Node Localization Research Articles

Design and implementation of anchor coprocessor architecture for wireless node localization applications

Design and implementation of anchor coprocessor architecture for wireless node localization applications

Seagull optimization algorithm for node localization in wireless sensor networks

Seagull optimization algorithm for node localization in wireless sensor networks

Node Localization Using Modified Wild Horse Optimization and Energy Efficient Secured Routing Protocol for IoT Based Wireless Sensor Networks

Internet of Things (IoT) devices are being utilized extensively as a result of the development of information and communication technology. Wireless sensor networks (WSNs), which are formed of inexpensive smart devices for information collection, plays a vital function in the establishment of the IoT. These smart devices are not without limitations, though, whether it comes to processing, memory, computing, and energy usage. In addition to these limitations, the core difficulties facing WSN include node localization, reliability, and data security during transmission in a dangerous environment from hostile nodes. The important and difficult problem for researchers to solve in order to improve network longevity, reliability, scalability, connectivity, throughput is accurate localization and routing. To improve the network period and data trustworthiness, this study intends to design an Energy-Efficient and Secure Routing protocol (EESR) and node localization centered on modified wild horse optimization (LMWHO) for intrusion avoidance in IoT utilizing WSN. Initially the suggested protocol bases its creation of various energy-efficient clusters on the inherent characteristics of nodes. Secondly, the base station (BS) and cluster head are able to reliably and securely share sensory data according to the (k,n) threshold-based Shamir secret sharing method. And finally, node localization centered on modified wild horse optimization (EESR-LMWHO), where the fitness function was formed by the development of residual energy and distance estimate. The suggested EESR-LMWHO utilizes less energy and prolongs the life of wireless networks. Lastly, the simulations are run to evaluate the suggested method's efficiency. The suggested approach, according to the experiments, approximates the location of the unknown node, offers a minimal localization error, and is a lightweight way to deal with intrusions caused by hostile nodes.

Wireless Sensor Networks Node Localization Algorithm Based on Range Optimization and Graph Optimization

<p>To address the problem of low localization accuracy in the node localization algorithms of wireless sensor networks (WSN) based on received signal strength indication (RSSI) ranging, a WSN node localization algorithm based on ranging optimization and graph optimization is proposed. In terms of RSSI ranging, the outliers are removed using the Grubbs method, and the data are processed using a moving average smoothing-Gaussian hybrid filter to establish a Bessel function ranging model to reduce the ranging error; in terms of node localization, the signal strength data are employed to construct a distance cost term, a cost function model is built based on these cost terms, and graph optimization is adopted to minimize this function. Then, the node position is estimated to minimize the overall observation error. Simulation results indicate that the proposed algorithm has higher ranging and localization accuracy than existing ranging and localization algorithms, and it can meet the requirements of node localization in large-scale WSN.</p> <p> </p>

The Sentinel Node and Occult Lesion Localization (SNOLL) Technique Using a Single Radiopharmaceutical in Non-palpable Breast Lesions.

In order to perform a full surgical resection on non-palpable breast lesions, a current method necessitates correct intraoperative localization. Additionally, because it is an important prognostic factor for these patients, the examination of the lymph node status is crucial. The aim of this study was to evaluate the efficiency of the sentinel node and occult lesion localization (SNOLL) technique in localizing nonpalpable breast lesions together with sentinel lymph node (SLN) using a single radiotracer, that is, nanocolloid particles of human serum albumin (NC) labeled with technetium-99m (99mTc). 39 patients were included, each having a single non-palpable breast lesion and clinically no evidence of axillary disease. Patients received 99mTc- NC intratumorally on the same day as surgery under the guidance of ultrasound. Planar and single-photon emission computed tomography/computed tomography lymphoscintigraphy were performed to localize the breast lesion and the SLN. The occult breast lesion and SLN were both localized using a hand-held gamma-probe, which was also utilized to determine the optimal access pathway for surgery. In order to ensure a radical treatment in a single surgical session and reduce the amount of normal tissue that would need to be removed, the surgical field was checked with the gamma probe after the specimen was removed to confirm the lack of residual sources of considerable radioactivity. Breast lesions were successfully localized and removed in all patients. Pathological findings revealed breast carcinoma in 11/39 patients (28%) and benign lesions in 28 (72%). Axillary SLNs were detected in 31/39 (79.5%) patients. The metastatic involvement of SLN was only seen in two cases. While the identification rate of the SNOLL technique performed with an intratumoral injection of 99mTc-NC as the sole radiotracer in non-palpable breast lesions was great, it was not fully satisfactory in SLNs.

