Search results for: Atomic data
23910 Reliable and Energy-Aware Data Forwarding under Sink-Hole Attack in Wireless Sensor Networks
Authors: Ebrahim Alrashed
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Wireless sensor networks are vulnerable to attacks from adversaries attempting to disrupt their operations. Sink-hole attacks are a type of attack where an adversary node drops data forwarded through it and hence affecting the reliability and accuracy of the network. Since sensor nodes have limited battery power, it is essential that any solution to the sinkhole attack problem be very energy-aware. In this paper, we present a reliable and energy efficient scheme to forward data from source nodes to the base station while under sink-hole attack. The scheme also detects sink-hole attack nodes and avoid paths that includes them.Keywords: energy-aware routing, reliability, sink-hole attack, WSN
Procedia PDF Downloads 39623909 A Near-Optimal Domain Independent Approach for Detecting Approximate Duplicates
Authors: Abdelaziz Fellah, Allaoua Maamir
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We propose a domain-independent merging-cluster filter approach complemented with a set of algorithms for identifying approximate duplicate entities efficiently and accurately within a single and across multiple data sources. The near-optimal merging-cluster filter (MCF) approach is based on the Monge-Elkan well-tuned algorithm and extended with an affine variant of the Smith-Waterman similarity measure. Then we present constant, variable, and function threshold algorithms that work conceptually in a divide-merge filtering fashion for detecting near duplicates as hierarchical clusters along with their corresponding representatives. The algorithms take recursive refinement approaches in the spirit of filtering, merging, and updating, cluster representatives to detect approximate duplicates at each level of the cluster tree. Experiments show a high effectiveness and accuracy of the MCF approach in detecting approximate duplicates by outperforming the seminal Monge-Elkan’s algorithm on several real-world benchmarks and generated datasets.Keywords: data mining, data cleaning, approximate duplicates, near-duplicates detection, data mining applications and discovery
Procedia PDF Downloads 38723908 Delivery Service and Online-and-Offline Purchasing for Collaborative Recommendations on Retail Cross-Channels
Authors: S. H. Liao, J. M. Huang
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The delivery service business model is the final link in logistics for both online-and-offline businesses. The online-and-offline business model focuses on the entire customer purchasing process online and offline, placing greater emphasis on the importance of data to optimize overall retail operations. For the retail industry, it is an important task of information and management to strengthen the collection and investigation of consumers' online and offline purchasing data to better understand customers and then recommend products. This study implements two-stage data mining analytics for clustering and association rules analysis to investigate Taiwanese consumers' (n=2,209) preferences for delivery service. This process clarifies online-and-offline purchasing behaviors and preferences to find knowledge profiles/patterns/rules for cross-channel collaborative recommendations. Finally, theoretical and practical implications for methodology and enterprise are presented.Keywords: delivery service, online-and-offline purchasing, retail cross-channel, collaborative recommendations, data mining analytics
Procedia PDF Downloads 3123907 A High Reliable Space-Borne File System with Applications of Device Partition and Intra-Channel Pipeline in Nand Flash
Authors: Xin Li, Ji-Yang Yu, Yue-Hua Niu, Lu-Yuan Wang
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As an inevitable chain of the space data acquirement system, space-borne storage system based on Nand Flash has gradually been implemented in spacecraft. In face of massive, parallel and varied data on board, efficient data management become an important issue of storage research. Face to the requirements of high-performance and reliability in Nand Flash storage system, a combination of hardware and file system design can drastically increase system dependability, even for missions with a very long duration. More sophisticated flash storage concepts with advanced operating systems have been researched to improve the reliability of Nand Flash storage system on satellites. In this paper, architecture of file system with multi-channel data acquisition and storage on board is proposed, which obtains large-capacity and high-performance with the combine of intra-channel pipeline and device partition in Nand Flash. Multi-channel data in different rate are stored as independent files with parallel-storage system in device partition, which assures the high-effective and reliable throughput of file treatments. For massive and high-speed data storage, an efficiency assessment model is established to calculate the bandwidth formula of intra-channel pipeline. Information tables designed in Magnetoresistive RAM (MRAM) hold the management of bad block in Nand Flash and the arrangement of file system address for the high-reliability of data storage. During the full-load test, the throughput of 3D PLUS Module 160Gb Nand Flash can reach 120Mbps for store and reach 120Mbps for playback, which efficiently satisfies the requirement of multi-channel data acquisition in Satellite. Compared with previous literature, the results of experiments verify the advantages of the proposed system.Keywords: device partition architecture, intra-channel pipelining, nand flash, parallel storage
