1. Introduction

The main characteristic of modernity is the rapid development of the processes functioning in it, which requires the employees of the enterprise to quickly adapt to the environment. The changes that occur in connection with the integration of capitals affect the transformation of relationships both within the enterprise and outside it. Updated technologies or made new products innovation (services) provide an enterprise with only short-term advantages, since competitors quickly adopt innovations, which allows them to occupy a leading position in the market.

The knowledge and skills of employees who are able to effectively use the limited resources of business entities form a special influence on the processes of maintaining competitive advantages. An employee of any company, who has a high level of general education, scientific and professional training, is capable not only of reproducing the acquired knowledge, but also of generalizing, analyzing and generating new knowledge in accordance with the needs of the labor market and operating conditions.

An important role in these processes is assigned to information resources, which, along with labor, capital and natural resources, determine the efficiency of production and the logic of macroeconomic dynamics. And, unlike the recent past, when the statement of the English banker, businessman, financier Nothan Rothschild was relevant that who owns information, he owns the world for the present, it is important, if not the generation of information, then at least the ability to quickly analyze and transform it into intelligent products. In these conditions, there is a process of formation of special professional characteristics of employees – competencies, which eventually determine the competitive advantages of the enterprise.

2. Literature Review

Well-known foreign and domestic scientists made a great contribution to the formulation and theoretical development of issues that illuminate the content of the concept of “competence” and the conditions for the formation of a set of competencies for employees of enterprises, depending on the knowledge gained on the basis of the resource concept.

In the course of their research, in [1], the famous Ukrainian scientists emphasized knowledge, which is becoming a major factor in the post-industrial economy, and efficiency, which is not being paid enough attention to. They support the research of Swiss scientists, where only 20% of the knowledge possessed by the company’s employees finds real application, despite the fact that 42% of corporate knowledge is the intelligence of the personnel, which is not recorded in any way on physical media.

Most often, knowledge is associated with such a concept as competence. For the first time the concept of “competence” was proposed by the American psychologist D. McClelland, who in 1973 in his article “Measuring competence instead of measuring intelligence” noted that competence is necessary to predict the level of performance of efficiency  According to his interpretation, competence is a circle of problems or a field of activity in which a person has knowledge and experience. In his theoretical study, [2] author described enterprise competence as a set of personnel competencies. The studies that conducted showed that traditional academic tests of aptitude and knowledge, as well as the availability of any diplomas from potential job performers, do not provide them with the effectiveness of performance of work duties and success in professional activities. Such conclusions led to the search for “competencies” as characteristics that distinguish and predict the level of performance of efficiency in specific performers.

In [3], the authors are considered directly the developers of the competence-based approach, according to which competence is the basic quality of an individual, which has a causal relationship to effective performance in work or other situations. Basic quality means that competence is a permanent (persistent) part of the personality that can determine a person’s behavior in a large number of situations and work tasks.

In [4], well-known scientists proposed the concept of key competencies, they became the founders of the work «Key competencies of corporations» (1990), which continued the development of the competence approach. These scholars define core competencies as the skills and abilities that enable a company to deliver fundamental benefits to consumers. Proposing their concept, in  [5], the authors argue that the term “core competence” is used to characterize a set of skills and technologies, a set of unsystematically accumulated knowledge and experience by a company, which become the basis of successful competition.

In [6],  the authors note that almost every company has at least one type of activity in which it has succeeded enough to consider the knowledge gained there as key competencies, that is, one that provides a competitive advantage. They argues that key competencies do not have a direct impact on the success or failure of a brand, since they are not directly focused on the needs of consumers and therefore cannot contribute to consolidating the brand’s position. Excellence in the marketplace can be achieved not simply through unique enterprise resources and capabilities, but through their proper application.

A number of scientists distinguish between “knowledge” and “value” components in the competence. Thus, European scientists in the TUNING project note that the concept of competence includes knowledge as understanding (theoretical knowledge of the academic field, the ability to know and understand), knowledge of how to act (practical and operational application of knowledge to specific situations), knowledge of how to be (values as inherent part of the way of perception and life with others in a social context) [7]. In  [8], the the authors explains that competence is a general ability based on knowledge, experience, values, inclinations that are acquired through training. In [9], the authtor described the term “competence” as the ability to solve problems, provided not only by the possession of ready-made information, but also by the intensive participation of the mind, experience, and creative abilities of students.

In [10], according to the views scientists competence is considered as an open system of procedural, value-semantic and declarative knowledge, taking into account the interacting components (associated with cognition, personal, social), which are activated and enriched in activity as real vital problems arise that the bearer of competence faces. In this sense, in [11], the autor  notes that competence is a set of interrelated personality traits (knowledge, abilities, skills, means of activity), which are set relative to a certain range of objects and processes, as well as necessary for effective productive activity.

However, the development of a rational and effective set of competencies for employees of the enterprise in accordance with the structure of knowledge that they received during their professional activities based on the model of an “effective consultant” of the company remains outside the field of vision of most scientists on personnel management..

3. Methodology

3.1. Studies of the structural characteristics of knowledge as an economic category

All the arguments that are accepted and form the human worldview are not uniquely determined by the data of experience, but depend on the choice of the conceptual apparatus with which they can be interpreted. At the same time, choosing one or another conceptual apparatus, one can change the entire worldview. The main thesis of traditional conventionalism, of which, for example, A. Poincaré is a representative, is that there are problems that cannot be solved based on experience until some conventions (concepts) are introduced, and only then these conventions together with experience data allow you to solve the problem. Therefore, before proceeding to highlight the objectives of the article, it is appropriate to provide an understanding of the basic concepts.

In the scientific literature, you can find many approaches to the problem of the relationship between the concepts of “information” and “knowledge”. Some scientists identify these concepts, consider them interchangeable. So, for example, the concept of “information” [12] as a set of knowledge, images, feelings available in the mind of a person or artificial intelligence, coming through various transmission channels, are processed and used in the process of human life and the operation of automatic computer systems, and the concept of “knowledge” [13]: information available in the mind of a person serves to solve intellectual and speech problems, is used in everyday cognitive and speech activities, predetermines human behavior.

In  [14], scientists notes that knowledge today is information that has practical value: arise from the need to achieve effectiveness. If knowledge isn’t challenged to grow, it disappears fast.

