Time Schedule Research Articles

HCV Treatment Outcomes in PWID: Impact of Addiction History on SVR12

People who inject drugs (PWIDs) experience high rates of hepatitis C virus (HCV) infection, primarily due to needle sharing and limited healthcare access, resulting in a disproportionate disease burden within this population. This prospective study evaluated treatment outcomes in 432 adult patients with chronic hepatitis C (CHC) treated with direct-acting antivirals (DAAs) at the University Clinical Center of Serbia. Patients were categorized into two groups based on a history of drug addiction: PWIDs (163, 37.7%) and non-PWIDs (269, 62.3%). The PWID group was further categorized into subpopulations of problematic PWIDs (39, 23.9%), ex-PWIDs (124, 76.1%), and PWIDs on OST (96, 58.9%). The PWID group demonstrated significantly lower treatment adherence, with an intention-to-treat (ITT) rate of 82.8%, compared to 96.3% in the control group (p < 0.001). In contrast, no significant differences were observed in per-protocol (PP) outcomes between the two groups. Additionally, PWIDs were significantly younger (p < 0.001) and had higher rates of psychiatric disorders (p < 0.001), alcohol abuse (p < 0.001), and HCV genotype 1a (p < 0.001). Advanced fibrosis was predictor of PP treatment failure among PWIDs, while mood disorders and alcohol use disorder were associated with interruptions before the scheduled completion time. For non-PWIDs, older age and advanced fibrosis emerged as key predictors of PP treatment failure. The loss to follow-up was most commonly observed in the problematic PWID subgroup (p = 0.001). These findings highlight the importance of addressing barriers in PWIDs through integrated care strategies that concurrently manage addiction and HCV.

Standardization of myocardial protection: comment on "Cardiac surgery 2023 reviewed".

There have been few recent innovations since the introduction of cardioplegia more than 50 years ago. Surprisingly, cardioplegia as one of the most essential steps in terms of heart muscle protection during a surgical procedure requiring cardiac arrest has never been really standardized. As a consequence, a considerable variety of cardioplegic solutions and applications have developed: cold versus warm, crystalloid versus blood cardioplegia, antegrade versus retrograde or both, as well as different time schedules for repeated administration. A new cardioplegia solution, called CardioplexolTM, has recently received CE-market approval as a drug - following two phase III studies. CardioplexolTM shows several advantages: the administration follows a very simple protocol, minimizing the risk of errors in manipulation, diastolic arrest occurs immediately, thus allowing immediate begin of the cardiac work once the aorta has been cross clamped. The very low volume of crystalloid solution (e.g. 100 ml as induction and a second application of 100 ml following 45-60 minutes of ischemia), avoids hemodilution and therefore the need for filtration during surgery. In addition, the injection through the aortic root canula eliminates the need for an additional cardioplegia pump and its disposable tubing system. This simplified cardioplegia that is not inferior to Buckberg solution has the potential for standardization of myocardial protection protocols.

At-Home Self-Collection of Pharmacokinetic Data: Design and Results From a Phase 1 Open-Label Feasibility Trial.

Pharmacokinetic (PK) studies pose unique technical challenges. We present the design of a Phase 1, open-label, fixed-sequence, PK trial that aimed to compare the timing accuracy of participant- versus staff-collected data, and we provide safety and tolerability outcomes for centanafadine treatment. Healthy adults aged 18-55 years received a single 100-mg centanafadine sustained-release tablet at Visits 1, 2, and 4. PK samples (venous sampling and blood microsampling) and safety assessments (12-lead electrocardiograms [ECGs] and vital signs) were collected by clinical site staff only at Visit 1. At Visit 2, site staff collected venous blood, and participants obtained blood microsamples, a 6-lead ECG, and vital signs under staff supervision. At Visit 4, participants obtained blood microsamples, a 6-lead ECG, and vital signs remotely. The absolute differences between actual and scheduled collection times for PK samples, ECGs, and vital signs are reported descriptively. Of the 20 participants, at least 75% obtained blood microsamples within 10 minutes of the planned nominal time. Absolute differences between actual and scheduled collection times of ECGs and vital signs were small. No adverse events were related to treatment. Overall, results support the feasibility of at-home collection of PK samples, ECGs, and vital signs.

Optimising Outpatient Registration System Implementation Using Critical Path Method: A Case Study.

