Search results for: link data

Authors: Weiliang Wen, Xinyu Guo, Ying Zhang, Jianjun Du, Boxiang Xiao

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Reconstructing and analyzing three-dimensional (3D) models from situ measured data is important for a number of researches and applications in plant science, including plant phenotyping, functional-structural plant modeling (FSPM), plant germplasm resources protection, agricultural technology popularization. It has many scales like cell, tissue, organ, plant and canopy from micro to macroscopic. The techniques currently used for data capture, feature analysis, and 3D reconstruction are quite different of different scales. In this context, morphological data acquisition, 3D analysis and modeling of plants on different scales are introduced systematically. The commonly used data capture equipment for these multiscale is introduced. Then hot issues and difficulties of different scales are described respectively. Some examples are also given, such as Micron-scale phenotyping quantification and 3D microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning, 3D reconstruction of leaf surfaces and feature extraction from point cloud acquired by using 3D handheld scanner, plant modeling by combining parameter driven 3D organ templates. Several application examples by using the 3D models and analysis results of plants are also introduced. A 3D maize canopy was constructed, and light distribution was simulated within the canopy, which was used for the designation of ideal plant type. A grape tree model was constructed from 3D digital and point cloud data, which was used for the production of science content of 11th international conference on grapevine breeding and genetics. By using the tissue models of plants, a Google glass was used to look around visually inside the plant to understand the internal structure of plants. With the development of information technology, 3D data acquisition, and data processing techniques will play a greater role in plant science.

Keywords: plant, three dimensional modeling, multi-scale, plant phenotyping, three dimensional data acquisition

Procedia PDF Downloads 278

Authors: Farzad Khajavi

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Studies about the interaction between active pharmaceutical ingredients (API) and excipients are so important in the pre-formulation stage of development of all dosage forms. Analytical techniques such as differential scanning calorimetry (DSC), Thermal gravimetry (TG), and Furrier transform infrared spectroscopy (FTIR) are commonly used tools for investigating regarding compatibility and incompatibility of APIs with excipients. Sometimes the interpretation of data obtained from these techniques is difficult because of severe overlapping of API spectrum with excipients in their mixtures. Principal component analysis (PCA) as a powerful factor analytical method is used in these situations to resolve data matrices acquired from these analytical techniques. Binary mixtures of API and interested excipients are considered and produced. Peaks of FTIR, DSC, or TG of pure API and excipient and their mixtures at different mole ratios will construct the rows of the data matrix. By applying PCA on the data matrix, the number of principal components (PCs) is determined so that it contains the total variance of the data matrix. By plotting PCs or factors obtained from the score of the matrix in two-dimensional spaces if the pure API and its mixture with the excipient at the high amount of API and the 1:1mixture form a separate cluster and the other cluster comprise of the pure excipient and its blend with the API at the high amount of excipient. This confirms the existence of compatibility between API and the interested excipient. Otherwise, the incompatibility will overcome a mixture of API and excipient.

Keywords: API, compatibility, DSC, TG, interactions

Procedia PDF Downloads 133

Authors: Rock-Hyun Choi, Won-Seok Kang, Chang-Sik Son

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Physical activity is important for healthy living. Recently wearable devices which motivate physical activity are quickly developing, and become cheaper and more comfortable. In particular, fitness trackers provide a variety of information and need to provide well-analyzed, and user-friendly results. In this study, frequency analysis was performed to classify various data sets of Fitbit into simple activity status. The data from Fitbit cloud server consists of 263 subjects who were healthy factory and office workers in Korea from March 7th to April 30th, 2016. In the results, we found assumptions of activity state classification seem to be sufficient and reasonable.

Keywords: activity status, fitness tracker, heart rate, steps

Procedia PDF Downloads 384

Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical analysis

Procedia PDF Downloads 48

Authors: Ebrahim Mansoori, Datin Joriah Muhammad

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Recent studies in finance have focused on the effect of external variables on working capital management. This study investigates the effect of corruption indexes on firms' working capital management. A large data set that covers data from 2005 to 2013 from five ASEAN countries, namely, Malaysia, Indonesia, Singapore, Thailand, and the Philippines, was selected to investigate how the level of corruption in these countries affect working capital management. The results of panel data analysis include fixed effect estimations showed that a high level of countries' corruption indexes encourages managers to shorten the CCC length. Meanwhile, the managers reduce the level of investment in cash and cash equivalents when the levels of corruption indexes increase. Therefore, increasing the level of countries' corruption indexes encourages managers to select conservative working capital strategies by reducing the level of NLB.

