Programming System Research Articles

ANALYSIS AND DESIGN OF DIGITAL APPLICATION SYSTEMS FOR EMPLOYEE DATA MANAGEMENT IN XYZ STORE

As technology and information systems develop in the digital era, managing employee data has become very important for organizations and companies. An efficient and accurate employee data input process is the first step in managing human resources optimally. XYZ Shop is a shop located in the Banten area, which sells retail goods to end consumers, usually on a small scale and at home. The shop provides a variety of products, ranging from clothing, food, electronic goods, to household equipment. However, the XYZ store still faces challenges in managing employee data, such as limited time and human energy in carrying out this process because it is still manual. To overcome this problem, an employee data input program was designed to be an effective solution. With this program, the employee data management process can become more efficient, accurate and organized. The author used three techniques for data collection activities, namely observation, interviews and literature study. Development of an application program system for managing employee data at XYZ store using the PHP programming language and MySql database. The application system built is web-based, so it can be accessed easily anywhere and anytime. This provides immediate benefits in day-to-day operational efficiency, allowing human resources to focus on more strategic tasks. With the ability to manage employee data efficiently, stores can easily adapt to company growth, including branch expansion and increased employment

A national survey of medical staffs' required capability and workload for accelerator-based boron neutron capture therapy.

This study aimed to identify the required capabilities and workload of medical staff in accelerator-based boron neutron capture therapy (BNCT). From August to September 2022, a questionnaire related to the capabilities and workload in the accelerator-based BNCT was administered to 12 physicians, 7 medical physicists and 7 radiological technologists engaged in BNCT and 6 other medical physicists who were not engaged in BNCT to compare the results acquired by those engaged in BNCT. Only 6-21% of patients referred for BNCT received it. Furthermore, 30-75% of patients who received BNCT were treated at facilities located within their local district. The median required workload per treatment was 55h. Considering additional workloads for ineligible patients, the required workload reached ~1.2 times longer than those for only eligible patients' treatment. With respect to capabilities, discrepancies were observed in treatment planning, quality assurance and quality control, and commissioning between medical physicists and radiological technologists. Furthermore, the specialized skills required by medical physicists are impossible to acquire from the experience of conventional radiotherapies as physicians engaged in BNCT were specialized not only in radiation oncology, but also in other fields. This study indicated the required workload and staff capabilities for conducting accelerator-based BNCT considering actual clinical conditions. The workload required for BNCT depends on the occupation. It is necessary to establish an educational program and certification system for the skills required to safely and effectively provide BNCT to patients.

Programmable 2D materials through shape-controlled capillary forces

In recent years, self-assembly has emerged as a powerful tool for fabricating functional materials. Since self-assembly is fundamentally determined by the particle interactions in the system, if we can gain full control over these interactions, it would open the door for creating functional materials by design. In this paper, we exploit capillary interactions between colloidal particles at liquid interfaces to create two-dimensional (2D) materials where particle interactions and self-assembly can be fully programmed using particle shape alone. Specifically, we consider colloidal particles which are polygonal plates with homogeneous surface chemistry and undulating edges as this particle geometry gives us precise and independent control over both short-range hard-core repulsions and longer-range capillary interactions. To illustrate the immense potential provided by our system for programming self-assembly, we use minimum energy calculations and Monte Carlo simulations to show that polygonal plates with different in-plane shapes (hexagons, truncated triangles, triangles, squares) and edge undulations of different multipolar order (hexapolar, octopolar, dodecapolar) can be used to create a rich variety of 2D structures, including hexagonal close-packed, honeycomb, Kagome, and quasicrystal lattices. Since the required particle shapes can be readily fabricated experimentally, we can use our colloidal system to control the entire process chain for materials design, from initial design and fabrication of the building blocks, to final assembly of the emergent 2D material.

