When and How-Long: A Unified Approach for Time Perception

The representation of the environment assumes the encoding of four basic dimensions in the brain, that is the 3D space and time. The vital role of time for cognition is a topic that recently attracted gradually increasing research interest. Surprisingly, the scientific community investigating mind-time interactions has mainly focused on interval timing, paying less attention on the encoding and processing of distant moments. The present work highlights two basic capacities that are necessary for developing temporal cognition in artificial systems. In particular, the seamless integration of agents in the environment assumes they are able to consider when events have occurred and how long they have lasted. This information, although rather standard in humans, is largely missing from artificial cognitive systems. In the present work we consider how a time perception model that is based on neural networks and the Streatal Beat Frequency (SBF) theory is extended in a way that besides the duration of events, facilitates the encoding of the time of occurrence in memory. The extended model is capable to support skills assumed in temporal cognition and answer time-related questions about the unfolded events

Temporal Cognition: A Key Ingredient of Intelligent Systems

Experiencing the flow of time is an important capacity of biological systems that is involved in many ways in the daily activities of humans and animals. However, in the field of robotics, the key role of time in cognition is not adequately considered in contemporary research, with artificial agents focusing mainly on the spatial extent of sensory information, almost always neglecting its temporal dimension. This fact significantly obstructs the development of high-level robotic cognitive skills, as well as the autonomous and seamless operation of artificial agents in human environments. Taking inspiration from biological cognition, the present work puts forward time perception as a vital capacity of artificial intelligent systems and contemplates the research path for incorporating temporal cognition in the repertoire of robotic skills

NGA Investment Incentives under Geographic Price Discrimination

This paper compares the impact of retail price discrimination and uniform pricing on a monopolist’s incentives to extend its Next Generation Access (NGA) network deployment to less densely populated geographic areas. It is found that geographic price discrimination provides the monopolist with higher incentives to deploy a larger NGA network. In addition, geographic price discrimination results in better welfare outcomes than uniform pricing as long as the investment cost is not extremely low. In such cases, the regulator should allow the monopolist to geographically price discriminate since the monopolist chooses the socially optimal pricing regime

NGA Investments: A departure from the existing cost and demand structure assumptions

The two most significant factors that affect the deployment of Next Generation Access (NGA) networks are the cost of the investment and the expected demand for the new fibre-based services. The related literature is based on very simplified assumptions regarding cost and demand structures. In particular, the investment cost is assumed to be increasing and convex reflecting the fact that fibre deployment becomes marginally more expensive as it is extended to rural, less populated areas. In addition, the demand for the new fibre-based services is estimated by assuming that a certain level of NGA investment leads all consumers to equally increase their willingness to pay for such services. This article contributes to the emerging research on the investment in access infrastructures. In particular, the assumptions about cost and demand structures are modified in order to capture the access networks’ underlying morphology complexity and the consumers’ socioeconomic characteristics, respectively. Firstly, an empirical analysis is conducted for the 100 major municipal departments from urban to rural in Greece. Their street network data are analyzed as the basis of the NGA installation combining GIS technology and Graph Theory techniques and hence the main cost-drivers are derived. Using regression analysis a real-data-based cost function is obtained. Secondly, a novel model that takes into account socioeconomic characteristics affecting the impact of a certain level of NGA investment on consumers’ willingness to pay is developed. The Pareto consumer distribution is used to reflect the greater (lower) positive impact of NGA investments on the willingness to pay of the consumers who live in more (less) populated areas. 2 The comparison of the existing models with the ones developed in this paper shows that: (i) the cost function used in the existing models always underestimates the investment cost of the higher populated areas and overestimates the investment cost of the lower populated areas; (ii) the demand for the new fibre-based services is higher under the proposed than the existing approach; and (iii) the level of NGA investment chosen by the investor is always much higher under the proposed than the existing approach

Robotic Interval Timing based on Active Oscillations

AbstractInterval timing is crucially involved in many of the daily activities of humans and animals. However, the cognitive mechanisms enabling the encoding and processing of time in the brain remain largely unknown. In the present work, we follow a self- organized modeling approach to study unconventional representations of time in neural network based cognitive system. A particularly interesting feature of our study regards the implementation of a single computational model to accomplish two different robotic behavioral tasks, which assume diverse manipulation of time intervals. The examination of the implemented cognitive system revealed that it is possible to integrate the two main theoretical models of time representation existing today - the dedicated and intrinsic representations - into a new theory that effectively combines their key characteristics

Weighing Price and Performance for Decisions for Multisource Pharmaceutical Bidding in Public Hospitals in Thailand

Following a national law introduced in 2017 in Thailand, the selection of winning bidders for multisourced pharmaceuticals and medical supplies in public hospitals must reflect “price-performance” aligned with the principles of worthiness, transparency, efficiency, effectiveness and accountability. We describe how a practical tool using Multiple Criteria Decision Analysis (MCDA) for evidence-based decision making in hospital bidding (tender) was developed through a multi-stakeholder workshop format. The local leader of the initiative together with 2 international advisors guided the 37 workshop participants through five interactive steps for local adaptation of the previously developed and validated global MCDA-tool: (1) Criteria selection, (2) Scoring definition, (3) Weighting of price criterion, (4) Definition of cut-off point for price criterion, (5) Ranking and weighting of remaining criteria. All consensus judgments were imported to the decision tool which can later be used in the real-world situation in the hospitals to support the selection and document the underlying rationale. The final list of criteria differs from the previously suggested international template and now reflects the Thai decision priorities and current decision processes. In the book chapter, the resulting model will be presented and a pathway for implementation will be discussed

A cost Malmquist productivity index capturing group performance

This paper develops an index for comparing the productivity of groups of operating units in cost terms when input prices are available. In that sense it represents an extension of a similar index available in the literature for comparing groups of units in terms of technical productivity in the absence of input prices. The index is decomposed to reveal the origins of differences in performance of the groups of units both in terms of technical and cost productivity. The index and its decomposition are of value in contexts where the need arises to compare units which perform the same function but they can be grouped by virtue of the fact that they operate in different contexts as might for example arise in comparisons of water or gas transmission companies operating in different countries

Pharmacoeconomic considerations in the treatment of breast cancer

Breast cancer is the most common malignancy in women worldwide and causes great economic burden. The aim of this paper is to present the available clinical and pharmacoeconomic evidence associated with different therapies for breast cancer. As significant progress was made in recent years and there are many alternative treatments, which are indicated according to the stage and the type of the disease, the age and health status of patient, and vary from surgery to hormonal treatment and chemotherapy. A broad literature review was undertaken and the paper presents the evidence available regarding the effectiveness and cost-effectiveness of the alternative options. Despite the high cost of most therapies and perceptions that treatments in this area may not be cost-effective, due to a combination of high costs and short survival, based on the literature review treatment options for breast cancer are in general deemed to be cost-effective. Time horizon, stage of the disease, patient age, therapy onset, benefit duration and time to recurrence may influence the results. Pharmacoeconomic analyses of alternative therapy options will improve decision-making and will help to optimize the use of scarce health care resources allocated to the care of breast cancer patients