This research presents PACE (Providing Authentication through Computational Gait Evaluation), a novel methodology for gait-based authentication leveraging the power of deep learning algorithms. The primary objective of PACE is to enhance the security and efficiency of user authentication mechanisms by capitalizing on the unique gait patterns exhibited by individuals. This study delineates the development and implementation of a deep learning model, which was trained on a set of extracted features. These features, including mean, variance, standard deviation, kurtosis, and skewness, were derived from accelerometer and gyroscope data, serving as descriptors of users' gait patterns for the deep learning model. The model's performance was evaluated based on its ability to classify and authenticate users accurately using these features. For the purpose of this study, twelve participants were enlisted, with sensors affixed to their back hip and right ankle to collect the requisite accelerometer and gyroscope data. The experimental results were highly promising, with the model achieving an exceptional accuracy rate of 99% in authenticating users. These findings underscore the potential of PACE as a viable alternative to conventional machine learning methods for gait authentication. The implications of this research are far-reaching, with potential applications spanning a multitude of scenarios where security is of paramount importance.

In wireless sensor networks (WSNs) with symmetric duty cycles, a block design technique produces an optimal solution for neighbor discovery in terms of the worst-case discovery latency. However, block design-based neighbor discovery methods may not be applicable to WSNs with asymmetric duty operations. Thus, to address this lack of support of asymmetric WSNs, we propose a new neighbor discovery protocol (NDP) that combines two block designs for generating a set of discovery schedules. We prove that the discovery schedule generated by the proposed NDP includes at least one common active slot with any neighboring nodes within a single cycle. We also conduct a simulation study and show that the proposed NDP is better than representative NDPs such as U-Connect, Disco, SearchLight, Hedis, and Todis in terms of discovery latency and energy efficiency.

In the Internet of Things (IoT) environment, a sensor network protocol must satisfy various application-specific requirements such as synchronous, asynchronous, symmetric, and asymmetric operations. Most block design-based neighbor discovery protocols can not support asymmetric operations. In this paper, we propose a new block cycle length-based asymmetric rendezvous protocol for neighbor discovery. The proposed protocol has better energy efficiency and shorter latency than existing asynchronous neighbor discovery protocols since it is based on optimized block designs.

The assessment of a person's ability to consistently perform the fundamental activities of daily living is essential in monitoring the patient's progress and measuring the success of treatment. Therefore, many researchers have been interested in this issue and have proposed various monitoring systems based on accelerometer sensors. However, few systems focus on energy consumption of sensor devices. In this paper, we introduce an energy-efficient physical activity monitoring system using a wearable wireless sensor. The proposed system is capable of monitoring most daily activities of the human body: standing, sitting, walking, lying, running, and so on. To reduce energy consumption and prolong the lifetime of the system, we have focused on minimizing the total energy spent for wireless data exchange by manipulating real-time acceleration data on the sensor platform. Furthermore, one of our key contributions is that all functionalities including data processing, activity classification, wireless communication, and storing classified activities were achieved in a single sensor node without compromising the accuracy of activity classification. Our experimental results show that the accuracy of our classification system is over 95%.

A report by the Institute of Medicine of the National Academy of Sciences estimates that as many as 98,000 people die in U.S. hospitals each year because of medical errors. In this project, we propose an innovative IT-based approach to prevent errors in various medical processes by utilizing advance

In this paper, we propose energy efficient schemes for data dissemination in sensor networks. Our schemes are based on a hierarchical data dissemination model. The hierarchical data dissemination scheme (HDDS) leverages the fact that a nonuniform grid can be constructed to disseminate data based on sink density without any prior information about the position of the sinks. This approach seems to be promising as preliminary experimental results show that an average energy savings of 10-30% can be achieved using our schemes. Even with large number of sources and sinks, the schemes scale well yielding high throughput.. Experimental results show FDDD is suitable for applications which require higher throughput and minimum latency; fully distinct data dissemination for networks with limited energy consumption but can withstand some delay and loss of data, and limited sharing data dissemination is suitable for applications with large number of sources and sinks and average energy consumption and delay.

In this paper, we introduce two encoding and decoding methods for balanced codes. The proposed methods are more efficient in terms of computational complexity. The first one complements several appropriate bits at a time instead of complementing one bit at a time as done in Knuth's method. The second one is a parallel implementation of Knuth's method.

In this paper, based on coding theory concepts, a new time scheduling algorithm for multihop packet radio networks is described. Each mobile host is assigned a word from an appropriate constant weight code of length n, distance d and weight w. The host can send a message at the j/sup th/ slot provided the assigned code has a 1 in this j/sup th/ bit. The proposed algorithm is better than the previously known algorithms in terms of minimum system throughput. The algorithm also preserves other desired properties, such as topology independence, guaranteed minimum throughput, bounded maximum delay, and fair transmission policy.

Mobile hosts typically have scarce energy due to short battery lifetimes. We propose a scheduling algorithm which is suitable for battery-constrained multihop packet radio networks. The proposed algorithm, called ECTS (energy conserving transmission scheduling), focuses on conserving battery power while preserving topology transparency, guaranteed minimum throughput, bounded maximum delay, and fair transmission policy. The ECTS algorithm conserves the power using strategies that allow the network interface to use the low power sleep mode instead of the idle mode, and eliminates data collisions using RTS (request-to-send) and CTS (clear-to-send) control slots. As observed in previous experiments, the cost of mode transition is quite expensive. To relieve this unnecessary power consumption, the ECTS algorithm significantly reduces the number of mode transitions. For low-power hosts, the ECTS protocol reduces the number of mode transitions further. We have simulated and compared the energy efficiency of our protocol with the IEEE 802.11 and GRAND (Galois radio network design) algorithms. Simulation results show our protocol is very efficient in terms of power conservation.

A fault ring is a connection of only nonfaulty adjacent nodes and links such that the interior of the ring contains only faulty components. This paper proposes two wormhole routing algorithms that deal with more relaxed shapes of fault rings than previously known algorithms in the mesh networks. As a result, the number of components to be made disabled would be reduced considerably in some cases. First algorithm, called F4, uses four virtual channels and allows all four sides of fault rings to contain concave shapes. Second algorithm, F3, permits up to three sides to contain concave shapes using only three virtual channels. Both F3 and F4 are free of deadlock and livelock and guarantee the delivery of messages between any pair of nonfaulty and connected nodes in the network.

A binary code of length n is called a balanced code if each codeword contains exactly [n/2] (or [n/2]) ones and [n/2] (or [n/2]) zeros. In this paper, we give two improved methods for encoding and decoding balanced codes. The first one, called improved single map, improves the computation complexity of Knuth's single map function. This method, instead of complementing one bit at a time as done in Knuth's method, complements several appropriate bits at a time. Some simulation results show the improvement of this scheme over the previously known methods. The second one is a parallel implementation of this method.