Egypt faces wheat insecurity due to the limited cropped area of agricultural lands and the limited horizontal expansion disproportionate to the population increase. The issue of food security, crop consumption rates, and self-sufficiency is considered one of the most important problems facing countries that seek to improve sustainable agriculture and economic development to eliminate poverty or hunger. This research aims to use data mining classification techniques and decision tree algorithms to predict the food security status of strategic agricultural crops (e.g., wheat) as an Agro intelligence technique. Also, the outputs and extracted information from the prediction process will help decision-makers to take an appropriate decision to improve the self-sufficiency rate of wheat, especially in epidemic crises and hard times such as COVID-19, political, and economic disturbances. On the other hand, the research investigates the patterns of wheat production and consumption for the Egyptian population from 2005 to 2020. This research presents a methodology to predict the food security status of strategic agricultural crops through the case study of wheat in Egypt. The proposed model predicts the food security status of wheat with an accuracy of 92.3% to determine the self-sufficiency ratio of wheat in Egypt during the years from 2015 to 2020. Also, it identifies the factors affecting the food security status of wheat in Egypt, their impact on determining and improving the food security state and its rate of self-sufficiency.

Available data increase quickly every moment, this eventually drags to big data flooding. Hence there is an emergent need for exploiting big data in order to extract valuable knowledge from it. Adoption of distributed architecture and data intensive algorithms facilitates handling and processing big data. This paper introduces a distributed single pass clustering algorithm based on MapReduce in order to reduce running time of processing big data. Also, it introduces median based single pass clustering in order to mitigate the order of the input data problem that is associated with single pass clustering. Furthermore, it introduces a new hybrid approach which integrates median based single pass clustering and k-means algorithm. The proposed integration improves the median based clustering to work well with sparse data such as text.

Digital data that come from different applications
such as, wireless sensor, bioinformatics next generation
sequencing, and high throughput instruments are growing in
high rate. Dealing with demands of analysis of ever-growing
data requires new techniques in software, hardware, and
algorithms. MapReduce is a programming model initiated by
Google’s Team for processing huge datasets in
distributed
systems; it helps programmers to write programs that process
big data. The aim of this paper is to investigate MapReduce
research trends, and current research efforts for enhancing
MapReduce performance and capabilities. This Study
concluded that the research directions of MapReduce
concerned with either enhancing MapReduce programming
model or adopting MapReduce for deploying existing algorithm
to run with MapReduce programming model.

Multi Criteria Business Intelligence approach (MCBI) aims to enhance Business Intelligence Applications (BIA) by applying Multi-Criteria Decision Making (MCDM). MCBI approach contributes to improve Business Intelligence Decision Support System (BIDSS) for BIA. Also MCBI approach presents a standard method to evaluate and select business decisions. The recommended business decision is the suitable and optimal choice to implement. The proposed model for MCBI approach that consists of five major components. The first component is business objectives, problem definition and main goals. The second component is a business heterogeneous data treatment which gathering from different resources and related with different areas. The third component is a unified business intelligence databases. The fourth component is a business intelligence processing. The fifth component is a evaluating the business decisions to select the suitable and optimal solution.

This Study presents a smart information retrieval methodology/smart retrieval query technique that depends on the power of search engine, clawers, full text indexing, and descriptions points for documents contents or websites as known as “An integration framework for search engine architecture to improve information retrieval quality” or smart information retrieval. The new idea for search engine architecture able to make search statement or document print that used in searching operations which depend on Boolean retrieval that uses Boolean algebra and truth table comparative technique. Search engine indexer makes indexing for documents and web sites contents which depend on the performance and quality of search engine, indexer and web clawer to produce precision, recall through crawling and indexing operations to identify folding and stemming words according to smart web query engine which has accurate crawler architecture, truth table comparative technique and search statement or document print.

