Search results for: government data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 27485

Search results for: government data

25205 Estimating Bridge Deterioration for Small Data Sets Using Regression and Markov Models

Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales

Abstract:

The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.

Keywords: concrete bridges, deterioration, Markov chains, probability matrix

Procedia PDF Downloads 336
25204 Validation of Visibility Data from Road Weather Information Systems by Comparing Three Data Resources: Case Study in Ohio

Authors: Fan Ye

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Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.

Keywords: RWIS, visibility distance, low visibility, adverse weather

Procedia PDF Downloads 251
25203 Design and Simulation of All Optical Fiber to the Home Network

Authors: Rahul Malhotra

Abstract:

Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 556
25202 The Consequences of Regime Change in Iraq; Formation and Continuation of Geopolitical Crises

Authors: Ali Asghar Sotoudeh

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Since the US invasion of Iraq in 2003 and the subsequent regime change, internal conflicts between political and ethnic-religious groups have become a hallmark of Iraqi political dynamism. The most important manifestations of these conflicts are the Kurdish-central government conflicts, as well as fundamentalism since 2003. As a result, it seems not only US presence in Iraq under the pretext of fighting terrorism and expanding democracy has not had a positive effect on controlling fundamentalism and political stability in Iraq, but it has paved the way for the formation and continuation of geopolitical crises in the form of disputes over territory and sources of power. In this regard, given the importance of the study, the main purpose of this study is to examine the process of the impact of US regime-change policy on the formation and continuation of geopolitical crises in Iraq. The central question of this study is, what effect has the US regime change policy had on Iraq's domestic political processes? Findings show that regime change and subsequent imposed federalism have widened the gaps in Iraq's sectarian-ethnic system. As a result, the geopolitical crisis in the context of the dispute over geographical territory and sources of power between ethnic-religious groups has become the most important political dynamic in Iraq since the occupation. The research method in this article is descriptive-analytical, and the data collection method is library and internet resources.

Keywords: Iraq, united states, geopolitical crisis, ethno-religious conflict, political federalism

Procedia PDF Downloads 147
25201 Troubleshooting Petroleum Equipment Based on Wireless Sensors Based on Bayesian Algorithm

Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

Procedia PDF Downloads 66
25200 Wage Differentiation Patterns of Households Revisited for Turkey in Same Industry Employment: A Pseudo-Panel Approach

Authors: Yasin Kutuk, Bengi Yanik Ilhan

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Previous studies investigate the wage differentiations among regions in Turkey between couples who work in the same industry and those who work in different industries by using the models that is appropriate for cross sectional data. However, since there is no available panel data for this investigation in Turkey, pseudo panels using repeated cross-section data sets of the Household Labor Force Surveys 2004-2014 are employed in order to open a new way to examine wage differentiation patterns. For this purpose, household heads are separated into groups with respect to their household composition. These groups’ membership is assumed to be fixed over time such as age groups, education, gender, and NUTS1 (12 regions) Level. The average behavior of them can be tracked overtime same as in the panel data. Estimates using the pseudo panel data would be consistent with the estimates using genuine panel data on individuals if samples are representative of the population which has fixed composition, characteristics. With controlling the socioeconomic factors, wage differentiation of household income is affected by social, cultural and economic changes after global economic crisis emerged in US. It is also revealed whether wage differentiation is changing among the birth cohorts.

Keywords: wage income, same industry, pseudo panel, panel data econometrics

Procedia PDF Downloads 397
25199 A New Approach for Improving Accuracy of Multi Label Stream Data

Authors: Kunal Shah, Swati Patel

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Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

Procedia PDF Downloads 584
25198 Secure Cryptographic Operations on SIM Card for Mobile Financial Services

Authors: Kerem Ok, Serafettin Senturk, Serdar Aktas, Cem Cevikbas

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Mobile technology is very popular nowadays and it provides a digital world where users can experience many value-added services. Service Providers are also eager to offer diverse value-added services to users such as digital identity, mobile financial services and so on. In this context, the security of data storage in smartphones and the security of communication between the smartphone and service provider are critical for the success of these services. In order to provide the required security functions, the SIM card is one acceptable alternative. Since SIM cards include a Secure Element, they are able to store sensitive data, create cryptographically secure keys, encrypt and decrypt data. In this paper, we design and implement a SIM and a smartphone framework that uses a SIM card for secure key generation, key storage, data encryption, data decryption and digital signing for mobile financial services. Our frameworks show that the SIM card can be used as a controlled Secure Element to provide required security functions for popular e-services such as mobile financial services.

