Search results for: algorithm integration

Authors: Said Baadel, Fadi Thabtah, Joan Lu

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Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper, we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold to be defined as a priority which can be difficult to determine by novice users.

Keywords: data mining, k-means, MCOKE, overlapping

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Authors: Younis R. Elhaddad, Mohamed A. Alshaari

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Since 2700 B.C the problem of constructing magic squares attracts many researchers. Magic squares one of most difficult challenges for mathematicians. In this work, we describe how to construct and enumerate Pan- magic squares using genetic algorithm, using new chromosome encoding technique. The results were promising within reasonable time.

Keywords: genetic algorithm, magic square, pan-magic square, computational intelligence

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Authors: A. P. Puvanasvaran, Suresh A. L. Vasu, N. Norazlin

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The Lean Environmental Management Integration System (LEMIS) framework development is integration between lean core element and ISO 14001. The curiosity on the relationship between continuous improvement and sustainability of lean implementation has influenced this study toward LEMIS. Characteristic of ISO 14001 standard clauses and core elements of lean principles are explored from past studies and literature reviews. Survey was carried out on ISO 14001 certified companies to examine continual improvement by implementing the ISO 14001 standard. The study found that there is a significant and positive relationship between Lean Principles: value, value stream, flow, pull and perfection with the ISO 14001 requirements. LEMIS is significant to support the continuous improvement and sustainability. The integration system can be implemented to any manufacturing company. It gives awareness on the importance on why organizations need to sustain its Environmental management system. At the meanwhile, the lean principle can be adapted in order to streamline daily activities of the company. Throughout the study, it had proven that there is no sacrifice or trade-off between lean principles with ISO 14001 requirements. The framework developed in the study can be further simplified in the future, especially the method of crossing each sub requirements of ISO 14001 standard with the core elements of Lean principles in this study.

Keywords: LEMIS, ISO 14001, integration, framework

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Authors: Yuqing Chen, Ying Xu, Renfa Li

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The development of matrix completion theory provides new approaches for data gathering in Wireless Sensor Networks (WSN). The existing matrix completion algorithms for WSN mainly consider how to reduce the sampling number without considering the real-time performance when recovering the data matrix. In order to guarantee the recovery accuracy and reduce the recovery time consumed simultaneously, we propose a new ALM algorithm to recover the weather monitoring data. A lot of experiments have been carried out to investigate the performance of the proposed ALM algorithm by using different parameter settings, different sampling rates and sampling models. In addition, we compare the proposed ALM algorithm with some existing algorithms in the literature. Experimental results show that the ALM algorithm can obtain better overall recovery accuracy with less computing time, which demonstrate that the ALM algorithm is an effective and efficient approach for recovering the real world weather monitoring data in WSN.

Keywords: wireless sensor network, matrix completion, singular value thresholding, augmented Lagrange multiplier

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Authors: Sahin Emrah Amrahov, Fatih Aybar, Serhat Dogan

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In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.

Keywords: rough sets, decision rules, rule induction, classification

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Authors: Denise Muro

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Conflict in Syria, producing over 11 million displaced persons, has incited global attention to displacement. Although neighboring countries have borne the largest part of the displacement burden, due to the influx of refugees into Europe, the so-called ‘refugee crisis’ is taking place on two fronts: Syria’s neighboring countries, with millions of refugees, and Europe, a destination goal for so many that European states face unprecedented challenges. With increasing attention to displacement, forcibly displaced persons are consistently portrayed as either un-agentic victims, or as dangerous free agents. Recognizing that these dominant portrayals involve discourses of power and inequality, this research investigates the extent to which this victim-agent dichotomy affects refugees and organizations that work closely with them during initial integration processes in Berlin, Germany. The research measures initial integration based on German policy measures regarding integration juxtaposed with the way refugees and those who work with them understand integration. Additionally, the study examines day-to-day interactions of refugees in Germany as a way to gauge social integration in a bottom-up approach. This study involved a discourse analysis of portrayals of refugees and participant observation and interviews with refugees and those who work closely with them, which took place during fieldwork in Berlin in the summer of 2016. Germany is unique regarding their migration history and lack of successful integration, in part due to the persistent refrain, ‘Wir sind kein einwanderungsland’ (‘We are not an immigration country’). Still, their accepted asylum seeker population has grown exponentially in the past few years. Findings suggest that the victim-agent dichotomy is present and impactful in the process of refugees entering and integrating into Germany. Integration is hindered due to refugees either being patronized or criminalized to such an extent that, despite being constantly told that they must integrate, they cannot become part of German society.

