相关论文: Increasing digital investigator availability throu…
It is imperative for all stakeholders that digital forensics investigations produce reliable results to ensure the field delivers a positive contribution to the pursuit of justice across the globe. Some aspects of these investigations are…
As the number of digital documents requiring investigation increases, it has become more important to identify relevant documents to a given case. There have been continual demands for finding relevant files in order to overcome this kind…
In today world we are confronted with increasing amounts of information every day coming from a large variety of sources. People and co-operations are producing data on a large scale, and since the rise of the internet, e-mail and social…
Recent studies have shown that carefully designed workflows coordinating large language models(LLMs) significantly enhance task-solving capabilities compared to using a single model. While an increasing number of works focus on autonomous…
Domain experts are increasingly employing machine learning to solve their domain-specific problems. This article presents six key challenges that a domain expert faces in transforming their problem into a computational workflow, and then…
Despite recent advancements in large language models (LLMs), their performance on complex reasoning problems requiring multi-step thinking and combining various skills is still limited. To address this, we propose a novel framework HDFlow…
The recent advent of autonomous laboratories, coupled with algorithms for high-throughput screening and active learning, promises to accelerate materials discovery and innovation. As these autonomous systems grow in complexity, the demand…
Smartphones have created a significant impact on the day to day activities of every individual. Now a days a wide range of Smartphone applications are available and it necessitates high computing resources in order to build these…
Modern scientific discovery increasingly requires coordinating distributed facilities and heterogeneous resources, forcing researchers to act as manual workflow coordinators rather than scientists. Advances in AI leading to AI agents show…
Drug discovery is lengthy and expensive, with traditional computer-aided design facing limits. This paper examines integrating quantum computing across the drug development cycle to accelerate and enhance workflows and rigorous…
Following a series of high profile miscarriages of justice in the UK linked to questionable expert evidence, the post of the Forensic Science Regulator was created in 2008. The main objective of this role is to improve the standard of…
The frequency and harmfulness of cyber-attacks are increasing every day, and with them also the amount of data that the cyber-forensics analysts need to collect and analyze. In this paper, we propose a formal analysis process that allows an…
The emergence of "big data" offers unprecedented opportunities for not only accelerating scientific advances but also enabling new modes of discovery. Scientific progress in many disciplines is increasingly enabled by our ability to examine…
The prevalence of scientific workflows with high computational demands calls for their execution on various distributed computing platforms, including large-scale leadership-class high-performance computing (HPC) clusters. To handle the…
Digital forensics and cloud forensics are increasingly important fields that face a range of challenges. This study aims to assess the general challenges faced in these fields. A literature review was conducted to identify the major…
Anti-forensics includes a growing set of techniques designed to obstruct forensic analysis. While cybercriminals increasingly rely on these methods, they also help researchers identify and remedy weaknesses in forensic tools, advancing the…
As Deep Neural Networks (DNNs) have become an increasingly ubiquitous workload, the range of libraries and tooling available to aid in their development and deployment has grown significantly. Scalable, production quality tools are freely…
The exponential growth of scientific production makes secondary literature abridgements increasingly demanding. We introduce a new open-source framework for systematic reviews that significantly reduces time and workload for collecting and…
Investigations are a significant step in the operational workflows for large scale systems across multiple domains such as services, data, AI/ML, mobile. Investigation processes followed by on-call engineers are often manual or rely on…
FPGAs are well-suited for dataflow architectures that process data in a streaming or pipelined manner, thus satisfying the high computational and communication demands of emerging applications. However, manually implementing an efficient…