Procedia PDF Downloads 28923906 A Survey in Techniques for Imbalanced Intrusion Detection System Datasets
Authors: Najmeh Abedzadeh, Matthew Jacobs
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An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.Keywords: IDS, imbalanced datasets, sampling algorithms, big data
Procedia PDF Downloads 32823905 Tourism Satellite Account: Approach and Information System Development
Authors: Pappas Theodoros, Mihail Diakomihalis
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Measuring the economic impact of tourism in a benchmark economy is a global concern, with previous measurements being partial and not fully integrated. Tourism is a phenomenon that requires individual consumption of visitors and which should be observed and measured to reveal, thus, the overall contribution of tourism to an economy. The Tourism Satellite Account (TSA) is a critical tool for assessing the annual growth of tourism, providing reliable measurements. This article introduces a system of TSA information that encompasses all the works of the TSA, including input, storage, management, and analysis of data, as well as additional future functions and enhances the efficiency of tourism data management and TSA collection utility. The methodology and results presented offer insights into the development and implementation of TSA.Keywords: tourism satellite account, information system, data-based tourist account, relation database
Procedia PDF Downloads 8423904 Magnetoelastically Induced Perpendicular Magnetic Anisotropy and Perpendicular Exchange Bias of CoO/CoPt Multilayer Films
Authors: Guo Lei, Wang Yue, Nakamura Yoshio, Shi Ji
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Recently, perpendicular exchange bias (PEB) is introduced as an active topic attracting continuous efforts. Since its discovery, extrinsic control of PEB has been proposed, due to its scientific significance in spintronic devices and potential application in high density magnetic random access memory with perpendicular magnetic tunneling junction (p-MTJ). To our knowledge, the researches aiming to controlling PEB so far are focused mainly on enhancing the interfacial exchange coupling by adjusting the FM/AFM interface roughness, or optimizing the crystalline structures of FM or AFM layer by employing different seed layers. In present work, the effects of magnetoelastically induced PMA on PEB have been explored in [CoO5nm/CoPt5nm]5 multilayer films. We find the PMA strength of FM layer also plays an important role on PEB at the FM/AFM interface and it is effective to control PEB of [CoO5nm/CoPt5nm]5 multilayer films by changing the magnetoelastically induced PMA of CoPt layer. [CoO5nm/CoPt5nm]5 multilayer films were deposited by magnetron sputtering on fused quartz substrate at room temperature, then annealed at 100°C, 250°C, 300°C and 375°C for 3h, respectively. XRD results reveal that all the samples are well crystallized with preferred fcc CoPt (111) orientation. The continuous multilayer structure with sharp component transition at the CoO5nm/CoPt5nm interface are identified clearly by transmission electron microscopy (TEM), x-ray reflectivity (XRR) and atomic force microscope (AFM). CoPt layer in-plane tensile stress is calculated by sin2φ method, and we find it increases gradually upon annealing from 0.99 GPa (as-deposited) up to 3.02 GPa (300oC-annealed). As to the magnetic property, significant enhancement of PMA is achieved in [CoO5nm/CoPt5nm]5 multilayer films after annealing due to the increase of CoPt layer in-plane tensile stress. With the enhancement of magnetoelastically induced PMA, great improvement of PEB is also achieved in [CoO5nm/CoPt5nm]5 multilayer films, which increases from 130 Oe (as-deposited) up to 1060 Oe (300oC-annealed), showing the same change tendency as PMA and the strong correlation with CoPt layer in-plane tensile stress. We consider it is the increase of CoPt layer in-plane tensile stress that leads to the enhancement of PMA, and thus the enhancement of magnetoelastically induced PMA results in the improvement of PEB in [CoO5nm/CoPt5nm]5 multilayer films.Keywords: perpendicular exchange bias, magnetoelastically induced perpendicular magnetic anisotropy, CoO5nm/CoPt5nm]5 multilayer film with in-plane stress, perpendicular magnetic tunneling junction
Procedia PDF Downloads 46223903 Interoperable Platform for Internet of Things at Home Applications
Authors: Fabiano Amorim Vaz, Camila Gonzaga de Araujo
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With the growing number of personal devices such as smartphones, tablets, smart watches, among others, in addition to recent devices designed for IoT, it is observed that residential environment has potential to generate important information about our daily lives. Therefore, this work is focused on showing and evaluating a system that integrates all these technologies considering the context of a smart house. To achieve this, we define an architecture capable of supporting the amount of data generated and consumed at a residence and, mainly, the variety of this data presents. We organize it in a particular cloud containing information about robots, recreational vehicles, weather, in addition to data from the house, such as lighting, energy, security, among others. The proposed architecture can be extrapolated to various scenarios and applications. Through the core of this work, we can define new functionality for residences integrating them with more resources.Keywords: cloud computing, IoT, robotics, smart house
