Approaches for FPGA Design Assurance

Field-Programmable Gate Arrays (FPGAs) are widely used for custom hardware implementations, including in many security-sensitive industries, such as defense, communications, transportation, medical, and more. Compiling source hardware descriptions to FPGA bitstreams requires the use of complex computer-aided design (CAD) tools. These tools are typically proprietary and closed-source, and it is not possible to easily determine that the produced bitstream is equivalent to the source design. In this work, we present various FPGA design flows that leverage pre-synthesizing or pre-implementing parts of the design, combined with open-source synthesis tools, bitstream-to-netlist tools, and commercial equivalence-checking tools, to verify that a produced hardware design is equivalent to the designer’s source design. We evaluate these different design flows on several benchmark circuits and demonstrate that they are effective at detecting malicious modifications made to the design during compilation. We compare our proposed design flows with baseline commercial design flows and measure the overheads to area and runtime.

Software-Defined Network Application for Inter-domain Routing in Transit ISPs

<p>Today, the Internet plays an vital part in our society. We rely greatly on the Internet to work, to communicate and to entertain. The Internet is a very large and complex computer network, consisting of tens of thousands of networks called autonomous systems (ASes). The key routing protocol for interdomain routing between ASes, Border Gateway Protocol (BGP), was invented three decades ago. Although BGP has undergone many improvements, many fundamental problems and limitations of BGP still exist today. For instance, BGP does not have the resiliency to attacks and good support for traffic engineering. To date, many evolutionary and revolutionary solutions have been proposed to address these problems. However, very few were adopted. While there are many reasons for this limited adoption, one may blame for the lack of deployability, scalability and more importantly adequate functionality. SDN is a new networking paradigm that decouples the control plane and data plane. SDN breaks the ossification of the Internet and enables network innovations. SDN has been thoroughly investigated for the enterprise environment. This research investigates the application of SDN for interdomain routing in transit ASes. Specifically, the main goal is to study how SDN capabilities can be utilised to develop a scalable, programmable and flexible routing architecture for transit ISPs.</p>

Software-Defined Network Application for Inter-domain Routing in Transit ISPs

<p>Today, the Internet plays an vital part in our society. We rely greatly on the Internet to work, to communicate and to entertain. The Internet is a very large and complex computer network, consisting of tens of thousands of networks called autonomous systems (ASes). The key routing protocol for interdomain routing between ASes, Border Gateway Protocol (BGP), was invented three decades ago. Although BGP has undergone many improvements, many fundamental problems and limitations of BGP still exist today. For instance, BGP does not have the resiliency to attacks and good support for traffic engineering. To date, many evolutionary and revolutionary solutions have been proposed to address these problems. However, very few were adopted. While there are many reasons for this limited adoption, one may blame for the lack of deployability, scalability and more importantly adequate functionality. SDN is a new networking paradigm that decouples the control plane and data plane. SDN breaks the ossification of the Internet and enables network innovations. SDN has been thoroughly investigated for the enterprise environment. This research investigates the application of SDN for interdomain routing in transit ASes. Specifically, the main goal is to study how SDN capabilities can be utilised to develop a scalable, programmable and flexible routing architecture for transit ISPs.</p>

CHAT framework to study affordances in CALL environments

This paper proposes to explore the theory of affordances in the light of cultural historical activity theory (CHAT) to study affordances in complex Computer Assisted Language Learning (CALL) environments. The term ‘affordance’ designates an action possibility that is offered by an environment or an object to an actor in the environment either “for good or ill” (Gibson, 1979). It depends not only on the inherent characteristics of the environment but also on the users’ perception and action capabilities. CALL affordances are said to be a unique combination of social, educational, linguistic, and technological affordances (Blin, 2016a). However, there is limited research to date that looks at affordances from an ecological perspective linking the micro moment-to-moment interaction levels with the macro level within which they are embedded in educational contexts (Blin, 2016a). This paper explores the analytical tools of CHAT (Leontyev, 1978; Engeström, 1987) as particularly suitable to investigate affordances at the macro, meso and micro levels of technology-mediated sociocultural educational contexts in CALL.

On the issue of analyzing the technical condition of agricultural machinery using neural networks

This article is devoted to the increasing role of artificial intelligence in agriculture, namely in the diagnosis of the state of agricultural machinery. The development of new software using artificial intelligence in its work is carried out all over the world. Also, in parallel with the programs, new computing devices are being developed that allow storing and processing large amounts of information. All this allows you to create complex computer systems that involve many third-party devices. In addition, agriculture should develop, focusing on current trends.

A Segmentation Method of Foramen Ovale Based on Multiatlas

Trigeminal neuralgia is a neurological disease. It is often treated by puncturing the trigeminal nerve through the skin and the oval foramen of the skull to selectively destroy the pain nerve. The process of puncture operation is difficult because the morphology of the foramen ovale in the skull base is varied and the surrounding anatomical structure is complex. Computer-aided puncture guidance technology is extremely valuable for the treatment of trigeminal neuralgia. Computer-aided guidance can help doctors determine the puncture target by accurately locating the foramen ovale in the skull base. Foramen ovale segmentation is a prerequisite for locating but is a tedious and error-prone task if done manually. In this paper, we present an image segmentation solution based on the multiatlas method that automatically segments the foramen ovale. We developed a data set of 30 CT scans containing 20 foramen ovale atlas and 10 CT scans for testing. Our approach can perform foramen ovale segmentation in puncture operation scenarios based solely on limited data. We propose to utilize this method as an enabler in clinical work.

Multi Expression Programming

Multi Expression Programming (MEP) is a new evolutionary paradigm intended for solving computationally difficult problems. MEP individuals are linear entities that encode complex computer programs. MEP chromosomes are represented in the same way as C or Pascal compilers translate mathematical expressions into machine code. MEP is used for solving some difficult problems like symbolic regression and game strategy discovering. MEP is compared with Gene Expression Programming (GEP) and Cartesian Genetic Programming (CGP) by using several well-known test problems. For the considered problems MEP outperforms GEP and CGP. For these examples MEP is two magnitude orders better than CGP.

Multi Expression Programming - an in-depth description

Multi Expression Programming (MEP) is a Genetic Programming variant that uses a linear representation of chromosomes. MEP individuals are strings of genes encoding complex computer programs. When MEP individuals encode expressions, their representation is similar to the way in which compilers translate C or Pascal expressions into machine code. A unique MEP feature is the ability to store multiple solutions to a problem in a single chromosome. Usually, the best solution is chosen for fitness assignment. When solving symbolic regression or classification problems (or any other problems for which the training set is known before the problem is solved) MEP has the same complexity as other techniques storing a single solution in a chromosome (such as GP, CGP, GEP, or GE). Evaluation of the expressions encoded into an MEP individual can be performed by a single parsing of the chromosome. Offspring obtained by crossover and mutation is always syntactically correct MEP individuals (computer programs). Thus, no extra processing for repairing newly obtained individuals is needed.

Multi Expression Programming

Multi Expression Programming (MEP) is a new evolutionary paradigm intended for solving computationally difficult problems. MEP individuals are linear entities that encode complex computer programs. MEP chromosomes are represented in the same way as C or Pascal compilers translate mathematical expressions into machine code. MEP is used for solving some difficult problems like symbolic regression and game strategy discovering. MEP is compared with Gene Expression Programming (GEP) and Cartesian Genetic Programming (CGP) by using several well-known test problems. For the considered problems MEP outperforms GEP and CGP. For these examples MEP is two magnitude orders better than CGP.