Search results for: public transportation network

Authors: Azaz Zaman, Mirazur Rahman

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Capital market is a crucial financial market place where companies and the government can raise long-term funds and, at the same time, investors get the opportunity to invest in the listed companies. Capital markets play a vital role not only in shifting the funds from surplus entity to deficit for investment, but also in the overall economic development of any developing country like Bangladesh. Being the first and biggest capital market of Bangladesh, Dhaka Stock Exchange (DSE) is the prime bourse of the country. The differences in the investment preference— among three broad categories of investors in DSE including individual investors, institutional investors, and government— are easily observed. Authors of this article have used five categories of investors such as sponsors or directors of the company, institutional investors, foreign investors, government, and the general public in order to present a comparative analysis of their investment patterns. Obtaining data on the percentage of investment by these five types of investors in different sectors from the DSE website, this study aims to analyze the sector-wise investment preference of these investors using August 2018 data. The study has found that the sponsors or directors of the company have the highest percentage of investment in the textile industry which is close to 16%. The Bangladesh government, as an investor, has the highest percentage of investment in the fuel & power sector, approximately 32%. It has also found that the mutual funds' sector is mostly financed by institutional investors, nearly 28%. Foreign investors have their most investments in the banking sector, which is close to 22%. It has also revealed that the textile sector is mostly financed by the general public, close to 17%. Nevertheless, general public, surprisingly, has the lowest percentage of investment in the telecommunication sector, which is 0.10%.

Keywords: stock market investment, Dhaka stock exchange, capital market, Bangladesh

Procedia PDF Downloads 119

Authors: Milena M. Melo, Jane M. Santos, Severine Frere, Valderio A. Reisen, Neyval C. Reis Jr., Mariade Fátima S. Leite

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Although there had been a many studies that shows the impact of air pollution on physical health, comparatively less was known of human behavioral responses and annoyance impacts. Annoyance caused by air pollution is a public health problem because it can be an ambient stressor causing stress and disease and can affect quality of life. The objective of this work is to evaluate the annoyance caused by air pollution in two different industrialized urban areas, Dunkirk (France) and Vitoria (Brazil). The populations of these cities often report feeling annoyed by dust. Surveys were conducted, and the collected data were analyzed using statistical analyses. The results show that sociodemographic variables, importance of air quality, perceived industrial risk, perceived air pollution and occurrence of health problems play important roles in the perceived annoyance. These results show the existence of a common problem in geographically distant areas and allow stakeholders to develop prevention strategies.

Keywords: air pollution, annoyance, industrial risks, public health, perception of pollution, settled dust

Procedia PDF Downloads 692

Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

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Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

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Authors: Jeonghwan Jeon

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As the science and technology (S&T) has been rapidly advanced, the national government attempts to reflect changes in the S&T for promoting public R&D activities and economic development. Amongst others, due to the rapid advances and changes of S&T, it becomes important to analyze the trends of S&T policies for formulating the new policy and investigating promising S&T fields. Thus, this paper aims to trace the national S&T policies during this decade for analyzing the change of major S&T fields in the case of South Korea. As one of the organization for S&T policy in South Korea, the National Science and Technology Council (NSTC) has been established to coordinate inter-ministerial policies and programs and to determine all of the national and public S&T policy of South Korea. In this regard, the items on national S&T policy determined by the NSTC are useful for understanding the needs for major S&T fields and adapting to the rapid change of S&T. To this end, we first gathered the data on 512 items on the S&T agenda from 1999 to 2013. Based on these items, the trend of S&T policies is monitored and the major S&T fields are derived. Differences of policy purposes between S&T fields are identified to provide guideline for policy making such as budget allocation or investment promotion as well.

