There is no doubt that custard apple diseases are among the important reasons that destroy the Custard Apple plant and its agricultural crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases is a good step to provide the appropriate and correct treatment. Determining the treatment with high accuracy depends on the method used to correctly diagnose the disease, expert systems can greatly help in avoiding damage to these plants. The expert system correctly (...) diagnoses Custard Apple disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: A specialized syllable language system was established for the diagnosis of Custard Apple plant disease. (shrink)

Diabetes is a major public health issue that affects the nations of our time to a large extent and is described as a non-communicable epidemic. Diabetes mellitus is a common disease where there is too much sugar (glucose) floating around in your blood. This occurs because either the pancreas can’t produce enough insulin or the cells in body have become resistant to insulin. The concentration in this paper is on diagnosis diabetes by designing a proposed expert system. The main goal (...) of this expert system is to get the appropriate diagnosing of the illness, dealing with it quickly, and tips for permanent treatment whenever possible is given out. SL5 object expert system language was used for designing and implementing the proposed expert system. (shrink)

Background: Dengue Disease is a mosquito-borne tropical disease caused by the dengue virus, symptoms typically begin three to fourteen days after infection. This may include a high fever, headache, vomiting, muscle and joint pains, and a characteristic skin rash. Dengue serology is applied in different settings, such as for surveillance, in health care facilities in endemic areas and in travel clinics in non-endemic areas. The applicability and quality of serological tests in dengue endemic regions has to be judged against a (...) background of potential cross reactivity with other flavi-viruses, difficulties in distinguishing primary from secondary infections and technological problems related to the fact that most dengue endemic regions are relatively poor of resources .Objectives: to help doctors and patients in diagnosing Dengue Disease and give them the information of how to prevent Dengue Disease and to be able to understand the signs and symptoms of Dengue Disease. Methods: We collected all relevant material for Dengue Disease. Then we designed and implemented a knowledge based system for diagnosing Dengue Disease using SL5 Object Language. Results: The knowledge based system was evaluated by a group of Patients and specialized doctors and they found it very friendly and easy to use. (shrink)

In this paper a Knowledge-Based System (KBS) for determining the appropriate students major according to his/her preferences for sophomore student enrolled in the Faculty of Engineering and Information Technology in Al-Azhar University of Gaza was developed and tested. A set of predefined criterions that is taken into consideration before a sophomore student can select a major is outlined. Such criterion as high school score, score of subject such as Math I, Math II, Electrical Circuit I, and Electronics I (...) taken during the student freshman year, number of credits passed, student cumulative grade point average of freshman year, among others, were then used as input data to KBS. KBS was designed and developed using Simpler Level Five (SL5) Object expert system language. KBS was tested on three generation of sophomore students from the Faculty of Engineering and Information Technology of the Al-Azhar University, Gaza. The results of the evaluation show that the KBS is able to correctly determine the appropriate students major without errors. (shrink)

Abstract: Background: In spite of the fact that computers continue to improve in speed and functions operation, they remain complex to use. Problems frequently happen, and it is hard to resolve or find solutions for them. This paper outlines the significance and feasibility of building a desktop PC problems diagnosis system. The system gathers problem symptoms from users’ desktops, rather than the user describes his/her problems to primary search engines. It automatically searches global databases of problem symptoms and solutions, and (...) also allows ordinary users to contribute exact problem reports in a structured manner. Objectives: The main goal of this Knowledge Based System is to get the suitable problem desktop PC symptoms and the correct way to solve the errors. Methods: In this paper the design of the proposed Knowledge Based System which was produced to help users of desktop PC in knowing many of the problems and error such as : Power supply problems, CPU errors, RAM dumping error, hard disk errors and bad sectors and suddenly restarting PC. The proposed Knowledge Based System presents an overview about desktop PC hardware errors are given, the cause of fault are outlined and the solution to the problems whenever possible is given out. CLIPS Knowledge Based System language was used for designing and implementing the proposed expert system. Results: The proposed PC desktop troubleshooting Knowledge Based System was evaluated by IT students and they were satisfied with its performance. (shrink)

The cucumber is a creeping vine that roots in the ground and grows up trellises or other supporting frames, wrapping around supports with thin, spiraling tendrils. The plant may also root in a soilless medium, whereby it will sprawl along the ground in lieu of a supporting structure. The vine has large leaves that form a canopy over the fruits. Among these common diseases, we single out the diseases that affect the cucumber, which is affected by about 22 diseases, with (...) different symptoms for each disease. Today, technology is facilitating human life in all areas of life, and among these facilities are expert systems that have become an integral part of human life as they contain several systems and areas, for example: Artificial Intelligence (AI), which refers to systems or devices that simulate Human intelligence to perform tasks that can improve itself based on some human information, and other areas, and with reference to expert systems and their importance to humans, an integrated expert system has been created in the agricultural field that diagnoses cucumber diseases using CLIPS Expert System language Delphi language. The system was used to design and implement the proposed expert system. The system facilitates the diagnosis of cucumber-related diseases. There is no doubt that this expert system will help farmers and those involved in the agricultural field to diagnose cucumber-related diseases. Objectives: is to help farmers diagnose pear diseases in the correct way and how to treat these diseases. Method: The system contains a program that diagnoses 22 diseases that affect cucumber. Results: The expert system was evaluated by farmers and praised for helping them with it. Conclusion: The expert system for diagnosing cucumber diseases is effective and usable. (shrink)

Lung cancer is a serious and deadly disease that affects the lungs, which are responsible for taking in oxygen and expelling carbon dioxide from the body. The disease can develop in any part of the lungs and is usually caused by smoking or exposure to certain chemicals. The main Objective: of this expert system is to provide an accurate diagnosis of lung cancer and the appropriate treatment options. In this paper, Methods: we present the design and implementation of an expert (...) system that can assist physicians in diagnosing lung cancer and determining the best course of treatment. The system provides an overview of the disease, its causes, symptoms, diagnosis, and treatment, along with relevant medical information. Results: The system was developed using the Clips expert system language and evaluated by medical professionals who found it to be an effective tool for diagnosing and treating lung cancer. Conclusion: The proposed expert system has the potential to improve patient outcomes and reduce healthcare costs associated with the treatment of lung cancer. (shrink)

