bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultra‐wideband technology: Prospective solution for 5G ultra‐small cell networks
Authors: Puerta Rafael , Rommel Simon , Jaramillo‐Ramirez Daniel , Tafur Monroy Idelfonso 
Published: September 2023

SummaryExhaustive research is being done to establish the technologies and standards of the fifth generation (5G) of wireless communication systems. Some of the most challenging requirements of 5G systems are to increase the spectral efficiency and the capacity by a factor of 10 and 1,000, respectively. New technologies must offer an adequate framework for the 5G uses cases, which will enable higher capacities and the flexibility to adapt to dynamic scenarios. To cope with these challenging demands, a compelling approach is to exploit the current radio service bands by means of spectrum sharing and cooperation techniques, which alleviate the bandwidth requirements. In addition, advanced modulation schemes have a fundamental role in ensuring the best usage of the spectrum available in band‐limited systems. In this manuscript, we present the ultra‐wideband (UWB) technology as a prospective solution for 5G picocells and femtocells. Its main feature is its capability to operate simultaneously, without introducing interference, with current radio services on an unlicensed basis. We report experimental results reaching data rates up to 35 Gbit/s using the multiband approach of carrierless amplitude phase (MB‐CAP) modulation. To validate the versatility of the proposed system, our experimental tests were performed under the UWB regulations defined by the United States' Federal Communications Commission (FCC), the European Electronic Communications Committee (ECC), and the Russian State Committee for Radio Frequencies (SCRF). The regulations chosen provide diversity enough to demonstrate the capacity of MB‐CAP modulation to comply with worldwide regulations.
A hybrid adaptive spatiotemporal compression scheme in cluster‐based wireless sensor networks
Authors: Al Fallah Samia , El Aasri Jihane , Arioua Mounir , El Oualkadi Ahmed 
Published: September 2023

SummaryEnergy efficiency and data reliability are the crucial issues to be explored in wireless sensor networks (WSNs). A large amount of power consumption is depleted by each sensor node to transmit its sensed data which typically induces high temporal and spatial dependencies. Therefore, efficient compression approaches are designed to exploit the data correlation in both space and time so as to discard information redundancies with accurate recovery. In this paper, we propose a hybrid and adaptive spatiotemporal compression approach named Distributed Temporal Source Coding, designed to extend the lifespan of cluster based WSNs. The proposed scheme takes advantage of the performed Distributed Source Coding as an effective spatial compression algorithm and adaptively exploits the Lightweight Temporal Compression as a promising solution to reduce the temporally correlated information. The obtained results have revealed that the proposed algorithm outperforms other compression methods, promotes the network battery life, and ensures compelling data accuracy. The proposed scheme has succeeded to reduce the gap between the energy efficiency and data reliability in WSNs.
Clustering healthcare big data using advanced and enhanced fuzzy C‐means algorithm
Authors: Purandhar N. , Ayyasamy S. , Saravanakumar N.M. 
Published: September 2023

SummaryThe procedure for revelation and extraction is known as the data mining (DM) where immense measure of information is included. The information mining along with the human services industry has developed solid frameworks and different social insurance that are related to the frameworks from the clinical and finding information. Numerous types of assistance have been offered by healthcare. This includes diagnosing, treatment, avoidance of maladies, sicknesses, wounds and other physical and mental issue. Enormous scopes that are appropriated for preparing applications in healthcare have essential idea that works on a lot of information. Large information application capacities are the primary piece of medicinal services activities. However, no far reaching and methodical review regarding the examining and assessing the significant systems in the field. The different researches associated with the field of healthcare are considered or different strategies, calculations and results. Enormous information object has countless traits, representing a wonderful test on fuzzy C‐means (FCM) for huge information constant grouping. An effective FCM depends on the tensor accepted polyadic deterioration for huge information clustering. The advanced and enhanced fuzzy C‐means algorithm for healthcare (AEFCH) calculation which is an introduced term is changed over to a high‐request tensor FCM calculation by means of a bijection work. Tensor authoritative polyadic deterioration is used to decrease qualities of the items for improving the grouping productivity. Outcomes obtained accomplish fundamentally higher productivity with a slight cluster exactness drop contrasted and the customary calculation, demonstrating the capability of plot that has been created for information of smart data from Internet of Things.
Design of quantum‐dot cellular automata technology based cost‐efficient polar encoder for nanocommunication systems
Authors: Ahmed Suhaib , Naz Syed Farah , Bhat Soha Maqbool 
Published: September 2023

