Error Rate Research Articles

A generalist vision-language foundation model for diverse biomedical tasks.

Traditional biomedical artificial intelligence (AI) models, designed for specific tasks or modalities, often exhibit limited flexibility in real-world deployment and struggle to utilize holistic information. Generalist AI holds the potential to address these limitations due to its versatility in interpreting different data types and generating tailored outputs for diverse needs. However, existing biomedical generalist AI solutions are typically heavyweight and closed source to researchers, practitioners and patients. Here, we describe BiomedGPT, the first open-source and lightweight vision-language foundation model, designed as a generalist capable of performing various biomedical tasks. BiomedGPT achieved state-of-the-art results in 16 out of 25 experiments while maintaining a computing-friendly model scale. We also conducted human evaluations to assess the capabilities of BiomedGPT in radiology visual question answering, report generation and summarization. BiomedGPT exhibits robust prediction ability with a low error rate of 3.8% in question answering, satisfactory performance with an error rate of 8.3% in writing complex radiology reports, and competitive summarization ability with a nearly equivalent preference score to human experts. Our method demonstrates that effective training with diverse data can lead to more practical biomedical AI for improving diagnosis and workflow efficiency.

Use of Nash equilibrium in finding game theoretic robust security bound on quantum bit error rate

Nash equilibrium is employed to find a game theoretic robust security bound on quantum bit error rate (QBER) for DL04 protocol which is a scheme for quantum secure direct communication that has been experimentally realized recently. The receiver, sender and eavesdropper (Eve) are considered to be quantum players (players having the capability to perform quantum operations). Specifically, Eve is considered to have the capability of performing quantum attacks (e.g., Wójcik’s original attack, Wójcik’s symmetrized attack and Pavičić attack) and classical intercept and resend attack. Game theoretic analysis of the security of DL04 protocol in the above scenario is performed by considering several game scenarios. The analysis revealed the absence of a Pareto optimal Nash equilibrium point within these game scenarios. Consequently, mixed strategy Nash equilibrium points are identified and employed to establish both upper and lower bounds for QBER. Further, the vulnerability of the DL04 protocol to Pavičić attack in the message mode is established. In addition, it is observed that the quantum attacks performed by Eve are more powerful than the classical attack, as the QBER value and the probability of detecting Eve’s presence are found to be lower in quantum attacks compared to classical ones.

Waveform optimization for future wireless communication: numerical simulation under mobile and vehicular scenarios in 5G and beyond

Abstract Code Division Multiple Access (CDMA) and Orthogonal Frequency Division Multiplexing (OFDM) are multicarrier regulating systems developed for quick communication. OFDM and its improved multi-carrier regulation technique employ equally distributed orthogonal sub-carriers for the transmission of data. These sub-carriers are modified using a conventional tweak plot, maintaining full information rates comparable to single carrier regulation schemes. The research also compares the two 5G modulation techniques, FBMC and UFMC, to OFDM, the 4G communication modulation technology. To evaluate the benefits of each contender, we compare important characteristics of different modulation approaches. The research compares the 5G modulation techniques FBMC and UFMC to OFDM, focusing on factors like power spectrum density, spectral efficiency, Bit Error rate, and Peak to Average Power Radio. To boost channel capacity and decrease interferences, the approach merges three alternative 5G waveforms under the LTE-V paradigm which is a specialized mode or configuration of Long Term Evolution (LTE) technology designed specifically for vehicular communication. MATLAB simulations show that FBMC performs better in terms of BER and capacity. In scenarios characterized by high interference due to power domain multiplexing and vehicular environment, FBMC demonstrates a maximum capacity that is 3.5 times greater than OFDM. However, in low-interference conditions, FBMC's capacity exceeds UFMC's by only a marginal 5%.

