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  Subjects -> MATHEMATICS (Total: 966 journals)
    - APPLIED MATHEMATICS (82 journals)
    - GEOMETRY AND TOPOLOGY (20 journals)
    - MATHEMATICS (711 journals)
    - MATHEMATICS (GENERAL) (43 journals)
    - NUMERICAL ANALYSIS (22 journals)
    - PROBABILITIES AND MATH STATISTICS (88 journals)

MATHEMATICS (711 journals)                  1 2 3 4 | Last

Showing 1 - 200 of 538 Journals sorted alphabetically
Abakós     Open Access   (Followers: 4)
Abhandlungen aus dem Mathematischen Seminar der Universitat Hamburg     Hybrid Journal   (Followers: 4)
Academic Voices : A Multidisciplinary Journal     Open Access   (Followers: 2)
Accounting Perspectives     Full-text available via subscription   (Followers: 7)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Mathematical Software (TOMS)     Hybrid Journal   (Followers: 6)
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 29)
Acta Applicandae Mathematicae     Hybrid Journal   (Followers: 1)
Acta Mathematica     Hybrid Journal   (Followers: 12)
Acta Mathematica Hungarica     Hybrid Journal   (Followers: 2)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5)
Acta Mathematica Sinica, English Series     Hybrid Journal   (Followers: 6)
Acta Mathematica Vietnamica     Hybrid Journal  
Acta Mathematicae Applicatae Sinica, English Series     Hybrid Journal  
Advanced Science Letters     Full-text available via subscription   (Followers: 10)
Advances in Applied Clifford Algebras     Hybrid Journal   (Followers: 4)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 19)
Advances in Decision Sciences     Open Access   (Followers: 3)
Advances in Difference Equations     Open Access   (Followers: 3)
Advances in Fixed Point Theory     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 13)
Advances in Linear Algebra & Matrix Theory     Open Access   (Followers: 3)
Advances in Materials Sciences     Open Access   (Followers: 14)
Advances in Mathematical Physics     Open Access   (Followers: 4)
Advances in Mathematics     Full-text available via subscription   (Followers: 11)
Advances in Numerical Analysis     Open Access   (Followers: 5)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Pure and Applied Mathematics     Hybrid Journal   (Followers: 6)
Advances in Pure Mathematics     Open Access   (Followers: 6)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aequationes Mathematicae     Hybrid Journal   (Followers: 2)
African Journal of Educational Studies in Mathematics and Sciences     Full-text available via subscription   (Followers: 5)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
Afrika Matematika     Hybrid Journal   (Followers: 1)
Air, Soil & Water Research     Open Access   (Followers: 11)
AKSIOMA Journal of Mathematics Education     Open Access   (Followers: 1)
Al-Jabar : Jurnal Pendidikan Matematika     Open Access   (Followers: 1)
Algebra and Logic     Hybrid Journal   (Followers: 5)
Algebra Colloquium     Hybrid Journal   (Followers: 4)
Algebra Universalis     Hybrid Journal   (Followers: 2)
Algorithmic Operations Research     Full-text available via subscription   (Followers: 5)
Algorithms     Open Access   (Followers: 11)
Algorithms Research     Open Access   (Followers: 1)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Mathematical Analysis     Open Access  
American Journal of Mathematics     Full-text available via subscription   (Followers: 6)
American Journal of Operations Research     Open Access   (Followers: 5)
An International Journal of Optimization and Control: Theories & Applications     Open Access   (Followers: 8)
Analele Universitatii Ovidius Constanta - Seria Matematica     Open Access   (Followers: 1)
Analysis     Hybrid Journal   (Followers: 2)
Analysis and Applications     Hybrid Journal   (Followers: 1)
Analysis and Mathematical Physics     Hybrid Journal   (Followers: 5)
Analysis Mathematica     Full-text available via subscription  
Annales Mathematicae Silesianae     Open Access  
Annales mathématiques du Québec     Hybrid Journal   (Followers: 4)
Annales UMCS, Mathematica     Open Access   (Followers: 1)
Annales Universitatis Paedagogicae Cracoviensis. Studia Mathematica     Open Access  
Annali di Matematica Pura ed Applicata     Hybrid Journal   (Followers: 1)
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Data Science     Hybrid Journal   (Followers: 11)
Annals of Discrete Mathematics     Full-text available via subscription   (Followers: 6)
Annals of Mathematics     Full-text available via subscription   (Followers: 1)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of the Alexandru Ioan Cuza University - Mathematics     Open Access  
Annals of the Institute of Statistical Mathematics     Hybrid Journal   (Followers: 1)
Annals of West University of Timisoara - Mathematics     Open Access  
Annuaire du Collège de France     Open Access   (Followers: 5)
ANZIAM Journal     Open Access   (Followers: 1)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applications of Mathematics     Hybrid Journal   (Followers: 2)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 11)
Applied Mathematics     Open Access   (Followers: 3)
Applied Mathematics     Open Access   (Followers: 7)
Applied Mathematics & Optimization     Hybrid Journal   (Followers: 6)
Applied Mathematics - A Journal of Chinese Universities     Hybrid Journal  
Applied Mathematics Letters     Full-text available via subscription   (Followers: 2)
Applied Mathematics Research eXpress     Hybrid Journal   (Followers: 1)
Applied Network Science     Open Access   (Followers: 3)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Arab Journal of Mathematical Sciences     Open Access   (Followers: 3)
Arabian Journal of Mathematics     Open Access   (Followers: 2)
Archive for Mathematical Logic     Hybrid Journal   (Followers: 2)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
Armenian Journal of Mathematics     Open Access  
Arnold Mathematical Journal     Hybrid Journal   (Followers: 1)
Artificial Satellites : The Journal of Space Research Centre of Polish Academy of Sciences     Open Access   (Followers: 20)
