Process Execution Research Articles

Analysis of Aliyun-based serverless on MapReduce efficiency

In the context of the current era of big data, traditional Hadoop and cluster-based MapReduce frameworks are unable to meet the demands of modern research. This paper presents a MapReduce framework based on the AliCloud Serverless platform, which has been developed with the objective of optimizing word frequency counting in large-scale English texts. Leveraging AliCloud's dynamic resource allocation and elastic scaling, we have created an efficient and flexible text data processing system. This paper details the design and implementation of the Map and Reduce phases and analyses the impact of vCPU and memory specifications, as well as parallel resource allocation on system performance. Experimental results show that increasing vCPU specifications significantly improves processing capacity and execution efficiency. While the impact of memory specifications is relatively minor, it can positively influence performance in specific scenarios. Parallel processing markedly enhances system performance. Experiments on "Harry Potter and the Sorcerer's Stone" validate the framework's performance across various configurations. This study offers valuable insights for the design and optimization of serverless-based MapReduce frameworks, as well as suggesting future enhancements. These include the implementation of advanced parallel computing strategies, improved error handling, and refined data preprocessing, which collectively aim to boost system performance and stability.

ОСОБЕННОСТИ ПРАВОВОГО ОБЕСПЕЧЕНИЯ ДЕЯТЕЛЬНОСТИ УЧРЕЖДЕНИЙ УГОЛОВНО-ИСПОЛНИТЕЛЬНОЙ СИСТЕМЫ РЕСПУБЛИКИ БЕЛАРУСЬ ПРИ ЧРЕЗВЫЧАЙНЫХ СИТУАЦИЯХ

The article examines the problems of legal regulation of the activities of the institution of the penal system in the event of emergency situations of an anthropogenic, technological and natural nature affecting the process of execution of punishment. Topical proposals have been formulated to improve Article 76 of the Penal Code of the Republic of Belarus, which regulates relations arising from the introduction of a special status regime in a correctional institution.382

تأثير تطبيق منهجية المشاريع الرشيقة "أجايل" على جودة الأداء والمدة الزمنية لمشروع نيوم

This study explores the impact of applying Agile methodology on performance quality and project duration within the NEOM project, which represents one of the largest and most complex projects in Saudi Arabia. The study analyzes the effect of Agile implementation based on data collected through surveys and interviews with a diverse group of project stakeholders. The study was divided into several phases, starting with understanding how Agile methodology was applied in the project and assessing participant satisfaction with the methodology. Analysis of the data revealed that Agile implementation led to significant improvements in performance quality. There was a noticeable reduction in errors and a decrease in the need for ongoing adjustments, which positively impacted customer satisfaction and increased alignment with technical specifications. In terms of project duration, the results showed that Agile methodology contributed to accelerating execution processes and reducing the time required to complete tasks. Flexibility and responsiveness to changes improved significantly, leading to progress within the set timelines. This improvement was supported by incremental delivery and continuous improvement that are hallmarks of Agile methodology. The study also highlighted that successful Agile implementation requires strong support from senior management, adequate resource provision, and sufficient team training. Additionally, the results emphasized the importance of cross-team collaboration and effective communication in achieving shared goals. Based on these findings, the study offers recommendations for enhancing Agile application in similar projects.

Implication of condemnatoir verdict in the case of child custody rights in the legal way of The Denpasar Agency (Case study of case No. 358/PDT. G/2023/PA. DPS)

This study aims to find out the implications of condemnatoir decisions in child custody cases in the jurisdiction of the Denpasar Religious Court, and the obstacles faced in the implementation of the execution of child custody decisions in this jurisdiction. The study employs both normative and empirical approaches, focusing on the norm vacuum regarding the enforcement of Hadhanah (child custody) decisions. The data analysis involves a legal analysis of the normative sources to interpret and evaluate the current laws, complemented by qualitative analysis of empirical data to identify patterns, issues, and challenges in the execution process. The research offers valuable insights into the practical difficulties of enforcing child custody rulings, which could inform legal reforms or improvements in the judicial process to better protect the interests of the child and ensure compliance with judicial decisions.