Keywords: ASEAN, corruption indexes, panel data analysis, working capital management

Procedia PDF Downloads 438

Authors: Mazharuddin Syed Ahmed

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This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

Procedia PDF Downloads 44

Authors: Akber Oumer Abdurezak

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Road traffic accident is a major problem in Ethiopia, resulting in the deaths of many people and potential injuries and crash every year and loss of properties. According to the Federal Transport Authority, one of the main causes of traffic accident and crash in Ethiopia is over speeding. Implementation of different technologies is used to monitor the speed of vehicles in order to minimize accidents and crashes. This research aimed at designing a speed monitoring system to monitor the speed of travelling vehicles and movements, reporting illegal speeds or overspeeding vehicles to the concerned bodies. The implementation of the system is through a wireless sensor network. The proposed system can sense and detect the movement of vehicles, process, and analysis the data obtained from the sensor and the cloud system. The data is sent to the central controlling server. The system contains accelerometer and gyroscope sensors to sense and collect the data of the vehicle. Arduino to process the data and Global System for Mobile Communication (GSM) module for communication purposes to send the data to the concerned body. When the speed of the vehicle exceeds the allowable speed limit, the system sends a message to database as “over speeding”. Both accelerometer and gyroscope sensors are used to collect acceleration data. The acceleration data then convert to speed, and the corresponding speed is checked with the speed limit, and those above the speed limit are reported to the concerned authorities to avoid frequent accidents. The proposed system decreases the occurrence of accidents and crashes due to overspeeding and can be used as an eye opener for the implementation of other intelligent transport system technologies. This system can also integrate with other technologies like GPS and Google Maps to obtain better output.

Keywords: accelerometer, IOT, GSM, gyroscope

Procedia PDF Downloads 75

Authors: Youngseok Kim, Chul Park, Jonghwa Yi, Sangsik Choi

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The 2-MHz Side Scan SONAR (SSS) attached to the boat for inspection of underwater structures is affected by shaking. It is difficult to determine the exact scale of damage of structure. In this study, a motion sensor is attached to the inside of the 2-MHz SSS to get roll, pitch, and yaw direction data, and developed the image stabilization tool to correct the sonar image. We checked that reliable data can be obtained with an average error rate of 1.99% between the measured value and the actual distance through experiment. It is possible to get the accurate sonar data to inspect damage in underwater structure.

Keywords: image stabilization, motion sensor, safety inspection, sonar image, underwater structure

Procedia PDF Downloads 280

Authors: K. Parandhama Gowd

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The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC)

Procedia PDF Downloads 574

Authors: Mouataz Zreika, Maria Estela Varua

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Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: clustering, force-directed, graph drawing, stock investment analysis

Procedia PDF Downloads 303

Authors: Manas Kotepui, Chatree Ratcha, Kwuntida Uthaisar

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Malaria infection is still to be considered a major public health problem in Thailand. This study, a retrospective data of patients in Surat Thani Province, Southern Thailand during 2012-2015 was retrieved and analyzed. These data include demographic data, clinical characteristics and laboratory diagnosis. Statistical analyses were performed to demonstrate the frequency, proportion, data tendency, and group comparisons. Total of 395 malaria patients were found. Most of patients were male (253 cases, 64.1%). Most of patients (262 cases, 66.3%) were admitted at 6 am-11.59 am of the day. Three hundred and fifty-five patients (97.5%) were positive with P. falciparum. Hemoglobin, hematocrit, and MCHC between P. falciparum and P. vivax were significant different (P value<0.05).During 2012-2015, prevalence of malaria was highest in 2013. Neutrophils, lymphocytes, and monocytes were significantly changed among patients with fever ≤ 3 days compared with patients with fever >3 days. This information will guide to understanding pathogenesis and characteristic of malaria infection in Sothern Thailand.