Asia-Pacific Journal of Operational Research     Hybrid Journal   (Followers: 3)
Asian Journal of Algebra     Open Access   (Followers: 1)
Asian Journal of Current Engineering & Maths     Open Access  
Asian-European Journal of Mathematics     Hybrid Journal   (Followers: 2)
Australian Mathematics Teacher, The     Full-text available via subscription   (Followers: 6)
Australian Primary Mathematics Classroom     Full-text available via subscription   (Followers: 4)
Australian Senior Mathematics Journal     Full-text available via subscription   (Followers: 1)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Axioms     Open Access   (Followers: 1)
Baltic International Yearbook of Cognition, Logic and Communication     Open Access   (Followers: 1)
Basin Research     Hybrid Journal   (Followers: 5)
BIBECHANA     Open Access   (Followers: 2)
BIT Numerical Mathematics     Hybrid Journal  
BoEM - Boletim online de Educação Matemática     Open Access  
Boletim Cearense de Educação e História da Matemática     Open Access  
Boletim de Educação Matemática     Open Access  
Boletín de la Sociedad Matemática Mexicana     Hybrid Journal  
Bollettino dell'Unione Matematica Italiana     Full-text available via subscription   (Followers: 1)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 20)
Bruno Pini Mathematical Analysis Seminar     Open Access  
Buletinul Academiei de Stiinte a Republicii Moldova. Matematica     Open Access   (Followers: 12)
Bulletin des Sciences Mathamatiques     Full-text available via subscription   (Followers: 4)
Bulletin of Dnipropetrovsk University. Series : Communications in Mathematical Modeling and Differential Equations Theory     Open Access   (Followers: 1)
Bulletin of Mathematical Sciences     Open Access   (Followers: 1)
Bulletin of Symbolic Logic     Full-text available via subscription   (Followers: 2)
Bulletin of the Australian Mathematical Society     Full-text available via subscription   (Followers: 1)
Bulletin of the Brazilian Mathematical Society, New Series     Hybrid Journal  
Bulletin of the London Mathematical Society     Hybrid Journal   (Followers: 4)
Bulletin of the Malaysian Mathematical Sciences Society     Hybrid Journal  
Calculus of Variations and Partial Differential Equations     Hybrid Journal  
Canadian Journal of Science, Mathematics and Technology Education     Hybrid Journal   (Followers: 19)
Carpathian Mathematical Publications     Open Access   (Followers: 1)
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
CHANCE     Hybrid Journal   (Followers: 5)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
ChemSusChem     Hybrid Journal   (Followers: 7)
Chinese Annals of Mathematics, Series B     Hybrid Journal  
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Mathematics     Open Access  
Clean Air Journal     Full-text available via subscription   (Followers: 1)
Cogent Mathematics     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Collectanea Mathematica     Hybrid Journal  
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Commentarii Mathematici Helvetici     Hybrid Journal   (Followers: 1)
Communications in Combinatorics and Optimization     Open Access  
Communications in Contemporary Mathematics     Hybrid Journal  
Communications in Mathematical Physics     Hybrid Journal   (Followers: 2)
Communications On Pure & Applied Mathematics     Hybrid Journal   (Followers: 3)
Complex Analysis and its Synergies     Open Access   (Followers: 2)
Complex Variables and Elliptic Equations: An International Journal     Hybrid Journal  
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Compositio Mathematica     Full-text available via subscription   (Followers: 1)
Comptes Rendus Mathematique     Full-text available via subscription   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 8)
Concrete Operators     Open Access   (Followers: 5)
Confluentes Mathematici     Hybrid Journal  
Contributions to Game Theory and Management     Open Access  
COSMOS     Hybrid Journal  
Cryptography and Communications     Hybrid Journal   (Followers: 13)
Cuadernos de Investigación y Formación en Educación Matemática     Open Access  
Cubo. A Mathematical Journal     Open Access  
Current Research in Biostatistics     Open Access   (Followers: 9)
Czechoslovak Mathematical Journal     Hybrid Journal   (Followers: 1)
Demographic Research     Open Access   (Followers: 11)
Demonstratio Mathematica     Open Access  
Dependence Modeling     Open Access  
Design Journal : An International Journal for All Aspects of Design     Hybrid Journal   (Followers: 29)
Developments in Clay Science     Full-text available via subscription   (Followers: 1)
Developments in Mineral Processing     Full-text available via subscription   (Followers: 3)
Dhaka University Journal of Science     Open Access  
Differential Equations and Dynamical Systems     Hybrid Journal   (Followers: 3)
Differentsial'nye Uravneniya     Open Access  
Discrete Mathematics     Hybrid Journal   (Followers: 8)
Discrete Mathematics & Theoretical Computer Science     Open Access  
Discrete Mathematics, Algorithms and Applications     Hybrid Journal   (Followers: 2)
Discussiones Mathematicae - General Algebra and Applications     Open Access  
Discussiones Mathematicae Graph Theory     Open Access   (Followers: 1)
Diskretnaya Matematika     Full-text available via subscription  
Dnipropetrovsk University Mathematics Bulletin     Open Access  
Doklady Akademii Nauk     Open Access  
Doklady Mathematics     Hybrid Journal  
Duke Mathematical Journal     Full-text available via subscription   (Followers: 1)
Eco Matemático     Open Access  
Edited Series on Advances in Nonlinear Science and Complexity     Full-text available via subscription  
Electronic Journal of Combinatorics     Open Access  
Electronic Journal of Differential Equations     Open Access  
Electronic Journal of Graph Theory and Applications     Open Access   (Followers: 2)
Electronic Notes in Discrete Mathematics     Full-text available via subscription   (Followers: 2)
Elemente der Mathematik     Full-text available via subscription   (Followers: 4)
Energy for Sustainable Development     Hybrid Journal   (Followers: 9)

