is vital in dynamic analysis and leads to the changes in the magnitude of displacements, accelerations and response spectrum. Therefore it is necessary for the surface structures to be wholly modeled and not just considered as a surcharge in dynamic analysis. The use of twin tunnel also leads to the reduction of dynamic residual settlement.

Keywords: superstructure, tunnel, site response, surcharge, interaction

Procedia PDF Downloads 164

Authors: Sheng-Shih Wang, Wei-Ting Wang

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This paper designs an intelligent guidance system, based on wireless sensor networks, for efficient parking in parking lots. The proposed system consists of a parking space allocation subsystem, a parking space monitoring subsystem, a driving guidance subsystem, and a vehicle detection subsystem. In the system, we propose a novel and effective virtual coordinate system for sensing and displaying devices to determine the proper vacant parking space and provide the precise guidance to the driver. This study constructs a ZigBee-based wireless sensor network on Arduino platform and implements the prototype of the proposed system using Arduino-based complements. Experimental results confirm that the proposed prototype can not only work well, but also provide drivers the correct parking information.

Keywords: Arduino, parking guidance, wireless sensor network, ZigBee

Procedia PDF Downloads 576

Authors: Supachai Supmak, Yachai Limpiyakorn

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Mutation testing can be applied for the quality assessment of test cases. Prioritization of mutation test generation has been a critical element of the industry practice that would contribute to the evaluation of test cases. The industry generally delivers the product under the condition of time to the market and thus, inevitably sacrifices software testing tasks, even though many test cases are required for software verification. This paper presents an approach of applying a social network centrality measure, PageRank, to prioritize mutation test generation. The source code with the highest values of PageRank will be focused first when developing their test cases as these modules are vulnerable to defects or anomalies which may cause the consequent defects in many other associated modules. Moreover, the approach would help identify the reducible test cases in the test suite, still maintaining the same criteria as the original number of test cases.

Keywords: software testing, mutation test, network centrality measure, test case prioritization

Procedia PDF Downloads 112

Authors: Lim Pey Huan

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In the second half of the 19th century, Vietnam has long been influenced by Han culture, so there are many similarities in religion and folk beliefs. Even after the acceptance process of the Catholic Church introduced from Europe is quite similar. Therefore, in the spiritual life of Vietnamese civil society, Confucianism, Buddhism, Taoism, Christianity, Islam, and folk beliefs can be said to be the main trend, but in the twentieth century, two indigenous new religions were born: Caodai and He Hao Jiao, both of which are produced and developed in the south, each of which has millions of believers and become important Vietnamese religions. Their political participation has a major impact on the development of the Republic of Vietnam, and their fate is also in the north and south. Significant changes have taken place after reunification. Caodai was later approved by the colonial authorities and became the third largest religion in Vietnam. The teachings of Caodai teach the ideas of the major religions of the world. The classics used in the teachings also contain important theories of various religions, with particular emphasis on the comprehensiveness of the three sects of Confucianism, Buddhism, and Taoism. The obvious manifestation lies in the interpretation of the important proposition of 'opening the three religions and returning to the five branches.' The full name of Caodaism is 'Da Dao San Qi Pu Du Gao Tai Jiao'. This name coincides with the 'Longhua Club' and the 'San Qi Mo Jie' idea and the consistent central idea. The emerging road of Caodai advocates to lead the sentient beings back to their original missions; the sentient beings will be centered on people, and the nature of the talks is nothing more than the original mission and standard. There are many opinions about the introduction of Caodaism into southern Vietnam. Caodai believers believe that Caodaism is an emerging new religion in Vietnam. If we further explore the teachings and religious rituals of Caodai, it is not difficult to find that many Chinese sects have been introduced to Vietnam. Some of the colors can be discussed from the spread and influence of Congenital Road in Vietnam. This article will present the author's analysis of the actual process of tutoring in Vietnam's Caodai, and then compare it with the consistent religious experience, trying to explore the Yi-Kuan-Tao and consistent Yi-Kuan-Tao rituals, religious organization, religious teachings, religious life care, and Funeral rituals and other comparative studies.

Keywords: Vietnam, Caodaism, Yi-Kuan-Tao, religious rituals

Procedia PDF Downloads 121

Authors: Srinivasan Chandrasekaran, Thailammai Chithambaram, Shihas A. Khader

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The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified.

