Actual Completion Time Research Articles

Radial Basis Function (RBF) and Multilayer Perceptron (MLP) Comparative Analysis on Building Renovation Cost Estimation: The Case of Greece

Renovation of buildings has become a major area of development for the construction industry. In the building construction sector, generating a precise and trustworthy cost estimate before building begins is the greatest challenge. Emphasizing the value of using ANN models to forecast the total cost of a building renovation project is the ultimate objective. As a result, building firms may be able to avoid financial losses as long as there is as little discrepancy between projected and actual costs for remodeling works in progress. To address the gap in the research, Greek contractors specializing in building renovations provided a sizable dataset of real project cost data. To build cost prediction ANNs, the collected data had to be organized, assessed, and appropriately encoded. The network was developed, trained, and tested using IBM SPSS Statistics software 28.0.0.0. The dependent variable is the final cost. The independent variables are initial cost, estimated completion time, actual completion time, delay time, initial and final demolition-drainage costs, cost of expenses, initial and final plumbing costs, initial and final heating costs, initial and final electrical costs, initial and final masonry costs, initial and final construction costs of plasterboard construction, initial and final cost of bathrooms, initial and final cost of flooring, initial and final cost of frames, initial and final cost of doors, initial and final cost of paint, and initial and final cost of kitchen construction. The first procedure that was employed was the radial basis function (RBF). The efficiency of the RBFNN model was evaluated and analyzed during training and testing, with up to 6% sum of squares error and nearly 0% relative error in the training sample, which accounted for roughly 70% of the total sample. The second procedure implemented was the method called the multi-layer perceptron (MLP). The efficiency of the MLPNN model was assessed and examined during training and testing; the training sample, which made up around 70% of the overall sample, had a relative error of 0–7% and a sum of squares error ranging from 1% to 5%, confirming specifically the efficacy of RBFNN in calculating the overall cost of renovations.

Abstract PO5-17-03: Relative Dose Intensity and Protraction of Neoadjuvant Chemotherapy in Early-Stage and Locally Advanced Breast Cancer: A collaborative multicenter analysis in Colombia

Abstract Introduction: Breast cancer (BC) is the most frequent neoplasm in Colombia. In contrast to high-income countries, the expected 5-year overall survival (OS) remains below 80% over the last years. Neoadjuvant chemotherapy (NACT) has reduced the risk of relapse and death by achieving higher pathological complete response (ypCR) rates, but delays and dose reductions could impact prognosis negatively. We have previously reported the outcomes of NACT from a real-world multicenter historical cohort of Colombian early and locally advanced BC patients. We aimed to analyze NACTRelative Dose Intensity (RDI) and protraction data as related to clinical outcomes in the same cohort. Methods: We performed a secondary analysis of the primary database of 312 BC patients treated with NACT where ypCR rate was 34·6%, with 88·2% 5-year OS. We considered RDI and protraction as independent variables for the same outcomes. The RDI was estimated using the Hrynuik method, and protraction was defined as the difference between planned and actual completion time for the NACT exceeding 7 days from standard 21-day cycles. Chemotherapy regimens are based on the National Hematology and Oncology Association (ACHO) guidelines. We excluded cases with missing or conflicting data. Univariate, and bivariate analysis, and partition survival trees were performed to examine variable interactions. Results: From the original cohort of 312 patients, 47 and 7 additional patients were excluded due to missing protraction and RDI data, respectively; the final analysis included 261 and 254 patients, respectively. The average days to complete planned chemotherapy cycles were 154,4 (SD 32,29 days). 203 patients (77,8%), 26 patients (10%), and 11 patients (4,2%) received complete 8,7 and 6 NACT cycles, respectively. Overall, 175 patients (67%) had protracted chemotherapy cycles, being highest in the 7-cycle subgroup (77%). 169 patients (66,5%) had a dose intensity over 85% and 90 patients (35.43%) achieved an RDI of 100% or more. The mean RDI for the cohort was 79,8% (SD 19,91%) and it differed according to expression profile subgroups in decreasing order as follows: HER2 pure 98,85% (SD 19,59%), Luminal A 96,03% (SD 21,28%), Triple Negative 97,81% (SD 19,73%), Luminal B HER+ and HER2- being lowest with 90,43% (SD 19,47%) and 87,75% (SD 23,22%), respectively. Neither NACT RDI nor protraction was associated significantly with ypCR, conservative surgery, or all-cause OS. Although statistically not-significant, sensitivity analysis through different RDI thresholds (20%-100%) demonstrated improved discriminatory capacity over ypCR for RDI >= 85%. Conclusion: On average, NACT-RDI greater than 85% was observed in Colombian patients with early and locally advanced BC similar to other cohorts. However, it was not associated with ypCR, conservative surgery, or OS. Also, NACT protraction beyond 7 days did not adversely affect clinical outcomes. However, this conclusion is limited due to the retrospective nature and loss of real-world data. Adverse events and their impact on RDI were not analyzed either. Further research is warranted to understand RDI's impact on clinical outcomes, and a large-scale trial is proposed to validate these findings. Citation Format: Alejandro Murillo, Andres Acevedo, Santiago Betancur, Mariana Borras-Osorio, Isabel Munevar, William Mantilla, Luis Pino. Relative Dose Intensity and Protraction of Neoadjuvant Chemotherapy in Early-Stage and Locally Advanced Breast Cancer: A collaborative multicenter analysis in Colombia [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-17-03.

