Automatic Software Research Articles

Novel analysis tool for the distance of gold dimers controlled by the DNA strand length on the DNA origami.

Metallic nanoparticle dimers have been used to enhance the excitation rate of single-quantum emitters. The interparticle distance (d) of the dimers has a crucial influence on the signal enhancement. Therefore, precise control of d is desired for optimal performance. However, statistical analysis of d has been often restricted to a small number of dimers due to the lack of reliable automatic software tools. For this reason, we developed a novel analysis tool for automatic dimer analysis. Our approach combines particle detection by circle Hough transformation (CHT) with custom classification routines optimised for distinct types of particles. We applied our tool to scanning electron microscopy (SEM) images and achieved great agreement in dimer detection, reaching an agreement of around 97% between automatic analysis and manual inspection for more than 3000 metallic nanoparticle dimers on DNA origami controlled by a combination of multiple DNA strands. Our study revealed the effects of the strand length (L) on the distribution of d. Based on geometric consideration, we expected a strong correlation between L and the standard deviation (σ) of d. We could verify this correlation by characterising four dimer designs with different L while analysing more than 1000 dimers per specimen.

SWA: SoftWare for Analog Design Automation

We have developed SWA: SoftWare for Analog design automation. Its commands can describe analog and mixed-signal (AMS) layouts and schematics to replace the graphic editor with a program reflecting the knowledge of design experts. Also, it is able to utilize variables to parameterize schematics and layouts to fulfill design needs. We programmed a 10b 1 GS/s DAC using SWA with 8.3 K lines of code, which is about 1/10 compared with conventional programs. The programmed DAC is configurable with multiple voltages and multiple resolutions from 4 to 12 bits. The DAC schematic and layout generation with DRC and LVS SWA API can be finished in about 1 min.

PD-Free Design of Insulation Systems: An Application to Laminated Busbars

The reliability of components of industrial electrical assets fed by power electronics might be at risk due to the type and extent of electrothermal stresses. The move of power electronics toward higher levels of voltage, switching frequency, slew rate, and specific power increases the risk of partial discharge inception and thus of accelerated extrinsic aging and premature failure. The reaction to this challenge is to embrace the concept of partial discharge-free (PD-free) design and operation. This paper presents a PD-free approach to the design of laminated busbars, considering both AC and DC insulation subsystems, and focusing on surface insulation. The availability of a recently proposed model to estimate the inception field is a key tool. The model is validated through PD measurements performed on a laminated busbar, using new automatic software that can identify the type of source generating PD. Combined with electric field calculations, the model provides estimates of the PD inception voltage which are almost coincident with the measurement results. Inception voltages in the order of 10 kV and 20 kV have been observed for AC and DC excitation, respectively. In the case of DC supply, tests at different ambient temperatures, 25 °C and 60 °C, indicate that the inception voltage does not change significantly with temperature. Disposability, scalability to any voltage/power, and capability to work, potentially, for any other type of insulation system, are interesting features of the proposed approach, which are discussed in the paper.

Combining Type Checking and Set Constraint Solving to Improve Automated Software Verification

Abstract This technical note shows how we have combined prescriptive type checking and constraint solving to increase automation during software verification. We do so by defining a type system and implementing a typechecker for $\{log\}$ (read ‘setlog’), a Constraint Logic Programming language and satisfiability solver based on set theory. The constraint solver is proved to be safe w.r.t. the type system. Two industrial-strength case studies are presented where this combination is used with very good results.

Retinal and Macular Changes in Pregnant Women of Advanced Maternal Age: A Retrospective Study.

