Elements Of Control Research Articles

Strategic behaviour and resilience of an industrial enterprise to the external environment

The growing turbulence of the environment requires an industrial enterprise to find new approaches to choosing its development strategy. The study proposes a method for assessing the level of resilience of machine-building companies depending on the type of their strategic behaviour. Methodologically, the research rests on the theory of the firm and strategic management theory. Structural and logical analysis, expert assessments, matrixing, statistical and financial analysis were used as research methods. The empirical evidence is the data from the Russian Federal State Statistics Service (Rosstat) and the SBIS counterparty verification system. We clarify the concepts of resilience and strategic behaviour of a machine-building enterprise and propose our own definition of resilience. We distinguish between four types of strategic behaviour of enterprises when contacting the external environment, namely the maximum control possible, constructive interaction, adaptation with elements of control, and forced adaptation. A relationship was discovered between the level of resilience and the type of strategic behaviour of an industrial enterprise. The findings were tested using the case of four machine-building plants specializing in the production of lifting equipment. We found significant differentiation in the level of resilience of the enterprises under study and established which of the four types of strategic behaviour was typical of each. This will allow them to exercise a more reasonable approach when instituting their development strategy amid turbulence.

Analisis Pengendalian Intern Pengeluaran Kas Pada PT. Aplikanusa Lintasarta Medan

This research aims to find out how the cash disbursement internal control system is implemented and to determine the suitability of implementing the cash disbursement internal control system at PT. Applicationnusa Lintasarta with elements of internal control in achieving the objectives of the internal control system. This research uses a descriptive approach. The object studied is the cash disbursement internal control system implemented at PT. Nusa Lintasarta Application. The informants in this research were the Director and Cashier. Data collection techniques include observation, interviews, documentation and literature study. The results of this research show that the results of the list obtained through interviews with the three respondents are 75%, which means the internal control system for cash disbursements implemented at PT. Applicationnusa Lintasarta Medan is quite in accordance with the elements of internal control in achieving the objectives of the internal control system, namely organizational structure, authorization system and recording procedures, healthy practices and employees whose quality is in accordance with their responsibilities.

Des droits de protection aux droits humains des enfants Mirjam Janett, Vormundschaft und Fremdplatzierung in der Schweiz im 20. Jahrhundert. Ein Einblick in die neuere Forschung

In the 20th century, tens of thousands of children grew up in care homes, reformatories or foster families in Switzerland. The article provides an insight into the most important findings of recent research on the out-of-home placement of children and adolescents. It shows how family became an element of social control in the 20th century. The out-of-home placement of minors from precarious families was part of a repressive welfare policy aimed at enforcing bourgeois ideas of order and making children « socially acceptable ». However, inclusion often led to exclusion

ВНЕДРЕНИЕ И ПРИМЕНЕНИЕ ВНУТРЕННЕГО КОНТРОЛЯ В УПРАВЛЕНИИ ПРЕДПРИЯТИЕМ

Enterprise management is a complex job with high professional requirements, it requires managers to allocate and regulate the human and material resources of the enterprise, as well as a variety of resources such as funds and information, starting with the integrity of the development of the enterprise, in order to optimize the allocation of resources and maximize the use of enterprise resources in limited resources and environment. Great utility, and then realize the desire to obtain economic benefits. Internal control requires strengthening the internal environment, risk assessment, information exchange, elements of supervision and control in enterprise management in order to achieve high-quality management of enterprise resources and provide a good internal basis for enterprise development, which will be discussed in this article.

Analysis of the Internal Control System for Receivables at CV. Putra Riau Mandiri

In carrying out its activities to achieve the stated goals, companies must exercise control. The controls implemented must provide benefits, in this case being able to increase the effectiveness and efficiency of operations. This research focuses on analysis of the receivables control system. The purpose of this research is to describe and analyze how internal control at CV. Putra Riau Mandiri Pekanbaru. This research uses qualitative tests with a descriptive-analysis approach to internal control of trade receivables which refers to the COSO framework on the elements of internal control. The results of the research show that in the transaction authorization section the separation of duties is still not in accordance with COSO theory because there are still trapped functions and responsibilities in the sales and billing sections. Then, adequate documents are in accordance with COSO theory that every transaction has been properly documented. However, in the internal information section between the billing, accounting and finance sections, there is still a need for internal documents, namely payment receipt documents in hardfile and softfile form. Then, in terms of data and file security, it is running in accordance with COSO theory because the existing data has been properly backed up. The cause of uncollected receivables due to the manager's ignorance regarding several invoices is because there are duplicate tasks in the billing department, then there are frequent delays in recording the repayment of receivables so that in recapitulation of repayment there are often errors in recording receivable payments.

