Robust methodology for investment climate assessment on productivity: application to investment climate surveys from Central America

Developing countries are increasingly concerned about improving country competitiveness and productivity, as they face the increasing pressures of globalization and attempt to improve economic growth and reduce poverty. Among such countries, Investment Climate Assessments (ICA) surveys at the firm level, have become the standard way for the World Bank to identify key obstacles to country competitiveness, in order to prioritize policy reforms for enhancing competitiveness. Given the surveys objectives and the nature and limitations of the data collected, this paper discusses the advantages and disadvantages of using different productivity measures. The main objective is to develop a methodology to estimate, in a consistent manner, the productivity impact of the investment climate variables. The paper applies it to the data collected for ICAs in four countries: Costa Rica, Guatemala, Honduras and Nicaragua. Observations on logarithms (logs) of the variables are pooled across three countries (Guatemala, Honduras and Nicaragua). Endogeneity of the production function inputs and of the investment climate variables is addressed by using a variant of the control function approach, based on individual firm information, and by aggregating investment climate variables by industry and region. It is shown that it is possible to get robust results for 10 different productivity measures. The estimates for the four countries show how relevant the investment climate variables are to explain the average level of productivity. IC variables in several categories (red tape, corruption and crime, infrastructure and, quality and innovation) account for over 30 percent of average productivity. The policy implications are clear: investment climate matters and the relative impact of the various investment climate variables indicate where reform efforts should be directed in each country. It is argued that this methodology can be used as a benchmark to assess productivity effects in other ICA surveys. This is important because ICA surveys are available now for more than 65 developing countries.Total factor productivity, Investment climate, Competitiveness, Firm level determinants of productivity, Robust productivity impacts,

Earth Abundant Thin Film Technology for Next Generation Photovoltaic Modules

With a cumulative generation capacity of over 100 GW, Photovoltaics (PV) technology is uniquely poised to become increasingly popular in the coming decades. Although, several breakthroughs have propelled PV technology, it accounts for only less than 1% of the energy produced worldwide. This aspect of the PV technology is primarily due to the somewhat high cost per watt, which is dependent on the efficiency of the PV cells as well as the cost of manufacturing and installing them. Currently, the efficiency of the PV conversion process is limited to about 25% for commercial terrestrial cells; improving this efficiency can increase the penetration of PV worldwide rapidly. A critical review of all possibilities pursued in the public domain reveals serious shortcomings and manufacturing issues. To make PV generated power a reality in every home, a Multi-Junction Multi-Terminal (MJMT) PV architecture can be employed combining silicon and another earth abundant material. However, forming electronic grade thin films of earth abundant materials is a non-trivial challenge; without solving this, it is impossible to increase the overall PV efficiency. Deposition of Copper (I) Oxide, an earth abundant semiconducting material, was conducted using an optimized Photo assisted Chemical Vapor Deposition process. X-Ray Diffraction, Ellipsometry, Transmission Electron Microscopy, and Profilometry revealed that the films composed of Cu2O of about 90 nm thickness and the grain size was as large as 600 nm. This result shows an improvement in material properties over previously grown thin films of Cu2O. Measurement of I-V characteristics of a diode structure composed of the Cu2O indicates an increase in On/Off ratio to 17,000 from the previous best value of 800. These results suggest that the electronic quality of the thin films deposited using our optimized process to be better than the results reported elsewhere. Using this optimized thin film forming technique, it is now possible to create a complete MJMT structure to improve the terrestrial commercial PV efficiency

Robust investment climate effects on alternative firm-level productivity measures

