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.

Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scanning techniques produce human body pictures in digital form, which are prohibitive in nature. Hence compression is necessary for storage and transmission purposes of such medical images. In general, medical images are compressed in a lossless manner in order to preserve details and to avoid wrong diagnosis. But this leads to a lower compression rate. Hence we consider region of interest (ROI) normally the abnormal region in the image and compress it without loss to achieve high compression ratio in par with maintaining high image quality and the Non-region of interest (Non-ROI) of the image is compressed in a lossy manner. This paper discusses two simple hybrid coding techniques (Hybrid A and Hybrid B) on MRI human brain tumor image datasets. Also we evaluate their performance by comparing them with the standard lossless technique JPEG 2000 in terms of compression ratio (CR) and peak to signal noise ratio (PSNR). Both hybrid codes have resulted in computationally economical scheme producing higher compression ratio than existing JPEG2000 and also meets the legal requirement of medical image archiving. The results obtained prove that our proposed hybrid schemes outperform existing schemes.