SummaryIn the current digital era, there is a need of secure and efficient nanocommunication systems with ultralow power consumption. One technology that can be used for designing these systems is the quantum‐dot cellular automata (QCA). In the nanoregime, QCA is able to operate with higher speed and lower power dissipation compared with complementary metal oxide semiconductor technology. This work explores the applicability and feasibility of polar encoders, which felicitates reliable data communication with reduced probability of error, in nanocommunication systems. In this paper, (8,4) polar encoder is proposed in QCA technology. The proposed design is a single‐layer structure designed using only 600 cells consuming cell area of 0.1944 μm2 and total area of 0.7225 μm2 with a latency of 3.75 clock cycles, which results in a cost of 10.16. Based on the performance comparison, it is observed that the proposed design is cost‐efficient and achieves improvement up to 49.49% in terms of number of cells and area consumption, 40% improvement in latency, and 86.42% improvement in terms of cost compared with the only design in the literature. In addition to this, the energy dissipation analysis of the proposed designs is also presented. Hence, the proposed designs can be efficiently utilized in nanocommunication systems requiring minimal area and ultralow power consumption.
Cost function‐based class of service provisioning strategy in elastic optical networks
Authors: Dixit Shruti , Batham Deepak , Narwaria Ravindra Pratap 
Published: September 2023

SummaryThe recent fog‐and‐cloud computing, Internet of things (IoT), artificial intelligence, machine learning, and store‐and‐forward datacenter applications gradually increase the Internet traffic. The arrival of this traffic is periodic, which remains high during certain time duration (known as peak or working/office hour) each day, resulting in an increase in the resource bottleneck problem, which causes high connections blocking. Due to these, many commercial and business data services may lose their connections which contain the urgent and important information. In order to handle such a critical situation in elastic optical networks (EONs), prioritization of connection requests based on the differentiated class of service (CoS) is a must. In this paper, the network traffic is categorized into three CoS requests. These are CoS1 (real‐time traffic), CoS2 (nonreal‐time traffic), and CoS3 (delay‐tolerant traffic) and proposed a cost function‐based CoS provisioning (CFCoSP) strategy in which the connection requests are served as per an increasing value of cost function. The cost function is a cumulative function of CoS, pathlength, and requested bandwidth demand (i.e., number of frequency slots required). The simulations are performed on INDIAN and ARPANET network topologies under uniform CoS ratio (i.e., CoS1:CoS2:CoS3 = 1:1:1) on the metrics of connection established, bandwidth blocking probability, resource utilization ratio, and network capacity utilization. The simulation results verify that the proposed CFCoSP strategy shows significantly improved performances as compared to an existing non‐cost CoS provisioning (CoSP) strategy on the investigated metrics.
SPEECH‐MAC: Special purpose energy‐efficient contention‐based hybrid MAC protocol for WSN and Zigbee network
Authors: Ajmi Nader , Helali Abdelhamid , Lorenz Pascal , Mghaieth Ridha 
Published: September 2023

SummaryEnergy‐efficient Zigbee‐based wireless sensor network (WSN) occupies a major role in emergency‐based applications. The foremost drawback of such applications is maintaining the battery power because frequent changing is not possible in those conditions. In the earlier days, several researches created new model MAC protocols in terms of increase the lifetime of the WSN. But still, there is a research gap particularly in emergency applications. In order to improve the lifetime of such applications, we introduced a novel hybrid MAC protocol, namely, special purpose energy‐efficient contention‐based hybrid MAC (SPEECH‐MAC) protocol. This protocol includes dual hop concept considerably to save the energy. Both the single hop network and the dual hop networks are developed, and the results are analyzed. Prioritization mechanism for SPEECH‐MAC protocol is introduced to analyze the emergency conditions in detail. In summary, according to the simulation, the calculated parameters are total residual energy, end‐to‐end delay, packet drop, packet delivery ratio, and network throughput.
A smart spectrum utilization approach using multiantenna‐based cognitive relays in cognitive radio network
Authors: Samanta Dipak , Kumar Bag Jayanta , Kumar De Chanchal , Chandra Abhijit 
Published: September 2023