Energy Efficiency for Faster-than-Nyquist Data Transmission Using Processing Algorithms with Decision Feedback

One of the ways to increase the volume of transmitted information is to increase the bit rate above the Nyquist barrier. However, an increase in bit rate in the case of FTN (Faster-Than-Nyquist) signals leads to an increase in energy costs for receiving information on channels with limited bandwidth, for example, in Digital Video Broadcasting satellite systems like DVB-S2/S2X. It is possible to minimize energy losses by using the processing algorithm “maximum likelihood sequence estimation”. However, the computational complexity of this algorithm is extremely high, which limits its use, especially in terrestrial mobile satellite terminals. We propose a new bit-by-bit decision feedback algorithm with maximum likelihood ratio estimation of subsequent symbols in the observation interval. This algorithm provides minimal energy costs comparable to the method “maximum likelihood sequence estimation” at speeds 2–3 times higher than the Nyquist barrier. At the same time, the complexity is two orders of magnitude less. It is shown by simulation for a channel with additive noise that energy losses in relation to the potential bit error rate (BER) are less than 4.5 dB. In the presence of Rayleigh fading, the application of the proposed algorithm makes it possible to provide the processing of FTN signals for double bit rates in urban areas with energy costs equal to 12 dB when using an equalizer. We give numerical estimations of the increase in computational complexity for the proposed processing algorithm. It is shown that an increase in the bit rate by 1.5 times leads to an increase in the computational complexity by more than an order of magnitude. The same conclusion can be reformulated in another form: for the proposed algorithm, each decibel of energy gain is achieved by increasing the number of computational operations by 1.5×105. It is experimentally shown that additional energy losses due to non-ideal phase and timing synchronization are no more than 1 dB when the proposed algorithm is applied in a fading channel. The energy costs in fading channels relative to a stationary channel for twice the Nyquist rate are equal to 13.8 dB when using an equalizer.

Skipped wells and scientific error during fosfomycin agar dilution and broth microdilution lead to inconsistent minimal inhibitory concentrations and may be cause for reevaluating testing methods for Klebsiella pneumoniae.

Despite the first-line recommendation of fosfomycin for uncomplicated urinary tract infections (UTIs), there are pressing barriers for optimizing its use for the treatment of non-Escherichia coli Enterobacterales UTI. There are no approved breakpoints for oral use against other Enterobacterales, and the recommended agar dilution (AD) reference method for minimal inhibitory concentration (MIC) determination is largely impractical. Using 160 clinical Klebsiella pneumoniae isolates, we sought to understand rates of skipped wells and MIC imprecision in broth microdilution (BMD) and how that compares to rates of error using AD. Though the Clinical and Laboratory Standards Institute refers to the skipped well phenomena in their recommendation against the use of BMD, there is a paucity of data on its frequency. While AD and BMD produced similar MIC50/90 values (32/256 µg/mL for AD and 64/256 µg/mL for BMD), essential agreement was poor. No-growth wells at concentrations below the MIC occurred in up to 10.9% of wells at a given concentration, as the most frequent scientific error. Growth in concentrations above the measured MIC occurred in up to 3.3% of wells and was seen within three dilutions of the MIC for BMD. Observation of single colonies either at or beyond the measured MIC for AD was also common and occurred up to 8.3% and 2.5% of the time, respectively. The frequent scientific error in both testing methods should prompt re-evaluation of AD guidelines and expansion of MIC testing methods for fosfomycin susceptibility testing, as poor agreement with another method prone to scientific error should not be the main detractor from BMD use.IMPORTANCEDespite the recommendation of fosfomycin for uncomplicated urinary tract infections (UTIs), there are barriers for optimizing its use. There are no approved breakpoints for oral use against other Enterobacterales, and the recommended agar dilution (AD) reference method for MIC determination is largely impractical. The use of broth microdilution (BMD) for fosfomycin testing is not recommended by the Clinical and Laboratory Standards Institute due to unsatisfactory precision and skipped wells-occurrence of no-growth in a single well before the minimal inhibitory concentration (MIC)-and trailing endpoints. We sought to understand rates of skipped wells and growth at concentrations above measured MICs in BMD and how that compares to scientific error using AD. No-growth wells at concentrations below the MIC occurred in up to 10.9% of wells for BMD and single colonies at or beyond measured MICs for AD were also common. Frequent scientific error in both methods should prompt re-evaluation of both AD and BMD for fosfomycin susceptibility testing.

