The composition of the diet of the barbel (Luciobarbus callensis) was studied in the K’sob reservoir near the town of M’Sila (Algeria). The capture of the barbels was carried out between September 2010 and August 2011.The diet was studied from 379 specimens collected by trammel net. During the study period, it was noted that the food spectrum essentially consisted of Chironomids, Ephemeroptera and Copepods, which are abundant in the environment. The barbel of the K’sob reservoir has a seasonal food pattern influenced by climatic and ecological conditions and by its reproductive cycle. The diet of L. callensis in the study area is omnivorous, with a zoo-benthophage tendency.

The composition of the diet of the barbel (Luciobarbus callensis) was studied in the K’sob reservoir near the town of M’Sila (Algeria). The capture of the barbels was carried out between September 2010 and August 2011.The diet was studied from 379 specimens collected by trammel net. During the study period, it was noted that the food spectrum essentially consisted of Chironomids, Ephemeroptera and Copepods, which are abundant in the environment. The barbel of the K’sob reservoir has a seasonal food pattern influenced by climatic and ecological conditions and by its reproductive cycle. The diet of L. callensis in the study area is omnivorous, with a zoo-benthophage tendency.

The composition of the diet of the barbel (Luciobarbus callensis) was studied in the K’sob reservoir near the town of M’Sila (Algeria). The capture of the barbels was carried out between September 2010 and August 2011.The diet was studied from 379 specimens collected by trammel net. During the study period, it was noted that the food spectrum essentially consisted of Chironomids, Ephemeroptera and Copepods, which are abundant in the environment. The barbel of the K’sob reservoir has a seasonal food pattern influenced by climatic and ecological conditions and by its reproductive cycle. The diet of L. callensis in the study area is omnivorous, with a zoo-benthophage tendency.

In this paper, we propose a new and practical variant of ElGamal encryption which is secure against every passive and active adversary. Under the hardiness of the decisional Diffie-Hellman assumption, we can prove that the proposed scheme is secure against an adaptive chosen ciphertext attacks in the standard model. Such security verifies not only the confidentiality but also verifies the integrity and the authentication of communications. We display that the modified scheme furthermore achieves anonymity as well as strong robustness.

In this paper, we propose a new and practical variant of ElGamal encryption which is secure against every passive and active adversary. Under the hardiness of the decisional Diffie-Hellman assumption, we can prove that the proposed scheme is secure against an adaptive chosen ciphertext attacks in the standard model. Such security verifies not only the confidentiality but also verifies the integrity and the authentication of communications. We display that the modified scheme furthermore achieves anonymity as well as strong robustness.

Diabetic patients are prone to daily and severe health-related risks, namely hyper and hypoglycaemia. Hypoglycaemia phenomenon happens when the glucose level in patient’s blood is lower than a well-determined sill. It may induce serious impacts, such as functional brain failure or even the death. Hypoglycaemia is especially dangerous when it occurs during the night while the patient is asleep because it becomes difficult to be detected by the patient itself or other persons around him. While all existing sensor-based solutions are detection-only driven, the proposed solution goes beyond and attempts to treat autonomously, and at low cost, the nocturnal hypoglycaemia. The presented system detects the nocturnal hypoglycaemia phenomenon based on accelerated heart-rate symptom and a progressive detection algorithm. The system treats then the detected nocturnal hypoglycaemia throughout safe and automatic injection of glucagon.

Diabetic patients are prone to daily and severe health-related risks, namely hyper and hypoglycaemia. Hypoglycaemia phenomenon happens when the glucose level in patient’s blood is lower than a well-determined sill. It may induce serious impacts, such as functional brain failure or even the death. Hypoglycaemia is especially dangerous when it occurs during the night while the patient is asleep because it becomes difficult to be detected by the patient itself or other persons around him. While all existing sensor-based solutions are detection-only driven, the proposed solution goes beyond and attempts to treat autonomously, and at low cost, the nocturnal hypoglycaemia. The presented system detects the nocturnal hypoglycaemia phenomenon based on accelerated heart-rate symptom and a progressive detection algorithm. The system treats then the detected nocturnal hypoglycaemia throughout safe and automatic injection of glucagon.

