Increase Operational Efficiency Research Articles

Risk-based performance assessment from fully manual to human-robot teaming in pressurized tank inspection operations

The use of robotics in the process industry has shown a stable, increasing trend, according to survey reports, reducing the exposure of operators to critical operations, mainly during maintenance. Moving from full manual (FM) to human-robot teaming (HRT) operations is expected to reduce the risks for operators and increase operational efficiency. The methods used to assess system performances require an adaptation. Traditional risk assessment techniques are no longer adapted to analyze the new way of working; the previous methods proposed for HRT systems have been criticized for their fragmentation, complexity, and lack of validation.This study proposed an integrated framework, including the qualitative and quantitative stages, to investigate the risk-based system performance and compare the full manual and human-robot teaming scenarios in pressurized tank inspection operations. The outputs demonstrated that the integrated framework worked for FM and HRT system performance assessment, considering multiple element types and their interdependencies, generating knowledge that can be exploited to reduce the system's risk and choose among different operational alternatives.

Optimizing the Security of Letter of Credit Transactions: Application of Blockchain Technology in Reducing the Risk of Fraud in Banking

Letter of Credit (LC) transactions play a vital role in facilitating international trade, but are vulnerable to various forms of fraud such as forgery of documents and manipulation of information. In the banking context, ensuring the security of LC transactions is an urgent challenge. This research aims to investigate the potential of applying blockchain technology in improving the security of LC transactions and reducing the risk of fraud in the banking sector. This research is included in descriptive quantitative research. This research was conducted at Banks in DKI Jakarta. The population in this research are customers who use Letter of Credit transactions. The sampling technique in this research is purposive sampling so that in this research the research sample was 100 customers who used letter of credit transactions. The data analysis technique in this research uses Partial Least Square (PLS). The research results show that blockchain technology has great potential to increase the security of LC transactions through aspects such as high data security, transparency and auditability, as well as automation through smart contracts. With proper implementation, blockchain technology can help reduce the risk of fraud, increase operational efficiency, and build trust in international trade. This study contributes to the understanding of the potential application of blockchain technology in the global financial context and highlights the importance of cross-sector collaboration to address transaction security challenges.

Reshaping 3PL Operations: Machine Learning Approaches to Mitigate and Manage Damage Parameters

In the third-party logistics (3PL) environment, it is very important to reduce damage parameters, increase operational efficiency and reduce costs. This study aims to develop strategies for reshaping 3P operations by analyzing the parameters involved in damage control with machine learning. The logistics sector is gradually growing in the world and the potential of the sector is better understood over time. Damage to products in the logistics sector, especially during transportation and storage, not only causes financial losses but also affects customer productivity and operational efficiency. With the use of artificial intelligence techniques, it is possible to determine consumer expectations, predict damage losses, and develop innovative strategies by applying machine learning algorithms. At the same time, options such as driverless vehicles, robots used in storage and shelves, and the easy use of big data within the system, which have emerged with artificial intelligence, minimize errors in the logistics sector. Thanks to the use of artificial intelligence in the logistics sector, businesses are more efficient. This study includes an estimation study in the field of error parameters for the logistics service sector with machine learning methods. In the application, real data of a 3PL company for the last 5 years is used. For the success of 3PL companies, warehousing and undamaged delivery of products are of great importance. The fewer damaged products they send, the more they increase their value. The company examined in the study kept its damage data and wanted it to be analyzed so that it could take precautions accordingly and follow a more profitable path. For this reason, the study focuses on data on errors and damages. This study shows what kind of problems can occur in such a company and how the 3PL company can evaluate the problems to increase customer service quality and cost efficiency.

An insight into the Application of AI in maritime and Logistics toward Sustainable Transportation

This review article looks at the developing field of artificial intelligence and machine learning in maritime and marine environment management. The marine industry is increasingly interested in applying advanced AI and ML technologies to solve sustainability, efficiency, and regulatory compliance issues. This paper examines maritime and marine AI and ML applications using a deep literature review and case study analysis. Modeling ship fuel consumption, which impacts the environment and operating expenses, is a top responsibility. The study demonstrates that ML approaches such as Random Forest and Tweedie models can estimate ship fuel use. Statistical analysis demonstrates that the Random Forest model beats the Tweedie model regarding accuracy and consistency. For the training and testing datasets, the Random Forest model has high R2 values of 0.9997 and 0.9926, indicating a solid match. Low Root Mean Square Error (RMSE) and average absolute relative deviation (AARD) suggest that the model accurately reflects fuel use variability. While still performing well, the Tweedie model has lower R2 values and higher RMSE and AARD values, suggesting reduced accuracy and precision in fuel consumption prediction. These findings provide light on the potential applications of artificial intelligence and machine learning in maritime and marine environment management. Advanced analytics enables decision-makers to analyze fuel consumption patterns better, increase operational efficiency, and decrease environmental impact, thus improving maritime sustainability.

