Generalizing Effective Spatial Bandwidth for Pole Location in MAS: The Elliptic Cylinder

The location of poles in the method of auxiliary sources for 2-D scatterers can be assisted using the effective spatial bandwidth (EBW) of the incident and scattered fields. Previously, only circular boundaries were considered. Here, EBW is extended to noncircular boundaries. Calculations presented for a cylinder with elliptical cross section verify EBW as an additional tool for pole placement for more general geometries

Name Disambiguation from link data in a collaboration graph using temporal and topological features

In a social community, multiple persons may share the same name, phone number or some other identifying attributes. This, along with other phenomena, such as name abbreviation, name misspelling, and human error leads to erroneous aggregation of records of multiple persons under a single reference. Such mistakes affect the performance of document retrieval, web search, database integration, and more importantly, improper attribution of credit (or blame). The task of entity disambiguation partitions the records belonging to multiple persons with the objective that each decomposed partition is composed of records of a unique person. Existing solutions to this task use either biographical attributes, or auxiliary features that are collected from external sources, such as Wikipedia. However, for many scenarios, such auxiliary features are not available, or they are costly to obtain. Besides, the attempt of collecting biographical or external data sustains the risk of privacy violation. In this work, we propose a method for solving entity disambiguation task from link information obtained from a collaboration network. Our method is non-intrusive of privacy as it uses only the time-stamped graph topology of an anonymized network. Experimental results on two real-life academic collaboration networks show that the proposed method has satisfactory performance.Comment: The short version of this paper has been accepted to ASONAM 201

MAS Pole Location and Effective Spatial Bandwidth of the Scattered Field

The concept of effective spatial bandwidth (EBW) is introduced for periodic domains. The EBW is applied to the incident and scattered fields along the boundary of an infinite circular cylinder. The scattered field is formulated using the method of auxiliary sources (MAS). In MAS, monopoles on an auxiliary surface (AS) are used to model the scattered field. It is shown that the EBW of the incident field can provide some insight regarding the placement of poles for the MAS scattered field model. Example simulations are provided to demonstrate the usefulness of EBW with respect to monopole placement rules in MAS

Analisis Metode Economic Order Quantity (Eoq) Sebagai Dasar Pengendalian Persediaan Bahan Baku Pembantu (Studi Pada Pg. Ngadirejo Kediri - PT. Perkebunan Nusantara X)

The purpose of this study was to determine the auxiliary raw material inventory control by PG. Ngadirejo Kediri and determine the auxiliary raw material inventory control using Economic Order Quantity. This type of research is descriptive research with quantitative approach. Source of data in this research using secondary data sources obtained directly from the company. Collecting data using interviews and documentation. Analysis of the data used in this research using Economic Order Quantity. Result of the analysis proves that when companies apply the method Economic Order Quantity in 2013, 2014, and 2015 in the purchase of raw materials auxiliary optimum, so there are the difference of spending cuts total cost for raw materials auxiliary belerang consecutive Rp. 1.010.959,19574, Rp. 957.208,54419, Rp. 1.165.215,68373. So also the raw material phosphate auxiliary in 2013, 2014, and 2015 there were a total savings respectively of Rp. 2.961.990,3358, Rp. 2.764.054,70668, Rp. 3.374.978,66496. Based on the analysis conducted, it should be PG. Ngadirejo Kediri apply method Economic Order Quantity in determining the quantity of the purchase of raw materials auxiliary materials optimal, so as to minimize total cost incurred by the company every year

Collaborative Deep Learning for Recommender Systems

Collaborative filtering (CF) is a successful approach commonly used by many recommender systems. Conventional CF-based methods use the ratings given to items by users as the sole source of information for learning to make recommendation. However, the ratings are often very sparse in many applications, causing CF-based methods to degrade significantly in their recommendation performance. To address this sparsity problem, auxiliary information such as item content information may be utilized. Collaborative topic regression (CTR) is an appealing recent method taking this approach which tightly couples the two components that learn from two different sources of information. Nevertheless, the latent representation learned by CTR may not be very effective when the auxiliary information is very sparse. To address this problem, we generalize recent advances in deep learning from i.i.d. input to non-i.i.d. (CF-based) input and propose in this paper a hierarchical Bayesian model called collaborative deep learning (CDL), which jointly performs deep representation learning for the content information and collaborative filtering for the ratings (feedback) matrix. Extensive experiments on three real-world datasets from different domains show that CDL can significantly advance the state of the art