Systematic Solution Research Articles

MODERN PROBLEMS OF STRATEGIC ANALYSIS AND THEIR IMPACT ON THE EFFECTIVE ACTIVITY AND MANAGEMENT OF ENTERPRISE DEVELOPMENT

Introduction. For the identification the current problems of strategic analysis of an enterprise, as well as their impact on the development and management of its activities in the context of rapid changes in the environment, it is necessary to form an effective system of their management. The purpose of the article. The purpose of the study is to identify the problems of modern strategic analysis and their impact on the activities of an enterprise. Methods. The article uses classical research methods, such as analysis, synthesis, comparison, which allowed to more effectively consider the current problems of strategic analysis development and propose measures for their systematic solution. Results. The main approaches to defining the concept of «strategic analysis» are considered and it is determined that strategic analysis involves identifying opportunities and threats of the external environment, strengths and weaknesses of the enterprise, determining competitive advantages and market position. It is investigated that, according to the direction of strategic analysis, the collected data is accumulated and the enterprise can make informed decisions, adapt to changes in the external environment. Conclusions. It is determined that the integration of new approaches to the implementation of strategic analysis with the help of modern analytical systems makes it possible to identify potential threats and respond to them promptly for the long-term and effective management of the enterprise in the future.

The Efficacy of Haar Wavelets in Addressing Discontinuities of McKean Equations with Heaviside Functions

This study explores the application of Haar wavelets to solve the McKean equation, a reaction-diffusion equation with discontinuous Heaviside step function. Haar wavelets, with their compact support and orthogonality, offer straightforward but yet powerful tool for addressing the equation’s nonlinear dynamics. We focus on the time-independent solution of the McKean equation, which is crucial for understanding the threshold phenomenon that determines the system’s behavior. Despite the existence of analytical time-independent solution to the McKean equation, achieving such solutions in closed form is uncommon for more complicated systems, highlighting the utility of the Haar wavelet approach. The proposed method integrates the Haar series expansion of the highest order derivative, enabling systematic solution derivation. Through a detailed comparison with analytical solution, we validate the Haar wavelet approach as a robust and computationally feasible tool for solving complex reaction-diffusion system. The results also demonstrate the method’s accuracy and efficiency, offering insights into its broader applicability to more complex reaction-diffusion system, especially those with discontinuity and sharp transitions.

KSP-SCOS: new Karp-Steele patching based streamlined customer order scheduling approach

Customer order scheduling (COS) encapsulates one of the most intricate problems in operational optimization, primarily due to the multifaceted interplay of constraints such as temporal dependencies, resource limitations, and cost minimization. This paper introduces the Karp-Steele Patching for Streamlined COS (KSP-SCOS), a cutting-edge framework designed to address these complexities with unparalleled precision and efficiency. By incorporating the dynamic problem decomposition capabilities of Karp-Steele Patching, KSP-SCOS enhances the scheduling landscape through systematic exploration of feasible solutions while eliminating suboptimal paths through strategic pruning. The proposed approach was subjected to rigorous testing across diverse datasets representing a broad spectrum of real-world operational scenarios. These scenarios range from minimally constrained environments to those characterized by extensive resource contention and tight scheduling windows. Experimental findings reveal that KSP-SCOS consistently delivers near-optimal solutions, demonstrating robust scalability and significant reductions in computational overhead, regardless of the problem complexity. This research makes several noteworthy contributions to COS optimization : (1) The integration of the Karp-Steele Patching method within COS, ensuring a systematic yet adaptable solution process. (2) An empirical analysis across datasets of varying complexity, illustrating the algorithm’s effectiveness in balancing computational efficiency and scheduling quality. (3) An exploration of cost-time trade-offs, shedding light on the practical implications of for resource allocation in dynamic operational settings. The adaptability of KSP-SCOS establishes it as a groundbreaking for industries demanding dynamic, accurate, and resource-efficient scheduling strategies. Its capability to seamlessly adjust to evolving operational constraints underscores its critical relevance in scenarios requiring immediate and responsive decision-making. This study marks a pivotal advancement in resolving the pressing challenges of modern COS, paving the way for elevated operational efficacy and adaptability in increasingly complex environments.