Keywords: national science and technology, policy, trends, S&T field

Procedia PDF Downloads 551

Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Kidist Mesfin Nguse

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Ethiopia is the second most densely populated nation in Africa, and about 121 million people as the 2022 Ethiopia population live report recorded. In recent years, the Ethiopian government (GOE) has been gradually growing its road network. With 138,127 kilometers (85,825 miles) of all-weather roads as of the end of 2018–19, Ethiopia possessed just 39% of the nation's necessary road network and lacked a well-organized system. The Ethiopian urban population report recorded that about 21% of the population lives in urban areas, and the high population, coupled with growth in various infrastructures, has led to the migration of the workforce from rural areas to cities across the country. In main roads, the heterogeneous traffic flow with various operational features makes it more unfavorable, causing frequent congestion in the stretch of road. The Level of Service (LOS), a qualitative measure of traffic, is categorized based on the operating conditions in the traffic stream. Determining the capacity and LOS for this city is very crucial as this affects the planning and design of traffic systems and their operation, and the allocation of route selection for infrastructure building projects to provide for a considerably good level of service.

Keywords: capacity, level of service, traffic volume, free flow speed

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Authors: Claire Biasco, Thaier Hayajneh

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A smart city is the integration of digital technologies in urban environments to enhance the quality of life. Smart cities capture real-time information from devices, sensors, and network data to analyze and improve city functions such as traffic analysis, public safety, and environmental impacts. Current smart cities face controversy due to their reliance on real-time data tracking and surveillance. Internet of Things (IoT) devices and blockchain technology are converging to reshape smart city infrastructure away from its centralized model. Connecting IoT data to blockchain applications would create a peer-to-peer, decentralized model. Furthermore, blockchain technology powers the ability for IoT device data to shift from the ownership and control of centralized entities to individuals or communities with Decentralized Autonomous Organizations (DAOs). In the context of smart cities, DAOs can govern cyber-physical systems to have a greater influence over how urban services are being provided. This paper will explore how the core components of a smart city now apply to DAOs. We will also analyze different definitions of DAOs to determine their most important aspects in relation to smart cities. Both categorizations will provide a solid foundation to conduct a cybersecurity assessment of DAOs in smart cities. It will identify the benefits and risks of adopting DAOs as they currently operate. The paper will then provide several mitigation methods to combat cybersecurity risks of DAO integrations. Finally, we will give several insights into what challenges will be faced by DAO and blockchain spaces in the coming years before achieving a higher level of maturity.

Keywords: blockchain, IoT, smart city, DAO

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Authors: Loha Hashimy, Isabella Castillo

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In today's rapidly evolving technological landscape, the importance of precise navigation and mapping systems cannot be understated. As various sectors undergo transformative changes, the market potential for Advanced Mapping and Management Systems (AMMS) emerges as a critical focus area. The Galileo/GNSS-Based Autonomous Mobile Mapping System (GAMMS) project, specifically targeted toward high-definition mapping (HDM), endeavours to provide insights into this market within the broader context of the geomatics and navigation fields. With the growing integration of Autonomous Vehicles (AVs) into our transportation systems, the relevance and demand for sophisticated mapping solutions like HDM have become increasingly pertinent. The research employed a meticulous, lean, stepwise, and interconnected methodology to ensure a comprehensive assessment. Beginning with the identification of pivotal project results, the study progressed into a systematic market screening. This was complemented by an exhaustive desk research phase that delved into existing literature, data, and trends. To ensure the holistic validity of the findings, extensive consultations were conducted. Academia and industry experts provided invaluable insights through interviews, questionnaires, and surveys. This multi-faceted approach facilitated a layered analysis, juxtaposing secondary data with primary inputs, ensuring that the conclusions were both accurate and actionable. Our investigation unearthed a plethora of drivers steering the HD maps landscape. These ranged from technological leaps, nuanced market demands, and influential economic factors to overarching socio-political shifts. The meteoric rise of Autonomous Vehicles (AVs) and the shift towards app-based transportation solutions, such as Uber, stood out as significant market pull factors. A nuanced PESTEL analysis further enriched our understanding, shedding light on political, economic, social, technological, environmental, and legal facets influencing the HD maps market trajectory. Simultaneously, potential roadblocks were identified. Notable among these were barriers related to high initial costs, concerns around data quality, and the challenges posed by a fragmented and evolving regulatory landscape. The GAMMS project serves as a beacon, illuminating the vast opportunities that lie ahead for the HD mapping sector. It underscores the indispensable role of HDM in enhancing navigation, ensuring safety, and providing pinpoint, accurate location services. As our world becomes more interconnected and reliant on technology, HD maps emerge as a linchpin, bridging gaps and enabling seamless experiences. The research findings accentuate the imperative for stakeholders across industries to recognize and harness the potential of HD mapping, especially as we stand on the cusp of a transportation revolution heralded by Autonomous Vehicles and advanced geomatic solutions.