Resource Scheduling Optimisation Study Considering Both Supply and Demand Sides of Services under Cloud Manufacturing

In cloud manufacturing environments, the scheduling of multi-user manufacturing tasks often fails to consider the impact of service supply on resource allocation. This study addresses this gap by proposing a bi-objective multi-user multi-task scheduling model aimed at simultaneously minimising workload and maximising customer satisfaction. To accurately capture customer satisfaction, a novel comprehensive rating index is introduced, integrating the actual completion cost, time, and processing quality against customer expectations. Furthermore, vehicle constraints are incorporated into the model to accommodate potential delays in transport vehicle availability, thereby enhancing its alignment with real-world manufacturing settings. The proposed mathematical model is solved using an improved three-stage genetic algorithm, which integrates the k-means algorithm and a real-time sequence scheduling strategy to optimise solution quality. Validation against alternative algorithms across various case scales demonstrates the efficacy of the approach in providing practical scheduling solutions for real-case scenarios.

Genetic Algorithm Based on Opposite Chromosome Multiple Genetic Operations Combined with Task Load Balancing

A collaborative optimization method for task allocation and path planning in multi-UAV execution of multi-objective cooperative inspection tasks is proposed. The method is based on the Opposite Genetic Algorithms (OGA), which combines the actual task completion time with the balance of UAV inspection flight time, fault downtime, and maximum-minimum time load. A Task Balancing Opposite Chromosome Multiple Mutation Operator Genetic Algorithm (TOMGA) is introduced to solve the task load balancing problem by optimizing the task allocation among multiple UAVs with time as the optimization objective. Simulation results demonstrate that, this algorithm can effectively allocate inspection tasks to UAVs and generate initial flight routes. It resolves the issue of task load imbalance, improves the rationality of task allocation, enhances convergence speed, and overcomes the problem of local optima.

Network Analysis on Phase 1B Building of the University Health Centre, FUTA, using Critical Path Method (CPM) and Program Evaluation Review Technique (PERT)

Project planning and scheduling plays a vital role in estimating the time and cost angle of a project. Finalizing a project on time and within the budget is challenging. This study focused on finding the shortest possible time required to complete the phase 1B Building project of the University Health Centre, FUTA and also to evaluate the probability of completing the project within the stipulated time. This project work has been able to give a concise view about network analysis in building construction; definitions of some terms commonly used in network analysis was also stated. Also, an introduction to CPM and PERT was stated; assumptions of CPM, advantages and disadvantages of CPM were stated; assumptions, advantages and disadvantages of PERT were also stated. Data analysis was carried out and all the possible routes of the activities involved in the building project were found; the location of the critical path of the building project was also found; the expected duration for every activity in the building project was determined; the probability of completing the project within the stipulated time was also evaluated. The results showed that there is a 50% chance for the project to be completed within the stipulated time. With the information gathered on the building project, the project was delayed due to some factors such as low circulation of money, inadequate equipments, loss of some weeks due to a change in plan, and inadequate manpower; thus, there was a two month difference between the initial completion and the now actual completion time.

