Earticle

The purpose of this study is to evaluate the resource value of existing mud flats in JANGWHARI, KANGWHADO, as strategies for ecotourism. The research methods used in this study are Limits of Acceptable Change(LAC), and Recreation Opportunity Spectrum(ROS). The LAC process draws attention to the existing area conditions that are judged to be acceptable. Managers must define desired area conditions and undertake actions to maintain or achieve these conditions. The ROS is within each of the recreation opportunity classes identified as being used at the regional level. The Results of this study are as follows: 1) The Opportunity Class of the ROS is ecological, physical, social, managerial setting as primitive, semi-primitive. non-motorized, semi-primitive$.$motorized, and roaded natural. 2) The indicator of the LAC is ecological, physical, social, and managerial setting; the indicator of ecological is wildlife populations, water quality, road paving; the indicator of physical is facilities; the indicator of social is visitor needs for knowledge, adventure, eco-experience, and environmental education programs; and, the indicator of managerial is limits of law, and degree of management. 3) Currently, the Opportunity Class of the ROS of JANGWHARI, KANGWHADO is levels II-III, and the Opportunity Class of the suggested ROS is levels I-II. 4) This paper describes strategies for mud flat area management: detection of water quality, resolving problems of equipment, supply of both environmental education programs and guide equipment.

In this paper, the average probability of the symbol error rate (SER) and throughput are studied in the presence of joint spectrum sensing and data transmission in a cognitive relay network, which is in the environment of an optimal power allocation strategy. In this investigation, the main component in calculating the secondary throughput is the inclusion of the spatial false alarms, in addition to the conventional false alarms. It has been shown that there exists an optimal secondary power amplification factor at which the probability of SER has a minimum value, whereas the throughput has a maximum value. We performed a Monte-Carlo simulation to validate the analytical results.

In this letter, we demonstrate a technique for spectrum-shaping in backscatter modulation-based communication systems. With backscatter modulation, data bits are transmitted by switching the load impedance connected to the antenna. In traditional communication systems, filters are used to perform the task of shaping the pulse or the spectrum. Since most backscatter modulation radios operate on power harvested from a reader’s RF signal, filtering may not be suitable. In this letter, we show a simple spectrum shaping technique that is based on switching three loads, instead of the usual two, to transmit a bit. We demonstrate two well known shaping techniques using only load switching. The advantages of shaping the spectrum are (i) lower complexity and power consumption at the receiver and (ii) lower bit error probability for a given signal to noise ratio.

The different issues in the wireless channel, such as multipath fading, shadowing, and hidden terminal problems, limit the sensing abilities of the single user in a cognitive radio network (CRN). In this connection, it is more suitable to follow cooperative spectrum sensing (CSS). However, the various categories of malicious users (MUs) pose threats to the performance of CSS. These MUs are eager to report false sensing data to the fusion center (FC) to deceive its decision. This work considered the CSS performance in the presence of always yes MU (AYMU), opposite MU (OMU), and always no MU (ANMU). Moreover, the considered particle swarm optimization (PSO) algorithm takes out reports of the MUs using one to many sensing distances (OTMSD) and z-score outlier detection techniques before the final decision. Simulation results validate the effectiveness of the proposed scheme in the presence of MUs.

This letter proposes an efficient spectrum sharing by using a smart channel selection with considering the spatial shape of white space (WS) for cognitive radio systems. Here, we consider the environment in which secondary users (SUs) share the same spectrum with multiple channels. In such situation, the assignment channel avoiding spatial fragmentation is important because other SUs can easily access to remaining WS. In this paper, we utilize a perimeter to area ratio of WS for channel assignment as a criterion for evaluating value of remaining WS. We confirm the effectiveness of the proposed spectrum sharing method by using computer simulations.

Single-user spectrum sensing is susceptible to multipath effects, shadow effects, hidden terminals and other unfavorable factors, leading to misjudgment of perceived results. In order to increase the detection accuracy and reduce spectrum sensing cost, we propose an adaptive cooperative sensing strategy based on an estimated signal-to-noise ratio (SNR). Which can adaptive select different sensing strategy during the local sensing phase. When the estimated SNR is higher than the selection threshold, adaptive double threshold energy detector (ED) is implemented, otherwise cyclostationary feature detector is performed. Due to the fact that only a better sensing strategy is implemented in a period, the detection accuracy is improved under the condition of low SNR with low complexity. The local sensing node transmits the perceived results through the control channel to the fusion center (FC), and uses voting rule to make the hard decision. Thus the transmission bandwidth is effectively saved. Simulation results show that the proposed scheme can effectively improve the system detection probability, shorten the average sensing time, and has better robustness without largely increasing the costs of sensing system.

Flavonoids are major plant constituents with numerous biological/pharmacological actions both in vitro and in vivo. Of these actions, their anti-inflammatory action is prominent. They can regulate transcription of many proinflammatory genes such as cyclooxygenase-2/inducible nitric oxide synthase and many cytokines/chemokines. Recent studies have demonstrated that certain flavonoid derivatives can affect pathways of inflammasome activation and autophagy. Certain flavonoids can also accelerate the resolution phase of inflammation, leading to avoiding chronic inflammatory stimuli. All these pharmacological actions with newly emerging activities render flavonoids to be potential therapeutics for chronic inflammatory disorders including arthritic inflammation, meta-inflammation, and inflammaging. Recent findings of flavonoids are summarized and future perspectives are presented in this review.