        1 2 3 4 | Last

Journal Cover
Computational and Mathematical Organization Theory
Journal Prestige (SJR): 0.186
Citation Impact (citeScore): 1
Number of Followers: 2  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1381-298X - ISSN (Online) 1572-9346
Published by Springer-Verlag Homepage  [2350 journals]
  • Blockmap: an interactive visualization tool for big-data networks
    • Authors: Terrill L. Frantz
      Pages: 149 - 168
      Abstract: This article describes the Blockmap, which is a mechanism for displaying and exploring network datasets. The data are presented in a squarified-mosaic form, which is well-suited for visual display on a computer or phone screen. The relational data are dimension-reduced and structured for interactive, hierarchical exploration. The Blockmap applies a combination of treemap and heatmap display schemes specifically to the analysis of large network datasets. The Blockmap offers the analyst a way to explore underlying node-level data, at the full-network level, according to shared characteristics of the constituent nodes. It offers a technique for exploring nodesets—collections of network nodes—which have been classified according to a user-defined set of rules or discriminative algorithms. Typically, nodes can be classified according to their common attributes or a stratification of their ego-level network measures, but means can be extended. Using a Blockmap, an analyst can profile a network according to the meaningful characteristics exhibited by the mosaic; this technique also offers theorists a platform for developing a methodological and analytic framework for characterizing and analyzing network data. Production versions of Blockmap technology are presently hosted in client- and web-based software and is available freely in *ORA-LITE.
      PubDate: 2018-06-01
      DOI: 10.1007/s10588-017-9252-6
      Issue No: Vol. 24, No. 2 (2018)
       
