Pseudo-code Of Algorithm Research Articles

Arithmetic modeling of k-ary n-cubes and toroidal k-ary grids

The use of toroidal topologies offers many advantages in the computing field when it comes to both pattern spotting and path finding strategies. The former is covered by de Bruijn shapes, which permit to uniquely locate a single pattern throughout the shape. However, the latter is mainly carried out by k-ary n-cubes, which label node identifiers in a sequential order according to rows, columns, layers, and so on. This scheme facilitates the movement among nodes by just applying arithmetic operations, such as integer divisions and arithmetic modulo n. On the othe hand, toroidal k-ary grids are an alternative available in some specific cases, where determined patterns appear in all dimensions of each node, thus allowing to use those patterns to dictate paths to move among nodes. In this paper, the arithmetic bases of both path finding strategies have been presented and some pseudocode algorithms have been designed.

Assisting Postgraduate Students To Synthesise Qualitative Propositions To Develop A Conceptual Framework

With the advent of the Fourth/Fifth Industrial Revolution (4/5IR), the interplay between using software for automated text analysis and the human researcher, for example, a postgraduate student, is becoming increasingly challenging. Having sourced the relevant publications to be used in the development of a literature review chapter, a student is faced with the task of analysing the said publications and extracting the sections relevant to their research. These analyses may arguably be automated through sophisticated software. Yet, to warrant a student's name on the title page of a dissertation or thesis, the student should do a substantial amount of the work manually in terms of surveying the scholarly literature as well as synthesising the collected content into a coherent piece of work. Depending on the subject area, it may be customary to develop a conceptual framework synthesised from the themes identified in the literature survey. As the body of knowledge in each subject increases, the development of a framework becomes hard. To this end, we present a methodology of proposition development that may guide a student to synthesise a framework from the important aspects in a literature review chapter. Our approach focuses on the development of four sets of propositions. We apply our approach to a small piece of text and formalise the approach in the form of a pseudo-code algorithm. Future work will involve the refinement of our technique.

Evolutionary Computation of the Generalized Hesitant Fuzzy Envelopment Analysis and Its Application in the Contractor Selection of Green Building Project

The evaluation presentation and numerical weight are two key factors that can affect final results in a decision-making process. In this article, we introduce the hesitant fuzzy set and the envelopment rate calculation to address these two issues respectively. Unlike the previous decision-making approaches, the newly proposed methods in this article focus on mutual influence relationships of all alternatives and make decisions by achieving the Pareto optimality. To do this, we first define the mutual hesitant fuzzy envelopment rate (MHFER) and then propose the generalized hesitant fuzzy envelopment analysis method and its two desired properties. Based on this, we develop an evolutionary computation by introducing the ideas of cooperative equilibrium and achieving the Pareto optimality of the whole decision-making process from a global perspective. After that, we further improve the evolutionary computation by fusing some inequality constraints to make the calculated MHFERs distinguishable. Then, the modeling steps and the pseudocode algorithm of the evolutionary computation are provided for an understanding of the proposed methods. Also, the computational convergence is proven, which shows the feasibility and effectiveness of the above methods. Finally, we present an example to select a suitable contractor for a green building project and it fully demonstrates the application of the proposed models. Moreover, the comparison calculations and further analysis are also provided.

Evasive actions to prevent pedestrian collisions in varying space/time contexts in diverse urban and non-urban areas

This study aims to identify driver-safe evasive actions associated with pedestrian crash risk in diverse urban and non-urban areas. The research focuses on the integration of quantitative methods and granular naturalistic data to examine the impacts of different driving contexts on transportation system performance, safety, and reliability. The data is derived from real-life driving encounters between pedestrians and drivers in various settings, including urban areas (UAs), suburban areas (SUAs), marked crossing areas (MCAs), and unmarked crossing areas (UMCAs). By determining critical thresholds of spatial/temporal proximity-based safety surrogate techniques, vehicle–pedestrian conflicts are clustered through a K-means algorithm into different risk levels based on drivers' evasive actions in different areas. The results of the data analysis indicate that changing lanes is the key evasive action employed by drivers to avoid pedestrian crashes in SUAs and UMCAs, while in UAs and MCAs, drivers rely on soft evasive actions, such as deceleration. Moreover, critical thresholds for several Safety Surrogate Measures (SSMs) reveal similar conflict patterns between SUAs and UMCAs, as well as between UAs and MCAs. Furthermore, this study develops and delivers a pseudo-code algorithm that utilizes the critical thresholds of SSMs to provide tangible guidance on the appropriate evasive actions for drivers in different space/time contexts, aiming to prevent collisions with pedestrians. The developed research methodology as well as the outputs of this study could be potentially useful for the development of a driver support and assistance system in the future.