The Knowledge Based System for Diagnosing Breast Cancer is used to assist medical students to improve their education on diagnosis and counseling the process of analyzing the biopsy image of the microscope, determining the type of tumor and the treatment method for each case and identifying the disease related questions. According to the Ministry of Health in its annual report in Gaza, between 2009 and 2014 there are 7069 cases of breast cancer, and in 2014 there are 1502 (...) cases of breast cancer . We are now in the age of visual information where 65% of the populations are visual learners; the Knowledge Based System is the easiest way to ensure students remember the information in the long term, using visual and textual information. The Knowledge Based System has an easy-to-use interface to help students diagnose the disease and enhance their information about the disease; the system can be used on smart phones. This Knowledge Based System can be divided into three main parts: The first part is specific questions for the patient, to help student to know questions type. The second part is the process of analyzing the biopsy sample image, to see if the biopsy image is intact or infected. The last part is the video shows ways to treat breast cancer in the form of animation. (shrink)

Diagnosing flatulence involves a thorough assessment of an individual's symptoms, medical history, and, if necessary, the use of diagnostic tests. Healthcare providers gather information about the patient's medical background and conduct a physical examination to identify any signs of gastrointestinal issues. Dietary habits are evaluated, and potential triggers are identified through an elimination diet. Diagnostic tests such as breath tests, stool analysis, or imaging studies may be performed to further investigate the underlying causes of excessive flatulence. Accurate diagnosis is crucial (...) for effective management and treatment of flatulence, enabling individuals to gain control over their symptoms and address any underlying conditions. (shrink)

Background: Persimmon is a grassy, perennial plant, belonging to the oral platoon, square-shaped leg, bifurcated, erect, and ranging in height from (10 - 201 cm). Home to Europe and Asia. The Persimmon plant has many benefits, the most important of which are pain relief, treatment of gallbladder disorders, the expulsion of gases, anti-inflammatory, and relaxing nerves. While the Persimmon plant is the ideal option for the start of gardens, it is prone to some common diseases that affect the plant's growth. (...) Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help Farmers and those interested in agriculture in diagnosing many of the Persimmon diseases such as Persimmon rust, Verticillium wilt, Anthracnose, Powdery mildew, Black Stem Rot, Stem and stolon canker, Septoria leaf spot. The proposed expert system presents an overview of Persimmon diseases are given, the cause of diseases outlined and the treatment of disease whenever possible is given out. CLIPS Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Persimmon diseases diagnosis expert system was evaluated by Agricultural Students at AL Azhar University and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture. (shrink)

A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used (...) to extract knowledge from a clinical dataset. The PART algorithm achieved the highest performance result with 98.06% accuracy under 10-fold cross-validation, and the generated rules were used to develop the knowledge-based system. The system achieved 90.9% accuracy in system performance testing and 89.2% in user acceptance testing, and is intended to serve as an assistant tool for healthcare experts. (shrink)

Abstract: background: Dental and oral health is an essential part of your overall health and well-being. Poor oral hygiene can lead to dental cavities and gum disease, and has also been linked to heart disease, cancer, and diabetes. Maintaining healthy teeth and gums is a lifelong commitment. The earlier you learn proper oral hygiene habits — such as brushing, flossing, and limiting your sugar intake — the easier it’ll be to avoid costly dental procedures and long-term health issues. (Healthline, n.d.) (...) Objectives The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment by presenting suggestions on Tooth Problems to the user by asking about symptoms. (shrink)

Recently, Intelligent Tutoring Systems (ITS) got much attention from researchers even though ITS educational technology began in the late 1960s and ITS is just embryonic from laboratories into the field. In this paper we outline an intelligent tutoring system for teaching basics of the databases system called (MDB). The MDB was built as education system by using the authoring tool (ITSB). MDB contains learning materials as a group of lessons for beginner level which include relational database system and lessons (...) in the process to install and set up a database. MDB system has exams for each level of the Lessons. An evaluation was done to see the effectiveness the MDB among learners and instructors. The outcome of the evaluation was promising. (shrink)

We describe and try to motivate our project to build systems using both a knowledge based and a neural network approach. These two approaches are used at different stages in the solution of a problem, instead of using knowledge bases exclusively on some problems, and neural nets exclusively on others. The knowledge base (KB) is defined first in a declarative, symbolic language that is easy to use. It is then compiled into an efficient neural network (...) (NN) representation, run, and the results from run time and (eventually) from learning are decompiled to a symbolic description of the knowledge contained in the network. After inspecting this recovered knowledge, a designer would be able to modify the KB and go through the whole cycle of compiling, running, and decompiling again. The central question with which this project is concerned is, therefore, How do we go from a KB to an NN, and back again? We are investigating this question by building tools consisting of a repertoire of language/translation/network types, and trying them on problems in a variety of domains. (shrink)

In this chapter I highlight the apparent tensions between Kant’s very stringent critique of metaphysical speculation in the “Discipline of Pure Reason” chapter and his endorsement of Belief (Glaube) and hope (Hoffnung) regarding metaphysical theses in the subsequent “Canon of Pure Reason.” In the process I will examine his distinction between the theoretical and the practical bases for holding a “theoretical” conclusion (i.e. a conclusion about “what exists” rather than “what ought to be”) and argue that the position is subtle (...) but coherent. In the second part of the paper I focus on Kant’s account of rational hope in the Doctrine of Method: its nature, scope, conditions, and role in the philosophy of religion generally. (shrink)

Recently, Intelligent Tutoring Systems (ITS) got much attention from researchers even though ITS educational technology began in the late 1960s and ITS is just embryonic from laboratories into the field. In this paper we outline an intelligent tutoring system for teaching basics of the databases system called (MDB). The MDB was built as education system by using the authoring tool (ITSB). MDB contains learning materials as a group of lessons for beginner level which include relational database system and lessons (...) in the process to install and set up a database. MDB system has exams for each level of the Lessons. An evaluation was done to see the effectiveness the MDB among learners and instructors. The outcome of the evaluation was promising. (shrink)

