Analysis of Pattern Searching Algorithms and Their Application

PurposeThis paper aims to describe the development and application of a manpower planning system for the Slovenian armed forces using a system approach, system dynamics (SD) and numerical optimization.Design/methodology/approachThe model of the hierarchical manpower system was developed by SD methodology and formulated in discrete time space. The problem of tracking the goal trajectories in the eight topmost ranks at the prescribed boundaries was solved by application of the quadratic performance index and finite automata (FA) which was used for classification of acceptable strategies. Genetic algorithms (GA) as well as pattern search were compared at the numeric optimization.FindingsEmploying SD and a system approach increases the understanding of the system control. The definition of an optimum strategy, which would consider only target values for ranks within prescribed parameter boundaries, could provide an undesired oscillatory solution. Inclusion of rules by FA to determine acceptable strategies based on the time response of a strategy provided acceptable, nonoscillatory solutions. GA and pattern search were considered where pattern search was shown to be significantly more suitable for the task of control strategy determination.Practical implicationsThe developed system and methodology was applied by the Slovenian Armed Forces in the process of restructuring.Social implicationsThe developed approach permits a moderate transition to the new desired structure. Restructuring without a clear understanding of the system structure and dynamics might result in undesired social impacts such as strikes and riots.Originality/valueProvision of the systemic view of the hierarchical manpower system and application of FA to determine the proper control of a complex system.

Programming languages for library and textual processing

Searchable encryption (SE) enables data users to securely search encrypted data stored in untrusted cloud servers. However, most SE schemes allow for leakages of access and search patterns to maximize efficiency and functionality. Recent attacks have shown that adversaries can recover query keywords with prior knowledge of the database by exploiting these leakages. Unfortunately, the existing schemes that protect access and search patterns result in frequent communications and high computational costs. Furthermore, complex calculation processes also raise challenges for verifying search results. To address these concerns, we first design an efficient conjunctive SE scheme with search and access pattern privacy using private set intersection. In the proposed scheme, we utilize random numbers to obfuscate the values of polynomials and randomly divide the results into two parts, which simplifies the search process, improves search efficiency, and eliminates the need for time-consuming ciphertext multiplication operations. We also extend this scheme to support search result verifiability. Specifically, by embedding a random number as the root of the return polynomial, we achieve verifiability of search results. Furthermore, we prove the security of both schemes employing the simulation-based method. Finally, we implement the schemes in a real database and thorough performance analyses demonstrate their efficiency.

Dig That Lick (DTL): Analyzing Large-Scale Data for Melodic Patterns in Jazz Performances

Echocardiography is a key assessment tool for the evaluation of cardiac structure and function. The ability to image cardiac structures using 3-dimensional (3D) echocardiography is evolving. In this article, we present some of the key features of the emerging 3D technology and review its applications with an emphasis on real-time 3D transesophageal echocardiography.

In block motion estimation, a search pattern with a different shape or size has a very important impact on search speed and distortion performance. A square-shaped search pattern is adopted in many popular fast algorithms. Recently, a diamond-shaped search pattern was introduced in fast block motion estimation and has exhibited a faster search speed. Based on an in-depth examination of the influence of the search pattern on speed performance, we propose a novel algorithm using a hexagon-based search pattern to achieve further improvement. The hexagon-based search pattern is investigated in comparison with diamond search pattern and demonstrates significant speedup gain over the diamond-based search. Analysis shows that a speed improvement rate of the hexagon-based search (HEXBS) algorithm over the diamond search (DS) algorithm can be over 80% for locating some motion vectors in certain scenarios. In short, the proposed HEXBS algorithm can find the same motion vector with fewer search points than the DS algorithm. Generally speaking, the larger the motion vector, the more search points the. HEXBS algorithm can save, which is further justified by experimental results.