Multi-objective optimization and improvement of multi-energy combined cooling, heating and power system based on system simplification

The multi-objective optimization of combined cooling, heating, and power (CCHP) systems typically focuses on optimizing objective functions that consider energy, environmental, and economic factors. However, the implementation of optimization solutions, which is related to decision variables, is often overlooked. This paper proposes a novel improved optimization method based on system simplification by reorganizing, re-optimizing and re-selecting the initial optimized population to improve decision variables. And created algorithm pseudocode. The improved algorithm is adopted to perform multi-objective optimization on the established multi-energy CCHP system. The hypervolume of the improved/original algorithm is 0.9770/0.9887, with only a 1.18% difference. The optimization results of the improved algorithm and the original algorithm are equal in the minimum values of the net present value (NPV) and fossil energy consumption (FEC), which are 2.26 × 107$ and 1.21 × 105GJ, respectively. There is only 1.4% difference in the carbon dioxide emissions (CDE). The number of equipment types corresponding to the decision variables of the improved algorithm is reduced from 8 to 4, significantly simplifying the systems. The proposed improved optimization method can harness the local energy-saving potential and comprehensively analyze optimization solutions in terms of energy, economy, and environment. It also obtains simplified systems to promote the implementation of the project.

Data Mining Oriented Automatic Scientific Documents Summarization

The scientific research process usually begins with an examination of the advanced, which may include voluminous publications. Summarizing scientific articles can assist researchers in their research by speeding up the research process. The summary of scientific articles differs from the abstract text in general due to its specific structure and the inclusion of cited sentences. Most of the important information in scientific articles is presented in tables, statistics, and algorithm pseudocode. These features, however, rarely appear in the standard text. Therefore, a number of methods that consider the value of the structure of a scientific article have been suggested that improve the standard of the produced summary. This paper makes use of clustering algorithms to handle CL- SciSumm 2020 and longsumm 2020 tasks for summarization of scientific documents. There are three well-known clustering algorithms that are employed to tackle CL- SciSumm 2020 and LongSumm 2020 tasks, and several sentences recording functions, with textual deduction, are used to retrieved phrases from each cluster to generate summary.

On replacing standard system error messages for relational database constraints with context aware natural language ones

The goal of this paper is to provide a rigorous methodology for enhancing VBA software application users’ experience when faced with attempts to violate the underlying SQL Server database constraints. The original contribution is a pseudo-code algorithm for assisting developers in this process. We exemplify the results of using it with a full code example for a class taken from a genealogy database software application designed and developed using this methodology. Consequently, it replaces all context-independent and developer jargon standard system error messages with context aware and natural language ones. Moreover, it also synchronizes combo-box instances after each update or delete. We also show that the proposed algorithm works fine not only for other relational database management systems, but even with NoSQL platform backends, and that the modifications needed to adapt it to other similar SQL embedding frontend platforms are minimal. This algorithm main merit is that it may serve as the basis for developing a tool for performing this important task through automatic code generation.

Computational Mathematics: Solving Dual Fully Fuzzy Nonlinear Matrix Equations Numerically using Broyden’s Method

Fuzzy numbers have many applications in various mathematical models in both linear and nonlinear forms. In the form of a nonlinear system, fuzzy nonlinear equations can be constructed in the form of matrix equations. Unfortunately, the matrix equations used to solve the problem of dual fully fuzzy nonlinear systems are still relatively few found in the publication of research results. This article attempts to solve a dual fully fuzzy nonlinear equation system involving triangular fuzzy numbers using Broyden’s method. This article provides the pseudocode algorithm and the implementation of the algorithm into the MATLAB program for the iteration process to be carried out quickly and easily. The performance of the given algorithm is the fastest in finding system solutions and provides a minimum error value.