Lean six sigma methodology for waste reduction in ship production

This study was conducted to reduce the amount of waste in ship production and assembly processes at PT ES. Several wastes during the ship production process result in the actual ship completion time being longer than the planning time set by the process planner. Therefore, accurate analysis is required to reduce waste. In this way, contributing factors can be identified, and more effective solutions can be obtained to reduce waste. This is done by implementing the Lean Six Sigma method (DMAIC processes) and several tools and methods, such as Pareto and fishbone diagrams and the FMEA method. The results show that the most critical potential root cause affecting production delays comes from the potential causes with the highest Risk Priority Number (RPN) value. The causes are welders who do not understand the WPS (RPN 432), unstable welding transformers (RPN 432), and unproductive loader movements (RPN 384). The recapitulation of welding defects produced in the production process at a sigma level of 2.48. Recommendations for the three potential critical wastes were made and planned for implementation. The estimated average RPN impairment for the three critical root causes was 32.3%. This condition will impact the total ship production time, which is 6% shorter (equivalent to 14 days) than the previous production time with a new sigma level of 2.55.

Application of matrix multiplication in signal sensor image perception

Abstract LOT wireless sensor nodes are limited by physical factors, usually have weak computing power and endurance, and wireless communication methods are very vulnerable to information theft. Therefore, it is of great significance to ensure the safe and efficient transmission of images in new application scenarios. In view of the need for an efficient image transmission, this paper combines compressed sensing technology with p-tensor product theory, applies the above theory to distributed wireless sensor networks, and uses the correlation of adjacent sensor nodes in wireless sensor networks to propose an improved a joint sparse model for measurement matrices and reduction algorithms. The feasibility is verified by simulation experiments, and the comparison between joint reconstruction and single reconstruction, and the application of various algorithms in other algorithms is carried out, and the actual completion time and storage capacity are analysed. The minimum completion time for wavelet transform is 1.29, the sparse estimated time for the selection of preliminary P waves is 0.07 and the compressed sensing time is 0.20. The maximum completion time for wavelet transform was 1.32, for sparse estimation, it is 0.62, for preliminary P-wave selection, it is 0.17, and for compressed sensing, it is 0.88. The processing time is no >3 s and the runtime is only 0.22–0.88 s. The results show that compared with the compressed sensing of a single node, the joint sparse model based on distributed compressed sensing has a smaller reconstruction error, and can achieve high-precision signal reconstruction when the measurement value is small.

Effective Scheduling and Time Management of Dhamra Railway Project Using Primavera P6

Indian construction industry is growing quickly and huge development projects are going on. Most certainly it’s justifiably or in a roundabout way connected with the Indian economy, the speed with which projects complete have appeared to influence the GDP of the country. Appropriate scheduling and planning are substantial in construction projects for decreasing and controlling postponements of the project, while an error in the same causes squandering of a significant quantity of time, capital, resources, and quality. Despite firm principles and policies, the monitoring process may be inefficient because of the practical problems prevailing or rising in the project. An attempt has been made in realizing the practical problems in project execution will contribute to proper recognition of the problem areas and implementing mitigation. The main objectives of this study are to plan, schedule, monitor, and control a railway infrastructure i.e. Dhamra Railway Project, Orissa, India with the help of Oracle Primavera P6 software. The review of various research articles has been performed and twenty-five factors from nine categories are shortlisted for the study and the time factor is considered for analysis. Thereafter, critical time analysis of the project has been performed, listing project activities with duration, their logical relationships, scheduling, and network updating considering factors from the nine categories. The main challenges leading to delays are climate, government approvals, material availability, and the remote project location. Further, project crashing is done by provision of additional labour resources to critical activities and observation can be made that a raise of 21% of labour resources would offer a reduction of 17% of the activity completion time, this trend doesn’t imply that surging the resources directly reduces duration, it will reduce duration but up to the minimum fundamental duration required only.