Trust Computation Model for IoT devices using Soft Computing and Machine Learning Techniques for Health Care Applications

The calculation of trust for online web services is of utmost importance due to the security risks associated with network devices. various cloud platforms offer diverse services for communicating with various IoT devices and generating predictions based on the collected data. Occasionally, data may be compromised by either internal or external groups through low-impact hacking techniques. Investigating assaults and ensuring the elimination of connections can be a laborious task in a sensitive setting. Despite some progress, there are still many unresolved security issues that provide barriers to addressing security problems. This article seeks to conduct a comprehensive examination of existing security solutions for the lowest layer of the Internet of Things (IoT) and promote the development of more inventive IoT designs for those who invest in them. This paper proposes a system for calculating trust in IoT devices using both supervised and unsupervised machine learning algorithms for non-invasive health care applications. Both strategies were assessed based on trust computation weights and compared with their respective machine learning algorithms. The K-means clustering technique is employed for one strategy, while the SVM algorithm is used for the other approach. The aim of this successful implementation is to identify and eradicate a minor threat that occurs during the trusted execution process. An experimental analysis was conducted using NS2 2.35 in combination with an open-source Java platform. At first, a total of 100 nodes are created in the simulation environment. These nodes are then assessed using a clustering method to determine if they are trustworthy or untrustworthy, resulting in the generation of labels. The experimental research demonstrated the superior efficacy of attack detection in comparison to traditional methods of attack detection.

Cognitive Stimulation with Music in Older Adults with Cognitive Impairment: A Scoping Review.

The use of music in cognitive interventions represents a possibility with potential worthy of further investigation in the field of aging, both in terms of prevention from dementia, in the phase of mild cognitive impairment, and in the treatment of overt dementia. Currently, the types of music-based interventions proposed in the literature are characterized by wide heterogeneity, which is why it is necessary to clarify which interventions present more evidence of effectiveness in stimulating different cognitive domains. The study was conducted in accordance with PRISMA guidelines for scoping reviews. By searching two different databases, PubMed and the Web of Science, all studies evaluating the cognitive effects of music-based interventions on people at early stages of cognitive decline (MCI or mild-to-moderate dementia) were selected. The study selection included a total of 28 studies involving n = 1612 participants (mean age ranged from 69.45 to 85.3 years old). Most of the studies analyzed agree with the observation of an improvement, or at least maintenance, of global cognitive conditions (mainly represented by the results of the MMSE test) following music-based interventions, together with a series of other positive effects on verbal fluency, memory, and executive processes. The results of this review suggest the introduction of music-based interventions as complementary approaches to usual cognitive treatments. Also, the use of standardized and well-defined protocols, in addition to strong methodological research approaches, is suggested. Music-based interventions are recommended in the early stages of dementia, in MCI, and in a preventive sense in healthy older adults.

The effects of attentional focus instructions on approach jump performance

Introduction Attentional focus has been shown to significantly influence motor learning and performance, with external focus instructions enhancing performance compared to internal focus instructions. Research has also demonstrated that novice performance is improved when instructed to focus on skill execution processes rather than outcomes. However, this effect remains untested in complex jumping skills crucial to numerous sports. Purpose This study aimed to investigate the effect of internally and externally directed process and outcome focus instructions on approach jump height and approach speed in novice participants. Methods Twelve individuals aged 18 to 22 participated across three sessions: Familiarization, Test Session 1, and Test Session 2. During the test sessions, participants executed approach jumps in various conditions, each emphasizing specific cues: External Focus-Outcome, Internal Focus-Outcome, External Focus-Process, and Internal Focus-Process. Jump-and-Reach Height, Estimated Jump Height by Flight Time, and Approach Speed were assessed through 2 × 2 repeated measures ANOVAs. Results External focus and outcome conditions led to the highest jump-and-reach height ( p < .05). Process conditions yielded faster approach speed compared to outcome conditions ( p < .001), irrespective of internal or external focus direction. Estimated jump height by flight time was similar across all conditions. Conclusions The study suggests that benefits of external focus and process instructions for novices may apply only to certain performance variables in complex motor skills. Practical Applications Practitioners can optimize novices’ performance using various process- and outcome-based instructions. External, outcome-based cues enhance overall task performance, while process-based cues may improve specific technical components.

A New Porosity Evaluation Method Based on a Statistical Methodology for Granular Material: A Case Study in Construction Sand

Sand porosity is an important compactness parameter that influences the mechanical properties of sand. In order to evaluate the temporal variation in sand porosity, a new method of sand porosity evaluation based on the statistics of target sand particles (which refers to particles within a specific particle size range) is presented. The relationship between sand porosity and the number of target sand particles at the soil surface considering observation depth is derived theoretically, and it is concluded that there is an inverse relationship between the two. Digital image processing and the k-means clustering method were used to distinguish particles in digital images where particles may mask each other, and a criterion for determining the number of particles was proposed, that is, the criterion of min(Dao). The execution process was implemented by self-written codes using Python (2021.3). An experiment on a simple case of Go pieces and sand samples of different porosities was conducted. The results show that the sum of the squared error (SSE) in the k-means method can converge with a small number of iterations. Furthermore, there is a minimum value between the parameter Dao and the set value of a single-particle pixel, and the pixel corresponding to this value is a reasonable value of a single-particle pixel, that is, the min(Dao) criterion is proposed. The k-means method combined with the min(Dao) criterion can analyze the number of particles in different particle size ranges with occlusion between particles. The test results of sand samples with different densities show that the method is reasonable.

