This document provides a summary of selected publications by Ivan Bratko. It lists 7 books he has authored or edited on topics including Prolog programming, machine learning, and qualitative knowledge for expert systems. It also lists over 50 papers and book chapters on artificial intelligence, machine learning, qualitative reasoning, and applications in biology, medicine, and other domains. A more detailed bibliography is available online at the provided URL.
This document is a resume for Amit Sethi summarizing his professional experience and qualifications. It outlines his objective to obtain a research and development position in industry. It then details his education at the University of Illinois at Urbana-Champaign where he is pursuing a PhD in Electrical and Computer Engineering, as well as a previous degree from Indian Institute of Technology. His experience includes research in machine learning, computer vision, and video processing. He has several publications and awards and is proficient in programming languages and computer skills relevant to his field.
This proposal seeks funding to develop technology for detecting insider threats through analyzing email data and application event traces. The proposal involves extending existing email tracking and mining technologies called MET and EMT to incorporate additional data sources like host-based sensors. The work will result in an integrated email security appliance called the EmailWall that can detect anomalous insider behavior, model groups of insiders, and quarantine potentially malicious emails. The work will be conducted by researchers at Columbia University and implemented by System Detection, Inc. over an 18 month period involving milestones like integrating additional data sources, testing on simulated data, and deploying the system for evaluation.
The document contains notifications acknowledging the insertion of several Partner Search inquiries into the ideal-ist website. The inquiries are seeking partners for projects related to topics such as in-car entertainment systems, e-learning, 3D television, intelligent transportation systems, mobile platform security, virtual presence technologies, accessibility of online information, and nanostructured materials. The notifications provide details about the project proposals such as keywords, deadlines, and links for further information.
The document discusses various machine learning and artificial intelligence topics including Markov decision processes, decision tree algorithms like ID3, reinforcement learning using Q-learning, and search techniques. It provides examples of applying these concepts to problems like classifying weather to decide whether to play ball, controlling processes with Markov models, and building decision trees from training data.
This document discusses machine learning concepts including what learning is, different types of learning tasks like classification and problem solving/planning, measuring performance, reasons to study machine learning, related disciplines, defining learning tasks, designing learning systems, sample learning problems, and lessons learned about learning. It uses the example of learning to play checkers to illustrate many of these concepts such as representing the target function, obtaining training data, choosing a learning algorithm, and discussing specific algorithms like least mean squares regression.
This document describes a study that used machine learning to analyze online knowledge sharing conversations between students collaboratively solving problems. The researchers used Hidden Markov Models to classify knowledge sharing episodes as either effective or ineffective based on features of the conversation. They were able to accurately classify episodes 93% of the time, significantly better than random chance. The study provides insights into how to better understand and assess how students share and assimilate new knowledge in collaborative learning groups.
This document provides information about a proposed workshop on knowledge acquisition from distributed, autonomous, and semantically heterogeneous data sources to be held at the 2005 IEEE International Conference on Data Mining. The workshop aims to bring together researchers from areas like machine learning, data mining, knowledge representation, databases, and selected application domains to address challenges in performing knowledge discovery from multiple distributed data sources that may have semantic differences. Topics of interest include learning from distributed data, making data sources self-describing through ontologies, learning ontologies and mappings between schemas, and handling semantic heterogeneity. The workshop will include invited talks and presentations of contributed papers, and targets researchers, students, and practitioners interested in knowledge acquisition from distributed data.
Alcantara Stone ha contribuido a la rehabilitación y remodelación de varias áreas del Observatorio Astronómico Nacional en Madrid, proporcionando uno de sus exclusivos materiales, el Alcantara Iridium®, para la creación de caminos y áreas en los jardines así como en la zona de la escalera principal y mirador.
This document is a resume for Amit Sethi summarizing his professional experience and qualifications. It outlines his objective to obtain a research and development position in industry. It then details his education at the University of Illinois at Urbana-Champaign where he is pursuing a PhD in Electrical and Computer Engineering, as well as a previous degree from Indian Institute of Technology. His experience includes research in machine learning, computer vision, and video processing. He has several publications and awards and is proficient in programming languages and computer skills relevant to his field.
This proposal seeks funding to develop technology for detecting insider threats through analyzing email data and application event traces. The proposal involves extending existing email tracking and mining technologies called MET and EMT to incorporate additional data sources like host-based sensors. The work will result in an integrated email security appliance called the EmailWall that can detect anomalous insider behavior, model groups of insiders, and quarantine potentially malicious emails. The work will be conducted by researchers at Columbia University and implemented by System Detection, Inc. over an 18 month period involving milestones like integrating additional data sources, testing on simulated data, and deploying the system for evaluation.
The document contains notifications acknowledging the insertion of several Partner Search inquiries into the ideal-ist website. The inquiries are seeking partners for projects related to topics such as in-car entertainment systems, e-learning, 3D television, intelligent transportation systems, mobile platform security, virtual presence technologies, accessibility of online information, and nanostructured materials. The notifications provide details about the project proposals such as keywords, deadlines, and links for further information.
The document discusses various machine learning and artificial intelligence topics including Markov decision processes, decision tree algorithms like ID3, reinforcement learning using Q-learning, and search techniques. It provides examples of applying these concepts to problems like classifying weather to decide whether to play ball, controlling processes with Markov models, and building decision trees from training data.
This document discusses machine learning concepts including what learning is, different types of learning tasks like classification and problem solving/planning, measuring performance, reasons to study machine learning, related disciplines, defining learning tasks, designing learning systems, sample learning problems, and lessons learned about learning. It uses the example of learning to play checkers to illustrate many of these concepts such as representing the target function, obtaining training data, choosing a learning algorithm, and discussing specific algorithms like least mean squares regression.
This document describes a study that used machine learning to analyze online knowledge sharing conversations between students collaboratively solving problems. The researchers used Hidden Markov Models to classify knowledge sharing episodes as either effective or ineffective based on features of the conversation. They were able to accurately classify episodes 93% of the time, significantly better than random chance. The study provides insights into how to better understand and assess how students share and assimilate new knowledge in collaborative learning groups.
This document provides information about a proposed workshop on knowledge acquisition from distributed, autonomous, and semantically heterogeneous data sources to be held at the 2005 IEEE International Conference on Data Mining. The workshop aims to bring together researchers from areas like machine learning, data mining, knowledge representation, databases, and selected application domains to address challenges in performing knowledge discovery from multiple distributed data sources that may have semantic differences. Topics of interest include learning from distributed data, making data sources self-describing through ontologies, learning ontologies and mappings between schemas, and handling semantic heterogeneity. The workshop will include invited talks and presentations of contributed papers, and targets researchers, students, and practitioners interested in knowledge acquisition from distributed data.
Alcantara Stone ha contribuido a la rehabilitación y remodelación de varias áreas del Observatorio Astronómico Nacional en Madrid, proporcionando uno de sus exclusivos materiales, el Alcantara Iridium®, para la creación de caminos y áreas en los jardines así como en la zona de la escalera principal y mirador.
International Journal on Cryptography and Information Security (IJCIS)ijcisjournal
International Journal on Cryptography and Information Security (IJCIS) is an open access peer
reviewed journal that focuses on cutting-edge results in applied cryptography and Information
security. It aims to bring together scientists, researchers and students to exchange novel ideas and
results in all aspects of cryptography, coding and Information security
Brief bibliography of interestingness measure, bayesian belief network and ca...Adnan Masood
This document provides a brief bibliography of papers related to interestingness measures, Bayesian belief networks, and causal inference. It lists over 60 references published between 1961-2012 on topics such as outlier detection, probabilistic graphical models, sensitivity analysis of Bayesian networks, rule interestingness measures, and applications of Bayesian networks in domains like fraud detection and credit risk evaluation. The references are grouped into sections on learning Bayesian networks from data, sensitivity analysis, outlier detection, rule interestingness measures, and applications.
October 2021: Top Read Articles in Soft Computingijsc
Soft computing is likely to play an important role in science and engineering in the future. The successful applications of soft computing and the rapid growth suggest that the impact of soft computing will be felt increasingly in coming years. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. This Open access peer-reviewed journal serves as a platform that fosters new applications for all scientists and engineers engaged in research and development in this fast growing field.
Pramod K.B is an electronics engineer with a PhD in electronics engineering. He has over 4 years of experience teaching electronics and communication engineering topics at the university level. He also has industry experience designing RF components at Icon Design and Automation. Pramod has published several papers in international journals and conferences on topics related to RF circuit design and microwave engineering. He is skilled in RF design tools like AWR Microwave Office and has experience designing components like low noise amplifiers and filters.
TOP READ NATURAL LANGUAGE COMPUTING ARTICLE 2020kevig
Natural Language Processing is a programmed approach to analyze text that is based on both a set of theories and a set of technologies. This forum aims to bring together researchers who have designed and build software that will analyze, understand, and generate languages that humans use naturally to address computers.
March 2021: Top Read Articles in Soft Computingijsc
Soft computing is likely to play an important role in science and engineering in the future. The successful applications of soft computing and the rapid growth suggest that the impact of soft computing will be felt increasingly in coming years. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. This Open access peer-reviewed journal serves as a platform that fosters new applications for all scientists and engineers engaged in research and development in this fast growing field.
