In this paper, we present a simple new human activity recognition method using discrete cosine transform (DCT). The scheme uses the DCT coefficients extracted from silhouettes as descriptors (features) and performs frame-by-frame recognition, which make it simple and suitable for real time applications. We carried out several tests using radial basis neural network (RBF) for classification, a comparative study against stat-of-the-art methods shows that our technique is faster, simple and gives higher accuracy performance comparing to discrete transform based techniques and other methods proposed in literature.

In this paper, we present a simple new human activity recognition method using discrete cosine transform (DCT). The scheme uses the DCT coefficients extracted from silhouettes as descriptors (features) and performs frame-by-frame recognition, which make it simple and suitable for real time applications. We carried out several tests using radial basis neural network (RBF) for classification, a comparative study against stat-of-the-art methods shows that our technique is faster, simple and gives higher accuracy performance comparing to discrete transform based techniques and other methods proposed in literature.

In this paper, we present a simple new human activity recognition method using discrete cosine transform (DCT). The scheme uses the DCT coefficients extracted from silhouettes as descriptors (features) and performs frame-by-frame recognition, which make it simple and suitable for real time applications. We carried out several tests using radial basis neural network (RBF) for classification, a comparative study against stat-of-the-art methods shows that our technique is faster, simple and gives higher accuracy performance comparing to discrete transform based techniques and other methods proposed in literature.

Redundant data retransmission problem in wireless sensor networks (WSNs) can be eliminated using the data aggregation process which combines similar data to reduce the resource-consumption and consequently, saves energy during data transmission. In the recent days, many researchers have focused on securing this paradigm despite the constraints it imposes such as the limited resources. Most of the solutions proposed to secure the data aggregation process in WSNs are essentially based on the use of encryption keys to protect data during their transmission in the network. Indeed, the key generation and distribution mechanisms involve additional computation costs and consume more of energy. Considering this, in this paper, we propose a new security mechanism to secure data aggregation in WSNs called SDAW (secure data aggregation watermarking-based scheme in homogeneous WSNs). Our mechanism aims to secure the data aggregation process while saving energy. For this, the mechanism uses a lightweight fragile watermarking technique without encryption to insure the authentication and the integrity of the sensed data while saving the energy. The links between the sensor nodes and the aggregation nodes, and also the links between the aggregation nodes and the base station are secured by using the watermarking mechanism.

Redundant data retransmission problem in wireless sensor networks (WSNs) can be eliminated using the data aggregation process which combines similar data to reduce the resource-consumption and consequently, saves energy during data transmission. In the recent days, many researchers have focused on securing this paradigm despite the constraints it imposes such as the limited resources. Most of the solutions proposed to secure the data aggregation process in WSNs are essentially based on the use of encryption keys to protect data during their transmission in the network. Indeed, the key generation and distribution mechanisms involve additional computation costs and consume more of energy. Considering this, in this paper, we propose a new security mechanism to secure data aggregation in WSNs called SDAW (secure data aggregation watermarking-based scheme in homogeneous WSNs). Our mechanism aims to secure the data aggregation process while saving energy. For this, the mechanism uses a lightweight fragile watermarking technique without encryption to insure the authentication and the integrity of the sensed data while saving the energy. The links between the sensor nodes and the aggregation nodes, and also the links between the aggregation nodes and the base station are secured by using the watermarking mechanism.

Redundant data retransmission problem in wireless sensor networks (WSNs) can be eliminated using the data aggregation process which combines similar data to reduce the resource-consumption and consequently, saves energy during data transmission. In the recent days, many researchers have focused on securing this paradigm despite the constraints it imposes such as the limited resources. Most of the solutions proposed to secure the data aggregation process in WSNs are essentially based on the use of encryption keys to protect data during their transmission in the network. Indeed, the key generation and distribution mechanisms involve additional computation costs and consume more of energy. Considering this, in this paper, we propose a new security mechanism to secure data aggregation in WSNs called SDAW (secure data aggregation watermarking-based scheme in homogeneous WSNs). Our mechanism aims to secure the data aggregation process while saving energy. For this, the mechanism uses a lightweight fragile watermarking technique without encryption to insure the authentication and the integrity of the sensed data while saving the energy. The links between the sensor nodes and the aggregation nodes, and also the links between the aggregation nodes and the base station are secured by using the watermarking mechanism.

