scholarly journals Real Time Data Logging of Different Parameters of Airjet Looms

2019 ◽  
Vol 8 (6) ◽  
pp. 2304-2306
Keyword(s):  
Wireless Communication ◽  
Real Time ◽  
Manufacturing Industry ◽  
Data Logging ◽  
Time Data ◽  
Time System ◽  
Real Time System ◽  
Air Jet ◽  
Real Time Data ◽  
Recorded Data

Real time data logging of different parameters of Air jet looms should be implemented to reduce the time-consuming method in the textile manufacturing industry. Implementation area of this system is a reduction of efforts and errors done by workers in the textile looms. Existing system is not able to give real time data required by the user at the required time. This system actually keeps record of different stoppages that leads to break the continuity of the machine and hence reduces the machine efficiency. This is a real time system in which wireless communication is used to transfer the recorded data to user’s computer. This recorded detail in turn is transmitted to the PC of the user to do further computation of wages of the worker and manage their work efficiency. This is a real time system in which wireless communication is used to transfer the recorded data to user’s computer as well as on mobile phone. This will provide an additional facility of monitoring the working condition of machine whether it is proper or not and thus user can also keep watch on the workers.

scholarly journals Real-time Web Search Framework for Performing Efficient Retrieval of Data

2021 ◽  
Vol 45 (1) ◽  
pp. 287-308
Author(s):  
Falah Al-akashi ◽  
Diana Inkpen
Keyword(s):  
Real Time ◽  
Web Search ◽  
Focal Point ◽  
Relevant Information ◽  
Life Cycles ◽  
Specific Information ◽  
Time Data ◽  
Time System ◽  
Real Time System ◽  
Real Time Data

With the rapidly growing amount of information on the internet, real-time system is one of the key strategies to cope with the information overload and to help users in finding highly relevant information. Real-time events and domain-specific information are important knowledge base references on the Web that frequently accessed by millions of users. Real-time system is a vital to product and a technique must resolve the context of challenges to be more reliable, e.g. short data life-cycles, heterogeneous user interests, strict time constraints, and context-dependent article relevance. Since real-time data have only a short time to live, real-time models have to be continuously adapted, ensuring that real-time data are always up-to-date. The focal point of this manuscript is for designing a real-time web search approach that aggregates several web search algorithms at query time to tune search results for relevancy. We learn a context-aware delegation algorithm that allows choosing the best real-time algorithms for each query request. The evaluation showed that the proposed approach outperforms the traditional models, in which it allows us to adapt the specific properties of the considered real-time resources. In the experiments, we found that it is highly relevant for most recently searched queries, consistent in its performance, and resilient to the drawbacks faced by other algorithms

The Real-Time Data Management System for Argo Profiling Float Observations

2007 ◽  
Vol 24 (9) ◽  
pp. 1608-1628 ◽  
Author(s):  
Claudia Schmid ◽  
Robert L. Molinari ◽  
Reyna Sabina ◽  
Yeun-Ho Daneshzadeh ◽  
Xiangdong Xia ◽  
...  
Keyword(s):  
Quality Control ◽  
Data Management ◽  
Real Time ◽  
Time Data ◽  
Time System ◽  
Real Time System ◽  
The Real ◽  
Argo Floats ◽  
Real Time Data ◽  
Argo Profiles

Abstract Argo is an internationally coordinated program directed at deploying and maintaining an array of 3000 temperature and salinity profiling floats on a global 3° latitude × 3° longitude grid. Argo floats are deployed from research vessels, merchant ships, and aircraft. After launch they sink to a prescribed pressure level (typically 1000–2000 dbar), where most floats remain for 10 days. The floats then return to the surface, collecting temperature and salinity profiles. At the surface they transmit the data to a satellite and sink again to repeat the cycle. As of 10 August 2006 there are 2489 floats reporting data. The International Argo Data Management Team oversees the development and implementation of the data management protocols of Argo. Two types of data systems are active—real time and delayed mode. The real-time system receives the transmissions from the Argo floats, extracts the data, checks their quality, and makes them available to the users. The objective of the real-time system is to provide Argo profiles to the operational and research community within 24 h of their measurement. This requirement makes it necessary to control the quality of the data automatically. The delayed-mode quality control is directed at a more detailed look at the profiles using statistical methods and scientific review of the data. In this paper, the real-time data processing and quality-control methodology is described in detail. Results of the application of these procedures to Argo profiles are described.

Why Ecological Momentary Assessment Surveys Go Incomplete?: When It Happens and How It Impacts Data

2020 ◽  
Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  
Keyword(s):  
Real Time ◽  
Self Report ◽  
Data Logging ◽  
Time Data ◽  
Real Time Data ◽  
Report Data ◽  
Self Report Data ◽  
Ecological Momentary ◽  
The Impact ◽  
Momentary Assessment

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.

