471 research outputs found

    La traduzione specializzata all’opera per una piccola impresa in espansione: la mia esperienza di internazionalizzazione in cinese di Bioretics© S.r.l.

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    Global markets are currently immersed in two all-encompassing and unstoppable processes: internationalization and globalization. While the former pushes companies to look beyond the borders of their country of origin to forge relationships with foreign trading partners, the latter fosters the standardization in all countries, by reducing spatiotemporal distances and breaking down geographical, political, economic and socio-cultural barriers. In recent decades, another domain has appeared to propel these unifying drives: Artificial Intelligence, together with its high technologies aiming to implement human cognitive abilities in machinery. The “Language Toolkit – Le lingue straniere al servizio dell’internazionalizzazione dell’impresa” project, promoted by the Department of Interpreting and Translation (Forlì Campus) in collaboration with the Romagna Chamber of Commerce (Forlì-Cesena and Rimini), seeks to help Italian SMEs make their way into the global market. It is precisely within this project that this dissertation has been conceived. Indeed, its purpose is to present the translation and localization project from English into Chinese of a series of texts produced by Bioretics© S.r.l.: an investor deck, the company website and part of the installation and use manual of the Aliquis© framework software, its flagship product. This dissertation is structured as follows: Chapter 1 presents the project and the company in detail; Chapter 2 outlines the internationalization and globalization processes and the Artificial Intelligence market both in Italy and in China; Chapter 3 provides the theoretical foundations for every aspect related to Specialized Translation, including website localization; Chapter 4 describes the resources and tools used to perform the translations; Chapter 5 proposes an analysis of the source texts; Chapter 6 is a commentary on translation strategies and choices

    Recent Developments in Federal Income Taxation: The Year 2012

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    This recent developments outline discusses, and provides context to understand the significance of, the most important judicial decisions and administrative rulings and regulations promulgated by the Internal Revenue Service and Treasury Department during the most recent twelve months — and sometimes a little farther back in time if we find the item particularly humorous or outrageous. Most Treasury Regulations, however, are so complex that they cannot be discussed in detail and, anyway, only a devout masochist would read them all the way through; just the basic topic and fundamental principles are highlighted – unless one of us decides to go nuts and spend several pages writing one up. This is the reason that the outline is getting to be as long as it is. Amendments to the Internal Revenue Code generally are not discussed except to the extent that (1) they are of major significance, (2) they have led to administrative rulings and regulations, (3) they have affected previously issued rulings and regulations otherwise covered by the outline, or (4) they provide Dan and Marty the opportunity to mock our elected representatives; again, sometimes at least one of us goes nuts and writes up the most trivial of legislative changes. The outline focuses primarily on topics of broad general interest (to the three of us, at least) – income tax accounting rules, determination of gross income, allowable deductions, treatment of capital gains and losses, corporate and partnership taxation, exempt organizations, and procedure and penalties. It deals summarily with qualified pension and profit sharing plans, and generally does not deal with international taxation or specialized industries, such as banking, insurance, and financial services. Please read this outline at your own risk; we take no responsibility for any misinformation in it, whether occasioned by our advancing ages or our increasing indifference as to whether we get any particular item right. Any mistakes in this outline are Marty’s responsibility; any political bias or offensive language is Ira’s; and Dan is just irresponsible

