A Case Study on Planning and Scheduling of a Project PIPLMC of a Package - 6A using Microsoft Project 2016
Bibliographic record
Abstract
There have been many case studies/review papers in area of project planning and scheduling from last few years. Various construction activities are managed to achieve the profit within limited funds, resources, and time. In project management there are many techniques are used for scheduling and coordinating the various resources by controlled method. Management techniques such as Critical Path Method (CPM), Program Evaluation and Review Techniques (PERT) have been successfully implemented prior to the 1970?s, in various construction projects in the countries like Canada, USA, Japan, Australia, etc. These techniques are helpful to manage in efficient and economic use of resources for completion of project objectives with limitless availability of resources, though it is observed that resources are limited in real time project scenario. While the focus of this paper will be on the project schedule of Polavaram Irrigation Project of Left Main Canal (PIPLMC) of Package-6A of 25.78KM from KM 111.000 to KM 136.780 (Part Work) by using MS Project 2016. This paper will briefly present an overview of the scheduling the project duration using software MS Project 2016. In this project, preparing an accurate and workable plan is very difficult. In this project by using project management technique like priority rule-based scheduling method used to resolve resource conflicts and useful in minimizing the project duration within limited availability of resources and time to make the project profitable and within project duration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".