Autonomous Management Research Articles

Carbon Asset Management Mode Selection for Capital-Constrained Enterprises

Carbon asset management has become an important way to reduce carbon costs. There are three main carbon asset management modes, including carbon quota compliance, carbon asset autonomous management, and custody. A key challenge faced by capital-constrained enterprises is how to scientifically select a carbon asset management mode based on actual needs. This paper considers the impacts of setup costs of carbon asset management departments, carbon asset appreciation, custody costs, and revenue sharing, maximizes the enterprises’ profits, develops optimization models for three modes, and provides the optimal low-carbon production strategies. This paper provides evidence for enterprises to choose optimal modes under different capital levels and carbon emissions by comparing modes. The conclusions are as follows. When setup costs are low, the carbon asset autonomous management mode is suggested for the optimal profit. With higher setup costs, either carbon asset compliance or custody mode is recommended. Under abundant capital, the carbon asset custody mode is suggested. Given a certain amount of capital and low setup costs, high-emission enterprises are encouraged to adopt the carbon asset autonomous management mode for a win–win of profits and carbon emissions. The carbon asset custody and compliance modes are suggested for medium-emission and low-emission enterprises, respectively.

Integration of Business Unit Financial Reporting Systems in Village-Owned Enterprises (BUMDes)

BUMDes is a village government-owned business institution established in an effort to strengthen the village economy, based on the needs and potential of the village concerned. In its operations, BUMDes can have various business units with autonomous management in one business entity. Each business unit makes its own financial report according to the type of business it runs. The resulting financial report will be submitted to the head office for merger and consolidation. Although each business unit has a different type of business, the process and provisions for preparing financial reports in each business unit are the same, because they are regulated in government regulations. The only differences are related to operational reporting and components/account names in the financial report. To improve the ease of preparation and accountability of its financial reports, the existence of an integrated accounting information system is a must. As an initial step, a design process is carried out which will be used as the basis or technical reference for the development process. The design process is carried out with an object-oriented approach, with the results in the form of classes/components and interactions between them which are the foundation of the system building. This will facilitate the development process and this integrated system can then be built/developed in stages according to the development/addition of business units from BUMDes.

Efficient crop row detection using transformer-based parameter prediction

The detection of crop rows is crucial for achieving visual navigation and is one of the key technologies for enabling autonomous management of maize fields. However, the current mainstream approach to maize crop row detection often involves two steps - feature extraction followed by post-processing. While useful, this method is inefficient, and the heuristic rules designed by humans limit the scalability of these methods. To simplify the solution and enhance its generality, crop row detection is defined as a process of approximating curves. Polynomial parameter learning is adopted to constrain the parameters of crop row shapes, and utilise a model built on the Transformer architecture to learn the elongated structures and global context of crop rows, achieving end-to-end output of crop row shape parameters. The proposed approach has achieved rapid and excellent detection results in complex field environments, even in the presence of curved crop rows.

A Brief Analysis of the Status Quo of the Autonomous Management of College Students

A Brief Analysis of the Status Quo of the Autonomous Management of College Students

InstaCropNet: An efficient Unet-Based architecture for precise crop row detection in agricultural applications

Autonomous navigation in farmlands is one of the key technologies for achieving autonomous management in maize fields. Among various navigation techniques, visual navigation using widely available RGB images is a cost-effective solution. However, current mainstream methods for maize crop row detection often rely on highly specialized, manually devised heuristic rules, limiting the scalability of these methods. To simplify the solution and enhance its universality, we propose an innovative crop row annotation strategy. This strategy, by simulating the strip-like structure of the crop row's central area, effectively avoids interference from lateral growth of crop leaves. Based on this, we developed a deep learning network with a dual-branch architecture, InstaCropNet, which achieves end-to-end segmentation of crop row instances. Subsequently, through the row anchor segmentation technique, we accurately locate the positions of different crop row instances and perform line fitting. Experimental results demonstrate that our method has an average angular deviation of no more than 2°, and the accuracy of crop row detection reaches 96.5%.