Today, hospital information systems (HISs) play an irreplaceable role in hospital management. At present, HIS construction projects in many hospitals have faced the setback of 'project quagmire' to varying degrees. The critical path method (CPM) mainly aims to find the critical path, thus managing project progress. To explore the importance and practical application of the CPM to the management of HIS project schedules. This study used the construction project of a hospital's outpatient registration subsystem as an example. CPM was used to determine the critical path. The time and workload required for the project were calculated using the forward and backward extrapolation methods. The earliest start time and earliest completion time as well as the latest start time and latest completion time of each task could be calculated using the forward and backward extrapolation methods. The path with the longest construction period was determined to be the critical path, and the unit speed rate of each activity was calculated on this basis. Then, the time schedule of the outpatient registration subsystem was compressed and the project schedule optimised. Path 3 [outpatient registration demand analysis (A)-basic data preparation (C)-subsystem test (F)-simulation test (G)] was determined to be the critical path according to the construction period, and the task time was compressed on this basis. Considering many factors, the time of the subsystem test task (F) was reduced from 7 weeks to 4 weeks. The total cost was saved by 1000 yuan, which not only ensured the progress ahead but also saved the overall cost. The CPM could effectively measure the completion and deviation of each stage of the registration system project, which provided an effective guarantee for the subsequent schedule compression to ensure that the project was completed as scheduled and was of sufficient quality. However, all conditions had to be considered comprehensively; doing otherwise would lead to increased risks and costs.

Predictability of Flight Arrival Times Using Bidirectional Long Short-Term Memory Recurrent Neural Network

The rapid growth in air traffic has led to increasing congestion at airports, creating bottlenecks that disrupt ground operations and compromise the efficiency of air traffic management (ATM). Ensuring the predictability of ground operations is vital for maintaining the sustainability of the ATM sector. Flight efficiency is closely tied to adherence to assigned airport arrival and departure slots, which helps minimize primary delays and prevents cascading reactionary delays. Significant deviations from scheduled arrival times—whether early or late—negatively impact airport operations and air traffic flow, often requiring the imposition of Air Traffic Flow Management (ATFM) regulations to accommodate demand fluctuations. This study leverages a data-driven machine learning approach to enhance the predictability of in-block and landing times. A Bidirectional Long Short-Term Memory (BiLSTM) neural network was trained using a dataset that integrates flight trajectories, meteorological conditions, and airport operations data. The model demonstrated high accuracy in predicting landing time deviations, achieving a Root-Mean-Square Error (RMSE) of 8.71 min and showing consistent performance across various long-haul flight profiles. In contrast, in-block time predictions exhibited greater variability, influenced by limited data on ground-level factors such as taxi-in delays and gate availability. The results highlight the potential of deep learning models to optimize airport resource allocation and improve operational planning. By accurately predicting landing times, this approach supports enhanced runway management and the better alignment of ground handling resources, reducing delays and increasing efficiency in high-traffic airport environments. These findings provide a foundation for developing predictive systems that improve airport operations and air traffic management, with benefits extending to both short- and long-haul flight operations.

ئAntiparasitic activity of Cerastes cerastes venom on Schistosoma mansoni infected mice‏

This study investigates whether Cerastes cerastes venom (CCV) administrated at different doses (3 and 6μg/mouse) and times (a week pre-infection, the first week post-infection, and the fifth week post-infection) possesses antischistosomal activity on Schistosoma mansoni infected mice. The results showed that treatment with half lethal dose (6 μg/mouse) of CCV, at various time schedules, led to a significant decrease in the total worm burden. However, quarter lethal dose (3μg/mouse) of CCV showed a significant decrease in the total worm burden only when administered a week pre-infection. The total number of deposited eggs by females of S. mansoni was significantly decreased in the liver and the intestine of mice treated with 3μg/mouse or 6μg/mouse CCV, associated with significant alterations in the oogram pattern with significant elevation in dead eggs levels and significant decrease in the number of mature eggs. Histological examinations illustrated a significant decrease in the number and diameter of hepatic granulomas in high dose (6μg/mouse) CCV-treated groups, while it was significant only a week pre-infection in low dose (3μg/mouse) CCV-treated groups. CCV also caused several tegumental changes in treated female and male worms, including loss of the normal surface architecture, tubercular destruction, loss of tubercles' spines, oedema, erosion, membrane blebbing, and swelling. S. mansoni-infected mice groups treated with CCV (6μg/mouse) a week before infection and at fifth week post-infection had, in all individuals up to a dilution of 1:1600, higher levels of antibodies against adult worm antigen. The current investigation found that C. cerastes venom has potential antischistosomal action in a time and dose-dependent manner (more enhanced antischistosomal effects at a dose of 6 μg and in the group treated in a week before infection), in addition to its potential immunomodulatory effect against schistosomiasis infection. More studies will be required to identify the venom's active ingredients that affect the host's immunology. This information could be used in the future to develop novel antischistosomal therapies.

