Knowledge-Based Systems

9
th International Conference of Artificial Intelligence and Fuzzy Logic (AI & FL 2021)
provides a forum for researchers who address this issue and to present their work in a peerreviewed forum. Authors are solicited to contribute to the conference by submitting articles that
illustrate research results, projects, surveying works and industrial experiences that describe
significant advances in the following areas, but are not limited to these topics only.
Authors are solicited to contribute to this conference by submitting articles that illustrate
research results, projects, surveying works and industrial experiences that describe significant
advances in the areas of Artificial Intelligence & applications

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.

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 Artificial Intelligence & applications.

We propose a set of methods to classify vendors based on estimated CPU performance and predict CPU performance based on hardware components. For vendor classification, we use the highest and lowest estimated performance and frequency of occurrences of each vendor to create classification zones. These zones can be used to identify vendors who manufacture hardware that satisfy a given performance requirement. We use multi-layered neural networks for performance prediction, which account for nonlinearity in performance data. Various neural network architectures are analysed in comparison to linear, quadratic, and cubic regression. Experiments show that neural networks obtain low error and high correlation between predicted and published performance values, while cubic regression produces higher correlation than neural networks when more data is used for training than testing. An analysis of how the neural network architecture affects prediction is also performed. The proposed methods can be used to identify suitable hardware replacements.

org/seapp/index Scope 11 th International Conference on Software Engineering and Applications (SEAPP 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software Engineering and Applications. The goal of this Conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts and establishing new collaborations in these areas. Authors are solicited to contribute to the Conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of software engineering & applications.

The long-term objective of our project is to develop a knowledge-based tool for Search and Rescue (SAR) operations to support a Canadian search mission coordinator in determining the likely location of a missing aircraft overland. In order to attain this objective, we used a knowledge engineering approach to acquire, structure and model SAR experts’ knowledge. This knowledge was modeled and implemented in a knowledge-based system prototype. The input to the interactive prototype consists of the known information regarding a given SAR case. Its main output is a set of scenarios describing the various hypotheses on what might have happened to the missing aircraft, why and where, the plausible routes followed, as well as the possibility area, defined as the region most likely to contain the missing aircraft. In this paper, we introduce the knowledge model, present an application example and briefly describe the prototype.

Abstract - Information and knowledge engineering is a significant field for various applications on processes around
the globe. This investigation paper provides an overview of the status of development of the concept and how it relates to other areas such as information technology. The area that is of primary concern to this research is the connection with artificial intelligence. There is a revelation that knowledge engineering derives most of its operational domains from the principles of that concept. There is also a strong relation with the area of software development. As the research shows, they both have the same end products and procedures of attaining it. They both produce a computer program that deals with a particular issue in their contexts. The discussion also focuses on the two modeling approaches that are canonical probabilistic and decision based software processes. There is a description of the typical knowledge engineering process that each activity has to go through for efficient operation. The paper also takes a look at of the applications of knowledge-based systems in the industry.

International Journal of Computer Science and Information Security (IJCSIS), Vol. 13, No. 10, October 2015

https://sites.google.com/site/ijcsis/
ISSN 1947-5500

We are increasingly squirming in our different webs, through new and newer transformations in a rapidly evolving world. In order to create a competitive advantage and to stay successfully in the race we have to work in a dynamically changing environment, with increased tension, filled with elements of unpredictability. That‘s why the author tries in this paper to offer a bit of chill out and informational wandering.

From the Wikipedia entry:
"Spacecraft Health Inference Engine (SHINE) is a software-development tool for knowledge-based systems and has been created as a product for research and development by the Artificial Intelligence Group, Information Systems Technology Section at NASA/JPL to meet many of their demanding and rigorous AI goals for current and future needs. The system is now in regular use in basic and applied AI research at JPL. SHINE was developed as a system that was designed to be efficient enough to operate in a real-time environment and to be utilized by non-LISP applications written in conventional programming languages such as C and C++. These non-LISP applications can be running in a distributed computing environment on remote computers or on a computer that supports multiple programming languages. It provides a variety of facilities for the development of software modules for the primary functions in knowledge-based reasoning engines. The system may be used to develop artificial intelligence applications as well as specialized tools for research efforts."

