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K. Liang

34 records found

Aging is the biological process that changes the body over time. When we age our bodies become more prone to disease and other health risks. But not everyone experiences these changes at the same age. This is because the age of our cells (biological age) does not always match our ...
The aim of this research is to investigate whether physical gene characteristics can predict age-related changes in gene expression. Specifically, we analyze gene length, GC content, distance to the ends of the chromosome, and similar features to determine their connection with d ...

Improving Single-Cell Transcriptomic Aging Clocks

Enhancing Accuracy and Biological Interpretability

Biological aging clocks estimate age from molecular data and provide insights into age-related functional decline. While aging clocks based on bulk transcriptomic data are well-studied, their single-cell counterparts remain limited and underexplored. In this study, we replicate a ...

Improving and Interpreting Epigenetic Age Predictors

A Machine Learning Approach to Improving Epigenetic Age Predictors and Understanding How DNA Methylation Affects Aging

Understanding the mechanisms of aging can help us live longer and healthier lives. Epigenetic age predictors are machine learning models that use methylation levels at CpG sites to predict the biological age of the cell. Horvath’s linear clock uses 353 CpGs with a median absolute ...

Automatic Hand Landmark Detection for Leprosy Diagnosis

Comparison of Output Adaptation Techniques for Hand Keypoint Prediction

Early detection of leprosy, a neglected tropical disease, is crucial to preventing irreversible nerve damage and disability. Analyzing temperature vari- ations in hands using infrared (IR) cameras offers a potential low-cost alternative to existing medical equipment for early det ...

In this work, we investigate how domain adaptation techniques can improve the performance of hand landmark detection models originally trained on RGB images when deployed on infrared (IR) data. Our motivation stems from a medical use case in Nepal, where clin ...

Skin temperature measurement for diagnosing leprosy in Nepal

Automatically measuring localized changes in temperature in the hand using IR-RGB thermography

This study investigates sensor technologies for di- agnosing leprosy in Nepal, focussing on skin tem- perature in the hands using contact and non-contact sensors. Leprosy affects the peripheral nervous system, causing thermoregulatory dysfunction de- tectable via localized skin t ...
Hand landmark detection in infrared (IR) images is essential for early leprosy diagnosis in developing countries like Nepal, helping to prevent serious complications and disability. However, current hand landmark detection models, such as Google’s detection models comprised in th ...
Leprosy remains a significant health challenge in developing countries, where early diagnosis is crucial to prevent severe disabilities and social stigma. Recent studies have shown that infrared imaging can be used to detect abnormalities associated with leprosy by analyzing hand ...
Large Language Models (LLMs) are increasingly used in software development, but their potential for misuse in generating harmful code, such as malware, raises significant concerns. We present a red-teaming approach to assess the safety and ethical alignment of LLMs in the context ...

Implications of LLMs4Code on Copyright Infringement

An Exploratory Study Through Red Teaming

Large Language Models (LLMs) have experienced a rapid increase in usage across numerous sectors in recent years. However, this growth brings a greater risk of misuse. This paper explores the issue of copyright infringement facilitated by LLMs in the domain of software engineering ...

Red Teaming Large Language Models for Code

Exploring Dangerous and Unfair Software Applications

The rapid advancement of large language models has enabled numerous innovative, but also harmful applications. It is therefore essential to create these models to behave safely and responsibly. One way to improve these models is by red teaming them. In this study, we aim to ident ...
Streamlined Byzantine Fault Tolerant (BFT) protocols, such as HotStuff [PODC'19], and weighted voting represent two possible strategies to improve consensus in the distributed systems world. Several studies have been conducted on both techniques, but the research on ...
This paper explores the integration of weighted vot-ing mechanisms into DAG-based consensus proto-cols, such as Tusk [EuroSys’22], which promise high throughput and low latency. Weighted voting,
pioneered by protocols like WHEAT [SRDS’15] and AWARE [TDSC’20], aims to optimize ...

Using Weighted Voting to Accelerate Blockchain Consensus

How to make sure that the latency that the nodes report prior to AWARE’s algorithm is realistic?

This research addresses the challenge of managing latency in distributed computer systems. Maintaining correct delays in data transmission across various network conditions is crucial for system efficiency and security. We focus on improving the Adaptive Wide-Area Replication (AW ...
Sound pollution is becoming an increasingly pressing issue in today’s world. To effectively address it, it must be measured. To this end, Serval was developed, an edge-ai powered sound recognition solution. Its lack of accuracy, however, makes it difficult to deploy. This thesis ...
The rapid evolution of 5G technology has paved the way for the proliferation of resource-constrained Internet of Things (IoT) devices, collectively known as ambient IoT. While these devices offer unprecedented opportunities for connectivity and data collection, their limited com ...
Hidden spy cameras are a growing worldwide threat to people’s intimacy and privacy. With the growing interest in full-screen devices and the underlying development of under-screen cameras, a new type of potential security risk is introduced. Recent smartphones such as the ZTE AXO ...
Privacy concerns in federated learning have attracted considerable attention recently. In centralized networks, it has been observed that even without directly exchanging raw training data, the exchange of other so-called intermediate parameters such as weights/gradients can stil ...