On the ways of forming information structures for modeling objects, environments and processes

The paper discusses the well-known concepts of matter, objects, environments, information and information field in relation to the proposed information representation of the interaction of objects and environments based on the description of their information structures. An overview of the methods of forming information structures for modeling objects, environments and processes is given. It is shown that without using the concept of the environment, as an entity in which objects exist and are reflected in time and in a certain space, it is not always possible to accurately describe the change in the state of an object. This is due to the fact that the current state of an object depends both on the action of other objects on it and on its ability to reflect a specific physical or other environment in which it and other objects exist. From the presented review of approaches to object-oriented methods of modeling objects, environments and processes, it can be concluded that it is fundamentally important to take into account the physical and spatial environment in which they interact in object methods of modeling and programming complex objects and systems. Using programming languages, we can create and even manage the information structures of objects and environments. They are called abstract because they are not informational representations of the corresponding physical objects and environments. An example of such capabilities are special programming languages ​​for creating virtual objects and virtual worlds. Created on the basis of special programming languages, virtual simulators help specialists of various professions acquire skills in managing real objects, technological processes, etc.

Object-oriented methods of analyzing the parameters of interaction of speech and music language

The article considers the methodological principles of analyzing the parameters of interaction of speech and music language in the context of object-oriented methods of Astafiev’s intonation theory, Yavorsky’s concept of music speech, the views on and ideas about the intonation basis of speech of Bonfeld, Medushevsky, Aranovsky and Nazaikinsky, and the new system of interaction of speech and music in the works of Helmut Lachenmann and  Luciano Berio. Music language and speech are the phenomena allowing for various intersections, complementarities and mutual interferences. These factors manifest themselves in various aspects spotlighting particular sides of these parameters characterizing speech and music language. Since there’s no unified methodology for analyzing these parameters at the moment, it is reasonable to study a music composition as a text (in a broad sense) using various methods of analysis. The author suggests considering the parameters of interaction of speech and music language in terms of object-oriented methods. In the works of composers, music and speech have different forms of interaction and, consequently, need to be studied via different analytical approaches. Comprehensive consideration of a piece of music as a text (by means of various approaches) allows considering it as an intercultural universum representing the code of the epoch. Based on the peculiarities of interpretation of voice as an instrument, and speech as music, and the opportunities it gives, the author formulates the classification of creative methods and principles and the system of analysis which can be used in musicology.   

Implementing a Work Program Monitoring Information System (Case Study at PT Telkom Tbk)

This research was conducted by purposed to gained knowledge regarding process of implementing the work programs which carried out by PT. Telkom, especially at Network Division of Central Jakarta area around these days. while Analyze these work program system and create WEB-based work program to monitoring system according to company requirements and regulations. PT. Telkom, especially Network Division of Central Jakarta area, which engaged in telecommunications and has the main duty as operation and maintenance of equipment that owned by PT. Telkom, especially Network Division at Central Jakarta area, so it could keep the assets owned by company always operating normally. According to research that carried out by employees itself, there are so many problems in creating work programs cause it was still manual, Assistant Manager of Network Area were difficulty to monitoring the development of work programs and report the results aswell it was because there has no integration in one application system, Analysis and this pattern of information system by object-oriented methods with UML notations. With web-based work program monitoring information system, it was expected that it could be a solution to sort of problems that faced in process of implementing work programs.

Improved CNN Classification Method for Groups of Buildings Damaged by Earthquake, Based on High Resolution Remote Sensing Images

