Local contrast as an effective means to robust clustering against varying densities
- Chen, Bo, Ting, Kaiming, Washio, Takashi, Zhu, Ye
- Authors: Chen, Bo , Ting, Kaiming , Washio, Takashi , Zhu, Ye
- Date: 2018
- Type: Text , Journal article
- Relation: Machine Learning Vol. 107, no. 8-10 (2018), p. 1621-1645
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- Description: Most density-based clustering methods have difficulties detecting clusters of hugely different densities in a dataset. A recent density-based clustering CFSFDP appears to have mitigated the issue. However, through formalising the condition under which it fails, we reveal that CFSFDP still has the same issue. To address this issue, we propose a new measure called Local Contrast, as an alternative to density, to find cluster centers and detect clusters. We then apply Local Contrast to CFSFDP, and create a new clustering method called LC-CFSFDP which is robust in the presence of varying densities. Our empirical evaluation shows that LC-CFSFDP outperforms CFSFDP and three other state-of-the-art variants of CFSFDP. © 2018, The Author(s).
- Authors: Chen, Bo , Ting, Kaiming , Washio, Takashi , Zhu, Ye
- Date: 2018
- Type: Text , Journal article
- Relation: Machine Learning Vol. 107, no. 8-10 (2018), p. 1621-1645
- Full Text:
- Reviewed:
- Description: Most density-based clustering methods have difficulties detecting clusters of hugely different densities in a dataset. A recent density-based clustering CFSFDP appears to have mitigated the issue. However, through formalising the condition under which it fails, we reveal that CFSFDP still has the same issue. To address this issue, we propose a new measure called Local Contrast, as an alternative to density, to find cluster centers and detect clusters. We then apply Local Contrast to CFSFDP, and create a new clustering method called LC-CFSFDP which is robust in the presence of varying densities. Our empirical evaluation shows that LC-CFSFDP outperforms CFSFDP and three other state-of-the-art variants of CFSFDP. © 2018, The Author(s).
PCA based population generation for genetic network optimization
- Youseph, Ahammed, Chetty, Madhu, Karmakar, Gour
- Authors: Youseph, Ahammed , Chetty, Madhu , Karmakar, Gour
- Date: 2018
- Type: Text , Journal article
- Relation: Cognitive Neurodynamics Vol. 12, no. 4 (2018), p. 417-429
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- Description: A gene regulatory network (GRN) represents a set of genes and its regulatory interactions. The inference of the regulatory interactions between genes is usually carried out using an appropriate mathematical model and the available gene expression profile. Among the various models proposed for GRN inference, our recently proposed Michaelis–Menten based ODE model provides a good trade-off between the computational complexity and biological relevance. This model, like other known GRN models, also uses an evolutionary algorithm for parameter estimation. Considering various issues associated with such population based stochastic optimization approaches (e.g. diversity, premature convergence due to local optima, accuracy, etc.), it becomes important to seed the initial population with good individuals which are closer to the optimal solution. In this paper, we exploit the inherent strength of principal component analysis (PCA) in a novel manner to initialize the population for GRN optimization. The benefit of the proposed method is validated by reconstructing in silico and in vivo networks of various sizes. For the same level of accuracy, the approach with PCA based initialization shows improved convergence speed.
- Authors: Youseph, Ahammed , Chetty, Madhu , Karmakar, Gour
- Date: 2018
- Type: Text , Journal article
- Relation: Cognitive Neurodynamics Vol. 12, no. 4 (2018), p. 417-429
- Full Text:
- Reviewed:
- Description: A gene regulatory network (GRN) represents a set of genes and its regulatory interactions. The inference of the regulatory interactions between genes is usually carried out using an appropriate mathematical model and the available gene expression profile. Among the various models proposed for GRN inference, our recently proposed Michaelis–Menten based ODE model provides a good trade-off between the computational complexity and biological relevance. This model, like other known GRN models, also uses an evolutionary algorithm for parameter estimation. Considering various issues associated with such population based stochastic optimization approaches (e.g. diversity, premature convergence due to local optima, accuracy, etc.), it becomes important to seed the initial population with good individuals which are closer to the optimal solution. In this paper, we exploit the inherent strength of principal component analysis (PCA) in a novel manner to initialize the population for GRN optimization. The benefit of the proposed method is validated by reconstructing in silico and in vivo networks of various sizes. For the same level of accuracy, the approach with PCA based initialization shows improved convergence speed.
When suddenly nothing works anymore within a team - Causes of collective sport team collapse
- Wergin, Vanessa, Zimanyi, Zsuzsanna, Mesagno, Christopher, Beckmann, Jurgen
- Authors: Wergin, Vanessa , Zimanyi, Zsuzsanna , Mesagno, Christopher , Beckmann, Jurgen
- Date: 2018
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 9, no. NOV (2018), p. 1-14
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- Description: Collective team collapse occurs when multiple players of a sport team experience a sudden and extreme underperformance within a game. To date, minimal research has been conducted on the causes of collective team collapse. Thus, goals of this study were to explore perceived causes of collective team collapse in different sports and to define team collapse in contrast to negative momentum. To investigate factors causing and maintaining collective sport team collapse, an inductive, exploratory qualitative analysis of individual interviews was conducted. Semi-structured interviews were carried out with 10 athletes of professional German teams of various sports playing in between first and fourth division. Participants were interviewed about a team collapse event they had experienced with their team during the past year. Data were collected and analyzed using a grounded theory methodology. Collective team collapse appeared to be induced by a temporal cascade of causes rather than by single triggers. This cascade included antecedents, which represent factors that make the occurrence of a team collapse more likely; critical events, which include specific events within the game that trigger a team collapse; as well as affective, cognitive, and behavioral outcomes that foster a maintenance of the collapse. Within this theoretical framework, social factors, such as decreased performance contagion or emotional contagion, played crucial roles in causing a team collapse. These results illustrate that collective team collapse is more than the sum of individual choking of multiple players at the same time. In conclusion, a new definition, differentiating team collapse from negative momentum, is introduced. Furthermore, a process model of causes of collective team collapse is proposed. The results provide first insights into causes of collective collapse in a variety of team sports. The developed model is supposed to help future research to better connect to practice and to support athletes, coaches, and sport psychologists.