Automated phenotyping empowered by deep learning for genomic prediction of body size in the tiger pufferfish, Takifugu rubripes

Although genomic selection (GS) is accelerating the genetic improvement of economically important traits in aquaculture species, the accurate phenotyping of thousands of individuals remains a bottleneck in GS programs. Computer vision (CV) technologies with the assistance of deep learning may provide a cost-efficient solution for automated phenotyping of fish body size. In this study, we designed a CV-based automated phenotyping system based on the deep learning model Mask R-CNN (region-based convolutional neural networks) and tested its ability to predict standard length (SL) of tiger pufferfish (Takifugu rubripes) fed low fishmeal (LFM) diet. Simultaneously, we investigated the impact of the automated phenotyping on genetic parameter estimation and genomic prediction for growth-related traits. We raised a test population (n = 1001) that was fed the LFM diet from three months old until harvest at 22 months. Manual phenotyping of the fish was performed at 10-, 14-, 17-, and 22-months-old. At the last two measurement times, images of each fish were collected to train Mask R-CNN for fish detection and pixel-level segmentation of the fish body excluding the tail fin. An automated phenotyping pipeline combining the trained Mask R-CNN and standard CV algorithms were designed to estimate SL. We found a high correlation (0.965–0.971) and low relative difference (0.015–0.027) between the CV-derived and manually measured SL, indicating high precision of our CV system. A high correlation (0.912–0.956) was also observed between CV-derived body area and manual body weight. The heritability estimations and genomic predictions on manual SLs were conducted using a Genomic Best Linear Unbiased Prediction (GBLUP) model using a total of 16,471 single nucleotide polymorphism (SNP). Estimated heritability at the four sampling points ranged from 0.573 to 0.622, and the predictive ability of genomic prediction for harvest size was 0.627. These values are comparable to those reported in previous studies collected from the population fed a normal fishmeal diet. Our heritability estimation and genomic prediction derived from automated SL measurements differed negligibly to those based on manual measurements. This finding indicates the utility of our CV-based automated phenotyping system for GS breeding programs.

Integrating capability index and generalized rule-switching mechanism for enhanced quick-switch sampling systems

Variables Quick-Switch Sampling Systems (VQSSs) that involve both normal and tightened inspections for lot dispositions have attracted significant attention and discussion. However, existing VQSS models exhibit limitations, particularly in their rule-switching mechanism. Practitioners may encounter situations where multiple rounds of tightened inspection are necessary to ensure submission quality when suspicions of process degradation arise. Current VQSS models do not effectively address this need. To overcome this limitation, we present VQSSG by integrating a VQSS with a generalized rule-switching mechanism and the widely used capability index Cpk. VQSSG offers practitioners the flexibility to specify the number of successive lot acceptances under tightened inspection before transitioning to normal inspection. Our research includes the derivation of operating characteristics and average sample number functions for VQSSG, based on the Cpk index. Through in-depth investigations, we construct nonlinear optimisation models to determine the optimal system design and identify distinct types and settings for VQSSG, highlighting its strengths and weaknesses. Additionally, we provide managerial insights and recommendations for the effective implementation and application of VQSSG. To validate the practicality of this system, an industrial case study is presented. This paper significantly enhances the efficiency and adaptability of sampling systems by introducing VQSSG. The findings and managerial suggestions contribute to a deeper understanding of potential real-world applications, thereby enhancing quality control and decision-making processes.

Single‐stage single‐phase multiport DC–AC inverter suitable for standalone applications due to its notable performance in different operation modes

AbstractA new multiport DC–AC converter is proposed for standalone and off‐grid tied applications. The configuration converts power from DC to AC form in a single stage with suitable voltage gain. To increase the certainty of supporting power, the converter is designed to operate in four modes, including battery‐alone mode. The other advantage of the presented work is supplying the output power during unbalanced voltage conditions of the input ports. The advanced features of the converter for being used in standalone applications are related to the suitable placement and structure of the bidirectional port. In addition, the configuration is designed in a way to contain appropriate structural properties such as the existence of a common ground between the DC section and inverter, continuity of input currents, configured by an acceptable number of components, and low‐voltage stress on the DC–DC section's switches. Furthermore, it has an impedance network to protect the inverter's switches in a shoot‐through state. To confirm the converter advantages from the mentioned points of view, it has been compared with similar configurations. A prototype rated at 110 V is prepared to demonstrate the advantages of the converter performance per different conditions. The results of the steady‐state and transient experiments validate the suitability of the presented converter.

