scholarly journals The Use of Intelligent Sensing Algorithm for Internet of Things and Hash Spatial Information Location Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Shaobo Wang ◽  
Yujia Liu
Keyword(s):  
Search Engine ◽  
Coal Mine ◽  
Hash Function ◽  
Focal Point ◽  
Recall Rate ◽  
Hash Tables ◽  
Position Information ◽  
Retrieval Time ◽  
Interval Size ◽  
Microseismic Location

This exploration is aimed at quickly obtaining the spatial position information of microseismic focal points and increasing the accuracy of microseismic rapid positioning, to take timely corresponding measures. A microseismic focal point location system completely different from the traditional microseismic location method is proposed. The search engine technology is introduced into the system, which can locate the microseismic focal point quickly and accurately. First, the propagation characteristics of microseismic signals in coal and rock layers are analyzed, and the focal position information is obtained. However, the collected microseismic signal of the coal mine contains noise, so it is denoised at first. Then, a waveform database is established for the denoised waveform data and focal point position. The structure and mathematical model of the location-sensitive hash (LSH) based on P stable distribution are introduced and improved, and the optimized algorithm multiprobe LSH is obtained. The microseismic location model is established according to the characteristics of microseismic data. The values of three parameters, hash table number, hash function family dimension, and interval size, are determined. The experimental data of the parameters of the search engine algorithm are analyzed. The results show that when the number of hash tables is 6, the dimension k of the hash function family is 14, and the interval size W is 8000, the retrieval time reaches a relatively small value, the recall rate reaches a large value, and the proportion of retrieved candidates is large; the parameters of the search engine algorithm of the measured coal mine microseismic data are analyzed. It is obtained that when the number of hash tables is 4, the dimension k of the hash function family is 6, and the interval size W is 500, the retrieval time reaches a relatively small value, the recall rate obtains a large value, and the proportion of retrieved candidates is large. The contents studied are of great significance to the evaluation of destructive mine earthquakes and impact risk.

scholarly journals Method for Retrieving Digital Agricultural Text Information Based on Local Matching

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1103
Author(s):  
Yue Song ◽  
Minjuan Wang ◽  
Wanlin Gao
Keyword(s):  
Recall Rate ◽  
Retrieval Method ◽  
Retrieval Time ◽  
Search Results ◽  
Retrieval Efficiency ◽  
Query Tree ◽  
Text Information ◽  
Relationship Of ◽  
The Relationship ◽  
Precision Rate

In order to improve the retrieval results of digital agricultural text information and improve the efficiency of retrieval, the method for searching digital agricultural text information based on local matching is proposed. The agricultural text tree and the query tree are constructed to generate the relationship of ancestor–descendant in the query and map it to the agricultural text. According to the retrieval method of the local matching, the vector retrieval method is used to calculate the digital agricultural text and submit the similarity between the queries. The similarity is sorted from large to small so that the agricultural text tree can output digital agricultural text information in turn. In the case of adding interference information, the recall rate and precision rate of the proposed method are above 99.5%; the average retrieval time is between 4s and 6s, and the average retrieval efficiency is above 99%. The proposed method is more efficient in information retrieval and can obtain comprehensive and accurate search results, which can be used for the rapid retrieval of digital agricultural text information.

Digital Signal Processing Techniques for Positioning of Off-Axis Solar Concentrators

Solar Energy ◽  
2003 ◽  
Author(s):  
Joseph N. Beasley
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Position Control ◽  
Focal Point ◽  
Digital Signal ◽  
Solar Concentrator ◽  
Solar Concentrators ◽  
Position Information ◽  
Discrete Fourier Analysis ◽  
Processing Techniques

This paper will discuss the results of using digital signal processing (DSP) techniques to determine the location of the focal point of an off-axis solar concentrator projected onto a visually complex thruster absorber and secondary concentrator. Once the location of the focal spot is located, position control information is generated to move the concentrator to a location that maximizes power transfer. A program that simulates an off-axis solar concentrator is used to generate binary “image” files to analyze for positioning information. The analysis progresses from Discrete Fourier analysis on the two-dimensional images, through spectrograms, to introduce wavelets and wavelet analysis to conceptually verify the use of DSP techniques to determine position information.