Philosophical investigation in synthetic biology has focused on the knowledge-seeking questions pursued, the kind of engineering techniques used, and on the ethical impact of the products produced. However, little work has been done to investigate the processes by which these epistemological, metaphysical, and ethical forms of inquiry arise in the course of synthetic biology research. An attempt at this work relying on a particular area of synthetic biology will be the aim of this chapter. I focus on the reengineering (...) of metabolic pathways through the manipulation and construction of small DNA-based devices and systems synthetic biology. Rather than focusing on the engineered products or ethical principles that result, I will investigate the processes by which these arise. As such, the attention will be directed to the activities of practitioners, their manipulation of tools, and the use they make of techniques to construct new metabolic devices. Using a science-in-practice approach, I investigate problems at the intersection of science, philosophy of science, and sociology of science. I consider how practitioners within this area of synthetic biology reconfigure biological understanding and ethical categories through active modelling and manipulation of known functional parts, biological pathways for use in the design of microbial machines to solve problems in medicine, technology, and the environment. We might describe this kind of problem-solving as relying on what Helen Longino referred to as “social cognition” or the type of scientific work done within what Hasok Chang calls “systems of practice”. My aim in this chapter will be to investigate the relationship that holds between systems of practice within metabolic engineering research and social cognition. I will attempt to show how knowledge and normative valuation are generated from this particular network of practitioners. In doing so, I suggest that the social nature of scientific inquiry is ineliminable to both knowledge acquisition and ethical evaluations. (shrink)

In this article, I explore the consequences of two commonsensical premises in semantics and epistemology: (1) natural language is a complex system rooted in the communal life of human beings within a given environment; and (2) linguistic knowledge is essentially dependent on natural language. These premises lead me to emphasize the process-socio-environmental character of linguistic meaning and knowledge, from which I proceed to analyse a number of long-standing philosophical problems, attempting to throw new light upon them on these (...) grounds. In particular, I criticize the use of expressions such as ‘absolute truth’, ‘absolute existence’ and ‘the thing in itself’, arguing that they lead to what I call ‘the ultralinguistic paradox’ (a fatal antinomy). In the same way, I review a number of mainstream topics in philosophical semantics, epistemology and metaphysics, reformulating them in terms much more naturalistic – and less mysterious – than usual. (shrink)

A. Newell and H. A. Simon were two of the most influential scientists in the emerging field of artificial intelligence (AI) in the late 1950s through to the early 1990s. This paper reviews their crucial contribution to this field, namely to symbolic AI. This contribution was constituted mostly by their quest for the implementation of general intelligence and (commonsense) knowledge in artificial thinking or reasoning artifacts, a project they shared with many other scientists but that in their case was (...) theoretically based on the idiosyncratic notions of symbol systems and the representational abilities they give rise to, in particular with respect to knowledge. While focusing on the period 1956-1982, this review cites both earlier and later literature and it attempts to make visible their potential relevance to today's greatest unifying AI challenge, to wit, the design of wholly autonomous artificial agents (a.k.a. robots) that are not only rational and ethical, but also self-conscious. (shrink)

Disaster response is a highly collaborative and critical process that requires the involvement of multiple emergency responders (ERs), ideally working together under a unified command, to enable a rapid and effective operational response. Following the 9/11 and 11/13 terrorist attacks and the devastation of hurricanes Katrina and Rita, it is apparent that inadequate communication and a lack of interoperability among the ERs engaged on-site can adversely affect disaster response efforts. Within this context, we present a scenario-based terrorism case study (...) to highlight the challenges of operational disaster command and response. In this article, which is based on the French emergency response doctrine, we outline a semantics-based common operational command system that is designed to guarantee an efficient information flow among ERs. Our focus is on offering to all ERs, a real-time operational picture of the situation in order to enable multilevel coordination among firefighters, police, healthcare units, public authorities, and other stakeholders. Our approach consolidates information to promote timely sharing of data among ERs. The proposed system is based on an ontology that has been developed to represent the different types of knowledge on the part of ERs, providing a shared vocabulary that covers a variety of interoperability concerns. (shrink)

In this paper, we analyse how GPS-based navigation systems are transforming some of our intellectual virtues and then suggest two strategies to improve our practices regarding the use of such epistemic tools. We start by outlining the two main approaches in virtue epistemology, namely virtue reliabilism and virtue responsibilism. We then discuss how navigation systems can undermine five epistemic virtues, namely memory, perception, attention, intellectual autonomy, and intellectual carefulness. We end by considering two possible interlinked ways of (...) trying to remedy this situation: [i] redesigning the epistemic tool to improve the epistemic virtues of memory, perception, and attention; and [ii] the cultivation of cognitive diligence for wayfinding tasks scaffolding intellectual autonomy and carefulness. (shrink)

The present article is an attempt to give - in the frame of the theory of the organism - environment system - a new interpretation to the role of efferent influences on receptor activity and to the functions of senses in the formation of knowledge. It is argued, on the basis of experimental evidence and theoretical considerations, that the senses are not transmitters of environmental information, but they create a direct connection between the organism and the environment, which makes (...) the development of a dynamic living system, the organism - environment system, possible. In this connection process the efferent influences on receptor activity are of particular significance, because with their help the receptors may be adjusted in relation to the parts of the environment which are most important in the achievement of behavioral results. Perception is the process of joining of new parts of the environment to the organism - environment system ; thus, the formation of knowledge by perception is based on reorganization of the organism - environment system, and not on transmission of information from the environment. With the help of the efferent influences on receptors each organism creates its own peculiar world which is simultaneously subjective and objective. The present considerations have far reaching influences as well on experimental work in neurophysiology and psychology of perception as on philosophical considerations of knowledge formation. (shrink)

