Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

  Computer software is frequently used for medical decision support systems in different areas. Magnetic Resonance Images (MRI) are widely used images for brain classification issue. This paper presents an improved method for brain classification of MRI images. The proposed method contains three phases, which are, feature extraction, dimensionality reduction, and an improved classification technique. In the first phase, the features of MRI images are obtained by discrete wavelet transform (DWT). In the second phase, the features of MRI images have been reduced, using principal component analysis (PCA). In the last (third) stage, an improved classifier is developed. In the proposed classifier, Dragonfly algorithm is used instead

In recent years, the number of applications utilizing mobile wireless sensor networks (WSNs) has increased, with the intent of localization for the purposes of monitoring and obtaining data from hazardous areas. Location of the event is very critical in WSN, as sensing data is almost meaningless without the location information. In this paper, two Monte Carlo based localization schemes termed MCL and MSL* are studied. MCL obtains its location through anchor nodes whereas MSL* uses both anchor nodes and normal nodes. The use of normal nodes would increase accuracy and reduce dependency on anchor nodes, but increases communication costs. For this reason, we introduce a new approach called low communication cost schemes to reduce communication

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

Wireless  lietworking is·  constantly improving,  changing  and

though  ba ic  principle  is the same.  ['nstead of  using standard  cables  to transmit information fmm one point to another (qr more), it .uses  radio signals.  This paper  presents .a case  study considedng real-time remote

cqntroJ using Wireless UDP/JP-based networks,. The aim of-this werk is to

reduce  real-time· remote control  system  based upon a simulatio.n  model,

which can operate via general communication  l"]etworks, whieh on bodies. modern wireles  tcchnolqgy.

The  first  part includes· a  brief

This study reported the investigation of the Radio Frequency (RF) signal propagation of Global System for Mobile Communications (GSM) coverage in Emmanuel Alayande College of Education (EACOED), Oyo, Oyo State, Nigeria. The study aims at amplifying the quality of service and augment end users' sensitivity of the wireless services operation. The drive test method is adopted with estimation of coverage level and received signal strength. The Network Cell Info Lite application installed in three INFINIX GSM mobile phones was employed to take the measurement of the signal strength received from the transmitting stations of different mobile networks. The results of the study revealed that MTN has the maximum signal strength with a mean value

The ongoing research to improve the clinical outcome of titanium implants has resulted in the implementation of multiple approaches to deliver osteogenic growth factors accelerating and sustaining osseointegration. Here we show the presentation of human bone morphogenetic protein 7 (BMP-7) adsorbed to titanium discs coated with poly(ethyl acrylate) (PEA). We have previously shown that PEA promotes fibronectin organization into nanonetworks exposing integrin- and growth-factor-binding domains, allowing a synergistic interaction at the integrin/growth factor receptor level. Here, titanium discs were coated with PEA and fibronectin and then decorated with ng/mL doses of BMP-7. Human mesenchymal stem cells were used to investigate cellular resp

Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al