Point Analysis Method Research Articles

Equilibrium Point Analysis and Power Sharing Methods for Distribution Systems Driven by Solid-State Transformers

The feasible equilibria of operation of distribution-level power system models interfaced with solid-state transformers (SST) are analyzed and presented through a set of analytical relationships. The active and reactive power balances in the SST are realized through control of power electronic converters with appropriate choices for voltage and current setpoints. These setpoints parameterize the nonlinear model of the SST. Therefore, choosing them appropriately in sync with the generation and load profiles in the system is critical for maintaining a feasible equilibrium. These equilibrium sets are derived by first considering a fundamental physics-based model of a single-SST system, and thereafter, by extending them to systems with multiple SSTs connected to a radial distribution feeder. Power sharing methods are developed by which multiple SSTs can share a given change in load by generating an appropriate set of feasible setpoints for their input stage rectifiers. A control architecture is proposed for executing these load-sharing methods for both instantaneous and predictive load commands. The algorithms are verified by simulations on a representative distribution test system with nine SSTs.

Sektor Unggulan dan Interaksi Antarwilayah pada Kawasan Strategis Nasional Perkotaan MEBIDANGRO

This research aims to analyze the priority sectors in MEBIDANGRO districts and their regional hierarchy and interactions. It used a quantitative descriptive method based on secondary data. The priority sectors were analyzed using Location Quotient (LQ), Shift-Share (S-S), and Klassen Typology. For analyzing the regional hierarchy, the research employed scalogram analysis and Marshall centrality index. The regional interactions were determined by gravitation and breaking point analysis methods. The results show that the regions in MEBIDANGRO have two distinctive priority sectors, namely primary sector specialization and sector diversification. The research also found that Percut Sei Tuan District performs at the highest hierarchy with the strongest influence on regional interactions.

Studies on convergence and scaling law of Thomson backscattering spectra in strong fields**Project supported by the National Natural Science Foundation of China (Grant Nos. 11475026 and 11175023).

With the saddle point analysis method for the Bessel function structure and property, the convergence problem and the scaling laws of Thomson backscattering spectra are solved and studied in both cases that are for the plane wave laser field without and with applied external constant magnetic field. Some unclear points appeared in previous work are clarified. The extension of the method to a general situation for the laser field with an arbitrary polarization is discussed. We also make a simple analysis and discussion about the optimal spectra dependence of field parameters and its implication to practical applications.

Functional size approximation based on use-case names

Context: Functional size measures, such as IFPUG Function Points or COSMIC, are widely used to support software development effort estimation. Unfortunately, applying the COSMIC or IFPUG Function Point Analysis methods at early stages of software development is difficult or even impossible because available functional requirements are imprecise. Moreover, the resources that could be allocated to perform such measurement are usually limited. Therefore, it is worth investigating the possibility of automating the approximation of IFPUG Function Points or COSMIC early in software projects.Objective: Given a UML use-case diagram or a list of use-case names, approximate COSMIC and IFPUG FPA functional size in an automatic way.Method: We propose a two-step process of approximating the functional size of applications based on use-case goals. In the first step, we process the names of use cases, expressed in a natural language and assign each of their goals into one of thirteen categories. In the second step, we employ information about categories of use-case goals and historical data to construct prediction models and use them to approximate the size in COSMIC and Function Points. We compare the accuracy of the proposed methods to the average use-case approximation (AUC), which is their most intuitive counterpart, and the automatic method proposed by Hussain, Kosseim and Ormandjieva (HKO).Results: The prediction accuracy of the two proposed approximation methods was evaluated using a cross-validation procedure on a data set of 26 software development projects. For both methods, the prediction error was low compared to AUC and HKO.Conclusion: Developers who document functional requirements in a form of use cases might use the proposed methods to obtain an early approximation of the application size as soon as use-case goals are identified. The proposed methods are automatic and can be considered as a replacement for AUC.

