Linga Reddy Cenkeramaddi

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• Doctor of Philosophy
• Professor - ACPS Research Group Leader at University of Agder

Federated Learning (FL) is an emerging learning paradigm facilitating privacy-preserving machine learning at a large scale without the need for training data aggregation. The existing literature on FL mainly focuses on optimizing learning to enhance convergence time and accuracy. However, the need for developing incentivisation strategies to motiva...

In a conventional Domain Adaptation (DA) setting, we only have one source and target domain, whereas, in many real-world applications, data is often collected from several related sources in different conditions. This has led to a more practical and challenging knowledge transfer problem called Multi-source Domain Adaptation (MDA). Several methodol...

Resource-constrained wearable photoplethysmography (PPG) monitoring devices highly demand energy consumption reduction strategies to maximize the battery lifetime under continuous health monitoring applications. In this paper, we present a digital compressed PPG sensing (DCS-PPG) framework with a resource-efficient sensing matrix, sparse recovery a...

Recently, drones have attracted considerable attention for sensing hostile areas. Multiple drones are deployed to communicate and coordinate sensing and data transfer in the Internet of Drones (IoD) network. Traditionally, multi-hop routing is employed for communication over long distances to increase the network’s lifetime. However, multi-hop rout...

Millimeter-wave (mmWave) radars are integral to advanced driver assistance systems (ADAS) for object detection and tracking. However, these radars are vulnerable to interference from other mmWave radars in the vicinity, potentially leading to false detections and tracking errors. This paper focuses on identifying which frames of ego radar data are...

Domain Generalization (DG) techniques have emerged as a popular approach to address the challenges of domain shift in Deep Learning (DL), with the goal of generalizing well to the target domain unseen during the training. In recent years, numerous methods have been proposed to address the DG setting, among which one popular approach is the adversar...

NAND flash memory is a non-volatile storage device that is extensively used in personal electronic gadgets, digital television, digital cameras, and many consumer and professional electronics devices. Error control coding techniques have been incorporated to improve the integrity of information stored in these devices. We have synthesized the Subfi...

Photoplethysmogram (PPG) is a bio-optical technology used heavily in wearable health devices for monitoring vital sign parameters. Therefore, ensuring the quality of PPG signals is crucial for accurate measurements, as these signals are susceptible to various artifacts and noises. This article proposes a derivative-based PPG (dPPG) signal quality a...

Hand gesture recognition has gained a lot of attention in computer vision due to multiple applications. Further, most of the existing works utilized RGB data for hand gesture recognition. However, RGB cameras mainly depend on lighting, angles, and other factors including skin color which impacts the accuracy. Thus, we propose a methodology for vide...

In wireless networks, automatic modulation classification (AMC) is crucial for enabling intelligent signal de-modulation, thereby enhancing the system's adaptability across various applications. Concurrently, the rapid expansion of the internet of things (IoT) necessitates scalable network solutions with limited power consumption. Moreover, address...

Modern radar systems are designed to emit low probability of intercept (LPI) waveforms to avoid interception and detection by enemies. In this process, automatic radar LPI waveform recognition becomes a helpful tool for electronic countermeasures. In this paper, we propose LPI-Network (LPI-Net) that uses the complex radar returns to the multi-chann...

Kidney illness constitutes a category of many serious persistent diseases that can affect an individual. Early diagnosis of this condition is critical for effective therapy. Kidney tumors are the 2nd most common type of urological tumor. They come in a variety of forms, the majority of which are cancerous. In comparison to the laborious and lengthy...

To provide service to an abundant number of communication users and to avoid the spectrum scarcity problem, many researchers are fascinated to work towards the convergence of radar sensing and communication systems. In addition, future intelligent systems like autonomous vehicles, Vehicle-to-everything (V2X), Unmanned Aerial Vehicles (UAV), and all...

Gossip algorithms are often considered suitable for wireless sensor networks (WSNs) because of their simplicity, fault tolerance, and adaptability to network changes. They are based on the idea of distributed information dissemination, where each node in the network periodically sends its information to randomly selected neighbors, leading to a rap...

Low Power Wide Area Network (LPWAN) has emerged as a dominating communication technology that offers low-power and wide coverage for the Internet of Things (IoT) applications. However, the direct data transmission approach has a limited network lifetime. Even multi-hop data transmission experiences many difficulties including high data latency, poo...

Diabetes is a long-term condition in which a person’s body cannot break down blood sugar adequately due to a shortage of insulin. The most crucial element of health care is continuously monitoring blood glucose (BG) levels. The main concern of effective glucose monitoring equipment is based on the blood-pricking technique. However, this may not be...

Edge Servers (ESs) enhance the efficiency and reliability of modern Beyond Fifth-Generation (B5G) network systems by reducing latency, boosting responsiveness, and optimizing network usage. From an industry standpoint, the optimal positioning of ESs is critical to enhancing coverage reach while reducing potential conflicts with neighboring servers,...

The detection and ranking of influential nodes in complex networks are crucial for various practical applications such as identifying potential drug targets in protein-to-protein interaction networks, critical devices in communication networks, key people in social networks, and transportation hubs in logistics networks. The knowledge of influentia...

The breath rate can now be monitored remotely due to the advancements in digital stethoscope sensor technology, signal processing, and machine learning. Automatic breathing rate classification, on the other hand, provides additional benefits in medical diagnostics. In this paper, a lightweight convo-lutional neural network is proposed for automatic...

