Advances in Social Media Research: Past,Present and Future

Social media comprises communication websites that facilitate relationship forming between users from diverse backgrounds, resulting in a rich social structure. User generated content encourages inquiry and decision-making. Given the relevance of social media to various stakeholders, it has received significant attention from researchers of various fields, including information systems. There exists no comprehensive review that integrates and synthesises the findings of literature on social media. This study discusses the findings of 132 papers (in selected IS journals) on social media and social networking published between 1997 and 2017. Most papers reviewed here examine the behavioural side of social media, investigate the aspect of reviews and recommendations, and study its integration for organizational purposes. Furthermore, many studies have investigated the viability of online communities/social media as a marketing medium, while others have explored various aspects of social media, including the risks associated with its use, the value that it creates, and the negative stigma attached to it within workplaces. The use of social media for information sharing during critical events as well as for seeking and/or rendering help has also been investigated in prior research. Other contexts include political and public administration, and the comparison between traditional and social media. Overall, our study identifies multiple emergent themes in the existing corpus, thereby furthering our understanding of advances in social media research. The integrated view of the extant literature that our study presents can help avoid duplication by future researchers, whilst offering fruitful lines of enquiry to help shape research for this emerging field.     

An adaptive block-based matching algorithm for crowd motion sequences

For crowd analytics and surveillance systems, motion estimation is an essential first step. Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. However, algorithms based on optical flow and background subtraction have numerous limitations such as the complexity of the computation in the presence of high dense crowd and sudden motion changes. Therefore, a novel estimation algorithm is proposed to measure the motion of crowd with less computational complexity and satisfy the real time requirements. The proposed algorithm is based on block-based matching, particle advection, and social force model. By the block-based matching, the motion is estimated in each frame, and the corresponding motion field is created. The particle advection process provides more information about the behavior of pedestrians groups, their tracked trajectories and the boundary of each group segment. Relying on the social force model, a predicted direction of the motion vectors (MV) could be measured significantly. Subsequently, the block-based technique is combined with the social force model to obtain the accurate motion vector with the less possible number of search points. The experimental results indicate that the proposed method achieves high performance by reducing the search points, particularly when many collision situations or obstacles exist in the scenes. Considering the reduction in the computational complexity, the quality of degradation is very low. In all cases, average PSNR degradation of the proposed algorithm is only 0.09.     

Blobworld: image segmentation using expectation-maximization and its application to image querying

Retrieving images from large and varied collections using image content as a key is a challenging and important problem. We present a new image representation that provides a transformation from the raw pixel data to a small set of image regions that are coherent in color and texture. This "Blobworld" representation is created by clustering pixels in a joint color-texture-position feature space. The segmentation algorithm is fully automatic and has been run on a collection of 10,000 natural images. We describe a system that uses the Blobworld representation to retrieve images from this collection. An important aspect of the system is that the user is allowed to view the internal representation of the submitted image and the query results. Similar systems do not offer the user this view into the workings of the system; consequently, query results from these systems can be inexplicable, despite the availability of knobs for adjusting the similarity metrics. By finding image regions that roughly correspond to objects, we allow querying at the level of objects rather than global image properties. We present results indicating that querying for images using Blobworld produces higher precision than does querying using color and texture histograms of the entire image in cases where the image contains distinctive objects.     

Spectral grouping using the Nyström method

Spectral graph theoretic methods have recently shown great promise for the problem of image segmentation. However, due to the computational demands of these approaches, applications to large problems such as spatiotemporal data and high resolution imagery have been slow to appear. The contribution of this paper is a method that substantially reduces the computational requirements of grouping algorithms based on spectral partitioning making it feasible to apply them to very large grouping problems. Our approach is based on a technique for the numerical solution of eigenfunction problems known as the Nystrom method. This method allows one to extrapolate the complete grouping solution using only a small number of samples. In doing so, we leverage the fact that there are far fewer coherent groups in a scene than pixels.     