Navigating techniques in job recommender systems on internship profile matching: a systematic review

PurposeThis review article is focused on the following research questions: RQ1: What are the methods used by authors to collect data in order to evaluate one's profile? RQ2: What are the classification algorithms and ranking metrics used to give suggestions to users? RQ3: How effective are these algorithms and metrics identified in RQ2?Design/methodology/approachThere are four major systematic review phases being carried out in this survey, namely the formulation of research questions, conducting the review, which includes the selection of articles and appraising evidence quality, data extraction and narrative data synthesis.FindingsCollecting from primary sources is more personalized and relevant. Embedded skill sets that have a considerable impact on one’s career aspirations could be mined from secondary sources. A hybrid recommender system helped mitigate the limitations of both. The effectiveness of the models depends not only rely on the filtering techniques used but also on the metrics used to measure similarity and the frequency of words or phrases used in a document.Research limitations/implicationsThe study benefits internship program coordinators of a university aiming to develop a recommender or matching system platform for their students. The content of the study may shed a light on how university decision-makers can explore options on what are the techniques or algorithms to be integrated. One of the advantages of internship or industrial training programs is that they would help students align them with their career goals. Research studies have discussed other RS filtering techniques apart from the three major filtering techniques.Practical implicationsThe outcome of the study, which is a recommendation system to match a student's profile with the knowledge and skills being sought by organizations, may help ease the challenges encountered by both parties. The study benefits internship coordinators of a university who are planning to create a recommendation system, an innovative project to be used in teaching and learning.Social implicationsInternship programs can help a student grow personally and professionally. A university student looking for internship opportunities can find it a daunting task to undertake, as there is a vast pool of opportunities offered in the market. The confidence levels needed to match their knowledge, skills and career goals with the job descriptions (JDs) could be challenging. The same holds with companies, as finding the right people for the right job is a tough endeavor. The main objective of conducting this study is to identify models implemented in recommendation systems to give and/or rank suggestions given to users.Originality/valueWhile surveys regarding recommender systems (RS) exist, there are gaps in the presentation of various data collection methods and the comparison of recommendation filtering techniques used for both primary and secondary sources of data. Most recommendation systems for internship programs are intended for European universities and not much for Southeast Asia. There are also a limited number of comparative studies or systematic review articles related to recommendation systems for internship programs offered in an Southeast Asian landscape. Systematic reviews on the usability of the proposed recommendation systems are also limited. The study presents reviews of articles, from data collection and techniques used to the usability of the proposed recommendation systems, which were presented in the articles being studied.

Effects of a Pharmacist-Designed Clinical Decision Support System on Antimicrobial Stewardship.

Clinical decision support systems (CDSSs) are computer applications, which can be applied to give guidance to practitioners in antimicrobial stewardship (AS) activities; however, further information is needed for their optimal use. Our objective was to analyze the implementation of a CDSS program in a second-level hospital, describing alerts, recommendations, and the effects on consumption and clinical outcomes. In October 2020, a pharmacist-driven CDSS designed for AS was implemented in a second-level hospital. The program provides a list of alerts related to antimicrobial treatment and microbiology, which were automatized for revision by the AS professionals. To analyze the implementation of the CDSS, a pre-post-intervention, retrospective study was designed. AS-triggered alerts and recommendations (total number and rate of acceptance) were compiled. The effect of the CDSS was measured using antimicrobial consumption, duration of antimicrobial treatments, in-hospital mortality, and length of stay (LOS) for patients admitted for infectious causes. The AS team revised a total of 7,543 alerts and 772 patients had at least one recommendation, with an acceptance rate of 79.3%. Antimicrobial consumption decreased from 691.1 to 656.8 defined daily doses (DDD)/1,000 beds-month (p = 0.04) and the duration of antimicrobial treatment from 3.6 to 3.3 days (p < 0.01). In-hospital mortality decreased from 6.6 to 6.2% (p = 0.46) and mean LOS from 7.2 to 6.2 days (p < 0.01). The implementation of a CDSS resulted in a significant reduction of antimicrobial DDD, duration of antimicrobial treatments, and hospital LOS. There was no significant difference in mortality.

Disease intervention specialist-delivered interventions and other partner services for HIV and sexually transmitted infections: A systematic review.