Procedia PDF Downloads 38123902 Visualization Tool for EEG Signal Segmentation
Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh
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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation
Procedia PDF Downloads 39723901 Identification of Factors and Impacts on the Success of Implementing Extended Enterprise Resource Planning: Case Study of Manufacturing Industries in East Java, Indonesia
Authors: Zeplin Jiwa Husada Tarigan, Sautma Ronni Basana, Widjojo Suprapto
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The ERP is integrating all data from various departments within the company into one data base. One department inputs the data and many other departments can access and use the data through the connected information system. As many manufacturing companies in Indonesia implement the ERP technology, many adjustments are to be made to align with the business process in the companies, especially the management policy and the competitive advantages. For companies that are successful in the initial implementation, they still have to maintain the process so that the initial success can develop along with the changing of business processes of the company. For companies which have already implemented the ERP successfully, they are still in need to maintain the system so that it can match up with the business development and changes. The continued success of the extended ERP implementation aims to achieve efficient and effective performance for the company. This research is distributing 100 questionnaires to manufacturing companies in East Java, Indonesia, which have implemented and have going live ERP for over five years. There are 90 returned questionnaires with ten disqualified questionnaires because they are from companies that implement ERP less than five years. There are only 80 questionnaires used as the data, with the response rate of 80%. Based on the data results and analysis with PLS (Partial Least Square), it is obtained that the organization commitment brings impacts to the user’s effectiveness and provides the adequate IT infrastructure. The user’s effectiveness brings impacts to the adequate IT infrastructure. The information quality of the company increases the implementation of the extended ERP in manufacturing companies in East Java, Indonesia.Keywords: organization commitment, adequate IT infrastructure, information quality, extended ERP implementation
Procedia PDF Downloads 16723900 Enhancement Method of Network Traffic Anomaly Detection Model Based on Adversarial Training With Category Tags
Authors: Zhang Shuqi, Liu Dan
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For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation
Procedia PDF Downloads 10523899 IoT Based Monitoring Temperature and Humidity
Authors: Jay P. Sipani, Riki H. Patel, Trushit Upadhyaya
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Today there is a demand to monitor environmental factors almost in all research institutes and industries and even for domestic uses. The analog data measurement requires manual effort to note readings, and there may be a possibility of human error. Such type of systems fails to provide and store precise values of parameters with high accuracy. Analog systems are having drawback of storage/memory. Therefore, there is a requirement of a smart system which is fully automated, accurate and capable enough to monitor all the environmental parameters with utmost possible accuracy. Besides, it should be cost-effective as well as portable too. This paper represents the Wireless Sensor (WS) data communication using DHT11, Arduino, SIM900A GSM module, a mobile device and Liquid Crystal Display (LCD). Experimental setup includes the heating arrangement of DHT11 and transmission of its data using Arduino and SIM900A GSM shield. The mobile device receives the data using Arduino, GSM shield and displays it on LCD too. Heating arrangement is used to heat and cool the temperature sensor to study its characteristics.Keywords: wireless communication, Arduino, DHT11, LCD, SIM900A GSM module, mobile phone SMS
Procedia PDF Downloads 28223898 Detect Cable Force of Cable Stayed Bridge from Accelerometer Data of SHM as Real Time
Authors: Nguyen Lan, Le Tan Kien, Nguyen Pham Gia Bao
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The cable-stayed bridge belongs to the combined system, in which the cables is a major strutual element. Cable-stayed bridges with large spans are often arranged with structural health monitoring systems to collect data for bridge health diagnosis. Cables tension monitoring is a structural monitoring content. It is common to measure cable tension by a direct force sensor or cable vibration accelerometer sensor, thereby inferring the indirect cable tension through the cable vibration frequency. To translate cable-stayed vibration acceleration data to real-time tension requires some necessary calculations and programming. This paper introduces the algorithm, labview program that converts cable-stayed vibration acceleration data to real-time tension. The research results are applied to the monitoring system of Tran Thi Ly cable-stayed bridge and Song Hieu cable-stayed bridge in Vietnam.Keywords: cable-stayed bridge, cable fore, structural heath monitoring (SHM), fast fourie transformed (FFT), real time, vibrations
Procedia PDF Downloads 7123897 Impacts of Building Design Factors on Auckland School Energy Consumptions
Authors: Bin Su