International Journal of Network Security & Its Applications (IJNSA) - Curren...IJNSA Journal
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
June 2020: Most Downloaded Article in Soft Computing ijsc
Soft computing is likely to play an important role in science and engineering in the future. The successful applications of soft computing and the rapid growth suggest that the impact of soft computing will be felt increasingly in coming years. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. This Open access peer-reviewed journal serves as a platform that fosters new applications for all scientists and engineers engaged in research and development in this fast growing field.
New research articles 2020 october issue international journal of multimedi...ijma
The International Journal of Multimedia & Its Applications (IJMA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Multimedia & its applications. The journal focuses on all technical and practical aspects of Multimedia and its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding recent developments this arena, and establishing new collaborations in these areas.
June 2022: Top 10 Read Articles in Signal & Image Processingsipij
This article summarizes two papers published in the journal Signal & Image Processing.
The first paper describes a Gaussian mixture model-based speech recognition system developed using MATLAB. It analyzes the accuracy of GMM for modeling speech and the performance of the overall system.
The second paper proposes two new methods for securing images using cryptography and steganography. The first method encrypts an image into ciphertext using S-DES encryption and hides the text in a second image. The second method directly encrypts an image using a key image as the S-DES key and hides the encrypted data in a second image.
May 2024: Top 10 Read Articles in Software Engineering & Applications Interna...sebastianku31
Welcome To IJSEA ...!!!
Call for papers___!
International Journal of Software Engineering & Applications(IJSEA)
ISSN:0975-3834 [Online]; 0975-4679 [Print]
ERA Indexed, H Index 31
Web Page URL : https://airccse.org/journal/ijsea/ijsea.html
Submission URL :https://airccse.com/submissioncs/home.html
Contact Us : ijseajournal@airccse.org or ijsea@aircconline.com
May 2024: Top 10 Read Articles Posted Url:https://www.academia.edu/119977684/April_2024_Top_10_Read_Articles_in_Software_Engineering_and_Applications_International_Journal_of_Software_Engineering_and_Applications_IJSEA_ERA_Indexed
New Research Articles 2020 June Issue International Journal on Cryptography a...ijcisjournal
International Journal on Cryptography and Information Security ( IJCIS)
ISSN : 1839-8626
https://wireilla.com/ijcis/index.html
New Research Articles 2020 June Issue International Journal on Cryptography and Information Security (IJCIS)
Selective Encryption of Image by Number Maze Technique
Santosh Mutnuru, Sweeti Kumari Sah and S. Y Pavan Kumar, Eastern Michigan University, USA
Towards A Deeper NTRU Analysis: A Multi Modal Analysis
Chuck Easttom1, Anas Ibrahim2, Alexander Chefranov3, Izzat Alsmadi4 and Richard Hansen5, 1Adjunct Georgetown University and University of Dallas, 2&3Eastern Mediterranean University, 4Texas A&M University, 5Capitol Technology University
https://wireilla.com/ijcis/vol10.html
April 2023: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
July 2022: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
This document is a curriculum vitae for Dr. Ajay Kumar Singh, an Assistant Professor in the Department of Computer Science & Engineering at Mody University of Science & Technology in Lakshmangarh, Rajasthan, India. It outlines his educational background, research interests, publications, teaching experience, professional memberships, and seminars/conferences attended and organized. His research focuses on image processing, computer vision, and soft computing techniques. He has over 14 years of teaching experience and has authored over 24 peer-reviewed articles and book chapters.
April 2022: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
May 2022: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
October 2022: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
Top 5 most viewed articles from academia in 2019 - gerogepatton
The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications
January 2023: Top 10 Read Articles in Signal &Image Processing sipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
Este documento analiza el modelo de negocio de YouTube. Explica que YouTube y otros sitios de video online representan un nuevo modelo de negocio para contenidos audiovisuales debido al cambio en los hábitos de consumo causado por las nuevas tecnologías. Describe cómo YouTube aprovecha la participación de los usuarios para mejorar continuamente y atraer una audiencia diferente a la de los medios tradicionales.
International Journal on Cryptography and Information Security (IJCIS)ijcisjournal
International Journal on Cryptography and Information Security (IJCIS) is an open access peer
reviewed journal that focuses on cutting-edge results in applied cryptography and Information
security. It aims to bring together scientists, researchers and students to exchange novel ideas and
results in all aspects of cryptography, coding and Information security
Brief bibliography of interestingness measure, bayesian belief network and ca...Adnan Masood
This document provides a brief bibliography of papers related to interestingness measures, Bayesian belief networks, and causal inference. It lists over 60 references published between 1961-2012 on topics such as outlier detection, probabilistic graphical models, sensitivity analysis of Bayesian networks, rule interestingness measures, and applications of Bayesian networks in domains like fraud detection and credit risk evaluation. The references are grouped into sections on learning Bayesian networks from data, sensitivity analysis, outlier detection, rule interestingness measures, and applications.
October 2021: Top Read Articles in Soft Computingijsc
Soft computing is likely to play an important role in science and engineering in the future. The successful applications of soft computing and the rapid growth suggest that the impact of soft computing will be felt increasingly in coming years. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. This Open access peer-reviewed journal serves as a platform that fosters new applications for all scientists and engineers engaged in research and development in this fast growing field.
Pramod K.B is an electronics engineer with a PhD in electronics engineering. He has over 4 years of experience teaching electronics and communication engineering topics at the university level. He also has industry experience designing RF components at Icon Design and Automation. Pramod has published several papers in international journals and conferences on topics related to RF circuit design and microwave engineering. He is skilled in RF design tools like AWR Microwave Office and has experience designing components like low noise amplifiers and filters.
TOP READ NATURAL LANGUAGE COMPUTING ARTICLE 2020kevig
Natural Language Processing is a programmed approach to analyze text that is based on both a set of theories and a set of technologies. This forum aims to bring together researchers who have designed and build software that will analyze, understand, and generate languages that humans use naturally to address computers.
March 2021: Top Read Articles in Soft Computingijsc
Soft computing is likely to play an important role in science and engineering in the future. The successful applications of soft computing and the rapid growth suggest that the impact of soft computing will be felt increasingly in coming years. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. This Open access peer-reviewed journal serves as a platform that fosters new applications for all scientists and engineers engaged in research and development in this fast growing field.
International Journal of Network Security & Its Applications (IJNSA) - Curren...IJNSA Journal
The International Journal of Network Security & Its Applications (IJNSA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer Network Security & its applications. The journal focuses on all technical and practical aspects of security and its applications for wired and wireless networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern security threats and countermeasures, and establishing new collaborations in these areas.
June 2020: Most Downloaded Article in Soft Computing ijsc
Soft computing is likely to play an important role in science and engineering in the future. The successful applications of soft computing and the rapid growth suggest that the impact of soft computing will be felt increasingly in coming years. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. This Open access peer-reviewed journal serves as a platform that fosters new applications for all scientists and engineers engaged in research and development in this fast growing field.
New research articles 2020 october issue international journal of multimedi...ijma
The International Journal of Multimedia & Its Applications (IJMA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Multimedia & its applications. The journal focuses on all technical and practical aspects of Multimedia and its applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding recent developments this arena, and establishing new collaborations in these areas.
June 2022: Top 10 Read Articles in Signal & Image Processingsipij
This article summarizes two papers published in the journal Signal & Image Processing.
The first paper describes a Gaussian mixture model-based speech recognition system developed using MATLAB. It analyzes the accuracy of GMM for modeling speech and the performance of the overall system.
The second paper proposes two new methods for securing images using cryptography and steganography. The first method encrypts an image into ciphertext using S-DES encryption and hides the text in a second image. The second method directly encrypts an image using a key image as the S-DES key and hides the encrypted data in a second image.
May 2024: Top 10 Read Articles in Software Engineering & Applications Interna...sebastianku31
Welcome To IJSEA ...!!!
Call for papers___!
International Journal of Software Engineering & Applications(IJSEA)
ISSN:0975-3834 [Online]; 0975-4679 [Print]
ERA Indexed, H Index 31
Web Page URL : https://airccse.org/journal/ijsea/ijsea.html
Submission URL :https://airccse.com/submissioncs/home.html
Contact Us : ijseajournal@airccse.org or ijsea@aircconline.com
May 2024: Top 10 Read Articles Posted Url:https://www.academia.edu/119977684/April_2024_Top_10_Read_Articles_in_Software_Engineering_and_Applications_International_Journal_of_Software_Engineering_and_Applications_IJSEA_ERA_Indexed
New Research Articles 2020 June Issue International Journal on Cryptography a...ijcisjournal
International Journal on Cryptography and Information Security ( IJCIS)
ISSN : 1839-8626
https://wireilla.com/ijcis/index.html
New Research Articles 2020 June Issue International Journal on Cryptography and Information Security (IJCIS)
Selective Encryption of Image by Number Maze Technique
Santosh Mutnuru, Sweeti Kumari Sah and S. Y Pavan Kumar, Eastern Michigan University, USA
Towards A Deeper NTRU Analysis: A Multi Modal Analysis
Chuck Easttom1, Anas Ibrahim2, Alexander Chefranov3, Izzat Alsmadi4 and Richard Hansen5, 1Adjunct Georgetown University and University of Dallas, 2&3Eastern Mediterranean University, 4Texas A&M University, 5Capitol Technology University
https://wireilla.com/ijcis/vol10.html
April 2023: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
July 2022: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
This document is a curriculum vitae for Dr. Ajay Kumar Singh, an Assistant Professor in the Department of Computer Science & Engineering at Mody University of Science & Technology in Lakshmangarh, Rajasthan, India. It outlines his educational background, research interests, publications, teaching experience, professional memberships, and seminars/conferences attended and organized. His research focuses on image processing, computer vision, and soft computing techniques. He has over 14 years of teaching experience and has authored over 24 peer-reviewed articles and book chapters.
