Search results for: open data

Authors: Nangialai Yousufzai, Eysosiyas Etana, Ikuo Sugiyama

Abstract:

Kabul population has been growing continually since 2001 and reaching six million in 2025 due to the rapid inflow from the neighboring countries. As a result of the population growth, lack of living facilities supported by infrastructure services is becoming serious in social and economic aspects. However, about 70% of the city is still occupied illegally and the government has little information on the infrastructure demands. To improve this situation, land readjustment is one of the powerful development tools, because land readjustment does not need a high governmental budget of itself. Instead, the method needs cooperation between stakeholders such as landowners, developers and a local government. So it is becoming crucial for both government and citizens to implement land readjustment for providing tidy urban areas with enough public services to realize more livable city as a whole. On the contrary, the traditional land readjustment tends to spend a long time until now to get consensus on the new plan between stakeholders. One of the reasons is that individual land area (land parcel) is decreased due to the contribution to public such as roads/parks/squares for improving the urban environment. The second reason is that the new plan is difficult for dwellers to imagine new life after the readjustment. Because the paper-based plan is made by an authority not for dwellers but for specialists to precede the project. This paper aims to shorten the time to realize quick consensus between stakeholders. The first improvement is utilizing questionnaire(s) to assess the demand and preference of the landowners. The second one is utilizing 3D model for dwellers to visualize the new environment easily after the readjustment. In additions, the 3D model is reflecting the demand and preference of the resident so that they could select a land parcel according to their sense value of life. The above-mentioned two improvements are carried out after evaluating total land prices of the new plans to select for maximizing the project value. The land price forecasting formula is derived from the current market ones in Kabul. Finally, it is stressed that the rapid consensus-building of land readjustment utilizing ICT and open data analysis is essential to redevelop slums and illegal occupied areas in Kabul.

Keywords: land readjustment, consensus building, land price formula, 3D simulation

Procedia PDF Downloads 332

Authors: Hankyu Lee, Seoung Bum Kim

Abstract:

The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

Procedia PDF Downloads 308

Authors: Ankit Sharma, Mudit Sachan, Anurag Prakash

Abstract:

Rapid growth in data acquisition technologies through drones, have led to advances and interests in collecting high-resolution images of geological fields. Being advantageous in capturing high volume of data in short flights, a number of challenges have to overcome for efficient analysis of this data, especially while data acquisition, image interpretation and processing. We introduce a method that allows effective mapping of geological fields using photogrammetric data of surfaces, drainage area, water bodies etc, which will be captured by airborne vehicles like UAVs, we are not taking satellite images because of problems in adequate resolution, time when it is captured may be 1 yr back, availability problem, difficult to capture exact image, then night vision etc. This method includes advanced automated image interpretation technology and human data interaction to model structures and. First Geological structures will be detected from the primary photographic dataset and the equivalent three dimensional structures would then be identified by digital elevation model. We can calculate dip and its direction by using the above information. The structural map will be generated by adopting a specified methodology starting from choosing the appropriate camera, camera’s mounting system, UAVs design ( based on the area and application), Challenge in air borne systems like Errors in image orientation, payload problem, mosaicing and geo referencing and registering of different images to applying DEM. The paper shows the potential of using our method for accurate and efficient modeling of geological structures, capture particularly from remote, of inaccessible and hazardous sites.

Keywords: digital elevation model, mapping, photogrammetric data analysis, geological structures

Procedia PDF Downloads 686

Authors: Dong Seop Lee, Byung Sik Kim

Abstract:

In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

Procedia PDF Downloads 129

Authors: Hosuk Shin, Young-Hyun Seo, Eunhak Lee, Seung-Young Kho

Abstract:

Currently, in Seoul, users have the privilege to avoid riding crowded buses with the installation of Bus Information System (BIS). BIS has three levels of on-board bus ridership level information (spacious, normal, and crowded). However, there are flaws in the system due to it being real time which could provide incomplete information to the user. For example, a bus comes to the station, and on the BIS it shows that the bus is crowded, but on the stop that the user is waiting many people get off, which would mean that this station the information should show as normal or spacious. To fix this problem, this study predicts the bus ridership level using smart card data to provide more accurate information about the passenger ridership level on the bus. An Artificial Neural Network (ANN) is an interconnected group of nodes, that was created based on the human brain. Forecasting has been one of the major applications of ANN due to the data-driven self-adaptive methods of the algorithm itself. According to the results, the ANN algorithm was stable and robust with somewhat small error ratio, so the results were rational and reasonable.

