Asian Journal of Electrical Sciences (AJES) is a quarterly international peer-reviewed journal of Electrical Sciences. One of the objectives of this journal is to disseminate knowledge on various research issues connected with the topics include, but are not limited to:

Telecommunications – transmission of information, coax cable, optical fiber or free space, amplitude modulation and frequency modulation, transmitters and receivers, transceiver.
Instrumentation – pressure, flow and temperature, electromagnetic theory, thermocouples, sensors of larger electrical systems, control engineering.
Computers – Computers and computer systems, hardware, software, software engineering.

Power engineering – generation, transmission and distribution of electricity, transformers, electric generators, electric motors, high voltage engineering and power electronics.
Control engineering – dynamic systems, design of controllers, electrical circuits, digital signal processors, microcontrollers and PLCs (Programmable Logic Controllers), industrial automation. Electronic Engineering -Electronic circuits, resistors, capacitors, inductors, diodes and transistors, radio engineering, radar, television, audio systems, computers and microprocessors.
Microelectronics – Electronic circuit, integrated circuit, semiconductor transistors, resistors, capacitors, inductors, Nanoelectronics.

Signal processing – signals, analog, digital, telecommunications, Digital Signal Processing, SDTV | HDTV sets, radios and mobile communication devices, Hi-Fi audio equipments, Dolby noise reduction algorithms, GSM mobile phones, mp3 multimedia players, camcorders and digital cameras, automobile control systems, noise cancelling headphones, digital spectrum analyzers, intelligent missile guidance, radar, GPS based cruise control systems, image processing, video processing, audio processing and speech processing systems.

It is indeed an art to match maximum number of preferences by utilizing limited number of resources. During the current academic year 75% of the admissions to Engineering Colleges have gone down, as only 30% to 40% of intake has been filled. Without reaching the breakeven point, the management of the institution becomes a complicated issue. In this situation providing quality education to the students is the question mark. The main aim of this paper is to discover a pattern to identify the choice of preferences of the candidates to seek admissions in any academic institutions. The candidate finds admission in an institution only when his/her own preference matches exactly, otherwise the candidate continues to go by the next alternate in the list of preference. If the institution analyzes the preferences of the candidates and tries to satisfy them, surely the institution can reach even above their intake. Generally satisfaction of individual candidate is practically not possible. Hence the institution should try to satisfy maximum number of candidates by utilizing our existing infrastructure and viable number of preferences. Here the viability is the main constraint. For the purpose of matching optimum number of candidates to suit our existing system, we have designed our algorithmic approach. Here our new system is used to extract frequent item sets from various preferences. By thresholds, it can fix the preferences either decrease or increase the level of frequent. The new algorithm is based on association rule classification which is one of data mining techniques. Data mining is the process of extracting knowledge hidden from large volumes of raw data.