In this review, the EMI shielding properties of the various carbonaceous fillers are thoroughly reviewed. Electromagnetic interference (EMI) had been a cause of major concern in the live broadcasting, entertainment, aviation and defense industries since vital radio signals could create more interference, which could lead to poor performance. To reduce the effect of EMI, the organic polymeric composites along with the carbonaceous fillers are mostly used since they are flexible, low denser, high mechanical strength, high thermo-stability, high electrical and thermal conductivity, excellent fracture toughness, and high friction/wear resistance. There are lot of carbon based materials are being used as EMI shielding material in mono and compound form. This review gives a broad understanding of the utilization of carbonaceous fillers in polymer matrixes. Thus, the overall coverage on this carbon based materials and their effectiveness could help the researchers to find right carbon material for suitable application. According to this review, the absorption mechanism is vital to achieve high EMI shielding effect. The fillers such as graphene and CNTs are most preferable EMI shielding filler, according to the vast coverage of previous articles. However, there are more magnetoelectric materials also evolved recently, having combined properties of both conductive and magnetic, yielding high SE at elevated frequencies.

The knowledge discovery from large database is useful for decision making in industry real-time problems. Given a large voluminous transaction database, the knowledge is discovered by extracting maximal pattern after some analysis. Various methods have been proposed for extracting maximal pattern including FP and CP trees. It has been noticed that time taken by these methods for mining is found to be large. This paper modifies tree construction strategy of CP-tree for mining maximal pattern and the strategy takes less time for mining. The proposed modified CP-tree is constructed in two phases. The first phase constructs the tree based on user given item order along with its corresponding item list. In the second phase, each node in the branch of the constructed tree is dynamically rearranged based on item sorted list. The maximal patterns are retrieved from the proposed tree using the FPmax algorithm. The proposed tree has been built to support both interactive and incremental mining. The performance is evaluated using both dense and sparse bench mark data sets such as CHESS, MUSHROOM, CONNECT-4, PUMSB, and RETAIL respectively. The performance of the modified CP-tree is encouraging compared to some of the recently proposed approaches.

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