Investigating the Origin of Epimerization Attenuation during Pd-Catalyzed Cross-Coupling Reactions.

Palladium-catalyzed cross-couplings remain among the most robust methodologies to form carbon-carbon and carbon-heteroatom bonds. In particular, carbon-nitrogen (C-N) couplings (Buchwald-Hartwig aminations) find widespread use in fine chemicals industries. The use of base in these reactions is critical for catalyst activation and proton sequestration. Base selection also plays an important role in process design, as strongly basic conditions can impact sensitive stereocenters and result in erosion of stereochemical purity. Herein we investigate the role of a Pd catalyst in suppressing base-mediated epimerization of a sultam stereocenter during a C-N cross-coupling reaction to access the RORγ inhibitor GDC-0022. Online high-performance liquid chromatography-mass spectrometry (HPLC-MS) was employed to acquire reaction time course profiles and to delineate epimerization behavior, identify decomposition pathways, and monitor Pd-containing species. Our ability to monitor organopalladium complexes in real time by HPLC-MS provided strong evidence that the degree of epimerization was correlated to the Pd speciation in solution. Specifically, Pd(II) complexes were associated with mitigating epimerization of six-membered sultams. Additional studies showed that the suppression of epimerization in the presence of Pd(II) can impact Pd-catalyzed reactions of other substrates such as enolizable ketones, thus providing practical insight on the execution and optimization of such processes.

A multi-level action coupling reinforcement learning approach for online two-stage flexible assembly flow shop scheduling

Multi-product centralized delivery and kitting assembly present significant challenges to hierarchical co-processing in multi-stage manufacturing systems. The combinations of priority dispatching rules at each level are transiently adaptive, and the performance in online scheduling deteriorates rapidly with changing environment. This paper investigates the selection of rule combinations for sustained high-performance responsive scheduling in two-stage flexible assembly flow shop scheduling problem with asynchronous execution and complex decision correlation. A Multi-Level Action Coupling Deep Q-Network (MALC-DQN) approach is proposed for adaptive integrated scheduling in hybrid processing and assembly shops. Firstly, the problem is skillfully established as an event-triggered integrated decision markov decision process. The prioritized batch experience replay mechanism is employed to retain the complete correlation information of key decision sequences. Then, coupling and sequence feature extraction modules are developed to enhance the agent’s ability to perceive execution process and the environment. Furthermore, the multi-level wait-limit mechanism and efficient action filtering mechanism are designed to mitigate ineffective waiting waste and action space explosion during learning. Finally, a series of sophisticated experiments are conducted to validate the effectiveness of the proposed methodology. In 20 actual instances of different sizes, MLAC-DQN outperformed its closest competitor, with a 26.6% improvement in average tardiness. Moreover, extraordinary robustness is demonstrated in 16 sets of experiments involving different configurations of resources, orders, and arrival concentration levels.

An enhanced round robin using dynamic time quantum for real-time asymmetric burst length processes in cloud computing environment.

Cloud computing is a popular, flexible, scalable, and cost-effective technology in the modern world that provides on-demand services dynamically. The dynamic execution of user requests and resource-sharing facilities require proper task scheduling among the available virtual machines, which is a significant issue and plays a crucial role in developing an optimal cloud computing environment. Round Robin is a prevalent scheduling algorithm for fair distribution of resources with a balanced contribution in minimized response time and turnaround time. This paper introduced a new enhanced round-robin approach for task scheduling in cloud computing systems. The proposed algorithm generates and keeps updating a dynamic quantum time for process execution, considering the available number of process in the system and their burst length. Since our method dynamically runs processes, it is appropriate for a real-time environment like cloud computing. The notable part of this approach is the capability of scheduling tasks with asymmetric distribution of burst time, avoiding the convoy effect. The experimental result indicates that the proposed algorithm has outperformed the existing improved round-robin task scheduling approaches in terms of minimized average waiting time, average turnaround time, and number of context switches. Comparing the method against five other enhanced round robin approaches, it reduced average waiting times by 15.77% and context switching by 20.68% on average. After executing the experiment and comparative study, it can be concluded that the proposed enhanced round-robin scheduling algorithm is optimal, acceptable, and relatively better suited for cloud computing environments.