Keywords: condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network

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Authors: Van-Thanh Ho, Hyoungsoon Lee, Jaiyoung Ryu

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Efficient pressure distribution within soft robotic systems, specifically to the pneumatic artificial muscle (PAM) regions, is essential to minimize energy consumption. This optimization involves adjusting reservoir pressure, pipe diameter, and branching network layout to reduce flow speed and pressure drop while enhancing flow efficiency. The outcome of this optimization is a lightweight power source and reduced mechanical impedance, enabling extended wear and movement. To achieve this, a branching network system was created by combining pipe components and intricate cross-sectional area variations, employing the principle of minimal work based on a complete virtual human exosuit. The results indicate that modifying the cross-sectional area of the branching network, gradually decreasing it, reduces velocity and enhances momentum compensation, preventing flow disturbances at separation regions. These optimized designs achieve uniform velocity distribution (uniformity index > 94%) prior to entering the connection pipe, with a pressure drop of less than 5%. The design must also consider the length-to-diameter ratio for fluid dynamic performance and production cost. This approach can be utilized to create a comprehensive PAM system, integrating well-designed tube networks and complex pneumatic models.

Keywords: pneumatic artificial muscles, pipe networks, pressure drop, compressible turbulent flow, uniformity flow, murray's law

Procedia PDF Downloads 84

Authors: Claudia Trillo

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Regional innovation eco-ecosystems are composed of a variety of interconnected urban innovation eco-systems, mutually reinforcing each other and making the whole territorial system successful. Combining principles drawn from the new economic growth theory and from the socio-constructivist approach to the economic growth, with the new geography of innovation emerging from the networked nature of innovation districts, this paper explores the spatial configuration of urban innovation districts, with the aim of unveiling replicable spatial patterns and transferable portfolios of urban policies. While some authors suggest that cities should be considered ideal natural clusters, supporting cross-fertilization and innovation thanks to the physical setting they provide to the construction of collective knowledge, still a considerable distance persists between regional development strategies and urban policies. Moreover, while public and private policies supporting entrepreneurship normally consider innovation as the cornerstone of any action aimed at uplifting the competitiveness and economic success of a certain area, a growing body of literature suggests that innovation is non-neutral, hence, it should be constantly assessed against equity and social inclusion. This paper draws from a robust qualitative empirical dataset gathered through 4-years research conducted in Boston to provide readers with an evidence-based set of recommendations drawn from the lessons learned through the investigation of the chosen innovation districts in the Boston area. The evaluative framework used for assessing the overall performance of the chosen case studies stems from the Habitat III Sustainable Development Goals rationale. The concept of inclusive growth has been considered essential to assess the social innovation domain in each of the chosen cases. The key success factors for the development of the Boston innovation ecosystem can be generalized as follows: 1) a quadruple helix model embedded in the physical structure of the two cities (Boston and Cambridge), in which anchor Higher Education (HE) institutions continuously nurture the Entrepreneurial Environment. 2) an entrepreneurial approach emerging from the local governments, eliciting risk-taking and bottom-up civic participation in tackling key issues in the city. 3) a networking structure of some intermediary actors supporting entrepreneurial collaboration, cross-fertilization and co-creation, which collaborate at multiple-scales thus enabling positive spillovers from the stronger to the weaker contexts. 4) awareness of the socio-economic value of the built environment as enabler of cognitive networks allowing activation of the collective intelligence. 5) creation of civic-led spaces enabling grassroot collaboration and cooperation. Evidence shows that there is not a single magic recipe for the successful implementation of place-based and social innovation-driven strategies. On the contrary, the variety of place-grounded combinations of micro and macro initiatives, embedded in the social and spatial fine grain of places and encompassing a diversity of actors, can create the conditions enabling places to thrive and local economic activities to grow in a sustainable way.

Keywords: innovation-driven sustainable Eco-systems , place-based sustainable urban development, sustainable innovation districts, social innovation, urban policie

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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Authors: Kasun U. G. Palihakkara

