Abstract
Even renewable energy sources provide several advantages, especially from an environmental point of view, where the world has faced great challenges in the last few decades; several negative issues also exist regarding the integration of renewable resources-based power production units in electric power systems. One of the main problems related to pivotal renewable energy resources such as solar, wind, etc., is their stochastic and uncontrollable nature in terms of power production. Therefore, this stochasticity in the supply side of the power system may pose many challenges for system operators. This issue is also problematic for smaller applications where the stochastic production by a main resource, such as a roof-top photovoltaic system, and load demand may not match perfectly at each time instant and therefore should be compensated by additional resources such as battery-based energy storage systems. Herein, the economic considerations to ensure minimum costs for such a hybrid system design are vital so as to increase the penetration of such systems. Therefore, the optimal sizing and planning of hybrid systems have recently gained increasing importance to enhance power system operation in the context of the smart grid paradigm. From a different perspective, harmonics are one of the most important power quality problems in system operations caused by widespread integration of power electronic loads with non-linear characteristics that should be considered. Thus, a new approach for grid-connected hybrid renewable energy system sizing is provided. In order to determine optimal capacities for photovoltaic (PV) and energy storage system (ESS) units for covering residential consumer demand, a mixed integer linear programming (MILP)-based formulation is presented. The main objective is minimizing total costs of the system consisting of investment, capital and maintenance cost functions. A daily power curve is created accurately with real measurements of non-linear loads considering harmonic contents of smart home appliances in Yildiz Technical University, Istanbul, Turkey. In addition, real radiation and temperature values are used in PV production as well as dynamic pricing schemes for realistic evaluations. Moreover, optimal sizing results are compared for both the harmonic-based power curve and rated power curve in terms of satisfying objective function.

Abstract
The importance of recycling is well known, either for environmental or economic reasons, it is impossible to escape it and the industry demands efficiency. Manual labour and traditional industrial sorting techniques are not capable of keeping up with the objectives demanded by the international community. Solutions based in computer vision techniques have the potential automate part of the waste handling tasks. In this paper, we propose a hierarchical deep learning approach for waste detection and classification in food trays. The proposed two-step approach retains the advantages of recent object detectors (as Faster R-CNN) and allows the classification task to be supported in higher resolution bounding boxes. Additionally, we also collect, annotate and make available to the scientific community a new dataset, named Labeled Waste in the Wild, for research and benchmark purposes. In the experimental comparison with standard deep learning approaches, the proposed hierarchical model shows better detection and classification performance. © 2019 IEEE.

Abstract
Purpose Considering the differences between rural and urban spaces, through the theoretical framework developed, the purpose of this paper is to uncover and rationalize the differences between rural and urban new ventures in terms of the environment surrounding the new venture, their general characteristics (e.g. sector, size) and export/economic performance. Design/methodology/approach The theoretical framework is empirically assessed resorting to exploratory statistical analysis based on data collected from a questionnaire survey responded by 408 new ventures headquartered in Portuguese business incubators and science parks. The data collected were treated with the Software Package for the Social Sciences. Findings The results evidence that rural and urban new ventures differ in terms of generic characteristics, namely sector, size and collaborators' human capital. Additionally, they differ concerning export and economic performance as well in relation to the perception of the municipality support. Originality/value The present study innovatively contributes to uncover the role of rural and urban context in entrepreneurship and adds to the scanty empirical literature in the area.

Abstract
Literature has highlighted the challenges of selling experience (vs. search) products online. In addition, the role of celebrity endorsers in purchase intention and attitudes towards brands has been emphasized by scholars. This article argues that celebrities provide cues on products' sensorial characteristics that have been so far disregarded by extant literature. By choosing perfume as a complex experience product, twenty-seven participants from three countries were interviewed in order to find how endorsers could assist e-shoppers to identify fragrant characteristics in the absence of the real scent. The results of the qualitative content analysis reveal that endorsers' personality traits and lifestyle could act as predictor of the type of scent. Scent categorization based on such traits are presented. This article provides valuable contributions to both researchers and practitioners interested in online sales of experience goods. Limitations and avenues for future search are also provided.

Abstract

Abstract
The growth in Internet usage has increased the use of electronic services requiring users to register their identity on each service they subscribe to. This has resulted in the prevalence of redundant users data on different services. To protect and regulate access by users to these services identity management systems (IdMs) are put in place. IdMs uses frameworks and standards e.g SAML, OAuth and Shibboleth to manage digital identities of users for identification and authentication process for a service provider. However, current IdMs have not been able to address privacy issues (unauthorised and fine-grained access) that relate to protecting users identity and private data on web services. Many implementations of these frameworks are only concerned with the identification and authentication process of users but not authorisation. They mostly give full control of users digital identities and data to identity and service providers with less or no users participation. This results in a less privacy enhanced solutions that manage users available data in the electronic space. This article proposes a user-centred mandate representation system that empowers resource owners to take full of their digital data; determine and delegate access rights using their mobile phone. Thereby giving users autonomous powers on their resources to grant access to authenticated entities at their will. Our solution is based on the OpenID Connect framework for authorisation service. To evaluate the proposal, we've compared it with some related works and the privacy requirements yardstick outlined in GDPR regulation [1] and [2]. Compared to other systems that use OAuth 2.0 or SAML our solution uses an additional layer of security, where data owner assumes full control over the disclosure of their identity data through an assertion issued from their mobile phones to authorisation server (AS), which in turn issues an access token. This would enable data owners to assert the authenticity of a request, while service providers and requestors also benefit from the correctness and freshness of identity data disclosed to them.