- Authors: Wergin, Vanessa , Zimanyi, Zsuzsanna , Mesagno, Christopher , Beckmann, Jurgen
- Date: 2018
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 9, no. NOV (2018), p. 1-14
- Full Text:
- Reviewed:
- Description: Collective team collapse occurs when multiple players of a sport team experience a sudden and extreme underperformance within a game. To date, minimal research has been conducted on the causes of collective team collapse. Thus, goals of this study were to explore perceived causes of collective team collapse in different sports and to define team collapse in contrast to negative momentum. To investigate factors causing and maintaining collective sport team collapse, an inductive, exploratory qualitative analysis of individual interviews was conducted. Semi-structured interviews were carried out with 10 athletes of professional German teams of various sports playing in between first and fourth division. Participants were interviewed about a team collapse event they had experienced with their team during the past year. Data were collected and analyzed using a grounded theory methodology. Collective team collapse appeared to be induced by a temporal cascade of causes rather than by single triggers. This cascade included antecedents, which represent factors that make the occurrence of a team collapse more likely; critical events, which include specific events within the game that trigger a team collapse; as well as affective, cognitive, and behavioral outcomes that foster a maintenance of the collapse. Within this theoretical framework, social factors, such as decreased performance contagion or emotional contagion, played crucial roles in causing a team collapse. These results illustrate that collective team collapse is more than the sum of individual choking of multiple players at the same time. In conclusion, a new definition, differentiating team collapse from negative momentum, is introduced. Furthermore, a process model of causes of collective team collapse is proposed. The results provide first insights into causes of collective collapse in a variety of team sports. The developed model is supposed to help future research to better connect to practice and to support athletes, coaches, and sport psychologists.
A logical approach to experience-based reasoning
- Authors: Sun, Zhaohao
- Date: 2017
- Type: Text , Journal article , Review
- Relation: New Mathematics and Natural Computation Vol. 13, no. 1 (2017), p. 21-40
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- Description: Experience-based reasoning (EBR) is a paradigm used in almost every human activity as a part of human reasoning. However, EBR has not been seriously studied from a logical viewpoint. This paper will attempt to fill this gap by providing a unified logical approach to EBR. More specifically, this paper first examines EBR and inference rules. Then it proposes eight different rules of inference for EBR, which cover all possible EBRs from a logical viewpoint. These eight different rules of inference constitute the fundamentals for all EBR paradigms, and therefore will be the theoretical foundation for EBR. The proposed approach will facilitate research and development of EBR, human reasoning, and common sense reasoning. © 2017 World Scientific Publishing Company.
- Authors: Sun, Zhaohao
- Date: 2017
- Type: Text , Journal article , Review
- Relation: New Mathematics and Natural Computation Vol. 13, no. 1 (2017), p. 21-40
- Full Text:
- Reviewed:
- Description: Experience-based reasoning (EBR) is a paradigm used in almost every human activity as a part of human reasoning. However, EBR has not been seriously studied from a logical viewpoint. This paper will attempt to fill this gap by providing a unified logical approach to EBR. More specifically, this paper first examines EBR and inference rules. Then it proposes eight different rules of inference for EBR, which cover all possible EBRs from a logical viewpoint. These eight different rules of inference constitute the fundamentals for all EBR paradigms, and therefore will be the theoretical foundation for EBR. The proposed approach will facilitate research and development of EBR, human reasoning, and common sense reasoning. © 2017 World Scientific Publishing Company.
Growth mixture modeling of depression symptoms following traumatic brain injury
- Gomez, Rapson, Skilbeck, Clive, Thomas, Matt, Slatyer, Mark
- Authors: Gomez, Rapson , Skilbeck, Clive , Thomas, Matt , Slatyer, Mark
- Date: 2017
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 8, no. AUG (2017), p. 1-14
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- Description: Growth Mixture Modeling (GMM) was used to investigate the longitudinal trajectory of groups (classes) of depression symptoms, and how these groups were predicted by the covariates of age, sex, severity, and length of hospitalization following Traumatic Brain Injury (TBI) in a group of 1074 individuals (696 males, and 378 females) from the Royal Hobart Hospital, who sustained a TBI. The study began in late December 2003 and recruitment continued until early 2007. Ages ranged from 14 to 90 years, with a mean of 35.96 years (SD = 16.61). The study also examined the associations between the groups and causes of TBI. Symptoms of depression were assessed using the Hospital Anxiety and Depression Scale within 3 weeks of injury, and at 1, 3, 6, 12, and 24 months post-injury. The results revealed three groups: low, high, and delayed depression. In the low group depression scores remained below the clinical cut-off at all assessment points during the 24-months post-TBI, and in the high group, depression scores were above the clinical cut-off at all assessment points. The delayed group showed an increase in depression symptoms to 12 months after injury, followed by a return to initial assessment level during the following 12 months. Covariates were found to be differentially associated with the three groups. For example, relative to the low group, the high depression group was associated with more severe TBI, being female, and a shorter period of hospitalization. The delayed group also had a shorter period of hospitalization, were younger, and sustained less severe TBI. Our findings show considerable fluctuation of depression over time, and that a non-clinical level of depression at any one point in time does not necessarily mean that the person will continue to have non-clinical levels in the future. As we used GMM, we were able to show new findings and also bring clarity to contradictory past findings on depression and TBI. Consequently, we recommend the use of this approach in future studies in this area. © 2017 Gomez, Skilbeck, Thomas and Slatyer.