SummaryEfficient spectrum utilization is a promising technique for a prolonged unused radio frequency (RF) spectrum in a wireless network. In this paper, an adaptive spectrum sharing cognitive radio (CR) network has been proposed consisting of a primary user (PU) and secondary user transmitter (SU − Tx) that communicates with secondary user receiver (SU − Rx) via multiantenna‐based proactive decode‐and‐forward (DF) relay selection scheme. In our model, strategically an adaptable joint venture on underlay/overlay protocol is defined based on channel occupancy using spectrum sensing technique. Here, secondary transmitters (i.e., source transmitter) continuously sense the PU activities by energy detector and can simultaneously transmit to secondary receivers. Depending on sensing result secondary transmitters automatically switches in underlay mode if PU is active otherwise operates in overlay mode. The advantage of this scheme is that the joint mode of transmission allows the SUs to maximize their transmission rate. The outage performance at SU − Rx and closed‐form expressions of joint underlay/overlay protocol has been evaluated. The power control policies at different transmitter nodes are taken care of. With the same diversity order, a trade‐off between multiantenna and multirelay is shown. This comparison shows improvement in outage behavior when the count in relays surpasses the number of antennas. Finally, the analytical model of smart efficient spectrum utilization without harming license users in CR is validated by MATLAB simulation.
Throughput and resource optimization for adaptive coding‐based random access networks with correlated sources
Authors: Mehta Ridhima 
Published: September 2023

SummaryModern wireless communication networks frequently have lower application throughput due to higher number of collisions and subsequent retransmission of data packets. Moreover, these networks are characterized by restricted computational capacity due to limited node‐battery power. These challenges can be assessed for deploying fast, reliable network design with resource‐restrained operation by means of concurrent optimization of multiple performance parameters across different layers of the conventional protocol stack. This optimization can be efficiently accomplished via cross‐layer design with the aid of network coding technique and optimal allocation of limited resources to wireless links. In this paper, we evaluate and analyze intersession coding across several source–destination pairs in random access ad hoc networks with inherent power scarcity and variable capacity links. The proposed work addresses the problem of joint optimal coding, rate control, power control, contention, and flow control schemes for multi‐hop heterogeneous networks with correlated sources. For this, we employ cross‐layer design for multiple unicast sessions in the system with network coding and bandwidth constraints. This model is elucidated for global optimal solution using CVX software through disciplined convex programming technique to find the improved throughput and power allocation. Simulation results show that the proposed model effectively incorporates throughput and link power management while satisfying flow conservation, bit error rate, data compression, power outage, and capacity constraints of the challenged wireless networks. Finally, we compare our model with three previous algorithms to demonstrate its efficacy and superiority in terms of various performance metrics such as transmission success probability, throughput, power efficiency, and delay.
Hybrid Chameleon Search and Remora Optimization Algorithm‐based Dynamic Heterogeneous load balancing clustering protocol for extending the lifetime of wireless sensor networks
Authors: Kumar Janjarapu David Sukeerthi , Subramanyam Makam Venkata , Kumar Arugudi Pataiah Siva 
Published: September 2023