Keywords: SIM card, mobile financial services, cryptography, secure data storage

Procedia PDF Downloads 312
25197 Synthetic Data-Driven Prediction Using GANs and LSTMs for Smart Traffic Management

Authors: Srinivas Peri, Siva Abhishek Sirivella, Tejaswini Kallakuri, Uzair Ahmad

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Smart cities and intelligent transportation systems rely heavily on effective traffic management and infrastructure planning. This research tackles the data scarcity challenge by generating realistically synthetic traffic data from the PeMS-Bay dataset, enhancing predictive modeling accuracy and reliability. Advanced techniques like TimeGAN and GaussianCopula are utilized to create synthetic data that mimics the statistical and structural characteristics of real-world traffic. The future integration of Spatial-Temporal Generative Adversarial Networks (ST-GAN) is anticipated to capture both spatial and temporal correlations, further improving data quality and realism. Each synthetic data generation model's performance is evaluated against real-world data to identify the most effective models for accurately replicating traffic patterns. Long Short-Term Memory (LSTM) networks are employed to model and predict complex temporal dependencies within traffic patterns. This holistic approach aims to identify areas with low vehicle counts, reveal underlying traffic issues, and guide targeted infrastructure interventions. By combining GAN-based synthetic data generation with LSTM-based traffic modeling, this study facilitates data-driven decision-making that improves urban mobility, safety, and the overall efficiency of city planning initiatives.

Keywords: GAN, long short-term memory (LSTM), synthetic data generation, traffic management

Procedia PDF Downloads 14
25196 A Study on the Measurement of Spatial Mismatch and the Influencing Factors of “Job-Housing” in Affordable Housing from the Perspective of Commuting

Authors: Daijun Chen

Abstract:

Affordable housing is subsidized by the government to meet the housing demand of low and middle-income urban residents in the process of urbanization and to alleviate the housing inequality caused by market-based housing reforms. It is a recognized fact that the living conditions of the insured have been improved while constructing the subsidized housing. However, the choice of affordable housing is mostly in the suburbs, where the surrounding urban functions and infrastructure are incomplete, resulting in the spatial mismatch of "jobs-housing" in affordable housing. The main reason for this problem is that the residents of affordable housing are more sensitive to the spatial location of their residence, but their selectivity and controllability to the housing location are relatively weak, which leads to higher commuting costs. Their real cost of living has not been effectively reduced. In this regard, 92 subsidized housing communities in Nanjing, China, are selected as the research sample in this paper. The residents of the affordable housing and their commuting Spatio-temporal behavior characteristics are identified based on the LBS (location-based service) data. Based on the spatial mismatch theory, spatial mismatch indicators such as commuting distance and commuting time are established to measure the spatial mismatch degree of subsidized housing in different districts of Nanjing. Furthermore, the geographically weighted regression model is used to analyze the influencing factors of the spatial mismatch of affordable housing in terms of the provision of employment opportunities, traffic accessibility and supporting service facilities by using spatial, functional and other multi-source Spatio-temporal big data. The results show that the spatial mismatch of affordable housing in Nanjing generally presents a "concentric circle" pattern of decreasing from the central urban area to the periphery. The factors affecting the spatial mismatch of affordable housing in different spatial zones are different. The main reasons are the number of enterprises within 1 km of the affordable housing district and the shortest distance to the subway station. And the low spatial mismatch is due to the diversity of services and facilities. Based on this, a spatial optimization strategy for different levels of spatial mismatch in subsidized housing is proposed. And feasible suggestions for the later site selection of subsidized housing are also provided. It hopes to avoid or mitigate the impact of "spatial mismatch," promote the "spatial adaptation" of "jobs-housing," and truly improve the overall welfare level of affordable housing residents.

Keywords: affordable housing, spatial mismatch, commuting characteristics, spatial adaptation, welfare benefits

Procedia PDF Downloads 109
25195 The Structuring of Economic of Brazilian Innovation and the Institutional Proposal to the Legal Management for Global Conformity to Treat the Technological Risks

Authors: Daniela Pellin, Wilson Engelmann

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Brazil has sought to accelerate your development through technology and innovation as a response to the global influences, which has received in internal management practices. For this, it had edited the Brazilian Law of Innovation 13.243/2016. However observing the Law overestimated economic aspects the respective application will not consider the stakeholders and the technological risks because there is no legal treatment. The economic exploitation and the technological risks must be controlled by limits of democratic system to find better social development to contribute with the economics agents for making decision to conform with global directions. The research understands this is a problem to face given the social particularities of the country because there has been the literal import of the North American Triple Helix Theory consolidated in developed countries and the negative consequences when applied in developing countries. Because of this symptomatic scenario, it is necessary to create adjustment to conduct the management of the law besides social democratic interests to increase the country development. For this, therefore, the Government will have to adopt some conducts promoting side by side with universities, civil society and companies, informational transparency, catch of partnerships, create a Confort Letter document for preparation to ensure the operation, joint elaboration of a Manual of Good Practices, make accountability and data dissemination. Also the Universities must promote informational transparency, drawing up partnership contracts and generating revenue, development of information. In addition, the civil society must do data analysis about proposals received for discussing to give opinion related. At the end, companies have to give public and transparent information about investments and economic benefits, risks and innovation manufactured. The research intends as a general objective to demonstrate that the efficiency of the propeller deployment will be possible if the innovative decision-making process goes through the institutional logic. As specific objectives, the American influence must undergo some modifications to better suit the economic-legal incentives to potentiate the development of the social system. The hypothesis points to institutional model for application to the legal system can be elaborated based on emerging characteristics of the country, in such a way that technological risks can be foreseen and there will be global conformity with attention to the full development of society as proposed by the researchers.The method of approach will be the systemic-constructivist with bibliographical review, data collection and analysis with the construction of the institutional and democratic model for the management of the Law.