- Authors: Gomez, Rapson , Skilbeck, Clive , Thomas, Matt , Slatyer, Mark
- Date: 2017
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 8, no. AUG (2017), p. 1-14
- Full Text:
- Reviewed:
- Description: Growth Mixture Modeling (GMM) was used to investigate the longitudinal trajectory of groups (classes) of depression symptoms, and how these groups were predicted by the covariates of age, sex, severity, and length of hospitalization following Traumatic Brain Injury (TBI) in a group of 1074 individuals (696 males, and 378 females) from the Royal Hobart Hospital, who sustained a TBI. The study began in late December 2003 and recruitment continued until early 2007. Ages ranged from 14 to 90 years, with a mean of 35.96 years (SD = 16.61). The study also examined the associations between the groups and causes of TBI. Symptoms of depression were assessed using the Hospital Anxiety and Depression Scale within 3 weeks of injury, and at 1, 3, 6, 12, and 24 months post-injury. The results revealed three groups: low, high, and delayed depression. In the low group depression scores remained below the clinical cut-off at all assessment points during the 24-months post-TBI, and in the high group, depression scores were above the clinical cut-off at all assessment points. The delayed group showed an increase in depression symptoms to 12 months after injury, followed by a return to initial assessment level during the following 12 months. Covariates were found to be differentially associated with the three groups. For example, relative to the low group, the high depression group was associated with more severe TBI, being female, and a shorter period of hospitalization. The delayed group also had a shorter period of hospitalization, were younger, and sustained less severe TBI. Our findings show considerable fluctuation of depression over time, and that a non-clinical level of depression at any one point in time does not necessarily mean that the person will continue to have non-clinical levels in the future. As we used GMM, we were able to show new findings and also bring clarity to contradictory past findings on depression and TBI. Consequently, we recommend the use of this approach in future studies in this area. © 2017 Gomez, Skilbeck, Thomas and Slatyer.
Sending nudes : Sex, self-rated mate value, and trait Machiavellianism predict sending unsolicited explicit images
- March, Evita, Wagstaff, Danielle
- Authors: March, Evita , Wagstaff, Danielle
- Date: 2017
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 8, no. DEC (2017), p. 1-6
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- Description: Modern dating platforms have given rise to new dating and sexual behaviors. In the current study, we examine predictors of sending unsolicited explicit images, a particularly underexplored online sexual behavior. The aim of the current study was to explore the utility of dark personality traits (i.e., narcissism, Machiavellianism, psychopathy, and sadism) and self-rated mate value in predicting attitudes toward and behavior of sending unsolicited explicit images. Two hundred and forty participants (72% female; Mage = 25.96, SD = 9.79) completed an online questionnaire which included a measure of self-rated mate value, a measure of dark personality traits, and questions regarding sending unsolicited explicit images (operationalized as the explicit image scale). Men, compared to women, were found to have higher explicit image scale scores, and both self-rated mate value and trait Machiavellianism were positive predictors of explicit image scale scores. Interestingly, there were no significant interactions between sex and these variables. Further, Machiavellianism mediated all relationships between other dark traits and explicit image scale scores, indicating this behavior is best explained by the personality trait associated with behavioral strategies. In sum, these results provide support for the premise that sending unsolicited explicit images may be a tactic of a short-term mating strategy; however, future research should further explore this claim. © 2017 March and Wagstaff.
- Authors: March, Evita , Wagstaff, Danielle
- Date: 2017
- Type: Text , Journal article
- Relation: Frontiers in Psychology Vol. 8, no. DEC (2017), p. 1-6
- Full Text:
- Reviewed:
- Description: Modern dating platforms have given rise to new dating and sexual behaviors. In the current study, we examine predictors of sending unsolicited explicit images, a particularly underexplored online sexual behavior. The aim of the current study was to explore the utility of dark personality traits (i.e., narcissism, Machiavellianism, psychopathy, and sadism) and self-rated mate value in predicting attitudes toward and behavior of sending unsolicited explicit images. Two hundred and forty participants (72% female; Mage = 25.96, SD = 9.79) completed an online questionnaire which included a measure of self-rated mate value, a measure of dark personality traits, and questions regarding sending unsolicited explicit images (operationalized as the explicit image scale). Men, compared to women, were found to have higher explicit image scale scores, and both self-rated mate value and trait Machiavellianism were positive predictors of explicit image scale scores. Interestingly, there were no significant interactions between sex and these variables. Further, Machiavellianism mediated all relationships between other dark traits and explicit image scale scores, indicating this behavior is best explained by the personality trait associated with behavioral strategies. In sum, these results provide support for the premise that sending unsolicited explicit images may be a tactic of a short-term mating strategy; however, future research should further explore this claim. © 2017 March and Wagstaff.
Group decision making in health care : A case study of multidisciplinary meetings
- Sharma, Vishakha, Stranieri, Andrew, Burstein, Frada, Warren, Jim, Daly, Sharon, Patterson, Louise, Yearwood, John, Wolff, Alan
- Authors: Sharma, Vishakha , Stranieri, Andrew , Burstein, Frada , Warren, Jim , Daly, Sharon , Patterson, Louise , Yearwood, John , Wolff, Alan
- Date: 2016
- Type: Text , Journal article
- Relation: Journal of Decision Systems Vol. 25, no. (2016), p. 476-485
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- Description: Abstract: Recent studies have demonstrated that Multi-Disciplinary Meetings (MDM) practiced in some medical contexts can contribute to positive health care outcomes. The group reasoning and decision-making in MDMs has been found to be most effective when deliberations revolve around the patient’s needs, comprehensive information is available during the meeting, core members attend and the MDM is effectively facilitated. This article presents a case study of the MDMs in cancer care in a region of Australia. The case study draws on a group reasoning model called the Reasoning Community model to analyse MDM deliberations to illustrate that many factors are important to support group reasoning, not solely the provision of pertinent information. The case study has implications for the use of data analytics in any group reasoning context. © 2016 Informa UK Limited, trading as Taylor & Francis Group.
- Authors: Sharma, Vishakha , Stranieri, Andrew , Burstein, Frada , Warren, Jim , Daly, Sharon , Patterson, Louise , Yearwood, John , Wolff, Alan
- Date: 2016
- Type: Text , Journal article
- Relation: Journal of Decision Systems Vol. 25, no. (2016), p. 476-485
- Full Text:
- Reviewed:
- Description: Abstract: Recent studies have demonstrated that Multi-Disciplinary Meetings (MDM) practiced in some medical contexts can contribute to positive health care outcomes. The group reasoning and decision-making in MDMs has been found to be most effective when deliberations revolve around the patient’s needs, comprehensive information is available during the meeting, core members attend and the MDM is effectively facilitated. This article presents a case study of the MDMs in cancer care in a region of Australia. The case study draws on a group reasoning model called the Reasoning Community model to analyse MDM deliberations to illustrate that many factors are important to support group reasoning, not solely the provision of pertinent information. The case study has implications for the use of data analytics in any group reasoning context. © 2016 Informa UK Limited, trading as Taylor & Francis Group.
