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Search Results: 1 - 10 of 514 matches for " Latha Banda "
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A HYBRID MODEL FOR DETECTION AND ELIMINATION OF NEAR- DUPLICATES BASED ON WEB PROVENANCE FOR EFFECTIVE WEB SEARCH
Tanvi Gupta,Latha Banda
International Journal of Advances in Engineering and Technology , 2012,
Abstract: Users of World Wide Web utilize search engines for information retrieval in web as search engines play a vital role in finding information on the web. But, the voluminous amount of web documents has weakened the performance and reliability of web search engines. As, the subsistence of near-duplicate data is an issue that accompanies the growing need to incorporate heterogeneous data. These pages either increase the index storage space or increase the serving costs thereby irritating the users. Near-duplicate detection has been recognized as an important one in the field of plagiarism detection, spam detection and in focused web crawling scenarios. Such near-duplicates can be detected and eliminated using the concept of Web Provenance and TDW matrix Algorithm. The proposed work is the model that combines content, context, semantic structure and trust based factors for classifying and eliminating the results as original or near-duplicates.
MONITORING LOCAL AREA NETWORK USING REMOTE METHOD INVOCATION
Harsh Mittal,Manoj Jain,Latha Banda
International Journal of Computer Science and Mobile Computing , 2013,
Abstract: The project aim is to secure the network or a LAN by implementing such a software which isenable to carry out operations which are capable to monitor whole of the network ,sitting on one chair byviewing remote desktop ,passing messages to remote system and is also able to shut down the system byperforming remote aborting operations . This software is purely developed in JAVA RMI (REMOTEMETHOD INVOCATION). This project is to provide the maximum details about the network to theadministrator on their screen without knowing them their users. The administrator can view the static imageof client’s desktop and then he/she could sends warning message to the user to stop that operationimmediately. Even than if client do not stops than administrator has the facility to abort the system remotelyor restart the system whatever necessary he thinks.
A Novel Approach to Detect the Near Duplicate by Refining Provenance Matrix
Tanvi Gupta,Asst.Prof. Latha Banda
International Journal of Computer Technology and Applications , 2012,
Abstract: In this paper, the provenance matrix is refined to get more accuracy and efficiency in detecting near-duplicates by adding two more factors ‘How’ and ‘Why’ , as the performance of the web search depends on the search results having information without duplicates or redundancy . More redundancy leads to more time consume and more storage, that’s why search engines try to avoid indexing of duplicates documents. Provenance model combines both the content-based and trust-based factors for classifying near-duplicates or original documents, as now a days, many of near-duplicates are from the distrusted websites
CANFIS—a computer aided diagnostic tool for cancer detection  [PDF]
Latha Parthiban, R. Subramanian
Journal of Biomedical Science and Engineering (JBiSE) , 2009, DOI: 10.4236/jbise.2009.25048
Abstract: In this investigation, an approach using Coac-tive Neuro-Fuzzy Inference System (CANFIS) as diagnosis system for breast cancer has been proposed on Wisconsin Breast Cancer Data (WBCD). It is occasionally difficult to attain the ultimate diagnosis even for medical experts due to the complexity and non-linearity of the rela-tionships between the large measured factors, which can be possibly resolved with a human like decision-making process using Artificial Intelligence (AI) algorithms. CANFIS is an AI algorithm which has the advantages of both fuzzy inference system and neural networks and can deal with ambiguous data and learn from the past data by itself. The Multi Layer Percep-tron Neural Network (MLPNN), Probabilistic Neural Network (PNN) Principal Component Analysis (PCA), Support Vector Machine (SVM) and Self Organizing Map (SOM) were also tested and benchmarked for their p
Application of Extreme Learning Machine in Fault Classification of Power Transformer  [PDF]
Athikkan Venkatasami, Pitchai Latha
Circuits and Systems (CS) , 2016, DOI: 10.4236/cs.2016.710242
Abstract: Reliability of power system is very essential for every nation to generate and transmit power without interruption. Power transformer is one of the most significant electrical apparatus and hence it must be kept in good health. Identification and classification of faults in power transformer is a major research area. Conventional method of fault classification in transformer uses gas concentrations data and interprets them using international standards. These standards are not able to classify the faults correctly under certain conditions. To overcome this limitation, several soft computing tools namely artificial neural network (ANN), Support Vector Machine (SVM) etc. are used to automate the process of classification of faults in transformers. However, there is a scope exists to improve the classification accuracy. Hence, this research work focuses to design Extreme Learning Machine (ELM) method for classifying fault very accurately using enthalpy of dissolved gas content in transformer oil as an input feature. The ELM method is tested with two databases: one based on IEC TC10 database (DB1) and the other one based on data collected from utilities in India (DB2). The application of ELM to Power Transformer fault classification based on enthalpy as input feature outperforms over the conventional classification based on gas concentration as input feature.