Keywords: smartcard data, ANN, bus, ridership

Procedia PDF Downloads 167

Authors: Sirilak Areerachakul

Abstract:

Water quality has initiated serious management efforts in many countries. Artificial Neural Network (ANN) models are developed as forecasting tools in predicting water quality trend based on historical data. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (T-Coliform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 94.23% in classifying the water quality of Saen Saep canal in Bangkok. Subsequently, this encouraging result could be combined with GIS data improves the classification accuracy significantly.

Keywords: artificial neural network, geographic information system, water quality, computer science

Procedia PDF Downloads 343

Authors: Isabel Latz, Mark Lusk, Josiah Heyman

Abstract:

The rise of restrictive U.S. immigration policies and their strengthened enforcement has reportedly caused concerns among providers about their inadvertent effects on service utilization among Latinx and immigrant communities. This study presents perceptions on this issue from twenty service providers in health care, mental health, nutrition assistance, legal assistance, and immigrant advocacy in El Paso, Texas. All participants were experienced professionals, with fifteen in CEO, COO, executive director, or equivalent positions, and based at organizations that provide services for immigrant and/or low-income populations in a bi-national border community. Quantitative and qualitative data were collected by two primary investigators via semi-structured telephone interviews with an average length of 20 minutes. A survey script with closed and open-ended questions inquired about participants’ demographic information and perceptions of impacts of immigration enforcement policies under the current federal administration on their work and patient or client populations. Quantitative and qualitative data were analyzed to produce descriptive statistics and identify salient themes, respectively. Nearly all respondents stated that their work has been negatively (N=13) or both positively and negatively (N=5) affected by current immigration enforcement policies. Negative effects were most commonly related to immigration enforcement-related fear and uncertainty among patient or client populations. Positive effects most frequently referred to a sense of increased community organizing and greater cooperation among organizations. Similarly, the majority of service providers either reported an increase (N=8) or decrease (N=6) in service utilization due to changes in immigration enforcement policies. Increased service needs were primarily related to a need for public education about immigration enforcement policy changes, information about how new policies impact individuals’ service eligibility, legal status, and civil rights, as well as a need to correct misinformation. Decreased service utilization was primarily related to fear-related service avoidance. While providers observed changes in service utilization among undocumented immigrants and mixed-immigration status families, in particular, participants also noted ‘spillover’ effects on the larger Latinx community, including legal permanent and temporary residents, refugees or asylum seekers, and U.S. citizens. This study reveals preliminary insights into providers’ widespread concerns about the effects of current immigration enforcement policies on health, social, and legal service utilization among Latinx individuals. Further research is necessary to comprehensively assess impacts of immigration enforcement policies on service utilization in Latinx and immigrant communities. This information is critical to address gaps in service utilization and prevent an exacerbation of health disparities among Latinx, immigrant, and border populations. In a global climate of rising nationalism and xenophobia, it is critical for policymakers to be aware of the consequences of immigration enforcement policies on the utilization of essential services to protect the well-being of minority and immigrant communities.

Keywords: immigration enforcement, immigration policy, provider perceptions, service utilization

Procedia PDF Downloads 147

Authors: Ping Bo, Meng Yunshan

Abstract:

Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.

Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter

Procedia PDF Downloads 325

Authors: Fanqiang Kong, Chending Bian

Abstract:

In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation

Procedia PDF Downloads 262

Authors: Rishi Kanth Saripalle

Abstract:

Medical experts highly recommend to include physical activity in everyone’s daily routine irrespective of gender or age as it helps to improve various medical issues or curb potential issues. Simultaneously, experts are also diligently trying to provide various healthcare services (interventions, plans, exercise routines, etc.) for promoting healthy living and increasing physical activity in one’s ever increasing hectic schedules. With the introduction of wearables, individuals are able to keep track, analyze, and visualize their daily physical activities. However, there seems to be no common agreed standard for representing, gathering, aggregating and analyzing an individual’s physical activity data from disparate multiple sources (exercise pans, multiple wearables, etc.). This issue makes it highly impractical to develop any data-driven physical activity applications and healthcare programs. Further, the inability to integrate the physical activity data into an individual’s Electronic Health Record to provide a wholistic image of that individual’s health is still eluding the experts. This article has identified three primary reasons for this potential issue. First, there is no agreed standard, both structure and semantic, for representing and sharing physical activity data across disparate systems. Second, various organizations (e.g., LA fitness, Gold’s Gym, etc.) and research backed interventions and programs still primarily rely on paper or unstructured format (such as text or notes) to keep track of the data generated from physical activities. Finally, most of the wearable devices operate in silos. This article identifies the underlying problem, explores the idea of reusing existing standards, and identifies the essential modules required to move forward.