In [15], the authors call knowledge the information contained in the human mind and is used to make decisions in a situation of uncertainty. In the sense of this study, as in cognitive psychology, the concepts of “information” and “knowledge” are clearly differentiated: knowledge is formed from information by means of its transformation and transformation, knowledge is an ordered accumulation of information. Based on this, objectivity is inherent in information, and knowledge is influenced by individual or social subjectivity.

In [16], the author described that sensory knowledge (information) is somewhat changeable, single, and knowledge is constant, stable, general, knowledge is nothing without understanding. The conditional structure of human knowledge can be depicted as a chain (fig. 1).

Figure 1: Conditional structure of knowledge

Data is a collection of facts, numbers (for example, measurements), in general, it is raw information. After processing the content data, information is obtained through analysis. As a result, of the synthesis of information, more complex structures are formed based on models describing an object or process, and knowledge arises. People, groups of people collect, process information and form knowledge. Knowledge is the result of a person’s mental activity, his professional experience gained as a result of practical activity, or, in other words, information becomes knowledge when it is realized by a person, becomes part of her surrounding world, affects her opinion and actions. So, a specialist in a certain field is someone who is able to carry out the process of transforming data information knowledge.

Regarding the concept of “knowledge”, there are many theories about their classification, but the most common is the division into “explicit” (objective, with a clearly expressed content, which can be written down, saved, transmitted, disseminated) and “hidden” (abstract, non-formalized, most often, subjective sensory knowledge, which is based on individual experience, represent beliefs, ideas). In the scientific literature, you can find similar names: “wandering” and “attached”, formalized and non-formalized, “hard” and «soft” and others.

Based on this distribution, in [17], the author described the theory of knowledge creation (“SECI model”). He believes that the creation of knowledge is an abstract spiral process of interaction between explicit and hidden knowledge, which leads to the emergence of new knowledge. This knowledge transformation process is shown in Figure 2. The transformation of knowledge, which is carried out by a successive transition through four processes, forms a spiral, so that it increases with each new turn of the spiral both in the vertical and in the horizontal plane, embracing the new knowledge of people. Space in which the spiral located,  I. Nonaka called “Wa” (from Japanese philosophy – the space in which the created knowledge is located), and the knowledge that accumulates as a result of the model’s action is “activated” knowledge. “Wa” is divided into four types depending on sequential processes: postal (environment for socialization), conversational (for externalization), simple systemic (for combination), research (for internationalization). These types correspond to different levels of knowledge.

Figure 2: The SECI model

It should be noted that according to I. Nonaka’s theory of knowledge creation, knowledge cannot be created from nothing. To create them, you need resources – “assets” of knowledge, which are the source for creating knowledge. “Assets” are divided, according to the previously considered processes (fig. 2) and types of “Wa”, into: empirical (transmitted exclusively through the exchange of experience), conceptual (transmitted through images, symbols, language), template (laid down in practical activity based on internal rules and operating conditions of the enterprise) and systemic (formalized knowledge such as patents, copyright certificates, regulatory documents, etc.). Such distribution, according to I. Nonaka, will allow the company to take into account the “assets” of knowledge more effectively.

Nowadays, knowledge of the company (practical knowledge, experience of employees, patents, etc.) is an important and rather valuable resource or “intangible asset”. Usually, the process of preserving knowledge, one way or another, is implemented in each company, since reports, instructions, notes and other documents are created. Over the years, the number of documents only grows, then no one at all remembers about some of them and does not use them. This leads to ineffective use of the “assets” of knowledge of the enterprise [18]. In such circumstances, the company’s employees become the main resource that is able to rationally use their knowledge and apply it effectively, depending on tactical and strategic situations in the process of the company’s functioning.

3.2. Analysis of the process of transforming knowledge into an intellectual product – competence

In [19] and [20], prominent scientists noted that the employee, as human capital, was defined as the main resource that, depending on the circumstances, uses a set of his knowledge, skills and abilities to effectively manage the resources of the enterprise, and forms the competitive advantages of the company, characteristic and significant features of its products and market behavior, its know-how, image and brand. From the standpoint of the competence-based approach proposed, the employee’s set of knowledge should be considered as the competitive advantages of human capital in accordance with the formed set of key competencies.

Studies prove that in the scientific world there is no clear opinion on the concepts of “competence”. So, according to the personal approach (American School), competence is the highest level of achievement of knowledge, which is considered as a quality (characteristics, ability) of a person, ensuring success in work. Supporters of the functional approach (British School) prove, competencies are the structural components of general  competence, which are understood as the characteristics of work tasks and expected results of work. Most scientists perceive the personal aspect of the American School in addition to the functional aspect of the British School, since it provides criteria for the level of development of workers, studies positions, performance standards, professional requirements, while the American aspect studies the employee, his abilities and qualities [21]. The results of research by scientists confirm the fact that competence is the ability of a person to effectively perform a certain (in particular professional) activity, and competencies (plural of “competence”) are personal characteristics of a person that determine his behavior and affect the level of performance of a certain (in particular professional) activities.

Composite analysis of the essence of the concept of “competence” has revealed the dual nature of its substantive characteristics. In this regard, it is proposed to take the definition as the basis for the concept of “competence”, where competence is considered as an open system of knowledge, abilities and personality traits, in the process of creating company values, it provides effective productive activity, which is regulated by the professional requirements of the position and quality standards [21]. The complex of competencies of the company’s employees creates its intellectual capital, the set of qualities of which is proposed to be divided into [22]:

• -hereditary (features of the nervous system that determine the nature, inclinations of work, thinking, speech, mental inclinations and abilities);
• physical (endurance; agility);
• intellectual;
• convergent abilities (efficiency of the information processing process, first of all, the correctness and speed of finding the only possible (normative) solution in accordance with the requirements of a given situation);
• divergent abilities (creativity – originality, sensitivity to unusual details and metaphorical thinking) ability to learn; cognitive style).

The qualities of human capital are determined, they are individual and specific for each individual employee of the company, they are formed and implemented in the production process through a set of key competencies that the employee improves over time. In these conditions, employees become a strategic resource of the company, and the process of generating and transforming their knowledge will be provided with a set of key competencies in accordance with the standards, norms and rules that are formed in the company.