A new data-driven production scheduling method based on digital twin for smart shop floors

As a mainstream means for solving smart shop floor production scheduling problems, the data-driven scheduling method has gained considerable attention in recent years. However, extant studies have primarily utilized physical shop floor data with limited quantity and quality to train scheduling models, which suffer from the drawbacks of long training time and poor scheduling performance. Therefore, this study proposes a new data-driven scheduling method based on digital twin for smart shop floors, which utilizes the data from physical shop floor and digital shop floor constructed by digital twin to train scheduling models. Specifically, in this method, a model-level data fusion mechanism is designed to achieve the fusion and complementary advantages of these two types of data, thus providing sufficient and high-quality data support for high-precision model training. Additionally, a multi-layer feedforward neural network with a generative adversarial network-based sample expansion mechanism is further integrated to efficiently generate scheduling decisions. Experiments in a semiconductor production shop floor are conducted to confirm the effectiveness of the proposed method.

IoT Assistive Technology for People with Disabilities

This project is dedicated to developing a Smart Medication Alert System utilizing Arduino and a variety of hardware components designed to improve medication adherence, particularly for individuals with disabilities. The system combines visual, auditory, and display-based notifications through LEDs, a buzzer, and an LCD screen, making it accessible to users with visual impairments or those managing complex medication schedules. With real-time tracking and user-specific reminders, the system will prompt users about scheduled medication times, notify them of missed doses, and provide dosage instructions if necessary. By streamlining the medication-taking process and reducing the risk of missed doses or errors, this system aims to foster greater independence, enhance the user's quality of life, and ultimately support improved health outcomes for those requiring regular medications.

Bus Schedule Time Prediction Based on LSTM-SVR Model

With the acceleration of urbanization, urban bus scheduling systems are facing unprecedented challenges. Traditional bus scheduling provides the original schedule time and the planned time of arrival at the destination, where the schedule time is the departure time of the bus. However, various factors encountered during the drive result in significant differences in the driving time of the bus. To ensure timely arrivals, the bus scheduling system has to rely on manual adjustments to optimize the schedule time to determine the actual departure time. In order to reduce the scheduling cost and align the schedule time closer to the actual departure time, this paper proposes a dynamic scheduling model, LSTM-SVR, which leverages the advantages of LSTM in capturing the time series features and the ability of SVR in dealing with nonlinear problems, especially its generalization ability in small datasets. Firstly, LSTM is used to efficiently capture features of multidimensional time series data and convert them into one-dimensional effective feature outputs. Secondly, SVR is used to train the nonlinear relationship between these one-dimensional features and the target variables. Thirdly, the one-dimensional time series features extracted from the test set are put into the generated nonlinear model for prediction to obtain the predicted schedule time. Finally, we validate the model using real data from an urban bus scheduling system. The experimental results show that the proposed hybrid LSTM-SVR model outperforms LSTM-BOA, SVR-BOA, and BiLSTM-SOA models in the accuracy of predicting bus schedule time, thus confirming the effectiveness and superior prediction performance of the model.

학교 축제와 연계한 중학교 학교자율시간 운영 방안의 시론적 탐색: 핵심프로젝트를 중심으로

Objectives This study explored a plan to operate a school festival that links core-projects of each subject in the 16+1 autonomous school hours system in middle school through the subject of ‘Planning a School Festival’. Methods We analyzed literature and previous studies on the organization and operation of school autonomous hours, cases of operating middle and high school festivals, and cases of operating domestic and international core-projects. Based on this, we examined the relationship between school festivals and core-projects in school autonomous hours, and discussed ways to operate school autonomous hours linked to school festivals. Results Firstly, the class schedule of school autonomous time linked to school festivals can be operated as a festival for the entire week or only part of the week. Secondly, a new subject called ‘Planning a School Festival’ can be opened in school autonomous time. Thirdly, the core project of school autonomous time linked to school festivals can be operated in various ways by subject. Conclusions Firstly, it provides a convergent educational experience. Secondly, cooperation and creativity are strengthened. Thirdly, connections with the local community are strengthened. Fourthly, various learning topics and activities are integrated.