  • Explaining the emergence of online popularity through a model of
           information diffusion
    • Authors: António Fonseca; Jorge Louçã
      Pages: 169 - 187
      Abstract: This paper proposes a new formal modeling approach to popularity dynamics based on a generic notion of message propagation within society. The approach is demonstrated with two original models of information diffusion. These are a branching model of popularity and a epidemic model of popularity. The first is based on the principles of a branching process, while the second emulates an epidemic equation with a specific infection rate. This allows us to consider the replication phenomena on information diffusion. The approach is validated using a very large dataset collected online that involves keywords in blogs and hashtags on Twitter. Our main results point to an overall good fit of both models, both when the process of popularity grows and when it decays. This is due to endogenous information transfer, as in an epidemic process, but also when the process is initially triggered by an external event. Overall, on balance, our models confirm that popularity builds through message diffusion, which is of the multiplicative kind.
      PubDate: 2018-06-01
      DOI: 10.1007/s10588-017-9253-5
      Issue No: Vol. 24, No. 2 (2018)
       
  • Exchange process-based social mechanisms and social functions: an
           operational approach to the macro functional aspects of agent societies
    • Authors: Antônio Carlos da Rocha Costa
      Pages: 188 - 223
      Abstract: This paper presents elements for an operational approach to the formal modeling of the macro functional aspects of agent societies. The concept of agent society used in the paper is summarized. The exchange process-based concept of elementary social function is reviewed and a corresponding concept of elementary social mechanism is introduced. Together, these concepts allow for the recursive definition of the concept of functional system, with which one can account for the general functions performed by the core organizational structure of agent societies. Two case studies are developed to illustrate the type of functional modeling of agent societies that is enabled by the concepts introduced in the paper. The first case study concerns the functional analysis of a simple motivating thought experiment. The second concerns the use of agent societies as formal models for natural societies: it sketches the formalization of Pierre Bourdieu’s functional analysis of the reproduction process of contemporary human societies.
      PubDate: 2018-06-01
      DOI: 10.1007/s10588-017-9254-4
      Issue No: Vol. 24, No. 2 (2018)
       
  • Mining online communities to inform strategic messaging: practical methods
           to identify community-level insights
    • Authors: Matthew Benigni; Kenneth Joseph; Kathleen M. Carley
      Pages: 224 - 242
      Abstract: The ability of OSNs to propagate civil unrest has been powerfully observed through the rise of the ISIS and the ongoing conflict in Crimea. As a result, the ability to understand and in some cases mitigate the effects of user communities promoting civil unrest online has become an important area of research. Although methods to detect large online extremist communities have emerged in literature, the ability to summarize community content in meaningful ways remains an open research question. We introduce novel applications of the following methods: ideological user clustering with bipartite spectral graph partitioning, narrative mining with hash tag co-occurrence graph clustering, and identifying radicalization with directed URL sharing networks. In each case we describe how the method can be applied to social media. We subsequently apply them to online Twitter communities interested in the Syrian revolution and ongoing Crimean conflict.
      PubDate: 2018-06-01
      DOI: 10.1007/s10588-017-9255-3
      Issue No: Vol. 24, No. 2 (2018)
       