Our gums (gingiva) act as a significant barricade in guarding our teeth and their neighboring support structures. A tiny known fact is that gum disease is the foremost cause of tooth loss in grown persons. Healthy, strong, teeth are reliant on on healthy gums. The core culprit for gum problems is bacteria in dental plaque. The bacteria in plaque yield harmful toxins that generate an inflammatory process that happens in the gum tissue. If left for a sufficient period of time, (...) bacterial plaque causes hurt to our teeth as well as our gums. In this paper, we present a knowledge based system that help people with teeth and gums problems to diagnose their problems and get recommendation for the treatment. This expert system was designed and implemented using SL5 Object language for knowledge based system. (shrink)

International regulation of autonomous weapon systems (AWS) is increasingly conceived as an exercise in risk management. This requires a shared approach for assessing the risks of AWS. This paper presents a structured approach to risk assessment and regulation for AWS, adapting a qualitative framework inspired by the Intergovernmental Panel on Climate Change (IPCC). It examines the interactions among key risk factors—determinants, drivers, and types—to evaluate the risk magnitude of AWS and establish risk tolerance thresholds through a risk matrix informed (...) by background knowledge of event likelihood and severity. Further, it proposes a methodology to assess community risk appetite, emphasizing that such assessments and resulting tolerance levels should be determined through deliberation in a multistakeholder forum. The paper highlights the complexities of applying risk-based regulations to AWS internationally, particularly the challenge of defining a global community for risk assessment and regulatory legitimization. (shrink)

Chest pain is the pain felt in the chest by infants, children and adolescents. In most cases the pain is not associated with the heart. It is mainly recognized by the observance or report of pain by the infant, child or adolescent by reports of distress by parents or care givers. Chest pain is not unusual in children. Lots of children are seen in ambulatory clinics, emergency rooms and hospitals and cardiology clinics. Usually there is a benign cause for the (...) pain for utmost children. Certain patients have conditions that are serious and perhaps life-threatening. Chest pain in pediatric patients needs careful physical examination and a detailed history that would point to the possibility of a serious cause. Researches of pediatric chest pain are scarce. It has been difficult to create evidence-based guidelines for evaluation. In this paper we propose an expert system to help doctors and parents, and care giver in diagnosing chest pain in infants and children. This expert System is design and implemented in SL5 Object language. (shrink)

Tinnitus is a common condition characterized by the perception of sound in the absence of an external source, with potential negative physical and psychological impacts. Accurate and efficient diagnosis of tinnitus is crucial for appropriate treatment and management. Traditional diagnostic methods have limitations in terms of time, cost, and accuracy. To address these challenges, expert systems have emerged as a promising tool for tinnitus diagnosis. This paper explores the application of expert systems in tinnitus diagnosis, highlighting their potential (...) to improve accuracy and efficiency. By incorporating a knowledge base and rule-based decision-making, expert systems can provide valuable insights for accurate diagnosis and appropriate management of tinnitus. Further research and development in this area can enhance the clinical assessment and treatment of tinnitus, ultimately improving the quality of life for affected individuals. (shrink)

The study aimed to identify the knowledge management processes and their role in achieving competitive advantage at Al-Quds Open University. The study was based on the descriptive analytical method, and the study population consists of academic and administrative staff in each of the branches of Al-Quds Open University in (Tulkarm, Nablus and Jenin). The researchers selected a sample of the study population by the intentional non-probability method, the size of (70) employees. A questionnaire was prepared and supervised by (...) a number of specialists in order to obtain the results of the study. The study concluded that there is a positive direct relationship, that is, the higher the degree of application of knowledge management processes, the greater the degree of competitive advantage. Knowledge Technology came first with a score of 80.02% on all items. Competitive advantage came second with 81.74%. In the third place came "knowledge generation" where the total score on all paragraphs in this area (78.24%). In the fourth place, "knowledge transfer" (77.21%). "Developing and storing knowledge" came in fifth place (77.13%). "Acquisition of knowledge" came in sixth place (76.45%). Knowledge Organization ranked seventh (74.26%). The study recommended that the university should enable the employees to benefit from the experiences and expertise available to help generate knowledge. The University encourages the creation of knowledge through the system of incentives and open the way for creators to apply their creations and spread and invest in excellence and creativity. The university should design work performance levels based on the integration of knowledge and organize it according to policies that support freedom of research. The need for Palestinian universities to adopt a knowledge management approach. The need to adopt a system of incentives that rewards cognitive efforts, and give workers enough freedom to enable them to apply their knowledge. (shrink)

Migraine is a complex neurological disorder characterized by recurrent moderate to severe headaches, accompanied by additional symptoms such as nausea, sensitivity to light and sound, and visual disturbances. Accurate and timely diagnosis of migraines is crucial for effective management and treatment. However, the diverse range of symptoms and overlapping characteristics with other headache disorders pose challenges in the diagnostic process. In this research, we propose the development of an expert system for migraine diagnosis using artificial intelligence and the CLIPS (C (...) Language Integrated Production System) framework. The expert system utilizes a rule-based inference engine to analyze patient-reported symptoms and provide reliable diagnoses or probability scores indicating the likelihood of migraine. The knowledge base of the expert system is designed based on expert knowledge obtained from medical professionals specializing in migraines. The collected knowledge is translated into a structured format suitable for the CLIPS inference engine, incorporating rules and facts to represent the diagnostic criteria and associated symptoms. The system prompts users to provide relevant information about their symptoms, medical history, and potential triggers. It applies the defined rules and facts to evaluate the likelihood of migraine and generate accurate diagnoses or probability scores. Preliminary evaluation results demonstrate the potential of the expert system as a valuable tool for diagnosing migraines. A dataset of anonymized patient records with confirmed migraine cases was used to test the system. The diagnoses generated by the expert system were compared against the known diagnoses, and a high level of accuracy was observed, with 90% of cases correctly diagnosed as migraines. These results highlight the effectiveness and reliability of the system in assisting medical professionals in the diagnosis of migraines. The proposed expert system offers several advantages for migraine diagnosis. It leverages the collective knowledge and expertise of experienced migraine specialists, providing a standardized and consistent approach to diagnosis. The system can handle large amounts of patient data and effectively analyse complex relationships between symptoms, risk factors, and diagnostic criteria. Furthermore, it offers real-time feedback and recommendations, supporting medical professionals in their clinical decision-making process. Future work involves refining the expert system based on feedback from medical experts, expanding the knowledge base to encompass a wider range of symptoms and risk factors, and conducting further evaluations to enhance its accuracy and applicability in clinical settings. The development of an expert system for migraine diagnosis has the potential to improve the diagnostic process, leading to more effective management and treatment strategies for individuals suffering from migraines. (shrink)

