Specific Objectives Research Articles

Computer Vision Algorithms on a Raspberry Pi 4 for Automated Depalletizing

The primary objective of a depalletizing system is to automate the process of detecting and locating specific variable-shaped objects on a pallet, allowing a robotic system to accurately unstack them. Although many solutions exist for the problem in industrial and manufacturing settings, the application to small-scale scenarios such as retail vending machines and small warehouses has not received much attention so far. This paper presents a comparative analysis of four different computer vision algorithms for the depalletizing task, implemented on a Raspberry Pi 4, a very popular single-board computer with low computer power suitable for the IoT and edge computing. The algorithms evaluated include the following: pattern matching, scale-invariant feature transform, Oriented FAST and Rotated BRIEF, and Haar cascade classifier. Each technique is described and their implementations are outlined. Their evaluation is performed on the task of box detection and localization in the test images to assess their suitability in a depalletizing system. The performance of the algorithms is given in terms of accuracy, robustness to variability, computational speed, detection sensitivity, and resource consumption. The results reveal the strengths and limitations of each algorithm, providing valuable insights for selecting the most appropriate technique based on the specific requirements of a depalletizing system.

Cézanne’s paintings and Judd’s Specific Objects: from objects in painting to objects in space

ABSTRACT This article examines Judd’s Specific Objects in light of Cézanne’s paintings and suggests that the two artists share a conception of the relation between objects and space. I argue that, much like Cézanne, Judd saw objects and space as related elements that constantly define each other. Cézanne and Judd are prominent figures who represent two distinct positions in the history of Western art. I consider these positions in relation to the topic of artistic autonomy and suggest that, even though theoreticians have framed Judd’s work in opposition to the modernist concept of the autonomous work of art—the American founding figure of Minimalism has something in common with the French ‘Father of Modern Art’. The proposed phenomenological analysis of works by Judd and Cézanne moves beyond period-based and medium-oriented interpretations and differs from much art-historical discourse, to suggest an additional perspective on their works.

Expansive learning in the learning assistant model: how instructors’ goals lead to differences in implementation and development of LAs’ practices

BackgroundThe learning assistant (LA) model supports student success in undergraduate science courses; however, variation in outcomes has led to a call for more work investigating how the LA model is implemented. In this research, we used cultural historical activity theory (CHAT) to characterize how three different instructors set up LA-facilitated classrooms and how LAs’ understanding and development of their practices was shaped by the classroom activity. CHAT is a sociocultural framework that provides a structured approach to studying complex activity systems directed toward specific objects. It conceptualizes change within these systems as expansive learning, in which experiencing a contradiction leads to internalization and critical self-reflection, and then externalization and a search for solutions and change.ResultsThrough analyzing two semi-structured retrospective interviews from three professors and eleven LAs, we found that how the LA model was implemented differed based on STEM instructors’ pedagogical practices and goals. Each instructor leveraged LA-facilitated interactions to further learning and tasked LAs with emotionally supporting students to grapple with content and confusions in a safe environment; however, all three had different rules and divisions of labor that were influenced by their perspectives on learning and their objects for the class. For LAs, we found that they had multiple, sometimes conflicting, motives that can be described as either practical, what they described as their day-to-day job, or sense-making, how they made sense of the reason for their work. How these motives were integrated/separated or aligned/misaligned with the collective course object influenced LAs’ learning in practice through either a mechanism of consonance or contradiction. We found that each LA developed unique practices that reciprocally shaped and were shaped by the activity system in which they worked.ConclusionsThis study helps bridge the bodies of research that focus on outcomes from the LA model and LA learning and development by describing how LA learning mechanisms are shaped by their context. We also show that variation in the LA model can be described both by classroom objects and by LAs’ development in dialogue with those objects. This work can be used to start to develop a deeper understanding of how students, instructors, and LAs experience the LA model.

Seeing the Forest but Naming the Trees: An Object-Over-Place Bias in Learning Noun Labels.

