Computer Engineering

This study characterized the alpha-amylase from maize based on the amylolytic activity initiated during the germination of the maize (Zea mays) grain. Alpha amylase was partially characterized from maize and the protein concentration was determined (found to be 4.48mg/ml) using the Biuret method. The enzyme assay; effect of metal, effect of pH, effect of substrate and temperature was determined. The optimum temperature of the enzyme activity was 50oC and the enzyme activity was stable at this temperature till when a sharp decrease was observed at temperature of 55oC. The crude ? – amylase was optimally active at pH 7.0. The apparent km value and Vmax of the enzyme from the Line weaver-Bulk plot during hydrolysis of soluble starch were 0.535mM and 0.451µmol/min/ml respectively. The activities of the ? amylase were stimulated by MgCl2 and CaCl2 but inhibited by HgCl2. Therefore, this invention could proffer an alternative to the complex nature of malt extract, with alpha amylase considered difficult to characterize. The procedure offers characterization in a simple and efficient manner and product obtained is at least 95% pure with little impurities. This study shows that the alpha amylase activity of the maize grain was discovered to be high and this could be an alternative source of the enzyme in beer and wine production, as well as industrial source of the enzyme. Thus, it can be used in various industries to degrade starch and accurate result can be generated.

Internet of Things (IoT) is a significant idea of another innovation era. It is a dream that allows the sensors or implanted gadgets to be interconnected over the Internet. The up and coming IoT will be significantly exhibited by the tremendous amount of heterogeneous organized installed gadgets that create seriously "Huge information". Immensely a lot of information is being gathered today by numerous associations and in a persistent raise. It ends up being computationally wasteful to break down such gigantic information. The amount of the accessible crude information has been developing an exponential scale. In an enormous database, the important data is covered up. The new grew Big information methods can deal with numerous difficulties that face information investigation and can remove profitable data. This study demonstrates the investigation of IoT and Big information. The study talks about Big information on IoT and how it is made. Numerous IoT existing, future application and an assortment of IoT advances whether wired or remote are seen. Difficulties and procedures that fathom these issues are talked about and the design of IoT is watched.

In present day to day life, effective data hiding methods are needed due to attack made on data communication. This paper presents the technique for the above requirement. In this proposed method, secret message in form of audio file is embedded within another carrier audio file(.wav). In the transmitter end the output will be similar to the carrier with secret message embedded inside. The hacker will be blinded by the transmitted signal. At the receiver end the original message can be retrieved without any loss. The entire proposed system is simulated and their corresponding waveforms prove the effectiveness of this method.

Closed sequential pattern mining has attracted increasing concerns in recent data mining research because it is more efficient than sequential pattern mining and produces more compact result set. Genetic algorithms perform global search and have less time complexity compared to other algorithms. In this paper, we propose a novel algorithm GCSP for mining closed sequential patterns using genetic approach. It uses an efficient fitness function to improve the performance. The results show that the proposed algorithm GCSP can find closed sequential patterns efficiently and outperforms CloSpan and ClaSP.

In this paper, the pattern recognition and classification based on clustering algorithm and linear decision is studied. The research method is used for an example of a car and a background in a picture,The experimental results show that the recognition effect is better than other traditional methods.

The main aim of edge detection operation is a method to detect the presence of object image that commonly used in the field of image processing. The most well known technique for edge detection is gradient-based. There are number of methods that have been used to make an implementation of a gradient-based Edge detection algorithm design. This project proposes a design and implementation of gradient based edge detection algorithm using of Sobel & prewitt operator. Sobel operator is better noise suppression characteristics when compared to other operators such as Robert operator &2 order laplacian operator & others. An original image is converted into grayscale to obtain image intensity for edge detection. Sobel & prewitt operators are used for computing digital gradients. The whole process is performed in the hardware level. The result shows good performance of edge detection with which is able to detect just within 2ms.

The content of a kidney image can be expressed in terms of different features such as auto correlation, contrast, promenance, shade, dissimilarity, energy, entropy, homogeneity, maximum probability, variance, co-variance, correlation, inverse difference moment and inertia. Retrieval methods based on these features can be varied depending on how the feature values are combined. Many of the existing approaches assume linear relationships between different features, and also require users to assign weights to features for themselves. In this paper, we study the neural network-based image retrieval system. This approach allows the user to select an initial query image and incrementally search target images through training the images which are stored in the image database. The experimental results show that this approach provides better image retrieval performance than the existing linearly combining approach methods.

Ant colony optimization is unique convergence of Swarm Intelligence and Bio-Inspired Artificial Intelligence. Ants are social insects with limited skills that live in colonies able to solve complex problems. The intelligence of the global society arises from self organization mechanisms, based on the indirect communication between individuals through pheromones. The Symmetric Travelling Salesman Problem here presented is a typical case that requires a self organization type of algorithm, in order to cope with the problem dynamics. The simulation results show how the ant colony optimization is able to solve the different possible routing cases. The innovation in this entire proposal (paper) is that an attempt has been made to improve the existing ant colony algorithm and then apply to the problem set. Ant colony optimization (ACO) has been successfully applied to solve combinatorial optimization problems, but it still has some drawbacks such as stagnation behavior, long computational time, and premature convergence. These drawbacks are more evident when the problem size increases. In this paper, I have reported the analysis of using a reduced/lower pheromone trail bound and a dynamic updating rule for the heuristic parameters based on entropy to improve the efficiency of ACO in solving Traveling Salesman Problems (TSPs). TSPs are NP-hard problem. Even though the problem itself is simple, when the number of city is large, the search space will become extremely large and it becomes very difficult to find the optimal solution in a short time. From my simulations, it can be found that the proposed algorithm indeed has superior search performance over traditional ACO algorithms do.

A trial was conducted during 2005 06 & 2006-06 at All India Coordinated Research Project for Dryland Agriculture Phulbani, Orissa ,India., with an objective to obtain the water loss and economics of the lined ponds .There were three treatments T1-Lined pond with soil cement plaster (6:1) 8cm thickness ,T2-Unlined pond,T-3-No pond.10% of the cropped area was dug for construction of the pond in Lined and Unlined pond treatments. The size of the pond is 7m top widths, 1m-bottom width, 3m heights, and 1:1side slope. The water harvested in pond was reutilized for the pumpkin crop, which was sown only in Lined pond treatment, as there was no water available in unlined pond so the crop was not sown there. Lined pond with soil cement (6:1) plaster of 8cm thickness gave highest Tomato yield of 4.8 t/ha during kharif 2008-09 and radish root yield of 25.5 t/ha in rabi seasons of 2008-09.. The water loss was 326 lit/day in lined pond and 24,000 lit/day in unlined pond. The benefit: cost ratio in lined pond was 3.04 as compared to 1.64 in unlined pond during 2008-09.

The evolution of web 2.0 has made social media networks more prevalent. Forums, blogs, tweets and posts, have become an important media for internet users to share views. With the evolution of Natural Language Processing (NLP), sentiment analysis is being essentially used as a means to determine the attitude of a person with respect to some topic or the overall contextual polarity from these inputs. The attitude may be his or her judgment or evaluation, effective state mind or the intended emotional communication. As e-commerce is becoming increasingly popular, the number of customer reviews that a product receives grows rapidly, which is being encouraged by the merchants selling the products. For a popular product, the number of reviews can be in hundreds or even thousands. This paper describes the concepts of sentiment analysis from unstructured text, looking at why they are useful and what tools and techniques are available. It also focuses specifically on a novel feature based opinion extraction scheme demonstrated with key open-source tools and applications and the problems associated with opinion detection in social media have also been analyzed.