Concept Of Systems Research Articles

A monochrome pipelined HMI system for foodborne microorganisms testing

Hyperspectral microscopy imaging (HMI) is an efficient and non-destructive method to detect microbial contaminants in food, as it can provide both spatial morphology and spectral signature. Aims at reducing thermal effect, low cost, and improving spectral resolution in testing, a pipeline-operated LEDs monochromatic illumination mode is proposed, which integrates the design concepts of both grating-based and LED-based HMI systems. By design of the LED set, shared grating monochromatic optical path, and coordinated control system, an HMI system has been developed that could obtain the hyperspectral data cube with 101 bands in 400–700 nm. Hyperspectral datasets of three species of Aspergillus are prepared using the prototype, and efficient results have been achieved in the training and testing of classical classification algorithms (1D-CNN (97.33 %), k-NN (96.33 %), SVM (97.67 %) and ResNet-18 (95.67 %)). The results demonstrate that the proposed monochromatic illumination mode and associated system are potential detection solutions for foodborne microbial contaminants with low-cost and high-accurate.

Synergistic Modeling of Liquid Properties: Integrating Neural Network-Derived Molecular Features with Modified Kernel Models.

A significant challenge in applying machine learning to computational chemistry, particularly considering the growing complexity of contemporary machine learning models, is the scarcity of available experimental data. To address this issue, we introduce an approach that derives molecular features from an intricate neural network-based model and applies them to a simpler conventional machine learning model that is robust to overfitting. This method can be applied to predict various properties of a liquid system, including viscosity or surface tension, based on molecular features drawn from the ab initio calculated free energy of solvation. Furthermore, we propose a modified kernel model that includes Arrhenius temperature dependence to incorporate theoretical principles and diminish extreme nonlinearity in the model. The modified kernel model demonstrated significant improvements in certain scenarios and possible extensions to various theoretical concepts of molecular systems.

Context-Aware Recommender Systems: Exploring the Role of Time, Location, and Social Influence in Personalized Recommendations

Recommender systems have become a cornerstone of personalized user experiences across various domains, from e-commerce to entertainment. While traditional models focus on user-item interactions, they often overlook critical contextual information that could significantly enhance prediction accuracy. In this paper, we explore the concept of context-aware recommender systems, which integrate temporal, geospatial, and social context to improve recommendation quality. Temporal context considers factors such as time of day, seasonality, or the user's activity history, while geospatial context leverages the user's location or proximity to items, enhancing the relevance of recommendations. Additionally, social context incorporates user interactions with social networks or communities, enriching the understanding of preferences through peer influence and shared interests. We examine various techniques for incorporating these contexts into recommendation algorithms, including hybrid models, deep learning approaches, and context-sensitive matrix factorization. Furthermore, we address the challenges in balancing the complexity of these models with the need for real-time recommendations and scalability. Finally, we present empirical evaluations on real-world datasets, demonstrating that context-aware models significantly outperform traditional recommender systems in terms of prediction accuracy, diversity, and user satisfaction. This paper aims to provide a comprehensive framework for developing context-aware recommender systems and outline key areas for future research, such as integrating emerging contextual dimensions like sentiment and emotional state.

Rainmaking: Observed with social systems theory

AbstractThis article examines contemporary efforts to control climate change through the lens of social systems theory, particularly by drawing comparisons to rain dances and shamanic rituals. It argues that modern climate control strategies bear functional similarities to archaic rituals aimed at influencing weather patterns, despite the absence of direct causality. Using Niklas Luhmann's concepts of autopoietic systems and functional equivalence, the article demonstrates that both historical and contemporary approaches to climate influence rely on blame‐shifting mechanisms and the social production of scapegoats, with failure often attributed not to the rituals or solutions themselves but to noncompliance or impurity among participants. The originality of this article lies in its application of social systems theory to link contemporary climate control strategies with ancient rituals, positioning them as functionally equivalent social phenomena. By drawing comparisons between shamanistic practices, corporate consulting, and global climate governance, the article provides a unique lens for understanding that the primary function of modern climate efforts may be to regulate social behaviour rather than achieving concrete natural environmental outcomes.

