Prototype of a remotely controlled model of a tugboat with an azimuth rudder and a hazard identification function

The author’s approach, based on the technology of control actions, is proposed for the interface display of the algorithm for the operation of an automatic tugboat with an azimuth rudder and a hazard assessment function. To define the object as presumably dangerous, the article used the formulas of the direct and inverse navigation problems. To compare the coordinates of the vessel and the perceived “hazard”, one first needs to enter data, process the information, and display information that is understandable for the decision-maker. To eliminate the misunderstanding of this situation, the operation of the danger prevention algorithm was demonstrated using the visual basic programming language as an example. When constructing an algorithm for the safe movement of the vessel and the existing danger, each object, even a stand-alone one, has many coordinate points. Knowing the number of points of coordinates of the vessel and “danger”, they were taken as n and m, respectively. The algorithm searches for the optimal point-object. The scheme of interaction of the components of the automatic tug azimuth model (ABA) is proposed. It is based on a Raspberry Pi single-board computer with an Arduino Mega board connected to it. A program has been written to control the ABA model using omnidirectional wheels to simulate maneuvering on water.

A Fragmentation Region-based Skyline Computation Framework for a Group of Users

Skyline processing, an established preference evaluation technique, aims at discovering the best, most preferred objects, i.e. those that are not dominated by other objects, in satisfying the user’s preferences. In today’s society, due to the advancement of technology, ad-hoc meetings or impromptu gathering are becoming more and more common. Deciding on a suitable meeting point (object)for a group of people (users) to meet is not a straightforward task especially when these users are located at different places with distinct preferences. A place which is close by to the users might not provide the facilities/services that meet all the users’ preferences; while a place having the facilities/services that meet most of the users’ preferences might be too distant from these users. Although the skyline operator can be utilised to filter the dominated objects among the objects that fall in the region of interest of these users, computing the skylines for various groups of users in similar region would mean rescanning the objects of the region and repeating the process of pair wise comparisons among the objects which are undoubtedly unwise. On this account, this study presents a region-based skyline computation framework which attempts to resolve the above issues by fragmenting the search region of a group of users and utilising the past computed skyline results of the fragments. The skylines, which are the objects recommended to be visited by a group of users, are derived by analysing both the locations of the users, i.e. spatial attributes, as well as the spatial and non-spatial attributes of the objects. Several experiments have been conducted and the results show that our proposed framework outperforms the previous works with respect to CPU time.

Mathematical model of scanning infrared sensor reaction to point object in telecommunication systems

The problem of constructing a «correct» mathematical model of the bell-shaped reaction of a scanning infrared sensor to a point object is considered. The suggested model takes into account changes in amplitude, duration and a shape of channel pulses in different situations when a light spot hits photosensitive areas. The results of computer modeling have shown low efficiency of traditional matched filtering in estimating amplitude of pulses from point objects when the sin2 function is used as a pulse model.

Using visual analysis in tourism attraction management of puncak menara api gunung Saribu village, Munte district, Karo regency

Puncak Menara Api in Gunung Saribu Village, Munte Sub-District, Karo Regency, is a buffer zone of the protected forest area in Karo Regency. In 2020, all the local communities through village funds are trying to pioneer the development of Puncak Menara Api as a new tourist attraction. In relation to such an effort, the community service team of Universitas Sumatera Utara assisted the people in Gunung Saribu Village in creating the concept of developing Puncak Menara Api as a nature-based and education-based tourist attraction in Karo Regency. The assistance includes but not limited to improving the capacity of tourism management for rural communities, mapping the tourist sites, marketing the tourist sites, and so forth. For the many development activities items that must be done, the team selected mapping tourist sites as the only activity to be carried out in 2020. This study was conducted using a qualitative method. The data were collected using focus group discussion, observation, and interview techniques. The data were analyzed using visual analysis, including visualizing the point object attributes, visualizing point object distribution, and visualizing spatial groupings. The results of the study are: (i) the visualization on the point object attributes finds four main components related to tourism: Attractions, Accessibility, Amenities, and Ancillary Services; (ii) the visualization on the point object distribution results in predicting the initial picture of the arrangement of tourist attractions in Puncak Menara Api; and (iii) the visualization on the spatial groupings results in designing the tourist location in a three-dimensional design.

COORDINATOR SIMULATION COMPUTER MODEL WORKING AS APART OF BIOMETRIC RECOGNITION SYSTEM

Simulation computer model of an optoelectronic coordinate measurer for point objects is considered that is a part of the subject recognition system based on biometric features. The presented model allows you to virtually explore and analyze the processes of functioning of the coordinator, which ensures optimal coordination of parameters and characteristics of various parts of the device, as well as to choose the most effective algorithm for processing the resulting digital image by minimizing the error of measuring the coordinates of a single point object. The simulation is based on the Monte Carlo method of multiple statistical tests, which provides most accurate representation of noise processes that occur when receiving and converting optical information in the optical-electronic path of a coordinate device, since these processes, under solid equal conditions, make a decisive contribution to the final measurement error. The principles of the model are described and the results obtained are discussed, as well as the future development of the model and its application for solving problems of optimal system design of biometric recognition systems.

Certification of a two-channel automated infrared imaging synthesis system to test matrix photo receivers

A program and methodology of the primary (periodic) certification of the two-channel automated system of synthesis of dynamic and static infrared images to control the characteristics of matrix photo reception devices has been developed. The method of appraisal of the most significant characteristics of the system is described: the accuracy of positioning of a three-coordinated scanning device with numerical software control; The size of the linear field in the plane of the image of the objects and background channels; Working spectral range and irradiation range the diameter of the point object and the energy concentration factor in the object scattering spot in the plane of the image of the object's channel. Confirmed by independent irradiance levels change in optical object channel in the range 10–9–10–6 W/cm2, and the background channel 10–9–10–7 W/cm2. The minimum size of a dynamic object does not exceed 30 μm, the speed of its displacement reaches 250 μm/s. Three-dimensional precision positioning system provides repeatability for coordinates less than 2 μm range up to 200 mm.

A real-time semantic visual SLAM approach with points and objects

Visual simultaneously localization and mapping (SLAM) is important for self-localization and environment perception of service robots, where semantic SLAM can provide a more accurate localization result and a map with abundant semantic information. In this article, we propose a real-time PO-SLAM approach with the combination of both point and object measurements. With point–point association in ORB-SLAM2, we also consider point–object association based on object segmentation and object–object association, where the object segmentation is employed by combining object detection with depth histogram. Also, besides the constraint of feature points belonging to an object, a semantic constraint of relative position invariance among objects is introduced. Accordingly, two semantic loss functions with point and object information are designed and added to the bundle adjustment optimization. The effectiveness of the proposed approach is verified by experiments.