Development of multiplex digital PCR based droplex NSCLC panel test for detecting major mutations in patients with non-small cell lung cancer (NSCLC).

46 Background: Recently, in the treatment of non-small cell lung cancer(NSCLC) patient, immunotherapies and targeted therapies aimed at various genes have been developed. Next-Generation Sequencing(NGS) technology is currently known as the only method for detecting genetic alterations in many different genes simultaneously. However, this technology requires a substantial amount of DNA or RNA input from patients to obtain high-quality results in a clinical setting. We have developed a Droplex NSCLC Panel Test Kit based on multiplex digital PCR, which is known as ideal molecular diagnostic technique due to its simple workflow, minimal sample input, high sensitivity and specificity. In addition, it has a one-day TAT (Turn around time) and low costs compared NGS, resulting in a lower financial burden for patients. Recently, the development of non-invasive liquid biopsy diagnostics as an alternative to tissue biopsy is emerging important issue. The kit, applying a digital PCR platform, enables multiple mutation detection using plasma samples of blood. The digital PCR-based Droplex NSCLC Panel Test Kit is designed to detect over 170 key mutations in 11 genes, namely EGFR, ALK, ROS1, BRAF, MET, RET, KRAS, HER2, NTRK1, NTRK2, and NTRK3, using DNA and RNA extracted from NSCLC FFPET and plasma samples. Methods: The Droplex NSCLC Panel Test Kit consists of four Oligo Mixtures (OMs) for detecting mutations of 4 genes on DNA and two OMs for detecting 7 gene rearrangements on RNA. After extracting DNA and RNA from a single sample, cDNA synthesis from RNA is prioritized, followed by simultaneous execution of droplet generation, PCR processes, and data analysis. The kit test was based on QX600 droplet digital PCR system of Bio-rad with 6 fluorescent channels. To validate the analytical performance of the Droplex NSCLC Panel Test Kit for each type of sample, DNA and RNA samples were extracted from FFPET sections and plasma isolated from NSCLC patients. Each type of samples, contrived samples were manufactured and tested for analytical performance. Results: The results showed that DNA/RNA multiple mutations can be detected simultaneously on a 6-fluorescent channel system. The kit was highly sensitive for low-input sample in dilutions studies ranging from 5 to 20ng DNA or RNA for FFPET samples and plasma sample. The Digital PCR NSCLC panel test detected an analytical specificity of 100% and detection limit of 0.25% or higher for all genes included in the kit. Conclusions: We demonstrated that the performance of the Droplex NSCLC Panel Test is reliable and effective for the detection of above 170 clinically relevant mutations of 11 genes in FFPET and plasma samples of patients with NSCLC. Additionally, it will be necessary to evaluate the utility of the kit through further clinical studies with NSCLC patients, as well as expanding its compatibility to various digital PCR platforms.

The Poverty of Policy Execution: The Nigerian Experience

Policy summersault in Nigeria has to a large extent eroded public confidence in government’s ability to provide essential service as a way of solving societal problems. There is greater attention being paid to public policy execution in and out of intellectual discourse. The concept of public policy execution is not without its attending challenges and creative process of getting it done. Thus various proposals are faced with difficulties enroute execution. Various proposals fail to materialise, while those that do appeared distorted or mutilated, for them not to serve their envisioned drives. This paper objectively examines the challenges of policy execution in Nigeria. The paper relies on primary and secondary data for analysis and presentation these underlying factors. The paper found that effective policy execution can only be attained through unceasing commitment politically with clear responsibilities definition and effective coordination, by ensuring that genuinely, commitment to elimination of corruption at all levels of government is achieved for free flow of policy execution process. The paper concluded that poverty of policy execution is premised on government genuine commitment

Mobile toolbox (MTB) remote measures of executive function and processing speed: development and validation.

