scholarly journals Large Scale Hotel Resource Retrieval Algorithm Based on Characteristic Threshold Extraction

2022 ◽  
Vol 16 ◽  
pp. 26-31
Author(s):  
Min Fang
Keyword(s):  
Energy Consumption ◽  
Data Processing ◽  
Large Scale ◽  
High Energy ◽  
Error Component ◽  
Retrieval Algorithm ◽  
Data Detection ◽  
Redundant Data ◽  
Variable Window ◽  
Resource Data

At present, the hotel resource retrieval algorithm has the problem of low retrieval efficiency, low accuracy, low security and high energy consumption, and this study proposes a large scale hotel resource retrieval algorithm based on characteristic threshold extraction. In the large-scale hotel resource data, the mass sequence is decomposed into periodic component, trend component, random error component and burst component. Different components are extracted, the singular point detection is realized by the extraction results, and the abnormal data in the hotel resource data are obtained. Based on the attribute of hotel resource data, the data similarity is processed with variable window, the total similarity of data is obtained, and the abnormal detection of redundant resource data is realized. The abnormal data detection results and redundant data detection results are substituted into the space-time filter, and the data processing is completed. The retrieval problem is identified, and the data processing results are replaced in the hotel resource retrieval based on the characteristic threshold extraction to achieve the normalization of data source and rule knowledge. The characteristic threshold and retrieval strategy are determined, and data fusion reasoning is carried out. After repeated iteration, effective solutions are obtained. The effective solution is fused to get the best retrieval result. Experimental results showed that the algorithm has higher retrieval accuracy, efficiency and security coefficient, and the average search energy consumption is 56n J/bit.

Energy-Efficiency in Cloud Data Centers

2013 ◽  
pp. 241-263
Author(s):  
Burak Kantarci ◽  
Hussein T. Mouftah
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Data Center ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Centers ◽  
High Energy ◽  
It Services ◽  
Data Center Network ◽  
Cloud Data

Cloud computing aims to migrate IT services to distant data centers in order to reduce the dependency of the services on the limited local resources. Cloud computing provides access to distant computing resources via Web services while the end user is not aware of how the IT infrastructure is managed. Besides the novelties and advantages of cloud computing, deployment of a large number of servers and data centers introduces the challenge of high energy consumption. Additionally, transportation of IT services over the Internet backbone accumulates the energy consumption problem of the backbone infrastructure. In this chapter, the authors cover energy-efficient cloud computing studies in the data center involving various aspects such as: reduction of processing, storage, and data center network-related power consumption. They first provide a brief overview of the existing approaches on cool data centers that can be mainly grouped as studies on virtualization techniques, energy-efficient data center network design schemes, and studies that monitor the data center thermal activity by Wireless Sensor Networks (WSNs). The authors also present solutions that aim to reduce energy consumption in data centers by considering the communications aspects over the backbone of large-scale cloud systems.

The Key Technology Research of the Water Injection System Energy Saving for Super Low Permeability Reservoir in Changqing Oil Field

2012 ◽  
Vol 524-527 ◽  
pp. 1217-1222 ◽  
Author(s):  
Zhi Qiang Huang ◽  
Zhen Chen ◽  
Gang Zheng ◽  
Jian Qiang Xue ◽  
Xue Yuan Li
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Large Scale ◽  
Water Injection ◽  
High Energy ◽  
Economic Benefits ◽  
Oil Field ◽  
Injection System ◽  
Low Permeability ◽  
Load Rate

With the characteristics of low permeability, pressure and abundance, it's extremely hard to exploit the super low permeability reservoirs in ChangQing oil field. For this reason, the water injection recovery technique has been widely used. Analysis showed that a serious problem of high energy consumption exist in the water injection system, the power consumption of which accounts for about 44%. And the energy cost of pump units reach up to 43%, it's the highest energy consumption link in the system. In this paper the load rate classification method (LRCM) is firstly adopted to statistical analyze water injection stations, which are divided into the owing and over load rate stations. As a result, the owing load rate stations accounts for 83.8%, with a serious phenomenon of the Big Horse Pull A Small Carriage, causing the large-scale backflow in the station, and the efficiency is low, the energy consumption is on the high side. Aimed at water injection stations with different load rate, the methods of reasonable shutting down the pumps, pump replacement, optimizing the transmission ratio and piston size, as well as the speed control technology have been used to make the outlet flow and actual demand reasonable matching. The test result shows that the energy saving technology is well targeted, simple, practical and low cost. The pump units’ efficiency improves obviously, the consumption reduces by 10%, which greatly improve the oilfield economic benefits.

