A compact four-element UWB MIMO antenna is proposed and its characteristics are investigated. The proposed antenna has a hexagon molecule-shaped fractal structure as its radiating element. The antenna elements are placed orthogonally to each other in order to yield good isolation, without any additional decoupling structure. The band rejection in WLAN band is attained by etching a C-shaped slot on each radiating element. The antenna has a compact size of 40 × 40 × 1.6 mm 3 and exhibits stable omni-directional radiation pattern. In addition, it shows an acceptable impedance bandwidth (S 11 < −10 dB) in the range 2.4-10.6 GHz with an isolation better than −20 dB over the UWB range. The performance of the proposed antenna is calculated in terms of antenna characteristics and MIMO parameters. The isolation level in-between the elements is found to be reasonable for MIMO application. The simulated and measured results are in good accord which makes the antenna a suitable candidate for massive MIMO and high-density packaging applications.

Table 3 presents the comparison of the proposed parasitic patch array antenna in different literatures. 4,10,11 The parameters including number of layer and patch, the size of the antenna, the impedance bandwidth and the peak gain are taken into account. From the table, we can see that the 5 3 5 CPPS-based array antenna has the advantages of simple structure, wide bandwidth and high gain. | C ONCL US I ONThis article presents a design of a 5 3 5 array antenna based on coplanar parasitic patch structure. A feed network is formed via dual ports stimulating the two center patches and resonance branches between the central patches and the parasitic patches. The designed array antenna has a simple structure, high gain, strong orientation, and low crosspolarization. It has good reference value to the array antenna research. Therefore, it has important applications in communication and radar system.

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Of late, there has been an increase in hearing impairment cases and to provide the most advantageous solutions to them is an uphill task for audiologists. Significant difficulty faced by the audiologists is in effective programming of hearing aids to provide enhanced satisfaction to the users. The main aim of our study was to develop a software intelligent system (SIS): (i) to perform the required audiological investigations for finding the degree and type of hearing loss, and (ii) to suggest appropriate values of hearing aid parameters for enhancing the speech intelligibility and the satisfaction level among the hearing aid users. In this paper, we present a Neuro-Fuzzy based SIS to automatically predict and suggest the hearing-aid parameters such as gain values, compression ratio and threshold knee point, which are needed to be fixed for different octave frequencies of sound inputs during the hearing-aid trial. The test signals for audiological investigations are generated through the standard hardware present in a personal computer system and with the aid of a software algorithm. The proposed system was validated with 243 subjects' data collected at the Government General Hospital, Chennai, India. The calculated sensitivity, specificity and accuracy of the proposed audiometer incorporated in the SIS were 98.6%, 96.4 and 98.2%, respectively, by comparing its interpretations with those of the 'gold standard' audiometers. Furthermore, 91% (221 of 243) of the hearing impaired subjects attained satisfaction in the first hearing aid trials itself with the gain values as recommended by the improved SIS. The proposed system reduced around 75% of the 'trial and error' time spent by audiologists for enhancing satisfactory usage of the hearing aid. Hence, the proposed SIS could be used to find the degree and type of hearing loss and to recommend hearing aid parameters to provide optimal solutions to the hearing aid users.

Text classification in medical domain could result in an easier way of handling large volumes of medical data. They can be segregated depending on the type of diseases, which can be determined by extracting the decisive key texts from the original document. Due to various nuances present in understanding language in general, a requirement of large volumes of text-based data is required for algorithms to learn patterns properly. The problem with existing systems such as MedScape, MedLinePlus, Wrappin, and MedHunt is that they involve human interaction and high time consumption in handling a large volume of data. By employing automation in this proposed field, the large involvement of manpower could be removed which in turn speeds up the process of classification of the medical documents by which the shortage of medical technicians in third world countries are addressed.

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