Keywords: prevalence, malaria, Surat Thani, Thailand

Procedia PDF Downloads 277

Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

Procedia PDF Downloads 443

Authors: Rizwan Rizwan

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This paper provides an overview of Federated Learning (FL) and its application in enhancing data security, privacy, and efficiency. FL utilizes three distinct architectures to ensure privacy is never compromised. It involves training individual edge devices and aggregating their models on a server without sharing raw data. This approach not only provides secure models without data sharing but also offers a highly efficient privacy--preserving solution with improved security and data access. Also we discusses various frameworks used in FL and its integration with machine learning, deep learning, and data mining. In order to address the challenges of multi--party collaborative modeling scenarios, a brief review FL scheme combined with an adaptive gradient descent strategy and differential privacy mechanism. The adaptive learning rate algorithm adjusts the gradient descent process to avoid issues such as model overfitting and fluctuations, thereby enhancing modeling efficiency and performance in multi-party computation scenarios. Additionally, to cater to ultra-large-scale distributed secure computing, the research introduces a differential privacy mechanism that defends against various background knowledge attacks.

Keywords: federated learning, differential privacy, gradient descent strategy, convergence, stability, threats

Procedia PDF Downloads 34

Authors: E. Asadollahi-Yazdi, J. Gardan, P. Lafon

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Nowadays, manufactures are encountered with production of different version of products due to quality, cost and time constraints. On the other hand, Additive Manufacturing (AM) as a production method based on CAD model disrupts the design and manufacturing cycle with new parameters. To consider these issues, the researchers utilized Design For Manufacturing (DFM) approach for AM but until now there is no integrated approach for design and manufacturing of product through the AM. So, this paper aims to provide a general methodology for managing the different production issues, as well as, support the interoperability with AM process and different Product Life Cycle Management tools. The problem is that the models of System Engineering which is used for managing complex systems cannot support the product evolution and its impact on the product life cycle. Therefore, it seems necessary to provide a general methodology for managing the product’s diversities which is created by using AM. This methodology must consider manufacture and assembly during product design as early as possible in the design stage. The latest approach of DFM, as a methodology to analyze the system comprehensively, integrates manufacturing constraints in the numerical model in upstream. So, DFM for AM is used to import the characteristics of AM into the design and manufacturing process of a hybrid product to manage the criteria coming from AM. Also, the research presents an integrated design method in order to take into account the knowledge of layers manufacturing technologies. For this purpose, the interface model based on the skin and skeleton concepts is provided, the usage and manufacturing skins are used to show the functional surface of the product. Also, the material flow and link between the skins are demonstrated by usage and manufacturing skeletons. Therefore, this integrated approach is a helpful methodology for designer and manufacturer in different decisions like material and process selection as well as, evaluation of product manufacturability.

Keywords: additive manufacturing, 3D printing, design for manufacturing, integrated design, interoperability

Procedia PDF Downloads 316

Authors: Amir Rashid

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Today is the world of innovation and Cloud Computing is becoming a day to day technology with every passing day offering remarkable services and features on the go with rapid elasticity. This platform took business computing into an innovative dimension where clients interact and operate through service provider web portals. Initially, the trust relationship between client and service provider remained a big question but with the invention of several cryptographic paradigms, it is becoming common in everyday business. This research work proposes a solution for building a cloud storage service with respect to Data Security addressing public cloud infrastructure where the trust relationship matters a lot between client and service provider. For the great satisfaction of client regarding high-end Data Security, this research paper propose a layer of cryptographic primitives combining several architectures in order to achieve the goal. A survey has been conducted to determine the benefits for such an architecture would provide to both clients/service providers and recent developments in cryptography specifically by cloud storage.

Keywords: data security in cloud computing, cloud storage architecture, cryptographic developments, token key

Procedia PDF Downloads 296

Authors: Shivi Agarwal, Trilok Mathur

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This paper proposes the method to measure the total factor productivity (TFP) change by credibility theory for fuzzy input and output variables. Total factor productivity change has been widely studied with crisp input and output variables, however, in some cases, input and output data of decision-making units (DMUs) can be measured with uncertainty. These data can be represented as linguistic variable characterized by fuzzy numbers. Malmquist productivity index (MPI) is widely used to estimate the TFP change by calculating the total factor productivity of a DMU for different time periods using data envelopment analysis (DEA). The fuzzy DEA (FDEA) model is solved using the credibility theory. The results of FDEA is used to measure the TFP change for fuzzy input and output variables. Finally, numerical examples are presented to illustrate the proposed method to measure the TFP change input and output variables. The suggested methodology can be utilized for performance evaluation of DMUs and help to assess the level of integration. The methodology can also apply to rank the DMUs and can find out the DMUs that are lagging behind and make recommendations as to how they can improve their performance to bring them at par with other DMUs.