Disease intervention specialists (DIS) are critical for delivering partner services programs that provide partner notification, counseling, referral, and other services for HIV, sexually transmitted infections (STIs), and other infections. This systematic review of partner services and other DIS-delivered interventions for HIV and STIs was conducted to summarize the effectiveness of these programs and identify evidence gaps. A systematic literature review was conducted with a narrative synthesis. Articles were located using keyword searches in MEDLINE, Web of Science, CINAHL, and ProQuest through December 2022 and analyzed in 2023-2024. Included studies addressed an intervention of partner services or other DIS-delivered services for HIV or STIs; a United States setting; primary data collection; and an external comparison group or pre-post design. 1,915 unique records were screened for eligibility, with 30 studies included. Overall, DIS-delivered interventions improved clinical outcomes among index patients and population outcomes. Many studies focused on program process measures rather than population-level epidemiologic outcomes. All but one studies were scored as having low or medium strength of evidence. The evidence could be strengthened by establishing a streamlined set of core metrics, assessing impact using rigorous causal inference methodologies, linking program and clinical data systems, and supplementing impact evaluations with evidence on implementation strategies.

Identifying an acceptable number of ambulatory blood pressure measurements for accuracy of average blood pressure and nocturnal dipping status.

We aimed to identify the minimum number of ambulatory blood pressure (ABP) measures to accurately determine daytime and nighttime systolic blood pressure (BP) averages and nocturnal dipping status (i.e., relative daytime:nighttime change). A total of 43 midlife participants wore an ABP monitor for 24 h with measurements every 20/30 min during the daytime/nighttime, as identified by a sleep diary. We calculated daytime/nighttime systolic BP average and dipping status from all available measurements per participant (i.e., normative data). We then calculated daytime and nighttime BP per participant based on a random selection of 8-20 and 4-10 measurements and replicated random selections 1,000 times. We calculated accuracy by checking the proportion from 1,000 different randomly selected samples for a particular number of measurements that systolic BP was ±5 mmHg of normative data, and dipping status remained unchanged for each participant compared with the normative value. The best fit for the regression model estimated the minimal number of measurements for an accuracy of 95% in BP averages. For a 95% accuracy in estimating daytime and nighttime systolic BP, 11 daytime and 8 nighttime measurements were required. The highest accuracy for dipping status was 91.6 ± 13.4% using 20 daytime and 10 nighttime measures, while the lowest was (83.4 ± 15.1%) using 8 daytime and 4 nighttime measures. In midlife adults, 11 daytime and 8 nighttime measurements are likely enough to calculate average systolic BPs accurately. However, no minimum number is suggested to accurately calculate dipping status.NEW & NOTEWORTHY We found that a minimum of 11 blood pressure (BP) measures are necessary to calculate an accurate average daytime BP, and 8 nighttime measures are necessary to calculate an accurate nighttime average if 95% accuracy is acceptable. Regarding BP dipping status, the current recommendations (20 daytime/7 nighttime) inaccurately classified the dipping status 10.5% of the time, suggesting that guidelines may need to be updated to classify patients as nocturnal dippers or nondippers correctly.

The Role of Reciprocated Friendships in the Behavioral Correlates of Sociometric Categories

Children live complex social lives that has various aspects, including intimate friendships, peer-acceptance and bullying dynamics which is usually studied separately in research. This study aims to investigate the interplays of these three important fields by analyzing the moderating effects of number of friendships on the relation between sociometric categories and behavioral correlates via moderated logistic regression models. Participants were 291 elementary school students from schools located in Budapest, Hungary. Computerized peer-nominations were used to assess number of mutual friendships, behavioral variables, peer acceptance and bullying-roles. Results suggest that in a few cases, number of mutual friendships may have an effect on the relationship analyzed. Questions of limited and unlimited nomination based friendship questions are discussed. The results may facilitate further studies in the direction of more refined logistic regressions and has implications on bullying diagnostics and offers an electronic assessment tool for practitioners.

Development of Standalone Extended-Reality-Supported Interactive Industrial Robot Programming System

Extended reality (XR) is one of the most important technologies in developing a new generation of human–machine interfaces (HMIs). In this study, the design and implementation of a standalone interactive XR-supported industrial robot programming system using the Unity game engine is presented. The presented research aims to achieve a cross-platform solution that enables novel tools for robot programming, trajectory validation, and robot programming debugging within an extended reality environment. From a robotics perspective, key design tasks include modeling in the Unity environment based on robot CAD models and control design, which include inverse kinematics solution, trajectory planner development, and motion controller set-up. Furthermore, the integration of real-time vision, touchscreen interaction, and AR/VR headset interaction are involved within the overall system development. A comprehensive approach to integrating Unity with established industrial robot modeling conventions and control strategies is presented. The proposed modeling, control, and programming concepts, procedures, and algorithms are verified using a 6DoF robot with revolute joints. The benefits and challenges of using a standalone XR-supported interactive industrial robot programming system compared to integrated Unity–robotics development frameworks are discussed.