Parenting Emerging Adults with Multiple Sclerosis: A Qualitative Analysis of the Parents’ Perspective

Parents of emerging adults are requested to adjust their level of support and control according to their child’s developmental age and to foster their autonomy. This developmental task may be more difficult when emerging adults are suffering from a chronic illness. Parenting emerging adults with a chronic illness is an under-investigated topic, especially with reference to multiple sclerosis (MS), a chronic neurological disease usually diagnosed in emerging adulthood. The study aims to qualitatively explore the characteristics of the relationship that parents report having with their emerging adult children (18–29 years) with MS. Specifically, we investigated how the dimensions of support and control emerge from the parents’ perspective, whether overparenting (characterized by both oversupport and overcontrol) emerges, and its characteristics. Eleven semi-structured interviews were conducted with parents of emerging adults with MS, and a qualitative content analysis was performed through Atlas.ti 6.0 software, combining a deductive and an inductive approach in relation to the study aims. A system of 13 codes was defined and a total of 141 quotations were codified. Overparenting appears to be the most frequent relational mode among the parents interviewed. Most quotations referred to oversupport (in particular, parents report anticipatory anxiety about child’s well-being and show excessive indulgence and permissiveness) and overcontrol (in particular, parents report a vicarious management of daily life and medical therapies). The study gives indications for psychological interventions helping parents to adequately support their children while encouraging their autonomous management of daily life and illness-related difficulties.

Enhancing IoT data confidentiality and energy efficiency through decision tree-based self-management

Given the widespread deployment of IoT devices characterized by heterogeneity and energy limits, a greater emphasis on IoT data security within IoT environments has become required. This critical situation encouraged the deployment of lightweight encryption solutions to avoid additional attacks. These solutions, which are based on traditional encryption algorithms, are intended to fulfill the demands of resource-constrained devices while maintaining a high security level. In this research, we provide a novel IoT framework that uses lightweight cryptographic ciphers and the Autonomic Computing paradigm to self-manage the security of IoT devices. Our framework is based on a decision tree technique to guarantee the IoT data confidentiality by selecting and changing in an autonomic manner the most appropriate lightweight encryption algorithm to be used in order to improve energy efficiency by extending the lifespan of IoT devices and to provide an adapted security level according to IoT application type and IoT object state.

Autonomic end-to-end quality-of-service assurance over QKD-secured optical networks

Quantum key distribution (QKD) provides future-proof security for data communications over optical networks. Currently, sophisticated QKD systems are developed and the scale of QKD-secured optical networks (QKD-ONs) becomes larger. Given the complex network conditions and dynamic end-to-end security services in QKD-ONs, autonomic management and control becomes a promising paradigm to support end-to-end quality-of-service (QoS) assurance in an efficient and stable way without requiring human intervention. Hence, to enable and utilize the autonomic functionalities over QKD-ONs for realizing the end-to-end QoS assurance becomes a challenge. This work enhances the software defined networking (SDN) technique to tackle this challenge because SDN can add programmability and flexibility for QKD-ON’s management and control. A new architecture of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance is designed, where a knowledge engine with autonomic control loops is developed in the SDN controller. We present the autonomic end-to-end QoS assurance procedure, and the cross-layer collaborative QoS assurance (CLC-QA) strategy for implementing the autonomic functionalities in the network level over QKD-ONs. We also establish an experimental testbed of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance, and perform the numerical simulation to verify our proposed approaches. Experimental results demonstrate that our presented approaches can achieve the millisecond-level overall latency of 337 ms and 618 ms, during the first and second autonomic adjustment without human intervention in case of the autonomic QoS protection. Moreover, the CLC-QA strategy is evaluated under different traffic loads by being compared with the baseline strategy without cross-layer collaboration. It can improve 22.5% protection success ratio and save 5.7% average key consumption.

A Survey of MPSoC Management toward Self-Awareness.

Managing Multi-Processor Systems-on-Chip (MPSoCs) is becoming increasingly complex as demands for advanced capabilities rise. This complexity is due to the involvement of more processing elements and resources, leading to a higher degree of heterogeneity throughout the system. Over time, management schemes have evolved from simple to autonomous systems with continuous control and monitoring of various parameters such as power distribution, thermal events, fault tolerance, and system security. Autonomous management integrates self-awareness into the system, making it aware of its environment, behavior, and objectives. Self-Aware Cyber-Physical Systems-on-Chip (SA-CPSoCs) have emerged as a concept to achieve highly autonomous management. Communication infrastructure is also vital to SoCs, and Software-Defined Networks-on-Chip (SDNoCs) can serve as a base structure for self-aware systems-on-chip. This paper presents a survey of the evolution of MPSoC management over the last two decades, categorizing research works according to their objectives and improvements. It also discusses the characteristics and properties of SA-CPSoCs and explains why SDNoCs are crucial for these systems.