  • Realizing the effects of trust and personality in cross functional teams
           using ANFIS classification framework
    • Authors: R. Krishankumar; K. S. Ravichandran
      Pages: 243 - 276
      Abstract: Social behaviors are an integral part of team building. In this context, we propose a novel classification model that chooses an optimal classifier from the pool of classifiers for predicting the overall performance (OP). Secondly, the chosen classifier is used to investigate the impact of trust and personality on OP. To achieve these goals a pilot study with real time data from 442 respondents are collected from cross functional teams (CFTs) in India using an E-Questionnaire system. The results indicate that the adaptive neuro fuzzy inference system (ANFIS) method is an optimal classifier (A = 89.14%) with respect to other classifiers. We also infer that the predictors, trust and personality are most suitable for predicting OP with a direct relationship to OP and play an indispensable role; as a catalyst; for boosting OP.
      PubDate: 2018-06-01
      DOI: 10.1007/s10588-017-9256-2
      Issue No: Vol. 24, No. 2 (2018)
       
  • Theories of communication networks by Peter R. Monge and Noshir S.
           Contractor
    • Authors: Terrill L. Frantz
      Pages: 277 - 280
      PubDate: 2018-06-01
      DOI: 10.1007/s10588-017-9250-8
      Issue No: Vol. 24, No. 2 (2018)
       
  • Neural networks: an introductory guide for social scientists by G. David
           Garson
    • Authors: Terrill L. Frantz
      Pages: 281 - 283
      PubDate: 2018-06-01
      DOI: 10.1007/s10588-017-9251-7
      Issue No: Vol. 24, No. 2 (2018)
       
  • The meso-unit theory of post-merger integration
    • Authors: Terrill L. Frantz
      Pages: 99 - 111
      Abstract: This article introduces the meso-unit theory of post-merger integration. The theory offers that the number of constituent work-units involved in an organizational merger has a greater detrimental effect on the time-to-integration than does the total number of constituent personnel involved. Its establishment is based on the results of controlled experiments conducted in a virtual laboratory. The simulation utilizes agent-based modeling software that encapsulates organizational behavior models such as the knowledge-based view of the firm, social and communication network theory, and CONSTRUCT theory. The software is configured for a two-organization merger and implements classic behavior dynamics to simulate communicative behavior of information-seeking actors. As a result, detailed micro- and macro-level data on the integration progress is available for examination, analysis and interpretation. The results give rise to the development of the meso-unit theory, which directs integration managers’ attention toward a key aspect of the integration that is often overlooked.
      PubDate: 2018-03-01
      DOI: 10.1007/s10588-017-9248-2
      Issue No: Vol. 24, No. 1 (2018)
       
  • Integrating simulation and signal processing in tracking complex social
           systems
    • Authors: Fan Yang; Wen Dong
      Abstract: Data that continuously track the dynamics of large populations have the potential to revolutionize how we study complex social systems. However, coping with massive, noisy, unstructured, and disparate data streams is not easy. In this paper, we describe a particle filter algorithm that integrates signal processing and simulation modeling to study complex social systems using massive, noisy, unstructured data. This integration enables researchers to specify and track the dynamics of real-world complex social systems by building a simulation model. To show the effectiveness of this algorithm, we infer city-scale traffic dynamics from the observed trajectories of a small number of probe vehicles uniformly sampled from the system. The results show that our model can not only track and predict human mobility, but also explain how traffic is generated through the movements of individual vehicles. The algorithm and its application point to a new way of bringing together modelers and data miners to turn the real world into a living lab.
      PubDate: 2018-05-26
      DOI: 10.1007/s10588-018-9276-6
       
  • A knowledge-based image enhancement and denoising approach
    • Authors: Hafiz Syed Muhammad Muslim; Sajid Ali Khan; Shariq Hussain; Arif Jamal; Hafiz Syed Ahmed Qasim
      Abstract: The emergence of computer-aided diagnostic technology has revolutionized the health sector and by use of medical imaging records, health experts are able to get detailed analysis which enable them in precise diagnosis of gliomas tumors. In this paper, we present an approach that uses domain-specific knowledge together with hybrid image enhancement techniques that provides resulting image(s) with more details and lesser noise levels. We did comparison of our KB proposed approach with existing techniques and the experimentation results showed improvement in quality and reduction of arbitrariness of images. The approach is proved to be feasible and effective, thus resulting in better medical diagnosis and evaluation of gliomas problems. Proposed research work recommends a new approach for medical imaging enhancements.
      PubDate: 2018-05-22
      DOI: 10.1007/s10588-018-9274-8
       
