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Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1964
Creator: Brandt & Associates
Date: 1964
Description: Aerial photograph of the Illinois Institute of Technology campus, looking northeast.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1958
Creator: Brandt & Associates
Date: 1958
Description: Aerial photograph of the Illinois Institute of Technology campus, looking southwest.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1963
Creator: Brandt & Associates
Date: 1963
Description: Aerial photograph of the Illinois Institute of Technology campus, looking north.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1950
Date: 1950
Description: Aerial photograph of the Illinois Institute of Technology campus, looking southwest. Photographer unknown.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1940
Date: 1940
Description: Aerial photograph of the Illinois Institute of Technology campus, looking north. Photographer unknown.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1975
Creator: Brandt & Associates, Ltd.
Date: 1975
Description: Aerial photograph of Mies Campus, looking north.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1985
Date: 1985-10-24
Description: Aerial photograph of Mies Campus, looking north, 1985. Photographer unknown.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: The Cycle, 1938
Creator: Armour Institute of Technology
Date: 1938
Description: Volume 26 of The Cycle, the 1938 yearbook for the Armour Institute of Technology. The Armour Institute of Technology yearbooks was known by...
Show moreVolume 26 of The Cycle, the 1938 yearbook for the Armour Institute of Technology. The Armour Institute of Technology yearbooks was known by three different titles: Integral (1898-1910), Senior Class Book (1911-1912), and The Cycle (1913-1940). A 1902 volume of Integral is not a part of Galvin Library collections; it is uncertain of a yearbook was published that year. Publication of the Armour Institute ceased in 1941, when the Armour Institute of Technology merged with the Lewis Institute to form Illinois Institute of Technology.
Sponsorship: Scanning of the Armour Institute of Technology yearbooks was supported in part by an award from the Illinois State Historical Records Advisory Board, through funding from the National Historical Publications and Records Commission, National Archives and Records Administration.
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Collection: Armour Institute of Technology yearbooks, 1898-1940

Title: The Cycle, 1934
Creator: Armour Institute of Technology
Date: 1934
Description: Volume 22 of The Cycle, the 1934 yearbook for the Armour Institute of Technology. The Armour Institute of Technology yearbooks was known by...
Show moreVolume 22 of The Cycle, the 1934 yearbook for the Armour Institute of Technology. The Armour Institute of Technology yearbooks was known by three different titles: Integral (1898-1910), Senior Class Book (1911-1912), and The Cycle (1913-1940). A 1902 volume of Integral is not a part of Galvin Library collections; it is uncertain of a yearbook was published that year. Publication of the Armour Institute ceased in 1941, when the Armour Institute of Technology merged with the Lewis Institute to form Illinois Institute of Technology.
Sponsorship: Scanning of the Armour Institute of Technology yearbooks was supported in part by an award from the Illinois State Historical Records Advisory Board, through funding from the National Historical Publications and Records Commission, National Archives and Records Administration.
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Collection: Armour Institute of Technology yearbooks, 1898-1940

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1964
Creator: Brandt & Associates
Date: 1964
Description: Aerial photograph of the Illinois Institute of Technology campus, looking north.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1964
Creator: Brandt & Associates
Date: 1964
Description: Aerial photograph of the Illinois Institute of Technology campus, looking north.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1967
Creator: Brandt & Associates
Date: 1967
Description: Aerial photograph of the Illinois Institute of Technology campus, looking north.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, ca. 1955-1959
Date: 1955-1959
Description: Aerial photograph of the Illinois Institute of Technology campus, looking southwest. Photographer unknown. Date of photograph unknown. Date...
Show moreAerial photograph of the Illinois Institute of Technology campus, looking southwest. Photographer unknown. Date of photograph unknown. Date range listed is approximate.
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Collection: IIT Campus Aerial photographs, 1940-2002

Title: Aerial view of the Illinois Institute of Technology campus, Chicago, Illinois, 1957
Date: 1957
Description: Aerial photograph of the south portion of the Illinois Institute of Technology campus, looking south. Photographer unknown.
Collection: IIT Campus Aerial photographs, 1940-2002

Title: Synthesis and Photophysical Characterization of Novel Organic Triplet Donor–Acceptor Dyads for Light-Harvesting/Modulation Application
Creator: Yun, Young Ju
Date: 2022
Description: Donor–acceptor chromophoric systems (D–A) are important scaffolds for several light-harvesting/initiated processes and devices, including...