Research of Intelligent Search Engine Based on Multi-Ontology

2012 ◽  
Vol 241-244 ◽  
pp. 1659-1663
Author(s):  
Shu Dong Zhang ◽  
Can Zhang ◽  
Jing Wang
Keyword(s):  
Semantic Web ◽  
Search Engine ◽  
Domain Knowledge ◽  
Recall Rate ◽  
Domain Ontology ◽  
Semantic Retrieval ◽  
Engine Model ◽  
Cross Domain ◽  
User Query ◽  
Primary Means

With the development of the Semantic Web, ontology has become the primary means of expression of many fields of knowledge. Introducing the Semantic Web technology into the field of search engine is a valuable research topic. In order to meet the complex semantic retrieval demands, the paper proposes a search engine model based on multi-domain ontology, the model using ontology mapping rewrite the user query to achieve multiple ontology query, and provide a richer and accurate semantic information for the retrieval of cross-domain knowledge; And the paper proposes a method of cross-domain ontology annotation, providing a basis for the user semantic retrieval. The experimental results show that the search results improve the precision and recall rate.

scholarly journals MyRice: Pangkalan Data Pengetahuan Padi Malaysia

2014 ◽  
Vol 70 (6) ◽  
Author(s):  
Nurul Shakina Mohd Talkah ◽  
Faezah Mohd Salleh ◽  
Mohd Shahir Shamsir ◽  
Zaidah Rahmat ◽  
Alina Wagiran ◽  
...  
Keyword(s):  
Food Security ◽  
Search Engine ◽  
High Throughput ◽  
Focal Point ◽  
Google Scholar ◽  
Archival Data ◽  
Research Information ◽  
Knowledge Database ◽  
Trace Back ◽  
Digital Knowledge

Currently, all information regarding rice research in Malaysia are scattered over many different publications, depositories and databases using various digital and analogue formats. Although several international databases of rice research are available, they are not linked to geolocation and other basic archival information. We present MyRice; a systematic Malaysian online rice knowledge database for researchers and citizen scientists to curate their data. The creation of this database will enable   scientific researchers to trace back rice research information and their locality effectively. It is constructed using a digitization pipeline that allow high throughput digitization of archival data and connected with publication search engine such as Google Scholar. The main functions include bibliography, map locational visualization and media uploader to share videos and images. We believe that MyRice will contribute to the digital knowledge ecosystem among rice researchers to elevate access and become a focal point for driving Malaysian rice research towards a sulf-sufficient country on food security. The database is available http://biodiversity.fbb.utm.my/myrice/.

An Algorithm for Mining Frequent Stream Data Items Using Hash Function and Fading Factor

2011 ◽  
Vol 130-134 ◽  
pp. 2661-2665 ◽  
Author(s):  
Qing Ling Mei ◽  
Ling Chen
Keyword(s):  
Processing Speed ◽  
Hash Function ◽  
Data Stream ◽  
Computation Time ◽  
Experimental Results ◽  
Memory Requirement ◽  
Stream Data ◽  
Hash Tables ◽  
Frequent Items ◽  
Fading Factor

A new algorithm to mine the frequent items in data stream is presented. The algorithm adopts a time fading factor to emphasize the importance of the relatively newer data, and records the densities of the data items in Hash tables. For a given threshold of density S and an integer k, our algorithm can mine the top k frequent items. Computation time for processing each data item is O(1) . Experimental results show that the algorithm outperforms other methods in terms of accuracy, memory requirement, and processing speed.

