Basic Version Research Articles

Research Design with Weighted Lotteries in School Choice

Centralized admissions are an integral part of parental school choice programs. Most districts use a version of the deferred acceptance algorithm to assign applicants to schools. Centralized admissions produce data with quasi-experimental variation in student assignment that is integral in program evaluation. Recent developments in research design consider the basic version of the deferred acceptance algorithm. However, most districts adapt advanced versions of the deferred acceptance algorithm to implement their diversity policy in admissions, such as favoring applicants from disadvantaged backgrounds in lottery tie-breaking. We develop research design for data from the deferred acceptance algorithm with weighted lotteries.

Trustworthy semi‐supervised anomaly detection for online‐to‐offline logistics business in merchant identification

AbstractThe rise of online‐to‐offline (O2O) e‐commerce business has brought tremendous opportunities to the logistics industry. In the online‐to‐offline logistics business, it is essential to detect anomaly merchants with fraudulent shipping behaviours, such as sending other merchants' packages for profit with their low discounts. This can help reduce the financial losses of platforms and ensure a healthy environment. Existing anomaly detection studies have mainly focused on online fraud behaviour detection, such as fraudulent purchase and comment behaviours in e‐commerce. However, these methods are not suitable for anomaly merchant detection in logistics due to the more complex online and offline operation of package‐sending behaviours and the interpretable requirements of offline deployment in logistics. MultiDet, a semi‐supervised multi‐view fusion‐based Anomaly Detection framework in online‐to‐offline logistics is proposed, which consists of a basic version SemiDet and an attention‐enhanced multi‐view fusion model. In SemiDet, pair‐wise data augmentation is first conducted to promote model robustness and address the challenge of limited labelled anomaly instances. Then, SemiDet calculates the anomaly scoring of each merchant with an auto‐encoder framework. Considering the multi‐relationships among logistics merchants, a multi‐view attention fusion‐based anomaly detection network is further designed to capture merchants' mutual influences and improve the anomaly merchant detection performance. A post‐hoc perturbation‐based interpretation model is designed to output the importance of different views and ensure the trustworthiness of end‐to‐end anomaly detection. The framework based on an eight‐month real‐world dataset collected from one of the largest logistics platforms in China is evaluated, involving 6128 merchants and 16 million historical order consignor records in Beijing. Experimental results show that the proposed model outperforms other baselines in both AUC‐ROC and AUC‐PR metrics.

The priming of stimulus-elicited involuntary mental imagery

Percepts, urges, and even high-level cognitions often enter the conscious field involuntarily. The Reflexive Imagery Task (RIT) was designed to investigate experimentally the nature of such entry into consciousness. In the most basic version of the task, participants are instructed not to subvocalize the names of visual objects. Involuntary subvocalizations arise on the majority of the trials. Can these effects be influenced by priming? In our experiment, participants were exposed to an auditory prime 300 ms before being presented with the RIT stimuli. For example, participants heard the word “FOOD” before seeing two RIT stimuli (e.g., line drawings of BANANA and CAT, with the former being the target of the prime). The short span between prime and target allowed us to assess whether the RIT effect is strategic or automatic. Before each trial, participants were instructed to disregard what they hear, and not to think of the name of any of the objects. On an average of 83% of the trials, the participants thought (involuntarily) of the name of the object associated with the prime. This is the first study to use a priming technique within the context of the RIT. The theoretical implications of these involuntary effects are discussed.

Measuring the Reliability of a Gamified Stroop Task: Quantitative Experiment.