Keywords: electronic physical activity record, physical activity in EHR EIM, tracking physical activity data, physical activity data standards

Procedia PDF Downloads 282

Authors: Gregory Kelly, Gary Chai, Sittampalam Manoharan, Deborah Delaney

Abstract:

A Structural Number (SN) can be calculated for a road pavement from the properties and thicknesses of the surface, base course, sub-base, and subgrade. Historically, the cost of collecting structural data has been very high. Data were initially collected using Benkelman Beams and now by Falling Weight Deflectometer (FWD). The structural strength of pavements weakens over time due to environmental and traffic loading factors, but due to a lack of data, no structural deterioration curve for pavements has been implemented in a Pavement Management System (PMS). International Roughness Index (IRI) is a measure of the road longitudinal profile and has been used as a proxy for a pavement’s structural integrity. This paper offers two conceptual methods to develop Pavement Structural Deterioration Curves (PSDC). Firstly, structural data are grouped in sets by design Equivalent Standard Axles (ESA). An ‘Initial’ SN (ISN), Intermediate SN’s (SNI) and a Terminal SN (TSN), are used to develop the curves. Using FWD data, the ISN is the SN after the pavement is rehabilitated (Financial Accounting ‘Modern Equivalent’). Intermediate SNIs, are SNs other than the ISN and TSN. The TSN was defined as the SN of the pavement when it was approved for pavement rehabilitation. The second method is to use Traffic Speed Deflectometer data (TSD). The road network already divided into road blocks, is grouped by traffic loading. For each traffic loading group, road blocks that have had a recent pavement rehabilitation, are used to calculate the ISN and those planned for pavement rehabilitation to calculate the TSN. The remaining SNs are used to complete the age-based or if available, historical traffic loading-based SNI’s.

Keywords: conceptual, pavement structural number, pavement structural deterioration curve, pavement management system

Procedia PDF Downloads 544

Authors: Ahmed Amine Hachicha

Abstract:

Temperature effect on the performance of a photovoltaic module is one of the main concern that face this renewable energy, especially in the hot arid region, e.g United Arab Emirates. Overheating of the PV modules reduces the open circuit voltage and the efficiency of the modules dramatically. In this work, water cooling is developed to enhance the performance of PV modules. Different scenarios are tested under UAE weather conditions: front, back and double cooling. A spraying system is used for the front cooling whether a direct contact water system is used for the back cooling. The experimental results are compared to a non-cooling module and the performance of the PV module is determined for different situations. A mathematical model is presented to estimate the theoretical performance and validate the experimental results with and without cooling. The experimental results show that the front cooling is more effective than the back cooling and may decrease the temperature of the PV module significantly.

Keywords: PV cooling, solar energy, cooling methods, electrical efficiency, temperature effect

Procedia PDF Downloads 497

Authors: Nader Parsazadeh

Abstract:

The variety of bed sediment load relationships, insufficient information and data, and the influence of river conditions make the selection of an optimum relationship for a given river extremely difficult. Hence, in order to select the best formulae, the bed load equations should be evaluated. The affecting factors need to be scrutinized, and equations should be verified. Also, re-evaluation may be needed. In this research, sediment bed load of Dez Dam at Tal-e Zang Station has been studied. After reviewing the available references, the most common formulae were selected that included Meir-Peter and Muller, using MS Excel to compute and evaluate data. Then, 52 series of already measured data at the station were re-measured, and the sediment bed load was determined. 1. The calculated bed load obtained by different equations showed a great difference with that of measured data. 2. r difference ratio from 0.5 to 2.00 was 0% for all equations except for Nilsson and Shields equations while it was 61.5 and 59.6% for Nilsson and Shields equations, respectively. 3. By reviewing results and discarding probably erroneous measured data measurements (by human or machine), one may use Nilsson Equation due to its r value higher than 1 as an effective equation for estimating bed load at Tal-e Zang Station in order to predict activities that depend upon bed sediment load estimate to be determined. Also, since only few studies have been conducted so far, these results may be of assistance to the operators and consulting companies.

Keywords: bed load, empirical relation ship, sediment, Tale Zang Station

Procedia PDF Downloads 362

Authors: Quang Dong Dang

Abstract:

This paper examines the possible effects of stock market developments by channels on income and wealth inequality. We use the Bayesian Multilevel Model with the explanatory variables of the market’s channels, such as accessibility, efficiency, and market health in six selected countries: the US, UK, Japan, Vietnam, Thailand, and Malaysia. We found that generally, the improvements in the stock market alleviate income inequality. However, stock market expansions in higher-income countries are likely to trigger income inequality. We also found that while enhancing the quality of channels of the stock market has counter-effects on wealth equality distributions, open accessibilities help reduce wealth inequality distributions within the scope of the study. In addition, the inverted U-shaped hypothesis seems not to be valid in six selected countries between the period from 2006 to 2020.

