Abstract
Denial of Service attacks, which have become commonplace on the Information and Communications Technologies domain, constitute a class of threats whose main objective is to degrade or disable a service or functionality on a target. The increasing reliance of Cyber-Physical Systems upon these technologies, together with their progressive interconnection with other infrastructure and/or organizational domains, has contributed to increase their exposure to these attacks, with potentially catastrophic consequences. Despite the potential impact of such attacks, the lack of generality regarding the related works in the attack prevention and detection fields has prevented its application in real-world scenarios. This paper aims at reducing that effect by analyzing the behavior of classification algorithms with different dataset characteristics. © 2019, Springer Nature Switzerland AG.

Abstract
Besides fuel and waste distribution, one core application of multi-compartment vehicles (MCVs) is the distribution of groceries, as they enable retailers to jointly transport products with different temperature requirements, thus reducing the number of visits to a store. Grocery stores usually define preferable time windows that depend on the temperature of products (for example, fresh products in the morning) to indicate when deliveries should occur to better plan their in-store operations. Distribution planning therefore needs to take these preferences into consideration to obtain consistent delivery times. This work extends the research on multi-compartment vehicle routing problems (MCVRPs) by tackling a multi-period setting with a product-oriented time window assignment. In this problem, a fleet of MCVs is used for distribution and a unique time window for the delivery of each product segment to each store is defined consistently throughout the planning horizon. An ALNS is proposed to solve the product-oriented time window assignment for MCVRP. Daily and weekly operators are developed respectively focusing on the improvement of routing aspects of the problem on each day and aligning the time window assignment consistently throughout the planning horizon. The approach is tested on benchmark instances from the literature to demonstrate its effectiveness. We also use direct information from retail practice and enhance this with simulated data to further generalize our findings. The numerical experiments demonstrate that planning consistent MCV distribution leads to better overall solutions than the ex-post time window assignment of daily plans, facilitating more on-time deliveries.

Abstract
This paper presents iMPAcT tool that tests recurring common behavior on Android mobile applications. The process followed combines exploration, reverse engineering and testing to automatically test Android mobile applications. The tool explores automatically the App by firing UI events. After each event fired, the tool checks if there are UI patterns present using a reverse engineering process. If a UI pattern is present, the tool runs the corresponding testing strategy (Test Pattern). During reverse engineering the tool uses a catalog of UI Patterns which describes recurring behavior (UI Patterns) to test and the corresponding test strategies (Test Patterns). This catalog may be extended in the future as needed (e.g., to deal with new interaction trends). This paper describes the implementation details of the iMPAcT tool, the catalog of patterns used, the outputs produced by the tool and the results of experiments performed in order to evaluate the overall testing approach. These results show that the overall testing approach is capable of finding failures on existing Android mobile applications.

Abstract
In this article, a self-referencing intensity-based fiber optic sensor relying on the principle of Fabry-Perot interference is proposed and demonstrated to measure curvature. The sensor is manufactured producing an air bubble cavity between two sections of multimode fiber. By detecting optical power variations at specific wavelengths, it was possible to measure curvature, enabling this sensor as a self-referencing system. For this setup, the achieved curvature sensitivity was 0.561 ± 0.014 dB/m-1, with a correlation factor up to 0.997, within the measurement range of 0.0-0.8 m-1. The proposed system has several features, including the self-referencing characteristic and its structure simplicity in terms of measuring procedure, making it a useful system. © 2017 IEEE.

Abstract
Trusted open data can be used for auditing, accountability, business development, or as an anti-corruption mechanism. Metadata information can address provenance concerns, and trust issues can somehow be mitigated by digital signatures. Those approaches can trace the data origin, but usually lack information about the transformation process. Creating trust in an open data service through technology can reduce the need for third-party certifications, and creating a distributed consensus mechanism capable of validating all the transformations can guarantee that the datasets are reliable and easy to use. This work aims to leverage blockchain technologies to track open data transformations, allowing consumers to verify the data using a distributed ledger, and providing a mechanism capable of publishing trusted transformed data without relying on third-party certifications. To validate the proposed approach, use cases for data transformation will be used. The consensus protocol must be capable of validating the transformations according to a predefined algorithm, the provider must be capable of publishing verifiable transformed data, and the consumer should be able to check if a dataset originated by a transformation is legit. © 2020, Springer Nature Switzerland AG.

Abstract
To deliver more intense and enhanced experiences, multisensory applications have the goal to stimulate all our senses. The way these multisensory systems have been implemented is very distinct, since there are a lot of different approaches among them, aiming different goals. Thus, the structure defined for these systems depends on the stimuli that are being exploited, the technologies that are being used, the context in which they are being implemented, and on what is intended to obtain with the system. This study aims to propose the design of a multisensory system, named SensiMAR, that will provide an outdoor multisensory AR experience located at a cultural heritage site, allowing users to perceive different levels of immersion with the addition of a spatialized soundscape and with related smells.