Using the example of a consulting company in accordance with the existing competence-based approach and taking into account the methodological foundations of the “Effective Consultant” model, the process of formation of knowledge and key competencies of consultants in the mechanism of consulting interaction is first schematically presented (fig. 3) [21].

Figure 3: The process forming the knowledge and key competencies of consultants in the mechanism of consulting interaction

At the beginning we will rank the main features of the concepts “consultant-manager”, and “consultant-expert”,, then will describe the main stages of the implementation of the algorithm of the model “effective consultant” of a consulting company, based on which it is proposed to conduct a practical assessment of the proposed competencies by the levels of performance of their professional tasks.

Figure 4: Model “Effective Consultant” of a consulting company as a component of the mechanism of internal consulting interaction

A consulting company, like any company, has a large intellectual capital (potential) to create its value, the basis of which is the concept of knowledge (value) and information management, which makes it possible to introduce intellectual products into the activities of customer enterprises and give recommendations on their development in a constant competitive struggle and self-organization of their human capital. In their activities, competence is defined as an open system of knowledge, abilities and personality traits; in the process of creating company values, it ensures effective productive activity, which is regulated by the professional requirements of the position and quality standards. The complex of competencies of the company’s employees creates its intellectual capital or potential during the communication process in the mechanism of consulting interaction [23].

In the course of the study, the main representatives of the consulting company identified the following groups of consultants as managers and experts. In terms of content, a “consultant-manager” is a specialist who is endowed with the functions of a leader in managing a business and its individual business processes based on a goal-setting system in a strategic perspective, and a “consultant-expert” is a professional in a separate business process who is endowed with qualities of synthesis and analysis, rational assessment of the situation, aimed at achieving the goals set by the manager. The consultant-specialist is the direct executor of the tasks provided by the consultant-manager [21].

In the course of its activity, the efficiency of the consulting company is associated with the accurate fulfillment of tasks, in the future, they will affect the quality, content and terms of work performed. The solution of these tasks is proposed to be carried out using methodological tools, which are implemented in the “Effective Consultant” model of a consulting company based on a competency-based approach (fig. 4) [21].

The scientific and methodological approach to the construction the model “Effective Consultant” a consulting company is presented by the author in  [21], consists of the following stages:

Stage 1 – the formation of a set of competencies for the company’s consultants by levels of human capital development.

At the first stage of the “Effective Consultant” model, we form a set of competencies according to the levels of human capital development (fig. 5), according to which competencies will be considered as an integral indicator, presented in the form of functional dependence:

К = F (SG1, SS2, BA3, BP4),                     (1)

where: SG – superficial general competences,

SS – superficial special competences,

BА – behavioral adaptive competencies,

BP – behavioral personal competencies.

The levels of human capital development of the consulting company are given in (fig. 5) [21].

Figure 5: The level of human capital development of a consulting company

Note that the basic set of competencies of a consultant, according to the first level of human capital development, which he receives after graduating from a higher educational institution, are those that are formed in accordance with the guidelines for the development of educational programs [24].

Stage 2. At the second stage of building the “Effective Consultant” model of a consulting company, a set of competencies is assessed by levels of development in accordance with their weight. To determine the degree of production and consumer novelty, the Analytic Hierarchy Process method (AHP) [17] is used. The weight of the factors according to all experts is calculated by the formula:

                                                                                                                                                     where: W_ij – weight assessment i-th competence given by the j-th expert, score;

m – number of experts;

n – number of competencies in the group.

Stage 3. At the third stage, a package of intellectual resource “Effective Consultant” of a consulting company for consultants (managers, experts and specialists) is formed, in which key competencies are selected in accordance with modern requirements.

4. Еmpirical findings

Using the example of a consulting company in Ukraine, we carried out the practical implementation of the stages of building the “Effective Consultant” model.

According to the results of data processing carried out in the process of analyzing the set of matrices for comparison of the I-level of human capital development of the consulting company “Competence of a consultant upon graduation from a higher educational institution”, the most significant competencies were identified in the groups «Superficial general competences” (0,644) and “superficial special competences (0,229). The key competencies are those that affect after receiving a diploma in the relevant specialty: skills in the use of information and communication technologies; expert knowledge in a certain area (economics, finance, accounting, reengineering, psychology, etc., the ability to generate new ideas, skills to establish interaction with partners (Table 1) [21].

Table 1: The results of the assessment of competencies for the I-level of development – “Competence upon graduation from a higher educational institution”

According to the results of processing by experts of the data carried out in the process of analyzing the set of comparison matrices of the II-level of human capital development of the consulting company «Competences that are presented to the consultant by employers in Ukraine», the most significant competencies are determined by groups «Behavioral adaptive competencies» (0,598) and “Behavioral personality competencies” (0,259). Significant are those competencies that are defined as key from the point of view of employers: knowledge of marketing technologies (customer orientation); knowledge of planning changes and developing new projects; interaction risk and conflict management skills; ability to plan and control business processes; skills of making informed decisions (tab. 2) [21].

Also, by rejecting practical tips, which are valued by employer, from theoretical and scientific knowledge, as it is hoped for the completion of  study at universities, to form the protagonist of a consulting company as which is becoming a human capital of Ukrainian company.

If we add to the proposed II-level human capital development “Competences that are presented to a consultant by employers in Ukraine” the competence of the International Standard “Guidelines for management consultancy services” in accordance with the International Framework of Competence developed under the leadership of the International Council of Management Consulting Institutions, then we get an improved III-level of development of the company’s human capital with “А set of consultant competencies in Ukraine, taking into account the International Standard ISO 20700: 2017”.

In the process of improving the set of key competencies at the III-level of human capital development, it was proved that the main ones in the structure of competencies are “Behavioral personal competencies” (0,658) and “Superficial special competencies” (0,215). Significant are the competencies that are separated by key ones taking into account the International Standard ISO 20700:2017:

• skills of risk management of interaction, including risk identification and the ability to work to minimize it;
• ability to observe ethical behavior;
• ability to define success criteria to ensure the required quality of results;
• knowledge of marketing technologies;
• ability to solve problem situations and create innovative solutions for customers;
• skills to form expert opinions;
• to ensure the quality of work performed (projects) and decisions, taking into account the rules and regulations of corporate culture;
• be able to effectively manage their own time to complete tasks on time;
• ability to deepen knowledge and improve skills, based on the experience of their own and other past project tasks;
• skills to analyze the market of consulting services, its competitors and identify the capabilities of a consulting company.

