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AbstractA memoryless agent can acquire arbitrarily many signals. After each signal observation, she either terminates and chooses an action, or she discards her observation and draws a new signal. By conditioning the probability of termination on the information collected, she controls the correlation between the payoff state and her terminal action. We provide an optimality condition for the emerging stochastic choice. The condition highlights the benefits of selective memory applied to the extracted signals. Implications—obtained in simple examples—include (i) confirmation bias, (ii) speed-accuracy complementarity, (iii) overweighting of rare events, and (iv) salience effect.

AbstractAlthough we can support Heyes' call for more research on mechanisms, we disagree that the problem has been ignored as Heyes suggests. We also doubt that basic learning mechanisms are alone sufficient to account for the broad range of findings in the selective social learning literature. Although phylogenetically shared learning mechanisms must support selective social learning, we believe that they must also be guided by top‐down conceptual considerations that may be special to humans. Research to date has been focused on establishing the boundary conditions on selective social learning, with the goal of making generalizations that will constrain theorizing about the character of that special knowledge. This is critical to our understanding of both why and how selective social learning manifests in children.

This paper investigates the application of MIMO to the FBMC/OQAM scheme in highly frequency selective channels. The system model that is considered in this work does not make any assumption about the flatness of the channel. In this scenario, it is definitely challenging the design of MIMO precoding and decoding matrices that succeed in removing the interference. In this regard, we have derived the degrees of freedom, in terms of number of streams (S), transmit (NT ) and receive (NR) antennas, required to eliminate the unwanted signals. The analysis reveals that in some multi-antenna configurations some residual interference should be expected. In this case, we have further studied existing low-complexity solutions that solve optimization problems that depend on the MSE. Numerical results show that the sum-rate in FBMC/OQAM is on pair with OFDM when NR - 1 = NT = S = 2. This result is relevant because the adoption of FBMC/OQAM brings substantial improvements with respect to OFDM in a variety of contexts. ; Grant number: This work has received funding from the Catalan Government under grant 2014 SGR 1567. © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Most of the time the budget constraints in the socialist economies were harder than in developing countries and no less hard than in developed countries. The soft budget constraints (SBC) in socialist economies were not pervasive, as most authors believe, but selective, i.e. involved subsidization of some enterprises/industries at the expense of the other. This type of selective subsidization is a classic case of industrial policy: it may be good or bad, leading to success (China, Vietnam) or failure (USSR, Eastern Europe), but cannot be regarded as an intrinsic feature of the socialist centrally planned economy and an example of pervasive SBC. Pervasive SBC should be associated with permanent government budget deficit, debt accumulation, high inflation and other forms of macroeconomic populism. In the Soviet Union in the post-war period (after the monetary reform of 1947 and until the Gorbachev financial and monetary expansion that started in 1987) budget deficit and debt were very low, open and hidden inflation was less than several percent a year - a better record than in most Western countries. But in the 1990s in Russia, other former Soviet republics and most East European countries budget constraints were weakened dramatically and inflation increased to hundreds and thousands percent a year. SBC is just one type of this populist macroeconomic policy that was rare in socialist countries, but is found in abundance in many developing countries (especially Latin America and Sub-Sahara Africa) and transition economies (especially FSU states).

The MDGs has been carved out of the UN Millennium Declaration adopted in the fifty-fifth session of the UN General Assembly in September, 2000. Significantly, the MDGs has a bias towards health, education and empowerment. This could be construed as a positive move in international policy as far as the development agenda is concerned. But a closer look at the strategies show that there are several roadblocks towards achieving these goals. The major constraint is the lack of reliable data in developing countries for planning public health programmes. This results in an element of uncertainty and leads to unrealistically high targets which could distort the already fragile health systems in several countries. The selective approach could also spiral intensive drives which might further erode the primary health care system as has happened with the attempt to eradicate polio. The alternative, therefore, is to evolve longer-term, broader, system-based interventions to address the health concerns in the MDGs.

Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations ; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable.