On the Generalisation Performance of Geometric Semantic Genetic Programming for Boolean Functions: Learning Block Mutations

In this paper we present the first rigorous theoretical analysis of the generalisation performance of a Geometric Semantic Genetic Programming (GSGP) system. More specifically, we consider a hill-climber using the GSGP Fixed Block Mutation (FBM) operator for the domain of Boolean functions. We prove that the algorithm cannot evolve Boolean conjunctions of arbitrary size that are correct on unseen inputs chosen uniformly at random from the complete truth table i.e., it generalises poorly. Two algorithms based on the Varying Block Mutation (VBM) operator are proposed and analysed to address the issue. We rigorously prove that under the uniform distribution the first one can efficiently evolve any Boolean function of constant size with respect to the number of available variables, while the second one can efficiently evolve general conjunctions or disjunctions of any size without requiring prior knowledge of the target function class. An experimental analysis confirms the theoretical insights for realistic problem sizes and indicates the superiority of the proposed operators also for small parity functions not explicitly covered by the theory.

Implementation of Integrated Development Environment for Machine Vision-Based IEC 61131-3

IEC 61131-3 is an international standard for developing standardized software for automation and control systems. Machine vision systems are a prominent technology in the field of computer vision and are widely used in various industries, such as manufacturing, robotics, healthcare, and automotive, and are often combined with AI technologies. In industrial automation systems, software developed for defect detection or product classification typically involves separate systems for automation and machine vision programs, leading to increased system complexity and unnecessary resource wastage. To address these limitations, this study proposes an IEC 61131-3-based integrated development environment for programmable machine vision. We selected 11 APIs commonly used in machine vision systems, evaluated their functions in an IEC 61131-3 compliant development environment, and measured the performance of representative machine vision applications. This approach demonstrates the feasibility of developing PLC and machine vision programs within a single-controller system. We investigated the impact of controller performance on function execution.

Perceived Competencies and Training Needs of Public Health Nurses in the Philippines: Basis for the Development of NurseLEAD: A Leadership Course on Advanced Practice Nursing in Public Health.

Public health nurses (PHNs) perform more than the provision of direct care to clients. They are also expected to perform roles as leaders, managers, and collaborators in different settings, especially in areas where there are no physicians. Their continuous professional development must be facilitated to empower them to lead the delivery of health programs and services in pursuit of universal healthcare. This study aims to determine the perceived competencies of public health nurses and describe their training needs. A descriptive, cross-sectional study was utilized, where an online survey was administered to PHNs across the Philippines to determine their self-perceived competencies and training needs based on the eight domains of core competencies of public health professionals. Descriptive statistics was used to summarize the data. A total of 330 PHNs answered the survey. The results showed that at baseline, PHNs perceived themselves to be competent (from most to least) in the following: communication, analytical/assessment, community dimensions of practice, policy development/ program planning, leadership and systems thinking, cultural competency skills, public health science, and financial planning and management. In terms of training needs, the enablers mentioned include a supportive work environment that can provide a work schedule that is inclusive of time for professional development and work-life balance; a learning environment where colleagues and supervisors support the need for training and innovation; strong internet connection; and enough equipment to participate and submit deliverables for courses taken. Filipino public health nurses perceived themselves to be competent in the areas of communication and community practice, but less competent in public health science, and financial planning and management. Future capacity-building programs must be designed to meet this demand. Furthermore, to make training programs truly responsive to the needs of nurses, steps must be taken to promote capacity-building enablers.

ISAND: AN INFORMATION SYSTEM FOR SCIENTIFIC ACTIVITY ANALYSIS (IN THE FIELD OF CONTROL THEORY AND ITS APPLICATIONS)

This paper describes the approaches underlying ISAND, an information system for scientific activity analysis in the field of control theory and its applications. ISAND is being developed at the Trapeznikov Institute of Control Sciences, the Russian Academy of Sciences. The ISAND ontology is oriented toward the representation and collection of knowledge in the field of control theory and its applications, namely, scientific knowledge (the ontology of control theory) and knowledge related to the scientific activity of agents (organizations, journals, conferences, and individual researchers) in this field. Based on this ontology, the ISAND architecture is a complex program system to collect, store, and analyze publications and their metadata from external sources. The ISAND algorithm for building the thematic profiles of scientific objects (publications, researchers, organizations, journals, and conferences), as well as ISAND text processing and network analysis capabilities, are presented. Finally, the main possibilities of using ISAND are considered.