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This study focuses on the impact of school building design factors on winter extra energy consumption which mainly includes space heating, water heating and other appliances related to winter indoor thermal conditions. A number of Auckland schools were randomly selected for the study which introduces a method of using real monthly energy consumption data for a year to calculate winter extra energy data of school buildings. The study seeks to identify the relationships between winter extra energy data related to school building design data related to the main architectural features, building envelope and elements of the sample schools. The relationships can be used to estimate the approximate saving in winter extra energy consumption which would result from a changed design datum for future school development, and identify any major energy-efficient design problems. The relationships are also valuable for developing passive design guides for school energy efficiency.Keywords: building energy efficiency, building thermal design, building thermal performance, school building design
Procedia PDF Downloads 44323896 The Meta–Evaluation of Master Degree Theses in Science Program of Evaluation Methodology, Srinakharinwirot University
Authors: Panwasn Mahalawalert
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The objective of this study was to meta-evaluation of Master Degree theses in Science Program of Evaluation Methodology at Srinakharinwirot University, published during 2008-2011. This study was summative meta-evaluation that evaluated all theses of Master Degree in Science Program of Evaluation Methodology. Data were collected using the theses characteristics recording form and the evaluation meta-evaluation checklist. The collected data were analyzed by two parts: 1) Quantitative data were analyzed by descriptive statistics presented in frequency, percentages, mean, and standard deviation and 2) Qualitative data were analyzed by content analysis. The results of this study were found the theses characteristics was results revealed that most of theses were published in 2011. The largest group of theses researcher were female and were from the government office. The evaluation model of all theses were Decision-Oriented Evaluation Model. The objective of all theses were evaluate the project or curriculum. The most sampling technique were used the multistage random sampling technique. The most tool were used to gathering the data were questionnaires. All of the theses were analysed by descriptive statistics. The meta-evaluation results revealed that most of theses had fair on Utility Standards and Feasibility Standards, good on Propriety Standards and Accuracy Standards.Keywords: meta-evaluation, evaluation, master degree theses, Srinakharinwirot University
Procedia PDF Downloads 53623895 Re-Stating the Origin of Tetrapod Using Measures of Phylogenetic Support for Phylogenomic Data
Authors: Yunfeng Shan, Xiaoliang Wang, Youjun Zhou
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Whole-genome data from two lungfish species, along with other species, present a valuable opportunity to re-investigate the longstanding debate regarding the evolutionary relationships among tetrapods, lungfishes, and coelacanths. However, the use of bootstrap support has become outdated for large-scale phylogenomic data. Without robust phylogenetic support, the phylogenetic trees become meaningless. Therefore, it is necessary to re-evaluate the phylogenies of tetrapods, lungfishes, and coelacanths using novel measures of phylogenetic support specifically designed for phylogenomic data, as the previous phylogenies were based on 100% bootstrap support. Our findings consistently provide strong evidence favoring lungfish as the closest living relative of tetrapods. This conclusion is based on high internode certainty, relative gene support, and high gene concordance factor. The evidence stems from five previous datasets derived from lungfish transcriptomes. These results yield fresh insights into the three hypotheses regarding the phylogenies of tetrapods, lungfishes, and coelacanths. Importantly, these hypotheses are not mere conjectures but are substantiated by a significant number of genes. Analyzing real biological data further demonstrates that the inclusion of additional taxa leads to more diverse tree topologies. Consequently, gene trees and species trees may not be identical even when whole-genome sequencing data is utilized. However, it is worth noting that many gene trees can accurately reflect the species tree if an appropriate number of taxa, typically ranging from six to ten, are sampled. Therefore, it is crucial to carefully select the number of taxa and an appropriate outgroup, such as slow-evolving species, while excluding fast-evolving taxa as outgroups to mitigate the adverse effects of long-branch attraction and achieve an accurate reconstruction of the species tree. This is particularly important as more whole-genome sequencing data becomes available.Keywords: novel measures of phylogenetic support for phylogenomic data, gene concordance factor confidence, relative gene support, internode certainty, origin of tetrapods
Procedia PDF Downloads 6023894 Predicting Daily Patient Hospital Visits Using Machine Learning
Authors: Shreya Goyal
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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.Keywords: machine learning, SVM, HIPAA, data
Procedia PDF Downloads 6523893 Analyzing Keyword Networks for the Identification of Correlated Research Topics
Authors: Thiago M. R. Dias, Patrícia M. Dias, Gray F. Moita
