![](/events_files/441/Banner3a IOCA 2021 hero.jpg?1725173886)
The 1st Online Conference on Algorithms
27 Sep–10 Oct 2021
Database Algorithms, Data Structures, Combinatorial Optimization, Evolutionary Algorithms, Randomized Approximation, Online Algorithms, Complexity Theory, Algorithm Engineering, Parallel Algorithms
- Go to the Webinar
- Go to the Sessions
-
- A. Databases and Data Structures
- B. Combinatorial Optimization, Graph and Network Algorithms
- C. Evolutionary Algorithms and Machine Learning
- D. Parallel and Distributed Algorithms
- E. Randomized, Online and Approximation Algorithms
- F. Analysis of Algorithms and Complexity Theory
- G. Algorithms for Multidisciplinary Applications
- H. Artificial Intelligence Algorithms
- Event Details
-
- Best Paper Award Winners Annoucement
- Welcome from the Chair
- IOCA 2021 | Live Session
- Conference Chairs
- Conference Committee
- Session Chairs
- Program Committee
- Sessions
- Event Calls
- Conference Speakers
- List of Keynotes & Videos from Invited Speakers
- Instructions for Authors
- List of Video Submissions from Authors
- List of Accepted Submissions
- Event Awards
- Sponsors and Partners
- Conference Secretariat
Best Paper Award Winners Annoucement
The 1st International Electronic Conference on Algorithms (IOCA 2021) established the Best Paper Awards to acknowledge the support of the conference participants and to recognize their outstanding scientific accomplishments. Nominated candidates are selected by the committees based on the rigor of their science, the significance of their contribution to the field, and the originality of their work. The Best Paper Award winners are as follows:
Title: Quickest transshipment in an integrated network topology
by Iswar Mani Adhikari, Tanka Nath Dhamala
https://sciforum.net/paper/view/conference/10879
Title: A Hybrid Deep Learning Approach for COVID-19 Diagnosis via CT and X-Ray Medical Images
by Pramodha M, Abullah Y Muaad, Benifa Bibal J. V., Hanumanthappa J., Channabasava Chola, Mugahed A Al-antari
https://sciforum.net/paper/view/conference/10909
Each winner will receive a cash award of CHF 250 and an award certification. We look forward to posting your contributions.
Kind regards,
Frank Werner
Welcome from the Chair
Dear colleagues,
It is my pleasure to invite you to participate in the 1st International Online Conference on Algorithms (IOCA 2021). Since the global pandemic has forced us to reduce our mobility, this event will occur completely online at https://ioca2021.sciforum.net/ between September 27 and October 10, 2021.
IOCA 2021 aims to promote and advance all disciplines of the development of algorithms, a field that is rapidly growing. Both theoretical and application works are welcome. The conference will bring together impressive researchers and practitioners currently working in the area of the design and analysis of algorithms and their latest results will be presented. Subjects of interest include, but are not limited to:
- Databases and Data Structures;
- Combinatorial Optimization, Graph and Network Algorithms;
- Evolutionary Algorithms and Machine Learning;
- Parallel and Distributed Algorithms;
- Randomized, Online and Approximation Algorithms;
- Analysis of Algorithms and Complexity Theory;
- Algorithms for Multidisciplinary Applications.
Submitted abstracts will be reviewed by the conference committee. The authors of the accepted contributions will be invited to prepare an extended abstract for the conference proceedings, as well as a slide presentation of their work. IOCA 2021 will make your presentation accessible to hundreds of researchers worldwide. Participants will also be invited to submit an extended version for publication in the journal Algorithms, published by MDPI, after the conference is over.
I am looking forward to receiving many submissions of your recent work in the field of algorithms and I hope that you will join us in this exciting new form of conference.
If you need extension after the abstract deadline, please feel free to contact us.
Kind regards,
Frank Werner
Chair of the 1st International Online Conference on Algorithms
IOCA 2021 | Live Session
Welcome! You are invited to join a webinar: IOCA 2021 | Live Session. This FREE webinar was held on 7 October 2021 at 12:00pm CEST. The recording of the live session can be found below.