Keywords: development, governance of law, institutionalization, triple helix

Procedia PDF Downloads 140
25194 Food Security and Utilization in Ethiopia

Authors: Tuji Jemal Ahmed

Abstract:

Food security and utilization are critical aspects of ensuring the well-being and prosperity of a nation. This paper examines the current state of food security and utilization in Ethiopia, focusing on the challenges, opportunities, and strategies employed to address the issue. Ethiopia, a country in East Africa, has made significant progress in recent years to improve food security and utilization for its population. However, persistent challenges such as recurrent droughts, limited access to resources, and low agricultural productivity continue to pose obstacles to achieving sustainable food security. The paper begins by providing an overview of the concept of food security, emphasizing its multidimensional nature and the importance of access, availability, utilization, and stability. It then explores the specific factors influencing food security and utilization in Ethiopia, including natural resources, climate variability, agricultural practices, infrastructure, and socio-economic factors. Furthermore, the paper highlights the initiatives and interventions implemented by the Ethiopian government, non-governmental organizations, and international partners to enhance food security and utilization. These efforts include agricultural extension programs, irrigation projects, investments in rural infrastructure, and social safety nets to protect vulnerable populations. The study also examines the role of technology and innovation in improving food security and utilization in Ethiopia. It explores the potential of sustainable agricultural practices, such as conservation agriculture, improved seed varieties, and precision farming techniques. Additionally, it discusses the role of digital technologies in enhancing access to market information, financial services, and agricultural inputs for smallholder farmers. Finally, the paper discusses the importance of collaboration and partnerships between stakeholders, including government agencies, development organizations, research institutions, and communities, in addressing food security and utilization challenges. It emphasizes the need for integrated and holistic approaches that consider both production and consumption aspects of the food system.

Keywords: food security, utilization, Ethiopia, challenges

Procedia PDF Downloads 123
25193 Food Security and Utilization in Ethiopia

Authors: Tuji Jemal Ahmed

Abstract:

Food security and utilization are critical aspects of ensuring the well-being and prosperity of a nation. This paper examines the current state of food security and utilization in Ethiopia, focusing on the challenges, opportunities, and strategies employed to address the issue. Ethiopia, a country in East Africa, has made significant progress in recent years to improve food security and utilization for its population. However, persistent challenges such as recurrent droughts, limited access to resources, and low agricultural productivity continue to pose obstacles to achieving sustainable food security. The paper begins by providing an overview of the concept of food security, emphasizing its multidimensional nature and the importance of access, availability, utilization, and stability. It then explores the specific factors influencing food security and utilization in Ethiopia, including natural resources, climate variability, agricultural practices, infrastructure, and socio-economic factors. Furthermore, the paper highlights the initiatives and interventions implemented by the Ethiopian government, non-governmental organizations, and international partners to enhance food security and utilization. These efforts include agricultural extension programs, irrigation projects, investments in rural infrastructure, and social safety nets to protect vulnerable populations. The study also examines the role of technology and innovation in improving food security and utilization in Ethiopia. It explores the potential of sustainable agricultural practices, such as conservation agriculture, improved seed varieties, and precision farming techniques. Additionally, it discusses the role of digital technologies in enhancing access to market information, financial services, and agricultural inputs for smallholder farmers. Finally, the paper discusses the importance of collaboration and partnerships between stakeholders, including government agencies, development organizations, research institutions, and communities, in addressing food security and utilization challenges. It emphasizes the need for integrated and holistic approaches that consider both production and consumption aspects of the food system.

Keywords: food security, utilization, Ethiopia, challenges

Procedia PDF Downloads 85
25192 Scenarios of Digitalization and Energy Efficiency in the Building Sector in Brazil: 2050 Horizon

Authors: Maria Fatima Almeida, Rodrigo Calili, George Soares, João Krause, Myrthes Marcele Dos Santos, Anna Carolina Suzano E. Silva, Marcos Alexandre Da