Comparison of Fuzzy Grey Markov Model (1,1) and Fuzzy Grey Markov Model (2,1) in Forecasting Gold Prices in Indonesia

Currently, gold investment is considered promising despite the ever-changing price of gold. However, obtaining optimal profits is a challenge for investors. Therefore, a proper forecasting method is needed to forecast the gold price so investors can know the best transaction time. This study used two forecasting methods: the Fuzzy Grey Markov Model (1,1) and a new, never-before-used approach, the Fuzzy Grey Markov Model (2,1). The Fuzzy Grey Markov Model (2,1) approach is interesting because it can be considered for forecast data that shows varying increases and decreases, such as the gold price data used in this study. Both methods are combined models that utilize fuzzy logic to handle uncertainty in data; the Grey model forms a forecasting model, and the Markov chain determines the state transition probability matrix. Next, the error rates of the two methods are compared based on the Mean Absolute Percentage Error (MAPE) value to obtain the best forecasting method. As a result of this study, the Fuzzy Grey Markov Model (1,1) was chosen as the best forecasting method with a MAPE value of 0.28%.

Novel differential scanning calorimetry (DSC) application to select polyhydroxyalkanoate (PHA) producers correlating 3-hydroxyhexanoate (3-HHx) monomer with melting enthalpy.

Polyhydroxyalkanoate (PHA) is an environmental alternative to petroleum-based plastics because of its biodegradability. The polymer properties of PHA have been improved by the incorporation of different monomers. Traditionally, the monomer composition of PHA has been analyzed using gas chromatography (GC) and nuclear magnetic resonance (NMR), providing accurate monomer composition. However, sequential analysis of the thermal properties of PHA using differential scanning calorimetry (DSC) remains necessary, providing crucial insights into its thermal characteristics. To shorten the monomer composition and thermal property analysis, we directly applied DSC to the analysis of the obtained PHA film and observed a high correlation (r2 = 0.98) between melting enthalpy and the 3-hydroxyhexanoate (3-HHx) mole fraction in the polymer. A higher 3-HHx fraction resulted in a lower melting enthalpy as 3-HHx provided the polymer with higher flexibility. Based on this, we selected the poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (P(3HB-co-3HHx)) producing strain from Cupriavidus strains that newly screened and transformed with vectors containing P(3HB-co-3HHx) biosynthetic genes, achieving an average error rate below 1.8% between GC and DSC results. Cupriavidus sp. BK2 showed a high 3-HHx mole fraction, up to 10.38mol%, with Tm(℃) = 171.5 and ΔH of Tm (J/g) = 48.0, simultaneously detected via DSC. This study is an example of the expansion of DSC for PHA analysis from polymer science to microbial engineering.

Helicopter cockpit speech recognition method based on transfer learning and context biasing

Abstract Currently, Chinese speech recognition technology is generally designed for common domains, primarily focusing on accurate recognition of standard Mandarin Chinese in low-noise environments. However, helicopter cockpit speech presents unique challenges, characterized by high-noise environments, specific industry jargon, low contextual relevance, and a lack of publicly available datasets. To address these issues, this paper proposes a helicopter cockpit speech recognition method based on transfer learning and context biasing. By fine-tuning a general speech recognition model, we aim to better adapt it to the characteristics of speech in helicopter cockpits. This study explores noise reduction processing, context biasing, and speed perturbation in helicopter cockpit speech data. Combining pre-trained models with language models, we conduct transfer training to develop a specialized model for helicopter cockpit speech recognition. Finally, the effectiveness of this method is validated using a real dataset. Experimental results show that, on the helicopter speech dataset, this method reduces the word error rate from 72.69% to 12.58%. Furthermore, this approach provides an effective solution for small-sample speech recognition, enhancing model performance on limited datasets.