  • Work process improvement through simulation optimization of task
           assignment and mental workload
    • Authors: Cansu Kandemir; Holly A. H. Handley
      Abstract: The outcome of a work process depends on which tasks are assigned to which employees. However, sometimes optimized assignments based on employees’ qualifications may result in an uneven and ineffective workload distribution. Likewise, an even workload distribution without considering the employee’s qualifications may cause unproductive employee-task matching that results in low performance. This trade-off is even more noticeable for work processes during critical time junctions, such as in military command centers and emergency rooms that require fast, effective and error free performance. This study evaluates optimizing task-employee assignments according to their capabilities while also maintaining a workload threshold. The goal is to select the employee-task assignments in order to minimize the average duration of a work process while keeping the employees under a workload threshold to prevent errors caused by overload. Due to uncertainties related with the inter-arrival time of work orders, task durations and employees’ instantaneous workload, a simulation–optimization approach is required. A discrete event human performance simulation model was used to evaluate the objective function of the problem coupled with a genetic algorithm based meta-heuristic optimization approach to search the solution space. A sample work process is used to show the effectiveness of the developed simulation–optimization approach. Numerical tests indicate that the proposed approach finds better solutions than common practices and other simulation–optimization methods. Accordingly, by using this method, organizations can increase performance, manage excess-level workloads, and generate higher satisfactory environments for employees, without modifying the structure of the process itself.
      PubDate: 2018-05-02
      DOI: 10.1007/s10588-018-9275-7
       
  • Knowledge based quality analysis of crowdsourced software development
           platforms
    • Authors: Asad Habib; Shahid Hussain; Arif Ali Khan; Muhammad Khalid Sohail; Manzoor Ilahi; Muhammad Rafiq Mufti; Muhammad Imran Faisal
      Abstract: As an emerging and promising approach, crowdsourcing-based software development has become popular in many domains due to the participation of talented pool of developers in the contests, and to promote the ability of requesters (or customers) to choose the ‘wining’ solution with respect to their desired quality levels. However, due to lack of a central mechanism for team formation, continuity in the developer’s work on consecutive tasks and risk of noise in submissions of a contest, there is a gap between the requesters of a domain and their quality concerns related to the adaptation of a crowdsourcing-based software development platform. In order to address concerns and aid requesters, we describe three measures; Quality of Registrant Developers (QRD), Quality of Contest (QC) and Quality of Support (QS) to compute and predict the quality of a crowdsourcing-based platform through historical information on its completed tasks. We evaluate the capacity of the QRD, QC and QS as assessors to predict the quality. Subsequently, we implement a crawler to mine the information of completed development tasks from the TopCoder platform to inspect the proposed measures. The promising results of our QRD, QC, and QS measures suggest to use the proposed measures to the requesters and researchers of other domains such as pharmaceutical research and development, in order to investigate and predict the quality of crowdsourcing-based software development platforms.
      PubDate: 2018-04-20
      DOI: 10.1007/s10588-018-9269-5
       
  • XM-tree: data driven computational model by using metric extended nodes
           with non-overlapping in high-dimensional metric spaces
    • Authors: Zineddine Kouahla; Adeel Anjum; Sheeraz Akram; Tanzila Saba; José Martinez
      Abstract: Finding similar objects based on a query and a distance, remains a fundamental problem for many applications. The general problem of many similarity measures is to focus the search on as few elements as possible to find the answer. The index structures divides the target dataset into subsets. With large amounts of data, the volumes of the subspaces grow exponentially, that will affect the search algorithms. This problem is caused by inherent deficiencies of space partitioning, and also, the overlap factor between regions. This methods have proven to be unreliable, it becomes hard to store, manage, and analyze these quantities. The research tends to degenerate into a complete analysis of the data set. In this paper, we propose a new indexing technique called XM-tree, that partitions the space using spheres. The idea is to combine two structures, arborescent and sequential, in order to limit the volume of the outer regions of the spheres, by creating extended regions and inserting them into linked lists named extended regions, and also by excluding of the empty sets—separable partitions—that do not contain objects. The goal is to eliminate some objects without the need to compute their relative distances to a query object. Therefore, we proposed a parallel version of the structure on a set of real machine. We also discuss the efficiency of the construction and querying phases, and the quality of our index by comparing it with recent techniques.
      PubDate: 2018-04-18
      DOI: 10.1007/s10588-018-9272-x
       
