FACSGen 2.0 animation software: generating three-dimensional FACS-valid facial expressions for emotion research

In this article, we present FACSGen 2.0, new animation software for creating static and dynamic threedimensional facial expressions on the basis of the Facial Action Coding System (FACS). FACSGen permits total control over the action units (AUs), which can be animated at all levels of intensity and applied alone or in combination to an infinite number of faces. In two studies, we tested the validity of the software for the AU appearance defined in the FACS manual and the conveyed emotionality of FACSGen expressions. In Experiment 1, four FACS-certified coders evaluated the complete set of 35 single AUs and 54 AU combinations for AU presence or absence, appearance quality, intensity, and asymmetry. In Experiment 2, lay participants performed a recognition task on emotional expressions created with FACSGen software and rated the similarity of expressions displayed by human and FACSGen faces. Results showed good to excellent classification levels for all AUs by the four FACS coders, suggesting that the AUs are valid exemplars of FACS specifications. Lay participants’ recognition rates for nine emotions were high, and comparisons of human and FACSGen expressions were very similar. The findings demonstrate the effectiveness of the software in producing reliable and emotionally valid expressions, and suggest its application in numerous scientific areas, including perception, emotion, and clinical and euroscience research.

Acceptable use policy and employee computer usage: case of Sri Lankan software development industry

Organizations introduce acceptable use policies to deter employee computer misuse. Despite the controlling, monitoring and other forms of interventions employed, some employees misuse the organizational computers to carry out their personal work such as sending emails, surfing internet, chatting, playing games etc. These activities not only waste productive time of employees but also bring a risk to the organization. A questionnaire was administrated to a random sample of employees selected from large and medium scale software development organizations, which measured the work computer misuse levels and the factors that influence such behavior. The presence of guidelines provided no evidence of significant effect on the level of employee computer misuse. Not having access to Internet /email away from work and organizational settings were identified to be the most significant influences of work computer misuse.

Random Prism: a noise-tolerant alternative to Random Forests

Ensemble learning can be used to increase the overall classification accuracy of a classifier by generating multiple base classifiers and combining their classification results. A frequently used family of base classifiers for ensemble learning are decision trees. However, alternative approaches can potentially be used, such as the Prism family of algorithms that also induces classification rules. Compared with decision trees, Prism algorithms generate modular classification rules that cannot necessarily be represented in the form of a decision tree. Prism algorithms produce a similar classification accuracy compared with decision trees. However, in some cases, for example, if there is noise in the training and test data, Prism algorithms can outperform decision trees by achieving a higher classification accuracy. However, Prism still tends to overfit on noisy data; hence, ensemble learners have been adopted in this work to reduce the overfitting. This paper describes the development of an ensemble learner using a member of the Prism family as the base classifier to reduce the overfitting of Prism algorithms on noisy datasets. The developed ensemble classifier is compared with a stand-alone Prism classifier in terms of classification accuracy and resistance to noise.

WCSC 2013: the 3rd World Chess Software Championship

The 3rd World Chess Software Championship took place in Yokohama, Japan during August 2013. It pits chess engines against each other on a common hardware platform - in this instance, the Intel i7 2740 Ivy Bridge with 16GB RAM supporting a potential eight processing threads. It was narrowly won by HIARCS from JUNIOR and PANDIX with JONNY, SHREDDER and MERLIN taking the remaining places. Games, occasionally annotated, are available here.

Software-based study of a non-sorting method for median calculation on a set of integer numbers

This paper presents a software-based study of a hardware-based non-sorting median calculation method on a set of integer numbers. The method divides the binary representation of each integer element in the set into bit slices in order to find the element located in the middle position. The method exhibits a linear complexity order and our analysis shows that the best performance in execution time is obtained when slices of 4-bit in size are used for 8-bit and 16-bit integers, in mostly any data set size. Results suggest that software implementation of bit slice method for median calculation outperforms sorting-based methods with increasing improvement for larger data set size. For data set sizes of N > 5, our simulations show an improvement of at least 40%.

Prescription software for recovery and rehabilitation using Microsoft Kinect

Brain injuries, including stroke, can be debilitating incidents with potential for severe long term effects; many people stop making significant progress once leaving in-patient medical care and are unable to fully restore their quality of life when returning home. The aim of this collaborative project, between the Royal Berkshire NHS Foundation Trust and the University of Reading, is to provide a low cost portable system that supports a patient's condition and their recovery in hospital or at home. This is done by providing engaging applications with targeted gameplay that is individually tailored to the rehabilitation of the patient's symptoms. The applications are capable of real-time data capture and analysis in order to provide information to therapists on patient progress and to further improve the personalized care that an individual can receive.

