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Data aggregation, gathering and gossiping are all vital communication tasks in wireless sensor networks (WSNs). When all networking devices are always active, scheduling algorithms for these communication tasks have been extensively investigated under both the protocol and physical interference models. However, wireless devices usually switch between the sleep state and the active state for the…

The use of wireless sensor networks (WSN) can be a valuable contribution in disaster situations or life-threatening exploration. Using wireless mobile robots, it is possible to explore vast areas without human intervention. However, the wireless network coverage that can keep mobile robots connected to the base station / gateway is a major limitation. With this…

In this paper we propose an algorithmic approach for Convolutional Neural Network (CNN) for digital watermarking which outperforms the existing frequency domain techniques in all aspects including security along with the criteria in the neural networks such as conditions embedded, and types of watermarking attack. This research addresses digital watermarking in deep neural networks and…

It is the age of information. Social networks are the main reason why, following the increasing activity of online users. With this comes a big impact on the real world, it can be positive and highly negative as well. Therefore, research in this field is highly needed for the betterment of societal behaviors within social…

Comparing to other types of vehicle accidents, fatality rate of tipped rollover accidents shows significant number. Thus, tripped rollover prevention systems are important in order to keep driver safe. In other hands, different rollover indices are defined to handle the risk. The variable unknown parameters of each index, for instance, current load of the vehicle…

This paper presents a comparative study for using the classic networks in remote sensing images classification. There are four deep convolution models that used in this comparative study; the DenseNet 196, the NASNet Mobile, the VGG 16, and the ResNet 50 models. These learning convolution models are based on the use of the ImageNet pre-trained…

Contextual continuous word representation showed promising performances in different natural language processing tasks. It stems from the fact that these word representations consider the context in which a word appears. But until recently, very little attention was paid to the contextual representations in Arabic question classification task. In the present study, we employed a contextual…

Over the last decades, numerous distributed consensus-based algorithms have found a wide application as a complementary mechanism for data aggregation in wireless sensor networks. In this paper, we provide an analysis of the generalized Metropolis-Hastings algorithm for data aggregation with a fully-distributed stopping criterion. The goal of the implemented stopping criterion is to effectively bound…

Suppose we want to classify a query item Q with a classification model that consists of a large set of predefined classes L and suppose we have a knowledge that indicates to us that the target class of Q belongs to a small subset from L. Naturally, this filtering will improve the accuracy of any…

Vietnam is one of the top 5 largest shrimp exporters globally, and Mekong delta of Vietnam contributes more than 80% of total national production. Along with intensive farming and growing shrimp farming area, diseases are a severe threat to productivity and sustainable development. Timely response to emerging shrimp diseases is critical. Early detection and treatment…

Blurred small objects produced by cropping, warping, or intrinsically so, are challenging to detect and classify. Therefore, much recent research is focused on feature extraction built on Faster R-CNN and follow-up systems. In particular, RPN, SPP, FPN, SSD, and DSSD are the layered feature extraction methods for multiple object detections and small objects. However, super-resolution…

Recurrent Neural Networks has been widely used by researchers in the domain of weather prediction. Weather Prediction is forecasting the atmosphere for the future. In this proposed paper, Deep LSTM networks has been implemented which is the variant of RNNs having additional memory block and gates making them capable of remembering long term dependencies. Fifteen…

Many real-life applications based on the wireless sensor networks are equipped with data aggregation mechanisms for suppressing or even overcoming negative environmental effects and data redundancy. In this paper, we present an extended analysis of the linear average consensus algorithm for distributed summing with bounded execution over wireless sensor networks. We compare a centralized and…

An emerging trend has been observed in the Trust and Reputation (T & R) systems in field of decision-making support for a majority of the provisions propagated by the Internet. It is the extreme importance that peers (users) are able to trust each other and rely on them for file sharing and for services. This…

Recently, opportunistic networks are considered as one of the most attractive developments of ad hoc mobile networks (MANETs) that have emerged thanks to the development of intelligent devices. Due to the mobility-related instability of the paths between nodes and due to the limited buffer and energy resources, the ultimate objective of routing protocols in opportunistic…

In more recent times, researchers have turned their attention to link prediction and the role link inference can play in better understanding the evolutionary nature of social networking sites. The objective of this paper is to present an in-depth review, analysis, and discussion of the cutting-edge link prediction methods that can be applied to better…

This paper proposes a new classification model distinguishing four classes of attacks in Wireless Sensor Networks (WSNs) namely: attacks based on the protocol stack, on the capability of the attacker, on the attack impacts and on the attack target. Then, it presents and classifies the most known attacks in WSNs based the proposed model. Simulations…

This paper addresses the generation of stylized texts in a multilingual setup. A long short-term memory (LSTM) language model with extended phonetic and semantic embeddings is shown to capture poetic style when trained end-to-end without any expert knowledge. Phonetics seems to have a comparable contribution to the overall model performance as the information on the…

In an enterprise Wifi network, indoor and dense, co-channel interference is a major issue. Wifi controllers help tackle this problem thanks to radio resource management (RRM). RRM is a fundamental building block of any controller functional architecture. One aim of RRM is to process the radio plan such as to maximize the overall network transmit…

We present findings on classifying the class of executable code using convolutional, re- current neural networks by creating images from only the .text section of executables and dividing them into standard-size windows, using minimal preprocessing. We achieve up to 98.24% testing accuracy on classifying 9 types of malware, and 99.50% testing accuracy on classifying malicious…

Water distribution networks are infrastructural systems designed for providing potable water to consumers. In these last decades, the importance of assessing and identifying emerging leakages has become a primary issue, because of the high level of water loss characterizing such systems worldwide. In this paper, a new approach aimed at the prompt localization of leakages…

Popularity and a_ordability of smart phones and other data hungry devices add exponentially to the tra_c demand of existing cellular networks. Cell densification and small cell deployment over existing macrocell has been identified as an e_ective solution to high tra_c demand predicted for future wireless networks like 5G. Small cells are deployed over existing macrocells…

The major problem in electric utility is Electrical Theft, which is harmful to electric power suppliers and causes economic loss. Detecting and controlling electrical theft is a challenging task that involves several aspects like economic, social, regional, managerial, political, infrastructural, literacy rate, etc. Numerous methods were proposed formerly for detecting electricity theft. However, the previous…

The paper deals with hardware emulation of bio-inspired devices and nonlinear dynamic processes of complex nature by means of mixed-mode analog-digital emulators. The discretized state model of the emulated system serves for real-time calculation of dependent quantities. In contrast to input-output emulation known in control systems, the proposed approach emulates the ports of an electrical…

The main problem of the distribution of freight in archipelago countries such as Indonesia is how to ensure that the outlying and outermost islands are served optimally, with low freight costs and optimal frequency of vessel stops at ports. There are three types of vessels that are subsidized and have the duty of public service…