Few gamified cognitive tasks are subjected to rigorous examination of psychometric properties, despite their use in experimental and clinical settings. Even small manipulations to cognitive tasks require extensive research to understand their effects. This study aims to investigate how game elements can affect the reliability of scores on a Stroop task. We specifically investigated performance consistency within and across sessions. We created 2 versions of the Stroop task, with and without game elements, and then tested each task with participants at 2 time points. The gamified task used points and feedback as game elements. In this paper, we report on the reliability of the gamified Stroop task in terms of internal consistency and test-retest reliability, compared with the control task. We used a permutation approach to evaluate internal consistency. For test-retest reliability, we calculated the Pearson correlation and intraclass correlation coefficients between each time point. We also descriptively compared the reliability of scores on a trial-by-trial basis, considering the different trial types. At the first time point, the Stroop effect was reduced in the game condition, indicating an increase in performance. Participants in the game condition had faster reaction times (P=.005) and lower error rates (P=.04) than those in the basic task condition. Furthermore, the game condition led to higher measures of internal consistency at both time points for reaction times and error rates, which indicates a more consistent response pattern. For reaction time in the basic task condition, at time 1, rSpearman-Brown=0.78, 95% CI 0.64-0.89. At time 2, rSpearman-Brown=0.64, 95% CI 0.40-0.81. For reaction time, in the game condition, at time 1, rSpearman-Brown=0.83, 95% CI 0.71-0.91. At time 2, rSpearman-Brown=0.76, 95% CI 0.60-0.88. Similarly, for error rates in the basic task condition, at time 1, rSpearman-Brown=0.76, 95% CI 0.62-0.87. At time 2, rSpearman-Brown=0.74, 95% CI 0.58-0.86. For error rates in the game condition, at time 1, rSpearman-Brown=0.76, 95% CI 0.62-0.87. At time 2, rSpearman-Brown=0.74, 95% CI 0.58-0.86. Test-retest reliability analysis revealed a distinctive performance pattern depending on the trial type, which may be reflective of motivational differences between task versions. In short, especially in the incongruent trials where cognitive conflict occurs, performance in the game condition reaches peak consistency after 100 trials, whereas performance consistency drops after 50 trials for the basic version and only catches up to the game after 250 trials. Even subtle gamification can impact task performance albeit not only in terms of a direct difference in performance between conditions. People playing the game reach peak performance sooner, and their performance is more consistent within and across sessions. We advocate for a closer examination of the impact of game elements on performance.

Not yet another BPM lifecycle: A synthesis of existing approaches using BPMN

ContextBusiness Process Management (BPM) is considered an important management approach that encompasses a set of methods for managing the business processes of an organization. To maximize the benefits of BPM, scholars have conceptualized its steps in schematic diagrams with interrelated phases called BPM lifecycles. As this approach has been established, the phenomenon of perpetual proposition of BPM lifecycles has been observed in relevant literature. This practice obscures what should be relatively straightforward: a consensus among researchers and practitioners regarding the steps that a business process should flow through during its lifecycle. ObjectiveThe aim of this work is to investigate the existing BPM lifecycle models proposed in literature, identify convergences and variations in these models, analyze their core components and locate common patterns that will enable the synthesis of a BPM lifecycle that is conceptualized with Business Process Model and Notation (BPMN), the community de-facto business process modeling notation. MethodTo formalize the research problem and develop the design of a solution, the Design Science Research Process (DSRP) model was adopted. To investigate the perpetual proposition of BPM lifecycles in literature, the authors conducted a Systematic Literature Review (SLR). On whether recurring patterns can emerge from the BPM lifecycles, a normalization process was introduced to homogenize the data and four metrics were used to evaluate the results. The emerging patterns were assembled into a graph that formed the basis for proposing a synthetic BPM lifecycle. ResultsThe outcome of the paper is three-fold: First, the identification of four major inefficiencies of existing BPM lifecycles, namely varying granularity, inconsistent nomenclature, subjective polysemy, and lack of formal conceptualization approaches. Also, a standardized definition of the inclusive steps that exist in the lifecycles by clustering the existing ones in a conceptually systematic manner. Finally, a synthetic BPM lifecycle is conceptualized that systematizes the existing concepts and their interrelations based on a formalized BPMN model in two levels of granularity: a basic version that illustrates the functional and control-flow aspects of the BPM lifecycle and an enhanced version incorporating additionally the resource and data perspectives. ConclusionThis paper proposes a BPMN-based conceptualization of the BPM lifecycle that can facilitate the management of business processes by providing enhanced clarity, improved resource management, and predefined error handling in a BPM initiative. By systematizing the control-flow, data, and resource perspective of the BPM lifecycle, stakeholders can gain a clear understanding of the sequence of steps, the interrelated data flows, and the distribution of work.