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Although vaccine coverage in Sri Lanka is close to 100%, with the widely spreading vaccine rejection trend reaching South Asian regions, it is essential to catch on whether Sri Lankans are being misinformed from the common misconceptions regarding vaccines. As the rates of target diseases decrease, parents become less accepting of even minor common adverse events. It is essential to preserve the integrity of immunization programs and protect public health by finding out the prevalence of anti-immunization trends. The primary objective of this study was to assess the immunization practices and prevalence of trends related to anti-immunization among urban community in Sri Lanka. A descriptive cross-sectional quantitative study on 323 participants using convenient sampling with 213 self-administered questionnaires. Additionally, 110 online questionnaires were distributed. 31% of the study population does not maintain immunization records for their children. While majority seek information regarding immunization from reliable sources such as the family physician or specialist pediatricians, 30% also refer to unreliable sources such as online communities for their opinion. 31% of study population had not vaccinated for Japanese encephalitis. 73% of the study population had encountered with side effects of vaccination such as fever & 47% believed that such side effects are rare. 52% of the population had hostile attitude regarding the administration of several doses multiple vaccines within a child’s first year. Diseases like polio had been successfully eradicated from Sri Lanka with the help of vigorous vaccination programs. However, majority of the study population believe that there’s no need to keep vaccinating the children for those eradicated diseases and exposing the child for adverse effects of such vaccines. Majority of the population were aware of the existing misconceptions regarding immunization. The most popular misconceptions about vaccines popular among the study population were the MMR (Measles, Mumps, and Rubella) vaccine being a possible cause leading to autism and bowel disease and children getting infected with the disease even after they get vaccinated, may be due to the inactivated vaccine. Disturbingly 22% of the study population believed that vaccines are useless in preventing diseases nowadays. These data obtained from the urban study population reveals that even though statistically Sri Lankan immunization coverage is 100%, there is a possibility of anti-vaccination trend arising in Sri Lanka due to the prevalence of various misconceptions and rumors related to it. Therefore these data recommend the need for thorough awareness among the mothers.

Keywords: anti-vaccination, immunization, infectious diseases, pediatric health

Procedia PDF Downloads 139

Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

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Authors: Mohammad Salah Abdullatif, Salam Hajjar, Paul Khanna

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The development of instrument grade mmWave transceivers comes with many challenges. A general rule of thumb is that the performance of the instrument must be higher than the performance of the unit under test in terms of accuracy and stability. The calibration and characterizing of mmWave transceivers are important pillars for testing commercial products. Using a Vector Network Analyzer (VNA) with a mixer option has proven a high performance as an approach to calibrate mmWave transceivers. However, this approach comes with a high cost. In this work, a reduced-cost method to calibrate mmWave transceivers is proposed. A comparison between the proposed method and the VNA technology is provided. A demonstration of significant challenges is discussed, and an approach to meet the requirements is proposed.

Keywords: mmWave transceiver, scalar characterization, coupler connection, magic tee connection, calibration, VNA, vector network analyzer

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Authors: Yangyang Zhou

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Rapid urbanization has caused the urban heat island effect, which will threaten the physical and mental health of urban dwellers, and blue-green spaces can mitigate the thermal environment effectively. In this study, we calculated the average LST from 2013 to 2022, Northeastmonsoon and Southwestmonsoon of Singapore, and compared the cooling effect differences of the four blue-green spaces. Then, spatial correlation and spatial autoregression model were conducted between cooling distance intensity (CDI) and 11 independent variables. The results reveal that (1) the highest mean land surface temperature (LST) in all years, Northeast monsoon and Southwest monsoon can reach 42.8 ℃, 41.6 ℃, and 42.9 ℃, respectively. (2) the temperature-changing tendency in the three time periods is similar to each other, while the overall LST changing trends of the Southwest monsoon are lower than all year and Northeast monsoon. (3) the cooling distance of the sea can reach 1200 m, and CEI is highly positively correlated with NDBI and BuildD and highly negatively correlated with SVF, NDVI and TreeH. LISA maps showed that the zones that passed the significance test between CDI, NDBI and BuildD were nearly the same locations; the same phenomenon also happened between CDI and SVF, NDVI and TreeH. (4) SLM had better regression results than SEM in all the regions; only 3 independent variables passed the significance test in region 1, and most independent variables can pass the significance test in other regions. Variables DIST and NDBI were significantly affecting the CDI in all the regions. In the whole region, all the variables passed the significance test, and NDBI (1.61), SVF (0.95) and NDVI (0.5) had the strongest influence on CDI.