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In Brazil, the building sector accounts for 1/6 of energy consumption and 50% of electricity consumption. A complex sector with several driving actors plays an essential role in the country's economy. Currently, the digitalization readiness in this sector is still low, mainly due to the high investment costs and the difficulty of estimating the benefits of digital technologies in buildings. Nevertheless, the potential contribution of digitalization for increasing energy efficiency in the building sector in Brazil has been pointed out as relevant in the political and sectoral contexts, both in the medium and long-term horizons. To contribute to the debate on the possible evolving trajectories of digitalization in the building sector in Brazil and to subsidize the formulation or revision of current public policies and managerial decisions, three future scenarios were created to anticipate the potential energy efficiency in the building sector in Brazil due to digitalization by 2050. This work aims to present these scenarios as a basis to foresight the potential energy efficiency in this sector, according to different digitalization paces - slow, moderate, or fast in the 2050 horizon. A methodological approach was proposed to create alternative prospective scenarios, combining the Global Business Network (GBN) and the Laboratory for Investigation in Prospective Strategy and Organisation (LIPSOR) methods. This approach consists of seven steps: (i) definition of the question to be foresighted and time horizon to be considered (2050); (ii) definition and classification of a set of key variables, using the prospective structural analysis; (iii) identification of the main actors with an active role in the digital and energy spheres; (iv) characterization of the current situation (2021) and identification of main uncertainties that were considered critical in the development of alternative future scenarios; (v) scanning possible futures using morphological analysis; (vi) selection and description of the most likely scenarios; (vii) foresighting the potential energy efficiency in each of the three scenarios, namely slow digitalization; moderate digitalization, and fast digitalization. Each scenario begins with a core logic and then encompasses potentially related elements, including potential energy efficiency. Then, the first scenario refers to digitalization at a slow pace, with induction by the government limited to public buildings. In the second scenario, digitalization is implemented at a moderate pace, induced by the government in public, commercial, and service buildings, through regulation integrating digitalization and energy efficiency mechanisms. Finally, in the third scenario, digitalization in the building sector is implemented at a fast pace in the country and is strongly induced by the government, but with broad participation of private investments and accelerated adoption of digital technologies. As a result of the slow pace of digitalization in the sector, the potential for energy efficiency stands at levels below 10% of the total of 161TWh by 2050. In the moderate digitalization scenario, the potential reaches 20 to 30% of the total 161TWh by 2050. Furthermore, in the rapid digitalization scenario, it will reach 30 to 40% of the total 161TWh by 2050.

Keywords: building digitalization, energy efficiency, scenario building, prospective structural analysis, morphological analysis

Procedia PDF Downloads 115
25191 Machine Learning Facing Behavioral Noise Problem in an Imbalanced Data Using One Side Behavioral Noise Reduction: Application to a Fraud Detection

Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

Procedia PDF Downloads 130
25190 Automatic Detection of Traffic Stop Locations Using GPS Data

Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

Procedia PDF Downloads 275
25189 Gradient Boosted Trees on Spark Platform for Supervised Learning in Health Care Big Data

Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

Procedia PDF Downloads 241
25188 Mitigating Acid Mine Drainage Pollution: A Case Study In the Witwatersrand Area of South Africa

Authors: Elkington Sibusiso Mnguni

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In South Africa, mining has been a key economic sector since the discovery of gold in 1886 in the Witwatersrand region, where the city of Johannesburg is located. However, some mines have since been decommissioned, and the continuous pumping of acid mine drainage (AMD) also stopped causing the AMD to rise towards the ground surface. This posed a serious environmental risk to the groundwater resources and river systems in the region. This paper documents the development and extent of the environmental damage as well as the measures implemented by the government to alleviate such damage. The study will add to the body of knowledge on the subject of AMD treatment to prevent environmental degradation. The method used to gather and collate relevant data and information was the desktop study. The key findings include the social and environmental impact of the AMD, which include the pollution of water sources for domestic use leading to skin and other health problems and the loss of biodiversity in some areas. It was also found that the technical intervention of constructing a plant to pump and treat the AMD using the high-density sludge technology was the most effective short-term solution available while a long-term solution was being explored. Some successes and challenges experienced during the implementation of the project are also highlighted. The study will be a useful record of the current status of the AMD treatment interventions in the region.

Keywords: acid mine drainage, groundwater resources, pollution, river systems, technical intervention, high density sludge

Procedia PDF Downloads 186
25187 Prevalence of Work-Related Musculoskeletal Disorder among Dental Personnel in Perak

Authors: Nursyafiq Ali Shibramulisi, Nor Farah Fauzi, Nur Azniza Zawin Anuar, Nurul Atikah Azmi, Janice Hew Pei Fang