Integrating active demand into the distribution system using metaheuristic techniques

AbstractIntegrating non‐conventional renewable energy sources into distribution systems, alongside data science and enabling technological infrastructures, presents significant challenges, particularly in managing active demand. The rapid evolution of the electric energy system and increasing electricity demand highlight the need for reliable tracking and predictive methods to manage Distributed Energy Resources and digital infrastructure. These methods are essential for advancing carbon neutrality, democratizing environmental sustainability, and improving energy efficiency. Effective active demand monitoring requires understanding the transactional system concept, including digital infrastructure and decentralized demand. Although metaheuristic techniques are increasingly important in demand response integration, much research focuses on specific techniques rather than providing a comprehensive view of dynamic transaction integration for active demand. Technological advancements, like smart meters and communication systems, are shifting from basic consumption measurement to active customer participation. This article reviews key concepts in electrical distribution systems, such as active demand, DERs, and transactive systems. It examines prevalent metaheuristic techniques, emphasizing their role in integrating and predicting active demand and DER behaviors. Additionally, the study presents a methodology serving as a roadmap for efficient DER integration and the transition to active demand and transactive electricity systems, addressing gaps in the current literature.

Self-Organization of Micro- and Nanosystems in the Form of Patterns

In this work, the peculiarities of self-organization of patterned micro- and nanosystems under near-equilibrium condensation conditions were consistently considered. The criteria for stationarity of near-equilibrium condensation were introduced, and interrelations between the condensate local growth kinetics and the corresponding local technological parameters were described. Dissipative self-organization of small supersaturations in physically and chemically active medium-condensate systems were compared. The effectiveness of the unification of dissipative self-organization of small supersaturations and conservative self-organization of patterned micro- and nanosystems formation was shown, which forms the basis of a new concept of complete self-organized systems.

Relationship Between Multi-Teaching Styles and Didactics Effectiveness on Rugby Instructors and Minirugby Players

Background/Objectives: The concept of educational systems thinking shows the rugby educational system as a network of multiple interactive and interconnected elements. However, the frameworks presented in the literature for developing sports practice through an educational vision and multisport engagement do not always have direct transferability to instructors’ training courses. The study aims to evaluate the correlation between rugby instructors’ methodological and didactical competencies and compare them with children’s motor competence and psychological aspects. Methods: Two hundred twenty children (9.6 ± 1.1 years) and 50 instructors (39.0 ± 13.6 years) were enrolled. Instructors’ competencies were investigated during the internship through evaluation sheets, questionnaires, and video analysis. Children’s motor competence and psychological aspects were investigated through motor tests, questionnaires, and video analysis. Results: The correlation between methodological competencies and didactical-communicative competencies showed a positive significance, especially regarding production styles. Motor competence and play skills in children showed poor results. The group of instructors with more methodological competencies (a greater number of teaching styles used) showed a strong correlation between motor competence and psychological aspects. Conclusions: For successful teaching, knowledge of specific technical skills is not enough, and it is important to consider all the factors (in particular, the teaching-communicative and methodological skills) that contribute most to instructors’ skills.

Detection and interpretation of central type structures within the territory of southeastern Transbaikalia for prediction of ore-forming systems

Extremely little attention is paid to the issues of detecting and interpreting of central type structures (CTS) when conducting remote structural-geological and structural-geomorphological studies. At the same time, in the 70–80s of the 20th century, the important role of CTSs in the localization of deposits and ore fields was proven. The position of these structures must necessarily be taken into account when solving problems of searching for and predicting mineral resources in the context of metallogenic analysis and reconstruction of the geological history of development of the studied areas. The almost absence of results of mass detecting and interpreting of CTSs can be explained by the still poorly developed methodology for identifying and analyzing this type of structure. In the present study for the territory of southeastern Transbaikalia, based on modern geoinformation technologies, the use of remote sensing data (radar topographic survey) of high resolution, the creation of a digital elevation model and the application of an integrated structural-spatial analysis, an author’s approach to detection and interpretation of the CTSs is presented, including in connection with the localization of ore objects of various geological-industrial (geological-genetic) types within the framework of the concept of the formation of mineral systems. A statistical analysis of the CTSs identified in the area was carried out, which made it possible to establish a smooth increase in the number of structures with a decrease in their diameter. It is shown that the spatial maxima of ore mineralization extent within the territory are concentrated on the periphery of large CTSs and in their immediate vicinity. Most of the known large ore objects are confined to the internal areas of structures less than 10 km in diameter. Based on the approach of constructing model sections, it was possible to reconstruct the deep position of magma chambers associated with the identified CTSs, and, thereby, to determine the probable sources of metal-bearing fluids. A close spatial relationship between the identified magma chambers and deep faults has been established. To determine the most favorable sites for the deposition of ore mineralization, based on structural-spatial criteria, which include not only structural elements of the CTSs, but also segments of known fault structures, weight of evidence models of the territory have been created. The accuracy of the complex model is 89%. Thus, in accordance with the concept of mineral systems, the sources, migration pathways and sites of the most probable deposition of ore mineralization have been reconstructed.