Keywords: cooling effect, land surface temperature, thermal environment mitigation, spatial autoregression model

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Authors: Abdullah Almowanes

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The speed of adoption of new information and communication technologies is often seen as an indicator of the growth of knowledge- and technological innovation-based regional economies. Indeed, technological progress and scientific inquiry in any society have undergone a particularly profound transformation with the introduction of computer networks. In the spring of 1981, the Bitnet network was launched to link thousands of nodes all over the world. In 1985 and as one of the first adopters of Bitnet, Saudi Arabia launched a Bitnet-based network named Gulfnet that linked computer centers, universities, and libraries of Saudi Arabia and other Gulf countries through high speed communication lines. In this paper, the origins and the deployment of Gulfnet are discussed as well as social, economical, political, and cultural ramifications of the new information reality created by the network. Despite its significance, the social and cultural aspects of Gulfnet have not been investigated in history of science and technology literature to a satisfactory degree before. The presented research is based on an extensive archival research aimed at seeking out and analyzing of primary evidence from archival sources and records. During its decade and a half-long existence, Gulfnet demonstrated that the scope and functionality of public computer networks in Saudi Arabia have to be fine-tuned for compliance with Islamic culture and political system of the country. It also helped lay the groundwork for the subsequent introduction of the Internet. Since 1980s, in just few decades, the proliferation of computer networks has transformed communications world-wide.

Keywords: Bitnet, computer networks, computing and culture, Gulfnet, Saudi Arabia

Procedia PDF Downloads 245

Authors: Bin Su

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The draft Auckland Unitary Plan outlines the future land used for new housing and businesses with Auckland population growth over the next thirty years. According to Auckland Unitary Plan, over the next 30 years, the population of Auckland is projected to increase by one million, and up to 70% of total new dwellings occur within the existing urban area. Intensification will not only increase the number of median or higher density houses such as terrace house, apartment building, etc. within the existing urban area but also change mean housing design data that can impact building thermal performance under the local climate. Based on mean energy consumption and building design data, and their relationships of a number of Auckland sample houses, this study is to estimate the future mean housing energy consumption associated with the change of mean housing design data and evaluate housing energy efficiency with the Auckland Unitary Plan.

Keywords: Auckland Unitary Plan, building thermal design, housing design, housing energy efficiency

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Authors: Wipada Chaiwchan

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This research aims to study behaviors in using social networks of Corporate personnel of Suan Sunandha Rajabhat University. The sample used in the study were two groups: 1) Academic Officer 70 persons and 2) Operation Officer 143 persons were used in this study. The tools in this research consisted of questionnaire which the data were analyzed by using percentage, average (X) and Standard deviation (S.D.) and Independent Sample T-Test to test the difference between the mean values obtained from two independent samples, and One-way anova to analysis of variance, and Multiple comparisons to test that the average pair of different methods by Fisher’s Least Significant Different (LSD). The study result found that the most of corporate personnel have purpose in using social network to information awareness aspect was knowledge and online conference with social media. By using the average more than 3 hours per day in everyday. Using time in working in one day and there are computers connected to the Internet at home, by using the communication in the operational processes. Behaviors using social networks in relation to gender, age, job title, department, and type of personnel. Hypothesis testing, and analysis of variance for the effects of this analysis is divided into three aspects: The use of online social networks, the attitude of the users and the security analysis has found that Corporate Personnel of Suan Sunandha Rajabhat University. Overall and specifically at the high level, and considering each item found all at a high level. By sorting of the social network (X=3.22), The attitude of the users (X= 3.06) and the security (X= 3.11). The overall behaviors using of each side (X=3.11).

Keywords: social network, behaviors, social media, computer information systems

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Authors: Anne Allmrodt

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Regions of South-East Europe are characterised by high out-migration for decades. The reasons for leaving range from the hope of a better work situation to a better health care system and beyond. In Serbia, this high out-migration hits the rural areas in particular so that the population number is in the red repeatedly. It might not be hard to guess that this negative population growth has the potential to create different challenges for those who stay in rural areas. So how are they coping with the – statistically proven – high out-migration? Having this in mind, the study is investigating the people‘s individual awareness of the social phenomenon high out-migration and their daily life strategies in rural areas. Furthermore, the study seeks to find out the people’s resilient skills in that context. Is the condition of high out-migration conducive for resilience? The methodology combines a quantitative and a qualitative approach (mixed methods). For the quantitative part, a standardised questionnaire has been developed, including a multiple choice section and a choice experiment. The questionnaire was handed out to people living in rural areas of Serbia only (n = 100). The sheet included questions about people’s awareness of high out-migration, their own daily life strategies or challenges and their social network situation (data about the social network was necessary here since it is supposed to be an influencing variable for resilience). Furthermore, test persons were asked to make different choices of coping with high out-migration in a self-designed choice experiment. Additionally, the study included qualitative interviews asking citizens from rural areas of Serbia. The topics asked during the interview focused on their awareness of high out-migration, their daily life strategies, and challenges as well as their social network situation. Results have shown the following major findings. The awareness of high out-migration is not the same with all test persons. Some declare it as something positive for their own life, others as negative or not effecting at all. The way of coping generally depended – maybe not surprising – on the people’s social network. However – and this might be the most important finding - not everybody with a certain number of contacts had better coping strategies and was, therefore, more resilient. Here the results show that especially people with high affiliation and proximity inside their network were able to cope better and shew higher resilience skills. The study took one step forward in terms of knowledge about societal resilience as well as coping strategies of societies in rural areas. It has shown part of the other side of nowadays migration‘s coin and gives a hint for a more sustainable rural development and community empowerment.