Automatic Speech Recognition in Primary Progressive Apraxia of Speech

Introduction: Transcribing disordered speech can be useful when diagnosing motor speech disorders such as primary progressive apraxia of speech (PPAOS), who have sound additions, deletions, and substitutions, or distortions and/or slow, segmented speech. Since transcribing speech can be a laborious process and requires an experienced listener, using automatic speech recognition (ASR) systems for diagnosis and treatment monitoring is appealing. This study evaluated the efficacy of a readily available ASR system (wav2vec 2.0) in transcribing speech of PPAOS patients to determine if the word error rate (WER) output by the ASR can differentiate between healthy speech and PPAOS and/or among its subtypes, whether WER correlates with AOS severity, and how the ASR's errors compare to those noted in manual transcriptions. Method: Forty-five patients with PPAOS and 22 healthy controls were recorded repeating 13 words, 3 times each, which were transcribed manually and using wav2vec 2.0. The WER and phonetic and prosodic speech errors were compared between groups, and ASR results were compared against manual transcriptions. Results: Mean overall WER was 0.88 for patients and 0.33 for controls. WER significantly correlated with AOS severity and accurately distinguished between patients and controls but not between AOS subtypes. The phonetic and prosodic errors from the ASR transcriptions were also unable to distinguish between subtypes, whereas errors calculated from human transcriptions were. There was poor agreement in the number of phonetic and prosodic errors between the ASR and human transcriptions. Conclusions: This study demonstrates that ASR can be useful in differentiating healthy from disordered speech and evaluating PPAOS severity but does not distinguish PPAOS subtypes. ASR transcriptions showed weak agreement with human transcriptions; thus, ASR may be a useful tool for the transcription of speech in PPAOS, but the research questions posed must be carefully considered within the context of its limitations. Supplemental Material: https://doi.org/10.23641/asha.26359417

Non‐linear phylogenetic regression using regularised kernels

Abstract Phylogenetic regression is a type of generalised least squares (GLS) method that incorporates a modelled covariance matrix based on the evolutionary relationships between species (i.e. phylogenetic relationships). While this method has found widespread use in hypothesis testing via phylogenetic comparative methods, such as phylogenetic ANOVA, its ability to account for non‐linear relationships has received little attention. To address this, here we implement a phylogenetic Kernel Ridge Regression (phyloKRR) method that utilises GLS in a high‐dimensional feature space, employing linear combinations of phylogenetically weighted data to account for non‐linearity. We analysed two biological datasets using the Radial Basis Function and linear kernel function. The first dataset contained morphometric data, while the second dataset comprised discrete trait data and diversification rates as response variable. Hyperparameter tuning of the model was achieved through cross‐validation rounds in the training set. In the tested biological datasets, phyloKRR reduced the error rate (as measured by RMSE) by around 20% compared to linear‐based regression when data did not exhibit linear relationships. In simulated datasets, the error rate decreased almost exponentially with the level of non‐linearity. These results show that introducing kernels into phylogenetic regression analysis presents a novel and promising tool for complementing phylogenetic comparative methods. We have integrated this method into Python package named phyloKRR, which is freely available at: https://github.com/ulises‐rosas/phylokrr.

Studying the influence of correction codes on coherent reception of M-PSK signals in the presence of noise and harmonic interference

Objectives. Signals with multiple phase shift keying (M-PSK) exhibiting good spectral and energy characteristics are successfully used in many information transmission systems. These include satellite communication systems, GPS, GLONASS, DVB/DVB-S2, and a set of IEEE 802.11 wireless communication standards. In radio communication channels, the useful signal is affected by various interferences in addition to noise. One of these is harmonic interference. As a result, high intensity harmonic interference practically destroys the reception of M-PSK signals. One of the important requirements for the quality of data transmission is the system error tolerance. There are different ways of improving the quality of information transmission. One of these is the use of corrective encoding technology. The aim of the paper is to assess the noise immunity of a coherent demodulator of M-PSK signals using Hamming codes (7,4) and (15,11), and convolutional encoding with Viterbi decoding algorithm (7,5) when receiving M-PSK signals under noise and harmonic interference in the communication channel.Methods. The methods of statistical radio engineering, optimal signal reception theory and computer simulation modeling were used.Results. Experimental dependencies of the bit error rate on the signal-to-noise ratio and on the intensity of harmonic interference of coherent reception of M-PSK signals in a channel with noise and harmonic interference were obtained using computer simulation modeling. This was done without using correction codes and with Hamming code (7.4) and (15.11) and convolutional encoding with Viterbi decoding algorithm (7,5).Conclusions. It is shown that the application of the correction codes effectively corrects errors in the presence of noise and harmonic interference with lower intensity. The correction is ineffective in the presence of high intensity interference. These results can provide important guidance in designing the reliable and energy efficient system.