CHHM: a Manually Curated Catalogue of Human Histone Modifications Revealing Hotspot Regions and Unique Distribution Patterns.

Histone modification is one of the key elements in epigenetic control and plays important roles in regulation of biological processes and disease development. Currently, records of human histone modifications with various levels of confidence in evidence are scattered in various knowledgebases and databases. In the present study, a curated catalogue of human histone modifications, CHHM, was obtained by manual retrieval, evidence assessment, and integration of modification records from 10 knowledgebases/databases and 3 complementary articles. CHHM contains 6612 nonredundant modification entries covering 31 types of modifications (including 9 types of emerging modifications) and 2 types of histone-DNA crosslinks, that were identified in 11 H1 variants, 21 H2A variants, 21 H2B variants, 9 H3 variants, and 2 H4 variants. For ease of visualization and accessibility, modification entries are presented with aligned protein sequences in an Excel file. Confidence level in evidence is provided for each entry. Acylation modifications contribute to the highest number of modification entries in CHHM. This supports that cellular metabolic status plays a very important role in epigenetic control. CHHM reveals modification hotspot regions and uneven distribution of the modification entries across the histone families. Such uneven distribution may suggest that a particular histone family is more susceptible to certain types of modifications. CHHM not only serves as an important and user-friendly resource for biomedical and clinical researches involving histone modifications and transcriptional regulation, but also provides new insights for basic researches in the mechanism of human histone modifications and epigenetic control.

Learning Robotic Milling Strategies Based on Passive Variable Operational Space Interaction Control

This paper addresses the problem of robotic cutting during disassembly of products for materials separation and recycling. Waste handling applications differ from milling in manufacturing processes, as they engender considerable variety and uncertainty in the parameters (e.g. hardness) of materials which the robot must cut. To address this challenge, we propose a learning-based approach incorporating elements of interaction control, in which the robot can adapt key parameters, such as feed rate, depth of cut, and mechanical compliance during task execution. We show how a mathematical model of cutting mechanics, embedded in a simulation environment, can be used to rapidly train the system without needing large amounts of data from physical cutting trials. The simulation approach was validated on a real robot setup based on four case study materials with varying structural and mechanical properties. We demonstrate the proposed method minimises process force and path deviations to a level similar to offline optimal planning methods, while the average time to complete a cutting task is within 25% of the optimum, at the expense of reduced volume of material removed per pass. A key advantage of our approach over similar works is that no prior knowledge about the material is required. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This work is motivated by challenges in emerging fields such as recycling of electric vehicles, where products such as batteries adopt a range of designs with varying physical geometry and materials. More generally, this applies when considering robotic disassembly of any unknown component where semi-destructive operations such as cutting are required. Product-to-product variation introduces challenges when planning cutting processes required to disassemble a component, as contemporary planning approaches typically require advance knowledge of the material properties, shape and desired path to select tool speed, feed and depth of cut. In this paper, we show a mathematical model of milling force embedded in a simulation environment can be used as a relatively inexpensive approach to simulate a broad spectrum of cutting processes the robot may encounter. This allows the robot to learn from experience a strategy that can select these key parameters of a milling task online without user assistance. We develop a framework for controlling a robot using this strategy that allows the stiffness of the robot arm to be modulated over time to best satisfy metrics of productivity (e.g. required cutting time), while maintaining safe interaction of the robot with its environment (e.g. by avoiding force limits), similarly to how a human operator can vary muscular tension to accomplish different tasks. We posit that the proposed method can substitute a trial-and-error strategy of selecting process parameters for disassembly of novel products, or integrated with existing planning approaches to adjust the parameters of milling tasks online.