Keywords: coping, out-migration, resilience, rural development, social networks, south-east Europe

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Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader

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DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.

Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform

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Authors: Maria Florencia Ferrer, Saulo Fabiano Amancio-Vieira

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The use of the blockchain in the public sector is present today and no longer the future of disruptive institutional and technological models. There are still some cultural barriers and resistance to the proper use of its potential. This research aims to present the strengths and weaknesses of using a public-permitted and distributed network in the context of the public sector. Therefore, bibliographical/documentary research was conducted to raise the main aspects of the studied platform, focused on the use of the main demands of the public sector. The platform analyzed was LACChain, which is a global alliance composed of different actors in the blockchain environment, led by the Innovation Laboratory of the Inter-American Development Bank Group (IDB Lab) for the development of the blockchain ecosystem in Latin America and the Caribbean. LACChain provides blockchain infrastructure, which is a distributed ratio technology (DLT). The platform focuses on two main pillars: community and infrastructure. It is organized as a consortium for the management and administration of an infrastructure classified as public, following the ISO typologies (ISO / TC 307). It is, therefore, a network open to any participant who agrees with the established rules, which are limited to being identified and complying with the regulations. As benefits can be listed: public network (open to all), decentralized, low transaction cost, greater publicity of transactions, reduction of corruption in contracts / public acts, in addition to improving transparency for the population in general. It is also noteworthy that the platform is not based on cryptocurrency and is not anonymous; that is, it is possible to be regulated. It is concluded that the use of record platforms, such as LACChain, can contribute to greater security on the part of the public agent in the migration process of their informational applications.

Keywords: blockchain, LACChain, public sector, technological disruptions

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Authors: Hritik Bhattarai

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Land use and land cover play a crucial role in preserving and managing Earth's natural resources. Various factors, such as economic, demographic, social, cultural, technological, and environmental processes, contribute to changes in land use and land cover (LULC). Rupandehi District is significantly influenced by a combination of driving forces, including its geographical location, rapid population growth, economic opportunities, globalization, tourism activities, and political events. Urbanization and urban growth in the region have been occurring in an unplanned manner, with internal migration and natural population growth being the primary contributors. Internal migration, particularly from neighboring districts in the higher and lower Himalayan regions, has been high, leading to increased population growth and density. This study utilizes geospatial technology, specifically geographic information system (GIS), to analyze and illustrate the land cover and land use changes in the Rupandehi district for the years 2009 and 2019, using freely available Landsat images. The identified land cover categories include built-up area, cropland, Das-Gaja, forest, grassland, other woodland, riverbed, and water. The statistical analysis of the data over the 10-year period (2009-2019) reveals significant percentage changes in LULC. Notably, Das-Gaja shows a minimal change of 99.9%, while water and forest exhibit increases of 34.5% and 98.6%, respectively. Riverbed and built-up areas experience changes of 95.3% and 39.6%, respectively. Cropland and grassland, however, show concerning decreases of 102.6% and 140.0%, respectively. Other woodland also indicates a change of 50.6%. The most noteworthy trends are the substantial increase in water areas and built-up areas, leading to the degradation of agricultural and open spaces. This emphasizes the urgent need for effective urban planning activities to ensure the development of a sustainable city. While Das-Gaja seems unaffected, the decreasing trends in cropland and grassland, accompanied by the increasing built-up areas, are unsatisfactory. It is imperative for relevant authorities to be aware of these trends and implement proactive measures for sustainable urban development.

