Law and Development

This is a draft of a book to accompany a course on the sociology of law and law and development at Boston University

COMET: Co-simulation of Multi-Energy Systems for Energy Transition

The ongoing energy transition to reduce carbon emissions presents some of the most formidable challenges the energy sector has ever experienced, requiring a paradigm change that involves diverse players and heterogeneous concerns, includ- ing regulations, economic drivers, societal, and environmental aspects. Central to this transition is the adoption of integrated multi-energy systems (MES) to efficiently produce, distribute, store, and convert energy among different vectors. A deep understanding of MES is fundamental to harness the potential for energy savings and foster energy transition towards a low carbon future. Unfortunately, the inherent complexity of MES makes them extremely difficult to analyze, understand, design and optimize. This work proposes a digital twin co-simulation platform that provides a structured basis to design, develop and validate novel solutions and technologies for multi-energy system. The platform will enable the definition of a virtual representation of the real-world (digital twin) as a composition of models (co-simulation) that analyze the environment from multiple viewpoints and at different spatio-temporal scales

HARDWARE ATTACK DETECTION AND PREVENTION FOR CHIP SECURITY

Hardware security is a serious emerging concern in chip designs and applications. Due to the globalization of the semiconductor design and fabrication process, integrated circuits (ICs, a.k.a. chips) are becoming increasingly vulnerable to passive and active hardware attacks. Passive attacks on chips result in secret information leaking while active attacks cause IC malfunction and catastrophic system failures. This thesis focuses on detection and prevention methods against active attacks, in particular, hardware Trojan (HT). Existing HT detection methods have limited capability to detect small-scale HTs and are further challenged by the increased process variation. We propose to use differential Cascade Voltage Switch Logic (DCVSL) method to detect small HTs and achieve a success rate of 66% to 98%. This work also presents different fault tolerant methods to handle the active attacks on symmetric-key cipher SIMON, which is a recent lightweight cipher. Simulation results show that our Even Parity Code SIMON consumes less area and power than double modular redundancy SIMON and Reversed-SIMON, but yields a higher fault -detection-failure rate as the number of concurrent faults increases. In addition, the emerging technology, memristor, is explored to protect SIMON from passive attacks. Simulation results indicate that the memristor-based SIMON has a unique power characteristic that adds new challenges on secrete key extraction

Hardware Certification for Real-time Safety-critical Systems: State of the Art

This paper discusses issues related to the RTCA document DO-254 Design Assurance Guidance for Airborne Electronic Hardware and its consequences for hardware certification. In particular, problems related to circuits’ compliance with DO-254 in avionics and other industries are considered. Extensive literature review of the subject is given, including current views on and experiences of chip manufacturers and EDA industry with qualification of hardware design tools, including formal approaches to hardware verification. Some results of the authors’ own study on tool qualification are presented

Exposing Fake Logic

Exposing Fake Logic by Avi Sion is a collection of essays written after publication of his book A Fortiori Logic, in which he critically responds to derivative work by other authors who claim to know better. This is more than just polemics; but allows further clarifications of a fortiori logic and of general logic. This collection includes essays on: a fortiori argument (in general and in Judaism); Luis Duarte D’Almeida; Mahmoud Zeraatpishe; Michael Avraham (et al.); an anonymous reviewer of BDD (a Bar Ilan University journal); and self-publishing

Property as the Law of Things

The New Private Law takes seriously the need for baselines in general and the traditional ones furnished by the law in particular. One such baseline is the “things” of property. The bundle of rights picture popularized by the Legal Realists downplayed things and promoted the expectation that features of property are detachable and tailorable without limit. The bundle picture captures too much to be a theory. By contrast, the information cost, or architectural, theory proposed here captures how the features of property work together to achieve property’s purposes. Drawing on Herbert Simon’s notions of nearly decomposable systems and modularity, the article shows how property employs a thing-based exclusion-governance architecture to manage complexity of the interactions between legal actors. Modular property first breaks this system of interactions into components, and this begins with defining the modular things of property. Property then specifies the interface between the modular components of property through governance strategies that make more direct reference to uses and purposes, as in the law of nuisance, covenants, and zoning. In contrast to the bundle of rights picture, the modular theory captures how a great number of features of property – ranging from in-rem-ness, the right to exclude, and the residual claim, through alienability, persistence, and compatibility, and beyond to deep aspects like recursiveness, scalability, and resilience – follow from the modular architecture. The Article then shows how the information cost theory helps explain some puzzling phenomena such as the pedis possessio in mining law, fencing in and fencing out, the unit rule in eminent domain, and the intersection of state action and the enforcement of covenants. The Article concludes with some implications of property as a law of modular things for the architecture of private law