Aims/Background Pregnancy may cause physiological and pathological changes in multiple organs in a woman's body, including the heart, liver, and eyes. With rapid advances in societies and economies, the proportion of advanced maternal age (AMA) women has significantly increased. Here, we aimed to investigate the changes in arteriole retinal diameter, venule diameter, macular layer thickness, and arteriole to venule ratio (AVR) in this population. Methods This retrospective case-control study included 523 pregnant women (1046 eyes) and was performed on both eyes. In total, 318 subjects were included in the AMA group, and 205 subjects were included in the non-AMA group. Nonmydriatic fundus photography and optical coherence tomography (OCT) were performed on the same day, and the results were analyzed for the central retinal arteriolar equivalent (CRAE), central retinal venular equivalent (CRVE), AVR, and macular thickness (9 subfields) by integrative vessel analysis and automatic OCT software. Results In both eyes, the CRAE was significantly lower in the AMA group than that in the non-AMA group (p < 0.05; respectively). The CRVE in the AMA group was higher than that in the non-AMA group (p < 0.001; respectively). Compared to the non-AMA group, the AMA group exhibited a significant reduction in macular thickness within the inner nasal, outer nasal, and inner temporal subfields of both eyes (p < 0.05; respectively). Age was significantly correlated with CRVE and AVR in both eyes of pregnant women (CRVE: p < 0.0001; AVR: p < 0.01). Conclusion This study reports variations in the diameter of the retinal vasculature and the thickness of the macula in women of AMA. It is important to consider these changes when interpreting the adverse eye outcomes experienced by women of AMA.

The role of semi-quantitative parameters of thallium-201 myocardial perfusion imaging in predicting mortality rate among CKD population

Abstract Background Chronic kidney disease (CKD) is a major public health concern worldwide, with high morbidity and mortality rates. Myocardial perfusion imaging (MPI) is a non-invasive diagnostic tool that can detect early-stage cardiovascular disease in CKD patients. Purpose This study aimed to investigate the role of semi-quantitative parameters of Thallium-201 MPI in predicting mortality rates among CKD patients. Methods This retrospective study included 579 CKD patients who underwent Thallium-201 MPI between October 2005 and December 2019. Semi-quantitative parameters were analyzed using automation software, including transient ischemic dilation (TID), lung-to-heart ratio (LHR), total perfusion deficit (TPD), summed stress score (SSS), summed rest score (SRS), summed difference score (SDS), summed thickening percent (ST%), summed motion percent (SM%), stress end-diastolic volume (EDV), stress end-systolic volume (ESV), and stress left ventricular ejection fraction (LVEF). The primary endpoint was overall mortality. Results During a median follow-up of 52 months, 148 patients died. The older age group, lower hemoglobin levels, and lower estimated glomerular filtration rate (eGFR) were associated with higher mortality rates. The semi-quantitative parameters that predicted overall mortality included LHR above 0.4, elevated ST% , increased stress EDV and ESV, and reduced stress LVEF in a multivariable Cox regression model. Conclusion Thallium-201 MPI with semi-quantitative parameters can predict mortality rates in CKD patients without a definite diagnosis of coronary artery disease. The identified parameters, including LHR above 0.4, elevated ST levels, increased stress EDV and ESV, and reduced stress LVEF can assist in early detection the mortality risk in CKD patients.Characteristics of CKD PatientsMultivariable Analysis

Practice and Application of Intelligent Technology in Software Automation Testing

Practice and Application of Intelligent Technology in Software Automation Testing

Framework to enable and test conversational assistant for APIs and RPAs

AbstractIn the realm of business automation, conversational assistants are emerging as the primary method for making automation software accessible to users in various business sectors. Access to automation primarily occurs through application programming interface (APIs) and robotic process automation (RPAs). To effectively convert APIs and RPAs into chatbots on a larger scale, it is crucial to establish an automated process for generating data and training models that can recognize user intentions, identify questions for conversational slot filling, and provide recommendations for subsequent actions. In this paper, we present a technique for enhancing and generating natural language conversational artifacts from API specifications using large language models (LLMs). The goal is to utilize LLMs in the “build” phase to assist humans in creating skills for digital assistants. As a result, the system does not need to rely on LLMs during conversations with business users, leading to efficient deployment. Along with enabling digital assistants, our system employs LLMs as proxies to simulate human interaction and automatically evaluate the digital assistant's performance. Experimental results highlight the effectiveness of our proposed approach. Our system is deployed in the IBM Watson Orchestrate product for general availability.