Table 2: The results of the assessment of competencies for the II-level of development – “Competencies that are presented to the consultant by employers in Ukraine”

However, it is desirable to confirm the above key competencies with a certificate of at least one year of counseling experience. The results of the expert assessment on the third level of human capital development of the company “Improved set of competencies of a consultant in Ukraine, taking into account the International Standard ISO 20700:2017” Guidelines for management consulting services” in their importance are presented in Table 3 [21].

Table 3: The results of the assessment of competencies for III-level “An improved set of competencies for a consultant in Ukraine, taking into account the International Standard ISO 20700:2017”

The calculations carried out by a group of experts in the second stage to assess the set of competencies of the company’s consultants by levels of development according to their importance allow ranking the competencies of human consulting company, which form the basis for building the package (Table 4) [20].

Table 4: Ranking of competencies by groups and levels of development human capital consulting company

Based on the results of the assessment of competencies, it was found that the competencies defined by employers, combined with theoretical and scientific knowledge, which are provided after completion of training at the university, form an employee of a consulting company, who has already become the company’s human capital.

If we add to this level some competencies of the International Standard ISO 20700: 2017 «Guidelines for management consultancy services» according to the International Framework of Competence, developed under the leadership of the International Council of Management Consulting Institutions, we get an improved set of competencies for consultants of a consulting company.

According to the results of the competence assessment, high importance is given to “Behavioral personal competencies” (0,658), which the consultant develops in the process of accumulation of professional skills and self-development on the basis of “Superficial special competencies” (0,215) and “Superficial general competencies” (0,031). In modern conditions, the Behavioral adaptive competencies group does not significantly influence the development of the company’s consultants, modern gadgets and information platforms help them to adapt, etc.

Nevertheless, the main asset of the “Effective Consultant” model is the construction of the “Effective Consultant” intellectual resource package based on the results of the competence assessment for each individual group of consultants according to their key features (Table 5) [21].

The joint competencies of the consultants of the consulting company are as follows [20]:

• basic general knowledge (higher education for I-, II- and III-levels) (BP1);
• certificate confirming less than one year of experience in consulting management (SS2);
• knowledge of analysis and synthesis (SG2);
• application of knowledge and tools to create value for the client (SG3);
• ability to work with the regulatory framework (BP6);
• ability to deepen knowledge and improve skills based on the experience of one’s own and other past tasks (SG7);
• knowledge of corporate culture (SS12).

The proposed model “Effective Consultant” regulates the process of forming a universal set of key competencies according to the levels of human capital development for a consultant-manager, consultant-expert and consultant-specialist in accordance with the demand by external or internal circumstances. The process of assessing competencies at structural levels has an innovative content that will certainly affect the quality of the company’s consulting services. Under such conditions, the formation in the process of consulting interaction will ensure a balance between the performance and organizational efficiency of resources. Formed package of intellectual resource “effective consultant” is not universal. Over time, knowledge and information change, providing for a revision of the company’s potential management system and its human capital management system. A decrease in the growth rate of labor productivity of employees of a consulting company at all levels of management will certainly affect the rate of profit growth. It is advisable to annually conduct expert research to revise the package of intellectual resource “Effective Consultant” and form such a set of key competencies, which is in demand by the time, existing and potential clients [20].

Table 5: A set of key competencies for the skin group and consultants at the border of the package “Intellectual resource”

To continuously improve their existing competencies and acquire new knowledge, consultants must distribute their stock, generate new knowledge, take courses to improve professional skills and engage in their own training during the implementation of consulting projects. Moreover, the knowledge transfer process, taking into account the key competencies of consultants, will take place in accordance with the consulting service standard created by the owners of the consulting company itself or proposed for use at the level of a regulatory and legislative act.

5. Conclusions

Based on the consideration of the above, we can conclude that the personnel management of the company today is expanding its economic content and acquires a new meaning as capital. The modern process of human capital management is aimed at its effective use and development. In these circumstances, the owner has the opportunity to maximize the return on the skills, knowledge of the worker, and the worker – to receive the maximum level of material and psychological satisfaction from his work. Then the goal of management acquires strategic development in two directions.

The first should provide for a high degree of competitiveness of the enterprise, flexibility of forms and methods of human capital management, intensification of labor of highly qualified workers and participation of workers in the distribution of profits. The second direction should include ensuring responsibility for the creation of competitive advantages of the enterprise by the employees themselves, and their participation in the affairs of the enterprise is achieved through such factors as effective organizational communication, high motivation and flexible leadership. However, in both the first and second directions, the role of human capital in the process of consulting interaction, accompanied by the value chain, is endless. The human capital of a consulting company is not just its main intellectual resource, its potential, in contrast to other resources, is formed through the renewal of intellectual knowledge and information. In these conditions, human capital becomes the source of the company’s values, which over time are recognized as competitive advantages for a reasonable desire to transform resources into capital.

The article presents a scientific and methodological approach to building the model “Effective Consultant”. The methodological basis for assessing competencies according to the “Effective Consultant” model has an innovative content. The proposed model regulates the process of forming a universal set of key competencies according to the levels of human capital development for a consultant-manager, consultant-expert and consultant-specialist. The Effective Consultant model takes into account a set of competencies in accordance with the demand from external or internal factors. In the course of the research, it was found that the weighty groups defined “Behavioral personal competencies» and “Superficial special competencies”.

The “Effective Consultant” model has been tested and implemented in the activities of consulting companies in Ukraine, which allows to be recommended for widespread use by any consulting company in the world. Human resources and academic departments of the company can use the “Effective Consultant” profile of consultants as a tool for managing business processes. Consultants can use the recommendations as part of a scientific and methodological approach to building the model “Effective Consultant” as a source of personal growth. It is proposed to evaluate consultants periodically so that the dynamics of the development of their competencies can be tracked.

