U.S. Army front line artillery observation during the 1945 Okinawa campaign: An oral history case study

This dissertation explores the role of artillery forward observation teams during the battle of Okinawa (April–June 1945). It addresses a variety of questions associated with this front line artillery support. First, it examines the role of artillery itself in the American victory over the Japanese on Okinawa. Second, it traces the history of the forward observer in the three decades before the end of World War II. Third, it defines the specific role of the forward observation teams during the battle: what they did and how they did it during this three-month duel. Fourth, it deals with the particular problems of the forward observer. These included coordination with the local infantry commander, adjusting to the periodic rotation between the front lines and the artillery battery behind the line of battle, responding to occasional problems with "friendly fire" (American artillery falling on American ground forces), dealing with personnel turnover in the teams (due to death, wounds, and illness), and finally, developing a more informal relationship between officers and enlisted men to accommodate the reality of this recently created combat assignment. Fifth, it explores the experiences of a select group of men who served on (or in proximity to) forward observation teams on Okinawa. Previous scholars and popular historians of the battle have emphasized the role of Marines, infantrymen, and flame-throwing armor. This work offers a different perspective on the battle and it uses new sources as well. A pre-existing archive of interviews with Okinawan campaign forward observer team members conducted in the 1990s forms the core of the oral history component of this research project. The verbal accounts were checked against and supplemented by a review of unit reports obtained from the U.S. National Archives and various secondary sources. The dissertation concludes that an understanding of American artillery observation is critical to a more complete comprehension of the battle of Okinawa. These mid-ranking (and largely middle class) soldiers proved capable of adjusting to the demands of combat conditions. They provide a unique and understudied perspective of the entire battle.

Cancer therapy combining the modalities of hyperthermia and chemotherapy: In vitro cellular response after rapid heat accumulation in the cancer cell

Hyperthermia is usually used at a sub-lethal level in cancer treatment to potentiate the effects of chemotherapy. The purpose of this study is to investigate the role of heating rate in achieving synergistic cell killing by chemotherapy and hyperthermia. For this purpose, in vitro cell culture experiments with a uterine cancer cell line (MES-SA) and its multidrug resistant (MDR) variant MES-SA/Dx5 were conducted. The cytotoxicity, mode of cell death, induction of thermal tolerance and P-gp mediated MDR following the two different modes of heating were studied. Doxorubicin (DOX) was used as the chemotherapy drug. Indocyanine green (ICG), which absorbs near infrared light at 808nm (ideal for tissue penetration), was chosen for achieving rapid rate hyperthermia. A slow rate hyperthermia was provided by a cell culture incubator. The results show that the potentiating effect of hyperthermia to chemotherapy can be maximized by increasing the rate of heating as evident by the results from the cytotoxicity assay. When delivered at the same thermal dose, a rapid increase in temperature from 37°C to 43°C caused more cell membrane damage than gradually heating the cells from 37°C to 43°C and thus allowed for more intracellular accumulation of the chemotherapeutic agents. Different modes of cell death are observed by the two hyperthermia delivery methods. The rapid rate laser-ICG hyperthermia @ 43°C caused cell necrosis whereas the slow rate incubator hyperthermia @ 43°C induced very mild apoptosis. At 43°C a positive correlation between thermal tolerance and the length of hyperthermia exposure is identified. This study shows that by increasing the rate of heating, less thermal dose is needed in order to overcome P-gp mediated MDR.

Off-line and on-line affective recognition of a computer user through a biosignal processing approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. ^ In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment ("relaxation" vs. "stress") are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. ^ For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). ^ In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the "relaxation" vs. "stress" states.^

Characterization and modeling of multi-conductor transmission line using Finite-difference Time-Domain method

A two-dimensional, 2D, finite-difference time-domain (FDTD) method is used to analyze two different models of multi-conductor transmission lines (MTL). The first model is a two-conductor MTL and the second is a threeconductor MTL. Apart from the MTL's, a three-dimensional, 3D, FDTD method is used to analyze a three-patch microstrip parasitic array. While the MTL analysis is entirely in time-domain, the microstrip parasitic array is a study of scattering parameter Sn in the frequency-domain. The results clearly indicate that FDTD is an efficient and accurate tool to model and analyze multiconductor transmission line as well as microstrip antennas and arrays.

Off-line and On-line Affective Recognition of a Computer User through A Biosignal Processing Approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.