Enhancing Faculty Grading Productivity Using Robotic Process Automation (RPA): The Development of a Structured Query Language (SQL) Automated Grading Tool

ABSTRACT Using the design science methodology, we develop an automated grading bot using robotic process automation (RPA) software. This grader demonstrates RPA’s capability to enhance the efficiency and accuracy of grading structured query language (SQL) queries. Validation of the RPA grader demonstrates that it can grade assignments and/or exams in 30 to 60 minutes, a task that would take a human grader approximately 50 hours. In contrast to human graders, who misgraded 5 to 8 percent of queries, the RPA grader graded all queries correctly. Notably, it correctly evaluated 188 distinct correct solutions submitted by students to a single question. To facilitate broad adoption, we provide instructions and the necessary code for implementing the RPA grader. We validate that professors and teaching assistants can successfully implement the RPA grader even with no previous bot building experience.

Energy Aware Technology Mapping of Genetic Logic Circuits.

Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers─as caused by the additional burden of artificial genetic circuits─shifts a cell's priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state model of gene expression, capturing characteristics like energy dissipation─which we link to the entropy production rate─and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit's functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energetic costs of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.

Multi-reference coupled cluster theory using the normal ordered exponential ansatz.

Properly spin-adapted coupled-cluster theory for general open-shell configurations remains an active area of research in electronic structure theory. In this contribution we examine Lindgren's normal-ordered exponential ansatz to correlate specific spin states using spin-free excitation operators, with the aid of automatic equation generation software. We present an intermediately normalised and size-extensive reformulation of the unlinked working equations, and analyse the performance of the method with single and double excitations for simple molecular systems in terms of accuracy and size-consistency.

Preoperative Planning for Shoulder Arthroplasty is Feasible with Computed Tomography at Lower-Than-Conventional Radiation Doses

Computed tomography (CT) offers a detailed assessment of the shoulder for preoperative shoulder arthroplasty planning; however, this technique exposes the patient to ionizing radiation. The purpose of this study was to prospectively evaluate the practicality of reducing the CT radiation dose compared to conventional dose levels for manual and preoperative planning software measurements for shoulder arthroplasty. A total of 10 shoulder CT examinations were performed for preoperative planning purposes on a dual x-ray source CT scanner. A specialized dose-split scan technique was utilized to reconstruct CT images corresponding to 100%, 70%, and 30% radiation dose relative to our institution's standard of care imaging protocol. Glenoid version, inclination, and humeral head subluxation were measured manually by three authors and by commercially available software platforms. These measurements were analyzed for agreement between the 100%, 70%, and 30% dose levels for each patient. Tolerances of 5° of glenoid version, 5° of glenoid inclination, and 10% humeral head subluxation were used as equivalent for preoperative planning. Automated measurements of 70% dose images were within 5° of version, 5° of inclination, and 10% subluxation in 95.0% of cases. Manual measurements of 70% RD images were within 5° of version for 90.0% of cases, 5° of inclination in 86.7% of cases, and 10% subluxation in 100% of cases. Automated measurements from the 30% dose images were within 5° of version, 5° of inclination, and 10% subluxation for 100% of cases. Manual measurements from the 30% dose images were within 5° of version for 86.7% of cases, 5° of inclination in 76.7% of cases, and 10% subluxation in 100% of cases. The mean absolute difference in software measurement of glenoid version (p = 0.96), glenoid inclination (p = 0.64), or humeral head subluxation (p = 0.09) or in aggregated manual mean absolute difference of version (p = 0.22), inclination (p = 0.31), or humeral head subluxation (p = 0.56) was not significant. Good to excellent reliability was determined by interclass correlation coefficients among the manual observers and automatic software platforms for measurements at all doses (P<0.001) CONCLUSIONS: The results indicate that both preoperative planning software platforms and human observers produced similar measurements of glenoid version, inclination, and humeral head subluxation from reduced-dose images compared to standard of care doses. By implementing reduced dose techniques in preoperative shoulder CT, the potential risks associated with radiation exposure could be reduced for patients undergoing shoulder arthroplasty.

