Miracle-dz/UniFAR-FTUs huggingface dataset:
Ripple: Reflection analysis for Android apps in incomplete information environments

Reflection poses grave problems for static security analysis, despite its widespread use in Android apps. In general, string inference has been mainly used to handle reflection, resulting in significantly missed security vulnerabilities. In this work, we bring forward the ubiquity of incomplete information environments (IIEs) for Android apps, where some critical dataflows are missing during static analysis and the need for resolving reflective calls under IIEs. We present Ripple, the first IIE‐aware static reflection analysis for Android apps that resolves reflective calls more soundly than string inference. Validation with 17 popular Android apps from Google Play demonstrates the effectiveness of Ripple in discovering reflective targets with a low false positive rate (due to its trade‐off made among soundness, precision, and scalability). As a result, Ripple enables FlowDroid, a taint analysis for Android apps, to find hundreds of sensitive data leakages that would otherwise be missed. As a fundamental analysis, Ripple will be valuable for many security analysis clients, since more program behaviors can now be analyzed under IIEs.
W-Band GaN Receiver Components Utilizing Highly Scaled, Next Generation GaN Device Technology

We report the first W-band GaN receiver components using a next generation, highly scaled GaN device technology. This technology (40nm, fT= 220 GHz, fmax= 400 GHz, Vbrk > 40V) enables receiver components that meet or exceed performance reported by competing device technologies while maintaining > 5x higher breakdown voltage, higher linearity, dynamic range and RF survivability. This paper includes results for a 4 and a 5 stage low noise amplifier (LNA) (gain over 5 dB/stage at 110 GHz), a single-pole single-throw (SPST) and a single-pole double-throw (SPDT) switch with loss of 0.9 dB and 1.3 dB respectively and a reflective type phase shifter
Additive Partitioning of Species Diversity across Multiple Spatial Scales: Implications for Regional Conservation of Biodiversity

Abstract: Ecologists and conservation biologists are keenly interested in how patterns of species diversity change across spatial scales. We examined how additive partitioning can be used to statistically evaluate spatial patterns of species diversity and develop conservation strategies. We applied additive partitioning to data on arboreal beetle diversity ( richness, Shannon, Simpson ) collected from a nested design consisting of four hierarchical levels—trees, forest stands, sites, and ecoregions—that corresponded to increasingly broader spatial scales within the eastern deciduous forest of Ohio and Indiana ( U.S.A. ). A significant percentage ( relative to that of randomization tests ) of total species richness and Shannon and Simpson diversity was attributed to beta diversity between ecoregions and, to a lesser extent, among sites ( parks and nature preserves ) within ecoregions. Hierarchical cluster analysis corroborated these findings. We also found differences between rare species (<0.05% of total abundance ) and common species ( >0.5% of total abundance ) in the overall percentage of richness explained by each spatial scale. Rare species accounted for the majority ( 45% ) of the 583 total beetle species in our study and were strongly influenced by broad spatial scales ( i.e., ecoregions ), whereas the richness of common species was significantly greater than expected across the range of spatial scales ( from trees to ecoregions ). Our results suggest that the most effective way to preserve beetle diversity in the eastern deciduous forest of the United States is to acquire and protect multiple sites within different ecoregions. More generally, we advocate the use of diversity partitioning because it complements existing models in conservation biology and provides a unique approach to understanding species diversity across spatial scales.
Reviewing Pakistan’s Import Demand Function: A Time-Series Analysis, 1970–2010

This paper investigates the conventional import demand function for Pakistan using time-series data sourced from the World Development Indicators for the period 1970 to 2010. Using a vector error correction model and impulse response functions, we show that, for the given period, relative prices and income lose their significance as long-run determinants of import demand. This indicates the need for additional determinants. We compare the residuals of the conventional import demand function with those of a model that includes the terms of trade and foreign exchange availability (in addition to the conventional parameters) as determinants of import demand, and find that the latter largely resolves much of what is nondeterministic in the former model. The paper also explores the peculiar trend of a falling imports-to-GDP ratio (from the 1980s to the 2000s), which is unusual for a developing country. In a subsidiary regression analysis for this period, we argue that falling net capital inflows explain this persistent fall in the imports-to-GDP ratio. The recovery thereafter, when Pakistan started catching up with other developing economies, may have been responsible for the 2008 balance-of-payments crisis.
Production and Technical Efficiency on Australian Dairy Farms

