Water buffalo (Bubalus bubalis) is an important source of meat and milk in countries with relatively warm weather. Compared to the cattle genome, a little has been done to reveal its genome structure and genomic traits. This is due to the complications stemming from the large genome size, the complexity of the genome, and the high repetitive content. In this paper, we introduce a high-quality draft assembly of the Egyptian water buffalo genome. The Egyptian breed is used as a dual purpose animal (milk/meat). It is distinguished by its adaptability to the local environment, quality of feed

Using stochastic geometry, this letter studies the retransmission performance in uplink cellular networks with fractional path-loss inversion power control (FPC). We first show that the signal-to-interference-ratio (SIR) is correlated across time, which imposes temporal diversity loss in the retransmission performance. In particular, FPC with lower path-loss compensation factor decreases inter-cell interference but suffers from degraded retransmission diversity. On the other hand, full path-loss inversion achieves almost full temporal diversity (i.e., temporal SIR independence) at the expense

This paper is concerned with the evaluation of nuclear research reactor under two types of predictive controllers. The first one is Receding Horizon Predictive Controller (RHPC) which is considered a simple linear predictive controller. The other one is Neural Network Predictive Controller (NNPC) which is a type of nonlinear predictive controller. These controllers are applied over multi-point reactor core model. This model takes into consideration the nonlinearity of the reactor. It also takes into consideration some important physical phenomena like temperature effect, time variant fuel

Predicting the remaining cycle time of running cases is one important use case of predictive process monitoring. Different approaches that learn from event logs, e.g., relying on an existing representation of the process or leveraging machine learning approaches, have been proposed in literature to tackle this problem. Machine learning-based techniques have shown superiority over other techniques with respect to the accuracy of the prediction as well as freedom from knowledge about the underlying process models generating the logs. However, all proposed approaches learn from complete traces

Left ventricle (LV) segmentation is crucial to assess left ventricle global function. U-Net; a Convolutional Neural Network (CNN); boosted the performance of many biomedical image segmentation tasks. In LV segmentation, U-Net suffered from accurately extracting small objects such as the apical short-axis slices. In this paper, we propose a fully automated left ventricle segmentation method for both short-axis and long-axis views. The proposed model utilizes U-Net architecture and Multi-Gate input block to enhance the performance by aggregating multi-scale features and adding different vision

This paper proposes an efficient and secure quantum video encryption algorithm for quantum videos based on qubit-planes controlled-XOR operations and improved logistic map in multi-layer encryption steps. Three simple cryptosystem steps are presented in the proposed approach to accomplish the whole encryption process: inter-frame permutation, intra-frame pixel position geometric transformation, and high 4-intra-frame-qubit-planes scrambling. Firstly, the inter-frame positions of quantum video are permutated via inter-frame permutation that is controlled by the keys which are generated by

Current security issues in mobile networks have great impact on user privacy. With the focus directed to signaling protocols security, network security and air interface encryption, critical configurations and design flaws that would impact user privacy can be overlooked. The leakage of IMSI on the broadcast channels during network paging is a privacy issue worth considering. In this paper, we present an experimental analysis for the IMSI leakage in the GSM broadcast channels during the paging procedure and the impact of this type of passive attack on user's privacy. © 2018 IEEE.

Cancer is a group of diseases that involve abnormal cell growth with the potential to spread to other parts of the body. Cancer microarray data usually include a small number of samples with a large number of gene expression levels as features. Gene expression or microarray is a technology that monitors the expression of the large number of genes in parallel that make it useful in cancer classification, high dimensionality in cancer microarray data results in the overfitting problem. This article proposes novel hybrid feature selection model called the RBARegulizer model, which is based on two

The Increasing number of mobiles and handheld devices that allow wireless access to enterprise data and services is considered a major concern for network designers, implementers and analysts. Enhancements of wireless technologies also accelerate the adoptions of enterprise wireless networks that are widely deployed solely or as an extension to existing wired networks. Bring Your Own Device is an example of the new challenging wireless trends. BYOD environments allow the use of personal mobile computing devices like smart phones, tablets, and laptops for business activities. BYOD has become

The recommendation system, also known as recommender system or recommendation engine/platform, is considered as an interdisciplinary field. It uses the techniques of more than one field. Recommender system inherits approaches from all of machine learning, data mining, information retrieval, information filtering and human-computer interaction. In this paper, we propose our value-added architecture of the hybrid information filtering engine for job recommender system (HIFE-JRS). We discuss our developed system’s components to filter the most relevant information and produce the most