In cognitive radio (CR), spectrum sensing is an essential function since secondary users (SUs) must determine whether the primary user (PU) is utilizing the channel or not, and furthermore, SUs opportunistically access the licensed channel when the PU is absent. In this paper, spectrum sensing is implemented by energy detection, and a software-defined radio testbed is built to evaluate sensing performance by energy detection in a real environment. In particular, the testbed was built based on the GNU's Not Unix (GNU) Radio software platform and Universal Software Radio Peripheral National Instruments 2900 devices. More specifically, a new block of energy detection is developed by using an out-of-tree module from GNU Radio. To successfully integrate CR into the cloud computing paradigm, we also implement cloud computing-based spectrum sensing by utilizing a cloud server with ThingSpeak, such that we can store, process, and share the sensing information more efficiently in a centralized way in the cloud server.

Spectrum sensing in cognitive radio networks allows secondary users to sense the unused spectrum without causing interference to primary users. Cognitive radio requires more accurate sensing results from unused portions of the spectrum. Accurate spectrum sensing techniques can reduce the probability of false alarms and misdetection. In this paper, a two-stage spectrum sensing scheme is proposed for cooperative spectrum sensing in cognitive radio networks. In the first stage, spectrum sensing is executed for each secondary user using energy detection based on double adaptive thresholds to determine the spectrum condition. If the energy value lies between two thresholds, a fuzzy logic scheme is applied to determine the channel conditions more accurately. In the second stage, a fusion center combines the results of each secondary user and uses a fuzzy logic scheme for combining all decisions. The simulation results show that the proposed scheme provides increased sensing accuracy by about 20% in some cases.

This work proposes a Spectrum Sensing (SS) scheme based on a Convolutional Autoencoder (CAE) for application in Cognitive Radio Networks. The channel occupancy is modeled as an anomaly detection problem. The CAE is trained only with noise-signal samples so that any random modulated signal observed in the wireless channel will be regarded as an outlier. The relationship between the detection threshold and the system performance is evaluated. Experiments demonstrate that the SS proposal can identify primary signal presence with better accuracy (high detection and low false alarm rate) than conventional Energy Detection.

Frequency bands above 1.5 GHz have traditionally been used for 3G and 4G mobile communication services and new frequency bands will be allocated for 5G services in the near future. In this paper, the spectrum value in rural environments is analyzed using an engineering-economic modeling. In order to evaluate the spectrum values, three metrics are selected: maximum cell radius, annual infrastructure cost per square kilometer, and spectrum value per MHz-POP. Frequency bands ranging from 1.5 GHz to 3 GHz and 3 GHz to 11 GHz, are evaluated.

Axial mesodermal dysplasia complex (AMDC) arises in variable combinations of craniocaudal anomalies such as musculoskeletal deformities, neuroschisis, or rhombencephalic developmental disorders. To the best of our knowledge, the co-existence of AMDC with associated musculoskeletal anomalies, medullary neuroschisis with mirror movements, and cranial nerve anomalies has not yet been reported. Here, we report the case of a 4-year-old boy whose clinical features were suggestive of Goldenhar syndrome and Poland syndrome with Sprengel deformity. Moreover, he showed mirror movements in his hands suspected of rhombencephalic malformation, and infranuclear-type facial nerve palsy of the left side of his face, the opposite side to the facial anomalies of Goldenhar syndrome. After conducting radiological studies, he was diagnosed with medullary neuroschisis without pontine malformations and Klippel-Feil syndrome with rib anomalies. Based on these findings, we propose that clinical AMDC can be accompanied by a wide variety of musculoskeletal defects and variable degrees of central nervous system malformations. Therefore, in addition to detailed physical and neurological examinations, imaging studies should be considered in AMDC.

본 연구에서는 세균의 항균제 내성기전을 연구하기 위해 일개의 대학병원에서 분리된 Enterobacter cloacae를 대상으로 extended spectrum β-lactamase (ESBL) 및 16S rRNA methyltransferase 유전자를 검출하고 항균제 감수성 양상을 조사하였다. 대상균주 중 총 8 균주가 CTX-M-15형 ESBL을 생성하는 것으로 확인되었으며 이 균주들 중 3 균주는 16S rRNA methyltransferase의 한 종류인 armA 유전자도 동시에 가지고 있는 것으로 나타났다. CTX-M-15형 ESBL 유전자와 armA 유전자를 동시에 가지고 있는 E. cloacae는 3세대 cephalosporin 계열 및 aminoglycoside 계열의 항균제 뿐 만 아니라 fluoroquinolone 계열의 항균제에도 내성을 보였다. 더구나 이러한 항균제 내성 유전자들은 플라스미드를 통해 다른 세균으로 전달 될 수 있어 다제내성 세균의 출현 및 확산을 촉진 할 수 있다. 따라서 E. cloacae를 대상으로 지속적인 항균제 내성 유전자를 모니터링 하는 것은 항균제 내성 확산방지를 위해 중요할 것으로 사료된다.