Keywords: high-definition mapping (HDM), autonomous vehicles, PESTEL analysis, market drivers

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Authors: Navneet Kaur, Amarpreet Singh

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In Vehicular Adhoc Networks, Data Dissemination is a challenging task. There are number of techniques, types and protocols available for disseminating the data but in order to preserve limited bandwidth and to disseminate maximum data over networks makes it more challenging. There are broadcasting, multicasting and geocasting based protocols. Multicasting based protocols are found to be best for conserving the bandwidth. One such protocol named BEAM exists that improves the performance of Vehicular Adhoc Networks by reducing the number of in-network message transactions and thereby efficiently utilizing the bandwidth during an emergency situation. But this protocol may result in multicar chain collision as there was no V2V communication. So, this paper proposes a new protocol named Enhanced Bandwidth Efficient Cluster Based Multicasting Protocol (EBECM) that will overcome the limitations of existing BEAM protocol. And Simulation results will show the improved performance of EBECM in terms of Routing overhead, throughput and PDR when compared with BEAM protocol.

Keywords: BEAM, data dissemination, emergency situation, vehicular adhoc network

Procedia PDF Downloads 348

Authors: Xiaohan Gu

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China is perceived as one of the most politically corrupt countries in the world. The 2021 Transparency International Corruption Perceptions Index China (RPC) ranks the country in 66th place out of 180 countries in the Index, where the 180 countries are perceived to have the most corrupt public sector. This paper proposes a theory on the impact of corruption on the consumption of luxury goods. We test the theory and evaluate the effectiveness of China’s anti-corruption campaign in 2012 by conducting a difference-in-differences analysis of product-city-level alcohol and cigarette consumption from 2013 to 2022. We find that the campaign increased sales of middle-end baijiu and cigarettes but decreased sales of luxury baijiu and cigarettes, contrasting with the trend for low-end products. This substitution pattern may be attributable to decreased public spending on luxury goods. This substitution pattern is moderated by officials’ wages and anti-corruption efforts, which supports the theoretical predictions.

Keywords: substitution effect, baijiu, corruption, anti-corruption, chinese political connection

Procedia PDF Downloads 83

Authors: Mohan Kotamrazu

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Cyclone Hudhud which battered the city of Visakhapatnam on 12^th October, 2014, damaged many buildings, public amenities and infrastructure facilities along the Visakha- Bheemili coastal corridor. More than half the green cover of the city was wiped out. Majority of the trees along the coastal corridor suffered from complete or partial damage. In order to understand the different ways that trees incurred damage during the cyclone, a damage assessment study was carried out by the author. The areas covered by this study included two university campuses, several parks and residential colonies which bore the brunt of the cyclone. Post disaster attempts have been made to restore many of the trees that have suffered from partial or complete damage from the effects of extreme winds. This paper examines the various ways that trees incurred damage from the cyclone Hudhud and presents some examples of the restoration efforts carried out by educational institutions, public parks and religious institutions of the city of Visakhapatnam in the aftermath of the devastating cyclone.

