Search results for: data infrastructure
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 26549

Search results for: data infrastructure

24899 Classification of Poverty Level Data in Indonesia Using the Naïve Bayes Method

Authors: Anung Style Bukhori, Ani Dijah Rahajoe

Abstract:

Poverty poses a significant challenge in Indonesia, requiring an effective analytical approach to understand and address this issue. In this research, we applied the Naïve Bayes classification method to examine and classify poverty data in Indonesia. The main focus is on classifying data using RapidMiner, a powerful data analysis platform. The analysis process involves data splitting to train and test the classification model. First, we collected and prepared a poverty dataset that includes various factors such as education, employment, and health..The experimental results indicate that the Naïve Bayes classification model can provide accurate predictions regarding the risk of poverty. The use of RapidMiner in the analysis process offers flexibility and efficiency in evaluating the model's performance. The classification produces several values to serve as the standard for classifying poverty data in Indonesia using Naive Bayes. The accuracy result obtained is 40.26%, with a moderate recall result of 35.94%, a high recall result of 63.16%, and a low recall result of 38.03%. The precision for the moderate class is 58.97%, for the high class is 17.39%, and for the low class is 58.70%. These results can be seen from the graph below.

Keywords: poverty, classification, naïve bayes, Indonesia

Procedia PDF Downloads 65
24898 Web Search Engine Based Naming Procedure for Independent Topic

Authors: Takahiro Nishigaki, Takashi Onoda

Abstract:

In recent years, the number of document data has been increasing since the spread of the Internet. Many methods have been studied for extracting topics from large document data. We proposed Independent Topic Analysis (ITA) to extract topics independent of each other from large document data such as newspaper data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis. The topic represented by ITA is represented by a set of words. However, the set of words is quite different from the topics the user imagines. For example, the top five words with high independence of a topic are as follows. Topic1 = {"scor", "game", "lead", "quarter", "rebound"}. This Topic 1 is considered to represent the topic of "SPORTS". This topic name "SPORTS" has to be attached by the user. ITA cannot name topics. Therefore, in this research, we propose a method to obtain topics easy for people to understand by using the web search engine, topics given by the set of words given by independent topic analysis. In particular, we search a set of topical words, and the title of the homepage of the search result is taken as the topic name. And we also use the proposed method for some data and verify its effectiveness.

Keywords: independent topic analysis, topic extraction, topic naming, web search engine

Procedia PDF Downloads 124
24897 Extracting Terrain Points from Airborne Laser Scanning Data in Densely Forested Areas

Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

Abstract:

Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: airborne laser scanning, digital terrain models, filtering, forested areas

Procedia PDF Downloads 142
24896 Estimating the Life-Distribution Parameters of Weibull-Life PV Systems Utilizing Non-Parametric Analysis

Authors: Saleem Z. Ramadan

Abstract:

In this paper, a model is proposed to determine the life distribution parameters of the useful life region for the PV system utilizing a combination of non-parametric and linear regression analysis for the failure data of these systems. Results showed that this method is dependable for analyzing failure time data for such reliable systems when the data is scarce.

Keywords: masking, bathtub model, reliability, non-parametric analysis, useful life

Procedia PDF Downloads 564
24895 Urban Ecotourism Development in Borderlands: An Exploratory Study of Xishuangbanna Dai Autonomous Prefecture, China

Authors: Min Liu, Thanapauge Chamaratana

Abstract:

Integrating ecotourism into urban borderlands holds significant potential for promoting sustainable development, enhancing cross-border cooperation, and preserving cultural and natural heritage. This study aims to evaluate the current status and strategic measures for sustainable ecotourism development in the border urban areas of Xishuangbanna, leveraging the unique opportunities and challenges presented by its policy and geographical location. Employing a qualitative research approach, the exploratory study utilizes documentary research, observation, and in-depth interviews with 20 key stakeholders, including local government officials, tourism operators, community members, and tourists. Content analysis is conducted to interpret the collected data. The findings reveal that Xishuangbanna holds significant potential for ecotourism due to its rich biodiversity, cultural heritage, and strategic location along the Belt and Road Initiative route. The integration of ecotourism can drive economic growth, create employment opportunities, and foster a deeper appreciation for conservation efforts. By promoting ecotourism practices, the region can attract environmentally conscious travelers, thereby contributing to global sustainability goals. However, challenges such as inadequate infrastructure, limited community involvement, and environmental concerns are also identified. The study recommends enhancing ecotourism development in urban borderlands through integrated planning, stakeholder collaboration, and sustainable practices. These measures are essential to ensure long-term benefits for both the local community and the environment. Moreover, the study underscores the importance of a holistic approach to ecotourism development, which balances economic, social, and environmental priorities to achieve sustainable outcomes for urban borderlands.