Objects and places are foundational spatial domains represented in human symbolic expressions, like drawings, which show a prioritization of depicting small-scale object-shape information over the large-scale navigable place information in which objects are situated. Is there a similar object-over-place bias in language? Across six experiments, adults and 3- to 4-year-old children were asked either to extend a novel noun in a labeling phrase, to extend a novel noun in a prepositional phrase, or to simply match pictures. To dissociate specific object and place information from more general figure and ground information, participants either saw scenes with both place information (a room) and object information (a block in the room), or scenes with two kinds of object information that matched the figure-ground relations of the room and block by presenting an open container with a smaller block inside. While adults showed a specific object-over-place bias in both extending novel noun labels and matching, they did not show this bias in extending novel nouns following prepositions. Young children showed this bias in extending novel noun labels only. Spatial domains may thus confer specific and foundational biases for word learning that may change through development in a way that is similar to that of other word-learning biases about objects, like the shape bias. These results expand the symbolic scope of prior studies on object biases in drawing to object biases in language, and they expand the spatial domains of prior studies characterizing the language of objects and places.

Согласие на причинение вреда как потенциальное обстоятельство, исключающее преступность деяния: к вопросу о содержании понятия

The problem of consent to injury raises almost the largest number of discussions in the Russian criminal law theory. Although the social relations need the respective legal regulation, the criminal law has no provision to determine legality of causing an injury upon the victim’s consent. The concept of consent to injury is the critical aspect of the problem under consideration. In this article, the author analyzes classical and contemporary approaches to defining the named concept and the list of its attributes and concludes that the consent to injury as a circumstance that excludes the criminal nature of the act is a will of a person that is formed based on personal interest gives rise to permissive criminal relations and is aimed at performance of an act by another person leading to socially relevant changes in a specific criminal law protection object owned by the consent subject. The conclusions presented in the article can be used as a theoretical basis for studies of conditions of acknowledging an injury caused upon the victim’s consent as legal, and in law making activities at design of respective legal provisions on consent to injury as a circumstance that excludes the criminal nature of the act.

Orthodox Church Architecture of the Kuban Settlements of the Late 18th – First Half of the 19th Century

A retrospective analysis of the history of the architecture of Orthodox churches in Kuban from the end of the 18th to the first half of the 19th century was carried out on specific objects of religious architecture. The historical approach allows us to consider these objects as unique elements of the architectural and urban heritage of the period under study. The special value of Orthodox churches in the concept of forming a holistic environment of urban and rural settlements is indicated. The main means of artistic expression based on volumetric planning techniques, with the help of which the compositional image of the temple is created, are noted. The presented illustrative material graphically displays the scientific content, executed on certain visual images of religious architecture structures and visually complements the text material. Great importance is given to the current issues of integrity and sustainable balance of modern buildings and structures with previously erected religious architecture objects and monuments of historical and cultural heritage.

Object-based image retrieval and detection for surveillance video

With technological advancement worldwide, the video surveillance market is growing drastically in a versatile field. Monitoring, browsing, and retrieving a specific object in a long video becomes difficult due to the enormous amount of data produced by the surveillance camera. With limitations on human resources and browsing time, there is a need for a new video analytics model to handle more complex tasks, such as object detection and query retrieval. The current approach involves techniques like unsupervised segmentation, multiscale segmentation, and feature-based descriptions. However, these methods often encounter extensive space and time consumption challenges. A solution has been developed for retrieving targeted objects from surveillance videos via user queries, employing a graphical interface for input. Extracting relevant frames based on user-entered text queries is enabled through using YOLOv8 for object detection. Users interact through a graphical user interface deployed on a Jetson Xavier Development board. The system's outcome is a time-efficient and highly accurate automated model for object detection and query retrieval, eliminating human errors associated with manually locating objects in videos upon user queries.

