Types Of Objects Research Articles

СТИЛІСТИЧНЕ ТРАКТУВАННЯ ЗРАЗКІВ ЛЬВІВСЬКОЇ АРХІТЕКТУРИ 1990-2000-Х РОКІВ. ПРОБЛЕМИ ТЕРМІНОЛОГІЇ ТА СВІТОГЛЯДНОЇ ДЕТЕРМІНАЦІЇ

The article considers the problem of stylistic definition of objects of Lviv architecture in the 1990-2000s. Having studied the similar Ukrainian scientific publications, here is presented own arguments regarding the correct terminology for this type of objects. An important role is also given to the worldview prevailing at that time in professional circles, as it makes it possible to determine which values in design they adhered to - modernist or postmodern. On the basis of the conducted analysis, it was established that in the period of 1990-2000s, the development of processes that began in the late Soviet era, when experiments with regional tradition and local identity took place on a regional scale within the framework of so-called "individual projects" ( for example "Carpathian style"). Therefore, the objects of Lviv architecture of the 1990-2000s are mostly devoid of ambiguity and irony characteristic of postmodernism, as well as a deliberate desystematization of stylistic and tectonic rules. The postmodern understanding of form as language is not characteristic of post-Soviet samples. In view of the comparative assessment, it was established that the stylistic definition of Lviv architecture of the 1990s-2000s can be associated with modernism to a much greater extent than it was believed until now. The sum of the listed factors and the nature of the analyzed objects indicate that a probably more correct term for these monuments is "decorated modernism" or "deco-modernism". It was established that despite the fact that the practice of standard design was the object of unanimous criticism both in the professional environment and at the general societal level, this did not mean criticism of modernism as such, since (neo-)modernist objects are built on the so-called individual projects, were generally approved and were examples of a positive alternative. The main worldview motive of that time in the field of creating architectural form was the desire for individualism and imagery, which is not at all identical to postmodernism.

Standing up to problematic content on social media: which objection strategies draw the audience’s approval?

Abstract Problematic content on social media can be countered through objections raised by other community members. While intended to deter offenses, objections can influence the surrounding audience observing the interaction, leading to their collective approval or disapproval. The results of an experiment manipulating seven types of objections against common types of offenses indicate audiences’ support for objections that implore via appeals and disapproval of objections that threaten the offender, as they view the former as more moral, appropriate, and effective compared to the latter. Furthermore, audiences tend to prefer more benign and less threatening objections regardless of the offense severity (following the principle of “taking the high road”) instead of objections proportionate to the offense (“an eye for an eye”). Taken together, these results show how objections to offensive behaviors may impact collective perceptions on social media, paving the way for interventions to foster effective objection strategies in social media discussions.

Methodology for Designing Road Vehicle Service Facilities

In modern methods of technological design, the capacity of service facilities depends on the number of cars entering them per unit of time. At the same time, regardless of the type of service object, the number of visits is somehow associated with intensity of the vehicle traffic on a given road, as well as with one of the characteristics that determine speed of this event. Such a characteristic, for example, for service or maintenance stations is intensity of vehicle failures, for fuelling stations – intensity of fuel consumption, for hotels and parking lots – intensity of the onset of fatigue for drivers and passengers. This gives ground for conclusion that there is a significant similarity between the processes that result in an event that can be called a visit to a service facility. Thus, the purpose of this theoretical study was to develop a common approach applicable to all road service facilities to determine the number of such events, as well as to develop a common methodology for their design.A characteristic feature of operation of service objects is a time-varying flow of demand for the operation of service facilities, as well as variable labour intensity and duration of troubleshooting or the provision of other service services. Systems in which the moments of receipt of requests for service and the duration of the services themselves are variable and random are called a queuing system. Therefore, to justify the number of car arrivals at road service facilities, the authors proposed a probabilistic method, the main tools of which are provisions and mathematical apparatus of the queuing theory.The main condition for functioning of the queuing system is the ratio between the incoming flow of requirements and the absolute throughput of the system. Thus, the mathematical model proposed by the authors considers the performance indicators of service facilities, depending on the size of the incoming flow of requirements and its variation, on the one hand, and on the throughput and performance of service facilities, on the other hand.

