The Smart City concept has been recognised as the way forward for cities that have strong ICT facilities and support. This concept provides the basis for a comprehensive city development strategy that could promote efficiency in city management and administration among city dwellers. Any city development concept must be formulated with the user and city characteristics in mind. The requirements of the city users are important in shaping the Smart City policies and programmes for the city. During the implementation of the Smart City initiatives, there is a need to ensure that the level of Smart City implementation matches user expectations. When the actual provision of Smart City features falls below user expectations, it can be said that there are gaps in the provision of Smart City initiatives for the city. The identification of these gaps would assist city managers in diverting more resources into the areas that need attention. This study proposes a framework for a gap analysis that indicates the achievement of required vs. actual Smart City initiative provision. Using Putrajaya, Malaysia as a case study, the intensity of initiative provision is calculated and then 'adjusted' against the intensity of user expectations to yield what is termed as Adjusted Level of Provision (ALP). Since the study has uncovered provision that needs improvement in turning Putrajaya as smart city, this framework could offer a useful tool for Smart City managers in measuring the city's performance.

This paper studied the human ear and human brain as a new idea to analyze sound. The human ear to be exact; the eardrum detects the sound signal and the cochlea filters the frequency signal. Subsequently, the brain is capable to recognize and learn the sound signal. This research mapped the biologically-inspired ability to computational process then developed an abstraction model. From this model it provided a guideline to obtain the capability requirements for the of sound signal analyzer as a new idea for information retrieval. The research aims to generate faster and more detailed results as well as to achieve better accuracy in producing definite sound. Therefore, this research proposed an abstraction model of human ear and human brain to developed biologicallyinspired sound signal analyzer (BISSA).

Abstract-This paper presents a method to prevent duplication of digital audio file in a personal device which is called biologically-inspired audio storing management process (BiASMP). This method is better than other software applications by preventing the duplication of digital music record from the start of the file being inserted into the personal device. Hence, the hard disk of personal device is always optimized with the required singular audio file. A comparative analysis is made to show advantage of BiASMP. The results of exemplar settings simulation are also provided to show how BiASMP works.Index Terms-Biologically-inspired, software engineering, and multimedia database.

Sound is one of the media that brings information to human. However this information also distracted by noises that surround us. How human brain recognizes to the required sound is very much impressive. Vice versa, the human brain can learn to the new sound. Thus, we can just concentrate to the sound that we want to listen only. For instance, when two human communicate each other, to be precise in a loud area such as at the market, both are paying attention merely to the conversation of what they are talking. Here, in this situation, human without notice can filter the unintended noise and only recognize to the particular sound we wanted to listen only. Hence, this research studies the human ear and human brain as a new idea to analyze sound. The human ear to be exact; the eardrum detects the signal sound and the cochlea filters the signal frequency. Subsequently, the brain is capable to identify on the required sound by recognizing and learning the signal sound. Therefore, with the analysis of the biologically-inspired entities, this research investigates the capability requirements to develop the biologically-inspired signal sound analyzer (BISSA) as a new idea for information gathering.

This paper tries to create a new biologically-inspired abstract model for the sound signal processing. The abstract model also shows the memory storage for the sound signal processor. This research adapts the functions from the biologically-inspired entities, which are the human auditory system and the human brain. This research aims to provide integrated and structured database to store the sound signal processing data. This research provides the framework to the implementation of the soft computing approach for the memory storage of a sound signal processor. This paper is a preliminary investigation paper. Therefore, this research creates the abstract model for the Biologically-Inspired Sound Signal Analyzer (BISSA) as a new idea for information gathering.