Keywords: ecotourism, sustainable tourism, urban, borderland

Procedia PDF Downloads 34
24894 Preliminary Design of Maritime Energy Management System: Naval Architectural Approach to Resolve Recent Limitations

Authors: Seyong Jeong, Jinmo Park, Jinhyoun Park, Boram Kim, Kyoungsoo Ahn

Abstract:

Energy management in the maritime industry is being required by economics and in conformity with new legislative actions taken by the International Maritime Organization (IMO) and the European Union (EU). In response, the various performance monitoring methodologies and data collection practices have been examined by different stakeholders. While many assorted advancements in operation and technology are applicable, their adoption in the shipping industry stays small. This slow uptake can be considered due to many different barriers such as data analysis problems, misreported data, and feedback problems, etc. This study presents a conceptual design of an energy management system (EMS) and proposes the methodology to resolve the limitations (e.g., data normalization using naval architectural evaluation, management of misrepresented data, and feedback from shore to ship through management of performance analysis history). We expect this system to make even short-term charterers assess the ship performance properly and implement sustainable fleet control.

Keywords: data normalization, energy management system, naval architectural evaluation, ship performance analysis

Procedia PDF Downloads 452
24893 Geospatial Data Complexity in Electronic Airport Layout Plan

Authors: Shyam Parhi

Abstract:

Airports GIS program collects Airports data, validate and verify it, and stores it in specific database. Airports GIS allows authorized users to submit changes to airport data. The verified data is used to develop several engineering applications. One of these applications is electronic Airport Layout Plan (eALP) whose primary aim is to move from paper to digital form of ALP. The first phase of development of eALP was completed recently and it was tested for a few pilot program airports across different regions. We conducted gap analysis and noticed that a lot of development work is needed to fine tune at least six mandatory sheets of eALP. It is important to note that significant amount of programming is needed to move from out-of-box ArcGIS to a much customized ArcGIS which will be discussed. The ArcGIS viewer capability to display essential features like runway or taxiway or the perpendicular distance between them will be discussed. An enterprise level workflow which incorporates coordination process among different lines of business will be highlighted.

Keywords: geospatial data, geology, geographic information systems, aviation

Procedia PDF Downloads 421
24892 Anisotropic Total Fractional Order Variation Model in Seismic Data Denoising

Authors: Jianwei Ma, Diriba Gemechu

Abstract:

In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

Procedia PDF Downloads 211
24891 Research on the Mode and Strategy of Urban Renewal in the Old Urban Area of China: A Case Study of Chongqing City

Authors: Sun Ailu, Zhao Wanmin

Abstract:

In the process of rapid urbanization, old urban renewal is an important task in China's urban construction. This study, using status survey and Analytic Hierarchy Process (AHP) method, taking Chongqing of China as an example, puts forward the problems faced by the old urban area from the aspects of function, facilities and environment. Further, this study summarizes the types of the old urban area and proposes space renewal strategies for three typical old urban areas, such as old residential area, old factory and old market. These old urban areas are confronted with the problems of functional layout confounding, lack of infrastructure and poor living environment. At last, this paper proposes spatial strategies for urban renewal, which are hoped to be useful for urban renewal management in China.

Keywords: old urban renewal, renewal mode, renewal strategy, Chongqing, China

Procedia PDF Downloads 189
24890 NSBS: Design of a Network Storage Backup System

Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

Abstract:

The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

Procedia PDF Downloads 463
24889 A t-SNE and UMAP Based Neural Network Image Classification Algorithm

Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

Abstract:

Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

Procedia PDF Downloads 204
24888 Advancing Sustainable Seawater Desalination Technologies: Exploring the Sub-Atmospheric Vapor Pipeline (SAVP) and Energy-Efficient Solution for Urban and Industrial Water Management in Smart, Eco-Friendly, and Green Building Infrastructure

Authors: Mona Shojaei

Abstract:

The Sub-Atmospheric Vapor Pipeline (SAVP) introduces a distinct approach to seawater desalination with promising applications in both land and industrial sectors. SAVP systems exploit the temperature difference between a hot source and a cold environment to facilitate efficient vapor transfer, offering substantial benefits in diverse industrial and field applications. This approach incorporates dynamic boundary conditions, where the temperatures of hot and cold sources vary over time, particularly in natural and industrial environments. Such variations critically influence convection and diffusion processes, introducing challenges that require the refinement of the convection-diffusion equation and the derivation of temperature profiles along the pipeline through advanced engineering mathematics. This study formulates vapor temperature as a function of time and length using two mathematical approaches: Eigen functions and Green’s equation. Combining detailed theoretical modeling, mathematical simulations, and extensive field and industrial tests, this research underscores the SAVP system’s scalability for real-world applications. Results reveal a high degree of accuracy, highlighting SAVP’s significant potential for energy conservation and environmental sustainability. Furthermore, the integration of SAVP technology within smart and green building systems creates new opportunities for sustainable urban water management. By capturing and repurposing vapor for non-potable uses such as irrigation, greywater recycling, and ecosystem support in green spaces, SAVP aligns with the principles of smart and green buildings. Smart buildings emphasize efficient resource management, enhanced system control, and automation for optimal energy and water use, while green buildings prioritize environmental impact reduction and resource conservation. SAVP technology bridges both paradigms, enhancing water self-sufficiency and reducing reliance on external water supplies. The sustainable and energy-efficient properties of SAVP make it a vital component in resilient infrastructure development, addressing urban water scarcity while promoting eco-friendly living. This dual alignment with smart and green building goals positions SAVP as a transformative solution in the pursuit of sustainable urban resource management.

Keywords: sub-atmospheric vapor pipeline, seawater desalination, energy efficiency, vapor transfer dynamics, mathematical modeling, sustainable water solutions, smart buildings

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24887 An Online Adaptive Thresholding Method to Classify Google Trends Data Anomalies for Investor Sentiment Analysis

Authors: Duygu Dere, Mert Ergeneci, Kaan Gokcesu

Abstract:

Google Trends data has gained increasing popularity in the applications of behavioral finance, decision science and risk management. Because of Google’s wide range of use, the Trends statistics provide significant information about the investor sentiment and intention, which can be used as decisive factors for corporate and risk management fields. However, an anomaly, a significant increase or decrease, in a certain query cannot be detected by the state of the art applications of computation due to the random baseline noise of the Trends data, which is modelled as an Additive white Gaussian noise (AWGN). Since through time, the baseline noise power shows a gradual change an adaptive thresholding method is required to track and learn the baseline noise for a correct classification. To this end, we introduce an online method to classify meaningful deviations in Google Trends data. Through extensive experiments, we demonstrate that our method can successfully classify various anomalies for plenty of different data.

Keywords: adaptive data processing, behavioral finance , convex optimization, online learning, soft minimum thresholding

Procedia PDF Downloads 174
24886 The Role of Financial and Non-Financial Institutions in Promoting Entrepreneurship in Micro small and Medium Enterprises

Authors: Lemuel David

Abstract:

The importance of the Micro, Small, and Medium Enterprises sector is well recognized for its legitimate contribution to the Macroeconomic objectives of the Republic of Liberia, like generation of employment, input t, exports, and enhancing entrepreneurship. Right now, Medium and Small enterprises accounts for about 99 percent of the industrial units in the country, contributing 60 percent of the manufacturing sector output and approximately one-third of the nation’s exports. The role of various financial institutions like ECO bank and Non-financial Institutions like Bearch Limited support promoting the growth of Micro, Small, and Medium Enterprises is unique. A small enterprise or entrepreneur gets many types of assistance from different institutions for varied purposes in the course of his entrepreneurial journey. This paper focuses on the factors related to financial institutional support and non-financial institutional support entrepreneurs to the growth of Medium and Small enterprises in the Republic of Liberia. The significance of this paper is to support Policy and Institutional Support for Medium and Small enterprises to know the views of entrepreneurs about financial and non-financial support systems in the Republic of Liberia. This study was carried out through a survey method, with the use of questionnaires. The population for this study consisted of all registered Medium and Small enterprises which have been registered during the years 2004-2014 in the republic of Liberia. The sampling method employed for this study was a simple random technique and determined a sample size of 400. Data for the study was collected using a standard questionnaire. The questionnaire consisted of two parts: the first part consisted of questions on the profile of the respondents. The second part covers (1) financial, promotional factors and (2) non-financial promotional factors. The results of the study are based on financial and non-financial supporting activities provided by institutions to Medium and Small enterprises. After investigation, it has been found that there is no difference in the support given by Financial Institutions and non-financial Institutions. Entrepreneurs perceived “collateral-free schemes and physical infrastructure support factors are highest contributing to entry and growth of Medium and Small enterprises.