Speakers
Prof. Dr. Alberto Pinto |
Mathematics Department, Faculty of Sciences, University of Porto, Praça de Gomes Teixeira, Porto, Portugal Research Keywords |
Dr. Pietro Oliveto |
Department of Computer Science, The University of Sheffield, Regent Court, Portobello, Sheffield, UK Research Keywords |
Prof. Dr. Bruce Watson |
FASTAR Group, Information Science Department, Stellenbosch University, Stellenbosch, South Africa Research Keywords |
Program
Speaker/Presentation |
Time in CEST |
Prof. Dr. Alberto Pinto |
12:00 - 12:30 pm |
Dr. Pietro Oliveto |
12:30 - 13:00 pm |
Prof. Dr. Bruce Watson |
13:00 - 13:30 pm |
Recording
Conference Chair
![](/events_files/441/committee/3be9dd2fc0eb35f08f74748e440a7415.jpeg?1725173886)
Faculty of Mathematics, Otto-von-Guericke-University, P.O. Box 4120, D-39016 Magdeburg, Germany
Website
frank.werner@mathematik.uni-magdeburg.de
Conference Committee
![](/events_files/441/committee/2e3243e52e386770e16011cdb454405e.jpeg?1725173886)
Prof. Dr. Qianping Gu
School of Computing Science, Simon Fraser University, Burnaby, Canada
graph algorithms; tree-/branch-decompositions of graphs; routing algorithms
Session B: Combinatorial Optimization, Graph and Network Algorithms
![](/events_files/441/committee/78cfa62fb37a9695a6448f0d6ec82f44.png?1725173886)
Prof. Dr. Bogdan Dumitrescu
Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Bucuresti, Romania
numerical methods; signal processing; optimization; sparse representations
Session G: Algorithms for Multidisciplinary Applications
![](/events_files/441/committee/036f0034d57f6e7ec2df22c60defb999.png?1725173886)
Dr. Mircea-Bogdan Radac
Department of Automation and Applied Informatica, Politehnica University of Timisoara, Timisoara, Romania
learning systems; control systems and algorithms; data-driven control; model-free control; iterative learning; approximate dynamic programming and reinforcement learning; neuro-fuzzy systems; machine learning; neural networks; optimization
Session G: Algorithms for Multidisciplinary Applications
![](/events_files/441/committee/ba10a72dd9a780cf8afa173af668f89a.jpeg?1725173886)
Dr. Ilya Safro
School of Computing, Clemson University, Clemson, USA
quantum algorithms; machine learning; data mining; graph algorithms; network science; hypothesis generation; text mining; combinatorial scientific computing; multiscale methods; complex systems
Session B: Combinatorial Optimization, Graph and Network Algorithms
![](/events_files/441/committee/375aa00132aa55fa3870b515a1695718.png?1725173886)
Prof. Dr. Christos D. Zaroliagis
Department of Computer Engineering and Informatics, University of Patras, Patras, Greece
innovative algorithmic technology; data-driven and scalable computing; large-scale optimization; intelligent transportation systems and services; decentralized computing; mobility in smart cities; cryptography and information security
Session B: Combinatorial Optimization, Graph and Network Algorithms
![](/events_files/441/committee/aa4d8a810c95281b255e53be3f24a07c.png?1725173886)
Prof. Theodore B. Trafalis
School of Industrial and Systems Engineering, The University of Oklahoma, Norman, USA
operations research/management science; mathematical programming; interior point methods; multiobjective optimization; control theory; computational and algebraic geometry; artificial neural networks; kernel methods; evolutionary programming; global optimization
Session C: Evolutionary Algorithms and Machine Learning
![](/events_files/441/committee/e347110b4ebde48721b53c0410df2924.jpeg?1725173886)
Dr. Sergey Korotov
Department of Computing, Mathematics and Physics, Western Norway University of Applied Sciences, Bergen, Norway
finite element method; mesh generation; computational geometry
Session F: Analysis of Algorithms and Complexity Theory
![](/events_files/441/committee/5ecd1c29ab284589d3504c155746f605.png?1725173886)
Prof. Dr. Vangelis Th. Paschos
Université Paris-Dauphine, PSL Research University, CNRS, UMR 7243 LAMSADE, Paris, France
complexity theory; worst-case complexity of exact algorithms for NP-hard problems; approximation of NP-hard optimization problems; polynomial approximability; moderately exponential; subexponential and parameterized approximation; algorithmics in dynamic environments
Session B: Combinatorial Optimization, Graph and Network Algorithms
![](/events_files/441/committee/e32fe63e1b3b07d0469e879a96756230.jpeg?1725173886)
