Use of a Virtual Twin for Dynamic Storage Space Monitoring in a Port Terminal

Aiming at the characteristics of data stream, the paper presents an incremental decision tree algorithm based on binary-attribute tree on the basis of SPRINT algorithm. The attribute set of this improved algorithm adopts the maximum entropy attribute classification and dynamic storage method of Bayesian method. By using this improved algorithm, static organization form of candidate attributes set for traditional SPRINT algorithm has been changed and it is much more suitable for concept drift and reduces the time complexity for new sampling insertion and best division node selection as well as saves storage space and increases classification efficiency.

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Indirect measurements in micro-space with the EM

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100139366 ◽

1995 ◽

Vol 53 ◽

pp. 598-599

Author(s):

Sterling P. Newberry

Keyword(s):

Electron Microscope ◽

Standard Model ◽

Particle Physics ◽

Information Storage ◽

Storage Space ◽

Indirect Measurements ◽

Storage And Retrieval ◽

Adequate Information ◽

Compelling Reason ◽

The Standard Model

At the 1958 meeting of our society, then known as EMSA, the author introduced the concept of microspace and suggested its use to provide adequate information storage space and the use of electron microscope techniques to provide storage and retrieval access. At this current meeting of MSA, he wishes to suggest an additional use of the power of the electron microscope.The author has been contemplating this new use for some time and would have suggested it in the EMSA fiftieth year commemorative volume, but for page limitations. There is compelling reason to put forth this suggestion today because problems have arisen in the “Standard Model” of particle physics and funds are being greatly reduced just as we need higher energy machines to resolve these problems. Therefore, any techniques which complement or augment what we can accomplish during this austerity period with the machines at hand is worth exploring.

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Collaborative Demand Response Optimization of Electric Vehicles and Storage Space Heating for Residential Peak Shaving

International Review of Electrical Engineering (IREE) ◽

10.15866/iree.v9i6.4829 ◽

2014 ◽

Vol 9 (6) ◽

pp. 1154

Author(s):

Farhan Hameed Malik ◽

Ali Mubbashir ◽

Matti Lehtonen

Keyword(s):

Electric Vehicles ◽

Demand Response ◽

Space Heating ◽

Storage Space ◽

Peak Shaving ◽

Response Optimization ◽

And Storage

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PERANCANGAN DAN IMPLEMENTASI ALGORITMA ELIAS GAMMA CODE UNTUK MENGKOMPRESI RECORD DATABASE PADA APLIKASI RANGKUMAN PENGETAHUAN UMUM LENGKAP

KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) ◽

10.30865/komik.v3i1.1600 ◽

2019 ◽

Vol 3 (1) ◽

Author(s):

Hikka Sartika ◽

Taronisokhi Zebua

Keyword(s):

Compression Ratio ◽

General Public ◽

Storage Capacity ◽

Storage Space ◽

File Size ◽

Compression Technique ◽

Code Algorithm ◽

Database File ◽

Large File

Storage space required by an application is one of the problems on smartphones. This problem can result in a waste of storage space because not all smartphones have a very large storage capacity. One application that has a large file size is the RPUL application and this application is widely accessed by students and the general public. Large file size is what often causes this application can not run effectively on smartphones. One solution that can be used to solve this problem is to compress the application file, so that the size of the storage space needed in the smartphone is much smaller. This study describes how the application of the elias gamma code algorithm as one of the compression technique algorithms to compress the RPUL application database file. This is done so that the RPUL application can run effectively on a smartphone after it is installed. Based on trials conducted on 64 bit of text as samples in this research it was found that compression based on the elias gamma code algorithm is able to compress text from a database file with a ratio of compression is 2 bits, compression ratio is 50% with a redundancy is 50%. Keywords: Compression, RPUL, Smartphone, Elias Gamma Code

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IMPLEMENTASI ALGORITMA LEVENSTEIN DALAM MENGKOMPRESI TEKS PADA APLIKASI RANGKUMAN PENGETAHUAN ALAM LENGKAP

KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) ◽

10.30865/komik.v3i1.1594 ◽

2019 ◽

Vol 3 (1) ◽

Author(s):

Winda Winda ◽

Taronisokhi Zebua

Keyword(s):

Compression Ratio ◽

Mobile Application ◽

Storage Space ◽

Compression Technique ◽

The Public ◽

Natural Knowledge ◽

Database Size ◽

Text Database

The size of the data that is owned by an application today is very influential on the amount of space in the memory needed one of which is a mobile-based application. One mobile application that is widely used by students and the public at this time is the Complete Natural Knowledge Summary (Rangkuman Pengetahuan Alam Lengkap or RPAL) application. The RPAL application requires a large amount of material storage space in the mobile memory after it has been installed, so it can cause this application to be ineffective (slow). Compression of data can be used as a solution to reduce the size of the data so as to minimize the need for space in memory. The levestein algorithm is a compression technique algorithm that can be used to compress material stored in the RPAL application database, so that the database size is small. This study describes how to compress the RPAL application database records, so as to minimize the space needed on memory. Based on tests conducted on 128 characters of data (200 bits), the compression results obtained of 136 bits (17 characters) with a compression ratio is 68% and redundancy is 32%.Keywords: compression, levestein, aplication, RPAL, text, database, mobile

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Design and Implementation of Low Energy Wireless Network Nodes based on Hardware Compression Acceleration

Recent Patents on Computer Science ◽

10.2174/2213275912666190715164024 ◽

2019 ◽

Vol 12 ◽

Author(s):

Hui Yang ◽

Anand Nayyar

Keyword(s):

Energy Consumption ◽

Data Compression ◽

Energy Saving ◽

Optimization Design ◽

Hardware Acceleration ◽

Transmission Efficiency ◽

General Purpose ◽

Storage Space ◽

General Purpose Processor ◽

Compression Time

: In the fast development of information, the information data is increasing in geometric multiples, and the speed of information transmission and storage space are required to be higher. In order to reduce the use of storage space and further improve the transmission efficiency of data, data need to be compressed. processing. In the process of data compression, it is very important to ensure the lossless nature of data, and lossless data compression algorithms appear. The gradual optimization design of the algorithm can often achieve the energy-saving optimization of data compression. Similarly, The effect of energy saving can also be obtained by improving the hardware structure of node. In this paper, a new structure is designed for sensor node, which adopts hardware acceleration, and the data compression module is separated from the node microprocessor.On the basis of the ASIC design of the algorithm, by introducing hardware acceleration, the energy consumption of the compressed data was successfully reduced, and the proportion of energy consumption and compression time saved by the general-purpose processor was as high as 98.4 % and 95.8 %, respectively. It greatly reduces the compression time and energy consumption.

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