Recent Patents on Computer Science - Volume 5, Issue 1, 2012

With an initial investment of $400 each, engineer Bill Fair and mathematician Earl Isaac founded Fair Isaac Corporation (FICO) in 1956 on the principle that data, used intelligently, can improve business decisions. This extraordinary foresight has come to be known as Business Intelligence (BI), an umbrella term encompassing a wide range of activities and technologies involved in the process of collecting data, translating data into information, using information to guide and support decision making with the ultimate goal of enhancing corporate performance. As a forerunner in the field of Business Intelligence, FICO has been awarded more than 100 patents for its diverse products, among which FICO score and Falcon payment authorization system are used by millions of customers on a daily basis. This paper examines sixteen most recent patents that were awarded to Fair Isaac Corp between September 2010 and August 2011 in the area of Business Intelligence. Unlike traditional detailed patent reviews that are focused on at a specific topic involving multiple companies, we adopt a company-centered approach to achieve three specific contributions to the literature: 1) to provide concrete examples of how specific FICO patents have advanced the field of Business Intelligence; 2) to synchronize knowledge between academics and practitioners in terms of most urgent and practical issues facing the industry; and 3) to use these cutting-edge innovations to highlight current trends in the Business Intelligence field.

This paper reviews some recent developments from the field of Artificial Intelligence aimed at the determination of credit scores of firms and individuals. Specifically, the academic research efforts which are reviewed are those that consist of hybrid systems. These systems combine two or more intelligent techniques in several forms to derive the advantages of all of them. There are four ways to elaborate a hybrid system: first, by constructing a hybrid algorithm which tightly combines two or more single algorithms. Second, by using an ensemble, which is the combination of the results of a pool of models. Third, by using an algorithm to select the relevant variables and another one to perform the scoring. And finally, by clustering individuals and using this information for the scoring stage. Some patents have used these developments, but in our opinion only a small part of the research has been translated into patents and practical applications.

Textures have been a research focus for many years in human perception, computer graphics and computer vision. Recently, research activities in this area emphasize on texture synthesis. Given one or more example textures, a texture synthesis algorithm generates a new one bearing the same visual characteristics. The synthesized texture can be made of arbitrary size specified by the user. It can be used in many fields such as computer animation, virtual reality, data compression, non-photorealistic rendering and so on. In this paper, the basic concepts of texture and the development process of texture synthesis techniques are introduced first. Then the recent key patents on texture synthesis schemes are reviewed. Finally, this paper points out future works in this area.

Agricultural product quality safety is one of the hot topics in the world. From the technical view, the agricultural production management and traceability are the key measurement for insuring the quality safety. The paper introduced the research progress of traceability systems, and also discussed relevant patents. From 2005 until now, based on long-term requirement investigation and analysis, we have been investigating the system architecture for the data flow of information service for agricultural product quality safety, and developed six techniques, four equipments and six kinds of information systems. The six techniques include individual identification and coding, barcode generating and printing middleware, barcode encryption and decryption, RFID middleware, GAP-based (good agricultural practices) early warning, and XML-based data transferring. The four equipments are portable real-time record-keeping equipments for agricultural production, portable intelligent dispatching equipments for agricultural products, portable supervision equipments for agricultural products, and control equipments for agricultural product sale. The six kinds of information systems are environmental evaluation systems for agricultural fields, management information systems for agricultural safe production, wholesale market management system, logistics management system, agricultural product quality safety supervision and traceability systems and emergency management systems for agricultural product quality. Until October 2011, we have applied the above techniques to aquatic products, vegetables and fruits, as well as livestock traceability in Beijing, Tianjin, and Guangdong, China. The application has gained significant economical, social and ecological benefits.

