Speed Of Process Research Articles

FEATURES OF MANAGEMENT OF OPERATIONAL ACTIVITIES OF RESTAURANT ENTERPRISES

The article reveals the essence of managing the operational activities of a restaurant business enterprise. The functions of production management at the restaurant business enterprise were considered. The condition and evaluation of the operational efficiency of the restaurant enterprise was analyzed. The main indicators characterizing the production capacity of the operating system at the enterprises of the restaurant industry were established. Indicators that increase the efficiency of the use of production facilities and indicators that characterize the organizational and technical level of production are systematized. Production efficiency indicators were formed into general groups. On the basis of the research, it was found that different both foreign and domestic scientists form certain groups of indicators in their scientific research. It has been proven that operational management requires measurement indicators of such factors as: product quality; innovations; costs; speed of processes; flexibility. The main factors affecting the level of satisfaction of the needs of consumers of restaurant products are considered. The directions for improving the features and a comprehensive approach to the effectiveness of management of the operational activities of the restaurant business have been defined and substantiated. On the basis of this study, it was determined that it is appropriate to accept the profitability of the enterprise's operational activity as the largest generalizing indicator of the efficiency of the enterprise's operational activity. The essence of managing the operational activities of a restaurant is to ensure the effective functioning of all aspects of the business related to its daily activities. The main aspects of this management include: processes and operations; product and service quality; HR; financial management; risk and security management; strategic planning and business development. These aspects help to ensure efficient and stable operation of the restaurant, ensuring that customer needs are met, costs are optimized and business goals are achieved.

Robust guided wave inversion for estimating bone thickness and elasticity.

Accurately characterizing bone properties using quantitative ultrasound remains a significant challenge due to the dispersive nature of guided waves, limited observations, irregularity of bone structure, and heterogeneity of bone tissues. In this paper, an inversion technique is proposed that combines weighted mean absolute criteria and the simulated annealing algorithm to extract the thicknesses and elastic properties of a bilayer bone model. By utilizing the L1 norm with an appropriate weighting parameter, this method effectively reduces the influence of outliers and noises commonly encountered in ultrasonic data, leading to more accurate estimation. This paper also introduces an asymptotic scheme to significantly reduce the search domain, improving the speed and precision of the inversion process. This approach employs a spectral collocation method as a forward modeling technique to simulate guided waves in a bone plate coated by a soft tissue layer. This paper validates the inversion using simulated and ex vivo data and demonstrates its ability to estimate features of cortical bone and soft tissue with high accuracy. Results are presented for the isotropic model. These findings hold great promise for the accurate characterization of bone properties using quantitative ultrasound, with potential applications in clinical diagnosis and treatment of bone-related diseases and injuries.

Optimization in Extrusion Process for Polypropylene and High-Density Polyethylene Pellets in Additive Manufacturing of 3D Printing Filament

The increasing demand for sustainable and cost-effective materials in additive manufacturing has driven research into optimizing the extrusion process for creating 3D printing filament from Polypropylene (PP) and High-Density Polyethylene (HDPE) pellets. This study explores the critical parameters in the extrusion process, including temperature, and screw speed, to enhance the quality and consistency of the resulting filament. Through a series of controlled experiments, we analyze the effects of these parameters on the filament’s diameter, mechanical properties, and printability. Our findings demonstrate that by optimizing these variables, it is possible to produce high-quality 3D printing filament with excellent mechanical strength and dimensional accuracy, meeting industry standards. This research not only contributes to the broader adoption of PP and HDPE in 3D printing but also supports the development of more sustainable manufacturing practices by utilizing recyclable materials.

