The Role of DBMS in Analytical Processes of the Logistic of Stock Reserves

One of main problems of corporate information systems is the precise evaluation of speed of transactions and the speed of making reports. The core of the problem is based on the DBMS that is used. Most DBMS which are oriented for high performance and reliability of transactions do not give fast access to analytical and summarized data and vice versa. It is quite difficult to estimate which class of database to use. The author of the article gives a concise observation of the problem and a possible way to be solved.

Expert System for Decision-Making Problem in Economics

An expert system (ES) is a class of computer programs developed by researchers in artificial intelligence. In essence, they are programs made up of a set of rules that analyze information about a specific class of problems, as well as provide analysis of the problems, and, depending upon their design, recommend a course of user action in order to implement corrections. ES are computerized tools designed to enhance the quality and availability of knowledge required by decision makers in a wide range of industries. Decision-making is important for the financial institutions involved due to the high level of risk associated with wrong decisions. The process of making decision is complex and unstructured. The existing models for decision-making do not capture the learned knowledge well enough. In this study, we analyze the beneficial aspects of using ES for decision- making process.

About Methods of Mathematical Modelling in the Development of Information Systems

This article describes the approach, which allows to develop information systems without taking into consideration details of physical storage of the relational model and type database management system. Described in terms of graph model, this approach allows to construct several algorithms, for example, for verification application domain. This theory was introduced into operation testing as a part of CASE-system METAS.

How to Use a Desktop Version of a DBMS for Client-Server Applications

DBMS (Data base management systems) still have a very high price for small and middle enterprises in Bulgaria. Desktop versions are free but they cannot function in multi-user environment. We will try to make an application server which will make a Desktop version of a DBMS open to many users. Thus, this approach will be appropriate for client-server applications. The author of the article gives a concise observation of the problem and a possible way of solution.

Constructing a Canonical form of a Matrix in Several Problems about Combinatorial Designs

Partially supported by the Bulgarian Science Fund contract with TU Varna, No 487.

Cluster Supercomputer Architecture

The paper describes the architecture of SCIT - supercomputer system of cluster type and the base architecture features used during this research project. This supercomputer system is put into research operation in Glushkov Institute of Cybernetics NAS of Ukraine from the early 2006 year. The paper may be useful for those scientists and engineers that are practically engaged in a cluster supercomputer systems design, integration and services.

Adjusting WSMO API Reference Implementation to Support More Reliable Entity Persistence

* The research has been partially supported by INFRAWEBS - IST FP62003/IST/2.3.2.3 Research Project No. 511723 and “Technologies of the Information Society for Knowledge Processing and Management” - IIT-BAS Research Project No. 010061.

An Adaptive Genetic Algorithm with Dynamic Population Size for Optimizing Join Queries

The problem of finding the optimal join ordering executing a query to a relational database management system is a combinatorial optimization problem, which makes deterministic exhaustive solution search unacceptable for queries with a great number of joined relations. In this work an adaptive genetic algorithm with dynamic population size is proposed for optimizing large join queries. The performance of the algorithm is compared with that of several classical non-deterministic optimization algorithms. Experiments have been performed optimizing several random queries against a randomly generated data dictionary. The proposed adaptive genetic algorithm with probabilistic selection operator outperforms in a number of test runs the canonical genetic algorithm with Elitist selection as well as two common random search strategies and proves to be a viable alternative to existing non-deterministic optimization approaches.

Performance Comparison of MATLAB and Neuro Solution Software on Estimation of Fuel Economy by Using Artificial Neural Network

In the world, scientific studies increase day by day and computer programs facilitate the human’s life. Scientists examine the human’s brain’s neural structure and they try to be model in the computer and they give the name of artificial neural network. For this reason, they think to develop more complex problem’s solution. The purpose of this study is to estimate fuel economy of an automobile engine by using artificial neural network (ANN) algorithm. Engine characteristics were simulated by using “Neuro Solution” software. The same data is used in MATLAB to compare the performance of MATLAB is such a problem and show its validity. The cylinder, displacement, power, weight, acceleration and vehicle production year are used as input data and miles per gallon (MPG) are used as target data. An Artificial Neural Network model was developed and 70% of data were used as training data, 15% of data were used as testing data and 15% of data is used as validation data. In creating our model, proper neuron number is carefully selected to increase the speed of the network. Since the problem has a nonlinear structure, multi layer are used in our model.

Dynamic Determination of Personalized Educational Paths

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

User-centric music information retrieval

The rapid growth of the Internet and the advancements of the Web technologies have made it possible for users to have access to large amounts of on-line music data, including music acoustic signals, lyrics, style/mood labels, and user-assigned tags. The progress has made music listening more fun, but has raised an issue of how to organize this data, and more generally, how computer programs can assist users in their music experience. An important subject in computer-aided music listening is music retrieval, i.e., the issue of efficiently helping users in locating the music they are looking for. Traditionally, songs were organized in a hierarchical structure such as genre->artist->album->track, to facilitate the users’ navigation. However, the intentions of the users are often hard to be captured in such a simply organized structure. The users may want to listen to music of a particular mood, style or topic; and/or any songs similar to some given music samples. This motivated us to work on user-centric music retrieval system to improve users’ satisfaction with the system. The traditional music information retrieval research was mainly concerned with classification, clustering, identification, and similarity search of acoustic data of music by way of feature extraction algorithms and machine learning techniques. More recently the music information retrieval research has focused on utilizing other types of data, such as lyrics, user-access patterns, and user-defined tags, and on targeting non-genre categories for classification, such as mood labels and styles. This dissertation focused on investigating and developing effective data mining techniques for (1) organizing and annotating music data with styles, moods and user-assigned tags; (2) performing effective analysis of music data with features from diverse information sources; and (3) recommending music songs to the users utilizing both content features and user access patterns.

