Aeromagnetic survey in Wisconsin 1997-98; digital data files

NOTE: This article was published in a former series of GEUS Bulletin. Please use the original series name when citing this article, for example: Stemp, R. W. (1997). Airborne geophysical surveys in Greenland – 1996 update. Geology of Greenland Survey Bulletin, 176, 75-79. https://doi.org/10.34194/ggub.v176.5069 _______________ Two major airborne geophysical surveys were carried out in 1996, the third year of a planned five-year electromagnetic and magnetic survey programme (project AEM Greenland 1994–1998) financed by the Government of Greenland, and the second year of an aeromagnetic survey programme (project Aeromag) jointly financed by the governments of Denmark and Greenland; both projects are managed by the Geological Survey of Denmark and Greenland (GEUS). The two 1996 surveys were: 1) Project Aeromag 1996 in South-West and southern West Greenland;2) Project AEM Greenland 1996 in South-West Greenland. All areas surveyed and planned for future surveys as of March 1997 are shown in Figure 1. Results of both the 1996 surveys were released in March 1997, as a continuation of a major effort to make high quality airborne geophysical data available for both mineral exploration and geological mapping purposes. The data acquired are included in geoscientific databases at GEUS for public use; digital data and maps may be purchased from the Survey. The main results from the 1996 surveys are described in Thorning & Stemp (1997) and Stemp (1997). Two further new airborne surveys have already been approved for data acquisition during the 1997 field season, with subsequent data release in March 1998. A summary of all surveys completed, in progress or planned since the formal inception of project AEM Greenland 1994–1998 is given in Table 1. The programme was expanded to include a separate regional aeromagnetic survey in 1995, provisionally for 1995–1996, with extension subject to annual confirmation and funding.

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A Novel approach of data deduplication for distributed storage

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.4.10040 ◽

2018 ◽

Vol 7 (2.4) ◽

pp. 46 ◽

Cited By ~ 2

Author(s):

Shubhanshi Singhal ◽

Akanksha Kaushik ◽

Pooja Sharma

Keyword(s):

Distributed Storage ◽

Search Time ◽

Search Tree ◽

Digital Data ◽

Binary Search Tree ◽

Data Deduplication ◽

Novel Approach ◽

Best Value ◽

Chunk Size ◽

Data Files

Due to drastic growth of digital data, data deduplication has become a standard component of modern backup systems. It reduces data redundancy, saves storage space, and simplifies the management of data chunks. This process is performed in three steps: chunking, fingerprinting, and indexing of fingerprints. In chunking, data files are divided into the chunks and the chunk boundary is decided by the value of the divisor. For each chunk, a unique identifying value is computed using a hash signature (i.e. MD-5, SHA-1, SHA-256), known as fingerprint. At last, these fingerprints are stored in the index to detect redundant chunks means chunks having the same fingerprint values. In chunking, the chunk size is an important factor that should be optimal for better performance of deduplication system. Genetic algorithm (GA) is gaining much popularity and can be applied to find the best value of the divisor. Secondly, indexing also enhances the performance of the system by reducing the search time. Binary search tree (BST) based indexing has the time complexity of which is minimum among the searching algorithm. A new model is proposed by associating GA to find the value of the divisor. It is the first attempt when GA is applied in the field of data deduplication. The second improvement in the proposed system is that BST index tree is applied to index the fingerprints. The performance of the proposed system is evaluated on VMDK, Linux, and Quanto datasets and a good improvement is achieved in deduplication ratio.

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User Innovation and System Management

Information Technology and Military Power ◽

10.7591/cornell/9781501749568.003.0005 ◽

2020 ◽

pp. 109-135

Author(s):

Jon R. Lindsay

Keyword(s):

Air Force ◽

Relevant Information ◽

Digital Data ◽

Software Systems ◽

Weapon System ◽

Defense Contractors ◽

Air Defense ◽

Weapon Systems ◽

Data Files ◽

Operations Center

This chapter investigates the Combined Air Operations Center (CAOC), the analogue to the Fighter Command Ops Room in the modern U.S. Air Force. The air force formally designates the CAOC as a weapon system, even as it is basically just a large office space with hundreds of computer workstations, conference rooms, and display screens. The CAOC is an informational weapon system that coordinates all of the other weapon systems that actually conduct air defense, strategic attack, close air support, air mobility and logistics, and intelligence, surveillance, and reconnaissance (ISR). One might be tempted to describe the CAOC as “a center of calculation,” but modern digital technology tends to decenter information practice. Representations of all the relevant entities and events in a modern air campaign reside in digital data files rather than a central plotting table. The relevant information is fragmented across collection platforms, classified networks, and software systems that are managed by different services and agencies. Thus, in each of the four major U.S. air campaigns from 1991 to 2003, CAOC personnel struggled with information friction. They rarely used the mission planning systems that were produced by defense contractors as planned, and they improvised to address emerging warfighting requirements.