Keywords: discourse analysis, Germany, integration, refugee crisis

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Authors: Rachel Gugu Mkhasibe

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Incorporation of technology as a pedagogy has many benefits. For instance, improvement of pedagogy, increased information access, increased cooperation, and collaboration. However, as good as it may be, this integration of technology as a pedagogy has not been widely adopted in most historically Black higher education institutions especially those in developing countries. For example, the socioeconomic background of students in historically black universities, the weak financial support available from these universities, as well as a large population of students struggle to access the recommended modern physical resources such as iPads, laptops, mobile phones, to name a few. This contributes to an increase in the increase of educational inequalities. The qualitative research approach was utilized in this work to gather detailed data about the obstacles created by the integration of technology as a pedagogy. Interviews were conducted to generate data from 20 academics from 10 Leve two students from one of the historically disadvantaged higher education Institutions in South Africa. The findings revealed that although both students and academics had overwhelming support of the integration of technology as a pedagogy in their institution, the environment which they found themselves in compromise the incorporation of technology as a pedagogy. Therefore, this paper recommends that Department of Higher Education and University Management should intervene and budget for technology to be provided in all the institutions of higher education regardless of where the institutions are situated.

Keywords: collaboration, integration, pedagogy, technology

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Authors: Nirmal Yadav, Tanuja Srivastava

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Shannon theory is an exact method to recover a band limited signals from its sampled values in discrete implementation, using sinc interpolators. But sinc based results are not much satisfactory for band-limited calculations so that convolution with window function, having compact support, has been introduced. Convolution Backprojection algorithm with window function is an approximation algorithm. In this paper, the error has been calculated, arises due to this approximation nature of reconstruction algorithm. This result will be defined for fan beam projection data which is more faster than parallel beam projection.

Keywords: computed tomography, convolution backprojection, radon transform, fan beam

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Authors: Shahram Jamali, Samira Hamed

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One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.

Keywords: active queue management, RED, Markov model, random early detection algorithm

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Authors: Juan Manuel Sanchez-Cartas, Gonzalo Leon

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A price competition algorithm for ABMs based on game theory principles is proposed to deal with the simulation of theoretical market models. The algorithm is applied to the classical Hotelling’s model and to a two-sided market model to show it leads to the optimal behavior predicted by theoretical models. However, when theoretical models fail to predict the equilibrium, the algorithm is capable of reaching a feasible outcome. Results highlight that the algorithm can be implemented in other simulation models to guarantee rational users and endogenous optimal behaviors. Also, it can be applied as a tool of verification given that is theoretically based.

Keywords: agent-based models, algorithmic game theory, multi-sided markets, price optimization

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Authors: Smail Tigani, Mohamed Ouzzif

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This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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Authors: Muhammad Umar Kiani, Waseem Sakawat

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This study presents the development of FEM code using Quadrilateral 4-Node (Q4) and Triangular 3-Node (T3) elements. Code is formulated using MATLAB language. Instead of using both elements in the same code, two separate codes are written. Quadrilateral element is difficult to handle directly, that is why natural coordinates (eta, ksi) are used. Due to this, Q4 code includes numerical integration (Gauss quadrature). In this case, complete numerical integration is performed using 2 points. On the other hand, T3 element can be modeled directly, by using direct stiffness approach. Axially loaded element, cantilever (special constraints) and Patch test cases were analyzed using both codes and the results were verified by using Ansys.

Keywords: FEM code, MATLAB, numerical integration, ANSYS

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Authors: B. Selma, S. Chouraqui

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The pancreas is an elongated organ that extends across the abdomen, below the stomach. In addition, it secretes certain enzymes that aid in food digestion. The pancreas also manufactures hormones responsible for regulating blood glucose levels. In the present paper, we propose a mathematical model to study the homeostasis of glucose and insulin in healthy human, and a simulation of this model, which depicts the physiological events after a meal, will be represented in ordinary humans. The aim of this paper is to design an algorithm which regulates the level of glucose in the blood. The algorithm applied the concept of expert system for performing an algorithm control in the form of an "active" used to prescribe the rate of insulin infusion. By decomposing the system into subsystems, we have developed parametric models of each subsystem by using a forcing function strategy. The results showed a performance of the control system.