Single-pixel real-part and magnitude imaging system based on digital micromirror device

Single-pixel imaging (SPI) can capture images using a single-pixel detector. However, conventional SPI schemes only provide a magnitude image of the object, where the phase information is completely lost. Here, we present a dual-modal SPI (DMSPI) system capable of simultaneously capturing the real-part and magnitude images. Since the real-part image fuses the phase distribution, DMSPI has a strong information acquisition capability for all types of objects. The DMSPI system utilizes the two reflection arms provided by the digital micromirror device (DMD) to perform zero-frequency detection in one arm and bucket detection in the other to achieve dual-modal imaging. Benefiting from the unique modulation characteristics of DMD, the DMSPI system is simple and efficient, with high spatial resolution and fast imaging speed. Thus, it might find broad applications in biomedical diagnostics and industrial inspection.

Semantic Segmentation of Urban Airborne LiDAR Point Clouds Based on Fusion Attention Mechanism and Multi-Scale Features

Semantic segmentation of point clouds provided by airborne LiDAR survey in urban scenes is a great challenge. This is due to the fact that point clouds at boundaries of different types of objects are easy to be mixed and have geometric spatial similarity. In addition, the 3D descriptions of the same type of objects have different scales. To address above problems, a fusion attention convolutional network (SMAnet) was proposed in this study. The fusion attention module includes a self-attention module (SAM) and multi-head attention module (MAM). The SAM can capture feature information according to correlation of adjacent point cloud and it can distinguish the mixed point clouds with similar geometric features effectively. The MAM strengthens connections among point clouds according to different subspace features, which is beneficial for distinguishing point clouds at different scales. In feature extraction, lightweight multi-scale feature extraction layers are used to effectively utilize local information of different neighbor fields. Additionally, in order to solve the feature externalization problem and expand the network receptive field, the SoftMax-stochastic pooling (SSP) algorithm is proposed to extract global features. The ISPRS 3D Semantic Labeling Contest dataset was chosen in this study for point cloud segmentation experimentation. Results showed that the overall accuracy and average F1-score of SMAnet reach 85.7% and 75.1%, respectively. It is therefore superior to common algorithms at present. The proposed model also achieved good results on the GML(B) dataset, which proves that the model has good generalization ability.

Objectives of State Human Rights Protection Activities in the Russian Federation

The paper defines the author’s approach to the concept, types, characteristics of the goals of state human rights protection. In its most general form, human rights protection includes a system of actions carried out by State bodies and organizations, as well as civil society institutions and international organizations, aimed at restoring violated and creating appropriate conditions for implementation of human and citizen rights, freedoms and legitimate interests, as well as collective rights and public interests of groups of citizens, commercial and non-commercial organizations.Researchers propose to distinguish the following types of human rights protection objectives: general and particular; basic and non-basic; final, intermediate and immediate; objectively true and objectively false; real and unreal; timely and untimely; substantive and instrumental. Indeed, the available academic developments on this issue are of great interest, but largely they characterize the human rights objectives enshrined in legislation, rather than practice of human rights protection.The paper elucidates and describes in detail such necessary signs of a human rights protection objective as its humanism, moral validity, social conditionality and legal significance.The classification of the types of human rights objectives is defined; it is proposed to distinguish strategic (general) and tactical (private) objectives; law enforcement, law-making and «law-enlightening» ones; positive and natural law human rights objectives.The paper concludes that there is a need for comprehensive consideration of the goals of human rights protection in legislation and law enforcement practice. It is also indicated that a necessary characteristic of human rights protection is its implementation by specific legal methods that are subject to strict regulation by means of provisions of existing normative legal acts or, in any case, they do not contradict them, and in addition, should not go beyond ethical norms and principles.