A Time Synchronization Algorithm Based on Cluster-Tree

2014 ◽  
Vol 1046 ◽  
pp. 348-351
Author(s):  
Hao Gang ◽  
Yi Zhuang
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Time Synchronization ◽  
High Energy ◽  
Cluster Tree ◽  
Network Synchronization ◽  
Hop Count ◽  
Synchronization Algorithm ◽  
Reduce Energy Consumption ◽  
High Energy Consumption

Concerning the problem that classical time synchronization algorithms applied to large-scale Wireless Sensor Network have low precision and high energy consumption, this paper proposes a time synchronization algorithm based on cluster-tree. The algorithm can decrease the synchronization hop count by constructing a spanning tree, and uses two-way SRS in inter-cluster and one-way ROS in intra-cluster to reduce the number of messages required for the network synchronization. The experimental results show that the algorithm can keep the network synchronization precision at a higher level and effectively reduce energy consumption of nodes compared with the RBS and TPSN.

Process Optimization of One-Stage Propane Pre-Cooled MRC Cycle for Small-Scale LNG Plant

2012 ◽  
Vol 516-517 ◽  
pp. 1184-1187
Author(s):  
Heng Sun ◽  
Dan Shu ◽  
Hong Mei Zhu
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Process Parameters ◽  
Large Scale ◽  
High Energy ◽  
Small Scale ◽  
Main Process ◽  
One Stage ◽  
High Energy Efficiency ◽  
The One

One-stage pre-cooled mixture refrigerant cycle can be applied in small-scale LNG plant and be special suitable for skit mounted LNG plant. It has different character with the C3MR cycle used in large-scale LNG plant. The optimization of the mixture refrigerant is carried out using HYSYS software. The effect of the main process parameters on the performance of the cycle is calculated and discussed. The result shows that appropriate ranges of the process parameters exist. Higher and lower values of the parameters will increase the energy consumption significantly. The results also indicate that the optimization of the one-stage pre-cooled mixture refrigerant cycle can obtain rather high energy efficiency that is competitive with that of the SMR which is widely employed in small-scale LNG plant.

scholarly journals The Cherenkov Telescope Array production system proto-type for large-scale data processing and simulations

2021 ◽  
Vol 251 ◽  
pp. 02029
Author(s):  
Luisa Arrabito ◽  
Johan Bregeon ◽  
Patrick Maeght ◽  
Michèle Sanguillon ◽  
Andrei Tsaregorodtsev ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Data Processing ◽  
Production System ◽  
Large Scale ◽  
Current System ◽  
High Energy ◽  
Current Status ◽  
Telescope Array ◽  
Cherenkov Telescope ◽  
Very High

The Cherenkov Telescope Array (CTA) is the next-generation instrument in the very-high energy gamma ray astronomy domain. It will consist of tens of Cherenkov telescopes deployed in 2 arrays at La Palma (Spain) and Paranal (ESO, Chile) respectively. Currently under construction, CTA will start operations around 2023 for a duration of about 30 years. During operations CTA is expected to produce about 2 PB of raw data per year plus 5-20 PB of Monte Carlo data. The global data volume to be managed by the CTA archive, including all versions and copies, is of the order of 100 PB with a smooth growing profile. The associated processing needs are also very high, of the order of hundreds of millions of CPU HS06 hours per year. In order to optimize the instrument design and study its performances, during the preparatory phase (2010-2017) and the current construction phase, the CTA consortium has run massive Monte Carlo productions on the EGI grid infrastructure. In order to handle these productions and the future data processing, we have developed a production system based on the DIRAC framework. The current system is the result of several years of hardware infrastructure upgrades, software development and integration of different services like CVMFS and FTS. In this paper we present the current status of the CTA production system and its exploitation during the latest large-scale Monte Carlo campaigns.

scholarly journals Bacterial synthesis of nanoparticles: A green approach

2020 ◽  
Vol 28 (1) ◽  
pp. 9-17 ◽  
Author(s):  
S. I. Tsekhmistrenko ◽  
V. S. Bityutskyy ◽  
O. S. Tsekhmistrenko ◽  
L. P. Horalskyi ◽  
N. O. Tymoshok ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Heterogeneous Catalysts ◽  
Nanoparticle Synthesis ◽  
Catalytic Efficiency ◽  
High Energy ◽  
Synthesis Of Nanoparticles ◽  
Green Approach ◽  
Wide Range ◽  
Catalytic Applications

