IDENTIFIKASI SENYAWA METABOLIT SEKUNDER PADA TANAMAN RUMPUT KEBAR (Biophytum petersianum Klotzsch)

Grass crop kebar (Biophytum petersianum Klotzsch), included in family Oxalidaceae. This crop as according to it’s the name, of course grows either in region Kebar Tengah and Kebar Timur, glorious Manokwari Irian. Grass Kebar (Biophytum petersianum Klotzsch) many applied as drug \ud crop between it for uterine fertility, stomachache drug, back ache drug, laxative and tumor drug. \ud This research aim to know secodary metabolit types which implied in grass plant kebar (Biophytum petersianum Klotzsch). Research type applied is qualitative research having the character of descriptive. Material applied in this research is all part of crop Biophytum \ud petersianum Klotzsch which dry. In determination of secodary metabolit content type which implied in crop Biophytum petersianum Klotzsch applies method spot test while determination of secodary metabolit content type standing in reproduction at crop grass kebar (Biophytum \ud petersianum Klotzsch) applied method KLT (Thin layer chromatography) \ud Based on result of inferential research that in crop grass kebar (Biophytum petersianum Klotzsch), contains type secodary metabolit type Flavonoid, Fenolik and alkaloid,dan generation compound isoflavon that is daidzein

Orthogonal series estimation of the pair correlation function of a spatial point process

The pair correlation function is a fundamental spatial point process characteristic that, given the intensity function, determines second order moments of the point process. Non-parametric estimation of the pair correlation function is a typical initial step of a statistical analysis of a spatial point pattern. Kernel estimators are popular but especially for clustered point patterns suffer from bias for small spatial lags. In this paper we introduce a new orthogonal series estimator. The new estimator is consistent and asymptotically normal according to our theoretical and simulation results. Our simulations further show that the new estimator can outperform the kernel estimators in particular for Poisson and clustered point processes

Non-thermal atmospheric pressure plasma jet and its application for polymer treatment

Non-thermal atmospheric pressure plasma jet is a suitable source for polymer treatment. The main characteristic of this plasma jet is the remote operation and its scalable dimension, thus, allowing local treatment of 3D surfaces. In this work an atmospheric pressure DBD plasma jet has been constructed and the application of the plasma jet for polymer treatment is investigated

Rehabilitation of a water distribution system using sequential multiobjective optimization models

Identification of the optimal rehabilitation plan for a large water distribution system (WDS) with a substantial number of decision variables is a challenging task, especially when no supercomputer facilities are available. This paper presents an initiative methodology for the rehabilitation of WDS based on three sequential stages of multiobjective optimization models for gradually identifying the best-known Pareto front (PF). A two-objective optimization model is used in the first two stages where the objectives are to minimize rehabilitated infrastructure costs and operational costs. The optimization model in the first stage applies to a skeletonized WDS. The PFs obtained in Stage 1 are further improved in Stage 2 using the same two-objective optimization problem but for the full network. The third stage employs a three-objective optimization model by minimizing the cost of additional pressure reducing valves (PRVs) as the third objective. The suggested methodology was demonstrated through use of a real and large WDS from the literature. Results show the efficiency of the suggested methodology to achieve the optimal solutions for a large WDS in a reasonable computational time. Results also suggest the minimum total costs that will be obtained once maximum leakage reduction is achieved due to maximum possible pipeline rehabilitation without increasing the existing tanks

A New Efficient Stochastic Energy Management Technique for Interconnected AC Microgrids

Cooperating interconnected microgrids with the Distribution System Operation (DSO) can lead to an improvement in terms of operation and reliability. This paper investigates the optimal operation and scheduling of interconnected microgrids highly penetrated by renewable energy resources (DERs). Moreover, an efficient stochastic framework based on the Unscented Transform (UT) method is proposed to model uncertainties associated with the hourly market price, hourly load demand and DERs output power. Prior to the energy management, a newly developed linearization technique is employed to linearize nodal equations extracted from the AC power flow. The proposed stochastic problem is formulated as a single-objective optimization problem minimizing the interconnected AC MGs cost function. In order to validate the proposed technique, a modified IEEE 69 bus network is studied as the test case