Fair compensation of crowdsourcing work: the problem of flat rates

ABSTRACT Compensating crowdworkers for their research participation often entails paying a flat rate to all participants, regardless of the amount of time they spend on the task or skill level. If the actual time required varies considerably between workers, flat rates may yield unfair compensation. To study this matter, we analyzed three survey studies with varying complexity. Based on the United Kingdom minimum wage and actual task completion times, we found that more than 3 in 4 (76.5%) of the crowdworkers studied were paid more than the intended hourly wage, and around one in four (23.5%) was paid less than the intended hourly wage when using a flat rate compensation model based on estimated completion time. The results indicate that the popular flat rate model falls short as a form of equitable remuneration, when perceiving fairness in the form of compensating one’s time. Flat rate compensation would not be problematic if the workers’ completion times were similar, but this is not the case in reality, as skills and motivation can vary. To overcome this problem, the study proposes three alternative compensation models: Compensation by Normal Distribution, Multi-Objective Fairness, and Post-Hoc Bonuses.

Implementasi Critical Path Method dalam Produksi Feature Radio “Sudut Pandang” Episode “Mengenal Stunting”

The production of radio feature “Sudut Pandang” Episode of “Mengenal Stunting” imlements the Critical Path Method to map out all the steps need to be taken in order to complete and identify activities based on the priority; and also to identify the sequence of activities to complete first or need to be completed at the same time. It begins by determining the amount of time required to critically complete the priority work path, and analyzing the relationship between program requirements and available human resources, as well as the time required to complete production.The result of the Critical Path Method implementation is network analysis schedule that has succeeded in optimizing the total cost of production by reducing or accelerating the completion time of production activities in the creation of radio feature production works.

Estimating Project Completion Time with Monte Carlo Simulation

Risk and uncertainty are factors that construction project managers have been increasingly had to deal with. Project completion time is one of the areas where the expected time is often underestimated or shorter than the actual completion time. Monte Carlo simulation is a widely used simulation technique in modeling a process that is difficult to predict due to its random variables. This study provides a practical way to use Monte Carlo simulation to simulate a project using functions available in a spreadsheet application. A project with five activities was simulated 2000 times using minimum, maximum, and expected duration. The mean, mode, and median simulation results were then plugged into their respective precedence diagram networks to compare them. The precedence diagram computations found that mean, mode, and median project completion times were longer than the initially expected completion time. The mean, mode, and median were 50, 53, and 48 days, respectively, which were 8, 11, and 6 days longer, respectively, than the 42 days initially expected. The study showed that the Monte Carlo simulation could assist the project manager in planning a project schedule that deals with risk and uncertainty more realistically.

Joint optimization of production and maintenance for a serial–parallel hybrid two-stage production system

Effective machine maintenance and job scheduling strategies are two critical interactive tasks to upgrade the production efficiency in manufacturing industries. In this study, we mainly consider the interaction between production scheduling and maintenance, while optimizing the job scheduling problem in a serial–parallel hybrid two-stage production system. We formulate the problem by introducing the stochastic and workload-ratio degradation, and the actual job completion time and maintenance costs can be modeled according to the degradation status of each machine. To solve this problem, a two-step opportunistic maintenance (OM) strategy is developed, and finally an adaptive random-key genetic algorithm (GA) is designed by incorporating the OM coefficients. Numerical studies have been conducted to validate the proposed approach, and the results indicate the effectiveness compared to three existing methods under varying machine degradation scenarios.