A dilated convolution-based feature adaptation method for detection of high aspect ratio objects in aerial images

In real scenarios, objects with high aspect ratios are actually very common, and such objects hold significant importance in the field of object detection. However, most of the existing object detection algorithms tend to overlook this specific type of object. After analyzing the statistical data, we observed a substantial decrease in mAP (mean Average Precision) for classical object detection algorithms when they are tasked with detecting only high aspect ratio objects. Therefore, we conducted an analysis of the factors that influence the detection performance of these objects and made the following improvements: (1) We introduced large-kernel attention convolution between the backbone network layers. This addition allows each position feature to have a larger receptive field, facilitating better feature learning; (2) By incorporating multiple sets of deformable convolutions for feature-adaptive processing, we were able to enhance the learning of characteristic information specific to the object itself. This approach also promotes network convergence. The proposed method yielded a significant improvement in accuracy, approximately 5[Formula: see text] higher than the baseline, when evaluated on the FGSD2021 dataset. Furthermore, our method outperformed the current best method by approximately 0.5[Formula: see text].

HDGT: Heterogeneous Driving Graph Transformer for Multi-Agent Trajectory Prediction via Scene Encoding.

Encoding a driving scene into vector representations has been an essential task for autonomous driving that can benefit downstream tasks e.g., trajectory prediction. The driving scene often involves heterogeneous elements such as the different types of objects (agents, lanes, traffic signs) and the semantic relations between objects are rich and diverse. Meanwhile, there also exist relativity across elements, which means that the spatial relation is a relative concept and need be encoded in a ego-centric manner instead of in a global coordinate system. Based on these observations, we propose Heterogeneous Driving Graph Transformer (HDGT), a backbone modelling the driving scene as a heterogeneous graph with different types of nodes and edges. For heterogeneous graph construction, we connect different types of nodes according to diverse semantic relations. For spatial relation encoding, the coordinates of the node as well as its in-edges are in the local node-centric coordinate system. For the aggregation module in the graph neural network (GNN), we adopt the transformer structure in a hierarchical way to fit the heterogeneous nature of inputs. Experimental results show that HDGT achieves state-of-the-art performance for the task of trajectory prediction, on INTERACTION Prediction Challenge and Waymo Open Motion Challenge.

Optimization of RF Frequencies in Dual-Frequency Capacitively Coupled Plasma Apparatus Using Genetic Algorithm (GA) and Plasma Simulation

As a method to optimize the power frequency of dual-frequency plasma, we propose an optimization method that combines genetic algorithm and plasma simulation. A two-dimensional plasma simulation model of Ar plasma was constructed with a fluid model. Combining this simulation model with a genetic algorithm, 300 cases of plasma conditions with high plasma density and small variation in electron density were calculated. As a result, the optimum conditions were 175 to 210 MHz for the high-frequency generator and 1.0 to 2.5 MHz for the low-frequency generator. Furthermore, two types of single objective functions that combine the electron density and the variation rate were proposed. The single objective functions with emphasis on electron density and with emphasis on variation rate were introduced, and each objective function was optimized.

Use of digital 3D urban models for view evaluation in building envelope design

A feature of digital 3D urban models is that they provide semantic information on various objects in urban space. This paper proposes a basic framework for obtaining visual information about the external conditions of a building to be designed using a 3D urban model. Ray emission and collision detection are used in a game engine to identify the type and distance of objects surrounding the building in the 3D urban model. Tagging the objects with their semantics identifies their type such as sky, building, road, greenery and so on. This paper also proposes setting two different viewpoints at the façade and the interior to consider the building design and the indoor visual environment design from both aspects of the whole building and individual rooms.