Development of the architecture of a computer aided diagnosis system in medicine

With the development of information technology, automation of various production processes is an urgent task, and medical diagnostics is no exception. In recent decades, artificial intelligence and information technology have been widely used in computer diagnostic systems. However, as technology advances, so do the challenges. Not every system is optimized and fast, and traditional methods are fading into the background. Often, systems do not use cloud technologies and have unoptimized architectures. This all affects their performance and, accordingly, is an urgent problem. The study analyzes the methods used in computer diagnostic systems and compares them in terms of advantages and disadvantages. The scientific works related to computer diagnostic systems in medicine for specific tasks are analyzed. The existing architectures of computer diagnostic systems are analyzed, which made it possible to identify the use of consistent approaches to diagnosis. Based on the analyzed data, the purpose, objectives, object and subject of the study are determined. A new architecture has been developed that uses the capabilities of U-Net for image segmentation and convolutional neural networks for medical image classification. The developed architecture is designed to increase the speed and automation of diagnostic processes through the use of neural networks and, accordingly, reduce human intervention. The scientific novelty of the developed architecture lies in the parallel execution of medical image segmentation and classification tasks, which gives a potential increase in data processing speed, and in the availability of an image generator, which solves the problem of lack of test data for model training.

Application of Micro/Nanomotors in Environmental Remediation: A Review

The advent of self-propelled micro/nanomotors represents a paradigm shift in the field of environmental remediation, offering a significant enhancement in the efficiency of conventional operations through the exploitation of the material phenomenon of active motion. Despite the considerable promise of micro/nanomotors for applications in environmental remediation, there has been a paucity of reviews that have focused on this area. This review identifies the current opportunities and challenges in utilizing micro/nanomotors to enhance contaminant degradation and removal, accelerate bacterial death, or enable dynamic environmental monitoring. It illustrates how mobile reactors or receptors can dramatically increase the speed and efficiency of environmental remediation processes. These studies exemplify the wide range of environmental applications of dynamic micro/nanomotors associated with their continuous motion, force, and function. Finally, the review discusses the challenges of transferring these exciting advances from the experimental scale to larger-scale field applications.

Online alcohol deliveries: age verification processes of online alcohol delivery companies in Auckland, New Zealand

aim: This study aims to document the age verification processes for online alcohol deliveries in Auckland, New Zealand, with a focus on rapid alcohol delivery (delivery within 2 hours of ordering). methods: Alcohol orders from Auckland online alcohol delivery companies were placed by a researcher under 25 years of age over a 2-month period in 2023. Procedures were recorded around speed of delivery and age verification processes. results: In total, 33 (73%) of the 45 online alcohol orders did not require age verification at delivery. This comprises 22 (49% of the total) deliveries left unattended at the door and 11 (24%) in-person deliveries that did not request age verification. The average speed of delivery for rapid alcohol delivery companies was 29.5 minutes and the standard deviation 9.5 minutes. conclusion: It is common for online alcohol deliveries in Auckland to be left unattended on delivery or delivered without requesting identification. This has implications for increasing alcohol-related harm, including supply to minors. Additional regulation addressing alcohol delivery is needed in New Zealand.

The Effect of Mixing Time and Rotation Speed on the Consistency of Dough Viscosity in a Horizontal Mixer

Cassava must go through several manufacturing processes before it becomes chips on the market, including the process of stirring the dough. The stirring process is an important stage in various food industries. In the stirring process, the viscosity change in the dough is influenced by various factors, including the stirring process time and speed in stirring. Research on dough viscosity is important because it is directly related to the quality of the final product. The purpose of this study is to provide recommendations to users, both in the context of using horizontal mixers and the process of making similar products. The type of research used is quantitative research based on experimental methods that aim to test a hypothesis by collecting data that can be measured using statistics, mathematics, and computing. The independent variables in this study are rotation speed (20, 40, and 80 rpm) and stirring time (5 minutes, 10 minutes, and 15 minutes). From these independent variables calculations and data analysis, the optimal setting was obtained using a rotation speed of 80 rpm and a stirring time of 15 minutes with a dough viscosity of 1411.12 PaS. The rotation speed of 80 rpm has more even data or more consistent data compared to the rotation speed values of 20 rpm and 40 rpm.

The Application of Accounting Information Systems at CV Fael Jaya in the City of Manado

The purpose of this research is to understand the implementation of the accounting information system for cash receipts and cash expenditures at CV. Fael Jaya in the City of Manado, particularly in the sales department of goods (construction materials) based on the fundamental elements of the accounting information system. Given that this company is a growing enterprise, managing cash receipts and expenditures is crucial to facilitate accuracy and speed in all financial transaction processes within the company. The type of research used is a case study, and data are obtained from interviews and documentation. The data analysis technique employed is qualitative descriptive, in which the researcher elaborates on the implementation of the accounting information system at CV. Fael Jaya and then compares it with relevant theories about the accounting information system. The research findings indicate that the implementation of the accounting information system for cash receipts and expenditures at CV. Fael Jaya in the City of Manado is not yet adequate. Observing the functions and documents related to the theories and what occurs at CV. Fael Jaya, not everything aligns.

