3,368 research outputs found

    A clinical decision support system for detecting and mitigating potentially inappropriate medications

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    Background: Medication errors are a leading cause of preventable harm to patients. In older adults, the impact of ageing on the therapeutic effectiveness and safety of drugs is a significant concern, especially for those over 65. Consequently, certain medications called Potentially Inappropriate Medications (PIMs) can be dangerous in the elderly and should be avoided. Tackling PIMs by health professionals and patients can be time-consuming and error-prone, as the criteria underlying the definition of PIMs are complex and subject to frequent updates. Moreover, the criteria are not available in a representation that health systems can interpret and reason with directly. Objectives: This thesis aims to demonstrate the feasibility of using an ontology/rule-based approach in a clinical knowledge base to identify potentially inappropriate medication(PIM). In addition, how constraint solvers can be used effectively to suggest alternative medications and administration schedules to solve or minimise PIM undesirable side effects. Methodology: To address these objectives, we propose a novel integrated approach using formal rules to represent the PIMs criteria and inference engines to perform the reasoning presented in the context of a Clinical Decision Support System (CDSS). The approach aims to detect, solve, or minimise undesirable side-effects of PIMs through an ontology (knowledge base) and inference engines incorporating multiple reasoning approaches. Contributions: The main contribution lies in the framework to formalise PIMs, including the steps required to define guideline requisites to create inference rules to detect and propose alternative drugs to inappropriate medications. No formalisation of the selected guideline (Beers Criteria) can be found in the literature, and hence, this thesis provides a novel ontology for it. Moreover, our process of minimising undesirable side effects offers a novel approach that enhances and optimises the drug rescheduling process, providing a more accurate way to minimise the effect of drug interactions in clinical practice

    Effective player guidance in logic puzzles

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    Pen & paper puzzle games are an extremely popular pastime, often enjoyed by demographics normally not considered to be ‘gamers’. They are increasingly used as ‘serious games’ and there has been extensive research into computationally generating and efficiently solving them. However, there have been few academic studies that have focused on the players themselves. Presenting an appropriate level of challenge to a player is essential for both player enjoyment and engagement. Providing appropriate assistance is an essential mechanic for making a game accessible to a variety of players. In this thesis, we investigate how players solve Progressive Pen & Paper Puzzle Games (PPPPs) and how to provide meaningful assistance that allows players to recover from being stuck, while not reducing the challenge to trivial levels. This thesis begins with a qualitative in-person study of Sudoku solving. This study demonstrates that, in contrast to all existing assumptions used to model players, players were unsystematic, idiosyncratic and error-prone. We then designed an entirely new approach to providing assistance in PPPPs, which guides players towards easier deductions rather than, as current systems do, completing the next cell for them. We implemented a novel hint system using our design, with the assessment of the challenge being done using Minimal Unsatisfiable Sets (MUSs). We conducted four studies, using two different PPPPs, that evaluated the efficacy of the novel hint system compared to the current hint approach. The studies demonstrated that our novel hint system was as helpful as the existing system while also improving the player experience and feeling less like cheating. Players also chose to use our novel hint system significantly more often. We have provided a new approach to providing assistance to PPPP players and demonstrated that players prefer it over existing approaches

    Supporting the executability of R markdown files

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    R Markdown files are examples of literate programming documents that combine R code with results and explanations. Such dynamic documents are designed to execute easily and reproduce study results. However, little is known about the executability of R Markdown files which can cause frustration among its users who intend to reuse the document. This thesis aims to understand the executability of R Markdown files and improve the current state of supporting the executability of those files. Towards this direction, a large-scale study has been conducted on the executability of R Markdown files collected from GitHub repositories. Results from the study show that a significant number of R Markdown files (64.95%) are not executable, even after our best efforts. To better understand the challenges, the exceptions encountered while executing the files are categorized into different categories and a classifier is developed to determine which Markdown files are likely to be executable. Such a classifier can be utilized by search engines in their ranking which helps developers to find literate programming documents as learning resources. To support the executability of R Markdown files a command-line tool is developed. Such a tool can find issues in R Markdown files that prevent the executability of those files. Using an R Markdown file as an input, the tool generates an intuitive list of outputs that assist developers in identifying areas that require attention to ensure the executability of the file. The tool not only utilizes static analysis of source code but also uses a carefully crafted knowledge base of package dependencies to generate version constraints of involved packages and a Satisfiability Modulo Theories (SMT) solver (i.e., Z3) to identify compatible versions of those packages. Findings from this research can help developers reuse R Markdown files easily, thus improving the productivity of developers. [...

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Structural Parameterizations for Two Bounded Degree Problems Revisited

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    Efficient and linear static approach for finding the memory leak in C

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    Code analysis has discovered that memory leaks are common in the C programming language. In the literature, there exist various approaches for statically analyzing and detecting memory leaks. The complexity and diversity of memory leaks make it difficult to find an approach that is both effective and simple. In embedded systems, costly resources like memory become limited as the system’s size diminishes. As a result, memory must be handled effectively and efficiently too. To obtain precise analysis, we propose a novel approach that works in a phase-wise manner. Instead of examining all possible paths for finding memory leaks, we use a program slicing to check for a potential memory leak. We introduce a source-sink flow graph (SSFG) based on source-sink properties of memory allocation-deallocation within the C code. To achieve simplicity in analysis, we also reduce the complexity of analysis in linear time. In addition, we utilize a constraint solver to improve the effectiveness of our approach. To evaluate the approach, we perform manual scanning on various test cases: link list applications, Juliet test cases, and common vulnerabilities and exposures found in 2021. The results show the efficiency of the proposed approach by preparing the SSFG with linear complexity