(ProQuest: ... denotes formulae omitted.)1 IntroductionOften seen as a reincarnation of Decision Sup-port Systems [1] and sometimes referred as Business Intelligence and Analytics [2], Busi-ness intelligence (BI) is a broad category of applications, technologies, and processes for gathering, storing, accessing, and analyzing data to help business users make better deci-sions [3]. Figure 1 displays a classical BI ar-chitecture [4].Common business intelligence related tasks are:* data storage* data extraction-transformation-load from various sources in a different for-mats, more or less structured, to the stor-age layer* data processing* information integration* visualization* exploratory analysis* data mining/data science etc.Slightly outdated, the schema in figure 1 is still valid in suggesting the vast array of tech-nologies, processes and tools gathered (or re-branded) within BI umbrella. Chen et al [Chen 2012] identified three generations of BI and Analytics (BI&A) systems whore core tech-nologies have been:* data management and warehousing [5] [6]* text and web analytics for unstructured web contents [7]* mobile technologies [8].Implementation of BI platforms requires vast quantity of organizational resources. Some of the most important current BI solutions are shown in figure 2 [9]. As with Enterprise Re-source Planning applications, BI systems im-plementation requires extensive organiza-tional changes and business expertise and sometimes it requires full vendor participa-tion.Apart from impressive costs, BI platforms have the drawback of keeping captive the cus-tomer. Every organizational change and also new or updated external data source and ser-vice must be negotiated with BI platform pro-vider, which usually attracts new costs and also delays.In this paper we scrutinize two languages, SQL and R, involved not only in BI applica-tion development but especially in the de-mocratization of BI as they allow various types of data professionals and users to access and process vast quantity of data in an inter-active, ad-hoc, way. Using two reliable sources, their role and popularity in current BI market will be outlined, taking into account job demand and a survey concerning BI tools and languages usage. Next the range of BI ac-tivities that can be supported by each SQL and R will be presented. The main section will compare SQL and R features syntax for the most common data processing/reporting prob-lems, particularly important for BI users.2 Languages and Tools for Business Intel-ligenceThere is a vast array of tools, languages and technologies covering large extents of BI tasks. Some of them target regular users who are unable to write code and scripts in any pro-gramming language. Others are BI application developer's toolbox. But there some technol-ogies that serve both users and developers in data processing, integration, visualization and analysis. Comparison of BI tools and lan-guages is also problematic because they can be available as programming languages, de-velopment environments, ecosystems or inte-grated platforms.In evaluating the popularity of Business Intel-ligence languages and tools, we gather infor-mation from two reliable sources. Search en-gine www.indeed.com provides data about job trends. Figure 3 compares job demand in 2012-2016 interval for some of the most im-portant data processing and analysis lan-guages [10].SQL and R share most of the job postings. In 2012 SQL was by far the most demanded data language. Its share decreased slightly and seems to have stabilized since the end of 2014. R grew spectacularly in 2012-2014 interval, overpass SQL in 2014 for a brief period, and then fell back. Since 2014 it has fluctuated around 2% share. After SQL and R, the next popular is Python followed by SAS, SPSS, Stata and Julia. Currently there is still a visible lag between SQL-R group and the rest of the languages/tools, although Python seems to in-crease steadily and might catch up with the leading group. …

Pattern search algorithms, such as diamond search, hexagonal search and their variations, have been widely adopted by the block matching motion estimations in the modern video encoding systems. Recently we propose a weighting function (WF) to model the number of search points of a pattern search. Yet, WF fails to properly describe the behavior of the genetic pattern search algorithms due to some over-simplifications in their models. Therefore, we propose a refined weighting function (RWF) to more accurately describe both genetic and non-genetic pattern searches. In addition, we propose a new search algorithm, namely, the momentum directed genetic rhombus pattern search (MD-GRPS). It can accelerate the previous genetic rhombus pattern search by 8% on the average and this concept can be applied to the other genetic pattern searches.

In block motion estimation, search patterns with different shape or size have a very important impact on search speed and distortion performance. In this paper, we propose a novel algorithm using a hexagon-based search (HEXBS) pattern for fast block motion estimation. The proposed HEXBS algorithm may find any motion vector with fewer search points than the diamond search (DS) algorithm. The speedup gain of the HEXBS method over the DS algorithm is more striking for finding large motion vectors. Experimental results substantially justify the fastest performance of the HEXBS algorithm compared with several other popular fast algorithms.

