Online Media and Crisis? of Advertising Media Planning

Nowadays, online media represent a great choice for advertising. From de advertising media planning, new media give new ways to reach the consumers, but they also add more complexity. The communication capacity of online media and the greater use of that media by part of the users open up the debate about the necessity of rethinking the approach of the ‘traditional’ advertising media planning, which structure and work processes were developed when media were offline. So, this article gives a panoramic view about the influence of new media in advertising media planning. To do this, in first place, describes the current scenario, analyzing the penetration and advertising expenditure in Internet. Also, it shows the main online media according to their proximity to the offline advertising media planning conception. In second place, this article addresses the current challenges at measuring new media as a symptom of the impulse at the change of model. Finally, the article ends up showing some trends that are presented as drivers of change. However, after this analysis, comes up the point that those aspects would not change the essence of advertising media planning, so it is questionable if we can speak of a crisis or, instead, if new media are showing the necessity that media planning have to be involved with this new scenario.

Los medios online y la ¿crisis? de la planificación de medios publicitarios

Los medios online representan actualmente una gran apuesta para la publicidad. Desde la planificación de medios publicitarios, los nuevos medios ofrecen otros caminos para llegar al público, pero añaden mayor complejidad. La capacidad comunicativa de los medios online y el mayor consumo de esos medios por parte de la población abre el debate de la necesidad de replantear el enfoque de la planificación de medios, digamos, tradicional, cuya estructura y procesos de trabajo se desarrollaron cuando los medios eran offline. Así, este artículo proporciona una panorámica general de la influencia de los nuevos medios en la planificación. Para ello, en primer lugar, describe el escenario actual, analizando la penetración y las inversiones publicitarias en Internet. Además, expone los principales soportes online según su proximidad a la concepción de la planificación de medios offline. En segundo lugar, aborda los retos actuales en la medición de los nuevos medios como síntoma del impulso del cambio de modelo. Finalmente, el artículo termina exponiendo algunas tendencias que se presentan como motores de cambio. Sin embargo, tras este análisis se advierte que tales aspectos no modificarían la esencia de la planificación de medios, por lo que cabe cuestionarse si se puede hablar de crisis, o si los nuevos medios están mostrando la necesidad de que la investigación y planificación se comprometa con este nuevo escenario.

Powell's practical advertiser; a practical work for advertising writers and business men, with instruction on planning, preparing, placing and managing modern publicity,

Mode of access: Internet.

From the account manager’s conscience to top-of-mind : account planning in Australia

What began as the “account manager’s conscience” has grown to be top-of-mind in Australian advertising today. Account planning is a hybrid discipline which uses research to bring the consumer voice to the campaign process during strategy generation, creative development and evaluation. In Australia, account planning is subjected to the “Vegemite Factor” where planners are spread too thinly across accounts and much of the market is dominated by freelance researchers and planners. This unique environment has shaped many different perceptions of account planning in Australia. These are compared with an international definition of account planning and the current research. While many basic tenants of the definition are shared by Australian advertising professionals, the difference appears to be in the ongoing nature, team approach and level of commitment. In Australia, account planners seem to be more facilitators of the strategic direction, than directors of it. Instead of exerting a sustained influence across the campaign, most energy appears to be expended at the start of campaign development, rather than extending through to its evaluation.

Guided chaos : path planning and control for a UAV-forced landing

In recent years, unmanned aerial vehicles (UAVs) have been widely used in combat, and their potential applications in civil and commercial roles are also receiving considerable attention by industry and the research community. There are numerous published reports of UAVs used in Earth science missions [1], fire-fighting [2], and border security [3] trials, with other speculative deployments, including applications in agriculture, communications, and traffic monitoring. However, none of these UAVs can demonstrate an equivalent level of safety to manned aircraft, particularly in the case of an engine failure, which would require an emergency or forced landing. This may be arguably the main factor that has prevented these UAV trials from becoming full-scale commercial operations, as well as restricted operations of civilian UAVs to only within segregated airspace.

Big project ventures: facilitating a collaborative planning and implementation process

This book is based on a study of a complex project proposal by governments and corporations for a futuristic city, the Multifunction Polis (MFP). It encompasses issues and challenges symptomatic of growth initiatives in the global competitive environment. Academic rigor is applied using corporate strategy and business principles to undertake a detailed analysis of the project proposal & feasibility study and to subsequently construct practical guidelines on how to effectively manage the interpretation & implementation of a large-scale collaborative venture. It specifically addresses a venture which involves fragmented groups representing a diversity of interests but which aspire to related goals and, to this end, there is a need for cooperation & synergy across the planning process.This is an easy to read book of general interest and well suited to practitioners and academics alike. Its relevance is far-reaching, extending to venture situations defined by location, industry, community or social interest, the context, scale and scope of the project, and the role of organization management, project management, market and industry development and public policy. flap text of book

Multi-objective four-dimensional vehicle motion planning in large dynamic environments

