Higgs phenomenology in the Peccei-Quinn invariant NMSSM

We study the Higgs phenomenology in the Peccei-Quinn invariant NMSSM (PQ-NMSSM) where the low energy mass parameters of the singlet superfield are induced by a spontaneous breakdown of the Peccei-Quinn symmetry. In the generic NMSSM, scalar mixing among CP-even Higgs bosons is constrained by the observed properties of the SM-like Higgs boson, as well as by the LEP bound on the chargino mass and the perturbativity bound on the singlet Yukawa coupling. In the minimal PQ-NMSSM, scalar mixing is further constrained due to the presence of a light singlino-like neutralino. It is noticed that the $2\sigma$ excess of the LEP $Zb\bar b$ events at $m_{b\bar b}\simeq$ 98 GeV can be explained by a singlet-like 98 GeV Higgs boson in the minimal PQ-NMSSM with low $\tan\beta$, stops around or below 1 TeV, and light doublet-higgsinos around the weak scale.Comment: 31 pages, 4 figures; v2: references added, light stop effects discussed, bound on the Higgs invisible decay rate correcte

Proto-type installation of a double-station system for the optical-video-detection and orbital characterisation of a meteor/fireball in South Korea

We give a detailed description of the installation and operation of a double-station meteor detection system which formed part of a research & education project between Korea Astronomy Space Science Institute and Daejeon Science Highschool. A total of six light-sensitive CCD cameras were installed with three cameras at SOAO and three cameras at BOAO observatory. A double-station observation of a meteor event enables the determination of the three-dimensional orbit in space. This project was initiated in response to the Jinju fireball event in March 2014. The cameras were installed in October/November 2014. The two stations are identical in hardware as well as software. Each station employes sensitive Watec-902H2 cameras in combination with relatively fast f/1.2 lenses. Various fields of views were used for measuring differences in detection rates of meteor events. We employed the SonotaCo UFO software suite for meteor detection and their subsequent analysis. The system setup as well as installation/operation experience is described and first results are presented. We also give a brief overview of historic as well as recent meteor (fall) detections in South Korea. For more information please consult http://meteor.kasi.re.kr .Comment: Technical/instrumentation description of a professional meteor detection system, 23 pages, 20 figures (color/monochrome), 5 tables, submitted to the Journal of Korean Astronomical Society (JKAS, http://jkas.kas.org/, http://jkas.kas.org/history.html

Learning Speed Enhancement of Iterative Learning Control with Advanced Output Data based on Parameter Estimation

Learning speed enhancement is one of the most important issues in learning control. If we can improve both learning speed and tracking performance, it will be helpful to the applicability of learning control. Considering these facts, in this paper, we propose a learning speed enhancement scheme for iterative learning control with advanced output data (ADILC) based on parameter estimation. We consider linear discrete-time non-minimum phase (NMP) systems, whose model is unknown, except for the relative degree and the number of NMP zeros. In each iteration, estimates of the impulse response are obtained from input-output relationship. Then, learning gain matrix is calculated from the estimates, and by using new learning gain matrix, learning speed can be enhanced. Simulation results show that the learning speed has been enhanced by applying the proposed method

Wearable System for Daily Activity Recognition Using Inertial and Pressure Sensors of a Smart Band and Smart Shoes

Human Activity Recognition (HAR) is a challenging task in the field of human-related signal processing. Owing to the development of wearable sensing technology, an emerging research approach in HAR is to identify user-performed tasks by using data collected from wearable sensors. In this paper, we propose a novel system for monitoring and recognizing daily living activities using an off-the-shelf smart band and two smart shoes. The system aims at providing a useful tool for solving problems regarding body part placement, fusion of multimodal sensors and feature selection for a specific set of activities. The system collects inertial and plantar pressure data at wrist and foot to analyze and then, extract, select important features for recognition. We construct and compare two predictive models of classifying activities from the reduced feature set. A comparison of the classification for each wearable device and a fusion scheme is provided to identify the best body part for activity recognition: either the wrist or the feet. This comparison also demonstrated the effective HAR performance of the proposed system

A Defected Ground Structure without Ground Contact Problem and Application to Branch Line Couplers

A new defected ground structure (DGS) microstrip line that is free from the ground contact problem is described together with its application example. The proposed DGS microstrip line adopts a double-layered substrate. The first layer contains the microstrip line and DGS patterns on the top and bottom planes as with the conventional DGS line. The second substrate, of which upper metal plane has already been removed, is attached to the bottom ground plane of the first layer. This structure prevents the ground plane of the first substrate with DGS patterns from making contact with the metal housing. The proposed DGS microstrip line has advantageous transmission and rejection characteristics, without the ground contact problem of DGS patterns, which has been a critical problem of previous DGS lines. A 10 dB branch line hybrid coupler is designed and measured, as an example of application of the proposed DGS microstrip line

A study on Biosorptive Removal of Cd from Wastewater using Chironomid Larvae (Diptera: Chironomidae)

Cadmium (Cd) has caused serious public health problem due to its toxic nature. It is necessary to find a cost-effective method to dispose of wastewater containing Cd. Chironomid larvae as an alternative to conventional adsorbents were applied to remove Cd from wastewater. The sorption studies of Cd were carried out using laboratory-reared Glyptotendipes tokunagai (Diptera: Chironomidae) larvae. Kinetic and sorption capacity of chironomid larvae for Cd were determined by means of controlled experiments in a batch system. It was observed that removal efficiency of Cd was largely concentration dependent and more effective in lower concentration. At equilibrium, Cd was removed up to roughly 53 %. The sorption kinetics were found to conform to the pseudo-first-order kinetic model with a good correlation. Equilibrium sorption data were best fitted to the both Freundlich and Langmuir isotherm models owing to their correlation coefficient R2 values greater than 0.99. Considering the values obtained from isotherm constants 1/n and r, it is confirmed that Cd is sorbed favorably by chironomid larvae. With its relatively high removal capability for Cd, Chironomid larvae have enormous potential for application in wastewater treatment technologies.Â

Trustworthiness-Driven Graph Convolutional Networks for Signed Network Embedding

The problem of representing nodes in a signed network as low-dimensional vectors, known as signed network embedding (SNE), has garnered considerable attention in recent years. While several SNE methods based on graph convolutional networks (GCN) have been proposed for this problem, we point out that they significantly rely on the assumption that the decades-old balance theory always holds in the real-world. To address this limitation, we propose a novel GCN-based SNE approach, named as TrustSGCN, which corrects for incorrect embedding propagation in GCN by utilizing the trustworthiness on edge signs for high-order relationships inferred by the balance theory. The proposed approach consists of three modules: (M1) generation of each node's extended ego-network; (M2) measurement of trustworthiness on edge signs; and (M3) trustworthiness-aware propagation of embeddings. Furthermore, TrustSGCN learns the node embeddings by leveraging two well-known societal theories, i.e., balance and status. The experiments on four real-world signed network datasets demonstrate that TrustSGCN consistently outperforms five state-of-the-art GCN-based SNE methods. The code is available at https://github.com/kmj0792/TrustSGCN.Comment: 12 pages, 8 figures, 9 table