A Deep Learning Based Approach to Recognizing Accompanying Status of Smartphone Users Using Multimodal Data (스마트폰 다종 데이터를 활용한 딥러닝 기반의 사용자 동행 상태 인식)
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- Journal of Intelligence and Information Systems
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- v.25 no.1
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- pp.163-177
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- 2019
As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.
The purpose of this study is to compare and analyze the effect of changes in the patient's central position on the exposure dose and image quality of surrounding organs during a chest lateral examination using an Auto Exposure Control(AEC). The experiment was conducted on a human body phantom. A needle was attached to the lower part of the center of the coronal plane of the phantom, and a lead ruler was attached to the lower part of the detector so that the 50 cm point was located at the lower center of the AEC ion chamber. The exposure conditions were 125 kVp, 320 mA, the distance between the source and the image receptor was 180 cm, and the exposure field size was 14 × 17 inches. Only one AEC ion chamber was used at the bottom center, and the density was set to '0' and sensitivity to 'Middle', and the central X-ray was incident vertically toward the 6th thoracic vertebra. With AEC mode applied, the 50 cm point of the needle and lead ruler were aligned and the phantom was moved 5 cm toward the stomach (F5) and 5 cm toward the back (B5), and the dose factor was analyzed by measuring ESD. The ESD of the thyroid gland according to the change in patient center position was 232.60±2.20 μGy for Center, 231.22±1.53 μGy for F5, and 184.37±1.19 μGy for B5, and the ESD of the breast was 288.54±3.03 μGy for Center, F5 was 260.97±1.93 μGy, B5 was 229.80±1.62 μGy, and the ESD of the center of the lung was 337.02±3.25 μGy for Center, F5 was 336.09±2.29 μGy, and B5 was 261.76±1.68 μGy. As a result of comparing the average values of dose factors between each group, the difference in average values was statistically significant (p<0.01), and each group appeared to be independent. As a result of the study, there was no significant difference in the dose to the thyroid, breast, and center of the lung according to the change in the patient's central position, except for the breast (10%) when the patient moved forward about 5 cm. However, movement of about 5 cm posteriorly resulted in an average dose reduction of 23.7%. Additionally, when the patient's central position was moved to the rear, image quality deteriorated.
This survey was conducted in order to obtain the basic data for desirable consumption habits through investigation and analysis of university students' fast food consumption behaviors. Questionnaires were collected from a total of 374 male and female students living in big or small and medium-sized cities in August, 2004. The contents surveyed were utilization and expenses of fast foods, choice of fast foods, relationship between fast foods and a diet, and characteristics of fast food restaurants. The results obtained are summarized as follows: 1. The ratio of the surveyees varied according to gender, residence, and the size of a city they're living in. For example, males took up 48.66% of the surveyees, while females did 51.34%. The ratio of residents in apartments and stand-alone houses was 54.81% and 45.19% each. 47.33% of the respondents were living in big cities, while 52.67% of them in small and medium-sized cities. 2. 70.1% of the surveyees responded that they are with friends when having fast foods. There was a highly significant difference between male and female in the type of eating companions (p<0.001). The average number of days that they eat fast foods was 1 to 2 times a week, which accounted for 63.7% of the respondents. However, in the case of eating foods, there was no significant differences between two sexes. 3. 64.2% of the surveyees paid more than 20,000 won to buy fast foods for a week, which showed no significant differences between genders. They tend to split a bill, rather than one person pays all. There was a highly significant difference between genders in paying method (p<0.001). 4. 52.1 % of the respondents chose a menu themselves. Their most favored food was chickens (26.5%), which showed a statistically significant difference between genders (p<0.001). 46.8% of them preferred coke as a drink, which had no significant difference between genders. 42.2% of the surveyees had fast foods between lunch and dinner, which also had no significant difference between genders. The most important factor in choosing a menu was its taste (62.8%), which indicated a significant difference between males and females (p<0.05). 5. The preference to fast foods was due to the influence of western culture (36.4%) and eating-out habits (29.1%), which was significantly different between genders (p<0.05). Those who eat fast foods answered they have normal weight and normal body type (49.5%). 24.3% of them were relatively fat with significant difference between genders (p<0.05). 63.4% of the surveyees thought themselves not picky with foods, and there was a significant difference between genders (p<0.05). 78.3% of them mostly preferred franchise restaurants because they are convenient and cheap.
