Miracle-dz/UniFAR-FTUs huggingface dataset:
A Probabilistic Public Key Encryption Scheme Based on Quartic Reciprocity (Draft 1.41)

Using a novel class of single bit one-way trapdoor functions we construct a theoretical probabilistic public key encryption scheme that has many interesting properties. These functions are constructed from binary quadratic forms and rational quartic reciprocity laws. They are not based on class group operations nor on universal one-way hash functions. Inverting these functions appears to be as di ﬃ cult as factoring, and other than factoring, we know of no reductions between this new number theory problem and the standard number theoretic problems used cryptographically. We are unable to ﬁnd away to construct a ciphertext without knowing the plaintext, hence this encryption scheme appears to be plaintext aware ( PA 1). By using quartic reciprocity properties there is less information leakage than with quadratic reciprocity based schemes and consequently this encryption scheme appears to be completely non-malleable as deﬁned by M. Fischlin (2005), and strongly plaintext aware ( S PA ) and secret-key aware ( S KA ) as well, as deﬁned by M. Barbosa and P. Farshim (2009). Assuming plaintext awareness ( PA 1), the di ﬃ culty of inverting our one-way trapdoor function and the hardness of certain standard number theoretic problems, then this scheme is provably secure against adaptive chosen ciphertext attacks ( IND − CCA 2). The public key is a product of two secret primes. Decryption is fast, requiring just one modular multiplication and one Jacobi symbol evaluation. The encryption step is polynomial time, but slow, and there is a great deal of message expansion. However, the encryption step is amenable to parallelization, both across bits, as well as at the level of encrypting a single bit. The encryption step is also amenable to asynchronous pre-computation. After the pre-computation step, for a t bit public key, encryption only requires three multiplications (with t + 2 c + 5 bit length numbers) per encrypted bit, where 100 ≤ c ≤ 150 is an adjustable security parameter. The computational cost to break an encrypted bit can be optionally adjusted down on a per bit basis. With no additional keys, multiple senders can individually join secret information to each encrypted bit without changing the parity of the encrypted bit. (Recovering this secret information is harder than recovering the private key.) Each sender can separately and publicly reveal their secret information without revealing the plaintext bit. The senders of the encrypted message bit can also individually authenticate they are senders without the use of a message authentication code and without revealing the plaintext bit. We are not aware of any hardware faults or other adverse events that might occur during decryption that could be exploited to break the secret key. Encryption faults can occur that could be exploited to reveal plaintext bits, however, these faults can be detected with high probability and with low computational cost.
Optical characterization of photovoltaic materials and structures for thin-film solar cells based on advanced texturization

Advanced texturization is a promising approach to increase the performance of thin-film solar cells. Currently, light trapping schemes implemented in state-of-the-art devices utilize randomly textured interfaces to increase their optical performance. Periodic gratings, however, have the potential to outperform their random counterparts and are thus of great interest for PV applications. In this work, an analysis of the optical performance of different advanced grating concepts applied to thin-film solar cells is presented. Different types of absorber materials were taken into account: amorphous and micro-crystalline silicon, crystalline silicon and Copper-Indium-Gallium-diSelenide chalcopyrite semiconductors.
Extending fairness expressibility of ECTL: a tree-style one-pass tableau approach (Extended Abstract)

Temporal logic has become essential for the specification and verification of hardware and software systems. For the specification of the reactive and distributed systems, or, most recently, autonomous systems, the modelling of the possibilities ‘branching’ into the future is essential. Among important properties of these systems, so called fairness properties are important. In the standard formalisation of fairness, operators ♦ (eventually) and (always) have been used: A♦ p – ‘p’ is true along all computation paths except possibly their finite initial interval, where ‘A’ is ‘for all paths’ quantifier, and E ♦p – ‘p’ is true along a computation path at infinitely many states, where ‘E’ stands for ‘there exists a path’ quantifier. Branching-time logics (BTL) here give us an appropriate reasoning framework, where the most used class of formalisms are ‘CTL’ (Computation Tree Logic) type logics. CTL itself requires every temporal operator to be preceded by a path quantifier, thus, cannot express fairness. ECTL (Extended CTL) [5] enables simple fairness constraints but not their boolean combinations. ECTL+ [6] further extends the expressiveness of ECTL allowing boolean combinations of temporal operators and ECTL fairness constraints (but not permitting their nesting). The logic CTL? , often considered as ‘the full branching-time logic’ overcomes these restrictions on expressing fairness. However, CTL? is extremely challenging for the application of any known technique of automated reasoning. Note that, unlike fair CTL [3] which, in tackling fairness, changes the underlying trees to those with ‘fair paths’ only, ECTL and ECTL+ do not impose these changes. From another perspective, the literature on fairness constraints, even in the linear-time setting, lacks the analysis of their formulation with the U (‘until’) operator. To the best of our knowledge, there are only a few research papers that raise or discuss the problem. For example, [10], introduces the logic LCTL, providing an extension of liveness constraints by the "until" operator. However, LCTL belongs to ‘Fair CTL-type’ logics [7]. ‘Generalised liveness assumptions, which allow to express that
What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture?