Keywords: defoliaton, salt spray damage, uprooting and wind throw, restoration

Procedia PDF Downloads 530

Authors: Sudha Subramani, Hua Wang

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Domestic Violence (DV) against women is now recognized to be a serious and widespread problem worldwide. There is a growing concern that violence against women has a global public health impact, as well as a violation of human rights. From the existing statistical surveys, it is revealed that there exists a strong relationship between DV and health issues of women like bruising, lacerations, depression, anxiety, flashbacks, sleep disturbances, hyper-arousal, emotional distress, sexually transmitted diseases and so on. This social problem is still considered as behind the closed doors issue and stigmatized topic. Women conceal their sufferings from family and friends, as they experience a lack of trust in others, feelings of shame and embarrassment among the society. Hence, women survivors of DV experience some barriers in seeking the support of specialized services such as health care access, crisis support, and legal guidance. Fortunately, with the popularity of social media like Facebook and Twitter, people share their opinions and emotional feelings to seek the social and emotional support, for sympathetic encouragement, to show compassion and empathy among the public. Considering the DV, social media plays a predominant role in creating the awareness and promoting the support services to the public, as we live in the golden era of social media. The various professional people like the public health researchers, clinicians, psychologists, social workers, national family health organizations, lawyers, and victims or their family and friends share the unprecedentedly valuable information (personal opinions and experiences) in a single platform to improve the social welfare of the community. Though each tweet or post contains a less informational value, the consolidation of millions of messages can generate actionable knowledge and provide valuable insights about the public opinion in general. Hence, this paper reports on an exploratory analysis of the effectiveness of social media for unobtrusive assessment of attitudes and awareness towards DV. In this paper, mixed methods such as qualitative analysis and text mining approaches are used to understand the social media disclosures of DV through the lenses of opinion sharing, anonymity, and support seeking. The results of this study could be helpful to avoid the cost of wide scale surveys, while still maintaining appropriate research conditions is to leverage the abundance of data publicly available on the web. Also, this analysis with data enrichment and consolidation would be useful in assisting advocacy and national family health organizations to provide information about resources and support, raise awareness and counter common stigmatizing attitudes about DV.

Keywords: domestic violence, social media, social stigma and support, women health

Procedia PDF Downloads 290

Authors: Tewelde Gebresslase Haile, S. P. Singh

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To bridge the existing knowledge gap on public intervention implementations, this study estimates the impact of social protection intervention (SPI) on alleviating social vulnerability. Following a multi-stage sampling, primary information was gathered through a self-administered questionnaire, FGD, and interviews from the target households located at four systematically selected districts of Tigrai, Ethiopia. Factor analysis and Propensity Score Matching are applied to construct Social Vulnerability Index (SVI) and measuring the counterfactual impact of selected intervention. As a multidimensional challenge, social vulnerability is found as an important concept used to guide policy evaluation. Accessibility of basic services of Social Affairs, Agriculture, Health and Education sectors, and Food Security Program are commonly used as SPIs. Finally, this study discovers that the households who had access to SPI have scored 9.65% lower SVI than in the absence of the intervention. Finally, this study suggests the provision of integrated, proactive, productive, and evidence-based SPIs to alleviate social vulnerability.

Keywords: social protection, livelihood assets, social vulnerability, public policy SVI

Procedia PDF Downloads 89

Authors: Jeonghwan Jeon

Abstract:

As the science and technology(S&T) has been rapidly advanced, the national government attempts to reflect changes in the S&T for promoting public R&D activities and economic development. Amongst others, due to the rapid advances and changes of S&T, it becomes important to monitor the trends of S&T policies for formulating the new policy and investigating promising S&T fields. Thus, this paper aims to trace the national S&T policies during this decade for monitoring the change of major S&T fields in the case of South Korea. As one of the organization for S&T policy in South Korea, the National Science and Technology Council (NSTC) has been established to coordinate inter-ministerial policies and programs and to determine all of the national and public S&T policy of South Korea. In this regard, the items on national S&T policy determined by the NSTC are useful for understanding the needs for major S&T fields and adapting to the rapid change of S&T. To this end, we first gathered the data on 512 items on the S&T agenda from 1999 to 2013. Based on these items, the trend of S&T policies is monitored and the major S&T fields are derived. Differences of policy purposes between S&T fields are identified to provide guideline for policy making such as budget allocation or investment promotion as well.