  • Ligature categorization based Nastaliq Urdu recognition using deep neural
           networks
    • Authors: Muhammad Jawad Rafeeq; Zia ur Rehman; Ahmad Khan; Iftikhar Ahmed Khan; Waqas Jadoon
      Abstract: The cursive nature, Nastaliq writing style and a large number of different ligatures make ligature recognition very difficult in Urdu. In this paper, we present a segmentation-free approach to holistically recognize Urdu ligatures. We first generate a rich dataset which contains 17,010 ligatures with different orientation and different degrees of noise. Secondly, the ligatures are clustered (categorized) in order to reduce the search space and make the learning robust. Finally, we employ a deep neural network with dropout regularization to classify ligatures. The detailed experiments show that a deep neural network with dropout regularization and clustering of ligatures significantly enhances the classification accuracy.
      PubDate: 2018-04-16
      DOI: 10.1007/s10588-018-9271-y
       
  • Individual knowledge management engagement, knowledge-worker productivity,
           and innovation performance in knowledge-based organizations: the
           implications for knowledge processes and knowledge-based systems
    • Authors: Muhammad Ali Butt; Faisal Nawaz; Saddam Hussain; Maria José Sousa; Minhong Wang; Muhammad Saleem Sumbal; Muhammad Shujahat
      Abstract: The literature on the knowledge management relatively ignores an important concept, the individual knowledge management engagement-the degree to which a knowledge worker is involved with the knowledge management-related activities. This concept is imperative for nurturing the productivity of knowledge workers, knowledge management architecture effectiveness, and innovation. Therefore, this study proposes the mediating role of knowledge-worker productivity between individual knowledge management engagement and innovation. The data were collected from the 330 knowledge workers of IT sector of Pakistan and analyzed using the SmartPLS 3 Version 2.6. The results indicate the partial mediation of knowledge-worker productivity between the individual knowledge management engagement and innovation. The results suggest the pivotal role of individual knowledge management engagement in increasing the innovation and knowledge-worker productivity in the knowledge-based organizations.
      PubDate: 2018-04-05
      DOI: 10.1007/s10588-018-9270-z
       
  • Process mining of a multi-agent business simulator
    • Authors: Sohei Ito; Dominik Vymětal; Roman Šperka; Michal Halaška
      Abstract: A multi-agent system is a useful modeling architecture in business process modeling in the sense that we can naturally implement participants in a real company with software agents. However, analyzing and interpreting the simulation results of multi-agent models tends to be difficult due to the inherent complexity of the models. In this regard, another discipline—process mining—is useful for such purposes because it has demonstrated its usefulness in analyzing real processes. In this article, our aim is to combine these two disciplines for exploitation in business process modeling and simulation; we extend a multi-agent-based business simulator named Multi-Agent system with Resource-Event-Agent ontology (MAREA) to be able to be analyzed by means of process mining techniques. To this end, we formalize the abstract multi-agent architecture of MAREA and establish its relationship to process mining by defining how execution of a multi-agent system can be recorded as an event log, which is later analyzed by process mining techniques. Based on this definition, we implement functionality to extract event logs from simulation runs in MAREA. For demonstration, we implement a model of a generic trading company in MAREA and perform process structure verification and social network analyzes by means of process mining techniques.
      PubDate: 2018-04-04
      DOI: 10.1007/s10588-018-9268-6
       
  • Mathematical model based traffic violations identification
    • Authors: Fozia Mehboob; Muhammad Abbas; Abdul Rauf
      Abstract: Traffic rules violations and accidents on road are major issues now-a-days. Identification of vehicles violating traffic rules and manual monitoring of vehicles is difficult, due to traffic congestion on freeways. A novel mathematical model is proposed to generalize detection of a number of traffic violations on highways. The model, using image processing techniques translates lanes on the road as equation of lines. A tracking algorithm generates a vehicle trace which is modelled as equations. A piecewise linearity is used for the modelling and ease of computation of traffic violation. The model then solves a number of equations for finding intersection of traces with the traffic lanes to identify the violations. This novel modelling approach can help machine based identification of a number of traffic violations and proposed system need not to be installed in vehicles and all along road for violation detection. To cover larger length of the road, camera handoff algorithm is also designed. This technique keeps track of all vehicles along with their traces on Google maps.
      PubDate: 2018-03-20
      DOI: 10.1007/s10588-018-9264-x
       