Effective extraction of disaster information of buildings from remote sensing images is of great importance to supporting disaster relief and casualty reduction. In high-resolution remote sensing images, object-oriented methods present problems such as unsatisfactory image segmentation and difficult feature selection, which makes it difficult to quickly assess the damage sustained by groups of buildings. In this context, this paper proposed an improved Convolution Neural Network (CNN) Inception V3 architecture combining remote sensing images and block vector data to evaluate the damage degree of groups of buildings in post-earthquake remote sensing images. By using CNN, the best features can be automatically selected, solving the problem of difficult feature selection. Moreover, block boundaries can form a meaningful boundary for groups of buildings, which can effectively replace image segmentation and avoid its fragmentary and unsatisfactory results. By adding Separate and Combination layers, our method improves the Inception V3 network for easier processing of large remote sensing images. The method was tested by the classification of damaged groups of buildings in 0.5 m-resolution aerial imagery after the earthquake of Yushu. The test accuracy was 90.07% with a Kappa Coefficient of 0.81, and, compared with the traditional multi-feature machine learning classifier constructed by artificial feature extraction, this represented an improvement of 18% in accuracy. Our results showed that this improved method could effectively extract the damage degree of groups of buildings in each block in post-earthquake remote sensing images.

Analysis on the Relationship between Mangrove and Aquaculture in Maowei Sea Based on Object-oriented Method

Before 2000, a large number of mangrove forests in Guangxi were cut down for aqua-cultural purposes. After 2000, with the introduction of national, provincial and municipal policies on mangrove protection, this phenomenon was less frequently seen. By using the object-oriented method, referring to the spectral and texture characteristics of the ground target, and using the Landsat remote sensing images of 2000-2019, this paper extracts and analyzes the area and change of mangrove and aquaculture area in Maowei sea, Guangxi. The results show that the use of object-oriented methods can extract mangroves and aquaculture areas with higher accuracy. The area of mangroves generally shows an upward trend, with the area of aquaculture increasing first and then decreasing.

Effective Identification of Terrain Positions from Gridded DEM Data Using Multimodal Classification Integration

Terrain positions are widely used to describe the Earth’s topographic features and play an important role in the studies of landform evolution, soil erosion and hydrological modeling. This work develops a new multimodal classification system with enhanced classification performance by integrating different approaches for terrain position identification. The adopted classification approaches include local terrain attribute (LA)-based and regional terrain attribute (RA)-based, rule-based and supervised, and pixel-based and object-oriented methods. Firstly, a double-level definition scheme is presented for terrain positions. Then, utilizing a hierarchical framework, a multimodal approach is developed by integrating different classification techniques. Finally, an assessment method is established to evaluate the new classification system from different aspects. The experimental results, obtained at a Loess Plateau region in northern China on a 5 m digital elevation model (DEM), show reasonably positional relationship, and larger inter-class and smaller intra-class variances. This indicates that identified terrain positions are consistent with the actual topography from both overall and local perspectives, and have relatively good integrity and rationality. This study demonstrates that the current multimodal classification system, developed by taking advantage of various classification methods, can reflect the geographic meanings and topographic features of terrain positions from different levels.

THE EXTRACTION OF POST-EARTHQUAKE BUILDING DAMAGE INFORMATIOM BASED ON CONVOLUTIONAL NEURAL NETWORK

The seismic damage information of buildings extracted from remote sensing (RS) imagery is meaningful for supporting relief and effective reduction of losses caused by earthquake. Both traditional pixel-based and object-oriented methods have some shortcoming in extracting information of object. Pixel-based method can’t make fully use of contextual information of objects. Object-oriented method faces problem that segmentation of image is not ideal, and the choice of feature space is difficult. In this paper, a new stratage is proposed which combines Convolution Neural Network (CNN) with imagery segmentation to extract building damage information from remote sensing imagery. the key idea of this method includes two steps. First to use CNN to predicate the probability of each pixel and then integrate the probability within each segmentation spot. The method is tested through extracting the collapsed building and uncollapsed building from the aerial image which is acquired in Longtoushan Town after Ms 6.5 Ludian County, Yunnan Province earthquake. The results show that the proposed method indicates its effectiveness in extracting damage information of buildings after earthquake.

Description Mirror Features and Data Structures in an Optical CAD System

CAD is presented in optical design, the use of object-oriented methods, optical lens structure described. Using object-oriented techniques to describe the object lens, and with VC++ language features to build such systems, construct a data structure of the optical system components. This method has a simple structure, portability, reusability of characteristics.