The dairy industry plays an important role in both Australia and the world dairy market. Domestically, it is one of the most important agricultural industries, valued at $A3.7 billion a year. Internationally, the industry exports more than $A3 billion a year, making Australia the third largest dairy exporter in the world. Using traditional farm survey input and output data and a unique biannual data set on farm technology use, this paper estimates a stochastic production frontier and technical efficiency model for Australian dairy farms, determining the relative importance of each input in dairy production, the quantitative effects of key technology variables on farm efficiency and overall farm profiles based on the efficiency rankings of dairy producers. Estimated results show that production exhibits constant returns to scale and although feed concentration and the number of cows milked at peak season matter, the key determinants of differences in dairy farm efficiency are the type of dairy shed used and the proportion of irrigated farm area. Overall farm profiles also indicate that those in the high efficiency group employ either rotary or swingover dairy shed technology and have (by far) the largest proportion of land under irrigation.
Improving robustness of real-time geo-registration process

In this paper, a modified correspondence matching method is proposed for geo-registration system that enables parallelism and image update detection. The image to be geo-referenced is divided into blocks which can be processed in parallel. A voting process is performed on the correlation measures obtained from different blocks to determine the match point. An image update detection method is also presented, which uses the correlation data from the proposed block based matching method to determine which parts of the image have been updated or changed with respect to an existing reference image. The experimental results to evaluate the proposed methods are presented. The proposed method gives better matching scores compared to the conventional correlation approach.
A powered ankle-foot orthoses for ankle rehabilitation

Ankle rehabilitation training becomes a tough question for the patients with ankle joint injuries especially with the hemiplegia after stroke. Here a novel powered ankle-foot orthoses which can provide ankle dorsiflexion and plantar flexion assistant using electric motor is proposed in this paper. The mechanical structure of the orthoses including wearing parts, ankle joint hinged part, driving unit, transmission mechanism and sensing units is mainly described. In order to obtain the ankle's moment-angle relationship, the dynamics model of the ankle-foot is established. In addition, for the motor control of ankle-foot orthoses, motion path is planned based on the human walking gait and the simulation. This study provides a new method for ankle-foot orthoses design and has great significance for ankle rehabilitation.
Evaluation of Possibilities of Climate Stabilization Policy considering Different Discount Rates: Simulation Analysis using the Modified RICE Model

This study is intended to show, using simulation analyses, the validity of using a discount rate for changing combinations of the pure rate of time preference and the elasticity of marginal utility of consumption. Furthermore, this study explores climate stabilization policies, both global and Japanese, and suggests Japan's correct action based on those results. In Japan, interpretations of reducing 50% of CO2 emissions by 2055 as a baseline of the BASE case, and reductions or emissions to 1995 emission levels differ greatly. In the scenarios assumed for this study, although the former reduction is infeasible, the latter is feasible but costly.
When and Why Did Brains Break Symmetry?

Asymmetry of brain function is known to be widespread amongst vertebrates, and it seems to have appeared very early in their evolution. In fact, recent evidence of functional asymmetry in invertebrates suggests that even small brains benefit from the allocation of different functions to the left and right sides. This paper discusses the differing functions of the left and right sides of the brain, including the roles of the left and right antennae of bees (several species) in both short- and long-term recall of olfactory memories and in social behaviour. It considers the likely advantages of functional asymmetry in small and large brains and whether functional asymmetry in vertebrates and invertebrates is analogous or homologous. Neural or cognitive capacity can be enhanced both by the evolution of a larger brain and by lateralization of brain function: a possible reason why both processes occur side-by-side is offered.
Shape Modeling with Sketched Feature Lines in Immersive 3D Environments

In this paper we address the question whether automatic shape creation using sketched strokes as input in an immersive 3D environment supports the sketching process in early phases of product design. To investigate this question, model creation and deformation algorithms of the desktop sketch-based modeling tool FiberMesh [NISA07] were transferred to an immersive 3D environment. A comparative user study was conducted among twelve design students and professional designers. Line-based sketching in a 3D environment and sketch-based modeling, both in a 3D and 2D environment were compared. The analysis of the study yielded few differences between the conditions, but two findings were made: usability for a creative sketching task was perceived higher for line-based sketching than for sketch-based modeling - both in an immersive 3D environment. Shape modeling in immersive 3D environments was perceived as more stimulating and attractive than under 2D conditions.
A Coherent Signature of Anthropogenic Nitrogen Deposition to Remote Watersheds of the Northern Hemisphere