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5. Faraz Farhidi, Yahia Baghzouz, Maxim Rusakov, "Cooperative Game Theory for Grid Service Pricing: A Utility-Centric Approach", Advances in Science, Technology and Engineering Systems Journal, vol. 10, no. 3, pp. 21–28, 2025. doi: 10.25046/aj100304
6. Ya Gao, Fatma Layas, Xiangyu Dong, Yijing Li, Jiayi Li, "A Study of the Digital Health Management Needs of the Elderly", Advances in Science, Technology and Engineering Systems Journal, vol. 10, no. 2, pp. 42–48, 2025. doi: 10.25046/aj100205
7. Maikel Leon, "Generative Artificial Intelligence and Prompt Engineering: A Comprehensive Guide to Models, Methods, and Best Practices", Advances in Science, Technology and Engineering Systems Journal, vol. 10, no. 2, pp. 01–11, 2025. doi: 10.25046/aj100201
8. Tamao Kobayashi, Koichi Murata, "Development and Application of Value Karuta to Understand Value in Lean Management: Initial Small-group Trial in Japan and the UK", Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 6, pp. 21–29, 2024. doi: 10.25046/aj090603
9. Diego Costa, Gabriel Matos, Anderson Lins, Leon Barroso, Carlos Aguiar, Erick Bezerra, "Web Application Interface Data Collector for Issue Reporting", Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 5, pp. 01–08, 2024. doi: 10.25046/aj090501
10. Declan Mallamo, Michael Azarian, Michael Pecht, "Early Detection of SMPS Electromagnetic Interference Failures Using Fuzzy Multi-Task Functional Fusion Prediction", Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 4, pp. 35–50, 2024. doi: 10.25046/aj090405
11. Brandon Wetzel, Haiping Xu, "Deploying Trusted and Immutable Predictive Models on a Public Blockchain Network", Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 3, pp. 72–83, 2024. doi: 10.25046/aj090307
12. Pegah Yazdkhasti, Julian Luciano Cárdenas–Barrera, Chris Diduch, "Smart Agent-Based Direct Load Control of Air Conditioner Populations in Demand Side Management", Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 1, pp. 114–123, 2024. doi: 10.25046/aj090111
13. Wordh Ul Hasan, Kimia Tuz Zaman, Shadi Alian, Tianyi Liang, Vikram Pandey, Jun Kong, Cui Tao, Juan Li, "Bridging Culture and Care: A Mobile App for Diabetes Self-Care Honoring Native American Cultural Practices", Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 1, pp. 104–113, 2024. doi: 10.25046/aj090110
14. Fazalur Rehman, Safwan Hashmi, "Enhancing Cloud Security: A Comprehensive Framework for Real-Time Detection, Analysis and Cyber Threat Intelligence Sharing", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 6, pp. 107–119, 2023. doi: 10.25046/aj080612
15. John Tsiligaridis, "Tree-Based Ensemble Models, Algorithms and Performance Measures for Classification", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 6, pp. 19–25, 2023. doi: 10.25046/aj080603
16. Mauricio Flores-Nicolás, Magally Martínez-Reyes, Felipe de Jesús Matías-Torres, "The Graded Multidisciplinary Model: Fostering Instructional Design for Activity Development in STEM/STEAM Education", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 5, pp. 55–61, 2023. doi: 10.25046/aj080506
17. Eilin Gómez Mesino, Joaquín Caicedo, Miguel Mamaní, David Romero Quete, Andrés Cerón Piamba, Diego García Gómez, Guillermo Aponte Mayor, José Caicedo Erazo, Wilmar Moreno López, Edward Jay, Andrés Romero Quete, "Condition Assessment of Medium Voltage Assets: A Review", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 5, pp. 35–54, 2023. doi: 10.25046/aj080505
18. Yangshichi, Hayoung Oh, HyunJong Kim, "The Influence Analysis of Internet Finance on China’s Banking Industry Development", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 3, pp. 250–261, 2023. doi: 10.25046/aj080328
19. Hermagasantos Zein, Ahmad Deni Mulyadi, Achmad Mudawari, "Minimum Static VAR Compensation Capacity for Bad Voltage Drop Buses in Power Systems", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 3, pp. 212–217, 2023. doi: 10.25046/aj080324
20. Mohammadali Hayerikhiyavi, Aleksandar Dimitrovski, "Three-phase Continuously Variable Series Reactor – Realistic Modeling and Analysis", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 3, pp. 202–211, 2023. doi: 10.25046/aj080323
21. Evgeniy Kostyrin, Evgeniy Sokolov, "Social Financial Technologies for the Development of Enterprises and the Russian Economy", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 3, pp. 118–135, 2023. doi: 10.25046/aj080314
22. Jin Uk Yeon, Ji Whan Noh, Innyeal Oh, "Temperature-Compensated Overcharge Protection Measurement Technology", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 2, pp. 24–29, 2023. doi: 10.25046/aj080203
23. Zhanna Dedovets, Mikhail Rodionov, Anna Novichkova, "A Model for Teaching Mathematics to Gifted Students Based on an Effective Combination of Various Approaches for their Preparation", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 1, pp. 138–148, 2023. doi: 10.25046/aj080117
24. Ossama Embarak, "Multi-Layered Machine Learning Model For Mining Learners Academic Performance", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 850–861, 2021. doi: 10.25046/aj060194
25. Richard Romero Izurieta, Segundo Moisés Toapanta Toapanta, Luis Jhony Caucha Morales, María Mercedes Baño Hifóng, Eriannys Zharayth Gómez Díaz, Oscar Marcelo Zambrano Vizuete, Luis Enrique Mafla Gallegos, José Antonio Orizaga Trejo, "Prototype to Identify the Capacity in Cybersecurity Management for a Public Organization", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 1, pp. 108–115, 2023. doi: 10.25046/aj080113
26. Sathyabama Kaliyapillai, Saruladha Krishnamurthy, Thiagarajan Murugasamy, "An Ensemble of Voting- based Deep Learning Models with Regularization Functions for Sleep Stage Classification", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 1, pp. 84–94, 2023. doi: 10.25046/aj080110
27. Clemens Gnauer, Andrea Prochazka, Elke Szalai, Sebastian Chlup, Anton Fraunschiel, "Technical Aspects and Social Science Expertise to Support Safe and Secure Handling of Autonomous Railway Systems", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 283–294, 2022. doi: 10.25046/aj070632
