Design System Fuel Inventory Control In Gas Stations With The Concept Of Min-Max Stock Level And Time Phased Order Point Case Study Gas Stations 44.501.01

The concept of supply chain inventory requirement has been widely used by companies to improve meeting the needs of its customers. Lost sales due to inventory shortage is an important thing to be avoided by the company. This research aims to build a inventory control system supplies fuel to the method of Distribution Requirements Planning (DRP) web-based on gas stations in the area of Semarang. The method used for planning is the ordering of distribution requirements planning with the stage of determining the net requirements (netting), selection Lot (lotting), the timing of orders (offsetting) and the determination of gross requirements for next level (exploision). The Time Phased Order Point and min-max stock level Consept used for optimalitation needs Planning. Model Design of the system is using waterfall model which consists of system analysis, system design, system implementation and testing programs. The research design of this system is the ordering of the supply system can be used to support and improve inventory control at retail outlets. The results of testing the system states that the system developed to support inventory control, increased security at gas stations supply needs to be better and minimize losses orders. Keywords: Inventory Control; Needs Planning; Time Phased Order Point; Distribution Requirement Planning; Design system; Waterfall mode

Semantic Support for Log Analysis of Safety-Critical Embedded Systems

Testing is a relevant activity for the development life-cycle of Safety Critical Embedded systems. In particular, much effort is spent for analysis and classification of test logs from SCADA subsystems, especially when failures occur. The human expertise is needful to understand the reasons of failures, for tracing back the errors, as well as to understand which requirements are affected by errors and which ones will be affected by eventual changes in the system design. Semantic techniques and full text search are used to support human experts for the analysis and classification of test logs, in order to speedup and improve the diagnosis phase. Moreover, retrieval of tests and requirements, which can be related to the current failure, is supported in order to allow the discovery of available alternatives and solutions for a better and faster investigation of the problem.Comment: EDCC-2014, BIG4CIP-2014, Embedded systems, testing, semantic discovery, ontology, big dat

Pro-Resume: The Infographic Resume Builder

Scoring an interview is a challenge for any job seeker these days, thus having a unique and well-organized resume is crucial to grab a recruiter’s attention. Online resume builders such as ResumeNow and VisualizeMe have been created to help users build resumes; however, their templates are lacking in quantity, customizability, and in some instances, even legibility. Thus, our team set out to create an infographic online resume builder, a web application that allows its users to build, organize, and beautify their resumes to aid them in their job search. Our system allows for easy integration with their LinkedIn profiles so that their work history can be easily duplicated without typing everything out. There is also a large scope of infographic template options that users can choose from and, most importantly, users will have the ability to further customize their content and organization by using the system’s editing mode

Moving Usability Testing onto the Web

Abstract: In order to remotely obtain detailed usability data by tracking user behaviors within a given web site, a server-based usability testing environment has been created. Web pages are annotated in such a way that arbitrary user actions (such as "mouse over link" or "click back button") can be selected for logging. In addition, the system allows the experiment designer to interleave interactive questions into the usability evaluation, which for instance could be triggered by a particular sequence of actions. The system works in conjunction with clustering and visualization algorithms that can be applied to the resulting log file data. A first version of the system has been used successfully to carry out a web usability evaluation

Cross Validation Of Neural Network Applications For Automatic New Topic Identification

There are recent studies in the literature on automatic topic-shift identification in Web search engine user sessions; however most of this work applied their topic-shift identification algorithms on data logs from a single search engine. The purpose of this study is to provide the cross-validation of an artificial neural network application to automatically identify topic changes in a web search engine user session by using data logs of different search engines for training and testing the neural network. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that it could be possible to identify topic shifts and continuations successfully on a particular search engine user session using neural networks that are trained on a different search engine data log