Hybridized Black Widow-Honey Badger Optimization: Swarm Intelligence Strategy for Node Localization Scheme in WSN

Hybridized Black Widow-Honey Badger Optimization: Swarm Intelligence Strategy for Node Localization Scheme in WSN

A CFO-Assisted Algorithm for Wireless Time-Difference-of-Arrival Localization Networks: Analytical Study and Experimental Results

Localization of wireless transmitters is traditionally done using Radio Frequency (RF) sensors that measure the propagation delays between the transmitter and a set of anchor receivers. One of the major challenges of wireless localization systems is the need for anchor nodes to be time-synchronized to achieve accurate localization of a target node. Using a reference transmitter is an efficient way to synchronize the anchor nodes Over-The-Air (OTA), but such algorithms require multiple periodic messages to achieve tight synchronization. In this paper, we propose a new synchronization method that only requires a single message from a reference transmitter. The main idea is to use the Carrier Frequency Offset (CFO) from the reference node, alongside the Time of Arrival (ToA) of the reference node messages, to achieve tight synchronization. The ToA allows the anchor nodes to compensate for their absolute time offset, and the CFO allows the anchor nodes to compensate for their local oscillator drift. Additionally, using the CFO of the messages sent by the reference nodes and the target nodes also allow us to estimate the speed of the targets. The error of the proposed algorithm is derived analytically and is validated through controlled laboratory experiments. Finally, the algorithm is validated by realistic outdoor vehicular measurements with a software-defined radio testbed.

Improved DV-Hop based on parallel compact Willow Catkin Optimization algorithm for 3D nodes localization in WSN

Improved DV-Hop based on parallel compact Willow Catkin Optimization algorithm for 3D nodes localization in WSN

POSTMORTEM HEART DISSECTION FOR SUDDEN DEATH EXAMINATION

The article describes the postmortem heart examination technique during a forensic autopsy of adults. The heart examination technique is based on the recommendations of scientific societies of pathologists, publications on autopsy techniques used in recent decades. The achievements of morphologists of the second half of the 20th century are also taken into account. The postmortem heart examination technique provides an examination of the coronary vessels, as well as myocardium and heart valves. The possibilities for examination of the elements of the conductive system are also represented. The following method ensures preservation of topographic relationships of morphological structures within the heart and possibility of its re-examination. The postmortem heart examination includes the following stages: examination of the coronary arteries, the making of three transverse incisions from the apex to the middle of the ventricles, “blood flow” incisions taking into account the localization of the main nodes of the conducting system, as well as the peculiarities of the examination of the heart valves. Peer Review History: Received: 12 October 2023; Revised: 21 November; Accepted: 27 December, Available online: 15 January 2024 Academic Editor: Dr. Nuray Arı, Ankara University, Turkiye, ari@ankara.edu.tr Received file: Reviewer's Comments: Average Peer review marks at initial stage: 6.0/10 Average Peer review marks at publication stage: 7.0/10 Reviewers: Prof. Hassan A.H. Al-Shamahy, Sana'a University, Yemen, shmahe@yemen.net.ye Dr. Rima Benatoui,Laboratory of Applied Neuroendocrinology, Department of Biology, Faculty of Science, Badji Mokhtar University Annaba, Algeria. benattouiryma@gmail.com Dr. Bilge Ahsen KARA, Ankara Gazi Mustafa Kemal Hospital, Turkey, ahsndkyc@gmail.com

Instantaneous Wireless Robotic Node Localization Using Collaborative Direction of Arrival

Instantaneous Wireless Robotic Node Localization Using Collaborative Direction of Arrival

Concordancia entre SPECT portátil y la gammagrafía convencional para detección de ganglio centinela en cáncer de mama

IntroductionFreehand SPECT can be a useful imaging technique for preoperative planning of sentinel lymph node biopsy (SLNB) as it allows localization of the sentinel node by 3D and real-time tomographic imaging and determines its depth after a few minutes of scanning.The aim of the study was to evaluate the correlation between the number of detected SNs between freehand SPECT images and lymphoscintigraphy (LS). Materials and methodsOne hundred patients with a diagnosis of invasive breast cancer and no clinical evidence of lymph node involvement prospectively underwent SLNB. The preoperative study included freehand SPECT imaging at 15min after injection and LS imaging at 25 and 60–90min after injection (early and late). The observed agreement was analyzed and a concordance study was performed between the number of SNs detected with freehand SPECT and LS. ResultsThe observed agreement in the detection of SNs between freehand SPECT and early LS was 72%; between freehand SPECT and late LS was 85%; and between early and late LS was 87%. In the concordance study, there was moderate concordance between freehand SPECT and early LS (kappa coefficient: 0.42); moderate-high concordance between freehand SPECT and late LS (kappa coefficient: 0.60); and moderate-high concordance between early and late LS (kappa coefficient: 0.70), with no significant differences between them (p-value=0.16). ConclusionFreehand SPECT showed a moderate-high concordance with conventional imaging studies and could be a valid alternative for the presurgical study of SLNB in breast cancer.