Sustainable Transportation in The Brazilian Agroindustrial Supply Chain: A Literature Review

Objective: This article aims to discuss the importance of incorporating sustainable transportation practices into the supply chains of the Brazilian agro-industry, highlighting their potential to reduce costs, increase operational efficiency, and enhance companies' reputation in an increasingly sustainability-focused global context. Theoretical framework: Agribusiness plays a vital role in the Brazilian economy, converting agricultural raw materials into higher value-added products and driving economic gains and job creation. However, transportation in this chain has a significant environmental impact, with Brazil heavily reliant on road transport, contributing to carbon emissions. Companies from various sectors are adopting sustainable transportation practices to address these challenges, recognizing the growing importance of sustainability as a business strategy to ensure competitive advantage in the global market. Method: The literature review was conducted in five detailed stages: formulation of the research question, identification and careful selection of relevant studies, analysis and synthesis of data, and description and dissemination of results. Scientific articles, book chapters, and technical reports published between 2015 and 2023 were considered, ensuring a solid and updated basis for analysis. Results and conclusion: The analysis of 102 studies highlighted the relevance of implementing sustainable transportation practices, such as the use of electric vehicles and bioenergy, in reducing greenhouse gas emissions and optimizing logistics costs. Intermodality also emerged as an effective strategy adopted to mitigate environmental impacts and strengthen competitiveness. However, there is a continuous need for future research to understand the nuances of sustainable transportation strategies in different segments and regions of the Brazilian agro-industrial supply chain. Research implications: This study emphasizes the urgency and importance of transitioning to sustainable transportation practices in the Brazilian agro-industry, highlighting the need for government intervention and investment in research to develop approaches tailored to the specific challenges of each sector and region. Additionally, it underscores the importance of public policies that incentivize and promote sustainability in supply chains. Originality/value: It significantly contributes to understanding the complexities of sustainable transportation in the Brazilian agro-industry, providing insights for companies and policymakers interested in promoting sustainability in supply chains. By filling knowledge gaps and presenting innovative perspectives, this study stands out for its original contribution and practical value.

A Survey Paper on Automation of Attendance System through Facial Recognition

Abstract—In recent times almost, everything around us is being automated in some way just to make life easier for us. With the use of machine learning and deep learning we can allow non- living objects to program themselves to self-learn from the available data and perfect itself in the process. The process of recording attendance in educational institutions and workplaces has traditionally relied on manual methods, which are time- consuming, error-prone, and lack the level of security and accuracy desired in today’s digital age. This research presents a technological solution to these challenges. This technology offers a range of compelling advantages. It eliminates the need for manual attendance tracking, reducing the potential for errors and administrative workload. Moreover, it enhances security by ensuring that only authorized individuals can mark their attendance. Real-time data is available for monitoring and generating attendance reports, offering valuable insights into punctuality and attendance patterns. This research provides a comprehensive overview of the system’s architecture, algorithms, and the underlying technology, along with a discus- sion of the ethical and privacy considerations associated with face recognition. By implementing this innovative technology, educa- tional institutions and organizations can streamline attendance management, increase operational efficiency, and contribute to a more secure and productive environment. Keywords: Face recognition, LBPH, Haar-cascade, face detection, Viola n Jones, openCV, Adaboost

Role of Digital Transformation and Innovation in Enhancing the Competitiveness and Sustainability of Hospitality and Tourism Businesses in South Africa

Purpose: The study sought to analyze the role of digital transformation and innovation in enhancing the competitiveness and sustainability of hospitality and tourism businesses
 Methodology: The study adopted a desktop methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.
 Findings: Digital transformation and innovation are essential drivers for enhancing the competitiveness and sustainability of hospitality and tourism businesses in South Africa. By embracing digital technologies, businesses can improve customer experiences, increase operational efficiency, make data-driven decisions, and adapt to changing market dynamics, ultimately securing their position in the evolving industry landscape.
 Unique Contribution to Theory, Practice and Policy: Resource-Based View (RBV), Dynamic capabilities theory & Disruptive innovation theory may be used to anchor future studies in the role of digital transformation and innovation in enhancing the competitiveness and sustainability of hospitality and tourism businesses. Encourage research that explores the intersection of digital transformation, innovation, and competitiveness within the hospitality and tourism sector. Promote the adoption of digital technologies and innovation strategies among hospitality and tourism businesses.