Keywords: chance-constrained programming, credibility theory, data envelopment analysis, fuzzy data, Malmquist productivity index

Procedia PDF Downloads 368

Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: social media, text mining, knowledge discovery, predictive analysis, machine learning

Procedia PDF Downloads 426

Authors: Brayan S. Pabón, R. Ricardo Moreno, Edith Gonzalez

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Inside the wide Colombian natural fiber set is the banana stem leaf, known as Calceta de Plátano, which is a material present in several regions of the country and is a fiber extracted from the pseudo stem of the banana plant (Musa paradisiaca) as a regular maintenance process. Colombia had a production of 2.8 million tons in 2007 and 2008 corresponding to 8.2% of the international production, number that is growing. This material was selected to be studied because it is not being used by farmers due to it being perceived as a waste from the banana harvest and a propagation pest agent inside the planting. In addition, the Calceta does not have industrial applications in Colombia since there is not enough concrete knowledge that informs us about the properties of the material and the possible applications it could have. Based on this situation the industrial design is used as a link between the properties of the material and the need to transform it into industrial products for the market. Therefore, the project identifies potential design attributes that the banana stem leaf can have for product development. The methodology was divided into 2 main chapters: Methodology for the material recognition: -Data Collection, inquiring the craftsmen experience and bibliography. -Knowledge in practice, with controlled experiments and validation tests. -Creation of design attributes and material profile according to the knowledge developed. Moreover, the Design methodology: -Application fields selection, exploring the use of the attributes and the relation with product functions. -Evaluating the possible fields and selection of the optimum application. -Design Process with sketching, ideation, and product development. Different protocols were elaborated to qualitatively determine some material properties of the Calceta, and if they could be designated as design attributes. Once defined, performed and analyzed the validation protocols, 25 design attributes were identified and classified into 4 attribute categories (Environmental, Functional, Aesthetics and Technical) forming the material profile. Then, 15 application fields were defined based on the relation between functions of product and the use of the Calceta attributes. Those fields were evaluated to measure how much are being used the functional attributes. After fields evaluation, a final field was defined , influenced by traditional use of the fiber for packing food. As final result, two products were designed for this application field. The first one is the Multiple Container, which works to contain small or large-thin pieces of food, like potatoes chips or small sausages; it allows the consumption of food with sauces or dressings. The second is the Chorizo container, specifically designed for this food due to the long shape and the consumption mode. Natural fiber research allows the generation of a solider and a more complete knowledge about natural fibers. In addition, the research is a way to strengthen the identity through the investigation of the proper and autochthonous, allowing the use of national resources in a sustainable and creative way. Using divergent thinking and the design as a tool, this investigation can achieve advances in the natural fiber handling.

Keywords: banana stem leaf, Calceta de Plátano, design attributes, natural fibers, product design

Procedia PDF Downloads 260

Authors: Chien-Hung Liu, Yu-Fen Chen

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This study used triangular laser probe and three-axial direction mobile platform for surface measurement, programmed it and applied it to real-time analytic statistics of different measured data. This structure was used to design a system integration program: using triangular laser probe for scattering or reflection non-contact measurement, transferring the captured signals to the computer through RS-232, and using RS-485 to control the three-axis platform for a wide range of measurement. The data captured by the laser probe are formed into a 3D surface. This study constructed an optical measurement application program in the concept of visual programming language. First, the signals are transmitted to the computer through RS-232/RS-485, and then the signals are stored and recorded in graphic interface timely. This programming concept analyzes various messages, and makes proper presentation graphs and data processing to provide the users with friendly graphic interfaces and data processing state monitoring, and identifies whether the present data are normal in graphic concept. The major functions of the measurement system developed by this study are thickness measurement, SPC, surface smoothness analysis, and analytical calculation of trend line. A result report can be made and printed promptly. This study measured different heights and surfaces successfully, performed on-line data analysis and processing effectively, and developed a man-machine interface for users to operate.