Endosome-microautophagy targeting chimera (eMIATAC) for targeted proteins degradation and enhance CAR-T cell anti-tumor therapy.

Rationale: Since oncogene expression products often exhibit upregulation or abnormally activated activity, developing a technique to regulate abnormal protein levels represent a viable approach for treating tumors and protein abnormality-related diseases. Methods: We first screened out eMIATAC components with high targeted degradation efficiency and explored the mechanism by which eMIATAC induced target protein degradation, and verified the degradation efficiency of the target protein by protein imprinting and flow cytometry. Next, we recombined eMIATAC with some controllable elements to verify the regulatable degradation performance of the target protein. Subsequently, we constructed eMIATAC that can express targeted degradation of AKT1 and verified its effect on GBM cell development in vitro and in vivo. Finally, we concatenated eMIATAC with CAR sequences to construct CAR-T cells with low BATF protein levels and verified the changes in their anti-tumor efficacy. Results: we developed a system based on the endosome-microautophagy-lysosome pathway for degrading endogenous proteins: endosome-MicroAutophagy TArgeting Chimera (eMIATAC), dependent on Vps4A instead of lysosomal-associated membrane protein 2A (LAMP2A) to bind to the chaperone Hsc70 and the protein of interest (POI). The complex was then transported to the lysosome by late endosomes, where degradation occurred similarly to microautophagy. The eMIATACs demonstrated accuracy, efficiency, reversibility, and controllability in degrading the target protein EGFP. Moreover, eMIATAC exhibited excellent performance in knocking down POI when targeting endogenous proteins in vivo and in vitro. Conclusions: The eMIATACs could not only directly knock down abnormal proteins for glioma treatment but also enhance the therapeutic effect of CAR-T cell therapy for tumors by knocking down T cell exhaustion-related proteins. The newly developed eMIATAC system holds promise as a novel tool for protein knockdown strategies. By enabling direct control over endogenous protein levels, eMIATAC has the potential to revolutionize treatment for cancer and genetic diseases.

Digital potential of the Russian agro-Industrial complex based on the results of technological innovations

The article analyzes the current state of innovation activity and the fundamental features of technological development in the agricultural sector of the economy, identifies barriers and prerequisites for the transition to digital transformation, and demonstrates the results of the introduction of domestic technological innovations. In the context of modern realities, innovations are becoming a fundamental component of the development of the national economy. The process of digitalization for the agro-industrial complex is due to the urgent need to increase the efficiency and sustainability of its functioning through radical transformations of managerial efficiency by technological processes and decision-making processes at all levels of the hierarchical ladder, based on innovative approaches to production and the subsequent application of information data on the state of controlled elements and subsystems and forecasting their potential adjustments, as well as economic conditions in the agricultural sector. The practice of a global scale and the experience of authoritative domestic agricultural producers illustrate that the use of modern technological solutions contributes to ensuring optimal soil, agrotechnical and organizational and territorial conditions, which make it possible throughout the full life cycle of agricultural products to contribute to an increase in yield and labor productivity, reduce material costs for fuels and lubricants (F&amp;L), electricity, plant protection products (PPP), wages and other types of expenses, maintaining soil fertility and preserving the environment. Increasing and stimulating innovative and technological activity in the agro-industrial complex will also increase production volumes, increase the competitiveness of domestic agricultural products, eliminate the problem of import substitution and increase the level of profitability of agricultural enterprises.

A Real-Time Automated Defect Detection System for Ceramic Pieces Manufacturing Process Based on Computer Vision with Deep Learning.

Defect detection is a key element of quality control in today's industries, and the process requires the incorporation of automated methods, including image sensors, to detect any potential defects that may occur during the manufacturing process. While there are various methods that can be used for inspecting surfaces, such as those of metal and building materials, there are only a limited number of techniques that are specifically designed to analyze specialized surfaces, such as ceramics, which can potentially reveal distinctive anomalies or characteristics that require a more precise and focused approach. This article describes a study and proposes an extended solution for defect detection on ceramic pieces within an industrial environment, utilizing a computer vision system with deep learning models. The solution includes an image acquisition process and a labeling platform to create training datasets, as well as an image preprocessing technique, to feed a machine learning algorithm based on convolutional neural networks (CNNs) capable of running in real time within a manufacturing environment. The developed solution was implemented and evaluated at a leading Portuguese company that specializes in the manufacturing of tableware and fine stoneware. The collaboration between the research team and the company resulted in the development of an automated and effective system for detecting defects in ceramic pieces, achieving an accuracy of 98.00% and an F1-Score of 97.29%.