A multi-objective indirect neural adaptive processes control design for minimization of energy consumption: An experimental validation on a transesterification reactor

Nowadays, energy management environment is a very important issue that technologies have focused on in order to save costs and minimize energy waste. This objective can be achieved by means of an energy resource management approach through an appropriate optimization technique. However, energy savings can conflict with other objective functions, to solve the problem a multi-objective optimization that considers the minimization of the control energy can be adopted. In this paper, we propose to use a multi-objective indirect neural adaptive control concept for nonlinear systems with unknown dynamics. The control scheme consists of an adaptive instantaneous neural emulator and neural controller built on fully connected real-time recurrent learning networks (RTRL). The multi-objective particle swarm optimization (MOPSO) algorithm is used as a mechanism to find NE and NC adaptive learning rates that optimize the proposed objective functions: control energy minimization and closed-loop preservation. Comparative studies and experimental validation on a semi-batch reactor, used to generate cleaner biofuels, are performed to confirm the effectiveness of the proposed strategy.

Corporate Governance: Exploring Key Concepts, Mechanisms, and Historical Evolution

Corporate governance involves several key concepts that help define its scope and purpose. Though review of key corporate governance concepts and historical evolution is widespread in the extant literature, detailed review across the globe is limited. Motivated by this dearth, this study reviewed these concepts and explored how firms rely on them to implement effective corporate governance. The study employed documentary and descriptive research methods to review concepts of corporate governance, systems, mechanisms and historical perspectives around the world. Our study discovered that understanding internal controls helps ensure compliance, minimize risks and safeguard the firm’s assets. Similarly, the study discovered that executive compensation structures help align management interests with shareholder value and external oversight through auditing and regulation which provides an unbiased assessment of the firm’s financial reports. Our historical perspective of corporate governance highlighted significant milestones that have shaped its evolution. Importantly, these include reports and acts aimed at addressing corporate scandals and improving governance practices. We also discovered that to improve corporate governance standards worldwide, multilateral organizations like the Organisation for Economic Cooperation and Development (OECD) among others have played a number of roles in developing international guidelines and codes of best practice. Further, the study explored the dynamic nature of corporate governance in response to evolving economic, social and technological trends. The study concluded that understanding the concepts, systems, mechanisms and historical perspectives of corporate governance is essential for firms and stakeholders to maintain transparency, accountability and sustainable performance.

Experimental verification of a common assumption in the use of concentration-dependent interdiffusion coefficient

There has generally been a view that concentration-dependent interdiffusion coefficient, D(C), obtained at any diffusion temperature and time is a material constant and can be reliably used to predict diffusion effects at all other isothermal diffusion times. This notion which is implicitly predicated on the assumption that diffusion-induced stress (DIS) rapidly and completely relaxes once formed and does not influence D(C) is experimentally verified in the present work. The results of the study show that reliably computed D(C) from concentration profile obtained at long diffusion time fails to correctly predict concentration profiles at shorter diffusion periods, due to isothermal variation of the D(C) with time. Accordingly, instead of continuing to assume that D(C) is time-independent and can be reliably used to predict diffusion effects at any isothermal diffusion time, without appropriate experimental support, proper experimental verification of this crucial concept in other alloy systems, as done in the present work, is imperative.

Quantized embedding approaches for collective strong coupling-Connecting abinitio and macroscopic QED to simple models in polaritonics.

Collective light-matter interactions have been used to control chemistry and energy transfer, yet accessible approaches that combine abinitio methodology with large many-body quantum optical systems are missing due to the fast increase in computational cost for explicit simulations. We introduce an accessible abinitio quantum embedding concept for many-body quantum optical systems that allows us to treat the collective coupling of molecular many-body systems effectively in the spirit of macroscopic quantum electrodynamics while keeping the rigor of abinitio quantum chemistry for the molecular structure. Our approach fully includes the quantum fluctuations of the polaritonic field and yet remains much simpler and more intuitive than complex embedding approaches such as dynamical mean-field theory. We illustrate the underlying assumptions by comparison to the Tavis-Cummings model. The intuitive application of the quantized embedding approach and its transparent limitations offer a practical framework for the field of abinitio polaritonic chemistry to describe collective effects in realistic molecular ensembles.