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The production and publication of scientific works have increased significantly in the last years, being the Internet the main factor of access and distribution of these works. Faced with this, there is a growing interest in understanding how scientific research has evolved, in order to explore this knowledge to encourage research groups to become more productive. Therefore, the objective of this work is to explore repositories containing data from scientific publications and to characterize keyword networks of these publications, in order to identify the most relevant keywords, and to highlight those that have the greatest impact on the network. To do this, each article in the study repository has its keywords extracted and in this way the network is characterized, after which several metrics for social network analysis are applied for the identification of the highlighted keywords.Keywords: bibliometrics, data analysis, extraction and data integration, scientometrics
Procedia PDF Downloads 25723892 A New Approach towards the Development of Next Generation CNC
Authors: Yusri Yusof, Kamran Latif
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Computer Numeric Control (CNC) machine has been widely used in the industries since its inception. Currently, in CNC technology has been used for various operations like milling, drilling, packing and welding etc. with the rapid growth in the manufacturing world the demand of flexibility in the CNC machines has rapidly increased. Previously, the commercial CNC failed to provide flexibility because its structure was of closed nature that does not provide access to the inner features of CNC. Also CNC’s operating ISO data interface model was found to be limited. Therefore, to overcome that problem, Open Architecture Control (OAC) technology and STEP-NC data interface model are introduced. At present the Personal Computer (PC) has been the best platform for the development of open-CNC systems. In this paper, both ISO data interface model interpretation, its verification and execution has been highlighted with the introduction of the new techniques. The proposed is composed of ISO data interpretation, 3D simulation and machine motion control modules. The system is tested on an old 3 axis CNC milling machine. The results are found to be satisfactory in performance. This implementation has successfully enabled sustainable manufacturing environment.Keywords: CNC, ISO 6983, ISO 14649, LabVIEW, open architecture control, reconfigurable manufacturing systems, sustainable manufacturing, Soft-CNC
Procedia PDF Downloads 51623891 A Study on the Establishment of a 4-Joint Based Motion Capture System and Data Acquisition
Authors: Kyeong-Ri Ko, Seong Bong Bae, Jang Sik Choi, Sung Bum Pan
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A simple method for testing the posture imbalance of the human body is to check for differences in the bilateral shoulder and pelvic height of the target. In this paper, to check for spinal disorders the authors have studied ways to establish a motion capture system to obtain and express motions of 4-joints, and to acquire data based on this system. The 4 sensors are attached to the both shoulders and pelvis. To verify the established system, the normal and abnormal postures of the targets listening to a lecture were obtained using the established 4-joint based motion capture system. From the results, it was confirmed that the motions taken by the target was identical to the 3-dimensional simulation.Keywords: inertial sensor, motion capture, motion data acquisition, posture imbalance
Procedia PDF Downloads 51523890 Predictive Analytics in Oil and Gas Industry
Authors: Suchitra Chnadrashekhar
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Earlier looked as a support function in an organization information technology has now become a critical utility to manage their daily operations. Organizations are processing huge amount of data which was unimaginable few decades before. This has opened the opportunity for IT sector to help industries across domains to handle the data in the most intelligent manner. Presence of IT has been a leverage for the Oil & Gas industry to store, manage and process the data in most efficient way possible thus deriving the economic value in their day-to-day operations. Proper synchronization between Operational data system and Information Technology system is the need of the hour. Predictive analytics supports oil and gas companies by addressing the challenge of critical equipment performance, life cycle, integrity, security, and increase their utilization. Predictive analytics go beyond early warning by providing insights into the roots of problems. To reach their full potential, oil and gas companies need to take a holistic or systems approach towards asset optimization and thus have the functional information at all levels of the organization in order to make the right decisions. This paper discusses how the use of predictive analysis in oil and gas industry is redefining the dynamics of this sector. Also, the paper will be supported by real time data and evaluation of the data for a given oil production asset on an application tool, SAS. The reason for using SAS as an application for our analysis is that SAS provides an analytics-based framework to improve uptimes, performance and availability of crucial assets while reducing the amount of unscheduled maintenance, thus minimizing maintenance-related costs and operation disruptions. With state-of-the-art analytics and reporting, we can predict maintenance problems before they happen and determine root causes in order to update processes for future prevention.Keywords: hydrocarbon, information technology, SAS, predictive analytics