Abstract
The mathematical model described in this paper is
based on a discovery of a phenomenon related to red blood
cells. In this phenomenon, the hemolysate of red blood cells
reacts with antibodies from the plasma of the same patient.
Using proteomics approach to identify those hemolysate
antigens and then build a database containing those antigens
can help in diagnosis, prognosis, and treatment of disease
disorders. In this paper, algorithms and a tool, based on the
mathematical model and the database, are described. The tool
is tested using hypothetically generated data and it achieved
satisfying results as it detected the proposed diseases.
Keywords- Red Blood Cells; Antigens; Proteomics; Data
Mining Tool; Bioinformatics

This work presents a model for assigning trust values to agents operating within a collaborative multi-agent system. The model enables agents to assess the trustworthiness of their peers, and thus, to be able to select reliable ones for cooperation and coalition formation. In this work, the performance of a group of agents – a team – that collaborate to achieve a shared goal where the individual contribution of each agent is unknown, is evaluated. The work thus aims to present a reliable method for calculating a trust value for agents involved in teamwork. More specifically, this research presents a model – called Inducing the Trust Ratio Model - for evaluating the individual trustworthiness of a group of agents. Toward this end, the model makes use of genetic algorithms to induce the trust ratio of each coalition member. Empirical analysis is undertaken to evaluate the effectiveness of this model

Just like any system, the immune system has a security hole. The process of maintaining tolerance to self antigens can be exploited by invaders to escape from an effective immune
response, at lest temporarily. In the presented work, the transport of antigens to the central organs of an immune system is identified as a critical issue for the induction of tolerance. As red blood cells (RBCs) are specialized for transport, work was directed towards studying the existence of fetal antigens in RBCs. When this was proved, the study of self and bacterial antigens in RBCs was conducted. The results point out that RBCs playa crucial role in tolerance and represent a security hole that is exploited positively by a fetus and negatively by microorganisms

E coli of the serotype 0157:H7 has recently been isolated from
cattle and human fecal samples in Egypt. The aim of this study is to develop an effective method for extraction of flagella from E. coli OI57:H7.
Flagella were prepared through the following steps: dissociated by incubation of bacteria, ethanol treatment, supernatant collection, and finally precipitated by centrifugation. Flagellar filaments in E.coli O157:H7 were demonstrated by transmission electron microscopy and by PCR .H7 flagellin proteins were shown to be immunogenic. They induced a systemic immune response against those H7 proteins when injected SIC into animals or when given orally.
Polyclonal antiserum raised to H7 flagellin proteins reacted with intact E.coli 0157:H7. Also, this antiserum reacted strongly with E.coli 011:K+.H34 and O156:K-:H23. .In effect, the prepared polyclonal sera have the potential to serve as high-quality diagnostic reagent.
Keywords: flagellar antigen; polyclonal H7 antiserum; Transmission Electron Microscopy (TEM) and (EHEC) Entrohemorragic E. coli O157:H7

Escherichia coli 015 7 antigen share elements with Brucella smooth strains which cause cross reactivity in serological standard tests for Brucellosis. In infected animals with Escherichia coli O 157:H7 , antibodies against E. coli cross react with the Brucella antigens (Strain 99 Rose Bengal Test). Consequently, Brucellosis is difficult to diagnosis because shared with E. coli 0157:H7. The aim of this study was to elaborate on a method of antigen preparation that is useful in detecting specific antibodies against each bacterial strain without cross reactivity. In this study, sera were examined from animals that are: vaccinated with Brucella vaccines (Rev.1 and S19); natura1ly infected with Escherichia coli 0151:H7 and Brucellosis; and experimentally infected with Escherichia coli 0151:H7, wild field Brucella melitensis, and other E. coli serotypes. All those sera were ex-amined for antibodies against the developed two antigens. Cross reaction disappeared.. E. coli 0157:H7 antibodies failed to react with the modified Brucella antigen and Brucella antibodies failed to react with the colored antigen of E. coli 0151:H7 .In effect, we were able to demon-strate mixed infection and prove the effectively of the developed antigens. This implicitly proves that the developed antigens have a high degree of specificity and sensitivity. They could be a useful tool for clinical diagnosis and epidemiological studies of E. coli 0151:H7 in-fection and Brucellosis in animals with potential use in humans.

Keywords: Bacterial antigens, bacterial cross reaction. Brucellosis, Enterohaemorrhagic Escherichia coli, TEM (Transmission Electron Microscopy)