Biometric Authentication of Remote Fingerprint Live Scan Using Artificial Neural Network with Back Propagation Algorithm and Possibility for Wider Security Applications (Published)
This study is aim to experiments the development of an automated foolproof university library system that integrates fingerprint technique with fingerprint-based Personally Identified Number (PIN)/password architecture for enhanced registration and login security. The development environment for creating the electronic library application for universities as RESTful Web Service is Jersey Framework. This framework implements JAS-RX 2.0 API, which is a de facto specification for developing a RESTful Web Service-based software system. Other necessary programming technologies employed in the research work are JDK, Apache Tomcat and Eclipse, which were set up prior to setting up the Jersey Framework as the development environment. The study is therefore summarized by generating hash digital values of perfectly matched reference shape signatures formed from the extraction of global minutiae features, comparing and further matching each hash value with its corresponding highly encrypted password equivalence for unique establishment of a person’s identity, minimal mean-square errors and unnecessary ambiguity introduced through false positives, as an extended security enhancement measure in biometric systems. , the study investigates the algorithm for generating templates for matching minutiae  together with the algorithm for generating reference axis , which infers that for a pair of minutiae (pn , q0) to match, there exists a reference point that corresponds between the two fingerprint images. The experimental result shows that the Sample fingerprint images were captured using a biometric scanner, which was integrated with the help of JAVA libraries, and stored in a database as raw image files..
Comparison of Floyd-Warshall and Mills Algorithms for Solving All Pairs Shortest Path Problem:Case Study of Sunyani Municipality (Published)
The Floyd-Warshall and Mill algorithm were used to determine the all pair shortest paths within the Sunyani Municipality so as to compare which of the algorithms runs faster on the computer. The two algorithms were used on a network of 80 nodes with respective edge distances in matrix format as inputs. Matlab codes were generated to run the algorithms. All the two algorithms were able to compute the all pair shortest paths. The running time for the Floyd-Warshall and Mills are 1057.22 and 444.53 ( in seconds ) respectively. The two algorithms computed the shortest path from node 1 (Ohunukurom) to node 80 (Addae Boreso) to be 17.3000 km. Based on this study, it is convenient to conclude that Mills decomposition algorithm runs more faster on a computer than the Floyd-Warshall algorithm
Searching Isomorphic Graphs (Published)
To determine that two given undirected graphs are isomorphic, we construct for them auxiliary graphs, using the breadth-first search. This makes capability to position vertices in each digraph with respect to each other. If the given graphs are isomorphic, in each of them we can find such positionally equivalent auxiliary digraphs that have the same mutual positioning of vertices. Obviously, if the given graphs are isomorphic, then such equivalent digraphs exist. Proceeding from the arrangement of vertices in one of the digraphs, we try to determine the corresponding vertices in another digraph. As a result we develop an algorithm for constructing a bijective mapping between vertices of the given graphs if they are isomorphic. The running time of the algorithm equal to O(n5), where n is the number of graph vertices.
The applicability of the method of managing an aero gas turbine engine using wavelet neural networks is considered in this article. The use of wavelet functions provides the traditional neural network of local approximation, which provides rapid training of the network and reduces the typical for multi-layer perceptrons dependence of the quality of learning from the sequence of submission of training data. The structural scheme of the control system and algorithm for determination of the number of wavelet-bases and the size of the network are developed.
A Web-Based Clinical Decision Support System for the Management of Diabetes Neuropathy Using Naïve Bayes Algorithm (Published)
Diabetes Neuropathy is a chronic health problem with devastating, yet preventable consequences. Due to this shortage of specialists, there is a need for a Clinical Decision Support System that will diagnose and manage diabetes neuropathy. This work therefore aimed at designing a web-based Clinical Decision Support System for the management of early diabetes neuropathy. Four pattern classification algorithms (K-nearest neighbor, Decision Tree, Decision Stump and Rule Induction) were adopted in this work and were evaluated to determine the most suitable algorithm for the clinical decision support system. Datasets were gathered from reliable sources; two teaching hospitals in Nigeria, these were used for the evaluation Benchmarks such as performance, accuracy level, precision, confusion matrices and the models building’s speed were used in comparing the generated models. The study showed that Naïve Bayes outperformed all other classifiers with accuracy being 60.50%. k-nearest neighbor, Decision Tree, Decision Stump and Rule induction perform well with the lowest accuracy for x- cross validation being 36.50%. Decision Tree falls behind in accuracy, while k-nearest neighbour and Decision Stump maintain accuracy at equilibrium 41.00%. Therefore, Naïve Bayes is adopted as optimal algorithm in the domain of this study. The rules generated from the optimal algorithm (Naïve Bayes) forms the back-end engine of the Clinical Decision Support System. The web-based clinical decision support system was then designed The automatic diagnosis of diabetes neuropathy is an important real-world medical problem. Detection of diabetes neuropathy in its early stages is a key for controlling and managing patients early before the disabling effect present. This system can be used to assist medical programs especially in geographically remote areas where expert human diagnosis not possible with an advantage of minimal expenses and faster results. For further studies, researchers can improve on the proposed clinical decision support system by employing more than one efficient algorithm to develop a hybrid system.
Comparison of Floyd-Warshall and Mills Algorithms for Solving All Pairs Shortest Path Problem. Case Study: Sunyani Municipality (Published)
The Floyd-Warshall and Mill algorithm were used to determine the all pair shortest paths within the Sunyani Municipality so as to compare which of the algorithms runs faster on the computer. The two algorithms were used on a network of 80 nodes with respective edge distances in matrix format as inputs. Matlab codes were generated to run the algorithms. All the two algorithms were able to compute the all pair shortest paths. The running time for the Floyd-Warshall and Mills are 1057.22 and 444.53 ( in seconds ) respectively. The two algorithms computed the shortest path from node 1 (Ohunukurom) to node 80 (Addae Boreso) to be 17.3000 km. Based on this study, it is convenient to conclude that Mills decomposition algorithm runs more faster on a computer than the Floyd-Warshall algorithm.
There various algorithms that can factor large integers but very few of these algorithms run in polynomial time. This fact makes them inefficient. The apparent difficulty of factoring large integers is the basis of some modern cryptographic algorithms. In this paper we propose an algebraic approach to factoring composite integer. This approach reduces the number of steps to a finite number of possible differences between two primes.