• Tuberculosis and Respiratory Diseases
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• v.43 no.3
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• pp.367-376
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• 1996

Background : The diagnosis of emphysema during life is based on a combination of clinical, functional, and radiographic findings, but this combination is relatively insensitive and nonspecific. The development of rapid, high-resolution third and fourth generation CT scanners has enabled us to resolve pulmonary parenchymal abnormalities with great precision. We compared the chest HRCT findings to the pulmonary function test and arterial blood gas analysis in pulmonary emphysema patients to test the ability of HRCT to quantify the degree of pulmonary emphysema. Methods : From october 1994 to october 1995, the study group consisted of 20 subjects in whom HRCT of the thorax and pulmonary function studies had been obtained at St. Mary's hospital. The analysis was from scans at preselected anatomic levels and incorporated both lungs. On each HRCT slice the lung parenchyma was assessed for two aspects of emphysema: severity and extent. The five levels were graded and scored separately for the left and right lung giving a total of 10 lung fields. A combination of severity and extent gave the degree of emphysema. We compared the HRCT quantitation of emphysema, pulmonary function tests, ABGA, CBC, and patients characteristics(age, sex, height, weight, smoking amounts etc.) in 20 patients. Results : 1) There was a significant inverse correlation between HRCT scores for emphysema and percentage predicted values of DLco(r = -0.68, p < 0.05), DLco/VA(r = -0.49, p < 0.05), FEV1(r = -0.53, p < 0.05), and FVC(r = -0.47, p < 0.05). 2) There was a significant correlation between the HRCT scores and percentage predicted values of TLC(r = 0.50, p < 0.05), RV(r = 0.64, p < 0.05). 3) There was a significant inverse correlation between the HRCT scores and PaO2(r = -0.48, p < 0.05) and significant correlation with D(A-a)O2(r = -0.48, p < 0.05) but no significant correlation between the HRCT scores and PaCO2. 4) There was no significant correlation between the HRCT scores and age, sex, height, weight, smoking amounts in patients, hemoglobin, hematocrit, and wbc counts. Conclusion : High-Resolution CT provides a useful method for early detection and quantitating emphysema in life and correlates significantly with pulmonary function tests and arterial blood gas analysis.

• Tuberculosis and Respiratory Diseases
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• v.44 no.2
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• pp.232-240
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• 1997

Background : Postprimary pulmonary tuberculosis is located mainly in upper lobes. The tuberculous lesion involving the lower lobes usually arises from the upper lobe cavity through endobronchial spread. When tuberculosis is confined to the lower lung field, it often masquerades as pneumonia, lung cancer, bronchiectasis, or lung abscess. Thus the correct diagnosis may be sometimes delayed for a long time. Methods : We carried out, retrospectively, a clinical study on 50 patients confirmed with lower lung field tuberculosis who visited the Department of Pulmonary Medicine at Hanyang University Hospital from January 1992 to December 1994. The following results were obtained. Results : Lower lung field tuberculosis without concomitant upper lobe disease occurred in fifty patients representing 6.9% of the total admission with active pulmonary tuberculosis over a period of 3 years. It occurred most frequently in the third decade but age distribution was relatively even. The mean age was 43 years old. Female was more frequently affected than male (male to female ratio 1 : 1.9). The most common symptom was cough(68%), followed by sputum(52%), fever(38%), and chest discomfort(30%). On chest X-ray of the 50patients, consolidation was the most common finding in 52%, followed by solitary nodule(22%) collapse(16%), cavitary lesion(10%), in decreasing order. The disease confined to the right side in 25 cases, left side 20 cases, and both sides 5 cases. Endobronchial tuberculosis (1) Endobronchial involvement was proved by bronchoscopic examination in 20 of 50patients. (2) Mean age was 44years old and female was more affected than man (male to female ratio 1 : 3). Sputum AFB stain and Mycobacterium tuberculosis culture were positive only in 50% of cases unlikely upper lobe tuberculosis, additional diagnostic methods were needed. In our study, bronchoscopic examination and percutaneous fine needle aspiration biopsy increased diagnostic yield by 18% and 32%, respectively. The most common associated condition was diabetes mellitus(18%) and others were anemia, anorexia nervosa, stomach cancer, and systemic steroid usage. Conclusion : When we find a lower lung field lesion, we should suspect tuberculosis if the patient has diabetes mellitus, anemia, systemic steroid usage, malignancy or other immune suppressed states. Because diagnostic yield of sputum AFB smear & Mycobacterium tuberculosis culture was low, additional diagnostic methods such as bronchoscopy and fine needle aspiration biopsy were needed.