Keywords: Bayesian multilevel model, income inequality, inverted u-shaped hypothesis, stock market development, wealth inequality

Procedia PDF Downloads 108

Authors: Stephen Kyakulumbye, Vivian Kobusingye

Abstract:

Generally, World over, COVID-19 has had adverse effects on all sectors but with more debilitating effects on the education sector. After reactive lockdowns, education institutions that could continue teaching and learning had to go a distance mediated by digital technological tools. In Uganda, the Ministry of Education thereby issued COVID-19 Online Distance E-learning (ODeL) emergent guidelines. Despite such guidelines, academic institutions in Uganda and similar developing contexts with academically constrained resource environments were caught off-guard and ill-prepared to transform from face-to-face learning to online distance learning mode. Most academic institutions that migrated spontaneously did so with no deliberate tools, systems, strategies, or software to cause active, meaningful, and engaging learning for students. By experience, most of these academic institutions shifted to Zoom and WhatsApp and instead conducted online teaching in real-time than blended synchronous and asynchronous tools. This paper provides students’ experiences while blending synchronous and asynchronous content-creating and learning tools within a technological resource-constrained environment to navigate in such a challenging Uganda context. These conceptual case-based findings, using experience from Uganda Christian University (UCU), point at the design of learning activities with two certain characteristics, the enhancement of synchronous learning technologies with asynchronous ones to mitigate the challenge of system breakdown, passive learning to active learning, and enhances the types of presence (social, cognitive and facilitatory). The paper, both empirical and experiential in nature, uses online experiences from third-year students in Bachelor of Business Administration student lectured using asynchronous text, audio, and video created with Open Broadcaster Studio software and compressed with Handbrake, all open-source software to mitigate disk space and bandwidth usage challenges. The synchronous online engagements with students were a blend of zoom or BigBlueButton, to ensure that students had an alternative just in case one failed due to excessive real-time traffic. Generally, students report that compared to their previous face-to-face lectures, the pre-recorded lectures via Youtube provided them an opportunity to reflect on content in a self-paced manner, which later on enabled them to engage actively during the live zoom and/or BigBlueButton real-time discussions and presentations. The major recommendation is that lecturers and teachers in a resource-constrained environment with limited digital resources like the internet and digital devices should harness this approach to offer students access to learning content in a self-paced manner and thereby enabling reflective active learning through reflective and high-order thinking.

Keywords: synchronous learning, asynchronous learning, active learning, reflective learning, resource-constrained environment

Procedia PDF Downloads 139

Authors: M. L. Akinyemi, T. J. Abodurin, A. O. Boyo, J. A. O. Olugbuyiro

Abstract:

Organic dyes from Cola acuminata (C. acuminata), Lupinus arboreus (L. arboreus) and Bougainvillea spectabilis (B. spectabilis) leaves and their mixtures were used as sensitizers to manufacture dye-sensitized solar cells (DSSC). Photoelectric measurements of C. acuminata showed a short circuit current (J_sc) of 0.027 mA/ cm², 0.026 mA/ cm² and 0.018 mA/ cm² with a mixture of mercury chloride and iodine (Hgcl₂ + I); potassium bromide and iodine (KBr + I); and potassium chloride and iodine (KCl + I) respectively. The open circuit voltage (V_oc) was 24 mV, 25 mV and 20 mV for the three dyes respectively. L. arboreus had J_sc of 0.034 mA/ cm², 0.021 mA/ cm² and 0.013 mA/ cm²; and corresponding V_oc of 28 mV, 14.2 mV and 15 mV for the three electrolytes respectively. B. spectabilis recorded J_sc 0.023 mA/ cm², 0.026 mA/ cm² and 0.015 mA/ cm²; and corresponding V_oc values of 6.2 mV, 14.3 mV and 4.0 mV for the three electrolytes respectively. It was observed that the fill factor (FF) was 0.140 for C. acuminata, 0.3198 for L. arboreus and 0.1138 for B. spectabilis. Internal conversions of 0.096%, 0.056% and 0.063% were recorded for three dyes when combined with (KBr + I) electrolyte. The internal efficiency of C. acuminata DSSC was highest in value.