SummaryClustering is an indispensable strategy that helps towards the extension of lifetime of each sensor nodes with energy stability in wireless sensor networks (WSNs). This clustering process aids in sustaining energy efficiency and extended network lifetime in sensitive and critical real‐life applications that include landslide monitoring and military applications. The dynamic characteristics of WSNs and several cluster configurations introduce challenge in the process of searching an ideal network structure, a herculean challenge. In this paper, Hybrid Chameleon Search and Remora Optimization Algorithm‐based Dynamic Clustering Method (HCSROA) is proposed for dynamic optimization of wireless sensor node clusters. It utilized the global searching process of Chameleon Search Algorithm for selecting potential cluster head (CH) selection with balanced trade‐off between intensification and extensification. It determines an ideal dynamic network structure based on factors that include quantity of nodes in the neighborhood, distance to sink, predictable energy utilization rate, and residual energy into account during the formulation of fitness function. It specifically achieved sink node mobility through the integration of the local searching capability of Improved Remora Optimization Algorithm for determining the optimal points of deployment over which the packets can be forwarded from the CH of the cluster to the sink node. This proposed HCSROA scheme compared in contrast to standard methods is identified to greatly prolong network lifetime by 29.21% and maintain energy stability by 25.64% in contrast to baseline protocols taken for investigation.
Efficacy and safety of perampanel monotherapy in Chinese patients with focal‐onset seizures: A single‐center, prospective, real‐world observational study
Authors: Ma Haiyan , Zhu Haitao , Chen Fangqing , Yang Yiqing , Qu Xuefeng , Xu Honghao , Yang Lu , Zhang Rui 
Published: September 2023

AbstractObjectiveEfficacy and safety of perampanel monotherapy for treating focal‐onset seizures (FOS) has been barely studied in China. This observational study aimed to evaluate the efficacy and safety of perampanel monotherapy in treating Chinese patients with FOS.MethodsThis single‐center, prospective, real‐world observational study enrolled patients aged ≥4 years with FOS who visited the Epilepsy Out‐Patient Clinic of Nanjing Brain Hospital affiliated to Nanjing Medical University from January 2020 to December 2021. All patients were treated with perampanel monotherapy. Seizure‐freedom rates after 6 and 12 months of treatment were calculated. Adverse events (AEs) were recorded.ResultsSeventy patients with FOS were enrolled. The mean maintenance perampanel dose was 4.64 ± 1.55 mg/day. The 6‐ and 12‐month retention rates of perampanel monotherapy were 78.6% (55/70) and 70.0% (49/70), respectively. The 6‐ and 12‐month seizure‐freedom rates were 69.84% (44/63) and 65.08% (41/63), respectively. Patients with focal to bilateral tonic–clonic seizures had significantly higher 6‐month and numerically higher 12‐month seizure freedom rates than patients with focal impaired awareness seizures (P = 0.046 and P = 0.204, respectively). Twenty‐six (37.1%) patients experienced treatment‐emergent AEs, and the most common AE was dizziness. Four (5.7%) patients withdrew from the study due to AEs. No new safety concern was observed.SignificanceThis is the first prospective study on the efficacy and safety of perampanel monotherapy in treating Chinese patients with FOS, and perampanel monotherapy was effective and safe in treating Chinese patients aged ≥4 years with FOS up to 12 months. More multicenter, real‐world studies with large sample sizes and longer follow‐ups are needed to further evaluate the long‐term efficacy and safety of perampanel monotherapy.
An intelligent Hybrid‐Q Learning clustering approach and resource management within heterogeneous cluster networks based on reinforcement learning
Authors: Mughal Fahad Razaque , He Jingsha , Zhu Nafei , Almutiq Mutiq , Dharejo Fayaz Ali , Jain Deepak Kumar , Hussain Saqib , Zardari Zulfiqar Ali 
Published: September 2023

AbstractRecently, heterogeneous cluster networks (HCNs) have been the subject of significant research. The nature of the next‐generation HCN environment is decentralized and highly dynamic; optimization techniques cannot quite express the dynamic characteristics of node resource utilization and communication of HCN networks. In this article, we present an intelligent Hybrid‐Q Learning approach (Hybrid QL)‐based clustering approach for IoT and WSN. Using the self‐learning abilities of (HCNs), we propose a model for dynamic accessing systems on nodes and agents that identify the best possible paths and communication over heterogeneous cluster networks using reinforcement learning. In addition to reducing energy consumption, it creates efficient and effective resource utilization and node communication performance. Through increased throughput and link management, the HCN aims to reduce energy consumption. The proposed model is compared to existing approaches based on various scenarios. Finally, the results of the evaluation tasks demonstrate high accuracy, low‐level complexity, fast dynamic response times, and scalability for heterogeneous cluster networks. Our model showed exceptional node allocation efficiency for dynamic IOT environments and WSNs.
Revisiting geophagy: An evolved sickness behavior to microbiome‐mediated gastrointestinal inflammation
Authors: Dorsey Achsah F. , Miller Elizabeth M. 
Published: September 2023

