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Predictive Process Mining a Systematic Literature Review 12th

Predictive Process Mining a Systematic Literature Review

引用

12th World Conference on Information systems and Technologies (WorldCIST)

作者： Silva, Eduardo Marreiros, Goreti Polytech Porto Inst Engn Porto Portugal Polytech Porto Res Grp Intelligent Engn & Comp Adv Innovat & Dev Porto Portugal

ISBN: (纸本)9783031602207;9783031602214

As business process complexity reaches an all-time high, the competitive and rapidly changing environments where organisations operate created the need for business processes to be continuously analysed, improved, and supported by adequate tools and techniques, which led to the conception of Process Mining (PM). Recently, Predictive Process Mining (PPM) emerged as a novel field that integrates PM with predictive techniques, such as Machine Learning, allowing the future behaviour of ongoing processes to be predicted and actions to be taken to steer them in favour of business interests. This allows PM to evolve from a reactive to a proactive tool for process enhancement, which helps reduce costs, time, and necessary resources. Nevertheless, the impact and value of PPM remain mostly unproven and the number of related studies is relatively low. A systematic review has therefore been elaborated to support future studies, based on a search carried out in three databases and according to the PRISMA statement. This review aims to identify the methods and techniques used in the implementation of PPM use cases and to understand the perceived business impact and value. In total, 411 articles were initially identified, with 24 meeting the defined criteria and being selected for discussion. From these articles, next-event, outcome, and suffix prediction have been identified as the most common use cases of PPM, in addition to the predictive techniques (e.g. XGBoost, LSTM, BERT, GAN) and optimisation methods (e.g. trace bucketing) being applied in their development. Finally, although limited, the perceived impact and value of PPM in organisations have been recorded, according to stakeholders actively using PPM in their daily work.

关键词： Process Mining Business Processes Process Enhancement Predictive Techniques Machine Learning Deep Learning

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Topologized Graphical Method in Solving Fuzzy Transportation Problem with Computational Techniques

Topologized Graphical Method in Solving Fuzzy Transportation...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Kungumaraj, E. Anand, M. Clement Joe Saikia, Utpal Dabass, Vandana Ranjitha, B. Tiwari, Mohit Nehru Inst Engn & Technol Dept Sci & Humanities Coimbatore 641105 Tamil Nadu India Mt Carmel Coll Autonomous Dept Math Bengaluru 560052 Karnataka India Silapathar Coll Dept Math Dhemaji 787059 Assam India Inst Innovat Technol & Management Dept Comp Sci Delhi 110058 India Mohan Babu Univ Dept Math Tirupati 517501 Andhra Pradesh India Bharati Vidyapeeths Coll Engn Dept Comp Sci & Engn Delhi 110063 India

ISBN: (纸本)9783031671913;9783031671920

The fuzzy transportation problem (FTP) is a well-known upgrading problem that transactions with the allocation of goods from a set of sources to a set of destinations, considering imprecise or uncertain parameters. This article targets a novel approach called the topologized graphical method for solving FTP. The method integrates concepts from topology and graphical techniques to provide an effective and intuitive solution procedure. The proposed topologized graphical method (TGM) begins by representing the FTP as a graph, where nodes represent sources, destinations, and intermediate points, and edges represent the transportation routes. The imprecise or uncertain parameters of the problem, such as supply, demand, and transportation costs, are modeled as fuzzy numbers (FN). The planned technique is illustrated with numerical examples to demonstrate its effectiveness and applicability. The results attained from the TGM are associated with existing approaches, and it is revealed that the proposed method provides efficient solutions while maintaining inter predictability and transparency in the decision-making process.

关键词： Fuzzy Transportation Problem Topologized Graphical Method Topologized Graph python

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Parallelization Algorithm for the Calculation of Typical Testors Based on YYC 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Soria-Salgado, Ariana Ibarra-Fiallo, Julio Alba-Cabrera, Eduardo Univ San Francisco Quito Colegio Ciencias & Ingn Cumbaya Ecuador

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

In the present work, a new method is proposed to find typical testors, which helps reduce the number of features needed to carry out classification processes. Using the strategy of divide and conquer, we divide a basic matrix into blocks, then we find the typical testors of the defined blocks. To find the typical testors of the complete basic matrix, unions between the elements of these sets obtained from the blocks are tested. A criterion is developed to determine when the unions of typical testors of blocks form typical testors of the complete matrix. The performance of the method is evaluated using synthetic matrices. The execution time of the method in parallel and sequential versions was compared and contrasted with the YYC algorithm used for the complete basic matrix. Finally, its performance is analyzed in a real database obtained from the UCI Repository.

