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Collaborating Filtering (CF) is a recommendation method that can make predictions about a given user's interest by collecting a large number of other user' appreciation. Some of the major problems encountered in the use of CF are the cold-start problem and the fact that personalized recommendations cannot be done. In turn, CF-based recommendations produces ranked results where the success rate can...
Object recognition and pedestrian detection are of crucial importance to autonomous driving applications. Deep learning based methods have exhibited very large improvements in accuracy and fast decision in real time applications thanks to CUDA support. In this paper, we propose two Convolutions Neural Networks (CNNs) architectures with different layers. We extract the features obtained from the proposed...
The paper presents a knowledge based approach applied to air pollution effects analysis in the case of PM2.5 air pollutant which has potential significant negative effects on human health. The use of knowledge derived from various sources (e.g. literature, databases, questionnaires, human experts' experience, and decision tables) via manual, semiautomatic and automatic methods is proposed for a multi-parameters...
Nowadays, a dataset includes a huge number of features with irrelevant and redundant ones. Feature selection is required for a better machine-learning algorithms' performance. A system for feature selection is proposed in this work using a sine cosine algorithm (SCA). SCA is a new stochastic search algorithm for optimization problems. SCA optimization adaptively balances the exploration and exploitation...
The estimation of user position in indoor environment using WLAN technology based on Received Signal Strength (RSS) is becoming increasingly important in recent years. Various indoor positioning techniques are proposed in the literature. Fingerprint positioning technique is the most promising one that consists of radio frequency (RF) map construction and location estimation phases. Machine learning...
There are three main classes of modifiers that can affect the polarity of the sentiments described in natural language texts: negations, intensifiers and diminishers. In this paper, we concentrate on the study of these particular words which have a very important semantic role in any natural language description. Our study is applied on a real data set extracted from the popular Romanian Web site...
One of the most crucial problems in any Natural Language Processing (NLP) task is the representation of time. This includes applications such as Information Retrieval techniques (IR), Information Extraction (IE) and Question/answering systems (QA). This paper deals with temporal information involving several forms of inference in Arabic language.
The wind farm location optimization (WFLO) problem is an active area of research. This paper is investigating the suitability of the no speeds and coefficients particle swarm optimization (NSC-PSO) method for solving the WFLO problem. In order to prove the competitiveness of the NSC-PSO method, a simplified wake model is implemented, which is similar to the model used in the pioneering work of Grady...
Lemmatization of the words is an important preprocess for Natural Language Processing (NLP) studies. Especially in language applications (such as part of speech tagging, spell-checking, and document clustering), selection of the right lemma with morphological features can provide better results. In this study, we present a new hybrid approach for Turkish inflected words by using morphological similarity...
Paxos is regarded as one of the most important protocols for distributed consensus in the presence of failures. It uses a number of 2f+1 processes to tolerate the benign failure of f processes, by splitting them into different roles with tailored tasks. The protocol presents multiple engineering challenges, two of which are pinpointing the cause for stalling and identifying the faulty processes. In...
The structure and workflows of an organization can be modelled by business agents following a set of roles. The agents act according to the established rules, and can interact in order to achieve the organizational objectives. Business processes described by means of role-activity diagrams can be formalized and implemented as multiagent systems. In this paper we compare two implementations of business...
This paper proposes the application of Symbiotic Organisms Search (SOS) Algorithm to solve the various Economic Load Dispatch (ELD) problems. Both classical ELD problem which has smooth fuel cost function and nonconvex ELD problem which has nonconvex and discontinuous fuel cost function due to considering of some practical constraints like valve point effects, ramp rate limits and prohibited generating...
The work presents the design of a fuzzy rule base aimed at intelligent merging of measurements by the two sensor types in a Micro Electro-Mechanical Sensor (MEMS) device — accelerometers and three gyroscopes placed on the three axes in the 3D space. The idea aroused from the available expert knowledge how to merge the measurements from both sensors in order to asses inertial force vectors on three...
This paper presents one of the latest nature-inspired meta-heuristics algorithms known as Cuckoo Search Algorithm (CSA) to solve optimal capacitor placement and sizing (OCPS) problem in radial power systems for the purpose of maximizing annual net saving by reducing the power losses with the acceptable voltage ranges. In the proposed algorithm, discrete nature of the capacitors is considered. Forward...
It was long time ago, when the Internet was a basic network used for data and information sharing. The evolutionary process of the Internet started with connecting people and then with the increasing popularity of it and with the emerging concept of smart systems, device-to-device communications within smart systems dawned. And now; by taking the advantage of another emerging concept: mobility, we...
Automatic classification of makams from sound data is a challenging yet rarely studied topic. In this work, it is aimed to develop an MIR system which determines a song's makam. To overcome this problem, mel frequency cepstral coefficients were utilized as features. Five classifiers were considered. The best result was obtained by deep belief network as 93.10 which is comparable to the recent works.
The aim of this paper is to analyse the variation of the gesture recognition accuracy of several classifiers, based on input provided by two different sensors: Kinect for XBox 360 (Kinect 1) and its improved, newer version, Kinect for XBox One (Kinect 2). The accurate and meaningful recognition of body postures and gestures is a problem that depends on multiple factors, including the machine learning...
Image segmentation is important part of image processing applications. A given image is separated the different regions with homogeneous characteristics at image segmentation process. This paper will introduce an image segmentation approach that can be used in image processing applications. Recently Neutrosophic Set (NS) that use to evulate indeterminacy information, and metaheuristic algorithms are...
Human-machine interaction is becoming a sufficient part of coming future. Being a bright example of HMI, embedded eye-tracking systems allow user to interact with objects by using human's eye-movements. Due to wearable form-factor, developed eye-tracking system has to conform to low-power consumption, low-heat generation and low EM radiation as well as support wireless data transmission and be space...
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