• Tuberculosis and Respiratory Diseases
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• v.47 no.6
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• pp.824-835
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• 1999

Background: Sleep-related breathing disorders are commonly found in patients with chronic renal failure and particularly, sleep apnea may have an influence on the long-term mortality rates in these patients. Maintenance hemodialysis is the mainstay of medical measures for correcting the metabolic derangements of chronic renal failure but it is uncertain whether it may alleviate sleep disorders including sleep apnea. Methods: Forty seven patients on maintenance hemodialysis were surveyed with the sleep questionnaire about their clinical symptoms related to sleep disorders. Among them, 15 patients underwent the polysomnography and their blood levels of urea nitrogen, creatinine, electrolytes and the arterial blood gases in the nights before and following hemodialysis were measured. Results: Forty(85.1%) of the 47 patients complained of the symptoms associated with sleep-wake cycle disturbances, 55.3% experienced snoring and 27.7% reported witnessed apneas. The duration of REM sleep increased significantly in the nights after hemodialysis compared to the nights without hemodialysis(p<0.05) and the percentage of total sleep time comprising NREM sleep decreased significantly in the nights following hemodialysis compared to the nights before hemodialysis(p<0.05). The percentage of total sleep time consisting of the stage 1 and 2 NREM sleep showed the trend for a decrease in the nights after hemodialysis(p=0.051), while the percentage of total sleep time comprising the stage 3 and 4 NREM sleep did not change between nights. The obstructive sleep apnea was more predominant type than the central one in both nights and there were no differences in the apnea index and the apnea-hypopnea index between the nights. The decrease in the blood level of urea nitrogen, creatinine, potassium and phosphorus was observed after hemodialysis(p<0.05), but the differences of parameters measured during polysomnography between the nights did not correlate with the changes of biochemical factors obtained on the two nights. Arterial blood gas analysis showed that pH was significantly greater in the nights after hemodialysis than in the nights before hemodialysis(p<0.05), but there were no correlations between the parameters examined during polysomnography and the parameters of arterial blood gas analysis(p<0.05). Conclusion: These results suggest that chronic renal failure is an important systemic disorder which is strongly associated with sleep disorders. Maintenance hemodialysis, although it is a widely accepted measure to treat chronic renal failure, did not significantly modulate the sleep architecture and the severity of sleep apnea. Thus, taking the patients with chronic renal failure into account, it is advisable to try not only to find a substantial way for correcting metabolic derangements but also to consider the institution of more effective treatments for sleep disorders.

• Tuberculosis and Respiratory Diseases
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• v.47 no.4
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• pp.442-450
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• 1999

Background : Isoniazid(INH) and rifampicin(RFP) are the most effective anti-tuberculosis drugs which make the short-course chemotherapy possible. Although prescribed dosages of INH and RFP in Korea are different from those recommended by American Thoracic Society, there has been few study about pharmacokinetic profiles of INH and RFP in Korean patients who receive INH, RFP, ethambutol(EMB) and pyrazinamide(PZA) simultaneously. Methods : Among the patients with active tuberculosis from Dec. 1997 to July 1998, we selected 17 patients. After an overnight fast, patients were given INH 300mg, RFP 450mg, EMB 800mg and PZA 1500mg daily. Blood samples for the measurement of plasma INH(n=15) and RFP(n=17) level were drawn each at 0, 0.5, 1, 1.5, 2, 4, 6, 8 and 12hrs, and urine was also collected. INH and RFP level in the plasma and the urine were measured by high-performance liquid chromatography(HPLC). Pharmacokinetic parameters such as peak serum concentration(Cmax), time to reach to peak serum concentration(Tmax), half-life, elimination rate constant(Ke), total body clearance(CLtot), nonrenal clearance(CLnr), and renal clearance(CLr) were calculated. Results : 1) Pharmacokinetic parameters of INH were as follows: Cmax; $7.63{\pm}3.20{\mu}g/ml$, Tmax; $0.73{\pm}0.22hr$, half-life; $2.12{\pm}0.84hrs$, Ke; $0.83{\pm}0.15hrs^{-1}$, CLtot; $17.54{\pm}8.89L/hr$, CLnr; $14.74{\pm}8.35L/hr$, CLr; $2.79{\pm}1.31L/hr$. 2) Pharmacokinetic parameters of RFP were as follows: Cmax; $8.93{\pm}3.98{\mu}g/ml$, Tmax; $1.76{\pm}1.13hrs$, half-life; $2.27{\pm}0.54hrs$, Ke; $0.32{\pm}0.08hrs^{-1}$, CLtot; $14.63{\pm}6.60L/hr$, CLr; $1.04{\pm}0.55L/hr$, CLnr; $13.59{\pm}6.21L/hr$. 3) While the correlation between body weight and Cmax of INH was not statistically significant (r=-0.514, p value>0.05), Cmax of RFP was significantly affected by body weight of the patients(r=-0.662, p value<0.01). Conclusion : In Korean patients with tuberculosis, 300mg of INH will be sufficient to reach the ideal peak blood level even in the patients over 50kg of body weight However, 450mg of RFP will not be the adequate dose in the patients who weigh over 50~60kg.