The paper provides a selective survey of the literature on the Feldstein-Horioka paradox. The observed high correlation between national savings and domestic investment emerges as a robust empirical regularity. If this regularity is to be attributed to low capital mobility (due to government interventions or market imperfections) or other factors (such as immobility of goods, shocks or intertemporal budget constraints) cannot be resolved. The empirical evidence on the relative importance of the possible factors is too sketchy. Excluding government interventions, the possible impact of market imperfections in causing saving-investment corrrelations has hardly been investigated so far.

Nowadays, in the European Union selective solid waste management be-longs to important responsibilities of municipalities. In Solid Waste Management (SWM) the main operational task is to set a schedule for solid waste collection and to find optimal routes for garbage trucks so that the total costs of solid waste collection service can be minimized subject to a series of constraints which guarantee not only fulfillment of SWM's obligations but also desirable level of quality of that service. Optimization problem of garbage trucks routing is a special case of rich Vehicle Routing Problem as it has to cover following constraints: pickup nodes (clients) must be visited during their predefined time windows; the number and capacity of depots and specialized sorting units can-not be exceeded; each garbage truck can be assigned to at most one depot; each route should be dedicated to collecting one type of segregated solid waste, and the route must be served by a garbage truck which can collect that type of solid waste; availability of garbage trucks and their drivers must be respected; each garbage truck must be drained at a specialized sorting unit before going back to the depot. This paper contributes with a new Mixed-Integer Programming (MIP) model for the Selective Solid Waste Collection Routing Problem (SS-WCRP) with time windows, limited heterogeneous fleet, and different types of segregated solid waste to be collected separately. Utilization of MIP for solving small-sized instance of the Fleet Optimization Problem for Selective Solid Waste Collection (FOPSSWC) is and obtained results are reported.

PurposeTo provide an Asia‐Pacific viewpoint of the key constraints associated with large geographic distances for smaller westerns firms entering central and eastern Europe (CEE), described as a turbulent transitional environment.Design/methodology/approachAn exploratory study was used within a qualitative methodology, using eight case studies across multiple industries. Semi‐structured interviews were the main method of data collection conducted in 2003/2004. Open, axial and selective coding was used for the analysis to identifying issues.FindingsKey internal constraints for smaller western firms (mindset of western management and middle management in CEE; and lack of management in CEE with decision‐making authority) related to managements' inability to recognize geographic and psychic distance as major external constraints. Largely overcome by enhancing communication between various functional groups; adapting organizational structure; maintaining frequent communicational; developing partnerships in international joint ventures; finding reliable distributors and commitment from re‐sellers and working with government. While no single international business theory adequately explains this process, there is overwhelming support for the network perspective and international entrepreneurship.Research limitations/implicationsThe study is limited by small sample size. The explanatory phase is proposed with further western companies, such as the UK, operating in CEE to identify geographic distance, and additional CEE markets to verify dimensions in this environment.Practical implicationsThe paper provides a checklist of strategies for overcoming constraints facing managers of smaller firms, entering emerging markets with geographic distance.Originality/valuePrevious studies, using a European or Nordic viewpoint, fail to identify the constraints associated with large geographic distances. This paper provides practical assistance to managers starting out in CEE from the Asia‐Pacific.

In an actual industrial or military operations environment, a multi-state system (MSS) consisting of multi-state components often needs to perform multiple missions in succession. To improve the probability of the system successfully completing the next mission, all the maintenance activities need to be performed during maintenance breaks between any two consecutive missions under limited maintenance resources. In such case, selective maintenance is a widely used maintenance policy. As a typical discrete mathematics problem, selective maintenance has received widespread attention. In this work, a selective maintenance model considering human reliability for multi-component systems is investigated. Each maintenance worker can be in one of multiple discrete working levels due to their human error probability (HEP). The state of components after maintenance is assumed to be random and follow an identified probability distribution. To solve the problem, this paper proposes a human reliability model and a method to determine the state distribution of components after maintenance. The objective of selective maintenance scheduling is to find the maintenance action with the optimal reliability for each component in a maintenance break subject to constraints of time and cost. In place of an enumerative method, a genetic algorithm (GA) is employed to solve the complicated optimization problem taking human reliability into account. The results show the importance of considering human reliability in selective maintenance scheduling for an MSS.