The relationship between online game playing motivation and selection of online game characters – the case of Taiwan

The alarming growth rate in the online game industry calls for a need of understanding the determinants of online gamers’ behaviour. Investigating how online gamers choose different online characters assists online game vendors to design characters that match the needs of different online gamers. Recently, numerous online game designers have introduced celebrity figures as characters for certain online games. The popularity of those celebrities has resulted in greater awareness of these games, and hopefully further increases the playability of online games. While different online gamers are motivated by different desires for playing, it is insufficiently researched whether these online celebrity characters have actually altered players’ choice in giving preference to these games. Thus, this study conducts an experimental design to study the reasons behind players’ choice of characters by studying how online games perceive the interpersonal attractiveness of celebrity online characters, and how online gamers with different playing motivations display different behaviours in their choice of online game characters. Results from the survey filled out by participants after the experiments show that the attractiveness of celebrity online characters is significantly higher than that of non-celebrity characters. Further, online game players with a social playing motivation tend to choose celebrities as their online game characters.     

Using ontologies to perform threat analysis and develop defensive strategies for mobile security

Existing studies on the detection of mobile malware have focused mainly on static analyses performed to examine the code-structure signature of viruses, rather than the dynamic behavioral aspects. By contrast, the unidentified behavior of new mobile viruses using the self-modification, polymorphic, and mutation techniques for variants have largely been ignored. The problem of precision regarding malware variant detection has become one of the key concerns in mobile security. Accordingly, the present study proposed a threat risk analysis model for mobile viruses, using a heuristic approach incorporating both malware behavior analysis and code analysis to generate a virus behavior ontology associated with the Protégé platform. The proposed model can not only explicitly identify an attack profile in accordance with structural signature of mobile viruses, but also overcome the uncertainty regarding the probability of an attack being successful. This model is able to achieve this by extending frequent episode rules to investigate the attack profile of a given malware, using specific event sequences associated with the sandbox technique for mobile applications (apps) and hosts. For probabilistic analysis, defense evaluation metrics for each node were used to simulate the results of an attack. The simulations focused specifically on the attack profile of a botnet to assess the threat risk. The validity of the proposed approach was demonstrated numerically by using two malware cyber-attack examples. Overall, the results presented in this paper prove that the proposed scheme offers an effective countermeasure, evaluated using a set of security metrics, for mitigating network threats by considering the interaction between the attack profiles and defense needs.     

A sliding mode observer for uncertain nonlinear systems based on multiple models approach

This paper presents a method of state estimation for uncertain nonlinear systems described by multiple models approach. The uncertainties, supposed as norm bounded type, are caused by some parameters’ variations of the nonlinear system. Linear matrix inequalities (LMIs) have been established in order to ensure the stability conditions of the multiple observer which lead to determine the estimation gains. A sliding mode gain has been added in order to compensate the uncertainties. Numerical simulations through a state space model of a real process have been realized to show the robustness of the synthesized observer.     

Wire antennas optimized using genetic algorithm

In this work, wire antennas are designed to jam GSM frequencies using genetic algorithms. These antennas are designed to block communication at 3-band GSM frequencies. They are planned to be mounted on a vehicle and therefore are modeled on a ground plane. Jammer antennas designed in this work are composed of wires, placed on two square dielectric frames, perpendicular to each other. Genetic optimization routines are developed on MATLAB environment for the designs carried out in this work. Electromagnetic simulation program called SuperNEC, which analyses antennas by the method of moments, is used to determine the antenna performances and is called by the developed GA routines. The purpose of the antenna optimization is to obtain low VSWR values and omni-directional radiation pattern near ground at θ = [70° 80° 90°] planes at all GSM frequencies, since the targets will be near ground for this application. Original and interesting antenna designs are obtained as the result of genetic optimization, and are presented in the paper.     

Using RFID for the management of pharmaceutical inventory — system optimization and shrinkage control

Motivated by a case study at a radiology practice, we analyze the incremental benefits of RFID technology over barcodes for managing pharmaceutical inventories. Unlike barcode technology, RFID enables accurate real-time visibility, which in turn enables several process improvements. We analyze the impact of automatic counting and discuss the system redesign critical to optimizing the inventory policy and eliminating shrinkage. We show that continuous review is superior to periodic review whenever accurate real-time information is available at no additional cost. We explain how RFID-enabled strategies vary with inventory parameters and provide a cost-benefit analysis for the implementation of RFID for the radiology practice.     

Log-based mining techniques applied to Web service composition reengineering

Web service compositions are becoming more and more complex, involving numerous interacting ad-hoc services. These services are often implemented as business processes themselves. By analysing such complex web service compositions one is able to better understand, control and eventually re-design them. Our contribution to this problem is a mining algorithm, based on a statistical technique to discover composite web service patterns from execution logs. Our approach is characterised by a “local” pattern’s discovery that covers partial results through a dynamic programming algorithm. Those locally discovered patterns are then composed iteratively until the composite Web service is discovered. The analysis of the disparities between the discovered model and the initial ad-hoc composite model (delta-analysis) enables initial design gaps to be detected and thus to re-engineer the initial Web service composition.     

Privacy-preserving boosting

We describe two algorithms, BiBoost (Bipartite Boosting) and MultBoost (Multiparty Boosting), that allow two or more participants to construct a boosting classifier without explicitly sharing their data sets. We analyze both the computational and the security aspects of the algorithms. The algorithms inherit the excellent generalization performance of AdaBoost. Experiments indicate that the algorithms are better than AdaBoost executed separately by the participants, and that, independently of the number of participants, they perform close to AdaBoost executed using the entire data set. Responsible Editor: Charu Aggarwal.     

Electroclinical manifestations elicited by intracerebral electric stimulation "shocks" in temporal lobe epilepsy

In patients with severe drug-resistant partial epilepsy, undergoing Stereo-EEG investigations, spatial definition of the "epileptogenic area" is mainly based on spontaneous seizures recordings, but also on seizures induced by intracerebral electrical stimulation (ES). Only "trains" ES (TES, 50 pps) are currently used with this aim; "shocks" ES (SES, 1 pps) are principally applied to localize motor pathways. We have shown, during a prospective study concerning 10 temporal lobe epileptic patients, that SES could frequently induce seizures, especially when stimulation is applied in the anterior part of the Ammon's horn. Even if its efficacy seems lower than by TES, this kind of stimulation, in the majority of the cases, does reproduce isolated ictal subjective symptomatology, allowing the visualization of the progressive organisation of ictal electrical discharges, and avoids "unexpected" ("false positive"?) clinical responses.