Redundant data retransmission problem in wireless sensor networks (WSNs) can be eliminated using the data aggregation process which combines similar data to reduce the resource-consumption and consequently, saves energy during data transmission. In the recent days, many researchers have focused on securing this paradigm despite the constraints it imposes such as the limited resources. Most of the solutions proposed to secure the data aggregation process in WSNs are essentially based on the use of encryption keys to protect data during their transmission in the network. Indeed, the key generation and distribution mechanisms involve additional computation costs and consume more of energy. Considering this, in this paper, we propose a new security mechanism to secure data aggregation in WSNs called SDAW (secure data aggregation watermarking-based scheme in homogeneous WSNs). Our mechanism aims to secure the data aggregation process while saving energy. For this, the mechanism uses a lightweight fragile watermarking technique without encryption to insure the authentication and the integrity of the sensed data while saving the energy. The links between the sensor nodes and the aggregation nodes, and also the links between the aggregation nodes and the base station are secured by using the watermarking mechanism.

Redundant data retransmission problem in wireless sensor networks (WSNs) can be eliminated using the data aggregation process which combines similar data to reduce the resource-consumption and consequently, saves energy during data transmission. In the recent days, many researchers have focused on securing this paradigm despite the constraints it imposes such as the limited resources. Most of the solutions proposed to secure the data aggregation process in WSNs are essentially based on the use of encryption keys to protect data during their transmission in the network. Indeed, the key generation and distribution mechanisms involve additional computation costs and consume more of energy. Considering this, in this paper, we propose a new security mechanism to secure data aggregation in WSNs called SDAW (secure data aggregation watermarking-based scheme in homogeneous WSNs). Our mechanism aims to secure the data aggregation process while saving energy. For this, the mechanism uses a lightweight fragile watermarking technique without encryption to insure the authentication and the integrity of the sensed data while saving the energy. The links between the sensor nodes and the aggregation nodes, and also the links between the aggregation nodes and the base station are secured by using the watermarking mechanism.

Redundant data retransmission problem in wireless sensor networks (WSNs) can be eliminated using the data aggregation process which combines similar data to reduce the resource-consumption and consequently, saves energy during data transmission. In the recent days, many researchers have focused on securing this paradigm despite the constraints it imposes such as the limited resources. Most of the solutions proposed to secure the data aggregation process in WSNs are essentially based on the use of encryption keys to protect data during their transmission in the network. Indeed, the key generation and distribution mechanisms involve additional computation costs and consume more of energy. Considering this, in this paper, we propose a new security mechanism to secure data aggregation in WSNs called SDAW (secure data aggregation watermarking-based scheme in homogeneous WSNs). Our mechanism aims to secure the data aggregation process while saving energy. For this, the mechanism uses a lightweight fragile watermarking technique without encryption to insure the authentication and the integrity of the sensed data while saving the energy. The links between the sensor nodes and the aggregation nodes, and also the links between the aggregation nodes and the base station are secured by using the watermarking mechanism.

This paper proposes a semi-structured information retrieval model based on a new method for calculation of similarity. We have developed CASISS (Calculation of Similarity of Semi-Structured documents) method to quantify how two given texts are similar. This new method identifies elements of semi-structured documents using elements descriptors. Each semi-structured document is pre-processed before the extraction of a set of descriptors for each element, which characterize the contents of elements.It can be used to increase the accuracy of the information retrieval process by taking into account not only the presence of query terms in the given document but also the topology (position continuity) of these terms.

This paper proposes a semi-structured information retrieval model based on a new method for calculation of similarity. We have developed CASISS (Calculation of Similarity of Semi-Structured documents) method to quantify how two given texts are similar. This new method identifies elements of semi-structured documents using elements descriptors. Each semi-structured document is pre-processed before the extraction of a set of descriptors for each element, which characterize the contents of elements.It can be used to increase the accuracy of the information retrieval process by taking into account not only the presence of query terms in the given document but also the topology (position continuity) of these terms.

Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.