Analysis of the Effect of Using the SIPLah Application on User Satisfaction in Procuring Elementary School Books in Pangkalpinang City

The advancement of information technology has become more widespread across various sectors, particularly in education. The integration of information technology has increasingly simplified many aspects of human life. This study aims to evaluate the impact of the SIPLah (School Procurement Information System) application on user satisfaction in the procurement of books for elementary schools. SIPLah is a government-provided digital platform designed to streamline the procurement of goods and services within schools, promoting greater transparency, efficiency, and accountability. The research data was collected through surveys involving SIPLah users, such as school principals, teachers, and administrative staff engaged in book procurement. The study measured variables including ease of use, system reliability, procurement process speed, and user satisfaction with the procurement outcomes. The analysis revealed that the SIPLah application has a significant impact on user satisfaction. Among the factors studied, ease of use and system reliability had the most positive influence. However, some respondents reported technical challenges, such as delays in data updates and insufficient technical support. To enhance future user satisfaction, the study recommends improvements in technical services and system optimization.

Burn-through point prediction and control based on multi-cycle dynamic spatio-temporal feature extraction

Burn-Through Point (BTP) is a critical state in the sintering process, and maintaining a stable BTP is crucial for ensuring the quality of sintered products. However, the complex mechanistic relationships during the sintering process make it challenging to extract meaningful correlations between data, leading to suboptimal performance of prediction-based control methods. To address this issue, this paper proposed a BTP prediction method based on multi-period dynamic spatio-temporal extraction. Building upon this, a comprehensive fuzzy controller based on historical and future state recognition is introduced to achieve stable BTP. Firstly, a time series alignment method based on multi-cycle partitioning is proposed. The Fast Fourier Transform (FFT) operations is introduced to identify hidden data patterns within the observation sequence. Time series alignment is achieved by weighted time delay through fuzzy curve analysis applied to different data patterns. Temporal features are extracted along the temporal dimension using multi-scale 2D convolution, while the graph learning module generates the graph structure by introducing an attentional mechanism to capture the inter-variable dependencies in the learning window. Next, the spatial feature extraction module uses the outputs of the above two modules as inputs to further capture potential spatial features in the time series. Finally, the comprehensive fuzzy controller, by recognizing historical and future states, provides recommendations for the current sintering process speed, stabilizing the sintering process towards the desired operating states. According to the simulation results on actual datasets, this method not only exhibits high predictive accuracy but also effectively maintains control over BTP within a fluctuation range with a mean square error of 0.0109.

A Roadmap to Systematic Review: Evaluating the Role of Data Networks and Application Programming Interfaces in Enhancing Operational Efficiency in Small and Medium Enterprises

The adoption of Data Networks and Application Programming Interfaces (APIs) has become crucial for small and medium enterprises (SMEs) to streamline operations, improve efficiency, and reduce costs. However, SMEs often face challenges such as resource limitations and security vulnerabilities, which hinder their ability to fully leverage these technologies. This systematic review examines the role of Data Networks and APIs in enhancing operational efficiency within SMEs, focusing on key metrics such as speed, cost reduction, scalability, and security challenges. Following PRISMA 2020 guidelines, we conducted a systematic search across multiple databases including Web of Science, Scopus, IEEE Xplore, and Google Scholar. Studies published between 2014 and 2024, focused on SMEs, and addressing the role of Data Networks and APIs in operational efficiency were included. A total of 49 studies met the inclusion criteria and were analyzed for key outcomes related to operational efficiency, cost-effectiveness, and security risks. The review found that Data Networks and APIs significantly improve operational efficiency by increasing process speed (12% increase), reducing operational costs (8% reduction), and enhancing overall productivity. However, security challenges, particularly related to API vulnerabilities, were a major concern, with cyberattacks on APIs increasing by 400% in Q1 2023 alone. Despite these risks, the benefits of implementing Data Networks and APIs in SMEs, particularly in terms of scalability and real-time data processing, were evident across industries. Data Networks and APIs offer substantial improvements in operational efficiency for SMEs, although security remains a significant challenge. Future efforts should focus on developing security frameworks tailored to SMEs while maintaining the operational benefits of these technologies. Further research is needed to explore scalable and secure API models for SMEs.