Determination of reliability for a complex technical system on the example of a mobile medical module

The article presents a proposal for a method to determine a total and partial reliability for a mobile medical module as a complex technical system. The dedicated functions of such a module are to evacuate the wounded from the battlefield (in the basic version) and to ensure the maintenance of his vital functions and the performance of necessary medical procedures (in the extended version). Work on developing the concept or advanced construction of such modules using unmanned aerial vehicles as transport drones has been carried out for several years by many countries and aviation companies, including: DARPA agency (USA) and AFIT (Poland). Even though there is no fleet of such machines in Poland yet, this comes from experience in managing aircraft in the Armed Forces RP results from the need to simultaneously secure the operation of such modules in an IT support system using algorithms and mathematical relationships in determining a total and partial reliability . Due to the structural complexity of the mobile medical module (carrier platform, drive, basic and additional avionics equipment and basic and extended medical equipment), a total and partial reliability can be determined for a simple object (in a simplified reliability version as full) or a complex system (as a total and partial reliability).

Mathematical programming for simultaneous feature selection and outlier detection under l1 norm

The goal of simultaneous feature selection and outlier detection is to determine a sparse linear regression vector by fitting a dataset possibly affected by the presence of outliers.The problem is well-known in the literature. In its basic version it covers a wide range of tasks in data analysis. Simultaneously performing feature selection and outlier detection strongly improves the application potential of regression models in more general settings, where data governance is a concern. To trigger this potential, flexible training models are needed, with more parameters under control of decision makers.The use of mathematical programming, although pertinent, is scarce in this context and mostly focusing on the least-squares setting. Instead we consider the least absolute deviation criterion, proposing two mixed-integer linear programs, one adapted from existing studies, and the other obtained from a disjunctive programming argument. We show theoretically and computationally that the disjunctive-based formulation is better in terms of both continuous relaxation quality and integer optimality convergence.We experimentally benchmark against existing methodologies from the literature. We identify the characteristics of contamination patterns, in which mathematical programming is better than state-of-the-art algorithms in combining prediction quality, sparsity and robustness against outliers. Additionally, the mathematical programming approaches allow the decision maker to directly control parameters like the number of features or outliers to tolerate, those based on least absolute deviations performing best. On real world datasets, where privacy is a concern, our approach compares well to state-of-the-art methods in terms of accuracy, being at the same time more flexible.

The Pólya-Szegő inequality for smoothing rearrangements

A basic version of the Pólya-Szegő inequality states that if Φ is a Young function, the Φ-Dirichlet energy—the integral of Φ(‖∇f‖)—of a suitable function f∈V(Rn), the class of nonnegative measurable functions on Rn that vanish at infinity, does not increase under symmetric decreasing rearrangement. This fact, along with variants that apply to polarizations and to Steiner and certain other rearrangements, has numerous applications. Very general versions of the inequality are proved that hold for all smoothing rearrangements, those that do not increase the modulus of continuity of functions. The results cover all the main classes of functions previously considered: Lipschitz functions f∈V(Rn), functions f∈W1,p(Rn)∩V(Rn) (when 1≤p<∞ and Φ(t)=tp), and functions f∈Wloc1,1(Rn)∩V(Rn). In addition, anisotropic versions of these results, in which the role of the unit ball is played by a convex body containing the origin in its interior, are established. Taken together, the results bring together all the basic versions of the Pólya-Szegő inequality previously available under a common and very general framework.

Development of a computational system to design a helical spring

AbstractSprings are the most basic mechanical elements used in transmission mechanisms. The rapid development of the computer and cellular industry has encouraged spring manufacturers to develop the industry to produce very small springs. Most computer-aided design programs for mechanical parts provide the possibility of designing these parts, as these programs include different types of decisions. All these decisions require coordinates for geometric data as well as metadata. The paper aims to develop software programs to design and analyze springs as one of the most significant mechanical elements used. This paper aims to develop a design software of a helical spring system, where this software is built using a computer program in the language of Visual Basic Version 5. When the user enters data into the system, the system will perform a series of complex calculations in the system, then provide a detailed report on all the engineering dimensions of the spring, and test its efficiency. The output of the software shows the required spring wire parameters. The software was tested with test data from the open literature, and the required wire spring parameters were obtained.