Keywords: micro, small, and medium enterprises financial institutions, entrepreneurship

Procedia PDF Downloads 106
24885 Optimisation of the Hydrometeorological-Hydrometric Network: A Case Study in Greece

Authors: E. Baltas, E. Feloni, G. Bariamis

Abstract:

The operation of a network of hydrometeorological-hydrometric stations is basic infrastructure for the management of water resources, as well as, for flood protection. The assessment of water resources potential led to the necessity of adoption management practices including a multi-criteria analysis for the optimum design of the region’s station network. This research work aims at the optimisation of a new/existing network, using GIS methods. The planning of optimum network stations is based on the guidelines of international organizations such as World Meteorological Organization (WMO). The uniform spatial distribution of the stations, the drainage basin for the hydrometric stations and criteria concerning the low terrain slope, the accessibility to the stations and proximity to hydrological interest sites, were taken into consideration for its development. The abovementioned methodology has been implemented for two different areas the Florina municipality and the Argolis area in Greece, and comparison of the results has been conducted.

Keywords: GIS, hydrometeorological, hydrometric, network, optimisation

Procedia PDF Downloads 291
24884 Enhanced Weighted Centroid Localization Algorithm for Indoor Environments

Authors: I. Nižetić Kosović, T. Jagušt

Abstract:

Lately, with the increasing number of location-based applications, demand for highly accurate and reliable indoor localization became urgent. This is a challenging problem, due to the measurement variance which is the consequence of various factors like obstacles, equipment properties and environmental changes in complex nature of indoor environments. In this paper we propose low-cost custom-setup infrastructure solution and localization algorithm based on the Weighted Centroid Localization (WCL) method. Localization accuracy is increased by several enhancements: calibration of RSSI values gained from wireless nodes, repetitive measurements of RSSI to exclude deviating values from the position estimation, and by considering orientation of the device according to the wireless nodes. We conducted several experiments to evaluate the proposed algorithm. High accuracy of ~1m was achieved.

Keywords: indoor environment, received signal strength indicator, weighted centroid localization, wireless localization

Procedia PDF Downloads 237
24883 Energy Efficient Assessment of Energy Internet Based on Data-Driven Fuzzy Integrated Cloud Evaluation Algorithm

Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu

Abstract:

Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.

Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model

Procedia PDF Downloads 207
24882 China's Health Diplomacy in Africa

Authors: Wanda Luen-Wun Siu, Xiaowen Zhang

Abstract:

The outbreak of the COVID-19 epidemic has caused great difficulties for South-South cooperation, but there are also opportunities. China’s health diplomacy has changed from dispatching medical teams, assisting in the construction of hospitals, and encouraging medical investment in the Africa health sector. This paper adopted a retrospective review of China’s health diplomacy in Africa from 1963 to 2020. Findings suggested that China has a preference for aiding Africa health infrastructure and sending medical teams to African countries. China’s health diplomacy in Africa is a success and has established secure diplomatic relations with African countries, thanks to the medical and health assistance to Africa over 60 years. This research contributes to the literature of health diplomacy and foreign relations and indicates that China’s health aid has fostered cooperation at the medical and diplomatic levels.

Keywords: Africa, china’s health diplomacy, COVID-19, bilateral relations

Procedia PDF Downloads 230
24881 Graph Based Traffic Analysis and Delay Prediction Using a Custom Built Dataset

Authors: Gabriele Borg, Alexei Debono, Charlie Abela

Abstract:

There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale. Furthermore, a series of traffic prediction graph neural network models are conducted to compare MalTra to large-scale traffic datasets.