Deposition of reactive nitrogen from human activities occurred in the preindustrial era. Humans have more than doubled the amount of reactive nitrogen (Nr) added to the biosphere, yet most of what is known about its accumulation and ecological effects is derived from studies of heavily populated regions. Nitrogen (N) stable isotope ratios (15N:14N) in dated sediments from 25 remote Northern Hemisphere lakes show a coherent signal of an isotopically distinct source of N to ecosystems beginning in 1895 ± 10 years (±1 standard deviation). Initial shifts in N isotope composition recorded in lake sediments coincide with anthropogenic CO2 emissions but accelerate with widespread industrial Nr production during the past half century. Although current atmospheric Nr deposition rates in remote regions are relatively low, anthropogenic N has probably influenced watershed N budgets across the Northern Hemisphere for over a century.
On Combinational Redundancy and Identification of Undetectable Faults in Synchronous Sequential Circuits

Several theorems exist that allow the identification of undetectable faults in synchronous sequential circuits by applying combinational ATPG to an iterative logic array of limited length. In this paper, we consider the theorem that resulted in one of the most effective procedures for identifying undetectable faults. We show conditions on fault free sequential circuits under which the only undetectable faults that can be identified by this theorem using an iterative logic array of any length are combinationally redundant faults. Such faults can be identified using an iterative logic array of length one, or techniques specifically developed for combinationally redundant faults. Whereas for a general circuit, increasing the length of the iterative logic array may help identify additional undetectable faults, this is not the case for circuits with the properties identified here. We demonstrate the existence of benchmark circuits that satisfy these conditions.
Multimedia mapping using continuous state space models

In this paper, a system that transforms speech waveforms to animated faces are proposed. The system relies on a state space model to perform the mapping. To create a photo realistic image, an active appearance model is used. The main contribution of the paper is to compare a Kalman filter and a hidden Markov model approach to the mapping. It is shown that even though the HMM can get a higher test likelihood than the Kalman filter, it is much easier to train and the animation quality is better for the Kalman filter.
Cross-Layer Data-Centric Usage Control

Usage control (UC) specifies what happens to data after access to it has been granted. Within the system, data (e.g. “a picture”) exists in form of various representations, possibly located at different levels of abstraction (e.g. a file, a set of pixels or a Java object). To control data, one must control the usage of all its different representations.This work (1) presents a generic UC model and a policy specification language that capture the distinction between data and representations of data and (2) discusses how to improve the model’s precision leveraging additional information about the system.
Two-Player Kidney Exchange Game

Kidney exchange programs have been set in several countries within national, regional or hospital frameworks, to increase the possibility of kidney patients being transplanted. For the case of hospital programs, it has been claimed that hospitals would benefit if they collaborated with each other, sharing their internal pools and allowing transplants involving patients of different hospitals. This claim led to the study of multi-hospital exchange markets. We propose a novel direction in this setting by modeling the exchange market as an integer programming game. The analysis of the strategic behavior of the entities participating in the kidney exchange game allowed us to prove that the most rational game outcome maximizes the social welfare and that it can be computed in polynomial time.
Blind Super-Resolution Image Reconstruction using a Maximum a Posteriori Estimation

This paper proposes a new algorithm to address blind image super-resolution by fusing multiple blurred low-resolution (LR) images to render a high-resolution (HR) image. Conventional super-resolution (SR) image reconstruction algorithms assume either the blurring during the image formation process is negligible or the blurring function is known a priori. This assumption, however, is impractical as it is difficult to eliminate blurring completely in some applications or characterize the blurring function fully. In view of this, we present a new maximum a posteriori (MAP) estimation framework that performs joint blur identification and HR image reconstruction. An iterative scheme based on alternating minimization is developed to estimate the blur and HR image progressively. A blur prior that incorporates the soft parametric blur information and smoothness constraint is introduced in the proposed method. Experimental results show that the new method is effective in performing blind SR image reconstruction where there is limited information about the blurring function.
Research Statement Motivation and Vision

