Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
This paper presents the factor clustering analysis for violent crimes. The efficiency of Rough-fuzzy C-means algorithm is affected by the numbers of clusters, and not all centroids are beneficial. The analyzing of violent crime data does not need human intervention for impartiality. The information entropy is a helpful tool for resolving those issues. In this paper, a novel discrete Rough-fuzzy C-means...
In this paper we propose a local search algorithm to tackle scheduling radiotherapy problems. Our scheduling radiotherapy problem has a set of constraints that must be satisfied and another set of soft constraints that are suitable to be satisfied. Many resources are involved in the scheduling as doctors, patients and machines. The goal is focused on improving the patient care services. Our algorithm...
Reliability modeling of electronic circuits can be best performed by the stressor - susceptibility interaction model. A circuit or a system is deemed to be failed once the stressor has exceeded the susceptibility limits. Complex manufacturing systems often require a high level of reliability from the incoming electricity supply. Modern industrial time power quality monitoring systems can be used for...
For every business, where the product escalation of an organization depends on proper distribution of product and services in a region, analyzing customer behavior over time in that region can produce useful results. In this article, we strive to develop a system, which when provided past customer records will predict the forthcoming customer behavior. The proposed system is specially designed to...
This paper proposes two improvements of the ant clustering-based segmentation; first by applying new heuristic function of the ant colony system based on probability theory. Second by selecting any one of new two global update mechanisms of the ant colony system. These improvements evaluation is performed in the domain of automatic retinal blood vessels segmentation. The automatic segmentation of...
The purpose of this research is to understand from a Multivariable optimization associated with the path of a group of vehicles integrated in a Community Caravan Range and determine the optimal route involve speed, storage and travel resources for determining the cost benefit have partnered with a travel plan, which has as principal basis the orography restriction, although this problem has been studied...
Community detection in complex networks has attracted a lot of attention in recent years. Communities play special roles in the structure-function relationship; therefore, detecting communities can be a way to identify substructures that could correspond to important functions. Social networks can be formalized by a statistical model in which interactions between actors are generated based on some...
In this paper, we proposed the new system for Hajj event classification in diverse and realistic Hajj videos and image scenes is investigated based on machine learning techniques. This challenging but important subject has mostly been ignored in the past due to several problems one of which is the lack of realistic and annotated video datasets. The main contribution of this work is to address the...
This paper presents an approach for underdetermined blind source separation in the case of additive Gaussian white noise and pink noise. Likewise, the proposed approach is applicable in the case of separating I + 3 sources from I mixtures with additive two kinds of noises. This situation is more challenging and suitable to practical real world problems. Moreover, unlike to some conventional approaches,...
We propose in this paper an emotional recognition system based on physiological signals. We adopt the seven basic emotions that are: neutrality, joy, sadness, fear, anger, disgust and surprise. An experiment has been conducted to verify the feasibility of the proposed system. This experience has allowed us to acquire EEG signals and to create an emotional database. For this, we have used the Emotiv...
Predictive control of systems is very much related to the efficiency and cost of systems, as well as to the quality of systems outcomes. However, it is difficult to achieve optimal predictive control because most predictive controls for systems have characteristics of randomness, strong and complex constraints and nonlinearity. Conventional methods of solving constrained nonlinear optimization problems...
This paper describes the design of a system providing room occupancy information in a university campus. The system and its possible influence on the human environment are designed to enhance the work environment through pervasive information delivery. The work is motivated by recent advances in the domain of ubiquitous computing. The authors describe a case study of delivering a solution to university...
In this paper, a novel approach, called Repeated Reselling Permission based Multiple Reselling (RRP-MR), is proposed. This approach allows a consumer who has bought his license from another consumer to resell this license to a third consumer. This reselling process continues till the license is resold N-times. This multiple reselling process is achieved without compromising neither the content owner's...
This paper discusses the use of intelligent technology to solve the problem of grasp planning known as a difficult problem. The scope aims to find points of contact between a five-fingered hand and an object. In this paper, we applied a new hierarchical approach for distributed Multi-Objective Particles Swarms Optimization, based on dynamic subdivision of the population using Pareto fronts (pbMOPSO)...
In this paper, Kekre's transform is proposed for protecting fingerprint template and a symmetric bio-hash function is used to improve the protection of the fingerprint biometric template. In the proposed approach; firstly the principal curve approach is used to extract the features from the fingerprint template. Then, we applied a transformation phase using Kekre's transform. It starts by calculating...
Intrusion detection systems (IDS) are well-known research area for the detection of anomalous activities in a system from both inside and outside intruders. In this article, a multi-layer hybrid machine learning intrusion detection system is designed and developed to achieve high efficiency and improve the detection and classification rate accuracy inspired by immune systems with negative selection...
This paper investigates a Hybrid Naïve Possibilistic Classifier (HNPC) to detect the presence of heart disease from the heterogeneous data (numerical and categorical) of the Cleveland dataset. The proposed classifier stands for the hybridization of two versions of Naïve Possibilistic Classifier (NPC) which have been recently applied on numerical and categorical data, respectively. To estimate possibility...
This article presents an intelligent automatic approach for galaxies images classification based on Artificial Neural Network (ANN) and moment-based features extraction algorithms. The proposed approach consists of three phases; namely, image denoising, feature extraction, and classification phases. For the denoising phase, noise pixels are removed from input images, then input galaxy image is normalized...
Commonly, aquatic experts use traditional methods such as casting nets or underwater human monitoring for detecting existence and quantities of different species of fish. However, the recent breakthrough in digital cameras and storage abilities, with consequent cost reduction, can be utilized for automatically observing different underwater species. This article introduces an automatic classification...
Bayesian networks tend to be increasingly used for the management of uncertainty in user modeling and provide a simple and effective approach for constructing and manipulating probabilistic models. In the Web context, user models used by such adaptive applications contain personal information such as knowledge, preferences, objectives which are required for learning personalized process. In this paper,...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.