GIS-based service network optimisation for location of postal delivery system

ABSTRACT Public postal organisations aim to determine the optimal locations for postal delivery service branches to enhance service quality, increase operational efficiency, reduce costs, and optimise resource utilisation. In this paper, we consider how to enhance the process of identifying suitable sites for these branches in Istanbul, Turkey, through a case study that evaluates land-use categories – and their influence on demand for postal services – within different districts so as to pinpoint the most appropriate locations for service branches. We employ Kernel Density Estimation (KDE) analyses in conjunction with Geographic Information Systems (GIS) to optimise the service network. This optimisation aids in deciding whether to close underperforming branches or to establish new branches in neighbourhoods with higher demand. Turkish postal delivery system statistics serve as the basis for our case study. Consequently, this study provides valuable insights into the selection of postal service branch locations and offers practical implications for improving branch accessibility in relation to spatial variability in demand. Such applied insights can be crucial for administrators and policymakers when making informed decisions regarding long-term location planning and initiatives across various sectors.

Electric Motor Maintenance

Electric motors play a vital role in industrial operations, and their protection from overloading is crucial for ensuring longevity, safety, and efficiency. This article explores the significance of motor overload protection devices in safeguarding motors from damage caused by overloading, which can lead to overheating and potential failure. It discusses the functioning of various protection devices, such as thermal, magnetic, and electronic overload relays, and emphasizes the importance of selecting the right device based on motor type, size, application, and environmental conditions. The article also highlights the role of regular maintenance and adherence to safety standards in ensuring the reliable and effective functioning of these protection systems. By implementing appropriate protection measures, companies can optimize energy use, increase operational efficiency, and reduce damage and production disruptions, thus contributing to the sustainability and safety of electric motors in industrial settings vulnerable to overloading. Highlight : Overload relays protect the motor, motor branch circuit, and motor branch circuit components from excessive heat from the overload condition Overload relays are part of the motor starter and protect the motor by monitoring the current flowing in the circuit The selection of an overload relay is important because repeated tripping and reset can reduce the mechanical life of the relay and may cause damage to the motor Keywords: electric motors, overload protection devices, thermal overload relays, magnetic overload relays, electronic overload relays, motor type.

Main provisions of the concept of project ergonomics of automated information display systems

Automation of information technologies is developing at a rapid pace, the issue of effective interaction between man and machine is becoming increasingly significant and pressing. This paper examines the problem of designing automated control systems for special purposes based on a systems approach and design ergonomics. Investigate the information display subsystem in a special-purpose automated control system as a separate system, and also consider the influence of this subsystem on the efficiency of human-machine interaction. Particular attention is paid to the analysis of cognitive function and its significance for achieving the goals of functioning of the automated system under consideration. The conceptual foundations of the design ergonomics of automated information display systems are presented. The key stages of implementing the concept of design ergonomics of the above-mentioned systems are studied, including problem analysis, formulation of theoretical foundations, study of the effectiveness of interaction in the “man-machine” system and development of design technology. The developed concept of design ergonomics of automated information display systems can serve as a basis for the creation of more efficient control systems that provide improved interaction between man and machine, which helps to increase operator efficiency and improve the overall performance of automated control systems for special applications.

Управление устойчивым развитием предприятия с использованием инструментов социального инвестирования и «зелёных» финансов при реализации концепции социально-этического маркетинга

This work examines the implementation by commercial enterprises and organizations of the concept of sustainable development, which is so relevant at present, with the help of such innovative financial instruments as “green” financing and social investment; the possibility and effectiveness of their use in the practice of managing a commercial organization is substantiated. The purpose of the presented research is to determine the possibility and economic feasibility of using such financial instruments as “green” finance and social investment in the practice of managing a commercial organization. The object of the study is the EFKO group of companies (RF, Belgorod region) – one of the largest food companies in the Russian Federation, the subject is “green” finance and social investments as innovative financial instruments that ensure the sustainable development of a commercial organization and an indicator of its effective management. According to the results of the study, it was established that for 30 years the company under study has been carrying out effective commercial activities, while carrying out active social investment, the object of which is both the internal environment of the organization (personnel, internal infrastructure, etc.) and the external environment (active environmental management, development territories, charity, etc.), ensuring the implementation of the concept of sustainable development. At the same time, it has been established that against the backdrop of an increase in the volume of investments for the implementation of social goals and objectives, there is a positive trend in the main indicators of economic activity and basic financial indicators. The forecast of the main performance indicators of the Group of Companies also allows us to draw a conclusion about the feasibility of implementing social investment, in general, and “green” financing, in particular, since against the backdrop of growing investments in their implementation, the forecast is positive. Undoubtedly, the practice of “green” financing and social investment is a tool for creating and maintaining a positive image and business reputation of the company, which is confirmed by the high results of an independent rating assessment, which has a positive effect on the investment attractiveness of the company and its competitiveness, and allows for a permanent increase in operational efficiency.