Keywords: science and technology policy, trends, S&T field, monitoring

Procedia PDF Downloads 322

Authors: Madhura Yadav

Abstract:

Urban redevelopment planning initiatives in developing countries have been largely criticised due to top-down planning approach and lack of involvement of the targeted beneficiaries which have led to a challenging situation which is contrary to the perceived needs of beneficiaries. Urban renewal projects improve the lives of people and meaningful participation of community plays a pivotal role. Public perceptions on satisfaction and participation have been given less priority in the investigation, which hinders effective planning and implementation of urban renewal projects. Moreover, challenges of community participation in urban renewal projects are less documented, particularly in relation to public participation and satisfaction. There is a need for new paradigm shift focusing on community participatory approach in urban renewal projects. The over 125-year-old Bhendi Bazar in Mumbai, India is the country’s first ever cluster redevelopment project, popularly known as Bhendi Bazaar redevelopment and it will be one of the largest projects for urban rejuvenation of one of Mumbai’s oldest and dying inner city areas. The project is led by the community trust, inputs were taken from various stakeholders, including residents, commercial tenants and expert consultants to shape the master plan and design of the project. The project started in 2016 but there is a significant delay in implementing the project. The study aimed at studying and assessing public perceptions on satisfaction and the relationship between community participation and community satisfaction in Bhendi Bazaar of Mumbai, India. Furthermore, the study will outline the challenges and problems of community participation in urban renewal projects and it suggests recommendations for the future. The qualitative and quantitative methods such as reconnaissance survey, key informant interviews, focus group discussions, walking interviews, a narrative inquiry is used for analysis of data. Preliminary findings revealed that all tenants are satisfied for the redevelopment of an area but the willingness of residential tenants to move in transit accommodation has made the projects successful and reductant of some residential and commercial tenants, regulatory provisions rising to face challenges in implementation. Experiences from the case study can help to understand dynamics behind public participation and government. At the same time, they serve as an inspiration and learning opportunity for future projects to ensure that they are sustainable not only from an economic standpoint but also, a social perspective.

Keywords: urban renewal, Bhendi Bazaar, community participation, satisfaction, social perspective

Procedia PDF Downloads 178

Authors: Tamás Hartványi, Ferenc Tóth

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European telecommunication distribution center performance is measured by service lead time and quality. Operation model is CTO (customized to order) namely, a high mix customization of telecommunication network equipment and parts. CTO operation contains material receiving, warehousing, network and server assembly to order and configure based on customer specifications. Variety of the product and orders does not support mass production structure. One of the success factors to satisfy customer is to have a proper aggregated planning method for the operation in order to have optimized human resources and highly efficient asset utilization. Research will investigate several methods and find proper way to have an order book simulation where practical optimization problem may contain thousands of variables and the simulation running times of developed algorithms were taken into account with high importance. There are two operation research models that were developed, customer demand is given in orders, no change over time, customer demands are given for product types, and changeover time is constant.

Keywords: CTO, aggregated planning, demand simulation, changeover time

Procedia PDF Downloads 267

Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Pius Akindele Adeniyi

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The World's tropical forests are disappearing at an alarming rate of more than 200,000 ha per year as a result of deforestation due mainly to population pressures, economic growth, poor management and inappropriate policy. A forest policy determines the role of the sector in a nation's economy and it is formulated in accordance with the objectives of the national economic development. Urban forestry as a concept is relatively new in Nigeria when compared to European and American countries. It consists of growing of trees, shrubs and grass along streets, in parks, and around public or private buildings whose management rests in the hands of the public and private owners. Major urban centers in Nigeria are devoid of efficiently planned tree-planting programs. Hence, various factors militating against environmental improvements, such as climate and other agents of degradation, are highlighted for the necessary attention. The paper discusses the need for forest policy formulation and the objectives of forest policy. Elements of forest policy are also discussed and in particular, those peculiar to urbanization and degraded lands are Forest policy and land-use and policy implementation together with some problem issues in forest policy are discussed while recommendations are given on formulation of a forest policy.

