Effect of Light-Emitting Grid Panel on Indoor Aquaculture for Measuring Fish Growth.

This study is related to Smart Aqua Farm, which combines artificial intelligence (AI) and Internet of things (IoT) technology. This study aimed to monitor fish growth in indoor aquaculture while automatically measuring the average size and area in real time. Automatic fish size measurement technology is one of the essential elements for unmanned aquaculture. Under the condition of labor shortage, operators have much fatigue because they use a primitive method that samples the size and weight of fish just before fish shipment and measures them directly by humans. When this kind of process is automated, the operator's fatigue can be significantly reduced. Above all, after measuring the fish growth, predicting the final fish shipment date is possible by estimating how much feed and time are required until the fish becomes the desired size. In this study, a video camera and a developed light-emitting grid panel were installed in indoor aquaculture to acquire images of fish, and the size measurement of a mock-up fish was implemented using the proposed method.

Detection of Abnormal Changes on the Dorsal Tongue Surface Using Deep Learning.

Background and Objective: The tongue mucosa often changes due to various local and systemic diseases or conditions. This study aimed to investigate whether deep learning can help detect abnormal regions on the dorsal tongue surface in patients and healthy adults. Materials and Methods: The study collected 175 clinical photographic images of the dorsal tongue surface, which were divided into 7782 cropped images classified into normal, abnormal, and non-tongue regions and trained using the VGG16 deep learning model. The 80 photographic images of the entire dorsal tongue surface were used for the segmentation of abnormal regions using point mapping segmentation. Results: The F1-scores of the abnormal and normal classes were 0.960 (precision: 0.935, recall: 0.986) and 0.968 (precision: 0.987, recall: 0.950), respectively, in the prediction of the VGG16 model. As a result of evaluation using point mapping segmentation, the average F1-scores were 0.727 (precision: 0.717, recall: 0.737) and 0.645 (precision: 0.650, recall: 0.641), the average intersection of union was 0.695 and 0.590, and the average precision was 0.940 and 0.890, respectively, for abnormal and normal classes. Conclusions: The deep learning algorithm used in this study can accurately determine abnormal areas on the dorsal tongue surface, which can assist in diagnosing specific diseases or conditions of the tongue mucosa.

Distance Error Correction in Time-of-Flight Cameras Using Asynchronous Integration Time.

A distance map captured using a time-of-flight (ToF) depth sensor has fundamental problems, such as ambiguous depth information in shiny or dark surfaces, optical noise, and mismatched boundaries. Severe depth errors exist in shiny and dark surfaces owing to excess reflection and excess absorption of light, respectively. Dealing with this problem has been a challenge due to the inherent hardware limitations of ToF, which measures the distance using the number of reflected photons. This study proposes a distance error correction method using three ToF sensors, set to different integration times to address the ambiguity in depth information. First, the three ToF depth sensors are installed horizontally at different integration times to capture distance maps at different integration times. Given the amplitude maps and error regions are estimated based on the amount of light, the estimated error regions are refined by exploiting the accurate depth information from the neighboring depth sensors that use different integration times. Moreover, we propose a new optical noise reduction filter that considers the distribution of the depth information biased toward one side. Experimental results verified that the proposed method overcomes the drawbacks of ToF cameras and provides enhanced distance maps.

Measurement of Respiration Rate and Depth Through Difference in Temperature Between Skin Surface and Nostril by Using Thermal Image.

The purpose of the present study was to propose a method to measure a respiration rate (RR) and depth at once through difference in temperature between the skin surface and nostril by using a thermal image. Although there have been a lot of devices for contact RR monitoring, it was considered that the subjects could be inconvenienced by having the sensing device in contact with their body. Our algorithm enabled us to make a breathing periodic function (BPF) under the non-contact and non-invasive condition through temperature differences near the nostril during the breath. As a result, it was proved that our proposed method was able to classify differences in breathing pattern between normal, deep, and shallow breath (P < 0.001). These results lead us to conclude that the RR and depth is simultaneously measured by the proposed algorithm of BPF without any contact or invasive procedure.

Analysis of Difference in Center-of-Pressure Positions Between Experts and Novices During Asymmetric Lifting.

Although numerous studies have analyzed the relationship between manual material handling (MMH) and the forces acting on the lumbar spine, the difference in the MMH between experts and novices through the analysis of measured data has not been well studied. The purpose of this paper was to analyze the difference in the MMH positions between ten skilled experts working at a freight transport company (Group 1) and five unskilled novices without any experience (Group 2) during asymmetric lifting. All the human subjects performed asymmetric lifting experiments with closed eyes; the experiments involved moving loads (6 and 18 kg) to the left side. Time series data of the vertical ground reaction force were measured, using a Wii Balance Board, and then, the center-of-pressure (CoP) trajectories were calculated. The balance board was used for the measurement, because it was reliable, inexpensive, and portable and provided good repeatability even on rough surfaces, and all the information pertaining to the load and worker under various conditions was captured without any omissions. Under the 18 kg load condition, the CoP positions for Group 2 were located on the same side during left asymmetric lifting; however, those for Group 1 were located on the opposite side during left asymmetric lifting ([Formula: see text]). Furthermore, under the 6 kg load condition, the load weight influenced asymmetric lifting for most subjects of Group 2 such that the CoP positions were located on the opposite side ([Formula: see text]). Based on the simulation and electromyography measurement results, we inferred that the difference in the CoP positions between the two different groups could be attributed to the difference in the hip positions. Most skilled experts position their hips in such a way that their CoP trajectories move toward the opposite side during left asymmetric lifting. Although the skillful characteristics of experts may be responsible for the lightening of the burden on the waist during asymmetric lifting, there are still two points that this paper does not clarify: the relationship between the experts' adjustment of the hip position and the load of the weight, and the influence of an imbalance of the CoP position on the forces acting on the lumbar spine.

Improvement of touch sensitivity by pressing.

It is really interesting to know how a blood flow has an influence on a touch sensitivity during human fingertip exploration over an environment. In this paper, we examine experimentally how the touch sensitivity is changed under the condition that the blood flow is interrupted compulsorily by pressing the proximal phalange of human finger. Through the weight discrimination test based on Weber's Law, we found that the touch sensitivity improves temporarily with the statistical significance test of below 0.1 %, when a finger proximal phalange is bound and pressed. Experimental results also show that there exists a meaningful correlationship between the stiffness of fingertip and the touch sensitivity.