Synthetic aperture X-ray ghost imaging with sub-micron pixel resolution

Synthetic aperture X-ray ghost imaging (SAXGI) is proposed to achieve megapixel X-ray ghost imaging together with a reduced number of measurements. As the bucket detector array is artificially generated by post-pixel-binning of the images collected with the same detector as that in the reference arm, the unique advantages of SAXGI are not verified experimentally. In this paper, we developed a systematic solution of the experimental implementation of SAXGI, with the automatic interchange of 2× and 20× optical magnification of the detector for object and reference signal acquisition respectively, together with electronic pixel-binning of the detector. Taking the experimentally achieved 40×40 blocks as the bucket array in the object arm and addressing the challenge of image registration among the reference and object signals, we successfully achieved SAXGI imaging of 1960×1920 pixels with a pixel size of 0.325 µm. By developing a set of protocols improved in each part of the experiments, we can implement the data acquisition process of SAXGI in a few minutes, which is anticipated to facilitate the further application of the SAXGI method in related research fields.

Step solution treatment of a wire-arc directed energy deposited Al-Zn-Mg-Cu alloy: defects suppression and mechanical property improvement

ABSTRACT Wire-arc directed energy deposition is promising for manufacturing ultra-high-strength Al-Zn-Mg-Cu alloy components. However, the undesired microstructure and performance of as-deposited alloys make the heat treatment a mandatory post-process, which still lacks systematic investigation. This work aims to establish a comprehensive understanding of it. An interplay between second-phase dissolution and defect formation in the single-stage solution of as-deposited Al-Zn-Mg-Cu alloy was found: as solution temperatures increase, the equilibrium proportion of residual phases decreases, but the proportion of pore defects increases significantly. Based on a systematic full-factor solution test, a 430°C/4 h + 450°C/4 h step solution process was proposed, which suppressed the pore defects by about 54.8% while keeping the effect of the residual phase dissolution unchanged. After the step solution and artificial aging, the average yield strength of the alloy reached 475 MPa, and the elongation reached 6.5%, showing 201.6% and 85.7% improvement compared with the as-deposited state, respectively.

Системный подход к обеспечению качества и безопасности пищевых продуктов на базе квалиметрии рисков

The article introduces a new systematic approach to product safety and quality. It relies on the measures of technological risk management based on the principles of Hazard Analysis and Critical Control Points (HACCP), qualimetric forecasting, and risk qualimetry. The stages and tools of risks identification, prediction, and analysis make it possible to detect faulty produce from field to market. The case study involved a line of flavored dairy products. The experiment demonstrated high efficiency in the field of risk management of safety and quality inconsistencies across the entire range of safety and quality requirements, including the sensory profile. The new approach provides a systematic solution to various safety and quality issues that every food-producing enterprise has to face.

Pengembangan Sistem Informasi Mahasiswa Universitas Amikom Purwokerto dengan Menggunakan Metode TOGAF

Currently, the Amikom University Purwokerto student portal is still not equipped with a student data search feature that can make it easier to access related information. The unavailability of this feature can provide significant obstacles to various students' daily activities, especially in activities such as academic research, collaborative group work across study programs, and interactions between departments. The aim of this research is to apply the TOGAF framework which is expected to be able to help identify the root of the problem and provide a more comprehensive, systematic and effective solution in an effort to improve the functionality of this portal, so that it can better support students' academic needs. This research uses the TOGAF method which includes Understanding Business Context, Vision Architecture, Definition Architecture, and Transition Architecture. The result of this research is a flowchart design for the student data search feature which was created and analyzed using the Bizagi Modeler application which was compared between the design and the current process. Based on the results, it shows that the design of the student data search flow through Student Amikom Purwokerto is much faster and more efficient because the data search time is reduced from 40 minutes to 3 minutes.

Focus on the comorbidities of heart failure: the importance of multidisciplinary management

The diagnosis and treatment of heart failure comorbidities present a significant clinical challenge, as these comorbidities significantly affect patient prognosis. The causes of heart failure comorbidities are complex, and the underlying mechanisms are not fully understood. Moreover, traditional heart failure management methods are inadequate in addressing these issues. Improving the management and treatment of comorbidities can significantly enhance patient quality of life and prognosis. This requires clinicians to have a comprehensive understanding of heart failure and its comorbidities and to be capable of devising effective treatment plans. Multidisciplinary management should be utilized to create individualized treatment plans for heart failure patients to better address the challenges of multiple comorbidities. Clinicians need to have a broad perspective and employ systematic approaches to improve treatment outcomes. This article emphasizes the importance of individualized and multidisciplinary management strategies in the treatment of heart failure comorbidities, aiming to provide a systematic solution to enhance patient quality of life and improve prognosis.

