Hard Disk Space Research Articles

A PROGRAM FOR CALCULATING THE PROJECTIVE RANGE AND STRAGGLING OF IONS IN A SOLIDUSING THE APPROXIMATION OF V.V. YUDIN

Ion implantation is the basis of many technological processes in electronics and microelectronics. The main quantities characterizing the penetration of ions into a solid are as follows; the length of the path of the ion until it stops completely, the average value of the projection of the total path on the direction of motion R̅p, and the average normal deviation of the projection of the path ΔR̅p. To calculate these values, computer programs SRIM, TRIM, and DYNE have been created, which require installation on a personal computer and occupy a large amount of hard disk space, which is not always justified in engineering practice. This paper describes an algorithm for a simple, installation-free program for calculating R̅p and ΔR̅p. The program algorithm is based on the Lindhard-Scharff-Schiott theory.

Sparse Hard-Disk Packings and Local Markov Chains

We propose locally stable sparse hard-disk packings, as introduced by Böröczky, as a model for the analysis and benchmarking of Markov-chain Monte Carlo (MCMC) algorithms. We first generate such Böröczky packings in a square box with periodic boundary conditions and analyze their properties. We then study how local MCMC algorithms, namely the Metropolis algorithm and several versions of event-chain Monte Carlo (ECMC), escape from configurations that are obtained from the packings by slightly reducing all disk radii by a relaxation parameter. We obtain two classes of ECMC, one in which the escape time varies algebraically with the relaxation parameter (as for the local Metropolis algorithm) and another in which the escape time scales as the logarithm of the relaxation parameter. A scaling analysis is confirmed by simulation results. We discuss the connectivity of the hard-disk sample space, the ergodicity of local MCMC algorithms, as well as the meaning of packings in the context of the NPT ensemble. Our work is accompanied by open-source, arbitrary-precision software for Böröczky packings (in Python) and for straight, reflective, forward, and Newtonian ECMC (in Go).

Using blockchain technology in IoT manufacture environment for intelligence prediction

Blockchain technology has become more important in recent years in Internet of Things (IoT) manufacturing. Many IoT manufacturing factories have successively invested in the blockchain architecture in the system to manage the data of the IoT manufacturing system for intelligence prediction. The blockchain-based system architecture can ensure the process of data transmission and preservation. However, any node must hold complete blockchain information. When there are thousands of nodes, the cost of hard disk space for storing these data will increase drastically as the number of nodes increases. In order to solve the above problems, this paper proposed a blockchain structure to reduce the space and network transmission costs. This architecture divides the traditional blockchain into two parts, which are divided into private blockchain and public blockchain according to the edge and the cloud. Each workshop will manage its own private blockchain, and the cloud will manage itself public blockchain. Under the proposed structure, each working node only needs to maintain the blockchain at its edge node and does not need to communicate with other edge node. The experimental results can effectively intelligence predict the space cost of node expansion, and it can also avoid the unnecessary network communication overhead caused by the traditional architecture. It can improve the space used of blockchain and reduce the network transfer time, and the cost of expanding nodes can be greatly reduced.

An Efficient Analytical Approach to Visualize Text-Based Event Logs for Semiconductor Equipment

Semiconductor equipment consists of a complex system in which numerous components are organically connected and controlled by many controllers. EventLog records all the information available during system processes. Because the EventLog records system runtime information so developers and engineers can understand system behavior and identify possible problems, it is essential for engineers to troubleshoot and maintain it. However, because the EventLog is text-based, complex to view, and stores a large quantity of information, the file size is very large. For long processes, the log file comprises several files, and engineers must look through many files, which makes it difficult to find the cause of the problem and therefore, a long time is required for the analysis. In addition, if the file size of the EventLog becomes large, the EventLog cannot be saved for a prolonged period because it uses a large amount of hard disk space on the CTC computer. In this paper, we propose a method to reduce the size of existing text-based log files. Our proposed method saves and visualizes text-based EventLogs in DB, making it easier to approach problems than the existing text-based analysis. We will confirm the possibility and propose a method that makes it easier for engineers to analyze log files.

Products of Interest

Products of Interest

Fast Solution of Rotor Losses in Inverter-Fed Cage Induction Motors With Skewed Slots

The conventional calculation of rotor losses in cage induction motors by the time-stepping finite element method requires the full slip waves of the rotor flux densities and currents. The calculations of the full slip waves are extremely expensive in CPU time, memory, and hard disk space for the induction motors with skewed slots and pulsewidth modulated supply. This article proposes a technique that reproduces those full slip waves by utilizing both the time varying and the spatial information of the rotor electromagnetic quantities and, hence, significantly saves the calculation cost. The more rotor bars per pair of poles the induction motor has, the more calculation cost this technique saves. The calculation costs of the proposed and conventional methods are compared for the rotor losses of a 5.5-kW inverter-fed skewed induction motor under load condition, and the calculated losses are validated by tests.