The ability to remotely monitor cognitive skills is increasing with the ubiquity of smartphones. The Mobile Toolbox (MTB) is a new measurement system that includes measures assessing Executive Functioning (EF) and Processing Speed (PS): Arrow Matching, Shape-Color Sorting, and Number-Symbol Match. The purpose of this study was to assess their psychometric properties. MTB measures were developed for smartphone administration based on constructs measured in the NIH Toolbox® (NIHTB). Psychometric properties of the resulting measures were evaluated in three studies with participants ages 18 to 90. In Study 1 (N = 92), participants completed MTB measures in the lab and were administered both equivalent NIH TB measures and other external measures of similar cognitive constructs. In Study 2 (N = 1,021), participants completed the equivalent NIHTB measures in the lab and then took the MTB measures on their own, remotely. In Study 3 (N = 168), participants completed MTB measures twice remotely, two weeks apart. All three measures exhibited very high internal consistency and strong test-retest reliability, as well as moderately high correlations with comparable NIHTB tests and moderate correlations with external measures of similar constructs. Phone operating system (iOS vs. Android) had a significant impact on performance for Arrow Matching and Shape-Color Sorting, but no impact on either validity or reliability. Results support the reliability and convergent validity of MTB EF and PS measures for use across the adult lifespan in remote, self-administered designs.

Interaction of the dorsolateral prefrontal cortex with the precuneal medial parietal cortex for the monitoring of information in working memory in the macaque monkey.

The executive control process of monitoring information in working memory depends on the mid-dorsolateral prefrontal cortical region (cytoarchitectonic areas 46 and 9/46) in interaction with the hippocampal memory system. Anatomical studies demonstrated strong connectivity between the mid-dorsolateral prefrontal cortex and the medial parietal area PGm that lies on the precuneus. Area PGm is also strongly connected with the attentional system on the lateral inferior parietal lobule (area PG) and the limbic retrosplenial/posterior cingulate region that interacts with the hippocampal memory system. Thus, in terms of anatomical connectivity, area PGm appears to be a critical node for the integration of executive control processing from the prefrontal cortex with the online attentional and memory related processing. This hypothesis was tested in macaque monkeys with the crossed unilateral lesion methodology. A unilateral lesion in the mid-dorsolateral prefrontal cortex was combined with a unilateral lesion in area PGm in the opposite hemisphere. The results demonstrated an impairment on the externally ordered working memory task that assesses the monitoring of information in working memory. Thus, the medial parietal area PGm is a critical node in mediating the functional interaction between the prefrontal region for the executive control process of monitoring information and the memory system.

Institute of Mediation: current state and development prospects.

This article analyzes the current state of the institution of mediation as an alternative method of resolving disputes and possible ways of its development. The most important problems of mediation that exist at the current stage of its development in the Russian Federation are studied. Among such problems, the author highlighted the insufficient level of professional education of mediators and the process of execution of the mediation agreement. Attention was also drawn to the lack of awareness among civil society participants of the nature and essence of the mediation procedure. The author conducted a study of an array of statistical data on the use of mediation procedures for the previous period 2014–2022. Based on these statistics, as well as gaps in legislation, the main conclusions of this work were drawn, aimed at the evolutionary development of the covered institution. The author’s main conclusions based on the results of the research are: the need to legislatively establish in the Law on Mediation the required level of additional education for professional mediators and, possibly, the type of document that confirms this education; legislate the principle of competence in the professional activity of a mediator (by analogy with the communities of lawyers and notaries); the need for further regulation of rules to guarantee the execution of a mediation agreement by contacting a notary; the introduction of the above innovations will resolve another problem – it will increase awareness of the essence of mediation and its significance in the eyes of potential participants in the procedure, and increase confidence in the mediator as a professional conciliator. The author also put forward a proposal to introduce a mediation procedure in disputes about the protection of consumer rights (within the framework of online trading on marketplaces), which will reduce the burden on the judicial system.

ARM4CH: A Methodology for Autonomous Reality Modelling for Cultural Heritage.

Nowadays, the use of advanced sensors, such as terrestrial, mobile 3D scanners and photogrammetric imaging, has become the prevalent practice for 3D Reality Modeling (RM) and the digitization of large-scale monuments of Cultural Heritage (CH). In practice, this process is heavily related to the expertise of the surveying team handling the laborious planning and time-consuming execution of the 3D scanning process tailored to each site's specific requirements and constraints. To minimize human intervention, this paper proposes a novel methodology for autonomous 3D Reality Modeling of CH monuments by employing autonomous robotic agents equipped with the appropriate sensors. These autonomous robotic agents are able to carry out the 3D RM process in a systematic, repeatable, and accurate approach. The outcomes of this automated process may also find applications in digital twin platforms, facilitating secure monitoring and the management of cultural heritage sites and spaces, in both indoor and outdoor environments. The main purpose of this paper is the initial release of an Industry 4.0-based methodology for reality modeling and the survey of cultural spaces in the scientific community, which will be evaluated in real-life scenarios in future research.

