316 research outputs found
Cooperative Avoidance Control-based Interval Fuzzy Kohonen Networks Algorithm in Simple Swarm Robots
A novel technique to control swarm robot’s movement is presented and analyzed in this paper. It allows a group of robots to move as a unique entity performing the following function such as obstacle avoidance at group level. The control strategy enhances the mobile robot’s performance whereby their forthcoming decisions are impacted by its previous experiences during the navigation apart from the current range inputs. Interval Fuzzy-Kohonen Network (IFKN) algorithm is utilized in this strategy. By employing a small number of rules, the IFKN algorithms can be adapted to swarms reactive control. The control strategy provides much faster response compare to Fuzzy Kohonen Network (FKN) algorithm to expected events. The effectiveness of the proposed technique is also demonstrated in a series of practical test on our experimental by using five low cost robots with limited sensor abilities and low computational effort on each single robot in the swarm. The results show that swarm robots based on proposed technique have the ability to perform cooperative behavior, produces minimum collision and capable to navigate around square shapes obstacles
Multi crteria decision making and its applications : a literature review
This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM
Swarm Robots Control System based Fuzzy-PSO
In this paper describes swarm robots control design using combination Fuzzy logic and Particle swarm optimization algorithm. They can communicate with each other to achieve the target. Fuzzy Logic technique is used for navigating swarm robots in unknown environment and Particle Swarm Optimization (PSO) is used for searching and finding the best position of target. In this experiment utilize three identical robots with different color. Every robot has three infrared sensors, two gas sensors, 1 compass sensor and one X-Bee. A camera in the roof of robot arena is utilized to determine the position of each robot with color detection methods. Swarm robots and camera are connected to a computer which serves as an information center. From the experimental results the Fuzzy-PSO algorithm is able to control swarm robots, achieves the best target position in short time and produce smooth trajector
Educating the educators: Incorporating bioinformatics into biological science education in Malaysia
Bioinformatics can be defined as a fusion of computational and biological sciences. The urgency to process and analyse the deluge of data created by proteomics and genomics studies has caused bioinformatics to gain prominence and importance. However, its multidisciplinary nature has created a unique demand for specialist trained in both biology and computing. In this review, we described the components that constitute the bioinformatics field and distinctive education criteria that are required to produce individuals with bioinformatics training. This paper will also provide an introduction and overview of bioinformatics in Malaysia. The existing bioinformatics scenario in Malaysia was surveyed to gauge its advancement and to plan for future bioinformatics education strategies. For comparison, we surveyed methods and strategies used in education by other countries so that lessons can be learnt to further improve the implementation of bioinformatics in Malaysia. It is believed that accurate and sufficient steerage from the academia and industry will enable Malaysia to produce quality bioinformaticians in the future
Multi-agent reinforcement learning for route guidance system
Nowadays, multi-agent systems are used to create applications in a variety of areas, including economics, management, transportation, telecommunications, etc. Importantly, in many domains, the reinforcement learning agents try to learn a task by directly interacting with its environment. The main challenge in route guidance system is to direct vehicles to their destination in a dynamic traffic situation, with the aim of reducing travel times and ensuring efficient use of available road network capacity. This paper proposes a multi-agent reinforcement learning algorithm to find the best and shortest path between the origin and destination nodes. The shortest path such as the lowest cost is calculated using multi-agent reinforcement learning model and it will be suggested to the vehicle drivers in a route guidance system. The proposed algorithm has been evaluated based on Dijkstra's algorithm to find the optimal solution using Kuala Lumpur (KL) road network map. A number of route cases have been used to evaluate the proposed approach based on the road network problems. Finally, the experiment results demonstrate that the proposed approach is feasible and efficient
Swarm Robots Control System Based Fuzzy-PSO
In this paper describes swarm robots control design using combination Fuzzy logic and Particle swarm optimization algorithm. They can communicate with each other to achieve the target. Fuzzy Logic technique is used for navigating swarm robots in unknown environment and Particle Swarm Optimization (PSO) is used for searching and finding the best position of target. In this experiment utilize three identical robots with different color. Every robot has three infrared sensors, two gas sensors, 1 compass sensor and one X-Bee. A camera in the roof of robot arena is utilized to determine the position of each robot with color detection methods. Swarm robots and camera are connected to a computer which serves as an information center. From the experimental results the Fuzzy-PSO algorithm is able to control swarm robots, achieves the best target position in short time and produce smooth trajector
Antidiabetic efficacy of polar extracts of the leaves of tetracera indica merr. (dilleniaceae) in alloxanized rats
Background review: Plants are considered less toxic than synthetic drugs. Recently, the search for appropriate anti-diabetic agents has been focused on plants used in traditional medicine partly because of leads provided by traditional medicine to natural products that may be better treatments than currently used drugs responsible for serious side effects among diabetics. In folk remedies, leaves of Tetracera indica Merr. (Dilleniaceae) are effectively used in the treatment of diabetes. However, there is no scientific claim about its efficacy in the management of diabetes.