Wake-up timer and binary exponential backoff for ZigBee-based wireless sensor network for flexible movement control system of a self-lifting scaffold
- Liang, Hua, Yang, Guangxiang, Xu, Ye, Gondal, Iqbal, Wu, Chao
- Authors: Liang, Hua , Yang, Guangxiang , Xu, Ye , Gondal, Iqbal , Wu, Chao
- Date: 2016
- Type: Text , Journal article
- Relation: International Journal of Distributed Sensor Networks Vol. 12, no. 9 (2016), p. 1-12
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- Description: Synchronous movement of attached self-lifting scaffolds is traditionally monitored with wired sensors in high-rise building construction, which limits their flexibility of movements. A ZigBee-based wireless sensor system has been suggested in this article to prove the effectiveness of wireless sensor networks in actual implementation. Two optoelectronic sensors are integrated into a ZigBee node for measuring the displacement of attached self-lifting scaffolds. The proposed wireless sensor network combines an end device and a coordinator to allow easy replacement of sensors as compared to a wired network. A wake-up timer algorithm is proposed to reduce the transmitting power during continuous wireless data communication in the wireless sensor network. Furthermore, a variant binary exponential backoff transmission algorithm for data loss avoidance is proposed. The variant binary exponential backoff algorithm reduces packet collisions during simultaneous access by increasing the randomizing moments at nodes attempting to access the wireless channels. The performance of three of the proposed modules - a cable sensor, a 315-MHz sensor, and a ZigBee sensor - is evaluated in terms of packet delivery ratio and the end-to-end delay of a ZigBee-based wireless sensor network. The experimental results show that the proposed variant binary exponential backoff transmission algorithm achieves a higher packet delivery ratio at the cost of higher delays. The average cost of the developed ZigBee-based wireless sensor network decreased by 24% compared with the cable sensor. The power consumption of ZigBee is approximately 53.75% of the 315-MHz sensor. The average current consumption is reduced by approximately 1.5 mA with the wake-up timer algorithm at the same sampling rate. © The Author(s) 2016.
- Authors: Liang, Hua , Yang, Guangxiang , Xu, Ye , Gondal, Iqbal , Wu, Chao
- Date: 2016
- Type: Text , Journal article
- Relation: International Journal of Distributed Sensor Networks Vol. 12, no. 9 (2016), p. 1-12
- Full Text:
- Reviewed:
- Description: Synchronous movement of attached self-lifting scaffolds is traditionally monitored with wired sensors in high-rise building construction, which limits their flexibility of movements. A ZigBee-based wireless sensor system has been suggested in this article to prove the effectiveness of wireless sensor networks in actual implementation. Two optoelectronic sensors are integrated into a ZigBee node for measuring the displacement of attached self-lifting scaffolds. The proposed wireless sensor network combines an end device and a coordinator to allow easy replacement of sensors as compared to a wired network. A wake-up timer algorithm is proposed to reduce the transmitting power during continuous wireless data communication in the wireless sensor network. Furthermore, a variant binary exponential backoff transmission algorithm for data loss avoidance is proposed. The variant binary exponential backoff algorithm reduces packet collisions during simultaneous access by increasing the randomizing moments at nodes attempting to access the wireless channels. The performance of three of the proposed modules - a cable sensor, a 315-MHz sensor, and a ZigBee sensor - is evaluated in terms of packet delivery ratio and the end-to-end delay of a ZigBee-based wireless sensor network. The experimental results show that the proposed variant binary exponential backoff transmission algorithm achieves a higher packet delivery ratio at the cost of higher delays. The average cost of the developed ZigBee-based wireless sensor network decreased by 24% compared with the cable sensor. The power consumption of ZigBee is approximately 53.75% of the 315-MHz sensor. The average current consumption is reduced by approximately 1.5 mA with the wake-up timer algorithm at the same sampling rate. © The Author(s) 2016.
Advances in multimedia sensor networks for health-care and related applications
- Hossain, M. Shamim, Pathan, Al-Sakib, Goebel, Stefan, Rahman, Shawon, Murshed, Manzur
- Authors: Hossain, M. Shamim , Pathan, Al-Sakib , Goebel, Stefan , Rahman, Shawon , Murshed, Manzur
- Date: 2015
- Type: Text , Journal article , Editorial
- Relation: International Journal of Distributed Sensor Networks Vol. 2015, no. (2015), p. 1-2
- Full Text:
- Reviewed:
- Description: Multimedia sensor services and technologies play an important role in seamlessly providing andmanaging health, sports, and other services to anyone, everywhere, and anytime. Media sensors are usually equipped with cameras, microphones, and other devices that produce media content and services. Such services and technologies enable caregivers and related professionals to have immediate access to required information for efficient decision making. Since media sensing technology development is growing, many research opportunities are emerging in a broad spectrum of application domains.
- Authors: Hossain, M. Shamim , Pathan, Al-Sakib , Goebel, Stefan , Rahman, Shawon , Murshed, Manzur
- Date: 2015
- Type: Text , Journal article , Editorial
- Relation: International Journal of Distributed Sensor Networks Vol. 2015, no. (2015), p. 1-2
- Full Text:
- Reviewed:
- Description: Multimedia sensor services and technologies play an important role in seamlessly providing andmanaging health, sports, and other services to anyone, everywhere, and anytime. Media sensors are usually equipped with cameras, microphones, and other devices that produce media content and services. Such services and technologies enable caregivers and related professionals to have immediate access to required information for efficient decision making. Since media sensing technology development is growing, many research opportunities are emerging in a broad spectrum of application domains.