ABSTRACT Remote sensing from unmanned aircraft systems (UAS) was expected to be an important new technology to assist farmers with precision agriculture, especially crop nutrient management. There are three advantages using UAS platforms compared to manned aircraft platforms with the same sensor for precision agriculture: (1) smaller ground sample distances, (2) incident light sensors for image calibration, and (3) canopy height models created from structure-from-motion point clouds. These developments hold promise for future data products. In order to better match vendor capabilities with farmer requirements, we classify applications into three general niches: (1) scouting for problems, (2) monitoring to prevent yield losses, and (3) planning crop management operations. The three different niches have different requirements for sensor calibration and have different costs of operation. Planning crop management operations may have the most environmental and economic benefits. However, a USDA Economic Research Report showed that only about 20% of farmers in the USA have adopted variable rate applicators; so, most farmers in the USA may not have the technology to benefit from management plans. In the near-term, monitoring to prevent yield losses from weeds, insects, and diseases may provide the most economic and environmental benefits, but the costs for data acquisition need to be reduced.
Bayesian Inverse Reinforcement Learning for Expert’s Demonstrations in Multiple Dynamics

Reinforcement learning has been applied in numerous decision-making problems; however, it requires a careful specification of a reward function that represents the objective of the problem. There are many problems whose objectives are difficult to represent as a function, and thus, it is easier to give experts’ demonstrations for such problems. Inverse reinforcement learning can be applied to such problems because it helps to estimates the reward function from the expert’s demonstrations. Most of the existing inverse re-inforcement learning methods assume that an expert gives demonstrations in a fixed environment, though the expert can provide demonstrations for a specific objective in multiple environments. For instance, it is difficult to formulate a suitable reward function to represent car driving and the driver can give demonstrations under multiple situations. In such cases, it is normal to use demonstrations in multiple environments to estimate the expert’s reward. We formulated and proposed an algorithm for this problem based on Bayesian inverse reinforcement learning. Experimental results show that the proposed method quantitatively outperforms the existing methods.
Cs 260 Decision Diagram Techniques and Applications (fall 2009) List of Readings

Below you will find readings to be presented in class by the students. You must select a paper (or papers, if multiple ones are listed on the same line), then send an email to request it. If nobody else has asked for the paper(s) already, it will be assigned to you. If you like, you can propose multiple choices, in decreasing order of preference, and I will assign to you the non-yet-assigned paper(s) you prefer most. I will periodically update the list with new student-paper(s) pairings. New papers may be added as well.
Supplementary Materials for Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning

In Section 3.2. 3, we formulate the m-step back search as a Metropolis-Hasting sampler to perform sampling from p′(z|x, y), which is a smoothing of the true posterior distribution p(z|x, y) as shown in Equation 11. Intuitively, as gets smaller, the distance between two distribution p′(z|x, y) and p(z|x, y) becomes smaller as well. Accordingly, we have the following lemma proved with Equation 9 and Equation 11: Lemma 1.1. Given an small , the Kullback–Leibler divergence of p′(z|x, y) from p(z|x, y) is O( ).
Dynamic visual servoing of a small scale autonomous helicopter in uncalibrated environments

This paper presents a novel adaptive controller for image-based visual servoing of a small autonomous helicopter to cope with uncalibrated camera parameters and unknown 3-D geometry of the feature points. The controller is based on the backstepping technique but differs from the existing backstepping-based methods because the controller maps the image errors onto the actuator space via a depth-independent interaction matrix to avoid estimation the depth of the feature points. The new design method makes it possible to linearly parameterize the closed-loop dynamics by the unknown camera parameters and coordinates of the feature points in the three dimensional space so that an adaptive algorithm can be developed to estimate the unknown parameters and coordinates on-line. Two potential functions are introduced in the controller to guarantee convergence of the image errors and to avoid trivial solutions of the estimated parameters. The Lyapunov method is used to prove the asymptotic stability of the proposed controller based on the nonlinear dynamics of the helicopter. Simulations have been also conducted to demonstrate the performance of the proposed method.
The light field stereoscope