Keywords: urban, forest, policy, environment, interaction, degraded

Procedia PDF Downloads 92

Authors: Hong Su, Qiuju Yan, Wei Du, En Hu, Zhaoyu Yang, Wei Zhang, Yusheng Li, Tao Tang, Wang yang, Shushan Zhao

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Osteoarthritis (OA) is a severe chronic inflammatory disease. As the main active component of Astragalus mongholicus Bunge, a classic traditional ethnic herb, calycosin exhibits anti-inflammatory action and its mechanism of exact targets for OA have yet to be determined. In this study, we established an anterior cruciate ligament transection (ACLT) mouse model. Mice were randomized to sham, OA, and calycosin groups. Cartilage synthesis markers type II collagen (Col-2) and SRY-Box Transcription Factor 9 (Sox-9) increased significantly after calycosin gavage. While cartilage matrix degradation index cyclooxygenase-2 (COX-2), phosphor-epidermal growth factor receptor (p-EGFR), and matrix metalloproteinase-9 (MMP9) expression were decreased. With the help of network pharmacology and molecular docking, these results were confirmed in chondrocyte ATDC5 cells. Our results indicated that the calycosin treatment significantly improved cartilage damage, this was probably attributed to reversing the imbalance between chondrocyte synthesis and catabolism.

Keywords: calycosin, osteoarthritis, network pharmacology, molecular docking, inflammatory, cyclooxygenase 2

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Authors: Bassem Boshra Thabet, Mohammed Ibrahim Elsabagh, Mohammad Adly Talaat

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The number of cellular mobile phone users has increased enormously worldwide over the last two decades. Consequently, the monitoring of the performance of the Mobile Network Operators (MNOs) in terms of network coverage and broadband signal strength has become vital for both of the MNOs and regulators. This monitoring helps telecommunications operators and regulators keeping the market playing fair and most beneficial for users. However, the adopted methodologies to facilitate this continuous monitoring process are still problematic regarding cost, effort, and reliability. This paper introduces My Operator Coverage (MOC) system that is using Internet of Things (IoT) concepts and tools to monitor the MNOs performance using a crowd-sourced real-time methodology. MOC produces robust and reliable geographical maps for the user-perceived quality of the MNOs performance. MOC is also meant to enrich the telecommunications regulators with concrete, and up-to-date information that allows for adequate mobile market management strategies as well as appropriate decision making.

Keywords: mobile performance monitoring, crowd-sourced applications, mobile broadband performance, cellular networks monitoring

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Authors: Jirarat Teeravaraprug, Tarathorn Podcharathitikull

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Nowadays, Ministry of Industry has given an attention to develop Eco-industrial towns in Thailand. Eco-industrial towns are a way of demonstrating the application of industrial ecology and are subjects of increased interest as government, business and society. This concept of Eco-industrial town is quite new in Thailand. It is used as a way of achieving more sustainable industrial development. However, many firms or organizations have misunderstood the concept and treated with suspicion. The planning and development of Eco-industrial towns is a significant challenge for the developers and public agencies. This research then gives an attempt to determine current problems of being Eco-Industrial towns and determine success factors for developing Eco-Industrial towns in Thailand. The research starts with giving knowledge about Eco-industrial towns to stakeholders and conducting public hearing in order to acquire the problems of being Eco-industrial towns. Then, factors effecting the development of Eco-Industrial town are collected. The obtained factors are analyzed by using the concept of IOC. Then, the remained factors are categorized and structured based on the concept of AHP. A questionnaire is constructed and distributed to the experts who are involved in the Eco-industrial town project. The result shows that the most significant success criterion is management teams of industrial parks or groups and the second most significant goes to governmental policies.

Keywords: AHP, Eco-Industrial town, success factors, Thailand

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Serap Durkut, A. Eser Elcin, Y. Murat Elcin

