The scatter form of multimedia data such as text, image, audio, and video posted regularly in the social media may contain useful information for the organizations. But, this information should be derived with the use of some form of analysis known as Multimodal Sentiment Analysis (MSA). But, there is a lack of pro per analytic tools for such analysis. This paper presents a thorough overview of more than fifty most recent MSA research articles to find the gaps in terms of tasks, approaches theories and applications used till date. There seems to be no single approach, theory, and tool which can support MSA. The study showed that each and every mode presents different difficulties which have not been fully solved yet, such as feature points of a face, voice clarity in audio, video summarization and so on, and are great research opportunities for the future researchers. Also, this research recommends a list of existing and upcoming difficulties and opportunities of MSA research.

Data is particularly valuable to scientists when details of its provenance are known. This research concerned deploying a user-orientated electronic laboratory notebook (ELN) system within a scientific community. The ELN system supported the capture and retrieval of semantic metadata describing the provenance of the modelling activities of scientists within that community. The research was grounded within the atmospheric chemistry community but has applicability to other communities using an iterative model development process. The ELN system involved the automatic capture of metadata concerning the modelling process together with inline annotations added by the modeller explaining the reasoning for modelling decisions at each step of the process. A full realisation of the ELN system was built and evaluated by members of the atmospheric chemistry community. In order to promote reusability the ELN system architecture had domain-independent as well as domain-dependent elements. An ontology (in OWL) was used to ensure that the specific terminology of the community was used within the provenance metadata and also that it was used consistently. Other domain-independent elements of the architecture included a dynamic graphic interface that allowed the modeller to view his/her modelling history. This was recorded as a set of nodes each pointing to the stored provenance metadata associated with a specific simulation run. In addition, there was an innovative mechanism that enabled the modeller to navigate through the various nodes. The navigation process supported making comparisons between different nodes: a facility that users found particularly valuable. Members of the atmospheric chemistry community took part in a two-day summative evaluation of the ELN system. This confirmed its value to the modellers and it is now being introduced more widely across the modelling community. In addition, the research proposes a methodology for transferring this ELN system to other modelling communities making use of the domain-independent elements of the architecture. (C) 2013 Elsevier B.V. All rights reserved.

Adaptive threshold works at pixel level and the result of the adaptive threshold is either background or foreground. The adaptive threshold produces superior result compared to global threshold, especially for the images that have uneven pixel intensity distribution. In the dental age assessment, X-ray image is used as an aid to estimate the age of the person. The existing process of assessment is done manually. However, this can be made automatically. The process of automated dental age assessment, require threshold segmentation to separate the background and the teeth area. In order to optimize the result of the adaptive threshold, it depends on the threshold value. In this paper, we present three methods (i.e. mean, median and OTSU) to estimate the range of the threshold value. The result of the study shown that the median threshold provides better results than the mean and OTSU thresholds. In terms of the region of the segmentation, median threshold value covers more teeth followed by mean threshold and OTSU threshold. The region of segmentation is important because one of the requirements in Demirjian method is to assess all the teeth types in quadrant 2 and quadrant 3. Based on the result of the experiment shown the region of median threshold able to segment most of the teeth area in quadrant 2 and quadrant 3.

The x-ray image is a greyscale image and the distribution of the intensity of the pixel is uneven. The x-ray image widely use in dental age assessment especially Demirjian method. The purpose of the dental age assessment is to estimate the age of unidentified bodies. The current process is done manually by the examiner. The process potentially converted to an automated system. The development an automated dental age assessment required segmentation process; which is dividing the image into multiple meaningful parts based on region and edge. The edge segmentation form a contour based on the links detected. The authors present two types of edge segmentation methods (i.e Sobel and Canny). The objective of the study is to make a comparison between the two methods. Result showed Sobel method was able to segment all the teeth area and remove the noise on the x-ray image while Canny algorithm was not able to segment all the teeth area especially incisors. The region of segmentation is important because one of the requirements in Demirjian method is to assess all the teeth types in quadrant 2 and quadrant 3. Based on the result, the experiment showed the Sobel algorithm able to segment most of the teeth area in quadrant 2 and quadrant 3.