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In recent years many people age above 25 are suffering from Neural Foraminal Stenosis (NFS) disease. Neural Formanial Stenosis is a problem of narrowing the spaces between the bones of the spine. It is curable at the earliest stage. A simple exercise can give relief to this problem. But Identification of this problem at the initial stage is a difficult task. It requires more screening techniques and knowledge about the problem. The motivation for this work is to identify the disease at the earliest stage. In clinically, it is identified by analyzing the CT and MRI images. Accurate boundary delineation is important in the clinical diagnosis and also for the proper treatment. Surveys say that boundary detection is subjective to the experience of the clinician. These variations make an impact on the detection of Boundary delineation. Image segmentation algorithms can be used to assist clinicians to detect the boundaries. The classifier can also be used to classify the level of the NFS. This paper utilizes the hierarchical clustering to detect the boundary of the affected region and it is found that, it gives a better assistance to the clinicians.

The enormous increase of mobile data growth needs a super-efficient mobile network that provides a superior communication while at the same time judiciously dealing with the shortage ofglobal bandwidth. When the mobile service providers compete among themselves to provide high quality of service (QoS), and low latency video and multimedia applications for wireless applications, the major constrain that impedes the progress is limited available spectrum range between 700MHz to 2.6GHz where each of the service providersare allocated approximately 200MHz across all the different cellular bands of the available spectrum. This can be surmounted by using Millimeter wave (mm-wave).The main focus of the paper is two-fold: to throw some lights on how mm-wave can be used for 5G cellular and to discuss how the next generation mobile users can be highly benefited by prudently using the bandwidth available in the mm-wave spectrumranging from 3 to 300GHz.In addition to the fact that the usage of mm-waves can substantially reduce the size of various components, especially the antenna size, using steerable antennas at both base and mobile stations make mm-wave a paramount and viable option for its usage in cellular mobile applications.

This paper enables the personnel to monitor and acquire data from hazardous environments where the human inspection is difficult. The wireless sensor motes are developed for measuring the real-time parameters like temperature, humidity, pressure etc. Further ZigBee protocol has been utilized to enable Inter networking of sensor motes which allows the personnel to aggregate data which makes the available data more reliable. The data sensed by different motes are communicated to the cluster head. The cluster head performs data aggregation which is then communicated to the officials through GSM technology. Whenever the measured real time data crosses a predefined threshold, a complete picture of the environment is sent to the official's mobile as MMS. Failure of any node wont affect the Data Aggregation and data from the remaining node can be used to know about the Environment. The proposed algorithm is built using Atmel Processor and the results are presented.