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Background: Work related musculoskeletal disorders (WRMD) among dental personnel have been underestimated and under-reported worldwide and specifically in Malaysia. The problem will arise and progress slowly over time, as it results from accumulated injury throughout the period of work. Several risk factors, such as repetitive movement, static posture, vibration, and adapting poor working postures, have been identified to be contributing to WRMSD in dental practices. Dental personnel is at higher risk of getting this problem as it is their working nature and core business. This would cause pain and dysfunction syndrome among them and result in absence from work and substandard services to their patients. Methodology: A cross-sectional study involving 19 government dental clinics in Perak was done over the period of 3 months. Those who met the criteria were selected to participate in this study. Malay version of the Self-Reported Nordic Musculoskeletal Discomfort Form was used to identify the prevalence of WRMSD, while the intensity of pain in the respective regions was evaluated using a 10-point scale according to ‘Pain as The 5ᵗʰ Vital Sign’ by MOH Malaysia and later on were analyzed using SPSS version 25. Descriptive statistics, including mean and SD and median and IQR, were used for numerical data. Categorical data were described by percentage. Pearson’s Chi-Square Test and Spearman’s Correlation were used to find the association between the prevalence of WRMSD and other socio-demographic data. Results: 159 dentists, 73 dental therapists, 26 dental lab technicians, 81 dental surgery assistants, and 23 dental attendants participated in this study. The mean age for the participants was 34.9±7.4 and their mean years of service was 9.97±7.5. Most of them were female (78.5%), Malay (71.3%), married (69.6%) and right-handed (90.1%). The highest prevalence of WRMSD was neck (58.0%), followed by shoulder (48.1%), upper back (42.0%), lower back (40.6%), hand/wrist (31.5%), feet (21.3%), knee (12.2%), thigh 7.7%) and lastly elbow (6.9%). Most of those who reported having neck pain scaled their pain experiences at 2 out of 10 (19.5%), while for those who suffered upper back discomfort, most of them scaled their pain experience at 6 out of 10 (17.8%). It was found that there was a significant relationship between age and pain at neck (p=0.007), elbow (p=0.027), lower back (p=0.032), thigh (p=0.039), knee (p=0.001) and feet (p=0.000) regions. Job position also had been found to be having a significant relationship with pain experienced at the lower back (p=0.018), thigh (p=0.011), knee, and feet (p=0.000). Conclusion: The prevalence of WRMSD among dental personnel in Perak was found to be high. Age and job position were found to be having a significant relationship with pain experienced in several regions. Intervention programs should be planned and conducted to prevent and reduce the occurrence of WRMSD, as all harmful or unergonomic practices should be avoided at all costs.

Keywords: WRMSD, ergonomic, dentistry, dental

Procedia PDF Downloads 88
25186 Analysis of Sediment Distribution around Karang Sela Coral Reef Using Multibeam Backscatter

Authors: Razak Zakariya, Fazliana Mustajap, Lenny Sharinee Sakai

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A sediment map is quite important in the marine environment. The sediment itself contains thousands of information that can be used for other research. This study was conducted by using a multibeam echo sounder Reson T20 on 15 August 2020 at the Karang Sela (coral reef area) at Pulau Bidong. The study aims to identify the sediment type around the coral reef by using bathymetry and backscatter data. The sediment in the study area was collected as ground truthing data to verify the classification of the seabed. A dry sieving method was used to analyze the sediment sample by using a sieve shaker. PDS 2000 software was used for data acquisition, and Qimera QPS version 2.4.5 was used for processing the bathymetry data. Meanwhile, FMGT QPS version 7.10 processes the backscatter data. Then, backscatter data were analyzed by using the maximum likelihood classification tool in ArcGIS version 10.8 software. The result identified three types of sediments around the coral which were very coarse sand, coarse sand, and medium sand.

Keywords: sediment type, MBES echo sounder, backscatter, ArcGIS

Procedia PDF Downloads 87
25185 Management Strategies for Risk Events in Construction Industries during Economic Situation and COVID-19 Pandemic in Nigeria

Authors: Ezeabasili Chibuike Patrick

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The complex situation of construction industries in Nigeria and the risk of failures involved includes cost overrun, time overrun, Corruption, Government influence, Subcontractor challenges, Political influence and Instability, Cultural differences, Human resources deficiencies, cash flow Challenges, foreign exchange issues, inadequate design, Safety, low productivity, late payment, Quality control issues, project management issues, Environmental issues, Force majeure Competition amongst others has made the industry prone to risk and failures. Good project management remains effective in improving decision-making, which minimizes these risk events. This study was done to address these project risks and good decision-making to avert them. A mixed-method approach to research was used to do this study. Data collected by questionnaires and interviews on thirty-two (32) construction professionals was used in analyses to aid the knowledge and management of risks that were identified. The study revealed that there is no good risk management expertise in Nigeria. Also, that the economic/political situation and the recent COVID-19 pandemic has added to the risk and poor management strategies. The contingency theory and cost has therefore surfaced to be the most strategic management method used to reduce these risk issues and they seem to be very effective.