Prof. Dr. Alicia Cordero Barbero
Department of Applied Mathematics and Institute for Multidisciplinary Mathematics, Universitat Politècnica de València, Valencia, Spain
iterative processes; numerical analysis; dynamic analysis
Session G: Algorithms for Multidisciplinary Applications
![](/events_files/441/committee/97862436343f8f5d5f1d6b5b3e52bd2d.png?1725173886)
Dr. Jesper Jansson
Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
graph algorithms; bioinformatics; computational complexity; data structures
Session F: Analysis of Algorithms and Complexity Theory
Prof. Dr. Hirotaka Ono
Department of Mathematical Informatics, Graduate School of Informatics Nagoya University, Furocho, Chikusa-ku, Nagoya, Japan
Combinatorial Optimization; Algorithmic Game Theory; Approximation; Boolean functions
Session B: Combinatorial Optimization, Graph and Network Algorithms
![](/events_files/441/committee/9477e90acd19fd0e69f83650a3b417f4.jpeg?1725173886)
Dr. Francesc Pozo
Escola d'Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
structural health monitoring; statistics; wind turbines; PCA
Session G: Algorithms for Multidisciplinary Applications
Session Chairs
![](/events_files/441/committee/6819cc54888e3e95e01cf90c26daec73.png?1725173886)
Dr. Stefano Mariani
Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Milano, Italy
stefano.mariani@polimi.it
MEMS; structural sensors; Kalman filtering
Session C: Evolutionary Algorithms and Machine Learning
![](/events_files/441/committee/901a1f91a34fc7a224d41f9735ca181b.jpeg?1725173886)
Prof. Dr. Eugene Levner
Department of Computer Science, Holon Institute of Technology, Holon, Israel
levner@hit.ac.il
computer algorithms; artificial intelligence; operations research
Artificial Intelligence Algorithms
Program Committee
Prof. Dr. Oscar Castillo Computer Science in the Graduate Division, Tijuana Institute of Technology |
Tatiana Tchemisova Department of Mathematics, University of Aveiro |
Dr. Ke-Lin Du Department of Electrical and Computer Engineering, Concordia University |
Dr. Polinpapilinho Katina Informatics and Engineering Systems, University of South Carolina Upstate |
Dr. Jakub Nalepa Faculty of Automatic Control, Electronics and Computer Science / Institute of Computer Science ul. |
Dr. Francisco Cuevas De La Rosa Centro de Investigaciones en Óptica |
Dr. Guangming Zhang Faculty of Engineering and Technology, Liverpool John Moores University |
Dr. Maxim A. Dulebenets Civil & Environmental Engineering |
Dr. Jiajia Li High Performance Computing group, Pacific Northwest National Laboratory (PNNL) |
Dr. Christian Mata Miquel Automatic Control Department (ESAII), Barcelona East School of Engineering (EEBE), Universitat Politècnica de Catalunya (UPC) |
Dr. Gokarna Sharma Department of Computer Science, Kent State University |
Dr. Maria Letizia Guerra Department of Statistical Sciences, University of Bologna |
Dr. Jay Rajasekera Institute of International Strategy (IIS), Tokyo International University
|
Dr. Grzegorz Karoń Silesian University of Technology, Faculty of Transport and Aviation Engineering Department of Transport Systems, Traffic and Logistics Engineering
|
Sessions
B. Combinatorial Optimization, Graph and Network Algorithms
C. Evolutionary Algorithms and Machine Learning
D. Parallel and Distributed Algorithms
E. Randomized, Online and Approximation Algorithms
F. Analysis of Algorithms and Complexity Theory
G. Algorithms for Multidisciplinary Applications
H. Artificial Intelligence Algorithms
Call for Submissions
e-conference, virtual everywhere
The 1st International Online Conference on Algorithms (IOCA 2021) aims to promote and advance all disciplines of the development of algorithms, a field that is rapidly growing. This event will occur completely online from September 27 to October 10, 2021. Both theoretical and application works are welcome. The conference will bring together impressive researchers and practitioners currently working in the area of the design and analysis of algorithms and their latest results will be presented. Subjects of interest include, but are not limited to
- Databases and Data Structures;
- Combinatorial Optimization, Graph and Network Algorithms;
- Evolutionary Algorithms and Machine Learning;
- Parallel and Distributed Algorithms;
- Randomized, Online and Approximation Algorithms;
- Analysis of Algorithms and Complexity Theory;
- Algorithms for Multidisciplinary Applications.
