Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity

Agent-based modeling is a simulation method in which autonomous agents interact with their environment and one another, given a predefined set of rules. It is an integral method for modeling and simulating complex systems, such as socio-economic problems. Since agent-based models are not described by simple and concise mathematical equations, the code that generates them is typically complicated, large, and slow. Here we present Agents.jl, a Julia-based software that provides an ABM analysis platform with minimal code complexity. We compare our software with some of the most popular ABM software in other programming languages. We find that Agents.jl is not only the most performant but also the least complicated software, providing the same (and sometimes more) features as the competitors with less input required from the user. Agents.jl also integrates excellently with the entire Julia ecosystem, including interactive applications, differential equations, parameter optimization, and so on. This removes any “extensions library” requirement from Agents.jl, which is paramount in many other tools.

Design of Low-Power SPIHT Decoder Based ECG Compression and Reconstruction System

This article proposes a 1D biomedical signal encoding scheme to allow embedding of metadata and to protect privacy. The compression of ECG signal and its reconstruction is implemented. The design concentrates on an overview of the criteria for safe and effective m-health storage, transmission, and access to medical tests. However, existing architectures for encoding SPIHT are designed to process images/videos. Significant memory and complex sorting algorithms are required for both architectures, and they all require time-consuming tasks that do not apply to mobile ECG applications. On the basis of our previously updated SPIHT coding research, we used flags and bit controls to reduce memory needs and code complexity through a combination of three search processes in one phase. The goal of real-time architecture for mobile ECG applications is therefore to be accomplished. In order first, to solve the disadvantages of the low-encryption speed of coded and complex hardware architectures that characterize previous SPIHT algorithms, we propose a SPIHT coding algorithm that uses several types of state registry files because of its need for dynastic c to attain real-time and performance design objectives. Secondly, a highly piped and efficient VLSI architecture is used to implement a high-efficiency and low-power SPIHT design based on the proposed algorithm.

DBOS

This paper lays out the rationale for building a completely new operating system (OS) stack. Rather than build on a single node OS together with separate cluster schedulers, distributed filesystems, and network managers, we argue that a distributed transactional DBMS should be the basis for a scalable cluster OS. We show herein that such a database OS (DBOS) can do scheduling, file management, and inter-process communication with competitive performance to existing systems. In addition, significantly better analytics can be provided as well as a dramatic reduction in code complexity through implementing OS services as standard database queries, while implementing low-latency transactions and high availability only once.

Study on Insights in Software Defect prediction

Software defect prediction is a process of constructing machine learning classifiers to predict defective code snippets, using historical information in software repositories such as code complexity and change records to design software defect metrics , In this research article we have tried to understand the relationships between various variables which are important for IT SME’s ,The study is carried out with the help of a well structured questionnaire using IBM SPSS tool for data analysis and interpretation .

The Costs of Corporate Tax Complexity

Does tax code complexity alter corporate behavior? We investigate this question by studying the decision to claim refunds for tax losses. In a sample of 1.2 million observations from the population of corporate tax returns, only 37 percent of eligible firms claim their refund. A simple cost-benefit analysis of the tax loss choice cannot explain low take-up, motivating an exploration of how complexity alters this calculation. Research designs exploiting tax preparer switches, deaths, and relocations show that sophisticated preparers increase claim rates for small firms. Imperfect take-up has implications for measuring marginal tax rates and for the design of fiscal policy. (JEL D22, D61, E62, H25, K34)