Developing countries are increasingly concerned about improving country competitiveness and productivity, as they face the increasing pressures of globalization and attempt to improve economic growth and reduce poverty. Among such countries, Investment Climate surveys (ICs) at the firm level, have become the standard way for the World Bank to identify key obstacles to country competitiveness, in order to prioritize policy reforms for enhancing competitiveness. Given the surveys objectives and the nature and limitations of the data collected, this paper discusses the advantages and disadvantages of using different total factor productivity (TFP) measures. The main objective is to develop a methodology to generate robust investment climate impacts (elasticities) on TFP under alternative measures. The paper applies it to the data collected for ICs in four developing countries: Costa Rica, Guatemala, Honduras and Nicaragua. Observations on logarithms of the production function variables are pooled across three countries (Guatemala, Honduras and Nicaragua). Endogeneity of the production function inputs and of the investment climate variables is addressed by using observable firm level information, a variant of the control function approach, considering IC variables as proxy and also by aggregating certain investment climate variables by industry and region. It is shown that by using this methodology it is possible to get robust IC “elasticities” on TFP for more than ten different TFP measures. The robust IC elasticity estimates for the five countries show how relevant the investment climate variables are to explain the average productivity of each country. IC variables in several categories (red tape, corruption and crime, infrastructure and, quality and innovation) account for over 30 percent of average productivity. The policy implications are clear: investment climate matters and the relative impact of the various investment climate variables helps indentifying where reform efforts should be directed in each country. It is argued that this robust methodology can be used as a benchmark to assess cross-country productivity effects in other IC surveys. This is important since similar firm-level IC surveys on several sectors (manufacturing, services, etc.) are now available at the World Bank for more than 65 developing countries.Total factor productivity measures, Investment climate, Observable fixed effects, Robust investment climate elasticities, Input-output elasticities

공정변이를 고려한 3차원 집적 회로 설계 및 패키징 기법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 김태환.As CMOS scaling down, The control of variation in chip performance (i.e. speed and power) becomes highly important to improve the chip yield. The increased variation of chip performance demands additional design efforts such as the increase of guard-band or longer design turnaround time (TAT), which cause degradation of both chip performance and economic profit. Meanwhile, through-silicon via (TSV) based 3D technology has been regarded as the promising solution for long interconnect wire and huge die size problem. Since a 3D IC is manufactured by stacking multiple dies which are fabricated in different wafers, integration of the dies that have far different process characteristic can enlarge the difference of device performance on different dies within a single chip. In this dissertation, we analyze the effect of on-package (within-chip) variation on 3D IC and presents effective methods to mitigate the onpackage variation. First, a parametric yield improvement method is presented to resolve the mismatches of dies having different process characteristic. Comprehensive 3D integration algorithms considering post-silicon tuning technique is developed for the multi-layered 3D IC. Then, we show that a careful clock edge embedding in 3D clock tree can greatly reduce the impact of on-package variation on 3D clock skew and propose a two-step solution for the problem of on-package variation-aware layer embedding in 3D clock tree synthesis. In summary, this dissertation presents effective 3D integration method and 3D clock tree synthesis algorithm for process-variation tolerant 3D IC designs.Abstract i Contents ii List of Figures iv List of Tables vii 1 Introduction 1 1.1 Process Variation in 3D ICs . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Contributions of This Dissertation . . . . . . . . . . . . . . . . . . . 6 2 Post-silicon Tuning Aware Die/WaferMatching Algorithms for Enhancing Parametric Yield of 3D IC Design 7 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.3 The Die-to-Die Matching Problem and Proposed Algorithm Considering Body Biasing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3.1 Motivation and Problem Definition . . . . . . . . . . . . . . 13 2.3.2 The Proposed Die-to-Die Matching Algorithm . . . . . . . . 15 2.4 TheWafer-to-Wafer Matching Problem and Proposed Algorithm Considering Body Biasing . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.4.1 Problem Definition and The Proposed Wafer-to-Wafer Matching Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.5 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3 Edge Layer Embedding Algorithm for Mitigating On-Package Variation in 3D Clock Tree Synthesis 32 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.2 Problem Definitions and Motivation . . . . . . . . . . . . . . . . . . 35 3.3 The Proposed Algorithm for On-Package Variation Aware Edge Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 3.3.1 Algorithm for Maximizing Layer Sharing of Edges . . . . . . 39 3.3.2 Refinement: Partial Edge Embedding on Layers . . . . . . . . 47 3.3.3 Clock Tree Routing and Buffer Insertion . . . . . . . . . . . . 49 3.4 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 52 3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4 Conclusion 64 4.1 Chapter 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 4.2 Chapter 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Abstract in Korean 72Docto

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care

Robust methodology for investment climate assessment on productivity: application to investment climate surveys from Central America