Submitted abstracts will be reviewed by the conference committee. The authors of the accepted contributions will be invited to prepare an extended abstract for the conference proceedings, as well as a slide presentation of their work. IOCA 2021 will make your presentation accessible to hundreds of researchers worldwide. Participants will also be invited to submit an extended version for publication in the journal Algorithms, published by MDPI, after the conference is over.
Critical Dates
Invited Speakers
![](/events_files/441/committee/cc33b5abf88ab02b7d795a2d169033e3.png?1725173886)
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan
computational biology; string and tree algorithms; complex networks
![](/events_files/441/committee/1080b106414cc458e5d08ce328614b85.png?1725173886)
Department of Applied Mathematics and Institute for Multidisciplinary Mathematics (im2) Universitat Politècnica de València, Valencia, Spain
iterative processes; numerical analysis; dynamic analysis
![](/events_files/441/committee/765f4578424ba37a993375e1ff902f43.png?1725173886)
The Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics and Engineering, Brown University, Rhode Island, USA
machine learning for scientific computing (Scientific Machine Learning)
![](/events_files/441/committee/904427a3c1dd9fd452ca73321f577b66.png?1725173886)
Department of Electrical Engineering and Computer Science, Tickle College of Engineering, University of Tennessee, Knoxville, USA
big data analytics; graph theoretical algorithms; life science applications
![](/events_files/441/committee/ee80d16a5eaf25719a6d2920e642437b.jpeg?1725173886)
Mathematics Department, Faculty of Sciences, University of Porto, Praça de Gomes Teixeira, Porto, Portugal
dynamics; game theory; applications of mathematics to biological and social sciences
![](/events_files/441/committee/5d32d264c15bee0daa8b05873bf9dac5.png?1725173886)
theoretical computer science; parameterized complexity; bridging parameterized algorithmics and practice.
![](/events_files/441/committee/071cbb057a29401fb817320742088811.png?1725173886)
Centro de Investigación en Ciencias, Universidad Autónoma del Estado de Morelos, Morelos, Mexico
Centro de Investigación en Ciencias, Universidad Autónoma del Estado de Morelos, Morelos, Mexico
![](/events_files/441/committee/16495b8f2ccc0d3113f836e86056be04.jpeg?1725173886)
FASTAR Group, Information Science Department, Stellenbosch University, Stellenbosch, South Africa
algorithm design; correctness by construction; (network) security; stringology; tree processing; programming language design; compilers
![](/events_files/441/committee/51ce6e9365b9364552646f894855a4a1.png?1725173886)
Department of Computer Science, University of Regina, 3737 Wascana Pkwy, Regina, Canada
algorithmic graph theory; combinatorial optimization; computational geometry
![](/events_files/441/committee/f939032933eb7649cdedfc2048b4fa97.jpeg?1725173886)
Department of Computer Science, The University of Sheffield, Regent Court, Portobello, Sheffield, UK
design and analysis of bio-inspired optimisation algorithms; design and analysis of randomised search heuristics
List of Keynotes & Videos from Invited Speakers
On the Compressive Power of Boolean Threshold Autoencoders
by Prof. Dr. Tatsuya Akutsu
Related Paper: https://sciforum.net/paper/view/10894
Simple Methods for Traveling Salesman Problems
The Parameterized View of Computational Complexity and some Current Horizons
Vectorial Iterative Schemes with Memory for Solving Nonlinear Systems of Equations
by Dr. Ramandeep Behl, Dr. Alicia Cordero, Dr. Juan R. Torregrosa
Related Paper: https://sciforum.net/paper/view/10892
Challenges in the Analysis of Heterogeneous Health Sciences Data
The One-Visibility Cops and Robber Game on Trees
Instructions for Authors
Submissions should be done by the authors online by registering with www.sciforum.net, and using the "Start New Submission" function once logged into system.