Image Cryptography Based On A Second-Order QRT Difference Equation

The use of mathematical concepts of mapping in cryptography provides advantages in securing text or image data. The qualitative properties of mapping can preserve data that is kept confidential. Two of the essential properties in the mapping are the reversible and the preserving area. In this article, besides constructing a linear mapping derived from a second-order QRT difference equation and examining its qualitative properties, the coding procedure is used to encrypt text and fractal images based on the two-dimensional linear maps. For the digital text and image security algorithms, we developed the pseudo code algorithm implemented in Mathematica®. The proposed encoding technique will be compared with a 2D mKdV linear map to demonstrate its efficacy.

Parallel Hough Transform based on Object Dual and Pymp Library

Geometric shape detection in an image is a classical problem that leads to many applications, in cartography to highlight roads in a noisy image, in medical imaging to localize disease in a region and in agronomy to fight against weeds with pesticides. The Hough Transform method contributes effectively to the recognition of digital objects, as straight lines, circles and arbitrary objects. This paper deals with the theoretical comparisons of object dual based on the definition of Standard Hough Transform. It also focuses on parallelism of Hough Transform. A generic pseudo-code algorithm, using the Openmp library for the parallel computing of object dual is proposed in order to improve the execution time. In simulation, a triangular mesh superimposed on the image is implemented with the pymp library in python, in considering threads as inputs to read the image and to update the accumulator. The parallel computing presents reduction of the execution time accordingly to the rate of lit pixels in each virtual object and the number of threads. In perspectives, it will contribute to strenghen the developement of a toolkit for the Hough Transform method.

Applying Interactive Technology to Construct a Popular-Science Teaching Aid System for Protecting Cetaceans along Sea Coasts

Wang, C.-M. and Chen, I-T., 2022. Applying interactive technology to construct a popular-science teaching aid system for protecting cetaceans along sea coasts. Journal of Coastal Research, 38(2), 389–413. Coconut Creek (Florida), ISSN 0749-0208. Cetaceans, such as whales and dolphins, are often found stranded at sea coasts. Teaching the public to rescue such endangered animals in emergency cases is important for educational learning of environmental conservation. Based on the interactive technology, a teaching aid system for popular-science cetacean rescue education is proposed. After a review of related literature, theories of interactive design, tangible interfacing, and science communication are adopted to derive the principles for designing the system. Accordingly, a dolphin model and a series of graphics were designed to construct the teaching aid scheme of the system in the form of a five-level game with a smart phone or pad as the tangible interface. Implemented by a pseudo-code algorithm, the game-play process is designed according to a rule of “Three Musts and Four Nos” advocated by a cetacean conservation society, including the five operation steps of rescue requesting, cetacean identification, holding upright, moisturizing, and recording. The system was exhibited in a public space to invite visitors to play the game. A questionnaire was conducted to collect 124 users' opinions, which were then analyzed, using the software packages of SPSS and AMOS, to evaluate the effectiveness of the proposed system with the aim of cetacean rescue education, leading to the following findings: (1) the interactive popular-science teaching aid provided by the proposed system helps spread cetacean conservation concepts; (2) the interactive game-play process provided by the system teaches correct scientific knowledge; (3) the teaching aid of the system in the form of interactive game holds users' attention; (4) the users enjoyed operating the interactive teaching aid system and wanted to know more about the issue of cetacean rescues; and (5) the interactive popular-science teaching content cannot build some of the users’ confidence to face real cetacean rescue situations.

Efficient, High-Fidelity Modeling and Simulation of Global Navigation Satellite System Constellations

This paper presents a method for modeling and simulation of Global Navigation Satellite System (GNSS) constellations by the use of Chebyshev polynomials fit to publicly available precision data. The Global Positioning System (GPS) is used to demonstrate the method, but the method applies to all GNSS with precise ephemeris data including Galileo and GLONASS. The method facilitates highly accurate satellite orbit and clock modeling, including relativistic effects, with mean fit differences of the order in position, in velocity, and microseconds in clock offset. The method also improves simulation run time by using a fast technique for evaluating the Chebyshev polynomials. Runtime comparisons demonstrate the polynomial method reduces runtime by up to 72% of more traditional methods. The speed of the method makes it well suited for practical, accurate Monte Carlo simulation techniques. The method can be used in simulations for the verification and validation of GNSS receivers embedded in autonomous aerospace navigation systems, for uncertainty analysis, and for other purposes. Details for validating the precision data are given. Pseudocode algorithms are provided for fitting and evaluating Chebyshev polynomials. Also provided are high-level concepts of one approach for integrating the method into larger, multisystem aerospace simulations, including the effects of signal propagation delay and Earth blockage.