Developing countries are increasingly concerned about improving country competitiveness and productivity, as they face the increasing pressures of globalization and attempt to improve economic growth and reduce poverty. Among such countries, Investment Climate Assessments (ICA) surveys at the firm level, have become the standard way for the World Bank to identify key obstacles to country competitiveness, in order to prioritize policy reforms for enhancing competitiveness. Given the surveys objectives and the nature and limitations of the data collected, this paper discusses the advantages and disadvantages of using different productivity measures. The main objective is to develop a methodology to estimate, in a consistent manner, the productivity impact of the investment climate variables. The paper applies it to the data collected for ICAs in four countries: Costa Rica, Guatemala, Honduras and Nicaragua. Observations on logarithms (logs) of the variables are pooled across three countries (Guatemala, Honduras and Nicaragua). Endogeneity of the production function inputs and of the investment climate variables is addressed by using a variant of the control function approach, based on individual firm information, and by aggregating investment climate variables by industry and region. It is shown that it is possible to get robust results for 10 different productivity measures. The estimates for the four countries show how relevant the investment climate variables are to explain the average level of productivity. IC variables in several categories (red tape, corruption and crime, infrastructure and, quality and innovation) account for over 30 percent of average productivity. The policy implications are clear: investment climate matters and the relative impact of the various investment climate variables indicate where reform efforts should be directed in each country. It is argued that this methodology can be used as a benchmark to assess productivity effects in other ICA surveys. This is important because ICA surveys are available now for more than 65 developing countries

Energy Efficiency

Energy efficiency is finally a common sense term. Nowadays almost everyone knows that using energy more efficiently saves money, reduces the emissions of greenhouse gasses and lowers dependence on imported fossil fuels. We are living in a fossil age at the peak of its strength. Competition for securing resources for fuelling economic development is increasing, price of fuels will increase while availability of would gradually decline. Small nations will be first to suffer if caught unprepared in the midst of the struggle for resources among the large players. Here it is where energy efficiency has a potential to lead toward the natural next step - transition away from imported fossil fuels! Someone said that the only thing more harmful then fossil fuel is fossilized thinking. It is our sincere hope that some of chapters in this book will influence you to take a fresh look at the transition to low carbon economy and the role that energy efficiency can play in that process

Hardware Attacks and Mitigation Techniques

Today, electronic devices have been widely deployed in our daily lives, basic infrastructure such as financial and communication systems, and military systems. Over the past decade, there have been a growing number of threats against them, posing great danger on these systems. Hardware-based countermeasures offer a low-performance overhead for building secure systems. In this work, we investigate what hardware-based attacks are possible against modern computers and electronic devices. We then explore several design and verification techniques to enhance hardware security with primary focus on two areas: hardware Trojans and side-channel attacks. Hardware Trojans are malicious modifications to the original integrated circuits (ICs). Due to the trend of outsourcing designs to foundries overseas, the threat of hardware Trojans is increasing. Researchers have proposed numerous detection methods, which either take place at test-time or monitor the IC for unexpected behavior at run-time. Most of these methods require the possession of a Trojan-free IC, which is hard to obtain. In this work, we propose an innovative way to detect Trojans using reverse-engineering. Our method eliminates the need for a Trojan-free IC. In addition, it avoids the costly and error-prone steps in the reverse-engineering process and achieves significantly good detection accuracy. We also notice that in the current literature, very little effort has been made to design-time strategies that help to make test-time or run-time detection of Trojans easier. To address this issue, we develop techniques that can improve the sensitivity of designs to test-time detection approaches. Experiments show that using our method, we could detect a lot more Trojans with very small power/area overhead and no timing violations. Side-channel attack (SCA) is another form of hardware attack in which the adversary measures some side-channel information such as power, temperature, timing, etc. and deduces some critical information about the underlying system. We first investigate countermeasures for timing SCAs on cache. These attacks have been demonstrated to be able to successfully break many widely-used modern ciphers. Existing hardware countermeasures usually have heavy performance overhead. We innovatively apply 3D integration techniques to solve the problem. We investigate the implication of 3D integration on timing SCAs on cache and propose several countermeasures that utilize 3D integration techniques. Experimental results show that our countermeasures increase system security significantly while still achieving some performance gain over a 2D baseline system. We also investigate the security of Oblivious RAM (ORAM), which is a newly proposed hardware primitive to hide memory access patterns. We demonstrate both through simulations and on FPGA board that timing SCAs can break many ORAM protocols. Some general guidelines in secure ORAM implementations are also provided. We hope that our findings will motivate a new line of research in making ORAMs more secure