With the growth of trends in computing and requirement for developing a reliable computing environment the need for performing tasks in distributed manner has gained much importance. Atomic commit protocols are used to preserve the ACID property in distributed systems when several sites need to
update their database with the same information. A variety of protocols have been proposed for last few decades, but among all Two-Phase Commit (2PC) are most widely used. 2PC is a blocking protocol, i.e. If a coordinator fails while the participants are waiting for a decision in its uncertain state, all the participants remain in a blocked state till the coordinator recovers and terminates the transaction. This is undesirable as these sites may be holding locks on the resources. In the event of message loss, the 2PC protocol will result in the sending of more messages. As an alternative, non-blocking atomic commit protocol has been suggested: This non-blocking protocol is Three-Phase Commit (3PC) protocol, which requires an extra phase (pre-commit) to
remove blocking state.

Although, the existing protocols are sufficient to ensure that ACID properties are maintained in a distributed transaction environment, but the substantial cost associated with the normal transaction execution adversely affects the performance of the system. These protocols require so many messages  transfer from the coordinator to participants and vice versa during different phases and corresponding increase communication and time complexity and hold the locks acquire by different participants till the end of last phase, forcing other transactions also to be blocked just because of the objects that are locked. All the existing protocols give the same performance for both deferred and immediate consistency constraints databases. Lots of protocols are
being proposed and mainly the concentration was to make the 2PC protocol non-blocking or to minimize the blocking possibilities in 2PC. There has been a renewed interest in developing and optimization of more efficient ACPs. This is also crucial in modern electronics and e-commerce environment which are characterized by high volume of transactions at several levels.

This paper is an effort to propose a new technique to optimize atomic commit protocols by optimizing voting phase based on deferred and immediate consistency constraints. Also an attempt has been made to propose reduction in communication complexity which will require less number of messages to be shared between coordinator and participants, the cost of execution as well as time delays.

This paper represents the improved meta-data search model for efficient content based image retrieval. This paper includes brief information of improved features i.e. dominant color and relative smoothness and other features like color histogram and edge histogram all together. This approach shows a step by step approach to get the accurate relevant results (images) from the database using meta-data. To achieve this goal the work also included the DWT (discrete wavelet transform) algorithm for the better results.

Facial Expression Recognition is essential for designing ny human-machine interface. The main concern of Facial Expression Recognition is to come to a decision what features are required to represent a Facial Expression. A research has been carried out in facial expression recognition by solving the research issues of facial expression recognition under different illuminations, orientations and many other variations but no technique so far has achieved a 100% accurate recognition rate. Feature extraction is the main research issue for facial expression recognition and the objective of this paper work is to extract a comparative performance analysis of different feature extraction
technique for facial expression recognition. Experimental are performed on seven expressions, (anger, disgust, fear, happiness, sadness, surprise, neutral) of JAFFE dataset. The features of facial expression image have been extracted by using Discrete Cosine Transform, Gabor Filter, Discrete Wavelet Transform and  Gaussian distribution of a facial image and feature vector is then proceed to Adaboost classifier for automatic recognition.

In Ad-hoc wireless networks, the basic 802.11 Media Access Control (MAC) protocol uses the distributed coordination function (DCF) to share the medium between multiple devices. But the uses of 802.11 MAC protocol in an Ad - hoc network are affected by various issues such as limited power capacity, packet losses due to transmission errors, a lot of control traffic and inability to avoid packet collision. To resolve these issues many protocols have been developed. But we have not found any efficient protocol, which can solve the power management, packet collision and packet loss issues efficiently. In this paper, we propose a new protocol that adjusts the upper and lower bounds of the contention window to reduce the number of collisions. It also uses a power control scheme, triggered by the MAC layer to limit the packet loss, energy wastage and decrease the number of collisions. The proposed protocol has been implemented and its
performance is compared with the existing 802.11 MAC protocol. We calculated the packet delivery fraction, average (e-e) delay, average throughput and packet losses in various situations. We found our proposed protocol is fairly better than the existing protocol.

Image processing is an important and challenging task in the computer-aided diagnostic systems. Artifacts contained in brain images throttle both, the visual interpretation by experts as well as processing and analysis. In medical image processing and especially in segmentation task, it is very important to pre-process the image so that segmentation and feature extraction algorithms work precisely. This paper propounds the pre-processing algorithm for brain CT scan images. This algorithm removes noise from the image by using median filter and uses morphological operations to remove artifacts from brain images. This pre-processing algorithm is simple, execution time is less, independent of image orientation and will also reduce the over segmentation problems in further processing of the brain images.