Impact of Construction Delay-Controlling Parameters on Project Schedule: DEMATEL-System Dynamics Modeling Approach

Project delay has been a phenomenon contending with the construction sector opposing time, cost, and quality. This study develops a model, which is a combination of two mathematical decision-making methods DEMATEL and system dynamics modeling, to investigate the impact of the factors on the entire project schedule. The simulation results reveal the importance of minimizing design error to reduce the project delay at the beginning (or preconstruction stage) of the project. Rework, design changes, and change orders must also be closely monitored during the construction to ensure work productivity and on-time project completion. The results also reveal that experienced designers and the use of updated design technology help reduce design errors, thus enhancing work performance in the long term. As shown in the simulation results, the actual project completion time and magnitude of delay steadily reduce with the project series. This explains the fact that the more the consistency and effectiveness in handling the delay factors as similar projects are performed in turns, the better the project performance in terms of time. Therefore, careful consideration of the delay factors reduces the time lag and delay magnitude in construction projects. Other improvements, such as effective supervision during construction which is a function of experienced supervisors, good project management, and cooperation among key stakeholders, including owners, consultants, and contractors, also assist in reducing the construction delay in the long term.

Improving radiotherapy safety and efficiency with the customized ARIA oncology information system.

To improve safety and efficiency of radiotherapy process by customizing a Varian ARIA oncology information system following the guidelines provided in AAPM TG-100 report. First, failure mode and effects analysis (FMEA) and quality management program were implemented for radiotherapy process. We have customized the visual care path in the ARIA system and set up a series of templates for simulation, prescription, contouring, treatment planning, and multiple checklists. Average time of activities' completion and amount of planning errors were compared before and after the use of the customized ARIA to evaluate its impact on the efficiency and safety of radiotherapy. Completion time and on-time completion rate of the key activities in the care path are improved. The time of OAR/targets contouring decreases from (1.94±1.51) days to (1.64±1.07) days (p = 0.003), with the on-time completion rate increases from 77.4%to 83.3%(p = 0.048). Treatment planning time decreases from (0.81±0.65) days to (0.55±0.51) days (p < 0.001), with the on-time completion rate increases from 96.6%to 98.3%(p = 0.163). Waiting time of patients decreases from (4.50±1.83) days to (4.04±1.34) days (p < 0.001), with the on-time completion rate increases from 81.9%to 89.7%(p = 0.003). In addition, the average plan error rate decreases from 5.5%(2.9%for safety errors and 2.6%for non-normative errors) to 2.4%(1.6%for safety errors and 0.8%for non-normative errors) (p = 0.029). Our study demonstrates that the customized ARIA system has the potential to promote efficiency and safety in radiotherapy process management. It is beneficial to organize and accelerate the treatment process with more effective communications and fewer errors.

Evaluation of Estimated Survey Duration Equations Using a Health Risk Assessment

Survey duration—the time it takes to complete a survey—affects response and completion rates. Estimated survey duration equations may be used to estimate survey duration, however, there are no studies assessing their use. The objective of this study is to evaluate estimated survey duration equations using a health risk assessment. Six existing estimated survey duration equations were identified. Using health risk assessment data from January 1, 2018 to December 31, 2018, an average participant profile was built to inform the inputs into the estimated survey duration equations. Estimated survey duration of the health risk assessment ranged from 7.64 minutes to 39.6 minutes. Using the same dataset, the estimated survey duration was compared to the actual completion time of the health risk assessment. The average completion time of the health risk assessment was 11.27 minutes. The estimated survey duration equations either under- or overestimated the completion time of the health risk assessment. The equation that is based on word count, number of questions, decisions, and open text boxes is recommended for use to estimate the duration of a health risk assessment although it was an overestimate. Using estimated survey duration equations appear to be a suitable alternative to pilot testing but future studies are needed to further evaluate these equations in other types of surveys.

UNCERTAINTY IN PROCUREMENT CONTRACTING WITH TIME INCENTIVES

AbstractThis article studies cost‐plus‐time (A+B) procurement contracting with time incentives in the highway construction industry. In the presence of construction uncertainty, the contractor's actual completion time may deviate from the bid completion time, and the A+B contract design is not ex post efficient. Using data from highway procurement contracts in California, we show that an ex post efficient lane rental contract would reduce the social cost by $41.39 million (43.11%) on average. Moreover, the average commuter cost would decrease by $62.06 million (78.96%), suggesting a substantial reduction in the construction externality to commuters from lane rental contracts.

