Technology options to help people with dementia or acquired cognitive impairment perform multistep daily tasks: a scoping review

Purpose The purpose of this paper is to review studies that evaluated technology-based prompting systems for supporting participants with dementia or acquired cognitive impairment in their performance of multistep daily tasks. Design/methodology/approach A scoping review was conducted to identify eligible studies through a search of four electronic databases, that is, PubMed, PsycINFO, Web of Science and Institute of Electrical and Electronics Engineers. Findings The search, which covered the 2010–2020 period, led to the identification of 1,311 articles, 30 of which were included in the review. These articles evaluated six different types of prompting systems: context-aware, automatic computer prompting, context-aware, mediated computer prompting, teleoperated robot prompting, self-operated augmented reality prompting, self-operated computer or tablet prompting and time-based (preset) computer, tablet or smartphone prompting. Originality/value Technology-aided prompting to help people with dementia or acquired cognitive impairment perform relevant multistep daily tasks is considered increasingly important. This review provides a picture of the different prompting options available and of their level of readiness for application in daily contexts.

METHOD OF COMPUTER CONTROL OF TWISTED THREAD PARAMETERS FROM ITS IMAGE

A non-hardware method for computer control of the geometric parameters of a twisted thread using a two-dimensional Fourier transform program of its computer image is proposed. First, the program calculates the diffraction pattern from the investigated image of the thread. Then, the same program builds a diffraction pattern from the image of the first pattern, which does not contain speckles in the proposed method. This makes it possible to carry out its automatic computer analysis with the output to the digital values ​​of the calculated parameters. The effectiveness of the method is illustrated on model and industrial samples of synthetic threads.

Improving skeleton algorithm for helping Caenorhabditis elegans trackers

One of the main problems when monitoring Caenorhabditis elegans nematodes (C. elegans) is tracking their poses by automatic computer vision systems. This is a challenge given the marked flexibility that their bodies present and the different poses that can be performed during their behaviour individually, which become even more complicated when worms aggregate with others while moving. This work proposes a simple solution by combining some computer vision techniques to help to determine certain worm poses and to identify each one during aggregation or in coiled shapes. This new method is based on the distance transformation function to obtain better worm skeletons. Experiments were performed with 205 plates, each with 10, 15, 30, 60 or 100 worms, which totals 100,000 worm poses approximately. A comparison of the proposed method was made to a classic skeletonisation method to find that 2196 problematic poses had improved by between 22% and 1% on average in the pose predictions of each worm.

How to Fix Coordination Lags in the Keynesian Macroeconomical Intervention?

The Keynesian macroecomic intervention often fails. This is most likely due to forecasting problems of the macroeconomy. This article present a software idea of fuzzy logic controlling unit which replaces long and tedious human intervention in macroeconomic stimulation process. The Keynesian Macroeconomic intervention now made by officials and politicians is suggested to be made by much faster and more purposeful automatic computer adjustment process. It is assumed that this kind of just in time and very fast automatic computer intervention would lead to optimimal usage of the resources in a much better way than any current human lead systems would be able to do.

Diagnostic performance of artificial intelligence to identify deeply invasive colorectal cancer on non-magnified plain endoscopic images

Background and study aims Colorectal cancers (CRC) with deep submucosal invasion (T1b) could be metastatic lesions. However, endoscopic images of T1b CRC resemble those of mucosal CRCs (Tis) or with superficial invasion (T1a). The aim of this study was to develop an automatic computer-aided diagnosis (CAD) system to identify T1b CRC based on plain endoscopic images. Patients and methods In two hospitals, 1839 non-magnified plain endoscopic images from 313 CRCs (Tis 134, T1a 46, T1b 56, beyond T1b 37) with sessile morphology were extracted for training. A CAD system was trained with the data augmented by rotation, saturation, resizing and exposure adjustment. Diagnostic performance was assessed using another dataset including 44 CRCs (Tis 23, T1b 21) from a third hospital. CAD generated a probability level for T1b diagnosis for each image, and > 95 % of probability level was defined as T1b. Lesions with at least one image with a probability level > 0.95 were regarded as T1b. Primary outcome is specificity. Six physicians separately read the same testing dataset. Results Specificity was 87 % (95 % confidence interval: 66–97) for CAD, 100 % (85–100) for Expert 1, 96 % (78–100) for Expert 2, 61 % (39–80) for both gastroenterology trainees, 48 % (27–69) for Novice 1 and 22 % (7–44) for Novice 2. Significant differences were observed between CAD and both novices (P = 0.013, P = 0.0003). Other diagnostic values of CAD were slightly lower than of the two experts. Conclusions Specificity of CAD was superior to novices and possibly to gastroenterology trainees but slightly inferior to experts.