Deciphering the Potential Shifts in Highly Concentrated Litfsi Aqueous Electrolyte

This study unravels the potential shifts in LiTFSI aqueous solutions, including Li-salt activity effect and liquid junction potential, by characterizing concentration-dependent cation transference numbers (t +) and thermodynamic factors (θ). In the 0.5–5 M concentration range, t + decreases from 0.6 to 0.3, while θ increases from 1.2 to 12.2. The concentration-dependent correlations of t + and θ yields +32 mV of ∆E j between the 5 M test solution and 1 M reference solution and a 103-fold increase in salt activity, corresponding to a ~180 mV upward shift in Li-ion (de)-intercalation potential. Lastly, the cyclic voltammetry of Fe(CN)6 3−/4− in LiTFSI solutions, corrected by ∆E j, revealed that the increasing Li-ion reactivity upward shifts the redox potential of Fe(CN)6 3−/4− upon increasing LiTFSI concentration, evidenced by solution polarity measurement. This work offers a systematic solution for the potential shift and insights into the highly concentrated electrolytes. Figure 1

Merged-nets enumeration for the systematic design of multicomponent reticular structures.

Rational design of intricate multicomponent reticular structures is often hindered by the lack of suitable blueprint nets. We established the merged-net approach, proffering optimal balance between designability and complexity, as a systematic solution for the rational assembly of multicomponent structures. In this work, by methodically mapping node-net relationships among 53 basic edge-transitive nets, we conceived a signature net map to identify merging net pairs, resulting in the enumeration of 53 merged nets. We developed a practical design algorithm and proposed more than 100 multicomponent metal-organic framework platforms. The effectiveness of this approach is commended by the successful synthesis of four classes of materials, which is based on merging three-periodic nets with the four possible net periodicities. The construction of multicomponent materials based on derived nets of merged nets highlights the potential of the merged-net approach in accelerating the discovery of intricate reticular materials.

Primary healthcare as a strategy for eliminating hepatitis C: the METRIC toolkit.

This paper presents the development of the METRIC toolkit, aimed at enhancing primary healthcare interventions in the context of hepatitis C control, thus contributing to the World Health Organization's global strategy to achieve the elimination of the disease by 2030. At the global level, most people living with hepatitis C are unaware of their condition. As such, the eradication of hepatitis C necessitates comprehensive strategies within primary healthcare settings, as it provides an opportunity to reach the general population, facilitates the identification of potential patients who may be unfamiliar with hepatitis C, and guides them toward adequate care. Herein, we propose the METRIC toolkit as a means to optimize the efficiency and efficacy of healthcare services dedicated to hepatitis C control. The development of the METRIC toolkit was guided by a thorough review of pertinent literature, focusing on primary healthcare interventions in hepatitis C control. Key components were identified, encompassing systematic problem identification, solution formulation, outcome evaluation, and feedback integration. The METRIC toolkit represents a valuable resource for strengthening primary healthcare interventions in hepatitis C control. By fostering a culture of continuous improvement and data-driven decision-making, this framework holds promise in advancing the global agenda towards hepatitis C elimination. However, its successful application requires careful consideration of contextual factors and ongoing adaptation to local needs and circumstances.

Exploring a New CPD Model for Promoting Chinese Teachers’ Success: A Review Paper

People's ideas are constantly evolving with changes in society and the times. This attracted more attention to the issue of continuous professional development for Chinese teachers. The traditional approach to professional development only addresses issues relevant to the current situation and may not be sufficient to support teachers' growth in more complex and challenging contexts. This paper examines the environment and context of teacher professional development, focusing on both domestic and international educational theories and practices. It proposes a systematic solution that is aligned with the current state of teacher professional development in China.

Application of Mobile Technology in Enterprise Management: From Mobile Office to Intelligent Decision Support

With the rapid advancement of information technology, the application of mobile technology in enterprise management has become increasingly widespread. From mobile office solutions to intelligent decision support systems, the proliferation of mobile technology has not only enhanced operational efficiency but also provided more flexible and convenient management methods. Existing research indicates that the adoption of mobile office solutions enables enterprises to overcome limitations of time and space, improving work efficiency and employee satisfaction. Additionally, the implementation of intelligent decision support systems allows enterprises to make faster and more accurate business decisions. However, current studies often focus on individual mobile technologies or application scenarios, lacking a systematic exploration of mobile office data sharing and intelligent decision-making collaboration. Moreover, most research overlooks privacy protection issues in the enterprise management decision-making process. To address these gaps, this paper proposes a scheme for mobile office data sharing and intelligent decision-making collaboration and examines the integration of privacy protection in the decision-making process. The findings not only enrich the theoretical framework of management studies but also provide enterprises with a systematic and practical solution for mobile technology applications, enhancing management efficiency and intelligence while effectively safeguarding data privacy and security.

