• Title/Summary/Keyword: Two stage approach

Search Result 554, Processing Time 0.022 seconds

Combined Chemoradiotherapy vs Radiotherapy Alone for Locally Advanced Squamous Cell Carcinoma of the Head and Neck (국소적으로 진행된 두경부 편평상피세포종양의 방사선- 항암화학 병용요법과 방사선단독치료의 비교)

  • Jeong, Hyeon-Ju;Suh, Hyun-Suk;Kim, Chul-Soo;Kim, Re-Hwe;Kim, Sung-Rok
    • Radiation Oncology Journal
    • /
    • v.14 no.1
    • /
    • pp.9-15
    • /
    • 1996
  • Purpose: The traditional approach with surgery and/or radiotherapy(RT) for advanced head and neck cancer Provides anticipated cure rates of $10-65\%$ depending on stages and sites. Recently, combined modality with chemotherapy have been extensively investigated in attempts to improve survival and local control. We retrospectively analysed our experience of 31 patients with advanced head and neck cancer. Materials and Methods : November 1983 to October 1994. 31 Patients with Stage III and IV squamous cell head and neck cancer were treated with RT. Sixteen patients were treated with RT alone, and IS patients were treated with combined RT plus chemotherapy. All patients were treated with 4-MV LINAC and radiation dose ranged from 5000 cGy to 7760 cGy (median 7010 cGy). In combined group, 7 patients were treated with cisplatin plus 5-FU 2 patients were treated with methotrexate plus leucovorin plus 5-FU plus cisplatin or carboplatin, and 6 patients were treated with cisplatin as a radiosensitizer. Results : Median follow up period was 16 months (range 4-134 months). The major responses (CR+PR) were noted in 10 patient ($66.6\%$) of the RT alone group and 14 patient ($93.3\%$) of the chemoradiation group. There was no statistical difference in CR rate between the two groups The overall survival rates at 5 years were $23.4\%$ in the radiation alone group, $23.5\%$ in the chemoradiation group Disease-free survival rates at 3 years were $44.5\%$ in the radiation alone group, $40\%$ in the chemoradiation group. There was no statistical differences in overall survival rates and disease-free survival rates between the two groups. Local recurrences occurred in $71.5\%$ of the radiation alone group, $72.7\%$ of the chemoradiation group and distant metastasis occurred in $14.4\%$ of radiation alone group, $9.1\%$ of the chemoradiation group. The frequencies of complications were comparable in both groups except hematologic toxicity Conclusion : Total response rates in the combined chemotherapy and radiotherapy was relatively higher than radiotherapy alone. But our result failed to show any survival benefit of the combined chemotherapy and radiotherapy. The accrual of large number of patients and long term follow-un may be necessary to confirm the present result of combined chemotherapy and radiotherapy.

  • PDF

A Study on the Visions of Zechariah in the Old Testament from a Perspective of Analytical Psychology (구약성서 '스가랴'서의 환상에 대한 분석심리학적 연구)

  • Sang Ick Han
    • Sim-seong Yeon-gu
    • /
    • v.29 no.1
    • /
    • pp.1-45
    • /
    • 2014
  • Mystic experience such as seeing an vision could be explained as experiencing elusive and mysterious unique existence in religious way. In depth psychology, which is based on unconsciousness like analytical psychology, this could be explained as a something that gives a meaning of life and purpose through discovering health and healing. The importance of primodial experience in depth psychology is that it can possibly discover the base of present acts. In Christian theology, symbolic mystery and truth of religious experience that appear in Christian tradition have interest on human situation. These two fields' approach methods are different, but both show common interest on unique experience which can be said properly as raw experience. Various visions appear in many parts of the Bible. Among many visions, the book of Zechariah, one of the 12 Prophets, describes rich and diverse 8 visions through chapter 1 to chapter 8. However, due to the Genre of revelation, it lacks historicity, and because of vagueness and symbolic meanings, its visions are hard to understand and interpret. Theologically, visions of Zechariah show communality of Israelites by reconstructing kingdom of Judah and church in a way of historical circumstances. Though, these visions could deliver the meaning of an ethnical aspect as reporting continuous conversation between the God and humans. Furthermore, it could mean a personal aspect of the Prophet Zechariah as reaching for a opportunity of new change. Moreover, those who read these visions could try to interpret the meanings of various images which represent meeting mysterious existences. Therefore, the Author would concentrate on the fact that 8 visions in the book of Zechariah, which has not been received much attention to neither Christians nor non-believers, develop in chiastic structure (stylistic contrast), so that tries to interpret the first, second, seventh, and the eighth visions in analytic psychology way. In visions of Zechariah, excepting the 4th vision which probably was inserted later, rest of 7 visions each shows the stage of the hours of darkness. 1st to 3rd visions represent evening, 5th vision represents deep in the night, and 6th to 8th visions represent dawn to morning. Moreover, since structure of visions arranged in chiastic way, horse appears in 1st and 8th vision, measuring rope and measure tools are used as main motif in 2nd and 7th vision. However, same motifs could have different symbolic meanings and roles as visions are formed in different situations and conditions. In the first vision, angels who ride horses look around the world and report it is calm and peaceful. Concerning the political situation back in the day, the world being calm and peaceful in the beginning of evening means that it is not ready to change to a whole new world. Psychologically, if there is no readiness to adopt new world, it means being hopeless. It is sending you a message to get out of those kinds of situation. Moreover, appearance of four angels who rode red, brown, and white horses to a myrtus tree in the valley means that it is time for individuation and it is right and good timing for changing. In second vision, you will be able to see that Israelites had long years being caught in the shadows by foreign country, and long years succumbed by the strength of four horns, which shows the progress of renewing strength and being oneness with oneself from overwhelmed situation by paternity. In seventh vision, meaning of two women bringing the godness of the sky, who were locked up in a rice basket, back to the temple in Babylon is going towards in a level of Self-actualization by separating one's ego captured excessively by matherhood and putting back to a place where it was before. In eighth vision, chariots pulled by horses are scattered far and wide, and horses which went to north had rest in the land of North. After horses and chariots are seen between two mountains of bronze with the image of Self and anima/animus. These images can be explained as the changing progress are almost completed and the God and human, in other words Self and ego are being united and is now time for rest. All of 8 visions contains the conversation between angel and Zechariah who willing to know the meaning of visions. Zechariah asks the angel actively about the meaning of visions because of his wish for Israelites to return home and rebuild church. Conversation among the God, Zechariah, who asks questions until he knows everything, an Angel, who gives answer to given questions, is conversation between ego and anima/animus. Eventually, it is a conversation between Self and ego.