Streamlining logistics flows with lean tools using TX Plant Simulation software support

A critical factor in the manufacturing industry is waste and losses in individual operations and processes. The expansion of elements of lean production, such as the pull system with the interconnection of key technologies, brings new elements of production planning and control. Thanks to new technologies, many more possibilities exist to uncover potential bottlenecks. Simulations and modelling bring new possibilities for experimentation in the virtual environment of prepared systems or devices without directly disturbing the functioning system. The presented article deals with the issue of applying lean approaches in finding optimal solutions within logistics flows. The aim of the article is to define and test the potential for streamlining logistics flows with TX Plant Simulation software support. The research and empirical part of the study was solved based on a rigorous analysis of the initial situation in a specific company for the selected product group, as the Value Stream Mapping method was used for the analysis. A simulation model of a real line was created in the TX Plant Simulation software with the help of the Value Stream Mapping library for value creation, which is part of the software. The goal was to find out possible waste within the logistics flow, and its causes and propose the necessary steps to eliminate the waste.

Analysis of the results of field tests of viscoelastic compositions under the conditions of a complex terrigenous reservoir in the Caspian sea

The publication analyzes the use of viscoelastic systems in order to increase the efficiency of oil production in the Caspian fields. The conducted studies of the results of pilot field work on the introduction of polymer flooding technologies in complexly constructed terrigenous reservoirs have shown a number of disadvantages of the systems used at the pilot site. In particular, the premature destruction of the polymer compositions used and the subsequent sharp watering of the extracted products were revealed. The research covers technology tests from November 2014 to October 2021, the results of which established the presence of deteriorating dynamics in the removal of polymer material, in addition, the study revealed a high influence of thermobaric and reservoir conditions on the polymer formation process and its subsequent properties. The classic solution to the described problem is the use of compositions with higher viscosity indices, however, laboratory experiments with the use of reservoir fluid have shown a decrease in the characteristics of the compositions used while maintaining conditions close to reservoir conditions. Based on the results of the research, an approach based on a systematic solution of the problem was proposed, the existing line of agents was modernized taking into account experimental data with the reaction of compositions to reservoir fluids, including elements of control and regulation of the oil recovery process during exposure, changes in the volumes of injected polymer solutions. Keywords: water intrusion; systemic approach; viscoelastic systems; oil recovery.

MARKETING TOOLS OF ENTERPRISES OF THE AGRICULTURAL SECTOR OF UKRAINE

The article is devoted to the justification and rationalization of the instrumental content of the marketing activity of domestic enterprises in the agrarian sector. Provisions characterizing the role and importance of agricultural marketing are defined, among which are highlighted: optimization of resource use and management of results; increase in farm income; expansion of markets; growth of the agricultural industry; introduction and distribution of new technologies; job creation; allowance to national income; value creation. It was determined that many factors should be considered in agribusiness when determining the marketing strategy, and the marketing complex as a strategy will positively affect the work of the enterprise. Twelve controllable marketing elements are outlined, which include the following components: product planning, pricing, branding, distribution channels, personal selling, advertising, promotions and promotions, packaging, display, service, delivery, research, and analysis. The difference between consumer and agricultural goods is substantiated, and the specifics of agricultural goods are determined, including the dependence of production on natural and biological factors, seasonality of production, predominance of wholesale sales; the need for processing, short consumption period, lack of ideal substitutes; lack of effective quality control mechanisms; the limited influence of the brand, advertising, after-sales service, fashion and style, emotional factors; low elasticity of demand. Certain aspects of state policy are revealed as an addition to the traditional Ps of the marketing mix for the sale of agricultural products; in particular, it is stated that the agricultural policy should be structured in such a way as to provide support to small farmers through projects of improvement, diversification, and sale of agricultural products.