Keywords: laser probe, non-contact measurement, triangulation measurement principle, statistical process control, labVIEW

Procedia PDF Downloads 360

Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

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Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

Procedia PDF Downloads 422

Authors: Xin-Yan Ji

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The historical failures data of the spacecraft is very useful to improve the spacecraft design and the test philosophies and reduce the spacecraft flight risk. A study of spacecraft failures data was performed, which is the most comprehensive statistics of spacecrafts in China. 2593 on-orbit failures data and 1298 ground data that occurred on 150 spacecraft launched from 2000 to 2016 were identified and collected, which covered the navigation satellites, communication satellites, remote sensing deep space exploration manned spaceflight platforms. In this paper, the failures were analyzed to compare different spacecraft subsystem and estimate their impact on the mission, then the development of spacecraft in China was evaluated from design, software, workmanship, management, parts, and materials. Finally, the lessons learned from the past years show that electrical and mechanical failures are responsible for the largest parts, and the key solution to reduce in-orbit failures is improving design technology, enough redundancy, adequate space environment protection measures, and adequate ground testing.

Keywords: spacecraft anomalies, anomalies mechanism, failure cause, spacecraft testing

Procedia PDF Downloads 118

Authors: Chin-Hsiang Chu

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This article review the literature in the field among the marketing and aesthetics, the current market and customer-oriented product sales, and gradually from the practical functionality, transformed into the visual appearance of the concept note and the importance of marketing experience substance 'economic Aesthetics' trend. How to introduce the concept of aesthetic and differentiate products have become an important content of marketing management in for an organization in marketing.In previous studies,marketing aesthetic related researches are rare.Therefore, the purpose of this study to explore the connection between aesthetics and marketing of the market economy, and aggregated content through literature review, trying to find related research implications for the management of marketing aesthetics, market-oriented and customer value and development of the product. In this study, the problem statement and background, the development of the theory of evolution, as well as methods and results of discovery stage, literature review was conducted to explore. The results found: (1) Study of Aesthetics will help deepen the shopping environment and service environment commonly understood. (2) the perceived value of products imported aesthetic, consumer willingness to buy, and even premium products will be more attractive. (3) marketing personnel for general marketing management with a high degree of aesthetic identity. (4) management in marketing aesthetics connotation, aesthetic characteristics of five elements is greatly valued by the real-time, complex, specificity, attract sexual and richness. (5) allows consumers to experience through the process due to stimulate the senses, the mind and thinking with the corporate brand or have a deeper link. Results of this study can be used as business in a competitive market, new product development and design of the guide.

Keywords: marketing aesthetics, aesthetics economic, aesthetic, experiential marketing

Procedia PDF Downloads 260

Authors: Salim Yusif

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Fiber optic technology has revolutionized telecommunications and data transmission, providing unmatched speed, bandwidth, and reliability. This paper presents the latest advancements in fiber optic technology, focusing on innovations in fiber materials, transmission techniques, and network architectures that enhance the performance of high-speed data transmission systems. Key advancements include the development of ultra-low-loss optical fibers, multi-core fibers, advanced modulation formats, and the integration of fiber optics into next-generation network architectures such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV). Additionally, recent developments in fiber optic sensors are discussed, extending the utility of optical fibers beyond data transmission. Through comprehensive analysis and experimental validation, this research offers valuable insights into the future directions of fiber optic technology, highlighting its potential to drive innovation across various industries.

Keywords: fiber optics, high-speed data transmission, ultra-low-loss optical fibers, multi-core fibers, modulation formats, coherent detection, software-defined networking, network function virtualization, fiber optic sensors