- Scholars interested in participating in the conference can submit their abstract (about 200-250 words) online on this website until 20th July 2021.
- The Conference Committee will pre-evaluate, based on the submitted abstract, whether a contribution from the authors of the abstract will be welcome for the 1st International Online Conference on Algorithms. All authors will be notified by 10th August about the acceptance of their abstract.
- If the abstract is accepted for this conference, the author will be invited to prepare a full description of their work (max. 8 pages), or a PowerPoint presentation /poster, by the submission deadline of 7th September 2021.
- The conference proceedings papers and presentations will be available on the conference website for discussion during the time of the conference 27 September–10 October 2021.
- The accepted proceedings papers will probably be published as one dedicated volume in MDPI Computer Sciences & Mathematics Forum (ISSN 2813-0324). Publication of proceedings paper is free of charge.
*Note*
Before publication, Proceedings Series Journals will review accepted papers using the powerful text comparison tool: iThenticate. This procedure aims to prevent scholarly and professional plagiarism.Articles with a high repetition rate and lack of novelty will not be published in the conference proceedings - The Open Access Journal Algorithms will publish Special Issue of the conference. After the conference, the Conference Committee will select manuscripts that may be included for publication in the Special Issue of the journal Algorithms (the submission to the journal is independent from the conference proceedings and will follow the usual process of the journal, including peer-review, APC, etc.).
Manuscripts should be prepared in MS Word or any other word processor and should be converted to the PDF format before submission. The publication format will be PDF. The manuscript should count at least 3 pages long (including figures, tables and references).
Manuscripts for the proceedings issue must have the following organization:
- Title
- Full author names
- Affiliations (including full postal address) and authors' e-mail addresses
- Abstract
- Keywords
- Introduction
- Methods
- Results and Discussion
- Conclusions
- (Acknowledgements)
- References
Manuscripts should be prepared in MS Word and should be converted to the PDF format before submission. The publication format will be PDF. There is no page limit on the length, although authors are asked to keep their papers as concise as possible.
Authors must use the Microsoft Word template to prepare their manuscript. Using the template file will substantially shorten the time to complete copy-editing and publication of accepted manuscripts. Manuscript prepared in MS Word must be converted into a single file before submission. Please do not insert any graphics (schemes, figures, etc.) into a movable frame which can superimpose the text and make the layout very difficult.
IOCA-2021-template
- Paper Format: A4 paper format, the printing area is 17.5 cm x 26.2 cm. The margins should be 1.75 cm on each side of the paper (top, bottom, left, and right sides).
- Formatting / Style: Papers should be prepared following the style of IOCA-2021 template. The full titles and the cited papers must be given. Reference numbers should be placed in square brackets [ ], and placed before the punctuation; for example [4] or [1-3], and all the references should be listed separately and as the last section at the end of the manuscript.
- Authors List and Affiliation Format: Authors' full first and last names must be given. Abbreviated middle names can be added. For papers written by various contributors a corresponding author must be designated. The PubMed/MEDLINE format is used for affiliations: complete street address information including city, zip code, state/province, country, and email address should be added. All authors who contributed significantly to the manuscript (including writing a section) should be listed on the first page of the manuscript, below the title of the article. Other parties, who provided only minor contributions, should be listed under Acknowledgments only. A minor contribution might be a discussion with the author, reading through the draft of the manuscript, or performing English corrections.
- Figures, Schemes and Tables: Authors are encouraged to prepare figures and schemes in color. Full color graphics will be published free of charge. Figure and schemes must be numbered (Figure 1, Scheme I, Figure 2, Scheme II, etc.) and an explanatory title must be added. Tables should be inserted into the main text, and numbers and titles for all tables supplied. All table columns should have an explanatory heading. Please supply legends for all figures, schemes and tables. The legends should be prepared as a separate paragraph of the main text and placed in the main text before a table, a figure or a scheme.
Authors are encouraged to prepare a presentation in PowerPoint or similar software, to be displayed online along with the manuscript. Slides, if available, will be displayed directly in the website using Sciforum.net's proprietary slides viewer. Slides can be prepared in exactly the same way as for any traditional conference where research results can be presented. Slides should be converted to the PDF format before submission so that our process can easily and automatically convert them for online displaying.
