Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two supervised machine learning classification techniques, Learning Vector Quantization (LVQ) and Support Vector Machine (SVM) classifiers, to achieve better search performance and high classification accuracy in a heterogeneous WBASN. These classification techniques are responsible for categorizing each incoming packet into normal, critical, or very critical, depending on the patient's condition, so that any problem affecting him can be addressed promptly. Comparative analyses reveal that LVQ outperforms SVM in terms of accuracy at 91.45% and 80%, respectively.
In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates
... Show More—Medical images have recently played a significant role in the diagnosis and detection of various diseases. Medical imaging can provide a means of direct visualization to observe through the human body and notice the small anatomical change and biological processes associated by different biological and physical parameters. To achieve a more accurate and reliable diagnosis, nowadays, varieties of computer aided detection (CAD) and computer-aided diagnosis (CADx) approaches have been established to help interpretation of the medical images. The CAD has become among the many major research subjects in diagnostic radiology and medical imaging. In this work we study the improvement in accuracy of detection of CAD system when comb
... Show MoreThe sending of information at the present time requires the speed and providing protection for it. So compression of the data is used in order to provide speed and encryption is used in order to provide protection. In this paper a proposed method is presented in order to provide compression and security for the secret information before sending it. The proposed method based on especial keys with MTF transform method to provide compression and based on RNA coding with MTF encoding method to provide security. The proposed method based on multi secret keys. Every key is designed in an especial way. The main reason in designing these keys in special way is to protect these keys from the predication of the unauthorized users.
Gypsiferous soil deposits (Gypcrete) are weakly consolidate earthy mixture of secondary gypsum, sand and clay. It is formed in arid and semi- arid area with annual precipitation rainfall less than 400mm. These sediments occur in surface and subsurface in region of little rainfall and rapid evaporation. This research deals with the study of gypcrete in Alexandria to improve the mineralogical and geochemical properties of the gypcrete. The gypcrete soil is used as raw material to produce the plaster for building purposes. Three samples of gypcrete were chemically and geochemically analyzed. The common mineral is howed in 0-0.5m Gypsum followed by Calcite in 0-1m and Quartz in 1-1.5m due to leaching and infiltration by rainfall as well as it
... Show MoreThis paper deals with a preliminary survey helminth parasites of the black partridge. Francolinus francolinus arabistanicus in Baghdad area, middle of Iraq. It was found that the bird was infected with the cestodes Cotugnia digonopora and Raillietina tetragona with infection rates of 61.9% and 4.8% respectively, and the nematodes Heterakis gallinarum and Paroneoccrca rouss-lotti with infection rates of 4.8% and 19% respectively. Some important measurements, distribution and occurrence according host-sex of each parasite were provided along with some remarks on parasites biology.
An interpretive (structural and stratigraphic) study of the two,-dimensional seismic, data of East Nasiriya area (30 km to the south east of Nasiriya oil field within Thi-Qar province, southeastern Iraq) was carried out using Petrel 2017 program. The study area has an importance due to its location between many oil fields, but still without exploration of oil wells. Twenty five seismic lines were used, date back to different types of seismic surveys conducted in the region at different time periods. Also, the seismic velocity surveys of the nearest wells to oil fields, such as Nasiriya-1 and Subba-8, in addition to their sonic and density logs were used. A synthetic seismogram with a good matching with the seismic section was achie
... Show MoreThis paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward
... Show MoreThis research is focused on an interpretive of 2D seismic data to study is reinterpreting seismic data by applying sufficient software (Petrel 2017) of the area between Al-Razzazah Lake and the Euphrates river belonging to Karbala'a and Al-Anbar Governorates, central Iraq. The delineation of the sub-surface structural features and evaluation of the structure of Najmah and Zubair Formations was done. The structure interpretation showed that the studied area was affected by normal fault bearing (NW-SE) direction with a small displacement. In contrast, time and depth maps showed monocline structures (nose structures) located in the western part of the studied area.