Abstract In this paper, we design a module that can change password when Excel VBA password is set. Especially, we designed it to be applicable to VBA environment using macros in Excel. It often happens that you cannot access important file data due to password loss, after setting the VBA password. For these users, it is possible to access valuable data by more convenient... In this paper, we design a module that can change password when Excel VBA password is set. Especially, we designed it to be applicable to VBA environment using macros in Excel. It often happens that you cannot access important file data due to password loss, after setting the VBA password. For these users, it is possible to access valuable data by more convenient VBA password using the proposed program. We actually implemented the proposed design in this paper. Experiments were performed on the actual contents of the excel file. Experimental results show that the contents of Excel VBA password can change. Read More Read Less

Abstract This paper describes an original and straightforward architecture for a logic circuit implementation of the RSA algorithms. The architecture is ideal for teaching advanced undergraduate or graduate students topics associated with public-key cryptography and digital system design. The system is designed with VHDL for execution on a FPGA. Software implementations of RSA running on standard PCs are relatively slow as standard microprocessors are... This paper describes an original and straightforward architecture for a logic circuit implementation of the RSA algorithms. The architecture is ideal for teaching advanced undergraduate or graduate students topics associated with public-key cryptography and digital system design. The system is designed with VHDL for execution on a FPGA. Software implementations of RSA running on standard PCs are relatively slow as standard microprocessors are not optimized for the operations RSA must carry out. A key aspect of this approach is the use of Montgomery Multiplication, a method for performing fast modular multiplication. Read More Read Less

Abstract Spoken language understanding(SLU), which usually involves slot filling and intent detection, is an important task in natural language processing. Most of the state-of-the-art methods are usually take single utterance as input, which would introduce much ambiguity because the loss of context information. To address this issue, we propose a new neural network based joint intent detection and slot filling model which takes multiple... Spoken language understanding(SLU), which usually involves slot filling and intent detection, is an important task in natural language processing. Most of the state-of-the-art methods are usually take single utterance as input, which would introduce much ambiguity because the loss of context information. To address this issue, we propose a new neural network based joint intent detection and slot filling model which takes multiple utterances as input. In our method, we use an utterance2utterance attention mechanism to combine the information of multiple continuous utterances. We also combine the intent information to the slot filling process with a gating mechanism. Using this proposed model, we participated in the task2 of CCKS2018. Finally, our model ranks NO.2 among the hugely competitive models. Read More Read Less