Implementing and testing a U-space system: lessons learnt

Within the framework of the European Union’s Horizon 2020 research and innovation program, one of the main goals of the Labyrinth project, which ended on May 2023, was to develop and test the Conflict Management services of a U-space-based Unmanned Traffic Management (UTM) system. The U-space ConOps provides a high-level description of the architecture, requirements and functionalities of these systems, but the implementer has a certain degree of freedom in aspects like the techniques used or some policies and procedures. The current document describes some of those implementation decisions. The prototype included, at least in a basic version, part of the services defined by the ConOps, namely e-identification, Tracking, Geo-awareness, Drone Aeronautical Information Management, Geo-fence Provision, Operation Plan Preparation/Optimization, Operation Plan Processing, Strategic and Tactical Conflict Resolution, Emergency Management, Monitoring, Traffic Information and Legal Recording. Besides, a web app interface was developed for the operator/pilot. The system was tested in simulations and real visual line of sight (VLOS) and beyond VLOS (BVLOS) flights, with both vertical take-off and landing (VTOL) and fixed-wing platforms, while assisting final users interested in incorporating drones to support their daily tasks. The three-year experience developing and testing the environment provided many lessons at different levels: functionalities, compatibility, procedures, information, usability, ground control station (GCS) integration and aircrew roles during the mission.

Interface Development of a Module for the interFoam Solver of the OpenFOAM Package

The results of a study on expanding the list of tasks solved using the graphical shell of the OpenFOAM platform by creating and connecting an additional module for the interFoam solver to the basic version of the graphical shell are presented. The relevance of the problem is formulated, the goal and the list of tasks necessary to achieve it. The features of this solver are studied and described in relation to experiments on numerical modeling of problems in continuum mechanics. The possibility of using open technologies to supplement the source code of the graphical shell with new modules covering a larger range of types of problems in continuum mechanics is analyzed. Graphic materials have been prepared that describe the structure and logic of the module being developed. The technology stack used is presented, and the results of testing the updated version of the graphical shell using the example of one of the classic problems of continuum mechanics are presented. The results of the research were summed up, the tasks completed were noted, the expected practical value of the development and possible ways for further research in this direction were indicated, the repository with the source code of the graphical shell on the GitHub service was updated.

Formulation of Energy Bars by using Sunflower Seeds

The study discusses the popularity and nutritional benefits of snack foods, with a focus on granola bars as a versatile and nutrient-dense option. The importance of energy bars for athletes and individuals with busy lifestyles is highlighted. The study aims to develop a high-protein, high-energy nutritional bar using plant sources. Oats are emphasized for their rich nutrient profile, including carbohydrates, fiber, proteins and various bioactive compounds. Dates and almonds contribute additional nutrients and health benefits. Sunflower seeds are recognized for their therapeutic benefits, while honey is for its antibacterial and nutritional properties. The energy bars, including a basic version and two variations, were analyzed for various nutritional parameters. The moisture content exhibited slight increments, measuring from 6.83±0.01, to 7.03±0.01, while the ash content showed minimal differences at 0.05±0.01. Energy content increased from 380±0.032 to 410±0.026, and protein content ranged from 9.17±0.01 to 9.19±0.01. Fat composition showed marginal variations while the fiber content was measured at 6.67±0.01, 6.77±0.01 and 6.78±0.01 grams. Ascorbic acid concentrations increased from 0.7±0.015 to 0.81±0.0026, while thiamine and riboflavin concentrations showed slight fluctuations. Sensory evaluation revealed that T2 (30% honey) scored highest in various categories, including color (8.5±0.527), taste (8.6±0.516), texture (8.2±0.788), flavor (8.5±0.707), appearance (8.5±0.527) and overall acceptability (8.6±0.516). T2 emerged as the most preferred, followed by T1 (25% honey) and T3 (35% honey).

Multidimensional Multi-Connected Fuzzy Interval-Logic Controller

The key features and the principle of operation of a multidimensional fuzzy interval-logic controller with interconnected adjustable parameters developed by the authors are considered. The scheme of interpretation of continuous physical quantities by an equivalent set of terms and the basic version of the block diagram of the regulator are presented. The main elements of the logical output block are described, including the block of production rules, which includes a predefined database of values of control actions on control objects in the form of ordinal numbers of terms of output continuous quantities. The advantages and features of setting up the mutual connections between the input and output continuous values of the regulator are considered, which is expressed in determining the functional dependencies between them. The set of parameters possessed by the terms of input continuous quantities in relation to specific output continuous quantities of the regulator is described. The methods of defuzzification of the values of output continuous quantities within the boundaries of their terms are shown. The possibility of combining input and output continuous quantities into groups when setting up mutual connections between them is described. The mechanism of determining groups of interrelated continuous quantities is illustrated, the total number of which is determined by forming a matrix of relationships, according to the author’s scheme. The algorithm of sequential processing of the contents of the cells of the matrix of relationships, consisting of three steps, is considered. Expressions are given for calculating the basic parameters of a multidimensional fuzzy interval-logic controller with interrelated adjustable parameters. The results of a computational experiment to reduce the system of production rules of the regulator in determining the relationships between input and output continuous quantities are presented.