Keywords: modeling, algorithm, regulation, glucose-insulin, blood, control system

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Authors: Hong Lu, Xin Chen, Zhengcheng Fan

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Prior research has claimed a close association between handwriting and mathematics attainment with the help of spatial cognition. However, the exact mechanism behind this relationship remains un-investigated. Focusing on visual-motor integration (VMI), one critical spatial skill, this meta-analysis aims to estimate the size of the handwriting- visual-motor integration relationship and examine the moderating effect of handwriting dimensions on the link. With a random effect model, a medium relation (r=.26, 95%CI [.22, .30]) between handwriting and VMI was summarized in 38 studies with 55 unique samples and 141 effect sizes. Findings suggested handwriting dimensions significantly moderated the handwriting- VMI relationship, with handwriting legibility showing a substantial correlation with VMI, but neither handwriting speed nor pressure. Identifying the essential relationship between handwriting legibility and VMI, this study adds to the literature about the key cognitive processing needs underlying handwriting, and spatial cognition thus highlights the cognitive mechanism regarding handwriting, spatial cognition, and mathematics performances.

Keywords: handwriting, visual-motor integration, legibility, meta-analysis

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Authors: Jigg Pelayo, Ricardo Villar

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The Philippines is long considered as a valuable producer of high value crops globally. The country’s employment and economy have been dependent on agriculture, thus increasing its demand for the efficient agricultural mechanism. Remote sensing and geographic information technology have proven to effectively provide applications for precision agriculture through image-processing technique considering the development of the aerial scanning technology in the country. Accurate information concerning the spatial correlation within the field is very important for precision farming of high value crops, especially. The availability of height information and high spatial resolution images obtained from aerial scanning together with the development of new image analysis methods are offering relevant influence to precision agriculture techniques and applications. In this study, an algorithm was developed and implemented to detect and count high value crops simultaneously through adaptive scaling of support vector machine (SVM) algorithm subjected to object-oriented approach combining watershed transformation and local maxima filter in enhancing tree counting and detection. The methodology is compared to cutting-edge template matching algorithm procedures to demonstrate its effectiveness on a demanding tree is counting recognition and delineation problem. Since common data and image processing techniques are utilized, thus can be easily implemented in production processes to cover large agricultural areas. The algorithm is tested on high value crops like Palm, Mango and Coconut located in Misamis Oriental, Philippines - showing a good performance in particular for young adult and adult trees, significantly 90% above. The s inventories or database updating, allowing for the reduction of field work and manual interpretation tasks.

Keywords: high value crop, LiDAR, OBIA, precision agriculture

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Authors: Bircan Demiral

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Cognitive radio (CR) is the promising technology that addresses the spectrum scarcity problem for future wireless communications. Orthogonal Frequency Division Multiplexing (OFDM) technology provides more power band ratios for cognitive radio networks (CRNs). While CR is a solution to the spectrum scarcity, it also brings up the capacity problem. In this paper, a novel power allocation algorithm that aims at maximizing the sum capacity in the OFDM based cognitive radio networks is proposed. Proposed allocation algorithm is based on the previously developed water-filling algorithm. To reduce the computational complexity calculating in water filling algorithm, proposed algorithm allocates the total power according to each subcarrier. The power allocated to the subcarriers increases sum capacity. To see this increase, Matlab program was used, and the proposed power allocation was compared with average power allocation, water filling and general power allocation algorithms. The water filling algorithm performed worse than the proposed algorithm while it performed better than the other two algorithms. The proposed algorithm is better than other algorithms in terms of capacity increase. In addition the effect of the change in the number of subcarriers on capacity was discussed. Simulation results show that the increase in the number of subcarrier increases the capacity.