Research on Occupational Poisoning and Biological Monitoring

A new system for the regulation of chemical substances was introduced in Japan in April 2023. Unlike delineated rules, the new system does not specify any specific measures for individual substances, but is rather based on the management of health through the voluntary implementation of measures in order to reduce exposure to all dangerous/hazardous chemical substances. Regarding specific methods, exposures will be mainly elucidated through the measurement of a work environment. However, the necessity of biological monitoring should also be considered. This study aimed to identify the importance of biological monitoring by reviewing changes made over time in biological monitoring methods used for occupational poisoning. The study presents occupational poisoning by several compounds (methyl bromide, polycyclic aromatic hydrocarbons, and MOCA) and the corresponding biological monitoring methods utilized, as researched by the author. Changes in biological monitoring based on the history of the Study Group on Occupational Poisoning and Biological Monitoring of the Japan Society for Occupational Health are also introduced. The areas of occupational poisoning at different times and cases of occupational cancer caused by exposure to chemical substances were presented in lectures held by the Study Group on Occupational Poisoning and Biological Monitoring. These lectures showed that although biological monitoring was previously implemented primarily by measuring the urinary metabolites of the exposed substance, the monitoring methods used have changed as the nature of exposure has changed, leading to the development of new tools that detect trace, low concentration, and mixed exposures. The health management of workers handling chemical substances at occupational sites will be shifted to autonomous management. However, it should be noted that only biological monitoring can detect and prove true exposure. Particularly, risk assessment by biological monitoring is necessary for substances that are suspected to be absorbed through the skin, and the measurement methods used should continue to be developed and refined. The significance of biological monitoring will continue to increase.

Impact of Integrated Artificial Intelligence and Internet of Things Technologies on Smart City Transformation

Rapid urbanization is placing tremendous pressure on limited resources and aging infrastructure in cities worldwide. Meanwhile, new technologies are emerging to help address urban challenges through data-driven solutions. This paper explores how the strategic integration of artificial intelligence (AI) and Internet of Things (IoT) can transform urban management and services delivery for smart and sustainable cities. The Internet of Things enables the ubiquitous collection of real-time data across urban systems through embedded sensors. However, extracting actionable insights requires advanced analytics. Concurrently, artificial intelligence provides techniques to autonomously analyze huge volumes of IoT-sensed urban data. When combined effectively, AI and IoT can automatically monitor infrastructure, optimize operations, and enhance citizen experiences. This paper first defines key concepts and outlines applications of AI and IoT independently in areas like transportation, energy, environment, and public safety. It then examines how both technologies can be integrated for mutual benefit. Examples of integrated solutions such as predictive maintenance, intelligent transportation, and emergency response optimization are discussed. Challenges to adoption like data privacy, infrastructure costs, skills gaps, and technical standardization are also covered. The conclusion underscores the tremendous potential of AI and IoT to create efficient, resilient and livable urban environments through ubiquitous sensing and autonomous management. With proper policy support and collaborations, cities worldwide can leverage these smart technologies to sustainably combat problems facing urbanization.

Trustworthiness modeling and evaluation for a nearly autonomous management and control system

The Nearly Autonomous Management and Control (NAMAC) system supports the advanced reactor operation by recommending control actions to operators based on real-time measurements and digital twins (DTs) learning from the knowledge base. To enable the safe and reliable use of autonomous technologies, NAMAC and its recommendations should be trustworthy to operators and regulators at both the design and operation stages. This study proposes a NAMAC trustworthiness modeling and evaluation framework supported by trustworthiness ontologies and evidence-based approaches. The development-time and run-time ontologies are separately constructed and then converted to Bayesian networks to quantitatively evaluate the NAMAC trustworthiness. This evaluation is demonstrated by collecting and characterizing evidence from NAMAC practices, such as the development and assessment of the NAMAC system, data coverage assessment, and the training and optimizations of neural-network-based DTs. Our proposed approach can aggregate various trustworthiness attributes of complex artificial-intelligence-supported systems for safety-critical applications. It also considers the interaction between different DTs and extends beyond the trustworthiness evaluation of a single DT. The evidence-based method enhances the transparency of the trustworthiness modeling and evaluation processes and helps identify uncertainties and subjectivity involved in the processes.