Applying Multidimensional Geometry to Basic Data Centre Designs

Fog computing deployments are catching up by the day due to their advantages on latency and bandwidth compared to cloud implementations. Furthermore, the number of required hosts is usually far smaller, and so are the amount of switches needed to make the interconnections among them. In this paper, an approach based on multidimensional geometry is proposed for building up basic switching architectures for Data Centres, in a way that the most common convex regular N-polytopes are first introduced, where N is treated in an incremental manner in order to reach a generic high-dimensional N, and in turn, those resulting shapes are associated with their corresponding switching topologies. This way, N-simplex is related to a full mesh pattern, N-orthoplex is linked to a quasi full mesh structure and N-hypercube is referred to as a certain type of partial mesh layout. In each of those three contexts, a model is to be built up, where switches are first identified, afterwards, their downlink ports leading to the end hosts are exposed, along with those host identifiers, as well as their uplink ports leading to their neighboring switches, and eventually, a pseudocode algorithm is designed, exposing how a packet coming in from any given port of a switch is to be forwarded through the proper outgoing port on its way to the destination host by using the appropriate arithmetic expressions in each particular case. Therefore, all those algorithmic models represent how their corresponding switches may work when dealing with user data traffic within a Data Centre, guiding it towards its destination.

Damaged area assessment of cultivated agricultural lands affected by cyclone bulbul in coastal region of Bangladesh using Landsat 8 OLI and TIRS datasets

Tropical cyclones cause tremendous damage to agricultural lands in global south countries almost every year. It is significantly important to identify the damage assessment for rice growing agricultural land areas in the south and south-east Asian countries. Therefore, the objective of this research was to develop a new damaged area assessment (DAA) method to measure the area of each damage type class (DTC) for cyclone-prone agricultural lands using Landsat 8 OLI and TIRS datasets. The weighted overlay method was incorporated with a pix-code sum (plus+) operation based on conditional pseudocode algorithm using NDVI, SAVI and SMI change detection (CD) and change type classes (CTC). The assessment of the damaged area classes was reported as (1) Not damaged (7.71 km2, 2.5%); (2) slightly damaged (32.96 km2, 10.66%); (3) moderately damaged (79 km2, 5.56%); (4) very damaged (131.56 km2, 42.56%); and (5) extremely damaged (57.85 km2, 18.72%) at cyclone Bulbul affected Kalapara sub-district in the coastal region of Bangladesh. This cyclone-prone hotspot was adjacent with the Bay of Bengal and total 420 ground reference points were selected by their farmers’ location to validate our research. In the study, it was randomly observed that totals of 4 (0.95%); 13 (3.10%); 52 (12.38%); 205 (48.81%); and 146 ground reference points (34.76%) were accurately distributed into the said damaged type classes (1–5) respectively. The DAA method with DTCs could be helpful for researchers creating new yield loss assessment policies to help affected farming communities to prepare an effective recovery plan for their needs fulfilment in the cyclone-prone countries.

Storing Hypergraph-Based Data Models in Non-Hypergraph Data Storage and Applications for Information Systems

Data structures and especially the relationship among the data entities have changed in the last couple of years. The network-like graph representations of data-model are becoming more and more common nowadays, since they are more suitable to depict these, than the well-established relational data-model. The graphs can describe large and complex networks — like social networks — but also capable of storing rich information about complex data. This was mostly of relational data-model trait before. This also can be achieved with the use of the knowledge representation tool called “hypergraphs”. To utilize the possibilities of this model, we need a practical way to store and process hypergraphs. In this paper, we propose a way by which we can store hypergraphs model in the SAP HANA in-memory database system which has a “Graph Core” engine besides the relational data model. Graph Core has many graph algorithms by default however it is not capable to store or to work with hypergraphs neither are any of these algorithms specifically tailored for hypergraphs either. Hence in this paper, besides the case study of the two information systems, we also propose pseudo-code level algorithms to accommodate hypergraph semantics to process our IS model.