REPLOT : REtrieving Profile Links on Twitter for malicious campaign discovery
- Perez, Charles, Birregah, Babiga, Layton, Robert, Lemercier, Marc, Watters, Paul
- Authors: Perez, Charles , Birregah, Babiga , Layton, Robert , Lemercier, Marc , Watters, Paul
- Date: 2015
- Type: Text , Journal article
- Relation: AI Communications Vol. 29, no. 1 (2015), p. 107-122
- Full Text:
- Reviewed:
- Description: Social networking sites are increasingly subject to malicious activities such as self-propagating worms, confidence scams and drive-by-download malwares. The high number of users associated with the presence of sensitive data, such as personal or professional information, is certainly an unprecedented opportunity for attackers. These attackers are moving away from previous platforms of attack, such as emails, towards social networking websites. In this paper, we present a full stack methodology for the identification of campaigns of malicious profiles on social networking sites, composed of maliciousness classification, campaign discovery and attack profiling. The methodology named REPLOT, for REtrieving Profile Links On Twitter, contains three major phases. First, profiles are analysed to determine whether they are more likely to be malicious or benign. Second, connections between suspected malicious profiles are retrieved using a late data fusion approach consisting of temporal and authorship analysis based models to discover campaigns. Third, the analysis of the discovered campaigns is performed to investigate the attacks. In this paper, we apply this methodology to a real world dataset, with a view to understanding the links between malicious profiles, their attack methods and their connections. Our analysis identifies a cluster of linked profiles focusing on propagating malicious links, as well as profiling two other major clusters of attacking campaigns. © 2016 - IOS Press and the authors. All rights reserved.
- Authors: Perez, Charles , Birregah, Babiga , Layton, Robert , Lemercier, Marc , Watters, Paul
- Date: 2015
- Type: Text , Journal article
- Relation: AI Communications Vol. 29, no. 1 (2015), p. 107-122
- Full Text:
- Reviewed:
- Description: Social networking sites are increasingly subject to malicious activities such as self-propagating worms, confidence scams and drive-by-download malwares. The high number of users associated with the presence of sensitive data, such as personal or professional information, is certainly an unprecedented opportunity for attackers. These attackers are moving away from previous platforms of attack, such as emails, towards social networking websites. In this paper, we present a full stack methodology for the identification of campaigns of malicious profiles on social networking sites, composed of maliciousness classification, campaign discovery and attack profiling. The methodology named REPLOT, for REtrieving Profile Links On Twitter, contains three major phases. First, profiles are analysed to determine whether they are more likely to be malicious or benign. Second, connections between suspected malicious profiles are retrieved using a late data fusion approach consisting of temporal and authorship analysis based models to discover campaigns. Third, the analysis of the discovered campaigns is performed to investigate the attacks. In this paper, we apply this methodology to a real world dataset, with a view to understanding the links between malicious profiles, their attack methods and their connections. Our analysis identifies a cluster of linked profiles focusing on propagating malicious links, as well as profiling two other major clusters of attacking campaigns. © 2016 - IOS Press and the authors. All rights reserved.
Understanding personal use of the Internet at work: An integrated model of neutralization techniques and general deterrence theory
- Cheng, Lijiao, Li, Wenli, Zhai, Qingguo, Smyth, Russell
- Authors: Cheng, Lijiao , Li, Wenli , Zhai, Qingguo , Smyth, Russell
- Date: 2014
- Type: Text , Journal article
- Relation: Computers in Human Behavior Vol. 38, no. (September 2014 2014), p. 220-228
- Full Text:
- Reviewed:
- Description: This paper examines the influence of neutralization techniques, perceived sanction severity, perceived detection certainty and perceived benefits of using the Internet for personal purposes on intention to use the Internet at work for personal use. To do so, we draw on a conceptual framework integrating neutralization theory and general deterrence theory. The study finds that both neutralization techniques and perceived benefits have a positive effect on personal use of the Internet. Perceived detection certainty is found to have a negative effect on personal use of the Internet, while the effect of perceived sanctions severity on personal use of the Internet is not significant. The effect of neutralization and perceived benefits are much stronger than perceived detection certainty. The findings suggest that people may think more about neutralization and perceived benefits than they do about costs, when deciding whether to use the Internet at work for personal purposes.
- Description: C1
- Authors: Cheng, Lijiao , Li, Wenli , Zhai, Qingguo , Smyth, Russell
- Date: 2014
- Type: Text , Journal article
- Relation: Computers in Human Behavior Vol. 38, no. (September 2014 2014), p. 220-228
- Full Text:
- Reviewed:
- Description: This paper examines the influence of neutralization techniques, perceived sanction severity, perceived detection certainty and perceived benefits of using the Internet for personal purposes on intention to use the Internet at work for personal use. To do so, we draw on a conceptual framework integrating neutralization theory and general deterrence theory. The study finds that both neutralization techniques and perceived benefits have a positive effect on personal use of the Internet. Perceived detection certainty is found to have a negative effect on personal use of the Internet, while the effect of perceived sanctions severity on personal use of the Internet is not significant. The effect of neutralization and perceived benefits are much stronger than perceived detection certainty. The findings suggest that people may think more about neutralization and perceived benefits than they do about costs, when deciding whether to use the Internet at work for personal purposes.
- Description: C1
Activation of self-focus and self-presentation traits under private, mixed, and public pressure
- Geukes, Katharina, Mesagno, Christopher, Hanrahan, Stephanie, Kellmann, Michael
- Authors: Geukes, Katharina , Mesagno, Christopher , Hanrahan, Stephanie , Kellmann, Michael
- Date: 2013
- Type: Text , Journal article
- Relation: Journal of Sport and Exercise Psychology Vol. 35, no. 1 (2013), p. 50-59
- Full Text:
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- Description: Trait activation theorists suggest that situational demands activate traits in (pressure) situations. In a comparison of situational demands of private (monetary incentive, cover story), mixed (monetary incentive, small audience), and public (large audience, video taping) high-pressure situations, we hypothesized that situational demands of private and mixed high-pressure conditions would activate self-focus traits and those of a public high-pressure condition would activate self-presentation traits. Female handball players (N = 120) completed personality questionnaires and then performed a throwing task in a low-pressure condition and one of three high-pressure conditions (n = 40). Increased anxiety levels from low to high pressure indicated successful pressure manipulations. A self-focus trait negatively predicted performance in private and mixed high-pressure conditions, and self-presentation traits positively predicted performance in the public high-pressure condition. Thus, pressure situations differed in their trait-activating situational demands. Experimental research investigating the trait-performance relationship should therefore use simulations of real competitions over laboratory-based scenarios. © 2013 Human Kinetics, Inc.