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Stimuli-sensitive polymeric hydrogels have received extensive attention in the biomedical field due to their sensitivity to physical and chemical stimuli (temperature, pH, ionic strength, light, etc.). This study describes the rheological properties of a novel thermoresponsive poly(N-vinylcaprolactam)-g-collagen hydrogel. In the study, we first synthesized a facile and novel synthetic carboxyl group-terminated thermo-responsive poly(N-vinylcaprolactam)-COOH (PNVCL-COOH) via free radical polymerization. Further, this compound was effectively grafted with native collagen, by utilizing the covalent bond between the carboxylic acid groups at the end of the chains and amine groups of the collagen using cross-linking agent (EDC/NHS), forming PNVCL-g-Col. Newly-formed hybrid hydrogel displayed novel properties, such as increased mechanical strength and thermoresponsive characteristics. PNVCL-g-Col showed low critical solution temperature (LCST) at 38ºC, which is very close to the body temperature. Rheological studies determine structural–mechanical properties of the materials and serve as a valuable tool for characterizing. The rheological properties of hydrogels are described in terms of two dynamic mechanical properties: the elastic modulus G′ (also known as dynamic rigidity) representing the reversible stored energy of the system, and the viscous modulus G″, representing the irreversible energy loss. In order to characterize the PNVCL-g-Col, the rheological properties were measured in terms of the function of temperature and time during phase transition. Below the LCST, favorable interactions allowed the dissolution of the polymer in water via hydrogen bonding. At temperatures above the LCST, PNVCL molecules within PNVCL-g-Col aggregated due to dehydration, causing the hydrogel structure to become dense. When the temperature reached ~36ºC, both the G′ and G″ values crossed over. This indicates that PNVCL-g-Col underwent a sol-gel transition, forming an elastic network. Following temperature plateau at 38ºC, near human body temperature the sample displayed stable elastic network characteristics. The G′ and G″ values of the PNVCL-g-Col solutions sharply increased at 6-9 minute interval, due to rapid transformation into gel-like state and formation of elastic networks. Copolymerization with collagen leads to an increase in G′, as collagen structure contains a flexible polymer chain, which bestows its elastic properties. Elasticity of the proposed structure correlates with the number of intermolecular cross-links in the hydrogel network, increasing viscosity. However, at 8 minutes, G′ and G″ values sharply decreased for pure collagen solutions due to the decomposition of the elastic and viscose network. Complex viscosity is related to the mechanical performance and resistance opposing deformation of the hydrogel. Complex viscosity of PNVCL-g-Col hydrogel was drastically changed with temperature and the mechanical performance of PNVCL-g-Col hydrogel network increased, exhibiting lesser deformation. Rheological assessment of the novel thermo-responsive PNVCL-g-Col hydrogel, exhibited that the network has stronger mechanical properties due to both permanent stable covalent bonds and physical interactions, such as hydrogen- and hydrophobic bonds depending on temperature.

Keywords: poly(N-vinylcaprolactam)-g-collagen, thermoresponsive polymer, rheology, elastic modulus, stimuli-sensitive

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Authors: J. K. Adedeji, M. O. Oyekanmi

Abstract:

This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Rui de Abrantes, André Luiz Silva Forcetto

Abstract:

Air pollution is a big problem in many cities around the world. Brazilian big cities also have this problem, where millions of people are exposed daily to pollutants levels above the recommended by WHO. Brazil has taken several actions to reduce air pollution, among others, controlling the atmospheric emissions from vehicles, non-road mobile machinery, and motorcycles, but on the other side, there are no emissions controls for locomotives, which are exposing the population to tons of pollutants annually. The rail network is not homogeneously distributed in the national territory; it is denser near the big cities, and this way, the population is more exposed to pollutants; apart from that, the government intends to increase the rail network as one of the strategies for greenhouse gas mitigation, complying with the international agreements against the climate changes. This paper initially presents the estimated emissions from locomotive fleets with no emission control and with emission control equivalent to US Tier 3 from 2028 and for the next 20 years. However, we realized that a program equivalent to phase Tier 3 would not be effective, so we proposed a program in two steps that will avoid the release of more than 2.4 million tons of CO and 531,000 tons of hydrocarbons, 3.7 million tons of nitrogen oxides, and 102,000 tons of particulate matter in 20 years.

Keywords: locomotives, emission control, air pollution, pollutants emission

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Authors: C. Temaneh-Nyah

Abstract:

Electromagnetic compatibility (EMC) is the ability of a Radio Communication Equipment (RCE) to operate with a desired quality of service in a given Electromagnetic Environment (EME) and not to create harmful interference with other RCE. This paper presents an algorithm which improves the simulation speed of estimating EMC of RCE in a complex EME, based on a stage by stage frequency-energy criterion of filtering. This algorithm considers different interference types including: Blocking and intermodulation. It consist of the following steps: simplified energy criterion where filtration is based on comparing the free space interference level to the industrial noise, frequency criterion which checks whether the interfering emissions characteristic overlap with the receiver’s channels characteristic and lastly the detailed energy criterion where the real channel interference level is compared to the noise level. In each of these stages, some interference cases are filtered out by the relevant criteria. This reduces the total number of dual and different combinations of RCE involved in the tedious detailed energy analysis and thus provides an improved simulation speed.