Application of Deep Learning and Intelligent Sensing Analysis in Smart Home

Deep learning technology can improve sensing efficiency and has the ability to discover potential patterns in data; the efficiency of user behavior recognition in the field of smart homes has been further improved, making the recognition process more intelligent and humanized. This paper analyzes the optical sensors commonly used in smart homes and their working principles through case studies and explores the technical framework of user behavior recognition based on optical sensors. At the same time, CiteSpace (Basic version 6.2.R6) software is used to visualize and analyze the related literature, elaborate the main research hotspots and evolutionary changes of optical sensor-based smart home user behavior recognition, and summarize the future research trends. Finally, fully utilizing the advantages of cloud computing technology, such as scalability and on-demand services, combining typical life situations and the requirements of smart home users, a smart home data collection and processing technology framework based on elderly fall monitoring scenarios is designed. Based on the comprehensive research results, the application and positive impact of optical sensors in smart home user behavior recognition were analyzed, and inspiration was provided for future smart home user experience research.

PEMEM Percentile: New Plasma Environment Specification Model for Surface Charging Risk Assessment

AbstractThe Plasma Environment Modeling in the Earth's Magnetosphere (PEMEM) is a European Space Agency activity supporting the development of a new specification model for the spacecraft surface charging risk assessment. This paper presents a description of the basic model version: the PEMEM percentile model. The model is intended to be used for space missions with near‐equatorial orbits. The model is based on the Van Allen Probes particle measurements inside the geostationary orbit. The model's primary input is a planned spacecraft trajectory. It outputs statistical characteristics of the plasma environment which are expected to be encountered during a mission lifetime. These characteristics include differential electron and proton flux percentiles for a set of energies (percentile spectra), and percentiles of the integrated electron flux. The model covers the energy range of 1–100 keV for electrons and 40 eV–51 keV for protons. Since extreme spacecraft charging usually occurs in the eclipse, the same characteristics can be separately output for the periods when the spacecraft is shadowed by the Earth.

Assessing the Transformative Influence of ChatGPT on Research Practices among Scholars in Pakistan

This article investigates the transformative impact of ChatGPT on research practices within the scholarly community in Pakistan. ChatGPT, a powerful AI language model, has added significant consideration for its possibility of improving academic research. Survey data was gathered via a structured questionnaire distributed to researchers in Pakistan. A total of 278 questionnaires were distributed for the randomly chosen sample, of which 223 were returned. For calculating descriptive statistics, SPSS was utilized. Results of the study indicated that 90% of scholars are familiar with the practice of ChatGPT in research activities. 86% of scholars used 3.5 (Basic version) of ChatGPT for their research and only 14% used 4 (Plus version) of ChatGPT for their research work. The overall satisfaction level was 46% response satisfied with the usage of ChatGPT in research activities. The article discusses how ChatGPT's natural language processing capabilities have advanced literature reviews, data analysis, and content generation, thereby saving time and fostering greater productivity. Moreover, it examines how the tool’s accessibility and affordability have democratized research, making it more inclusive and open to a broader range of scholars. By shedding light on these critical aspects, this article provides valuable insights into the evolving landscape of research practices in Pakistan and highlights the potential for ChatGPT to revolutionize academic scholarship in the digital age.

