Abstract
Nowadays, mobile manipulators are increasing its popularity on modern industries due to their ability to enhance process flexibility and performance. Mobile manipulators are a wide field of research and one of the main directions is trying to control the whole system as a single device. In this context, this paper addresses the problem of path planning of the end-effector of a mobile manipulator. The proposed approach is based on the integration of the kinematic chain of both the manipulator and the omni-directional base. At the end, a collision-free path planner for the mobile manipulator in complex and known environments with obstacles using A * is derived.

Abstract
The demand side, which was formerly considered as an inelastic part of the power system operation, has recently been evaluated as a source of flexibility to enhance the effectiveness and economy of power system operation. Several real world examples and literature studies exist to evaluate the contribution of demand side flexibility in power system operation in this manner. Accordingly, in this study, a smart thermostat controller for direct load control based demand response applications for controlling the thermostatically controllable loads by Thermostat Set-point Control Mechanism (TSCM) method is developed differently from the existing studies, where few of them have considered the real world applicability requirements of such concepts. The concept has been experimentally verified under different case studies. © 2019 IEEE.

Abstract
The multi-energy systems (MES) contain key resources driving the evolution of the future systems. Various components and convertors that are available in a MES make it operationally flexible and a potential source to be deployed in system operation. Like any other resources in the system, the flexibility brought by MES needs to be fairly valued. One of the approaches is through market participation of these resources. In this regard, new agents and trade system need to be defined. This paper studies the interactions of a multi-energy aggregator on various trade levels defined within the multi-energy paradigm. The levels include the upstream multi-energy markets as well as local energy trades such as local resources and flexible demand. The results discuss the increased level of profit due to the availability of multi-energy trade to the aggregator.

Abstract
This research evaluates IRCA registered auditors' perspectives of the added value of ISO 9001:2015 to the organizations that adopt it and are certified accordingly, bringing P a more independent perspective than previous studies based on quality managers or consultants' views. Supported by a worldwide survey among IRCA registered auditors and the adoption of a Covariance based- Structural Equation Modelling (CB-SEM) approach the results point out that the auditors' judgment regarding the ISO 9001:2015 value is influenced by their perceptions (regarding the document) and experience (auditing). The research results highlight the importance of selecting auditors with the appropriate ISO 9001:2015 knowledge and experience to assess ISO 9001:2015 Quality Management Systems (QMSs) within the certification process, therefore, contributing to the business and processes performance improvement and sustainable outcomes.

Abstract
This paper proposes a stochastic decision making problem for a wind power producer (WPP) in the day-ahead (DA) and balancing markets. In this problem, bidding strategy of the WPP in a competitive electricity market and also its participation to supply demand response (DR) and electric vehicle (EV) aggregators is determined to achieve the maximum profit. In this model, DR and EV aggregators are able to choose the most competitive WPP in such a way that their energy payments be minimized in the scheduling horizon. Therefore, the problem is formulated as a stochastic bi-level programming model with conflict objectives of the WPP and the aggregators. Moreover, owing to the uncertainties associated with market prices, offered prices by rival WPPs, demand of DR and EV aggregators, conditional value at risk (CVaR) is applied to the proposed model. The attained stochastic bi-level problem is transformed to a linear stochastic single level problem with equilibrium constraints using Karush Kuhn Tucker (KKT) optimality conditions. The proposed model is evaluated on a realistic case study and the impacts of risk-averse behavior and demand response participants on the decision making problem of the WPP are investigated. Numerical results indicate that with increasing DR participants of 0%, 60% and 100%, CVaR of WPP increases 33.81%, 40.79% and 46.99%, respectively. This means that if the loads are more responsive, the WPP tries to control the profit variability due to the uncertainties of loads.

Abstract
In this article a new Data-Driven formulation of the Particle Filter framework is proposed. The new formulation is able to learn an approximate proposal distribution from previous data. By doing so, the need to explicitly model all the disturbances that might affect the system is relaxed. Such characteristics are particularly suited for Terrain Based Navigation for sensor-limited AUVs, where typical scenarios often include non-negligible sources of noise affecting the system, which are unknown and hard to model. Numerical results are presented that demonstrate the superior accuracy, robustness and efficiency of the proposed Data-Driven approach.