Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6

Publications

6 Different Formula of Mixed Bacteria as a Bio-Treatment for Sewage Wastewater

Authors: E. Marei, A. Hammad, S. Ismail, A. El-Gindy

Abstract:

This study aims to investigate the ability of different formula of mixed bacteria as a biological treatments of wastewater after primary treatment as a bio-treatment and bio-removal and bio-adsorbent of different heavy metals in natural circumstances. The wastewater was collected from Sarpium forest site-Ismailia Governorate, Egypt. These treatments were mixture of free cells and mixture of immobilized cells of different bacteria. These different formulas of mixed bacteria were prepared under Lab. condition. The obtained data indicated that, as a result of wastewater bio-treatment, the removal rate was found to be 76.92 and 76.70% for biological oxygen demand, 79.78 and 71.07% for chemical oxygen demand, 32.45 and 36.84 % for ammonia nitrogen as well as 91.67 and 50.0% for phosphate after 24 and 28 hrs with mixed free cells and mixed immobilized cells, respectively. Moreover, the bio-removals of different heavy metals were found to reach 90.0 and 50. 0% for Cu ion, 98.0 and 98.5% for Fe ion, 97.0 and 99.3% for Mn ion, 90.0 and 90.0% Pb, 80.0% and 75.0% for Zn ion after 24 and 28 hrs with mixed free cells and mixed immobilized cells, respectively. The results indicated that 13.86 and 17.43% of removal efficiency and reduction of total dissolved solids were achieved after 24 and 28 hrs with mixed free cells and mixed immobilized cells, respectively.

Keywords: Biological desalination, bio-sorption heavy metals, free cell bacteria, immobilized bacteria, wastewater bio-treatment.

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5 Triangular Geometric Feature for Offline Signature Verification

Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad

Abstract:

Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.

Keywords: biometrics, euclidean classifier, feature extraction, offline signature verification, VOTING-based classifier

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4 Big Data Analytics and Data Security in the Cloud via Fully Homomorphic Encryption

Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Moses Noel Dogonyaro

Abstract:

This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.

Keywords: Data Analytics, Security, Privacy, Bootstrapping, and Fully Homomorphic Encryption Scheme.

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3 Development of Neural Network Prediction Model of Energy Consumption

Authors: Maryam Jamela Ismail, Rosdiazli Ibrahim, Idris Ismail

Abstract:

In the oil and gas industry, energy prediction can help the distributor and customer to forecast the outgoing and incoming gas through the pipeline. It will also help to eliminate any uncertainties in gas metering for billing purposes. The objective of this paper is to develop Neural Network Model for energy consumption and analyze the performance model. This paper provides a comprehensive review on published research on the energy consumption prediction which focuses on structures and the parameters used in developing Neural Network models. This paper is then focused on the parameter selection of the neural network prediction model development for energy consumption and analysis on the result. The most reliable model that gives the most accurate result is proposed for the prediction. The result shows that the proposed neural network energy prediction model is able to demonstrate an adequate performance with least Root Mean Square Error.

Keywords: Energy Prediction, Multilayer Feedforward, Levenberg-Marquardt, Root Mean Square Error (RMSE)

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2 Experimental Design and Performance Analysis in Plasma Arc Surface Hardening

Authors: M.I.S. Ismail, Z. Taha

Abstract:

In this paper, the experimental design of using the Taguchi method is employed to optimize the processing parameters in the plasma arc surface hardening process. The processing parameters evaluated are arc current, scanning velocity and carbon content of steel. In addition, other significant effects such as the relation between processing parameters are also investigated. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the effects of these processing parameters. Through this study, not only the hardened depth increased and surface roughness improved, but also the parameters that significantly affect the hardening performance are identified. Experimental results are provided to verify the effectiveness of this approach.

Keywords: Plasma arc, hardened depth, surface roughness, Taguchi method, optimization.

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1 Properties of Bricks Produced With Recycled Fine Aggregate

Authors: S. Ismail, Z. Yaacob

Abstract:

The main aim of this research is to study the possible use of recycled fine aggregate made from waste rubble wall to substitute partially for the natural sand used in the production of cement and sand bricks. The bricks specimens were prepared by using 100% natural sand; they were then replaced by recycled fine aggregate at 25, 50, 75, and 100% by weight of natural sand. A series of tests was carried out to study the effect of using recycled aggregate on the physical and mechanical properties of bricks, such as density, drying shrinkage, water absorption characteristic, compressive and flexural strength. Test results indicate that it is possible to manufacture bricks containing recycled fine aggregate with good characteristics that are similar in physical and mechanical properties to those of bricks with natural aggregate, provided that the percentage of recycled fine aggregates is limited up to 50-75%.

Keywords: Bricks, cement, recycled aggregate, sand

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