Procedia PDF Downloads 36023889 Urban Change Detection and Pattern Analysis Using Satellite Data
Authors: Shivani Jha, Klaus Baier, Rafiq Azzam, Ramakar Jha
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In India, generally people migrate from rural area to the urban area for better infra-structural facilities, high standard of living, good job opportunities and advanced transport/communication availability. In fact, unplanned urban development due to migration of people causes seriou damage to the land use, water pollution and available water resources. In the present work, an attempt has been made to use satellite data of different years for urban change detection of Chennai metropolitan city along with pattern analysis to generate future scenario of urban development using buffer zoning in GIS environment. In the analysis, SRTM (30m) elevation data and IRS-1C satellite data for the years 1990, 2000, and 2014, are used. The flow accumulation, aspect, flow direction and slope maps developed using SRTM 30 m data are very useful for finding suitable urban locations for industrial setup and urban settlements. Normalized difference vegetation index (NDVI) and Principal Component Analysis (PCA) have been used in ERDAS imagine software for change detection in land use of Chennai metropolitan city. It has been observed that the urban area has increased exponentially in Chennai metropolitan city with significant decrease in agriculture and barren lands. However, the water bodies located in the study regions are protected and being used as freshwater for drinking purposes. Using buffer zone analysis in GIS environment, it has been observed that the development has taken place in south west direction significantly and will do so in future.Keywords: urban change, satellite data, the Chennai metropolis, change detection
Procedia PDF Downloads 40823888 HelpMeBreathe: A Web-Based System for Asthma Management
Authors: Alia Al Rayssi, Mahra Al Marar, Alyazia Alkhaili, Reem Al Dhaheri, Shayma Alkobaisi, Hoda Amer
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We present in this paper a web-based system called “HelpMeBreathe” for managing asthma. The proposed system provides analytical tools, which allow better understanding of environmental triggers of asthma, hence better support of data-driven decision making. The developed system provides warning messages to a specific asthma patient if the weather in his/her area might cause any difficulty in breathing or could trigger an asthma attack. HelpMeBreathe collects, stores, and analyzes individuals’ moving trajectories and health conditions as well as environmental data. It then processes and displays the patients’ data through an analytical tool that leads to an effective decision making by physicians and other decision makers.Keywords: asthma, environmental triggers, map interface, web-based systems
Procedia PDF Downloads 29423887 Geographic Information Systems and Remotely Sensed Data for the Hydrological Modelling of Mazowe Dam
Authors: Ellen Nhedzi Gozo
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Unavailability of adequate hydro-meteorological data has always limited the analysis and understanding of hydrological behaviour of several dam catchments including Mazowe Dam in Zimbabwe. The problem of insufficient data for Mazowe Dam catchment analysis was solved by extracting catchment characteristics and aerial hydro-meteorological data from ASTER, LANDSAT, Shuttle Radar Topographic Mission SRTM remote sensing (RS) images using ILWIS, ArcGIS and ERDAS Imagine geographic information systems (GIS) software. Available observed hydrological as well as meteorological data complemented the use of the remotely sensed information. Ground truth land cover was mapped using a Garmin Etrex global positioning system (GPS) system. This information was then used to validate land cover classification detail that was obtained from remote sensing images. A bathymetry survey was conducted using a SONAR system connected to GPS. Hydrological modelling using the HBV model was then performed to simulate the hydrological process of the catchment in an effort to verify the reliability of the derived parameters. The model output shows a high Nash-Sutcliffe Coefficient that is close to 1 indicating that the parameters derived from remote sensing and GIS can be applied with confidence in the analysis of Mazowe Dam catchment.Keywords: geographic information systems, hydrological modelling, remote sensing, water resources management
Procedia PDF Downloads 33623886 A Bayesian Model with Improved Prior in Extreme Value Problems
Authors: Eva L. Sanjuán, Jacinto Martín, M. Isabel Parra, Mario M. Pizarro
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In Extreme Value Theory, inference estimation for the parameters of the distribution is made employing a small part of the observation values. When block maxima values are taken, many data are discarded. We developed a new Bayesian inference model to seize all the information provided by the data, introducing informative priors and using the relations between baseline and limit parameters. Firstly, we studied the accuracy of the new model for three baseline distributions that lead to a Gumbel extreme distribution: Exponential, Normal and Gumbel. Secondly, we considered mixtures of Normal variables, to simulate practical situations when data do not adjust to pure distributions, because of perturbations (noise).Keywords: bayesian inference, extreme value theory, Gumbel distribution, highly informative prior
Procedia PDF Downloads 19823885 Quantitative, Preservative Methodology for Review of Interview Transcripts Using Natural Language Processing
