Unbalanced bidding is a cash flow management strategy that is recognized as an illegal/disqualifying practice by public owners;and unethical practice by most private owners. This practice provides the awarded bidder w...Unbalanced bidding is a cash flow management strategy that is recognized as an illegal/disqualifying practice by public owners;and unethical practice by most private owners. This practice provides the awarded bidder with unjustified advantages at the expense of the owner. Unfortunately, limited tools and techniques are currently available to identify and detect unbalanced bids during the evaluation process. This paper presents an innovative detection tool to identify unbalanced bids in unit price contracts during the bid evaluation process. The proposed technique develops BMDI graphs to visualize total markup variation patterns during the project lifetime to detect unbalanced bids. The proposed method also uses Monte Carlo simulation to take in consideration the impact of cost uncertainties and risks. An illustrative example was presented to show the capabilities and features of the proposed method in determining the status of submitted bids during the evaluation process.展开更多
Fatigue impairs workers’judgment,reduces their productivity,and jeopardizes their safety.The paper presents a tool to predict workers’fatigue based on their vital signs.An experimental study was conducted in w...Fatigue impairs workers’judgment,reduces their productivity,and jeopardizes their safety.The paper presents a tool to predict workers’fatigue based on their vital signs.An experimental study was conducted in which the heart rate and sleep quality for three individuals were monitored using fitness trackers(wearable sensors).The data collected were used to develop two models based on regression analysis and Artificial Neural Networks(ANN),to predict their fatigue level.A Borg’s scale was used to estimate the Rating of Perceived Exertion(RPE)of the participants.The two models were able to satisfactorily predict the RPE(workers fatigue level)with an average validity of 75%and 80%for the regression ANN models,respectively.The developed models can provide project managers and superintendents with early warning to avoid potential worker overexertion,injuries,and fatalities.展开更多
文摘Unbalanced bidding is a cash flow management strategy that is recognized as an illegal/disqualifying practice by public owners;and unethical practice by most private owners. This practice provides the awarded bidder with unjustified advantages at the expense of the owner. Unfortunately, limited tools and techniques are currently available to identify and detect unbalanced bids during the evaluation process. This paper presents an innovative detection tool to identify unbalanced bids in unit price contracts during the bid evaluation process. The proposed technique develops BMDI graphs to visualize total markup variation patterns during the project lifetime to detect unbalanced bids. The proposed method also uses Monte Carlo simulation to take in consideration the impact of cost uncertainties and risks. An illustrative example was presented to show the capabilities and features of the proposed method in determining the status of submitted bids during the evaluation process.
文摘Fatigue impairs workers’judgment,reduces their productivity,and jeopardizes their safety.The paper presents a tool to predict workers’fatigue based on their vital signs.An experimental study was conducted in which the heart rate and sleep quality for three individuals were monitored using fitness trackers(wearable sensors).The data collected were used to develop two models based on regression analysis and Artificial Neural Networks(ANN),to predict their fatigue level.A Borg’s scale was used to estimate the Rating of Perceived Exertion(RPE)of the participants.The two models were able to satisfactorily predict the RPE(workers fatigue level)with an average validity of 75%and 80%for the regression ANN models,respectively.The developed models can provide project managers and superintendents with early warning to avoid potential worker overexertion,injuries,and fatalities.