Feasibility and accuracy of targeted axillary dissection in breast cancer patients; single center experience.

Axillary complete response (pCR) was observed in approximately half of breast cancer patients who received neoadjuvant chemotherapy (NAC) due to axillary positivity. Preventing axillary morbidity due to unnecessary axillary lymph node dissection (ALND) is extremely important for patients' quality of life. Targeted axillary dissection (TAD) is a technique developed to improve axillary staging and reduce the false negative rate in sentinel lymph node biopsy. Patients with cN1-N2 (clinically node) breast cancer whose axillary lymph node metastasis was confirmed by biopsy and who received NAC marked with a clip were included in the study. Patients who achieved clinical response after systemic treatment underwent sentinel lymph node biopsy (SLNB) with additional methods such as methylene blue guided dissection, skin marking for clip on lymph node (CLN) localization, and wire guided with imaging excision of the CLN. TAD and ALND pathology results were evaluated and analyzed with patient and tumor characteristics. 83 patients who met the eligibility criterias for the study were examined retrospectively. 21 of the patients underwent TAD alone, and 62 patients underwent ALND after TAD. CLN rate was 98.8% in patients underwent only TAD and this rate was increased to 100% in patients underwent ALND after TAD. FNR in SLN, CLN, and TAD were 28.6%, 10.7%, and 3.6%, respectively. TAD is a feasible and reliable surgical approach to detect axillary residual disease with a high success rate.

An efficient node localization and failure node detection in the MANET environment

An efficient node localization and failure node detection in the MANET environment

Modeling of Dung Beetle Optimization-based Sink Node Localization Approach for Wireless Sensor Networks

Wireless sensor network (WSN) performs monitoring of each aspect of the area of interest by detecting the surrounding physical phenomena with sensor nodes and transferring the information to the gateway through the corresponding system. Several researcher workers have introduced localization methods to accomplish high accuracy of localization. An intelligent optimization technique has attracted various researcher workers due to its advantages such as strong optimization capability and few parameters to optimize the localization performance of the DV-Hop method. Sink node localization (NL) using metaheuristics in WSN includes applying optimization techniques inspired by human behavior or natural phenomena to define the geographical coordinates of the sink nodes within the network coverage region. WSNs can accomplish better localization performance, especially in dynamic or complex environments, improving the efficiency and reliability of network management and data transmission by leveraging metaheuristics. In this view, this manuscript develops a Dung Beetle Optimization based Sink Node Localization Approach (DBO-SNLA) for WSN. In the DBO-SNLA technique, the DBO algorithm involved is based on the social behavior of dung beetle populations and is developed with five updated rules to assist in finding high-quality solutions. In addition, the DBO-SNLA technique addresses the issues of defining the sink node location with lowest localization error once the data between the nodes is transferred wirelessly. Finally, the localization errors are calculated and the location of the different unknown nodes is computed. A detailed set of simulation takes place to examine the performance of the DBO-SNLA technique. The empirical analysis stated the betterment of the DBO-SNLA method than other techniques

Clinical anatomy of pulmonary connections in young people

Aim: To study the clinical anatomy of the pulmonary ligaments of young people. Materials and Methods: The study was carried out when performing 28 autopsies of young people aged 25 to 44 years. Methods of dissection of chest organocomplexes, macro-microscopy, morphometry and planimetry, and statistical processing were used. The shape and topography of the pulmonary ligaments was assessed, their area, the localization of lymph nodes was examined. Results: The pulmonary ligament is an anatomical formation, which is formed as a result of a combination of leaves of the mediastinal pleura, which, covering the surfaces of the roots of the lungs, descend towards the diaphragm and are located between the mediastinal organs and the lungs. Pulmonary connections on both sides have a few edges: the inner, outer and lower free. The pulmonary ligaments with lower free edges do not pass to the diaphragmatic surface of the pleura, but only with inner ones, which are located on the right along the esophagus, and on the left along the aorta. Pulmonary ligaments on both sides pass into the mediastinal part of the pleura, covering the pericardium. Conclusions: There are individual differences between the shape and size of the right and left pulmonary ligaments in males and females. There is no significant difference between the sizes of the right and left pulmonary ligaments, but such dimensions as: the width, the angle of inclination and the ratio of their lower free edge to the lower edge of the lungs are not found in all cases.