Congruent and Hierarchical Intra-Lake Subdivisions from Nuclear and Mitochondrial Data of a Lake Baikal Shoreline Amphipod

A central goal of molecular studies on ancient lake faunas is to resolve the origin and phylogeny of their strikingly diverse endemic species flocks. Another equally intriguing goal is to understand the integrity of individual morphologically diagnosed species, which should help to perceive the nature and speed of the speciation process, and the true biological species diversity. In the uniquely diverse Lake Baikal amphipod crustaceans, molecular data from shallow-water species have often disclosed their cryptic subdivision into geographically segregated genetic lineages, but the evidence so far is mainly based on mitochondrial DNA. We now present a lake-wide parallel survey of both mitochondrial and multilocus nuclear genetic structuring in the common shoreline amphipod Eulimnogammarus verrucosus, known to comprise three deep, parapatric mtDNA lineages. Allele frequencies of seven nuclear allozyme loci divide the data into three main groups whose distributions exactly match the distributions of the main mitochondrial lineages S, W, and E and involve a further division of the W cluster into two subgroups. The inter-group differences involve one to four diagnostic loci and additional group-specific alleles. The transition zones are either abrupt (1 km), occur over a long segment of uninhabitable shoreline, or may be gradual with non-coincident clinal change at different loci. Mitochondrial variation is hierarchically structured, each main lineage further subdivided into 2–4 parapatric sublineages or phylogroups, and patterns of further local segregation are seen in some of them. Despite the recurring observations of cryptic diversity in Baikalian amphipods, the geographical subdivisions and clade depths do not match in different taxa, defying a common explanation for the diversification in environmental history.

Deliberative Democracy in the Digital Age Opportunities and Challenges of Online Public Discourse

Deliberative democracy is a model of democracy in which decision-making processes are based on public participation, and public debate is prioritised. In this model, citizens make joint decisions through rational discussion and negotiation, and this process forms the basis of democratic legitimacy. As one of the main actors in 21st-century democracy debates, deliberative democracy aims to create more inclusive and fair policies by encouraging broad participation. In the digital age, the concept of deliberative democracy faces new challenges and opportunities. This study examines the intersection between deliberative democracy and digital technologies, focusing on how online platforms influence public discourse and democratic engagement. The core objective is to explore how digital technologies enhance inclusivity, speed, and scalability in deliberative processes while simultaneously raising concerns about misinformation, polarization, and exclusion. Drawing from the theoretical framework of deliberative democracy, which emphasizes rational discourse and public reasoning, the paper investigates the benefits and challenges that arise when deliberation moves online. Through case studies such as Iceland's crowdsourced constitution, global climate change discussions, and the role of social media during the 2020 U.S. election, the paper highlights how digital platforms facilitate rapid, large-scale deliberation but also contribute to political fragmentation and echo chambers. The study employs a qualitative research methodology, analyzing the impact of digital platforms on deliberative processes through literature reviews and case studies. The hypothesis is that while digital platforms offer significant potential for enhancing democratic deliberation by broadening participation, they also present new risks to the integrity of public discourse, particularly due to misinformation and the manipulation of algorithms. Ultimately, the paper argues that deliberative democracy must adapt to the realities of the digital age by integrating online and offline deliberation, fostering digital literacy, and establishing regulatory frameworks for transparency and accountability. The findings offer theoretical contributions to understanding the relationship between digital technology and democracy while also providing practical recommendations for enhancing the quality of digital public discourse.