A Robust Young Stellar Object Identification Method Based on Deep Learning

Young stellar objects (YSOs) represent the earliest stage in the process of star formation, offering insights that contribute to the development of models elucidating star formation and evolution. Recent advancements in deep-learning techniques have enabled significant strides in identifying special objects within vast data sets. In this paper, we present a YSO identification method based on deep-learning principles and spectra from the LAMOST. We designed a structure based on a long short-term memory network and a convolutional neural network and trained different models in two steps to identify YSO candidates. Initially, we trained a model to detect stellar spectra featuring the Hα emission line, achieving an accuracy of 98.67%. Leveraging this model, we classified 10,495,781 stellar spectra from LAMOST, yielding 76,867 candidates displaying a Hα emission line. Subsequently, we developed a YSO identification model, which achieved a recall rate of 95.81% for YSOs. Utilizing this model, we further identified 35,021 YSO candidates from the Hα emission-line candidates. Following cross validation, 3204 samples were identified as previously reported YSO candidates. We eliminated samples with low signal-to-noise ratios and M dwarfs by using the equivalent widths of the N ii and He i emission lines and visual inspection, resulting in a catalog of 20,530 YSO candidates. To facilitate future research endeavors, we provide the obtained catalogs of Hα emission-line star candidates and YSO candidates along with the code used for training the model.

Penerapan Sistem Perjanjian Kerja Waktu Tertentu Dalam Perspektif Hukum Positif Indonesia

Introduction: Indonesia, as a country under the rule of law, upholds the principle of equality before the law. This principle is also applied in the freedom to contract, which requires a valid agreement to meet four conditions: agreement, competency, specific object, and lawful cause. The Fixed-Term Employment Agreement is a form of employment relationship between employers and workers that suffers from shortcomings in its implementation. Many employers do not understand the rules, leading to deviations in practice.Purposes of the Research: The aim of this research is to examine and analyze the implementation of the Fixed-Term Employment Agreement system from the perspective of positive law in Indonesia.Methods of the Research: This research is a normative juridical research, using a descriptive analytical research type using primary, secondary and tertiary legal sources. The approach used is a statutory approach (Statute Approach) and conceptual approach (conceptual approach). The technique of collecting legal materials uses a literature study which is then analyzed qualitatively in order to answer the problems studied.Results of the Research: Based on the research results, it is shown that the protection of workers in Fixed-Term Employment Agreements is not optimal in its implementation due to frequent violations. This is attributed to the unclear regulations regarding the application of The Fixed-Term Employment Agreement, particularly concerning types of work that are one-time, temporary, seasonal, or related to new products. Furthermore, the lack of government supervision in the The Fixed-Term Employment Agreement creation process enables employers to easily violate regulations without legal repercussions.

Semi-supervised anchorless single-engine grip detection

The extensive application of artificial intelligence in wireless communication, 3D reconstruction, and target location has successfully solved the modeling problem. Grasping specific objects in a stacked scene is a difficult task to achieve robot grasping. In this paper, a semi-supervised anchor-less single-gun grasping detection framework is proposed to help robots grasp objects easily. The framework first designs the AFMaskDetDep (AFMDD) network and then predicts the contours of objects by looking at sensing modules. Finally, the boundary value of the minimum boundary rectangle is obtained by judging the optimal target and the optimal grasping point of the inference module, and the final result is obtained by rotating back to the coordinate output on the original image area. Our proposed approach yields state-of-the-art performance with improved accuracy and computational speed on the VMRD and Cornell datasets, respectively. Experiments show that the algorithm can help the robot grasp a single specific object and has a high success rate in overlapping scenes. The success rate of each grip exceeds 93.5%.