28. Mikhail Lavrentiev, Andrey Marchuk, Konstantin Oblaukhov, Mikhail Shadrin, "Natural Tsunami Wave Amplitude Reduction by Straits – Seto Inland Sea", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 161–166, 2022. doi: 10.25046/aj070616
29. Fabrizio Striani, Chiara Colucci, Angelo Corallo, Roberto Paiano, Claudio Pascarelli, "Process Mining in Healthcare: A Systematic Literature Review and A Case Study", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 151–160, 2022. doi: 10.25046/aj070615
30. Segundo Moisés Toapanta Toapanta, Rodrigo Humberto Del Pozo Durango, Luis Enrique Mafla Gallegos, Eriannys Zharayth Gómez Díaz, Yngrid Josefina Melo Quintana, Joan Noheli Miranda Jimenez, Ma. Roció Maciel Arellano, José Antonio Orizaga Trejo, "Prototype to Mitigate the Risks, Vulnerabilities and Threats of Information to Ensure Data Integrity", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 139–150, 2022. doi: 10.25046/aj070614
31. Faris Abdullah Almalki, Asrar Mohammed Mutawi, Ibtihal Abduljalil Turkistani, Lujain Khalaf Alqurashi, Maha Talat Fattah, Malak Tammam Almogher, Reem Shaman Aldaher, Ruzan Ahmed Wali, Wafa Muidh Almalki, Yusra Muhamed Almubayed, "Developing CubeSat and AI Framework for Crowd Management Case of Short-Term Large-Scale Events", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 114–125, 2022. doi: 10.25046/aj070612
32. Jhoys Alinson Delgado Delgado, José Sulla-Torres, "Redesign and Improvement in the Management of the Raw Material Inventory Control Process with Oracle APEX", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 103–113, 2022. doi: 10.25046/aj070611
33. Gianvito Mitrano, Antonio Caforio, Tobia Calogiuri, Chiara Colucci, Luca Mainetti, Roberto Paiano, Claudio Pascarelli, "A Cloud Telemedicine Platform Based on Workflow Management System: A Review of an Italian Case Study", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 87–102, 2022. doi: 10.25046/aj070610
34. Nan Noon Noon, Janusz R. Getta, Tianbing Xia, "Optimization of Query Processing on Multi-tiered Persistent Storage", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 20–30, 2022. doi: 10.25046/aj070603
35. Angela Pearce, "The Perceptions of Students and Teachers When using ICTs for Educational Practices Matter: A Systematic Review", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 1–12, 2022. doi: 10.25046/aj070601
36. Ferdinand Friedrich, Christoph Ament, "Model Order Reduction and Distribution for Efficient State Estimation in Sensor and Actuator Networks", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 5, pp. 146–156, 2022. doi: 10.25046/aj070516
37. Jabrane Slimani, Abdeslam Kadrani, Imad EL Harraki, El hadj Ezzahid, "Long-term Bottom-up Modeling of Renewable Energy Development in Morocco", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 5, pp. 129–145, 2022. doi: 10.25046/aj070515
38. Javier Calle, Itziar Sagastiberri, Mikel Aramburu, Santiago Cerezo, Jorge García, "Automatic Counting Passenger System using Online Visual Appearance Multi-Object Tracking", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 5, pp. 113–128, 2022. doi: 10.25046/aj070514
39. Bouassale Nasr-Eddine, Sallaou Mohamed, Aittaleb Abdelmajid, Benaissa Elfahim, "DEM models Calibration and Application to Simulate the Phosphate Ore Clogging", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 5, pp. 79–90, 2022. doi: 10.25046/aj070511
40. Kelebaone Tsamaase, Japhet Sakala, Kagiso Motshidisi, Edward Rakgati, Ishmael Zibani, Edwin Matlotse, "Performance Adjustment Factor for Fixed Solar PV Module", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 4, pp. 98–104, 2022. doi: 10.25046/aj070413
41. Zhumakhan Nazir, Temirlan Zarymkanov, Jurn-Guy Park, "A Machine Learning Model Selection Considering Tradeoffs between Accuracy and Interpretability", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 4, pp. 72–78, 2022. doi: 10.25046/aj070410
42. Ming Fong Sie, Jingze Wu, Seth Austin Harding, Chien-Lung Lin, San-Tai Wang, Shih-wei Liao, "Secured Multi-Layer Blockchain Framework for IoT Aggregate Verification", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 3, pp. 106–115, 2022. doi: 10.25046/aj070312
43. Lu Xiong, Spendylove Duncan-Williams, "Generalized Linear Model for Predicting the Credit Card Default Payment Risk", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 3, pp. 51–61, 2022. doi: 10.25046/aj070306
44. Aicha Lamjahdi, Hafida Bouloiz, Maryam Gallab, "Heuristic Analysis of Overall Performance Measurement Perception and Management in Automotive Industry", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 3, pp. 1–11, 2022. doi: 10.25046/aj070301
45. Inam Abousaber, "Digital Competencies of Saudi University Graduates Towards Digital Society: The Case of The University of Tabuk", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 2, pp. 171–178, 2022. doi: 10.25046/aj070217
46. Haruka Motohashi, Hayato Ohwada, "Interpretable Rules Using Inductive Logic Programming Explaining Machine Learning Models: Case Study of Subclinical Mastitis Detection for Dairy Cows", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 2, pp. 143–148, 2022. doi: 10.25046/aj070214
47. Nils Finke, Ralf Möller, "On the Construction of Symmetries and Retaining Lifted Representations in Dynamic Probabilistic Relational Models", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 2, pp. 73–93, 2022. doi: 10.25046/aj070207
48. Rachida Hassani, Younès El Bouzekri El Idrissi, "IT Project Management Models in an Era of Digital Transformation: A Study by Practice", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 2, pp. 53–62, 2022. doi: 10.25046/aj070205
49. Othmani Mohammed, Lamchich My Tahar, Lachguar Nora, "Power Management and Control of a Grid-Connected PV/Battery Hybrid Renewable Energy System", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 2, pp. 32–52, 2022. doi: 10.25046/aj070204
50. Alexander Núñez, Fernando Solares, Alejandro Crisanto, "Estimation of Non-homogeneous Thermal Conductivity using Fourier Heat Equation Considering Uncertainty and Error Propagation", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 1, pp. 90–99, 2022. doi: 10.25046/aj070109