Outbreak definition by change point analysis: a tool for public health decision?

BackgroundMost studies of epidemic detection focus on their start and rarely on the whole signal or the end of the epidemic. In some cases, it may be necessary to retrospectively identify outbreak signals from surveillance data. Our study aims at evaluating the ability of change point analysis (CPA) methods to locate the whole disease outbreak signal. We will compare our approach with the results coming from experts’ signal inspections, considered as the gold standard method.MethodsWe simulated 840 time series, each of which includes an epidemic-free baseline (7 options) and a type of epidemic (4 options). We tested the ability of 4 CPA methods (Max-likelihood, Kruskall-Wallis, Kernel, Bayesian) methods and expert inspection to identify the simulated outbreaks. We evaluated the performances using metrics including delay, accuracy, bias, sensitivity, specificity and Bayesian probability of correct classification (PCC).ResultsA minimum of 15 h was required for experts for analyzing the 840 curves and a maximum of 25 min for a CPA algorithm. The Kernel algorithm was the most effective overall in terms of accuracy, bias and global decision (PCC = 0.904), compared to PCC of 0.848 for human expert review.ConclusionsFor the aim of retrospectively identifying the start and end of a disease outbreak, in the absence of human resources available to do this work, we recommend using the Kernel change point model. And in case of experts’ availability, we also suggest to supplement the Human expertise with a CPA, especially when the signal noise difference is below 0.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-016-0271-x) contains supplementary material, which is available to authorized users.

Improvements to the Function Point Analysis Method: A Systematic Literature Review

Function point analysis (FPA) is a standardized method to systematically measure the functional size of software. This method is proposed by an international organization and it is currently recommended by governments and organizations as a standard method to be adopted for this type of measurement. This paper presents a compilation of improvements, focused on increasing the accuracy of the FPA method, which have been proposed over the past 13 years. The methodology used was a systematic literature review (SLR), which was conducted with four research questions aligned with the objectives of this study. As a result of the SLR, of the 1600 results returned by the search engines, 454 primary studies were preselected according to the criteria established for the SLR. Among these studies, only 18 specifically referred to accuracy improvements for FPA, which was the goal of this study. The low number of studies that propose FPA improvements might demonstrate the maturity of the method in the current scenario of software metrics. Specifically in terms of found issues, it was found that the step for calculating the functional size exhibited the highest number of problems, indicating the need to revise FPA in order to encompass the possible improvements suggested by the researchers.

A novel Ag+ cation sensor based on polyamidoamine dendrimer modified with 1,8-naphthalimide derivatives

In this study, 4-amino-1,8-naphthalimide-conjugated polyamidoamine dendrimer was synthesized and characterized and its potentiality as a cation sensor was investigated. 4-Amino-1,8-naphthalic anhydride reacted with polyamidoamine dendrimer and the product was characterized using FTIR, 1H NMR, 13C NMR and melting point analysis method. The synthesized compound was applied to detect various cations in water media and N,N-dimethylformamide (DMF) via monitoring the quenching of the fluorescence intensity. Furthermore, various metal cations including Cu2+, Ni2+, Zn2+, Pb2+,Ca2+, Ba2+, Cd2+, Hg2+, Fe2+, Fe3+ and Ag+ were tested. The complexes formed between the synthesized compound and metal cations in solution and their effects on Photoinduced Electron Transfer (PET) process were investigated regarding the potential application of the newly-synthesized dendrimer as a colorimetric and fluorescent sensor for such cations. The results clearly confirmed that the 1,8-naphthalimide groups surrounding the central dendrimer core showed strong green fluorescence emission at 553nm. This effect considerably decreased with the introduction of all cations, except Ag+ where the fluorescence quenching effect was remarkable and more dominant. Therefore, it can be concluded that the synthesized dye has the potentiality of being a highly sensitive and selective fluorescence sensor for Ag+ cation.