Detecting microfragments of glass in scar tissues

The identification of traumatic causes in the case of damage caused by sharp objects has always been one of the main issues of interest to the investigating authorities. Currently, forensic medicine allows for determining a specific acute traumatic object, including glass fragments. However, in the available literature, no information is available about the possibility of detecting microfragments of glass in the scar. Herein, the case of a man who suffered a chest wound is presented. The patient was brought to the hospital, where the wound was sutured. In the medical records, the wound was described as a stab wound and could have been caused by a knife. The accused categorically denied inflicting a knife wound on this person and argued that the victim was in a state of severe alcoholic intoxication and fell repeatedly, including on a sideboard, glass from which was found during an inspection of the scene. Four months later, the victim died from alcohol poisoning. A forensic medical examination was conducted to confirm the possibility of injury from glass fragments from the sideboard. A scar was identified on the victim’s chest. Microparticles were found in the scar tissue, and their characteristics led to the conclusion that they were microfragments of colorless, transparent glass. Determining the presence of glass microfragments in scar tissue does not require complex technical equipment and are common in wide expert practice; their use has confirmed the possibility of detecting glass microfragments not only in soft tissues along the wound channel but also in scar tissue after wound healing.

Об идентификации характеристик неоднородных вязкоупругих тел в рамках модели дробного порядка

Nowadays, the development of models of viscoelastic materials with complex inhomogeneous structure is one of the hottest problems of continuum mechanics. Along with classical models, fractional-differential models of viscoelasticity have become increasingly popular. In this paper, we present a model for describing steady-state oscillations of inhomogeneous viscoelastic bodies in terms of fractional-order differential operators. Taking into account the fractional order of the model operators, the corresponding form of the complex module describing the material properties is constructed. The module includes four characteristics: instantaneous and long-term elastic moduli (in the case of material inhomogeneity, they are the functions of coordinates), relaxation time and fractionality parameter. The properties of the complex module are studied, and the ranges of the model parameters, at which the rheological properties are most pronounced, are identified. A general formulation of the inverse problem (IP) on the identification of function-parameters of the model based on the acoustic sounding data is proposed. In the framework of this formulation, the inverse problems for specific objects , namely, an inhomogeneous rod and a round plate, are considered. In both model problems, the influence of the fractionalization parameter on the amplitude-frequency characteristics is analyzed. It has been found that in the vicinity of viscoelastic resonances the fractionality parameter affects the parameters of the oscillatory process most significantly, which is typical for such problems. A solution to the nonlinear IPs under consideration is constructed based on the linearization method, which also serve as basis for the iterative processes supplemented with the elements of the projection approach. This allows one to determine corrections to the required functions in the specified classes of functions using regularization. For both IPs, a series of computational experiments were carried out. The analysis of the experimental results made it possible to formulate recommendations for the selection of optimal sensing modes.

Practical object and flow structure segmentation using artificial intelligence

This paper explores integrating artificial intelligence (AI) segmentation models, particularly the Segment Anything Model (SAM), into fluid mechanics experiments. SAM’s architecture, comprising an image encoder, prompt encoder, and mask decoder, is investigated for its application in detecting and segmenting objects and flow structures. Additionally, we explore the integration of natural language prompts, such as BERT, to enhance SAM’s performance in segmenting specific objects. Through case studies, we found that SAM is robust in object detection in fluid experiments. However, segmentations related to flow properties, such as scalar turbulence and bubbly flows, require fine-tuning. To facilitate the application, we have established a repository (https://github.com/AliRKhojasteh/Flow_segmentation) where models and usage examples can be accessed.

Research on the Application of Geographic Information Systems in the Construction of Smart Cities

With the continuous deepening of globalization and informatization, the construction of smart cities is gradually becoming a core strategy in the process of urban modernization. In this strategy, Geographic Information Systems (GIS) play a crucial technical support role. This article adopts a case study method, taking the construction of a smart city in Nanjing as the specific research object, and deeply explores the practical application of GIS in key fields such as urban planning, environmental protection, and traffic management. Through comprehensive analysis of these examples, this article systematically summarizes the significant achievements of GIS technology in improving urban management efficiency, optimizing decision support systems, enhancing public service levels, and promoting sustainable urban development. The research results indicate that GIS technology provides solid data support and decision-making support for the core areas of cities through precise integration and analysis of geographic information. GIS technology not only optimizes the layout of urban infrastructure, but also significantly enhances the city's response to emergency events through real-time monitoring and dynamic simulation, while promoting efficient allocation and utilization of urban resources. The research conclusion points out that, GIS technology is the cornerstone of smart city construction, greatly enhancing the scientific and forward-looking nature of urban management. The effective application of GIS has opened up new avenues for intelligent and refined urban management, significantly improving the quality of life of residents and providing solid technical support for the sustainable development of cities.