Automatic variable extraction from 3D coxal bone models for sex estimation using the DSP2 method.

Thanks to technical progress and the availability of virtual data, sex estimation methods as part of a biological profile are undergoing an inevitable evolution. Further reductions in subjectivity, but potentially also in measurement errors, can be brought by approaches that automate the extraction of variables. Such automatization also significantly accelerates and facilitates the specialist's work. The aim of this study is (1) to apply a previously proposed algorithm (Kuchař et al. 2021) to automatically extract 10 variables used for the DSP2 sex estimation method, and (2) to test the robustness of the new automatic approach in a current heterogeneous population. For the first aim, we used a sample of 240 3D scans of pelvic bones from the same individuals, which were measured manually for the DSP database. For the second aim a sample of 108 pelvic bones from the New Mexico Decedent Image Database was used. The results showed high agreement between automatic and manual measurements with rTEM below 5% for all dimensions except two. The accuracy of final sex estimates based on all 10 variables was excellent (error rate 0.3%). However, we observed a higher number of undetermined individuals in the Portuguese sample (25% of males) and the New Mexican sample (36.5% of females). In conclusion, the procedure for automatic dimension extraction was successfully applied both to a different type of data and to a heterogeneous population.

Implicit and Explicit Sequence Learning in Adults With Developmental Language Disorder.

Developmental language disorder (DLD) is a neurodevelopmental disorder that impacts approximately 7% of the population and is characterized by unexplained deficits in expressive and/or receptive components of language. A common procedural learning task, serial reaction time (SRT), has been used to develop models of the basis of DLD. However, paradigms involve differing levels of implicit and explicit learning during this task, muddying interpretations of the data. Here, we tested adults with DLD on implicit and explicit SRT tasks to better understand implicit and explicit procedural learning in this population. We hypothesized that adults with DLD would demonstrate reduced learning on only the implicit SRT task, as alternate explicit neural mechanisms could lead to equivalent performance on the explicit task. Fifty participants (25 with DLD and 25 with typical language) completed implicit and explicit SRT tasks, measuring their ability to learn visually presented 10-element sequences. Group differences were evaluated on sequence learning, error rates, and explicit recall of the sequence after learning. Sequence learning was the same between the groups on both tasks. However, individuals with DLD showed increased errors and significantly worse recall of the explicitly learned sequence. Results suggest that sequence learning may be intact in this population, while aspects of explicit learning and motoric responses are impaired. Results are interpreted in light of a neurobiological model of DLD. https://doi.org/10.23641/asha.26210651.

Stereo Matching Method with Cost Volume Collaborative Filtering

Aiming at the problem of matching ambiguity and low disparity accuracy at the object boundary in stereo matching, a novel stereo matching algorithm with cost volume collaborative filtering is proposed. Firstly, for each pixel, two support windows are built, namely a local cross- support window as well as a global support window for the whole image. Secondly, a new adaptive weighted guide filter with a cross-support window as a kernel window is derived, and it is used to locally filter the cost volume. In addition, a minimum spanning tree is constructed in the whole image window, and then the minimum spanning tree filter is used to globally filter the cost volume. The collaborative filtering of cost volume is realized by fusing the filtering results of the local filter and global filter, so that each pixel can not only receive the support of the neighboring pixels in the local adaptive window, but can also receive the effective support of other pixels in the whole image, thus effectively eliminating the matching ambiguity in different texture regions while maintaining the disparity edges. The experimental results show that the average matching error rate of our method on the Middlebury stereo images is 3.17%. Compared with the other state-of-the-art methods, our method has higher robustness and matching accuracy, the generated disparity maps are smoother, and the disparity edges are better preserved.