On-road measurements of NMVOCs and NO x : Determination of light-duty vehicles emission factors from tunnel studies in Brussels city center

Emission factors (EFs) of pollutants emitted by light-duty vehicles (LDV) were investigated in the Leopold II tunnel in Brussels city center (Belgium), in September 2011 and in January 2013, respectively. Two sampling sites were housing the instruments for the measurements of a large range of air pollutants, including non-methane volatile organic compounds (NMVOCs), nitrogen oxides (NOx) and carbon dioxide (CO2). The NMVOCs and NOx traffic EFs for LDV were determined from their correlation with CO2 using a single point analysis method. The emission factor of NOx is (544 ± 199) mg vehicle−1 km−1; NMVOCs emission factors vary from (0.26 ± 0.09) mg vehicle−1 km−1 for cis-but-2-ene to (8.11 ± 2.71) mg vehicle−1 km−1 for toluene. Good agreement is observed between the EFs determined in the Leopold II tunnel and the most recent EFs determined in another European roadway tunnel in 2004, with only a slight decrease of the EFs during the last decade. An historical perspective is provided and the observed trend in the NMVOCs emission factors reflect changes in the car fleet composition, the fuels and/or the engine technology that have occurred within the last three decades in Europe.

Tropospheric temperature climatology and trends observed over the Middle East

In this study, we report for the first time, the upper air temperature climatology, and trends over the Middle East, which seem to be significantly affected by the changes associated with hot summer and low precipitation. Long term (1985–2012) radiosonde data from 12 stations are used to derive the mean temperature climatology and vertical trends. The study was performed by analyzing the data at different latitudes. The vertical profiles of air temperature show distinct behavior in terms of vertical and seasonal variability at different latitudes. The seasonal cycle of temperature at the 100hPa, however, shows an opposite pattern compared to the 200hPa levels. The temperature at 100hPa shows a maximum during winter and minimum in summer. Spectral analysis shows that the annual cycle is dominant in comparison with the semiannual cycle. The time-series of temperature data was analyzed using the Bayesian change point analysis and cumulative sum method to investigate the changes in temperature trends. Temperature shows a clear change point during the year 1999 at all stations. Further, Modified Mann–Kendall test was applied to study the vertical trend, and analysis shows statistically significant lower tropospheric warming and cooling in upper troposphere after the year 1999. In general, the magnitude of the trend decreases with altitude in the troposphere. In all the latitude bands in lower troposphere, significant warming is observed, whereas at higher altitudes cooling is noticed based on 28 years temperature observations over the Middle East.

Temperature monitoring along the Rhine River based on airborne thermal infrared remote sensing: estimation ofin situwater temperatures and inflow detection compared to artificial satellite data

Water temperature is an important parameter of water quality. It influences the survival and growth of animal and plant species in river ecosystems. Current in situ measurements do not allow for the spatial coverage that is necessary for continuous monitoring. Hence, the ability of remote sensing temperatures from aerial and artificial satellite datasets to accurately identify and investigate water temperature and inflows is evaluated for a case study of the Upper and Middle Rhine River. Water surface temperatures acquired by an aerial survey and the results of two correction methods were evaluated: the difference to in situ measurements could be reduced to 0.04±0.21°C with a calibration based on in situ measurements and to 0.14±0.33°C based on atmospheric parameters modeled with MODTRAN®5.3.2. Inflows and mixing processes of water bodies with differing temperatures could be identified successfully with the change point analysis method and based on the standard deviation of the distributed longitudinal profile even for smaller dischargers. With the artificial satellite datasets, the ability to detect inflows decreases mainly with the noise of the dataset, also leading to a higher number of false positive change points.

