A four-levels hierarchical wireless body sensor network (WBSN) system is designed for biometrics and healthcare applications. It also separates pathways communication control. In order to improve performance, a cycle constructed synchronizing the WBSN with pipeline. low-power adaptive process necessity long-time monitoring. includes data encoder an power conserving algorithm within each node along accurate control switch The thermal consists of micro unit (MCU), bipolar junction transistor...

Caries is a dental disease caused by bacterial infection. If the cause of caries detected early, treatment will be relatively easy, which in turn prevents from spreading. The current common procedure dentists to first perform radiographic examination on patient and mark lesions manually. However, work judging markings requires professional experience very time-consuming repetitive. Taking advantage rapid development artificial intelligence imaging research technical methods help make...

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where lesion area is marked manually, which therefore time consuming. Additionally, some images significant details might not be recognizable due to different shooting angles or doses. To make diagnosis process shorter efficient, repetitive tasks should...

As the popularity of dental implants continues to grow at a rate about 14% per year, so do risks associated with procedure. Complications such as sinusitis and nerve damage are not uncommon, inadequate cleaning can lead peri-implantitis around implant, jeopardizing its stability potentially necessitating retreatment. To address this issue, research proposes new system for evaluating degree periodontal using Periapical film (PA). The utilizes two Convolutional Neural Networks (CNN) models...

In recent years, there has been a significant increase in collaboration between medical imaging and artificial intelligence technology. The use of automated techniques for detecting symptoms become increasingly prevalent. However, lack research on the relationship impacted teeth inferior alveolar nerve (IAN) DPR images. severe compression against IAN may necessitate requirement canal treatment. To reduce occurrence such events, this study aims to develop an auxiliary detection system capable...

The convergence of edge computing systems with Field-Programmable Gate Array (FPGA) technology has shown considerable promise in enhancing real-time applications across various domains. This paper presents an innovative system design specifically tailored for pavement defect detection within the Advanced Driver-Assistance Systems (ADASs) domain. seamlessly integrates AMD Xilinx AI platform into a customized circuit configuration, capitalizing on its capabilities. Utilizing cameras as input...

Common dental diseases include caries, periodontitis, missing teeth and restorations. Dentists still use manual methods to judge label lesions which is very time-consuming highly repetitive. This research proposal uses artificial intelligence combined with image judgment technology for an improved efficiency on the process. In terms of cropping in images, proposed study histogram equalization flat-field correction pixel value assignment. The details bone structure improves resolution...

Electrocardiogram (ECG) is the primary basis for diagnosis of cardiovascular diseases. However, amount ECG data patients makes manual interpretation time-consuming and onerous. Therefore, intelligent recognition technology an important means to decrease shortage medical resources. This study proposes a novel classification method arrhythmia that uses very first time three-heartbeat multi-lead (THML) in which each fragment contains three complete heartbeat processes multiple leads. The THML...

Furcation defects pose a significant challenge in the diagnosis and treatment planning of periodontal diseases. The accurate detection furcation involvements (FI) on periapical radiographs (PAs) is crucial for success therapy. This research proposes deep learning-based approach to defect using convolutional neural networks (CNN) with an accuracy rate 95%. has undergone rigorous review by Institutional Review Board (IRB) received accreditation under number 202002030B0C505. A dataset 300 teeth...

In the field of dentistry, presence dental calculus is a commonly encountered issue. If not addressed promptly, it has potential to lead gum inflammation and eventual tooth loss. Bitewing (BW) images play crucial role by providing comprehensive visual representation structure, allowing dentists examine hard-to-reach areas with precision during clinical assessments. This aid significantly aids in early detection calculus, facilitating timely interventions improving overall outcomes for...

In dental diagnosis, evaluating the severity of periodontal disease by analyzing radiographic defect angle intrabony is essential for effective treatment planning. However, dentists often rely on clinical examinations and manual analysis, which can be time-consuming labor-intensive. Due to high recurrence rate after treatment, accurately vital implementing targeted interventions, improve outcomes reduce recurrence. This study aims streamline practices enhance patient care in managing...

This study aims to establish an innovative AI-based social–emotional music classification model named SEM-Net, specifically designed integrate three core positive elements—positive outlook, empathy, and problem-solving—into classical music, facilitating accurate emotional of musical excerpts related states. SEM-Net employs a convolutional neural network (CNN) architecture composed 17 meticulously structured layers capture complex features effectively. To further enhance the precision...

With the rapid development of portable electronics, wearable devices have become widely used to monitor body signals for long-term health care and home applications. They detect vital through physiological sensors then transmit them a cloud database evaluation monitoring purposes wireless communication systems. In this paper, smart analog-to-digital converter (ADC) was realized by mixed-signal application-specific integrated circuit (ASIC) based on adaptive resolution lossless compression...