Procedia PDF Downloads 62

Authors: Lida Balilan, Dariush Sattarzadeh, Rana Koorepaz

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In the Ilkhanid era, the mystical school of Tabriz manifested itself as an art school in various aspects, including miniatures, architecture, urban planning and design, simultaneously with the expansion of the many sciences of its time. In this era, mysticism, both in form and in poetry and prose, as well as in works of art reached its peak. Mysticism, as an inner belief and thought, brought the audience to the artistic and aesthetical view using allegorical and symbolic expression of the religion and had a direct impact on the formation of the intellectual and cultural layers of the society. At the same time, Mystic school of Tabriz could create a symbolic and allegorical language to create magnificent works of architecture with the expansion of science in various fields and using various sciences such as mathematics, geometry, science of numbers and by Abjad letters. In this era, geometry is the middle link between mysticism and architecture and it is divided into two categories, including intellectual and sensory geometry and based on its function. Soltaniyeh dome is one of the prominent buildings of the Tabriz school with the shrine land use. In this article, information is collected using a historical-interpretive method and the results are analyzed using an analytical-comparative method. The results of the study suggest that the designers and builders of the Soltaniyeh dome have used shapes, colors, numbers, letters and words in the form of motifs, geometric patterns as well as lines and writings in levels and layers ranging from plans to decorations and arrays for architectural symbolization and encryption to express and transmit mystical ideas.

Keywords: geometry, Tabriz school, mystical thoughts, dome of Soltaniyeh

Procedia PDF Downloads 87

Authors: Nour Tawil, Sandra Weber, Kirsten K. Roessler, Martin Mau, Simone Kuhn

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The link between “quality” residential environments and human health and well-being has long been proposed. While the physical properties of a sound environment have been fairly defined, little focus has been given to the psychological impact of architectural elements. Recently, studies have investigated the response to architectural parameters, using measures of physiology, brain activity, and emotion. Results showed different aspects of interest: detailed and open versus blank and closed facades, patterns in perceiving different elements, and a visual bias for capturing faces in buildings. However, in the absence of a consensus on methodologies, the available studies remain unsystematic and face many limitations regarding the underpinning psychological mechanisms. To bridge some of these gaps, an online study was launched to investigate design features that influence the aesthetic judgement and emotional evaluation of house facades, using a well-controlled stimulus set of Canadian houses. A methodical modelling of design features will be performed to extract both high and low level image properties, in addition to segmentation of layout-related features. 300 participants from Canada, Denmark, and Germany will rate the images on twelve psychological dimensions representing appealing aspects of a house. Subjective ratings are expected to correlate with specific architectural elements while controlling for typicality and familiarity, and other individual differences. With the lack of relevant studies, this research aims to identify architectural elements of beneficial qualities that can inform design strategies for optimized residential spaces.

Keywords: architectural elements, emotions, psychological response, residential facades.

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Authors: Iñaki Aliende, Tom Webb, Lorenzo Escot

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There is a concern about the decrease in football referees globally. A study in Spain has analyzed the factors affecting a referee's career over the past 30 years through a survey of 758 referees. Results showed the impact of factors such as threats, education, initial vocation, and dependents on a referee's career. To improve the situation, the federation needs to provide better information, support young referees, monitor referees, and raise public awareness of violence toward referees. The study also formed a comprehensive model for federations to enhance their officiating policies by means of data-driven techniques that can serve other federations to improve referees' careers.

Keywords: data science, football referees, sport management, sport careers, survival analysis

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Authors: O. A. Ajigini, E. N. Mwim

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Cybersecurity is the protection of computers, programs, networks, and data from attack, damage, unauthorised, unintended access, change, or destruction. Organisations collect, process and store their confidential and sensitive information on computers and transmit this data across networks to other computers. Moreover, the advent of internet technologies has led to various cyberattacks resulting in dangerous consequences for organisations. Therefore, with the increase in the volume and sophistication of cyberattacks, there is a need to develop models and make recommendations for the management of cybersecurity threats in organisations. This paper reports on various threats that cause malicious damage to organisations in cyberspace and provides measures on how these threats can be eliminated or reduced. The paper explores various aspects of protection measures against cybersecurity threats such as handling of sensitive data, network security, protection of information assets and cybersecurity awareness. The paper posits a model and recommendations on how to manage cybersecurity threats in organisations effectively. The model and the recommendations can then be utilised by organisations to manage the threats affecting their cyberspace. The paper provides valuable information to assist organisations in managing their cybersecurity threats and hence protect their computers, programs, networks and data in cyberspace. The paper aims to assist organisations to protect their information assets and data from cyberthreats as part of the contributions toward community engagement.