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Designing a Nasal Prosthesis using CAD-RP Technology

International Journal of Prosthodontics and Restorative Dentistry ◽

10.5005/jp-journals-10019-1058 ◽

2012 ◽

Vol 2 (3) ◽

pp. 108-112

Author(s):

R Vanitha ◽

K Ramkumar ◽

G Rajtilak ◽

V Rajasekar

Keyword(s):

Digital Data ◽

3D Image ◽

3 Dimensional ◽

Digital Database ◽

Nasal Prosthesis ◽

Nasal Defect ◽

Patient Reported ◽

Defect Area ◽

Computer Aided ◽

Data Files

ABSTRACT A 37-year-old female patient reported to the hospital with a nasal defect due to carcinoma. She was previously restored with nasal prostheses, but was not satisfied with its cosmetic appeal. A computerized tomographic (CT) scan of the defect area was made and converted into 3- dimensional (3D) digital data using dedicated medical imaging software. From the 3D image, measurements of the defect were calculated and compared with various nasal fossa measurements available in the digital database. A 3D nose model which had measurements that closely matched the defect area was extracted and superimposed on the defect area and margins adjusted. The data files were then sent for rapid prototyping (RP). A RP model was fabricated which was duplicated in wax and processed. The final result was a nasal prosthesis that conformed well to the patients’ face and was also esthetically acceptable. The main advantage of computer-aided designing (CAD)-RP is that it allows trying various nasal forms on the patients face within few hours. This saves chair time, eliminates the impression step and provides patient and dentist an option of variety. How to cite this article Vanitha R, Ramkumar K, Rajtilak G, Rajasekar V. Designing a Nasal Prosthesis using CAD-RP Technology. Int J Prosthodont Restor Dent 2012;2(3):108-112.

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Data-In-Image: a novel concept for data manipulation and encryption implementation

10.5194/egusphere-egu21-309 ◽

2021 ◽

Author(s):

Mohamed Abdelwahed

Keyword(s):

Machine Learning ◽

Binary Data ◽

Numerical Data ◽

Digital Data ◽

Response Code ◽

Quick Response Code ◽

Data Files ◽

Novel Concept ◽

Encryption Method ◽

Image Format

Conventionally, the way of storing and exchange numerical data depends mainly on binary data files in compressible form. In this era of the Big Data and machine learning systems and with the accumulation of data with different forms and types, it is important to find an alternative way for handling the data. The binary data are software dependent which does not exhibit its content and type without accessing the data by the proper software. In addition, it does not have any encryption ability. To solve this issue, we propose a new concept to handle the digital data in a descriptive, encrypted, compressed form, and able to be previewed. The idea is to pack the binary bits into a bitmap image with specific coding scheme. This approach employs the Steim scheme as a primary compression tool with a 128-bit encryption method then packs the encrypted codes into a WebP image file. The WebP image is featured by being an independent, web friendly, and highly compressed file. In order to make the file describing its contents, we reserved some pixels as coded descriptive pixels. By this way, the now packed data exhibits its contents and type during image preview.It is proven that the Data-In-Image format, regardless of being encrypted, occupies the least amount of storage space among other image formats that can be easily handled, stored, and shared through clouds and devices safely with a lower cost. For seismic data, &#160;the size of the WebP image comprises ~20% of the corresponding binary size with a bit-rate of ~5.6 b/s which is smaller than that of the Steim form, 27% and 8.9 b/s, respectively. Regarding the compression speed, it is found that the code compresses data with a rate of ~11,118 samples/s or&#8201;~&#8201;44 Kbytes/s in average.In addition, the data image is able to be digitally scanned and with some modifications can be remotely accessed like the quick response code, the thing that is not possible in the binary form. Moreover, the descriptive pixels in the image allow the implementations of smart tools to archive and classify data by machine learning and recognition algorithms.

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