Improving the safety of radiotherapy treatment processes via incident-driven FMEA feedback loops.

Failure mode and effects analysis (FMEA) is a valuable tool for radiotherapy risk assessment, yet its outputs might be unreliable due to failures not being identified or due to a lack of accurate error rates. A novel incident reporting system (IRS) linked to an FMEA database was tested and evaluated. The study investigated whether the system was suitable for validating a previously performed analysis and whether it could provide accurate error rates to support the expert occurrence ratings of previously identified failure modes. Twenty-three pre-identified failure modes of our external beam radiotherapy process, covering the process steps from patient admission to treatment delivery, were proffered on dedicated FMEA feedback and incident reporting terminals generated by the IRS. The clinical setting involved a computed tomography scanner, dosimetry, and five linacs. Incoming reports were used as basis to identify additional failure modes or confirm initial ones. The Kruskal-Wallis H test was applied to compare the risk priorities of the retrospective and prospective failure modes. Wald's sequential probability ratio test was used to investigate the correctness of the experts' occurrence ratings by means of the number of incoming reports. Over a 15-month period, 304 reports were submitted. There were 0.005 (confidence interval [CI], 0.0014-0.0082) reported incidents per imaging study and 0.0006 (CI, 0.0003-0.0009) reported incidents per treatment fraction. Sixteen additional failure modes could be identified, and their risk priorities did not differ from those of the initial failure modes (p=0.954). One failure mode occurrence rating could be increased, whereas the other 22 occurrence ratings could not be disproved. Our approach is suitable for validating FMEAs and deducing additional failure modes on a continual basis. Accurate error rates can only be provided if a sufficient number of reports is available.

Effect of single-photon emission computed tomography acquisition method and sampling angles on image quality and quantitative accuracy in xSPECT-reconstructed images.

The aim of this study was to evaluate the effects of the single-photon emission computed tomography (SPECT) acquisition method and sampling angles on the qualitative and quantitative interpretations of xSPECT-reconstructed images. The spatial resolution was evaluated using a JSP phantom, and the uniformity and quantitative accuracy were verified with a NEMA IEC Body Phantom using an SIEMENS Symbia Intevo SPECT/computed tomography system. SPECT was performed using three acquisition methods (step-and-shoot, continuous, and acquire during the step), and the sampling angles were set to 2, 3, 4, 5, and 6°. The xSPECT-reconstruction technology which is used with ordered subset-conjugated gradient minimization was used for image reconstruction. Full width of half maximum, an evaluation index of spatial resolution, varied up to 2.73 mm with different sampling angles and up to 2.06 mm with different acquisition methods. Uniformity, as assessed by the coefficient of variation, improved with increasing sampling angles. The accuracy of the quantification of the hot sphere showed an error rate of approximately 10% depending on the sampling angle, and an error rate of approximately 5% depending on the different acquisition methods. In xSPECT-reconstructed images, the difference in sampling angle has a greater impact on image quality and quantitativity than the difference in the acquisition method. For tests in which uniformity is important, a larger sampling angle is recommended.

Enhanced fingerprint classification through modified PCA with SVD and invariant moments

This research introduces a novel MOMENTS-SVD vector for fingerprint identification, combining invariant moments and SVD (Singular Value Decomposition), enhanced by a modified PCA (Principal Component Analysis). Our method extracts unique fingerprint features using SVD and invariant moments, followed by classification with Euclidean distance and neural networks. The MOMENTS-SVD vector reduces computational complexity by outperforming current models. Using the Equal Error Rate (EER) and ROC curve, a comparative study across databases (CASIA V5, FVC 2002, 2004, 2006) assesses our method against ResNet, VGG19, Neuro Fuzzy, DCT Features, and Invariant Moments, proving enhanced accuracy and robustness.

