Study on the existence of the transportation particle tracking model in the interactive medium

This paper assumes that the particle jumps randomly (Guassian jumps) from one point to another along one of the imaginary lines inside the interactive medium. Since this study was done in the space, we consider that the position of the particle at any time [Formula: see text] has a multivariate distribution. The random waiting time of the particle for each Gaussian jump depends on its length. An identical set of programed nanosensors (with unit speed) were used to track this particle. Each line has a sensor that starts the tracking process from the origin. The existence of the necessary conditions which give the optimal search plan and the minimum expected value of the particle detection has been proven. This study is supported by a numerical example.

Inattention in Contract Markets: Evidence from a Consolidation of Options in Telecom

We study customer inattention by utilizing a notification about a future price change in the mobile subscription market. With detailed customer-level data from a large telecom operator, together with data on prices and contracts offered by competitors, we document that the notification causes an increase in customer attention, which triggers search, plan switching, and churn. In particular, we show that the monthly propensity to churn increases by 60% (from 1% to 1.6%) among customers whose costs would decrease with the new prices. We also document an increase in churn directly after the notification, not at the time of the future price change, and argue that this timing pattern is evidence of sophisticated inattention: customers take immediate action to mitigate the impact of their own future inertia. We supplement the analysis with a survey and find supporting evidence for the important role of inattention in determining how consumers adapt to changes in the market. This paper was accepted by Eric Anderson, marketing.

How it's done: search tools and techniques for major bibliographic databases

This article explains how to write an effective search plan using simple steps. The article takes you through the tools and techniques that are widely used in major bibliographic databases such as MEDLINE and CINAHL to conduct searches. These include Boolean logic, truncation and wildcards, in-field searching, proximity operators, limits and subject thesauri. Each process is illustrated with an example to help you apply them to your own searches. The process of using these tools and techniques to either narrow (find fewer results) or broaden (find more results) is described and summarised in an easy-to-use table.

PECULIARITIES OF INVESTIGATION OF CRIMINAL CASES ASSOCIATED WITH ARSONS

The article discusses some of the features of the investigation of criminal cases involving arson. Recommendations are given for the officers of the investigative-operational groups when planning further actions at the initial stage of the investigation of arson. The questions about the influence on the detection rate of the promptness of arrival to the place of the fire of the investigator (interrogator), about the features of collecting information at the place of the fire are touched upon. Obtaining information on the basis of special knowledge, allowing to formulate a search plan for the alleged offender and his criminological personality portrait. With the development of new technologies, for the efficiency of obtaining information from a specialist (expert) in the investigation of arson, it is necessary to use the technology of immersive telepresence (video presence). This allows for a better inspection of the crime scene in the absence of an expert (specialist) directly on the spot. The use of electronic databases and the use of modern means of communication also contribute to solving crimes related to arson hot on the trail.

Extended Search Planning for Multiple Moving Targets Incorporating Search Priorities

This article deals with a one-searcher multi-target search problem where targetswith different detection priorities move in Markov processes in each discrete time interval over agiven space search area, and the total number of search time intervals is fixed. A limitedsearch resource is available in each search time interval and an exponential detection functionis assumed. The searcher can obtain a target detection reward, if the target is detected, whichrepresents the detection priority of target and does not increase with respect to time. The objective is toestablish the optimal search plan that allocates the search resource effort over the search areasin each time interval in order to maximize the total detection reward. The analysis shows that the given problem can be decomposed into interval-wise individualsearch problems, each being treated as a single stationary target problem for each timeinterval. Thus, an iterative procedure is derived to solve a sequence of stationary targetproblems. The computational results show that the proposed algorithm guaranteesoptimality.