April 2022: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
May 2022: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
October 2022: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
Top 5 most viewed articles from academia in 2019 - gerogepatton
The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications
January 2023: Top 10 Read Articles in Signal &Image Processing sipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
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Este documento analiza el modelo de negocio de YouTube. Explica que YouTube y otros sitios de video online representan un nuevo modelo de negocio para contenidos audiovisuales debido al cambio en los hábitos de consumo causado por las nuevas tecnologías. Describe cómo YouTube aprovecha la participación de los usuarios para mejorar continuamente y atraer una audiencia diferente a la de los medios tradicionales.
The defense was successful in portraying Michael Jackson favorably to the jury in several ways:
1) They dressed Jackson in ornate costumes that conveyed images of purity, innocence, and humility.
2) Jackson was shown entering the courtroom as if on a red carpet, emphasizing his celebrity status.
3) Jackson appeared vulnerable, childlike, and in declining health during the trial, eliciting sympathy from jurors.
4) Defense attorney Tom Mesereau effectively presented a coherent narrative of Jackson as a victim and portrayed Neverland as a place of refuge, undermining the prosecution's arguments.
Michael Jackson was born in 1958 in Gary, Indiana and rose to fame in the 1960s as the lead singer of The Jackson 5, topping music charts in the 1970s. As a solo artist in the 1980s, his album Thriller broke music records. In the 1990s and 2000s, Jackson faced several legal issues related to child abuse allegations while continuing to release music. He married Lisa Marie Presley and Debbie Rowe and had two children before his death in 2009.
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The prosecution lost the Michael Jackson trial due to several key mistakes and weaknesses in their case:
1) The lead prosecutor, Thomas Sneddon, was too personally invested in the case against Jackson, having pursued him for over a decade without success.
2) Sneddon's opening statement was disorganized and weak, failing to effectively outline the prosecution's case.
3) The accuser's mother was not credible and damaged the prosecution's case through her erratic testimony, history of lies and con artist behavior.
4) Many prosecution witnesses were not credible due to prior lawsuits against Jackson, debts owed to him, or having been fired by him. Several witnesses even took the Fifth Amendment.
Here are three examples of public relations from around the world:
1. The UK government's "Be Clear on Cancer" campaign which aims to raise awareness of cancer symptoms and encourage early diagnosis.
2. Samsung's global brand marketing and sponsorship activities which aim to increase brand awareness and favorability of Samsung products worldwide.
3. The Brazilian government's efforts to improve its international image and relations with other countries through strategic communication and diplomacy.
The three most important functions of public relations are:
1. Media relations because the media is how most organizations reach their key audiences. Strong media relationships are crucial.
2. Writing, because written communication is at the core of public relations and how most information is
Michael Jackson Please Wait... provides biographical information about Michael Jackson including his birthdate, birthplace, parents, height, interests, idols, favorite foods, films, and more. It discusses his background, career highlights including influential albums like Thriller, and films he appeared in such as The Wiz and Moonwalker. The document contains photos and details about Jackson's life and illustrious music career.
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Michael Jackson was a child star who rose to fame with the Jackson 5 in the late 1960s and early 1970s. As a solo artist in the 1970s and 1980s, he had immense commercial success with albums like Off the Wall, Thriller, and Bad, which featured hit singles and groundbreaking music videos. However, his career and public image were plagued by controversies related to allegations of child sexual abuse in the 1990s and 2000s. He continued recording and performing but faced ongoing media scrutiny into his private life until his death in 2009.
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The document discusses using social networking tools like Twitter and Facebook in K-12 education. Twitter allows students and teachers to share short updates and can be used to give parents a window into classroom activities. Facebook allows targeted advertising that could be used to promote educational activities. Both tools could help facilitate communication between schools and communities if used properly while managing privacy and security concerns.
Facebook has over 300 million active users who log on daily, and allows brands to create public profile pages to interact with users. Pages are for brands and organizations only, while groups can be made by any user about any topic. Pages do not show admin names and have no limits on fans, while groups display admin names and are limited to 5,000 members. Content on pages should aim to provoke action from subscribers and establish a regular posting schedule using a conversational tone.
Executive Summary Hare Chevrolet is a General Motors dealership ...butest
Hare Chevrolet is a car dealership located in Noblesville, Indiana that has successfully used social media platforms like Twitter, Facebook, and YouTube to create a positive brand image. They invest significant time interacting directly with customers online to foster a sense of community rather than overtly advertising. As a result, Hare Chevrolet has built a large, engaged audience on social media and serves as a model for how brands can use online presences strategically.
Welcome to the Dougherty County Public Library's Facebook and ...butest
This document provides instructions for signing up for Facebook and Twitter accounts. It outlines the sign up process for both platforms, including filling out forms with name, email, password and other details. It describes how the platforms will then search for friends and suggest people to connect with. It also explains how to search for and follow the Dougherty County Public Library page on both Facebook and Twitter once signed up. The document concludes by thanking participants and providing a contact for any additional questions.
Paragon Software announces the release of Paragon NTFS for Mac OS X 8.0, which provides full read and write access to NTFS partitions on Macs. It is the fastest NTFS driver on the market, achieving speeds comparable to native Mac file systems. Paragon NTFS for Mac 8.0 fully supports the latest Mac OS X Snow Leopard operating system in 64-bit mode and allows easy transfer of files between Windows and Mac partitions without additional hardware or software.
This document provides compatibility information for Olympus digital products used with Macintosh OS X. It lists various digital cameras, photo printers, voice recorders, and accessories along with their connection type and any notes on compatibility. Some products require booting into OS 9.1 for software compatibility or do not support devices that need a serial port. Drivers and software are available for download from Olympus and other websites for many products to enable use with OS X.
To use printers managed by the university's Information Technology Services (ITS), students and faculty must install the ITS Remote Printing software on their Mac OS X computer. This allows them to add network printers, log in with their ITS account credentials, and print documents while being charged per page to funds in their pre-paid ITS account. The document provides step-by-step instructions for installing the software, adding a network printer, and printing to that printer from any internet connection on or off campus. It also explains the pay-in-advance printing payment system and how to check printing charges.
The document provides an overview of the Mac OS X user interface for beginners, including descriptions of the desktop, login screen, desktop elements like the dock and hard disk, and how to perform common tasks like opening files and folders. It also addresses frequently asked questions for Windows users switching to Mac OS X, such as where documents are stored, how to save or find documents, and what the equivalent of the C: drive is in Mac OS X. The document concludes with sections on file management tasks like creating and deleting folders, organizing files within applications, using Spotlight search, and an overview of the Dashboard feature.
This document provides a checklist for securing Mac OS X version 10.5, focusing on hardening the operating system, securing user accounts and administrator accounts, enabling file encryption and permissions, implementing intrusion detection, and maintaining password security. It describes the Unix infrastructure and security framework that Mac OS X is built on, leveraging open source software and following the Common Data Security Architecture model. The checklist can be used to audit a system or harden it against security threats.
This document summarizes a course on web design that was piloted in the summer of 2003. The course was a 3 credit course that met 4 times a week for lectures and labs. It covered topics such as XHTML, CSS, JavaScript, Photoshop, and building a basic website. 18 students from various majors enrolled. Student and instructor evaluations found the course to be very successful overall, though some improvements were suggested like ensuring proper software and pairing programming/non-programming students. The document also discusses implications of incorporating web design material into existing computer science curriculums.
1. SELECTED PUBLICATIONS
More detailed and up-to-date bibliography can be found at
http://cobiss.izum.si/ under Ivan Bratko.
Books
BRATKO, Ivan. Prolog Programming for Artificial Intelligence; Third edition. Pearson
Education, Addison-Wesley, 2001. Second edition, Addison-Wesley 1990. First edition,
Addison-Wesley 1986. Translations: German, Italian, French, Slovenian, Japanese, Russian.
BRATKO, Ivan, DŽEROSKI, Sašo (eds.). Machine Learning: Proceedings of 16th International
Conference on Machine Learning (ICML '99), Bled, Slovenia, 1999. San Francisco: Morgan
Kaufmann, 1999.
MICHALSKI, Ryszard S., BRATKO, Ivan , KUBAT, Miroslav (eds.). MachineLlearning and
Data Mining: Methods and Applications. J. Wiley & Sons, 1998.
BRATKO, Ivan, CESTNIK, Bojan. Programming Language Pascal with Extensions of Turbo
Pascal. Ljubljana: Državna založba Slovenije, 1990 (in Slovenian).
BRATKO, Ivan, MOZETIČ, Igor, LAVRAČ, Nada. KARDIO: A Study in Deep and Qualitative
Knowledge for Expert Systems. Cambridge, Massachusetts: MIT Press, 1989.