In block motion estimation, search patterns with different shapes or sizes and the center-biased characteristics of motion-vector distribution have a large impact on the searching speed and quality of performance. We propose a novel algorithm using a cross-search pattern as the initial step and large/small diamond search (DS) patterns as the subsequent steps for fast block motion estimation. The initial cross-search pattern is designed to fit the cross-center-biased motion vector distribution characteristics of the real-world sequences by evaluating the nine relatively higher probable candidates located horizontally and vertically at the center of the search grid. The proposed cross-diamond search (CDS) algorithm employs the halfway-stop technique and finds small motion vectors with fewer search points than the DS algorithm while maintaining similar or even better search quality. The improvement of CDS over DS can be up to a 40% gain on speedup. Experimental results show that the CDS is much more robust, and provides faster searching speed and smaller distortions than other popular fast block-matching algorithms.

The block matching motion estimation is a very time consuming part in video compression standard. In this paper, we propose anew fast motion estimation algorithm, which improves on the UMHexagonS search algorithm. The multi-hexagon-grid search pattern is replaced by a quadrant-based multi-dodecagon grid search (QBMDD) pattern in order to reduce the computational complexity and effectively predict the optimal motion vectors. The proposed algorithm can find a motion vector with fewer search points than the UMHexagonS algorithm. The simulation experimentation results show that the proposed algorithm has a better performance compared with the UMHexagonS algorithm and it reduces the number of search points and maintains similar peak signal noise ratio (PSNR) values, without loss of its coding accuracy.

Mastering Rust helps the reader master the powerful Rust programming language for creating stable and versatile applications and projects. Rust is a dependable and robust programming language that was created with today’s needs in mind, which is something that several other scripting languages lack. Rust was developed to provide high functions comparable to those of C and C++, and with a focus on code integrity, which is, arguably, lacking in languages such as C. Rust is a dynamically typed language that emphasizes performance and reliability, particularly in parallelism and storage organization. Rust allows you to store data on the tower or the shedload, and it recognizes the importance of performance optimization. It permits even more effective memory usage as well as faster memory management than most other programming languages in its league. Make no mistake about it – Rust is a programming language with a strong learning curve, and is considered complicated by even the most experienced of developers. The rewards for learning Rust are aplenty, but the learning process itself requires a good deal of determination and hard work. Nonetheless, Rust aims to provide a secure, concurrent, and practical systems language in ways that other programming languages do not, and this is primarily why Rust is often the preferred choice for building complex and highly stable apps. Rust boasts of advantages over many other programming languages in terms of expressiveness, speed, sound design, and memory storage. Though the language is new and constantly changing with time, there is an excellent opportunity in this field for future employment. That said, to learn the reliable language that is Rust, you need to have an equally reliable companion guide in your hands, and this is where Mastering Rust comes in. With Mastering Rust, learning Rust programming language becomes a charm, and will undoubtedly help readers advance their careers. The Mastering Computer Science series is edited by Sufyan bin Uzayr, a writer and educator with more than a decade of experience in the computing field.