Special Geometric Objects in Generalized Riemannian Spaces

In this paper, we obtained the geometrical objects that are common in different definitions of the generalized Riemannian spaces. These objects are analogies to the Thomas projective parameter and the Weyl projective tensor. After that, we obtained some geometrical objects important for applications in physics.

Information and Logic Model Development Natural Engineering System Environmental Monitoring

Environmental monitoring is the main source of information on the current environment state and its changes associated with man-made and anthropogenic impact. The system of environmental monitoring of increased danger technogenic objects includes state observations of air and water environments, soil snow cover, as well as monitoring of flora and fauna, including biotesting and bioindication. An example of an integrated approach to organizing the environment conditionobserving system is environmental monitoring in the zone of chemical weapons destruction facilities. The results of monitoring activities are numerical arrays of quantitative indicators of the environment state related to specific monitoring objects: concentrations of pollutants in natural environments (air, water, and soil); indicators of the state of flora and fauna; bioindication results. The complexity of the monitoring result integrated analysis is primarily associated with the diversity of the structure and number of indicators for individual natural environments, different dimensions of indicators, as well as the sparseness of the matrices of data arrays. Taking into account the above-mentioned information, it is relevant to develop methods for storing and updating environmental monitoring data arrays, as well as algorithms for operational analysis of the results of monitoring studies. The paper presents an information and logical model that allows to form databases for storing and replenishing data on the state of the natural engineering system. The developed information and logic model is focused on building OLAP cubes for subsequent analysis of environmental monitoring data. The presented information and logical model is the main stage of developing a system for storing, updating and analyzing the results of environmental monitoring of the TCP. Systematization and structuring of indicators of natural environments and ecosystems makes it possible to formulate a number of practical tasks for assessing and predicting the state of the environment in the presence of technogenic impact.

REDUCING OF WATER AND ENERGY RESOURCES CONSUMPTION IN IRRIGATION BASED ON RESOURCE OPTIMISATION

The need for further development of irrigation practices on the basis of nature oriented and ecologically efficient solutions is considered primarily regarding the saving of water and energy resources for the adaptation of irrigated agricultural production to the current global challenges and threats, the achievement of sustainable development goals. It is shown that there is an objective need to change methodological approaches to the assessment of overall efficiency and justification of optimal solutions in design, reconstruction, and operation projects of irrigation systems based on the principles of resource optimization. On the basis of the indicator of the level of irrigation sufficiency (introduced by the authors), which reflects the reduction of the studied watering and irrigation rates in relation to their design values, a study of the impact of reducing the use of water and energy resources under different modes of sprinkler irrigation on the corresponding decrease in the level of cultivated crops productivity was carried out. At the same time, it was experimentally determined that the intensity (rate) of the decrease in the cultivated crops productivity, which occurs due to the decrease in the usage of water and energy resources during the application of irrigation, is significantly lower than the intensity (rate) of the decrease in the usage of the resources themselves. The studied options for reducing the consumption on water and energy resources as a whole turned out to be economically profitable when with a decrease in water and electricity usage by 27–48% there is more than two times lower decrease in the costs of gross products by 10,80–18,06% with the achievement of a net income of 11,4 to 5,7 thousand UAH. The influence of various options of reducing water and electricity consumption on the discounted investment payback period shows that several options may be acceptable, for which the investment payback period does not exceed 10 years, and the choice of the optimal solution requires taking into account the conditions of a specific object, limitations of water resources, and the interests of investors and land users. At the same time, the ecological component of the overall efficiency of irrigation practices consists in the decrease in the use of water and energy resources that a priori reflects the decrease in the negative impact of irrigation on the environment. Thus, reducing the usage of water and energy resources is a fully justified decision on the way to adapt irrigated agriculture production to the modern conditions and requirements, and the presented results can be a scientific basis for the implementation of this approach while practically applying irrigation.

