Study on wave energy resource assessing method based on altimeter data——A case study in Northwest Pacific

Wave energy resource is a very important ocean renewable energy. A reliable assessment of wave energy resources must be performed before they can be exploited. Compared with wave model, altimeter can provide more accurate in situ observations for ocean wave which can be as a novel method for wave energy assessment.The advantage of altimeter data is to provide accurate significant wave height observations for wave. In order to develop characteristic and advantage of altimeter data and apply altimeter data to wave energy assessment, in this study, we established an assessing method for wave energy in local sea area which is dedicated to altimeter data.This method includes three parts including data selection and processing, establishment of evaluation indexes system and criterion of regional division. Then a case study of Northwest Pacific was performed to discuss specific application for this method. The results show that assessing method in this paper can assess reserves and temporal and spatial distribution effectively and provide scientific references for the siting of wave power plants and the design of wave energy convertors.

Assessment of International GNSS Service Global Ionosphere Map products over China region based on measurements from the Crustal Movement Observation Network of China

The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.

Application of a Bayesian method to data-poor stock assessment by using Indian Ocean albacore (Thunnus alalunga) stock assessment as an example

It is widely recognized that assessments of the status of data-poor fish stocks are challenging and that Bayesian analysis is one of the methods which can be used to improve the reliability of stock assessments in data-poor situations through borrowing strength from prior information deduced from species with good-quality data or other known information. Because there is considerable uncertainty remaining in the stock assessment of albacore tuna（Thunnus alalunga） in the Indian Ocean due to the limited and low-quality data, we investigate the advantages of a Bayesian method in data-poor stock assessment by using Indian Ocean albacore stock assessment as an example. Eight Bayesian biomass dynamics models with different prior assumptions and catch data series were developed to assess the stock. The results show（1） the rationality of choice of catch data series and assumption of parameters could be enhanced by analyzing the posterior distribution of the parameters;（2） the reliability of the stock assessment could be improved by using demographic methods to construct a prior for the intrinsic rate of increase（r）. Because we can make use of more information to improve the rationality of parameter estimation and the reliability of the stock assessment compared with traditional statistical methods by incorporating any available knowledge into the informative priors and analyzing the posterior distribution based on Bayesian framework in data-poor situations, we suggest that the Bayesian method should be an alternative method to be applied in data-poor species stock assessment, such as Indian Ocean albacore.

ASSESSMENT AND OPTIMIZATION OF THE PHASE DIAGRAMS AND THERMODYNAMIC DATA OF SOME BINARY SYSTEMS CONTAINING PRASEODYMIUM CHLORIDES

In this paper a critical assessment and optimization of the phase diagrams and thermodynamic properties of the PrCl_3-MCl(M=Li,Na)and PrCl_3-MCl_2(M=Mg,Ca,Sr,Ba) binary systems have been per- formed.The assessed and optimized binary phase diagrams and thermodynamic data with self consistency are a better basis for constructing multicomponent phase diagrams.

Kinetic assessment of measured mass flow rates and streamwise pressure distributions in microchannel gas flows

Measured mass flow rates and streamwise pressure distributions of gas flowing through microchannels were reported by many researchers. Assessment of these data is crucial before they are used in the examination of slip models and numerical schemes, and in the design of microchannel elements in various MEMS devices. On the basis of kinetic solutions of the mass flow rates and pressure distributions in microchannel gas flows, the measured data available are properly normalized and then are compared with each other. The 69 normalized data of measured pressure distributions are in excellent agreement, and 67 of them are within 1 ± 0.05. The normalized data of mass flow-rates ranging between 0.95 and 1 agree well with each other as the inlet Knudsen number Kni 〈 0.02, but they scatter between 0.85 and 1.15 as Kni 〉 0.02 with. to some extent, a very interesting bifurcation trend.

