2018 6th International Symposium on Computational and Business Intelligence (ISCBI)

27-29 Aug. 2018

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  • [Title page i]

    Publication Year: 2018, Page(s): 1
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  • [Title page iii]

    Publication Year: 2018, Page(s): 3
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  • [Copyright notice]

    Publication Year: 2018, Page(s): 4
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  • Table of contents

    Publication Year: 2018, Page(s):5 - 7
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  • Welcome Message

    Publication Year: 2018, Page(s): 8
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  • Conference Committees

    Publication Year: 2018, Page(s): 9
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  • International Program Committee

    Publication Year: 2018, Page(s): 10
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  • Reviewers

    Publication Year: 2018, Page(s): 11
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  • Keynote Speakers

    Publication Year: 2018, Page(s):12 - 15
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (126 KB)

    We present a constructive preference learning methodology, called Robust Ordinal Regression, for Multiple Criteria Decision Aiding. Identification of Decision Maker's (DM's) preferences is a crucial step in decision aiding. It is known that the dominance relation established in the set of alternatives evaluated on multiple criteria is the only objective information that comes from the formulation ... View full abstract»

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  • Invited Speaker

    Publication Year: 2018, Page(s):16 - 17
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    Previous studies on knowledge management have centered on investigating the relationship between knowledge management and organizational performance, thus reinforcing the importance of managing knowledge in organizations. Despite this, previous research has not explicitly considered the linkage between knowledge management and manufacturing performance. In addition, a prediction model for manufact... View full abstract»

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  • Optimality in Vector Spaces

    Publication Year: 2018, Page(s):1 - 4
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (196 KB) | HTML iconHTML

    This research work is devoted to the general Optimaliy presented inside the best appropriate environment of the Infinite Dimensional Ordered Vector Spaces, with its natural projections in the Vectorial Optimization. It is also a short but original scientific Survey on the Efficiency by the Optimality and conversely, in the most general context of the Ordered Vector Spaces, the foundations for the ... View full abstract»

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  • Time and Cost Dependent TSP Problem: An Experimentation System for the Practical Users

    Publication Year: 2018, Page(s):5 - 9
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (374 KB) | HTML iconHTML

    The paper presents various approaches to finding the optimal solution for a problem, which is an extension of the classical travelling salesmen problem (TSP). The problem consists in choosing the route between two distinct towns: starting and target, when there are available not only free standard roads but toll highway, either. The four variants of the problem and three heuristic algorithms solvi... View full abstract»

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  • Gig Work Business Process Improvement

    Publication Year: 2018, Page(s):10 - 15
    Cited by:  Papers (1)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (309 KB) | HTML iconHTML

    We collaborate with a gig work platform company (GPC) in Switzerland. The project aims to improve the business by influencing process management within the GPC, providing automated matching of jobs to workers, improving worker acquisition and worker commitment, and particularly focusing on the prevention of no shows. One expects to achieve financial, organizational and efficiency gains. As researc... View full abstract»

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  • Pathfinding Optimization when Solving the Paparazzi Problem Comparing A* and Dijkstra's Algorithm

    Publication Year: 2018, Page(s):16 - 22
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (437 KB) | HTML iconHTML

    This paper aims to compare the application of the A* algorithm and Dijkstra's algorithm to solve a particular variant of pathfinding problem based on the so-called paparazzi problem. The problem consists of a grid with different fixed obstacles, leading to different traversing time factors respectively costs. A specific model of this problem is derived and the performance of these two pathfinding ... View full abstract»

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  • Bottleneck Identification of Extended Flexible Job Shop Scheduling Problem

    Publication Year: 2018, Page(s):23 - 27
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (310 KB) | HTML iconHTML

    The following topics are dealt with: optimisation; Internet; social networking (online); learning (artificial intelligence); production engineering computing; crowdsourcing; sentiment analysis; knowledge management; organisational aspects; neural nets. View full abstract»

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  • A Novel Virtual Machine Selection Policy for Virtual Machine Consolidation

    Publication Year: 2018, Page(s):28 - 32
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (203 KB) | HTML iconHTML

    Cloud computing has been focused by a wide range of researches and organizational considerations. One of the most important challenges in this area is to reduce the energy consumption of cloud data centers. Virtualization, which is one of the key features of the machine consolidation technique, is a major step to improve the energy consumption and resource management in this area. Selection of app... View full abstract»