Traffic Awareness-Based Target Wake Time Scheduling in 802.11ax WLANs

In recent years, the rapid growth of mobile communication has led to the continuous expansion of network scale, and the energy consumption of wireless communication has also increased rapidly. Under the high-density networking conditions, frequent communication activities greatly increase the energy consumption. In order to reduce channel competition, optimize resource scheduling and reduce equipment power consumption, the target wake-up time (TWT) mechanism in IEEE 802.11ax system plays an important role through timely scheduling and transmission. To improve channel efficiency for multi-user (MU) transmission and tackle with complicated traffic conditions, this paper presents a traffic awareness-based TWT scheduling scheme (TAT). The traffic is predicted and classified using a spatio-temporal series model for traffic-based TWT parameter generation. Subsequently, the time–frequency scheduling table is developed to adaptively assign Resource Units (RUs) and time slices to active STAs. Simulation results show that TAT can guarantee the Quality of Service (QoS) under dynamic changes in power service and delay requirements while reducing power consumption, effectively meeting the energy-saving demands in the intelligent access scenarios for power terminals.

HPB SO65 - An audit of the day-case rate of laparoscopic cholecystectomies at a busy district general hospital and factors affecting this

Abstract Background The target day case rate of laparoscopic cholecystectomies at a busy district general hospital is 75%, as per Model Hospital Guidelines. The current rate at which day cases are achieved is 55%. This audit aims to identify factors relating to the DGH not reaching their day case target and explore potential solutions for these, with the intention to reduce patient’s hospital stay and, therefore, overall costs. Method 119 patients had undergone a laparoscopic cholecystectomy in the first five months of 2024. Exclusion criteria included hot cholecystectomies, common bile duct explorations and planned admissions. The remaining 85 patients were included in this audit. The data proforma included age, ASA, BMI, co-morbidities, Nassar grade, scheduled and actual time of operation and any reasons for delay. Results Of the 85 patients included in this audit, 34% (29) were not daycases. 11 remained an inpatient due to post-operative nausea or pain, 3 due to requiring an MRCP, 9 were kept in for monitoring, 2 had intraoperative bleeding, 3 had social issues and 1 required IV antibiotics. 58% of the 29 had afternoon operations. 48% of the 29 had a Nassar grade of greater than 1. 38% of the 29 had a BMI greater than 30. Conclusion Various reasons for a case to not achieve daycase status were found, with the most common being post-operative pain or nausea. It would prove beneficial to educate patients on common post-operative symptoms and focus on managing these symptoms effectively. Pre-operative appointments should aim to explore a patients home setting at the time of the operation and ensure to book inpatient stays for those who require it, in advance. Theatre lists should be optimised by giving high-risk patients morning slots.

What's the Cost: Financial Toxicity and Screening Fatigue in Li-Fraumeni Syndrome.

Patients with Li-Fraumeni syndrome are recommended to follow a comprehensive surveillance protocol, but the demanding nature may limit adherence. We sought to identify barriers to adherence, and to determine whether screening fatigue and financial hardship are contributors. A 39-item online survey was developed and distributed to patients presenting to a LFS clinic between 2017 and 2022. Of the 39 patients eligible, 20 responded to the survey (51%). Of respondents, 75% reported they do not skip surveillance tests, though this was not consistent when asked about specific tests, with only 65% and 40% up to date with colonoscopy and esophagogastroduodenoscopy, respectively. 100% of those diagnosed within the last 5 years said they never skip tests, whereas only 50% of those diagnosed over 5 years ago reported the same (p=0.01). Barriers to adherence were reported by 85% and most commonly included finances (40%), time (25%), and difficulty scheduling (25%). Only 21% felt no financial stress. 63% worried at least somewhat about their future financial situation because of LFS. Even with insurance, 65% felt their share of healthcare costs was too high. Adherence to rigorous cancer surveillance is imperfect and decreases over time among patients with LFS. While number of tests was not a commonly cited barrier, time and difficulty scheduling were common and may contribute to screening fatigue. The degree of financial stress in the affluent population studied should raise even greater concern about financial strain in the LFS population in general.

