One of the most interested problems that recently attracts many research investigations in Protein-protein interactions (PPI) networks is complex detection problem. Detecting natural divisions in such complex networks is proved to be extremely NP-hard problem wherein, recently, the field of Evolutionary Algorithms (EAs) reveals positive results. The contribution of this work is to introduce a heuristic operator, called protein-complex attraction and repulsion, which is especially tailored for the complex detection problem and to enable the EA to improve its detection ability. The proposed heuristic operator is designed to fine-grain the structure of a complex by dividing it into two more complexes, each being distinguished with a core protein. Then, it is possible for each of the remaining proteins associated with the original coarse-grained complex to repulse from one of the new generated complexes while attracted by the core protein of the second complex. The topology-based complex detection models presented in the literature are adopted to inter-play with the proposed heuristic operator inside the EA general framework. To assess the performance of the EA when coupled with the proposed heuristic operator, the well known Saccaromycaes Cerevisiae yeast PPI network and one reference set of benchmark complexes created from MIPS are used in the experiments. The results prove the positive impact of the heuristic operator to harness the strength of almost all adopted EA models.
The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca
... Show MoreThis paper presents a study of a syndrome coding scheme for different binary linear error correcting codes that refer to the code families such as BCH, BKLC, Golay, and Hamming. The study is implemented on Wyner’s wiretap channel model when the main channel is error-free and the eavesdropper channel is a binary symmetric channel with crossover error probability (0 < Pe ≤ 0.5) to show the security performance of error correcting codes while used in the single-staged syndrome coding scheme in terms of equivocation rate. Generally, these codes are not designed for secure information transmission, and they have low equivocation rates when they are used in the syndrome coding scheme. Therefore, to improve the transmiss
... Show MorePlanning of electrical distribution networks is considered of highest priority at the present time in Iraq, due to the huge increase in electrical demand and expansions imposed on distribution networks as a result of the great and rapid urban development.
Distribution system planning simulates and studies the behavior of electrical distribution networks under different operating conditions. The study provide understanding of the existing system and to prepare a short term development plan or a long term plan used to guide system expansion and future investments needed for improved network performance.
The objective of this research is the planning of Al_Bayaa 11 kV distribution network in Baghdad city bas
... Show MoreWastewater recycling for non-potable uses has gained significant attention to mitigate the high pressure on freshwater resources. This requires using a sustainable technique to treat natural municipal wastewater as an alternative to conventional methods, especially in arid and semi-arid rural areas. One of the promising techniques applied to satisfy the objective of wastewater reuse is the constructed wetlands (CWs) which have been used extensively in most countries worldwide through the last decades. The present study introduces a significant review of the definition, classification, and components of CWs, identifying the mechanisms controlling the removal process within such units. Vertical, horizontal, and hybrid CWs
... Show MoreThe study aims to identify the impact of the round-robin strategy on the logical thinking of fourth-year middle school students in chemistry. Two groups were employed: an experimental group consisted of (30) students who were taught according to the round-robin strategy, and the control group consisted of (30) students who were taught according to the traditional method. The researcher adopted the experimental design with partial control by preparing the visual thinking test tool, which consists of (20) multiple-choice items, it was applied as a post-test on the research sample. The result showed that there was a statistically significant difference in favor of the experimental group, which was taught according to the Round Robin s
... Show MoreInformation centric networking (ICN) is the next generation of internet architecture with its ability to provide in-network caching that make users retrieve their data efficiently regardless of their location. In ICN, security is applied to data itself rather than communication channels or devices. In-network caches are vulnerable to many types of attacks, such as cache poisoning attacks, cache privacy attacks, and cache pollution attacks (CPA). An attacker floods non-popular content to the network and makes the caches evict popular ones. As a result, the cache hit ratio for legitimate users will suffer from a performance degradation and an increase in the content’s retrieval latency. In this paper, a popularity variation me
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreThe present study aims to present a proposed realistic and comprehensive cyber strategy for the Communications Directorate for the next five years (2022-2026) based on the extent of application and documentation of cybersecurity measures in the Directorate and the scientific bases formulating the strategy. The present study is significant in that it provides an accurate diagnosis of the capabilities of the cyber directorate in terms of strengths and weaknesses in its internal environment and the opportunities and threats that surround it in the external environment, based on the results of the assessment of the reality of cybersecurity according to the global Cybersecurity index, which provides a strong basis for building its strategic dire
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