Keywords: graph neural networks, traffic management, big data, mobile data patterns

Procedia PDF Downloads 138
24880 Learning Compression Techniques on Smart Phone

Authors: Farouk Lawan Gambo, Hamada Mohammad

Abstract:

Data compression shrinks files into fewer bits than their original presentation. It has more advantage on the internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature, therefore, making them difficult to digest by some students (engineers in particular). This paper studies the learning preference of engineering students who tend to have strong, active, sensing, visual and sequential learning preferences, the paper also studies the three shift of technology-aided that learning has experienced, which mobile learning has been considered to be the feature of learning that will integrate other form of the education process. Lastly, we propose a design and implementation of mobile learning application using software engineering methodology that will enhance the traditional teaching and learning of data compression techniques.

Keywords: data compression, learning preference, mobile learning, multimedia

Procedia PDF Downloads 454
24879 Investigation of Delivery of Triple Play Services

Authors: Paramjit Mahey, Monica Sharma, Jasbinder Singh

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 544
24878 Nazca: A Context-Based Matching Method for Searching Heterogeneous Structures

Authors: Karine B. de Oliveira, Carina F. Dorneles

Abstract:

The structure level matching is the problem of combining elements of a structure, which can be represented as entities, classes, XML elements, web forms, and so on. This is a challenge due to large number of distinct representations of semantically similar structures. This paper describes a structure-based matching method applied to search for different representations in data sources, considering the similarity between elements of two structures and the data source context. Using real data sources, we have conducted an experimental study comparing our approach with our baseline implementation and with another important schema matching approach. We demonstrate that our proposal reaches higher precision than the baseline.

Keywords: context, data source, index, matching, search, similarity, structure

Procedia PDF Downloads 366
24877 Spatially Random Sampling for Retail Food Risk Factors Study

Authors: Guilan Huang

Abstract:

In 2013 and 2014, the U.S. Food and Drug Administration (FDA) collected data from selected fast food restaurants and full service restaurants for tracking changes in the occurrence of foodborne illness risk factors. This paper discussed how we customized spatial random sampling method by considering financial position and availability of FDA resources, and how we enriched restaurants data with location. Location information of restaurants provides opportunity for quantitatively determining random sampling within non-government units (e.g.: 240 kilometers around each data-collector). Spatial analysis also could optimize data-collectors’ work plans and resource allocation. Spatial analytic and processing platform helped us handling the spatial random sampling challenges. Our method fits in FDA’s ability to pinpoint features of foodservice establishments, and reduced both time and expense on data collection.

Keywords: geospatial technology, restaurant, retail food risk factor study, spatially random sampling

Procedia PDF Downloads 352
24876 Slovenian Spatial Legislation over Time and Its Issues

Authors: Andreja Benko

Abstract:

Article presents a short overview of the architects’ profession over time with outlined work of the architectural theoreticians. In the continuation is described a former affiliation of Slovenia as well as the spatial planning documents that were in use until the Slovenia joint Yugoslavia (last part in 1919). This legislation from former Austro-Hungarian monarchy was valid almost until 1950 in some parts of Yugoslavia even longer. Upon that will be mentioned some valid Slovenian spatial documents which will be compared with the German legislation. Analysed will be the number of architect and spatial planners in Slovenia and also their number upon certain region in Slovenia. Based on that will be given also the number from statistical office of Slovenia of the number of buildings between years 2007 and 2012, and described also the collapse of the major construction companies in Slovenia and consequences of that. At the end will be outlined the morality and ethics by spatial interventions and lack of the architectural law in Slovenia as well as the problematic of minimal collaboration between the Ministry of infrastructure and spatial planning with the profession.

Keywords: architect, history, legislation, Slovenia

Procedia PDF Downloads 366
24875 Automatic MC/DC Test Data Generation from Software Module Description

Authors: Sekou Kangoye, Alexis Todoskoff, Mihaela Barreau

Abstract:

Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that is highly recommended or required for safety-critical software coverage. Therefore, many testing standards include this criterion and require it to be satisfied at a particular level of testing (e.g. validation and unit levels). However, an important amount of time is needed to meet those requirements. In this paper we propose to automate MC/DC test data generation. Thus, we present an approach to automatically generate MC/DC test data, from software module description written over a dedicated language. We introduce a new merging approach that provides high MC/DC coverage for the description, with only a little number of test cases.

Keywords: domain-specific language, MC/DC, test data generation, safety-critical software coverage

Procedia PDF Downloads 448
24874 Blockchain-Based Approach on Security Enhancement of Distributed System in Healthcare Sector

Authors: Loong Qing Zhe, Foo Jing Heng

Abstract:

A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.

Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)

Procedia PDF Downloads 196
24873 Demographic Factors Influencing Employees’ Salary Expectations and Labor Turnover

Authors: M. Osipova

Abstract:

Thanks to informational technologies development every sphere of economics is becoming more and more data-centralized as people are generating huge datasets containing information on any aspect of their life. Applying research of such data to human resources management allows getting scarce statistics on labor market state including salary expectations and potential employees’ typical career behavior, and this information can become a reliable basis for management decisions. The following article presents results of career behavior research based on freely accessible resume data. Information used for study is much wider than one usually uses in human resources surveys. That is why there is enough data for statistically significant results even for subgroups analysis.

Keywords: human resources management, salary expectations, statistics, turnover

Procedia PDF Downloads 357
24872 Developing a Sustainable Business Model for Platform-Based Applications in Small and Medium-Sized Enterprise Sawmills: A Systematic Approach

Authors: Franziska Mais, Till Gramberg

Abstract:

The paper presents the development of a sustainable business model for a platform-based application tailored for sawing companies in small and medium-sized enterprises (SMEs). The focus is on the integration of sustainability principles into the design of the business model to ensure a technologically advanced, legally sound, and economically efficient solution. Easy2IoT is a research project that aims to enable companies in the prefabrication sheet metal and sheet metal processing industry to enter the Industrial Internet of Things (IIoT) with a low-threshold and cost-effective approach. The methodological approach of Easy2IoT includes an in-depth requirements analysis and customer interviews with stakeholders along the value chain. Based on these insights, actions, requirements, and potential solutions for smart services are derived. The structuring of the business ecosystem within the application plays a central role, whereby the roles of the partners, the management of the IT infrastructure and services, as well as the design of a sustainable operator model are considered. The business model is developed using the value proposition canvas, whereby a detailed analysis of the requirements for the business model is carried out, taking sustainability into account. This includes coordination with the business model patterns, according to Gassmann, and integration into a business model canvas for the Easy2IoT product. Potential obstacles and problems are identified and evaluated in order to formulate a comprehensive and sustainable business model. In addition, sustainable payment models and distribution channels are developed. In summary, the article offers a well-founded insight into the systematic development of a sustainable business model for platform-based applications in SME sawmills, with a particular focus on the synergy of ecological responsibility and economic efficiency.

Keywords: business model, sustainable business model, IIoT, IIoT-platform, industrie 4.0, big data

Procedia PDF Downloads 90
24871 Exploring Electroactive Polymers for Dynamic Data Physicalization

Authors: Joanna Dauner, Jan Friedrich, Linda Elsner, Kora Kimpel

Abstract:

Active materials such as Electroactive Polymers (EAPs) are promising for the development of novel shape-changing interfaces. This paper explores the potential of EAPs in a multilayer unimorph structure from a design perspective to investigate the visual qualities of the material for dynamic data visualization and data physicalization. We discuss various concepts of how the material can be used for this purpose. Multilayer unimorph EAPs are of particular interest to designers because they can be easily prototyped using everyday materials and tools. By changing the structure and geometry of the EAPs, their movement and behavior can be modified. We present the results of our preliminary user testing, where we evaluated different movement patterns. As a result, we introduce a prototype display built with EAPs for dynamic data physicalization. Finally, we discuss the potentials and drawbacks and identify further open research questions for the design discipline.

Keywords: electroactive polymer, shape-changing interfaces, smart material interfaces, data physicalization

Procedia PDF Downloads 104
24870 Analysis of the Factors Affecting the Public Bicycle Projects in Chinese Cities

Authors: Xiujuan Wang, Weiguo Wang, Lei Yu, Xue Liu

Abstract:

There are many purported benefits of public bike systems, therefore, it has seen a sharp increase since 2008 in Hangzhou, China. However, there are few studies on the public bicycle system in Chinese cities. In order to make recommendations for the development of public bicycle systems, this paper analyzes the influencing factors by using the system dynamics method according to the main characteristics of Chinese cities. The main characteristics of Chinese cities lie in the city size and process of urbanization, traffic mode division, demographic characteristics, bicycle infrastructure and right of way, regime structure. Finally, under the context of Chinese bike sharing systems, these analyses results can help to design some feasible strategies for the planner to the development of the public bicycles.

Keywords: engineering of communication and transportation system, bicycle, public bike, characteristics of Chinese cities, system dynamics

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