Unlimited Employee Autonomy over Working Time? The Potentially Empty Notion of Autonomous Workers in EU law

Digital technology is often associated with greater working time autonomy: in theory at least, digitalisation can result in workplaces where employees are less subordinate to their employers in terms of working time. Article 17(1) of Directive 2003/88/EC on certain aspects of the organisation of working time acknowledges that certain working time measures do not apply in case of ‘autonomous workers’. However, the Court of Justice of the European Union has interpreted this exception strictly, excluding from its scope workers who enjoy only partial autonomy over their working time. The aim of this study is to explore whether the EU concept of autonomous worker meets practical requirements or needs to be amended. In section 2, I argue for a more permissive interpretation, as a predominantly autonomous schedule could still justify some flexibility as regards working time rules. This interpretation would also better fit the dual system of subordinated employees and self-employed workers who enjoy more flexibility in the determination of the working hours. Under section 3, the article explores the various methods that employers use to maintain control over the organisation of working time in non-standard work environments. Research shows that the combination of different controlling measures can ensure that employers have a decisive influence over the measure and schedule of working time, even in nominally flexible working arrangements. Consequently, while a broader understanding of the concept of autonomous workers is suggested, it shall be carefully assessed in each case whether the worker actually enjoys autonomy in respect of working time.

Implementation of a Mobile-Based Laundry Order Management System at Barack Laundry in Sleman

Barack Laundry is a laundry service business operating in Trini Sleman, a district in the Special Region of Yogyakarta. Laundry is an important household necessity, and many people are looking for trustworthy laundry service. Customer demand for laundry services continues to increase along with increasingly busy lifestyles. Although Barack Laundry's services continue to grow, there are still some problems faced by customers in the Trini Sleman area. One of the main problems is the lack of accessibility of information regarding service schedules, laundry status, and estimated costs. It is necessary to develop a mobile-based Barack Laundry application in Trini Sleman to overcome the problems that exist in Barack Laundry. The purpose of designing this mobile-based Barack Laundry application is to facilitate laundry management and customers so as to increase efficiency in the clothing ordering process. Apps can also extend the reach of laundry services to make them more accessible to customers. Features available on the app include a selection of clothing types and services with options such as washing, ironing, and both. The app also provides detailed booking information, scheduling of pick-up and drop-off times, and the option of online payment methods. The user-centered design method is used in this research by focusing on user needs. Kotlin programming language and MySQL database are also used in the process of developing this application. Based on the results of the research that has been done, it can be concluded that the mobile-based Barack Laundry application in Trini Sleman has successfully designed and implemented a mobile-based application for laundry ordering services in the region. This application has been carried out a black box testing process that has been carried out as many as 19 scenarios, with the final test results reaching 100%.

IMPLEMENTASI SENAYAN LIBRARY MANAGEMENT SYSTEM (SLIMS): STUDI PENELITIAN KUALITATIF

The aim of the research is to analyze the implementation of the Senayan Library Management System (SLiMS) at Madrasah Aliyah Negeri (Man) 2 Karawang. The method used is a qualitative method with a case study approach model and literature study in this research. The data collection used is the documentation method. The data sources for this research were obtained from relevant literature such as books, academic articles and journals related to the selected topic. The results of this research are the SLiMS planning, the Principal of MAN 2 Karawang makes a time schedule, namely in the form of programs that will be planned. Such as short-term programs, medium-term programs and long-term programs. Then in the recruitment system, staff are selected according to their skills, abilities, knowledge and strong will. The implementation of the Senayan Library Management System (SLiMS) activities at the MAN 2 Karawang library has been quite effective. Since 2019 MAN 2 Karawang has been using SLiMS in library services until now. Started making barcodes for two thousand curtilage books which were revised in 2017.