Keywords: strategies, risk management, contingency theory, Nigeria

Procedia PDF Downloads 131
25184 Determining the Policy Space of the Partido Socialista Obrero Español Government in Managing Spain's Economic and Financial Crisis

Authors: A. Pascual Ramsay

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Accounts of the management of the economic and euro crisis in Spain have been dominated by an emphasis on external constraints. However, this approach leaves unanswered important questions about the role of domestic political factors. Using systematic qualitative primary research and employing elite interviewing and process tracing, this paper aims to fill this gap for the period of the Partido Socialista Obrero Español (PSOE) administration. The paper shows that domestic politics played a crucial role in the management of the crisis, most importantly by determining the shape of the measures undertaken. In its three distinct stages – downplaying/inaction, reaction/stimulus, and austerity/reform – the PSOE's response was certainly constrained by external factors, most notably EMU membership and the actions of sovereign-bond investors, the ECB and Germany. Yet while these external constraints forced the government to act, domestic political factors fundamentally shaped the content of key measures: the fiscal stimulus, the labour, financial and pension reforms, the refusal to accept a bailout or the reform of the Constitution. Seven factors were particularly influential: i) electoral and political cost, ii) party and partisanship, iii) organised interests, iv) domestic institutions, v) ideological preferences, vi) ineffective decision-making, and vii) judgement and personal characteristics of decision-makers. In conclusion, domestic politics played an important role in the management of the crisis, a role that has been underestimated by dominant approaches focusing on external constraints and weak domestic policy autonomy. The findings provide empirical evidence to support research agendas that identify significant state discretion in the face of international economic integration and an important role for domestic political factors such as institutions, material interests, partisanship and ideology in shaping economic outcomes.

Keywords: economic crisis, Euro, PSOE, Spain

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25183 External Program Evaluation: Impacts and Changes on Government-Assisted Refugee Mothers

Authors: Akiko Ohta, Masahiro Minami, Yusra Qadir, Jennifer York

Abstract:

The Home Instruction for Parents of Preschool Youngsters (HIPPY) is a home instruction program for mothers of children 3 to 5 years old. Using role-play as a method of teaching, the participating mothers work with their home visitors and learn how to deliver the HIPPY curriculum to their children. Applying HIPPY, Reviving Hope and Home for High-risk Refugee Mothers Program (RHH) was created to provide more personalized peer support and to respond to ongoing settlement challenges for isolated and vulnerable Government Assisted Refugee (GAR) mothers. GARs often have greater needs and vulnerabilities than other refugee groups. While the support is available, they often face various challenges and barriers in starting their new lives in Canada, such as inadequate housing, low first-language literacy levels, low competency in English or French, and social isolation. The pilot project was operated by Mothers Matter Centre (MMC) from January 2019 to March 2021 in partnership with the Immigrant Services Society of BC (ISSofBC). The formative evaluation was conducted by a research team at Simon Fraser University. In order to provide more suitable support for GAR mothers, RHH intended to offer more flexibility in HIPPY delivery, supported by a home visitor, to meet the need of refugee mothers facing various conditions and challenges; to have a pool of financial resources to be used for the RHH families when necessitated during the program period; to have another designated staff member, called a community navigator, assigned to facilitate the support system for the RHH families in their settlement; to have a portable device available for each RHH mother to navigate settlement support resources; and to provide other variations of the HIPPY curriculum as an option for the RHH mothers, including a curriculum targeting pre-HIPPY age children. Reflections on each program component was collected from RHH mothers and staff members of MMC and ISSofBC, including frontline workers and management staff, through individual interviews and focus group discussions. Each of the RHH program components was analyzed and evaluated by applying Moore’s four domains framework to identify key information and generate new knowledge (data). To capture RHH mothers’ program experience more in depth based on their own reflections, the photovoice method was used. Some photos taken by the mothers will be shared to illustrate their RHH experience as part of their life stories. Over the period of the program, this evaluation observed how RHH mothers became more confident in various domains, such as communicating with others, taking public transportations alone, and teaching their own child(ren). One of the major factors behind the success was their home visitors’ flexibility and creativity to create a more meaningful and tailored approach for each mother, depending on her background and personal situation. The role of the community navigator was tested out and improved during the program period. The community navigators took the key role to assess the needs of the RHH families and connect them with community resources. Both the home visitors and community navigators were immigrant mothers themselves and owing to their dedicated care for the RHH mothers; they were able to gain trust and work closely and efficiently with RHH mothers.

Keywords: refugee mothers, settlement support, program evaluation, Canada

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25182 A Named Data Networking Stack for Contiki-NG-OS

Authors: Sedat Bilgili, Alper K. Demir

Abstract:

The current Internet has become the dominant use with continuing growth in the home, medical, health, smart cities and industrial automation applications. Internet of Things (IoT) is an emerging technology to enable such applications in our lives. Moreover, Named Data Networking (NDN) is also emerging as a Future Internet architecture where it fits the communication needs of IoT networks. The aim of this study is to provide an NDN protocol stack implementation running on the Contiki operating system (OS). Contiki OS is an OS that is developed for constrained IoT devices. In this study, an NDN protocol stack that can work on top of IEEE 802.15.4 link and physical layers have been developed and presented.