Extended ArchiMate Metamodel with a context-awareness layer for a dynamic Enterprise architecture model

Nowadays, in a turbulent environment, enterprise must be proactive and even predictive to survive in front of the plenty natures of dynamics. Achieving the desired proactivity and predictability, supposes that the enterprise works in advance on its internal transformation plans, but also develops an awareness to its context, to intercept, analyze and simulate any potential trigger of change that could affect its stability or more precisely its state of equilibrium. In this work, the concept of enterprise architecture is considered as a tool for establishing alignment between business, strategy, and IT. This paper is a continuation to previous works seeking for a dynamic model of enterprise architecture, able to respond in an autonomic manner to the turbulent environment. The self-adaptiveness was highlighted basically using the well-known loop, monitor, analyze, plan, execute and Knowledge. The use of Case-Based Reasoning was suggested to store a collection of problems and their resolutions, then using algorithms of similarity and adaptation to suggest the problem’s best fit solution. To make the reasoning mechanism and similarity process as reliable as possible, it was important to maximize experiences and expand the knowledge base. For thus, the proposition was to share knowledge bases. In this paper, the context awareness is considered as second source to enrich the knowledge base and to stay vigilant and sensitive to triggers of change.

THE METHOD OF CONSTRUCTING THE LAW OF THE SECURITY MANAGEMENT SYSTEM OF CRITICAL INFRASTRUCTURE OBJECTS IN THE CONDITIONS OF EXTERNAL UNCONTROLLED INFLUENCES

The intensive development of information technologies with a high degree of autonomy requires the development of autonomous management systems for optimal management. This issue is especially acute for critical infrastructure objects that have been proven to be affected by extreme external factors and impacts. It is proposed to consider the management process as management in a system with incomplete a priori information about the managed process. The process of managing which changes as information accumulates and is used to improve the operation of the entire security system in general. An identification approach to the synthesis of indirect adaptive control is used, which consists in specifying the model of the object during the control process. On the basis of the refined model, a safety control signal of the object is produced. The model of the object needs clarification because the system is constantly affected by external uncontrolled influences. The difference between the proposed method and the existing ones is that it offers a method of building a robust control system that allows to compensate for unknown disturbances with a certain accuracy in the required time. At the same time, by selecting the parameters of the closed system, it is possible to make the error and time values sufficiently small.

Impact of telephone follow-up on COPD outcomes in pulmonary rehabilitation patients: A randomized clinical trial.

The educational component is a comprehensive part of Pulmonary Rehabilitation (PR), and telephone follow-up (TFU) is an alternative to reinforce face-to-face education. The objective was to determine the effect of telephone follow-up on educational needs, dyspnea, quality of life and functional capacity in Chronic Obstructive Pulmonary Disease (COPD) patients undergoing PR. Double-blind randomized controlled clinical trial in patients with COPD in a PR program in Cali-Colombia, allocation by randomization tables. All patients received 24 sessions of PR, which included face-to-face education sessions. In addition, the experimental group received telephone calls twice a week to reinforce the face-to-face educational content. The Lung Information Needs Questionnaire (LINQ) was used to measure disease knowledge, the Saint George's Respiratory Questionnaire to measure quality of life, the modified Medical Research Council (mMRC) scale to measure dyspnea, and the 6-minute walking test (6MWT) to measure functional capacity. Thirty-four patients were randomized and 31 were analyzed. PR group with conventional education (PRTE) n=15 and PR group with education plus telephone follow-up (PRTETFU) n=16. Significant improvement from baseline to endpoint in both groups: LINQ (PRTE 4±1.1, p=0.003, PRTETFU 5.8±10.6, p=0.000), mMRC (PRTE 1.6±0.3, p=0.000, PRTETFU 0.6±0.3, p=0.036) and functional capacity (PM6M: PRTE 45.9m±16.1, p=0.013, PRTETFU 62.8m±21.4, p=0.010). Analysis showed differences between groups for changes in LINQ knowledge domain after intervention, with greater improvement for PRTETFU (p=0.018). The TFU is an alternative to reinforce the education. This study demonstrated greater positive effects for the autonomous management of the pathology. Adding educational reinforcement through phone calls to patients with COPD during PR leads to improved knowledge and skills for managing the disease.