Real-Time Data Logging and Online Curve Fitting Using Raspberry Pi in Physics Laboratories

2020 ◽  
Vol 18 (3) ◽  
pp. 57-77
Author(s):  
Wing-Kwong Wong ◽  
Kai-Ping Chen ◽  
Jia-Wei Lin
Keyword(s):  
Experimental Data ◽  
Real Time ◽  
Curve Fitting ◽  
Empirical Studies ◽  
Error Rates ◽  
Raspberry Pi ◽  
Data Logging ◽  
Time Data ◽  
Real Time Data ◽  
Physics Laboratories

The results of PISA 2015 indicate that Taiwanese students have excellent mathematical and scientific knowledge but are weak in applying such knowledge and in conducting practical experiments in the laboratory. To support students conducting practical experiments in physics laboratories, a real-time data logging system and an online tool for fitting experimental data were developed. During data logging in an experiment, the data was immediately plotted, which enabled students to observe the characteristics of the plot. The online curve fitting system, which employed Internet of Things technologies, allowed students to fit experimental data to various mathematical functions and plot a function curve superimposed on the data. Two empirical studies were conducted involving first-year university students and secondary school teachers. The results indicated that these developed tools improved students' understanding of an experiment's mathematical characteristics. The average curve fitting error rates of students and teachers were 4.62% and 1.4%, respectively.

Design of Network Analysis System Based on Stream Computing

2017 ◽  
Vol 14 (1) ◽  
pp. 64-68 ◽  
Author(s):  
Peng Shi ◽  
Li Li
Keyword(s):  
Network Analysis ◽  
Load Balancing ◽  
Data Processing ◽  
Real Time ◽  
Network Data ◽  
Stream Computing ◽  
Time Data ◽  
Real Time System ◽  
Real Time Data ◽  
Analysis System

The functions of the network analysis system include detection and analysis of network data stream. According to the results of the network analysis, we monitor the network accident and avoid the security risks. This can improve the network performance and increase the network availability. As the data flow in the network is constantly produced, the biggest characteristic of network analysis system is that it is a real-time system. Because of the high requirements of the network data analysis and network fault processing, the system requires very high processing efficiency of the real time data of network. Stream computing is a technique specifically for processing real-time data streams. Its idea is that the value of the data is reduced with the lapse of time, so as long as the data appearing, it must be processed as soon as possible. So we use the technology of stream computing to design network analysis system to meet the needs of real-time capability. Moreover, the stream computing framework has been widely welcomed in the field because of its good expansibility, ease of use and flexibility. In this paper, firstly, we introduce the characteristics of the data processing based on stream computing and the traditional data processing separately. We point out their difference and introduce the technique of stream computing. Then, we introduce the architecture of network analysis system designed base on the technique of stream computing. The architecture includes two main components that are logic processing layer and communication layer. We describe the characteristics of each component and functional characteristics in detail, and we introduce the system load balancing algorithm. Finally, by experiments, we verify the effectiveness of the system’s characteristics of dynamic expansion and load balancing.

scholarly journals The Ground Control Station Design For Can-Sized Satellite (CanSAT) System

2020 ◽  
Vol 1 (2) ◽  
pp. 76-82
Author(s):  
Noor Thuwaibah Abdul Razak ◽  
Huda A Majid ◽  
Faiz Asraf Saparuddin ◽  
Muhamad Fitry Abdul Jalil ◽  
Muhamad Shakry Jamaluddin Jalil ◽  
...  
Keyword(s):  
Real Time ◽  
Software Design ◽  
Lightweight Design ◽  
Time Data ◽  
Time System ◽  
Real Time System ◽  
Ground Station ◽  
Medical Supplies ◽  
Emergency Medical ◽  
Main Components

Nowadays, Natural disaster tragedy is now one of the world's biggest concerns. Can-sized satellite, MedSAT: Location-Aware CanSAT for On-Site Emergency Medical Supplies develop a platform for finding direction and accurately locating an emergency patient and providing emergency medical supplies such as bandages, antiseptic wipes, sterile gauze pads of various sizes, insulin, pills, syringe and antivenom, as well as real-time visual feed for medical diagnosis during and after landing. This project focuses on the design of MedSAT and provides a real-time system to capture MedSAT’s real-time data during descent. The objective of the real-time system is to improve the accuracy and location speed of MedSAT data collection which can provide readings of altitude, latitude and longitude to help MedSAT navigate to the patient location. Hardware design (flight controller, GPS module and telemetry kit), software design (Mission Planner) and real-time system (RTS) are the main components of this platform. In addition, the ground station was developed to communicate with users via wireless telemetry communication using MAVLink protocol. Based on the overall findings, MedSAT and ground station's compact and lightweight design was developed in search and rescue operations for emergency location.

scholarly journals Towards Handling Incremental Load for Anomalies in Near Real Time Data Warehouse

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Real Time ◽  
Data Warehouse ◽  
Time Data ◽  
Time System ◽  
Time Limits ◽  
Time Out ◽  
Novel Approach ◽  
Real Time Data ◽  
Maintenance Work ◽  
System Time

Refreshment anomalies occur in a data warehousing environment while performing Extract Transform and Load (ETL) to get the data for analysis from sources. There could be several reasons for the anomalies like not able to capture the delta on time, system time out, duplicate entries due to outer join operations and many more. Once anomalies are detected the compensation operation is executed to get the data that was missing into the data warehouse. In this work we would like to analyze scenario where it is necessary to perform incremental loads based on priority in an ongoing data warehouse maintenance work. The work proposes a novel approach to decide on when to perform ETL so that refreshment anomalies do not occur and to maintain integrity of data such that analytics queries always provide right information to the analyst. Two novelties have been discussed in this work one is to have a threshold before compensation of updates and two is while performing compensation updates prioritize the query with less freshness interval to have more time limits for the updates to be completed.

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