Keywords: cognitive radio network, OFDM, power allocation, water filling

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Authors: Junior George Martin

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The purpose of this study was to explore college instructors’ integration of technology in their content area curriculum. The instructors indicated that they were in need of additional training to successfully integrate technology in their subject areas. The findings point to the implementation of a proposed the Technological, Pedagogical, and Content Knowledge (TPACK) model professional development workshop to satisfactorily address the weaknesses of the instructors in technology integration. The professional development workshop is proposed as a rational solution to adequately address the instructors’ inability to the successful integration of technology in their subject area in an effort to improve their pedagogy. The intense workshop would last for 5 days and will be designed to provide instructors with training in areas such as a use of technology applications and tools, and using modern methodologies to improve technology integration. Exposing the instructors to the specific areas identified will address the weaknesses they demonstrated during the study. Professional development is deemed the most appropriate intervention based on the opportunities it provides the instructors to access hands-on training to overcome their weaknesses. The purpose of the TPACK professional development workshop will be to improve the competence of the instructors so that they are adequately prepared to integrate technology successfully in their curricula. At the end of the period training, the instructors are expected to adopt strategies that will have a positive impact on the learning experiences of the students.

Keywords: higher education, modern technology tools, professional development, technology integration

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Authors: Majid Khalili

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This paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presents a new multi-objective variable neighborhood algorithm (MOVNS). A set of experimental instances are carried out to evaluate the algorithm by advanced multi-objective performance measures. The algorithm is carefully evaluated for its performance against available algorithm by means of multi-objective performance measures and statistical tools. The related results show that a variant of our proposed MOVNS provides sound performance comparing with other algorithms.

Keywords: no-wait hybrid flowshop scheduling; multi-objective variable neighborhood algorithm; makespan; total weighted tardiness

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Authors: Duckyong Kim, Jong Kang Park, Jong Tae Kim

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DOA (Direction of Arrival) estimation is an important method in array signal processing and has a wide range of applications such as direction finding, beam forming, and so on. In this paper, we briefly introduce the MUSIC (Multiple Signal Classification) Algorithm, one of DOA estimation methods for analyzing several targets. Then we apply the MUSIC algorithm to the two-dimensional antenna array to analyze DOA estimation in 3D space through MATLAB simulation. We also analyze the design factors that can affect the accuracy of DOA estimation through simulation, and proceed with further consideration on how to apply the system.

Keywords: DOA estimation, MUSIC algorithm, spatial spectrum, array signal processing

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Authors: Archit Yajnik

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Part of Speech Tagging has always been a challenging task in the era of Natural Language Processing. This article presents POS tagging for Nepali text using Hidden Markov Model and Viterbi algorithm. From the Nepali text, annotated corpus training and testing data set are randomly separated. Both methods are employed on the data sets. Viterbi algorithm is found to be computationally faster and accurate as compared to HMM. The accuracy of 95.43% is achieved using Viterbi algorithm. Error analysis where the mismatches took place is elaborately discussed.

Keywords: hidden markov model, natural language processing, POS tagging, viterbi algorithm

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Authors: Hussain K. Chaiel

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The development in the field of the digital signal processing (DSP) and the microelectronics technology reduces the complexity of the iterative algorithms that need large number of arithmetic operations. Virtex-Field Programmable Gate Arrays (FPGAs) are programmable silicon foundations which offer an important solution for addressing the needs of high performance DSP designer. In this work, Virtex-7 FPGA technology is used to implement an iterative algorithm to estimate the earthquake location. Simulation results show that an implementation based on block RAMB36E1 and DSP48E1 slices of Virtex-7 type reduces the number of cycles of the clock frequency. This enables the algorithm to be used for earthquake prediction.

Keywords: DSP, earthquake, FPGA, iterative algorithm

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Authors: A. Andreasyan, C. Connors

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The Elliptic Curve Digital Signature algorithm-based X509v3 certificates are becoming more popular due to their short public and private key sizes. Moreover, these certificates can be stored in Internet of Things (IoT) devices, with limited resources, using less memory and transmitted in network security protocols, such as Internet Key Exchange (IKE), Transport Layer Security (TLS) and Secure Shell (SSH) with less bandwidth. The proposed method gives another advantage, in that it increases the performance of the above-mentioned protocols in terms of key exchange by saving one scalar multiplication operation.