IOCA-2021_PPT-template.pptx
Authors are also encouraged to submit video presentations. If you are interested in submitting, please contact the conference organizer (ioca2021@mdpi.com) to get to learn more about the procedure.
Tips for authors: If you would like to prepare a video based on your PPT presentation, you may use the "record slide" function in the PowerPoint. The video will be uploaded to YouTube, as well as onto Sciforum. The video should be no longer than 5 minutes and be prepared with one of following formats:
- .MOV
- .MPEG4
- .MP4
- .AVI
- .WMV
- .MPEGPS
- .FLV
The video should be submitted in the system before 7th September 2021. If you fail to upload the video on the submission box, please feel free to contact us.
It is the authors' responsibility to identify and declare any personal circumstances or interests that may be perceived as inappropriately influencing the representation or interpretation of clinical research. If there is no conflict, please state here "The authors declare no conflict of interest." This should be conveyed in a separate "Conflict of Interest" statement preceding the "Acknowledgments" and "References" sections at the end of the manuscript. Financial support for the study must be fully disclosed under "Acknowledgments" section. It is the authors' responsibility to identify and declare any personal circumstances or interests that may be perceived as inappropriately influencing the representation or interpretation of clinical research.
MDPI, the publisher of the Sciforum.net platform, is an open access publisher. We believe that authors should retain the copyright to their scholarly works. Hence, by submitting a Communication paper to this conference, you retain the copyright of your paper, but you grant MDPI the non-exclusive right to publish this paper online on the Sciforum.net platform. This means you can easily submit your paper to any scientific journal at a later stage and transfer the copyright to its publisher (if required by that publisher).
List of Video Submissions from Authors
Learning the link between architectural form and structural efficiency
by SeyedPooyan KazemiSangedehi, Aldo Ghisi, Stefano Mariani
Related Paper: https://sciforum.net/paper/view/10891
New Explicit Asymmetric Hopscotch Methods for the Heat Conduction Equation
by Mahmoud Saleh and Endre Kovács
Related Paper: https://sciforum.net/paper/view/10902
Deep Learning Methodologies for Diagnosis of Respiratory Disorders from Chest X Ray Images: A Comparative Study
by Akhil Appu Shetty, CR Srinivasan, Aldrin Claytus Vaz and Navya Thirumaleshwar Hegde
Related Paper: https://sciforum.net/paper/view/10900
List of accepted submissions (31)
Id | Title | Authors | Poster PDF | ||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
sciforum-045015 | An Automated Image Based System for Colour Assessment of Prints and Textiles in Light Booth |
Srividya R ,
|
N/A |
Show Abstract |
|||||||||||||||||||||||||||||||||||||
Colour is a subjective perception, and in an industrial environment using colour, objectivity is of great significance. In pursuit of improvising the measurement approaches inheriting the scientific progressions, this research emphasis on the development of an automated system with image processing and machine learning techniques for non-contact colour assessment of both prints and textiles under user-defined daylight conditions in the light booth. The system consists of a light booth with tunable LED daylight luminaire to set the day-lighting conditions of D50, D65 and D75 with adjustable illuminance as per colour assessment standards of ISO/ASTM. The feature vectors of the sample images are extracted using colour histograms through histogram quantization. Colour classification is performed using K-Nearest Neighbor (KNN) algorithm trained with 140 shades of Macbeth colour checker chart SG. The proposed system is compared with visual and instrumental measurement methods for experimental validation. The results demonstrate an accuracy rate of 86% in colour classification of prints. Correlating to the lightness of textile samples an accuracy rate of 86% (very dark colour), 83% (medium light colour), 100% (very light colour) found |
|||||||||||||||||||||||||||||||||||||||||
sciforum-047676 | Multi-commodity Contraflow Problem on Lossy Network with Asymmetric Transit times | , , | N/A |
Show Abstract |
|||||||||||||||||||||||||||||||||||||
During transmission of commodities from one place to another, there may be loss due to death, leakage, damage, or evaporation. To address the problem, each arc of the network contains a gain factor. The network is a lossy network with a gain factor at most one on each arc. The generalized multi-commodity flow problem deals with routing several distinct goods from specific supply points to the corresponding demand points on an underlying network with minimum loss. The sum of all commodities on each arc does not exceed its capacity. Motivated by the uneven road condition of transportation network topology, we incorporate a contraflow approach with orientation-dependent transit times on arcs and introduce the generalized multi-commodity contraflow problem on a lossy network with orientation-dependent transit times. |
