Formal metatheory of second-order abstract syntax

Despite extensive research both on the theoretical and practical fronts, formalising, reasoning about, and implementing languages with variable binding is still a daunting endeavour – repetitive boilerplate and the overly complicated metatheory of capture-avoiding substitution often get in the way of progressing on to the actually interesting properties of a language. Existing developments offer some relief, however at the expense of inconvenient and error-prone term encodings and lack of formal foundations. We present a mathematically-inspired language-formalisation framework implemented in Agda. The system translates the description of a syntax signature with variable-binding operators into an intrinsically-encoded, inductive data type equipped with syntactic operations such as weakening and substitution, along with their correctness properties. The generated metatheory further incorporates metavariables and their associated operation of metasubstitution, which enables second-order equational/rewriting reasoning. The underlying mathematical foundation of the framework – initial algebra semantics – derives compositional interpretations of languages into their models satisfying the semantic substitution lemma by construction.

Algoritma pemrograman

An algorithm is a logical step or sequence in making a decision to solve a problem. Algorithms can be written in many ways, such as using everyday language, flow charts and even using programming languages such as C or C++. And in the algorithm there is also a Flowchart which means an image or graph of the steps that must be followed to make it easier to solve the problem. Programming languages cannot be separated from data types, if/else, arrays because these have an important role for beginners or those who want to know about programming languages. Writing scientific articles can make it easier for readers to know about algorithms and programming languages. Keywords: algorithm, algorithm and programming, programming language, data type, writing algorithm

Fragility indices for only sufficiently likely modifications

The fragility index is a clinically meaningful metric based on modifying patient outcomes that is increasingly used to interpret the robustness of clinical trial results. The fragility index relies on a concept that explores alternative realizations of the same clinical trial by modifying patient measurements. In this article, we propose to generalize the fragility index to a family of fragility indices called the incidence fragility indices that permit only outcome modifications that are sufficiently likely and provide an exact algorithm to calculate the incidence fragility indices. Additionally, we introduce a far-reaching generalization of the fragility index to any data type and explain how to permit only sufficiently likely modifications for nondichotomous outcomes. All of the proposed methodologies follow the fragility index concept.

FPGA-Based Convolutional Neural Network Accelerator with Resource-Optimized Approximate Multiply-Accumulate Unit

Convolutional neural networks (CNNs) are widely used in modern applications for their versatility and high classification accuracy. Field-programmable gate arrays (FPGAs) are considered to be suitable platforms for CNNs based on their high performance, rapid development, and reconfigurability. Although many studies have proposed methods for implementing high-performance CNN accelerators on FPGAs using optimized data types and algorithm transformations, accelerators can be optimized further by investigating more efficient uses of FPGA resources. In this paper, we propose an FPGA-based CNN accelerator using multiple approximate accumulation units based on a fixed-point data type. We implemented the LeNet-5 CNN architecture, which performs classification of handwritten digits using the MNIST handwritten digit dataset. The proposed accelerator was implemented, using a high-level synthesis tool on a Xilinx FPGA. The proposed accelerator applies an optimized fixed-point data type and loop parallelization to improve performance. Approximate operation units are implemented using FPGA logic resources instead of high-precision digital signal processing (DSP) blocks, which are inefficient for low-precision data. Our accelerator model achieves 66% less memory usage and approximately 50% reduced network latency, compared to a floating point design and its resource utilization is optimized to use 78% fewer DSP blocks, compared to general fixed-point designs.

Protein Structure, Models of Sequence Evolution, and Data Type Effects in Phylogenetic Analyses of Mitochondrial Data: A Case Study in Birds

Phylogenomic analyses have revolutionized the study of biodiversity, but they have revealed that estimated tree topologies can depend, at least in part, on the subset of the genome that is analyzed. For example, estimates of trees for avian orders differ if protein-coding or non-coding data are analyzed. The bird tree is a good study system because the historical signal for relationships among orders is very weak, which should permit subtle non-historical signals to be identified, while monophyly of orders is strongly corroborated, allowing identification of strong non-historical signals. Hydrophobic amino acids in mitochondrially-encoded proteins, which are expected to be found in transmembrane helices, have been hypothesized to be associated with non-historical signals. We tested this hypothesis by comparing the evolution of transmembrane helices and extramembrane segments of mitochondrial proteins from 420 bird species, sampled from most avian orders. We estimated amino acid exchangeabilities for both structural environments and assessed the performance of phylogenetic analysis using each data type. We compared those relative exchangeabilities with values calculated using a substitution matrix for transmembrane helices estimated using a variety of nuclear- and mitochondrially-encoded proteins, allowing us to compare the bird-specific mitochondrial models with a general model of transmembrane protein evolution. To complement our amino acid analyses, we examined the impact of protein structure on patterns of nucleotide evolution. Models of transmembrane and extramembrane sequence evolution for amino acids and nucleotides exhibited striking differences, but there was no evidence for strong topological data type effects. However, incorporating protein structure into analyses of mitochondrially-encoded proteins improved model fit. Thus, we believe that considering protein structure will improve analyses of mitogenomic data, both in birds and in other taxa.

Legal Issues of Smart Contracts in Contract Law

The research is carried out on some legal issues of smart contracts and their place in Russian and other countries’ contract law. By means of contract law such issues are analysed: 1) conclusion and performance of smart contracts’ obligations; 2) practical issues arising due to smart contracts’ use; 3) contract law provisions that might be applied to smart contracts; 4) issues that are not covered by the legislation but need to be addressed. A smart contract is considered to be a contract with the specific type of performance of obligations (automated performance). Smart contract is a contract concluded with an exchange of data (type of a written form). Smart contracts are performed with the help of automated performance and previously expressed consent of parties. It is proved that smart contracts could be modified and terminated giving a mechanism for that as well as provides for measures of defence and responsibility that could be applied for obligations out of smart contracts. As the result, provisions of smart contracts that reflect smart contracts’ place and peculiarities in contract law are formulated

The digital twin as data type in the Internet of Things

Digitalization is discussed nearly everywhere in the world. This article describes the basics of digitalization which were originally developed for Industry. However the concept can also be used in our daily life as a blue-print of the infrastructure for the Internet of Things and Services (IoTS) which is shown in this article.