Modeling and Validation of the Dynamic Host Configuration Protocol with Colored Petri Nets

Petri Networks with a graphical language are based on mathematical logic which have many uses and have capability for modeling and validation of distributed systems and concurrent applications. Colored Petri Networks (CPNs) are a type of Petri Network models that are used in modeling of systems which contain discrete and scattered events. In general, CPNs are used to evaluate system performance and demonstrate the correctness of systems. Dynamic Host Configuration Protocol (DHCP) is one of the main systems of protocols special for servers that are used for dynamic allocation of IP to the network computers (clients). In this paper, we highlight to analyze the correctness and authenticity of DHCPs with the use of CPNs with using the CPN Tools and to prove the accuracy of our protocol's performance.DOI:http://dx.doi.org/10.11591/ijece.v2i3.48

A New Approach for Text Documents Classification with Invasive Weed Optimization and Naive Bayes Classifier

With the fast increase of the documents, using Text Document Classification (TDC) methods has become a crucial matter. This paper presented a hybrid model of Invasive Weed Optimization (IWO) and Naive Bayes (NB) classifier (IWO-NB) for Feature Selection (FS) in order to reduce the big size of features space in TDC. TDC includes different actions such as text processing, feature extraction, forming feature vectors, and final classification. In the presented model, the authors formed a feature vector for each document by means of weighting features use for IWO. Then, documents are trained with NB classifier; then using the test, similar documents are classified together. FS do increase accuracy and decrease the calculation time. IWO-NB was performed on the datasets Reuters-21578, WebKb, and Cade 12. In order to demonstrate the superiority of the proposed model in the FS, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been used as comparison models. Results show that in FS the proposed model has a higher accuracy than NB and other models. In addition, comparing the proposed model with and without FS suggests that error rate has decreased

A Decision Support System for Diagnosis of Diabetes and Hepatitis, based on the Combination of Particle Swarm Optimization and Firefly Algorithm

Introduction: Clinical Decision Support Systems (CDSS) are designed in the form of computer programs that help medical professionals make decisions about disease diagnosis. The main aim of these systems is to assist physicians in diagnosing diseases, in other words, a physician can interact with the system and use them to analyze patient data, diagnose diseases, and other medical activities. Method: This is a descriptive-analytic study. The datasets include 768 records of diabetes with 8 features and 155 records of hepatitis with 19 features, which were provided by the Global Website of UCI. In this study, the Particle Swarm Optimization (PSO) algorithm was used for Feature Selection (FS) and the Firefly Algorithm (FA) was used to classify diabetes and hepatitis into two healthy and unhealthy classes. 80% of the data was used for training and the remaining (20%) was used for testing. Results: The experiments showed that the accuracy of the PSO and FA for the diabetes dataset was 84.41% and 82.08%, respectively. Also, the accuracy of the PSO and FA for the hepatitis dataset was 81.84% and 80.34%, respectively. The accuracy of the proposed model for the diabetes and hepatitis datasets was 95.38% and 94.09%, respectively. Conclusion: According to the results, the proposed model had a lower error rate in diagnosis compared to the PSO and FA. The results of this study can help doctors in timely diagnosis of diabetes and hepatitis

A New Approach in Dynamic Traveling Salesman Problem: A Hybrid of Ant Colony Optimization and Descending

ABSTRAC

Open Domain Factoid Question Answering Systems

Question Answering (QA) is a field of Artificial Intelligence (AI) and Information Retrieval (IR) and Natural Language Processing (NLP), and leads to generating systems that answer to questions natural language in open and closed domains, automatically. Question Answering Systems (QASs) have to deal different types of user questions. While answers for some simple questions can be short phrases, answers for some more complex questions can be short texts. A question with a single is known as a factoid question, and a question answering system that deals with factoid questions is called a factoid QAS.In this thesis, we present a factoid QAS that consists of three phases: question processing, document/passage retrieval, and answer processing. In the question processing phase, we consider a new two-level category structure using machine learning techniques to generate search engine from user questions queries.Soru Yanıtlama (SY), Yapay Zeka (YZ), Bilgi Tarama (IR) ve Doğal Dil İşleme (DDİ) bilim dalıdır ve doğal dil içerisindeki açık ve kapalı çalışma alanlarında soruları yanıtlayan sistemleri oluşturmayı otomatik olarak beraberinde getirir. Soru Yanıtlama Sistemleri (SYS) çeşitli kullanıcı sorularına değinmek durumundadıl2r. Bazı basit sorulara verilen cevaplar kısa cümlecikler olurken, daha karmaşık sorular için verilen cevaplar kısa metinler olabilir. Basit cevaplı bir soru tek yanıtlı soru olarak tanımlanır ve tek yanıtlı sorularla ilgilenen soru cevaplama sistemine de tek yanıtlı SYS denir.Bu Tezde, üç aşamadan oluşan tek yanıtlı SYS sunmaktayız: soru işleme, metin tarama ve cevap işleme. Soru işleme aşamasında, otomatik öğrenme teknikleri kullanarak kullanıcıların sorguladıkları sorulardan arama motoru elde etmek için yeni bir iki-aşamalı kategori yapısı ele almaktayız

İşletim sistemlerinde ölümcül kilitlenmenin önlenmesi için ajan sistemi tabanlı bir çözüm.

TEZ9366Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2011.Kaynakça (s. 79-102) var.x, 148 s. : tablo ; 29 cm.Bu tezde, kullanıcı, ajan programı ve isletim sistemi arasında bir arayüz olarak hareket eden bir kabuk programı gelistirilmistir.ajan programı amacı ilsem yürütme sırasında ortaya çıkan ölümcül kitlenmeyi çözmektir. Hafıza en önemli ortak kaynaklarından biri oldugu için; ajan programı her çalısan islemin bellek kullanımı için dosyalama islemlerini saglar ve kabuk isteklerini yanıtlar. Ajanların ögrenmesi çok katmanlı algılayıcı ileri besleme sinir agları üzerinden hata geri yayılım kullanılarak yapılır. Baslangıçta. kabuk program, çalısan islemlerin, islem hafıza kullanımını talep eder, daha sonra çok katmanlı algılayıcı sinir agında girisler olarak sıraya koyar ve organize eder. Sinir agının çıktısı daha önce kararlastırılmıs esik degerine esit ya da ondan büyükse kabuk islemi çalıstırır. Aksi halde, kilitlenme meydana gelme olasılıgı vardır, böylece kabuk islemi askıya alır ve kilitlenme yasanmasını engeller. Bu kilitlenme önleme çözümü için yeni ve dinamik bir yaklasımdır. Bu konuda daha önceki çalısmalar incelenmis ve mevcut ve önerilen çözümler arasındaki test sonuçları tartısılmıstır.In this thesis, a shell program that acts as an interface among user, agent program and operating system is developed. Aim of the agent program is to handle and solve the deadlock that occurs during the process execution. Since, the memory is one of the most important shared sources; the agent program provides filing operations for memory usage of each running process and replies requests of shell. Learning of the agents are done by using error back propagation learning on Multi-Layer Perceptron feed forward neural networks. Initially, shell program requests the process memory usage of running processes, and then it schedules and organizes the processes as inputs on the Multi-Layer Perceptron Neural Network. If the output of the Neural Network is greater than or equal to a pre-decided threshold shell runs the process. Otherwise, since there exist deadlock occurrence probability, the shell suspends the process and prevents the deadlock occurrence. This is a new and dynamic approach for deadlock prevention solution. The previous works about this subject is investigated and the test results among exist and proposed solution are concluded