346 research outputs found

    Evaluation Methodologies in Software Protection Research

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    Man-at-the-end (MATE) attackers have full control over the system on which the attacked software runs, and try to break the confidentiality or integrity of assets embedded in the software. Both companies and malware authors want to prevent such attacks. This has driven an arms race between attackers and defenders, resulting in a plethora of different protection and analysis methods. However, it remains difficult to measure the strength of protections because MATE attackers can reach their goals in many different ways and a universally accepted evaluation methodology does not exist. This survey systematically reviews the evaluation methodologies of papers on obfuscation, a major class of protections against MATE attacks. For 572 papers, we collected 113 aspects of their evaluation methodologies, ranging from sample set types and sizes, over sample treatment, to performed measurements. We provide detailed insights into how the academic state of the art evaluates both the protections and analyses thereon. In summary, there is a clear need for better evaluation methodologies. We identify nine challenges for software protection evaluations, which represent threats to the validity, reproducibility, and interpretation of research results in the context of MATE attacks

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling

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    In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the forefront. Nevertheless, the recent pandemic, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects. There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the COVID-19 pandemic has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects

    Occupant-Centric Simulation-Aided Building Design Theory, Application, and Case Studies

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    This book promotes occupants as a focal point for the design process

    Pushing the Boundaries of Spacecraft Autonomy and Resilience with a Custom Software Framework and Onboard Digital Twin

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    This research addresses the high CubeSat mission failure rates caused by inadequate software and overreliance on ground control. By applying a reliable design methodology to flight software development and developing an onboard digital twin platform with fault prediction capabilities, this study provides a solution to increase satellite resilience and autonomy, thus reducing the risk of mission failure. These findings have implications for spacecraft of all sizes, paving the way for more resilient space missions

    Specificity of the innate immune responses to different classes of non-tuberculous mycobacteria

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    Mycobacterium avium is the most common nontuberculous mycobacterium (NTM) species causing infectious disease. Here, we characterized a M. avium infection model in zebrafish larvae, and compared it to M. marinum infection, a model of tuberculosis. M. avium bacteria are efficiently phagocytosed and frequently induce granuloma-like structures in zebrafish larvae. Although macrophages can respond to both mycobacterial infections, their migration speed is faster in infections caused by M. marinum. Tlr2 is conservatively involved in most aspects of the defense against both mycobacterial infections. However, Tlr2 has a function in the migration speed of macrophages and neutrophils to infection sites with M. marinum that is not observed with M. avium. Using RNAseq analysis, we found a distinct transcriptome response in cytokine-cytokine receptor interaction for M. avium and M. marinum infection. In addition, we found differences in gene expression in metabolic pathways, phagosome formation, matrix remodeling, and apoptosis in response to these mycobacterial infections. In conclusion, we characterized a new M. avium infection model in zebrafish that can be further used in studying pathological mechanisms for NTM-caused diseases

    Exploration of Nurses\u27 Knowledge About Healthcare for Transgender Patients

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    AbstractThe transgender population is growing, and along with the population growth, the healthcare needs for gender transitioning of both medical and surgical procedures. Registered nurses (RNs) who care for hospitalized transgender patients are required to be knowledgeable about their care, yet little is known about what nurses know about the healthcare of the transgender patient. The purpose of this basic qualitative study, guided by Benner’s novice to expert theory, was to explore the knowledge and perceptions of RNs regarding healthcare of transgender persons undergoing transition to the opposite gender. Social media and snowball sampling were used to recruit 10 RNs from medical surgical settings in the southwestern United States. Participants were interviewed using semi structured and open-ended questions with interviews continuing until saturation was achieved. Transcribed interview data were analyzed using manual coding following Saldana’s method to identify codes, categories, and themes. Two themes were identified: attitude and knowledge. Attitudes were overall positive toward transitioning adults however participant knowledge was limited on specifics related to care of a transitioning adult patient. Social change is possible if nurse educators include programs of study on care of the transitioning transgender population. Recommendations for future research include interventional studies providing education and testing of nurses who care for patients who are undergoing transitioning

    Investigating the effects of non-insecticide pesticides widely used in Irish agriculture on the bumblebee Bombus terrestris (L. 1758)

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    Although pesticides are a key driver of bee decline globally, the contribution of non-insecticidal pesticides, specifically herbicides and fungicides, is poorly understood. The herbicide glyphosate and the fungicide prothioconazole are amongst the most widely used pesticides in Ireland. Consequently, characterising their impact on Ireland’s wild bee species is of urgent importance. Here, I investigated and characterised the impact of glyphosate and prothioconazole on the bumblebee B. terrestris at the molecular and organism level, in addition to two representative commercial formulations: Roundup Optima+® and Proline®, containing glyphosate and prothioconazole, respectively. Utilising mass spectrometry-based proteomics, DNA amplicon sequencing, and survival assays, I uncovered the impact of these pesticides and formulations on the digestive tract, brain, and fat body proteome, digestive tract microbiota, survival, behaviour, and food consumption in B. terrestris. Neither pesticide altered survival or food consumption, but prothioconazole altered behaviour at field-realistic concentrations. Further, all treatments led to microbiota dysbiosis. Glyphosate and Roundup Optima+® consistently altered oxidative stress regulation and mitochondrial proteins in all organs and led to decreases in structural proteins in the digestive tract. Both glyphosate-based treatments altered synaptic transmission and signaling in the brain, and protein biosynthesis and energy homeostasis in the fat body. However, differential impacts were also observed. Further, prothioconazole and Proline® had differential impacts on all key organs, indicating the impact of co-formulants in formulations and solvents used for pesticide solubility on bees, leading to significant alterations to detoxification, neurotransmitter biosynthesis and cytoskeletal proteins, and oxidative stress in the digestive tract, brain, and fat body, respectively. Overall, this research uncovered the impacts of glyphosate and prothioconazole, as well as representative formulations, on B. terrestris, and raised important questions on the complexities of pesticide impacts on bees when used as part of a formulation

    WiFi-Based Human Activity Recognition Using Attention-Based BiLSTM

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    Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the proposed models outperform state-of-the-art models. Also, the experiments show that the proposed models can be applied to other environments with different configurations, albeit with some caveats. The proposed ABiLSTM model achieves an overall accuracy of 94.03%, 91.96%, and 92.59% across the 3 target environments. While the proposed CNN-ABiLSTM model reaches an accuracy of 98.54%, 94.25% and 95.09% across those same environments
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