Studi Karakteristik Volume Tabung Udara Dan Beban Katup Limbah Terhadap Efisiensi Pompa Hydraulic Ram

A community that live far away from electricity power source has a problem in moving water from low to a higher location. One option for solving this problem is using hydraulic ram whose energy is the pressure that resulted from water hammer of water that flows into the pump through pipes. In this paper, a study on the effects of air-tube volume and disposal valve weight to the pump efficiency will be conducted and further the optimal setting for those factors that will gain the best efficiency will be determined.. After the experiments and analysis of variance and also response surface regression, resulting that both factors, air-tube volume and disposal valve weight, influence the efficiency as well as interaction between them. The optimal setting for best efficiecy is at 1300 ml tube volume and 400 gram weight to get efficiency of 42.9209%

Multi density DBSCAN

Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases.DBSCAN clustering algorithm relying on a density-based notion of clusters which is designed to discover clusters of arbitrary shape. DBSCAN requires only one input parameter and supports the user in determining an appropriate value for it. DBSCAN cannot find clusters based on difference in densities. We extend the DBSCAN algorithm so that it can also detect clusters that differ in densities and without the need to input the value of Eps because our algorithm can find the appropriate value for each cluster individually by replacing Eps by Local

Characteristics of events with metric-to-decahectometric type II radio bursts associated with CMEs and flares in relation to SEP events

A gradual solar energetic particle (SEP) event is thought to happen when particles are accelerated at a shock due to a fast coronal mass ejection (CME). To quantify what kind of solar eruptions can result in such SEP events, we have conducted detailed investigations on the characteristics of CMEs, solar flares and m-to-DH wavelength type II radio bursts (herein after m-to-DH type II bursts) for SEP-associated and non-SEP-associated events, observed during the period of 1997-2012. Interestingly, 65% of m-to-DH type II bursts associated with CMEs and flares produced SEP events. The SEP-associated CMEs have higher sky-plane mean speed, projection corrected speed, and sky-plane peak speed than those of non-SEP-associated CMEs respectively by 30%, 39%, and 25%, even though the two sets of CMEs achieved their sky-plane peak speeds at nearly similar heights within LASCO field of view. We found Pearson's correlation coefficients between the speeds of CMEs speeds and logarithmic peak intensity of SEP events are cc = 0.62 and cc = 0.58, respectively. We also found that the SEP-associated CMEs are on average of three times more decelerated (-21.52 m/s2) than the non-SEP-associated CMEs (-5.63 m/s2). The SEP-associated m type II bursts have higher frequency drift rate and associated shock speed than those of the non-SEP-associated events by 70% and 25% respectively. The average formation heights of m and DH type II radio bursts for SEP-associated events are lower than for non-SEP-associated events. 93% of SEP-associated events originate from the western hemisphere and 65% of SEP-associated events are associated with interacting CMEs. The obtained results indicate that, at least for the set of CMEs associated with m-to-DH type II bursts, SEP-associated CMEs are more energetic than those not associated with SEPs, thus suggesting that they are effective particle accelerators.Comment: 19 pages, 10 figures, 3 tables, accepted for publication by ApS

Simulation for Scanning Electron Microscopy

Simulations of images of surface steps obtained by high energy reflection electron microscopy are presented. It is shown that double images of simple steps, with no associated strain field, may occur when surface resonance conditions are established. Accurate calculation of image intensity requires large calculations and care is needed in relating the computed wave functions to those occurring for a semi-infinite incident wave. Estimates of the time to compute accurate wavefunctions are given and it is shown that they are reasonable for modem fast computers

Variety, plant population vs. severity of Ascochyta blight in chickpea

Non-Peer Reviewe

Pengendalian Kualitas Pada Produksi Pasta Gigi

One effort to increase productivity of a production process is by decreasing the defects. This can be done by implementing the apropriate quality control. This research is conducted in a tooth paste production to seek which factors that will influence defects and uses factorial design method to get the optimum condition. Results show that the paste weight is determined by air pressure in the mixer and stirring time with optimum condition at 5 cm Hg and 80 minutes, while precision tube folded is determined by the height of tube and the height of the table with optimum condition at 189 mm and 130 mm

Simulasi Diskriminasi Struktur Proses Produksi Yang Berdata Atribut

Data from a production process usually is correlated and doesnot fit normal distribution. In order to detect the existence of strutural changes in production process, especially attribute data, which is focused on changes that are influenced by the data covariance structure, it is necessary to model the covariance function which identical to the spectral distribution first. Accordingly, data is transformed into its spectral distribution by using Walsh-Fourier Transformation so that data will not be correlated and can be analize statistically. Transformed data will be tested with F-test to see if this method can detect the changes. This simulation will use time series data which is generated with INAR (Integer Valued Auto-Regressive) model