Mouth ulcers, also known as canker sores, are a common oral health issue affecting a significant portion of the population. Early and accurate diagnosis of mouth ulcers is crucial for effective treatment and prevention of complications. This paper presents an expert system developed using CLIPS (C Language Integrated Production System) to diagnose mouth ulcer disease. The expert system utilizes a rule-based approach, incorporating a comprehensive knowledge base consisting of symptoms, risk factors, and medical literature related to mouth ulcers. (...) By employing an inference engine, the system evaluates patient input against the rules and generates a diagnosis based on the matching symptoms and relevant factors. The system also provides detailed explanations and recommendations for each diagnosis, aiding healthcare professionals and patients in understanding the condition and selecting appropriate treatment options. The development and validation of the expert system involved a multi-step process, including knowledge acquisition, rule formulation, and testing against a diverse dataset of mouth ulcer cases. The system's performance was evaluated by comparing its diagnoses with those made by medical professionals, demonstrating a high level of accuracy and consistency. The implementation of an expert system for diagnosing mouth ulcer disease offers several advantages, including the ability to provide timely and accessible healthcare services, reduce misdiagnosis rates, and assist healthcare professionals in decision-making processes. Moreover, it empowers individuals to make informed decisions about their health and seek appropriate medical intervention. This paper contributes to the field of medical expert systems by showcasing the practical application of CLIPS in the diagnosis of mouth ulcer disease. The results demonstrate the potential of expert systems as valuable tools for healthcare professionals and patients alike, enhancing the efficiency and accuracy of diagnosis in oral health care. (shrink)

The truth of every human being is the end his life with death, and this leads to leaving assets and funds for those after him and can lead to hate between the heirs, it has made a point of Islamic law on all aspects of life, including the subject of the inheritance of the deceased. The main problem is how to get the knowledge of the basics of inheritance. This paper reviews work done in the use of expert system (...) software to calculate inheritance in Islam. A proposed expert system was designed and developed using CLIPS language to calculate the inheritance in Islam. (shrink)

Learning programming is thought to be troublesome. One doable reason why students don’t do well in programming is expounded to the very fact that traditional way of learning within the lecture hall adds more stress on students in understanding the Material rather than applying the Material to a true application. For a few students, this teaching model might not catch their interest. As a result, they'll not offer their best effort to grasp the Material given. Seeing however the information is (...) applied to real issues will increase student interest in learning. As a consequence, this may increase their effort to be taught. In the current paper, we try to help students learn C# programming language using Intelligent Tutoring System. This ITS was developed using ITSB authoring tool to be able to help the student learn programming efficiently and make the learning procedure very pleasing. A knowledge base using ITSB authoring tool style was used to represent the student's work and to give customized feedback and support to students. (shrink)

In this article we present an advanced version of Dual-PECCS, a cognitively-inspired knowledge representation and reasoning system aimed at extending the capabilities of artificial systems in conceptual categorization tasks. It combines different sorts of common-sense categorization (prototypical and exemplars-based categorization) with standard monotonic categorization procedures. These different types of inferential procedures are reconciled according to the tenets coming from the dual process theory of reasoning. On the other hand, from a representational perspective, the system relies on the (...) hypothesis of conceptual structures represented as heterogeneous proxytypes. Dual-PECCS has been experimentally assessed in a task of conceptual categorization where a target concept illustrated by a simple common-sense linguistic description had to be identified by resorting to a mix of categorization strategies, and its output has been compared to human responses. The obtained results suggest that our approach can be beneficial to improve the representational and reasoning conceptual capabilities of standard cognitive artificial systems, and –in addition– that it may be plausibly applied to different general computational models of cognition. The current version of the system, in fact, extends our previous work, in that Dual-PECCS is now integrated and tested into two cognitive architectures, ACT-R and CLARION, implementing different assumptions on the underlying invariant structures governing human cognition. Such integration allowed us to extend our previous evaluation. (shrink)

Abstract: Background: In spite of the fact that computers continue to improve in speed and functions operation, they remain complex to use. Problems frequently happen, and it is hard to resolve or find solutions for them. This paper outlines the significance and feasibility of building a desktop PC problems diagnosis system. The system gathers problem symptoms from users’ desktops, rather than the user describes his/her problems to primary search engines. It automatically searches global databases of problem symptoms and solutions, and (...) also allows ordinary users to contribute exact problem reports in a structured manner. Objectives: The main goal of this Knowledge Based System is to get the suitable problem desktop PC symptoms and the correct way to solve the errors. Methods: In this paper the design of the proposed Knowledge Based System which was produced to help users of desktop PC in knowing many of the problems and error such as : Power supply problems, CPU errors, RAM dumping error, hard disk errors and bad sectors and suddenly restarting PC. The proposed Knowledge Based System presents an overview about desktop PC hardware errors are given, the cause of fault are outlined and the solution to the problems whenever possible is given out. CLIPS Knowledge Based System language was used for designing and implementing the proposed expert system. Results: The proposed PC desktop troubleshooting Knowledge Based System was evaluated by IT students and they were satisfied with its performance. (shrink)

