Comment: Further sufficient conditions for an inverse relationship between productivity and employment

Extant empirical studies document that productivity gains due to technological progress often lead to reductions in employment. This paper rationalizes the stated empirical finding within the context of the theory of the competitive firm under price uncertainty. We show that technological progress affects employment adversely if the firm's coefficient of relative risk aversion is no less than unity and its production technology exhibits non-decreasing returns to scale. On the other hand, technological progress unambiguously increases output if the firm's preference has non-increasing absolute risk aversion. © 1999 Board of Trustees of the University of Illinois. All rights reserved.postprin

The Majority Report - Can we use big data to secure a better future?

With the widely adopted use of social media, it now becomes a common platform for calling supporters for civil unrest events. Despite the noble aims of these civil unrest events, sometimes these events might turn violent and disturb the daily lives of the general public. This paper aims to propose a conceptual framework regarding the study of using online social media data to predict offline civil unrest events. We propose to use time-series metrics as the prediction attributes instead of analyzing message contents because the message contents on social media are usually noisy, informal and not so easy to interpret. In the case of a data set containing both civil unrest event dates and normal dates, we found that it contains many more samples from the normal dates class than from the civil unrest event dates class. Thus, creating an imbalanced class problem. We showed using accuracy as the performance metrics could be misleading as civil unrest events were the minority class. Thus, we suggest to use additional tactics to handle the imbalanced class prediction problem. We propose to use a combination of oversampling the minority class and using feature selection techniques to tackle the imbalanced class problem. The current results demonstrate that use of time-series metrics to predict civil unrest events is a possible solution to the problems of handling the noise and unstructured format of social media data contents in the process of analysis and predictions. In addition, we have showed that the combination of special techniques to handle imbalanced class outperformed other classifiers without using such techniques.published_or_final_versio

Concerns on installing long-throw sprinklers in tall halls

There are concerns over long-throw sprinkler installation in halls with high ceilings which are likely to store large amount of combustible materials. These concerns will be addressed in this paper. At the moment, it is unknown whether such sprinkler installation can protect high-ceiling halls which store large amount of combustibles. The concept should be further explored with in-depth research through full-scale burning experiments with big fires.published_or_final_versio

The next generation for the forensic extraction of electronic evidence from mobile telephones

Electronic evidence extracted from a mobile telephone provide a wealth of information about the user. Before a court allows the trier of fact to consider the electronic evidence, the court must ensure that the subject matter, testimony of which is to be given, is scientific. Therefore, regard must, at the investigation stage, be given to fulfill the requirements of science and law, including international standards. Such compliance also moves the extraction of electronic evidence from mobile telephones into the next generation, a more rigorous position as a forensic science, by being able to give in court well- reasoned and concrete claims about the accuracy and validity of conclusions.published_or_final_versio

The Hong Kong Telephone Directory Enquiry System

Concerns the design and performance of the telephone directory enquiry system that has been newly adopted in Hong Kong. This system maintains three million telephone records and supports over 40,000 enquiries per hour at the peak. In Hong Kong society, the uses of English and Chinese (in particular, Cantonese) has been blending in a thrust of exciting language culture, giving rise to a variety of telephone enquires that traditional B-tree or hashing-based telephone directory enquiry systems fail to handle. The efficiency and flexibility achieved by the new system stem from hosting all indexing data structures in the main memory; these data structures occupy about half a giga-byte and would have been considered too expensive to be placed in main memory in the past.published_or_final_versio

Development of domestic and international computer forensics

With the increasing of computer crime, instant emergence of new digital product, new computer technology and computer forensics technology is promoted, developed constantly. This paper described basic information/content of computer forensics, and elaborated the development of current computer forensics at domestic and overseas market. The trends of computer forensics are pointed out and recent hot topics of research are introduced. © 2011 IEEE.published_or_final_versionThe 7th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2011), Dalian, China, 14-16 October 2011. In Proceedings of the 7th IIH-MSP, 2011, p. 388-39