Keywords: land use and land cover, geospatial, urbanization, geographic information system, sustainable urban development

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Authors: Jean Felix Tuyisingize

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Speeding or inappropriate speed is a major problem worldwide, contributing to 10-15% of road crashes and 30% of fatal injury crashes. The consequences of speeding put the driver's life at risk and the lives of other road users like motorists, cyclists, and pedestrians. To control vehicle speeds, governments, and traffic authorities enforced speed regulations through speed cameras and speed section control, which monitor all vehicle speeds and detect plate numbers to levy penalties. However, speed limit violations are prevalent, even on motorways with speed cameras. The problem with speed cameras is that they alter driver behaviors, and their effect declines with increasing distance from the speed camera location. Drivers decelerate short distances before the camera and vigorously accelerate above the speed limit just after passing by the camera. The sudden decelerating near cameras causes the drivers to try to make up for lost time after passing it, and they do this by speeding up, resulting in a phenomenon known as the "Kangaroo jump" or "V-profile" around camera/ASSC areas. This study investigated the impact of speed enforcement devices, specifically Average Speed Section Control (ASSCs) and fixed cameras, on acceleration and deceleration events within their vicinity. The research employed advanced statistical and Geographic Information System (GIS) analysis on naturalistic driving data, to uncover speeding patterns near the speed enforcement systems. The study revealed a notable concentration of events within a 600-meter radius of enforcement devices, suggesting their influence on driver behaviors within a specific range. However, most of these events are of low severity, suggesting that drivers may not significantly alter their speed upon encountering these devices. This behavior could be attributed to several reasons, such as consistently maintaining safe speeds or using real-time in-vehicle intervention systems. The complexity of driver behavior is also highlighted, indicating the potential influence of factors like traffic density, road conditions, weather, time of day, and driver characteristics. Further, the study highlighted that high-severity events often occurred outside speed enforcement zones, particularly around intersections, indicating these as potential hotspots for drastic speed changes. These findings call for a broader perspective on traffic safety interventions beyond reliance on speed enforcement devices. However, the study acknowledges certain limitations, such as its reliance on a specific geographical focus, which may impact the broad applicability of the findings. Additionally, the severity of speed modification events was categorized into low, medium, and high, which could oversimplify the continuum of speed changes and potentially mask trends within each category. This research contributes valuable insights to traffic safety and driver behavior literature, illuminating the complexity of driver behavior and the potential influence of factors beyond the presence of speed enforcement devices. Future research directions may employ various categories of event severity. They may also explore the role of in-vehicle technologies, driver characteristics, and a broader set of environmental variables in driving behavior and traffic safety.

Keywords: acceleration, deceleration, speeding, inappropriate speed, speed enforcement cameras

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Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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Authors: Nayara Torres B. Acioli, José Fernando T. Jucá

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The uncontrolled emission of gases in urban residues' embankment located near urban areas is a social and environmental problem, common in Brazilian cities. Several environmental impacts in the local and global scope may be generated by atmospheric air contamination by the biogas resulted from the decomposition of solid urban materials. In Brazil, the cities of small size figure mostly with 90% of all cities, with the population smaller than 50,000 inhabitants, according to the 2011 IBGE' census, most of the landfill covering layer is composed of clayey, pure soil. The embankments undertaken with pure soil may reach up to 60% of retention of methane, for the other 40% it may be dispersed into the atmosphere. In face of this figures the oxidative covering layer is granted some space of study, envisaging to reduce this perceptual available in the atmosphere, releasing, in spite of methane, carbonic gas which is almost 20 times as less polluting than Methane. This paper exposes the results of studies on the characteristics of the soil used for the oxidative coverage layer of the experimental embankment of Solid Urban Residues (SUR), built in Muribeca-PE, Brazil, supported of the Group of Solid Residues (GSR), located at Federal University of Pernambuco, through laboratory vacuum experiments (determining the characteristics curve), granularity, and permeability, that in soil with saturation over 85% offers dramatic drops in the test of permeability to the air, by little increments of water, based in the existing Brazilian norm for this procedure. The suction was studied, as in the other tests, from the division of prospection of an oxidative coverage layer of 60cm, in the upper half (0.1 m to 0.3 m) and lower half (0.4 m to 0.6 m). Therefore, the consequences to be presented from the lixiviation of the fine materials after 5 years of finalization of the embankment, what made its permeability increase. Concerning its humidity, it is most retained in the upper part, that comprises the compound, with a difference in the order of 8 percent the superior half to inferior half, retaining the least suction from the surface. These results reveal the efficiency of the oxidative coverage layer in retaining the rain water, it has a lower cost when compared to the other types of layer, offering larger availability of this layer as an alternative for a solution for the appropriate disposal of residues.

