Development of a selective assembly card of the «Koadut» lens

The work is devoted to the development of a selective assembly card of the «Koadut» lens, depending on the actual thickness of each of the seven lenses included in the optical scheme of the objective. Criteria for sorting options are substantiated, a macro for processing a file with the results of measurements of actual lens thicknesses, which forms an assembly card, is created. The macro was tested on a test file with a normal distribution of deviations from the nominal value of a batch of one hundred lenses.

NemFi

This paper presents NemFi: a trace-driven WiFi emulator. NemFi is a record-and-replay emulator that captures traces representing real WiFi conditions, and later replay these traces to reproduce the same conditions. In this paper, we demonstrate that the state-of-the-art emulator that was developed for cellular links cannot emulate WiFi conditions. We identify the three key differences that must be addressed to enable accurate WiFi record-and-replay: WiFi packet losses, medium-access control, and frame aggregation. We then extend the existing cellular network emulator to support WiFi record-and-replay. We evaluate the performance of NemFi via repeated experimentation across different WiFi conditions and for three different types of applications: speed-test, file download, and video streaming. Our experimental results demonstrate that average application performance over NemFi and real WiFi links is similar (with less than 3 percent difference).

Automated Assignment of Proteoform Classification Levels

Proteoform identification is required to fully understand the biological diversity present in a sample. However, these identifications are often ambiguous because of the challenges in analyzing full length proteins by mass spectrometry. A five-level proteoform classification system was recently developed to delineate the ambiguity of proteoform identifications and to allow for comparisons across software platforms and acquisition methods. Widespread adoption of this system requires software tools to provide classification of the proteoform identifications. We describe here implementation of the five-level classification system in the software program MetaMorpheus, which provides both bottom-up and top-down identifications. Additionally, we developed a stand-alone program called ProteoformClassifier that allows users to classify proteoform results from any search program, provided that the program writes output that includes the information necessary to evaluate proteoform ambiguity. This stand-alone program includes a small test file and database to evaluate if a given program provides sufficient information to evaluate ambiguity. If the program does not, then ProteoformClassifier provides meaningful feedback to assist developers with implementing the classification system. We tested currently available top-down software programs and found that none of them other than MetaMorpheus provided sufficient information regarding identification ambiguity to permit classification.

PENERAPAN ALGORITMA INTERPOLATIVE CODING PADA APLIKASI KOMPRESI FILE GAMBAR

The large amount of data that has been stored in memory or hard disk will result in increasing the amount of usage capacity on the storage media. Large file sizes can also affect the time of sending or transferring data between storage media. Therefore humans conduct a study in order to have alternative ways to overcome these problems, one of them is by means of compression techniques. In this research, an image file compression application program was built using the interpolative coding method. In building applications using Visual Basic.Net software. The construction of this application is expected to reduce storage media capacity usage. In this testing phase is done with an image file type that is a test file with RGB color type.Keywords: Compression, Image file, Interpolative Coding Algorithm

A Change Recommendation Approach Using Change Patterns of a Corresponding Test File

Change recommendation improves the development speed and quality of software projects. Through change recommendation, software project developers can find the relevant source files that they must change for their modification tasks. In an existing change-recommendation approach based on the change history of source files, the reliability of the recommended change patterns for a source file is determined according to the change history of the source file. If a source file has insufficient change history to identify its change patterns or has frequently been changed with unrelated source files, the existing change-recommendation approach cannot identify meaningful change patterns for the source file. In this paper, we propose a novel change-recommendation approach to resolve the limitation of the existing change-recommendation method. The basic idea of the proposed approach is to consider the change history of a test file corresponding to a given source file. First, the proposed approach identifies the test file corresponding to a given source file by using a source–test traceability linking method based on the popular naming convention rule. Then, the change patterns of the source and test files are identified according to their change histories. Finally, a set of change recommendations is constructed using the identified change patterns. In an experiment involving six open-source projects, the accuracy of the proposed approach is evaluated. The results show that the accuracy of the proposed approach can be significantly improved from 21% to 62% compared with the existing approach.