There is no doubt that Computer troubleshooting is important for organizations and companies and for personal use level. Sound cards troubles is one of the most annoying problems in computers. It causes damage and troubles in computers to persons, organizations and firms. Correctly, expert systems can greatly help to avoid damage to these computers. designed to diagnose and troubleshoot issues related to sound cards in computer systems. The expert system is developed using a combination of rule-based and machine learning approaches, (...) which allows for accurate and efficient diagnosis of a wide range of sound card problems. Objectives: An expert system has been established based on CLIPS to diagnose Computer Problems. (shrink)

This article examines what realists and anti-realist debates are all about. Through presenting the core of the main arguments in these debates, these are significant arguments and they are the kind of arguments that can clarify what it meant by ‘truth’ between Realist and anti-realist in general. The concluding remark is that though the main anti- realist’s arguments in these debates can be seen as some powerful arguments through raising questions on the relationship between theory and evidence, success and truth. (...) However, the success of science and the use of science in everyday life has not been given any satisfactory explanations by the anti-realists nor the use of it has been shut out from the daily life by these arguments against it. (shrink)

This article examines whether Willard Van Orman Quine’s indeterminacy thesis can be sustained. The argument from above, Quine argues, can derive indeterminacy as its conclusion. I will argue that the indeterminacy claim cannot be sustained. I further argue that Quine changed the formulation of the underdetermination of theory by evidence (UTE) argument from what Duhem said to the Quine/Pierce meaning verification view, in order use the new formulation of UTE to imply indeterminacy. Given all that, we see when we apply (...) the old UTE argument we only arrive at underdetermination of theory by evidence, and that applies to all sciences, philosophy and knowledge, including philosophy of language. (shrink)

In this short article, I will explore John Searle’s social ontology project from the perspective of social epistemology. The outcome of my analysis is that language is decisive for the collective acquisition and production of knowledge. I agree with Searle regarding the exposure of language as a central constitutive component of social forms of knowledge, a component that plays a significant role in the development of social epistemology.

This is a republication of 'Hegeby Zanin' in a second country for the use on international philosophy students and researchers in non English language, combines two epistemology books ; classic epistemology and social epistemology.

This is book l of three philosophy books in international language; formal academic philosophy source in Kurdish language Given overall view on classic epistemology for university student in non English language philosophy departments and philosophy schools .

This is book ll of three philosophy books in international language, formal academic philosophy source in Kurdish language. Written for non English speaking university students as a philosophy guide into epistemology/ Social epistemology, as a resource for the use of philosophy departments and philosophy schools.

Abstract: The efficiency and performance of sorting algorithms play a crucial role in various applications and industries. In this research paper, we present a comprehensive comparative analysis of popular sorting algorithms on datasets of different sizes and characteristics. The aim is to evaluate the algorithms' performance and identify their strengths and weaknesses under varying scenarios. We consider six commonly used sorting algorithms: QuickSort, TimSort, MergeSort, HeapSort, RadixSort, and ShellSort. These algorithms represent a range of approaches and techniques, including divide-and-conquer, hybrid (...) sorting, and simple comparison-based methods. To assess their performance, we employ a diverse set of datasets, including the Iris dataset (1K), student dataset (5.8K), Wine dataset (6.5K), Uniform (10K), Normal (10K), Exponential (10K), Bimodal (10K), Yelp dataset (10K), MNIST dataset (42K), Uniform (100K), Normal (100K), Exponential (100K), Bimodal (100K), Uniform (500K), Normal (500K), Exponential (500K), Bimodal (500K), Uniform (1M), Normal (1M), Exponential (1M), and Bimodal (1M). These datasets cover a wide range of sizes and characteristics, allowing us to analyze the algorithms' performance across different dimensions. We measure and compare several key metrics, including execution time, memory usage, algorithmic complexity and stability. By analyzing these metrics, we gain insights into the efficiency and suitability of each algorithm for different dataset sizes and characteristics. We also discuss the implications of the findings in practical applications. Our results reveal important trade-offs among the sorting algorithms. While some algorithms excel in certain scenarios, others demonstrate better scalability or memory efficiency. We identify the best-performing algorithms for specific dataset characteristics and highlight their strengths and limitations. This research can assist developers and practitioners in selecting appropriate sorting algorithms based on their specific requirements and dataset characteristics. In conclusion, this comparative analysis provides a valuable contribution to the understanding of sorting algorithm performance. The findings contribute insights into the efficiency and suitability of popular sorting algorithms across datasets of different sizes and characteristics. By evaluating key metrics and discussing the implications, we offer guidance for selecting the most appropriate sorting algorithm in various practical scenarios. (shrink)