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

PRIVATE SECURITY SURVEILLANCE SYSTEM

Security is an essential need for man. Without the sense of security, daily human activities will be greatly affected. Most people go to great lengths to ensure there is a presence of security in their environment, often employing dedicated personnel to keep watch over them and their property. This paper proposes a design of a microcontroller based electronic security system which helps to detect possible intruders to a home. This security system is designed to reduce the need of having personnel stationed as security guards over a home. It has the primary unit called the Area Watch Unit (AWU) consisting of a motion detection unit that effectively detects motion around specified perimeters which is then followed by a computer vision to identify and classify what caused the motion. A facial recognition algorithm is run on the face extracted from the image captured after the object that caused the motion is identified and classified as human. Access is then granted to the individual if the results from the facial recognition is positive otherwise a message is sent to the owner of the home indicating a possible intruder is present. There is also a Final Recovery Unit (FRU) which sends a message to the owner of the home and sounds an alarm whiles flashing lights in the event that the Area Watch Unit (AWU) is by-passed without authority

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

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

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

Computed tomography features of spontaneous acute intracranial hemorrhages in a tertiary hospital in Southern Ghana

Introduction: spontaneous acute intracranial hemorrhage (SICH) accounts for approximately 10-15% of all stroke cases. Early detection by computed tomography (CT) and early treatment are key. Hence this study to examine the CT features of SICH. Methods: this retrospective cohort study reviewed all 435 patients diagnosed with SICH from 1st March, 2017 to 1st January, 2021 in a tertiary facility in Southern Ghana. Data collected (age, sex, SICH type and the CT scan features) were organized and analyzed using GNU PSPP and Libre Office Calc. Statistical significance level was pegged at p≤0.05. Results: the SICH types were acute intracerebral hemorrhage (97.93%), acute subarachnoid/intraventricular hemorrhage (1.15%), acute epidural hemorrhage (0.46%) and acute subdural hemorrhage (0.46%). Acute intracerebral hemorrhage was more common in those >60 years (57.75%, p<0.001). The commonest CT feature for acute intracerebral hemorrhage was hyperdense lesion with perilesional edema (40.98%), with smoking (OR=2.24, 95% CI: 1.14-4.41, p=0.019) and anticoagulants intake (OR=2.56, 95% CI: 1.15-5.72, p=0.022) as the predictive factors; followed by hyperdense lesion extending to the edge of the brain (25.03%), also predictable by smoking (OR=0.23, 95% CI: 0.11-0.47, p<0.001); and hyperdense lesion with mass effects (22.70%) was not predictive with any risk factor. Type 2 diabetes mellitus (60.00%, p<0.001) and smoking (97.83%, p<0.001) were more common in males. Conclusion: hyperdense lesion with perilesional edema was the most frequent CT feature for acute intracerebral hemorrhage and was predictable by smoking and anticoagulants intake. Smoking was a predictive factor to the development of most of the features of acute intracerebral hemorrhage

Report of the Lancet Commission on the Value of Death: bringing death back into life

The story of dying in the 21st century is a story of paradox. While many people are overtreated in hospitals with families and communities relegated to the margins, still more remain undertreated, dying of preventable conditions and without access to basic pain relief. The unbalanced and contradictory picture of death and dying is the basis for this Commission