8,154 research outputs found
Evaluation Methodologies in Software Protection Research
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
Using machine learning to predict pathogenicity of genomic variants throughout the human genome
GeschĂ€tzt mehr als 6.000 Erkrankungen werden durch VerĂ€nderungen im Genom verursacht. Ursachen gibt es viele: Eine genomische Variante kann die Translation eines Proteins stoppen, die Genregulation stören oder das SpleiĂen der mRNA in eine andere Isoform begĂŒnstigen. All diese Prozesse mĂŒssen ĂŒberprĂŒft werden, um die zum beschriebenen PhĂ€notyp passende Variante zu ermitteln. Eine Automatisierung dieses Prozesses sind Varianteneffektmodelle. Mittels maschinellem Lernen und Annotationen aus verschiedenen Quellen bewerten diese Modelle genomische Varianten hinsichtlich ihrer PathogenitĂ€t.
Die Entwicklung eines Varianteneffektmodells erfordert eine Reihe von Schritten: Annotation der Trainingsdaten, Auswahl von Features, Training verschiedener Modelle und Selektion eines Modells. Hier prĂ€sentiere ich ein allgemeines Workflow dieses Prozesses. Dieses ermöglicht es den Prozess zu konfigurieren, Modellmerkmale zu bearbeiten, und verschiedene Annotationen zu testen. Der Workflow umfasst auĂerdem die Optimierung von Hyperparametern, Validierung und letztlich die Anwendung des Modells durch genomweites Berechnen von Varianten-Scores.
Der Workflow wird in der Entwicklung von Combined Annotation Dependent Depletion (CADD), einem Varianteneffektmodell zur genomweiten Bewertung von SNVs und InDels, verwendet. Durch Etablierung des ersten Varianteneffektmodells fĂŒr das humane Referenzgenome GRCh38 demonstriere ich die gewonnenen Möglichkeiten Annotationen aufzugreifen und neue Modelle zu trainieren. AuĂerdem zeige ich, wie Deep-Learning-Scores als Feature in einem CADD-Modell die Vorhersage von RNA-SpleiĂing verbessern. AuĂerdem werden Varianteneffektmodelle aufgrund eines neuen, auf AllelhĂ€ufigkeit basierten, Trainingsdatensatz entwickelt.
Diese Ergebnisse zeigen, dass der entwickelte Workflow eine skalierbare und flexible Möglichkeit ist, um Varianteneffektmodelle zu entwickeln. Alle entstandenen Scores sind unter cadd.gs.washington.edu und cadd.bihealth.org frei verfĂŒgbar.More than 6,000 diseases are estimated to be caused by genomic variants. This can happen in many possible ways: a variant may stop the translation of a protein, interfere with gene regulation, or alter splicing of the transcribed mRNA into an unwanted isoform. It is necessary to investigate all of these processes in order to evaluate which variant may be causal for the deleterious phenotype. A great help in this regard are variant effect scores. Implemented as machine learning classifiers, they integrate annotations from different resources to rank genomic variants in terms of pathogenicity.
Developing a variant effect score requires multiple steps: annotation of the training data, feature selection, model training, benchmarking, and finally deployment for the model's application. Here, I present a generalized workflow of this process. It makes it simple to configure how information is converted into model features, enabling the rapid exploration of different annotations. The workflow further implements hyperparameter optimization, model validation and ultimately deployment of a selected model via genome-wide scoring of genomic variants.
The workflow is applied to train Combined Annotation Dependent Depletion (CADD), a variant effect model that is scoring SNVs and InDels genome-wide. I show that the workflow can be quickly adapted to novel annotations by porting CADD to the genome reference GRCh38. Further, I demonstrate the integration of deep-neural network scores as features into a new CADD model, improving the annotation of RNA splicing events. Finally, I apply the workflow to train multiple variant effect models from training data that is based on variants selected by allele frequency.
In conclusion, the developed workflow presents a flexible and scalable method to train variant effect scores. All software and developed scores are freely available from cadd.gs.washington.edu and cadd.bihealth.org
AN EMPIRICAL STUDY OF CONCURRENT FEATURE USAGE IN GO
The Go language includes support for running functions or methods concurrently as goroutines, which are lightweight threads managed directly by the Go language runtime. Go is probably best known for the use of a channel-based, message-passing concurrency mechanism, based on Hoare's Communicating Sequential Processes (CSP), for inter-thread communication. However, Go also includes support for traditional concurrency features, such as mutexes and condition variables, that are commonly used in other languages. In this paper, we analyze the use of these traditional concurrency features, using a corpus of Go programs used in earlier work to study the use of message-passing concurrency features in Go. The goal of this work is to better support developers in using traditional concurrency features, or a combination of traditional and message-passing features, in Go
Modelling, Monitoring, Control and Optimization for Complex Industrial Processes
This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors
A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms
Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data.
