A Novel Approach to Arabic Chabot, Utilizing Google Colab and the Internet of Things: A Case Study at a Computer Center

A Chabot is a software program for humans to interact with natural-language computers. It has numerous applications in business, service, education, and healthcare, among others. Arabic Chabot’s, on the other hand, fight to generate and display Arabic characters correctly because of linguistic problems. In this paper, we propose a new method for the development of effective Arabic Chabot’s, which is improved by the use of the Internet of things (IOT). An experiment was performed utilizing Google Colab and the Python Chatterbot library to build and deploy an Arabic Chabot for a computer center based on IOT.

Predicting Hard Disk Failure by Means of Automatized Labeling and Machine Learning Approach

Today, cloud systems provide many key services to development and production environments; reliable storage services are crucial for a multitude of applications ranging from commercial manufacturing, distribution and sales up to scientific research, which is often at the forefront of computing resource demands. In large-scale computer centers, the storage system requires particular attention and investment; usually, a large number of diverse storage devices need to be deployed in order to match the varying performance and volume requirements of changing user applications. As of today, magnetic drives still play a dominant role in terms of deployed storage volume and of service outages due to device failure. In this paper, we study methods to facilitate automated proactive disk replacement. We propose a method to identify disks with media failures in a production environment and describe an application of supervised machine learning to predict disk failures. In particular, a proper stage to automatically label (healthy/at-risk) the disks during the training and validation stage is presented along with tuning strategy to optimize the hyperparameters of the associated machine learning classifier. The approach is trained and validated against a large set of 65,000 hard drives in the CERN computer center, and the achieved results are discussed.

High Performance Computing in Parallel Electromagnetics Simulation Code suite ACE3P

A comprehensive set of parallel finite-element codes suite ACE3P (Advanced Computational Electromagnetics 3D Parallel) is developed by SLAC for multi-physics modeling of particle accelerators running on massively parallel computer platforms for high fidelity and high accuracy simulation. ACE3P enables rapid virtual prototyping of accelerator and RF component design, optimization and analysis. Advanced modeling capabilities have been facilitated by implementations of novel algorithms for numerical solvers. Code performance on state-of-the-art high performance computing (HPC) platforms for large-scale RF modeling in accelerator applications will be presented in this paper. All the simulations have been performed on the supercomputers at National Energy Research Computer Center (NERSC).

Development of services in the field of research data management and scholarly communication at the University of Vienna

In 2008 the University of Vienna released the institutional repository PHAIDRA. With this release, several services for research data management followed soon. It is still essential to review the services and integrate new one, related to the change of the research practice. The demand for training and support is increasing, and more often, we see now the need for consulting services. That service supports the research cycle from writing a data management plan to getting DOIs for data and are integrated into the PHAIDRA portfolio. PHAIDRA is a cooperation between the Central University Computer Center and the University Library for researcher and research projects of the University of Vienna. To be alleged with the actual changes in research data management, PHAIDRA regularly participates in national and international projects, like Austrian Data Lab and Services and FAIR Data Austria nationally as well as implementing with COAR (Confederation of Open Access Repositories) a vocabulary service and engaging with researcher projects together with RDA (Research Data Alliance) internationally. Several networks such as the network for repository managers (RepManNet) or the network for sustainable software development (code4research), and the network of other PHAIDRA users at other universities in Austria, Italy and Balkan countries, enable constructive cooperation on a technical, library and scientific level on various topics. The poster intends to give an insight into these activities.

Erasure Coding for production in the EOS Open Storage system

The storage group of CERN IT operates more than 20 individual EOS[1] storage services with a raw data storage volume of more than 340 PB. Storage space is a major cost factor in HEP computing and the planned future LHC Run 3 and 4 increase storage space demands by at least an order of magnitude. A cost effective storage model providing durability is Erasure Coding (EC) [2]. The decommissioning of CERN’s remote computer center (Wigner/Budapest) allows a reconsideration of the currently configured dual-replica strategy where EOS provides one replica in each computer center. EOS allows one to configure EC on a per file bases and exposes four different redundancy levels with single, dual, triple and fourfold parity to select different quality of service and variable costs. This paper will highlight tests which have been performed to migrate files on a production instance from dual-replica to various EC profiles. It will discuss performance and operational impact, and highlight various policy scenarios to select the best file layout with respect to IO patterns, file age and file size. We will conclude with the current status and future optimizations, an evaluation of cost savings and discuss an erasure encoded EOS setup as a possible tape storage replacement.

Pengembangan PDPT Berbasis Framework Dengan Teknologi Web Service SOAP dan REST di Universitas Semarang

One indication of the development of a tertiary institution can be seen from the number of students applying from year to year. The increasing number of students is an identification that the tertiary institution is in high demand by the community. University student data is stored in a university database or often called PDPT. PDPT data is used for various things, such as calculating the ratio of lecturers and students, calculating the number of graduations, calculating class ratios to university income. Because of the importance of the PDPT data, the validity of the PDPT data must be maintained. The problem that arises at the University of Semarang is that the data is only contained in the central server and is not distributed well globally or in detail up to the Study Program and the Quality Assurance Agency. This requires an alternative way to validate student data so that student data can be monitored continuously. The method can be done by using software development methods using a framework. Data obtained through the computer center by utilizing a web service so that data can be retrieved directly.

Penerapan Algoritma Apriori Dalam Memprediksi Hasil Penjualan Sparepart PC (Studi Kasus : Toko Sentra Computer)

Technological advances are increasing and becoming an important need for everyday life both in the fields of education, economics, social, culture and politics. One of the technologies needed by society is computers. Sentra Computer is a store engaged in the sale of computers. The researcher has conducted research at the Computer Center Store and found a problem when the stock of PC spare parts that cost more than Rp. 450,000 is often insufficient because the stock is bought with a small amount so that capital can be used on a cheaper PC spare part. The purpose of this thesis research is to find out the sales data of PC spare parts at the Sentra Computer Shop which are most purchased by consumers. The methodology used is a priori algorithm by calculating the value of support and the value of confidence carried out manually and computerized using rapidminer. The result is that the Sentra Computer Store owner can provide sufficient stock.