A Multi-Objective Scheduling Algorithm for Multi-Mode Resource Constrained Projects in the Presence of Uncertain Resource Availability

Goal: The issue of resource allocation is a major concern for project engineers in the scheduling process of a project. Resources over-allocation are often seen in practice after the scheduling of a project, which makes scheduling unhelpful. Modifying an over-allocated schedule is very complicated and requires a lot of effort and time. Besides, during the scheduling process of resource-constrained projects in the constructing companies, managers should concern more than one objective at the same time. This research aims to propose a new heuristic algorithm for minimizing project completion time, cost or maximizing quality of execution of activities simultaneously while multi-mode activities are taken into consideration.&#x0D; Design / Methodology / Approach: In this research, a new heuristic method is proposed for solving multi-objective scheduling problem for multi-mode resource constrained project scheduling problems (MRCPSPs) where the aim is maximizing the net present value (NPV) of project, minimize completion time and maximize the quality of executing activities simultaneously and along with emerging the uncertainty of resources availability and activity durations. The proposed method is then coded by Matlab® 2016.&#x0D; Results: The outcomes of solving small, medium and large scale case studies, the following results achieved: (i) the algorithm could solve all problems in different circumstances with no difficulties; (ii) the large scale problems (with 200 activities, 20 resources and 3 execution modes for each activity) could be solved in 4.43 seconds. (iii) in none of the studied cases over-allocation problem. The proposed method can be considered among the fastest scheduling algorithms found in the literature. In addition, it is found that makespan, NPV and quality have co-relation must be taken into consideration during the scheduling process.&#x0D; Limitations of the investigation: The main limitations of this research is that it only covers resource constrained project scheduling. Moreover, risk factors associated with the objectives of this research have yet to be addressed in future research studies.&#x0D; Practical implications: The performance of the algorithm is validated by using 24 series of dataset that are found in the literature. In order to verify its performance in real practice, it has been applied for a part of a construction project in Malaysia. The outcomes indicated that the algorithm scheduled the problem with 23 activities, 5 constrained resources and 2 execution modes in less than a second and with no over-allocations. The proposed multi-objective algorithm allows the project managers to consider NPV, completion time and quality of activities while scheduling a multi-mode project. In practice, this algorithm can provide a better atmosphere for managers while they aim to consider more than one objective during the scheduling process.&#x0D; Originality / Value: The proposed algorithm is original and can be of great value for future studies and managers in preventing resource over-allocation during the scheduling of multi-objective multi-mode resource constraint project scheduling. Moreover, it can help project managers to find near optimum solutions for complex multi-objective resource constraint projects faster and also with more accuracy.

Real Or Not Real: The Impact of the Physical Fidelity of Virtual Learning Resources on Learning Anatomy.

Technological advancements have made it possible to create realistic virtual representations of the real world, although it is unclear in medical education whether high physical fidelity is required in virtual learning resources (VLRs). This study, therefore, aimed to compare the effectiveness of high-fidelity (HF) and low-fidelity (LF) VLRs for learning anatomy. For this study, HF and LF VLRs were developed for liver anatomy and participants were voluntarily recruited from two cohorts (cohorts 1 and 2). Knowledge outcomes were measured through pre- and post-tests, task outcomes including activity score and completion time were recorded and participants' perceptions of the VLRs were surveyed. A total of 333 participants (165 HF and 168 LF) took part in this study. Knowledge outcomes were higher for the HF activity in cohort 1 and for the LF activity in cohort 2, although not significantly. There were no significant differences in activity score within either cohort, although completion time was significantly longer for the HF activity in cohort 1 (P=0.001). There were no significant differences within either cohort in perceptions of the VLRs regarding usefulness for reviewing conceptual knowledge, esthetics, quality, mental effort experienced, or future use, although the LF VLR was scored significantly higher regarding the value for understanding in cohort 1 (P=0.027).This study suggests that high physical fidelity is not necessarily required for anatomy VLRs, although may potentially be valuable for improving knowledge outcomes. Also, level of prior knowledge may be an important factor when considering the physical fidelity of anatomy VLRs.