Keywords: dye-sensitized solar cells, organic dye, C. acuminate, L. arboreus, B. spectabilis, dye mixture

Procedia PDF Downloads 287

Authors: Juan Du

Abstract:

Climate change is one of the most crucial issues of this era, with contentious debates on it among scholars. But there are sparse studies on climate change discourse in China. Including China in the study of climate change is essential for a sociological understanding of climate change. China -- as a developing country and an essential player in tackling climate change -- offers an ideal case for studying climate change for scholars moving beyond developed countries and enriching their understandings of climate change by including diverse social settings. This project contrasts the macro- and micro-level understandings of climate change in China, which helps scholars move beyond a focus on climate skepticism and denialism and enriches sociology of climate change knowledge. The macro-level understanding of climate change is obtained by analyzing over 4,000 newspaper articles from various official outlets in China. State-controlled newspapers play an essential role in transmitting essential and high-quality information and promoting broader public understanding of climate change and its anthropogenic nature. Thus, newspaper articles can be seen as tools employed by governments to mobilize the public in terms of supporting the development of a strategy shift from economy-growth to an ecological civilization. However, media is just one of the significant factors influencing an individual’s climate change concern. Extreme weather events, access to accurate scientific information, elite cues, and movement/countermovement advocacy influence an individual’s perceptions of climate change. Hence, there are differences in the ways that both newspaper articles and the public frame the issues. The online forum is an informative channel for scholars to understand the public’s opinion. The micro-level data comes from Zhihu, which is China’s equivalence of Quora. Users can propose, answer, and comment on questions. This project analyzes the questions related to climate change which have over 20 answers. By open-coding both the macro- and micro-level data, this project will depict the differences between ideology as presented in government-controlled newspapers and how people talk and act with respect to climate change in cyberspace, which may provide an idea about any existing disconnect in public behavior and their willingness to change daily activities to facilitate a greener society. The contemporary Yellow Vest protests in France illustrate that the large gap between governmental policies of climate change mitigation and the public’s understanding may lead to social movement activity and social instability. Effective environmental policy is impossible without the public’s support. Finding existing gaps in understanding may help policy-makers develop effective ways of framing climate change and obtain more supporters of climate change related policies. Overall, this qualitative project provides answers to the following research questions: 1) How do different state-controlled newspapers transmit their ideology on climate change to the public and in what ways? 2) How do individuals frame climate change online? 3) What are the differences between newspapers’ framing and individual’s framing?

Keywords: climate change, China, framing theory, media, public’s climate change concern

Procedia PDF Downloads 131

Authors: A. Satty, H. Mwambi

Abstract:

Much clinical trials data-based research are characterized by the unavoidable problem of dropout as a result of missing or erroneous values. This paper aims to review some of the various techniques to address the dropout problems in longitudinal clinical trials. The fundamental concepts of the patterns and mechanisms of dropout are discussed. This study presents five general techniques for handling dropout: (1) Deletion methods; (2) Imputation-based methods; (3) Data augmentation methods; (4) Likelihood-based methods; and (5) MNAR-based methods. Under each technique, several methods that are commonly used to deal with dropout are presented, including a review of the existing literature in which we examine the effectiveness of these methods in the analysis of incomplete data. Two application examples are presented to study the potential strengths or weaknesses of some of the methods under certain dropout mechanisms as well as to assess the sensitivity of the modelling assumptions.

Keywords: incomplete longitudinal clinical trials, missing at random (MAR), imputation, weighting methods, sensitivity analysis

Procedia PDF Downloads 415

Authors: Claerchille Jhulia Robin

Abstract:

This paper discusses the perspective of ESL learners towards pronunciation instruction. It sought to determine how these learners view the type of feedback their speech teacher gives and its impact on their own classroom practice of providing feedback. This study utilized a quantitative-qualitative approach to the problem. The respondents were Education students majoring in English. A survey questionnaire and interview guide were used for data gathering. The data from the survey was tabulated using frequency count and the data from the interview were then transcribed and analyzed. Results showed that ESL learners favor immediate corrective feedback and they do not find any issue in being corrected in front of their peers. They also practice the same corrective technique in their own classroom.

Keywords: ESL, feedback, learner perspective, pronunciation instruction

Procedia PDF Downloads 234

Authors: Fouad. Inel, Lakhdar. Khochemane

Abstract:

This article presents a comparative response specification performance between two controllers of three and four cable based robots for various applications. The main objective of this work is: The first is to use the direct and inverse geometric model to study and simulate the end effector position of the robot with three and four cables. A graphical user interface has been implemented in order to visualizing the position of the robot. Secondly, we present the determination of static and dynamic tensions and lengths of cables required to flow different trajectories. At the end, we study the response of our systems in closed loop with a Proportional-Integrated Derivative (PID) and Proportional-Integrated (PD) controllers then this last are compared the results of the same examples using MATLAB/Simulink; we found that the PID method gives the better performance, such as rapidly speed response, settling time, compared to PD controller.

