Wear can be defined as the removal of material from solid surfaces by mechanical action. Wheel/rail wear is an everyday experience, and has been observed and studied for a very long time. Many railway accidents have occurred that were related to poor maintenance and wheel/rail wear. Therefore, there is a need to study the wheel and rail wear, so as to make informed decisions on wheel and rail maintenance, and reduce maintenance costs. This work focus on investigate the relationship between the wheel/rail surface roughness and wheel/rail wear. To study the relationship between the wheel/rail roughness parameters and the wheel/rail wear, a twin disc rig test and Alicona profilometer were used. This study can use to eliminate the wheel/rail wear and improve the design of the wheel and rail. This paper presented an Alicona profilometer and replica material as an effective tool to study the wheel/rail surface texture
Many industrial applications require that a hydraulic systems working automatically after an operator presses a START pushbutton. Such as cutting, bending, drilling, clamping and forming metals, that needs more force. Clamping and drilling system one of them, that need control for ability to clamp and drilling the workpiece with required force without damage or deforming the work piece. In this study, clamping and drilling system was developed and improvement by using PLC control system. The PLC is programed for control requirements to the hydraulic system of workpiece clamp and drilling. The Programming Software for GLOFA series GMWIN is selected and programming (LAD) software was used to program the system control process of the system. Using PLC control hydraulic system, can be easy to improve power the productivity greatly and increase the system stability, reliability, also security for factory workers.
In this paper, we explore the applicability of UML (Unified Modeling Language) as a Business Process Modeling tool (BPM). BPM is a critical component of any business improvement process; it allows capturing a broad outline and procedures that govern what it is a business does. This model provides an overview of where the proposed system will fit into the organizational structure and daily activities. Although there are quite a lot of modeling techniques, there is no a well-defined standard. Moreover, these techniques support wide range of definitions and notations. Meanwhile UML is based on well-defined meta model governed by an international research group (OMG: Object Modeling Group) and becomes a de-facto standard for software modeling. Its rich modeling tool, with different visual diagrams and notations, makes it a promising candidate for modeling any business process. A case study is presented to better understand how UML can be used as a BPM tool.
With the growth in heterogeneity, the current focus of designing parallel performance cost models is on providing low-level details of parallel execution to the programs to enable resource-aware partitioning and dynamic load balancing procedures, in particular, for heterogeneous parallel architectures. This Paper presents a survey of a classification of current and emerging cost models for parallel and distributed environments as well as algorithmic skeletons, and addressing major challenges such as complexity, target architectures, Optimisation and Skeleton-based Approachs.
This paper describes the design and implementation of two axis platform controller. The term two axis platform is a machine which rotate in two degrees of freedom, mainly it has two axis, one rotate about vertical axis and the other rotate about horizontal axis. The paper deals with two areas, study the DC motor as actuator and how it could be controlled using the computer software ("MATLAB", "Integral") technique to the integrated joint dynamic model and an independent joint control scheme was drive using a classic approach. The results obtained gave the required movement for the platform in terms of fluidity and smoothness in moving from one position to another one.
Diagram groups are created from geometric objects named semigroup presentation . These diagrams are drawn and considered as 2- complexes. The aim of this article is to determine the covering complex for diagram groups over union of two semigroup presentations by adding some initial generators and relations to alphabet and a set of relation correspondingly. The main aim is to study subgroups of diagram group, we present a method of producing normal subgroups of one generator. In addition, we design a new method for computing all generators and relations for the fundamental group
Objective: Student retention is one of the most challenging problems in higher education. It affects university rankings, school reputation, and financial resources. In order to understand and solve the problem, it is very important to know the factors that affect student retention to build a model that predicts students who are at risk of dropping out of college. This can be obtained by using data mining techniques. Methods: This paper describes a number of case studies that studied student retention using data mining and analysis their results. Results: The analysis shows that student retention is affected mostly by scholastic performance, such as GPA and SAT, and the most used data mining technique to predict retention model is decision trees. Moreover, using sufficient data with proper variables and using balanced dataset for binary classification help data mining techniques to predict freshman student retention with about 80% precision. Finally, using rich set of features, more data and more variables can help improve the data mining results. Conclusion: Universities and institutions can use their databases along with data mining techniques to predict student retention. They can build models that predict at risk students, so they can make a plan to retain them. Also, the factors that affect student retention can be monitored by the university and managed in somehow that improves retention. However, the success of data mining studies depends on the quantity and quality of data used to build models.