Larry Moss and Rohit Parikh used subset semantics to characterize a family of logics for reasoning about knowledge. An important feature of their framework is that subsets always decrease based on the assumption that knowledge always increases. We drop this assumption and modify the semantics to account for logics of knowledge that handle arbitrary changes, that is, changes that do not necessarily result in knowledge increase, such as the update of our knowledge due to (...) an action. We present a system which is complete for subset spaces and prove its decidability. (shrink)

Inventing novel knowledge to solve problems is a crucial, creative, mechanism employed by humans, to extend their range of action. In this paper, we present TCL (typicality-based compositional logic): a probabilistic, non monotonic extension of standard Description Logics of typicality, and will show how this framework is able to endow artificial systems of a human-like, commonsense based, concept composition procedure that allows its employment in a number of applications (ranging from computational creativity to goal-based reasoning (...) to recommender systems and affective computing). -/- The framework relies on 3 main ingredients: a non monotonic extension of standard Description Logics (allowing to reason on exceptions to inheritance in standard knowledge bases) a probabilistic extension coming from the field of logic programming (the DISPONTE semantics) a cognitive heuristics known ad HEAD-Modifier determining preference rules for the inheritance mechanisms of the novel concepts to be generated via commonsense rules. -/- We report the obtained results and the lessons learned of this research path in the context of model-based AI applications. -/- . (shrink)

Three classic distinctions specify that truths can be necessary versus contingent,analytic versus synthetic, and a priori versus a posteriori. The philosopher reading this article knows very well both how useful and ordinary such distinctions are in our conceptual work and that they have been subject to many and detailed debates, especially the last two. In the following pages, I do not wish to discuss how far they may be tenable. I shall assume that, if they are reasonable and non problematic (...) in some ordinary cases, then they can be used in order to understand what kind of knowledge the maker’s knowledge is. By this I mean the sort of knowledge that Alice enjoys when she holds the information that Bob’s coffee is sweetened because she just put two spoons of sugar in it herself. The maker’s knowledge tradition is quite important but it is not mainstream in modern and analytic epistemology and lacks grounding in terms of exactly what sort of knowledge one is talking about. My suggestion is that this grounding can be provided by a minimalist approach, based on an information-theoretical analysis. In the article, I argue that we need to decouple a fourth distinction, namely informative versus uninformative, from the previous three and, in particular, from its implicit association with analytic versus synthetic and a priori versus a posteriori; such a decoupling facilitates, and is facilitated by, moving from a monoagent to a multiagent approach: the distinctions qualify a proposition, a message, or some information not just in themselves but relationally, with respect to an informational agent; the decoupling and the multiagent approach enable a re-mapping of currently available positions in epistemology on these four dichotomies; within such a re-mapping, two positions, capturing the nature of a witness’ knowledge and of a maker’s knowledge, can best be described as contingent, synthetic, a posteriori, and uninformative and as contingent, synthetic, weakly a priori, and uninformative respectively. In the conclusion, I indicate why the analysis of the maker’s knowledge has important consequences in all those cases in which the poietic intervention on a system determines the truth of the model of that system. (shrink)

Physical systems without time and dynamics have been considered. The principle of how to construct spacetime in a physical system without time and dynamics has been proposed. It has been found what can be objects in such a spacetime, and what can be an interaction between such objects. Within the framework of the considered class of systems, answers to the following problems of philosophy and physics have been found: the nature of consciousness and the connection of body and (...) consciousness (mind-body problem), the nature of time, the anthropic principle and the problem of fine-tuning the universe, the effectiveness of mathematics in describing physical phenomena, the limits of knowledge. There are a number of indications that our Universe is not based on one of the systems of the class considered. The considered class of systems makes it possible to find answers to questions that cannot be answered for our Universe. This shows that it is fundamentally possible to find answers to these questions for our Universe as well. (shrink)

The evolution from pre-human primates to modern Homo sapiens is a complex one involving many domains, ranging from the material to the social to the cognitive, both at the individual and the community levels. This article focuses on a critical qualitative transition that took place during this evolution involving both the social and the cognitive domains. For the social domain, the transition is from the face-to-face forms of social interaction and organization that characterize the non-human primates that reached, with Pan, (...) a hiatus due to the centripetal effects that highly individualized behavior has on a social system. The transition is to the relation-based forms of social organization that evolved in the hominins ancestral to Homo sapiens and are universal in human societies today. For the cognitive domain, this transition involves going from behavior responding mainly to phenomenal level sensory inputs to behavior formed in accordance with the concept of a relation, initially abstracted from behavior patterns, then extending the concept of a relation beyond abstraction from behavior patterns to the concept of a relation generated recursively through constructing the relation of a relation. This extension made possible the construction of systems of relations; initially genealogical systems of relations constructed culturally using the logic of recursion, and subsequently, the symbolic, computational systems of kin term relations referred to by anthropologists as kinship terminologies. The latter are “constructed realities” in the sense this term is used by cultural anthropologists. It follows that the evolution of relation-based systems of social interaction is not adequately accounted for through population model evolutionary accounts such as the Dual Inheritance Theory of human evolution since “constructed realities” constitute collectively and publicly shared cultural knowledge rather than the individually and privately possessed knowledge that is assumed in the population model framework for human evolution. (shrink)

With increasing publication and data production, scientific knowledge presents not simply an achievement but also a challenge. Scientific publications and data are increasingly treated as resources that need to be digitally ‘managed.’ This gives rise to scientific Knowledge Management : second-order scientific work aiming to systematically collect, take care of and mobilise first-hand disciplinary knowledge and data in order to provide new first-order scientific knowledge. We follow the work of Leonelli, Efstathiou and Hislop in our analysis (...) of the use of KM in semantic systems biology. Through an empirical philosophical account of KM-enabled biological research, we argue that KM helps produce new first-order biological knowledge that did not exist before, and which could not have been produced by traditional means. KM work is enabled by conceiving of ‘knowledge’ as an object for computational science: as explicated in the text of biological articles and computable via appropriate data and metadata. However, these founded knowledge concepts enabling computational KM risk focusing on only computationally tractable data as knowledge, underestimating practice-based knowing and its significance in ensuring the validity of ‘manageable’ knowledge as knowledge. (shrink)

