Development of Flight Multifunctional Indicator Based on A320 and B737 NG Flight Indicator

The objectives of this research are: to know the concept of modeling and simulation the cockpit display based on disadvantages and differences between A320 and B737NG; to offer the development and new technology to design the development (new) flight instruments of the display based on Airbus A320 and Boeing B737 NG flight instrument technology. Methodologies that have been used in this research are literature review, interview/discussion/questionnaire, and descriptive analysis. Questionnaire towards the users/pilots who flies airplane A320 or B737 NG. For the questionnaire, the Likert-scale method is utilized to collect data and information. This research result’s in finding that: 1. the technology of flight instrument system between A320 and B737 NG visually displays similarity with several differences such as ergonomic side, ECAM technology, and VSD technology. 2. Based on works of literature review and response from the users/pilots, the author finds and proposes several technologies or requirements to apply in the new type model of PFD and Multi-function Display, they are including: PFD and MFD merged into one display only with some additional menu buttons; ECAM + engine warning display, ECAM + systems display, and digital instruction to solve the problem merged into one display only with some additional buttons; display design is using the fully digital display, computerized system, LCD technology, VSD, and EHSI technology, and layout display is using configuration “basic T”; standby flight instrument merged into one display only with some additional menu buttons

Identifikasi kecakapan inovasi lembaga riset di Indonesia berbasis dokumen

Introduction. Duplication in inventions produced by research institutions in Indonesia becomes an issue. It is important to map the specialization of the invention in research institutions. This study examines the mapping of the innovation in research institutions in Indonesia. Data Collection Method. This study uses a patent-based technology document analysis method to map the potential of technology. The data used is patent data registered in the Direktorat Jenderal Kekayaan Intelektual (DJKI) database. Data Analysis. Metadata analysis was conducted by using the K-Means Klastering method with R software. Results and Discussions. The findings in the pre-analysis show that when the independent variable involved in the model are very large, the Localized feature selection method can effectively select variables without losing much information. There are 5 dominant technology groups that can be produced by research institutions in Indonesia, namely 1) Technology related to the development of measurement and testing instrument technology; 2) Technologies related to food and food ingredients; and 3) microstructural test equipment / detectors; 4) radar technology; 5) Technology in agriculture. Conclusion. The findings show that there are still overlapping inventions by several research institutions in the same technology cluster. K-means clustering with LFSBSS pre analysis has a clear performance in the technology cluster space.

Productivity and competitiveness in medium-large forestry-furniture and automotive companies in the Municipality of Durango, Dgo.

The research determines the factors and dimensions that influence the productivity and competitiveness of medium-large companies in the forestry-furniture and automotive sector of the Municipality of Durango, in turn allowing these factors and dimensions to be transferred to a validated instrument. Technology support streamlines the analysis of the information that companies provide to determine the level of productivity and competitiveness. Know the status of companies with their various internal indicators, it shows the need to deploy an empirical study that involves variables and factors, which in turn allows to be Analyzed the results to establish clear and objective strategies all through a Web application. The validity of the instrument content with the V-Aiken methodology with value of .845 and the reliability of the Cronbach's alpha instrument α = .912 allows the instrument to be applied to obtain the Productivity Level 4.4 and the Competitiveness Level 3.8 in one scale of 0 to 5.