Methods for assessing the self-healing properties of asphalt concrete

The article presents the results of a study of the ability of asphalt concrete to independently restore the state of the structure or improve the operational state of the material. The quality indicators that reflect the degree of efficiency of the developed self-healing technology are: the degree of restoration of the operational state of the structure; timeliness of initiation of the self-healing process; the speed of the restoration process, as well as the durability of the operational state after self-healing. The article formulates requirements for new methods for testing the self-healing ability of materials with encapsulated modifiers. It is shown that the self-healing efficiency is significantly higher for asphalt concretes with encapsulated AR polymer than for SMA, which used encapsulated oil. With the optimal content of encapsulated oil, the loss of strength of asphalt concrete samples during repeated compression is 1.4 times less, and for encapsulated AR polymer it is 1.6–2.1 times less. For SMA with encapsulated oil, the failure rate is 1.05, and with encapsulated AR polymer 1.7. The coefficient values reflect that the achievement of the critical value of the strength limit for asphalt concrete with encapsulated AR polymer occurs later by 61.9% than for asphalt concrete with encapsulated oil. The speed of the self-healing process of asphalt concrete using encapsulated oil is 10% faster than asphalt concrete without capsules, and with the use of encapsulated AR polymer – by 23%.

Plasmochemical and Reactive Ion Etching of Gallium Arsenide in Difluorodichloromethane with Helium

The kinetics of interaction of high-frequency plasma of difluorodichloromethane and its mixture with helium with the surface of gallium arsenide was experimentally studied. It was established that in the studied range of conditions, complete decomposition of the original difluorodichloromethane molecule to atomic carbon occurs. It has been confirmed that the main chemically active particles responsible for etching are reactive chlorine atoms. It has been shown that the etching process occurs in the mode of an ion-stimulated chemical reaction, where the desorption of products under the influence of ion bombardment plays a significant role in surface cleaning. The emission spectra of plasma radiation in the presence of a gallium arsenide semiconductor wafer are analyzed. Control lines and stripes were selected to control the speed of the etching process based on the emission intensity of the lines and stripes of the etching products.

Correlational analysis of psychophysiological functions indicators, technical and physical readiness of young football players aged 12-13 at different training process stages

Background and purpose At the current stage, many teams in game sports have certain difficulties with stable success on the world sports arena. Football in this sense is no exception. The purpose of the study is to determine the relationship between psychophysiological functions and indicators of physical and technical readiness of young football players aged 12-13 years in the preparatory and competitive periods of the annual cycle of the training process. Materials and methods 12 football players of the Kharkiv Junior High School, 12-13 years old, took part in the study. We used the next methods. Determining the level of physical fitness: Running for 60 m, 1000 m run, Shuttle race, Pull-ups on the crossbar, Jump from a place. Determination of the level of technical preparation: Juggling. The main task of this test, the player needs to kick the ball so that it does not fall to the ground, this is done with the feet, the athlete must kick the ball as many times as possible; Shot at range. Held from the line of the field, the football player must hit the ball as far as possible from the run, this distance is measured in meters. Results In the preparatory phase for young soccer players aged 12-13 years, the total number of reliable relationships between the psychophysiological index and the physical and technical readiness index was 12. In the competition phase, the total number of reliable relationships between psychophysiological indicators and physical and technical readiness indicators remained the same for young soccer players aged 12-13 years, also 12 relationships. Conclusion The data obtained reflect the formative process of a specific type of soccer player, in which the speed of neurodynamic processes is related to the physical qualities of speed and speed-power.

Application of Machine Learning for the Prediction of Absorption, Distribution, Metabolism and Excretion (ADME) Properties from Cichorium intybus Plant Phytomolecules

Drug discovery is the process by which new drug candidates are discovered and drug development takes place. To enhance the efficiency, accuracy, and speed of the drug discovery process, machine learning (ML) could play a transformative role. For this research study, antidiabetic natural compounds from C. intybus, which is commonly known as chicory, were selected, as they have promising antidiabetic properties that can complement conventional diabetes treatments. A bioactive natural compound dataset was retrieved on the chicory plant using Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMPPAT) public source information. This collected dataset was analyzed for its absorption, distribution, metabolism, and excretion (ADME) properties using the SwissADME online tool. Principal component analysis (PCA) and correlation analysis were performed using trial-version XLSTAT software 2014.5.03 and Python. The obtained dataset from SwissADME was subjected to cleaning, after that, it was used to develop machine learning models, such as support vacuum (SVM) ML, random forest (RF), Naive Bayes (NB), and decision tree (DT). The Lipinski rule of violation was chosen as the target variable. To improve the vitality of the created ADME dataset, PCA, a biplot graph, and correlation analysis were carried out. A large dataset of naturally occurring antidiabetic compounds was used to predict the drug-likeness of ML models that were effectively deployed on heterogeneous ADME datasets. Among all these ML models, DT performed better than the rest of the models.

