A Survey for Ascertaining Details Related to Falls on Stairs or Escalators

Introduction: The Australian Institute of Health and Welfare, publication titled; ‘Injury in Australia: falls’ states that in 2017–18, 42% of hospitalized injury cases were due to falls, and 40% of injury deaths were due to falls. In Melbourne City, at various stations, there are extremely long escalators, and alarmingly, one sign previously displayed states there are approximately 2-3 falls/ week on train station escalators.Objectives: The aim of the survey was to ascertain the percentage of people who’ve fallen downstairs and escalators.Methods: Distribution of a general convenience survey [n=125] was performed to ascertain the percentage of people who’ve fallen downstairs and escalators. Additional questions related to rain, high-risk footwear, poor lighting, and how many falls they have had. Following that, regardless of whether or not they’d had a fall, questions then focused on whether they had a fear of falling and whether they felt uncomfortable around crowds on stairs or escalators.Results and Discussion: Completed survey forms were eighty-two in total. 29% of people had fallen, with 16% of those people indicating rain, 16% in either high heels or thongs, while 25% indicated poor visibility. Of those who had fallen, the estimate of the number of falls down stairs or escalators ranged from 1–20, with the average being three falls. 39% of respondents, irrespective of whether or not they had fallen, had fear, while 43% felt uncomfortable around crowds.Conclusion: Falls downstairs or escalators are relatively common, in addition to a large percentage of people having fear or feeling uncomfortable.

On Implementation of Plants in the Indoor Environment in Intelligent Buildings

The article deals with the research of the influence of plants on the potential energy savings in the field of ventilation of intelligent buildings. It is known that selected plants can effectively reduce the concentration of carbon dioxide even in the indoor environment of buildings in poor lighting conditions. The paper presents a theoretical simulation method that shows the potential of selected plants to reduce the concentration of carbon dioxide in the indoor environment and thus reduce the requirement for the amount of supplied air in intelligent buildings which are air-conditioned based on the current and required concentration of carbon dioxide. The results of the research are very influential; in terms of overall percentage savings, plants have the most significant effect in buildings with lower indoor air quality (IDA4+), while they have a less significant effect in areas with high air quality according to carbon dioxide concentration (IDA2, IDA3). Research with the help of computer simulation shows that the implementation of 1 m2 of living green plants, depending on the quality class of the IDA indoor environment, can bring savings on the amount of supplied air in the range of 0.058 % to 1.997 % for a typical office for 4 people.

The geometric attention-aware network for lane detection in complex road scenes

Lane detection in complex road scenes is still a challenging task due to poor lighting conditions, interference of irrelevant road markings or signs, etc. To solve the problem of lane detection in the various complex road scenes, we proposed a geometric attention-aware network (GAAN) for lane detection. The proposed GAAN adopted a multi-task branch architecture, and used the attention information propagation (AIP) module to perform communication between branches, then the geometric attention-aware (GAA) module was used to complete feature fusion. In order to verify the lane detection effect of the proposed model in this paper, the experiments were conducted on the CULane dataset, TuSimple dataset, and BDD100K dataset. The experimental results show that our method performs well compared with the current excellent lane line detection networks.

Industrial Protection System using Arduino and IoT

The Industrial protection system designed using Arduino and IOT mainly focuses on the protection of industries from various losses occurring due to accidents caused due to improper conditions and maintenance. Gas leaks can cause fires that cause huge industrial losses; Instant fire detection is also required in the event of a furnace explosion or other conditions. Additionally, poor lighting in industries can create unsuitable working conditions, increasing the likelihood of accidents. The system uses Arduino to achieve this functionality. The system uses temperature sensors in combination with gas light sensors to detect fires, gas leaks, and low light to prevent industrial accidents and avoid leaks. These setups also work as an anti-theft security system where it utilizes the IR sensor to detect the objects coming in its path. So this IR sensor works with the help of direct incidence of radiation on the photodiode. This IR LED which is placed on one side of the board and the photodiode is placed on the other helps to detect any obstacle or object which comes closer to contact with it. This object detection is indicated with the help of an alarm to notify us. The system consists of light, gas, and temperature sensors interconnected with Arduino and LCD screens. Sensor data is constantly scanned to record values and check for fire, gas leaks, or poor lighting, and then this data is transmitted online. The Wi-fi module is used to achieve internet functionality. The Blynk server then displays this information online, to achieve the desired result.