An Accurate Efficient and Scalable Event Based Video Search Method Using Spectral Clustering

2018 ◽  
Vol 15 (2) ◽  
pp. 537-541
Author(s):  
R. G. Sakthivelan ◽  
P. Rajendran ◽  
M. Thangavel
Keyword(s):  
Search Engine ◽  
Spectral Clustering ◽  
Web Mining ◽  
Video Retrieval ◽  
Focal Point ◽  
Event Extraction ◽  
Precision Data ◽  
Video Search ◽  
User Query ◽  
Event Based

Web mining discovers enormous set of data and gets hidden and valuable information which contains text, images, audio and video files from the web search engine which is software that provides a significant result of information. Video rehabilitation for the context gives efficient comprehension of the video content. Video retrieval refers to the task of retrieving most relevant videos from the video Search engine but the outcome listed result could not achieve the relevant videos according to the user needs. This paper addresses Event based Video Retrieval (EBVR) uses metadata, which gives the accurate result. The aim is detect the circumstances of a focal point such as birthday party. In order to overcome this issue, we proposed a personalization approach which captures the user query relevance to their event. Video preprocessing method used to extract related precision data and spectral clustering technique for Video Categorization which yields event extraction and contributes associated video.

Research on Manufacturing Resource Domain Ontology Modeling Method

2012 ◽  
Vol 220-223 ◽  
pp. 3058-3063
Author(s):  
Zhong Liu ◽  
Xian Guo Yan ◽  
Hong Guo ◽  
Shi Su ◽  
Chang Gui Xu ◽  
...  
Keyword(s):  
Search Engine ◽  
Recall Rate ◽  
Domain Ontology ◽  
Modeling Method ◽  
Model Description ◽  
Networked Manufacturing ◽  
Paper Model ◽  
Ontology Modeling ◽  
General Search ◽  
Manufacturing Resource

Retrieval, recall rate and precision are not acceptable according to the general search engine in searching networked manufacturing resource. Manufacturing Resource Domain Ontology was derived and established based on the concept of the ontology in this paper. Model description was completed with protégé.

DYNAMIC REDUCTS GENERATION USING CASCADING HASHES

2014 ◽  
Vol 25 (02) ◽  
pp. 219-246 ◽  
Author(s):  
PAI-CHOU WANG
Keyword(s):  
Rough Set ◽  
Execution Time ◽  
Random Sampling ◽  
Hash Function ◽  
Time Complexity ◽  
Decision Table ◽  
Hash Tables ◽  
Dynamic Reduct ◽  
Original Classification

Reducts preserve original classification properties using minimal number of attributes in a table. Dynamic reducts are the most stable reducts in the process of random sampling of original decision table, and they are proposed to classify unseen cases. Classical reduct generation methods can be applied to compute dynamic reducts but the time complexity of computing dynamic reducts are rarely discussed. This paper proposes a cascading hash function, and dynamic reduct can be derived in O(m2n) time with O(mn) space where m and n are total number of attributes and total number of instances of the table. Core of dynamic reducts is also discussed, and the computation of core of dynamic reducts takes O(mn) time with O(mn) space. Sixteen UCI datasets are applied to compute (F, ε)-dynamic reducts for ε = 1, and results are compared to Rough Set Exploration System (RSES). Results show the execution time on generating dynamic reducts using cascading hash tables is faster than RSES up to 1700 times. Besides the efficiency issue of the algorithms, our algorithms are also very easy to implement and applicable to any system.

Integrating perspectives: How the development of second-personal competence lays the foundation for a second-personal morality

2020 ◽  
Vol 43 ◽  
Author(s):  
John Corbit ◽  
Chris Moore
Keyword(s):  
Empirical Evidence ◽  
Developmental Process ◽  
Focal Point ◽  
Personal Information ◽  
Personal Competence ◽  
Triadic Interactions ◽  
Personal Morality ◽  
Integrative Process

Abstract The integration of first-, second-, and third-personal information within joint intentional collaboration provides the foundation for broad-based second-personal morality. We offer two additions to this framework: a description of the developmental process through which second-personal competence emerges from early triadic interactions, and empirical evidence that collaboration with a concrete goal may provide an essential focal point for this integrative process.

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