• Tuberculosis and Respiratory Diseases
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• v.43 no.6
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• pp.871-881
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• 1996

Objective: In the early short-term therapy of pulmonary tuberculosis, PZA is used for the first two months on 6EHRZ therapy but PZA is not effective in the case of long-tenn use PZA for retreatment in the sensitive relapse or acquired drug resistance for PZA. But in the endemic area as Korea, if we can't use PZA in the retreatment of pulmonary tuberculosis, we can't expect the success for retreatment of pulmonary tuberculosis, therefore we need new drugs substituting for PZA. In these days, 4 - fluoroquinolone derivatives were investigated and only ofloxacin and ciprofloxacin of derivatives were known to be effective but the effectiveness was also not certain because the result was experimental or combined with other bacteriocidal drugs and datas on effectiveness of pulmonary tuberculosis were so little. Therefore these drugs should be use with other two or three strong-acting drugs in the last period of retreatment of pulmonary tuberculosis. The ofloxacin or ciprofloxacin is used in some area in Korea but randomly and needed more study. We did this study for proving the effectiveness of these drugs and establishment of retreatment regimen for pulmonary tuberculosis. Methods: Retrospective cohort study of 83 drug-resistant pulmonary tuberculosis patients at National Masan Tuberculosis Hospital from Jan. 1994 to dec. 1995 was made. All the patients taken medicine for 2nd ami-tuberculosis regimens for the first lime. We separated the patients by two groups.(Group I : OFX+ PTA + CS+PAS + Injection, Group II: PZA + PTA+ CS + PAS + Injection). We compared the difference between two groups and tested the confidence limit about results after treatment by $\chi$2-test and T-test. Results : 1. The age distribution was most frequent in fourth decade(29.2% in Group I, 37.1% in Group II) and the mean age was 43.9 year in Group I, and 39.0 year in Group II, but had no significant difference between two groups. The sex distribution was more frequent in the males(68.8% in Group I, 85.7% in Group II), but had no significant difference. 2. Family history was 29.2% in Group I, 28.6% in Group II, but had no significant difference. 3. In the respect of extent of disease, far-advanced stare was 60.4% in Group I, 74.3% in Group II, but had no significant difference. 4. The side effects for drugs showed in 58.3% in Group I and 65.7% in Group II, and the gastrointestinal trouble showed 25.0% in Group and arthralgia 34.3% in Group II predominantly respectively and had the significant difference(p<0.05). 5. The negative conversion rate on sputum AFB smear was 87.5% in Group I and 80.0% in Group II, but had no significant difference. But the negative conversion rate on sputum AFB culture was 83.3% in Group I and 57.1 % in Group II and had the significant difference(p<0.05). 6. The success rate of treatment was 87.5 % in Group I and 83.3 % in Group II but had no significant difference. Conclusion : In the retreatment of pulmonary tuberculosis, ofloxacin is useful drug for the patients who are not available to use PZA and can be use effectively substituting for PZA.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.153-169
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• 2012