BRATKO, Ivan , LAVRAČ, Nada (eds.). Progress in Machine Learning: Proc. of EWSL 87.
Wilmslow: Sigma Press, 1987.
BRATKO, Ivan, RAJKOVIČ, Vladislav. Computer Science with the Pascal Language.
Ljubljana, Državna Založba Slovenije, 1984 (in Slovenian).
Papers and book chapters
BEŽEK, Andraž, GAMS, Matjaž, BRATKO, Ivan. Multi-agent strategic modeling in
a robotic soccer domain. V: STONE, Peter (ur.), WEISS, Gerhard (ur.). AAMAS'06 :
Proc. Fifth International Joint Conference on Autonomous Agents and Multiagent
Systems, Hakodate, Japan, May 8-12, 2006. New York: ACM, 2006, pp. 457-464.
VLADUŠIČ, Daniel, KOMPARE, Boris, BRATKO, Ivan. Modelling Lake Glumso
with Q2 learning. Ecological Modelling, Vol. 191 (2006), no. 1, pp. 33-46.
SADIKOV, Aleksander, BRATKO, Ivan, KONONENKO, Igor. Bias and pathology
in minimax search. Theoretical Computer Sc., Vol. 349 (2005), no. 2, pp. 268-281.
2. LUŠTREK, Mitja, GAMS, Matjaž, BRATKO, Ivan. Is real-valued minimax
pathological? Artificial Intelligence , Vol. 170 (2006), pp. 620-642.
ŽABKAR, Jure, ŽABKAR, Rahela, VLADUŠIČ, Daniel, ČEMAS, Danijel, ŠUC,
Dorian, BRATKO, Ivan. Q2 prediction of ozone concentrations. Ecological
Modellling. Vol. 191 (2006), no. 1, pp. 68-82.
SADIKOV, Aleksander, BRATKO, Ivan. Learning long-term chess strategies from
databases. Machine Learning. Vol. 63 (2006), no. 3, pp. 329-340.
ZAVEC PAVLINIĆ, Daniela, GERŠAK, Jelka, DEMŠAR, Janez, BRATKO, Ivan.
Predicting seam appearance quality. Textyle Research Journal, Vol. 76 (2006), no 3,
pp. 235-242. http://dx.doi.org/10.1177/0040517506061533.
Šuc, Dorian, Bratko, Ivan. Benefits of Qualitative Constraints in Numerical Learning. Proc.
IJCAI’05 (19th Int. Joint Conf. Artificial Intelligence), Edinburgh, Scotland, July 30 - August 5,
2005. Denver: International Joint Conferences on Artificial Intelligence, 2005.
CURK, Tomaž, DEMŠAR, Janez, QIKAI, Xu, LEBAN, Gregor, PETROVIČ, Uroš, BRATKO,
Ivan, SHAULSKY, Gad, ZUPAN, Blaž. Microarray data mining with visual programming.
Bioinformatics, Vol. 21 (2005), no. 3, pp. 396-398.
LEBAN, Gregor, BRATKO, Ivan, PETROVIČ, Uroš, CURK, Tomaž, ZUPAN, Blaž. VizRank :
finding informative data projections in functional genomics by machine learning. Bioinformatics,
Vol. 21, no. 3, pp. 413-414.
LUŠTREK, Mitja, GAMS, Matjaž, BRATKO, Ivan. Why minimax works : an
alternative explanation. Proc. IJCAI’05 (19th Int. Joint Conf. Artificial Intelligence),
Edinburgh, Scotland, July 30 - August 5, 2005. Denver: International Joint
Conferences on Artificial Intelligence, 2005, pp. 212-217.
JAKULIN, Aleks, MOŽINA, Martin, DEMŠAR, Janez, BRATKO, Ivan, ZUPAN,
Blaž. Nomograms for visualing support vector machines. Proc. KDD’2005 (11th
ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining) August 21-24,
2005, Chicago, Illinois, USA. New York: ACM, 2005, pp. 108-117.
LEBAN, Gregor, MRAMOR, Minca, BRATKO, Ivan, ZUPAN, Blaž. Simple and effective
visual models for gene expression cancer diagnostics. Proc. KDD’2005 (11th ACM SIGKDD Int.
Conf. on Knowledge Discovery and Data Mining) August 21-24, 2005, Chicago, Illinois, USA.
New York: ACM, 2005, pp. 167-176,
SRDOČ, Alira, SLUGA, Alojzij, BRATKO, Ivan. A quality management model based on the
"deep quality concept". Int. Journal Quality and Reliability Management, Vol. 22 (2005), no. 3,
pp. 278-302. http://www.emeraldinsight.com/ft.
ŽABKAR, Jure, VLADUŠIČ, Daniel, ŽABKAR, Rahela, ČEMAS, Danijel, ŠUC, Dorian,
BRATKO, Ivan. Using qualitative constraints in ozone prediction. Proc. QR’05 (19th Int.
Workshop on Qualitative Reasoning), Graz, Austria, 18-20 May 2005. Graz: 2005, pp. 149-156.
3. ŠUC, Dorian, VLADUŠIČ, Daniel, BRATKO, Ivan. Qualitatively faithful quantitative
prediction. Artificial Intelligence, 2004, Vol. 158, no. 2, pp. 189-214.
SADIKOV, Aleksander, BRATKO, Ivan, KONONENKO, Igor. Search versus knowledge: an
empirical study of minimax on KRK. In: van den Herik, J., Iida, H., Heinz, E. A. (eds.).
Advances in Computer Games: Many Games, Many Challenges (Proc. ICGA/IFIP SG16), (IFIP,
135). Boston; Dordrecht; London: Kluwer Academic Publishers, 2004, pp. 33-44.
JAKULIN, Aleks, BRATKO, Ivan. Testing the significance of attribute interactions. Proc.
ICML’04 (21st Int. Conf. on Machine Learning), July 4-8, 2004 Banff, Alberta, Canada, pp.
409-416.
BRATKO, Ivan, ŠUC, Dorian. Learning qualitative models. AI Magazine, Vol. 24 (2003), no. 4,
pp. 107-119.
ZUPAN, Blaž, BRATKO, Ivan, DEMŠAR, Janez, JUVAN, Peter, CURK, Tomaž, BORŠTNIK,
Urban, BECK, J. Robert, HALTER, John, KUSPA, Adam, SHAULSKY, Gad. GenePath: a
system for inference of genetic networks and proposal of genetic experiments. Artificial
Intelligence in Medicine, Vol. 29 (2003), pp. 107-130.
ZUPAN, Blaž, DEMŠAR, Janez, BRATKO, Ivan, JUVAN, Peter, HALTER, John A., KUSPA,
Adam, SHAULSKY, Gad. GenePath : a system for automated construction of genetic networks
from mutant data. Bioinformatics, Vol. 19 (2003), no. 3, pp. 383-389.
BRATKO, Ivan, ŠUC, Dorian. Qualitative data mining and its applications. CIT Journal.
Computing and Info. Technology, Vol. 11 (2003), no. 3, pp. 145-150.
LUŠTREK, Mitja, GAMS, Matjaž, BRATKO, Ivan. A program for playing tarok. ICGA
Journal, Vol. 26 (2003), pp. 190-197.
JAKULIN, Aleks, BRATKO, Ivan. Analyzing attribute dependencies. Proc. PKDD’03
(Knowledge discovery in databases), Lecture Notes in Computer Science, Lecture Notes in
Artificial Intelligence, Vol. 2838. Berlin; Heidelberg; New York: Springer, 2003, pp. 229-240.
ŠUC, Dorian, BRATKO, Ivan. Improving numerical prediction with qualitative constraints.
Proc. ECML’03, (European Conf. Machine Learning) (Lecture Notes in Computer Science,
Lecture Notes in Artificial Intelligence, Vol. 2837). Berlin; Heidelberg; New York: Springer,
2003, pp. 385-396.
BRATKO, Ivan, ŠUC, Dorian. Qualitative data mining and its applications. Proc. ITI’03 (25th
Int. Conf. Info. Technology Interfaces), June 16-19, 2003, Cavtat, Croatia. University of Zagreb,
SRCE, 2003, pp. 3-8 (invited talk).
JAKULIN, Aleks, BRATKO, Ivan, SMRKE, Dragica, DEMŠAR, Janez, ZUPAN, Blaž.
Attribute interactions in medical data analysis. Proc. AIME’03 (9th Conference on Artificial
Intelligence in Medicine in Europe), Protaras, Cyprus, October 18-22, 2003. (Lecture notes in
computer science, Lecture notes in artificial intelligence, Vol. 1211). Berlin: Springer, 2003, pp.
229-238.
4. BRATKO, Ivan, ŠUC, Dorian. Understanding control strategies. In: Della Riccia, Giacomo (ed.).
Planning Based on Decision Theory. Wien; New York: Springer, 2003, pp. 85-98.
ŠUC, Dorian, VLADUŠIČ, Daniel, BRATKO, Ivan. Qualitatively faithful quantitative
prediction. Proc. IJCAI-03 (18th Int. Joint Conf. on Artificial Intelligence), Acapulco, Mexico,
August 9-15, 2003. San Francisco: Morgan Kaufmann Publishers, 2003, pp. 1052-1057.
