Jonathan Doherty

Mobile development environments for electronic finance

Recent trends in e-finance have shown that mobile technology is growing and with this comes new opportunities for deploying new services for customers. Development of systems on mobile devices can require a lot more resources in the form of development time. There is a lack of documentation as to the merits of leading development environments for mobile platforms. The objective here is to compare the implementation process of developing on each mobile device. We set about investigating the various properties through building an e-finance application on each platform and we offer recommendations for e-finance mobile developers as to which is most suitable.

Pattern Matching Techniques for Replacing Missing Sections of Audio Streamed across Wireless Networks

Streaming media on the Internet can be unreliable. Services such as audio-on-demand drastically increase the loads on networks; therefore, new, robust, and highly efficient coding algorithms are necessary. One method overlooked to date, which can work alongside existing audio compression schemes, is that which takes into account the semantics and natural repetition of music. Similarity detection within polyphonic audio has presented problematic challenges within the field of music information retrieval. One approach to deal with bursty errors is to use self-similarity to replace missing segments. Many existing systems exist based on packet loss and replacement on a network level, but none attempt repairs of large dropouts of 5 seconds or more. Music exhibits standard structures that can be used as a forward error correction (FEC) mechanism. FEC is an area that addresses the issue of packet loss with the onus of repair placed as much as possible on the listeners device. We have developed a server--client-based framework (SoFI) for automatic detection and replacement of large packet losses on wireless networks when receiving time-dependent streamed audio. Whenever dropouts occur, SoFI swaps audio presented to the listener between a live stream and previous sections of the audio stored locally. Objective and subjective evaluations of SoFI where subjects were presented with other simulated approaches to audio repair together with simulations of replacements including varying lengths of time in the repair give positive results.

A self-similarity approach to repairing large dropouts of streamed music

Enjoyment of audio has now become about flexibility and personal freedom. Digital audio content can be acquired from many sources and wireless networking allows digital media devices and associated peripherals to be unencumbered by wires. However, despite recent improvements in capacity and quality of service, wireless networks are inherently unreliable communications channels for the streaming of audio, being susceptible to the effects of range, interference, and occlusion. This time-varying reliability of wireless audio transfer introduces data corruption and loss, with unpleasant audible effects that can be profound and prolonged in duration. Traditional communications techniques for error mitigation perform poorly and in a bandwidth inefficient manner in the presence of such large-scale defects in a digital audio stream. A novel solution that can complement existing techniques takes account of the semantics and natural repetition of music. Through the use of self-similarity metadata, missing or damaged audio segments can be seamlessly replaced with similar undamaged segments that have already been successfully received. We propose a technology to generate relevant self-similarity metadata for arbitrary audio material and to utilize this metadata within a wireless audio receiver to provide sophisticated and real-time correction of large-scale errors. The primary objectives are to match the current section of a song being received with previous sections while identifying incomplete sections and determining replacements based on previously received portions of the song. This article outlines our approach to Forward Error Correction (FEC) technology that is used to “repair” a bursty dropout when listening to time-dependent media on a wireless network. Using self-similarity analysis on a music file, we can “automatically” repair the dropout with a similar portion of the music already received thereby minimizing a listeners discomfort.

Good Practice for Strong Passwords

Abstract The creation of strong, secure passwords is vital in our life today due to the implications of compromised access to our data. Passwords are commonly used to prevent unauthorized access to important information, to guarantee security of personal information, and to prevent unauthorized access to various services. It seems that people tend to veer toward adopting the simplest characters in forming their passwords and they also tend to reuse the same password for multiple accounts. This is natural due to the weakness of the average human mind but it can lead to attack from any of the password-cracking tools. This article will examine best practice in creating secure passwords.

An Activity Monitoring Application for Windows Mobile Devices

Obesity is rising at an alarming rate. A great challenge facing the health community is introducing population-wide approaches to weight management as existing health and medical provisions do not have the capacity to cope. Technology is fast becoming an important tool to combat this trend. The use of activity monitors is becoming more common in health care as a device to measure everyday activity levels of patients as activity is often linked to weight. This paper outlines a research project where Bluetooth technology can be used to connect a commercial wrist-worn activity monitor with a Windows Mobile device to allow the user to upload the activity data to a remote server.