    Principles of ecosystem strategy

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    Strategy scholars and business practitioners alike are increasingly using the ecosystem concept to describe networks of interdependent firms that collaborate and align to offer complementary products and services and collectively contribute to an overarching value proposition. Companies that operate in ecosystems are playing by a different set of strategy rules to navigate these complex, interconnected and dynamic business environments. Accordingly, a whole new stream of literature is emerging, specifically looking at strategic management in the context of ecosystems. Early research in that field has generally taken a static view and examined firm strategy form the perspective of ecosystem leaders, who often exert a disproportionate influence over the ecosystem structure and capture the lion’s share of profits. Less is known about firm strategy from the perspective of ecosystem complementors, who are responsible for a significant share of the co-created value but are often dismissed as passive actors, subject to the whims of the more powerful ecosystem leader. This dissertation addresses this gap through three tightly linked studies. The first study reviews over 250 academic articles from the ecosystem literature and discusses the status quo of research on ecosystem strategy, identifying several blind spots and avenues for future research, among which the almost exclusive attention given to the ecosystem leader perspective at the cost of better understanding complementors’ strategic options. The second study builds upon the first one by taking aim at the burgeoning research on complementor strategy. It analyses this subset of the literature in depth, synthesises our current understanding of complementor strategy, and identifies several theoretical gaps and avenues for further research in that stream. This includes, for example, the question of how complementors can navigate ecosystem change. Finally, the third study specifically addresses this gap by empirically studying how complementors respond to and navigate ecosystem change. To do so, over 40 mobile app developers were interviewed in the context of Apple’s introduction of a new mobile operating system (iOS 14.5) for its iPhone. Together, these studies offer several theoretical and managerial contributions. The central theoretical contribution of this dissertation is to examine the multiple facets of strategic management in ecosystems, both from an ecosystem leader and from a complementor perspective. Specifically, the dissertation highlights how ecosystem members can gain a competitive edge and capture value in hypercompetitive and interconnected value creation systems, thus contributing both to the ecosystem and strategic management literature. Furthermore, my dissertation also uncovers how changes initiated by the ecosystem leader can ripple through an ecosystem and affect complementor performance, thus expanding our current understanding of platform dynamics and highlighting the importance of the dynamic capabilities concept for ecosystem research. Also, by elucidating how complementors adapt to ecosystem change, my dissertation contributes to the literature on business models and business model innovation in the context of ecosystems and platforms. Finally, by comparing and discussing the differences between ecosystem strategy and more established views in the strategic management literature, my dissertation also draws a bridge between seminal strategy work and the new field of ecosystem strategy. The central managerial contribution of this dissertation is to offer strategic insights into how firms (both ecosystem leaders and complementors) can successfully navigate ecosystem change, based on the case study of Apple’s introduction of the ATT framework. Concretely, my study suggests several ways in which ecosystem leaders could minimize disruption and successfully execute platform change, while also highlighting a wide range of strategies complementors have at their disposal to avoid the negative effects of ecosystem dynamics and seize potential opportunities arising in the context of ecosystem disruption

    A Low-Energy Security Solution for IoT-Based Smart Farms

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    This work proposes a novel configuration of the Transport Layer Security protocol (TLS), suitable for low energy Internet of Things (IoT), applications. The motivation behind the redesign of TLS is energy consumption minimisation and sustainable farming, as exemplified by an application domain of aquaponic smart farms. The work therefore considers decentralisation of a formerly centralised security model, with a focus on reducing energy consumption for battery powered devices. The research presents a four-part investigation into the security solution, composed of a risk assessment, energy analysis of authentication and data exchange functions, and finally the design and verification of a novel consensus authorisation mechanism. The first investigation considered traditional risk-driven threat assessment, but to include energy reduction, working towards device longevity within a content-oriented framework. Since the aquaponics environments include limited but specific data exchanges, a content-oriented approach produced valuable insights into security and privacy requirements that would later be tested by implementing a variety of mechanisms available on the ESP32. The second and third investigations featured the energy analysis of authentication and data exchange functions respectively, where the results of the risk assessment were implemented to compare the re-configurations of TLS mechanisms and domain content. Results concluded that selective confidentiality and persistent secure sessions between paired devices enabled considerable improvements for energy consumptions, and were a good reflection of the possibilities suggested by the risk assessment. The fourth and final investigation proposed a granular authorisation design to increase the safety of access control that would otherwise be binary in TLS. The motivation was for damage mitigation from inside attacks or network faults. The approach involved an automated, hierarchy-based, decentralised network topology to reduce data duplication whilst still providing robustness beyond the vulnerability of central governance. Formal verification using model-checking indicated a safe design model, using four automated back-ends. The research concludes that lower energy IoT solutions for the smart farm application domain are possible

    Identifying Ransomware Through Statistical and Behavioural Analysis

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    Ransomware is a devastating type of malicious software that restricts a user's access to a digital asset of value, demanding a ransom in order to restore it. Ransomware attacks have only increased in popularity over the years and show no signs of abating. Moreover, the complexity and potential impact of these attacks have also increased, such that modern-day ransomware attacks are capable of bringing businesses and organisations to a standstill, with ransom demands often in excess of millions of pounds. The research presented in this thesis aims to contribute to a stronger foundation of knowledge regarding this relatively new cyberthreat through the development of several novel countermeasures. An in-depth analysis of current state-of-the-art anti-ransomware tools was conducted, through which an overall preference towards statistical and behavioural detection methods was identified. Additionally, several datasets and an analysis environment were constructed in order to identify and subsequently improve current statistical and behavioural approaches, contributing towards more effective ransomware detection. Untapped potential within statistical-based approaches to ransomware detection was clearly identified, showing that near-perfect classification rates were possible within the scope of our experiments. Despite the continual growth both in terms of frequency and sophistication of ransomware attacks, our results suggest that the significant differences in system behaviour observed during a ransomware attack are enough to identify and thwart ransomware attacks. Future work should pay particular attention to these clear fingerprints created by ransomware attacks, such that damages can largely be mitigated, alleviating the need to pay the ransom and thus toppling the underground ransomware economy