Forecasting Substitution and Competition among Previous and New products using Choice-based Diffusion Model with Switching Cost: Focusing on Substitution and Competition among Previous and New Fixed Charged Broadcasting Services (전환 비용이 반영된 선택 기반 확산 모형을 통한 신.구 상품간 대체 및 경쟁 예측: 신.구 유료 방송서비스간 대체 및 경쟁 사례를 중심으로)

  • Koh, Dae-Young;Hwang, Jun-Seok;Oh, Hyun-Seok;Lee, Jong-Su
    • Journal of Global Scholars of Marketing Science
    • /
    • v.18 no.2
    • /
    • pp.223-252
    • /
    • 2008
  • In this study, we attempt to propose a choice-based diffusion model with switching cost, which can be used to forecast the dynamic substitution and competition among previous and new products at both individual-level and aggregate level, especially when market data for new products is insufficient. Additionally, we apply the proposed model to the empirical case of substitution and competition among Analog Cable TV that represents previous fixed charged broadcasting service and Digital Cable TV and Internet Protocol TV (IPTV) that are new ones, verify the validities of our proposed model, and finally derive related empirical implications. For empirical application, we obtained data from survey conducted as follows. Survey was administered by Dongseo Research to 1,000 adults aging from 20 to 60 living in Seoul, Korea, in May of 2007, under the title of 'Demand analysis of next generation fixed interactive broadcasting services'. Conjoint survey modified as follows, was used. First, as the traditional approach in conjoint analysis, we extracted 16 hypothetical alternative cards from the orthogonal design using important attributes and levels of next generation interactive broadcasting services which were determined by previous literature review and experts' comments. Again, we divided 16 conjoint cards into 4 groups, and thus composed 4 choice sets with 4 alternatives each. Therefore, each respondent faces 4 different hypothetical choice situations. In addition to this, we added two ways of modification. First, we asked the respondents to include the status-quo broadcasting services they subscribe to, as another alternative in each choice set. As a result, respondents choose the most preferred alternative among 5 alternatives consisting of 1 alternative with current subscription and 4 hypothetical alternatives in 4 choice sets. Modification of traditional conjoint survey in this way enabled us to estimate the factors related to switching cost or switching threshold in addition to the effects of attributes. Also, by using both revealed preference data(1 alternative with current subscription) and stated preference data (4 hypothetical alternatives), additional advantages in terms of the estimation properties and more conservative and realistic forecast, can be achieved. Second, we asked the respondents to choose the most preferred alternative while considering their expected adoption timing or switching timing. Respondents are asked to report their expected adoption or switching timing among 14 half-year points after the introduction of next generation broadcasting services. As a result, for each respondent, 14 observations with 5 alternatives for each period, are obtained, which results in panel-type data. Finally, this panel-type data consisting of $4{\ast}14{\ast}1000=56000$observations is used for estimation of the individual-level consumer adoption model. From the results obtained by empirical application, in case of forecasting the demand of new products without considering existence of previous product(s) and(or) switching cost factors, it is found that overestimated speed of diffusion at introductory stage or distorted predictions can be obtained, and as such, validities of our proposed model in which both existence of previous products and switching cost factors are properly considered, are verified. Also, it is found that proposed model can produce flexible patterns of market evolution depending on the degree of the effects of consumer preferences for the attributes of the alternatives on individual-level state transition, rather than following S-shaped curve assumed a priori. Empirically, it is found that in various scenarios with diverse combinations of prices, IPTV is more likely to take advantageous positions over Digital Cable TV in obtaining subscribers. Meanwhile, despite inferiorities in many technological attributes, Analog Cable TV, which is regarded as previous product in our analysis, is likely to be substituted by new services gradually rather than abruptly thanks to the advantage in low service charge and existence of high switching cost in fixed charged broadcasting service market.

  • PDF

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)

  • Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
    • Journal of Intelligence and Information Systems
    • /
    • v.25 no.1
    • /
    • pp.163-177
    • /
    • 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.