The existence and functionality of virtual environment at the Department of Computer Science and Educational Technology (KVD) of the University West Bohemia (UWB) in Pilsen are the current reality. The VMware ESX server has been in operation sinece 2007 at the KVD department. The software ESX 3.5.0 SP2 has been installed on the server Dell PE2900. Current status is as follows: about 10 virtual machines (VM) are used by department members, 6 virtual machines are used as a variety of servers and services for education and teaching, about 30 VM are designed as virtual labs to teach students. Earlier model to manage the VM bases solely on access via the ESX server using VMware Infrastructure client which is not effective and safe. In particular, the system of permissions and roles is not effective enough. It is not possible to set access rights (ACL) to each single VM separately. The new solution has been installed since September 2009, ESX host server and vCenter server as one entity. The new ELMS licensing model for VMware vSphere 4 provides unprecedented efficiency, control and choice. Virtual Center Server 4.0 (recently called vCenter Server 4.0) has been implemented on the operating system MS Srv2008 and as one of the virtual machines. Information systems educators must balance the need to protect the stability, availability, and security of computer laboratories with the learning objectives of various courses. The same requirements and needs have to be considered on our side. This paper presents this basic environment, configuration, licensing model and sample teaching laboratories at the KVD. The manuscript demonstrates the advantages, strengths but also the weaknesses in the creation of virtual laboratories for teaching purposes. The final chapter deals with considerations on the coexistence of virtual computer environments to traditional classrooms. We then review the main body of research in this area and identify the key patents that have emerged in this field.

Commercial bank's primary business is credit management. For commercial banks, how to make a scientific and effective credit decision is very important. Therefore, study on credit risk evaluation modeling has become an issue of great practical significance. For imbalanced sample data problem and concept drift problem which emerged in bank credit sample data with time passing, this paper proposed the use of rolling time window with a fixed window size and the ensemble of support vector machine (SVM) to simultaneously deal with concept drift and imbalanced dataset. Thus, we constructed a dynamic model on credit risk evaluation with fixed time window and SVM imbalanced ensemble. For concept drift, SVM was taken as the base model, rolling time window was applied to preliminarily process concept drift, and the ensemble mechanism was used to further improve the model's capacity of dealing with concept drift in prediction. For imbalanced data, ensemble mechanism was proposed to improve the importance of minority samples and their influence in modeling process. The results of empirical studies on imbalanced samples of Chinese listed companies from 2001 to 2010 indicated that the dynamic model on credit risk evaluation with fixed time window and SVM imbalanced ensemble was able to continuously update new knowledge for prediction with time past and handle the problem of imbalanced data mining very well. This model had absolute advantages when comparing with static model with fixed time window and SVM ensemble. The review also discussed relevant patents about credit risk evaluation, the application of SVM, concept drift and fixed time window, which enriched the content of this paper.

Time is coming to celebrate the 60th anniversary from the pioneering work of Markowitz on portfolio selection. His main contribution was to understand that investment decisions did not merely rely on which securities to own, but on how to divide the investor's wealth amongst securities, thus individuating in the portfolio diversification a key issue to focus on. This approach literally shivered the world of finance, and traced the path along which researchers and practitioners are still moving on. This paper is intended to provide a review on the state of the art for portfolio optimization sixty years later, pointing on the issues that still remain challenging, and identifying the key patents that have emerged in this field.

This study reports the design of a low-cost image-based mouth switch for the people with severe disabilities. Via this mouth switch and a communication aid, people with severe disabilities can manipulate computers and communicate with other people. Two experiments were conducted to test the performance of the mouth switch. Experimental results showed that this switch could help people manipulate computers simply by opening or closing the mouth. In addition, this article also presented some relevant patents about the human-computer interfaces for disabled people.

Stock market prediction is an important area of financial forecasting, which attracts great interest of stock investors, stock buyers/sellers, policy makers, applied researchers and many others who are involved in the capital market. This paper aims to develop an efficient model to predict the Dhaka Stock Market Index (DSPI) values using the appropriate forecasting model. It is widely believed that stock data are nonlinear, dynamic and chaotic. In this paper, we propose an adaptive network based fuzzy inference system (ANFIS) to predict DSPI values. We used the daily general DSPI values for the period of March 2003 to October 10, 2006 for the learning and October 11, 2006 to May 31, 2007 for validation. Results obtained by this model are also compared to the back-propagation ANN model and the traditional ARIMA model to show advantages of the proposed ANFIS model. The findings suggest that the ANFIS model can be used as a better predictor for daily general DSPI values as compared to the ANN and the ARIMA models. The review also discussed relevant patents related to our research.

The Patent s annotated in this section have been selected from various Patent databases. These recent Patent s are relevant to the articles published in this journal issue, categorized by different computation methods, bioinformatics, medical informatics, computer graphics, artificial intelligence, cybernetics, hardware architectures, software, theory and methods involved and related to computer science.