Evaluation and Prediction of Mechanical Properties According to Welding Methods of Ni 825/A516-70N Clad Plates

In this study, the microstructures and mechanical properties of different methods of FCAW (Flux-cored arc welding) + FCAW or FCAW + GTAW (Gas tungsten arc welding) welding on Ni825/A516-70N clad plate were investigated, using a double U groove angle on a laboratory scale. The amount of specimen deformation with FCAW + FCAW welding was ~1.5 mm, and that with FCAW + GTAW welding was ~3.6 mm. In the Vickers hardness tests, the average hardness value of the FCAW + GTAW welding specimens tended to be higher, and the hardness of the steel showed the same value. Also, in the tensile tests, the maximum strength and elongation of the FCAW + GTAW specimens were found to be higher. The SEM analysis of the welding boundaries of each specimen revealed the phenomenon of grain refinement in the specimens with FCAW + GTAW welding. This was due to the slow welding speed of this welding process and the rapid cooling rate caused by the relatively low layer thickness despite the relatively high number of weld passes. The computer simulation of the amounts of deformation were similar, with a value of 1.5 mm for FCAW + FCAW and 3.6 mm for the computer simulation, indicating the credibility of the simulation. In the computational simulation of butt welding, FCAW + GTAW showed high values for both residual stress and angular strain. The L-seam and C-seam of the demo vessel size were welded under the same conditions as the actual welding. The residual stress and angular deformation in the L-seam were 849 MPa and 2.3 mm for the FCAW + FCAW and 852 MPa and 2.9 mm for FCAW + GTAW. The residual stress and angular deformation in the C-seam were 920 MPa and 0.7 mm for FCAW + FCAW and 930 MPa and 0.9 mm for FCAW + GTAW, respectively.

A Parametric Study on the L-PBF Process of an AlSi10Mg Alloy for High-Speed Productivity of Automotive Prototype Parts

The AlSi10Mg alloy has garnered significant attention for its application in laser powder bed fusion (L-PBF), due to its lightweight properties and good printability using L-PBF. However, the low production speed of the L-PBF process is the main bottleneck in the industrial commercialization of L-PBF AlSi10Mg alloy parts. Furthermore, while L-PBF AlSi10Mg alloy exhibits excellent mechanical properties, the properties are often over-specified compared to the target properties of parts traditionally fabricated by casting. To accelerate production speed in L-PBF, this study investigated the effects of process parameters on the build rate and mechanical properties of the AlSi10Mg alloy. Guidelines are proposed for high-speed additive manufacturing of the AlSi10Mg alloy for use in automotive parts. The results show a significant increase in the build rate, exceeding the conventional build rate by a factor of 3.6 times or more, while the L-PBF AlSi10Mg alloy met the specifications for automotive prototype parts. This strategy can be expected to offer significant cost advantages while maintaining acceptable mechanical properties of topology-optimized parts used in the automobile industry.

The System Design of Payroll Accounting Information System at Private Primary School in East Jakarta

This research aims to design a system design of payroll Accounting Information System (AIS) at a primary private school (Madrasah Ibtidaiyah Al-Baidlo/”MIAB”), East Jakarta to improve the efficiency of payroll business processes. Business Process Improvement was used as a design approach in this research, with an applied research type. Collect data by interview with Headmaster and Treasurer. The tool used to document business processes is the Bizagi Modeler. Automation is carried out to prevent human error and increase the processing speed of payroll business processes. The business processes that are designed will be tested by material and information technology experts. The result of this research is that the proposed (to-be) business process increases the simplification of payroll activities by improving the quality of fast and accurate decision making which has economic value. Using Business Process Modelling Notation allows this research to present proposed business processes related to needs and solutions to problems in the research objects observed. This research is proven to be able to increase the simplification of business processes, increase efficiency in decision making by school principals in a relatively short time from 337 minutes to 41 minutes or a time saving of around 296 minutes (equivalent to 4.93 hours).Cutting manual activities to automated processes increases the opportunity for fraud and human error.