- Description: 2003010828
Aspects of attention predict real-world task performance in Alzheimer's Disease
- Miloyan, Beyon, Razani, Jill, Larco, Andrea, Avila, Justina, Chung, Julia
- Authors: Miloyan, Beyon , Razani, Jill , Larco, Andrea , Avila, Justina , Chung, Julia
- Date: 2013
- Type: Text , Journal article
- Relation: Applied Neuropsychology Vol. 20, no. 3 (2013), p. 203-210
- Full Text:
- Reviewed:
- Description: More research is needed to examine the relationship between specific neuropsychological functions and observation-based daily activity tests in patients with Alzheimer's disease (AD). Fifty-six patients with AD were administered tests of attention and processing speed and an observation-based activities-of-daily-living (ADL) task. Complex shortterm attention capacity best predicted real-world task performance, accounting for several domains of ADL functioning. These results suggest that complex attention requiring working-memory systems, but not simple attention or processing speed, account for moderate portions of variability in daily task performance. These results may aid in understanding the attentional processes required for performing daily activities and can be useful to health care professionals in treatment planning. Copyright © Taylor & Francis Group, LLC.
- Authors: Miloyan, Beyon , Razani, Jill , Larco, Andrea , Avila, Justina , Chung, Julia
- Date: 2013
- Type: Text , Journal article
- Relation: Applied Neuropsychology Vol. 20, no. 3 (2013), p. 203-210
- Full Text:
- Reviewed:
- Description: More research is needed to examine the relationship between specific neuropsychological functions and observation-based daily activity tests in patients with Alzheimer's disease (AD). Fifty-six patients with AD were administered tests of attention and processing speed and an observation-based activities-of-daily-living (ADL) task. Complex shortterm attention capacity best predicted real-world task performance, accounting for several domains of ADL functioning. These results suggest that complex attention requiring working-memory systems, but not simple attention or processing speed, account for moderate portions of variability in daily task performance. These results may aid in understanding the attentional processes required for performing daily activities and can be useful to health care professionals in treatment planning. Copyright © Taylor & Francis Group, LLC.
Attribute weighted Naive Bayes classifier using a local optimization
- Taheri, Sona, Yearwood, John, Mammadov, Musa, Seifollahi, Sattar
- Authors: Taheri, Sona , Yearwood, John , Mammadov, Musa , Seifollahi, Sattar
- Date: 2013
- Type: Text , Journal article
- Relation: Neural Computing & Applications Vol.24, no.5 (2013), p.995-1002
- Full Text:
- Reviewed:
- Description: The Naive Bayes classifier is a popular classification technique for data mining and machine learning. It has been shown to be very effective on a variety of data classification problems. However, the strong assumption that all attributes are conditionally independent given the class is often violated in real-world applications. Numerous methods have been proposed in order to improve the performance of the Naive Bayes classifier by alleviating the attribute independence assumption. However, violation of the independence assumption can increase the expected error. Another alternative is assigning the weights for attributes. In this paper, we propose a novel attribute weighted Naive Bayes classifier by considering weights to the conditional probabilities. An objective function is modeled and taken into account, which is based on the structure of the Naive Bayes classifier and the attribute weights. The optimal weights are determined by a local optimization method using the quasisecant method. In the proposed approach, the Naive Bayes classifier is taken as a starting point. We report the results of numerical experiments on several real-world data sets in binary classification, which show the efficiency of the proposed method.
- Authors: Taheri, Sona , Yearwood, John , Mammadov, Musa , Seifollahi, Sattar
- Date: 2013
- Type: Text , Journal article
- Relation: Neural Computing & Applications Vol.24, no.5 (2013), p.995-1002
- Full Text:
- Reviewed:
- Description: The Naive Bayes classifier is a popular classification technique for data mining and machine learning. It has been shown to be very effective on a variety of data classification problems. However, the strong assumption that all attributes are conditionally independent given the class is often violated in real-world applications. Numerous methods have been proposed in order to improve the performance of the Naive Bayes classifier by alleviating the attribute independence assumption. However, violation of the independence assumption can increase the expected error. Another alternative is assigning the weights for attributes. In this paper, we propose a novel attribute weighted Naive Bayes classifier by considering weights to the conditional probabilities. An objective function is modeled and taken into account, which is based on the structure of the Naive Bayes classifier and the attribute weights. The optimal weights are determined by a local optimization method using the quasisecant method. In the proposed approach, the Naive Bayes classifier is taken as a starting point. We report the results of numerical experiments on several real-world data sets in binary classification, which show the efficiency of the proposed method.
Automated unsupervised authorship analysis using evidence accumulation clustering
- Layton, Robert, Watters, Paul, Dazeley, Richard
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2013
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. 19, no. 1 (2013), p. 95-120
- Full Text:
- Reviewed:
- Description: Authorship Analysis aims to extract information about the authorship of documents from features within those documents. Typically, this is performed as a classification task with the aim of identifying the author of a document, given a set of documents of known authorship. Alternatively, unsupervised methods have been developed primarily as visualisation tools to assist the manual discovery of clusters of authorship within a corpus by analysts. However, there is a need in many fields for more sophisticated unsupervised methods to automate the discovery, profiling and organisation of related information through clustering of documents by authorship. An automated and unsupervised methodology for clustering documents by authorship is proposed in this paper. The methodology is named NUANCE, for n-gram Unsupervised Automated Natural Cluster Ensemble. Testing indicates that the derived clusters have a strong correlation to the true authorship of unseen documents. © 2011 Cambridge University Press.
- Description: 2003010584
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2013
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. 19, no. 1 (2013), p. 95-120
- Full Text:
- Reviewed:
- Description: Authorship Analysis aims to extract information about the authorship of documents from features within those documents. Typically, this is performed as a classification task with the aim of identifying the author of a document, given a set of documents of known authorship. Alternatively, unsupervised methods have been developed primarily as visualisation tools to assist the manual discovery of clusters of authorship within a corpus by analysts. However, there is a need in many fields for more sophisticated unsupervised methods to automate the discovery, profiling and organisation of related information through clustering of documents by authorship. An automated and unsupervised methodology for clustering documents by authorship is proposed in this paper. The methodology is named NUANCE, for n-gram Unsupervised Automated Natural Cluster Ensemble. Testing indicates that the derived clusters have a strong correlation to the true authorship of unseen documents. © 2011 Cambridge University Press.