LIBRARY MANAGEMENT SOFTWARE: A COMPARATIVE STUDY

This article will concentrate on library management software that provides either a web interface for some of its modules or a full web-based solution for all of its modules. Additionally, this article will investigate the evolution of such software, as well as its features and trends. A secondary purpose of this article is to assess library automation software by comparing and evaluating its features, services, and capacities. The findings of a survey that was carried out among software vendors in Delhi, India, are presented in this article. The survey was carried out with the intention of obtaining information on the features of the six software packages that were selected for this study. The information was acquired via the use of a questionnaire that was sent to the firms that supply software. The software industry provides a diverse range of programs, as can be seen in the previous observation. However, there are only a handful of them that function faultlessly on the web and provide access to all of the most recent technological specifications. The only software packages that are being investigated for this research are those that are available in Delhi. It is possible that library directors who are considering automating their libraries may find the comparison of library management software systems presented in this research to be helpful. This is because it will assist them in selecting and maintaining the program that is most suitable for their needs. There has not been a comprehensive examination of the web interfaces of library management software systems across the country of India.

Comparison of semi and fully automated artificial intelligence driven softwares and manual system for cephalometric analysis

BackgroundCephalometric analysis has been used as one of the main tools for orthodontic diagnosis and treatment planning. The analysis can be performed manually on acetate tracing sheets, digitally by manual selection of landmarks or by recently introduced Artificial Intelligence (AI)-driven tools or softwares that automatically detect landmarks and analyze them. The use of AI-driven tools is expected to avoid errors and make it less time consuming with effective evaluation and high reproducibility.ObjectiveTo conduct intra- and inter-group comparisons of the accuracy and reliability of cephalometric tracing and evaluation done manually and with AI-driven tools that is WebCeph and CephX softwares.MethodsDigital and manual tracing of lateral cephalometric radiographs of 54 patients was done. 18 cephalometric parameters were assessed on each radiograph by 3 methods, manual method and by using semi (WebCeph) and fully automatic softwares (Ceph X). Each parameter was assessed by two investigators using these three methods. SPSS was then used to assess the differences in values of cephalometric variables between investigators, between softwares, between human investigator means and software means. ICC and paired T test were used for intra-group comparisons while ANOVA and post-hoc were used for inter-group comparisons.ResultsTwelve out of eighteen variables had high intra-group correlation and significant ICC p-values, 5 variables had relatively lower values and only one variable (SNO) had significantly low ICC value. Fifteen out of eighteen variables had minimal detection error using fully-automatic method of cephalometric analysis. Only three variables had lowest detection error using semi-automatic method of cephalometric analysis. Inter-group comparison revealed significant difference between three methods for eight variables; Witts, NLA, SNGoGn, Y-Axis, Jaraback, SNO, MMA and McNamara to Point A.ConclusionThere is a lack of significant difference among manual, semiautomatic and fully automatic methods of cephalometric tracing and analysis in terms of the variables measured by these methods. The mean detection errors were the highest for manual analysis and lowest for fully automatic method. Hence the fully automatic AI software has the most reproducible and accurate results.

Dendritic Spine Quantification Using an Automatic Three-Dimensional Neuron Reconstruction Software.