Data-Driven Decision Making in Supply Chain Management

The importance of making decisions in supply chain management (SCM) based on data has grown significantly in recent years due to the quickly changing nature of the modern corporate environment. Within the scope of this abstract, the transformational influence of data analytics on supply chain management is investigated. Particular attention is paid to the ways in which data-driven strategies improve decision-making processes, increase operational efficiency, and boost competitive advantage. The coordination of a number of operations, including as distribution, manufacturing, inventory management, and procurement, is an essential part of supply chain management. In the past, these processes were handled by the use of intuition and facts from the past. But the introduction of sophisticated data analytics tools has completely changed the way that this approach is taken. Organisations are able to improve their operations, acquire deeper insights into the dynamics of their supply chains, and more correctly estimate demand when they make use of real-time data, predictive analytics, and machine learning algorithms.

Process reengineering using DMAIC framework for reduction of waiting time in daycare infusion therapy for better patient experience.

Daycare infusion therapy is an integral aspect of oncology, but increased waiting time raises concerns for patients. Patient-reported experience measures prompted the need to evaluate reasons for prolonged appointment delays. This study seeks to analyze and address patients' concerns, to streamline the process flow and reduce waiting time for daycare infusion therapy thereby enhancing patient experience. The define, measure, analyze, improve, and control methodology was implemented, and its impact on reducing waiting times was evaluated. The objective is to ensure that >85% of patients enter the daycare infusion unit within an hour of their appointment time in 6 months. The baseline data for patient waiting times was measured for a period of 2 months, and the average waiting time was determined. Potential causes contributing to prolonged waiting times were identified through time-motion analysis, with a fishbone diagram categorizing potential causes and a Pareto chart prioritizing them. Plan, do, study, and act cycles were conducted for implementing the changes, and a new process flow mapped. Baseline data showed 32% average adherence to the defined turnaround time of 1 hour, with an average waiting time of 108 minutes. Forty causes were identified for increased waiting time, of which eight were key. Adherence to waiting time turnaround time improved from 32% to 89% and the average waiting time decreased by 59 minutes from 108 minutes, increasing patient satisfaction index by 7.5%. The balancing measures include an increase in operational efficiency and throughput of the unit and the inventory levels of oncology medicine were decreased, leading to a 50% reduction in inventory value, while medication error declined by 0.62%, improving patient safety. The project gained tangible and intangible benefits impacting staff, patients, and relatives while improving operational efficiency. This study, with its scientific and systematic approach, enhanced patient satisfaction, patient safety, and better utilization of resources.

How RFID technology enables the supply chain and retail 4.0: A survey with Italian stakeholders

The research aims at assessing the level of interest towards and adoption of Radio Frequency IDentification (RFID) technology among a sample of manufacturers, retailers, logistic service providers, solution providers and vertically integrated fashion retailers belonging to the Fashion, Consumer Goods and Healthcare sectors in Italy. A survey was created in collaboration with GS1 Italy, a no-profit organization that develops standards for enhancing collaboration between companies, associations, institutions and consumers and enrols more than 40,000 companies. Overall, 58 useful responses were collected. Statistical analyses were carried out with the support of Statistical Package for the Social Sciences (SPSS) for Windows and MS Excel. Results show that RFID solutions are implemented by 31% of the interviewees and tested by 21% of them, mainly thanks to the favourable ROI and the possibility of gaining a competitive advantage over competitors through the automation of logistics processes, visibility of inventory and production progress, and avoided stock out. The RFID users often achieved results above expectations regarding the order picking errors reduction, the increase of operational efficiency and inventory accuracy. The few obstacles encountered are the read failures or the over-performing reading, but they are not perceived as relevant. Overall, most experimenters and non-users currently adopt barcode solutions, but showed their intention to implement RFID systems in the future, underlying a strong interest towards this identification technology.