|||||||||||||||||||||||||||||||||||||||||
sciforum-048122 |
Quickest transshipment in an integrated network topology |
, |
![]() |
Show Abstract |
|||||||||||||||||||||||||||||||||||||
The quickest transshipment of the evacuees in an integrated evacuation network topology depends upon the evacuee arrival pattern in the collection network and their better assignment in the assignment network with appropriate traffic route guidance, destination In this work, the quickest transshipment aspect in an integrated evacuation network topology is revisited concerning a transit-based evacuation system. Appropriate collection approaches for the evacuees and their better assignment to transit vehicles for their quickest transshipment in such an embedded evacuation network are presented with their solution strategies. |
|||||||||||||||||||||||||||||||||||||||||
sciforum-048651 | Detection of misogyny from Arabic Levantine Twitter tweets using machine learning techniques | , , , , | N/A |
Show Abstract |
|||||||||||||||||||||||||||||||||||||
Due to the increased abundance of user comments on the internet, such as Twitter, Arabic Text Detection (ATD) is one of the most difficult computational tasks for the machine learning field. Misogyny in Arabic text detection has become a touchy issue, especially among Arab women. Online misogyny has become a major threat to women in many countries, and online misogynistic harassment has grown in recent years In this article, we use misogynistic women in Levantine as a case study to build a new approach for detecting Arabic text. The suggested study's goal is to discover a novel Arabic text recognition algorithm for misogyny of women in Arabic countries. Our approach has been evaluated on the Arabic Levantine Twitter Dataset for Misogynistic, and we achieved an excellent accuracy of 90% using the BERTv2n in binary classification and 89 in multi classification . |
|||||||||||||||||||||||||||||||||||||||||
sciforum-048385 | Avoiding Temporal Confounding in Timeseries Forecasting using Machine Learning | , |
![]() |
Show Abstract |
|||||||||||||||||||||||||||||||||||||
Timeseries forecasting plays an important role in many applications where knowledge of the future behaviour of a given quantity of interest is required. Traditionally, this task is approached using methods such as exponential smoothing, ARIMA and, more recently, recurrent neural networs such as LSTM architectures or transformers. These approaches intrinsically rely on the auto-correlation or partial auto-correlation between subsequent events to forecast the future values. Essentially, the past values of the timeseries are used to model its future behaviour. Implicitly, this assumes that the auto-correlation and partial auto-correlation is genuine and not spurious. In the latter case, the methods exploit the (partial) auto-correlation in the prediction even though they are not grounded in the causal data generation process of the timeseries. This can happen if some external event or intervention affects the value of the timeseries at multiple times. In terms of causal analysis, this is equivalent to introducing a confounder into the timeseries where the variable of interest at different times takes over the role of multiple variables in standard causal analysis. This effectively opens a backdoor path between different times that in turn leads to a spurious auto-correlation. If a forecasting model is built including such spurious correlations, the generalizeability and forecasting power of the model is reduced and future predictions many consequently be wrong. Using a supervised learning approach, we show how machine learning can be used to avoid temporal confounding in timeseries forecasting, thereby limiting or avoiding the influence of spurious auto-correlations or partial auto-correlations. |
Event Awards
The 1st International Online Conference on Algorithms–Best Paper Award
To acknowledge the support of the conference authors and recognize their outstanding scientific accomplishments, we are pleased to launch the Best Paper Award.
Best Paper Award (500 CHF)
The Best Paper Award is given to the paper judged to make the most significant contribution to the conference.
Terms and Conditions:
As a sponsor, Algorithms would like to award the best paper as elected by the conference committee. The winner will receive a cash award of 500 CHF and an award certification. We look forward to posting your contributions.
Criteria:
- Full paper must be submitted to IOCA 2021;
- Originality/novelty of the paper;
- Significance of content;
- Scientific soundness;
- Interest to the readers;
- English language and style.
Evaluation:
- Each Evaluation Committee member will provide an assessment of each applicant in terms of the criteria outlined above;
- Total score for each presentation will be ranked, from highest to lowest;
- If two or more authors achieve the same score, further evaluation will be carried out;
- All decisions made by the Evaluation Committee are final.