Diabetic patients are prone to daily and severe health-related risks, namely hyper and hypoglycaemia. Hypoglycaemia phenomenon happens when the glucose level in patient’s blood is lower than a well-determined sill. It may induce serious impacts, such as functional brain failure or even the death. Hypoglycaemia is especially dangerous when it occurs during the night while the patient is asleep because it becomes difficult to be detected by the patient itself or other persons around him. While all existing sensor-based solutions are detection-only driven, the proposed solution goes beyond and attempts to treat autonomously, and at low cost, the nocturnal hypoglycaemia. The presented system detects the nocturnal hypoglycaemia phenomenon based on accelerated heart-rate symptom and a progressive detection algorithm. The system treats then the detected nocturnal hypoglycaemia throughout safe and automatic injection of glucagon.

Diabetic patients are prone to daily and severe health-related risks, namely hyper and hypoglycaemia. Hypoglycaemia phenomenon happens when the glucose level in patient’s blood is lower than a well-determined sill. It may induce serious impacts, such as functional brain failure or even the death. Hypoglycaemia is especially dangerous when it occurs during the night while the patient is asleep because it becomes difficult to be detected by the patient itself or other persons around him. While all existing sensor-based solutions are detection-only driven, the proposed solution goes beyond and attempts to treat autonomously, and at low cost, the nocturnal hypoglycaemia. The presented system detects the nocturnal hypoglycaemia phenomenon based on accelerated heart-rate symptom and a progressive detection algorithm. The system treats then the detected nocturnal hypoglycaemia throughout safe and automatic injection of glucagon.

Diabetic patients are prone to daily and severe health-related risks, namely hyper and hypoglycaemia. Hypoglycaemia phenomenon happens when the glucose level in patient’s blood is lower than a well-determined sill. It may induce serious impacts, such as functional brain failure or even the death. Hypoglycaemia is especially dangerous when it occurs during the night while the patient is asleep because it becomes difficult to be detected by the patient itself or other persons around him. While all existing sensor-based solutions are detection-only driven, the proposed solution goes beyond and attempts to treat autonomously, and at low cost, the nocturnal hypoglycaemia. The presented system detects the nocturnal hypoglycaemia phenomenon based on accelerated heart-rate symptom and a progressive detection algorithm. The system treats then the detected nocturnal hypoglycaemia throughout safe and automatic injection of glucagon.

Increasing the specter efficiency has been an object for many studies. In this paper, we investigate the higher modulation 256 QAM using Artificial Neural Networks (ANN) as an equalization model. Multilayer perceptron (MLP) and Radial Basis Function (RBF) are considered as non-linear equalizer based on back-propagation and Euclidian norm respectively. They are designed in a simplified architecture and employing some performing strategies for a better learning and an increased processing speed. ANNs are presented and applied with Orthogonal Frequency Division Multiplexing (OFDM) over Rayleigh fading channel in order to optimize the modulation scheme's processing and performances despite its sensitivity to noise. The models will be compared to the theoretical BER simulation in terms of BER, and also in terms of MSE to show performance and efficiency; by that, this work will show the supremacy of MLP in decision making with 256 QAM.

Increasing the specter efficiency has been an object for many studies. In this paper, we investigate the higher modulation 256 QAM using Artificial Neural Networks (ANN) as an equalization model. Multilayer perceptron (MLP) and Radial Basis Function (RBF) are considered as non-linear equalizer based on back-propagation and Euclidian norm respectively. They are designed in a simplified architecture and employing some performing strategies for a better learning and an increased processing speed. ANNs are presented and applied with Orthogonal Frequency Division Multiplexing (OFDM) over Rayleigh fading channel in order to optimize the modulation scheme's processing and performances despite its sensitivity to noise. The models will be compared to the theoretical BER simulation in terms of BER, and also in terms of MSE to show performance and efficiency; by that, this work will show the supremacy of MLP in decision making with 256 QAM.