Factor analysis of the external environment of foreign enterprises in the process of foreign economic activity

The article presents factor analysis factor analysis of the external environment of foreign enterprises in the process of foreign economic activity. The results show that an increase in operational efficiency increases the level of export indicators. In other words, if someone wants to make businesses competitive internationally, they need to expand their management capabilities. At the same time, the company must combine its abilities with market knowledge, creating a network at home and abroad if the company wants to achieve better results in foreign markets. In the course of the study, both general scientific and special methods were used, including the method of factor analysis and the graphical method. The method of mathematical analysis was used to systematize the factors that influence exports. Foreign economic activity explains to a limited extent the export behavior of companies in developing countries, where the business environment in which companies operate is unstable. Therefore, it is necessary to focus on external factors such as market dynamics and the institutional environment. This is because the efficiency of a firm is determined by the characteristics of its external environment, which is represented by the characteristics of its industry and the export market environment. The purpose of the article is to conduct a factor analysis of the external environment of foreign enterprises in the process of foreign economic activity It was found out that foreign economic activity is limited. This explains the export behavior of companies in developing countries, where the business conditions in which enterprises operate are unstable. Therefore, it is necessary to focus on external factors, such as market dynamics and the institutional environment. Because the effectiveness of a firm is determined by the characteristics of its external environment, which is represented by the characteristics of its industry and the environment of the export market.

Цифровізація банківського сервісу як стратегічний напрям розвитку для ощадних банків

Introduction. Digital means of expanding access to financial services are currently one of the promising tools for solving important socio-economic problems and stimulating economic development. The coronavirus pandemic gave a powerful impetus to the spread of digital banking. After the decline in morbidity and the relaxation of the quarantine, activity in the use of digital channels by customers of almost all segments has remained. Problem Statement. The relevance of the study is due to the global trend to replace the branch network with a remote service in order to reduce operating costs (increase operational efficiency) provided that customers' needs for reliable, fast and cheap services are met. The purpose is to determine the potential of digitalization of the delivery channels of banking products and services for savings banks in the conditions of the latest technologies and systemic stresses. Methods. The methodology of comparative analysis, system analysis, correlation of historical data, scientific synthesis was used. The research was conducted using the methods of statistical analysis of series dynamics and factor analysis of data. Content analysis was used in the review of scientific publications and reports. Results. In Ukraine, the introduction of digital financial technologies to expand access to banking services within the framework of remote banking technologies has both a number of achievements and many problems, the solution of which requires appropriate measures taken by state authorities. A positive thing is the rapid development of computer programs for the introduction of remote banking and their implementation in the work of state banks. The still relatively low share of remote service coverage for corporate and retail customers can be singled out as bottlenecks. Other significant problems include the slow implementation of legislative and regulatory initiatives in this area, in particular those defined in the framework of the Strategy for the Development of the Financial Sector. Conclusions. The analysis showed that Ukrainian banks differ significantly in the development of remote banking services (RBS), there is a gap between leaders and outsiders in the quality and scope of remote banking services. The leading positions of PrivatBank and Sens-Bank (in certain aspects) are largely due to the legacy of the period when they were in private ownership, but since then other commercial banks have made significant progress. In working out a development strategy, banks need to provide for regular surveys of the clientele and marketing analysis of situations and the latest trends in order to predict the behavior of customers and respond adequately to their needs and behavior patterns. At the same time, banks are already able to act proactively, educating and encouraging customers to use RBS channels. International and Ukrainian experience sometimes demonstrates failures in the implementation of RBS projects. Therefore, it is advisable to implement the concept of balanced development of all product delivery channels in the savings bank with an emphasis on remote customer service, introduce user training programs, and adapt application interfaces.

Principles of transport means maintenance optimization: equipment cost calculation

