Policing in cool and hot climates: legitimacy, power and the rise and fall of mass stop and search in Scotland

Prior to the amalgamation of Scotland’s eight police forces into Police Scotland in 2013 by the Scottish National Party government, Scottish policing generally enjoyed a ‘cool’ political climate, with low scrutiny and minimal political engagement. This paper argues these conditions hindered the critical interrogation of Scottish policing, allowing a policy of unregulated and unfettered stop and search to flourish unchallenged for two decades. We then show how this policy was swiftly dismantled in the ‘heated’ environment that followed centralization, a move that gave rise to the unprecedented scrutiny of Scottish policing by media and political commentators. The analysis suggests that the legitimacy and reputation of the police may owe a debt to political environments that encourage either ‘soft’ or ‘hard’ analysis. Also, that more heated political environments, often disparaged by academics and criminal justice practitioners, can drive accountability and contribute to more progressive outcomes.

Integrating collaborative filtering and search-based techniques for personalized online product recommendation

The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

Stop and revive? : the effectiveness of nap and active rest breaks for reducing driver sleepiness

The incidence of sleep-related crashes has been estimated to account for approximately 20% of all fatal and severe crashes. The use of sleepiness countermeasures by drivers is an important component to reduce the incidence rates of sleep-related crashes. Taking a brief nap and stopping for a rest break are two highly publicised countermeasures for driver sleepiness and are also believed by drivers to be the most effective countermeasures. Despite this belief, there is scarce evidence to support the utility of these countermeasures for reducing driver sleepiness levels. Therefore, determining the effectiveness of these countermeasures is an important road safety concern. The current study utilised a young adult sample (N = 20) to investigate the effectiveness of a nap and an active rest break. The countermeasures effects were evaluated by physiological, behavioural (hazard perception skill), and subjective measures previously found sensitive to sleepiness. Participants initially completed two hours of a simulated driving task followed by a 15 minute nap opportunity or a 15 minute active rest break that included 10 minutes of brisk walking. After the break, participants completed one final hour of the simulated driving task. A within-subjects design was used so that each participant completed both the nap and the active rest break conditions on separate occasions. The analyses revealed that only the nap break provided any meaningful reduction in physiological sleepiness, reduced subjective sleepiness levels, and maintained hazard perception performance. In contrast, the active rest break had no effect for reducing physiological sleepiness and resulted in a decrement in hazard perception performance (i.e., an increase of reaction time latencies), with a transient reduction in subjective sleepiness levels. A number of theoretical, empirical and practical issues were identified by the current study.

Capable but not able : the effect of institutional context and search breadth on the absorptive capacity-corporate entrepreneurship relationship

This study investigates how the interaction of institutional market orientation and external search breadth influence the ability to use absorptive capacity to raise the level of corporate entrepreneurship. The findings of a sample of 331 supplier companies providing products and services to the mining industry of Australia and Iran indicate that the positive association between absorptive capacity and corporate entrepreneurship is stronger for companies with greater external knowledge search breadth. Moreover, operating in a less market-oriented institutional context such as, Iran diminishes the ability to utilise a firm’s absorptive capacity to raise their level of corporate entrepreneurship. Yet, firms operating in such contexts are able to overcome these disadvantages posed by their institutional context by engaging in broader external search of knowledge.

Stop and revive? The effectiveness of nap and active rest breaks for reducing drivers sleepiness

The purpose of this study was to compare the effects of two commonly utilised sleepiness countermeasures: a nap break and an active rest break. The effects of the countermeasures were evaluated by physiological (EEG), subjective, and driving performance measures. Participants completed two hours of simulated driving, followed by a 15 minute nap break or a 15 minute active rest break then completed the final hour of simulated driving. The nap break reduced EEG and subjective sleepiness. The active rest break did not reduce EEG sleepiness, with sleepiness levels eventually increasing, and resulted in an immediate reduction of subjective sleepiness. No difference was found between the two breaks for the driving performance measure. The immediate reduction of subjective sleepiness after the active rest break could leave drivers with erroneous perceptions of their sleepiness, particularly with increases of physiological sleepiness after the break.