Show moreDonor–acceptor chromophoric systems (D–A) are important scaffolds for several light-harvesting/initiated processes and devices, including light-emitting diodes, photo-catalytic/redox systems, and photovoltaic cells. It has been hypothesized that for efficient photophysical processes (viz. energy/charge-transfer or excited-state interactions); it is ideal to tether the donor and acceptor chromophores into molecular dyads. To this end, I devised and synthesized several dyads by tethering an organic triplet energy donor and various polyaromatic chromophores (e.g., perylene derivatives and anthracene derivatives) onto a conjugated-/non-conjugated-linker (phenylene- and triptycene- linker, respectively). During the 4-5 years of my Ph.D., I synthesized a total of five (5) dyads: o–, p–3, and dyads 3–5. These systems were fully characterized using different spectroscopy tools/techniques. The spectroscopy investigations of the dyads have allowed me to decipher two important energy transfer pathways: through-bond and through-space with the phenylene linker and only through-space energy with the triptycene linker. Furthermore, the investigations led to the discovery that geometrical features such as face-to-face (co-facial) or slip-stacked interactions between the donor and acceptors chromophores might dictate the dynamic/kinetic of light-induced energy transfer in the dyads. Findings from my graduate research project paved the way for developing molecular engineering studies for light-harvesting/modulation applications.Subsequently, I was able to employ the dyads of my interest to achieve intramolecular and intermolecular triplet energy transfer (TEnT) triplet-triplet annihilation-based photon upconversion (TTA-PUC).
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Title: DEFAULT RISK AND MOMENTUM PREMIUM
Creator: Zhang, Yi
Date: 2022
Description: Birge and Zhang (2018) reported that combining common factors models with functions of the default risk improves models' performance to...
Show moreBirge and Zhang (2018) reported that combining common factors models with functions of the default risk improves models' performance to explain stock returns. Default risk contains firm specific information and may help to explain momentum premium that compensates investors for the firm specific risk exposures. In this paper, we confirmed that the forward-looking measure of default risk, as proposed by Birge and Zhang (2018), seems to capture some pricing information in the momentum premium. This provides an alternative to explain the underlying risks associated with the momentum strategy.
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Title: INTEGRATED DECISION SUPPORT SYSTEM FOR THE SELECTION AND IMPLEMENTATION OF DELAY ANALYSIS IN CONSTRUCTION PROJECTS
Creator: Yang, Juneseok
Date: 2022
Description: The goal of this study is to establish an objective, user-friendly, and reliable decision support system, called delay analysis selection and...
Show moreThe goal of this study is to establish an objective, user-friendly, and reliable decision support system, called delay analysis selection and implementation system (DASIS), which allows delay analysts and practitioners in the construction industry to select a type of delay analysis that is most appropriate for given conditions and to perform the selected type of delay analysis. DASIS integrates a delay analysis selection system (DASS) module and an implementation module (DAIS) that performs the type of delay analysis selected by DASS in construction projects.The model that operates the DASS module consists of (1) four different delay analysis approaches currently available to practitioners; (2) a set of 26 attributes that affect the selection of a type of delay analysis; (3) a case-base involving 3,776 cases described by these 26 attributes and their corresponding output values (i.e., the most appropriate delay analysis approach); (4) a set of 7 categories consisting of subsets of attributes; (5) the weights of the attributes and the categories; and (6) a spreadsheet designed in Microsoft Excel that performs the calculations involved in case-based similarity assessment. The implementation module is a computerized analytics and automation platform that performs the type of delay analysis selected by DASS. In developing the DASS module, 26 attributes that influence the selection of the most appropriate type of delay analysis were identified based on a thorough literature review and were organized in seven categories. These attributes were used to evaluate the four types of delay analysis (i.e., static, dynamic, additive, and subtractive analyses). Based on the results of this evaluation, a case-base of 3,776 cases