BRATKO, Ivan. Automated modelling with qualitative representations. In: Lucas, Peter (ed.)
Proc. Model-based and Qualitative Reasoning in Biomedicine (workshop at 9th European
Conference on Artificial Intelligence in Medicine, AIME'03, Protaras, Cyprus, 19th October, pp.
3-8 (invited talk).
BRATKO, Ivan, ŠUC, Dorian. Qualitative data mining. Proc. New Trends in Knowledge
Processing, Data Mining, Semantic Web and Computational Science : the Sixth SANKEN Int.
Symposium. Osaka, Japan, March 2003, pp. 10-12 (invited talk).
ŽNIDARŠIČ, Martin, BOHANEC, Marko, BRATKO, Ivan. Categorization of numerical values
for DEX hierarchical models. Informatica, Vol. 27 (2003), no. 4, pp. 405-409.
BRATKO, Ivan, ŠUC, Dorian. Qualitative explanation of controllers. Proc. QR’02 (16th Int.
Workshop on Qualitative Reasoning), June 10-12, 2002, Sitges – Barcelona, Spain. Sevilla:
Edición Digital, 2002, pp. 1-2 (invited paper)
PEČAR, Zdravko, RAJKOVIČ, Vladislav, BRATKO, Ivan. Obstacles to implementing TQM in
public organisations. In: Caddy, Joanne , Vintar, Mirko (eds.) Building Better Quality
Administration for the Public: Case Studies from Central and Eastern Europe. Bratislava:
NISPAcee, 2002, pp. 71-84.
BRATKO, Ivan, ŠUC, Dorian. Using machine learning to understand operator's skill. In:
Hendtlass, T., Ali, M. (eds.). Developments in Applied Artificial Intelligence, (Lecture notes in
computer science, Lecture notes in artificial intelligence, 2358). Berlin: Springer, 2002, pp.
812-823.
ŠUC, Dorian, BRATKO, Ivan. Qualitative reverse engineering. Proc. ICML’2002 (19th
International Conference on Machine Learning), University of New South Wales, Sydney,
Australia, July 8-12, 2002. San Francisco: Morgan Kaufmann, 2002, pp. 610-617.
BANDELJ, Aleksander, BRATKO, Ivan, ŠUC, Dorian. Qualitative simulation with CLP. Proc.
QR’2002 (16th Int. Workshop on Qualitative Reasoning), June 10-12, 2002, Sitges - Barcelona,
Spain. Sevilla: Edición Digital, 2002, pp. 5-9.
STANKOVSKI, Vlado, BRATKO, Ivan, DEMŠAR, Janez, SMRKE, Dragica. Induction of
hypotheses concerning hip arthroplasty : a modified methodology for medical research. Methods
Info. Medicine, Vol. 40 (2001), no. 5, pp. 392-396.
ZUPAN, Blaž, BRATKO, Ivan, DEMŠAR, Janez, BECK, Robert J., KUSPA, Adam,
SHAULSKY, Gad. Abductive inference of genetic networks. Proc. AIME’2001 (8th Conference
on Artificial Intelligence in Medicine in Europe), Cascais, Portugal, July 1-4, 2001. (Lecture
notes in computer science, Lecture notes in artificial intelligence, 2101). Berlin: Springer, 2001,
pp. 304-313.
5. DEMŠAR, Janez, ZUPAN, Blaž, BRATKO, Ivan. Transformation of attribute space by function
decomposition. In: Della Riccia, Giacomo, Lenz, H.-J., Kruse, R. (eds.). Data Fusion and
Perception, (CISM Courses and Lectures, no. 431). Wien; New York: Springer, 2001, pp.
237-247.
ŠUC, Dorian, BRATKO, Ivan. Qualitative induction. Proc. QR’2001 (15th Int. Workshop on
Qualitative Reasoning), May 17-18, 2001,San Antonio, Texas. Stoughton: The Printing House,
2001, pp. 13-20.
ŠUC, Dorian, BRATKO, Ivan. Induction of qualitative trees. Proc. ECML’2001 (European
Conf. on Machine Learning), (Lecture notes in artificial intelligence, Lecture notes in computer
science, 2167). Berlin: Springer, 2001, pp. 442-453.
JUVAN, Peter, ZUPAN, Blaž, DEMŠAR, Janez, BRATKO, Ivan, HALTER, John A., KUSPA,
Adam, SHAULSKY, Gad. Web-enabled knowledge-based analysis of genetic data. Proc.
ISMDA’2001 (2nd Int. Symp. Medical data analysis), Madrid, Spain, October 8-9, 2001 (Lecture
notes in computer science, 2199). Berlin: Springer, 2001, pp. 113-119.
ZUPAN, B., PORENTA, A., VIDMAR, G., AOKI, N., BRATKO, I., BECK, J. R. Decisions at
hand: a decision support system on handhelds. Proc. MEDINFO 2001 (10th World Congress on
Medical Informatics), London, UK, 2-5 September, 2001. Amsterdam: IOS Press: Ohmsha,
2001, pp. 566-700.
DEMŠAR, Janez, ZUPAN, Blaž, BRATKO, Ivan, KUSPA, Adam, HALTER, John A., BECK,
Robert J., SHAULSKY, Gad. GenePath : a computer program for genetic pathway discovery
from mutant data. Proc. MEDINFO 2001 (10th World Congress on Medical Informatics),
London, UK, 2-5 September, 2001. Amsterdam: IOS Press: Ohmsha, 2001, pp. 956-959.
ZUPAN, Blaž, DEMŠAR, Janez, SMRKE, Dragica, BOŽIKOV, K., STANKOVSKI, Vlado,
BRATKO, Ivan, BECK, J.R. Predicting patient's long - term clinical status after hip arthroplasty
using hierarchical decision modelling and data mining. Methods Info. Medicine, Vol. 40 (2001),
pp. 25-31.
ZUPAN, Blaž, DEMŠAR, Janez, KATTAN, Michael W., BECK, J. Robert, BRATKO, Ivan.
Machine learning for survival analysis: a case study on recurrence of prostate cancer. Articial
Intelligence in Medicine. Vol. 20 (2000), pp. 59-75.
ŠUC, Dorian, BRATKO, Ivan. Qualitative trees applied to bicycle riding. Electron. Trans. on
Artificial Intelligence, Vol. 4 (2000), Section B, pp. 125-140,
http://www.ep.liu.se/ej/etai/2000/014/
ŠUC, Dorian, BRATKO, Ivan. Skill modeling through symbolic reconstruction of operator's
trajectories. IEEE Trans. Syst. Man and Cybernetics, Part A, Syst. humans, Vol. 30 (2000), no. 6,
pp. 617-624.
BRATKO, Ivan. Abstractions between learning problems based on abstractions between
structured data. Proc. Dealing with Structured Data in Machine Learning and Statistics,
ECML’2000 Workshop, Barcelona, Spain, 30 May 2000 (invited paper).
6. ŠUC, Dorian, BRATKO, Ivan. Problem decomposition for behavioural cloning. Proc.
ECML’2000 (11th European Conference on Machine Learning), Barcelona, Catalonia, Spain,
May 31 - June 2, 2000. (Lecture notes in computer science, Lecture notes in artificial
intelligence, 1810). Berlin: Springer, 2000, pp. 382-391.
ZUPAN, Blaž, BRATKO, Ivan, BOHANEC, Marko, DEMŠAR, Janez. Induction of concept
hierarchies from noisy data. Proc. ICML’2000 (17th Int. Conf. on Machine Learning) June 29-
July 2, 2000, Stanford University. Morgan Kaufmann: San Francisco, pp. 1199-1206.
BRATKO, Ivan. Modelling operator's skill by machine learning. Proc. ITI’2000 (22nd
International conference on information technology interfaces), Pula, Croatia, June 13-16, 2000.
pp. 23-30 (invited paper).
ZUPAN, Blaž, BOHANEC, Marko, DEMŠAR, Janez, BRATKO, Ivan. Learning by discovery
concept hierarchies. Artificial Intelligence, Vol. 109 (1999), pp. 211-242. Also in: Paliouras, G.,
Karkaletsis, V., Spyropoulos, C. D. (eds.). Machine Learning and its Applications (Lecture notes
in computer science, Lecture notes in artificial intelligence, 2049). Berlin: Springer, 2001, pp.
71-101.
ZUPAN, Blaž, DEMŠAR, Janez, KATTAN, Michael W., BECK, J. Robert, BRATKO, Ivan.
Machine learning for survival analysis: a case study on recurrence of prostate cancer. Proc.
AIMDM’99 (Joint European Conference on Artificial Intelligence in Medicine and Medical
Decision Making), Aalborg, Denmark, June 20-24, 1999 (Lecture notes in computer science,
Lecture notes in artificial intelligence, 1620). Berlin: Springer, 1999, pp. 346-355.
BRATKO, Ivan. Refining complete hypotheses in ILP. Proc. ILP’99 (9th Int. Workshop on
Inductive logic programming), Bled, Slovenia, June 1999 (Lecture notes in computer science,
Lecture notes in artificial inteligence, 1634). Berlin: Springer, 1999, pp. 44-55.
DEMŠAR, Janez, ZUPAN, Blaž, KATTAN, Michael W., BECK, J. Robert, BRATKO, Ivan.