- Description: 2003010584
Evaluating authorship distance methods using the positive Silhouette coefficient
- Layton, Robert, Watters, Paul, Dazeley, Richard
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2013
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. 19, no. 4 (2013), p. 517-535
- Full Text:
- Reviewed:
- Description: Unsupervised Authorship Analysis (UAA) aims to cluster documents by authorship without knowing the authorship of any documents. An important factor in UAA is the method for calculating the distance between documents. This choice of the authorship distance method is considered more critical to the end result than the choice of cluster analysis algorithm. One method for measuring the correlation between a distance metric and a labelling (such as class values or clusters) is the Silhouette Coefficient (SC). The SC can be leveraged by measuring the correlation between the authorship distance method and the true authorship, evaluating the quality of the distance method. However, we show that the SC can be severely affected by outliers. To address this issue, we introduce the Positive Silhouette Coefficient, given as the proportion of instances with a positive SC value. This metric is not easily altered by outliers and produces a more robust metric. A large number of authorship distance methods are then compared using the PSC, and the findings are presented. This research provides an insight into the efficacy of methods for UAA and presents a framework for testing authorship distance methods.
- Description: C1
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2013
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. 19, no. 4 (2013), p. 517-535
- Full Text:
- Reviewed:
- Description: Unsupervised Authorship Analysis (UAA) aims to cluster documents by authorship without knowing the authorship of any documents. An important factor in UAA is the method for calculating the distance between documents. This choice of the authorship distance method is considered more critical to the end result than the choice of cluster analysis algorithm. One method for measuring the correlation between a distance metric and a labelling (such as class values or clusters) is the Silhouette Coefficient (SC). The SC can be leveraged by measuring the correlation between the authorship distance method and the true authorship, evaluating the quality of the distance method. However, we show that the SC can be severely affected by outliers. To address this issue, we introduce the Positive Silhouette Coefficient, given as the proportion of instances with a positive SC value. This metric is not easily altered by outliers and produces a more robust metric. A large number of authorship distance methods are then compared using the PSC, and the findings are presented. This research provides an insight into the efficacy of methods for UAA and presents a framework for testing authorship distance methods.
- Description: C1
Performing under pressure in private : Activation of self-focus traits
- Geukes, Katharina, Mesagno, Christopher, Hanrahan, Stephanie, Kellmann, Michael
- Authors: Geukes, Katharina , Mesagno, Christopher , Hanrahan, Stephanie , Kellmann, Michael
- Date: 2013
- Type: Text , Journal article
- Relation: International Journal of Sport and Exercise Psychology Vol. 11, no. 1 (2013), p. 11-23
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- Reviewed:
- Description: Self-focus and self-presentation traits have been found to predict performance under pressure. The interactionist principle of trait activation indicates that situational demands encourage different traits to be relevant to performance in high-pressure situations. Thus, the purpose of the current study was to investigate the relationship of self-focus and self-presentation traits with performance in a private high-pressure setting. Because the private high-pressure situation offered motivational incentives but only minimal self-presentation cues, only a self-focus trait (private self-consciousness), but not self-presentation traits (public self-consciousness and narcissism), was hypothesized to predict performance under pressure in a private setting. After completing personality questionnaires, future physical education university students (N = 59) with experience in sport competitions performed eight throws at a target in low-pressure and high-pressure conditions. The conditions were identical with the exception that the high-pressure condition involved a monetary incentive and a cover story. Participants' state anxiety increased from low to high pressure. Neither self-focus nor self-presentation traits predicted performance under low pressure. Only the self-focus trait, but not self-presentation traits, negatively contributed to the prediction of high-pressure performance. Hence, findings support the applicability of the trait activation principle and underline that the situational demands of private high-pressure situations activate self-focus personality traits. © 2013 Copyright International Society of Sport Psychology.
- Description: 2003010822
- Authors: Geukes, Katharina , Mesagno, Christopher , Hanrahan, Stephanie , Kellmann, Michael
- Date: 2013
- Type: Text , Journal article
- Relation: International Journal of Sport and Exercise Psychology Vol. 11, no. 1 (2013), p. 11-23
- Full Text:
- Reviewed:
- Description: Self-focus and self-presentation traits have been found to predict performance under pressure. The interactionist principle of trait activation indicates that situational demands encourage different traits to be relevant to performance in high-pressure situations. Thus, the purpose of the current study was to investigate the relationship of self-focus and self-presentation traits with performance in a private high-pressure setting. Because the private high-pressure situation offered motivational incentives but only minimal self-presentation cues, only a self-focus trait (private self-consciousness), but not self-presentation traits (public self-consciousness and narcissism), was hypothesized to predict performance under pressure in a private setting. After completing personality questionnaires, future physical education university students (N = 59) with experience in sport competitions performed eight throws at a target in low-pressure and high-pressure conditions. The conditions were identical with the exception that the high-pressure condition involved a monetary incentive and a cover story. Participants' state anxiety increased from low to high pressure. Neither self-focus nor self-presentation traits predicted performance under low pressure. Only the self-focus trait, but not self-presentation traits, negatively contributed to the prediction of high-pressure performance. Hence, findings support the applicability of the trait activation principle and underline that the situational demands of private high-pressure situations activate self-focus personality traits. © 2013 Copyright International Society of Sport Psychology.