Providing organizations with a validated instrument for an Enterprise Service Management capability

In light of new digital opportunities, enterprises require modernization also with regard to intra-organizational business and IT management. Enterprise Service Management (ESM) is an organizational capability aimed at a more efficient and effective IT and business service management in organizations. Although ESM has been recognized as an approach to improve customer and employee satisfaction and to create digital competitive advantage, there is a methodological and analytical void for organizations in how to measure their ESM capability. Motivated by this lack of measurability and tangibility, we aim to empirically validate the ESM capability model. Our contribution to this paper is empirical, as we provide a measurable instrument for further ESM studies. We aim to initiate a broader debate on ESM and thereby add to the scholarly establishment of the concept in the Information Systems and IT Management literature. Practically, we contribute by offering companies a validated and actionable set of ESM characteristics.

A LiDAR-Based Digital Twinning Workflow for Traffic Monitoring and Simulation

Abstract. The process of ensuring efficient and safe urban transportation is closely linked to urban planning, particularly through the aspects of transportation planning. Transportation planning is a pivotal concern for urban regions worldwide, reflecting the growing need to increase mobility while ensuring safety and sustainability in densely populated areas. This research focuses on developing a novel digital-twin-based approach for micro-traffic simulation to support data-driven decision-making for increasing traffic safety through scenario planning. Leveraging the traffic data obtained through monitoring one of the busiest intersections in Sofia city, this research workflow shows the effective integration of LiDAR data and the urban digital twin concept in intelligent transportation systems (ITS). The research addresses problems related to moving object classification, trajectory analysis, and reclassification of unrecognised objects by processing the LiDAR data, pre-processed in a .osef format, thereby transforming it to make it suitable for simulation. The proposed solution for the monitoring of urban traffic is demonstrated by the usage of SUMO (Simulation of Urban MObility) for performing simulations and a Random Forest model for unrecognized object reclassification to pre-existing vehicles and pedestrian classes. The architecture of the proposed workflow can possibly be applied in other similar urban settings, providing a scalable solution for both traffic management and urban planning. The study’s results support the wider use of urban digital twin principles in ITS by highlighting the value of advanced modelling tools and high-quality data in addressing today's urban transportation challenges.

Formation and Preservation conditions of ultra-deep (>6000 m) hydrocarbon systems

For 40 years, the concept of petroleum systems has been well developed and a considerable amount of actual data has been accumulated. However, with the beginning of the development of ultra-large depths (more than 6000 m, although nowadays this boundary has been lowered to 8000 m) it became clear that many processes proceed somewhat differently, and some a priori assumptions cease to be relevant. The article deals with the peculiarities of formation and conditions of preservation of petroleum systems when diving to ultra-large depths. Special attention is paid to numerous examples of HC detection in the liquid phase accumulated over the last decades, when the upper ‘classical’ threshold of formation temperatures, at which, as it was supposed, the transformation of liquid HC into gaseous should occur. Examples of studies of ultra-deep sections, first, well data, considered in the article, allow us to constantly revise upward the maximum temperatures in the pools, leading to oil destruction, previously estimated rather conservatively. This, in turn, causes reassessment of HC potential of many basins. At the same time, the volume of reserves of both oil and gas in ultra-deep sections is constantly increasing, especially in China, where vast experience of direct continental projects has been accumulated. At the same time, there are limited opportunities to prepare any practical recommendations directly, and the development of methods for forecasting such accumulations requires further significant efforts. It can be confidently assumed that the upper limit of the so-called ultra-deep will fall significantly below 8000 m, as the data show that geological constraints are significantly decreasing, technological solutions are continuously emerging, and their costs are steadily decreasing. The development of ultra-deep projects as an alternative to the so-called ‘shale’ projects will inevitably lead to an increase in their efficiency in developing oil and gas deposits, which are not perceived as such today. The article considers examples of ultra-deep hydrocarbon systems in the basins of continental China (Tarim, Dzungarian and Sichuan) and the Gulf of Mexico (Perdido folded zone).

Decision-making frameworks for assessment of small-scale off-grid photovoltaic home system-based design concepts in rural context of north-east India