Dedicated single-photon emission computed tomography (SPECT) systems based on pixelated semiconductors are being developed for studying small animal models of human disease. To clarify the possibility of using a SPECT system with CdTe for a high resolution low-dose small animal imaging, we compared the quality of reconstructed images from pixelated CdTe detector to those from a small SPECT system with NaI(Tl). The CdTe detector was
To investigate the utilization of calcium lactates (CaL) as coagulants for tofu manufacture, the quality characteristics and shelf-life of tofu made by CaL-P (black snail powder) and CaL-A (black snail ash) were investigated and compared to calcium chloride (CC), magnesium chloride (MC), calcium sulfate (CS ) and standard calcium lactate (CaL-S). And also, total microbe and turbidity of the tofu were determined during storage at 1
In this study, the dose distributions of a
Due to the development of industry, interest in air pollutants has increased. Air pollutants have affected various fields such as environmental pollution and global warming. Among them, environmental diseases are one of the fields affected by air pollutants. Air pollutants can affect the human body's skin or respiratory tract due to their small molecular size. As a result, various studies on air pollutants and environmental diseases have been conducted. Asthma, part of an environmental disease, can be life-threatening if symptoms worsen and cause asthma attacks, and in the case of adult asthma, it is difficult to cure once it occurs. Factors that worsen asthma include particulate matter and air pollution. Asthma is an increasing prevalence worldwide. In this paper, we study how air pollutants correlate with the number of emergency room admissions in asthma patients and predict the number of future asthma emergency patients using highly correlated air pollutants. Air pollutants used concentrations of five pollutants: sulfur dioxide(SO2), carbon monoxide(CO), ozone(O3), nitrogen dioxide(NO2), and fine dust(PM10), and environmental diseases used data on the number of hospitalizations of asthma patients in the emergency room. Data on the number of emergency patients of air pollutants and asthma were used for a total of 5 years from January 1, 2013 to December 31, 2017. The model made predictions using two models, Informer and LTSF-Linear, and performance indicators of MAE, MAPE, and RMSE were used to measure the performance of the model. The results were compared by making predictions for both cases including and not including the number of emergency patients. This paper presents air pollutants that improve the model's performance in predicting the number of asthma emergency patients using Informer and LTSF-Linear models.
Tooth implant is located in oral cavity and affects neck, skull base, and facail image. These magnetic inhomogeneities are usually frequency encoding direction which cause artifacts due to change of signal strength and geometric distortion. First, to evaluate signal to noise ratio (SNR) of magnetic resonance image caused by tooth implant this study uses meat phantom which is similar to human body and is consisted with fat, muscle, and water to measure signal to noise ratio. Second, signal to noise ratio by using custom-made fixed phantom is measured, and then signal to noise ratio size of different tooth implant types is compared and analyzed. The measured signal to noise ratio values of Brushite, HSA, Metal, and RBM for meat phantom were 2.76, 2.22, 1.88, and 1.57 on T1 SE, 1.88, 1.78, 1.65, and 1.79 on T2 FLAIR, 2.28, 2.25, 2.88, and 2.05 on T2 FSE, and 2.74, 1.94, 1.67, and 1.48 on T2 GRE. The measured signal to noise ratio values of Brushite, HSA, Metal, and RBM for fixed water phantom were 1.2, 1.06, 1.12, and 1.22 on DWI, 1.93, 1.87, 1.93, and 2.06 T1 SE, 1.83, 1.76, 1.82, and 1.92 on T2 FLAIR, 1.85, 1.79, 7.86, and 1.97 on T2 FSE, and 1.97, 1.93, 1.99, and 2.06 on T2 GRE. By considering through the results, patients and dentists need to consider some impacts from testing many aspects although their main purpose of having tooth implants is a dental restoration. Moreover, depending on the tooth implant characteristics of individual patients this study results can be used as baseline data when choosing test protocol.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70