Scripting Scenarios of Pedestrian Behavior in a Computer Simulator of Security Monitoring System: A Practitioner’s Perspective

Abstract The subject of this paper is the AvatarTraffic simulator – a computer system capable of modelling in real time environments such as subway stations or airport halls populated with tens or hundreds of moving figures, which, in addition to pedestrian traffic typical for this type of objects, can perform predefined sequences of events and actions formulated as a simulation scenario. Thanks to the integration with a real monitoring system, the simulator, in addition to providing data streams (including video) generated by the virtual scene, is also able to dynamically respond to actions taken by the system’s staff. Using the Unity simulation engine as the implementation platform, a number of practical problems had to be solved during the development, two of which are the subject of this article: a) supervising and correcting the work of AI algorithms used in Unity to simulate the pedestrian movement of avatars, and b) a textual description of the scenario of events taking place on the stage in a way editable for experts planning tests of the monitoring system. Some more challenging cases of people movement are discussed (including creating queues and passing through doors) and the paper presents original algorithms correcting the work of the Unity’s built-in methods in the situations when the coordinated behaviour of people groups is required. Because of the specifics of the simulator environment the scenario needed to be expressed in a JSON text file, and the article presents the implemented mechanisms of its compilation directly to the C# runtime environment and discusses the original command language which was created to model sequences of events and actions making up the scenario.

삼국시대 동경 부장의 의미

In ancient East Asia, bronze mirrors were objects that enabled their creators and users to reflect their perceptions. Each ancient East Asian society interpreted and utilized the mirrors differently according to their needs.
 Instead of simply perceiving the Three Kingdoms Period’s bronze mirrors, especially Han-style bronze mirrors and Japanese bronze mirrors, as foreign artifacts, this paper aims to delve into the significance of the bronze mirrors in the Korean Peninsula during that time and examine how they were received and utilized by different communities.
 Southern Korean Peninsula during the 4th~6th centuries, which were part of the Three Kingdoms Period, is first sorted into five regions based on topography, water systems, and political entities. Next, the excavated context of bronze mirrors from each region is examined to study how these mirrors were buried and disposed of. The significance of bronze mirrors within ancient East Asian societies is, then, used as a reference to infer the importance of the mirrors within Korean communities during the Three Kingdoms Period.
 In conclusion, bronze mirrors were not in high demand within various Three Kingdoms Period societies on the Korean Peninsula unlike within the societies that existed in other parts of ancient East Asia. Furthermore, each society on the Korean Peninsula interpreted and utilized bronze mirrors in a unique way that aligned with its specific needs. This was dissimilar to practices observed in other ancient East Asian societies.
 The way an object is perceived varies from person to person. Sometimes, perceptions of objects are shared, reproduced, and diffused throughout societies. At other times, the perceptions slowly fade away. Through examining bronze mirrors, this paper demonstrates that a type of object can be received and utilized in diverse ways depending on the context of time and space.

A QUALITATIVE STUDY ABOUT FALSE PERCEPTION STUDENTS TOWARDS THE MAGNETIC RESONANCE IMAGING EQUIPMENT IN RADIOLOGY DEPARTMENT

Introduction-Magnetic resonance imaging has been called the most important development in medical diagnosis since the discovery of the x-ray 100 years ago. It became the most important tools of modern radiology Purpose-The aim of the study is to find out the students false perception towards the magnetic resonance imaging equipment in radiology department. Methodology- A prospective study was conducted by making objective type questionnaire and filled it by the students of paramedical college. Result-At the end of study, following results were observed the studys result revealed several key themes regarding false perceptions of MRI equipment among students.23.04% students expressed fear of radiation exposure. 19.82% students held misconceptions about the potential danger of MRI scan. These misconceptions may arise from a lack of understanding and underlying principles of MR technology.18.43% students think that MRI generates images of the body by emitting sound waves and measuring their echoes. The most common false believe that MRI is only used for bone scan (28.57%). 20.74% students think that MRI can cause cancer.29.49% students have no idea about noise during the MRI scan.38.80% students are not aware about the prohibited items to the MRI room. Conclusion- Comparing courses wise MRI safety knowledge in subjects by using chi-square test It is found statistically significant with p – Value 0.00623, It means course wise MRI safety knowledge were change.Comparing to the others course medical lab technology (MLT) students have better knowledge about MRI equipment.The study did not find any significant differences in false perception of MRI equipment based on age or gender among the students. It implies that age and gender may not be significant factors in shaping these perceptions within this particular group.

