A SIX-PORT MEASUREMENT DEVICE FOR HIGH POWER MICROWAVE VECTOR NETWORK ANALYSIS

The changes experienced in technology due to the third industrial revolution have over the years contributed immensely to the development of efficient devices and systems. As a result, solutions have been provided to challenges encountered in the heating industry. However, higher efficiency and better performance has undoubtedly been highly sort after. This paper presents the complete industrial development of a new system of a microwave device for use in S-band networks (2.45 GHz ISM band in this application): a vector network analyzer (VNA). The VNA, which is designed based on the six-port measurement principle, provides accurate measurements of both magnitude and phase of the load reflection coefficient. The device is designed to have high power handling capabilities and works under the full operating conditions of high-power microwave generators. Initial measurements show that the device perform stable and can perform temperature-independent measurements over protracted periods. The system is suited for on-line monitoring and control of network parameters in industrial waveguide applications.

Design and Implementation of a Cloud Based Decentralized Cryptocurrency Transaction Platform

Trading in the crypto-currency market has seen rapid growth and adoption, as well as the interest in crypto related technologies like blockchain and smart contracts. Smart contracts have gained popularity in building so called Decentralized Applications (dApps) and Decentralized Finance (DeFi) apps, mainly because they are more secure, trustworthy, and largely distributed (removes centralized control). DeFi applications run on the blockchain technology and are secured by blocks (nodes) connected by cryptographical hash links. DeFi applications have a great potential in the crypto-currency trading domain, providing more secure and reliable means of trading, and performing transactions with crypto-currencies. Only verified transactions are added to the blockchain after being approved by miners through a consensus mechanism and then it is replicated (distributed) among the nodes on the blockchain network. This research paper proposes a DeFi Crypto Exchange by integrating a numerous-signature stamp with a crypto API. A numerous-signature stamp solves the issue of transaction verifiability and authenticity. A crypto API provides the data about each crypto currency with which trades and transactions will be performed. This paper also discusses the technical background of the technology and a few related works. Decentralization of transactions through smart contracts on the blockchain will improve trust, security and reliability of transactions and trades

Study of a printed split-ring monopole for dual-spectrum communications

In this study, we present a low-profile dual-spectrum split-ring monopole that operates at industrial, scientific and medical (ISM) (2.45 GHz) band and ultrawideband (UWB) spectrum (3.1-10.6 GHz). We optimised the design for dual-band operations by using circular split-ring radiators. The coupling between both rings drives the structure to achieve quasi-resonance frequencies in the UWB spectrum. A small stub combines the two radiators and both behave as a single element that enables the antenna to resonate at ISM band 2.45 GHz. The antenna achieves the desired characteristics in terms of good impedance matching, radiation properties as well as other physical and practical requirements such as compact geometry, planar profile and easy fabrication. The very good agreement between the simulated and measured results show that the proposed antenna has the potential for dual-band application

Blockchain-IoT peer device storage optimization using an advanced time-variant multi-objective particle swarm optimization algorithm

The integration of Internet of Things devices onto the Blockchain implies an increase in the transactions that occur on the Blockchain, thus increasing the storage requirements. A solution approach is to leverage cloud resources for storing blocks within the chain. The paper, therefore, proposes two solutions to this problem. The first being an improved hybrid architecture design which uses containerization to create a side chain on a fog node for the devices connected to it and an Advanced Time‑variant Multi‑objective Particle Swarm Optimization Algorithm (AT‑MOPSO) for determining the optimal number of blocks that should be transferred to the cloud for storage. This algorithm uses time‑variant weights for the velocity of the particle swarm optimization and the non‑dominated sorting and mutation schemes from NSGA‑III. The proposed algorithm was compared with results from the original MOPSO algorithm, the Strength Pareto Evolutionary Algorithm (SPEA‑II), and the Pareto Envelope‑based Selection Algorithm with region‑based selection (PESA‑II), and NSGA‑III. The proposed AT‑MOPSO showed better results than the aforementioned MOPSO algorithms in cloud storage cost and query probability optimization. Importantly, AT‑MOPSO achieved 52% energy efficiency compared to NSGA‑III. To show how this algorithm can be applied to a real‑world Blockchain system, the BISS industrial Blockchain architecture was adapted and modified to show how the AT‑MOPSO can be used with existing Blockchain systems and the benefits it provides