    Control Flow Graph-based Path Reconstruction in Android applications

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    openOver the years, the field of Android security research has faced significant limitations due to the absence of reliable methods for achieving automated interaction with mobile applications. The lack of such tools has resulted in the widespread use of automatic exercising software, which randomly interfaces with apps in the hopes of obtaining desired outcomes. However, this approach cannot always be considered a satisfactory solution, as it lacks solid criteria and fails to provide any Proof-of-Reachability. In the context of my thesis, I employed Control Flow Graphs to reconstruct pathways that lead to specified target methods within Android applications. This approach allowed me to extract high-level instructions that automatic interaction software can accurately and reliably execute in order to reach a designated endpoint. Tests and evaluations conducted on this technique demonstrate its potential to facilitate more precise and goal-oriented testing. Its applications in the future could span from fuzzing and exploitation to aiding in the disclosure of privacy violations.Over the years, the field of Android security research has faced significant limitations due to the absence of reliable methods for achieving automated interaction with mobile applications. The lack of such tools has resulted in the widespread use of automatic exercising software, which randomly interfaces with apps in the hopes of obtaining desired outcomes. However, this approach cannot always be considered a satisfactory solution, as it lacks solid criteria and fails to provide any Proof-of-Reachability. In the context of my thesis, I employed Control Flow Graphs to reconstruct pathways that lead to specified target methods within Android applications. This approach allowed me to extract high-level instructions that automatic interaction software can accurately and reliably execute in order to reach a designated endpoint. Tests and evaluations conducted on this technique demonstrate its potential to facilitate more precise and goal-oriented testing. Its applications in the future could span from fuzzing and exploitation to aiding in the disclosure of privacy violations

    Static Analysis of NumPy Programs

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    NumPy programs can be hard to debug. Due to the dynamic nature of Python, a bug can manifest itself after a long time of run time. This causes the computation to crash, ditching all the progress. Existing static analysis tools can't detect NumPy-specific errors. We propose a solution that uses data-flow analysis combined with symbolic execution to detect ndarray shape mismatch errors. With a dynamic set of symbols, our method tracks ndarray dimensions and constraints between them throughout the program. It uses an SMT solver to solve the constraints and locate the bug. Our implementation understands core NumPy constructs and detects some shape mismatch errors for 1D and 2D ndarrays.NumPy programy se těžko ladí. Kvůli dynamické povaze Pythonu se chyba často projeví až poté, co program delší dobu běží. Výpočet poté spadne a všechen výpočet je ztracen. Existující nástroje statické analýzy nedokážou poznat chyby specifické pro NumPy. Použili jsme data-flow analýzu zkombi- novanou se symbolickým vykonáváním programu k detekování chyb plynoucí z nevyhovujících tvarů matic. Naše metoda pomocí dynamické množiny sym- bolů sleduje ve vstupním program rozměry matic a vztahy mezi nimi. Ná- sledně pomocí SMT vyhodnotí, jestli jsou vztahy splnitelné, nebo jestli došlo k chybě a kde. Naše implementace rozumí základním NumPy konstrukcím a detekuje některé chyby pro pole a matice.Department of Distributed and Dependable SystemsKatedra distribuovaných a spolehlivých systémůFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult

    Certificates for decision problems in temporal logic using context-based tableaux and sequent calculi.

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    115 p.Esta tesis trata de resolver problemas de Satisfactibilidad y Model Checking, aportando certificados del resultado. En ella, se trabaja con tres lógicas temporales: Propositional Linear Temporal Logic (PLTL), Computation Tree Logic (CTL) y Extended Computation Tree Logic (ECTL). Primero se presenta el trabajo realizado sobre Certified Satisfiability. Ahí se muestra una adaptación del ya existente método dual de tableaux y secuentes basados en contexto para satisfactibilidad de fórmulas PLTL en Negation Normal Form. Se ha trabajado la generación de certificados en el caso en el que las fórmulas son insactisfactibles. Por último, se aporta una prueba de soundness del método. Segundo, se ha optimizado con Sat Solvers el método de Certified Satisfiability para el contexto de Certified Model Checking. Se aportan varios ejemplos de sistemas y propiedades. Tercero, se ha creado un nuevo método dual de tableaux y secuentes basados en contexto para realizar Certified Satisfiability para fórmulas CTL yECTL. Se presenta el método y un algoritmo que genera tanto el modelo en el caso de que las fórmulas son satisfactibles como la prueba en el caso en que no lo sean. Por último, se presenta una implementación del método para CTL y una experimentación comparando el método propuesto con otro método de similares características

    zk-Sherlock: Exposing Hardware Trojans in Zero-Knowledge

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    As integrated circuit (IC) design and manufacturing have become highly globalized, hardware security risks become more prominent as malicious parties can exploit multiple stages of the supply chain for profit. Two potential targets in this chain are third-party intellectual property (3PIP) vendors and their customers. Untrusted parties can insert hardware Trojans into 3PIP circuit designs that can both alter device functionalities when triggered or create a side channel to leak sensitive information such as cryptographic keys. To mitigate this risk, the absence of Trojans in 3PIP designs should be verified before integration, imposing a major challenge for vendors who have to argue their IPs are safe to use, while also maintaining the privacy of their designs before ownership is transferred. To achieve this goal, in this work we employ modern cryptographic protocols for zero-knowledge proofs and enable 3PIP vendors prove an IP design is free of Trojan triggers without disclosing the corresponding netlist. Our approach uses a specialized circuit compiler that transforms arbitrary netlists into a zero-knowledge-friendly format, and introduces a versatile Trojan detection module that maintains the privacy of the actual netlist. We evaluate the effectiveness of our methodology using selected benchmarks
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