Stop and revive? The effectiveness of nap and active rest breaks for reducing driver sleepiness

Objectives The purpose for this study was to determine the relative benefit of nap and active rest breaks for reducing driver sleepiness. Methods Participants were 20 healthy young adults (20-25 years), including 8 males and 12 females. A counterbalanced within-subjects design was used such that each participant completed both conditions on separate occasions, a week apart. The effects of the countermeasures were evaluated by established physiological (EEG theta and alpha absolute power), subjective (Karolinska Sleepiness Scale), and driving performance measures (Hazard Perception Task). Participants woke at 5am, and undertook a simulated driving task for two hours; each participant then had either a 15-minute nap opportunity or a 15-minute active rest break that included 10 minutes of brisk walking, followed by another hour of simulated driving. Results The nap break reduced EEG theta and alpha absolute power and eventually reduced subjective sleepiness levels. In contrast, the active rest break did not reduce EEG theta and alpha absolute power levels with the power levels eventually increasing. An immediate reduction of subjective sleepiness was observed, with subjective sleepiness increasing during the final hour of simulated driving. No difference was found between the two breaks for hazard perception performance. Conclusions Only the nap break produced a significant reduction in physiological sleepiness. The immediate reductions of subjective sleepiness following the active rest break could leave drivers with erroneous perceptions of their sleepiness, particularly as physiological sleepiness continued to increase after the break.

An analysis of theories of search and search behavior

Theories of search and search behavior can be used to glean insights and generate hypotheses about how people interact with retrieval systems. This paper examines three such theories, the long standing Information Foraging Theory, along with the more recently proposed Search Economic Theory and the Interactive Probability Ranking Principle. Our goal is to develop a model for ad-hoc topic retrieval using each approach, all within a common framework, in order to (1) determine what predictions each approach makes about search behavior, and (2) show the relationships, equivalences and differences between the approaches. While each approach takes a different perspective on modeling searcher interactions, we show that under certain assumptions, they lead to similar hypotheses regarding search behavior. Moreover, we show that the models are complementary to each other, but operate at different levels (i.e., sessions, patches and situations). We further show how the differences between the approaches lead to new insights into the theories and new models. This contribution will not only lead to further theoretical developments, but also enables practitioners to employ one of the three equivalent models depending on the data available.

Improving the optimum generalised stop-and-wait ARQ scheme

Instead of waiting for the acknowledgments from all the copies of a single data block sent, as in the optimum generalised stop-and-wait ARQ scheme, the transmitter in the proposed scheme starts sending an optimum number of copies of the next block in the queue, soon after receiving the positive acknowledgment from the receiver, thereby further improving the throughput efficiency.

Handpumps: problems and search for remedies

This paper gives a brief survey of research and development work done on hand pumps in India as well as elsewhere and sets out the approach adopted by ASTRA Working Group. Ten ways in which a hand pump breakdown in practice have been identified. The physical reasons behind each type of breakdown analysed. Remedial measures have been developed from this analysis. Laboratory test rigs fabricated to evaluate these measures have been described and some experimental results presented. The course of further work has been charted.

Deploy and search strategy for multi-agent systems using Voronoi partitions

In this paper we analyze a deploy and search strategy for multi-agent systems. Mobile agents equipped with sensors carry out search operation in the search space. The lack of information about the search space is modeled as an uncertainty density distribution over the space, and is assumed to be known to the agents a priori. In each step, the agents deploy themselves in an optimal way so as to maximize per step reduction in the uncertainty density. We analyze the proposed strategy for convergence and spatial distributedness. The control law moving the agents has been analyzed for stability and convergence using LaSalle's invariance principle, and for spatial distributedness under a few realistic constraints on the control input such as constant speed, limit on maximum speed, and also sensor range limits. The simulation experiments show that the strategy successfully reduces the average uncertainty density below the required level.