Mixed ligand complexes of acesulfame/nicotinamide with earth alkaline metal cations Mg(II), Ca(II), Ba(II) and Sr(II): synthesis and characterization

In the scope this study, acesulfame (ace, acs)-nicotinamide (na) mixed ligand complexes of Mg(II), Ca(II), Sr(II) and Ba(II) were synthesized for the first time. Possible formulas for complexes were determined as [Mg(H2O)4(na)2](acs)2, [Ca(H2O)6(na)2](acs)2, [Sr(H2O)7(na)2](acs)2, [Ba(H2O)7(na)2](acs)2). It was observed that acesulfame ligands within structure were located two moles each at outer surface of coordination sphere acting as counter-ion allowing the charge balance of structure. The solubility of compounds gaining ionic character in this way was determined as quite well as compared to complex structures. Characterizations of complexes synthesized in this study were performed via melting point analysis, elemental analysis, mass spectroscopy and FT-IR spectroscopy methods. Thermal properties of complexes obtained were determined with tandem TG-DTG and DTA techniques. It was found that coordination spheres of metal cations within compounds obtained in this study were filled with nicotinamide and aqua ligands. Keywords: Acesulfame; Nikotinamide; Earth Alkaline Metals; Coordination Compound; Thermal Properties DOI: 10.17350/HJSE19030000008 Full Text:

Life cycle impacts and benefits of a carbon nanotube-enabled chemical gas sensor.

As for any emerging technology, it is critical to assess potential life cycle impacts prior to widespread adoption to prevent future unintended consequences. The subject of this life cycle study is a carbon nanotube-enabled chemical gas sensor, which is a highly complex, low nanomaterial-concentration application with the potential to impart significant human health benefits upon implementation. Thus, the net lifecycle trade-offs are quantified using an impact-benefit ratio (IBR) approach proposed herein, where an IBR < 1 indicates that the downstream benefits outweigh the upstream impacts. The cradle-to-gate assessment results indicate that the midpoint impacts associated with producing CNTs are marginal compared with those associated with the other manufacturing stages. The cumulative upstream impacts are further aggregated to units of disability-adjusted life years (DALYs) using ReCiPe end point analysis method and quantitatively compared with the potential downstream DALY benefits, as lives saved, during the use phase. The approach presented in this study provides a guiding framework and quantitative method intended to encourage the development of nanoenabled products that have the potential to realize a net environmental, health, or societal benefit.

Influence of the Selected Parameters on the Effectiveness of IGCC System Integrated With CCS Installation

Abstract The paper presents the basic input data and modelling results of IGCC system with membrane CO2 capture installation and without capture. The models were built using commercial software (Aspen and GateCycle) and with the use of authors’ own computational codes. The main parameters of the systems were calculated, such as gross and net power, auxiliary power of individual installations and efficiencies. The models were used for the economic and ecological analysis of the systems. The Break Even Point method of analysis was used. The calculations took into account the EU emissions trading scheme. Sensitivity analysis on the influence of selected quantities on break-even price of electricity was performed

An experimental study on the conversion between IFPUG and UCP functional size measurement units

The use of functional size measurement (FSM) methods in software development organizations is growing during the years. Also, object oriented (OO) techniques have become quite a standard to design the software and, in particular, Use Cases is one of the most used techniques to specify functional requirements. Main FSM methods do not include specific rules to measure the software functionality from its Use Cases analysis. To deal with this issue some other methods like Kramer’s functional measurement method have been developed. Therefore, one of the main issues for those organizations willing to use OO functional measurement method in order to facilitate the use cases count procedure is how to convert their portfolio functional size from the previously adopted FSM method towards the new method. The objective of this research is to find a statistical relationship for converting the software functional size units measured by the International Function Point Users Group (IFPUG) function point analysis (FPA) method into Kramer-Smith’s use cases points (UCP) method and vice versa. Methodologies for a correct data gathering are proposed and results obtained are analyzed to draw the linear and non-linear equations for this correlation. Finally, a conversion factor and corresponding conversion intervals are given to establish the statistical relationship.