The International Journal of Software Engineering & Applications (IJSEA) is a bi-monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Software Engineering & Applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts & establishing new collaborations in these areas.

This paper focuses on the 'type' of design knowledge used in computational design environments. The paper discuss prototypical information in knowledge-based design systems, and suggests a functional type of knowledge for usage in such systems in order to achieve a degree of generalization in the domain of space design. A function in an architectural space depends on the activities that accomplish it. The paper focuses on human activities and how they may provide the means to semantically describe architectural spaces in different building types.

Simbiyotik kavramı tasarım ortamı ya da sürecinin artık ayrılmaz iki parçası olan bilgisayar ve tasarımcı insan birlikteliğine vurgu amacıyla kullanılıyor. Metin bu ortak yaşamı vurgularken, işlerin bilgisayarsız yürüyüp yürüyemeyeceğine-ya da o döneme-dair bir önerme/ çıkarım geliştirmiyor. Güncel ve yeni olanın herhangi bir yerde değişebileceğine dair akıl yürütme bir başka yazar tarından bir başka metnin konusu olarak işlenebilir.

The present work overviews the application of recom-mender systems in various financial domains. The relevant literature is investigated based on two directions. First, a domain-based cate-gorization is discussed focusing on those recommendation problems, where the existing literature is significant. Second, the application of various recommendation algorithms and data mining techniques is summarized. The purpose of this paper is providing a basis for further scientific research and product development in this field.

The paper attempts to analyze if the sentiment stability of financial 10-K reports over time can determine the company’s future mean returns. A diverse portfolio of stocks was selected to test this hypothesis. The proposed framework downloads 10-K reports of the companies from SEC’s EDGAR database. It passes them through the preprocessing pipeline to extract critical sections of the filings to perform NLP analysis. Using Loughran and McDonald sentiment word list, the framework generates sentiment TF-IDF from the 10-K documents to calculate the cosine similarity between two consecutive 10-K reports and proposes to leverage this cosine similarity as the alpha factor. For analyzing the effectiveness of our alpha factor at predicting future returns, the framework uses the alphalens library to perform factor return analysis, turnover analysis, and for comparing the Sharpe ratio of potential alpha factors. The results show that there exists a strong correlation between the sentiment stability of our portfolio’s 10-K statements and its future mean returns. For the benefit of the research community, the code and Jupyter notebooks related to this paper have been open-sourced on Github1.

With the increasing implementation of Building Information Modeling, the quantity surveyors’ fundamental responsibility of measuring and pricing is being challenged. For the continuation of their professional position within the industry, quantity surveyors need to be able to find information and knowledge based services provided, where requires quantity surveyor’s insight view and analysis on the information from various sources. However, throughout the building process quantity surveyors make decisions based on subjective judgments about the value and quality of the information; still they rarely find the key information to get the task done. The value and quality of information are both different in nature; information quality is context-independent, while the value of information content-dependent. The quality and value of information are inherently difficult to quantify, and so there is a lack of methodologies on assessing information value and quality. The research poses the following challenges to quantity surveyors: "How can we identify high value information within quantity surveying firms? Is it possible to establish a filter mechanism to record the high value information for reusing and help quantity surveyors judging the value of information?" This paper looks to investigate quantity surveyor’s information life-cycle within design centre environment. Investigation throughout people, process, and technology indicate that existing working flow is hard to be changed. At current stage of BIM, its contribution is focusing on bills of quantities. Because of lacking of a sufficient filter mechanism, quantity surveyor can not provide the insight view of information, where already been recorded throughout construction project process, e.g. Life Cycling Costing (LCC). Technology is available on providing such service, but the development on such system is stopped.