was generated while considering the constraints of each category. The weights of the attributes and categories were determined by using several methods. To determine the best-fit between a target case (defined by its 26 attributes) and the 3,776 cases stored in the case-base were used to perform a case-based similarity assessment to calculate weighted case similarity scores, and to find the best-informed solution to the delay analysis type selection problem. In developing the DAIS module, the four types of delay analysis were coded in Microsoft Excel using macros programmed in Visual Basic for Applications (VBA). This automated tool performs the selected delay analysis by DASS. The fully integrated DASIS model finds the best-fit match between a target case and cases stored in the case-base by means of similarity assessment methods by using weighted case similarity scores, hence identifying the most appropriate type of delay analysis for use in the target case, performs the selected type of delay analysis and generates a report about the results of the delay analysis to the analyst instantaneously, allowing the contractual parties to settle the issues quickly. This study is the first attempt to establish an objective decision support system (DASS) to assist delay analysts by automating the selection of a type of delay analysis using combinations of well recognized and reliable attributes and similarity assessment techniques. In addition, DASS is immediately followed by DAIS in an integrated system (DASIS) that does not only do the selection of the most appropriate type of delay analysis, but that also implements the selected delay analysis, hence providing ease of use and high speed. A case study based on fictitious scenarios is presented to demonstrate and validate the research approach. The use of the entropy weight method to calculate the weights of the attributes can be considered a minor limitation of the study. Finally, DASIS can be reformulated as a web-based application that allows analysts to work online using ordinary browsers anywhere and anytime.
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Title: Essays on Clean Energy Finance and Cryptocurrency Market
Creator: Xie, Yao
Date: 2021
Description: This dissertation includes four essays with several empirical investigations in the areas of clean energy finance and cryptocurrencies.In the...
Show moreThis dissertation includes four essays with several empirical investigations in the areas of clean energy finance and cryptocurrencies.In the first essay, I investigate the heterogeneous relationship between various determinants of the clean energy market across all subsectors of the clean energy stock market. My findings reveal that VIX is the most significant predictor of all clean energy subsectors conditional volatility. During the COVID-19 stress period, economic uncertainty measures become more significant measures. The heterogeneity of clean energy market persists in the out-of-sample results. These results suggest that portfolio diversification for different clean energy subsector is necessary. In the second essay, I study the safe haven property of several volatility indexes on clean energy subsectors. I compare the current COVID-19 stress period and the time before. The results show that market volatility and commodity volatility are good safe haven assets during the COVID-19 period. But they are not safe haven assets against the clean energy subsector before the pandemic period. Among all volatility indexes, gold volatility index is the most effective safe haven assets. In the third essay, I investigate the characteristics of Bitcoin as a financial asset. A comprehensive set of information variables under five categories: macroeconomics, blockchain technology, other markets, stress level, and investor sentiment. The empirical results show that blockchain technology, stress level and investor sentiment have strong predicting power on Bitcoin returns. In the fourth essay, I aim to study how extreme sentiment measures from Google Trend and Wikipedia Pageviews affect both traditional cryptocurrency, such as Bitcoin and stablecoin, like Tether. Our results show that Tether’s return is not affected by the extreme sentiment measures during the COVID-19 stress period which suggests that stablecoin can offer price stability.
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Title: DEEP LEARNING AND COMPUTER VISION FOR INDUSTRIAL APPLICATIONS: CELLULAR MICROSCOPIC IMAGE ANALYSIS AND ULTRASOUND NONDESTRUCTIVE TESTING
Creator: Yuan, Yu
Date: 2022
Description: For decades, researchers have sought to develop artificial intelligence (AI) systems that can help human beings on decision making, data...
