A Design Methodology for a Computer-Supported Collaborative Skills Lab in Technical Translation Teaching

Aim/Purpose The aim of this study is to adopt more systematically the collaborative learning dimension in the technical translation teaching at Master Degree level. In order to do so, a computer-supported skills lab approach is targeted. This approach is aimed at enhancing traditional courses on Computer-Assisted Translation (CAT) so that student competences and soft skills are enhanced. Background In traditional CAT courses, laboratory sessions complement theoretical lessons, thus providing students mainly with tool-oriented operational knowledge, while nowadays more intertwined competences are required by the labor market. Moreover, this sector lacks skills labs which engage students in collaborative activities mimicking professional workflows, thus not exploiting team-based learning potential effectiveness. Methodology In this paper, therefore, a design methodology to deploy and operate an enhanced skills lab as a remote Computer-Supported Collaborative Simulated Translation Bureau (CS2TB) is proposed and validated. The proposed methodology is based on a set of intertwined methodological frameworks that address: 1) student competences and educational requirements, 2) collaborative aspects, 3) regulatory policies as well as functional and interactional guidelines for the simulated fieldwork. The overall effectiveness of the proposed methodology has been assessed by using pre-post questionnaires to ascertain student feedback. The improvement in technology skills has been evaluated by collecting and examining student help requests as well as system error logs. Contribution The CS2TB provides a technology-enhanced simulation-based learning environment whose aim is twofold: first, enriching traditional approaches with a Computer-Supported Collaborative Learning (CSCL) experience and, second, incorporating widely adopted approaches for the translation-teaching domain as the required grounding knowledge. Findings Results demonstrate the effectiveness of CS2TB in improving students' competences (specifically in the IT area but also in the technical translation area), students' willingness to operate in a fieldwork-like context and cooperative learning efficacy. Recommendations for Practitioners The educational implications of the proposed approach concern the development of a full range of competences and soft skills for students in the technical translation teaching at the higher education level, ranging from language and translation proficiency to the usage of IT platforms as well as personal and interpersonal interactional soft skills. Recommendations for Researchers This study offers a wide overview of all the aspects entailed by the design, implementation, management, and evaluation of a skills lab for technical translation teaching. Researchers may benefit from the rigorous modelling approach as well as from the adopted assessment techniques. Moreover, the study stresses the pivotal role of a tight collaboration between language/translation teaching and computer engineering. Impact on Society Higher education institutions that already have courses on computer-assisted translation may benefit from the proposed CS2TB approach, which allows them to design new thematic activities leveraging team-based learning, collaborative learning, and fieldwork-situated simulation. Moreover, the presented broad range of assessment approaches can be used to measure the impact of CS2TB on learning outcomes of the involved students. Future Research Future research activities will be dedicated to examining the impact of a different set of enabling IT platforms on the collaborative learning perspective, to evaluate alternative scaffolding approaches (e.g., chatbots or augmented reality), and to increase simulation fidelity further, so that even more student competences can be fostered

Wave-Shaped Round Functions and Primitive Groups

Round functions used as building blocks for iterated block ciphers, both in the case of Substitution-Permutation Networks and Feistel Networks, are often obtained as the composition of different layers which provide confusion and diffusion, and key additions. The bijectivity of any encryption function, crucial in order to make the decryption possible, is guaranteed by the use of invertible layers or by the Feistel structure. In this work a new family of ciphers, called wave ciphers, is introduced. In wave ciphers, round functions feature wave functions, which are vectorial Boolean functions obtained as the composition of non-invertible layers, where the confusion layer enlarges the message which returns to its original size after the diffusion layer is applied. This is motivated by the fact that relaxing the requirement that all the layers are invertible allows to consider more functions which are optimal with regard to non-linearity. In particular it allows to consider injective APN S-boxes. In order to guarantee efficient decryption we propose to use wave functions in Feistel Networks. With regard to security, the immunity from some group-theoretical attacks is investigated. In particular, it is shown how to avoid that the group generated by the round functions acts imprimitively, which represent a serious flaw for the cipher

Crowd-sensing our Smart Cities: a Platform for Noise Monitoring and Acoustic Urban Planning

Environmental pollution and the corresponding control measurements put in place to tackle it play a significant role in determining the actual quality of life in modern cities. Amongst the several pollutant that have to be faced on a daily basis, urban noise represent one of the most widely known for its already ascertained health-related issues. However, no systematic noise management and control activities are performed in the majority of European cities due to a series of limiting factors (e.g., expensive monitoring equipment, few available technician, scarce awareness of the problem in city managers). The recent advances in the Smart City model, which is being progressively adopted in many cities, nowadays offer multiple possibilities to improve the effectiveness in this area. The Mobile Crowd Sensing paradigm allows collecting data streams from smartphone built-in sensors on large geographical scales at no cost and without involving expert data captors, provided that an adequate IT infrastructure has been implemented to manage properly the gathered measurements. In this paper, we present an improved version of a MCS-based platform, named City Soundscape, which allows exploiting any Android-based device as a portable acoustic monitoring station and that offers city managers an effective and straightforward tool for planning Noise Reduction Interventions (NRIs) within their cities. The platform also now offers a new logical microservices architecture