What Every Colorectal Surgeon Should Know About the Updated Medicare Access and Children's Healthcare Insurance Program Reauthorization Act and the Merit-Based Incentive Program System Legislation.

What Every Colorectal Surgeon Should Know About the Updated Medicare Access and Children's Healthcare Insurance Program Reauthorization Act and the Merit-Based Incentive Program System Legislation.

Application of regression and remote sensing technology for determining sufficiency of contact-based sensors in long-term SHM of civil structures

Long-span bridges are huge, complex, and vital civil engineering structures for every society. Due to the critical importance of such structures, structural health monitoring (SHM) systems utilizing both contact and non-contact sensor platforms are often considered to measure influential parameters, such as environmental/operational factors and various structural responses. In some circumstances, such as bridge locations, services, weather conditions, harsh environments, and budget constraints, it may not be practical or necessary to utilize all possible sensor systems and measure all parameters, especially environmental/operational (E/O) factors. To devise and implement an affordable SHM program for large-scale civil structures, it is necessary to develop more efficient sensing systems compared to state-of-the-art ones. Against this backdrop, this paper proposes a new methodology for verifying the sufficiency of contact-based E/O sensors installed in long-span bridges using spaceborne remote sensing and regression modeling. The main premise of the proposed methodology is that structural responses obtained from certain remote sensing products enable us to assess the sufficiency of contact sensors and the impacts of both measured and unmeasured E/O conditions. Utilizing structural displacement responses from remote sensing and measured E/O data from contact-based sensors, a supervised regression model using a feedforward artificial neural network is developed to reconstruct or predict displacement responses and to determine the regression accuracy using the R-squared measure. When the accuracy rate is high, one can infer that the contact-based E/O sensors are sufficient; otherwise, it may be essential to install additional E/O sensors and apply the proposed methodology with new information. Real-world long-span bridges are examined to validate the proposed methodology, using displacement responses and recorded temperature data from contact-based thermocouples. The results demonstrate that the methodology offers an effective but affordable system for long-term SHM programs.

Challenges and paradoxes in the regulation of scientific research in the EU: a comprehensive analysis

This article analyzes the legal regulation of scientific research in European Union law, examining the challenges and paradoxes the EU faces in this area. Through a systematic analysis of normative and programmatic documents, the crucial influence of EU law on shaping international scientific research standards is revealed. The study highlights the evolution of the European Research Area and the fundamental role of the Horizon Europe program in promoting scientific excellence and innovation. The findings have significant implications for EU research policy and its international cooperation in science and technology." The author applies a complex methodology including analysis and synthesis, structural, formal-legal methods, as well as approaches of scientific deduction and induction. The author argues that EU law has a significant impact on the development of international standards for scientific activity. Despite the absence of imperative supranational competence in the field of science, the EU has facilitated the formation of subsidiary mechanisms for funding and supporting scientific activity, leading to the establishment of sustainable institutions and mechanisms within the European Research Area and EU program systems such as “Horizon Europe”, which has resulted in a substantial evolution of standards for scientific activity. The author states that this primarily concerns scientific ethics, multiculturalism and non-discrimination, the evolution of views on transnational research, and the formation of a sustainable regime for funding and evaluating scientific projects.

Impact of Technology on Human Resources in Marine Logistics

Technology has significantly changed the landscape of the ocean logistics industry, affecting the roles, responsibilities, and skill needs of human resources. This research aims to explore the impact of technologies such as automation, digitalization, and information systems on human resources in ocean logistics. Through a qualitative and quantitative approach that includes a literature review, online surveys, and in-depth interviews, key findings reveal a shift in worker roles towards automation system oversight, data analysis, and strategic decision-making. New skills such as programming, data analytics, and understanding automation systems are becoming crucial. However, the industry faces challenges in recruiting a workforce with the required skills and resistance from workers to change. Strategies such as extensive training programs, collaboration with educational institutions, and effective change management help integrate technology with human resources. Technology adoption also drives changes in organizational structures and work cultures that are more collaborative and data-oriented. This research provides important insights for companies and policymakers in developing strategies to prepare a competent marine logistics workforce for digital transformation.