Show moreFor decades, researchers have sought to develop artificial intelligence (AI) systems that can help human beings on decision making, data analysis and pattern recognition applications where analytical methods are ineffective. In recent years, Deep Learning (DL) has been proven to be an effective AI technique that can outperform other methods in applications such as computer vision, natural language processing, autonomous driving. Realizing the potential of deep learning techniques, researchers have also started to apply deep learning on other industrial applications. Today, deep learning based models are used to innovate and accelerate automation, guidance, and decision making in various industries including automotive industry, pharmaceutical industry, finance, agriculture and more. In this research, several important industrial applications (on Biomedicine and Non-Destructive Testing) utilizing deep learning algorithms will be introduced and analyzed. The first biopharmaceutical application focuses on developing a deep learning based model to automate the visual inspection process in Median Tissue Culture Infectious Dose(TCID50). TCID50 is one of the most popular methods for viral quantification. An important step of TCID50 is to visually inspect the sample and decide if it exhibits cytopathic effect(CPE) or not. Two novel models have been developed to detect CPE in microscopic images of cell culture in 96 well-plates. The first model consists of a convolutional neural network (CNN) and support vector machine(SVM). The second model is a fully convolutional network (FCN) followed by morphological post-processing steps. The models are tested on 4 cell lines and achieve very high accuracy. Another biopharmaceutical application developed for cellular microscopic images is the clonal selection. Clonal selection is one of the mandatory steps in cell line development process. It focuses on verifying the clonality of the cell culture. The researchers used to visually inspect the microscopic images to verify the clonality. In this work, a novel deep learning based model and a workflow is developed to accelerate the process. This algorithm consists of multiple steps, including image analysis after incubation to detect the cell colonies, and verify its clonality in day0 image. The results and common mis-classification cases are shown in this thesis. Image analysis method is not the only technology that has been advancing for cellular image analysis in biopharmaceutical industry. A new class of instruments are currently used in biopharmaceutical industry which enable more opportunities for image analysis. To make the most of these new instruments, a convolutional neural network based architecture is used to perform accurate cell counting and cell morphology based segmentation. This analysis can provide more insight of the cells at very early stage in characterization process of cell line development. The architecture and the testing results are presented in this work. The proposed algorithm has achieved very high accuracy on both applications, and the cell morphology based segmentation enables a brand new feature for scientists to predict the potential productivity of the cells. Next part of this dissertation is focused on hardware implementation of Ultrasonic Non-Destructive Testing (NDT) methods based on deep learning, which can be highly useful in flaw detection and classification applications. With the help of a smart and mobile Non-Destructive Testing device, engineers can accurately detect and locate the flaws inside the materials without reliance on high performance computation resources. The first NDT application presents a hardware implementation of a deep learning algorithm on Field-programmable gate array(FPGA) for Ultrasound flaw detection. The Ultrasound flaw detection algorithm consists of a wavelet transform followed by a LeNet inspired convolutional neural network called Ultra-LeNet. This work is focused on implementing the computationally difficult part of this algorithm: Ultra-LeNet, so that it can be used in the field where high performance computation resources (e.g., AWS) are not accessible. The implementation uses resource partitioning to design two dedicated pipelined accelerators for convolutional layers and fully connected layers respectively. Both accelerators utilize loop unrolling, loop pipelining and batch processing techniques to maximize the throughput. The comparison to other work has shown that the implementation has achieved higher hardware utilization efficiency. The second NDT application is also focused on implementing a deep learning based algorithm for Ultrasound flaw detection on a FPGA. Instead of implementing the Ultra-LeNet, the deep learning model used in this application is Meta-learning based Siamese Network, which is capable for multi-class classification and it can also classify a new class even if it does not appear in the training dataset with the help of automated learning features. The hardware implementation is significantly different than the previous algorithm. In order to improve the inference operation efficiency, the model is compressed with both pruning and quantization, and the FPGA implementation is specifically designed to accelerate the compressed CNN with high efficiency. The CNN model compression method and hardware design are novel methods introduced in this work. Comparison against other compressed CNN accelerators is also presented.
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Title: MARKETABLE LIMIT ORDERS AND NON-MARKETABLE LIMIT ORDERS ON NASDAQ
Creator: ZHANG, DAN
Date: 2022
Description: My research includes two parts. In the first part of my research, I classify marketable limit orders into three different types: large...
Show moreMy research includes two parts. In the first part of my research, I classify marketable limit orders into three different types: large marketable order to buy, large marketable order to sell, and small marketable order. I use dummy variance method to research the effect of the three marketable orders on standardized variance, and find that LMOB and LMOS play significant role in variance increase. The second part of my research is about modelling of time to execution and time to cancellation of Non-marketable limit orders. I construct variables and model time to execution for NLO to buy and time to cancellation for NLO to buy and NLO to sell based on exponential distribution with accelerated failure time specification. My research shows that the longer the distance of limit price to buy away from the best bid price, the longer time to execution is. The longer the distance of limit price to buy away from the best bid price or limit price to sell away from the best ask price, the longer the time to cancellation is.
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