关键词： pattern recognition classification typical testors neural networks accuracy computational efficiency time execution

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Robust Sliding Mode Based on Partial Feedback Linearization Control for Underactuated Robot Manipulator 4th

Robust Sliding Mode Based on Partial Feedback Linearization ...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Cheikh, Imane Faqihi, Hachmia Benbrahim, Mohammed Kabbaj, Mohammed Nabil Sidi Mohammed Ben Abdellah Univ Fac Sci LIMAS Lab Fes Morocco Ibn Tofail Univ SETIME Lab Kenitra Morocco

ISBN: (纸本)9783031686740;9783031686757

In several sectors, manipulator robots are extensively employed to perform various repetitive or dangerous tasks. On the other side of the coin, those robot arms are embedded with controlled actuators which one or more of them may fail and cause accidents in the workspace environment. In consequence, the system becomes underactuated having active and passive joints. In this case, the controller is no longer working adequately and it must be changed to be suitable for underactuated robots. As a result, there are two different cases;The first one consists of engaging the brakes of the passive joint when the fault appears in order to maintain its position at a fixed one. And the second one is when the brakes aren't engaged and the passive joint rotates freely. For this purpose, a robust fault-tolerant method is designed by merging the Sliding Mode Control and the Partial Feedback Linearization Control to track a desired trajectory using an underactuated manipulator with a free or fixed defective joint actuator. Afterwards, a robot with a fourth passive joint was subjected to a co-simulation study conducted in Gazebo applying the proposed control method which was programmed using Matlab&Simulink.

关键词： Underactuated Manipulator Passive Joint Partial Feedback Linearization Control Sliding Mode Control Time-varying Boundary Layer Gazebo

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Cognitive Computing in the Travel and Tourism Industry 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Guarda, Teresa Lopes, Isabel Fernandes, Paula Odete Univ Estatal Peninsula Santa Elena La Libertad Ecuador Univ Estatal Peninsula Santa Elena CIST Ctr Invest Sistemas & Telecomunicac La Libertad Ecuador Minho Univ Algoritmi Ctr Guimaraes Portugal Inst Politecn Braganya IPB Appl Management Res Unit UNIAG P-5300253 Braganca Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

Cognitive computing emerged from a mixture of cognitive science and computer science. Although cognitive computing is seen as a challenge for companies, it is an opportunity that raises the bar for the services provided, allowing companies that are committed to investing in innovation, and in this particular case in the travel and tourism sector, being able to stand out from the competition by adopting new technologies that make it possible to offer revolutionary and value-added experiences. Whether optimizing processes or developing new services, this technology is the key to innovation and competitiveness in the travel and tourism sector. With the user's history and previous search data, cognitive systems, even before the user realizes it, present specific options according to their profile\preferences. In this sense, the system has the ability to automatically restrict the entire travel package. The main objective of this work is to explore the area of Cognitive computing in the context of Travel and Tourism Industry.

关键词： Cognitive computing Travel and Tourism Industry Natural Language Processing Artificial Intelligence

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An Overview of Generative Models for EEG Signal Processing 5th

An Overview of Generative Models for EEG Signal Processing

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5th International Conference on Communication and Intelligent systems (ICCIS)

作者： Belkar, Tanisha Bajpai, Vikas LNM Inst Informat Technol Jaipur 302031 Rajasthan India

ISBN: (纸本)9789819720811;9789819720828

In medical science, EEG data is often analyzed by doctors to detect diseases and to observe brain activity under stimuli. Over the years, researchers have attempted to use machine learning algorithms for the classification and analysis of EEG signals. This paper is a study of different methods, ranging from machine learning to deep learning that have been used for EEG signal processing.

关键词： EEG signals Deep learning Classification Processing Normalizing flows

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Optimization of Agrivoltaic Plants: Development and Validation of a Numerical Model to Account for Shading Effects on Crop Yields 1

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Intelligent systems Conference (IntelliSys)

作者： Costa, Michela Barba, Stefano Piazzullo, Daniele Palombo, Adolfo CNR Ist Sci & Tecnol Energia & Mobilita Sostenibili S Via Marconi 4 Naples Italy DG Twin Srl Campania NewSteel Via Coroglio 57d27 I-80124 Naples Italy Univ Naples Federico II Dept Agr Sci Naples Italy Univ Naples Federico II Dept Ind Engn Naples Italy

ISBN: (数字)9783031477157

ISBN: (纸本)9783031477140;9783031477157

Agrivoltaic systems are becoming increasingly popular as a relevant technology for the achievement of sustainable development goals, such as clean energy and mitigation of climate changes, by providing a significant economic advantage for farms. Understanding the effects of shading on crops is crucial for the selection of an optimal agrivoltaic system able to guarantee minimum loss in agricultural yields. In this study, an innovative numerical procedure is proposed for the evaluation of the dynamic performances of agrivoltaic plants with different configurations: fixed vertical structure, fixed with modules inclined by 30 degrees and tracking on a single axis. A parametric analysis is conducted to determine the optimal solution from the techno-economic point of view when serving a farm operating in the South of Italy. The three solutions are optimized by varying the size of the storage system in such a way to minimize the investment cost and maximize savings (and self-consumed energy). An innovative aspect of the present work is represented by the evaluation of the shading influence of the PV panels on the underlying crops. This influence is determined by developing an in-house numerical model capable of evaluating the shadows casted on the ground, once the geometry of the structure is defined, and the consequent reduction of incident radiation on the ground with the relative change in crop yield. The results in terms of incident radiation reduction showed an accuracy very similar to that evaluated through the commercial PVsyst (R) software. The solution emerged as optimal after the study is the plant configuration exhibiting a one-axis tracking system.