Hybrid optimization-based secured routing in mobile ad-hoc network

Mobile Ad hoc Networks (MANETs) pose significant routing challenges due to their decentralized and dynamic nature. Node mobility results in frequent changes in network topology, leading to unsFIG connectivity and link quality. Traditional RPs designed for static networks are inadequate for MANETs. To deal with these issues, a secure routing approach is proposed using the Red Panda-Lyrebrid Optimization (RePLO) algorithm, which combines the advantages of the Red Panda Optimization (RPO) and Lyrebird Optimization Algorithm (LOA) algorithms. The proposed approach consists of five steps: (i) configuring the system model, (ii) developing the energy model, (iii) creating the mobility model, (iv) selecting cluster heads using the RePLO algorithm, and (v) routing using the RePLO algorithm. The RePLO algorithm optimizes cluster head selection and routing while considering specific constraints such as delay, distance, energy, & security for Cluster Head (CH) selection, and link quality and enhanced trust for routing optimization. The effectiveness of the proposed approach is evaluated using various metrics to demonstrate its efficiency in MANET routing. By integrating multiple optimization techniques and considering critical constraints, the RePLO algorithm offers a systematic and secure solution for MANET routing. The evaluation results confirm the efficacy of the proposed approach in improving network performance, reliability, and security. Overall, the RePLO algorithm presents a promising approach to tackle the routing issues inherent in MANETs, paving the way for more robust and efficient communication in mobile ad hoc networks.

Zoning of the Lower Volga Region and Formation of Territory, Okrug, District and Rural Bodies of Soviet Authority in 1928: First Stage

Introduction. The article examines the process of formation of the Lower Volga region and Soviet authorities at the level of regional, district, and rural administration at the first stage of zoning (before the liquidation of okrugs). Methods and materials. The research was carried out based on traditional methods of historical research (historical-genetic, retrospective, historical-systemic, and historical-comparative). The use of an array of unpublished archival documents stored in the State Archives of the Volgograd Region and the Documentation Center for Contemporary History of the Volgograd Region, and materials from periodicals and legislative sources of government bodies of the USSR and the RSFSR, greatly facilitated the research process. Analysis. The study is aimed at identifying the regional specifics of the zoning process and the accompanying process of formation of Soviet authorities (at the level of councils and executive committees of councils of the Lower Volga region). Results. The zoning of the Lower Volga region already at the first stage revealed a range of problems, the systematic solution of which in the future will make it possible to transform the agricultural region into the industrial center of the Volga region. In the process of reform, along with positive aspects – the reduction in cost of the management apparatus, the bringing closer to the population of Soviet authorities endowed with significant powers (district executive committees and councils) – there were also clearly negative consequences. The distance of rural councils from middle management and the consolidation of individual rural councils, on the one hand, led to the planned reduction of hardware costs but, on the other hand, excluded remote villages from active public life. Districts became the main operational unit of economic and Soviet work in the region. There were several issues to address, including the imbalance between districts with different population sizes, from small ones with just over 2,000 people to large ones with populations approaching 100,000. Additionally, there was a lack of communication between administrative units and personnel problems, which emerged as a significant hurdle in the development of district and rural Soviet administration at the second stage of zoning (in the conditions of the liquidation of okrugs).

Resilience-oriented adaptive predictive maintenance optimization for continuous process manufacturing systems considering mission profile variation

Continuous process manufacturing systems (CPMSs) are typical phased mission systems that require high standards of operational stability, reliability, and safety. With the variation of production mission profiles, CPMSs are required to run in diverse modes or conditions in different phases; therefore, to meet these standards, maintenance decisions applied to CPMSs should be adapted to such variations. Considering that the concept of “resilience” provides a systematic solution to evaluate system adaptability via “disruption absorption” and “recoverability,” this paper proposes a CPMS resilience evaluation model and utilizes it as guidance for the optimization of CPMS predictive maintenance (PdM). The proposed method consists of the following steps: (1) applying a customized Seasonal Trend Decomposition model to predict the future trend of production mission profile variations, (2) assessing the production mission accomplishment capability of CPMS based on a Gamma process model of equipment performance degradation, (3) using disruption response ratio to evaluate CPMS resilience based on mission accomplishment capability, and (4) proposing a Simulated Annealing Q-Learning algorithm for adaptive PdM optimization, which keeps resilience above a threshold level while minimizing maintenance costs. The applicability and effectiveness of the proposed method are validated by an industrial case study of a nuclear fuel rod shielding component CPMS.