Employee Well-Being And Performance: The Role Of HR Practices

This study aims to elucidate the psychological determinants of resilience that promote employee well-being and examine their influence on improved performance to support organizational growth and attain competitive advantage. The study used descriptive research design and statistical quantitative data analysis, including snowball sampling and electronic questionnaires. The analysis reveals that HR practices are a key driver of both employee wellbeing and organizational performance, significantly contributing to these outcomes. The content variable shows weaker, non-significant relationships with both outcomes. In summary, HR practices significantly influence both employees' wellbeing and their performance, whereas the content variables show weaker and nonsignificant relationships. The findings of this study suggest that the changing work environment necessitates that the employees work relentlessly beyond their scheduled timings, experiencing challenging, demanding, and stressful situations

Fair and Efficient Ridesharing: A Dynamic Programming-based Relocation Approach

Recommending routes by their probability of having a rider has long been the goal of conventional route recommendation systems. While this maximizes the platform-specific criteria of efficiency, it results in sub-optimal outcomes with the disparity among the income of drivers who work for similar time frames. Pioneer studies on fairness in ridesharing platforms have focused on algorithms that match drivers and riders. However, these studies do not consider the time schedules of different riders sharing a ride in the ridesharing mode. To overcome this shortcoming, we present the first route recommendation system for ridesharing networks that explicitly considers fairness as an evaluation criterion. In particular, we design a routing mechanism that reduces the inequality among drivers and provides them with routes that have a similar probability of finding riders over a period of time. However, while optimizing fairness the efficiency of the platform should not be affected as both of these goals are important for the long-term sustainability of the system. In order to jointly optimize fairness and efficiency we consider repositioning drivers with low income to the areas that have a higher probability of finding riders in future. While applying driver repositioning, we design a future-aware policy and allocate the areas to the drivers considering the destination of requests in the corresponding area. Extensive simulations on real-world datasets of Washington DC and New York demonstrate superior performance by our proposed system in comparison to the existing baselines.

THE RELATIONSHIP BETWEEN ONLINE GAME ADDICTION WITH STUDENT LEARNING MOTIVATION AT SMPI MIFTAHUL JANNAH AND MTS NAHDLATUL NASYIIN IV PASANGGAR PEGANTENAN PAMEKASAN

Background: Rapid technological advances can change various aspects of everyday life, such as online gaming. Playing online games can foster curiosity and attract interest, and can even cause addiction that interferes with learning motivation. Objectives: This research aims to understand the correlation between addiction to playing online games and students' learning motivation at SMPI Miftahul Jannah and MTS Nahdlatul Nasyiin IV Pasanggar Pegantenan Pamekasan. Design: This research adopted a quantitative approach with correlational analysis methods and cross-sectional research, involving 60 students from SMPI Miftahul Jannah and MTS Nahdlatul Nasyiin IV using purposive sampling techniques. The data collection tool consists of questionnaires and data analysis is conducted using Spearman's rank correlation test. Results: This research found that the majority of respondents were addicted to playing online games at a high level, namely 37 respondents (61.7%). Meanwhile, most respondents had low-level learning motivation, and 37 respondents (61.7%). From the results of the Spearman Rank Test, a significant value of 0.000 (p < 0.05) was found with a correlation coefficient of -0.666, indicating a strong negative relationship between Addiction to Playing Online Games and Learning Motivation in students at SMPI Miftahul Jannah and MTS Nahdlatul Nasyiin IV in Pasangggar Pegantenan Pamekasan. Conclusion: Time management, schedules, supervision, family support, and healthy substitute activities are needed as a solution.

Heterogeneous system list scheduling algorithm based on improved optimistic cost matrix

In heterogeneous computing systems, efficient task-scheduling methods are paramount for enhancing computational performance. However, the existing algorithm exhibits certain deficiencies, notably its oversight of load balancing concerns and inadequate emphasis on the out-degree property of tasks. To address these issues, a novel list scheduling algorithm is proposed, Average Earliest Finish Time (AEFT), which proficiently allocates task flows onto heterogeneous processors. The AEFT algorithm primarily consists of two key stages: (1) prioritizing tasks to determine the distribution of task priorities and (2) assigning optimal processors for tasks with given priorities. By leveraging its specific topology, the AEFT algorithm minimizes the scheduling length of task flows. Simultaneously, a prediction mechanism in determining task prioritization and selecting processors stages is proposed to reduce the scheduling time of task flows. In addition, in the processor selection stage, AEFT algorithm considers the out-degree characteristics of tasks, ameliorating situations of processor load imbalance. The AEFT algorithm demonstrates superior performance compared to prior list scheduling algorithms concerning makespan, speedup, and the percentage of occurrences of better solutions, as evidenced by experiments conducted on randomly generated and real-application graphs. Specifically, for t tasks and p processors, the AEFT algorithm achieves a time complexity of O(t2p).