Central Texas College has developed a post secondary curriculum in data processing in conjunction with the United States Office of Education. The program has been developed around the career education guidelines established by the United States Office of Education. The following list of program advantages will be discussed in some detail at the June meeting:1. A complete unit of learning has been provided for the student in his first year and in his second year. At the end of his first year he will have received useful skills that are saleable in the market place. During the first year he will have had a balance of data processing courses, mathematics, business practices and effective communications. These subjects, combined with the learning of a basic programming language and systems analysis, will qualify him for many of the collateral jobs that exist in a data processing environment. He will have learned some advanced programming languages. He will have had applications courses. He will have learned some of the internal workings of the computers and programming. He will have been exposed to data management systems and transmission techniques providing him with an insight into the future of data processing. He will have had an elective during his last semester that could be an industry co-op program.2. The curriculum is flexible enough so that the student will be able to change his educational objectives to a four year program without extensive loss of credit.3. Through the new organization of courses, certain social and business objectives have been met as well as those of data processing. At specific points during education, well rounded educational objectives have been met.4. A balance of traditional courses and special computer oriented courses exist between his two years of education. He will receive five data processing courses his first year and five data processing courses his second year, plus his elective co-op program with industry.5. A balance of programming languages has been provided the student for his first and second year education. He will learn two programming languages his first, BASIC AND COBOL, and two programming languages his second year, FORTRAN and ASSEMBLY.6. The curriculum is designed to develop people to become working members of society. In addition to data processing capabilities, communications skills and social awareness development courses have been provided.7. Sufficient math has been provided in the curriculum to allow the student to advance his own studies of data processing after leaving school.8. Considerable applications experience has been gained in both the educational and working environments.

Data structure and software engineering is an integral part of computer science, which, as a whole, is the study of the theoretical foundations of information and computation and of practical techniques for their implementation and application in computer systems. This new book presents new approaches and methods to knowledge sharing, brain mapping, data integration, data storage, managing an organizations business process and domain data, new software and hardware testing methods, and a game development framework used as a learning aid in a software engineering at the university level. The book also features a review of social software engineering metrics, methods for processing business information, and using Pegasys to create and manage sequence analysis workflows in biology.Selected Contents: An Architecture to Support Learning, Awareness, and Transparency in Social Software Engineering; Comprehending Software Architecture Using a Unified Single-View Visualization; Determination of Neural Fiber Connections Based on Data Structure Algorithm; A Preliminary Analysis of Software Engineering Metricsbased Criteria for the Evaluation of Learning Objects Reusability; Extending Conceptual Schemas with Business Process Information; Software Test Automation in Practice: Empirical Observations; A Strategy for Automatic Quality Signing and Verification Processes for Hardware and Software Testing; A Tester-Assisted Methodology for Test Redundancy Detection; Automatic Generation of Web Applications from Visual High-Level Functional Web Components; Challenges and Improvements in Distributed Software Development: A Systematic Review; Vertical Mining of Frequent Patterns from Uncertain Data; An Open-Source Representation for 2-DE-Centric Proteomics and Support Infrastructure for Data Storage and Analysis; Pegasys: Software for Executing and Integrating Analyses of Biological Sequences; An Application of a Game Development Framework in Higher Education; Index

A comparative analysis for improving the efficiency of 100MW Delta IV Ughelli gas turbine power plant is performed. The study used non-dominated sorting genetic and pattern search algorithms to minimize the objective function by optimally adjusting the operating parameters (decision variables). The adjusted operating variables were compressor inlet temperature (T1), compressor pressure ratio (rp), compressor isentropic efficiency (ɳic), turbine isentropic efficiency (ɳit), turbine exhaust temperature (T4) and air mass flow rate (ma), fuel mass flow rate (mf) and fuel supply temperature (Tf). The ambient temperature and pressure were held constant at 304K and 1.01325bar respectively because of location limitation. The optimization code was written in Matlab programming language. The decision variables (constraints) were obtained randomly within the admission range. The GA and PS optimal values of the decision variables were obtained by minimizing the objective function. The determined GA and PS optimum operating variables have the same values which were compressor pressure ratio (rn) = 9.76, compressor isentropic efficiency (ɳic) = 86.40%, turbine isentropic efficiency (ɳit) = 89.12%, combustion chamber outlet temperature (T3) = 1481.8K, air mass flow rate = 530kg/s, fuel mass flow rate = 7.00kg/s. The total exergy destruction cost rate ( D) for PS and GAvaries by +0.00004% and the total investment cost rate for PS and GAvaries by +0.00038%. The results show that there is slight increase in total exergy destruction cost rate and total capital investment cost rate in PS optimum when compared to GA optimum. This shows that GA is better than PS as an optimization algorithm.