Recreational Food Service: A Growing Employment Option

The recreational food service industry represents a wealth of potential job opportunities for graduates of hospitality management degree programs. Most hospitality management curricula are saturated with core courses and basic hospitality education course work, leaving little room for additional components. Recreational food service, however, could be easily integrated into an existing pro- gram and made available for students interested in this growing employment option. The author presents one option as a model curriculum approach.

A deontic analysis of inter -organizational control requirements

This research focuses on the design and verification of inter-organizational controls. Instead of looking at a documentary procedure, which is the flow of documents and data among the parties, the research examines the underlying deontic purpose of the procedure, the so-called deontic process, and identifies control requirements to secure this purpose. The vision of the research is a formal theory for streamlining bureaucracy in business and government procedures. ^ Underpinning most inter-organizational procedures are deontic relations, which are about rights and obligations of the parties. When all parties trust each other, they are willing to fulfill their obligations and honor the counter parties’ rights; thus controls may not be needed. The challenge is in cases where trust may not be assumed. In these cases, the parties need to rely on explicit controls to reduce their exposure to the risk of opportunism. However, at present there is no analytic approach or technique to determine which controls are needed for a given contracting or governance situation. ^ The research proposes a formal method for deriving inter-organizational control requirements based on static analysis of deontic relations and dynamic analysis of deontic changes. The formal method will take a deontic process model of an inter-organizational transaction and certain domain knowledge as inputs to automatically generate control requirements that a documentary procedure needs to satisfy in order to limit fraud potentials. The deliverables of the research include a formal representation namely Deontic Petri Nets that combine multiple modal logics and Petri nets for modeling deontic processes, a set of control principles that represent an initial formal theory on the relationships between deontic processes and documentary procedures, and a working prototype that uses model checking technique to identify fraud potentials in a deontic process and generate control requirements to limit them. Fourteen scenarios of two well-known international payment procedures—cash in advance and documentary credit—have been used to test the prototype. The results showed that all control requirements stipulated in these procedures could be derived automatically.^

Pulsed parabolic equation model of acoustic transmission (PPEMAT)

Underwater sound is very important in the field of oceanography where it is used for remote sensing in much the same way that radar is used in atmospheric studies. One way to mathematically model sound propagation in the ocean is by using the parabolic-equation method, a technique that allows range dependent environmental parameters. More importantly, this method can model sound transmission where the source emits either a pure tone or a short pulse of sound. Based on the parabolic approximation method and using the split-step Fourier algorithm, a computer model for underwater sound propagation was designed and implemented. This computer model differs from previous models in its use of the interactive mode, structured programming, modular design, and state-of-the-art graphics displays. In addition, the model maximizes the efficiency of computer time through synchronization of loosely coupled dual processors and the design of a restart capability. Since the model is designed for adaptability and for users with limited computer skills, it is anticipated that it will have many applications in the scientific community.

Factors influencing university performance of associate in arts graduates transferring to the state university system

The purpose of this study was to examine the factorsbehind the failure rates of Associate in Arts (AA)graduates from Miami-Dade Community College (M-DCC) transferring to the Florida State University System (SUS). In M-DCC's largest disciplines, the university failure rate was 13% for Business & Management, 13% for Computer Science, and 14% for Engineering. Hypotheses tested were: Hypothesis 1 (H1): The lower division (LD) overall cumulative GPA and/or the LD major field GPA for AA graduates are predictive of the SUS GPA for the Business Management, Computer Science, and Engineering disciplines. Hypothesis 2 (H2): Demographic variables (age, race, gender) are predictive of performance at the university among M-DCC AA graduates in Engineering, Business & Management, and Computer Science. Hypothesis 3 (H3): Administrative variables (CLAST -College Level Academic Skills Test subtests) are predictive of university performance (GPA) for the Business/Management, Engineering, and Computer Science disciplines. Hypothesis 4 (H4): LD curriculum variables (course credits, course quality points) are predictive of SUS performance for the Engineering, Business/Management and Computer Science disciplines. Multiple Regression was the inferential procedureselected for predictions. Descriptive statistics weregenerated on the predictors. Results for H1 identified the LD GPA as the most significant variable in accounting for the variability of the university GPA for the Business & Management, Computer Science, and Engineering disciplines. For H2, no significant results were obtained for theage and gender variables, but the ethnic subgroups indicated significance at the .0001 level. However, differentials in GPA may not have been due directly to the race factor but, rather, to curriculum choices and performance outcomes while in the LD. The CLAST computation variable (H3) was a significant predictor of the SUS GPA. This is most likely due to the mathematics structure pervasive in these disciplines. For H4, there were two curriculum variables significant in explaining the variability of the university GPA (number of required critical major credits completed and quality of the student's performance for these credits). Descriptive statistics on the predictors indicated that 78% of those failing in the State University System had a LD major GPA (calculated with the critical required university credits earned and quality points of these credits) of less than 3.0; and 83% of those failing at the university had an overall community college GPA of less than 3.0.