Keywords: electromagnetic compatibility, electromagnetic environment, simulation of communication network

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Authors: Adam Beaunoyer, Cory Beaunoyer, Mohammed Elmorsy, Hanan Saleh

Abstract:

This research aims to create a reinforcement learning agent capable of racing in challenging simulated environments with a low collision count. We present a reinforcement learning agent that can navigate challenging tracks using both a Deep Q-Network (DQN) and a Soft Actor-Critic (SAC) method. A challenging track includes curves, jumps, and varying road widths throughout. Using open-source code on Github, the environment used in this research is based on the 1995 racing game WipeOut. The proposed reinforcement learning agent can navigate challenging tracks rapidly while maintaining low racing completion time and collision count. The results show that the SAC model outperforms the DQN model by a large margin. We also propose an alternative multiple-car model that can navigate the track without colliding with other vehicles on the track. The SAC model is the basis for the multiple-car model, where it can complete the laps quicker than the single-car model but has a higher collision rate with the track wall.

Keywords: reinforcement learning, soft actor-critic, deep q-network, self-driving cars, artificial intelligence, gaming

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Authors: Marium. K.Makhdoom, Talat Hussain, Syed H. Bukhari

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The motivation behind this paper is to focus the need of Zakat as a monetary framework with a specific end goal and as a social equity instrument and minimization of the level of poverty in society to assess the socioeconomic development. The procedure of the study includes investigating the applied system of Islamic economics to propose an option display so as to contribute fundamentally to the Ummah and serving the countries. This paper closes to be viewed Zakat as one of the best possible strategies to quantify the socioeconomic development, which implies when individuals pay Zakat the socioeconomic development level will be higher and vice versa. The duties of Muslims to pay Zakat to accomplish practical improvement as far as wealth redistribution in the middle of Muslims and in addition overcoming any and all hardships between the rich and the poor in the general public. The paper adds to consider Zakat as an index to gauge economic development, moreover, the part of Zakat as an instrument of social equity and neediness destruction in the public eye. By and large, this includes the installment every year of more than two percent of one's capital after the needs of the family have been met.

Keywords: Zakat, Waqf, economic development, Pakistan, Islamic economics, macroeconomics, microeconomics

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Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

Abstract:

The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

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Authors: Rebecca Haythorne

Abstract:

Background: Agendas continuously emphasise the need to increase work based training and opportunities for individuals with learning disabilities. However research and statistics suggest that there is still significant stigma and stereotypes as to what they can contribute, or gain from being part of the working environment. Method: To tackles some of these prejudices an Occupational Therapy based intervention was developed for learning disability service users working at a social enterprise farm. The intervention aimed to increase positive public perception around individual capabilities and encourage individuals with learning disabilities to take ownership and be proud of their individual personhood and citizenship. This was achieved by using components of the Model of Human Occupation to tailor the intervention to individual values, skills and working contributions. The final project involved making creative wall art for public viewing, focusing on 'who works there and what they do'. This was accompanied by a visitor information guide, allowing individuals to tell visitors about themselves, the work they do and why it is meaningful to them. Outcomes: The intervention has helped to increased metal well-being and confidence of learning disability service users “people will know I work here now” and “I now have something to show my family about the work I do at the farm”. The intervention has also increased positive public perception and community awareness “you can really see the effort that’s gone into doing this” and “it’s a really visual experience to see people you don’t expect to see doing this type of work”. Resources left behind have further supported individuals to take ownership in creating more wall art to be sold at the farm shop. Conclusion: the intervention developed has helped to improve mental well-being of both service users and staff and improve community awareness. Due to this, the farm has decided to roll out the intervention to other areas of the social enterprise and is considering having more Occupational Therapy involvement in the future.

Keywords: citizenship, intervention, occupational therapy, personhood

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