This paper presents a comprehensive survey on anti-drone systems. After drones were released for non-military usages, drone incidents in the unarmed population are gradually increasing. However, it is unaffordable to construct a military grade anti-drone system for every private or public facility due to installation and operation costs, and regulatory restrictions. We focus on analyzing anti-drone system that does not use military weapons, investigating a wide range of anti-drone technologies, and deriving proper system models for reliable drone defense. We categorized anti-drone technologies into detection, identification, and neutralization, and reviewed numerous studies on each. Then, we propose a hypothetical anti-drone system that presents the guidelines for adaptable and effective drone defense operations. Further, we discuss drone-side safety and security schemes that could nullify current anti-drone methods, and propose future solutions to resolve these challenges.

Forkhead box O (Foxo) transcription factors may be involved in the salutary effect of dietary restriction (DR). This study examined the role of Foxo3 in lifespan extension and cancer suppression in DR mice. Wild-type (WT) and Foxo3-knockout heterozygous ((+/-) ) and homozygous ((-/-) ) mice were subjected to a 30% DR regimen initiated at 12 weeks of age. Control mice were fed ad libitum (AL) throughout the study. In contrast to WT mice, DR did not significantly extend the lifespan of Foxo3(+/-) or Foxo3(-/-) mice. However, DR reduced the prevalence of tumors at death in WT, Foxo3(+/-) , and Foxo3(-/-) mice. These results indicate the necessity of Foxo3 for lifespan extension but not cancer suppression by DR. The findings in Foxo3(+/-) mice contrast with those in Foxo1(+/-) mice reported previously by our laboratory suggest differential regulation of cancer and lifespan by DR via Foxo1 and Foxo3.

Unmanned aerial vehicles (UAVs) with high mobility can perform various roles such as delivering goods, collecting information, recording videos and more. However, there are many elements in the city that disturb the flight of the UAVs, such as various obstacles and urban canyons which can cause a multi-path effect of GPS signals, which degrades the accuracy of GPS-based localization. In order to empower the safety of the UAVs flying in urban areas, UAVs should be guided to a safe area even in a GPS-denied or network-disconnected environment. Also, UAVs must be able to avoid obstacles while landing in an urban area. For this purpose, we present the UAV detour system for operating UAV in an urban area. The UAV detour system includes a highly reliable laser guidance system to guide the UAVs to a point where they can land, and optical flow magnitude map to avoid obstacles for a safe landing.

In this paper, we propose a scheme that implements a Distributed Ledger Technology (DLT) based on Directed Acyclic Graph (DAG) to generate, validate, and confirm the electricity transaction in Smart Grid. The convergence of the Smart Grid and distributed ledger concept has recently been introduced. Since Smart Grids require a distributed network architecture for power distribution and trading, the Distributed Ledger-based Smart Grid design is a spotlighted research domain. However, only the Blockchain-based methods, which are a type of the distributed ledger scheme, are currently either being considered or adopted in the Smart Grid. Due to computation-intensive consensus schemes such as Proof-of-Work and discrete block generation, Blockchain-based distributed ledger systems suffer from efficiency and latency issues. We propose a DAG-based distributed ledger for Smart Grids, called PowerGraph, to resolve this problem. Since a DAG-based distributed ledger does not need to generate blocks for confirmation, each transaction of the PowerGraph undergoes the validation and confirmation process individually. In addition, transactions in PowerGraph are used to keep track of the energy trade and include various types of transactions so that they can fully encompass the events in the Smart Grid network. Finally, to ensure that PowerGraph maintains a high performance, we modeled the PowerGraph performance and proposed a novel consensus algorithm that would result in the rapid confirmation of transactions. We use numerical evaluations to show that PowerGraph can accelerate the transaction processing speed by over 5 times compared to existing DAG-based DLT system.

This paper addresses the analysis and the deployment of the network infrastructure based on multiple Unmanned Air Vehicles (UAVs). Despite the unprecedented potential to the mobility of the network infrastructure, there has been no effort to establish a mathematical model of the infrastructure and formation control strategies. We model the generic dynamics of the network infrastructure and derive the network throughput of the infrastructure. Through the parametrization of the model, we extract the generic factors of the network protocols and verify our model through the Network Simulator 3 (ns-3). By exploiting our network analysis model, we propose a novel formation control algorithm that determines the location of the UAVs to maximize the efficiency of the network. To achieve the objectives of the infrastructure, we define the formation-shaping effect as forces and elaborately design them using the generic factors. The formation algorithm continuously approaches to the optimized formation of a fleet of UAVs to enhance the overall throughput of the terrestrial devices. Our evaluations show that the algorithm guarantees remarkably higher throughput than the static formations. Through the dynamic transformation of the UAV formation, we believe that the multi-UAV-based network infrastructure could expand the boundary of the existing infrastructure while reducing the network traffic.

Various unmanned aerial vehicles (UAVs), also called drones, have developed based on advances in hardware and software technologies. Thus, service providers in diverse areas have tried to utilize drones to create more effective solutions. In many cases, employing multiple drones is more effective to perform the given mission than using a single drone. To utilize multiple drones, the drones should be strongly connected, but it is not trivial to construct reliable and efficient networks for drones due to their high mobility. Therefore, we propose a ground control system (GCS) routing protocol (GCS-routing) to overcome this limitation and provide reliable and efficient multi-drone control system, where GCS-routing maximizes GCS utilization. GCS is the essential component of flying ad-hoc network (FANET) and can obtain information about drones. Using this information, GCS-routing can provide more effective routing, predict any topology changes, and react immediately. GCS-routing does not issue any periodic HELLO message for neighbor discovery or link cost estimation, which significantly enhances network performance. We implemented GCS-routing on real drones, and applied GCS-routing to actual drone fleets, as well as simulations to evaluate GCS-routing performance. The results clearly identify the advantages of the proposed routing protocol for drone networks compared with current routing protocols.