Synaptic connections allow for the exchange and processing of information between neurons. The post-synaptic site of excitatory synapses is often formed on dendritic spines. Dendritic spines are structures of great interest in research centered around synaptic plasticity, neurodevelopment, and neurological and psychiatric disorders. Dendritic spines undergo structural modifications during their lifespan, with properties such as total spine number, dendritic spine size, and morphologically defined subtype altering in response to different processes. Delineating the molecular mechanisms regulating these structural alterations of dendritic spines relies on morphological measurement. This mandates accurate and reproducible dendritic spine analysis to provide experimental evidence. The present study outlines a detailed protocol for dendritic spine quantification and classification using Neurolucida 360 (automatic three-dimensional neuron reconstruction software). This protocol allows for the determination of key dendritic spine properties such as total spine density, spine head volume, and classification into spine subtypes thus enabling effective analysis of dendritic spine structural phenotypes.

Energy Aware Technology Mapping of Genetic Logic Circuits.

Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers -as caused by the additional burden of artificial genetic circuits- shifts a cell's priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state (NESS) model of gene expression, capturing characteristics like energy dissipation -which we link to the entropy production rate- and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit's functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energy efficiency of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.

An Automatic Software Defect Repair Method Based on Multi-Objective Genetic Programming

Due to the explosive growth of software quantity and the mixed ability of software developers, a large number of software defects emerge during the later stages of software maintenance. The search method based on genetic programming is one of the most popular in search algorithms, but it also has some issues. The single-objective approach to validate and select offspring patches without considering other constraints can affect the efficiency of patch generation. To address this issue, this paper proposes an automatic software repair method based on Multi-objective Genetic Programming (MGPRepair). Firstly, the method adopts a lightweight context analysis strategy to find suitable repair materials. Secondly, it decouples the replacement statements and insertion statements in the repair materials, using a lower-granularity patch representation method to encode the patches in the search space. Then, the automatic software defect repair is treated as a multi-objective search problem, and the NSGA-II multi-objective optimization algorithm is used to find simpler repair patches. Finally, the test case filtering technique is used to accelerate the patch validation process and generate correct patches. MGPRepair was experimentally evaluated on 395 real Java software defects from the Defects4J dataset. The experimental results show that MGPRepair can generate test case-passing patches for 51 defects, of which 35 defect patches are equivalent to manually generated patches. Its repair the efficiency and success rate are higher to other excellent automatic software defect repair methods such as jGenProg, RSRepair, ARJA, Nopol, Capgen, and SequenceR.

IFC CLASS ASSIGNMENT ADD-ON: BIM MODELLING FOR ARCHITECTURAL AND ENGINEERING PROJECTS USING BLENDER

Building Information Modelling (BIM) is a working methodology for the design and management of construction projects that facilitates collaboration and communication between the different parties involved. It is based on the digital three-dimensional representation of infrastructures within the field of architecture and civil engineering. The generated models are true data containers, capable of storing the geometric and semantic information necessary to support the design, construction and maintenance operations of the assets. This methodology promotes data exchange between different software tools through interoperability and the use of standards. Usually in the development of projects throughout their life cycle, commercial, closed-source BIM software is used. This generally leads to limitations in interoperability and data reuse. This paper details advances in the use of Blender, a free and open-source software (FOSS), to support BIM workflows in construction projects. The paper addresses the automation of the process to export a 3D Blender model to a BIM model in IFC (Industry Foundation Classes). The IFC Class Assignment add-on is developed, which allows the automated assignment of IFC classes to the different elements of the 3D model in Blender to convert it into a BIM model, using scripts written in Python. The proposed extension is able to generate, in an agile and simple way, digital models in IFC4, adequately storing the geometric and semantic information of its components. The results provide a tool that contributes to automate the creation of BIM models in an open-source software such as Blender, simplifying modelling processes and supporting collaboration and standardisation in architectural and engineering projects. Keywords: BIM, IFC, Automation, Free and Open-Source Software, Blender, Python.

The role of software automation in improving industrial operations and efficiency

The role of software automation in improving industrial operations and efficiency

Newgenlib: A Review of the Next Generation of Open Source Library Automation Software, First Year College of Government Naragal

Newgenlib: A Review of the Next Generation of Open Source Library Automation Software, First Year College of Government Naragal