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The number of construction dispute cases has surged in recent years. The effective exploration and management of risks associated with construction contracts helps to directly enhance the overall project performance. The existing approaches to identify the risks associated with construction project contracts have a heavy reliance on manual review techniques, which are inefficient and highly restricted by personnel experience. The existing intelligent approaches only work for the contract query and storage. Hence, it is necessary to improve the intelligence level for contract risk management. This study aims to propose a novel method for the intelligent identification of risks in construction contract clauses based on natural language processing.

This proposed method can formalize the linguistic logic and semantic information of contract clauses into multiple triples and transform the structural processing results of general clauses in a construction contract into rights and interests rules for risk review. In addition, the core semantic information of special clauses in a construction contract, rights and interests rules are used for semantic conflict detection. Finally, this study achieves the intelligent risk identification of construction contract clauses.

The method is verified by selecting several construction contracts that had been applied in engineering contracting as a corpus. The results showed a high level of accuracy and applicability of the proposed method.

This novel method can identify the risks in contract clauses with complex syntactic structures and realize rule extension according to the semantic relation network of the ontology. It can support efficient contract review and assist the decision-making process in contract risk management.

The purpose of this study is to investigate the synergism of convection, current density distribution and additives by numerical simulation and electrochemical experiments for good throwing power (TP) of copper electro-deposition in printed circuit board (PCB) manufacture.

The flow field of THs and current density distribution on various AR of THs are calculated and analyzed. Meanwhile, corresponding simulation is used to study the performance of plating electrolytes on TP. Two electrochemical parameters, overpotential (η) and potential difference (△η), are chosen to evaluate the electrochemical properties of different plating solutions by galvanostatic measurement and potentiodynamic cathode polarization at different rotating speeds.

By combining both the results of simulation and practical plating, these two electrochemical properties of electrolytes exhibit significant impact to the system at varied conditions. Especially, the electrolyte with higher polarizing η and △η values lead to the elevated TP for AR of more than 2:1.

The harring cell model is built as a bridge between the theoretical and experimental study for control of uniformity of plating THs in PCB manufacturing. This dual-parameter evaluation is validated to be a promising decisive method to guide the THs plating with particular AR in industry.