AN-GCN: An Anonymous Graph Convolutional Network Against Edge-Perturbing Attacks.

Recent studies have revealed the vulnerability of graph convolutional networks (GCNs) to edge-perturbing attacks, such as maliciously inserting or deleting graph edges. However, theoretical proof of such vulnerability remains a big challenge, and effective defense schemes are still open issues. In this article, we first generalize the formulation of edge-perturbing attacks and strictly prove the vulnerability of GCNs to such attacks in node classification tasks. Following this, an anonymous GCN, named AN-GCN, is proposed to defend against edge-perturbing attacks. In particular, we present a node localization theorem to demonstrate how GCNs locate nodes during their training phase. In addition, we design a staggered Gaussian noise-based node position generator and a spectral graph convolution-based discriminator (in detecting the generated node positions). Furthermore, we provide an optimization method for the designed generator and discriminator. It is demonstrated that the AN-GCN is secure against edge-perturbing attacks in node classification tasks, as AN-GCN is developed to classify nodes without the edge information (making it impossible for attackers to perturb edges anymore). Extensive evaluations verify the effectiveness of the general edge-perturbing attack (G-EPA) model in manipulating the classification results of the target nodes. More importantly, the proposed AN-GCN can achieve 82.7% in node classification accuracy without the edge-reading permission, which outperforms the state-of-the-art GCN.

Node Localization Algorithm for Irregular Regions Based on Particle Swarm Optimization Algorithm and Reliable Anchor Node Pairs

Node Localization Algorithm for Irregular Regions Based on Particle Swarm Optimization Algorithm and Reliable Anchor Node Pairs

An Optimal Node Localization in WSN Based on Siege Whale Optimization Algorithm

An Optimal Node Localization in WSN Based on Siege Whale Optimization Algorithm

Enhancing Location Accuracy by Minimizing RMS Using RSS-AMLE in WSN

Over the past decade, there has been significant growth in wireless sensor networks, particularly in the context of industrial applications. Mobile sensor networks have garnered research interest due to their ability to facilitate communication between various devices. Still, the mobility of these nodes gives rise to challenges such as network coverage and connectivity issues. Addressing these challenges necessitates accurate estimation of sensor node locations, a critical factor in network performance. Numerous methods, such as Angle of Arrival (AOA) and Time of Arrival (TOA), have been proposed for node localization. Still, these methods are plagued by localization errors and high implementation costs. To overcome these localization errors in wireless sensor networks, we present an adaptive approach based on the Received Signal Strength (RSS) model. This model views localization as a non-convex problem and employs an adaptive maximum likelihood estimation to minimize localization errors. An extensive simulation study is carried out to measure the performance of the intended approach in minimizing the localization error. The results unequivocally demonstrate that our localization scheme achieves higher accuracy in locating sensor nodes while reducing deployment costs. Comparative analysis against existing methods further underscores the significance of our approach.

Secure multi-path routing for Internet of Things based on trust evaluation.

In the realm of the Internet of Things (IoT), ensuring the security of communication links and evaluating the safety of nodes within these links remains a significant challenge. The continuous threat of anomalous links, harboring malicious switch nodes, poses risks to data transmission between edge nodes and between edge nodes and cloud data centers. To address this critical issue, we propose a novel trust evaluation based secure multi-path routing (TESM) approach for IoT. Leveraging the software-defined networking (SDN) architecture in the data transmission process between edge nodes, TESM incorporates a controller comprising a security verification module, a multi-path routing module, and an anomaly handling module. The security verification module ensures the ongoing security validation of data packets, deriving trust scores for nodes. Subsequently, the multi-path routing module employs multi-objective reinforcement learning to dynamically generate secure multiple paths based on node trust scores. The anomaly handling module is tasked with handling malicious switch nodes and anomalous paths. Our proposed solution is validated through simulation using the Ryu controller and P4 switches in an SDN environment constructed with Mininet. The results affirm that TESM excels in achieving secure data forwarding, malicious node localization, and the secure selection and updating of transmission paths. Notably, TESM introduces a minimal 12.4% additional forwarding delay and a 5.46% throughput loss compared to traditional networks, establishing itself as a lightweight yet robust IoT security defense solution.