This paper presents a baseline perspective of knowledge engineering (KE) methodologies by taking a critical look at the methodological approaches currently used in knowledge engineering domain. A literature review bordering on; the knowledge role concept, knowledge elicitation techniques, and ontological approaches employed in knowledge engineering for the construction of knowledge-based systems (KBSs) was carried out. Journal and conference articles were sourced from multiple journals and research databases and a multi-step manual cross-checking based on carefully selected extraction and quality criteria were employed. The findings of the study show that the existing methodological approaches employed for constructing KBSs in KE is highly deficient and inefficient for solving KE problems under dynamic and uncertain environments. The paper concludes by presenting a strong argument as to why soft systems methodology is best suited for constructing knowledge base systems (KBS) in a spatially distributed, unstructured and shared domain specific context.

—The long jump is a part of track and field event. Also, it has been a standard event in modern Olympic Games. Athletes have to use their strength, skills and effort to make distance as far as possible from a jumping point. The long jump consists of 4 phases: run phase, takeoff phase, flight phase, and landing phase. The actions in each phase effect to the flight distance. If athletes perform right actions in each phase, their performance will be significantly improved prior. In order to have right actions, they need coaching from experts. However, due to the lack of experts in the field, coaching the right actions con not be proceeded widely. In this paper, we propose a framework of an expert system for training long jump athletes by combing computer vision techniques and knowledge management theory. The expert system will capture and learn the right actions of the long jump experts in each phase. Then it will be able to analyse and coach learner/jumper based on knowledge captured from the experts.

The customer's lifetime refers to the relationship between the customer and the organisation in which the organisation can achieve more profit from its customer. The RFM model is based on three variables: recency, frequency, and monetary. The methodology of the present paper is to review the databases of Agricultural Bank of Iran, to review the literature, and to interview with experts using questionnaires. Parameters of the RFM model are limited to five variables in three areas of recency, frequency, and monetary value. Variables are weighed using experts' judgements. The number of data records of customers, 12,359, is then classified into 852 special, 1755 major, and 9373 normal classes through applying a clustering method. In addition, customers are segmented into eight groups by the distance to mean of the three parameters of the model. The results show that the normal customers who form 80% of the total customers have the lowest profitability.

Prior knowledge plays a major role in architectural design. This knowledge pertains to the products and processes of design. Utilizing computers as a design medium requires the representation of such knowledge for reasoning purposes. The choice of what to represent from these concepts (i.e., products and processes) is critical in the utilization of knowledge-based systems in design.
The goals of this research are the enhancement of architectural flexibility and generative capabilities in design environments. Both goals are largely influenced by the knowledge represented in design environments. Architectural flexibility pertains to the compositional diversity required when using this stored knowledge to address the design of different space and building types. Generative capabilities pertain to the application of design processes to propose possible solutions, that add to the explication of the problems we are facing.
The problems of this research pertain to the level and type of decomposition that is applied on the concepts of architectural design, representation of these concepts, and their utilization in knowledge-based design systems. To enhance the flexibility and generation capabilities of design environments, the research proposes to aggregate space functions to the set of human activities that will be performed in them. This functional decomposition provides the basis for refining, adapting, and creating new space types from existing knowledge about human activities. Consequently, building types can be refined, adapted, and created from their functional aggregates (i.e., spaces).
The contributions of this research are based on the ability to represent, manipulate, and create space functions. Consequently, it is possible to describe and manipulate different building types. which achieve the goals of this research. Those contributions are theoretically grounded on cognitive and AI-based design research, and technically examined through the design and implementation of a knowledge-based experimental design environment (APE-1), that is intended to support architects in an early stage of design (i.e., architectural programming).

8th International Conference on Artificial Intelligence (ARIN 2022) is a forum for presenting new advances and research results in the fields of Artificial Intelligence. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. The scope of the conference covers all theoretical and practical aspects of the Artificial Intelligence.

