Purpose: The purpose of this paper is to examine the motives and emotions of Western tourists visiting Tuol Sleng Genocide Prison Museum in Phnom Penh, Cambodia and further contribute to a deeper understanding of the dark tourism consumption. Design/methodology/approach: Data were collected from popular travel blog sites. This study employs various qualitative and quantitative methods, such as netnography, semantic network analysis and critical content analysis in order to gain a deeper insight into the visitors’ emotions and motivations. Findings: This study reveals that people visit Tuol Sleng Genocide Museum mainly for “remembrance”, “worth visiting”, “learning and understanding”, “paying respect” and a “must visit” attraction. Emotions revealed in this study were “shocking“, “sadness“, “horror” and “depressive”. Research limitations/implications: This paper is limited to the analyses of travel blogs sites. Further research could include interviews with Western visitors, and professionals managing the site. Originality/value: To the best of the knowledge, this is the first study to examine the emotions of visitors in Tuol Sleng Genocide Museum.
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Differences in the oscillatory EEG dynamics of reading open class (OC) and closed class (CC) words have previously been found (Bastiaansen et al., 2005) and are thought to reflect differences in lexical-semantic content between these word classes. In particu-lar, the theta-band (4-7 Hz) seems to play a prominent role in lexical-semantic retrieval. We tested whether this theta effect is robust in an older population of subjects. Additionally, we examined how the context of a word can modulate the oscillatory dynamics underly-ing retrieval for the two different classes of words. Older participants (mean age 55) read words presented in either syntactically correct sentences or in a scrambled order ("scram-bled sentence") while their EEG was recorded. We performed time-frequency analysis to examine how power varied based on the context or class of the word. We observed larger power decreases in the alpha (8-12 Hz) band between 200-700 ms for the OC compared to CC words, but this was true only for the scrambled sentence context. We did not observe differences in theta power between these conditions. Context exerted an effect on the alpha and low beta (13-18 Hz) bands between 0 and 700 ms. These results suggest that the previously observed word class effects on theta power changes in a younger participant sample do not seem to be a robust effect in this older population. Though this is an indi-rect comparison between studies, it may suggest the existence of aging effects on word retrieval dynamics for different populations. Additionally, the interaction between word class and context suggests that word retrieval mechanisms interact with sentence-level comprehension mechanisms in the alpha-band.
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This essay is based on research promoted by INDIRE, Italian NationalInstitute for Documentation, Innovation and Educational Researchin Education, and is developed under the research on ‘Professionalnetworks, Educational models and School principal’s profile in Italy’. Onthe basis of observation and analysis of research data, a new theoryis assumed and new characteristics are defined, belonging to bothprofessional networks and educational models applied to all typesof professional networks. The characteristics so far identified are:plastic nature of networks, network punctuated equilibrium, networkconnectivity, emergent behavior and sociality of network members.It is also shown how the knowledge shared in a network materializes inEvents that produce Event Capital. The theory will be complemented byan experimentation phase.
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Prompt and timely response to incoming cyber-attacks and incidents is a core requirement for business continuity and safe operations for organizations operating at all levels (commercial, governmental, military). The effectiveness of these measures is significantly limited (and oftentimes defeated altogether) by the inefficiency of the attack identification and response process which is, effectively, a show-stopper for all attack prevention and reaction activities. The cognitive-intensive, human-driven alarm analysis procedures currently employed by Security Operation Centres are made ineffective (as opposed to only inefficient) by the sheer amount of alarm data produced, and the lack of mechanisms to automatically and soundly evaluate the arriving evidence to build operable risk-based metrics for incident response. This project will build foundational technologies to achieve Security Response Centres (SRC) based on three key components: (1) risk-based systems for alarm prioritization, (2) real-time, human-centric procedures for alarm operationalization, and (3) technology integration in response operations. In doing so, SeReNity will develop new techniques, methods, and systems at the intersection of the Design and Defence domains to deliver operable and accurate procedures for efficient incident response. To achieve this, this project will develop semantically and contextually rich alarm data to inform risk-based metrics on the mounting evidence of incoming cyber-attacks (as opposed to firing an alarm for each match of an IDS signature). SeReNity will achieve this by means of advanced techniques from machine learning and information mining and extraction, to identify attack patterns in the network traffic, and automatically identify threat types. Importantly, SeReNity will develop new mechanisms and interfaces to present the gathered evidence to SRC operators dynamically, and based on the specific threat (type) identified by the underlying technology. To achieve this, this project unifies Dutch excellence in intrusion detection, threat intelligence, and human-computer interaction with an industry-leading partner operating in the market of tailored solutions for Security Monitoring.