The winner will be announced by 10 October 2021.
The Awards
Number of Awards Available: 1
Terms and Conditions: As a sponsor, Algorithms would like to award the best paper as elected by all the conference committee. The winner will receive a cash award of 500 CHF. We look forward to posting your contributions.Conference Secretariat
IOCA 2021 | Live Session
07/10/2021 12:00
Game Theory,
applications of mathematics to biological and social sciences,
Algorithm Design,
Correctness by construction,
design and analysis of randomised search heuristics
Speakers
Alberto Pinto
Mathematics Department, Faculty of Sciences, University of Porto, Praça de Gomes Teixeira, Porto, Portugal
Prof. Dr.
dynamics; game theory; applications of mathematics to biological and social sciences
Pietro Oliveto
Department of Computer Science, The University of Sheffield, Regent Court, Portobello, Sheffield, UK
Dr.
design and analysis of bio-inspired optimisation algorithms; design and analysis of randomised search heuristics
Bruce Watson
FASTAR Group, Information Science Department, Stellenbosch University, Stellenbosch, South Africa
Prof. Dr.
algorithm design; correctness by construction; (network) security; stringology; tree processing; programming language design; compilers
B. Combinatorial Optimization, Graph and Network Algorithms
C. Evolutionary Algorithms and Machine Learning
Machine Learning (ML) is a vast field that is increasingly attracting the interest of researchers and policy makers due to its applicability to several aspects of our everyday life. In our digital era, the Internet of Everything and the Smart City paradigms require the handling of an enormous amount of data, and their processing. Algorithms should therefore become smarter and smarter on their own to tackle the issue of Big Data.
It is well recognized that ML algorithms can be specifically classified as unsupervised, supervised or reinforcement learning ones. Depending on whether the target is clustering, classification or regression, a single class out of the aforementioned ones may or have to be selected. In most cases, especially when Big Data are to be handled in real time and under variable environmental conditions, coupling with evolutionary algorithms and an efficient dimensionality reduction in the problem at hand become necessary too.
In this Section, contributions are welcome to address any issue linked to the application and optimization of currently available algorithms, as well as the formulation of new approaches and algorithms to advance the state of the art.
Session Chair
Dr. Stefano Mariani, Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milano, Italy
D. Parallel and Distributed Algorithms
E. Randomized, Online and Approximation Algorithms
Show all published submissions (1) Hide published submissions (1)
Submissions
List of Papers (1) Toggle list
F. Analysis of Algorithms and Complexity Theory
Show all accepted abstracts (1) Hide accepted abstracts (1)
List of Accepted Abstracts (1) Toggle list
G. Algorithms for Multidisciplinary Applications
H. Artificial Intelligence Algorithms
Artificial Intelligence (AI) algorithms can be defined as a set of smart computer algorithms that are able to successfully process and solve hard decision-making problems that are difficult or even impossible to solve using classical optimization algorithms due to a problem’s complex structure, unforeseen circumstances and various obstacles.
In recent years, AI algorithms have gained obvious importance and particular attention from researchers in the field of industrial engineering, computer science, operations research, and data science due to the fact that smart robots and automatic devices (or, more precisely, intelligent computer programs) are widely used across industries, in games, medicine, healthcare, military missions, and so on; to put it bluntly, robots are helping people almost everywhere on the surface of the earth, deep under water and in space.
In this section, we intend to publish new studies and meaningful scientific results on the design, analysis and extensions of the following types of the AI algorithms (but not necessarily limited to) as well as their widespread various applications:
- Algorithms for smart routing and navigation of robots, such as PRM Algorithm, A*, D*, etc.;
- Smart search of hidden or lost objects under unforeseen circumstances;
- Smart ranking such as PageRank algorithm;
- AI-oriented K-Nearest Neighbors and other clustering procedures;
- Biology-motivated algorithms, such as Ant Colony Optimization, Frog Leaps algorithm, etc.;
- Swarm Intelligence algorithms;
- Approximation algorithms with performance guarantees, such as the FPTAS;
- Decision Trees;
- Support Vector Machines;
- AI-applied logistic and other smart regression schemes, etc.