This works investigate the possible relation between three fields of science which are: Architecture, acoustics, And Expert Systems “branch of computer science”. By studying this relation in theater design with taking in account the great effect of the acoustical aspects on the architectural elements. The work focused on the correlative between reverberation time as the main acoustical factor, "sound pressure level as a complementary elements", and all other architectural elements such as area, volume, capacity, shape, dimensions, floor raking, seating, balcony design, and finishing materials.
This relation is complicated and it needs an Acoustician to be there during all design phases, but the work studies the availability to find alternative of the acoustics expert especially at the first stages of design, this goal can be achieved by following the right procedures to build a especial KB ‘knowledge base’ which contain all available information in both fields and the opinion of the experts in each case to solve the problems as the main expert can do by simulating his way of think using AI technique .

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.

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 Artificial Intelligence & applications. Topics of interest include, but are not limited to, the following:

"Advances in Real-Time Artificial Intelligence facilitate the creation of large AI applications. In order to
develop such applications, a methodology that encompasses development techniques, tools and processes
is needed. There are several important lines of research in RTAIS, such as architectures, languages,
methods and methodologies. All of them provide the necessary information and knowledge to build
computers systems to solve real-world problems.
This paper describes CommonKADS-RT, a methodology to analyse and design Real Time Intelligent
Systems. It is based on CommonKADS with the addition of elements necessary to model real-time
restrictions. We also present an application of this approach to examine maritime operation problems. On
this paper we describe the analysis phase."

A good user interface is a necessity for the success of knowledge-based expert systems. Issues such as user requirements, user model and system model have been given insufficient attention in the development of the majority of many such systems, particularly those for design applications. This paper discusses the requirements, the benefits and the problems of building user interfaces for knowledge-based expert systems. The notions of a user model and system model are discussed and their impact on the success of user interfaces considered. The paper concludes with a description of the user interface developed for a knowledge-based design tool for preliminary seismic design of reinforced concrete buildings.

Today, the global education market is one of the faster growing sectors,
and it has attracted several new actors or what we call educational
brokers who are now responsible for shaping national agendas. The
newer actors in education are vastly different for the former players in
that whereas previous actors engrossed national educational systems
through the provision of technical assistance to meet international standards,
best practices, and benchmarks, these newer players are for-profit
entities that emphasize austerity, leanness, human resource maximization,
performance targets, and competition. Therefore, in this new educational
landscape, national governments are seen as “clients” who receive
“expert” advice from “external consultants” that have an assortment of
experiences across different sectors. Education governance is no longer a statist endowed but one that incubates in laborites of best practices resonates
with existing case studies and results driven based on Big Date collected.
We argue that educational brokers are responsible for the
emergence of a hybrid form of education governance that use business
and market techniques to reform strategies within the education sector.
We conclude by suggesting that collectively educational brokers are
using what we call “educational sub-prime mechanisms” -higher interest
rates, reduced quality collateral, and less advantageous terms to
counterweight higher credit risk - to manage educational portfolios and
newer forms of educational risk.

International Conference on Artificial Intelligence Advances (AIAD 2022) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area advanced Artificial Intelligence. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the research area. Core areas of AI and advanced multi-disciplinary and its applications will be covered during the conferences.

The scope of the conference covers all theoretical and practical aspects of the Artificial Intelligence for presenting new advances and research results in the fields of Artificial Intelligence. The wide realms of research addressing any of the significant developments in the below-mentioned broad areas are welcome. The conference invites researchers to submit in the pivotal areas of publication interests.

8 th International Conference on Software Engineering (SOENG 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software Engineering and Applications. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts and establishing new collaborations in these areas. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area advanced Artificial Intelligence. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the research area. Core areas of AI and advanced multidisciplinary and its applications will be covered during the conferences.

8th International Conference on Artificial Intelligence (ARIN 2022) is a forum for presenting new advances and research results in the fields of Artificial Intelligence. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. The scope of the conference covers all theoretical and practical aspects of the Artificial Intelligence.

