We propose a fast real-time state estimator based on the belief propagation algorithm for the power system state estimation. The proposed estimator is easy to distribute and parallelize, thus alleviating computational limitations and allowing for processing measurements in real time. The presented algorithm may run as a continuous process, with each new measurement being seamlessly processed by the distributed state estimator. In contrast to the matrix-based state estimation methods, the belief propagation approach is robust to ill-conditioned scenarios caused by significant differences between measurement variances, thus resulting in a solution that eliminates observability analysis. Using the DC model, we numerically demonstrate the performance of the state estimator in a realistic real-time system model with asynchronous measurements. We note that the extension to the AC state estimation is possible within the same framework.

The term "portfolio analysis", introduced in the economic theory by Harry Markowitz, is not a new term in scientific literature. However, analysis and criticism in the papers of local and foreign authors are mainly based on the examples of developed capital markets. There are very few cases of application of the portfolio analysis in the domestic capital market. The focus of this paper is on implementation of diversification of the bonds on the Banja Luka Stock Exchange. Using Markowitz's portfolio selection, we will prove that diversification, including all limitations, is possible and applicable onto the domestic bonds in the capital market.

This study is intended to analyze the possible ways of using the SHERPA Ranger joint precision airdrop system, acquired by the Brazilian Army (EB), as well as its possible employment by the Brazilian Air Force (FAB) vectors. Historical aspects of development, acquisition and support of the joint precision airdrop system (JPADS) are here discussed. The study covers the use of SHERPA Ranger by the Brazilian Armed Forces (FFAA), based on the Military Defense Doctrine (2007) and the Doctrine of Joint Operations (2011). It is also investigated whether the inclusion of this equipment as Product of Defense (PRODE) can increase the projection of national military power

HCI researchers investigating the politics of technology design have recently focused on how design practice can tackle "Matters of Concern" - complex social issues perceived and experienced in multiple ways. These researchers suggest design research can generate new networks of human and non-human actors to express and act on these issues. Prior studies, however, tend to restrict their networks within traditional boundaries (e.g. existing organizations, local communities) and categories (e.g. human/nonhuman binary) without examining their significance for participants. We suggest collaborative map making as a reflexive method for understanding current Matters of Concern from the perspectives of diverse actors, not just researchers. As case studies of the method's use, we present two studies of domestic computing technologies in the US and South Korea, which show how collaborative map making allows salient networks to expand beyond the individual actors in the home to local and global power issues outside of boundaries (e.g. physical house) and categories (e.g. private/public space) commonly recognized in HCI. Our methodology provides HCI researchers with a way to understand existing Matters of Concern, so they can position themselves to address and act on these issues.

Knowing accurately the dynamic parameters of a manipulated object is required for common coordination strategies in physical human-robot interaction. Bias in object dynamics results in inaccurately calculated robot wrenches, which may disturb the human during interaction and bias the recognition of the human motion intention. This paper presents an identification strategy of object dynamics for physical human-robot interaction, which allows the tracking of desired human motion and inducing the motions necessary for parameter identification. The estimation of object dynamics is performed online and the estimator minimizes the least square error between the measured and estimated wrenches acting on the object. Identification-relevant motions are derived by analyzing the persistence of excitation condition, necessary for estimation convergence. Such motions are projected in the null space of the partial grasp matrix, relating the human and the robot redundant motion directions, to avoid disturbance of the human desired motion. The approach is evaluated in a physical human-robot object manipulation scenario.

Harvesting energy from nonconventional sources in the environment has received increased attention over the past decade from researchers who study these alternative energy sources for low power applications. Although that energy harvested is small and in the order of milliwatt, it can provide enough power for wireless sensors and other low-power applications. In the environment there is a lot of wasted energy that can be converted into electricity to power the various circuits and represents a potentially cheap source of power. Energy harvesting is important because it offers an alternative power supply for electronic devices where is does not exist conventional energy sources. This technology applied in a wireless sensor network (WSN) and devices on the IoT, will eliminate the need for network-based energy and conventional batteries, will minimize maintenance costs, eliminate cables and batteries and is ecological. It has the same advantage in applications from remote locations, underwater, and other hard to reach places where conventional batteries and energy are not suitable. Energy harvesting will promote environmentally friendly technologies that will save energy, will reduce CO2 emissions, which makes this technology indispensable for achieving next-generation smart cities and sustainable society. In response to the challenges of energy, in this article we remind the basics of harvesting energy and we discuss the various applications of this technology where traditional batteries cannot be used.