We investigated the prevalence of extended spectrum β-lactamase (ESBL) genes and 16S rRNA methyltransferase genes to study antimicrobial resistance mechanisms of Enterobacter cloacae strains isolated from a university hospital in the Chungcheong province of Korea. Eight of the bacteria strains involved in this study contained CTX-M-15 type ESBL. Among 8 strains harboring the ESBL gene, 3 strains also harbored armA gene. The three isolates showed resistance to antimicrobial agents belonged to third cephalosporin, aminoglycoside, and fluoroquinolones. Furthermore, interspecies plasmid transfer of the antimicrobial resistant genes may induced horizontal spreading of the genes and emergence of multidrug resistant bacteria. Therefore, surveillance for existence of antimicrobial resistance determinants is important to prevent distribution of antimicrobial resistant strains.

Cognitive radio has been attracting increased attention as an effective approach to improving spectrum efficiency. One component of cognitive radio, spectrum sensing, has an important relationship with the performance of cognitive radio. In this paper, after a summary and analysis of the existing spectrum-sensing algorithms, we report that the existing eigenvalue-based semi-blind detection algorithm and blind detection algorithm have not made full use of the eigenvalues of the received signals. Applying multi-antenna systems to cognitive users, we design a variety of spectrum-sensing algorithms based on the joint distribution of the eigenvalues of the received signal. Simulation results validate that the proposed algorithms in this paper are able to detect whether the signal of the primary user exists or not with high probability of detection in an environment with a low signal-to-noise ratio. Compared with traditional algorithms, the new algorithms have the advantages of high detection performance and strong robustness

In spectrum sensing, there is a tradeoff between the probability of missed detection and the probability of a false alarm according to the value of the sensing threshold. Therefore, it is important to determine the sensing threshold suitable to the environment of cognitive radio networks. In this study, we consider a cognitive radio-based ad hoc network where secondary users directly communicate by using the same frequency band as the primary system and control their transmit power on the basis of the distance between them. First, we investigate a condition in which the primary and the secondary users can share the same frequency band without harmful interference from each other, and then, propose an algorithm that controls the sensing threshold dynamically on the basis of the transmit power of the secondary user. The analysis and simulation results show that the proposed sensing threshold control algorithm has low probabilities of both missed detection and a false alarm and thus, enables optimized spectrum sharing between the primary and the secondary systems.

주파수 자원 가치는 무선통신의 발전과 함께 더욱 커지고 있다. 하지만 앞으로 정보화 사회에서는 주파수 자원의 수요가 공급에 비하여 매우 많기 때문에 주파수 부족 현상이 심각하게 대두된다. 따라서 사용되지 않고 있는 주파수 자원을 효율적으로 이용하기 위한 기술로서 최근 각광을 받고 있는 Cognitive Radio(CR) 기술이 필요한 시점이다. 본 논문은 임베디드 보드에서 CR 기반의 효율적인 Spectrum Sensing 기법을 적용하였다. 현재 이론적으로 제시되어 있는 여러 Spectrum Sensing 기법들에 대해 살펴보고 이 기법들을 CR 환경이 구현된 임베디드 플랫폼에 적용시켜 MAC 메시지를 통해 성능을 검증하였다.

The worth of frequency resources is growing up because of development of wireless communication. However, frequency resources is short, because demand is much more than supply. So it needs Cognitive Radio(CR), which manages frequency resources efficiently. In this paper, we apply the efficient Spectrum Sensing method based on CR in an embedded board. We examine various Spectrum Sensing methods and apply these methods to an embedded platform on CR environment and verify the performance through the MAC message.

Energy and spectral efficiency are attracting attention as “emerging technology” that exploits the opportunities of sensing, communications and artificial intelligence. This paper proposes the features of these state of art techniques a new energy and spectrum efficient technique for 5G and beyond networks. By using Interference aware (IA) beam selection in beam-space MIMO, the large number of users are supported with a smaller number of radio-frequency (RF) chains at the same time and frequency resource. It has been observed from the proposed scheme that the achievable sum-rate of mm-wave channel model is also improved. From the simulation results it is found that Interference aware (IA) beam selection is used in beam-space to minimize the total obligatory RF-chains in mm-wave massive MIMO communication systems without noticeable loss in performance.

For large facilities having several floors or containers, floor response spectra, FRS, other than ground response spectra need to be developed. However, FRS can have error especially when components are not small in their masses. In this paper, error is estimated in order to specify applicability of the FRS by deriving and comparing with analytic results for two degrees of freedom system. An identity regarding modal vectors and participation factors in the modal method is used to measure the FRS error. It is found that FRS is sufficiently accurate if the mass of a component is one hundredth or less than that of the floor. On the contrary, it is shown that fixed frequency of a component does not affect the FRS accuracy considerably. A compact power plant system consists of two main assemblies with spring mounts is applied as an example for the derivation of the FRS and several aspects associated with its modeling and calculation are discussed.