Mini-micro unmanned aerial vehicle intelligence: a threat to land vehicles

Increasing use of commercial off-the-shelf Mini-Micro Unmanned Aerial Vehicle (MAV) systems with enhanced intelligence methodologies can potentially be a threat, if this technology falls into the wrong hands. In this study, we investigate the level of threat imposed on critical infrastructure using different MAV swarm artificial intelligence traits and coordination methodologies. The critical infrastructure in consideration is a moving commercial land vehicle that may be transporting for example an important civil servant or politician. Non-dimensional fitness functions used for measuring MAV mission effectiveness have been established for the case studies considered in this paper. The findings indicated that increased in intelligent and coordination level elevate teams' efficiency, therefore poses a higher degree of threat to targeted land vehicle. Observations from the study have suggested that memory-based cooperative technique provides a consistent efficiency compared to other methods for the mission objectives considered in this paper. © 2014 The authors and IOS Press. All rights reserved.

A review on computational intelligence methods for controlling traffic signal timing

Urban traffic as one of the most important challenges in modern city life needs practically effective and efficient solutions. Artificial intelligence methods have gained popularity for optimal traffic light control. In this paper, a review of most important works in the field of controlling traffic signal timing, in particular studies focusing on Q-learning, neural network, and fuzzy logic system are presented. As per existing literature, the intelligent methods show a higher performance compared to traditional controlling methods. However, a study that compares the performance of different learning methods is not published yet. In this paper, the aforementioned computational intelligence methods and a fixed-time method are implemented to set signals times and minimize total delays for an isolated intersection. These methods are developed and compared on a same platform. The intersection is treated as an intelligent agent that learns to propose an appropriate green time for each phase. The appropriate green time for all the intelligent controllers are estimated based on the received traffic information. A comprehensive comparison is made between the performance of Q-learning, neural network, and fuzzy logic system controller for two different scenarios. The three intelligent learning controllers present close performances with multiple replication orders in two scenarios. On average Q-learning has 66%, neural network 71%, and fuzzy logic has 74% higher performance compared to the fixed-time controller.

Information quality and governance for business intelligence

This book presents the latest exchange of academic research on all aspects of practicing and managing information using a multidisciplinary approach that examines its quality for organizational growth.

A comprehensive diagnostic framework for evaluating business intelligence and analytics effectiveness

Business intelligence and analytics (BIA) initiatives are costly, complex and experience high failure rates. Organizations require effective approaches to evaluate their BIA capabilities in order to develop strategies for their evolution. In this paper, we employ a design scienceparadigm to develop a comprehensive BIA effectiveness diagnostic (BIAED) framework that can be easily operationalized. We propose that a useful BIAED framework must assess the correct factors, should be deployed in the proper process context and acquire the appropriateinput from different constituencies within an organization. Drawing on the BIAED framework, we further develop an online diagnostic toolkit that includes a comprehensive survey instrument. We subsequently deploy the diagnostic mechanism within three large organizations in North America (involving over 1500 participants) and use the results toinform BIA strategy formulation. Feedback from participating organizations indicates that the BIA diagnostic toolkit provides insights that are essential inputs to strategy development. This work addresses a significant research gap in the area of BIA effectiveness assessment.

Do military peacekeepers want to talk about their experiences? Perceived psychological support of UK military peacekeepers on return from deployment

Background: Little is known about what support the United Kingdom (UK) armed forces require when they return from operations. Aims: To investigate the perceived psychological support requirements for service personnel on peacekeeping deployments when they return home from operations and examine their views on the requirement for formal psychological debriefings. Methods: A retrospective cohort study examined the perceived psychological needs of 1202 UK peacekeepers on return from deployment. Participants were sent a questionnaire asking about their perceived needs relating to peacekeeping deployments from April 1991 to October 2000. Results: Results indicate that about two-thirds of peacekeepers spoke about their experiences. Most turned to informal networks, such as peers and family members, for support. Those who were highly distressed reported talking to medical and welfare services. Overall, speaking about experiences was associated with less psychological distress. Additionally, two thirds of the sample was in favour of a formalised psychological debriefing on return to the UK. Conclusions: This study suggests that most peacekeepers do not require formalised interventions on homecoming and that more distressed personnel are already accessing formalised support mechanisms. Additionally social support from peers and family appears useful and the UK military should foster all appropriate possibilities for such support. Declaration of Interest: The Stage 1 study was funded by the US Department of Defence (DoD) and the follow up study by the Medical Research Counsel (MRC). Neither the DoD nor MRC had any input into the design, conduct, analysis or reporting of the study. The views expressed are not those of any US or UK governmental organisation. We thank Mr Nick Blatchley of MOD for help in identifying the cohorts.

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

Electrical load forecasting plays a vital role in order to achieve the concept of next generation power system such as smart grid, efficient energy management and better power system planning. As a result, high forecast accuracy is required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment of power grid. Artificial Intelligence (AI) based techniques are being developed and deployed worldwide in on Varity of applications, because of its superior capability to handle the complex input and output relationship. This paper provides the comprehensive and systematic literature review of Artificial Intelligence based short term load forecasting techniques. The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. The accuracy of ANN based forecast model is found to be dependent on number of parameters such as forecast model architecture, input combination, activation functions and training algorithm of the network and other exogenous variables affecting on forecast model inputs. Published literature presented in this paper show the potential of AI techniques for effective load forecasting in order to achieve the concept of smart grid and buildings.