Are Carriers Unaffected? A Literature Review of Metabolic and Health Outcomes among Genetic Carriers of Phenylketonuria.

Phenylketonuria (PKU) is an autosomal recessive genetic condition that results in reduced enzymatic functioning within the phenylalanine hydroxylase (PAH) pathway, which is involved in the metabolism of phenylalanine (Phe) into tyrosine (Tyr). Without dietary intervention, individuals with PKU exhibit significantly elevated levels of Phe, which is presumed to cause severe neurological dysfunction and other associated health risks. Carriers of PKU are heterozygotes for a PAH gene mutation and are typically described in the literature as "unaffected." However, decades of existing research challenges this classical thinking and it is plausible that these individuals currently classified as carriers may present with an intermediate phenotype or may be "moderately affected." The purpose of this scoping review was to explore this hypothesis further, by searching for and summarizing existing literature on metabolism and health outcomes among PKU carriers. Preliminary research has suggested that some PKU carriers exhibit reduced PAH enzyme function, and relatedly, elevated circulating Phe levels compared to noncarriers. In addition, Phe dosing trials have further demonstrated that carriers have increased Phe levels and decreased Tyr levels compared to noncarriers. Because of these metabolic perturbations, it is biologically plausible for carriers to experience an intermediate phenotype in terms of metabolic consequences and clinical outcomes. While these outcomes have yet to be thoroughly explored, early research has found associations between PKU carrier status and lower IQs as well as decreased executive functioning, memory, processing speed, and inhibitory control. The PAH pathway is also involved in melanogenesis, and research has demonstrated increased melanoma risk among PKU carriers. However, there are many limitations to this research, and thus whether or not carriers are clinically impacted cannot yet be conclusively determined. Overall, while preliminary research suggests a possible intermediate phenotype among PKU carriers, the current available research is limited and PKU carriers are still clinically considered "unaffected." This review outlines the current literature while discussing future research endeavors related to the metabolism and health of PKU carriers.

DEVELOPMENT AND RESEARCH OF SOFTWARE SOLUTION FOR BUSINESS PROCESS MODEL CORRECTNESS ANALYSIS USING MACHINE LEARNING

Poorly designed business process models are a source of errors and the subsequent costs associated with these errors, such as monetary costs, lost time, or even some harmful impact on people or the environment if the erroneous business process models are associated with critical industries. The BPM (Business Process Management) lifecycle usually consists of designing, implementing, monitoring, and controlling the business process execution, but it lacks continuous quality control of the created BPMN (Business Process Model and Notation) models. Thus, this paper considers the problem of business process models classification based on their correctness, which solution will ensure quality control of the designed business process models. Thus, this study aims to improve the quality of business process models by developing a software solution for business process models classification based on their correctness. The subject of the study is the process of business process models classification based on their correctness, which uses quality measures and thresholds, usually, complexity measures. The subject of the study is a software solution for business process models classification based on their correctness. Therefore, in this study, the algorithm to solve the problem of BPMN models classification using logistic regression, interface complexity, and modularity measures is proposed, the software requirements are determined, the software development tools are selected, the software for business process models classification based on their correctness is designed, the corresponding software components are developed, the use of a software solution for solving the problem of business process models classification based on their correctness is demonstrated, the obtained results are analyzed and discussed. The developed software indicates high performance of BPMN models classification based on their correctness, achieving high accuracy (99.14 %), precision (99.88 %), recall (99.23 %), and F-score (99.56 %), highlighting the high performance of modeling errors detection.

Revitalizing the single batch environment: a ‘Quest’ to achieve fairness and efficiency

In the realm of computer systems, efficient utilization of the CPU (Central Processing Unit) has always been a paramount concern. Researchers and engineers have long sought ways to optimize process execution on the CPU, leading to the emergence of CPU scheduling as a field of study. In this research, we have analyzed the single offline batch processing and investigated other sophisticated paradigms such as time-sharing operating systems and wildly used algorithms, and their shortcomings. Our work is directed toward two fundamental aspects of scheduling: efficiency and fairness. We propose a novel algorithm for batch processing that operates on a preemptive model, dynamically assigning priorities based on a robust ratio, employing a dynamic time slice, and utilizing periodic sorting to achieve fairness. By engineering this responsive and fair model, the proposed algorithm strikes a delicate balance between efficiency and fairness, providing an optimized solution for batch scheduling while ensuring system responsiveness.