Keywords: internet of things (IoT), named-data, named data networking (NDN), operating system

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25181 Wealth-Based Inequalities in Child Health: A Micro-Level Analysis of Maharashtra State in India

Authors: V. Rekha, Rama Pal

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The study examines the degree and magnitude of wealth-based inequalities in child health and its determinants in India. Despite making strides in economic growth, India has failed to secure a better nutritional status for all the children. The country currently faces the double burden of malnutrition as well as the problems of overweight and obesity. Child malnutrition, obesity, unsafe water, sanitation among others are identified as the risk factors for Non-Communicable Diseases (NCDs). Eliminating malnutrition in all its forms will catalyse improved health and economic outcomes. The assessment of the distributive dimension of child health across various segments of the population is essential for effective policy intervention. The study utilises the fourth round of District Level Health Survey for 2012-13 to analyse the inequalities among children in the age group 0-14 years in Maharashtra, a state in the western region of India with a population of 11.24 crores which constitutes 9.3 percent of the total population of India. The study considers the extent of health inequality by state, districts, sector, age-groups, and gender. The z-scores of four child health outcome variables are computed to assess the nutritional status of pre-school and school children using WHO reference. The descriptive statistics, concentration curves, concentration indices, correlation matrix, logistic regression have been used to analyse the data. The results indicate that magnitude of inequality is higher in Maharashtra and child health inequalities manifest primarily among the weaker sections of society. The concentration curves show that there exists a pro-poor inequality in child malnutrition measured by stunting, wasting, underweight, anaemia and a pro-rich overweight inequality. The inequalities in anaemia are observably lower due to the widespread prevalence. Rural areas exhibit a higher incidence of malnutrition, but greater inequality is observed in the urban areas. Overall, the wealth-based inequalities do not vary significantly between age groups. It appears that there is no gender discrimination at the state level. Further, rural-urban differentials in gender show that boys from the rural area and girls living in the urban region experience higher disparities in health. The relative distribution of undernutrition across districts in Maharashtra reveals that malnutrition is rampant and considerable heterogeneity also exists. A negative correlation is established between malnutrition prevalence and human development indicators. The findings of logistic regression analysis reveal that lower economic status of the household is associated with a higher probability of being malnourished. The study recognises household wealth, education of the parent, child gender, and household size as factors significantly related to malnutrition. The results suggest that among the supply-side variables, child-oriented government programmes might be beneficial in tackling nutrition deficit. In order to bridge the health inequality gap, the government needs to target the schemes better and should expand the coverage of services.

Keywords: child health, inequality, malnutrition, obesity

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25180 South African Municipal Service Delivery Failure and Public Value Theory

Authors: Andrew Enaifoghe

Abstract:

Municipalities are the most fundamental units of governance, and they are responsible for providing basic services and supporting growth in the areas they rule. South African local government is primarily understood in terms of service delivery, and the South African constitution provides municipalities with the responsibility of mobilizing economic resources, to better the lives of all people. Essential public services are the primary pillars of enhanced quality of life, and appropriate supplies of safe water and sanitation are required for life, well-being, and human dignity. Therefore, having access to basic services is directly tied to social inclusion and social capital, and towns' inability to offer services can have a negative influence on social and economic growth. The problem of service delivery is seen as one of the biggest challenges facing South African municipalities today. This study attempts to assess South African municipal service delivery. Focusing on the main causes of service delivery challenges, the study also looks at the impact of these challenges to identify ways to minimize such challenges by introducing legal instruments such as municipal budgeting and annual reports. A qualitative design was adopted, and data were collected using a desktop technique and analyzed based on content. While public engagement in municipal affairs is required by law, considerable work has to be done to ensure successful participation. Finally, municipalities were deemed to need to do more to improve human capacity to offer services.

Keywords: municipalities, service delivery, corruption, monitoring, South Africa

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25179 Assessing the Implementation of Community Driven Development through Social Capital in Migrant and Indigenous Informal Settlements in Accra, Ghana

Authors: Beatrice Eyram Afi Ziorklui, Norihisa Shima

Abstract:

Community Driven Development (CDD) is now a widely recommended and accepted development strategy for informal communities across the continent. Centered on the utilization of social capital through community structures, different informal settlements have different structures and different levels of social capital, which affect the implementation and ability to overcome CDD challenges. Although known to be very successful, there are few perspectives on the implementation of CDD initiatives in different informal settlements. This study assesses the implementation of CDD initiatives in migrant and indigenous informal settlements and their ability to navigate challenges. The case study research design was adopted in this research, and respondents were chosen through simple random sampling. Using the Statistical Package for social scientists (SPSS) for data analysis, the study found that migrant informal settlements implement CDD projects through the network of hierarchical structures based on government systems, whereas indigenous informal settlements implement through the hierarchical social structure based on traditions and culture. The study also found that, with the exception of the challenge of land accessibility in migrant informal settlements, all other challenges, such as participation, resource mobilization, and maintenance, have a significant relationship with social capital, although indigenous informal settlements have higher levels of social capital than migrant informal settlements. The study recommends a framework that incorporates community characteristics and the underlying social capital to facilitate upgrading strategies in informal in Ghana.

