Informatics Publishing Limited

Seyed Aliakbar Mousavi ¹, Majid Meghdadi ², Zahra Hanifeloo ², Putra Sumari ¹, Muhammad Rafie Mohd Arshad ¹

Affiliations
1 School of Computer Science, Universiti Sains Malaysia (USM), MY
2 Computer Department, Faculty of Engineering, University of Zanjan, IR

Abstract

This paper provides a fast method to recognize a variety of Persian banknotes at different scales. In this technique, the PCA, LDA and sparse representation methods are utilized at feature extraction stage and follows with MLP neural networks, LVQ and SOM in classification. Finally, the application of sparse matrix representation method and combination of both SOM and LVQ neural networks would lead to the best efficiency with precision of 91.15% in recognition of Persian banknotes particularly the worn ones.

Keywords

Banknote Recognition, LVQ, Neural Network, PCA, Sparse Representation.

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Hadeel Haj Aliwi ¹, Putra Sumari ¹

Affiliations
1 School of Computer Sciences Universiti Sains Malaysia, 11800, Pulau Penang, MY

Abstract

In the last few years, multimedia communications has been developed and improved rapidly in order to enable users to communicate between each other over the internet. In general, the multimedia techniques consist of instant messages, audio, and video chatting services. However, users cannot phonetically communicate with each other unless they use the same chatting applications since each chatting application has its own control protocol to handle the call setup, the real time media transmission, and the call teardown sessions. The only way to enable the users to communicate phonetically using different chatting applications is to design a new architecture by proposing an interworking module between the control protocols used by the applications. The interworking module between at least two different protocols is a very critical issue as it solves the data transmission problems when using different chatting applications to create a voice call, and demonstrates that the voice conferencing between heterogeneous control protocols identifies the interest of combining the features and taking the advantages of more than one protocol in a single network. The two chosen protocols in this paper are: Inter-Asterisk exchange Protocol and the extension of extensible Messaging and Presence Protocol. Each protocol differs from the other one in many terms. Thus, this paper clarified the main differences between IAX Protocol and Jingle Protocol by doing a comparison in terms of registration, URI format, signals, transport methods, audio and control packets, bandwidth, scalability, functionality, services, etc. This comparison is due to define the common and the unique features to ease proposing the IAX-Jingle mapping architecture, signaling and media transfer modules. So, people around the world will be enabled to talk with each other without caring whether they are IAX or Jingle users.

Keywords

IAX, Jingle, Multimedia, Signaling Protocols, VoIP

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Saleh Ali K. Al-Omari ¹, Putra Sumari ¹

Affiliations
1 School of Computer Sciences, University Sains Malaysia, 11800 Penang, MY

Abstract

Problem statement: This paper examines Artificial Spiking Neural Network (ASNN) which inter-connects group of artificial neurons that uses a mathematical model with the aid of block cipher. The aim of undertaken this research is to come up with a block cipher where by the keys are randomly generated by ASNN which can then have any variable block length. This will show the private key is kept and do not have to be exchange to the other side of the communication channel so it present a more secure procedure of key scheduling. The process enables for a faster change in encryption keys and a network level encryption to be implemented at a high speed without the headache of factorization. Approach: The block cipher is converted in public cryptosystem and had a low level of vulnerability to attack from brute, and moreover can able to defend against linear attacks since the Artificial Neural Networks (ANN) architecture convey non-linearity to the encryption/decryption procedures. Result: In this paper is present to use the Spiking Neural Networks (SNNs) with spiking neurons as its basic unit. The timing for the SNNs is considered and the output is encoded in 1's and 0's depending on the occurrence or not occurrence of spikes as well as the spiking neural networks use a sign function as activation function, and present the weights and the filter coefficients to be adjust, having more degrees of freedom than the classical neural networks. Conclusion: In conclusion therefore, encryption algorithm can be deployed in communication and security applications where data transfers are most crucial. So this paper, the neural block cipher proposed where the keys are generated by the SNN and the seed is considered the public key which generates the both keys on both sides In future therefore a new research will be conducted on the Spiking Neural Network (SNN) impacts on communication.

Keywords

Spiking Neural Network, Virtual Private network, IP Security, Artificial Neural Networks, Simple-Data Encryption Standard, Encryption and Decryption.

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