Naive Bayesian-based nomogram for prediction of prostate cancer recurrence. Proc. Medical
Informatics Europe '99, (Studies in health technology and informatics, Vol. 68). Amsterdam:
IOS Press; Tokyo: Ohmsha, 1999, pp. 436-441.
SMRKE, Dragica, STANKOVSKI, Vlado, BRATKO, Ivan, DEMŠAR, Janez, ARNEŽ, Zoran
M. New indications for hip arthroplasty by using regression trees. Proc. SIROT (Int. Meeting of
International Research Society of Orthopaedic Surgery and Traumatology, Sydney, Australia,
April 16-19, 1999. London: Freund publishing house Ltd., 1999, pp. 757-761. [COBISS.SI-ID
11146713]
BRATKO, Ivan, URBANČIČ, Tanja. Control skill, machine learning and hand-crafting in
controller design. In: Furukawa, K., Michie, D., Muggleton, S. Machine intelligence 15:
intelligent agents. Oxford: Oxford University Press, 1999, pp. 130-153.
DŽEROSKI, Sašo, TODOROVSKI, Ljupčo, BRATKO, Ivan, KOMPARE, Boris, KRIŽMAN,
Viljem. Equation discovery with ecological applicatins. In: Fielding, A. H. (ed.). Machine
Learning Methods for Ecological Applications. Boston; Dordrecht; London: Kluwer Academic
Publishers, 1999, pp. 185-207.
7. ŠUC, Dorian, BRATKO, Ivan. Modelling of control skill by qualitative constraints. Proc. QR’99
(Thirteenth International Workshop on Qualitative Reasoning), Loch Awe, Scotland, 7-9 June
1999. Aberystwyth: University of Aberystwyth, 1999, pp. 212-220.
ŠUC, Dorian, BRATKO, Ivan. Symbolic and qualitative reconstruction of control skill.
Electron. Trans. on Articial Intelligence, Vol. 3 (1999), Section B, pp. 1-22,
http://www.ep.liu.se/ej/etai/1999/002/
DOLŠAK, Bojan, BRATKO, Ivan, JEZERNIK, Anton. Knowledge base for finite element mesh
design learned by inductive logic programming. Artificial Intelligence in Eng. Design Anal.
Manuf., Vol. 12 (1998), pp. 95-106.
STANKOVSKI, Vlado, DEBELJAK, Marko, BRATKO, Ivan, ADAMIČ, Miha. Modelling the
population dynamics of red deer (Cervus elaphus L.) with regard to forest development.
Ecological Modelling. Vol. 108 (1998), nos. 1-3, pp. 145-153.
ZUPAN, Blaž, BOHANEC, Marko, DEMŠAR, Janez, BRATKO, Ivan. Feature transformation
by function decomposition. In: Liu, H., Motoda, H. (eds.). Feature Extraction, Construction and
Selection : a Data Mining Perspective. Boston; Dordrecht; London: Kluwer Academic
Publishers, 1998, pp.325-340.
KUBAT, Miroslav, BRATKO, Ivan, MICHALSKI, Ryszard S. A review of machine learning
methods. V: MICHALSKI, Ryszard S. (ur.), BRATKO, Ivan (ur.), KUBAT, Miroslav (ur.).
Machine learning and data mining : methods and applications. Chichester [etc.]: J. Wiley &
Sons, cop. 1998, pp. 3-69, graf. prikazi. [COBISS.SI-ID 1170516]
BRATKO, Ivan, MUGGLETON, Stephen, KARALIČ, Aram. Applications of inductive logic
programming. In: Michalski, R. S., BRATKO, I., Kubat, M. (eds.). Machine Learning and Data
Mining: Methods and Applications. Chichester: J. Wiley & Sons, 1998, pp. 131-143.
DOLŠAK, Bojan, BRATKO, Ivan, JEZERNIK, Anton. Application of machine learning in
finite element computation. In: Michalski, R. S., BRATKO, I., Kubat, M. (eds.). Machine
Learning and Data Mining: Methods and Applications. Chichester: J. Wiley & Sons, 1998, pp.
147-171.
BRATKO, Ivan, URBANČIČ, Tanja, SAMMUT, Claude. Behavioural cloning of control skill.
In: Michalski, R. S., BRATKO, I., Kubat, M. (eds.). Machine Learning and Data Mining:
Methods and Applications. Chichester: J. Wiley & Sons, 1998, pp. 335-351.
KONONENKO, Igor, BRATKO, Ivan, KUKAR, Matjaž. Application of machine learning to
medical diagnosis. In: Michalski, R. S., BRATKO, I., Kubat, M. (eds.). Machine Learning and
Data Mining: Methods and Applications. Chichester: J. Wiley & Sons, 1998, pp. 389-408.
ZUPAN, Blaž, BOHANEC, Marko, DEMŠAR, Janez, BRATKO, Ivan. Feature transformation
by function decomposition. IEEE Intelligent Syst. and Their Appl., Vol. 13 (1998), pp. 38-43.
BRATKO, Ivan, URBANČIČ, Tanja. Transfer of control skill by machine learning. Eng. Appl.
Artificial Intelligence. Vol. 10 (1997), no. 1, pp. 63-71.
8. KARALIČ, Aram, BRATKO, Ivan. First order regression. Machine Learning. Vol. 26 (1997),
pp. 147-176.
ŠUC, Dorian, BRATKO, Ivan. Skill modelling through symbolic reconstruction of operator's
trajectories. Proc. 6th IFAC Symp. Automated systems based on human skill, Kranjska Gora,
Slovenia, September 17-19, 1997. Aachen: University of Technology; Ljubljana: J. Stefan
Institute, 1997, pp. 35-38.
ŠUC, Dorian, BRATKO, Ivan. Skill reconstruction as induction of LQ controllers with subgoals.
Proc. IJCAI-97 (15th Int. Joint Conference on Artificial Intelligence), Nagoya, Japan August
23-29, 1997. Volume 2., pp. 914-920.
JUNKAR, Mihael, BRATKO, Ivan, KRAMAR, Davorin. The selection of optimal CO2 laser
cutting parameters using machine learning. Proc. LANE'97 (Laser Assisted Net Shape
Engineering 2: 30th Int. CIRP Seminar on Manufacturing Systems), Erlangen, September 23-26,
1997. Bamberg: Meisenbach, 1997, pp. 203-210. [COBISS.SI-ID 2424859]
ZUPAN, Blaž, BOHANEC, Marko, BRATKO, Ivan, DEMŠAR, Janez. Machine learning by
function decomposition. Proc. ICML’97 (14th Int. Conf. on Machine Learning), Nashville,
Tennessee, July 8-12, 1997. San Francisco: Morgan Kaufmann, 1997, pp. 421-429.
DEMŠAR, Janez, ZUPAN, Blaž, BOHANEC, Marko, BRATKO, Ivan. Constructing
intermediate concepts by decomposition of real functions), Prague, Czech Republic, April 23-25,
1997. (Lecture notes in computer science, Lecture notes in artificial intelligence, 1224). Berlin:
Springer, 1997, pp. 93-107.
BOHANEC, Marko, ZUPAN, Blaž, BRATKO, Ivan, CESTNIK, Bojan. A function-
decomposition method for development of hierarchical multi-attribute decision models. Proc.
Fourth Conf. of Int. Society for Decision Support Systems. Lausanne, Switzerland July 21-22,
1997. pp. 503-514.
BRATKO, Ivan. Qualitative reconstruction of control skill. Proc. QR’07 (11th Int. Workshop on
Qualitative Reasoning), Cortona, Italy, June 3-6, 1997. Pubblicazioni N. 1036. Pavia: Instituto di
analisi numerica, 1997, pp. 41-52.
JUNKAR, Mihael, BRATKO, Ivan, KOMEL, Igor, VALENTINČIČ, Joško. Controller design
for electrical discharge machining. V: MONOSTORI, László (ur.). The Second World Congress
on Intelligent Manufacturing Processes & Systems, Budapest, Hungary, June 10-13, 1997 :
proceedings. Berlin [etc.]: Springer, 1997, pp. 382-387. [COBISS.SI-ID 2425371]
URBANČIČ, Tanja, BRATKO, Ivan. A study in automated extraction of control rules by
machine learning. Proc. 2nd World Congress on Intelligent Manufacturing Processes &
Systems, Budapest, Hungary, June 10-13, 1997. Berlin: Springer, 1997, pp. 622-627.
BRATKO, Ivan. Machine learning : between accuracy and interpretability. In: Della Riccia, G.,
Lenz, H.-J., Kruse, R. (eds.). Learning, Networks and Statistics, (CISM Courses and lectures, no.
382). Wien; York: Springer, 1997, pp. 163-177. [COBISS.SI-ID 1171028]
BRATKO, Ivan, CESTNIK, Bojan, KONONENKO, Igor. Attribute-based learning. AI commun.,
1996, Vol. 9, pp. 27-32.
9. BRATKO, Ivan. Experiments in reconstruction of control skill. In: Ramsay, A. M. (ed.).
Artificial Intelligence: Methodology, Systems, Applications, (Frontiers in artificial intelligence
and applications, Vol. 35). Amsterdam: IOS Press: Ohmsha, 1996.
