Journal of Signal Processing

ICH Segmentation Accuracy Improvement Using Gaussian Filtering

Anisa Kumari A — 2023-10-12

Intracranial Hemorrhage (ICH) refers to bleeding inside the skull, which can have various causes such as head trauma, arterial blockage, and blood clotting disorders. Timely detection of ICH in Head Computed Tomography (CT) scans is crucial for improved patient outcomes. However, limited expertise in interpreting CT scans can lead to missed haemorrhage diagnoses. To address this, we propose a computer-aided diagnosis model that employs deep learning techniques and Gaussian filtering for pre-processing. Gaussian filtering is employed as a pre-processing step to enhance CT scan images, effectively reducing noise and enhancing image quality. The filtered images are then subjected to an advanced and highly developed segmentation algorithm customized to identify ICH regions with precision. A deep learning architecture called U net is utilized to segment the haemorrhage region from the CT scan of the head. By incorporating Gaussian filtering into the workflow, we have significantly improved the accuracy of ICH segmentation. Our empirical findings underscore substantial progress in segmentation accuracy. Through attentive testing, our approach achieves remarkable precision and recall rates, for the particular problem. This heightened accuracy has great remarks for patient care, enabling clinicians to identify and treat intracranial haemorrhages more effectively and quickly. Our experimental results demonstrate a significant improvement in testing accuracy, achieving 99.82%.

Number Stations, their Analysis with Python Signal Processing Library, FFT Algorithm and their use in Global Espionage

Archit Sood — 2023-10-31

Number stations are shortwave radio stations that send encrypted messages to clandestine operators on the field. These stations have been used for many years, but their existence has long been mysterious. This paper investigates how to analyze radio station signals using Python and the SciPy module. The history of number stations and the methods used to encrypt their signals are covered in the first section of this paper. The Fourier transform and the Fast Fourier Transform technique, which we'll employ to analyze the signals, are next briefly discussed. A WebSDR, or a Software-Defined Radio receiver, a web-based radio receiver we use to receive and record the audio, is part of our experimental setup. It also attempts to describe our experimental setup, which consists of a WebSDR, or Software-Defined Radio receiver, a web-based radio receiver that we use to receive, record, and analyze signals. The study's findings are then shown, along with frequency spectra and spectrograms of various number station signals.

Fuzzy Logic-Based GPS Bus Tracking System for Enhanced Arrival Time Prediction

Jabin A. Mulla — 2023-12-06

In urban transportation, predicting precise bus arrival times is crucial for both passenger satisfaction and system optimization. This research introduces an innovative methodology within a GPS-based bus tracking system, harnessing the power of fuzzy logic to address inherent uncertainties in transit operations. The approach intricately incorporates membership functions, fuzzy rules, and inference mechanisms to enhance the accuracy of bus arrival time predictions. Through rigorous empirical evaluation, the system showcases its effectiveness in navigating the complexities of urban transit, offering improved precision in predicting bus arrival times. This contribution to the transportation engineering domain emphasizes the significant potential of fuzzy logic in elevating the efficiency of public transportation operations and enhancing the overall passenger experience. The findings underscore the practical application of fuzzy logic in tackling real-world uncertainties, marking a notable advancement in the realm of urban transit planning and management.

Signature Authentication Using AI -ML

Aditya Gadhave — 2023-12-12

This paper aims to provide an overview of a fundamental approach to signature detection and identification using standard Python and machine learning libraries. To address the challenge of image recognition, a binary classification process has been used to forecast text or signatures, and signature classifications have been conducted to identify the signer of each signature. The proposed algorithm functions to extract the signature area from scanned documents containing signatures and send it to the trained signature images during the pre-processing stage. The research findings are shown for documents of the same kind, with the signature at the same location. Tensor-slicing techniques applied to NumPy arrays are utilized to pinpoint a particular element within the document. Text and signature-containing areas are extracted using OpenCV tools. Promising results have been observed when certain writers' signatures are recognized. The proposed method illustrates how certain real-world problems can be resolved using classical Python and machine learning libraries.

IoT-Based Smart Key Finder For Smart Home Applications

Rambabu Kambhampati — 2023-12-21

Usually, when we misplace our keys, we have to look all over the house for them before we finally locate them though not always easily. Therefore, we suggest building a basic Internet of Things key finder in this work using a buzzer, battery, and Node-MCU. The construction of a key chain that is attached to a key will be discussed in this essay. The establishment of a website devoted to the hunt for the missing keys is also mentioned in the report. The Google Chrome browser on a mobile device can be used to find the missing keys. A buzzer built into the Internet of Things keychain will sound an alert when the website locates the misplaced keys. The developed Internet of Things (IoT)-based key finder is crucial for maintaining track of the keys in addition to saving time.