Bundle generation for the vehicle routing problem with occasional drivers and time windows

AbstractIn this paper, we address the vehicle routing problem (VRP) with occasional drivers (ODs) and time windows (TWs). The problem (VRP-OD-TW) is an extension of the VRP-OD, where ODs serve customers within given TWs. Differently from the basic version of VRP-OD-TW, we assume that ODs not only accept single requests, but they can also serve bundles of requests. To deal with the bundle-to-driver assignment problem, an auction-based system has been designed; a company offers a set of bundles to the ODs, who bid for all the bundles they consider attractive. There is no limit on the number of bids a driver can place, but at most one bid per OD can be assigned to avoid infeasible workloads. This system could yield a large cost reduction for the company, but its success is strongly related to the bundles offered. Hence, determining bundles which are attractive for ODs and profitable for the company, becomes a crucial issue. We propose two different bundling strategies, which make use of a spatial-temporal representation of customers in a three-dimensional (3D) space. The former is based on the generation of 3D corridors, while the latter relies on 3D clustering techniques. Through extensive computational results, we show that the former technique outperforms the latter in terms of both solution quality and computational times and that both the approaches strongly outperform bundle generation techniques that neglect the temporal dimension and rely only on spatial information.

S-shaped grey wolf optimizer-based FOX algorithm for feature selection

The FOX algorithm is a recently developed metaheuristic approach inspired by the behavior of foxes in their natural habitat. While the FOX algorithm exhibits commendable performance, its basic version, in complex problem scenarios, may become trapped in local optima, failing to identify the optimal solution due to its weak exploitation capabilities. This research addresses a high-dimensional feature selection problem. In feature selection, the most informative features are retained while discarding irrelevant ones. An enhanced version of the FOX algorithm is proposed, aiming to mitigate its drawbacks in feature selection. The improved approach referred to as S-shaped Grey Wolf Optimizer-based FOX (FOX-GWO), which focuses on augmenting the local search capabilities of the FOX algorithm via the integration of GWO. Additionally, the introduction of an S-shaped transfer function enables the population to explore both binary options throughout the search process. Through a series of experiments on 18 datasets with varying dimensions, FOX-GWO outperforms in 83.33 % of datasets for average accuracy, 61.11 % for reduced feature dimensionality, and 72.22 % for average fitness value across the 18 datasets. Meaning it efficiently explores high-dimensional spaces. These findings highlight its practical value and potential to advance feature selection in complex data analysis, enhancing model prediction accuracy.

ҚАЗАҚ ТІЛІНІҢ ПОЭТИКАЛЫҚ КОРПУСЫ МӘСЕЛЕСІ БОЙЫНША БІРЕР СӨЗ

The article is devoted to the study of the problem of the poetic language of the constituent poetic corpus of the Kazakh language. The poetic features of the variants of the song "Kozy Korpesh – Bayan Sulu", taken as the main version, are analyzed. Examples from the poem "Kyz Zhibek" are partially given. The purpose, main direction and idea of the research is to reveal the poetic value of the variants of the poem "Kozy Korpesh – Bayan Sulu". The article uses methods of selection, systematization, division into lexico-semantic and thematic groups, structural, descriptive, semantic grouping, synchronous analysis, and construction. The article examines from a historical and poetic point of view selected versions of one of the oldest cultural relics of the Kazakh people, "Kozy Korpesh-Bayan Sulu", with a comparison among themselves. It is known that this epic is a common heritage for all Turkic peoples. For example, the Altaians, Bashkirs, and Tatars have preserved several versions of this lyric epic. As for the Kazakh versions of the poem, this poem was first published in the third volume of V.Radlov's work in 1870 "Samples of folk literature of Turkic tribes" and in 1876 by I.Berezin as part of the "Turkish Anthology". Many intellectuals, led by Sh. Ualikhanov, G.N.Potanin participated in publication and research of the epic. The results obtained during the study: 1) comparing the poetic language of the main versions of the epic, we find, as the most basic, ancient and artistic version, the version sung by Zhanak akyn; 2) issues related to the life and fate of the main characters of lyric-epic poems, such as "Kozy Korpesh-Bayan Sulu", "Kyz Zhibek" are identified; 3) it is proved who is actually a positive hero, since in different versions of the epic Sarybai and Karabai are perceived differently as positive and negative characters.

A genetics algorithms for optimizing a function over the integer efficient set

In this paper, we propose an algorithm called Directional Exploration Genetic Algorithm (DEGA) to resolve a function Phi over the efficient set of a multi-objective integer linear programming problem (MOILP). DEGA algorithm belongs to evolutionary algorithms, which operate on the decision space by choosing the fastest improving directions that improve the objectives functions and Phi function. Two variants of this algorithm and a basic version of the genetic algorithm (BVGA) are performed and implemented in Python. Several benchmarks are carried out to evaluate the algorithm's performances and interesting results are obtained and discussed.