JUNKAR, Mihael, BRATKO, Ivan. Some applications of machine learning in machining. Proc.
Int. Coll. on Flexible Manufacturing Systems,Ljubljana, Slovenia, November 27, 1996.
Ljubljana: Faculty of Mechanical Engineering, 1996, pp. 1-15.
LAVRAČ, Nada, DŽEROSKI, Sašo, BRATKO, Ivan. Handling imperfect data in inductive logic
programming. In: De Raedt, L. (ed.). Advances in Inductive Logic Programming. Amsterdam:
IOS Press: Ohmsha, 1996, pp. 48-64.
DŽEROSKI, Sašo, BRATKO, Ivan. Applications of inductive logic programming. In: De Raedt,
L. (ed.). Advances in Inductive Logic Programming. Amsterdam: IOS Press: Ohmsha, 1996, pp.
65-81.
URBANČIČ, Tanja, BRATKO, Ivan, SAMMUT, Claude. Learning models of control skills:
phenomena, results and problems. Proc. 13th World Congress International Federation of
Automatic Control, San Francisco, USA, 30th June - 5th July 1996. Vol. L, Systems engineering
and managements. IFAC, 1996, pp. 391-396.
BRATKO, Ivan, URBANČIČ, Tanja. Transfer of control skill by machine learning. Proc. Int.
Workshop on Artificial Intelligence in Real-Time Control, Bled, Slovenia, November 29-
December 1, 1995, pp. 172-181.
BRATKO, Ivan, DŽEROSKI, Sašo. New AI techniques applied to modelling. Proc.
International Conference Design to Manufacture in Modern Industry, Bled, Slovenia, 29-30
May 1995, pp. 359-372.
BOHANEC, Marko, BRATKO, Ivan. Trading accuracy for simplicity in decision trees. Machine
Learning. Vol. 15 (1995), pp. 223-250.
BRATKO, Ivan, MUGGLETON, Stephen. Applications of inductive logic programming.
Commun. ACM, Vol. 38 (1995), pp. 65-70.
BRATKO, Ivan. Deriving qualitative control for dynamic systems. In: Furukawa, K., MICHIE,
Donald (ur.), MUGGLETON, Stephen (ur.). Applied machine intelligence, (Machine
intelligence, 14). Oxford: Clarendon Press, 1995, pp. 367-385.
URBANČIČ, Tanja, BRATKO, Ivan. Controlling container cranes : A case-study in
reconstruction of human skill. Elektroteh. vestn., Vol. 62 (1995), pp. 199-205.
BRATKO, Ivan, DŽEROSKI, Sašo. Engineering applications of ILP. New Generation
Computing, Vol. 13 (1995), pp. 313-333.
BOHANEC, Marko, BRATKO, Ivan. Trading accuracy for simplicity in decision trees. Machine
learning,Vol. 5 (1994), pp. 223-250.
10. URBANČIČ, Tanja, BRATKO, Ivan. Reconstructing human skill with machine learning. Proc.
ECAI’94 (11th European Conf. on Artificial Intelligence), August 8-12, 1994, Amsterdam, The
Netherlands. Chichester, UK: John Wiley & Sons, 1994, pp. 498-502.
DOLŠAK, Bojan, BRATKO, Ivan, JEZERNIK, Anton. Finite element mesh design: an
engineering domain for ILP application. Proc. ILP’94 (4th Int. Workshop on Inductive Logic
Programming), September 12-14, 1994 Bad Honnef/Bonn, Germany, (GMD-Studien, Nr. 237).
Sankt Augustin: Gesellschaft für Mathematik und Datenverarbeitung MBH, 1994, pp. 305-320.
BOHANEC, Marko, BRATKO, Ivan. Representing examples by examples. In: Della Riccia, G.,
KRUSE, R., Viertl, R. (eds.). Mathematical and Statistical Methods in Artificial Intelligence
(CISM Courses and Lectures, no. 363). Wien: Springer-Verlag, 1995, pp. 221-235.
BRATKO, Ivan. Machine lerning and qualitative reasoning. Machine Learning, Vol. 14 (1994),
pp. 305-312.
BRATKO, Ivan, KING, Ross. Applications of inductive logic programming. SIGART Bull., Vol.
5 (1994), pp. 43-49.
DOLŠAK, Bojan, JEZERNIK, Anton, BRATKO, Ivan. A knowledge base for finite element
mesh design. Artificial Intelligence in Eng., Vol. 9 (1994), pp. 19-27.
BRATKO, Ivan, MUGGLETON, Stephen, VARŠEK, Alen. Learning qualitative models of
dynamic systems. In: Johnson, J (ed.) Artificial Intelligence in Mathematics. Oxford: Claredon
press, 1994, pp. 67-76.
URBANČIČ, Tanja, BRATKO, Ivan. Learning to control dynamic systems. In: Michie, D.,
Spiegelhalter, D. J., Taylor, C. C. (eds.). Machine Learning, Neural and Statistical
Classification. New York: Ellis Horwood and Wiley, 1994, pp. 246-261.
KOMPARE, Boris, BRATKO, Ivan, STEINMAN, Franci, DŽEROSKI, Sašo. Using machine
learning techniques in the construction of models. Ecolological Modelling. Vol. 75/76 (1994),
pp. 617-628.
BRATKO, Ivan. Machine learning in artificial intelligence. Artificial Intelligence in Eng. Vol. 8
(1993), pp. 159-164.
BRATKO, Ivan. Applications of machine learning: towards knowledge synthesis. New
generation Computing, Vol. 11 (1993), pp. 343-360.
BRATKO, Ivan. Innovative design as learning from examples. Proc. DMMI’03 (Int. Conf.
Design to Manufacture in Modern Industry), Bled, Slovenia, 7-9 June 1993. pp. 355-362.
BRATKO, Ivan. Qualitative reasoning about control. Proc. ETFA'93 (Design and operations of
intelligent factories). Piscataway: IEEE, 1993, pp. 95-105.
MLADENIĆ, Dunja, BRATKO, Ivan, PAUL, R. J., GROBELNIK, Marko. Using machine
learning techniques to interpret results from discrete event simulation. Proc. ITI’93 (15th Int.
Conf. on Information Technology interfaces), Pula, Croatia, June 15-18, 1993. Zagreb:
University Computing Centre, 1993, pp. 401-406.
11. BRATKO, Ivan, GROBELNIK, Marko. Inductive learning applied to program construction and
verification. In: Cuena, J. (ed.). Knowledge Oriented Software Design (Extended papers from
AIFIPP'92 - IFIP TC12 wokshop on Artificial Intelligence from the Information Processing
Perspective, Madrid, Spain, 14-15 September, 1992). IFIP Transactions, A, Computer Science
and Technology, A-27, Amsterdam: North-Holland, 1993, pp. 169-182. Modified version in:
Proc. ILP’93 (Third Int. Workshop on Inductive Logic Programming), April 1-3, 1993, Bled
Slovenija. Ljubljana: J. Stefan Institute, 1993, pp. 279-292.
BRATKO, Ivan. Qualitative modelling and learning in KARDIO. In: Buchanan, B. G., Wilkins,
D. C. Readings in Knowledge Acquisition and Learning: Automating the Construction and
Improvement of Expert Systems. San Mateo, CA: Morgan Kaufmann, 1993, pp. 616-625.
URBANČIČ, Tanja, BRATKO, Ivan. Constructing control rules for dynamic systems:
probabilistic qualitative models, lookhead and exaggeration. Int. J. Syst. Sci., Vol. 24 (1993), no.
6, pp. 1155-1164.
BRATKO, Ivan. Machine learning and qualitative modelling in medical applications. In: Kopec,
D., Thompson, R. B. (ed.). Artificial Intelligence and Intelligent Tutoring Systems: Knowledge-
based Systems for Learning and Teaching. New York: E. Horwood and Wiley, 1992, pp. 25-42.
URBANČIČ, Tanja, BRATKO, Ivan. Knowledge acquisition for dynamic system control. In:
Souček, B. (ed.) Dynamic, Genetic, and Chaotic Programming, (Sixth-generation computer
technology series). New York: John Wiley, 1992, pp. 65-83.
CESTNIK, Bojan, BRATKO, Ivan. On estimating probabilities in tree pruning. Proc. EWSL’91
(European Working Session on Learning), Porto, Portugal, March 6-8, 1991 (Lecture notes in
computer science, Lecture notes in artificial intelligence, 482). Berlin: Springer-Verlag, 1991,
pp. 138-150.
FILIPIČ, Bogdan, JUNKAR, M., BRATKO, Ivan, KARALIČ, Aram. An application of machine
learning to a metal-working process. Proc. ITI’91 (13th Int. Conf. on Information Technology
Interfaces), Cavtat, Dubrovnik, Croatia, June 1991. Zagreb: University Computing Centre, 1991,
pp. 167-172.
JUNKAR, M., FILIPIČ, Bogdan, BRATKO, Ivan. Identifying the grinding process by means of
inductive machine learning. First CIRP Workshop on Learning in IMS, 6-8 March 1991,
Budapest, Hungary. Budapest: Hungarian Academy of Sciences, Computer and Automation
Institute, 1991, pp. 195-203.