In this work we present an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework (i.e. the TCL logic, see Lieto & Pozzato 2020) which is based on a human-like procedure for the automatic generation of novel concepts in a Description Logics knowledge base (see also Lieto et al. 2019, Chiodino et al. 2020 for other applications). In particular, in order to model human-like forms (...) of concept combinations, the TCL logic combines a probabilistic description logics of typicality with the HEAD-MODIFIER heuristics coming from cognitive semantics. In the context of our application of such framework, our system exploits the logic TCL to automatically generate novel commonsense semantic representations of compound emotions (e.g. Love as derived from the combination of Joy and Trust according to Plutchik’s theory of emotions, see Plutchik 2001). The generated emotions corresponds to prototypes, i.e. commonsense representations of given concepts, and have been used to reclassify emotion-related contents in a variety of artistic domains. We have tested our system in the context of the H2020 EU project SPICE for providing artistic recommendations of museum items in the Galleria di Arte Moderna (GAM) of Turin. The obtained results (reported in Lieto et al, 2021 and Lieto at al., to appear) show promising results for what concerns both the acceptance of the provided affective recommendation and the explainability associated to each suggestion made by the users. Here we discuss, the open problems and the lessons learned. -/- . (shrink)

Dynamic conceptual reframing represents a crucial mechanism employed by humans, and partially by other animal species, to generate novel knowledge used to solve complex goals. In this talk, I will present a reasoning framework for knowledge invention and creative problem solving exploiting TCL: a non-monotonic extension of a Description Logic (DL) of typicality able to combine prototypical (commonsense) descriptions of concepts in a human-like fashion [1]. The proposed approach has been tested both in the task of goal-driven concept (...) invention [2,3] and has additionally applied within the context of serendipity-based recommendation systems [4]. I will present the obtained results, the lessons learned, and the road ahead of this research path. -/- . (shrink)

This essay explores the connection between theories of the self and theories of self-knowledge, arguing (a) that empirical results strongly support a certain negative thesis about the self, a thesis about what the self isn’t, and (b) that a more promising account of the self makes available unorthodox – but likely apt – ways of characterizing self-knowledge. Regarding (a), I argue that the human self does not appear at a personal level the autonomous (or quasi-autonomous) status of which (...) might provide a natural home for a self that can be investigated reliably from the first-person perspective, independent of the empirical sciences. Regarding (b), I contend that the most promising alternative view of the self is revisionary: the self is to be identified with the cognitive system as a whole, the relatively integrated collection of mechanisms that produces intelligent behavior (Rupert 2009, 2010, 2019). The cognitive system teems with reliable, though not necessarily perfect, indicators (cf. Dretske 1988) of its own properties or of the properties of its proper parts, many of which are available for detection by, or the control of, further processes, such as motor control. I argue that indicating states should be treated as potential vehicles of self-knowledge, regardless of whether they are truth-evaluable states, such as beliefs. The investigation of self and self-knowledge frames discussion of a final topic, of some gravity: the way in which self-knowledge might contribute to self-improvement. In this regard, I emphasize the efficacy of certain forms of alignment between, on the one hand, elements of the cognitive system corresponding to a more commonsense-based conception of the self and, on the other hand, processes associated with what is frequently referred to as ‘implicit’ cognitive processing (Evans and Frankish 2009). (shrink)

Mango is an economically significant fruit crop cultivated in various tropical and subtropical regions around the world. However, the productivity and quality of mangoes can be severely impacted by a range of pests. This research paper introduces an innovative approach to identify mango pests using an expert system. The expert system integrates knowledge from entomology and plants to provide accurate identification of common mango pests. The paper outlines the development and implementation of the expert system using Clips shell, which (...) utilizes rule-based techniques to analyze symptoms associated with mango pests. By inputting observed symptoms, such as leaf spots, fruit damage, leaf mild and stem cankers the system can accurately identify the specific pest species affecting the mango tree. For each pest, the paper discusses their specific symptoms and Favorable conditions that affect the mango plant. By understanding the identification and symptoms of these pests, mango growers and agricultural professionals can implement appropriate pest management strategies to mitigate the economic losses caused by these insects. The research presented in this paper aims to contribute to the body of knowledge on mango pest management, facilitating sustainable mango production and ensuring the availability of high-quality mangoes in global markets. (shrink)

In the first months of the COVID-19 pandemic, we created and implemented from November 2020 to February 2021 a monthly educational pilot program of philosophical management of stress based on Science, Humanism and Epicurean Pragmatism, which was offered to employees of 26 municipalities in the Prefecture of Attica, Greece. The program named “Philosophical Distress Management Operation System” (Philo.Di.M.O.S.) is novel and unique in its kind, as it combines a certain Greek philosophical tradition (Epicurean) that concurs with modern scientific (...) class='Hi'>knowledge. The program was designed to be implemented in a period of crisis; therefore, it used a fast-paced, easy to learn and practice philosophical approach to stress management, based on cognitive psychotherapy. The philosophical approach to stress management has the advantage that it can be offered to most people, regardless of age and educational level. The pilot program was effective in achieving its objectives, shown by statistical comparisons of the trainees’ responses to anonymous questionnaires before and after the month-long training. The successful Philo.Di.M.O.S. program, thus, based on a solid scientific and philosophical basis, offers a paradigm of stress management during crises and could be useful in Greece and internationally. (shrink)

Empiricist modal epistemologies can be attractive, but are often limited in the range of modal knowledge they manage to secure. In this paper, I argue that one such account – similarity-based modal empiricism – can be extended to also cover justification of many scientifically interesting possibility claims. Drawing on recent work on modelling in the philosophy of science, I suggest that scientific modelling is usefully seen as the creation and investigation of relevantly similar epistemic counterparts of real target (...) systems. On the basis of experiential knowledge of what is actually the case with the models, one can draw justified conclusions about what is de re possible for the target systems. (shrink)