Software pirates: a criminal investigation

Computer program infringing materials are difficult to identify. There are common techniques to disguise the origin of copied codes. In order to decide on a legal basis whether a substantial part of copyright work has been taken, it is necessary to consider both the quality and quantity of the part taken. Various researches have carried out in relation to authorship identification and plagiarism identification. In a criminal case in Hong Kong, we used a common software to compare files contents and folders between a copyright work and the infringing copy instead of complex and technical metrics. We conclude that the source codes of the defendant started from the source codes of his previous employer using simple and easy to understand measurements. Though the magistrate was satisfied beyond reasonable doubt of the defendant’s guilt, the evidence in the case did not enable a scientific calculation in respect of the likelihood that a computer program may look like a derivative of another program by chance.postprintThe 33rd ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2012), Beijing, China, 11-16 June 2012. In Proceedings of the PLDI, 2012, p. 1-1

A Novel Object Segmentation Method for Silhouette Tracker in Video Surveillance Application

In recent years, surveillance cameras are deployed almost everywhere. More and more video analytics features have been developed and incorporated with video surveillance system for conducting intelligence tasks, such as motion detection, human identification, etc. One typical requirement is to track suspicious humans or vehicles in the cameras' live or recorded footages, and over the years researchers have proposed different tracking methods, such as point tracking, kernel tracking and silhouette tracking to support this requirement. In particular, silhouette tracker has received considerable attention because it works well for objects with a large variety of shape, provided that reasonably good object masks or contours are initialized properly for the silhouette tracker. A properly initialized object mask and contour, however, cannot be obtained easily. On one hand, a simple bounding box contains too much irrelevant background objects, while a manually specified mask could provide accurate silhouette but this also requires lots of interactive which greatly limits its practicality. In this paper, we present a novel block based object mask segmentation method for silhouette tracker initialization. Essentially, the proposed method re-uses the motion information extracted during the video encoding phase, which provides approximated object masks for silhouette tracker. Experimental results confirm that such a block-based object masks is sufficient for a robust silhouette tracker to reliably track moving objects. © 2014 IEEE.published_or_final_versio

Selection of Temporal Aligned Video Frames for Video Stitching Application

Multi-view image/video stitching algorithm is an extensive research area in computer vision and image based rendering. Most researches focus on stitching the images from different views with assumption that those images have been already aligned in temporal domain. However it is not the case in real application. If the images from different views are not aligned in temporal domain, or in another words, not time synchronized, the corresponding feature points or regions will not be located correctly among different views, which will result in ghost objects appearing in the final stitching/rendering result. In this paper, we present an epipolar geometry consistency scoring scheme to guide temporal aligned video frame pair selection for multi-view video stitching application. Essentially, the proposed scheme allows us to determine whether a given pair of video frames is temporally aligned well for video stitching. Experimental results confirm that better video stitching results can be obtained with the proposed scheme in place.published_or_final_versio

Learning domain-specific sentiment lexicon with supervised sentiment-aware LDA

Frontiers in Artificial Intelligence and Applications, v. 263 entitled: ECAI 2014: 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic - Including Prestigious Applications of Intelligent Systems (PAIS 2014)Analyzing and understanding people's sentiments towards different topics has become an interesting task due to the explosion of opinion-rich resources. In most sentiment analysis applications, sentiment lexicons play a crucial role, to be used as metadata of sentiment polarity. However, most previous works focus on discovering general-purpose sentiment lexicons. They cannot capture domain-specific sentiment words, or implicit and connotative sentiment words that are seemingly objective. In this paper, we propose a supervised sentiment-aware LDA model (ssLDA). The model uses a minimal set of domain-independent seed words and document labels to discover a domain-specific lexicon, learning a lexicon much richer and adaptive to the sentiment of specific document. Experiments on two publicly-available datasets (movie reviews and Obama-McCain debate dataset) show that our model is effective in constructing a comprehensive and high-quality domain-specific sentiment lexicon. Furthermore, the resulting lexicon significantly improves the performance of sentiment classification tasks. © 2014 The Authors and IOS Press.published_or_final_versio