Authors: Rowan P. Martnishn
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During the execution of a National Endowment of the Arts grant, approximately 55 interviews were collected from professionals across various fields. These interviews were used to create deliverables – historical connections for creations that began as art and evolved entirely into computing technology. With dozens of hours’ worth of transcripts to be analyzed by qualitative coders, a quantitative methodology was created to sift through the documents. The initial step was to both clean and format all the data. First, a basic spelling and grammar check was applied, as well as a Python script for normalized formatting which used an open-source grammatical formatter to make the data as coherent as possible. 10 documents were randomly selected to manually review, where words often incorrectly translated during the transcription were recorded and replaced throughout all other documents. Then, to remove all banter and side comments, the transcripts were spliced into paragraphs (separated by change in speaker) and all paragraphs with less than 300 characters were removed. Secondly, a keyword extractor, a form of natural language processing where significant words in a document are selected, was run on each paragraph for all interviews. Every proper noun was put into a data structure corresponding to that respective interview. From there, a Bidirectional and Auto-Regressive Transformer (B.A.R.T.) summary model was then applied to each paragraph that included any of the proper nouns selected from the interview. At this stage the information to review had been sent from about 60 hours’ worth of data to 20. The data was further processed through light, manual observation – any summaries which proved to fit the criteria of the proposed deliverable were selected, as well their locations within the document. This narrowed that data down to about 5 hours’ worth of processing. The qualitative researchers were then able to find 8 more connections in addition to our previous 4, exceeding our minimum quota of 3 to satisfy the grant. Major findings of the study and subsequent curation of this methodology raised a conceptual finding crucial to working with qualitative data of this magnitude. In the use of artificial intelligence there is a general trade off in a model between breadth of knowledge and specificity. If the model has too much knowledge, the user risks leaving out important data (too general). If the tool is too specific, it has not seen enough data to be useful. Thus, this methodology proposes a solution to this tradeoff. The data is never altered outside of grammatical and spelling checks. Instead, the important information is marked, creating an indicator of where the significant data is without compromising the purity of it. Secondly, the data is chunked into smaller paragraphs, giving specificity, and then cross-referenced with the keywords (allowing generalization over the whole document). This way, no data is harmed, and qualitative experts can go over the raw data instead of using highly manipulated results. Given the success in deliverable creation as well as the circumvention of this tradeoff, this methodology should stand as a model for synthesizing qualitative data while maintaining its original form.Keywords: B.A.R.T.model, keyword extractor, natural language processing, qualitative coding
Procedia PDF Downloads 2923884 Culture and Commodification: A Study of William Gibson's the Bridge Trilogy
Authors: Aruna Bhat
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Culture can be placed within the social structure that embodies both the creation of social groups, and the manner in which they interact with each other. As many critics have pointed out, culture in the Postmodern context has often been considered a commodity, and indeed it shares many attributes with commercial products. Popular culture follows many patterns of behavior derived from Economics, from the simple principle of supply and demand, to the creation of marketable demographics which fit certain criterion. This trend is exemplary visible in contemporary fiction, especially in contemporary science fiction; Cyberpunk fiction in particular which is an off shoot of pure science fiction. William Gibson is one such author who in his works portrays such a scenario, and in his The Bridge Trilogy he adds another level of interpretation to this state of affairs, by describing a world that is centered on industrialization of a new kind – that focuses around data in the cyberspace. In this new world, data has become the most important commodity, and man has become nothing but a nodal point in a vast ocean of raw data resulting into commodification of each thing including Culture. This paper will attempt to study the presence of above mentioned elements in William Gibson’s The Bridge Trilogy. The theories applied will be Postmodernism and Cultural studies.Keywords: culture, commodity, cyberpunk, data, postmodern
Procedia PDF Downloads 50423883 Impact of Safety and Quality Considerations of Housing Clients on the Construction Firms’ Intention to Adopt Quality Function Deployment: A Case of Construction Sector
Authors: Saif Ul Haq