HOGN-TVGN: Human-inspired Embodied Object Goal Navigation based on Time-varying Knowledge Graph Inference Networks for Robots

Object goal navigation tasks are critical for robots operating in unfamiliar environments, where they must locate specific objects using visual cues. The ability to leverage prior knowledge significantly enhances a robot’s associative capabilities, leading to improved navigation performance. However, existing methods struggle with the generalization challenge when transferring navigation models to new environments, a key issue addressed in this paper. To overcome this challenge, on the one hand, a time-varying knowledge graph is proposed to update the prior knowledge graph with context vectors derived from co-occurrence objects in the current observation. This approach prioritizes local graphs centered around the target and co-occurring objects, allowing for efficient and accurate target localization. Furthermore, the dynamic updating mechanism facilitates efficient exploration in new scenarios. On the other hand, to embed prior knowledge more rationally in the reinforcement learning-based navigation strategy, a time-varying knowledge graph inference network (TVGN) is presented. The TVGN utilizes context vectors and global spatial semantic information to perceive and understand the environment in real-time. It formulates navigation strategies based on the precise goal information encoded within the graph, thereby enhancing the robot’s efficiency in reaching the target. Based on the widely applied dataset AI2-THOR, extensive comparative experiments are conducted to illustrate the effectiveness of the proposed method. Experimental results indicate that our model outperforms state-of-the-art competitors, demonstrating notable advantages in navigation effectiveness and efficiency in previously unseen environments.

Professionally important personal prerequisites for entrepreneurship

The purpose of the article is to identify, systematize and structure personal prerequisites of people that are professionally important for successful entrepreneurship, in the context of interdisciplinary research into the phenomenon of entrepreneurship and its functional specifics. The understanding of entrepreneurship as a special type of professional activity, carried out in accordance with the request for it from society and its segments, extends to the analysis of the personal prerequisites for the professional development of modern entrepreneurs. Based on the psychological theory of activity, modern theories of abilities and on functional ideas about entrepreneurship as a type of professional activity, a professional-centric approach to assessing personal prerequisites that are important for successful entrepreneurship on a professional basis, as well as for the entrepreneurial professionalization of actors, is formulated. Special objects of consideration are clusters of professionally important prerequisites — people’s entrepreneurship ability, their personal competitiveness, ownership propensities. The illegality of synonymizing entrepreneurship as a type of activity and the entrepreneurship ability as a prerequisite for the success of this activity is argued. Entrepreneurship contains a readiness to make decisions, implement a program of action, reflect on the results of activity in an environment of comparative uncertainty of the market realities of the business environment, as well as to take on professional risks. The ownership propensities is interpreted as prerequisites that are professionally important for de facto entrepreneurs as business owners. It is shown that the personal competitiveness of the actors of this type of professional activity is of professional importance for successful entrepreneurship throughout the centuries-old history of reproducing the competitive nature of the entrepreneurship environment.

Subiektywny, obiektywny czy mieszany charakter rozboju kwalifikowanego?,

"The aim of this article was to address the issue of an object similarly dangerous to a knife or a firearm within the meaning of Article 280 § 2 of Penal Code to answer the question whether the qualified nature of this type of an offence originates from objective, subjective or mixed reasons. The focus was on what is meant by the concept of danger to which Article 280 § 2 of Penal Code refers, an analysis of which was carried out taking into account the doctrine and jurisprudence. It was emphasised that for the purposes of the cited type of prohibited act, it is necessary to examine the characteristics of a specific object which is evidence in the case, including a knife and a firearm, as the presumption of dangerousness covering them can be rebutted. Subsequently, it was considered which legal good is protected by the sanctioned norm of the Article 280 § 2 of Penal Code and juxtaposed with exemplary situational cases. As a result of this analysis, the conclusion was drawn that the qualified nature of robbery under Article 280 § 2 of Penal Code originates from objective factors, while subjective factors are not relevant for the fulfillment of the elements of this type of criminal act."