Comparative quantification of focal and diffuse visual field loss by the SPARK Precision threshold algorithm and SITA

Purpose The aims of this paper were to examine focal and diffuse visual field loss in terms of threshold agreement between the widely used SITA Standard Humphrey Field Analyser (HFA) threshold algorithm with the SPARK Precision algorithm (Oculus Twinfield 2). Methods A total of 39 treated glaucoma patients (34 primary open angle and 5 primary angle closure glaucoma) and 31 cataract patients without glaucoma were tested in succession with the Oculus Twinfield 2 (Oculus Optikgeräte GmbH, Wetzlar, Germany) using the SPARK Precision algorithm and with the HFA 3 (Carl Zeiss Meditec, Dublin, CA) using the 30–2 SITA Standard algorithm. Results SPARK Precision required around half the testing time of SITA Standard. There was a good correlation between the MS of the two threshold algorithms but MD and PSD were significantly less severe with SPARK Precision in both glaucoma (focal field loss) and cataract (diffuse field loss) groups (p < 0.001). There was poor agreement for all global indices (MS, MD and PSD) between the two algorithms and there was a significant proportional bias of MD in the glaucoma group and PSD in both glaucoma and cataract groups. The pointwise sensitivity analysis yielded higher threshold estimates in SPARK Precision than in SITA Standard in the nasal field. Classification of glaucoma severity using AGIS was significantly lower with SPARK Precision compared to SITA Standard (p < 0.001). Conclusion SITA renders deeper defects than SPARK. Compared to the SITA Standard threshold algorithm, SPARK Precision cannot quantify early glaucomatous field loss. This may be due to the mathematical linear interpolation of threshold sensitivity or deeper scotomas due to the plateau effect caused by the reduced dynamic range of the Twinfield 2 perimeter. Although not of clinical significance in early glaucoma, the plateau effect may hinder the long-term follow-up of patients during disease progression.

Global analysis of crystal energy landscapes: applying the threshold algorithm to molecular crystal structures

We describe the implementation of the Monte Carlo threshold algorithm for molecular crystals as a method to provide an estimate of the energy barriers separating crystal structures. By sampling the local energy minima accessible from multiple starting structures, the simulations yield a global picture of the crystal energy landscapes. This provides valuable information on the depth of the energy minima associated with crystal structures and adds to the information available from crystal structure prediction methods that are used for anticipating polymorphism. We present results from applying the threshold algorithm to four polymorphic organic molecular crystals, examine the influence of applying space group symmetry constraints during the simulations, and discuss the relationship between the structure of the energy landscape and the intermolecular interactions present in the crystals.

Development of upholstery electro-fabric for smart textile applications

Smart textile products developed by evaluating the human body’s data through sensors have become widespread in recent years. The majority of these products include textile-based information and communication technologies that integrate electronic components into clothing. People use seats, chairs, armchairs, etc., to sit constantly in vehicles, work or at home. The use of these items varies according to the requirements and purposes. In this study, an electro-textile-based upholstery fabric design was carried out to be used in sitting furniture. Electronic components containing capacitive sensors were placed in the designed fabric structure to make it usable in different areas where upholstery fabrics are used. In addition, the sensor connection circuit was developed to receive data from the fabric surface. The data taken from the fabric surface were made meaningful using the calibration and normalization algorithm. The 3D pressing map of the reaction on the fabric surface for different sitting positions was drawn. Electromagnetic field and vibration tests were carried out to examine the response behaviour in different environments where the fabric can be used. According to the findings, it was observed that the pressing areas formed on the surface were displayed in a significant way over the 3D pressing map, and the system was not affected by the electromagnetic field and vibrations. Besides, the fabric was applied on the various surfaces to test calibration and threshold algorithm. Obtained results and circumstances showed that the designed calibration and threshold algorithm were successful to obtained significant results. As a result of the study, upholstery electro fabric with a response time of 0.01 seconds in data collection was developed, which can be used in different environments such as home, workplace and vehicle. It can be used over furniture and in wet and dry conditions and is not affected by the electromagnetic field and vibration in the environment.

Research on Sheepskin Contour Extraction Method Based on Computer Vision Measurement Technology

Manual trimming of sheepskin is intensive labor, and the working environment is full of rotten smells. The tannery is facing increasingly severe recruitment difficulties. This paper uses computer vision technology to study automatic recognition of sheepskin contours, which is the basis for the subsequent automatic trimming of sheepskin. After observing and analyzing the raw sheepskin images collected by an industrial array camera, a method of sheepskin contour extraction based on computer vision measurement technology is proposed in this paper. This method uses the fast Otsu threshold algorithm based on the pixel set to perform binary image segmentation. Combined with morphological processing for edge defect filling and topology analysis of boundary contour tracking algorithm to extract maximum contour information, it has a pixel-level three-dimensional de-noising preprocessing function and can accurately extract the sheepskin contour in the raw sheepskin image. The experimental results show that using the fast Otsu threshold algorithm proposed in this paper for binary segmentation to extract sheepskin contours, the detection rate is nearly 160% faster than the traditional Otsu algorithm, the edge protection is better, the error segmentation is reduced by nearly 3% and it has good anti-noise performance. It can meet the industrial production requirements of subsequent automatic cutting of sheepskin.

Accident Detection and Safety System - (AUTO AID APP)

Nowadays we are able to track vehicles using many applications which help in securing personal vehicles, public vehicles, feet units and others. Furthermore there is a rapid increase in the occurrence of the Road accident. This project is about a system which is developed to automatically detect an accident and alert the nearest hospitals and medical services about it. This system can also locate the place of the accident so that the medical services can be directed immediately towards it. The goal of this paper is to build up a Vehicle accidental monitoring system using MEMS, GPS and GSM Technology. The system comprises of accelerometer, MCU, GPS & GSM Module support in sending message. The accelerometer is used to detect fall and Threshold Algorithm are used to detect accident. Short Message will contain GPS [Latitude, Longitude] which helps in locating the vehicles.