Over the last few years, virtual reality (VR) has re-emerged as a technology that is now feasible at low cost via inexpensive cellphone components. In particular, advances of high-resolution micro displays, low-latency orientation trackers, and modern GPUs facilitate immersive experiences at low cost. One of the remaining challenges to further improve visual comfort in VR experiences is the vergence-accommodation conflict inherent to all stereoscopic displays. Accurate reproduction of all depth cues is crucial for visual comfort. By combining well-known stereoscopic display principles with emerging factored light field technology, we present the first wearable VR display supporting high image resolution as well as focus cues. A light field is presented to each eye, which provides more natural viewing experiences than conventional near-eye displays. Since the eye box is just slightly larger than the pupil size, rank-1 light field factorizations are sufficient to produce correct or nearly-correct focus cues; no time-multiplexed image display or gaze tracking is required. We analyze lens distortions in 4D light field space and correct them using the afforded high-dimensional image formation. We also demonstrate significant improvements in resolution and retinal blur quality over related near-eye displays. Finally, we analyze diffraction limits of these types of displays.
Building Many-core Processor-to-dram Networks with Monolithic Cmos Silicon Photonics Silicon Photonics Is a Promising Technology for Addressing Memory Bandwidth Limitations in Future Many-core Processors. This Article First Introduces a New Monolithic Silicon-photonic Technology, Which Uses a Standa

Modern embedded, server, graphics, and network processors already include tens to hundreds of cores on a single die, and this number will continue to increase over the next decade. Corresponding increases in main memory bandwidth are also required, however, if the greater core count is to result in improved application performance. Projected enhancements of existing electrical DRAM interfaces are not expected to supply sufficient bandwidth with reasonable power consumption and packaging cost. To meet this many-core memory bandwidth challenge, we are combining monolithic CMOS silicon photonics with an optimized processor-memory network architecture. Existing approaches to on-chip photonic interconnect have required extensive process customizations, some of which are problematic for integration with many-core processors and memories. In contrast, we are developing new photonic devices that use the existing material layers and structures in a standard bulk CMOS flow. In addition to preserving the massive investment in standard fabrication technology, monolithic integration reduces the area and energy costs of interfacing electrical and optical components. Our technology supports dense wavelength-division multiplexing (DWDM) with dozens of wavelengths packed onto the same waveguide to further improve area and energy efficiency. The challenge when designing a photonic chip-level network is to turn the raw linklevel benefits of energy-efficient DWDM photonics into system-level performance improvements. Previous approaches have used photonics for intrachip circuit-switched networks with very large messages, intrachip Christopher Batten Ajay Joshi Jason Orcutt Anatol Khilo Benjamin Moss Charles W. Holzwarth Miloš A. Popović Hanqing Li Henry I. Smith Judy L. Hoyt Franz X. Kärtner Rajeev J. Ram Vladimir Stojanović Massachusetts Institute of Technology
Health Information System

More than a hundred years after its foundation, the Institute of Medicine (IOM) published a report called To err is human: building a safer health system, stating that between 44 thousand and 98 thousand patients die every year in the United States due to potentially preventable medical errors(1). With the intention of improving quality of healthcare and, as a consequence, decreasing the rates of adverse events, this report guided the implementation of electronic records and other forms of technology in Medicine(2), defining the goal of enhanced safety, effectiveness, quick access, efficiency, and equity(2). Two questions must be asked when considering this strategy: 1. Would the implementation of the electronic record be a guarantee of achieving the quality goals determined by the IOM? 2. Can one have return on investment with the implementation of the electronic record?
Research Area Markets and Politics Research Unit Market Processes and Governance Schwerpunkt Märkte Und Politik Abteilung Marktprozesse Und Steuerung Competition for Fdi with Vintage Investment and Agglomeration Advantages Competition for Fdi with Vintage Investment and Agglomeration Advantages

Countries compete for new FDI investment, whereas stocks of FDI generate agglomeration benefits and are potentially subject to extortionary taxation. We study the interaction between these aspects in a simple vintage capital framework with discrete time and infinite horizon, focussing on Markov perfect equilibrium in stationary strategies. We show that the tax revenue in the equilibrium is substantial, and higher on " old" FDI than on "new" FDI, even though countries are not allowed to use discriminatory taxation. Moreover, the agglomeration advantage is valuable, but is exploited in the short run and can be unstable over time.bei werden indirekt " alte " steuerlich höher als " neue " ausländische Direkt-investitionen belastet, obwohl den Ländern die diskriminierende Besteuerung untersagt wird. Zudem wird die Rolle von Subventionen und finanziellen Ansied-lungsanreizen behandelt. Die Möglichkeit, finanzielle Anreize für neue Investi-tionen zu geben, kann vorhandene Agglomerationsvorteile festigen, kann aber das Steueraufkommen im Gleichgewicht reduzieren.
Fusion of quickbird MS and Pan Data for urban studies