Wave-shaped round functions and primitive groups

Round functions used as building blocks for iterated block ciphers, both in the case of Substitution-Permutation Networks (SPN) and Feistel Networks (FN), are often obtained as the composition of different layers. The bijectivity of any encryption function is guaranteed by the use of invertible layers or by the Feistel structure. In this work a new family of ciphers, called wave ciphers, is introduced. In wave ciphers, round functions feature wave functions, which are vectorial Boolean functions obtained as the composition of non-invertible layers, where the confusion layer enlarges the message which returns to its original size after the diffusion layer is applied. Efficient decryption is guaranteed by the use of wave functions in FNs. It is shown how to avoid that the group generated by the round functions acts imprimitively, a serious flaw for the cipher. The primitivity is a consequence of a more general result, which reduce the problem of proving that a given FN generates a primitive group to proving that an SPN, directly related to the given FN, generates a primitive group. Finally, a concrete instance of real-world size wave cipher is proposed as an example, and its resistance against differential and linear cryptanalyses is also established.acceptedVersio

Trustworthiness of Context-Aware Urban Pollution Data in Mobile Crowd Sensing

Urban pollution is usually monitored via fixed stations that provide detailed and reliable information, thanks to equipment quality and effective measuring protocols, but these sampled data are gathered from very limited areas and through discontinuous monitoring campaigns. Currently, the spread of mobile devices has fostered the development of new approaches, like Mobile Crowd Sensing (MCS), increasing the chances of using smartphones as suitable sensors in the urban monitoring scenario, because it potentially contributes massive ubiquitous data at relatively low cost. However, MCS is useless (or even counter-productive), if contributed data are not trustworthy, due to wrong data-collection procedures by non-expert practitioners. Contextualizing monitored data with those coming from phone-embedded sensors and from time/space proximity can improve data trustworthiness. This work focuses on the development of an algorithm that exploits context awareness to improve the reliability of MCS collected data. It has been validated against some real use cases for noise pollution and promises to improve the trustworthiness of end users generated data

Commissioning and improvements of the instrumentation and launch of the scientific exploitation of OARPAF, the Regional Astronomical Observatory of the Antola Park

The OARPAF telescope is an 80-cm-diameter optical telescope installed in the Antola Mount Regional Reserve, in Northern Italy. We present the results of the characterization of the site, as well as developments and interventions that have been implemented, with the goal of exploiting the facility for scientific and educational purposes. During the characterization of the site, an average background brightness of 22.40mAB (B filter) to 21.14mAB (I) per arcsecond squared, and a 1.5″ to 3.0″ seeing, have been measured. An estimate of the magnitude zero points for photometry is also reported. The material under commissioning includes three CCD detectors for which we provide the linearity range, gain, and dark current; a 31-orders échelle spectrograph with R ∼ 8500 to 15,000 and a dispersion of n = 1.39 × 10 − 6 px − 1λ + 1.45 × 10 − 4 nm / px, where λ is expressed in nm. The scientific and outreach potential of the facility is proven in different science cases, such as exoplanetary transits and active galactic nuclei variability. The determination of time delays of gravitationally lensed quasars, the microlensing phenomenon, and the tracking and the study of asteroids are also discussed as prospective science cases

Learning Analytics and MOOLs: there is much more than equipment usage logs

When dealing with online laboratories (either remote or virtual), it is crucial to monitor experiment activities and their outcomes closely, as well as to control how students access to these labs. A similar need also exists for evaluating student learning patterns and results, at both the individual and group level, so that customized study paths and contents can be proposed. To such aim, the research in the field of Learning Analytics has been very prolific in the recent decade, especially in the STEM area. This scenario becomes more challenging when online labs are offered as Massive Open Online Laboratories (MOOLs), large-scale and cloud-based infrastructure allowing students to access catalogs of online experiments on several topics as normally happens with traditional courses accessible via Massive Open Online Courses (MOOCs). This paper aims at focusing on the most relevant aspects of LA for MOOLs in terms of data requirements and data-related challenges, by examining four aspects that are tightly related to LA: data models and catalogs, data quality and scope, data privacy and ethics, and data visualizations. The resulting considerations can be used as a set of guidelines to take into account when designing a MOOL