The B.A.M. Storage Capacity

1995 ◽  
Vol 5 (1) ◽  
pp. 85-96 ◽  
Author(s):  
H. Englisch ◽  
V. Mastropietro ◽  
B. Tirozzi
Keyword(s):  
Storage Capacity

Simulation of the internal temperature in the Passol Laboratory, University of Debrecen

2012 ◽  
Vol 3 (1) ◽  
pp. 63-73 ◽  
Author(s):  
I. Csáky ◽  
F. Kalmár
Keyword(s):  
Temperature Variation ◽  
Air Temperature ◽  
Indoor Air ◽  
Storage Capacity ◽  
Building Structures ◽  
Internal Temperature ◽  
The One ◽  
Heavy Structure ◽  
East West ◽  
Made In

Abstract Nowadays the facades of newly built buildings have significant glazed surfaces. The solar gains in these buildings can produce discomfort caused by direct solar radiation on the one hand and by the higher indoor air temperature on the other hand. The amplitude of the indoor air temperature variation depends on the glazed area, orientation of the facade and heat storage capacity of the building. This paper presents the results of a simulation, which were made in the Passol Laboratory of University of Debrecen in order to define the internal temperature variation. The simulation proved that the highest amplitudes of the internal temperature are obtained for East orientation of the facade. The upper acceptable limit of the internal air temperature is exceeded for each analyzed orientation: North, South, East, West. Comparing different building structures, according to the obtained results, in case of the heavy structure more cooling hours are obtained, but the energy consumption for cooling is lower.

The Use of Geomatic Technologies with the Purpose of Estimating Terrestrial Carbon Storage Capacity at a Level of Forest

2015 ◽  
Author(s):  
Merve ERSOY MİRİCİ ◽  
Süha BERBEROĞLU ◽  
Ahmet ÇİLEK
Keyword(s):  
Carbon Storage ◽  
Storage Capacity ◽  
Terrestrial Carbon

Overmature Shale Gas Storage Capacity Evaluation

2013 ◽  
Author(s):  
Hua Tian ◽  
Shuichang Zhang ◽  
Shaobo Liu ◽  
Jianping Chen
Keyword(s):  
Shale Gas ◽  
Storage Capacity ◽  
Gas Storage ◽  
Capacity Evaluation

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

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

Effect of sleep on memory for binding different types of visual information

2020 ◽  
Author(s):  
John J Shaw ◽  
Zhisen Urgolites ◽  
Padraic Monaghan
Keyword(s):  
Visual Information ◽  
Storage Capacity ◽  
Declarative Memory ◽  
Recognition Task ◽  
Forced Choice ◽  
Long Term Memory ◽  
Term Memory ◽  
Different Types ◽  
Types Of Information

Visual long-term memory has a large and detailed storage capacity for individual scenes, objects, and actions. However, memory for combinations of actions and scenes is poorer, suggesting difficulty in binding this information together. Sleep can enhance declarative memory of information, but whether sleep can also boost memory for binding information and whether the effect is general across different types of information is not yet known. Experiments 1 to 3 tested effects of sleep on binding actions and scenes, and Experiments 4 and 5 tested binding of objects and scenes. Participants viewed composites and were tested 12-hours later after a delay consisting of sleep (9pm-9am) or wake (9am-9pm), on an alternative forced choice recognition task. For action-scene composites, memory was relatively poor with no significant effect of sleep. For object-scene composites sleep did improve memory. Sleep can promote binding in memory, depending on the type of information to be combined.

The visual arrays task…visual storage capacity or attention control?

2019 ◽  
Author(s):  
Jessie Martin ◽  
Jason S. Tsukahara ◽  
Christopher Draheim ◽  
Zach Shipstead ◽  
Cody Mashburn ◽  
...  
Keyword(s):  
Working Memory ◽  
Storage Capacity ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Data Sets ◽  
Independent Data ◽  
Visual Storage ◽  
Design Selection ◽  
The Relationship

**The uploaded manuscript is still in preparation** In this study, we tested the relationship between visual arrays tasks and working memory capacity and attention control. Specifically, we tested whether task design (selection or non-selection demands) impacted the relationship between visual arrays measures and constructs of working memory capacity and attention control. Using analyses from 4 independent data sets we showed that the degree to which visual arrays measures rely on selection influences the degree to which they reflect domain-general attention control.

Compact specification of polar codes

2019 ◽  
pp. 40-47
Author(s):  
R. A. Morozov ◽  
P. V. Trifonov
Keyword(s):  
Storage Capacity ◽  
Low Complexity ◽  
Practical Implementation ◽  
Polar Codes ◽  
Practical Relevance ◽  
Memory Consumption ◽  
Full Size ◽  
The Family ◽  
Erasure Probability ◽  
Binary Erasure Channel

Introduction:Practical implementation of a communication system which employs a family of polar codes requires either to store a number of large specifications or to construct the codes by request. The first approach assumes extensive memory consumption, which is inappropriate for many applications, such as those for mobile devices. The second approach can be numerically unstable and hard to implement in low-end hardware. One of the solutions is specifying a family of codes by a sequence of subchannels sorted by reliability. However, this solution makes it impossible to separately optimize each code from the family.Purpose:Developing a method for compact specifications of polar codes and subcodes.Results:A method is proposed for compact specification of polar codes. It can be considered a trade-off between real-time construction and storing full-size specifications in memory. We propose to store compact specifications of polar codes which contain frozen set differences between the original pre-optimized polar codes and the polar codes constructed for a binary erasure channel with some erasure probability. Full-size specification needed for decoding can be restored from a compact one by a low-complexity hardware-friendly procedure. The proposed method can work with either polar codes or polar subcodes, allowing you to reduce the memory consumption by 15–50 times.Practical relevance:The method allows you to use families of individually optimized polar codes in devices with limited storage capacity. 

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