Concepção e realização de um framework para sistemas embarcados baseados em FPGA aplicado a um classificador Floresta de Caminhos Ótimos

Orientadores: Eurípedes Guilherme de Oliveira Nóbrega, Isabelle Fantoni-Coichot, Vincent FrémontTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica, Université de Technologie de CompiègneResumo: Muitas aplicações modernas dependem de métodos de Inteligência Artificial, tais como classificação automática. Entretanto, o alto custo computacional associado a essas técnicas limita seu uso em plataformas embarcadas com recursos restritos. Grandes quantidades de dados podem superar o poder computacional disponível em tais ambientes, o que torna o processo de projetá-los uma tarefa desafiadora. As condutas de processamento mais comuns usam muitas funções de custo computacional elevadas, o que traz a necessidade de combinar alta capacidade computacional com eficiência energética. Uma possível estratégia para superar essas limitações e prover poder computacional suficiente aliado ao baixo consumo de energia é o uso de hardware especializado como, por exemplo, FPGA. Esta classe de dispositivos é amplamente conhecida por sua boa relação desempenho/consumo, sendo uma alternativa interessante para a construção de sistemas embarcados eficazes e eficientes. Esta tese propõe um framework baseado em FPGA para a aceleração de desempenho de um algoritmo de classificação a ser implementado em um sistema embarcado. A aceleração do desempenho foi atingida usando o esquema de paralelização SIMD, aproveitando as características de paralelismo de grão fino dos FPGA. O sistema proposto foi implementado e testado em hardware FPGA real. Para a validação da arquitetura, um classificador baseado em Teoria dos Grafos, o OPF, foi avaliado em uma proposta de aplicação e posteriormente implementado na arquitetura proposta. O estudo do OPF levou à proposição de um novo algoritmo de aprendizagem para o mesmo, usando conceitos de Computação Evolutiva, visando a redução do tempo de processamento de classificação, que, combinada à implementação em hardware, oferece uma aceleração de desempenho suficiente para ser aplicada em uma variedade de sistemas embarcadosAbstract: Many modern applications rely on Artificial Intelligence methods such as automatic classification. However, the computational cost associated with these techniques limit their use in resource constrained embedded platforms. A high amount of data may overcome the computational power available in such embedded environments while turning the process of designing them a challenging task. Common processing pipelines use many high computational cost functions, which brings the necessity of combining high computational capacity with energy efficiency. One of the strategies to overcome this limitation and provide sufficient computational power allied with low energy consumption is the use of specialized hardware such as FPGA. This class of devices is widely known for their performance to consumption ratio, being an interesting alternative to building capable embedded systems. This thesis proposes an FPGA-based framework for performance acceleration of a classification algorithm to be implemented in an embedded system. Acceleration is achieved using SIMD-based parallelization scheme, taking advantage of FPGA characteristics of fine-grain parallelism. The proposed system is implemented and tested in actual FPGA hardware. For the architecture validation, a graph-based classifier, the OPF, is evaluated in an application proposition and afterward applied to the proposed architecture. The OPF study led to a proposition of a new learning algorithm using evolutionary computation concepts, aiming at classification processing time reduction, which combined to the hardware implementation offers sufficient performance acceleration to be applied in a variety of embedded systemsDoutoradoMecanica dos Sólidos e Projeto MecanicoDoutor em Engenharia Mecânica3077/2013-09CAPE

SUPPORTING ENGINEERING DESIGN OF ADDITIVELY MANUFACTURED MEDICAL DEVICES WITH KNOWLEDGE MANAGEMENT THROUGH ONTOLOGIES

Medical environments pose a substantial challenge for engineering designers. They combine significant knowledge demands with large investment for new product development and severe consequences in the case of design failure. Engineering designers must contend with an often-chaotic environment to which they have limited access and familiarity, a user base that is difficult to engage and highly diverse in many attributes, and a market structure that often pits stakeholders against one another. As medical care in general moves towards personalized models and surgical tools towards less invasive options emerging manufacturing technologies in additive manufacturing offer significant potential for the design of highly innovative medical devices. At the same time however these same technologies also introduce yet more challenges to the design process. This dissertation presents a knowledge-based approach to addressing the existing and emerging challenges of medical device design. The approach aims to address these challenges using knowledge captured in a suite of modular ontologies modeling knowledge domains that must be considered in medical device design. These include ontologies for understanding clinical context, human factors, regulation, enterprise, and manufacturability. Together these ontologies support design ideation, knowledge capture, and design verification. These ontologies are subsequently used to formulate a comprehensive knowledge framework for medical device design, and to enable an innovative design process. Case studies analyzing the design of surgical tools in several medical specialties are used to assess the capabilities of this approach