Exhibitions have played a key role of effective marketing activity which directly informs services and products to current and potential customers. Through participating in exhibitions, exhibitors have got the opportunity to make face-to-face contact so that they can secure the market share and improve their corporate images. According to this economic importance of exhibitions, show organizers try to adopt a new IT technology for improving their performance, and researchers have also studied services which can improve the satisfaction of visitors through analyzing visit patterns of visitors. Especially, as smart technologies make them monitor activities of visitors in real-time, they have considered booth recommender systems which infer preference of visitors and recommender proper service to them like on-line environment. However, while there are many studies which can improve their performance in the side of new technological development, they have not considered the choice factor of visitors for booth recommender systems. That is, studies for factors which can influence the development direction and effective diffusion of these systems are insufficient. Most of prior studies for the acceptance of new technologies and the continuous intention of use have adopted Technology Acceptance Model (TAM) and Extended Technology Acceptance Model (ETAM). Booth recommender systems may not be new technology because they are similar with commercial recommender systems such as book recommender systems, in the smart exhibition environment, they can be considered new technology. However, for considering the smart exhibition environment beyond TAM, measurements for the intention of reuse should focus on how booth recommender systems can provide correct information to visitors. In this study, through literature reviews, we draw factors which can influence the satisfaction and reuse intention of visitors for booth recommender systems, and design a model to forecast adaptation of visitors for booth recommendation in the exhibition environment. For these purposes, we conduct a survey for visitors who attended DMC Culture Open in November 2011 and experienced booth recommender systems using own smart phone, and examine hypothesis by regression analysis. As a result, factors which can influence the satisfaction of visitors for booth recommender systems are the effectiveness, perceived ease of use, argument quality, serendipity, and so on. Moreover, the satisfaction for booth recommender systems has a positive relationship with the development of reuse intention. For these results, we have some insights for booth recommender systems in the smart exhibition environment. First, this study gives shape to important factors which are considered when they establish strategies which induce visitors to consistently use booth recommender systems. Recently, although show organizers try to improve their performances using new IT technologies, their visitors have not felt the satisfaction from these efforts. At this point, this study can help them to provide services which can improve the satisfaction of visitors and make them last relationship with visitors. On the other hands, this study suggests that they managers along the using time of booth recommender systems. For example, in the early stage of the adoption, they should focus on the argument quality, perceived ease of use, and serendipity, so that improve the acceptance of booth recommender systems. After these stages, they should bridge the differences between expectation and perception for booth recommender systems, and lead continuous uses of visitors. However, this study has some limitations. We only use four factors which can influence the satisfaction of visitors. Therefore, we should development our model to consider important additional factors. And the exhibition in our experiments has small number of booths so that visitors may not need to booth recommender systems. In the future study, we will conduct experiments in the exhibition environment which has a larger scale.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.133-146
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• 2013

While the use of internet is routine nowadays, users receive and share information through a variety of media. Through the use of internet, information delivery media is diversifying from traditional media of one-way communication, such as newspaper, TV, and radio, into media of two-way communication. In contrast of traditional media, blogs enable individuals to directly upload and share news, which can be considered to have a differential speed of information diffusion than news media that convey information unilaterally. Therefore this Study focused on the difference between online news and social media blogs. Moreover, there are variations in the speed of information diffusion because that information closely related to one person boosts communications between individuals. We believe that users' standard of evaluation would change based on the types of information. As well, the speed of information diffusion would change based on the level of proximity. Therefore, the purpose of this study is to examine the differences in information diffusion based on the types of media. And then information is segmentalized and an examination is done to see how information diffusion differentiates based on the types of information. This study used the Bass diffusion model, which has been frequently used because this model has higher explanatory power than other models by explaining diffusion of market through innovation effect and imitation effect. Also this model has been applied a lot in other information diffusion related studies. The Bass diffusion model includes an innovation effect and an imitation effect. Innovation effect measures the early-stage impact, while the imitation effect measures the impact of word of mouth at the later stage. According to Mahajan et al. (2000), Innovation effect is emphasized by usefulness and ease-of-use, as well Imitation effect is emphasized by subjective norm and word-of-mouth. Also, according to Lee et al. (2011), Innovation effect is emphasized by mass communication. According to Moore and Benbasat (1996), Innovation effect is emphasized by relative advantage. Because Imitation effect is adopted by within-group influences and Innovation effects is adopted by product's or service's innovation. Therefore, ours study compared online news and social media blogs to examine the differences between media. We also choose different types of information including entertainment related information "Psy Gentelman", Current affair news "Earthquake in Sichuan, China", and product related information "Galaxy S4" in order to examine the variations on information diffusion. We considered that users' information proximity alters based on the types of information. Hence, we chose the three types of information mentioned above, which have different level of proximity from users' standpoint, in order to examine the flow of information diffusion. The first conclusion of this study is that different media has similar effect on information diffusion, even the types of media of information provider are different. Information diffusion has only been distinguished by a disparity between proximity of information. Second, information diffusions differ based on types of information. From the standpoint of users, product and entertainment related information has high imitation effect because of word of mouth. On the other hand, imitation effect dominates innovation effect on Current affair news. From the results of this study, the flow changes of information diffusion is examined and be applied to practical use. This study has some limitations, and those limitations would be able to provide opportunities and suggestions for future research. Presenting the difference of Information diffusion according to media and proximity has difficulties for generalization of theory due to small sample size. Therefore, if further studies adopt to a request for an increase of sample size and media diversity, difference of the information diffusion according to media type and information proximity could be understood more detailed.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.123-132
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• 2013

As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.