MOZETIČ, I., BRATKO, Ivan, URBANČIČ, Tanja. Varying levels of abstraction in qualitative
modelling. In:Hayes, J. E., Michie, D., Tyugu, E. K (eds.). Machine Intelligence 12: Towards an
Automated Logic of Human Thought. Oxford: Clarendon Press; New York: Oxford University
Press, 1991, pp. 259-280.
JUNKAR, Mihael, FILIPIČ, Bogdan, BRATKO, Ivan. Identifying the grinding process by
means of inductive machine learning. Comput. Ind., Vol. 17 (1991), pp. 147-153.
BRATKO, Ivan, LAVRAČ, Nada, MOZETIČ, Igor. Kardio : An expert system for ECG
interpretation expert systems. In: Bramer, M. A. (ed.). Practical Experience in Building Expert
Systems. Chichester: J. Wiley & sons, 1990, pp. 183-207.
12. BRATKO, Ivan, KODRATOFF, V. An analytical report on EWSL-88. AI commun., Vol. 2
(1989), pp. 24-29.
BRATKO, Ivan, KONONENKO, Igor. Learning diagnostic rules from incomplete
and noisy data. In: Interactions in AI and Statistics (Phelps, B., ed.) London: Gower
Technical Press 1987, str. 142-153.
MICHIE, Donald, BRATKO, Ivan. Ideas on knowledge synthesis stemming from the KBBKN
endgame. ICCA Journal., Vol. 10 (1987), pp. 3-13.
CESTNIK, Bojan, KONONENKO, Igor, BRATKO, Ivan. ASSISTANT 86: a
knowledge elicitation tool for sophisticated users. In: Progress in Machine Learning:
Proc. EWSL’87 (Second European Working Session on Learning). Bled, Slovenia,
13-15 May 1987.
BRATKO, Ivan, MICHIE, D. Some comments on rule induction. Knowledge Eng. Review, Vol.
1 (1987), pp. 65-67.
MOWFORTH, Peter, BRATKO, Ivan. AI and robotics: flexibility and integration.
Robotica Journal, Vol. 5 (1987), pp 93-98.
BRATKO, Ivan. AI tools and techniques for manufacturing systems. Robotics and Computer-
Integrated Manufacturing. Vol. 3 (1987).
ROŠKAR, Egidija, ABRAMS, P., BRATKO, Ivan, KONONENKO, Igor, VARŠEK, Alen.
MCUDS - an expert system for the diagnostics of lower urinary tract disorders. Biomed. meas.
inform. control, Vol. 1 (1986), pp. 201-204.
NIBLETT, Tim, BRATKO, Ivan. Learning decision rules in noisy domains. Proc. of Expert
Systems '86 (Sixth Annual Technical Conference of the British Computer Society Specialist
Group on Expert Systems), Brighton, 15-18 December 1986. Cambridge: Cambridge University
Press, 1987, pp. 25-34.
BRATKO, Ivan, MOZETIČ, Igor, LAVRAČ, Nada. Automatic synthesis and
compression of cardiological knowledge. In: Hayes, J. E., Michie, D., Richards, J.
Machine Intelligence 11: Lgic and the Aquisition of Kowledge. Oxford: Clarendon
Press, 1988, pp. 435-454. Also in: Michie, D., Bratko, I., Expert Systems:
Automating Knowledge Acquisition. Addison-Wesley 1986, pp. 45-61.
BRATKO, Ivan, KONONENKO, Igor, LAVRAČ, Nada, MOZETIČ, Igor, ROŠKAR, Egidija.
Automatic synthesis of knowledge. Automatika, Vol. 26 (1985), pp. 171-176.
KONONENKO, I, BRATKO, I., ROŠKAR, E. Inductive learning system
ASSISTANT. Informatica, Vol. 9 (1985), pp. 44-55.
LAVRAČ, Nada, BRATKO, Ivan, MOZETIČ, Igor, ČERČEK, B., GRAD, A., HORVAT, M.
KARDIO-E - An expert system for electrocardiographic diagnosis of cardiac arrhythmias.
Expert Systems, Vol. 2 (1985), pp. 46-50.
13. BRATKO, Ivan. Symbolic derivation of chess patterns.. In: Campbell, J., Steels, L.
(eds.) Progress in Artificial Intelligence. Ellis Horwood and Wiley, 1985, pp.
281-290.
BRATKO, Ivan, TANCIG, Peter, TANCIG, S. Detection of positional patterns in chess. In:
Beal, D. F. (ed.). Advances in Computer Chess 4. Oxford; New York: Pergamon, 1986, pp.
113-126.
GAMS, Matjaž, BRATKO, Ivan. A circuit analysis program that explains its reasoning. Cybern.
Syst., Vol. 2 (1984), pp. 811-816.
BRATKO, Ivan. Advice and planning in chess endgames. In: Elithorn, A., Banerji, R.
(eds.) Artificial and Human Thinking. North-Holland 1984, pp. 119-130.
MOZETIČ, Igor, BRATKO, Ivan, LAVRAČ, Nada. An experiment in automatic
synthesis of expert knowledge through qualitative modelling. Proc. Logic
Programming Workshop 83. Albufeira, Portugal, June 1983.
BOHANEC, Marko, BRATKO, Ivan, RAJKOVIČ, Vladislav. An expert system for
decision making . In: Sol, H. G. (ed.), Processes and Tools for Decision Support (IFIP
Publication), North-Holland 1983.
ZWITTER, Matjaž, BRATKO, Ivan, KONONENKO, Igor. Reservations against the
use of computers in medical diagnosis and prognosis. Proc. 3rd Mediterranean Conf.
on Biomedical Engineering, Portoroz, Slovenia, Sept. 1983.
BRATKO, Ivan. Knowledge-based problem-solving in AL3. In: Machine Intelligence
10 (Hayes, J., Michie, D., Pao, J.H., eds.), Ellis Hoorwood and Wiley, 1982, pp.
73-100. Modified versions appeared in Computer Game Playing: Theory and
Practice (ed. Bramer, M.A.) Ellis Horwood and Wiley, 1983, and in ACM SIGART
Newsletter Special Issue on Game Playing, April 1982.
BRATKO, Ivan, GAMS, Matjaž. Error analysis of the minimax principle. In: Clarke,
M.R.B. (ed.). Advances in Computer Chess. 3. Oxford: Pergamon Press, 1982, pp.
1-15.
KOPEC, Danny, BRATKO, Ivan. The Bratko-Kopec experiment: a comparison of
human and computer performance in chess. In: Clarke, M.R.B. (ed.) Advances in
Computer Chess 3. Pergamon Press, 1982, pp. 57-72.
BRATKO, Ivan, KONONENKO, Igor, MOZETIČ, Igor. An efficient implementation of advice
language 2. Informatica, Vol. 6 (1982), pp. 21-26.
BRATKO, Ivan. Streamlining problem-solving processes. In: Introductory Readings
in Expert Systems (ed. Michie, D.) Gordon & Breach, 1982, pp. 177-191.
BRATKO, Ivan. Symbolic derivation of chess patterns. Proc. ECAI 82 (European
Conf. on Artificial Intelligence). Paris - Orsay, July 1982, pp. 185-189.
14. BRATKO, Ivan. Computer chess: knowledge vs. brute force. Proc. SOFSEM 82, Byli
Kriz - Beskydy, Czechoslovakia, Nov - Dec 1982.
BRATKO, Ivan, MICHIE, D. An advice program for a complex chess programming task.
Computer Journal, Vol. 23 )(1981), pp. 353-359.
ZDRAHAL, Zdenek, BRATKO, Ivan, SHAPIRO, Alen. Recognition of complex patterns using
cellular arrays. Computer Journal, Vol. 24 (1981), pp. 263-270.
BRATKO, Ivan, MULEC, P. An experiment in automatic learning of diagnostic rules.
Informatica, 1980, št. 4, pp. 18-25.
BRATKO, Ivan, MICHIE, D. A representation for pattern-knowledge in chess endgames. In:
Clarke, M. R. B. (ed.). Advances in Computer Chess 2. Edinburgh University Press, 1980, pp.
31-57.
BRATKO, Ivan. Implementing search heuristics using the AL1 advice-taking system.
Proc.IJCAI’79 (6th Int. Joint Conf. on Artificial Intelligence), Tokyo, august 1979,
pp. 95-97.
BRATKO, Ivan, NIBLETT, Tim. Conjectures and refutations in a framework for
representing chess end-game knowledge. In: Expert Systems in the Microelectronic
Age (ed. D. Michie) Edinburgh University Press, 1979, pp. 83-101.
BRATKO, Ivan, KOPEC, Dannny, MICHIE, Donald. Pattern-based representation of
chess end-game knowledge. Computer Journal, Vol. 21 (1978) No. 2, pp. 149-153.
BRATKO, Ivan, MICHIE, Donald. Advice tables representations of chess end-game
knowledge. Proc. AISB/GI Conf. on Artificial Intelligence, Hamburg, 18-20 July
1978, pp. 194-200.
BRATKO, Ivan. Proving correctness of strategies in the AL1 assertional language. Information
Processing Letters, 1978, Vol. 7 (1978), pp. 223-230.
GAMS, Matjaž, BRATKO, Ivan. Computer generation of complete strategies for chess
endgames. Informatica, Vol. 2 (1978), pp. 43-48.