A Data-Driven Analytical Framework To Learn And Improve Clinical Workflow In Radiation Oncology

Radiation treatment planning is a complex process with multiple, dependent steps involving an interdisciplinary patient care team. We have previously implemented an interactive, web-based dashboard, which integrates with the departmental electronic medical record system (EMR), and provides real-time monitoring and visualization of the treatment planning workflow and resource utilization. In addition, the dashboard implements a standardized, integrated framework to acquire and analyze data for clinical workflow evaluation. We present this framework and the results of data-driven analyses to learn and evaluate clinical practice performance in an effort to improve clinical efficiency and assess the impact of potential workflow changes. Process maps and flowcharts were created to model the treatment planning workflow. The flowcharts described: (1) standardized activities associated with a patient’s care path for distinct treatment modalities from the time of CT simulation to treatment, (2) activity order and timeline, (3) activity ownership, and (4) staff interaction. Three treatment modalities, 3D, intensity modulated radiotherapy (IMRT), and stereotactic body radiotherapy (SBRT), were modeled. For each modality, an ideal timeline with a duration of 6 days for 3D and IMRT and 9 days for SBRT, and amenable to future refinement, was formulated based on perceived timelines, staffing levels and departmental throughput goals. Care team physicians, dosimetrists, physicists and therapists were trained in the use of the EMR to record activity status, which was also visualizable on the web-based dashboard. A quantitative representation of how different care path activities unfold was obtained from queryable timestamps in the EMR. Staff-reported actual completion times for the care path activities were computed and compared to their ideal timeline. We collected and analyzed data for 133 new patient treatments (72 3D, 55 IMRT, 6 SBRT) and 793 associated care path activities. The mean (standard deviation) of reported actual completion times in working days for the main activities are listed in the table below. On average, 3D, IMRT and SBRT treatments required 4.9, 6.6 and 9.2 days, respectively, from CT simulation to treatment. Actual total completion times for 3D treatments were significantly better than ideal (p < 0.05), but not for IMRT and SBRT treatments. The framework developed allows for informed, data-driven decisions regarding clinical workflow management and the impact of changes on existing workflow as we seek to optimize clinical efficiency and incorporate new interventions due to new treatments into clinical practice.Abstract 3799; TableCT importPhysician contour/beam placementTreatment planningPhysician plan approvalIMRT QAPre-treatment physics chart review3D0.1 (0.2)0.9 (1.0)4.2 (2.3)4.0 (2.3)4.9 (2.7)IMRT0.1 (0.3)1.8 (1.1)6.3 (2.2)5.8 (2.3)6.5 (2.3)6.6 (2.1)SBRT0.03 (0.02)2.6 (2.3)3.0 (2.2)8.7 (2.5)7.3 (2.5)9.2 (2.7) Open table in a new tab

Asynchronous Floating-Point Adders and Communication Protocols: A Survey

Addition is the key operation in digital systems, and floating-point adder (FPA) is frequently used for real number addition because floating-point representation provides a large dynamic range. Most of the existing FPA designs are synchronous and their activities are coordinated by clock signal(s). However, technology scaling has imposed several challenges like clock skew, clock distribution, etc., on synchronous design due to presence of clock signal(s). Asynchronous design is an alternate approach to eliminate these challenges imposed by the clock, as it replaces the global clock with handshaking signals and utilizes a communication protocol to indicate the completion of activities. Bundled data and dual-rail coding are the most common communication protocols used in asynchronous design. All existing asynchronous floating-point adder (AFPA) designs utilize dual-rail coding for completion detection, as it allows the circuit to acknowledge as soon as the computation is done; while bundled data and synchronous designs utilizing single-rail encoding will have to wait for the worst-case delay irrespective of the actual completion time. This paper reviews all the existing AFPA designs and examines the effects of the selected communication protocol on its performance. It also discusses the probable outcome of AFPA designed using protocols other than dual-rail coding.