AbstractGeophagy, the consumption of clay or similar substances, is known as an evolved behavior that protects vulnerable populations, such as pregnant women and children, against gastrointestinal injury. However, perplexing questions remain, like the presence of geophagy in the absence of overt gastrointestinal infection and the potential causal relationship between geophagy and iron deficiency anemia. In this review, we hypothesize that geophagy is an inflammation‐mediated sickness behavior regulated via the vagus nerve. We further hypothesize that the gut microbiome plays a critical role in mediating the relationship between inflammation and geophagy. By including inflammation and the microbiome within the existing protection hypothesis, we can explain how subclinical gastrointestinal states induce geophagy. Furthermore, we can explain how gastrointestinal inflammation is responsible for both geophagy and iron‐deficiency anemia, explaining why the two phenomena frequently co‐occur. Ultimately, defining geophagy as a sickness behavior allows us to integrate the gut‐brain axis into geophagy research.
Reviving grain quality in wheat through non‐destructive phenotyping techniques like hyperspectral imaging
Authors: Safdar Luqman B. , Dugina Kateryna , Saeidan Ali , Yoshicawa Guilherme V. , Caporaso Nicola , Gapare Brighton , Umer M. Jawad , Bhosale Rahul A. , Searle Iain R. , Foulkes M. John , Boden Scott A. , Fisk Ian D. 
Published: September 2023

AbstractA long‐term goal of breeders and researchers is to develop crop varieties that can resist environmental stressors and produce high yields. However, prioritising yield often compromises improvement of other key traits, including grain quality, which is tedious and time‐consuming to measure because of the frequent involvement of destructive phenotyping methods. Recently, non‐destructive methods such as hyperspectral imaging (HSI) have gained attention in the food industry for studying wheat grain quality. HSI can quantify variations in individual grains, helping to differentiate high‐quality grains from those of low quality. In this review, we discuss the reduction of wheat genetic diversity underlying grain quality traits due to modern breeding, key traits for grain quality, traditional methods for studying grain quality and the application of HSI to study grain quality traits in wheat and its scope in breeding. Our critical review of literature on wheat domestication, grain quality traits and innovative technology introduces approaches that could help improve grain quality in wheat.
CN‐N: A gridded dataset of nitrogen rate for rice, wheat and maize in China developed using the county‐level nitrogen statistics
Authors: Zhang Wenmeng , Zhang Tianyi , Yang Xiaoguang 
Published: September 2023

AbstractExisting agricultural nitrogen datasets in China are mostly developed using coarse national or provincial statistics. A crop‐specific nitrogen rate dataset based on the finest‐scale agricultural nitrogen statistics at the county level remains lacking. Here, we constructed a new dataset (CN‐N), which provides annual nitrogen rates for rice, wheat and maize in China at a 1‐km spatial resolution from 2004 to 2016. This dataset was developed by harmonizing county‐level and provincial agricultural nitrogen statistics with gridded crop distribution maps, resulting in 13 years of nitrogen rate maps for each crop covering 2004–2016. Validation against farmers' surveys by crop indicates CN‐N reliably quantifies average nitrogen rates and trends for each crop over 2004–2016, demonstrating improved spatial heterogeneity compared to previous datasets rasterized using only provincial statistics. Our study provides a crop‐specific, temporally consistent, gridded nitrogen rate dataset based on the finest‐scale county‐level agricultural nitrogen statistics. This can support future process‐based modelling for sustainable agricultural nitrogen management strategies.