Numerical-Computational Model for Nonlinear Analysis of Frames with Semirigid Connection

A numerical-computational model for static analysis of plane frames with semirigid connections and geometric nonlinear behavior is presented. The set of nonlinear equations governing the structural system is solved by the Potra–Pták method in an incremental procedure, with order of cubic convergence, combined with the linear arc-length path-following technique. The algorithm pseudo-code is presented, and the finite element corotational method is used for the discretization of the structures. The equilibrium paths with load and displacement limit points are obtained. The semirigidity is simulated by a linear connection element of null length, which considers the axial, tangential, and rotational stiffness. Nonlinear analyses of 2D frame structures are carried out with the free Scilab program. The results show that the Potra–Pták procedure can decrease the number of iterations and the computing time in comparison with the standard and modified Newton–Raphson iterative schemes. Also, the simulations show that the connection flexibility has a strong influence on the nonlinear behavior and stability of the structural systems.

Facility Location Problems: Models, Techniques, and Applications in Waste Management

This paper presents a brief description of some existing models of facility location problems (FLPs) in solid waste management. The study provides salient information on commonly used distance functions in location models along with their corresponding mathematical formulation. Some of the optimization techniques that have been applied to location problems are also presented along with an appropriate pseudocode algorithm for their implementation. Concerning the models and solution techniques, the survey concludes by summarizing some recent studies on the applications of FLPs to waste collection and disposal. It is expected that this paper will contribute in no small measure to an integrated solid waste management system with specific emphasis on issues associated with waste collection, thereby boosting the drive for effective and efficient waste collection systems. The content will also provide early career researchers with some necessary starting information required to formulate and solve problems relating to FLP.

APLIKASI BAHASA C++ DAN PHP UNTUK MENENTUKAN UKURAN SAMPEL PADA METODE STRATIFIED RANDOM SAMPLING

The accuracy of survey results depends on sample size. So far, in determining the sample size of the stratified random sampling method, researchers still use manual calculations. Because of that, this research aims to create a sample size determination program of the stratified random sampling method using C++ and PHP programming languages. This research begins with the study of literacy, creating flowcharts and pseudocode algorithms, writing program syntax, and implementing data on the number of civil servants in each UPK in Banyumas Regency. By entering a 95% confidence level, the error limit that can be tolerated is 5, and the strata cost of each is 1, the minimum sample size is 60 with the 1st and 2nd strata sample sizes is 45 and 15. The program is expected to help researchers to determine sample size more easily. So far, the program also minimizes errors in calculations because a warning will appear when an error occurs.

SDOWN: A novel algorithm for better Quality of Service and Experience in Software Defined Optical Wireless Network

There is manifold increase in global Internet traffic with the advancement of time and provision of ubiquitous Internet access efficiently in terms of Quality of Service and Experience (QoS and QoE) is a serious challenge for the service provider with existing conventional network technology. With Software Defined Optical Wireless Networking (SDOWN) technology world seems to move toward the Next Generation Network (NGN) which exposes itself to resolve many limitations of a conventional/traditional manually operated optical-wireless network via software-assisted and efficient network control through centralized controller. In this research paper, a layered and logical architecture of the proposed SDOWN model and mathematical analysis are presented. The paper also elucidates the implementation of SDOWN model with and without SDOWN Controller with the help of block and state diagrams. Besides, in this model OpenFlow (OF) governed six (06) MATLAB components has been designed such as SDOWN Controller, Ethernet switch-1 & 2, Optical switch-1 & 2, and Wi-Fi access point with suitable interfaces. Software Defined Networking (SDN) Controller interfacing with optical-wireless network i.e. SDOWN and its performance analysis have been carried out with the state-of-the-art (SotA), where pseudo codes of algorithms and flowcharts for the same are duly explained, which provides Unified Control Plane (UCP) via SDOWN Controller for better QoS and QoE. Simulation results and discussions with suitable Figures have also been presented.

Fourier-Based Shape Servoing: A New Feedback Method to Actively Deform Soft Objects into Desired 2-D Image Contours

This paper addresses the design of a vision-based method to automatically deform soft objects into desired two-dimensional shapes with robot manipulators. The method presents an innovative feedback representation of the object's shape (based on a truncated Fourier series) and effectively exploits it to guide the soft object manipulation task. A new model calibration scheme that iteratively approximates a local deformation model from vision and motion sensory feedback is derived; this estimation method allows us to manipulate objects with unknown deformation properties. Pseudocode algorithms are presented to facilitate the implementation of the controller. Numerical simulations and experiments are reported to validate this new approach.