International Journal of Cognitive Informatics and Natural Intelligence

Includes bibliographical references.

Article 1. Augmented context-based conceptual user modeling for personalized recommendation system in online social networks -- Article 2. Fitness distance correlation strategy for solving the RGV dynamic scheduling problem -- Article 3. Fuzzy ontology-based querying user' requests under uncertain environment -- Article 4. An improved firefly algorithm-based 2-D image thresholding for brain image fusion -- Article 5. DNA epidemic model construction and dynamics optimization -- Article 6. Optimizing for high resolution ADC model with combined architecture.

[Article Title: Augmented Context-Based Conceptual User Modeling for Personalized Recommendation System in Online Social Networks / Ammar Alnahhas and Bassel Alkhatib, p. 1 - 19] Abstract: As the data on the online social networks is getting larger, it is important to build personalized recommendation systems that recommend suitable content to users, there has been much research in this field that uses conceptual representations of text to match user models with best content. This article presents a novel method to build a user model that depends on conceptual representation of text by using ConceptNet concepts that exceed the named entities to include the common-sense meaning of words and phrases.;[Article Title: Fitness Distance Correlation Strategy for Solving the RGV Dynamic Scheduling Problem / Wei Li, Furong Tian, Ke Li, p. 20 - 40] Abstract: Rail guide vehicle (RGV) problems have the characteristics of fast running, stable performance, and high automation. RGV dynamic scheduling has a great impact on the working efficiency of an entire automated warehouse. However, the relative intelligent optimization research of different workshop components for RGV dynamic scheduling problems are insufficient scheduling in the previous works. They appear idle when waiting, resulting in reduced operating efficiency during operation.;[Article Title: Fuzzy Ontology-Based Querying User' Requests Under Uncertain Environment / Mohamed Nazih Omri, p. 41 - 59] Abstract: Assistance with the use of technical devices is required as soon as the tasks to be performed become complex. This assistance is also needed as soon as the authors provide assistance to users to find solutions to incidents that occur during the application of unsuitable procedures. The goal of this work is then to provide a knowledge extraction approach that can interpret user requests into valid system requests to respond appropriately to novice user requests. This approach is based on a fuzzy semantic network for the modeling of imprecise and uncertain knowledge and the automatic construction of temporary fuzzy ontology for the identification and interpretation of user requests.;[Article Title: An Improved Firefly Algorithm-Based 2-D Image Thresholding for Brain Image Fusion / Srikanth M. V., V. V. K. D. V. Prasad, K. Satya Prasad, p. 60 - 96] Abstract: In this article, an attempt is made to diagnose brain diseases like neoplastic, cerebrovascular, Alzheimer's, and sarcomas by the effective fusion of two images. The two images are fused in three steps. Step 1. Segmentation: The images are segmented on the basis of optimal thresholding, the thresholds are optimized with an improved firefly algorithm (pFA) by assuming Renyi entropy as an objective function. Earlier, image thresholding was performed with a 1-D histogram, but it has been recently observed that a 2-D histogram-based thresholding is better. Step 2: the segmented features are extracted with the scale invariant feature transform (SIFT) algorithm.;[Article Title: DNA Epidemic Model Construction and Dynamics Optimization / Yinglian Zhou, p. 97 - 117] Abstract: In order to solve some complex optimization problems, the SIR-DNA algorithm was constructed based on the DNA-based SIR (susceptible-infectious-recovered) infectious disease model. Since infectious diseases attack a very small part of the individual's genes, the number of variables per treatment is small; thus, the natural dimensionality reduction of the algorithm is achieved. Based on the DNA-SIR infectious disease model, different infections can be distinguished in the pathogenesis of viruses. The mechanisms of disease transmission are described by the SIR model, and these are used to construct operators such as SS, SI, II, IR, RR, and RS, so that individuals can naturally exchange information naturally through disease transmission. The test results show that the algorithm has the characteristics of strong search ability and has a high convergence speed for solving complex optimization problems.;[Article Title: Optimizing for High Resolution ADC Model With Combined Architecture / Wei Ding, Heng Liu, Tao Wu, p. 118 - 132] Abstract: High resolution analog-digital conversion (ADC) is a key instrument to convert analog signals to digital signals, which is deployed in data acquisition system to match high resolution analog signals from seismometers systems. To achieve high resolution, architecture of Σ-△ oversampling or pipeline ADC architecture have following disadvantages: high power consumption, low linearity of modulators, and complex structure. This work presents a novel model architecture, which design principle is validated by mathematical formulations which combined advantages of both pipeline and Σ-△oversampling ADC architecture. By discussing the adverse effects of the whole ADC architecture with an external noise theoretically, an amended theoretical model is proposed according to the assessment result of a noise simulation algorithm. The simulation results represent that the whole performance of combined architecture is determined by the noise level of integrator and subtractor. Using these two components with a noise index no more than 10-7 V/√Hz, the resolution of the prototype can achieve a reservation of 144.5 dB.