Elia Erwani Hassan

Economic load dispatch via an improved Bacterial Foraging Optimization

An economic dispatch is one of the most important research areas in power system. This is because an optimal power dispatch will contribute to a sound power system load management. As a result, the solution can ease the cost of fuel without ignoring the power operation constraints and system losses. Adaptive Tumble Bacterial Foraging Optimization (ATBFO) and Adaptive Mutation Bacterial Foraging Optimization (AMBFO), which are originally from basic Bacterial Foraging Optimization (BFO), are considered as alternative algorithms to minimize fuel cost. Thus, the two techniques are compared under the same parameters to determine the best optimal result. After several analyses on the results obtained, it was found that ATBFO outperformed AMBFO. Both of these adaptive bacterial foraging optimization techniques are tested on 26 bus Reliability test system using MATLAB R2009b on MS Window 7.

Development of learning object for engineering courses in UTeM

This paper views e-learning initiative in UTeM with a focus on the development of learning object for engineering courses in UTeM. Having a learning management system called SPeL, UTeM further promote e-learning culture by encouraging knowledge sharing through SPeLs learning object repository. UTeM is gradually building a collection of reusable learning objects to be shared across faculties. The paper discusses the concept of learning object in UTeM context, roles of Subject Matter Expert (SME), UTeMs learning object design strategy and the development stages of learning object in UTeM. The paper further stated briefly on the benefits of learning object to UTeM.

The Improved of BFOA for Ensuring the Sustainable Economic Dispatch

This paper introduced a new heuristic method the Improved to Bacterial Foraging Optimization Algorithm or IBFO to provide minimize objective functions in Secured Environmental Economic Dispatch (SEED) problems. An optimization problem may involve the highly non linear, non convex and non differentiable tends the solutions observed from a multiple local minima. The limitation faced by conventional methods are being trapped at any this local minima and prevent to reach the global minima. For that reason, this approach IBFO is tested under IEEE 118 bus system to obtain the minimum total cost function with less emission involved. Additionally, the proposed optimization approach is compared to original Bacterial Foraging Optimization Algorithm (BFO). As a result, all findings supported the novel IBFO as the competent and reliable technique.

Sustainable Environmental Economic Dispatch Optimization with Hybrid Metaheuristic Modification

Received Dec 04, 2017 Revised Jan 11, 2018 Accepted Apr 15, 2018 Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.A Weblogs contains the history of User Navigation Pattern while user accessing the websites. The user navigation pattern can be analyzed based on the previous user navigation that is stored in weblog. The weblog comprises of various entries like IP address, status code and number of bytes transferred, categories and time stamp. The user interest can be classified based on categories and attributes and it is helpful in identifying user behavior. The aim of the research is to identifying the interested user behavior and not interested user behavior based on classification. The process of identifying user interest, it consists of Modified Span Algorithm and Personalization Algorithm based on the classification algorithm user prediction can be analyzed. The research work explores to analyze user prediction behavior based on user personalization that is captured from weblogs.Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.

Multi objective Adaptive Tumbling Bacterial Foraging in VAR Solutions for Sustainable Power System Operation

Received Dec 04, 2017 Revised Jan 11, 2018 Accepted Apr 15, 2018 Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.A Weblogs contains the history of User Navigation Pattern while user accessing the websites. The user navigation pattern can be analyzed based on the previous user navigation that is stored in weblog. The weblog comprises of various entries like IP address, status code and number of bytes transferred, categories and time stamp. The user interest can be classified based on categories and attributes and it is helpful in identifying user behavior. The aim of the research is to identifying the interested user behavior and not interested user behavior based on classification. The process of identifying user interest, it consists of Modified Span Algorithm and Personalization Algorithm based on the classification algorithm user prediction can be analyzed. The research work explores to analyze user prediction behavior based on user personalization that is captured from weblogs.Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.