Keywords: oxidative coverage layer, permeability, suction, saturation

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Authors: Guenther Schuh, Sebastian Woelk

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Companies face increasing challenges in research due to higher costs and risks. The intensifying technology complexity and interdisciplinarity require unique know-how. Therefore, companies need to decide whether research shall be conducted internally or externally with partners. On the other hand, research institutes meet increasing efforts to achieve good financing and to maintain high research reputation. Therefore, relevant research topics need to be identified and specialization of competency is necessary. However, additional competences for solving interdisciplinary research projects are also often required. Secured financing can be achieved by bonding industry partners as well as public fundings. The realization of faster and better research drives companies and research institutes to cooperate in organized research networks, which are managed by an administrative organization. For an effective and efficient cooperation, necessary processes, roles, tools and a set of rules need to be determined. The goal of this paper is to show the state-of-art research and to propose a governance framework for organized research networks.

Keywords: interorganizational cooperation, design of network governance, research network

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Authors: Shishir Kumar, Chhaya Gangwal, Seema Raj

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Public health informatics (PHI) which has seen successful implementation in the developed world, become the buzzword in the developing countries in providing improved healthcare with enhanced access. In rural areas especially, where a huge gap exists between demand and supply of healthcare facilities, PHI is being seen as a major solution. There are factors such as growing network infrastructure and the technological adoption by the health fraternity which provide support to these claims. Public health informatics has opportunities in healthcare by providing opportunities to diagnose patients, provide intra-operative assistance and consultation from a remote site. It also has certain barriers in the awareness, adaptation, network infrastructure, funding and policy related areas. There are certain medico-legal aspects involving all the stakeholders which need to be standardized to enable a working system. This paper aims to analyze the potential and challenges of public health informatics services in rural communities.

Keywords: PHI, e-health, public health, health informatics

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Authors: S. S. Kenny Lee, C. C. Kong, S. K. Ting

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Teaching engineering lab provides opportunity for students to practice theories learned through physical experiment in the laboratory. However, building laboratories to accommodate increased number of students are expensive, making it impossible for an educational institution to afford the high expenses. In this paper, we develop a low cost and remote platform to aid teaching undergraduate students. The platform is constructed where the real experiment setting up in laboratory can be reconfigure and accessed remotely, the aim is to increase student’s desire to learn at which they can interact with the physical experiment using network enabled devices at anywhere in the campus. The platform is constructed with Raspberry Pi as a main control board that provides communication between computer interfaces to the actual experiment preset in the laboratory. The interface allows real-time remote viewing and triggering the physical experiment in the laboratory and also provides instructions and learning guide about the experimental.

Keywords: engineering lab, low cost, network, remote platform, reconfigure, real-time

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Authors: Massimiliano Condotta, Paolo Ruggeri, Chiara Scanagatta, Giovanni Borga

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Architects and urban planners, when designing and renewing cities, have to face a complex set of problems, including the issues of noise and air pollution which are considered as hot topics (i.e., the Clean Air Act of London and the Soundscape definition). It is usually taken for granted that these problems go by together because the noise pollution present in cities is often linked to traffic and industries, and these produce air pollutants as well. Traffic congestion can create both noise pollution and air pollution, because NO₂ is mostly created from the oxidation of NO, and these two are notoriously produced by processes of combustion at high temperatures (i.e., car engines or thermal power stations). We can see the same process for industrial plants as well. What have to be investigated – and is the topic of this paper – is whether or not there really is a correlation between noise pollution and air pollution (taking into account NO₂) in urban areas. To evaluate if there is a correlation, some low-cost methodologies will be used. For noise measurements, the OpeNoise App will be installed on an Android phone. The smartphone will be positioned inside a waterproof box, to stay outdoor, with an external battery to allow it to collect data continuously. The box will have a small hole to install an external microphone, connected to the smartphone, which will be calibrated to collect the most accurate data. For air, pollution measurements will be used the AirMonitor device, an Arduino board to which the sensors, and all the other components, are plugged. After assembling the sensors, they will be coupled (one noise and one air sensor) and placed in different critical locations in the area of Mestre (Venice) to map the existing situation. The sensors will collect data for a fixed period of time to have an input for both week and weekend days, in this way it will be possible to see the changes of the situation during the week. The novelty is that data will be compared to check if there is a correlation between the two pollutants using graphs that should show the percentage of pollution instead of the values obtained with the sensors. To do so, the data will be converted to fit on a scale that goes up to 100% and will be shown thru a mapping of the measurement using GIS methods. Another relevant aspect is that this comparison can help to choose which are the right mitigation solutions to be applied in the area of the analysis because it will make it possible to solve both the noise and the air pollution problem making only one intervention. The mitigation solutions must consider not only the health aspect but also how to create a more livable space for citizens. The paper will describe in detail the methodology and the technical solution adopted for the realization of the sensors, the data collection, noise and pollution mapping and analysis.