Keywords: cryptography, elliptic curve digital signature algorithm, key exchange, network security protocol

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Authors: Meng Wu

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Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.

Keywords: motion planning, gravity gradient inversion algorithm, ant colony optimization

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Authors: Sofiane Bououden, Ilyes Boulkaibet

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In terms of security of the information signal, the meta-heuristic Penguins Search Optimization Algorithm (PeSOA) is applied to synchronize chaotic encryption communications in the case of sensitive dependence on initial conditions in chaotic generator oscillator. The objective of this paper is the use of the PeSOA algorithm to exploring search space with random and iterative processes for synchronization of symmetric keys in both transmission and reception. Simulation results show the effectiveness of the PeSOA algorithm in generating symmetric keys of the encryption process and synchronizing.

Keywords: meta-heuristic, PeSOA, chaotic systems, encryption, synchronization optimization

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Authors: Watchara Songserm, Teeradej Wuttipornpun

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This paper presents a genetic algorithm based permutation and non-permutation scheduling heuristics (GAPNP) to solve a multi-stage finite capacity material requirement planning (FCMRP) problem in automotive assembly flow shop with unrelated parallel machines. In the algorithm, the sequences of orders are iteratively improved by the GA characteristics, whereas the required operations are scheduled based on the presented permutation and non-permutation heuristics. Finally, a linear programming is applied to minimize the total cost. The presented GAPNP algorithm is evaluated by using real datasets from automotive companies. The required parameters for GAPNP are intently tuned to obtain a common parameter setting for all case studies. The results show that GAPNP significantly outperforms the benchmark algorithm about 30% on average.

Keywords: capacitated MRP, genetic algorithm, linear programming, automotive industries, flow shop, application in industry

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Authors: Shreya Pare, Parvin Akhter

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Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Tshimangadzo Oscar Magadze

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For successful re-integration, the individual offender must adapt and transform, which requires that the offender should adopt and internalise socially approved norms, attitudes, values, and beliefs. However, the offender’s labelling and community stigmatisation decide the destination of the offender. Community involvement in ex-offenders’ re-integration is an important issue in efforts to reduce recidivism and to control overcrowding in our correctional facilities. Crime is a social problem that requires society to come together to fight against it. This study was conducted in the Limpopo Province in Vhembe District Municipality within four local municipalities, namely Musina, Makhado, Mutale, and Thulamela. A total number of 30 participants were interviewed, and all were members of the Community Corrections Forums. This was necessitated by the fact that Musina is a very small area, which compelled the Department of Correctional Services to combine the two (Musina and Makhado) into one social re-integration entity. This is a qualitative research study where participants were selected through the use of purposive sampling. Participants were selected based on the value they would add to this study in order to achieve the objectives. The data collection method of this study was the focus group, which comprised of three groups of 10 participants each. Thulamela and Mutale local municipalities formed a group with (10) participants each, whereas Musina (2) and Makhado (8) formed another. Results indicate that the current situation is not conducive for re-integration to be successful. Participants raised many factors that need serious redress, namely offenders’ discrimination, lack of forgiveness by members of the community, which is fuelled by lack of community awareness due to the failure of the Department of Correctional Services in educating communities on ex-offenders’ re-integration.

Keywords: ex-offender, labeling, re-integration, stigmatization

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Authors: Rym Ghariani, Younes Boujelbene

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This study aimed to examine the impact of digitalization and supply chain integration on the financial performance of companies in the agro-industrial sector in Tunisia, highlighting the growing importance of digital technologies in modern economies. The results were analyzed using a questionnaire and using principal component analysis, as well as linear regression modeling with SPSS26. The results demonstrate that the digitalization and integration of the supply chain have a significant impact on the financial results of Tunisian agro-industrial companies. In theory, this study provides a better understanding of the effects of digital advancements and supply chain strategies on financial results in this specific area. This study, therefore, studies the relationship between these variables and financial efficiency, highlighting the significant impacts of these technological and strategic elements on the financial results of agro-industrial companies in Tunisia.

Keywords: digitalization, supply chain integration, financial performance, Tunisian agro-industrial sector

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

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Authors: Nevena Jakovčević Stor, Ivan Slapničar

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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.

Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy

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