Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

The growing interest in the use of chaotic techniques for enabling secure communication in recent years has been motivated by the emergence of a number of wireless services which require the service provider to provide low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. While the use of Chaotic maps can enhance security, it is seen that the overall BER performance gets degraded when compared to conventional communication schemes. In order to overcome this limitation, we have proposed the use of a combination of Chaotic modulation and Alamouti Space Time Block Code. The performance of Chaos Shift Keying (CSK) wi

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

The  thermal  and  electrical  performance  of  different  designs  of  air  based  hybrid photovoltaic/thermal collectors is investigated experimentally and theoretically. The circulating air is used to cool PV panels and to collect the absorbed energy to improve their performance. Four different collectors have been designed, manufactured and instrumented namely; double PV panels without cooling (model I), single duct double pass collector (model II), double duct single pass (model III), and single duct single pass (model IV) . Each collector consists of: channel duct, glass cover, axial fan to circulate air and two PV panel in parallel connection. The temperature of the upper and

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con

There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input Multiple-Output (MIMO) channels by combining chaos modulation with a suitable Space Time Block Code (STBC). It is well known that the use of Chaotic Modulation techniques can enhance communication security. However, the performance of systems using Chaos modulation has been observed to be inferior in BER performance as compared to conventional communication

          Graphite Coated Electrodes (GCE) based on molecularly imprinted polymers were fabricated for the selective potentiometric determination of Risperidone (Ris). The molecularly imprinted (MIP) and nonimprinted (NIP) polymers were synthesized by bulk polymerization using (Ris.) as a template, acrylic acid (AA) and acrylamide (AAm) as monomers, ethylene glycol dimethacrylate (EGDMA) as a cross-linker and benzoyl peroxide (BPO) as an initiator. The imprinted membranes and the non-imprinted membranes were prepared using dioctyl phthalate (DOP) and Dibutylphthalate (DBP) as plasticizers in PVC matrix. The membranes were coated on graphite electrodes. The MIP electrodes using

Medical imaging is a technique that has been used for diagnosis and treatment of a large number of diseases. Therefore it has become necessary to conduct a good image processing to extract the finest desired result and information. In this study, genetic algorithm (GA)-based clustering technique (K-means and Fuzzy C Means (FCM)) were used to segment thyroid Computed Tomography (CT) images to an extraction thyroid tumor. Traditional GA, K-means and FCM algorithms were applied separately on the original images and on the enhanced image with Anisotropic Diffusion Filter (ADF). The resulting cluster centers from K-means and FCM were used as the initial population in GA for the implementation of GAK-Mean and GAFCM. Jaccard index was used to s