Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition using the recent artificial intelligent algorithms, the conventional neural network (CNN). Different CNN models were tested and modified to produce a system has two important features high performance accuracy and less testing time. These features are the most important factors for real time applications. The experimental results were conducted on a dataset includes over 400,000 handwritten names; the best performance accuracy results were 99.8% for SqueezeNet model.
Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,
... Show MoreThis study includes using green or biosynthesis-friendly technology, which is effective in terms of low cost and low time and energy to prepare V2O5NPs nanoparticles from vanadium sulfate VSO4.H2O using aqueous extract of Punica Granatum at a concentration of 0.1M and with a basic medium PH= 8-12. The V2O5NPs nanoparticles were diagnosed using several techniques, such as FT-IR, UV-visible with energy gap Eg = 3.734eV, and the X-Ray diffraction XRD was calculated using the Debye Scherrer equation. It was discovered to be 34.39nm, Scanning Electron Microscope (SEM), Transmission Electron Microscopy TEM. The size, structure, and composition of synthetic V2O5NPs were determined using the (EDX) pattern, Atomic force microscopy AFM. The a
... Show MoreA simple and accurate method to determinate furosemide (FUR) based on converting the secondary amine to primary amine with acidic hydrolysis then azotization by nitrous acid and coupled with resorcinol as a coupling agent in aqueous medium at pH 13. The optical characteristic like beers law limit found to be (0.25-2.5) μg.ml−1, detection and quantification limits (0.0196) (0.0654) μg.ml−1respectivly and Sandel sensitivity was 0.006738 μg.cm−2. The least-square method was used to evaluate the regression equation and the correlation coefficient. The resulted azo dye has a maximum absorbance at 430 nm with light oran
Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are
... Show MoreIn this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
... Show MoreRecording an Electromyogram (EMG) signal is essential for diagnostic procedures like muscle health assessment and motor neurons control. The EMG signals have been used as a source of control for powered prosthetics to support people to accomplish their activities of daily living (ADLs). This work deals with studying different types of hand grips and finding their relationship with EMG activity. Five subjects carried out four functional movements (fine pinch, tripod grip and grip with the middle and thumb finger, as well as the power grip). Hand dynamometer has been used to record the EMG activity from three muscles namely; Flexor Carpi Radialis (FCR), Flexor Digitorum Superficialis (FDS), and Abductor Pollicis Brevis (ABP) with different le
... Show MoreThe research aims to show the relationship between the use of automated accounting systems technology and its impact on enhancing the efficiency and effectiveness of the internal control system in a sample of Bahraini universities in light of the rapid changes in the electronic business environment. Automated accounting and its impact on enhancing the efficiency and effectiveness of the internal control system, and it is concluded through the analytical study of the research sample that there is a percenta
... Show MoreIn this research, the performance of a two kind of membrane was examined to recovering the nutrients (protein and lactose) from the whey produced by the soft cheese industry in the General Company for Food Products inAbo-ghraab.Wheyare treated in two stages, the first including press whey into micron filter made of poly vinylidene difluoride (PVDF) standard plate type 800 kilo dalton, The membrane separates the whey to permeate which represent is the main nutrients and to remove the fat and microorganisms.The second stage is to isolate the protein by using ultra filter made of polyethylsulphone(PES)type plate with a measurement of 10,60 kilo dalton and the recovery of lactose in the form of permeate.
The results showed that the percen