On the use of big data frameworks in big service management

AbstractOver the last few years, big data have emerged as a paradigm for processing and analyzing a large volume of data. Coupled with other paradigms, such as cloud computing, service computing, and Internet of Things, big data processing takes advantage of the underlying cloud infrastructure, which allows hosting and managing massive amounts of data, while service computing allows to process and deliver various data sources as on‐demand services. This synergy between multiple paradigms has led to the emergence of big services, as a cross‐domain, large‐scale, and big data‐centric service model. Apart from the adaptation issues (e.g., need of high reaction to changes) inherited from other service models, the massiveness and heterogeneity of big services add a new factor of complexity to the way such a large‐scale service ecosystem is managed in case of execution deviations. Indeed, big services are often subject to frequent deviations at both the functional (e.g., service failure, QoS degradation, and IoT resource unavailability) and data (e.g., data source unavailability or access restrictions) levels. Handling these execution problems is beyond the capacity of traditional web/cloud service management tools, and the majority of big service approaches have targeted specific management operations, such as selection and composition. To maintain a moderate state and high quality of their cross‐domain execution, big services should be continuously monitored and managed in a scalable and autonomous way. To cope with the absence of self‐management frameworks for large‐scale services, the goal of this work is to design an autonomic management solution that takes the whole control of big services in an autonomous and distributed lifecycle process. We combine autonomic computing and big data processing paradigms to endow big services with self‐* and parallel processing capabilities. The proposed management framework takes advantage of the well‐known MapReduce programming model and Apache Spark and manages big service's related data using knowledge graph technology. We also define a scalable embedding model that allows processing and learning latent big service knowledge in a distributed manner. Finally, a cooperative decision mechanism is defined to trigger non‐conflicting management policies in response to the captured deviations of the running big service. Big services' management tasks (monitoring, embedding, and decision), as well as the core modules (autonomic managers' controller, embedding module, and coordinator), are implemented on top of Apache Spark as MapReduce jobs, while the processed data are represented as resilient distributed dataset (RDD) structures. To exploit the shared information exchanged between the workers and the master node (coordinator), and for further resolution of conflicts between management policies, we endowed the proposed framework with a lightweight communication mechanism that allows transferring useful knowledge between the running map‐reduce tasks and filtering inappropriate intermediate data (e.g., conflicting actions). The experimental results proved the increased quality of embeddings and the high performance of autonomic managers in a parallel and cooperative setting, thanks to the shared knowledge.

Solar-Powered Peltier-Based Air Cooler and Warmer in Medical Systems

Presently, there are many more commercial applications for thermoelectric Peltier coolers, notably portable air/water refrigerators, electronics cooling processes, thermal management systems in medical applications, and others. Thus, the goal of this project is to develop an experimentally-based optimisation procedure for powered by sunlight peltier-based air conditioners and heaters for use in hospitals that are capable of running continuously. This enables patients to cook meals in the heating element and keep drugs in the cold compartment inside the cooler, both functions being incorporated into one model while also reducing the device’s dimensions and requirement for space. In this study, a model that employs perturb and observe (P&O) approaches applied to solar systems under constant and partially shady circumstances was powered by the Maximum Power Point Tracking (MPPT) methodology. Additionally, the Internet of Things modules offer user and autonomous management, while the entire system is tracked and shown on an OLED. An appropriate number of modules also reduces the expense per cooling unit for Peltier coolers and warmers.