Keywords: parallel cable-based robots, geometric modeling, dynamic modeling, graphical user interface, open loop, PID/PD controllers

Procedia PDF Downloads 450

Authors: Zeynep Selin Acar

Abstract:

In international system, there has always been a cycle of violence, war and peace. As there travels the time, after Christianity and later Just War theorists, international relations theorists have been tried to limit violence and war. As pieces of international law, Peace of Augsburg, Kellog-Briand Pact, League of Nations Covenant and UN Charter were and are still not effective to prevent war. Moreover, in order to find a way around these rules, it is believed that a new excuse started to be used instead of violence or war, humanitarian intervention. However, it has neither a legal nor a universally accepted framework. As a result, it is open to be manipulated by states. In order to prevent this, Responsibility to Protect (RtoP) which gives a state the responsibility to protect its citizens against violence, is created. Additionally, RtoP transfers this responsibility to regional or international group of states at the time when a state is the origin of violence. In the lights of these, this paper analyzes RtoP as an ethical approach to war and peace studies because it provides other states as guardians and care-takers of people who do not belong to them or do not share any togetherness.

Keywords: ethics, humanitarian intervention, responsibility to protect, UN charter

Procedia PDF Downloads 325

Authors: Chayanika Hazarika Bordoloi

Abstract:

This paper is an attempt to work on a highly inflectional language called Assamese. This is also one of the national languages of India and very little has been achieved in terms of computational research. Building a language processing tool for a natural language is not very smooth as the standard and language representation change at various levels. This paper presents inflectional suffixes of Assamese verbs and how the statistical tools, along with linguistic features, can improve the tagging accuracy. Conditional random fields (CRF tool) was used to automatically tag and train the text data; however, accuracy was improved after linguistic featured were fed into the training data. Assamese is a highly inflectional language; hence, it is challenging to standardizing its morphology. Inflectional suffixes are used as a feature of the text data. In order to analyze the inflections of Assamese word forms, a list of suffixes is prepared. This list comprises suffixes, comprising of all possible suffixes that various categories can take is prepared. Assamese words can be classified into inflected classes (noun, pronoun, adjective and verb) and un-inflected classes (adverb and particle). The corpus used for this morphological analysis has huge tokens. The corpus is a mixed corpus and it has given satisfactory accuracy. The accuracy rate of the tagger has gradually improved with the modified training data.

Keywords: CRF, morphology, tagging, tagset

Procedia PDF Downloads 194

Authors: Samuel John, S. Sharanya

Abstract:

Automation has become an important part of our life. It has been used to control home entertainment systems, changing the ambience of rooms for different events etc. One of the main parameters to control in a smart home is the atmospheric comfort. Atmospheric comfort mainly includes temperature and relative humidity. In homes, the desired temperature of different rooms varies from 20 °C to 25 °C and relative humidity is around 50%. However, it varies widely. Hence, automated measurement of these parameters to ensure comfort assumes significance. To achieve this, a fuzzy logic controller using Arduino was developed using MATLAB. Arduino is an open source hardware consisting of a 24 pin ATMEGA chip (atmega328), 14 digital input /output pins and an inbuilt ADC. It runs on 5v and 3.3v power supported by a board voltage regulator. Some of the digital pins in Aruduino provide PWM (pulse width modulation) signals, which can be used in different applications. The Arduino platform provides an integrated development environment, which includes support for c, c++ and java programming languages. In the present work, soft sensor was introduced in this system that can indirectly measure temperature and humidity and can be used for processing several measurements these to ensure comfort. The Sugeno method (output variables are functions or singleton/constant, more suitable for implementing on microcontrollers) was used in the soft sensor in MATLAB and then interfaced to the Arduino, which is again interfaced to the temperature and humidity sensor DHT11. The temperature-humidity sensor DHT11 acts as the sensing element in this system. Further, a capacitive humidity sensor and a thermistor were also used to support the measurement of temperature and relative humidity of the surrounding to provide a digital signal on the data pin. The comfort sensor developed was able to measure temperature and relative humidity correctly. The comfort percentage was calculated and accordingly the temperature in the room was controlled. This system was placed in different rooms of the house to ensure that it modifies the comfort values depending on temperature and relative humidity of the environment. Compared to the existing comfort control sensors, this system was found to provide an accurate comfort percentage. Depending on the comfort percentage, the air conditioners and the coolers in the room were controlled. The main highlight of the project is its cost efficiency.

