Languages which have a high concentration of distinct tokens within their inflectional morphology often lead to a reduction in the topics' potency. The use of lemmatization is often a means to get ahead of this problem. Gujarati's multifaceted morphology is notable, as a single word encompasses a variety of inflectional forms. A deterministic finite automaton (DFA)-based lemmatization technique for Gujarati is proposed in this paper to derive root words from lemmas. From this lemmatized collection of Gujarati text, the subject matter is subsequently deduced. Statistical divergence metrics are employed to identify topics that lack semantic coherence, being overly general. Results show that the learning of interpretable and meaningful subjects by the lemmatized Gujarati corpus is superior to that of the unlemmatized text. Conclusively, the results showcase that lemmatization resulted in a 16% diminution in vocabulary size, while concurrently bolstering semantic coherence. Specifically, Log Conditional Probability improved from -939 to -749, Pointwise Mutual Information from -679 to -518, and Normalized Pointwise Mutual Information from -023 to -017.
This research details a newly designed eddy current testing array probe and its integrated readout electronics, which are targeted for layer-wise quality control in powder bed fusion metal additive manufacturing. The design approach under consideration promotes the scalability of the number of sensors, investigates alternative sensor components, and streamlines the process of signal generation and demodulation. Employing surface-mount technology coils, small in scale and widely accessible commercially, as a replacement for the standard magneto-resistive sensors yielded outcomes displaying cost-effectiveness, design adaptability, and effortless integration into the accompanying readout electronics. Considering the specifics of sensor signals' characteristics, various strategies were suggested to optimize the performance of readout electronics. We propose an adjustable single-phase coherent demodulation strategy, which serves as a replacement for the conventional in-phase and quadrature techniques, under the premise that the monitored signals display minimal phase inconsistencies. Implementing a simplified amplification and demodulation frontend using discrete components, offset removal was integrated, along with vector amplification and digital conversion executed by the advanced mixed-signal peripherals within the microcontroller. With non-multiplexed digital readout electronics, an array probe of 16 sensor coils, with a 5 mm spacing, was created. This setup permits a sensor frequency up to 15 MHz, 12-bit resolution digitization, and a sampling rate of 10 kHz.
The performance of a communication system at its physical or link level can be usefully evaluated using a wireless channel digital twin, which enables the controllable reproduction of the physical channel's characteristics. This paper introduces a stochastic general fading channel model, encompassing a wide variety of fading types relevant to diverse communication environments. The generated channel fading's phase discontinuity was circumvented by the sum-of-frequency-modulation (SoFM) method. Subsequently, a general and flexible channel fading generation architecture was established, employing a field-programmable gate array (FPGA) for implementation. For trigonometric, exponential, and logarithmic functions, this architecture introduced enhanced CORDIC-based hardware circuits. This improvement produced a more efficient real-time system and optimized hardware resource use compared to traditional LUT and CORDIC techniques. Employing a compact time-division (TD) structure for a 16-bit fixed-point single-channel emulation yielded a substantial reduction in overall system hardware resource consumption, decreasing it from 3656% to 1562%. In addition, the conventional CORDIC algorithm incurred an extra 16 system clock cycles of latency, while the latency associated with the improved CORDIC algorithm was diminished by 625%. selleck products The culmination of the research effort resulted in a correlated Gaussian sequence generation scheme, designed to introduce adjustable arbitrary space-time correlation into a multi-channel channel generator. The theoretical results were entirely corroborated by the output of the developed generator, thereby establishing the accuracy of both the generation method and its hardware implementation. Under dynamic communication conditions, the proposed channel fading generator allows for the emulation of large-scale multiple-input, multiple-output (MIMO) channels.