The development of the architecture of consular offices in Manchuria

The article analyses the choice of objects for consular offices according to five periods of time. The main problems that arose during the appearance of the first consular institutions are shown. The political and economic patterns of development of consular institutions are determined. The analysis of the collected materials made it possible to identify three types of consular objects. This gave an opportunity to form a more complete picture of the consular facilities in Manchuria. The authors give a brief overview of the consular offices and architects who were involved in the design of this type of objects, as well as the buildings that were adapted to accommodate consular offices in Manchukuo. The article also highlights the features of the work of the consular service and provides information on the specifics of the selection of sites for construction of consular offices.

Multi-Scale Indoor Scene Geometry Modeling Algorithm Based on Segmentation Results

Due to the numerous objects with regular structures in indoor environments, identifying and modeling the regular objects in scenes aids indoor robots in sensing unknown environments. Typically, point cloud preprocessing can obtain highly complete object segmentation results in scenes which can be utilized as the objects for geometric analysis and modeling, thus ensuring modeling accuracy and speed. However, due to the lack of a complete object model, it is not possible to recognize and model segmented objects through matching methods. To achieve a greater understanding of scene point clouds, this paper proposes a direct geometric modeling algorithm based on segmentation results, which focuses on extracting regular geometries in the scene, rather than objects with geometric details or combinations of multiple primitives. This paper suggests using simpler geometric models to describe the corresponding point cloud data. By fully utilizing the surface structure information of segmented objects, the paper analyzes the types of faces and their relationships to classify regular geometric objects into two categories: planar and curved. Different types of geometric objects are fitted using random sampling consistency algorithms with type classification results as prior knowledge, and segmented results are modeled through a combination of size information associated with directed bounding boxes. For indoor scenes with occlusion and stacking, utilizing a higher-level semantic expression can effectively simplify the scene, complete scene abstraction and structural modeling, and aid indoor robots’ understanding and further operation in unknown environments.

Comparing the Efficacy of Individual Approaches and Team-Based Approaches in Solving Clinical Case Vignettes.

Background Clinical case vignettes are a widely adopted pedagogical approach in medical education. The cases may be presented to students with a closed response option for objectivity. While solving clinical cases has demonstrated its effectiveness in enhancing medical students' clinical reasoning, there is an ongoing debate regarding the most effective approach: individual problem-solving or team-based problem-solving. Objective To observe and compare the score obtained from individual clinical problem-solving approaches versus team-based clinical problem-solving approaches. Methods After obtaining consent, a total of 100 students were randomly selected for the study. The participants were divided into two groups: an individual approach group (IAG) (n=25) and a team-based approach group (TAG) comprising 25 groups of three students each. Both groups were presented with a set of 10 clinical problems, each requiring a closed-answer response of "yes", "no", or "don't know". The participants' responses were recorded and analyzed to evaluate their problem-solving efficacy. Results A total of 25 responses were obtained from 25 students from the IAG group and 25 responses from 25 groups from the TAG group. There was no difference between the score in IAG (7.44±1.12) and TAG (7.52 1.66) p-value=0.58. There was no difference between individual scores in 10 questions between IAG and TAG groups. Conclusion The study found no significant score differences between individual and team-based clinical case-solving groups. Hence, for the objective type of case-solving pattern used in this study, a team-based approach may not be necessary. Further research is needed to explore factors for such findings in future studies.

Recognition of Aerodynamic Objects on Spectral Portraits Taking into Account Design Features of Turbojets

In the article the device of radar-tracking recognition allowing on the basis of the analysis of a design of impellent installation to define a class (type) of observable air object is considered. Determination of the class (type) of the observed object was carried out by studying the ratios of the modulation frequencies of the spectral radar portrait. The solving rule, as well as the device block diagram are obtained, allowing to define the class and, in addition, the type of the observed air object equipped with a turbojet engine. To form a posteriori probability density, the numerical method of Monte-Carlo was used. The results of the mathematical modelling, confirming the efficiency of the proposed device, are presented.

