Abstract-Text classification is a tool to assign the predefined categories to the text documents using supervised machine learning algorithms. It has various practical applications like spam detection, sentiment detection, and detection of a natural language. Based on the idea we applied five well-known classification techniques on Urdu language corpus and assigned a class to the documents using majority voting. The corpus contains 21769 news documents of seven categories (Business, Entertainment, Culture, Health, Sports, and Weird). The algorithms were not able to work directly on the data, so we applied the preprocessing techniques like tokenization, stop words removal and a rule-based stemmer. After preprocessing 93400 features are extracted from the data to apply machine learning algorithms. Furthermore, we achieved up to 94% precision and recall using majority voting.
This paper presents a unidirectional, left handed circularly polarized (LHCP), single layered antenna array with improved interport isolation for simultaneous transmit and receive (STAR) or in-band full duplex (IBFD) wireless applications. The proposed IBFD antenna is comprised of three identical and sequentially rotated LHCP radiating elements where two R x patches are symmetrically placed with respect to a single T x patch. The symmetry of proposed antenna structure results in same amount of coupling or self interference (SI) from T x element and differentially driven R x patches achieve effective suppression of resulting SI to obtain improved T x-R x interport isolation required for STAR applications. The deployed feed network for differential-driven R x operation is composed of a simple 3dB/180 • rat-race coupler (ring hybrid coupler) with nice in-band amplitude and out-of-phase balance characteristics. The implemented single layer, compact (antenna elements and feeding network etched on single-layered PCB) antenna array achieves 10dB return-loss bandwidth ≥ 75MHz for both T x and R x ports. The prototype achieves ≥ 47dB interport isolation in 75MHz bandwidth and 3 dB axial ratio beam-width is ∼ 60 • for implemented antenna. INDEX TERMS Left hand circular polarized (LHCP) antenna, improved interport isolation, in-band full duplex, self interference cancellation (SIC), 3dB/180 • ring hybrid coupler.
Unmanned aerial vehicles (UAVs) (also known as drones) are aircraft that do not require the presence of a human pilot to fly. UAVs can be controlled remotely by a human operator or autonomously by onboard computer systems. UAVs have many military uses, including battlefield surveillance, effective target tracking and engagement in air-to-ground warfare, and situational awareness in challenging circumstances. They also offer a distinct advantage in various applications such as forest fire monitoring and surveillance. Surveillance systems are developed using advanced technologies in the modern era of communications and networks. As a result, UAVs require enhancements to control and manage systems efficiently. Network security is a critical concern with respect to UAVs due to the risk of surveillance information theft and physical misuse. Although several new tools have been introduced to secure networks, attackers can use more advanced methods to get into a UAV network and create problems that pose an organizational threat to the entire system. Security mechanisms also reduce the performance of systems because some restrictive measures prevent users from accessing specific resources, but a few techniques and tools have overcome the problem of performance reduction in various scenarios. There are many types of attacks, i.e., denial of service attacks (DOS), distributed denial of service attacks (DDOS), address resolution protocol (ARP) spoofing, sniffing, etc., that make it challenging to maintain a UAV network. This research paper proposes a lightweight challenge-response authentication that can overcome the previously mentioned problems. As security is provided by utilizing a minimum number of bits in memory, this technique offers the same security features while using fewer network resources, low computing resources, and low power consumption.
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