Rapid advancements in communication technologies in the Internet of Things (IoT) domain have had an impact on the application of positioning technology across multiple domains. Although there have been numerous fully-fledged approaches for detection and localization in outdoor scenarios, due to high path loss and shadowing, these are insufficiently...

The Tsetlin Machine is a novel and powerful algorithm for pattern recognition and decision-making tasks that has gained significant traction in recent years. Its features make it highly suitable for energy-efficient hardware implementations. This paper presents an FPGA design and implementation of an inference accelerator for a Multi Class Tsetlin...

The dataset includes thermal videos of various hand gestures captured by the FLIR Lepton Thermal Camera. A large dataset is created to accurately classify hand gestures captured from eleven different individuals. The dataset consists of 9 classes corresponding to various hand gestures from different people collected at different time instances with...

Unmanned aerial vehicles (UAVs) are getting significant attention from both researchers and the industry due to their wide range of applications. Remote sensing is one such application, in which UAVs are deployed to sense remote areas and transmit the data to a ground station for processing. However, due to the mobility and limited transmission ran...

Electrocardiogram (ECG) derived heart rate variability (HRV) analysis is widely used in both physiological and psychological monitoring. For HRV analysis, an automatic R-peak to R-peak interval (RRI) determination is most essential and that is performed by processing the ECG signal. Continuous HRV analysis is most essential for predicting health pr...

Continuous measurement of oxygen saturation (SpO2) and pulse rate (PR) is most essential for diagnosis of cardiovascular and chronic pulmonary diseases. Affordable miniaturized devices with limited battery capacity highly demand energy-efficient continuous vital sign measurement for long-term health and wellness monitoring. In this paper, we presen...

The richness of textures and semantic information from RGB images can be supplemented in computer vision by the robustness of thermal images to light variations and weather artifacts. While many models rely on inputs from one sensor modality, image translation among modalities can be a solution. The existing works use large models that only work in...

Ranking influential nodes within complex networks offers invaluable insights into a wide array of phenomena ranging from disease management to information dissemination and optimal routing in real-time networking applications. Centrality measures, which quantify the importance of nodes based on network properties and relationships of nodes within t...

In complex networks, node impact refers to an individual node’s significance or influence within the structure. Node impact evaluation is studied in information transmission, preventing pandemics, and infrastructure resilience applications. Centrality measures are crucial for understanding the impact of particular nodes in the network structure. Mo...

Unmanned aerial vehicles, and special multirotor drones, have shown great relevance in a plethora of missions that require high affordance, field of view, and precision. Their limited payload capacity and autonomy make its landing a crucial task. Despite many attempts in the literature to address drone landing, challenges and open gaps still exist....

Exploring the significance of popular node’s impact in complex networks yields numerous advantages, such as improving network resilience and accelerating information dissemination. While conventional centrality measures accurately quantify individual node importance, they may inadvertently overlook certain properties of influential nodes. The quest...

In recent years, the research community has gained more interest in spectral cooperation between radar and communication systems. This paper introduces a communication-aided radar measurement model as a function of transmitted waveforms in a cooperative radar communication system (CRCS). For this investigation a linear frequency modulated (LFM) pul...

Coarse-Grained Reconfigurable Array (CGRA) architectures are potential high-performance and power-efficient platforms. However, mapping applications efficiently on CGRA, which includes scheduling and binding operations on functional units and variables on registers, is a daunting problem. SiLago is a recently developed VLSI design framework compris...

Distress is any observable deterioration or damage that negatively impacts the road’s performance and safety. Potholes cracks, rutting, and bleeding are a few examples of distress. Maintaining the roads and detecting distress on the surface of road is critical to avoid impending accidents, consequently saving lives. The article primarily explains t...

Deep learning has been widely used in medical image processing, which has sparked the development of a wide range of applications and led to a notable increase in the number of therapeutic and diagnostic options available for a range of medical imaging problems. In the era of the Internet of Things (IoT), safeguarding the security and privacy of me...

The global system for mobile communications (GSM) is a 2G technology accepted by almost every communication device. However, the received GSM signals from different mobiles differ irrespective of their manufacturer or category. This paper proposes a GSM-based mobile handset identification approach using the Continuous Wavelet Transform (CWT) and de...

The identification of wireless technology is vital due to the rising use of wireless devices and the coexistence of multiple technologies. It enables dynamic spectrum access, facilitating efficient spectrum sharing among multiple users and applications within the same frequency bands, optimizing utilization, and minimizing interference. This study...

Efficiently synthesizing an entire application that consists of multiple algorithms for hardware implementation is a very difficult and unsolved problem. One of the main challenges is the lack of good algorithmic libraries. A good algorithmic library should contain algorithmic implementations that can be physically composable, and their cost metric...

Identifying influential nodes within complex networks holds significant importance for enhancing network resilience and understanding vulnerabilities, thereby providing insights for both theoretical exploration and practical applications. Understanding how quickly information spreads highlights the need to identify influential nodes promptly. Certa...

We propose MF-DBTSCAN, a novel clustering algorithm combining multivariate, fuzzy, temporal, and spatial features. The primary objective of the proposed clustering algorithm is to establish well-defined clusters that address the challenges associated with proximity targets, crossing targets, and targets overlapping in range, Doppler, angle and thei...

Federated learning (FL) has emerged as a powerful collaborative learning approach that enables client devices to train a joint machine learning model without sharing private data. However, the decentralized nature of FL makes it highly vulnerable to adversarial attacks from multiple sources. There are diverse FL data poisoning and model poisoning a...