Изменение бюджетных параметров в условиях турбулентности

Declining budget revenues, the coronavirus pandemic, economic sanctions imposed by unfriendly states, and other similar factors that have a significant impact on the budget and budget system require prompt management decisions. The fiscal policy of all budget levels is currently being implemented in conditions of turbulence, faced with the need to respond to the challenges of the new reality. The research hypothesis was that there are many facts and phenomena that reflect the presence of non-systemic external influence on the approval and execution of the budget. These include budget imbalance, deviation of its execution from the approved one, adjustments to the approved volumes of budget revenues and expenditures, asynchrony of its execution in during the financial year, etc. Using data collected from federal laws on the federal budget since 1999, as well as data from the Russian Treasury, we show that the above phenomena are generally characteristic of the budget policy of the Russian Federation, and elements of manual control only increase during crisis periods. At the same time, the lower levels of the budget system have fewer opportunities to respond to the challenges of turbulent time than the higher ones.

INFECTION CONTROL ADVOCATE AND RESIDENT EDUCATION (ICARE): PERSON-CENTERED INFECTION PREVENTION FOR QUALITY CARE

Abstract Applying infection prevention and control (IPC) measures while ensuring person-centered care (PCC) remains a major challenge in nursing homes. PCC focuses on resident rights to engage and empower nursing community residents, families, advocates, and staff to deliver quality care. To address this gap, The Infection Control Advocate and Resident Education (ICARE) program was developed for nursing home residents and families. ICARE is a step-based program which begins with educating participants on IPC and resident rights through seven web-based modules. The program encourages support and collaboration of nursing home advocate organizations including the long-term care ombudsman program, quality care organizations, and public health departments to assist residents and families in becoming more engaged and empowered in quality care beginning with infection prevention and control. Utilizing ICARE program materials, participants progress to engagement by learning how quality care is provided in their nursing home community, with the goal of empowering residents to actively participate in quality care improvement through quality improvement projects. The ICARE Program assists nursing home advocate organizations to identify opportunities to incorporate elements of infection control, quality care, and resident rights in current procedures and activities. The overall program design and theory of the ICARE program will be presented to provide a foundation for the creation of similar programs.

A circulating current suppression strategy of VSG based on adaptive virtual complex impedance

By adding inertia and damping elements in droop control, virtual synchronous generators (VSG) can simulate the output characteristics of synchronous generators and effectively reduce the impact of power electronic equipment connected to the power grid. Since the capacity and spatial distribution of each VSG is random, the output impedance of VSG and line impedance are mismatched, which will cause circulating current between VSGs. Considering the influence of line resistance, the traditional dynamic virtual inductance control strategy can be enhanced. A circulating current suppression strategy based on adaptive virtual complex impedance is proposed after analyzing the composition and causes of the circulating current between VSGs. The proposed strategy compensates the line impedance adaptively according to VSG's output reactive power, thus to reduce the reactive power sharing errors and suppress the circulating current between VSGs. The scheme is reliable and robust under fault as there is no need for measurement of line impedance or communication modules. The simulation results are presented to verify the effectiveness of the proposed strategy.

Applying Dynamic U-Value Measurements for State Forecasting in Buildings

Abstract In the present day, monitoring and automated control stand as pivotal factors for the energy-efficient and comfortable operation of buildings. As the demand for indoor climate control grows, building management systems have become more intricate, making their control challenging due to the increasing number of controllable elements. Replacing manual human analysis of complex systems can be achieved through the utilization of algorithms like model-based control. It is important to note that performance of this method usually relies on the accuracy of neural network-based building state forecasts. Studying the internal dynamics of climate as influenced by temperature changes necessitates a brief record of measurements, whereas evaluating structural modifications through moisture transfer demands data covering a more extended period. Neural networks such as Long Short-Term Memory have the potential to lose information within lengthy time-series data, and the intricate nature of moisture transfer further adds complexity to the task of approximating functions, ultimately leading to a reduction in energy efficiency. In order to improve the precision of indoor climate predictions, our suggestion involves not only assessing changes in temperature but also considering alterations in U-values triggered by temperature variations and moisture transfer. Our preliminary assessment of the influence of U-value, conducted through numerical simulations using WUFI6, exposes variations of up to 10 % of U-value in certain scenarios. Dealing with these computations in real time using physical models proves to be demanding due to computational requirements and limited data availability. To tackle this issue, we present an innovative preprocessing approach for on-the-fly evaluation of U-values. Empirical trials involving three years of monitoring data indicate that the suggested technique led to an approximate 8 % reduction in the average mean squared error of climate predictions based on neural network models, in specific instances.