Keywords: arduino, DHT11, soft sensor, sugeno

Procedia PDF Downloads 312

Authors: Hannele Laaksonen, Seija Nyqvist, Kari Nurmes

Abstract:

Objectives: In the year 2011 the City of Vaasa started to develop know-how in the technology and the introduction of services for aging people in cooperation with the Polytechnic Novia University of Applied Sciences and VAMK, University of Applied Sciences. The project´s targets included: to help elderly people to maintain their ability to function, to provide them social and physical activities, to prevent their social exclusion, to decrease their feelings of loneliness and insecurity and to develop their technical know-how. Methods: The project was built based on open source code, tailor-made service system and user interface for the elderly living at home and their families, based on the users´ expectations and experiences of services. Activation-TV®-project vas carried out 1.4.2011-31.3.2014. A pilot group of eight elderly persons, who were living at home, were selected to the project. All necessary technical means as well as guidance and teaching equipment were provided to the pilot group. The students of University of Applied Sciences (VAMK, Novia) and employees of Center of Ageing were made all programs to the Activation-TV®. The project group were interviewed after and before intervention. The data were evaluated both qualitatively and quantitatively. Results: The built service includes a video library, a group room for interactive programs and a personal room for bilateral meetings and direct shipment. The program is bilingual and produced in both national languages. The Activation TV® reduced elderly peoples´ (n=8) feelings of emptiness, added mental well-being and quality of life with social contacts. Relatives felt, that they were able to get in to older peoples´ everyday life with Activation TV®. Discussion: The built application was tailored to the model that has not been developed elsewhere in Finland. This model can be copied from one server to another and thus transferred to other municipalities but the program requires its own personnel system management and maintenance as well as program production cooperation between the different actors. This service can be used for the elderly who are living at home without dementia.

Keywords: mental well-being, quality of life, elderly people, Finland

Procedia PDF Downloads 343

Authors: M. Abdullah, Al-Wadud

Abstract:

Sensor-based activity recognition systems usually accounts which sensors have been activated to perform an activity. The system then combines the conditional probabilities of those sensors to represent different activities and takes the decision based on that. However, the information about the sensors which are not activated may also be of great help in deciding which activity has been performed. This paper proposes an approach where the sensory data related to both usage and non-usage of objects are utilized to make the classification of activities. Experimental results also show the promising performance of the proposed method.

Keywords: Naïve Bayesian, based classification, activity recognition, sensor data, object-usage model

Procedia PDF Downloads 322

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Harbor protection systems are so important. The need for automatic protection systems has increased over the last years. Diver detection active sonar has great significance. It used to detect underwater threats such as divers and autonomous underwater vehicle. To automatically detect such threats the sonar image is processed by algorithms. These algorithms used to detect, track and classify of underwater objects. In this work, divers tracking and classification algorithm is improved be proposing a robust wake detection method. To detect objects the sonar images is normalized then segmented based on fixed threshold. Next, the centroids of the segments are found and clustered based on distance metric. Then to track the objects linear Kalman filter is applied. To reduce effect of noise and creation of false tracks, the Kalman tracker is fine tuned. The tuning is done based on our active sonar specifications. After the tracks are initialed and updated they are subjected to a filtering stage to eliminate the noisy and unstable tracks. Also to eliminate object with a speed out of the diver speed range such as buoys and fast boats. Afterwards the result tracks are subjected to a classification stage to deiced the type of the object been tracked. Here the classification stage is to deice wither if the tracked object is an open circuit diver or a close circuit diver. At the classification stage, a small area around the object is extracted and a novel wake detection method is applied. The morphological features of the object with his wake is extracted. We used support vector machine to find the best classifier. The sonar training images and the test images are collected by ARMELSAN Defense Technologies Company using the portable diver detection sonar ARAS-2023. After applying the algorithm to the test sonar data, we get fine and stable tracks of the divers. The total classification accuracy achieved with the diver type is 97%.

Keywords: harbor protection, diver detection, active sonar, wake detection, diver classification

Procedia PDF Downloads 238

Authors: Nastaran Moosavi, Mohammad Mokhtari

Abstract:

Seismic inversion is a technique which has been in use for years and its main goal is to estimate and to model physical characteristics of rocks and fluids. Generally, it is a combination of seismic and well-log data. Seismic inversion can be carried out through different methods; we have conducted and compared post-stack and pre- stack seismic inversion methods on real data in one of the fields in the Persian Gulf. Pre-stack seismic inversion can transform seismic data to rock physics such as P-impedance, S-impedance and density. While post- stack seismic inversion can just estimate P-impedance. Then these parameters can be used in reservoir identification. Based on the results of inverting seismic data, a gas reservoir was detected in one of Hydrocarbon oil fields in south of Iran (Persian Gulf). By comparing post stack and pre-stack seismic inversion it can be concluded that the pre-stack seismic inversion provides a more reliable and detailed information for identification and prediction of hydrocarbon reservoirs.