Keywords: air quality, data analysis, data collection, NO₂, noise mapping, noise pollution, particulate matter

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Julio Jesus Salazar, Manuel Andres Jesus De Lama

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There are very few models that serve to analyze the use of water in the socio-economic process. On the supply side, the joint use of groundwater has been considered in addition to the simple limits on the availability of surface water. In addition, we have worked on waterlogging and the effects on water quality (mainly salinity). In this paper, a 'complex' water economy is examined; one in which demands grow differentially not only within but also between sectors, and one in which there are limited opportunities to increase consumptive use. In particular, high-value growth, the growth of the production of irrigated crops of high value within the basins of the case study, together with the rapidly growing urban areas, provides a rich context to examine the general problem of water management at the basin level. At the same time, the long-term aridity of nature has made the eco-environment in the basins located on the coast of Peru very vulnerable, and the exploitation and immediate use of water resources have further deteriorated the situation. The presented methodology is the optimization with embedded simulation. The wide basin simulation of flow and water balances and crop growth are embedded with the optimization of water allocation, reservoir operation, and irrigation scheduling. The modeling framework is developed from a network of river basins that includes multiple nodes of origin (reservoirs, aquifers, water courses, etc.) and multiple demand sites along the river, including places of consumptive use for agricultural, municipal and industrial, and uses of running water on the coast of Peru. The economic benefits associated with water use are evaluated for different demand management instruments, including water rights, based on the production and benefit functions of water use in the urban agricultural and industrial sectors. This work represents a new effort to analyze the use of water at the regional level and to evaluate the modernization of the integrated management of water resources and socio-economic territorial development in Peru. It will also allow the establishment of policies to improve the process of implementation of the integrated management and development of water resources. The input-output analysis is essential to present a theory about the production process, which is based on a particular type of production function. Also, this work presents the Computable General Equilibrium (CGE) version of the economic model for water resource policy analysis, which was specifically designed for analyzing large-scale water management. As to the platform for CGE simulation, GEMPACK, a flexible system for solving CGE models, is used for formulating and solving CGE model through the percentage-change approach. GEMPACK automates the process of translating the model specification into a model solution program.

Keywords: water economy, simulation, modeling, integration

Procedia PDF Downloads 155

Authors: Tamanna Rimi

Abstract:

A large body of literature has discussed the determinants of migration decision. However, the potential role of individual risk attitudes on migration decision has so far been overlooked. The research on migration literature has studied how the expected income differential influences migration flows for a risk neutral individual. However, migration takes place when there is no expected income differential or even the variability of income appears as lower than in the current location. This migration puzzle motivates a recent trend in the literature that analyzes how attitudes towards risk influence the decision to migrate. However, the significance of risk attitudes on migration decision has been addressed mostly in a theoretical perspective in the mainstream migration literature. The efficient outcome of labor market and overall economy are largely influenced by migration in many countries. Therefore, attitudes towards risk as a determinant of migration should get more attention in empirical studies. To author’s best knowledge, this is the first study that has examined the relationship between relative risk aversion and migration decision in US market. This paper considers movement across United States as a means of migration. In addition, this paper also explores the network effect due to the increasing size of one’s own ethnic group to a source location on the migration decision and how attitudes towards risk vary with network effect. Two ethnic groups (i.e. Asian and Hispanic) have been considered in this regard. For the empirical estimation, this paper uses two sources of data: 1) U.S. census data for social, economic, and health research, 2010 (IPUMPS) and 2) University of Michigan Health and Retirement Study, 2010 (HRS). In order to measure relative risk aversion, this study uses the ‘Two Sample Two-Stage Instrumental Variable (TS2SIV)’ technique. This is a similar method of Angrist (1990) and Angrist and Kruegers’ (1992) ‘Two Sample Instrumental Variable (TSIV)’ technique. Using a probit model, the empirical investigation yields the following results: (i) risk attitude has a significantly large impact on migration decision where more risk averse people are less likely to migrate; (ii) the impact of risk attitude on migration varies by other demographic characteristics such as age and sex; (iii) people with higher concentration of same ethnic households living in a particular place are expected to migrate less from their current place; (iv) the risk attitudes on migration vary with network effect. The overall findings of this paper relating risk attitude, migration decision and network effect can be a significant contribution addressing the gap between migration theory and empirical study in migration literature.

Keywords: migration, network effect, risk attitude, U.S. market

Procedia PDF Downloads 162