Scope & Topics
9 th International Conference on Artificial Intelligence & Applications (ARIA 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

The introduction of autonomous vehicles can potentially lead to enhanced situational awareness and safety for road transport. However, the performance required for autonomous operations places stringent requirements on the vehicle navigation systems design. Relevant performance measures include not only the accuracy of the system but also its ability to detect sensor faults within a specified Time-to-Alert (TTA) and without generating an excessive number of false alarms. A new integrated navigation system architecture is proposed which utilizes Global Navigation Satellite Systems (GNSS), low-cost Inertial Navigation Systems (INS), visual odometry and Vehicle Dynamic Models (VDM). The system design is based on various navigation modes, each with independent failure mechanisms and fault-detection capabilities. A two-step data fusion approach is adopted to optimize the system accuracy and integrity performance. This includes a Knowledge-Based Module (KBM) performing a detailed sensor integrity analysis followed by a conventional Extended Kalman Filer (EKF). CAV navigation integrity requirement (i.e., alert limits and time-to-alert) are considered in the KBM where fault detection probabilities are calculated for each mode and translated to protection levels. A simulation case study is executed to verify the performance of each navigation mode in the presence of faults affecting the individual navigation sensors. Results confirm that the required CAV integrity performances are met, while the inclusion of visual odometry and VDM data provides significant performance enhancements both in terms of accuracy and integrity over existing INS/GNSS systems.

11th International Conference on Soft Computing, Artificial Intelligence and Applications (SAI 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Soft Computing. The conference looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.

Scope & Topics 8 th International Conference on Software Engineering (SOENG 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software Engineering and Applications. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts and establishing new collaborations in these areas. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

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.

Ontology has come to gain huge currency in the information sciences, with techniques, applications, and results vastly exceeding the traditional concerns of philosophy. How did that happen? Where are we heading to? I do not have the answers. But I know what it took and what is needed. It took—and we need—the skills of a good Carnapian engineer, someone capable and willing to build bridges across fields even though each side regards them as a troublesome intruder.

11th International Conference on Soft Computing, Artificial Intelligence and Applications
(SAI 2022) will provide an excellent international forum for sharing knowledge and results in
theory, methodology and applications of Artificial Intelligence, Soft Computing. The conference
looks for significant contributions to all major fields of the Artificial Intelligence, Soft
Computing in theoretical and practical aspects. The aim of the conference is to provide a
platform to the researchers and practitioners from both academia as well as industry to meet and
share cutting-edge development in the field.

In this paper, a precise description of the threat evaluation process is presented. This is followed by a review describing which parameters that have been suggested for threat evaluation in an air surveillance context throughout the literature. Threat evaluation is a critical component of the system protecting the defended assets against the hostile targets like aircrafts, missiles, helicopters etc. The degree of threat is evaluated for all possible hostile targets on basis of heterogeneous parameter values extracted from various sensors, to improve the situational awareness and decision making. Taking into consideration the amount of uncertainty involved in the process of threat evaluation for dynamic targets, the fuzzy logic turns out to be a good candidate to model this problem. This model is based on a Fuzzy logic approach, making it possible to handle imperfect observations.  The structure of the Fuzzy Logic is described in detail. Finally, an analysis of the system’s performance as applied to a synthetic static scenario is presented. The simulation results are acceptable and fine and show that this model is reliability.

https://sites.google.com/site/ijcsis/

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.
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 Artificial Intelligence & applications.

8 th International Conference on Artificial Intelligence and Soft Computing (AIS 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology, and applications of Artificial Intelligence, Soft Computing. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

11th  International  Conference  on  Software  Engineering  and  Applications  (SEA  2022)  will  provide
an excellent international forum for sharing knowledge and results in theory, methodology and
applications  of Software Engineering and Applications. The goal of this  conference is  to bring together
researchers  and  practitioners  from  academia  and  industry  to  focus  on  understanding  Modern  software
engineering concepts and establishing new collaborations in these areas.