Objective: Present study was aimed to investigate the antidiabetic potential of the leaves of T. indica Merr. in vivo to prove its effectiveness in the treatment of diabetes.
Methods: Polar extracts (i.e., aqueous (AQ) and methanol (MEOH)) of the leaves of T. indica were prepared and administered to both normal and alloxan induced diabetic male albino rats (Sprague Dawley strain). Two doses of each extract (250 and 500 mg/kg b.w.) were evaluated. The blood glucose levels were measured at 0, 2, 4, 6 and 8 h after oral administration of AQ and MEOH extracts. Comparison was made with standard antidiabeteic drug, glibenclamide (GLBC).
Results and Conclusion: Both AQ and MEOH extracts exhibited significant antihyperglycemic activity in alloxan induced diabetic rats, however in normal rats no hypoglycemic activity was observed, when compared with both +ve and –ve controlled groups. The antidiabetic activity was also found to be comparable to that of the effect produced by GLBC (0.25 mg/kg b.w.). The LD50 of both AQ and MEOH extracts was found to be more than 5000 mg/kg body weight and no lethal toxicity was observed within this range. This study provides scientific evidence for the traditional use of leaves of T. indica Merr. in the management of diabetes in Malaysia.
Keywords: Tetracera indica Merr. (Dilleniaceae), antidiabetic activity, alloxanized rat
An automated framework for software test oracle
Context: One of the important issues of software testing is to provide an automated test oracle. Test oracles are reliable sources of how the software under test must operate. In particular, they are used to evaluate the actual results that produced by the software. However, in order to generate an automated test oracle, oracle challenges need to be addressed. These challenges are output-domain generation, input domain to output domain mapping, and a comparator to decide on the accuracy of the actual outputs. Objective: This paper proposes an automated test oracle framework to address all of these challenges. Method: I/O Relationship Analysis is used to generate the output domain automatically and Multi-Networks Oracles based on artificial neural networks are introduced to handle the second challenge. The last challenge is addressed using an automated comparator that adjusts the oracle precision by defining the comparison tolerance. The proposed approach was evaluated using an industry strength case study, which was injected with some faults. The quality of the proposed oracle was measured by assessing its accuracy, precision, misclassification error and practicality. Mutation testing was considered to provide the evaluation framework by implementing two different versions of the case study: a Golden Version and a Mutated Version. Furthermore, a comparative study between the existing automated oracles and the proposed one is provided based on which challenges they can automate. Results: Results indicate that the proposed approach automated the oracle generation process 97% in this experiment. Accuracy of the proposed oracle was up to 98.26%, and the oracle detected up to 97.7% of the injected faults. Conclusion: Consequently, the results of the study highlight the practicality of the proposed oracle in addition to the automation it offers
Phytochemical screening expedition 2009 : drug discovery from nature.
Malaysia is a tropical country endowed with very rich and diverse specIes of flora with promising medicinal values, which are still fully untapped, The country also has a strong tradition in ethnomedical practices, many ohvhich utilize the local flora. These two factors have initiated the research in natural products sciences, which provide an ideal common ground for collaboration between chemists, botanists and pharmacologists. In addition, phytochemical
research on our local medicinal plants is an area of great potential that needs to be explored further. For that reason, Phytochemical Screening Expedition has been regularly organized as yearly programme at Kulliyyah ofPharmacy since 200
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