Most of the satellite sensors, presently operating in the optical domain, are providing a data set comprising multispectral images at a low spatial resolution and images at a higher spatial resolution but with a lower spectral content. The trend of satellite sensors is similar to the present situation. The idea of fusing multispectral images with a highest spatial resolution enables the creation of useful products for urban planning and management. This paper aims at evaluating two methods for construction of synthetic multispectral images having a highest spatial resolution available within the data set, in the objective of studying urban areas. The first one is derived from the ARSIS concept and the second one is based on a correlation technique. The two methods are described and tested over the urban area of Strasbourg (France). The resulting images are evaluated through visual, qualitative and quantitative criteria. Some conclusions are drawn on the difference between the two algorithms and on the benefits of their use in urban studies.
The concept of concept in ' conceptual legal information retrieval '

Many recent publications on legal information retrieval agree that traditional automated systems for this purpose do not satisfy the demands of lawyers. A multitude of suggestions have been made for improvement. Many of these suggestion have in common that legal information retrieval systems should be 'conceptual'. Roughly speaking this means that legal information retrieval systems should contain more knowledge about the law and be more 'intelligent'. Wildemast and De Mulder (1992) give an overview of attempts to build such systems. On the basis of the conclusions in that overview, in this paper we would like to give an alternative approach to legal information retrieval that has been developed by the Centre for Computers and Law at the Erasmus University in Rotterdam.
ALGORITHMIC DIFFERENTIATION

We present Zygote, an algorithmic differentiation (AD) system for the Julia language. Zygote is designed to address the needs of both the machine learning and scientific computing communities, who have historically been siloed by their very different tools. As well as fostering increased collaboration between these communities, we wish to enable differentiable programming (∂P ), in which arbitrary numerical programs can make use of gradient-based optimisation. We present and evaluate our proposed solutions to the performance/expressiveness tradeoffs in current systems, as well as our work applying AD to many common programming language features, which is applicable to work in other languages and systems.
Virtual attacks and the problem of responsibility: the case of China and Russia

Virtual attacks are forming a new threat scenario for governments and other actors of global society. The first decade of the XXI century saw an intensification of cyberattacks on government networks which could not be traced back. However, due to political circumstances there were often actors suspected of being involved in cyberattacks. This case study is analyzing the methods and reasons of potential attackers in Russia and China which between 2004 and 2009 appeared in several cyber threat scenarios.
ICT and productivity in Europe and the United States

The surge in labour productivity growth in the United States in the late 1990s has prompted much speculation about the capacity of Information and Communication Technologies (ICT) to structurally increase growth. The simultaneous slowdown in productivity growth in the EU suggests the European countries are falling behind. In this paper we will analyse labour productivity growth in 51 industries in Europe and the United States. Using shift-share techniques we identify the industries in which the U.S. has gained a lead and the underlying reasons for this. The results show that the U.S. has grown faster than the EU because of a larger ICT producing sector and faster growth in services industries that make intensive use of ICT. Lagging growth in Europe is concentrated in wholesale and retail trade and the securities industry.
Variational Autoencoder Modular Bayesian Networks (VAMBN) for Simulation of Heterogeneous Clinical Study Data

In the area of Big Data one of the major obstacles for the progress of biomedical research is the existence of data “silos”, because legal and ethical constraints often do not allow for sharing sensitive patient data from clinical studies across institutions. While federated machine learning now allows for building models from scattered data, there is still the need to investigate, mine and understand clinical data that cannot be accessed directly. Simulation of sufficiently realistic virtual patients could be a way to fill this gap. In this work we propose a new machine learning approach (VAMBN) to learn a generative model of longitudinal clinical study data. VAMBN considers typical key aspects of such data, namely limited sample size coupled with comparable many variables of different numerical scales and statistical properties, and many missing values. We show that with VAMBN we can simulate virtual patients in a sufficiently realistic manner while making theoretical guarantees on data privacy. In addition, VAMBN allows for simulating counterfactual scenarios. Hence, VAMBN could facilitate data sharing as well as design of clinical trials.
Comparison Betweeu Sparsely Distributed Memory and Hopfield-type Neural Network Models

The Sparsely Distributed Memory (SDM) model (Kanerva, 1984) is compared to Hopfield-type neural-network models. A mathematical framework for comparing the two is developed, and the capacity of each model is investigated. The capacity of the SDM can be increased independently of the dimension of the stored vectors, whereas the Hopfield capacity is limited to a fraction of this dimension. However, the total number of stored bits per matrix element is the same in the two models, as well as for extended models with higher order interactions. The models are also compared in their ability to store sequences of patterns. The SDM is extended to include time delays so that contextual information can be used to recover sequences. Finally, it is shown how a generalization of the SDM allows storage of correlated input pattern vectors. 1 .