51. Nganyang Paul Bayendang, Mohamed Tariq Khan, Vipin Balyan, "Thermoelectric Generators (TEGs) and Thermoelectric Coolers (TECs) Modeling and Optimal Operation Points Investigation", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 1, pp. 60–78, 2022. doi: 10.25046/aj070107
52. Lucie Böhmová, Antonín Pavlíček, "Innovations in Recruitment—Social Media", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 6, pp. 88–97, 2021. doi: 10.25046/aj060613
53. Sarina Abdul Halim-Lim, Nurul Najihah Azalanzazllay, Anjar Priyono, Guven Gurkan Inan, Muhammad Iqbal Hussain, "Lean Six Sigma Implementation in the Food Sector: Nexus between Readiness-Critical Success Factors", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 6, pp. 12–21, 2021. doi: 10.25046/aj060603
54. Toshiki Watanabe, Hiroyuki Kameda, "Designing a Model of Consciousness Based on the Findings of Jungian Psychology", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 5, pp. 356–361, 2021. doi: 10.25046/aj060540
55. Caglar Arslan, Selen Sipahio?lu, Emre ?afak, Mesut Gözütok, Tacettin Köprülü, "Comparative Analysis and Modern Applications of PoW, PoS, PPoS Blockchain Consensus Mechanisms and New Distributed Ledger Technologies", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 5, pp. 279–290, 2021. doi: 10.25046/aj060531
56. Ibnu Daqiqil Id, Masanobu Abe, Sunao Hara, "Acoustic Scene Classifier Based on Gaussian Mixture Model in the Concept Drift Situation", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 5, pp. 167–176, 2021. doi: 10.25046/aj060519
57. Rim Mrani Alaoui, Abderrahim El-Amrani, Ismail Boumhidi, "Model Reduction H? Finite Frequency of Takagi-Sugeno Fuzzy Systems", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 5, pp. 53–58, 2021. doi: 10.25046/aj060507
58. Chia-En Yang, Yang-Ting Shen, Shih-Hao Liao, "SyncBIM: The Decision-Making BIM-Based Cloud Platform with Real-time Facial Recognition and Data Visualization", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 5, pp. 16–22, 2021. doi: 10.25046/aj060503
59. Olena Nosovets, Vitalii Babenko, Ilya Davydovych, Olena Petrunina, Olga Averianova, Le Dai Zyonh, "Personalized Clinical Treatment Selection Using Genetic Algorithm and Analytic Hierarchy Process", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 406–413, 2021. doi: 10.25046/aj060446
60. Zhiyuan Chen, Howe Seng Goh, Kai Ling Sin, Kelly Lim, Nicole Ka Hei Chung, Xin Yu Liew, "Automated Agriculture Commodity Price Prediction System with Machine Learning Techniques", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 376–384, 2021. doi: 10.25046/aj060442
61. Anas Laassiri, Abdelfettah Sedqui, "Segmentation of Stocks: Dynamic Dimensioning and Space Allocation, using an Algorithm based on Consumption Policy, Case Study", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 306–319, 2021. doi: 10.25046/aj060434
62. Jorge Joo-Nagata, Fernando Martínez-Abad, "Evaluation of Information Competencies in the School Setting in Santiago de Chile", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 298–305, 2021. doi: 10.25046/aj060433
63. Ahmed R. Sadik, Christian Goerick, "Multi-Robot System Architecture Design in SysML and BPMN", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 176–183, 2021. doi: 10.25046/aj060421
64. Montaño-Arango Oscar, Ortega-Reyes Antonio Oswaldo, Corona-Armenta José Ramón, Rivera-Gómez Héctor, Martínez-Muñoz Enrique, Robles-Acosta Carlos, "Multidisciplinary Systemic Methodology, for the Development of Middle-sized Cities. Case: Metropolitan Zone of Pachuca, Mexico", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 80–90, 2021. doi: 10.25046/aj060410
65. Kwun-Ping Lai, Jackie Chun-Sing Ho, Wai Lam, "Exploiting Domain-Aware Aspect Similarity for Multi-Source Cross-Domain Sentiment Classification", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 01–12, 2021. doi: 10.25046/aj060401
66. Mark Gourary, Sergey Rusakov, "Technique to Simulate an Oscillator Ensemble Represented by the Kuramoto Model", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 3, pp. 311–318, 2021. doi: 10.25046/aj060335
67. Nganyang Paul Bayendang, Mohamed Tariq Kahn, Vipin Balyan, "Power Converters and EMS for Fuel Cells CCHP Applications: A Structural and Extended Review", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 3, pp. 54–83, 2021. doi: 10.25046/aj060308
68. Svetlana Segarceanu, George Suciu, Inge Gavăt, "Environmental Acoustics Modelling Techniques for Forest Monitoring", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 3, pp. 15–26, 2021. doi: 10.25046/aj060303
69. Marlene Ofelia Sanchez-Escobar, Julieta Noguez, Jose Martin Molina-Espinosa, Rafael Lozano-Espinosa, "Supporting the Management of Predictive Analytics Projects in a Decision-Making Center using Process Mining", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 1084–1090, 2021. doi: 10.25046/aj0602123
70. Nhlanhla Nkosi, Edison Muzenda, Mohamed Belaid, Corina Mateescu, "A Critical Analysis of the Integrated Industry Waste Tyre Management Plan of South Africa", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 1046–1054, 2021. doi: 10.25046/aj0602119
71. Mamudu Hamidu, Jerry John Kponyo, "Closed Loop Capacitive Accelerometer Model using Simple Regression Test for Linearity", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 1038–1045, 2021. doi: 10.25046/aj0602118
72. Trust Nhubu, Edison Muzenda, Belaid Mohamed, Charles Mbohwa, "Framework for Decentralizing Municipal Solid Waste Management in Harare, Zimbabwe", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 1029–1037, 2021. doi: 10.25046/aj0602117
73. Zvanaka S. Mazhandu, Edison Muzenda, Mohamed Belaid, Tirivaviri A. Mamvura, Trust Nhubu, "A Review of Plastic Waste Management Practices: What Can South Africa Learn?", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 1013–1028, 2021. doi: 10.25046/aj0602116
74. Trust Nhubu, Edison Muzenda, Belaid Mohamed, Charles Mbohwa, "Assessment of the Municipal Solid Waste Transfer Stations Suitability in Harare, Zimbabwe", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 1002–1012, 2021. doi: 10.25046/aj0602115