The network sampling process's impact on infrared dim-small target features diminishes detection accuracy significantly. To lessen the loss, this paper proposes YOLO-FR, a YOLOv5 infrared dim-small target detection model, based on feature reassembly sampling. Feature reassembly sampling scales the feature map without adding or subtracting feature information. During the downsampling process in this algorithm, an STD Block is employed to retain spatial characteristics within the channel dimension. Subsequently, the CARAFE operator expands the feature map's size while preserving the mean feature value; this protects features from distortions related to relational scaling. This research proposes an enhanced neck network to fully leverage the detailed features generated by the backbone network. The feature after one downsampling stage of the backbone network is merged with the top-level semantic data through the neck network to yield the target detection head with a small receptive range. In experiments, the YOLO-FR model, newly introduced in this paper, recorded a remarkable 974% on mAP50. This marks a 74% improvement from the preceding network and superior performance to both J-MSF and YOLO-SASE.
The current paper investigates the distributed containment control of continuous-time linear multi-agent systems (MASs) in which multiple leaders are present on a fixed topology. A parametric dynamic compensated distributed control protocol, which integrates information from the observer in the virtual layer and the actual surrounding agents, is introduced. The distributed containment control's necessary and sufficient conditions are deduced from the standard linear quadratic regulator (LQR). The modified linear quadratic regulator (MLQR) optimal control, alongside Gersgorin's circle criterion, is used to configure the dominant poles, thereby enabling containment control of the MAS with the specified speed of convergence. The proposed design presents an additional advantage: in the event of virtual layer failure, the dynamic control protocol can be transitioned to a static protocol. Convergence speed can still be precisely defined using the dominant pole assignment method in conjunction with inverse optimal control. Ultimately, illustrative numerical examples are offered to showcase the efficacy of the theoretical findings.
Large-scale sensor networks and the Internet of Things (IoT) are often constrained by battery capacity and the difficulty of recharging them. A technique for collecting energy from radio frequencies (RF), designated as radio frequency energy harvesting (RF-EH), has been revealed by recent advancements, providing a solution for the energy requirements of low-power networks where cables or battery replacements are unsuitable. The technical literature's treatment of energy harvesting tends to separate it from the crucial aspects of the transmitter and receiver, treating them as distinct entities. Ultimately, the energy dedicated to the act of data transmission cannot be utilized for the combined purposes of battery charging and data interpretation. Expanding on the existing methods, a sensor network implementation using a semantic-functional communication framework is presented, enabling the retrieval of battery charge data. Additionally, we detail an event-driven sensor network, featuring battery recharging accomplished by means of the RF-EH technique. selleck products For the purpose of evaluating system performance, we studied event signaling, event detection, battery exhaustion, and the efficacy of signaling, alongside the Age of Information (AoI). The system's response to various parameters, as exemplified in a representative case study, is analyzed, along with the battery charge behavior. Numerical outcomes conclusively demonstrate the proposed system's effectiveness.
Fog nodes, proximate to client devices in a fog computing system, process user queries and transmit data to cloud servers. Patient sensor data in remote healthcare is encrypted before being sent to a nearby fog. This fog serves as a re-encryption proxy, producing a re-encrypted ciphertext targeted for the specific data users within the cloud. selleck products Cloud ciphertexts are accessible to data users upon submitting a query to the fog node. This query is relayed to the corresponding data owner, who has the final say on granting or denying access to their data. The access request's approval will prompt the fog node to obtain a unique re-encryption key for the accomplishment of the re-encryption procedure. Although some pre-existing concepts have been devised to fulfill these application criteria, they either suffer from established security vulnerabilities or demand higher computational intricacy. We have developed an identity-based proxy re-encryption system, incorporating the functionality of fog computing. Key distribution within our identity-based system is facilitated via public channels, thereby mitigating the difficulty of key escrow. We formally validate the proposed protocol's security against the IND-PrID-CPA security model. Our work, in addition, exhibits better computational complexity.
To maintain an uninterruptible power supply, the achievement of power system stability is a daily requirement for every system operator (SO). Proper information exchange between Service Organizations (SOs), particularly in the event of emergencies, is critical, especially at the transmission level for each SO.