Purpose. Justification of principles and methodology for effective calculation of the equipment costs and optimization of transport means maintenance. Methodology. The results of the presented scientific research were obtained using general and special methods of cognition: abstract and logical analysis, systematization and combination, method of theoretical generalization, method of dialectical cognition, deduction and induction, and statistical analysis. This paper analyzes the relationship between the probability of failure prevention by the maintenance system and the associated costs. The research investigates how the variation in the technical condition change rate influences the length of the operation cycle and the rate of its decline. The study’s outcomes are analyzed, including the formation of points of minimum unit costs, the effect of spare parts’ cost, and the practical importance of the conclusions drawn. Findings. This paper outlines the economic methodology for determining the specific expenses of maintaining means of transport. The methodology considers the distribution of expenses for spare parts, labor, and other components. Using this methodology, it is possible to estimate the total costs of maintenance and make informed decisions about the efficient use of resources. It has been determined that the cost of spare parts impacts the efficiency of the maintenance system. Therefore, it is imperative to balance the cost for spare parts and safety, while considering the probability of failure. The method outlined in this work is versatile, which allows its adaptation and application to the specialized road transport. Originality. The paper further develops the methodological approach to calculating equipment costs for transport maintenance, which is used to improve service efficiency and reduce expenses. The approach enables a comprehensive evaluation of the outcomes of enhancing failure prevention probability through the maintenance system. It also aids in managing unused parts’ resources, particularly during short operating cycles. Practical value. The study’s findings can optimize the maintenance system, increase operational efficiency, and enhance the safety and reliability of means of transport, while reducing the costs associated with spare parts, labor, and other maintenance components. This approach aids in conserving resources, reducing operating costs, and is crucial for the financial stability and profitability of management companies.

Technological Progress and Cultural Change in Sharia Insurance: Impact and Challenges

The aim of the research is to find out how the impact and challenges of technological advances and cultural changes in Islamic insurance. This is because this paradigm shift not only affects the operations of insurance companies, but also permeates cultural elements in the industry. The researcher used a qualitative methodology. The data collection technique is sourced from books, related journals and the internet. The analysis method used was descriptive analysis. The results of his research state that technological advances, such as the use of artificial intelligence, big data, have shaped a new landscape in risk management and insurance services. Meanwhile, cultural changes in society also affect consumer preferences and norms surrounding Islamic insurance. In terms of impact, the increase in operational efficiency, personalization of services, and product innovations that arise thanks to the latest technology or in general the impact is becoming efficient, personalized, scalable and agile. However, challenges such as lack of capital, lack of professional human resources, cyber security risks, evolving regulations, and adaptation to cultural changes

Deep Learning-Enhanced Dual-Module Large-Throughput Microinjection System for Adherent Cells

Despite the rapid development in providing precise delivery of extraneous samples to the vast majority of cells, robotic microinjection is still hindered by cumbersome operations and low throughput in practice. This study presents a new automated microinjection system equipped with two micromanipulators and a deep learning algorithm for cell identification. The introduction of two coordinated micromanipulators based on the same cell handling platform results in a large increase in injection throughput. A deep convolutional neural network, Mask R-CNN, is used to detect and segment stain-free adherent cells, leading to a considerable increase in operational efficiency and subsequent throughput. In the three independent experiments, over 10,000 MC3T3 mouse fibroblast cells are injected to evaluate the injection speed, success rate, and survival rate. Experimental results confirm that our system can inject around 4,000 cells in 1 h with an approximately 60.3% success rate and an 82.0% survival rate. This research’s success will make robotic microinjection a competitive tool in many biomedical applications, such as plasmid DNA transfection. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation of this study is to improve the throughput of cell microinjection, which has become a bottleneck problem hindering the clinical application of microinjection technology. Existing cell microinjection systems typically use only one micromanipulator and rely on manual identification of cells, resulting in a limited ability to process cells for one experimental cycle. This study proposes a novel method that identifies cells through deep learning automatically and uses two micromanipulators simultaneously to improve cell processing capabilities. The problem of manipulating two micromanipulators for nearby cells is formulated as a route optimization problem, which is also suitable for three or more micromanipulators. A deep learning algorithm is used to identify and select cells to increase the processing speed. Experiments are performed to demonstrate that the proposed method can greatly increase the throughput while maintaining satisfactory performance in microinjection.

Digital Transformation and Innovation Strategies for Traditional Retail Stores

Due to the global pandemic and world economy recession, the passenger flow of the retail industry is still relatively weak. Many countries have strengthened measures to prevent and control the epidemic, and then temporarily closed their stores. This reminds businesses that COVID-19 is still an ongoing challenge. This paper aims to identify the possible digital solutions for traditional offline retail stores to embrace digital innovation to become more smart and efficient. This research theme is to explore the feasibility of introducing a digitized business model into traditional retail stores using JD sports as the case. Business Model Canvas is used to identify the existing business model of JD retail shops, while Innovation Ambition Matrix is designed for making the innovation plan. The latest business model is presented with the help of the Customer Journey Map. By implementing the model, JD's traditional retail shop will reduce labour costs and increase operational efficiency, strengthening its competitive advantages.