- Description: 2003010822
Cognitive Specificity in Trait Anger in Relation to Depression and Anxiety in a Community Sample
- Maud, Monica, Shute, Rosalyn, McLachlan, Angus
- Authors: Maud, Monica , Shute, Rosalyn , McLachlan, Angus
- Date: 2012
- Type: Text , Journal article
- Relation: Australian Psychologist Vol. 47, no. 4 (2012), p. 254-261
- Full Text:
- Reviewed:
- Description: The current research explored 16 of Young's schemas in relation to trait anger and to anxiety and depression symptoms among 262 non-clinical Australian adults with low-level symptomatology and average anger levels. The study partially replicated previous work with a sample of Spanish students that investigated the relationship between anger, depression, and anxiety and Young's schemas. Predictions derived from Beck's notion of cognitive specificity were examined using structural equation modelling and showed that of the sixteen schemas, Vulnerability was linked to anxiety, Social Isolation and Enmeshment were linked to depression, and Entitlement, Insufficient Self-Control, Mistrust and Abuse, Subjugation (negatively), and Abandonment were linked to anger. The discrepancies between these and the Spanish findings and the difficulties of other researchers in establishing higher order aggregations of Young's schemas prompted further consideration of the range of such schemas with respect to anger, depression, and anxiety, and the possibility that sample characteristics may play a critical role in determining the varying affect-schema relationships. © 2011 The Australian Psychological Society.
- Description: 2003010575
- Authors: Maud, Monica , Shute, Rosalyn , McLachlan, Angus
- Date: 2012
- Type: Text , Journal article
- Relation: Australian Psychologist Vol. 47, no. 4 (2012), p. 254-261
- Full Text:
- Reviewed:
- Description: The current research explored 16 of Young's schemas in relation to trait anger and to anxiety and depression symptoms among 262 non-clinical Australian adults with low-level symptomatology and average anger levels. The study partially replicated previous work with a sample of Spanish students that investigated the relationship between anger, depression, and anxiety and Young's schemas. Predictions derived from Beck's notion of cognitive specificity were examined using structural equation modelling and showed that of the sixteen schemas, Vulnerability was linked to anxiety, Social Isolation and Enmeshment were linked to depression, and Entitlement, Insufficient Self-Control, Mistrust and Abuse, Subjugation (negatively), and Abandonment were linked to anger. The discrepancies between these and the Spanish findings and the difficulties of other researchers in establishing higher order aggregations of Young's schemas prompted further consideration of the range of such schemas with respect to anger, depression, and anxiety, and the possibility that sample characteristics may play a critical role in determining the varying affect-schema relationships. © 2011 The Australian Psychological Society.
- Description: 2003010575
Recentred local profiles for authorship attribution
- Layton, Robert, Watters, Paul, Dazeley, Richard
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2012
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. 18, no. 3 (2012), p. 293-312
- Full Text:
- Reviewed:
- Description: Authorship attribution methods aim to determine the author of a document, by using information gathered from a set of documents with known authors. One method of performing this task is to create profiles containing distinctive features known to be used by each author. In this paper, a new method of creating an author or document profile is presented that detects features considered distinctive, compared to normal language usage. This recentreing approach creates more accurate profiles than previous methods, as demonstrated empirically using a known corpus of authorship problems. This method, named recentred local profiles, determines authorship accurately using a simple 'best matching author' approach to classification, compared to other methods in the literature. The proposed method is shown to be more stable than related methods as parameter values change. Using a weighted voting scheme, recentred local profiles is shown to outperform other methods in authorship attribution, with an overall accuracy of 69.9% on the ad-hoc authorship attribution competition corpus, representing a significant improvement over related methods. Copyright © Cambridge University Press 2011.
- Description: 2003010688
- Authors: Layton, Robert , Watters, Paul , Dazeley, Richard
- Date: 2012
- Type: Text , Journal article
- Relation: Natural Language Engineering Vol. 18, no. 3 (2012), p. 293-312
- Full Text:
- Reviewed:
- Description: Authorship attribution methods aim to determine the author of a document, by using information gathered from a set of documents with known authors. One method of performing this task is to create profiles containing distinctive features known to be used by each author. In this paper, a new method of creating an author or document profile is presented that detects features considered distinctive, compared to normal language usage. This recentreing approach creates more accurate profiles than previous methods, as demonstrated empirically using a known corpus of authorship problems. This method, named recentred local profiles, determines authorship accurately using a simple 'best matching author' approach to classification, compared to other methods in the literature. The proposed method is shown to be more stable than related methods as parameter values change. Using a weighted voting scheme, recentred local profiles is shown to outperform other methods in authorship attribution, with an overall accuracy of 69.9% on the ad-hoc authorship attribution competition corpus, representing a significant improvement over related methods. Copyright © Cambridge University Press 2011.
- Description: 2003010688
Stuttering, disability and the higher education sector in Australia
- Meredith, Grant, Packman, Ann, Marks, Genee
- Authors: Meredith, Grant , Packman, Ann , Marks, Genee
- Date: 2012
- Type: Text , Journal article
- Relation: International Journal of Speech-Language Pathology Vol. 14, no. 4 (2012), p. 370-376
- Full Text:
- Reviewed:
- Description: The aim of this study was to ascertain the extent to which Australian public universities and their associated disability liaison services offer web-based information for current or prospective students who stutter. The disability pages of the websites of all 39 public universities in Australia were visited and the information about disability services assessed according to 12 criteria developed by the authors. Results indicate that there is a dearth of information on Australian university websites available for students or prospective students who stutter. Only 13% of the sites reported any form of alternative teaching and assessment procedures for speech-impaired students and only 51% of 39 disability liaison officers responded when contacted by email. Such a student could not make an informed choice to enrol in a university based upon the information on disability services available on public Australian university websites. © 2012 The Speech Pathology Association of Australia Limited.
- Authors: Meredith, Grant , Packman, Ann , Marks, Genee
- Date: 2012
- Type: Text , Journal article
- Relation: International Journal of Speech-Language Pathology Vol. 14, no. 4 (2012), p. 370-376
- Full Text:
- Reviewed:
- Description: The aim of this study was to ascertain the extent to which Australian public universities and their associated disability liaison services offer web-based information for current or prospective students who stutter. The disability pages of the websites of all 39 public universities in Australia were visited and the information about disability services assessed according to 12 criteria developed by the authors. Results indicate that there is a dearth of information on Australian university websites available for students or prospective students who stutter. Only 13% of the sites reported any form of alternative teaching and assessment procedures for speech-impaired students and only 51% of 39 disability liaison officers responded when contacted by email. Such a student could not make an informed choice to enrol in a university based upon the information on disability services available on public Australian university websites. © 2012 The Speech Pathology Association of Australia Limited.