DESIGN THINKING IN THE VISUALIZATION OF ECONOMIC DEVELOPMENT PROJECTS IN THE AGRARIAN SPHERE: SCIENCE AND ART

The article represents an attempt to comprehend the possibilities of applying general methodological principles of design thinking in the process of planning and developing innovative economic development projects in the agricultural sector. The relations of design and visualization as the science and art processes in the economy are outlined. It is noted that smart agriculture uses advanced technologies such as sensors, devices, machines and information technology, robots, GPS technologies, which will allow farms to be more profitable, efficient, safe, and environmentally friendly. The authors claim that the goal of digitalization of agriculture is to achieve a significant increase in the efficiency and sustainability of its functioning through fundamental changes in the quality of management of both technological processes and decision-making processes at all levels of the hierarchy, based on modern production methods, and the further use of information about the state of controlled elements and subsystems, as well as states of the economic environment of agriculture. Based on a study of the use of visualization technologies within the framework of the philosophy of design thinking, it is shown that the introduction of digital technologies in the agro-industrial complex will dramatically increase labor productivity and reduce risks in agriculture. In modern conditions of intense competition, digitalization based on such projects will give the agricultural sector of any country (which is especially important for developing countries) great competitive advantages.

Adaptive Learning in Agent-Based Models: An Approach for Analyzing Human Behavior in Pandemic Crowding

This study assesses the impact of incorporating an adaptive learning mechanism into an agent-based model simulating behavior on a university campus during a pandemic outbreak, with the particular case of the COVID-19 pandemic. Our model not only captures individual behavior, but also serves as a powerful tool for assessing the efficacy of geolocalized policies in addressing campus overcrowding and infections. The main objective is to demonstrate RL’s effectiveness in representing agent behavior and optimizing control policies through adaptive decision-making in response to evolving pandemic dynamics. By implementing RL, we identify different temporal patterns of overcrowding violations, shedding light on the complexity of human behavior within semi-enclosed environments. While we successfully reduce campus overcrowding, the study recognizes its limited impact on altering the pandemic’s course, underlining the importance of comprehensive epidemic control strategies. Our research contributes to the understanding of adaptive learning in complex systems and provides insights for shaping future public health policies in similar community settings. It emphasizes the significance of considering individual decision-making influenced by adaptive learning, implementing targeted interventions, and the role of geospatial elements in pandemic control. Future research directions include exploring various parameter settings and updating representations of the disease’s natural history to enhance the applicability of these findings. This study offers valuable insights into managing pandemics in community settings and highlights the need for multifaceted control strategies.

An Overview of Cancer in Djibouti: Current Status, Therapeutic Approaches, and Promising Endeavors in Local Essential Oil Treatment.

Djibouti, a developing economy, grapples with significant socioeconomic obstacles and the prevalence of infectious pathologies, including certain forms of neoplasms. These challenges are exacerbated by limited access to affordable medical technologies for diagnosis, coupled with a lack of preventive interventions, particularly in disadvantaged areas. The attention devoted to local phytotherapeutic treatments underscores the uniqueness of Djibouti's flora, resulting from its distinctive geographical position. International focus specifically centers on harnessing this potential as a valuable resource, emphasizing the phytoconstituents used to counter pathologies, notably carcinomas. This comprehensive overview covers a broad spectrum, commencing with an examination of the current state of knowledge, namely an in-depth investigation of oncological risk factors. Essential elements of control are subsequently studied, highlighting the fundamental prerequisites for effective management. The significance of dietary habits in cancer prevention and support is explored in depth, while traditional methods are examined, highlighting the cultural significance of indigenous essential oil therapies and encouraging further research based on the promising results.