75. Md. Tarequl Islam, Mostofa Kamal Nasir, Md. Mahedi Hasan, Mohammad Gazi Golam Faruque, Md. Selim Hossain, Mir Mohammad Azad, "Blockchain-Based Decentralized Digital Self-Sovereign Identity Wallet for Secure Transaction", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 977–983, 2021. doi: 10.25046/aj0602112
76. Mochammad Haldi Widianto, Ari Purno Wahyu, Dadan Gusna, "Prototype Design Internet of Things Based Waste Management Using Image Processing", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 709–715, 2021. doi: 10.25046/aj060282
77. Antoni Wibowo, Inten Yasmina, Antoni Wibowo, "Food Price Prediction Using Time Series Linear Ridge Regression with The Best Damping Factor", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 694–698, 2021. doi: 10.25046/aj060280
78. Yu-Chun Huang, "Analyze Performance of Enterprise Supervision System by Game Theory-Take the case of Tatung Management Rights Competition as Example", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 689–693, 2021. doi: 10.25046/aj060279
79. Marion Olubunmi Adebiyi, Oludayo Olufolorunsho Olugbara, "Homology Modeling of CYP6Z3 Protein of Anopheles Mosquito", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 580–585, 2021. doi: 10.25046/aj060266
80. Pritesh Shah, Ravi Sekhar, Iswanto Iswanto, Margi Shah, "Complex Order PI\(^{a+jb}\)D\(^{c+jd}\) Controller Design for a Fractional Order DC Motor System", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 541–551, 2021. doi: 10.25046/aj060261
81. Phillip Blunt, Bertram Haskins, "A Model for the Application of Automatic Speech Recognition for Generating Lesson Summaries", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 526–540, 2021. doi: 10.25046/aj060260
82. Abdulla M. Alsharhan, "Survey of Agent-Based Simulations for Modelling COVID-19 Pandemic", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 439–447, 2021. doi: 10.25046/aj060250
83. Amany Khalil, Osama Tolba, Sherif Ezzeldin, "Design Optimization of Open Office Building Form for Thermal Energy Performance using Genetic Algorithm", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 254–261, 2021. doi: 10.25046/aj060228
84. Mohab Gaber, Sayed El-Banna, Mahmoud El-Dabah, Mostafa Hamad, "Designing and Implementation of an Intelligent Energy Management System for Electric Ship power system based on Adaptive Neuro-Fuzzy Inference System (ANFIS)", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 195–203, 2021. doi: 10.25046/aj060223
85. Amine Mounaam, Ridouane Oulhiq, Ahmed Souissi, Mohamed Salouhi, Khalid Benjelloun, Ahmed Bichri, "A Model-Driven Digital Twin Framework Development for Sulfur Dioxide Conversion Units Simulation", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 122–131, 2021. doi: 10.25046/aj060215
86. Zarina Din, Dian Indrayani Jambari, Maryati Mohd Yusof, Jamaiah Yahaya, "Challenges in IoT Technology Adoption into Information System Security Management of Smart Cities: A Review", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 99–112, 2021. doi: 10.25046/aj060213
87. Yousra Karim, Abdelghani Cherkaoui, "Fuzzy Analytical Hierarchy Process and Fuzzy Comprehensive Evaluation Method Applied to Assess and Improve Human and Organizational Factors Maturity in Mining Industry", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 75–84, 2021. doi: 10.25046/aj060210
88. Futra Zamsyah Md Fadzil, Alireza Mousavi, Morad Danishvar, "Event Modeller Data Analytic for Harmonic Failures", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 1343–1359, 2021. doi: 10.25046/aj0601154
89. Naeem Ahmed Haq Nawaz, Musab Bassam Al-Zghoul, Hamid Raza Malik, Omar Radhi Aqeel Al-Zabi, Bilal Radi Ageel Al-Zabi, "Wireless Sensor Networks Simulation Model to Compute Verification Time in Terms of Groups for Massive Crowd", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 1229–1240, 2021. doi: 10.25046/aj0601140
90. Thinh Dang Cong, Toi Le Thanh, Phuc Ton That Bao, Trang Hoang, "A Novel Approach to Design a Process Design Kit Digital for CMOS 180nm Technology", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 1191–1198, 2021. doi: 10.25046/aj0601135
91. Saruntorn Mongkolchaichana, Busaba Phruksaphanrat, "Prioritization of Sustainable Supply Chain Management Practices in an Automotive Elastomer Manufacturer in Thailand", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 1079–1090, 2021. doi: 10.25046/aj0601120
92. Laurent Nana, François Monin, Sophie Gire, "Formal Proof of Properties of a Syntax-Oriented Editor of Robotic Missions Plans", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 1049–1057, 2021. doi: 10.25046/aj0601116
93. Shahrinaz Ismail, Faes Tumin, "Simulating Get-Understand-Share-Connect Model using Process Mining", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 1040–1048, 2021. doi: 10.25046/aj0601115
94. Abdulla Alsharhan, Said Salloum, Khaled Shaalan, "The Impact of eLearning as a Knowledge Management Tool in Organizational Performance", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 928–936, 2021. doi: 10.25046/aj0601102
95. Syeda Nadiah Fatima Nahri, Shengzhi Du, Barend Jacobus van Wyk, "Active Disturbance Rejection Control Design for a Haptic Machine Interface Platform", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 898–911, 2021. doi: 10.25046/aj060199
96. Carlos Juventino Ruiz Montoya, José Luis Martínez Flores, "Contingency Plan in the Supply Chain of Companies in the Retail Industry in the Face of the Impacts of COVID-19", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 819–832, 2021. doi: 10.25046/aj060191
97. Sana Elhidaoui, Khalid Benhida, Said Elfezazi, Yassine Azougagh, Abdellatif Benabdelhafid, "Model of Fish Cannery Supply Chain Integrating Environmental Constraints (AHP and TOPSIS)", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 798–809, 2021. doi: 10.25046/aj060189
98. Abdulla M. Alsharhan, "Simulating COVID-19 Trajectory in the UAE and the Impact of Possible Intervention Scenarios", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 791–797, 2021. doi: 10.25046/aj060188
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