In recent decades, the attention of scientists has been drawn towards nanoparticles (NPs) of metals and metalloids. Traditional methods for the manufacturing of NPs are now being extensively studied. However, disadvantages such as the use of toxic agents and high energy consumption associated with chemical and physical processes impede their continued use in various fields. In this article, we analyse the relevance of the use of living systems and their components for the development of "green" synthesis of nano-objects with exceptional properties and a wide range of applications. The use of nano-biotechnological methods for the synthesis of nanoparticles has the potential of large-scale application and high commercial potential. Bacteria are an extremely convenient target for green nanoparticle synthesis due to their variety and ability to adapt to different environmental conditions. Synthesis of nanoparticles by microorganisms can occur both intracellularly and extracellularly. It is known that individual bacteria are able to bind and concentrate dissolved metal ions and metalloids, thereby detoxifying their environment. There are various bacteria cellular components such as enzymes, proteins, peptides, pigments, which are involved in the formation of nanoparticles. Bio-intensive manufacturing of NPs is environmentally friendly and inexpensive and requires low energy consumption. Some biosynthetic NPs are used as heterogeneous catalysts for environmental restoration, exhibiting higher catalytic efficiency due to their stability and increased biocompatibility. Bacteria used as nanofactories can provide a new approach to the removal of metal or metalloid ions and the production of materials with unique properties. Although a wide range of NPs have been biosynthetic and their synthetic mechanisms have been proposed, some of these mechanisms are not known in detail. This review focuses on the synthesis and catalytic applications of NPs obtained using bacteria. Known mechanisms of bioreduction and prospects for the development of NPs for catalytic applications are discussed.

Research on a Novel High-Speed Pulsating Turning Technology

2015 ◽  
Author(s):  
Yuanfeng He ◽  
Wenwu Zhang
Keyword(s):  
Energy Consumption ◽  
High Speed ◽  
Large Scale ◽  
Cutting Speed ◽  
High Energy ◽  
Work Piece ◽  
Cutting Efficiency ◽  
Cutting Heat ◽  
Lathe Machine ◽  
Machine Speed

As one of the most important machining methods, common turning has been applied on vast machining fields. Parts in revolving shape can be easily machined using lathe machine. But severe cutting heat is often generated by the contact of tool and work-piece in the procedure of turning. High cutting heat not only affects tool life and processing quality but also leads to low cutting efficiency and high energy consumption. As to the demands of processing work-piece in large scale like marine shaft, heavy lathe is utilized. Considering the inertia load and the stability of the whole machine, speed of spindle is limited and the cutting efficiency is limited thusly because cutting speed is determined by rotate speed of spindle with fixed tool. A novel high-speed pulsating turning technology (HSPT) was proposed in this paper. The contact relation between tool and work-piece was modified to be pulsating instead of continuous in common methods. The advantages of HSPT include lower energy consumption, less cutting heat, higher cutting speed compared with common method. Features of energy consumption, contact duration of tools and work-piece, surface roughness, etc. was investigated through theoretical analysis and experiment study, which have verified the advanced performance of HSPT.

scholarly journals Information retrieval algorithm of industrial cluster based on vector space

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 60-68
Author(s):  
Rongsheng Li ◽  
Nasruddin Hassan
Keyword(s):  
Information Retrieval ◽  
Energy Consumption ◽  
Vector Space ◽  
Industrial Cluster ◽  
Relevant Information ◽  
High Energy ◽  
Industrial Clusters ◽  
Retrieval Algorithm ◽  
Web Pages ◽  
Information Database

AbstractThe current information retrieval research on industrial clusters has low precision, low recall ratio, obvious delay and high energy consumption. Thus, in this paper, a information retrieval algorithm based on vector space for industrial clusters is proposed. By optimizing the unlawful labels in the database network, dividing the web pages of the industrial cluster information database and calculating the keyword scores of the relevant information of the industrial cluster corresponding to a web page, a set of well-divided database pages is obtained, and the purification of the industrial cluster information database is realized. According to the purification of industrial cluster information database, RFD algorithm is used to extract the page data features of purified industrial cluster information database. The extracted results are substituted into the information retrieval, and the vectors composed of retrieval units are used to describe the information of various types of industrial clusters and each retrieval. The matching results of information retrieval are obtained by calculating the correlation between the information of industrial clusters and the query, and the information retrieval of industrial clusters is completed. Experimental results show that the algorithm has high precision and recall ratio, short retrieval time and low energy consumption.

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