Energy security plays an influential role in developing sustainable cities and promoting a better quality of life for the population. The United Nations' sustainable development goal focuses on energy security. Against the backdrop of India's energy concerns in the northeastern region, the study investigates the user-centric challenges related to the designs of solar photovoltaic home system concepts to facilitate access to energy. This is followed by the proposal of design concepts for solar photovoltaic home systems that take due cognizance of the identified challenges. To facilitate determining the optimal design concept in the context of small-scale off-grid photovoltaic home systems the paper proposes and applies an extended TOmada de Decisao Interativa Multicriteria (TODIM) methodology wherein the linguistic evaluations have been modelled using T-Spherical fuzzy sets. The information was aggregated using T-Spherical Fuzzy Aczel-Alsina Hammy Mean and T-Spherical Fuzzy Aczel-Alsina Weighted Hammy Mean operators. Ten design concepts were developed and evaluated through the proposed decision-making frameworks. Five performance metrics arising out of the field study: Functionality, Reliability, Affordability, Novelty and Usability have been chosen to appraise the conceptualized design concepts. Design concept 3 has been revealed to be the optimal design concept for the application of the proposed approach. Sensitivity analysis of the ranking results revealed that although both the proposed methodologies are robust, the methodology based on T-Spherical fuzzy Aczel-Alsina Weighted Hammy Mean operator was revealed to be the superior of the two. By presenting an effective method to address the complexities in design assessment for off-grid PV systems, this research offers practical insights to guide context-specific design in the region.

Compatible weak factorization systems and model structures

In this paper, the concept of compatible weak factorization systems in general categories is introduced as a counterpart of compatible complete cotorsion pairs in abelian categories. We describe a method to construct model structures on general categories via two compatible weak factorization systems satisfying certain conditions, and hence, generalize a very useful result by Gillespie for abelian model structures. As particular examples, we show that weak factorization systems associated to some classical model structures (for example, the Kan-Quillen model structure on sSet) satisfy these conditions.

THE TRAINING OF TEMPERATURE MONITORING SYSTEM WITH LM35 SENSOR BASED ON RESBEERY PI

Abstract. This community service activity aims to train the community on developing and implementing a temperature monitoring system using the LM35 sensor integrated with Raspberry Pi. This training was carried out to improve people's understanding and skills, especially in utilizing microcontroller-based technology and IoT (Internet of Things) in daily life, especially in the field of room temperature or environmental monitoring. This activity involves targets, for example, teachers, students, and technicians, at SMA AL-IRSYAD TEGAL, with training methods that include basic theories about temperature sensors, introduction to Raspberry Pi, and hands-on practice in assembling and programming temperature monitoring systems. The results of this training showed that participants could understand the basic concepts of temperature monitoring systems and could apply the knowledge gained in making simple devices that can measure and display temperature in real time. The activity evaluation showed that most of the participants felt helped by this training and showed high interest in further developing the system that had been studied. In the future, it is hoped that similar activities can continue to be carried out to empower the community to utilize technology for daily needs. Keywords: Community service, temperature monitoring system, LM35, Raspberry Pi, technology training.

System friendliness of distributed resources in sustainable energy systems

The increasing share of volatile renewable energy generation in current and future energy systems which does not follow the demand, makes it necessary to shift the synchronization tasks to the system and demand level. The intended demand side consumption management is usually incentivized via financial mechanisms. However, the optimum design of related incentives is still unclear. It is usually discussed under the term “system friendliness” which in turn still lacks a broadly accepted definition. In this article we introduce a new technical definition of “system friendliness” and develop comprehensive and holistic related indicators. For that, we introduce the burden concept for energy systems which represents the amount of technical infrastructure required for stable operation. We use the concept of a hypothetical system energy storage to derive indicators that are capable of quantifying the system friendliness of a given point-of-interest. The developed indicators are independent of regulations or market environments which enables comparability of results between studies and different systems. In a case study we demonstrate our newly developed methodology and exemplary examine decentral district energy storages. Our findings demonstrate that today’s regulatory environments that usually support residential self-consumption maximization are counterproductive. Instead, we show that dynamic end-user prices coupled with dynamic feed in tariffs are able to incentivize an almost 100% system friendly behavior of distributed prosumers.

Art therapy and neuroscience: evidence, limits, and myths.

The evidence base for the effectiveness of art therapy continues to grow, even as a mechanistic understanding of how art therapy works remains limited. One promising avenue for increasing our understanding of how and why art therapy works is through the lens of neuroscience. A neuroscience-based approach to art therapy provides opportunities for improving understanding of the neural processes that underlie the complex interaction between perception, cognition, emotion and behavior that play out in the art therapy process. Understanding how therapeutic change occurs can result in improved treatment and better outcomes for clients. However, it can be tricky to connect art therapy and psychological theory directly to neural responses. The purposes of this perspective are to provide an overview of the current evidence and limits of neurobiological concepts of neuroplasticity, mirror systems, and interoception as applied to art therapy practice, and to provide updated information about outdated concepts that are still actively used in clinical practice. Critical analysis and understanding of the current scientific knowledge base can then be used to guide art therapy practice and support the development of hypothesis-based research to determine the primary mechanisms that drive the observed effects of art therapy interventions.