Informatics Publishing Limited

S. Baskar ¹, N. Kumarappan ¹, R. Gnanadass ²

Affiliations
1 Dept. of EEE, Annamalai University, Chidambaram, IN
2 Dept. of EEE, Pondicherry Engineering College, Puducherry, IN

Abstract

To investigate the capability of regulating power flow in Single Machine Infinite bus system using Unified Power Flow Controller (UPFC) is the main focus of this paper. This paper presents the dynamic operational characteristics of Unified Power Flow Controller using switching level model. The real & reactive power flow is controlled by varying the shunt converter firing angle and modulation index of the series converter. The simulation is carried out in Simulink based MATLAB environment. The simulation result proves that the UPFC makes the power factor of the system is unity and the total harmonic distortion of line voltage are effectively minimized. The proposed controller shows the good performance & effectiveness of controlling the real and reactive power and also damping the oscillation due to system faults.

Keywords

Linear Firing Angle Control, Single Machine Infinite Bus System, Switching Level Modeling, Unified Power Flow Controller.

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S. Senthamarai Kannan ¹, N. Ramaraj ², S. Baskar ³

Affiliations
1 Department of IT, Thiagarajar College of Engineering, Madurai, IN
2 G.K.M College of Engineering, Chennai, IN
3 EEE Department, Thiagarajar College of Engineering, Madurai, IN

Abstract

Data reduction aims to reduce the dimensionality of large scale data with out losing useful information, is an important topic of knowledge discovery, data clustering and classification. This Paper introduces a novel concept of dependency based attribute reduction using Bayes Theorem. Bayesian Theory is of great interest in Data reduction. Attribute reduction is a data mining approach for detecting and characterizing combinations of attributes or independent variables that interact to influence a dependent or class variable. The basis of this attribute reduction is a method that converts two or more variables or attributes to a single attribute and by calculating the probabilities of their values in deciding the value of class attribute. Hence, the dependent attributes are found and are removed from the original dataset. The end goal is to improve the classification accuracy such that prediction of the class variable is improved over that of the original data with initial attribute set and also reduces the computational time.

Keywords

Attributes Reduction, Data Classification, Bayesian Theory, Clustering, Simple K-Means, Cobweb, EM.

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S. Senthamarai Kannan ¹, N. Ramaraj ², S. Baskar ³

Affiliations
1 Department of I.T, Thiagarajar College of Engineering, Madurai, IN
2 G.K.M College of Engineering, Chennai, Tamil Nadu, IN
3 E.E.E Department, Thiagarajar College of Engineering, Madurai, IN

Abstract

K-means clustering is widely used due to its fast convergence, but it is sensitive to the initial condition. The limitation of k-means algorithm is that the user has to specify the number of clusters (K). There are some methods to initialize the number of clusters. But those methods perform worse in some cases. So we are proposing a method called affinity propagation in this paper which resolves those problems. By making use of the convergence property of K-means and the good performance of affinity propagation, we presented a new clustering strategy which can produce much lower squared error than AP and standard k-means. The efficiency and effectiveness of our method is demonstrated through extensive comparisons with other methods using UCI datasets of high dimensionality.

Keywords

K-Means, Affinity Propagation, Centroid Initialization, Clustering Optimization.

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K. Karthikeyan ¹, S. Kannan ¹, S. Baskar ², C. Thangaraj ³

Affiliations
1 Department of Electrical and Electronics Engineering, Kalasalingam University, IN
2 Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, IN
3 Anna University of Technology, Chennai, IN

Abstract

This paper describes the application of an evolutionary algorithm, Restart Covariance Matrix Adaptation Evolution Strategy (RCMAES) to the Generation Expansion Planning (GEP) problem. RCMAES is a class of continuous Evolutionary Algorithm (EA) derived from the concept of self-adaptation in evolution strategies, which adapts the covariance matrix of a multivariate normal search distribution. The original GEP problem is modified by incorporating Virtual Mapping Procedure (VMP). The GEP problem of a synthetic test systems for 6- year, 14-year and 24-year planning horizons having five types of candidate units is considered. Two different constraint-handling methods are incorporated and impact of each method has been compared. In addition, comparison and validation has also made with dynamic programming method.