Keywords: community driven development, informal settlements, social capital, upgrading

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25178 Dao Din Student Activists: From Hope to Victims under the Thai Society of Darkness

Authors: Siwach Sripokangkul, Autthapon Muangming

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The Dao Din group is a gathering of students from the Faculty of Law, Khon Kaen University, a leading university in the northeast of Thailand. The Dao Din group has been one of the most prominent student movements in the past four decades since the bloody massacre of the 6th of October 1976. The group of student is a movement who gather to oppose and protest against different capitalist-run projects that have impacted upon the environment since 2009. The students have become heroes in Thai society and receive support from various groups, especially the middle class who regard the students as role models for the youth. Subsequently, the Dao Din group has received numerous awards between 2011-2013. However, the Dao Din group opposed the military coup d’état of 2014 and the subsequent military junta. Under the military dictatorship regime (2014-present), security officials have hunted, insulted, arrested, and jailed members of the group many times amidst silence from most of the from the middle class. Therefore, this article posits the question of why the Dao Din group which was once the hero and hope of Thai society, has become a political victim in only a few years. The study methods used are the analysis of documentaries, news articles, and interviews with representatives of the Dao Din group. The author argues that Thailand’s middle class previously demonstrated a positive perception of the Dao Din group precisely because that group had earlier opposed policies of the elected Yingluck Shinawatra government, which most of the middle class already despised. However, once the Dao Din group began to protest against the anti-Yingluck military government, then the middle class turned to harshly criticize the Dao Din group. So it can be concluded that the Thai middle class tends to put its partisan interests ahead of a civil society group which has been critical of elected as well as military administrations. This has led the middle class to support the demolishing of Thai democracy. Such a Thai middle-class characteristic not only poses a strong bulwark for the perpetuation of military rule but also destroys a civil society group (composed of young people) who should be the future hope of the nation rather than under the Thai society of darkness.

Keywords: Dao Din student activists, the military coup d’état of 2014, Thai politics, human rights violations

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25177 Location Privacy Preservation of Vehicle Data In Internet of Vehicles

Authors: Ying Ying Liu, Austin Cooke, Parimala Thulasiraman

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Internet of Things (IoT) has attracted a recent spark in research on Internet of Vehicles (IoV). In this paper, we focus on one research area in IoV: preserving location privacy of vehicle data. We discuss existing location privacy preserving techniques and provide a scheme for evaluating these techniques under IoV traffic condition. We propose a different strategy in applying Differential Privacy using k-d tree data structure to preserve location privacy and experiment on real world Gowalla data set. We show that our strategy produces differentially private data, good preservation of utility by achieving similar regression accuracy to the original dataset on an LSTM (Long Term Short Term Memory) neural network traffic predictor.

Keywords: differential privacy, internet of things, internet of vehicles, location privacy, privacy preservation scheme

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25176 The Political Economy of Green Trade in the Context of US-China Trade War: A Case Study of US Biofuels and Soybeans

Authors: Tonghua Li

Abstract:

Under the neoliberal corporate food regime, biofuels are a double-edged sword that exacerbates tensions between national food security and trade in green agricultural products. Biofuels have the potential to help achieve green sustainable development goals, but they threaten food security by exacerbating competition for land and changing global food trade patterns. The U.S.-China trade war complicates this debate. Under the influence of different political and corporate coordination mechanisms in China and the US, trade disputes can have different impacts on sustainable agricultural practices. This paper develops an actor-centred ‘network governance framework’ focusing on trade in soybean and corn-based biofuels to explain how trade wars can change the actions of governmental and non-governmental actors in the context of oligopolistic competition and market concentration in agricultural trade. There is evidence that the US-China trade decoupling exacerbates the conflict between national security, free trade in agriculture, and the realities and needs of green and sustainable energy development. The US government's trade policies reflect concerns about China's relative gains, leading to a loss of trade profits, making it impossible for the parties involved to find a balance between the three objectives and, consequently, to get into a biofuels and soybean industry dilemma. Within the setting of prioritizing national security and strategic interests, the government has replaced the dominant position of large agribusiness in the neoliberal food system, and the goal of environmental sustainability has been marginalized by high politics. In contrast, China faces tensions in the trade war between food security self-sufficiency policy and liberal sustainable trade, but the state-capitalist model ensures policy coordination and coherence in trade diversion and supply chain adjustment. Despite ongoing raw material shortages and technological challenges, China remains committed to playing a role in global environmental governance and promoting green trade objectives.

Keywords: food security, green trade, biofuels, soybeans, US-China trade war

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