Multistability and Instability of Competitive Neural Networks with Mexican-Hat-Type Activation Functions

We investigate the existence and dynamical behaviors of multiple equilibria for competitive neural networks with a class of general Mexican-hat-type activation functions. The Mexican-hat-type activation functions are not monotonously increasing, and the structure of neural networks with Mexican-hat-type activation functions is totally different from those with sigmoidal activation functions or nondecreasing saturated activation functions, which have been employed extensively in previous multistability papers. By tracking the dynamics of each state component and applying fixed point theorem and analysis method, some sufficient conditions are presented to study the multistability and instability, including the total number of equilibria, their locations, and local stability and instability. The obtained results extend and improve the very recent works. Two illustrative examples with their simulations are given to verify the theoretical analysis.

GNM ordered variational inequality system with ordered Lipschitz continuous mappings in an ordered Banach space

The main purpose of this paper is to introduce and study a new class of generalized nonlinear mixed ordered variational inequalities systems with ordered Lipschitz continuous mappings in ordered Banach spaces. Then, applying the matrix analysis and the vector-valued mapping fixed point analysis method, an existence theorem of solutions for this kind of the system is established. Furthermore, based on the existence theorem and the new ordered B-restricted-accretive mappings, a general algorithm for solving the systems is introduced and applied to the approximation solvability of the systems on hand. The obtained results seem to be general in nature.

変化点分析法を用いた圃場環境情報の特徴量抽出とその妥当性の検証

変化点分析法を用いた圃場環境情報の特徴量抽出とその妥当性の検証

Uncertainty estimation in robot kinematic calibration

Currently, the results of a robot calibration procedure are expressed generally in terms of the position and orientation error for a set of locations and orientations, which have been obtained from the previously identified kinematic parameters. In this work, a technique is presented to evaluate the calibration uncertainty for a robot arm calibrated using the circle point analysis method. The method developed is based on the probability distribution propagation calculation recommended by the Guide to the Expression of Uncertainty of Measurement and on the Monte Carlo method . This method makes it possible to calculate the uncertainty in the identification of each single robot parameter, and thus, to estimate the robot positioning uncertainty due to the calibration uncertainty, rather than based on a single set locations and orientations that are previously defined for a unique set of identified parameters. Additionally, this technique allows for the establishment of the best possible conditions for the data capture test, which identifies parameters and determines which of them have the least possible calibration uncertainty. This determination is based on the variables involved in the data capture process by propagating their influence up to the final robot accuracy. ► This method allows uncertainty evaluation in robot kinematic calibration procedures. ► Robot position and orientation can be evaluated offline depending on calibration. ► Data capture test for calibration can be optimised to minimise pose uncertainty. ► Individual influence of each parameter in the calibration phase can be characterised.

Unsupervised data mining technology based on research of stroke medication rules and discovery of prescription

For collecting and sorting literature on treatment of ancient and modern stroke at the entry point, frequency and charts analysis methods were applied. Modern computer technology and statistics were used to do in-depth study of stroke literature data, explore stroke differentiation of symptoms and signs and regular treatment by ancient physicians. On this basis, the unsupervised data mining technology was applied to obtain each syndrome commonly used for drug pair and combination of core. In assembling empirically drug pair and combination of core, 3 new prescriptions were obtained for each syndrome. Key words: Unsupervised data mining, stroke, medication rules, new prescription.

Ray-Tracing Method를 이용한 일영면적 산정방식 고찰

Nowadays, the solar expose right is very important with people`s life. Therefore, in calculating the sunshine hours, the point analysis and area analysis methods are used in previous studies. Previous two methods have merits and faults. Therefore, ray-tracing method is used as a alternative. Ray-tracing method is adopted by the software of Autodesk Ecotect which is a widely used program by the architectural company and academic university. In this study first, ray-tracing methodology is studied with how to calculate the overshadowing area and, secondly, the sensitivity of the two major factors, overshadowing accuracy and sky subdivision, is analyzed. With these results, appropriate application of the ray-tracing method is presented.