The Development of the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS©)

The purpose of this study was to develop the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS)©. This study used the on-line survey method from February to April 2015. There were 644 respondents comprised of professional nurses with minimum qualification of 3 years’ experience being in a psychiatric unit of a stand-alone 200-bed or more Psychiatric Hospital in Japan. Assessment items were derived from 211 specific items selected from nursing textbooks, excluding the North-American-Nursing-Diagnosis-Association (NANDA). The questionnaire contained Cover Letter, Demographic Data Sheet, and the PsyNACS© questionnaire. There were 644 questionnaires accessed but only 435 were completed and valid. Item levels of importance were evaluated: 1) Unnecessary, 2) Not very important, 3) Important and 4) Very important. Data analysis used descriptive and multivariate statistics. Factor analysis (principal factor analysis, varimax rotation), the Kaiser-Meyer-Olkin (KMO) and the Bartlett’s test of Sphericity assessed the adaptive validity of the factor analysis. Factor loadings were set at 0.4 or more for the configuration of items. Internal consistency and reliability were established using Cronbach’s alpha coefficient. Mean factor points were calculated, including standard deviation, range, and confidence interval at 95%. Statistical significance was at 0.05 level. Nine Patient Assessment Data (PAD) with 2 to 5 Cluster Assessment Data (CAD) each were categorized. Thirty one CADs comprised the Patient Assessment Data: (PAD1) Psychological symptom and stress, (PAD2) Information about treatment, (PAD3) Function of eating and balance of water, (PAD4) Life and value, (PAD5) Vital signs and health assessment, (PAD6) Self-care, (PAD7) Social support, (PAD8) Activity, sleeping and mobility capability, and (PAD9) Sexual function and sexual behavior. The PsyNACS© is a classification of items assessing health care needs within the Japanese psychiatric nursing care environment, and also can be used in various psychiatric patient care situations in all psychiatric units.

Quality assessment of volunteered geographic information for outdoor activities:an analysis of OpenStreetMap data for names of peaks in Japan

Geographical studies of outdoor activities have increased in recent years with the rise in popularity of these activities worldwide,including in Japan.Volunteered geographic information(VGI)is a key tool for organizing outdoor activities as it offers a means to determine the locational information and names of places.To evaluate the quality of VGI,geospatial data generated by land survey agencies and other VGI are often utilized as reference data.However,since these reference data may not be available,other methods are necessary to assure the quality of VGI.In this study,we examined five trust indicators based on the inherent characteristics of VGI through an empirical case study.We used mountain names extracted from OpenStreetMap in Japan as data because there were almost no other VGI in the vicinity.As a result,we isolated three trust indicators,namely versions,users,and tag corrections,to examine the thematic accuracy of VGI because these were the only statistically significant indicators.However,we found that the prediction rate of thematic accuracy was very low.To improve thematic accuracy,this study recommends using the most accurate versions,applying correctly given tags,and considering the motivations and characteristics of the VGI contributors.

Implementation of a drainage information, analysis and management system

An integrated drainage information, analysis and management system （DIAMS） was developed and implemented for the New Jersey Department of Transportation （N/DOT）. The purpose of the DIAMS is to provide a useful tool for managers to evaluate drainage infrastructure, to facilitate the determination of the present costs of preserving those in- frastructures, and to make decisions regarding the optimal use of their infrastructure budgets. The impetus for DIAMS is the culvert information management system （CIMS）, which is developed to manage the data for culvert pipes. DIAMS maintains and summa- rizes accumulated inspection data for all types of drainage infrastructure assets, including pipes, inlet/outlet structures, outfalls and manufactured treatment devices. DIAMS capa- bilities include identifying drainage infrastructure, maintaining inspection history, map- ping locations, predicting service life based on the current condition states, and assessing present asset value. It also includes unit cost values of 72 standard items to estimate the current cost for new assets with the ability to adjust for future inflation. In addition, DIAMS contains several different repair, rehabilitation and replacement options to remedy the drainage infrastructure. DIAMS can analyze asset information and determine decisions to inspect, rehabilitate, replace or do nothing at the project and network levels by comparing costs with risks and failures. Costs may be optimized to meet annual maintenance budget allocations by pfioritizing drainage infrastructure needing inspection, cleaning and repair. DIAMS functional modules include vendor data uploading, asset identification, system administration and financial analysis. Among the significant performance feature of DIAMS is its proactive nature, which affords decision makers the means of conducting a comprehensive financial analysis to determine the optimal proactive schedule for the proper maintenance actions and to prioritize them accordingly. Benefits of DIAMS include long-term savings that accrue by adopting optimized preventive maintenance strategies and facilitating compliance with Governmental Accounting Standards Board （GASB） and federal storm water regulations.