THE PROVISION OF ACCOUNTING AND FINANCIAL SUPPORT FOR BUMDES

Bunutin Village is situated inside the administrative boundaries of Bangli District, which is located in the regency of Bangli. The implementation of this PKM holds significant importance due to the various challenges encountered by BUMDes Panca Sedana Sari Bunutin. These challenges encompass human resources, company type, capital, professionalism, community support and trust, as well as planning. The implementation of BUMDes aims to foster collaboration among community institutions, leading to enhanced effectiveness in promoting equitable community welfare. The establishment of BUMDes is predicated upon the assessment of the village's needs and potential, with the aim of enhancing the welfare of the community. Hence, it is imperative to implement substantial measures in order to ensure the effective, efficient, professional, and autonomous management of BUMDes. The process of generating financial reports for every company, including BUMDes, necessitates diligent execution. Financial reports play a crucial role in assessing the financial standing and operational effectiveness of a corporate entity. The financial reports now utilised employ a manual system and do not adhere to the prescribed financial accounting standards. One potential solution to address this issue is to provide training to managers on the utilisation of computer-based accounting programmes. The current state of business management is deemed insufficient, necessitating the provision of comprehensive education on the subject. This will enable individuals to effectively harness the potential of their communities. Based on the findings obtained from the service conducted on May 17, 2023, which was attended by all BUMDes (Village-Owned Enterprises) across the Bangli district, it was observed that a significant number of BUMDes administrators had not submitted financial reports for their business activities. This lack of reporting was attributed to a limited comprehension of accounting terminology and processes among the administrators. There are only 27 BUMDes (Village-Owned Enterprises) that have achieved development and possess the capability to generate financial reports and get comprehensive explanations pertaining to BUMDes accounting principles and financial guidance. The forthcoming year, the director of the Community and Village Empowerment service expresses the desire for Warmadewa University to sustain its current service while exploring alternative subject matters. Additionally, the director aims to provide more comprehensive guidance to BUMDes administrators in the meticulous preparation of financial reports.

Design of Light, Small, and High-precision Digital Servo Clock for LEO Constellation

Modern low earth orbit (LEO) satellite systems have placed increasingly stringent requirements on spaceborne time-frequency systems in the fields of constellation autonomous management, distributed synthetic aperture radar (SAR) imaging, and navigation time service. Admittedly, the original high-stability constant-temperature crystal oscillator and high-stability temperature-compensated crystal oscillator can no longer comply with the indicator requirements of clock source frequency characteristics and clock synchronization accuracy. Likewise, traditional satellites use atomic clocks (rubidium atomic clocks and cesium atomic clocks). On account of their inherent characteristics, the ground receiving system needs to observe and count the clock parameter characteristics for a long time after the satellite enters orbit and frequently modify the future working state parameters. The features of being expensive and bulky increase the operation and maintenance costs of the ground system and the complexity of engineering implementation. In this paper, a kind of light and small high-precision digital servo clock based on the deep coupling of the global navigation satellite system (GNSS) is designed for the LEO satellite constellation. The tame clock is deeply coupled with the GNSS navigation receiver, and the high precision time-frequency difference between the local clock frequency source and GNSS is obtained by using the carrier and pseudo-range measurement information of visible satellite and carrier phase measurement information of the receiver. It not only utilizes the short-term high stability of OCXO but also employs the long-term time-frequency maintenance ability of GNSS so that the tamed OCXO is locked in GNSS for a long time, which can achieve frequency calibration of local clock sources and long-term output to various space-borne systems. The system is small in size and low in power consumption, with output frequency stability better than 3E-13 (10000 s), accuracy better than ±2E-13, and timing accuracy better than ±10 ns, which is comparable to the key technical indexes of spaceborne miniaturized rubidium clocks, in line with the current demand of miniaturization, low power consumption, and low cost of LEO constellations.

Interrupted Flight. Ukrainian Cinema of the All-Ukrainian Photo and Film Administration Era

Larysa Briukhovetska’s monograph “Interrupted Flight. Ukrainian Cinema of the VUFKU Era: An Attempt at Reconstruction”, based on documentary sources – 1920s periodicals, archives and memoirs of participants in the film process – reconstructs an almost unknown but extremely rich and fruitful period in the history of Ukrainian cinema, namely the activities of the All-Ukrainian Photo and Film Administration under conditions of autonomous management. This research is one of the first in Ukraine to comprehensively cover not only cinematic art but also the development of the film industry and film distribution, as well as the defence of national interests by the VUFCU board, which helped cinema to create conditions for successful development.