This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

Intelligent distribution planning and control incorporating microgrids

This paper proposes a comprehensive approach to the planning of distribution networks and the control of microgrids. Firstly, a Modified Discrete Particle Swarm Optimization (MDPSO) method is used to optimally plan a distribution system upgrade over a 20 year planning period. The optimization is conducted at different load levels according to the anticipated load duration curve and integrated over the system lifetime in order to minimize its total lifetime cost. Since the optimal solution contains Distributed Generators (DGs) to maximize reliability, the DG must be able to operate in islanded mode and this leads to the concept of microgrids. Thus the second part of the paper reviews some of the challenges of microgrid control in the presence of both inertial (rotating direct connected) and non-inertial (converter interfaced) DGs. More specifically enhanced control strategies based on frequency droop are proposed for DGs to improve the smooth synchronization and real power sharing minimizing transient oscillations in the microgrid. Simulation studies are presented to show the effectiveness of the control.

Choosing landmarks for risky planning

This work examines the effect of landmark placement on the efficiency and accuracy of risk-bounded searches over probabilistic costmaps for mobile robot path planning. In previous work, risk-bounded searches were shown to offer in excess of 70% efficiency increases over normal heuristic search methods. The technique relies on precomputing distance estimates to landmarks which are then used to produce probability distributions over exact heuristics for use in heuristic searches such as A* and D*. The location and number of these landmarks therefore influence greatly the efficiency of the search and the quality of the risk bounds. Here four new methods of selecting landmarks for risk based search are evaluated. Results are shown which demonstrate that landmark selection needs to take into account the centrality of the landmark, and that diminishing rewards are obtained from using large numbers of landmarks.

Planning most-likely paths from overhead imagery

This paper is about planning paths from overhead imagery, the novelty of which is taking explicit account of uncertainty in terrain classification and spatial variation in terrain cost. The image is first classified using a multi-class Gaussian Process Classifier which provides probabilities of class membership at each location in the image. The probability of class membership at a particular grid location is then combined with a terrain cost evaluated at that location using a spatial Gaussian process. The resulting cost function is, in turn, passed to a planner. This allows both the uncertainty in terrain classification and spatial variations in terrain costs to be incorporated into the planned path. Because the cost of traversing a grid cell is now a probability density rather than a single scalar value, we can produce not only the most-likely shortest path between points on the map, but also sample from the cost map to produce a distribution of paths between the points. Results are shown in the form of planned paths over aerial maps, these paths are shown to vary in response to local variations in terrain cost.

Embedding human expert cognition into autonomous UAS trajectory planning

This paper presents a new approach for the inclusion of human expert cognition into autonomous trajectory planning for unmanned aerial systems (UASs) operating in low-altitude environments. During typical UAS operations, multiple objectives may exist; therefore, the use of multicriteria decision aid techniques can potentially allow for convergence to trajectory solutions which better reflect overall mission requirements. In that context, additive multiattribute value theory has been applied to optimize trajectories with respect to multiple objectives. A graphical user interface was developed to allow for knowledge capture from a human decision maker (HDM) through simulated decision scenarios. The expert decision data gathered are converted into value functions and corresponding criteria weightings using utility additive theory. The inclusion of preferences elicited from HDM data within an automated decision system allows for the generation of trajectories which more closely represent the candidate HDM decision preferences. This approach has been demonstrated in this paper through simulation using a fixed-wing UAS operating in low-altitude environments.

Three-phase model of consumers' behaviours : a synthesis of the theory of planned behaviour, self-determination theory and planning

Using a longitudinal study, an overall behavioural model with three related phases (cognitive, motivational and volitional phase) across three studies was examined to identify the factors that most prominently drive consumer environmental behaviour. This thesis provides empirical evidence to support the behavioural model in an environmental consumption context and shows a new avenue for promoting consumer environmental behaviour.

Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

Motion planning and stochastic control with experimental validation on a planetary rover

Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This model is used to construct a control policy for navigation to a goal region in a terrain map built using an on-board RGB-D camera. The terrain includes flat ground, small rocks, and non-traversable rocks. We report the results of 200 simulated and 35 experimental trials that validate the approach and demonstrate the value of considering control uncertainty in maintaining platform safety.

Achieving intention-centric BPM through automated planning

As a result of the more distributed nature of organisations and the inherently increasing complexity of their business processes, a significant effort is required for the specification and verification of those processes. The composition of the activities into a business process that accomplishes a specific organisational goal has primarily been a manual task. Automated planning is a branch of artificial intelligence (AI) in which activities are selected and organised by anticipating their expected outcomes with the aim of achieving some goal. As such, automated planning would seem to be a natural fit to the BPM domain to automate the specification of control flow. A number of attempts have been made to apply automated planning to the business process and service composition domain in different stages of the BPM lifecycle. However, a unified adoption of these techniques throughout the BPM lifecycle is missing. As such, we propose a new intention-centric BPM paradigm, which aims on minimising the specification effort by exploiting automated planning techniques to achieve a pre-stated goal. This paper provides a vision on the future possibilities of enhancing BPM using automated planning. A research agenda is presented, which provides an overview of the opportunities and challenges for the exploitation of automated planning in BPM.