Keywords

Constraint Handling, Dynamic Programming, Generation Expansion Planning, Restart Covariance Matrix Adaptation Evolution Strategy and Virtual Mapping Procedure.

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S. Baskar ¹

Affiliations
1 Department of Electronics and Communication Engineering, Muthayammal Engineering College, Tamil Nadu, IN

Abstract

Blood oxygen content is considered as the 5th vital sign, joining: temperature, respiratory rate, heart rate and blood pressure [3]. The advantage of wireless pulse oximetry is completely non-invasive, wireless hassle free. It can be used to monitor the oxygen saturation of the blood as well as the pulse rate of the patient. it can even send the information. The wireless pulse oximeter is a wireless reflectance pulse oximeter device designed to monitor the blood oxygen content and pulse rate of the patients. Pulse oximetry has become a standard procedure for the measurement of blood-oxygen saturation in the hospital operating room and recovery room. Oximetry shortens the time passed before the detection of hypoxemia, or deficiency of oxygen. This design will provide this information wirelessly giving flexibility to the medical staffs.

Keywords

Oximeter, Oxygen Saturation, Wi-Fi, Oxyhemoglobin, Temperature.

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R. Rajan Prakash ¹, S. Charles Raja ¹, D. Kavitha ¹, S. Baskar ¹

Affiliations
1 Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Madurai – 625019, IN

Abstract

Outcome Based Education (OBE) came into practice in India in 2014. Earlier the priority of most of the faculty is just to complete the syllabus and for students to score better grade. One of the biggest challenges for faculty members in implementing OBE is to change the focus of students from scoring marks to learning the content particularly at the beginning of the programme while teaching fundamental courses. In this paper, the authors made an attempt to compare two strategies of teaching and learning; the Broiler Chicken Nourishing (BCN) verses the Desi Chicken Nourishing (DCN) in an Indian perspective. The BCN strategy shows only a short term and narrow goal though productive, it was in DCN strategy there is effective knowledge transfer which promotes more of self learning and self realization. A case study was done on Electric Circuit Analysis for second semester Electrical Engineering students. The analysis shows that DCN is more learner centered and yields fruitful results when compared to BCN. The DCN approach promotes original thinking of the students and develops good interpersonal skill.

Keywords

Outcome Based Education, Millenials, Chicken Feeding, Team Building, Mentoring.

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S. J. Thiruvengadam ¹, S. Baskar ¹, S. Saravana Perumaal ², C. Jeyamala ³, D. Anitha ³, R. Rajan Prakash ³

Affiliations
1 Professor, Academic Process Team, Thiagarajar College of Engineering, Madurai, IN
2 Associate Professor, Academic Process Team, Thiagarajar College of Engineering, Madurai, IN
3 Assistant Professor, Academic Process Team, Thiagarajar College of Engineering, Madurai, IN

Abstract

The CDIO INITIATIVE is an innovative educational framework that has been followed in many world-class educational institutions in USA, Europe and Asian countries for producing the next generation of engineers. It provides students with an education in the context of Conceiving — Designing — Implementing — Operating (CDIO) real-world systems and products. Thiagarajar College of Engineering (TCE), Madurai is one among those institutions following the CDIO framework for all undergraduate engineering programmes since the academic year 2018-19. Though there are training programs for selective faculty members, there had been no intensive hands - on training to all the faculty members. It has been felt from the formal meetings and informal discussions that faculty members needed more clarity and training on the CDIO framework. This has led to the conduct of training workshops online by the TCE academic process team for the faculty members of the institution (n=205), in three batches. Two quizzes have been conducted and feedback has been collected at the end of the workshop for each batch. This research paper analyses the outcome of these workshops measured through the Higher Order Thinking Skills (HOTS) exhibited in the assessment activities and feedback. It has been observed that the training workshop satisfies the expectations of the participants with a Satisfaction Index of 0.924. Recommendations have been proposed for interpreting the outcomes of such training workshops to enhance faculty competence through such workshops by addressing the necessary gaps in the forthcoming training workshops.

Keywords

CDIO, Faculty Development Programs, Workshops, Assessments, Satisfaction.

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