Teaching and Teacher Education for Health Professionals: Perspectives on Quality and Outlook of Health Professionals Education in Zambia
SS Banda
Medical Journal of Zambia , 2008,
Abstract: Purpos: To measure students’ perspectives on the teaching quality of the school of medicine at University of Zambia and concurrently measure health professionals educators perspectives on the need for teaching courses for health professionals educators (educational skills training). The results are discussed as indications for educational skills training for educators in health professionals’ education. Method: 250 medical students from the MB ChB programme were surveyed, in an evaluation exercise, to rate the teaching contribution of all the full-time and honorary lecturers (n=88). The students were requested to rate each lecturer out of 10 on eight scales: a) attendance, b) punctuality, c) clarity, d) interest in the subject, e) supportiveness to students, f) ability as a lecturer, g) appropriate use of audiovisual aids, and h) amount of workload done in the academic year. Additionally, a multi-site study surveyed 426 health professionals educators, defined as persons who considered themselves as continually participating in teaching students in a training institutions for health professions in the Country on the necessity for and their willingness to enroll into a teaching programme for health educators. Results: Two hundred students of the eligible 250 completed the evaluation giving a response rate of 80%. The scores for teaching quality ranged from 8/ 40 to 40/40. The mean score was 32.2. The results showed that about 27.2% (n=24) did not meet the merit standard which was set at 30/40 as the quality assurance benchmark by the School. This result suggests that a large proportion of teaching staff could benefit from teacher education. Four hundred and four questionnaires were completed and returned out of the 426 that had been distributed, yielding a response rate of 94.8 %. The Cronbach’s alpha for reliability test was 0.62 – 0.70 on the teaching skills sub-scale and 0.76 – 0.78 on the Educational skills sub-scale. The majority, over 85%, acknowledged they lacked expertise in educational skills and that they would enrol in a programme to improve their educational skills. There was overwhelming (>90%) agreement in topics to be covered. Limitations: Quality of teaching contributions only measured at school of medicine; Large proportion of educators’ survey were not full-time teaching staff. Implications: The belief that professional qualifications are sufficient for preparation for teaching health professionals is now being confronted. Formal systems of teacher education in the health professions have emerged worldwide and are now also available in Zambia.
The Case Anatomical Knowledge Index (CAKI) as a Tool for Selecting Clinical Cases for Clinically Oriented Anatomy Teaching: Approach and Content
SS Banda
Medical Journal of Zambia , 2009,
Abstract: No Key Words: Anatomy, Case Anatomical Knowledge Index (CAKI), Clinical, Clinically Oriented Anatomy Teaching (COAT), Case, Disease, Prevalence
Student Evaluation of Teaching: A Case Study from School of Medicine (UNZA)
SS Banda
Medical Journal of Zambia , 2008,
Abstract: Purpose: This paper presents a case study of an academic department’s experience with evaluation. The purpose is to review the impact of student evaluation of teaching. The paper also introduces a new evaluation scoring method: the University of Zambia Staff Appraisal System (UNZASAS) method. Method: Anonymous 5-point Likert scale evaluation rating forms were administered to 134 third-year medical students in two consecutive years to measure students’ perceptions of teaching quality of four faculty members in an academic department at School of Medicine. The rating forms were scored using the UNZASAS method. Results: The response rate averaged 83%. The group average lecturer rating improved from 120 to 141.5. Individual performance of three lecturers improved while that of one declined. The UNZASAS method was effective in summarizing data to identify the areas of weakness and strength in the faculty members. The specificity and sensitivity of this method were fundamental to its success as a diagnostic tool for formative evaluation of teaching quality. Conclusions & Implications: The quality of teaching in the academic department improved after evaluation of teaching was introduced. The UNZASAS method proved to be an effective tool for scoring evaluation data and for providing faculty with useful and specific formative feedback. Health professionals training institutions can consider using the UNZASAS method for their evaluation of teaching contribution by educators.
An Investigation of How Clinicians use Anatomical Knowledge in Diagnostic Reasoning: A Grounded Theory Study of Clinicians in Zambia
SS Banda
Medical Journal of Zambia , 2010,
Abstract: Background: The role of biomedical sciences in diagnostic reasoning is contentious but diagnostic reasoning is a principal activity in clinical settings. Such ambiguity creates a tension for medical educators who use clinically oriented anatomy teaching. Purposes: The aim of this paper is to contribute to the debate in the literature via a novel grounded theory about use of anatomy in diagnostic reasoning. Methods: Systematic grounded theory procedures were used to collect data using forty-six weeks-long participant observations, self-administered questionnaires from 168 respondents (140 doctors and 28 medical students at UTH), and unstructured interviews with doctors working in hospitals. Results: Use of anatomy in diagnostic reasoning is a 5-stage cognitive process: patient information data gathering; ascribing the information gathered to anatomical descriptors; interpretation; anatomical representation of the clinical circumstances; and diagnosis. Conclusion: Use of anatomy in diagnostic reasoning is a 5-stage cognitive process: patient information data gathering; ascribing the information gathered to anatomical descriptors; interpretation; anatomical representation of the clinical circumstances; and diagnosis. The conceptual model presented provides a framework for future research and comparison with existing theories.
Overview of diagnostic reasoning: Hypothetical-deductive strategy, problem representation, semantic qualifiers, illness scripts, pattern recognition and prototypes
SB Banda
Medical Journal of Zambia , 2009,
Abstract: No
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