This study presents a low-power multi-lead wearable electrocardiogram (ECG) signal sensor system design that can simultaneously acquire the electrocardiograms from three leads, I, II, and V1. The includes two parts, an ECG test clothing with five electrode patches acquisition device. Compared traditional 12-lead wired detection instrument, which limits patient mobility needs medical staff assistance to signal, proposed vest-type is very comfortable easy use by patients themselves anytime...

The dental panoramic radiograph (DPR) is a pivotal diagnostic tool in dentistry. However, despite the growing prevalence of artificial intelligence (AI) across various medical domains, manual methods remain prevailing means interpreting DPR images. This study aims to introduce an advanced identification system for detecting seven conditions images by utilizing Faster R-CNN. primary objectives are enhance dentists' efficiency and evaluate performance CNN models as foundational training...

A novel scaling algorithm is proposed for the implementation of 2-D image scalar. The consists a bilinear interpolation, clamp filter, and sharpening spatial filter. interpolation selected due to its having low complexity high quality. filters are added as pre-filters solve blurring aliasing effects produced by interpolation. Furthermore, an adaptive technology used enhance filters. To reduce memory buffers computing resources very large scale integration (VLSI) implementation, filter both...

In this paper, a low-complexity adaptive edge-enhanced algorithm is proposed for the implementation of 2-D image scaling applications. The novel consists linear space-variant edge detector, low complexity sharpening spatial filter, and simplified bilinear interpolation. detector designed to discover edges by low-cost edge-catching technique. filter added as prefilter reduce blurring effect produced Furthermore, an technology used enhance adaptively selecting input pixels addition, algebraic...

In this brief, a low-complexity, low-memory-requirement, and high-quality algorithm is proposed for VLSI implementation of an image scaling processor. The consists sharpening spatial filter, clamp bilinear interpolation. To reduce the blurring aliasing artifacts produced by interpolation, filters are added as prefilters. minimize memory buffers computing resources processor design, T-model inversed convolution kernels created realizing filters. Furthermore, two or combined into filter which...

In this paper, a novel near-lossless color filter array (CFA) image compression algorithm based on JPEG-LS is proposed for VLSI implementation. It consists of pixel restoration, prediction, run mode, and entropy coding modules. According to the information previous research, context table row memory consumed more than 81% hardware cost in encoder design. Hence, context-free presented. Since removing model causes decreasing performance, modified Golomb-Rice techniques were used improve...

This paper presents a very large-scale integration (VLSI) circuit design of micro control unit (MCU) for wireless body sensor networks (WBSNs) in cost-intention. The proposed MCU consists an asynchronous interface, multisensor controller, register bank, hardware-shared filter, lossless compressor, encryption encoder, error correct coding (ECC) circuit, universal receiver/transmitter power management, and QRS complex detector. A hardware-sharing technique was added to reduce the silicon area...

Diverse computer-aided diagnosis systems based on convolutional neural networks were applied to automate the detection of myocardial infarction (MI) found in electrocardiogram (ECG) for early and prevention. However, issues, particularly overfitting underfitting, not being taken into account. In other words, it is unclear whether network structure too simple or complex. Toward this end, proposed models developed by starting with simplest structure: a multi-lead features-concatenate narrow...

For a daily dental practice, the Panoramic (PANO) X-ray film is one of most commonly used X-rays. One its important advantages coverage anatomic structures and clinical findings in single film. Important information about treatment diagnosis can be provided from expert analysis PANO. Combined with assistance artificial intelligence, application has great potential. The purpose this study was to propose an automated detection system based on several modern convolutional neural networks (CNNs)...

Global precipitation is becoming increasingly intense due to the extreme climate. Therefore, creating new technology manage water resources crucial. To create a sustainable urban and ecological environment, level quality control system implementing artificial intelligence presented in this research. The proposed smart monitoring consists of four sensors (two different liquid sensors, turbidity pH sensor, oxygen sensor), module (an MCU, motor, pump, drain), power communication (a solar panel,...

The severity of periodontitis can be analyzed by calculating the loss alveolar crest (ALC) level and bone between tooth's cemento-enamel junction (CEJ). However, dentists need to manually mark symptoms on periapical radiographs (PAs) assess loss, a process that is both time-consuming prone errors. This study proposes following new method contributes evaluation disease reduces Firstly, innovative image enhancement methods are employed improve PA quality. Subsequently, single teeth accurately...

A new Schmitt trigger circuit, which is implemented by low-voltage devices to receive the high-voltage input signals without gate-oxide reliability problem, proposed. The proposed can be operated in a 3.3-V signal environment suffering overstress, has been fabricated 0.13-/spl mu/m 1/2.5-V 1P8M CMOS process. experimental results have confirmed that measured transition threshold voltages of circuit are about 1 and 2.5 V, respectively. suitable for mixed-voltage input-output interfaces reject noise.