Perilaku Pengendalian Bahaya Kecelakaan Kerja di Rumah Tangga Pada Masyarakat Kota Samarinda

The potential hazards and risks in the household are many hazards from physical, chemical, biological and psychological factors. This study aims to explain the hazards of work in households. This study used a descriptive qualitative design with 7 family heads selected as informants. Information collection was carried out in November 2020 in Teluk Lerong Ulu Village, Samarinda City. Interviews and indepth interviews using qualitative interviews and data analysis. The results of the research show that the dangers and risks of work accidents that can cause hospital occupants and eye health problems due to poor lighting, burns, scratches or injuries due to sharp objects, being pinched, crushed and crushed by falling objects. Resident health complaints such as allergic itching and skin diseases, respiratory problems, and complaints of Musculoskeletal Disorder. If not managed properly, these hazards and risks can lead to prolonged health complaints and serious accidents. Therefore, efforts to deal with hazards and risks appropriately are defeated by the daily activities of residents of the household.

UAV Photogrammetry under Poor Lighting Conditions—Accuracy Considerations

The use of low-level photogrammetry is very broad, and studies in this field are conducted in many aspects. Most research and applications are based on image data acquired during the day, which seems natural and obvious. However, the authors of this paper draw attention to the potential and possible use of UAV photogrammetry during the darker time of the day. The potential of night-time images has not been yet widely recognized, since correct scenery lighting or lack of scenery light sources is an obvious issue. The authors have developed typical day- and night-time photogrammetric models. They have also presented an extensive analysis of the geometry, indicated which process element had the greatest impact on degrading night-time photogrammetric product, as well as which measurable factor directly correlated with image accuracy. The reduction in geometry during night-time tests was greatly impacted by the non-uniform distribution of GCPs within the study area. The calibration of non-metric cameras is sensitive to poor lighting conditions, which leads to the generation of a higher determination error for each intrinsic orientation and distortion parameter. As evidenced, uniformly illuminated photos can be used to construct a model with lower reprojection error, and each tie point exhibits greater precision. Furthermore, they have evaluated whether commercial photogrammetric software enabled reaching acceptable image quality and whether the digital camera type impacted interpretative quality. The research paper is concluded with an extended discussion, conclusions, and recommendation on night-time studies.

A New Ball Detection Strategy for Enhancing the Performance of Ball Bees Based on Fuzzy Inference Engine

Sports video analysis has received much attention as it is turned to be a hot research area in the field of image processing. This led to opportunities to develop fascinating applications supported by analysis of different sports especially football. Identifying the ball in soccer images is an essential task for not only goal scoring but also players’ evaluation. However, soccer ball detection suffers from several hurdles such as; occlusions, fast moving objects, shadows, poor lighting, color contrast, and other static background objects. Although several ball detection techniques have been introduced such as; Frame Difference, Mixture of Gaussian (MoG), Optical Flow and etc., ball detection in soccer games is still an open research area. In this paper, a new Fuzzy Based Ball Detection (FB2D) strategy is proposed for identifying the ball through a set of image sequences extracted form a soccer match video. FB2D has the ability to accurately identify the ball even if it is attached to the white lines drawn on the playground or partially occluded behind players. FB2D has been compared to recent ball detection techniques. Experimental results have shown that FB2D outperforms recent detection techniques as it introduced the maximum accuracy and the accuracy of detection in the testing stage is close to 100%. As well as the minimum error.

Image Pixel Contrast Enhancement Using Enhanced Multi Histogram Equalization Method

Image Enhancement methods produce various sorts of problems, for example, unnatural impacts, over-improvement, and these downsides become increasingly unmistakable in improving dull Images. Histogram Equalization (HE) method is a straightforward and generally utilized Image contrast enhancement procedure. The fundamental task of HE is it changes the contrast of the Image. To perform this task, different HE techniques have been proposed. These techniques protect the brightness or contrast on the final Image that doesn't have a characteristic look. To overcome the drawbacks of HE, Enhanced Multi Histogram Equalization (EMHE) technique is proposed, which divide the Image into a few sub images and again these sub images are divided into sub-images, and traditional HE strategy is applied to each sub Image for getting better results. The improvement is brought about by repetitive data present in sub-pixel moves between relating Lightroom (LR) Images of a similar scene. The principal phase of the development incorporates Image enrollment of LR Images utilizing known parameters and geo-referencing methods for manufactured and genuine information individually. The proposed development of M-HE Images has been assessed on the LR Images obtained from satellite Image datasets to exhibit the clarity of the images by enhancing the contrast on the poor lighting images.

Peritonsillar abscess drainage: using oropharyngeal endoscopy as a therapeutic adjunct and training tool

BackgroundPeritonsillar abscess, or quinsy, is one of the most common emergency presentations to ENT departments, and is the most common deep tissue infection of the head and neck. In the UK, junior members of the ENT team are regularly required to independently assess, diagnose and treat patients with peritonsillar aspiration or incision and drainage.IssueInexperienced practitioners can stumble at several obstacles: poor access due to trismus; poor lighting; difficulty in learning the therapeutic procedure; and difficulty in accurately documenting findings and treatment.SolutionTo counter these and other difficulties, the authors describe the routine use of video endoscopy as a training tool and therapeutic adjunct in the management of quinsy.