Performance of a class of multi-robot deploy and search strategies based on centroidal voronoi configurations

This article considers a class of deploy and search strategies for multi-robot systems and evaluates their performance. The application framework used is deployment of a system of autonomous mobile robots equipped with required sensors in a search space to gather information. The lack of information about the search space is modelled as an uncertainty density distribution. The agents are deployed to maximise single-step search effectiveness. The centroidal Voronoi configuration, which achieves a locally optimal deployment, forms the basis for sequential deploy and search (SDS) and combined deploy and search (CDS) strategies. Completeness results are provided for both search strategies. The deployment strategy is analysed in the presence of constraints on robot speed and limit on sensor range for the convergence of trajectories with corresponding control laws responsible for the motion of robots. SDS and CDS strategies are compared with standard greedy and random search strategies on the basis of time taken to achieve reduction in the uncertainty density below a desired level. The simulation experiments reveal several important issues related to the dependence of the relative performances of the search strategies on parameters such as the number of robots, speed of robots and their sensor range limits.

View-Invariant Object Category Learning, Recognition, and Search: How Spatial and Object Attention Are Coordinated Using Surface-Based Attentional Shrouds

Air Force Office of Scientific Research (F49620-01-1-0397); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624)

Cortical Dynamics of Contextually-Cued Attentive Visual Learning and Search: Spatial and Object Evidence Accumulation

How do humans use predictive contextual information to facilitate visual search? How are consistently paired scenic objects and positions learned and used to more efficiently guide search in familiar scenes? For example, a certain combination of objects can define a context for a kitchen and trigger a more efficient search for a typical object, such as a sink, in that context. A neural model, ARTSCENE Search, is developed to illustrate the neural mechanisms of such memory-based contextual learning and guidance, and to explain challenging behavioral data on positive/negative, spatial/object, and local/distant global cueing effects during visual search. The model proposes how global scene layout at a first glance rapidly forms a hypothesis about the target location. This hypothesis is then incrementally refined by enhancing target-like objects in space as a scene is scanned with saccadic eye movements. The model clarifies the functional roles of neuroanatomical, neurophysiological, and neuroimaging data in visual search for a desired goal object. In particular, the model simulates the interactive dynamics of spatial and object contextual cueing in the cortical What and Where streams starting from early visual areas through medial temporal lobe to prefrontal cortex. After learning, model dorsolateral prefrontal cortical cells (area 46) prime possible target locations in posterior parietal cortex based on goalmodulated percepts of spatial scene gist represented in parahippocampal cortex, whereas model ventral prefrontal cortical cells (area 47/12) prime possible target object representations in inferior temporal cortex based on the history of viewed objects represented in perirhinal cortex. The model hereby predicts how the cortical What and Where streams cooperate during scene perception, learning, and memory to accumulate evidence over time to drive efficient visual search of familiar scenes.

Description and search labor for information retrieval

Selection power is taken as the fundamental value for information retrieval systems. Selection power is regarded as produced by selection labor, which itself separates historically into description and search labor. As forms of mental labor, description and search labor participate in the conditions for labor and for mental labor. Concepts and distinctions applicable to physical and mental labor are indicated, introducing the necessity of labor for survival, the idea of technology as a human construction, and the possibility of the transfer of human labor to technology. Distinctions specific to mental labor, particular between semantic and syntactic labor, are introduced. Description labor is exemplified by cataloging, classification, and database description, can be more formally understood as the labor involved in the transformation of objects for description into searchable descriptions, and is also understood to include interpretation. The costs of description labor are discussed. Search labor is conceived as the labor expended in searching systems. For both description and search labor, there has been a progressive reduction in direct human labor, with its syntactic aspects transferred to technology, effectively compelled by the high relative costs of direct human labor compared to machine processes.