Effect of acceptable use policy on employee computer use : case of Sri Lankan software development organizations

It is a known fact that some employees misuse the organizational computers to do their personal work such as sending emails, surfing the Internet, chatting, playing games. These activities not only waste productive time of employees but also bring a risk factor to the organization. This affects organizations in the software industry very much as almost all of their employees are connected to the Internet throughout them day./ By introducing an Acceptable Use Policy (AUP) for an organization, it is believed that the computer misuse by its employees could be reduced. In many countries Acceptable Use Policies are used and they have been studied with various perspectives. In Sri Lankan context research on these areas are scarce. This research explored the situation in Sri Lanka with respect to AUPs and their effectiveness./ A descriptive study was carried out to identify the large and medium scale software development organizations that had implemented computer usage guidelines for employees. A questionnaire was used to gather information regarding employee’s usual computer usage behavior. Stratified random sampling was employed to draw a representative sample from the population./ Majority of the organizations have not employed a written guideline on acceptable use of work computers. The study results did not provide evidence to conclude that the presence or non presence of an AUP has a significant difference in computer use behaviors of employees. A significant negative correlation was observed between level of awareness about AUP and misuse. Access to the Internet and organizational settings were identified as significant factors that influence employee computer misuse behavior.

Growth of entrepreneurial software firms in cities

Despite the prediction of the demise of cities with the advance of new information and communication technologies in the New Economy, the software industry has emerged from cities in the USA, Europe and Asia in the past two decades. This article explores the reasons why cities are centers of software clusters, with reference to Boston, London and Dublin. It is suggested that cities' roles as centres of knowledge flows and creativity are the key determinants of their competitiveness in the knowledge-intensive software industry.

Software evolution: a graph based model

A model based on graph isomorphisms is used to formalize software evolution. Step by step we narrow the search space by an informed selection of the attributes based on the current state-of-the-art in software engineering and generate a seed solution. We then traverse the resulting space using graph isomorphisms and other set operations over the vertex sets. The new solutions will preserve the desired attributes. The goal of defining an isomorphism based search mechanism is to construct predictors of evolution that can facilitate the automation of ’software factory’ paradigm. The model allows for automation via software tools implementing the concepts.

Software evolution: a graph based model

A model based on graph isomorphisms is used to formalize software evolution. Step by step we narrow the search space by an informed selection of the attributes based on the current state-of-the-art in software engineering and generate a seed solution. We then traverse the resulting space using graph isomorphisms and other set operations over the vertex sets. The new solutions will preserve the desired attributes. The goal of defining an isomorphism based search mechanism is to construct predictors of evolution that can facilitate the automation of ’software factory’ paradigm. The model allows for automation via software tools implementing the concepts.

A scalable expressive ensemble learning using Random Prism: a MapReduce approach

The induction of classification rules from previously unseen examples is one of the most important data mining tasks in science as well as commercial applications. In order to reduce the influence of noise in the data, ensemble learners are often applied. However, most ensemble learners are based on decision tree classifiers which are affected by noise. The Random Prism classifier has recently been proposed as an alternative to the popular Random Forests classifier, which is based on decision trees. Random Prism is based on the Prism family of algorithms, which is more robust to noise. However, like most ensemble classification approaches, Random Prism also does not scale well on large training data. This paper presents a thorough discussion of Random Prism and a recently proposed parallel version of it called Parallel Random Prism. Parallel Random Prism is based on the MapReduce programming paradigm. The paper provides, for the first time, novel theoretical analysis of the proposed technique and in-depth experimental study that show that Parallel Random Prism scales well on a large number of training examples, a large number of data features and a large number of processors. Expressiveness of decision rules that our technique produces makes it a natural choice for Big Data applications where informed decision making increases the user’s trust in the system.

WCSC 2015: the world chess software championship

This is the official report of the ICGA's 2015 World Chess Software Championship held in Leiden, The Netherlands.

OntoMap: an ontology-based architecture to perform the semantic mapping between an interlingua and software components

This paper is about the use of natural language to communicate with computers. Most researches that have pursued this goal consider only requests expressed in English. A way to facilitate the use of several languages in natural language systems is by using an interlingua. An interlingua is an intermediary representation for natural language information that can be processed by machines. We propose to convert natural language requests into an interlingua [universal networking language (UNL)] and to execute these requests using software components. In order to achieve this goal, we propose OntoMap, an ontology-based architecture to perform the semantic mapping between UNL sentences and software components. OntoMap also performs component search and retrieval based on semantic information formalized in ontologies and rules.