Normalized cuts and image segmentation

We propose a novel approach for solving the perceptual grouping problem in vision. Rather than focusing on local features and their consistencies in the image data, our approach aims at extracting the global impression of an image. We treat image segmentation as a graph partitioning problem and propose a novel global criterion, the normalized cut, for segmenting the graph. The normalized cut criterion measures both the total dissimilarity between the different groups as well as the total similarity within the groups. We show that an efficient computational technique based on a generalized eigenvalue problem can be used to optimize this criterion. We applied this approach to segmenting static images, as well as motion sequences, and found the results to be very encouraging     

Rule-based design of a material processing component

The main thrust of this research is in developing aknowledge-based system for the design of components for a material processing system. In particular, this paper concentrates on developing methodologies forinitial design andredesign in a quantitative and qualitative format. A die for plastic extrusion has been selected as the subject material processing component. A design algorithm using best first heuristic search and expert knowledge, both in procedural and declarative form, is the core of the scheme. Apart from this expert, the suggestedselection procedure for candidate design is also seen to accelerate the design scheme. The methodologies presented enableefficient design of the component. Some generality has been accomplished by the implementation of the techniques to dies of different cross-sectional shapes. The software is written inLisp within an object-oriented software package using analysis modules written in C.     

Morphological control and polarization switching in polymer dispersed liquid crystal materials and devices

Liquid crystals dispersed in polymer systems constitute novel class of optical materials. The precise control of the liquid crystal droplet morphology in the polymer matrix is essentially required to meet the prerequisites of display device. Experiments have been carried out to investigate and identify the material properties and processing conditions required for the precise control of the droplet morphology of the dispersed liquid crystal systems. Polarization switching has been studied. Aligned liquid crystal dispersed systems showed higher polarization over unaligned ones.     

Ultra-smooth nanostructured diamond films deposited from He/H2/CH4/N2 microwave plasmas

Addition of He to a high CH4 content (10.7 vol%) H2/CH4/N2 feedgas mixture for microwave plasma chemical vapor deposition produced hard (58-72 GPa), ultra-smooth nanostructured diamond films on Ti-6AI-4V alloy substrates. Upon increase in He content up to 71 vol%, root mean squared (RMS) surface roughness of the film decreased to 9-10 nm and average diamond grain size to 5-6 nm. Our studies show that increased nanocrystallinity with He addition in plasma is related to plasma dilution, enhanced fragmentation of carbon containing species, and enhanced formation of CN radical.     

Influence of the angular shape of the volume-scattering function and multiple scattering on remote sensing reflectance

Scattering phase functions derived from measured (volume-scattering meter, VSM) volume-scattering functions (VSFs) from Crimean coastal waters were found to have systematic differences in angular structure from Fournier-Forand (FF) functions with equivalent backscattering ratios. Hydrolight simulations demonstrated that differences in the angular structure of the VSF could result in variations in modeled subsurface radiance reflectances of up to +/-20%. Furthermore, differences between VSM and FF simulated reflectances were found to be nonlinear as a function of scattering and could not be explained with the single-scattering approximation. Additional radiance transfer modeling demonstrated that the contribution of multiple scattering to radiance reflectance increased exponentially from a minimum of 16% for pure water to a maximum of approximately 94% for turbid waters. Monte Carlo simulations demonstrated that multiple forward-scattering events were the dominant contributors to the generation of radiance reflectance signals for turbid waters and that angular structures in the shape of the VSF at forward angles could have a significant influence in determining reflectance signals for turbid waters.     

Characterisation of the cross-linking process in an E-glass fibre/epoxy composite using evanescent wave spectroscopy

The term “self-sensing composites” is sometimes used to describe the case where the reinforcing glass fibres in advanced fibre-reinforced composites are used as the sensors for chemical process-monitoring (cure monitoring). This paper presents conclusive evidence to demonstrate that reinforcing E-glass fibres can be used for in situ cure monitoring. The cure behaviour of an epoxy/amine resin system was compared using evanescent wave spectroscopy via the reinforcing E-glass fibres and conventional transmission Fourier transform infrared spectroscopy. This paper also reports for the first time that evanescent wave spectroscopy via E-glass fibres can be used to detect the presence of silane coupling agents. Preliminary results indicated that the cure kinetics on the E-glass fibre surface, as observed using evanescent wave spectroscopy, were influenced by the silane coupling agent.