Highly accurate single-color fluorogenic DNA decoding sequencing for mutational genotyping

We proposed a single-color fluorogenic DNA decoding sequencing method designed to improve sequencing accuracy, increase read length and throughput, as well as decrease scanning time. This method involves the incorporation of a mixture of four types of 3’-O-modified nucleotide reversible terminators into each reaction. Among them, two nucleotides are labeled with the same fluorophore, while the remaining two are unlabeled. Only one nucleotide can be extended in each reaction, and an encoding that partially defines base composition can be obtained. Through cyclic interrogation of a template twice with different nucleotide combinations, two sets of encodings are sequentially obtained, enabling the determination of the sequence. We demonstrate the feasibility of this method using established sequencing chemistry, achieving a cycle efficiency of approximately 99.5 %. Notably, this strategy exhibits remarkable efficacy in the detection and correction of sequencing errors, achieving a theoretical error rate of 0.00016 % at a sequencing depth of ×2, which is lower than Sanger sequencing. This method is theoretically compatible with the existing sequencing-by-synthesis (SBS) platforms, and the instrument is simpler, which may facilitate further reductions in sequencing costs, thereby broadening its applications in biology and medicine. Moreover, we demonstrate the capability to detect known mutation sites using information from only a single sequencing run. We validate this approach by accurately identifying a mutation site in the human mitochondrial DNA.

Adaptive Frame Structure Design for Sensing-Assisted Downlink Communication in the Vehicle-to-Infrastructure Scenario

Vehicle-to-everything (V2X) is considered a key factor in driving the future development of intelligent transport, which requires high-quality communication and fast sensing of vehicle information in high-speed mobile scenarios. However, high-speed mobility makes the wireless channel change rapidly, which requires frequent channel estimation and channel feedback between a vehicle and the roadside unit (RSU), resulting in an increase in communication overhead. At the same time, the high maneuverability of vehicles leads to frequent switching and misalignment of communication beams, so the RSU must have better beam prediction and tracking capabilities. To address this problem, this paper proposes an adaptive frame structure design scheme for sensing-assisted downlink (DL) communication. The basic idea of the scheme involves analyzing the communication model during the vehicle’s movement. This analysis aims to establish a theoretical relationship between the Symbol Error Rate (SER) and the following two key factors: the vehicle’s starting position and the distance it travels across. Subsequently, the scheme leverages the vehicle’s position data, as detected by the RSU, to calculate the real-time SER for DL communication. The SER threshold is set based on the requirements of DL communication. If the real-time SER is below this threshold, channel estimation becomes unnecessary. This decreases the frequency of channel estimation and frees up time and frequency resources that would otherwise be occupied by channel estimation processes within the frame structure. The design of an adaptive frame structure, as detailed in the above scheme, is presented. Furthermore, the performance of the proposed method is analyzed and compared with that of the traditional communication protocol frame structure and the beam prediction-based frame structure. The simulation results indicate that the communication throughput of the proposed method can be improved by up to 6% compared with the traditional communication protocol frame structure while maintaining SER performance.

Design and Implementation of Real-Time Sensors for Three-Phase Induction Motor Performance Monitoring using Internet of Thing (IoT)

This article delves into the design and implementation of cost-effective sensors tailored for real-time monitoring of three-phase induction motor performance. The research primarily centers on the assessment of the operational effectiveness of a suite of sensors, including the PZEM-004t power sensor, MLX90614 temperature sensors, NJK-5002C rotation sensors, and ADXL345 vibration sensors, within the context of three-phase induction motor performance analysis. The monitoring system for three-phase induction motor performance is built around the ESP-32 platform, incorporating the ADXL345 vibration sensor. This article successfully presents the individual sensor performance, which was systematically evaluated through testing on a three-phase induction motor that had been meticulously designed and closely observed. The unit tests reveal that all sensors employed in the experiments exhibit an average error rate of less than 5%. When assessed as an integrated system, the three-phase induction motor performance monitoring system demonstrates robust functionality, effectively measuring critical variables such as voltage, current, power factor, temperature, vibration, and rotational speed.