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Accepted Papers

Academic Support System Using Self-Organizing Map : A Remedial Process for Student with Learning Difficulties
Isagani M. Tano1 and Shaneth C. Ambat2, 1Quezon City Polytechnic University (QCPU), Philippines and 2AMA University (AMAU), Philippines

Abstract

Today freshmen students°« have difficulty in their college transition. Among the most prevalent risk factors are academic difficulty and failures. The early identification of vulnerable students who have difficulty in their academic journey is crucial for the success of any academic support programs and helps improve and increase the chance in staying in course chosen. The study utilizes the efficiency of Self Organizing Map in formulating clusters from students with learning data sets. The cluster analysis was used to develop an academic support framework and system. The purpose of the academic support system is to automatically recommend academic support program suited in the characteristics of values of students. The recommendation produced by the system was extracted from the analysis of the cluster model derived from the Self Organizing Map. This is in line with the college or department preparation in providing academic support program to help students to achieve better academic performance.

Eldersense, An IOT System for the Elderly Living Independently
Zhong Han Kong and Chai Kiat Yeo, Nanyang Technological University, Singapore

Abstract

This paper describes the implementation of an inexpensive °∆do-it-yourself (DIY)°« smart home system which allows for an unobtrusive and non-invasive monitoring system of the elderly°«s well-being in their own home using motion sensors. The system gathers the data from the sensors to learn and understand the behaviors of elderlies throughout the day. The activities will be presented to family members in a user-friendly manner via Android apps so that they can make better informed decisions with regards to ensuring the elderlies°« safety and well-being. Alerts will be sent to both the elderly°«s mobile as well as that of family member when the system detects anomalies. The implementation involves the use of Passive Infrared (PIR) Sensors, connected to a Raspberry Pi (RPi 3). Data is stored at a backend for processing. The elderly°«s activities and alerts displayed or sent to a mobile application developed for this purpose.

Reducing the Time Reconfiguration Overhead of a Reconfigurable Dynamic System Using Active Run Time Prediction
Hariharan. I and Kannan. M, Anna University, India

Abstract

The performance of the Field-Programmable Gate Array (FPGA) is largely affected by its reconfiguration overheads. For a dynamic system in which the nature of the system is unpredictable at design-time, these overheads are expensive in terms of performance. To reduce these overheads, an architecture along with two algorithms are proposed which dynamically predicts and schedules the configuration. As a result, the time reconfiguration overhead is reduced to improve the performance. In most cases, the scheduling result obtained exactly matches with the system whose configurations are fetched from HS memory. This could be the near maximum achievable performance for any FPGA architecture, executing a dynamic application.

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