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The current study intends to examine the safety and quality considerations of clients of housing projects and their impact on the adoption of Quality Function Deployment (QFD) by the construction firm. Mixed method research technique has been used to collect and analyze the data wherein a survey was conducted to collect the data from 220 clients of housing projects in Saudi Arabia. Then, the telephonic and Skype interviews were conducted to collect data of 15 professionals working in the top ten real estate companies of Saudi Arabia. Data were analyzed by using partial least square (PLS) and thematic analysis techniques. Findings reveal that today’s customer prioritizes the safety and quality requirements of their houses and as a result, construction firms adopt QFD to address the needs of customers. The findings are of great importance for the clients of housing projects as well as for the construction firms as they could apply QFD in housing projects to address the safety and quality concerns of their clients.Keywords: construction industry, quality considerations, quality function deployment, safety considerations
Procedia PDF Downloads 12523882 Measurement System for Human Arm Muscle Magnetic Field and Grip Strength
Authors: Shuai Yuan, Minxia Shi, Xu Zhang, Jianzhi Yang, Kangqi Tian, Yuzheng Ma
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The precise measurement of muscle activities is essential for understanding the function of various body movements. This work aims to develop a muscle magnetic field signal detection system based on mathematical analysis. Medical research has underscored that early detection of muscle atrophy, coupled with lifestyle adjustments such as dietary control and increased exercise, can significantly enhance muscle-related diseases. Currently, surface electromyography (sEMG) is widely employed in research as an early predictor of muscle atrophy. Nonetheless, the primary limitation of using sEMG to forecast muscle strength is its inability to directly measure the signals generated by muscles. Challenges arise from potential skin-electrode contact issues due to perspiration, leading to inaccurate signals or even signal loss. Additionally, resistance and phase are significantly impacted by adipose layers. The recent emergence of optically pumped magnetometers introduces a fresh avenue for bio-magnetic field measurement techniques. These magnetometers possess high sensitivity and obviate the need for a cryogenic environment unlike superconducting quantum interference devices (SQUIDs). They detect muscle magnetic field signals in the range of tens to thousands of femtoteslas (fT). The utilization of magnetometers for capturing muscle magnetic field signals remains unaffected by issues of perspiration and adipose layers. Since their introduction, optically pumped atomic magnetometers have found extensive application in exploring the magnetic fields of organs such as cardiac and brain magnetism. The optimal operation of these magnetometers necessitates an environment with an ultra-weak magnetic field. To achieve such an environment, researchers usually utilize a combination of active magnetic compensation technology with passive magnetic shielding technology. Passive magnetic shielding technology uses a magnetic shielding device built with high permeability materials to attenuate the external magnetic field to a few nT. Compared with more layers, the coils that can generate a reverse magnetic field to precisely compensate for the residual magnetic fields are cheaper and more flexible. To attain even lower magnetic fields, compensation coils designed by Biot-Savart law are involved to generate a counteractive magnetic field to eliminate residual magnetic fields. By solving the magnetic field expression of discrete points in the target region, the parameters that determine the current density distribution on the plane can be obtained through the conventional target field method. The current density is obtained from the partial derivative of the stream function, which can be represented by the combination of trigonometric functions. Optimization algorithms in mathematics are introduced into coil design to obtain the optimal current density distribution. A one-dimensional linear regression analysis was performed on the collected data, obtaining a coefficient of determination R2 of 0.9349 with a p-value of 0. This statistical result indicates a stable relationship between the peak-to-peak value (PPV) of the muscle magnetic field signal and the magnitude of grip strength. This system is expected to be a widely used tool for healthcare professionals to gain deeper insights into the muscle health of their patients.Keywords: muscle magnetic signal, magnetic shielding, compensation coils, trigonometric functions.
Procedia PDF Downloads 5723881 Customers’ Acceptability of Islamic Banking: Employees’ Perspective in Peshawar
Authors: Tahira Imtiaz, Karim Ullah
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This paper aims to incorporate the banks employees’ perspective on acceptability of Islamic banking by the customers of Peshawar. A qualitative approach is adopted for which six in-depth interviews with employees of Islamic banks are conducted. The employees were asked to share their experience regarding customers’ acceptance attitude towards acceptability of Islamic banking. Collected data was analyzed through thematic analysis technique and its synthesis with the current literature. Through data analysis a theoretical framework is developed, which highlights the factors which drive customers towards Islamic banking, as witnessed by the employees. The practical implication of analyzed data evident that a new model could be developed on the basis of four determinants of human preference namely: inner satisfaction, time, faith and market forces.Keywords: customers’ attraction, employees’ perspective, Islamic banking, Riba
Procedia PDF Downloads 333