Emotion recognition systems (ERS) offer the ability to identify the emotions of others, based on an analysis of their facial expressions and regardless of culture, ethnicity, context, gender or social class. By claiming universalism in the expression as well as in the recognition of emotions, we believe that ERS present significant risks of causing great harm to some individuals, in addition to targeting, in some contexts, specific social groups. Drawing on a wide range of multidisciplinary knowledge - (...) including philosophy, psychology, computer science and anthropology - this research project aims to identify the current limitations of ERS and the main risks that their use brings, with the goal of providing a clear and robust analysis of the use of ERS and their contribution to greater social justice. Pointing to technical limitations, we refute, on the one hand, the idea that ERS are able to prove the causal link between specific emotions and specific facial expressions. We support our argument with evidence of the inability of ERS to distinguish facial expressions of emotions from facial expressions as communication signals. On the other hand, due to the contextual and cultural limitations of current ERS, we refute the idea that ERS are able to recognise, with equal performance, the emotions of individuals, regardless of their culture, ethnicity, gender and social class. Our ethical analysis shows that the risks are considerably more numerous and important than the benefits that could be derived from using ERS. However, we have separated out a specific type of ERS, whose use is limited to the field of care, and which shows a remarkable potential to actively participate in social justice, not only by complying with the minimum requirements, but also by meeting the criterion of beneficence. While ERS currently pose significant risks, it is possible to consider the potential for specific types to participate in social justice and provide emotional and psychological support and assistance to certain members of society. (shrink)

Abstract: This research involved the design of an initial expert system which helps farmers and specialists diagnose and provide appropriate advice on banana diseases. The management of knowledge used in the expert system was also discussed. One of the key elements of this research was to find the appropriate language to diagnose the disease and the current situation in the knowledge base. Expert systems enable effective consultation. Production rules were used to capture knowledge. The expert system (...) was developed using CLIPS with the Delphi 10.2 as user interface. The expert system produced good results in analyzing cases of tested banana disease and enabling the system to determine the correct diagnosis in all cases. (shrink)

In §18 of Principles of Nature and Grace, Based on Reason, Leibniz says: ”Thus our happiness will never consist, and must never consist, in complete joy, in which nothing is left to desire, and which would dull our mind, but must consist in a perpetual progress to new pleasures and new perfections.” -/- This passage is typical in Leibniz’s Nachlass. Universal perfection creates in us joy or pleasure of the mind and its source is our creator, God. When this (...) joy is constant, we reach happiness and wisdom which is a kind of standing state of virtue, readiness to practice charity in the best of all possible worlds. However, it also indicates that our knowledge is never perfect. Perfecting our knowledge is a never-ending process which gives us joy in itself and motivates us to act in imitation of God. In this way some passions advance our knowledge and we can create ourselves a passionate habit of knowing more about the world and its perfection. In this paper I try to see this process of self-perfection from a cognitive rather than ethical point of view. While it is clear that in the final stage of wisdom we act mostly on our volitions which are founded on clear and distinct perceptions, it is less clear what cognitive status is to be attributed to our initial perceptions of perfection, our emotions and finally, the intellectual emotions which lead us to perfection and God. I will also reflect the role of the minute perceptions in our struggle for happiness. My argument is that a central cognitive role in Leibniz’s views on self-perfection is held by clear, but confused perfections which are subjective, undemonstrable impressions, shades, feelings. Therefore our ethical action is largely founded on passing, minute feelings rather than on deliberated conscious volitions, although the goal in Leibniz’s moral theory is to change this fact. -/- My discussion is founded on several texts from Leibniz’s later philosophy, such as the discussion following from New System of the Nature and the Communication of Substances of 1695, Leibniz’s letter to Queen Sophie Charlotte of 1702 (also known as On What is Independent in Sense and Matter), New Essays on Human Understanding (1704), Theodicy (1710) and naturally Leibniz’s most important epistemological text, Meditations of Truth, Knowledge and Ideas (1684). (shrink)

The preconditions and features of the formation of post-industrial society are defined in the article. The distinctive role of active innovation infrastructure of the country in integrating into the European community and society based on knowledge are proved. The characteristic features of the economy of post-industrial society are the increasing role of intangible resources in ensuring social reproduction, “softization” and “servization” the subjects of innovation infrastructure. The essence of economic category “innovation infrastructure“ is defined in the article. It (...) is a dynamic self-regulating system of markets and subjects that entering these markets in certain economic relations and it provides the necessary conditions for implementation of the innovation processes. Mechanism of functioning of the constituent elements of innovation infrastructure in market economy is proposed, relationships between them are defined. (shrink)

Emotion recognition systems (ERS) offer the ability to identify the emotions of others, based on an analysis of their facial expressions and regardless of culture, ethnicity, context, gender or social class. By claiming universalism in the expression as well as in the recognition of emotions, we believe that ERS present significant risks of causing great harm to some individuals, in addition to targeting, in some contexts, specific social groups. Drawing on a wide range of multidisciplinary knowledge - (...) including philosophy, psychology, computer science and anthropology - this research project aims to identify the current limitations of ERS and the main risks that their use brings, with the goal of providing a clear and robust analysis of the use of ERS and their contribution to greater social justice. Pointing to technical limitations, we refute, on the one hand, the idea that ERS are able to prove the causal link between specific emotions and specific facial expressions. We support our argument with evidence of the inability of ERS to distinguish facial expressions of emotions from facial expressions as communication signals. On the other hand, due to the contextual and cultural limitations of current ERS, we refute the idea that ERS are able to recognise, with equal performance, the emotions of individuals, regardless of their culture, ethnicity, gender and social class. Our ethical analysis shows that the risks are considerably more numerous and important than the benefits that could be derived from using ERS. However, we have separated out a specific type of ERS, whose use is limited to the field of care, and which shows a remarkable potential to actively participate in social justice, not only by complying with the minimum requirements, but also by meeting the criterion of beneficence. While ERS currently pose significant risks, it is possible to consider the potential for specific types to participate in social justice and provide emotional and psychological support and assistance to certain members of society. (shrink)