关键词： Numerical model Agrivoltaic systems Photovoltaic Shadings Crop yields

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PLC-Based Traffic Light Control for Flexible Testing of Automated Mobility 9th

PLC-Based Traffic Light Control for Flexible Testing of Auto...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Wagner, Tamas Tettamanti, Tamas Varga, Balazs Varga, Istvan Budapest Univ Technol & Econ Dept Control Transportat & Vehicle Syst Fac Transportat Engn & Vehicle Engn Muegyetem rkp. 3 H-1111 Budapest Hungary

ISBN: (纸本)9789819745807;9789819745814

Road infrastructure has evolved to meet diverse needs over time. This makes modernizing traffic control systems also necessary in order to keep pace with technological innovations and changing user habits. This paper presents a novel design and implementation strategy for the next generation of traffic control systems, with particular emphasis on the challenges posed by the integration of automated vehicles. General flexibility in future traffic management, proper use of standardized communication protocols, and safety solutions are essential factors in addressing the traffic challenges of the coming decades. The system has been developed primarily for PLCs (Programmable Logic Controllers) and has been tested and verified, providing the advantages of safety elements and software safety solutions. The proposed system demonstrated efficient and reliable performance while the applied OPC UA (Open Platform Communications Unified Architecture) communication protocol assured robustness and secure client-to-PLC communication.

关键词： PLC Traffic light controller CCAM Automated vehicles OPC UA

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Soft Robots for On-Orbit Servicing (OOS) Missions 6th

Soft Robots for On-Orbit Servicing (OOS) Missions

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6th International Conference Mechatronics - Ideas for Industrial Applications

作者： Gao, Xiaoqian Hyla, Bartosz Uhl, Tadeusz AGH Univ Krakow Fac Mech Engn & Robot Dept Robot & Mechatron Al A Mickiewicza 30 PL-30059 Krakow Poland

ISBN: (纸本)9783031634437;9783031634444

In response to the escalating demand for space exploration, the potential of space robots has gained significant attention. Within the realm of on-orbit servicing, the development of on-orbit robotic capabilities dedicated to the mission such as servicing of satellite, orbital debris removal, or construction and maintenance of orbital asset exerts a profound and indispensable influence. Cable-actuated continuum arms exhibit superior capabilities over conventional counterparts when grasping uncontrolled CubeSats. This paper introduces a novel continuous arm space robot design, dedicated to the dual tasks of satellite docking and maintenance, facilitated through the collaborative efforts of multiple arms. The Constant Curvature model (PCC) method is employed to formulate the kinematic model, while dynamic modeling utilizes Lumped Parameter methods and Simulink Multibody methods, and the robot workspace is analyzed. In the final section of the paper, potential areas for future research directions and further research are discussed.

关键词： On Orbit Serving Continuous Arm Space Robot CubeSat Multiple Arms

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Modelling Stock Prices Prediction with Long Short-Term Memory (LSTM): A Black Box Approach 1

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International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Bokhare, Anuja Rao, Madhuri Oliver, M. Pavie Rai, Rohit Adesara, Umang Symbiosis Int Deemed Univ Symbiosis Inst Comp Studies & Res Pune Maharashtra India Dr Vishwanath Karad MIT World Peace Univ Sch Comp Sci Engn & Technol Pune Maharashtra India

ISBN: (数字)9789819984763

ISBN: (纸本)9789819984756;9789819984763

A major requirement for small, medium or large investment firms is to be able to invest in the right stock and attain profitable growth. Giant firms use machine learning intelligence to maintain their competitive edge over the others by trying to predict the next profitable stock precisely. Stock price forecasting is a crucial part of these businesses, and this brings up the research questions such as, what will be the next price of the stock? Does the company need to short the stock? Is long-term holding the best approach at the moment? How to cut losses? Among its many benefits, predictive forecast is a key enabler for a better stock investment model. This research paper introspects on various key aspects of the Long Short-Term Memory (LSTM), a deep learning algorithm which focuses on Recurrent Neural networks (RNNs) and is a black box approach that is apt for predicting stock prices. The paper evaluates the performance of the proposed model and aims to explain the complexity of the system and the need to move towards grey box approach for better comprehension.

关键词： Stock prices prediction Machine learning LSTM Statistical modelling RNN Black box

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