My research interests lie in extensions of strongly-typed programming languages to support greater prescriptive and descriptive power. In doing so, I hope to improve the process of building reliable, secure, and efficient software. Why concentrate on typed programming languages? There are a number of formalisms for program verification, but type systems have been one of the most practical. The types of a programming language are an abstraction of the execution of a program written in that language, and so may describe its properties. Therefore, the type system may verify that the program is used consistently and correctly. This facility leads to more secure software because security flaws in software have often resulted from malicious users deliberately supplying arguments that do not satisfy the preconditions of an operation. For example, an intruder may supply a string argument that leads to buffer overflow in order to compromise a software system. The level of assurance about the reliability and security of a program is determined by the precision that we specify its operation. If that specification is too precise, it may restrict what programs may be verified and render the system impractical. Therefore type systems incorporate mechanisms for type abstraction in order to allow user control of the precision of the specification. Likewise, we may need to break the provided abstractions in order to verify certain operations through the use of run-time type checks. For example, if the type of an array statically records its length, but that length has been held abstract, we must check that an array access is within bounds at run time. Therefore, it is important that an expressive type system includes a facility to analyze types at run time. There is another reason to incorporate mechanisms for run-time type analysis: Modern systems are increasingly becoming more adaptive and evolutionary. These frameworks depend crucially on reflection facilities, the ability of programs to dynamically observe objects and adapt to them. Many necessary operations can be specified only in terms of abstractions of these objects (i.e. their types). For example, functions such as garbage-collector tracers, data marshalers, and structural-equality functions operate over the structure of data instead of its value. Therefore, it is important provide a firm basis for the programming languages that will be used to implement these new systems.
CpG Island Finding Using Graphical Models

CpG islands are short stretches in DNA sequence whose frequency of cytosine(C)and guanine (G) is higher than background of DNA sequence. They are around the promoter of frequently expressed genes. The conventional way to recognize CpG islands is to use the hidden Markov models (HMMs). While HMMs are known to suffer from not being able to capture long dynamic range information, they usually doesn’t provide satisfying results. In this work, we will try to find CpG islands with improved HMM systems (by means of introducing language model weights) as well as other family of graphical models: dynamic Bayesian networks (DBNs) [11] and conditional random fields (CRFs) [9]. By using different weights to different kinds of links in an HMM, we can get some improvements on the recognition. Significant improvements can be achieved by adding dependencies to the observation variables and thus change the structure of graphical models. The newly developed gene-trigram model can reduce the equal error rate by 42.3% relatively to baseline system. Unfortunately, even though CRFs show big benefit in tasks like text segmentation and part-of-speech tagging, it didn’t recognized any CpG island in our preliminary experiments.
Web Search Effectiveness : An Information Integration Perspective

Let us begin with a brief analysis of the stated topic of this workshop: user perspectives on Web search effectiveness. Clearly one of the goals of this workshop is to bring a variety of perspectives to bear on the issue of how to evaluate Web search effectiveness. This paper does not deal with the evaluation issue per se, but rather tries to locate evaluation of Web search effectiveness within the context of the user cognitive processes we are trying to support as they interact with complex, heterogeneous information sources on the Web. Rapid adoption of the Web over the past decade by both content producers and information consumers has resulted in greater volumes of content on an ever-widening array of subjects to be available to larger numbers of users. Clearly we are past the stage at which the primary challenge is being able to put the information where the public can have access to it; now the challenges include making it possible for the user to find the information she wants, and contributing to the user's ability to make sense of the information she finds. The search engine companies (Google being the most notable and successful) are working to improve the process of finding relevant information; the area that is the concern of this review has to do with what the user does with the information after it has been found, as this clearly will have an impact on whether the user deems the search effective. In particular, what are the processes involved with integrating information from a number of sources into some coherent piece of knowledge? What happens if the information from two different sources is contradictory? Which source is more reliable? How does the user know when it is appropriate to make comparisons between information gathered from more than one source? And, at the crux of the matter, are there things we as information scientists can do to make all of these processes easier and more successful for the user? We add a level of complexity to these issues by thinking about them in the context of a kind of information with which many users are unfamiliar: statistical information. The US Government offers a wide range of statistical data via the World Wide Web, but that data is often very difficult to use for the non-expert user. In many cases, the kinds of inquiries that users would like …
Fitness for change and Alberta health care organizations : a management perspective

Fitness For Change and Alberta Health Care Organizations: A Management Perspective What constitutes the definition of organizational effectiveness and the capabilities required for dealing with change among the Regional Health Authorities in Alberta was investigated. The perceptions of Regional Administrators and Medical Directors from across the province were measured in accordance to a dual methodology approach (survey plus case study interviews). The Survey of Organizational Fitness provided a means to acquire a measure of “fitness” along the key dimensions of environment; performance; capabilities and characteristics; levers for change; the capacity to change and learn; and strategic orientation in approaches to change (Theories E, EO or O). Theory E is based on the creation of economic value and Theory O on developing lasting organizational capabilities, the ideal objective is to integrate the two (Theory EO). The results indicate that although the majority of Regional Health Authorities perceive themselves as subscribing to a combined theoretical approach to change (Theory EO), those that subscribe solely to Theory E rate themselves as achieving overall higher levels of organizational effectiveness.