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  • Mathematical Modeling and Process Optimization of the Radial Continuous Casting of Steel

    Publication Year: 2018, Page(s):33 - 40
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (362 KB) | HTML iconHTML

    In this study, an analysis and synthesis methodology for complex engineering problems is applied to radial continuous casting processes for steel (SRCCI). The quality of the operations of the respective machines significantly influences the production cost because an uninterrupted sequence of casting allows reducing the losses of materials and influences the energy consumption in the casting proce... View full abstract»

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  • Automatic Tuning Methodology for Automotive Lean NOx Trap Catalyst Using Response Data

    Publication Year: 2018, Page(s):41 - 47
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    This article provides an overview of the Lean NOx trap (LNT) catalysts' operating mechanism and proposes a method for auto-tuning the LNT model using response data. LNT catalysts are used in automotive applications to reduce NOx emissions from diesel engines, or lean-burn engines in general. The LNT catalyst is a complex nonlinear chemical system designed for cyclic operations, which can be very d... View full abstract»

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  • Comparison of BPA-MLP and LSTM-RNN for Stocks Prediction

    Publication Year: 2018, Page(s):48 - 51
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (382 KB) | HTML iconHTML

    Neural networks is considered one of the most developed concept in artificial intelligence, due to its ability to solve complex computational tasks, and its efficiency to find solutions. There is a wide range of applications that adopt this technique, one of which is in the financial investment issues. This paper presents an approach to predict stock market ratios using artificial neural networks.... View full abstract»

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  • Autoeoncoders and Information Augmentation for Improved Generalization and Interpretation in Multi-layered Neural Networks

    Publication Year: 2018, Page(s):52 - 58
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (198 KB) | HTML iconHTML

    The present paper aims to propose a new type of learning method for multi-layered neural network to solve the vanishing information problem. The vanishing information problem means that multi-layered neural networks tend to lose their error information as well as input information by going through many hidden layers. To overcome this problem, the new method tries to capture information in inputs a... View full abstract»

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  • Support Vector Machine for Demand Forecasting of Canadian Armed Forces Spare Parts

    Publication Year: 2018, Page(s):59 - 64
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (327 KB) | HTML iconHTML

    The need to reduce inventory costs and increase system operational availability is the main motivation behind improving forecast accuracy of military spare parts demand. In this paper, we assess the potential of Support Vector Machine (SVM) approach for forecasting the demand of Canadian Armed Forces (CAF) spare parts and we introduce a forecasting evaluation method using inventory cost performanc... View full abstract»

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  • Farsi Handwriting Digit Recognition Based on Convolutional Neural Networks

    Publication Year: 2018, Page(s):65 - 68
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    In this paper, a convolutional neural network (CNN) is exploited for Farsi handwritten digit recognition. For training and evaluating the CNN, the "HODA" dataset was used which consists of 80000 images of Farsi handwritten digits. In the proposed method, we focused on the efficient and unique feature of Farsi digits that is using just the half upper part of the digits for recognition purpose. The ... View full abstract»

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  • A Network Root Cause Analysis and Repair System

    Publication Year: 2018, Page(s):69 - 73
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    Recently, Internet and computer networks are important infrastructures for businesses and must be reliable in order to serve customers or employees to do online transactions. However, network problems can be occurred, and must be solved as soon as possible. Time to analyze and solve network problems is varied depending on a network administrator's experience. This can be a challenge for a novice n... View full abstract»

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  • Link Predictability Analysis of US Political Blog Network with Structural Perturbation Method

    Publication Year: 2018, Page(s):74 - 78
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (341 KB) | HTML iconHTML

    Many link prediction methods have been developed in past few decades in network science, and most of them are tailored for specific fields that lose generalities. Luckily, a recent work named Structural Perturbation Method (SPM) proposed a consistency index of network organization without priori knowledge, and it did not need to test those predicting methods first. Since demonstrating whether ther... View full abstract»

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  • Evaluation of the Dirichlet Process Multinomial Mixture Model for Short-Text Topic Modeling

    Publication Year: 2018, Page(s):79 - 83
    Cited by:  Papers (1)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (135 KB) | HTML iconHTML

    Fast-moving trends, both in society and in highly competitive business areas, call for effective methods for automatic analysis. The availability of fast-moving sources in the form of short texts, such as social media and blogs, allows aggregation from a vast number of text sources, for an up to date view of trends and business insights. Topic modeling is established as an approach for analysis of... View full abstract»

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