Tracking Control for $(x,u)$-Flat Systems by Quasi-Static Feedback of Classical States

It is well known that for flat systems the tracking control problem can be solved by utilizing a linearizing quasi-static feedback of generalized states. If measurements (or estimates) of a so-called generalized Brunovský state are available, a linear, decoupled and asymptotically stable tracking error dynamics can be achieved. However, from a practical point of view, it is often desirable to achieve the same tracking error dynamics by feedback of a classical state instead of a generalized one. This is due to the fact that the components of a classical state typically correspond to measurable physical quantities, whereas a generalized Brunovský state often contains higher order time derivatives of the (fictitious) flat output which are not directly accessible by measurements. In this paper, a systematic solution for the tracking control problem based on quasi-static feedback and measurements of classical states only is derived for the subclass of $(x,u)$-flat systems.

Prediction of Resale Value of Pre-Owned Luxury Cars in the Indian Market Employing Machine Learning Techniques

Abstract: The market for second-hand luxury cars in India is witnessing a significant surge, expected to grow at a rate of 16.30% from 2024 to 2032. This growth is fueled by increased car manufacturing, rising disposable incomes, and a shift in consumer preferences towards luxury brands. However, accurately determining the resale value of these vehicles presents a challenge due to various influencing factors. In this dynamic market, informed decision-making is crucial for luxury car buyers. Digital platforms have revolutionized access to real-time market data, helping both buyers and sellers stay updated on pricing trends. Our research explores the complexities of predicting prices for pre-owned luxury cars and introduces a predictive analytics framework using advanced machine learning algorithms. We collected and preprocessed a comprehensive dataset and conducted an in-depth exploratory data analysis. Various regression techniques, including Linear Regression, Decision Tree, Random Forest, and Extreme Gradient Boosting, were employed to forecast prices. These models were evaluated using metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) to identify the most accurate predictive model. This study offers a systematic solution for price prediction, enhancing the buying process for stakeholders in the second-hand luxury car market

A systematic solution of distributed and trusted chain-network integration

Blockchain, with its characteristics of decentralization, transparency, openness, and intangibility, has become the preferred choice for enhancing the credibility of the industrial cluster network platform. Industrial clusters are an important organizational form for developing small and medium-sized enterprises, and the information service platform plays a key role. This paper constructs a trusted paradigm model and a new trusted framework for the industrial cluster network platform and proposes an adaptive distributed network scheme. Specifically, it includes a decentralized and non-repudiable solution for the autonomous scenario of the industrial cluster Industrial Internet, promoting the transformation of the network into a self-adjusting and self-managing distributed network, enhancing the credibility of the platform, and reducing the negative impact of distrust and information asymmetry; it proposes three models (private chain, alliance chain, and public chain) for the integration of blockchain and the Industrial Internet, providing a secure and reliable support platform for the development of industrial clusters, solving the problem of information asymmetry, promoting trust and synergy, and maximizing the synergistic effect; from the perspective of security and reliability, it deeply analyzes the industrial cluster network platform, proposes a trusted framework, and realizes the data layer and application layer of the network with the help of blockchain technology. The experimental results show that these models meet the requirements of the industrial cluster in terms of data privacy, control, and credibility and have a positive significance for promoting the development and digital transformation of the industrial cluster.

Research on the Impact and Countermeasures of Exhibition Environment on Hotel Indoors

In the modern hotel industry, the optimization of indoor display environment not only affects the first impression of customers, but also has a profound impact on the brand image and market competitiveness of the entire hotel. A well-designed display can significantly enhance customer experience, enhance customer satisfaction and loyalty towards the hotel. The focus of this study is to explore the overall impact of display environment on the indoor atmosphere of hotels, and provide targeted improvement strategies. Further empirical research is used to support theoretical analysis and strengthen the practical application value of display environment. The article aims to provide hotel managers with a systematic solution to optimize indoor displays and stimulate the potential commercial value of the hotel.