Adaptive Storage Optimization Scheme for Blockchain-IIoT Applications Using Deep Reinforcement Learning

Blockchain-IIoT integration into industrial processes promises greater security, transparency, and traceability. However, this advancement faces significant storage and scalability issues with existing blockchain technologies. Each peer in the blockchain network maintains a full copy of the ledger which is updated through consensus. This full replication approach places a burden on the storage space of the peers and would quickly outstrip the storage capacity of resource-constrained IIoT devices. Various solutions utilizing compression, summarization or different storage schemes have been proposed in literature. The use of cloud resources for blockchain storage has been extensively studied in recent years. Nonetheless, block selection remains a substantial challenge associated with cloud resources and blockchain integration. This paper proposes a deep reinforcement learning (DRL) approach as an alternative to solving the block selection problem, which involves identifying the blocks to be transferred to the cloud. We propose a DRL approach to solve our problem by converting the multi-objective optimization of block selection into a Markov decision process (MDP). We design a simulated blockchain environment for training and testing our proposed DRL approach. We utilize two DRL algorithms, Advantage Actor-Critic (A2C), and Proximal Policy Optimization (PPO) to solve the block selection problem and analyze their performance gains. PPO and A2C achieve 47.8% and 42.9% storage reduction on the blockchain peer compared to the full replication approach of conventional blockchain systems. The slowest DRL algorithm, A2C, achieves a run-time 7.2 times shorter than the benchmark evolutionary algorithms used in earlier works, which validates the gains introduced by the DRL algorithms. The simulation results further show that our DRL algorithms provide an adaptive and dynamic solution to the time-sensitive blockchain-IIoT environment

Intelligent Miniature Circuit Breaker

The traditional electrical distribution panel (or breaker panel) is a system that divides the main electrical power feed and distributes them to subsidiary circuits whiles providing a protective mechanism via the use of miniature circuit breakers, residual current devices, etc. The conventional panel distributes electrical power alright but the system does not make provision for any form of real time monitoring and feedback of power consumption levels in the home. This paper presents a design of a miniature circuit breaker distribution panel integrated with other electronic devices which helps achieve real time monitoring of power consumption and also automatically trips the circuit if there is a fault and reconnects the circuit if the fault is cleared to ensure little to no interruption in electricity to appliances

On Distributed Denial of Service Current Defense Schemes

Distributed denial of service (DDoS) attacks are a major threat to any network-based service provider. The ability of an attacker to harness the power of a lot of compromised devices to launch an attack makes it even more complex to handle. This complexity can increase even more when several attackers coordinate to launch an attack on one victim. Moreover, attackers these days do not need to be highly skilled to perpetrate an attack. Tools for orchestrating an attack can easily be found online and require little to no knowledge about attack scripts to initiate an attack. Studies have been done severally to develop defense mechanisms to detect and defend against DDoS attacks. As defense schemes are designed and developed, attackers are also on the move to evade these defense mechanisms and so there is a need for a continual study in developing defense mechanisms. This paper discusses the current DDoS defense mechanisms, their strengths and weaknesses

A Proposed DoS Detection Scheme for Mitigating DoS Attack Using Data Mining Techniques

A denial of service (DoS) attack in a computer network is an attack on the availability of computer resources to prevent users from having access to those resources over the network. Denial of service attacks can be costly, capable of reaching $100,000 per hour. Development of easily-accessible, simple DoS tools has increased the frequency and reduced the level of expertise needed to launch an attack. Though these attack tools have been available for years, there has been no proposed defense mechanism targeted specifically at them. Most defense mechanisms in literature are designed to defend attacks captured in datasets like the KDD Cup 99 dataset from 20 years ago and from tools no longer in use in modern attacks. In this paper, we capture and analyze traffic generated by some of these DoS attack tools using Wireshark Network Analyzer and propose a signature-based DoS detection mechanism based on SVM classifier to defend against attacks launched by these attack tools. Our proposed detection mechanism was tested with Snort IDS and compared with some already existing defense mechanisms in literature and had a high detection accuracy, low positive rate and fast detection time