Exploring the Perception of the Effect of Three-Dimensional Interaction Feedback Types on Immersive Virtual Reality Education

Immersive virtual reality (VR) systems are becoming widely used for education with three-dimensional (3D) information. Specifically, three-dimensional spaces to create virtual environments can help increase students’ learning interest and ability with spatial interaction. Also, with the use of multimodal interaction, VR systems can provide highly effective ways to solve problems through natural experiences. Additionally, immersive environments can bring together people in remote locations, which has been increasingly applied in education applications with the use of technology to simulate real situations. However, effective interaction methods that improve the learning ability of people participating in educational activities in 3D immersive environments are yet to be well defined. In this study, we investigated the effect of the interaction feedback types on the perception of students participating in VR environments. We conducted the experiment on three types of interaction responses, and our study was designed as a virtual chemistry class. Our experimental study showed that the interaction feedback type of a deformable object had a greater educational effect than other types of visual or audio feedback, and our results are expected to provide guidelines on how to create effective immersive education content and interaction methods.

Legal regulation of trade secrets under the legislation of Ukraine and the EU

Today, the legislation of Ukraine on trade secrets is not systematized and has significant gaps. Relations regarding trade secrets are regulated by the several legal acts relating to various branches of law, and determine only the general principles of legal regulation of such relations. Detection of discrepancies in the legislation of Ukraine and the EU means that the legal protection of trade secrets in Ukraine is uneven and fragmentary, and therefore insufficient. The development of cross-border economic relations between economic entities of Ukraine and the EU requires a unified approach to solving the issue of protecting trade secrets, the absence of which requires studying these issues and developing practical recommendations aimed at approaching the legalregimes of protecting trade secrets in Ukraine and the EU.This article contains the analysis of the provisions of the legislation of Ukraine on the protection of trade secrets, international legal acts in this field and Directive (EU) 2016/943 of the European Parliament and of the Council of 8 June 2016 on the protectionof undisclosed know-how and business information (trade secrets) against their unlawful acquisition, use and disclosure. As a result of the analysis, it was established that: in Ukraine, there is no special legislation on the protection of trade secrets; the concept of trade secret in Ukraine fully corresponds to the concept of a trade secret it the Directive (EU) 2016/943, as well as to the concept of an undisclosed information in the TRIPS Agreement. At the same time, the concept of trade secret in Ukraine needs to be clarified regarding one of the essential signs of trade secret. In addition, in the legislation of Ukraine there is no single approach to the use of the concept of knowhow, as well as regarding the assignment of know-how to IP.
 The legislation of Ukraine requires the implementation of the provisions of European legislation on the legal regulation of trade secrets, namely: not classifying trade secrets as IP objects, while it is an addition or an alternative to IP rights; allocation in the «trade secret» of two types of objects - know-how and business information; determination of reengineering by a fair way of identifying trade secrets; determining the conditions for the lawful acquisition, use and disclosure of trade secrets.

Artificial Intelligence-Based Medical Image Classification using a Multilayer Fuzzy Approach

A Convolutional Neural Network (CNN) is an effective Artificial Intelligence (AI) technique for the automation of image analysis. However, to achieve a high level of accuracy, a CNN usually requires a large amount of data and a long training time. The current study addresses the above problem by proposing a novel AI technique. The latter can detect and classify abnormalities in images using a small amount of available data and a short training time. The proposed technique, Artificial Intelligence Based Medical Image Classification Using a Multilayer Fuzzy Approach (MFA), was validated using open access medical image data, where an image with a particular type of abnormal object contained in it was compared with a normal image with the same object in it. The similarity was then computed in percentages and subtracted from the hundred, which is the abnormality in the first image. The results showed that the novel MFA outperforms significantly better than the benchmark, CNN, and is a useful tool for automated analysis of medical image data sets.