出版者・発行元：Future Internet  

While driving, stress and frustration can affect safe driving and pose the risk of causing traffic accidents. Therefore, it is important to control the driver’s anxiety level in order to improve the driving experience. In this paper, we propose and implement an intelligent system based on fuzzy logic (FL) for deciding the driver’s anxiety level (DAL). In order to investigate the effects of the considered parameters and compare the evaluation results, we implement two models: DAL Model 1 (DALM1) and DAL Model 2 (DALM2). The input parameters of DALM1 include driving experience (DE), in-car environment conditions (IECs), and driver age (DA), while for DALM2, we add a new parameter called the accident anxiety state (AAS). For both models, the output parameter is DAL. We carried out many simulations and compared the results of DALM1 and DALM2. The evaluation results show that the DAL is very good for drivers’ ages between 30 to 50 years old. However, when the driver’s age is below 30 or above 50, DAL tends to decline. With an increase in DE and IECs, the DAL value is decreased. But when the AAS is increased, the DAL is increased. DALM2 is more complex because the rule base is larger than DALM1, but it makes a better decision of DAL value.

DOI： 10.3390/fi16100348

Scopus

出版者・発行元：Frontiers in Plant Science  

The mitochondrial pyruvate dehydrogenase complex (PDC) plays a crucial role in linking the glycolysis pathway and the tricarboxylic acid (TCA) cycle. Previously, we reported that a mutation of MAB1, encoding an E1β subunit of PDC, affects the abundance of auxin efflux carriers PIN-FORMED proteins (PINs) via reduced recycling and enhanced degradation in vacuoles. Here, we further analyzed the effects of TCA cycle inhibition on vesicle trafficking using both the mab1-1 mutant and 3-BP, a TCA cycle inhibitor. Pharmacological and genetic impairment of the TCA cycle induced the aggregated components of ARA6, which is a plant-unique RAB5 GTPase that mediates endosomal trafficking to the plasma membrane. In addition, MAB4, which is an NPH3-like protein that inhibits PIN internalization from the plasma membrane, was severely reduced in 3-BP-treated roots and mab1-1. Furthermore, TCA cycle impairment led to the accumulation of reactive oxygen species in root tips, and treatment with H2O2 reduced MAB4 levels while increasing the internalization of PIN2 from the plasma membrane, and aggregated ARA6-positive compartments. These results suggest that TCA cycle impairment targets PIN proteins for degradation in the vacuole by disrupting both the MAB4-mediated block of internalization and the ARA6-mediated endocytic pathway.

DOI： 10.3389/fpls.2024.1462235

Scopus

For safe driving and decrasing the risk of traffic accidents, it is important to control the driver mental status. In this paper, we implement an intelligent system based on Fuzzy Logic (FL) for deciding Driver Mental Status (DMS). We call this system FL-based DMS System (FLDMSS). The input parameters for FLDMSS are Driver Anxiety Level (DAL), Traffic Situation (TS) and Driving Operating Time (DOT). The output parameter is DMS. We evaluated the implemented system by computer simulations. The simulation results show that DMS is very good when the driving operating time is short. With increasing of DAL and DOT values, the DMS value is decreased. But when TS is good, the DMS value is increased.

DOI： 10.1007/978-3-031-76452-3_34

Scopus

Wireless Mesh Networks (WMNs) are effective networks because they have high-robustness and rapid deployment capabilities. However, they have have some issues such as congestion, interference, diminished data transfer speeds, packet losses, and increased latency. The location of mesh routers is one of the most critical decisions to deal with these problems. However, determining the optimal location of mesh routers in WMNs is difficult task and it is known to be an NP-hard problem. In order to solve this problem, we propose and implement an intelligent simulation system based on Cuckoo Search (CS) algorithm, which is a meta-heuristic approach. In this work, we evaluate the performance of WMN-CS system considering Normal, Stadium, Subway and Uniform distributions of mesh clients. The simulation results show that the distribution of mesh clients affects the performance of WMN-CS. The Normal distribution achieves a faster convergence compared to the other distributions. Comparing Stadium and Subway distributions, the Stadium distribution converges faster than the Subway distribution. The Uniform distribution shows the slowest convergence speed and has the lowest NCMC values.

DOI： 10.1007/978-3-031-72322-3_3

Scopus

In Peer-to-Peer (P2P) networks, the peers should collaborate with trustworthy neighboring peers. However, it should be noted that in real applications, the peer may be faulty, which may make a wrong decision. For safe communication, the peers should be reliable. The reliability can be evaluated by the interaction of a peer with other peers but this procedure needs many parameters. In this paper, in order to make a qualitative evaluation, we implement a Fuzzy-based system and for quantitative evaluation we build another simulation system by taking into account the correlation coefficients and ns-3 simulator. Three parameters Packet Loss (PL), Delay Time (DT) and Throughput (TG) are considered for the evaluation of both systems. For Fuzzy-based system, the output is Peer Selection Decision (PSD). From the simulations results of FL-based system, we conclude that when PL and DL are increasing, the PSD is decreased. While, when TG is increased, the PSD is increased. By ns-3 simulator results, we found that by using the value of correlation coefficients is possible to select the best reliable peers.

DOI： 10.1007/978-3-031-64766-6_26

Scopus

その他リンク： https://dblp.uni-trier.de/db/conf/imis/imis2024.html#LiuSB24

Wireless Mesh Networks (WMNs) are effective networks because they have high-robustness and rapid deployment capabilities. However, they have some issues such as congestion, interference, diminished data transfer speeds, packet losses, and increased latency. The location of mesh routers is one of the most critical decisions to deal with these problems. However, determining the optimal location of mesh routers in WMNs is difficult task and it is known to be an NP-hard problem. In order to solve this problem, we propose and implement an intelligent simulation system based on Cuckoo Search (CS) algorithm, which is a meta-heuristic approach. In this work, we assess the performance of WMN-CS considering Uniform, Weibull and Chi-square distributions of mesh clients. For evaluation, we carried out computer simulations. The simulation results show that the distribution of mesh clients affects the performance of WMN-CS. In case of Uniform distribution of mesh clients, the convergence speed is faster than the Weibull and Chi-square distributions, but the converged value of NCMC is the lowest among these three distributions. In the case of Weibull distribution, the convergence speed is slower than the Uniform and Chi-square distributions, but the converged value of NCMC is the highest among three of them. The performance of WMN-CS for Chi-square distribution is between Uniform and Weibull distributions.

DOI： 10.1007/978-3-031-70011-8_12

Scopus

Wireless Mesh Networks (WMNs) are cost-effective and highly robust networks. However, WMNs have various challenges associated with wireless communication. To deal with these issues, it is needed to find appropriate locations of mesh routers. However, the problem is known as NP-hard problem. In order to solve this problem, we consider Cuckoo Search (CS) algorithm and implement an intelligent simulation system called WMN-CS. In this work, we evaluate the performance of WMN-CS considering different distributions of mesh clients. Simulation results show that for Normal distribution of mesh clients, the WMN-CS can find suitable mesh router locations for 30 phases. However, 200 phases are insufficient for WMN-CS convergence in case of Exponential and Weibull distributions.

DOI： 10.1007/978-3-031-57840-3_16

Scopus

その他リンク： https://dblp.uni-trier.de/db/conf/aina/aina2024-1.html#SakamotoBL024