Keywords: confidential information, cyberattacks, cybersecurity, cyberspace, sensitive information

Procedia PDF Downloads 260

Authors: Arup Saha Chaudhuri

Abstract:

Structural steel is a very ductile material with high strength carrying capacity, thus it is very useful to make earthquake resistant buildings. It is a homogeneous material also. The member section and the structural system can be made very efficient for economical design. As the steel is recyclable and reused, it is a green material. The embodied energy for the efficiently designed steel structure is less than the RC structure. For sustainable green building steel is the best material nowadays. Moreover, pre-engineered and pre-fabricated faster construction methodologies help the development work to complete within the stipulated time. In this paper, the usefulness of Eccentric Bracing Frame (EBF) in steel structure over Moment Resisting Frame (MRF) and Concentric Bracing Frame (CBF) is shown. Stability of the steel structures against horizontal forces especially in seismic condition is efficiently possible by Eccentric bracing systems with economic connection details. The EBF is pin–ended, but the beam-column joints are designed for pin ended or for full connectivity. The EBF has several desirable features for seismic resistance. In comparison with CBF system, EBF system can be designed for appropriate stiffness and drift control. The link beam is supposed to yield in shear or flexure before initiation of yielding or buckling of the bracing member in tension or compression. The behavior of a 2-D steel frame is observed under seismic loading condition in the present paper. Ductility and brittleness of the frames are compared with respect to time period of vibration and dynamic base shear. It is observed that the EBF system is better than MRF system comparing the time period of vibration and base shear participation.

Keywords: steel building, green and sustainable, earthquake resistant, EBF system

Procedia PDF Downloads 350

Authors: Philippe Larvet

Abstract:

This paper presents the concept of an object-based programming language where tests (if... then... else) and control structures (while, repeat, for...) disappear and are replaced by conditions on data. According to the object paradigm, by using this concept, data are still embedded inside objects, as variable-value couples, but object methods are expressed into the form of logical propositions (‘conditions on data’ or COD).For instance : variable1 = value1 AND variable2 > value2 => variable3 = value3. Implementing this approach, a central inference engine turns and examines objects one after another, collecting all CODs of each object. CODs are considered as rules in a rule-based system: the left part of each proposition (left side of the ‘=>‘ sign) is the premise and the right part is the conclusion. So, premises are evaluated and conclusions are fired. Conclusions modify the variable-value couples of the object and the engine goes to examine the next object. The paper develops the principles of writing CODs instead of complex algorithms. Through samples, the paper also presents several hints for implementing a simple mechanism able to process this ‘COD language’. The proposed approach can be used within the context of simulation, process control, industrial systems validation, etc. By writing simple and rigorous conditions on data, instead of using classical and long-to-learn languages, engineers and specialists can easily simulate and validate the functioning of complex systems.

Keywords: conditions on data, logical proposition, programming without code, object-oriented programming, system simulation, system validation

Procedia PDF Downloads 223

Authors: O. H. Gebril, N. A. Meguid

Abstract:

Background: Iron had been a focus of interest recently as a main exaggerating factor for oxidative stresses in the central nervous system and a link to various neurological disorders is suspected. Many studies with various techniques showed evidence of disturbed iron-related proteins in the cell in human and animal models of neurodegenerative disorders. Also, linkage to significant pathological changes had been evidenced e.g. apoptosis and cell signaling. On the other hand, the role of iron in neurodevelopmental disorders is still unclear. With increasing prevalence of autism worldwide, some changes in iron parameters and its stores were documented in many studies. This study includes Haemochromatosis HFE gene polymorphisms (p.H63D and p.C282Y) and ferroportin gene (SLC40A1) Q248H polymorphism in autism and control children. Materials and Methods: Whole genome DNA was extracted; p.H63D and p.C282Y genotyping was studied using specific sequence amplification followed by restriction enzyme digestion on a sample of autism patients (25 cases) and twenty controls. Results: The p.H63D is seen more than the C282Y among both autism and control samples, with no significant association of p.H63D or p.C282Y polymorphism and autism was revealed. Also, no association with Q248H polymorphism was evidenced. Conclusion: The study results do not prove the role of cellular iron genes polymorphisms as risk factors for neurodevelopmental disorders, and in turn highlights the specificity of cellular iron related pathways in neurodegeneration. These results demand further gene expression studies to elucidate the main pathophysiological pathways that are disturbed in autism and other neurodevelopmental disorders.

Keywords: iron, neurodevelopmental, oxidative stress, haemohromatosis, ferroportin, genes

Procedia PDF Downloads 361