Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System

In food industry, bioprocesses like fermentation often are a crucial part of the manufacturing process and decisive for the final product quality. In general, they are characterized by highly nonlinear dynamics and uncertainties that make it difficult to control these processes by the use of traditional control techniques. In this context, fuzzy logic controllers offer quite a straightforward way to control processes that are affected by nonlinear behavior and uncertain process knowledge. However, in order to maintain process safety and product quality it is necessary to specify the controller performance and to tune the controller parameters. In this work, an approach is presented to establish an intelligent control system for oxidoreductive yeast propagation as a representative process biased by the aforementioned uncertainties. The presented approach is based on statistical process control and fuzzy logic feedback control. As the cognitive uncertainty among different experts about the limits that define the control performance as still acceptable may differ a lot, a data-driven design method is performed. Based upon a historic data pool statistical process corridors are derived for the controller inputs control error and change in control error. This approach follows the hypothesis that if the control performance criteria stay within predefined statistical boundaries, the final process state meets the required quality definition. In order to keep the process on its optimal growth trajectory (model based reference trajectory) a fuzzy logic controller is used that alternates the process temperature. Additionally, in order to stay within the process corridors, a genetic algorithm was applied to tune the input and output fuzzy sets of a preliminarily parameterized fuzzy controller. The presented experimental results show that the genetic tuned fuzzy controller is able to keep the process within its allowed limits. The average absolute error to the reference growth trajectory is 5.2 × 106 cells/mL. The controller proves its robustness to keep the process on the desired growth profile

Kesan penggunaan e-konkrit berasaskan model needham lima fasa terhadap kesesuaian isi kandungan dan pencapaian pelajar

Kaedah pengajaran memainkan peranan yang penting di dalam meningkatkan tahap kefahaman pelajar. Kaedah pengajaran konvensional sedia ada kurang menarik perhatian pelajar jika ianya hanya melibatkan interaksi satu hala e-Pembelajaran merupakan salah satu kaedah yang boleh digunakan untuk menarik minat dan meningkatkan tahap kefahaman pelajar. Kajian yang dijalankan ini adalah untuk mengkaji kesan e-Konkrit menggunakan Model Needham Lima Fasa terhadap kesesuaian isi kandandungan dan pencapaian..

Design of microstrip patch antenna for IEEE 802.16-2004 applications

This thesis presents microstrip patch antenna IEEE 802.16-2004 standards for microwave applications and WiMax. Narrow bandwidth (BW) is the main defect of microstrip patch antenna in wireless communication. The bandwidth can be improved by increasing the substrate thickness, and using air as substrate with low dielectric constant. The antennas were fabricated using FR4 board. Two types of microstrip antenna were used, the first was a single microstrip patch antenna and the second was using an air-gap technique as the dielectric between two antenna boards. The spacer of the air-gap has thickness of 2mm. It was made of wood to separate between the two boards. The transmission line model was used to get the approximate dimension for the design. Different parameters were obtained depending on the simulation and measurement. The Computer Simulations Technology (CST) software was used to simulate the design and the measurement was executed by Vector Network Analyzer (VNA). The two designs were compared to each other and found that some improvements were obtained on the air-gap technique. The bandwidth was improved by 4.51 % with air-gap technique and only 1.02 % with the single patch antenna

Towards an Intelligent Tutor for Mathematical Proofs

Computer-supported learning is an increasingly important form of study since it allows for independent learning and individualized instruction. In this paper, we discuss a novel approach to developing an intelligent tutoring system for teaching textbook-style mathematical proofs. We characterize the particularities of the domain and discuss common ITS design models. Our approach is motivated by phenomena found in a corpus of tutorial dialogs that were collected in a Wizard-of-Oz experiment. We show how an intelligent tutor for textbook-style mathematical proofs can be built on top of an adapted assertion-level proof assistant by reusing representations and proof search strategies originally developed for automated and interactive theorem proving. The resulting prototype was successfully evaluated on a corpus of tutorial dialogs and yields good results.Comment: In Proceedings THedu'11, arXiv:1202.453

Karektor guru pendidikan khas aliran kemahiran berlandaskan nilai retorik dari perspektif pelajar pendidikan khas masalah pendengaran di Malaysia

Latar Belakang: Pendidikan Khas di Malaysia adalah satu usaha yang berterusan untuk melahirkan insan yang berkemahiran, berpandangan jauh, berupaya, beriman, berdikari, mampu merancang dan menguruskan kehidupan harian serta menyedari potensi diri sendiri yang selaras dengan Falsafah Pendidikan Kebangsaan. Aliran pendidikan teknikal dan vokasional juga tidak dikecualikan pelajar yang mempunyai keperluan khas. Oleh itu, guru pendidikan khas aliran kemahiran harus mempunyai karektor yang istimewa untuk mendidik pelajar golongan ini. Namun begitu, masih belum wujudnya satu model standard guru pendidikan khas terutamanya aliran kemahiran. Objektif: Kajian ini dijalankan untuk mengenal pasti tahap penerapan elemen dan dimensi nilai retorik dalam proses pengajaran dan pembelajaran guru aliran kemahiran bagi pelajar pendidikan khas masalah pendengaran. Keputusan: Dapatan kajian ini menunjukkan penerapan elemen nilai retorik ethos dan logos dalam kalangan guru berada pada tahap tinggi, diikuti dengan pathos pada tahap sederhana. Dapatan kajian juga menunjukkan penerapan nilai retorik bagi kebanyakan dimensi pada tahap tinggi, hanya dimensi perasaan dan visualisasi pada tahap sederhana. Kesimpulan: Umumnyaa, guru pendidikan khas aliran kemahiran telah menerapkan nilai retorik pada tahap yang tinggi. Setiap guru digalak untuk menguasai nilai retorik supaya dapat membantu para pelajar menerokai ilmu pengetahuan yang disampaikan oleh mereka dengan berkesan dan seterusnya memberi impak yang positif terhadap pencapaian pelajar

Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis

In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent "imitate" teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments

Extruder for food product (otak–otak) with heater and roll cutter

Food extrusion is a form of extrusion used in food industries. It is a process by which a set of mixed ingredients are forced through an opening in a perforated plate or die with a design specific to the food, and is then cut to a specified size by blades [1]. Summary of the invention principal objects of the present invention are to provide a machine capable of continuously producing food products having an’ extruded filler material of meat or similarity and an extruded outer covering of a moldable food product, such as otak-otak, that completely envelopes the filler material

An intelligent system for risk classification of stock investment projects

The proposed paper demonstrates that a hybrid fuzzy neural network can serve as a risk classifier of stock investment projects. The training algorithm for the regular part of the network is based on bidirectional incremental evolution proving more efficient than direct evolution. The approach is compared with other crisp and soft investment appraisal and trading techniques, while building a multimodel domain representation for an intelligent decision support system. Thus the advantages of each model are utilised while looking at the investment problem from different perspectives. The empirical results are based on UK companies traded on the London Stock Exchange