The effects of military body armour on trunk and hip kinematics during performance of manual handling tasks

Musculoskeletal injuries are reported as burdening the military. An identified risk factor for injury is carrying heavy loads; however, soldiers are also required to wear their load as body armour. To investigate the effects of body armour on trunk and hip kinematics during military-specific manual handling tasks, 16 males completed 3 tasks while wearing each of 4 body armour conditions plus a control. Three-dimensional motion analysis captured and quantified all kinematic data. Average trunk flexion for the weightiest armour type was higher compared with control during the carry component of the ammunition box lift (p < 0.001) and sandbag lift tasks (p < 0.001). Trunk rotation ROM was lower for all armour types compared with control during the ammunition box place component (p < 0.001). The altered kinematics with body armour occurred independent of armour design. In order to optimise armour design, manufacturers need to work with end-users to explore how armour configurations interact with range of personal and situational factors in operationally relevant environments. Practitioner Summary: Musculoskeletal injuries are reported as burdening the military and may relate to body armour wear. Body armour increased trunk flexion and reduced trunk rotation during military-specific lifting and carrying tasks. The altered kinematics may contribute to injury risk, but more research is required.

Cultural intelligence (CQ) in virtual, cross-cultural interactions: generalizability of measure and links to personality dimensions and task performance

Previous studies have focused on investigating CQ in face-to-face contexts but very few have assessed CQ in virtual, cross-cultural interactions. This study highlights the relevance of cultural intelligence (CQ) as an intercultural capability in cross-cultural communications that are virtual. This two-study research (study 1: n = 274; study 2: n = 223) conducted in call centers in the Philippines (a) assesses the generalizability of the four-factor CQ model (i.e., cognitive, metacognitive, motivational and behavioral CQ) as applied in the virtual context and (b) tests the relationship between CQ, personality dimensions (i.e., openness to experience and extraversion) and supervisor’s ratings of task performance. Study 1 results show that the structural validity of the four-factor CQ model was supported with minor issues in some ofthe items indicating the need to modify the CQ measure when utilized in the virtual context. Study 2 results show that CQ is positively and significantly related to openness to experience and extraversion. In addition, results show that CQ predicts task performance highlighting the importance of developing CQ among call center representatives and other working professionals who virtually engage and interact with clients and customers from culturally diverse backgrounds.

It’s not all about language ability: motivational cultural intelligence matters in call center performance

his study focuses on the role of motivational cultural intelligence (CQ) in call center performance. Call centers mainly rely on verbal communication with language ability playing a significant role in delivery of tasks. This study argues that motivational CQ, or the interest and efficacy when interacting with individuals from culturally diverse backgrounds, plays a significant role in call center performance. This study was conducted in the Philippines, one of the top destinations for offshore services like call centers. Studies were conducted at two time points to determine the relationship between language ability, motivational CQ, and task performance. At Time 1, the language ability of 125 call center agent applicants was determined and assessed. At Time 2 which was conducted six months later, performance data were obtained and the level of the motivational CQ of the respondents measured. Results show that language ability is positively and significantly related to task performance. However, when motivational CQ was included, the relationship between language ability and task performance became non-significant, which conveys the full mediating role of motivational CQ in that relationship.

Computational intelligence-based traffic signal timing optimization

 Traffic congestion has explicit effects on productivity and efficiency, as well as side effects on environmental sustainability and health. Controlling traffic flows at intersections is recognized as a beneficial technique, to decrease daily travel times. This thesis applies computational intelligence to optimize traffic signals' timing and reduce urban traffic.

Exploring the role of personality and resilience in the stress response: a comparison of military and civilian samples

In the context of emergency services and first responders (i.e. military), the ability to select personnel who have the innate ability to work well in highly charged environments would be advantageous. While there have been some efforts to explore the relationship between personality traits and physiological reactivity in the context of the emergency services, differences in stress responses between civilians and military personnel have not yet been investigated. Therefore the aim of the current study was to examine the relationship between personality, resilience and physiological stress responses. Fifteen civilians and 16 military personnel completed online personality (IPIP) and resilience (CD-RISC) inventories prior to commencing the experimental component of the study. The Mannheim Multi-component Stress Test (MMST) which utilises cognitive, audio, visual and motivational components was employed to elicit an acute stress response. Measures of correct responses and reaction time were sampled during the MMST. Prior to and following exposure to the MMST, positive and negative affect were measured (PANAS), and heart rate was sampled continuously across the study period. Results indicated that Military participants rated significantly lower than civilians on neuroticism; however there were no differences between groups for resilience or any of the other personality traits. Military participants displayed less emotional reactivity and less negative affect following the MMST testing period, and appeared to perform better on the MMST when compared to the civilian sample. However, there was no significant difference in heart rate measures between groups. Collectively, these results provide support for the broaden and buildhypothesis and the transactional stress theory. The results also build on previous empirical stress literature and support the effectiveness of the MMST in laboratory induced stress. Suggestions for future research in the area of resiliency and stress will be discussed. From an applied context, further research in this area may assist in military recruitment processes to place individuals in roles to which they are most suited within the Defence Force.