A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability.
To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity.
A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case.
The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change.
The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the âproblem of implementationâ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sectorâs emergence
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Into the Multiverse: Methods for Studying Developmental Neuroscience
One major challenge in developmental neuroscience research is the sheer number of choices researchers face when addressing even a single research question. Even once data collection is complete, the journey from raw data to interpretation of findings may depend on numerous decisions. To address this issue, this dissertation explores âmultiverseâ analysis techniques for following many analytical paths at once in the same dataset.
In chapter 1, multiverses are used to examine which analyses of age-related change in amygdala-medial prefrontal cortex circuitry are robust versus sensitive to researcher decisions. Chapter 2 uses multiverse analysis to identify optimal solutions for mitigating breathing-induced artifacts in resting-state functional magnetic resonance imaging data. Chapter 3 uses a variety of model specifications to characterize simultaneous reward learning strategies in youth contingent on both visual task cues and spatial-motor information.
Despite varied approaches and goals, each of the three studies highlight the benefits of conducting multiple parallel analyses for both addressing questions in developmental neuroscience and deepening understanding of the methods used to address them
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An Agile Musicology: Improvisation in Corporate Management and Lean Startups
The last decade of the twentieth century saw a proliferation of publications that use jazz as a metaphor for corporate management, arguing that in the contemporary knowledge economy, jazz is superior to the symphonic model that governed mid-century factory floors. As the literature on the jazz metaphor, and organizational improvisation more broadly, continued to develop into the twenty-first century, another managerial methodology became widely adopted by entrepreneurs: agile. While agile is yet to be fully theorized as an improvisatory practice, agile shares several core tenets with the models promoted by organizational improvisation scholars, including the use of small teams, an emphasis on feedback, and an openness to change. In this dissertation, I argue that agile methods, and the adjacent lean methodology, are inherently improvisatory and that understanding them as improvisatory offers opportunities not only for their deployment within growing businesses, but also for adoption at-scale in large corporations.
I draw on an array of disciplinary perspectives, including management science, organizational studies, musicology, and critical improvisation studies, as well as a wide range of sources, from peer-reviewed journal publications to trade manuals. Each chapter builds upon the former: a substantial and critical review of the jazz metaphor literature is followed by a dissection of its main themes under a musicological lens; after securing the foundations of organizational improvisation, the next chapter reveals the improvisatory nature of agile and lean startup practices and links them to concepts discussed within the jazz metaphor literature. Drawing on insights from large-scale improvisatory musical practices, the final chapter reveals how improvisation, as a set of practices shared between corporate management and agile methodologies, provides avenues for agile to be scaled up as startups grow or for its widespread adoption within established companies
Small firms and industrial districts
Editor's notes.
By Margherita Russo.
Sebastiano Brusco's collection of essays Piccole imprese e distretti industriali (Tori-no, Rosenberg & Sellier, 1989) was translated in English by Tim Keats in 1990, unless three chapters that were already available in English and chapter 7 that was too long for a publication as a book chapter. Having abandoned the project of publishing a vol-ume in English, Sebastiano Brusco asked me to share a photocopy of the English transla-tion with scholars who requested it, and so several copies arrived in the hands of re-searchers in various countries: South Africa, Norway, Denmark, the United States, France and the United Kingdom.
Twenty years after Sebastiano Brusco passed away, and me approaching to retirement, a working paper edition - in the DEMB Working Paper Series - will make the document freely available online.
This digital document has been created, in 2012, drawing on a folder of Sebastiano Brusco's digital archive "Backup of EnglishBook" that contained Lotus MS files. These files have been converted by Patrizio Magagni in a txt format and then inserted by me in a single Word file: "Backup of EnglishBook_from files converted by Patrizio_22.01.2012 Some graphs and tables have been added as images, taken from the Italian edition. The text is all flag-formatted, whereas in the Italian edition only the main introduction, chapter introduction and afterword were flag-formatted. The text is not justified be-cause, in the conversion of the original files, a manual line break was automatically inserted at the end of each line. To differentiate those parts of the text written by Brusco specifically for the publi-cation of the 1989 collection of essays, they are reproduced here in two columns, with a smaller font. A complete list of Sebastiano Brusco's publication is available online at:https://www.economia.unimore.it/site/home/dipartimento-di-economia---sebastiano-brusco-web-page.htm
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