    Technology Assessment of Dual-Use ICTs - How to Assess Diffusion, Governance and Design

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    Technologies that can be used in military and civilian applications are referred to as dual-use. The dual-use nature of many information and communications technologies (ICTs) raises new questions for research and development for national, international, and human security. Measures to deal with the risks associated with the various dual-use technologies, including proliferation control, design approaches, and policy measures, vary widely. For example, Autonomous Weapon Systems (AWS) have not yet been regulated, while cryptographic products are subject to export and import controls. Innovations in artificial intelligence (AI), robotics, cybersecurity, and automated analysis of publicly available data raise new questions about their respective dual-use risks. Dual-use risks have been systematically discussed so far, especially in the life sciences, which have contributed to the development of methods for assessment and risk management. Dual-use risks arise, among other things, from the fact that safety-critical technologies can be easily disseminated or modified, as well as used as part of a weapon system. Therefore, the development and adaptation of robots and software requires an independent consideration that builds on the insights of related dual-use discourses. Therefore, this dissertation considers the management of such risks in terms of the proliferation, regulation, and design of individual dual-use information technologies. Technology Assessment (TA) is the epistemological framework for this work, bringing together the concepts and approaches of Critical Security Studies (CSS) and Human-Computer Interaction (HCI) to help evaluate and shape dual-use technologies. In order to identify the diffusion of dual-use at an early stage, the dissertation first examines the diffusion of dual-use innovations between civilian and military research in expert networks on LinkedIn, as well as on the basis of AI patents in a patent network. The results show low diffusion and tend to confirm existing studies on diffusion in patent networks. In the following section, the regulation of dual-use technologies is examined in the paper through two case studies. The first study uses a discourse analysis to show the value conflicts with regard to the regulation of autonomous weapons systems using the concept of Meaningful Human Control (MHC), while a second study, as a long-term comparative case study, analyzes the change and consequences of the regulation of strong cryptography in the U.S. as well as the programs of intelligence agencies for mass surveillance. Both cases point to the central role of private companies, both in the production of AWS and as intermediaries for the dissemination of encryption, as well as surveillance intermediaries. Subsequently, the dissertation examines the design of a dual-use technology using an Open Source Intelligence System (OSINT) for cybersecurity. For this purpose, conceptual, empirical, and technical studies are conducted as part of the Value-Sensitive Design (VSD) framework. During the studies, implications for research on and design of OSINT were identified. For example, the representative survey of the German population has shown that transparency of use while reducing mistrust is associated with higher acceptance of such systems. Additionally, it has been shown that data sparsity through the use of expert networks has many positive effects, not only improving the performance of the system, but is also preferable for legal and social reasons. Thus, the work contributes to the understanding of specific dual-use risks of AI, the regulation of AWS and cryptography, and the design of OSINT in cybersecurity. By combining concepts from CSS and participatory design methods in HCI, this work provides an interdisciplinary and multi-method contribution

    Trustworthy machine learning through the lens of privacy and security

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    Nowadays, machine learning (ML) becomes ubiquitous and it is transforming society. However, there are still many incidents caused by ML-based systems when ML is deployed in real-world scenarios. Therefore, to allow wide adoption of ML in the real world, especially in critical applications such as healthcare, finance, etc., it is crucial to develop ML models that are not only accurate but also trustworthy (e.g., explainable, privacy-preserving, secure, and robust). Achieving trustworthy ML with different machine learning paradigms (e.g., deep learning, centralized learning, federated learning, etc.), and application domains (e.g., computer vision, natural language, human study, malware systems, etc.) is challenging, given the complicated trade-off among utility, scalability, privacy, explainability, and security. To bring trustworthy ML to real-world adoption with the trust of communities, this study makes a contribution of introducing a series of novel privacy-preserving mechanisms in which the trade-off between model utility and trustworthiness is optimized in different application domains, including natural language models, federated learning with human and mobile sensing applications, image classification, and explainable AI. The proposed mechanisms reach deployment levels of commercialized systems in real-world trials while providing trustworthiness with marginal utility drops and rigorous theoretical guarantees. The developed solutions enable safe, efficient, and practical analyses of rich and diverse user-generated data in many application domains
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