Keywords: density, p-impedance, s-impedance, post-stack seismic inversion, pre-stack seismic inversion

Procedia PDF Downloads 324

Authors: Fouzi Harrou, Ying Sun, Sofiane Khadraoui

Abstract:

Anomaly detection based on Principal Component Analysis (PCA) was studied intensively and largely applied to multivariate processes with highly cross-correlated process variables. Monitoring metrics such as the Hotelling's T2 and the Q statistics are usually used in PCA-based monitoring to elucidate the pattern variations in the principal and residual subspaces, respectively. However, these metrics are ill suited to detect small faults. In this paper, the Exponentially Weighted Moving Average (EWMA) based on the Q and T statistics, T2-EWMA and Q-EWMA, were developed for detecting faults in the process mean. The performance of the proposed methods was compared with that of the conventional PCA-based fault detection method using synthetic data. The results clearly show the benefit and the effectiveness of the proposed methods over the conventional PCA method, especially for detecting small faults in highly correlated multivariate data.

Keywords: data-driven method, process control, anomaly detection, dimensionality reduction

Procedia PDF Downloads 299

Authors: Elaheh Talebi, Fariba Yavari, Lucy Philip, Lesley Town

Abstract:

The mining industry generates vast amounts of data, necessitating robust data management systems and advanced analytics tools to achieve better decision-making processes in the development of mining production and maintaining safety. This paper highlights the advantages of Power BI, a powerful intelligence tool, over traditional Excel-based approaches for effectively managing and harnessing mining data. Power BI enables professionals to connect and integrate multiple data sources, ensuring real-time access to up-to-date information. Its interactive visualizations and dashboards offer an intuitive interface for exploring and analyzing geotechnical data. Advanced analytics is a collection of data analysis techniques to improve decision-making. Leveraging some of the most complex techniques in data science, advanced analytics is used to do everything from detecting data errors and ensuring data accuracy to directing the development of future project phases. However, while Power BI is a robust tool, specific visualizations required by geotechnical engineers may have limitations. This paper studies the capability to use Python or R programming within the Power BI dashboard to enable advanced analytics, additional functionalities, and customized visualizations. This dashboard provides comprehensive tools for analyzing and visualizing key geotechnical data metrics, including spatial representation on maps, field and lab test results, and subsurface rock and soil characteristics. Advanced visualizations like borehole logs and Stereonet were implemented using Python programming within the Power BI dashboard, enhancing the understanding and communication of geotechnical information. Moreover, the dashboard's flexibility allows for the incorporation of additional data and visualizations based on the project scope and available data, such as pit design, rock fall analyses, rock mass characterization, and drone data. This further enhances the dashboard's usefulness in future projects, including operation, development, closure, and rehabilitation phases. Additionally, this helps in minimizing the necessity of utilizing multiple software programs in projects. This geotechnical dashboard in Power BI serves as a user-friendly solution for analyzing, visualizing, and communicating both new and historical geotechnical data, aiding in informed decision-making and efficient project management throughout various project stages. Its ability to generate dynamic reports and share them with clients in a collaborative manner further enhances decision-making processes and facilitates effective communication within geotechnical projects in the mining industry.

Keywords: geotechnical data analysis, power BI, visualization, decision-making, mining industry

Procedia PDF Downloads 92

Authors: A. Azari, S. S. K. Seyyedi

Abstract:

One of the unaddressed and open challenges in the nano-networking is the characteristics of noise. The previous analysis, however, has concentrated on end-to-end communication model with no separate modelings for propagation channel and noise. By considering a separate signal propagation and noise model, the design and implementation of an optimum receiver will be much easier. In this paper, we justify consideration of a separate additive Gaussian noise model of a nano-communication system based on the molecular communication channel for which are applicable for MSK and MOSK modulation schemes. The presented noise analysis is based on the Brownian motion process, and advection molecular statistics, where the received random signal has a probability density function whose mean is equal to the mean number of the received molecules. Finally, the justification of received signal magnitude being uncorrelated with additive non-stationary white noise is provided.

Keywords: molecular, noise, diffusion, channel

Procedia PDF Downloads 279