  • Meta features-based scale invariant OCR decision making using LSTM-RNN
    • Authors: Asma Naseer; Kashif Zafar
      Abstract: Urdu optical character recognition (OCR) is a complex problem due to the nature of its script, which is cursive. Recognizing characters of different font sizes further complicates the problem. In this research, long short term memory-recurrent neural network (LSTM-RNN) and convolution neural network (CNN) are used to recognize Urdu optical characters of different font sizes. LSTM-RNN is trained on formerly extracted feature sets, which are extracted for scale invariant recognition of Urdu characters. From these features, LSTM-RNN extracts meta features. CNN is trained on raw binary images. Two benchmark datasets, i.e. centre for language engineering text images (CLETI) and Urdu printed text images (UPTI) are used. LSTM-RNN reveals consistent results on both datasets, and outperforms CNN. Maximum 99% accuracy is achieved using LSTM-RNN.
      PubDate: 2018-03-20
      DOI: 10.1007/s10588-018-9265-9
       
  • Measuring and monitoring diversity in organizations through functional
           instruments with an application to ethnic workforce diversity of the U.S.
           Federal Agencies
    • Authors: Fabrizio Maturo; Stefania Migliori; Francesco Paolone
      Abstract: The role of diversity in organizations has been widely discussed in recent decades; nevertheless, both theoretical perspectives and empirical results appear conflicting and inconsistent. Scholars identify many possible reasons such as the definition of diversity, theoretical perspectives, variables, and methodological approaches; this study focuses on the methodological issue of assessing variety. To evaluate the role of diversity, most studies adopt static approaches and refer to the classical univariate indices; this research shows their limitations and stresses the importance of treating diversity with a multivariate dynamic approach. Taking advantage of functional data analysis and some recent ecological studies, this dual gap of the organizational literature is addressed by proposing a new methodological approach for measuring and monitoring diversity in organizations. We illustrate an application of this method by using a real dataset concerning the workforce diversity of the “Corporation For National And Community Service Overview” within the project “Federal Equal Opportunity Recruitment Program (FEORP)” of the Government of the United States of America. The goal of this research is to provide human resources specialists, policy makers, and scholars with additional techniques to improve the understanding of the dynamics of workforce diversity and minority employment within organizations.
      PubDate: 2018-03-17
      DOI: 10.1007/s10588-018-9267-7
       
  • The impact of preprocessing steps on the accuracy of machine learning
           algorithms in sentiment analysis
    • Authors: Saqib Alam; Nianmin Yao
      Abstract: Big data and its related technologies have become active areas of research recently. There is a huge amount of data generated every minute and second that includes unstructured data which is the topic of interest for researchers now a days. A lot of research work is currently going on in the areas of text analytics and text preprocessing. In this paper, we have studied the impact of different preprocessing steps on the accuracy of three machine learning algorithms for sentiment analysis. We applied different text preprocessing techniques and studied their impact on accuracy for sentiment classification using three well-known machine learning classifiers including Naïve Bayes (NB), maximum entropy (MaxE), and support vector machines (SVM). We calculated accuracy of the three machine learning algorithms before and after applying the preprocessing steps. Results proved that the accuracy of NB algorithm was significantly improved after applying the preprocessing steps. Slight improvement in accuracy of SVM algorithm was seen after applying the preprocessing steps. Interestingly, in case of MaxE algorithm, no improvement in accuracy was seen. Our work is a comparative study, and our results proved that in case of NB algorithm, actuary was again significantly high than any other machine learning algorithm after applying the preprocessing steps; followed by MaxE and SVM algorithms. This research work proves that text preprocessing impacts the accuracy of machine learning algorithms. It further concludes that in case of NB algorithm, accuracy has significantly improved after applying text preprocessing steps.
      PubDate: 2018-03-16
      DOI: 10.1007/s10588-018-9266-8
       
 
 
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