Southwestern Nigerian University Undergraduates’ Acceptance of YouTube as a web-based Instructional Tool

The study assessed the Southwestern Nigerian undergraduates’ acceptance of YouTube as a web-based instructional tool using Unified Theory of Acceptance and Use of Technology (UTAUT) Model. It determined the level of awareness of YouTube as a web-based instructional tool by the undergraduates. It measured the undergraduates’ effort and performance expectancy of YouTube and the conditions that facilitate its acceptance at the universities. The study employed the descriptive survey research design. The population consisted all registered undergraduates in Southwestern Nigeria. 800 students were selected from Obafemi Awolowo University (OAU), Ile-Ife, Osun State, Ladoke Akintola University of Technology (LAUTECH), Oyo State and Covenant University, Ota, Ogun State using disproportionate stratified sampling. The three universities were purposively selected based on their webometric ranking in terms of ICT usage. Findings from the study indicated that 57.80% of the undergraduates are moderately aware of YouTube as an instructional tool. The effort expectancy (×̅=3.00, sd=0.60) as well as the performance expectancy (×̅=3.00, sd=0.62) show that the undergraduates accept YouTube. The conditions identified by the undergraduates that can militate the acceptance of YouTube in the region included low bandwidth (79.70%), low hard disk space (65.60%), epileptic electricity supply (68.60%) and high cost of required devices (68.40%). The study therefore concluded that Southwestern Nigerian undergraduates are prone to accepting YouTube as a web-based instructional tool. 
 The study assessed the Southwestern Nigerian undergraduates’ acceptance of YouTube as a web-based instructional tool using Unified Theory of Acceptance and Use of Technology (UTAUT) Model. It determined the level of awareness of YouTube as a web-based instructional tool by the undergraduates. It measured the undergraduates’ effort and performance expectancy of YouTube and the conditions that facilitate its acceptance at the universities. The study employed the descriptive survey research design. The population consisted all registered undergraduates in Southwestern Nigeria. 800 students were selected from Obafemi Awolowo University (OAU), Ile-Ife, Osun State, Ladoke Akintola University of Technology (LAUTECH), Oyo State and Covenant University, Ota, Ogun State using disproportionate stratified sampling. The three universities were purposively selected based on their webometric ranking in terms of ICT usage. Findings from the study indicated that 57.80% of the undergraduates are moderately aware of YouTube as an instructional tool. The effort expectancy (×̅=3.00, sd=0.60) as well as the performance expectancy (×̅=3.00, sd=0.62) show that the undergraduates accept YouTube. The conditions identified by the undergraduates that can militate the acceptance of YouTube in the region included low bandwidth (79.70%), low hard disk space (65.60%), epileptic electricity supply (68.60%) and high cost of required devices (68.40%). The study therefore concluded that Southwestern Nigerian undergraduates are prone to accepting YouTube as a web-based instructional tool.

A Survey of Parallel Sequential Pattern Mining

With the growing popularity of shared resources, large volumes of complex data of different types are collected automatically. Traditional data mining algorithms generally have problems and challenges including huge memory cost, low processing speed, and inadequate hard disk space. As a fundamental task of data mining, sequential pattern mining (SPM) is used in a wide variety of real-life applications. However, it is more complex and challenging than other pattern mining tasks, i.e., frequent itemset mining and association rule mining, and also suffers from the above challenges when handling the large-scale data. To solve these problems, mining sequential patterns in a parallel or distributed computing environment has emerged as an important issue with many applications. In this article, an in-depth survey of the current status of parallel SPM (PSPM) is investigated and provided, including detailed categorization of traditional serial SPM approaches, and state-of-the art PSPM. We review the related work of PSPM in details including partition-based algorithms for PSPM, apriori-based PSPM, pattern-growth-based PSPM, and hybrid algorithms for PSPM, and provide deep description (i.e., characteristics, advantages, disadvantages, and summarization) of these parallel approaches of PSPM. Some advanced topics for PSPM, including parallel quantitative/weighted/utility SPM, PSPM from uncertain data and stream data, hardware acceleration for PSPM, are further reviewed in details. Besides, we review and provide some well-known open-source software of PSPM. Finally, we summarize some challenges and opportunities of PSPM in the big data era.

TANet: A Tiny Plankton Classification Network for Mobile Devices

This paper is devoted to a lightweight convolutional neural network based on the attention mechanism called the tiny attention network (TANet). The TANet consists of three main parts termed as a reduction module, self-attention operation, and group convolution. The reduction module alleviates information loss caused by the pooling operation. The new parameter-free self-attention operation makes the model to focus on learning important parts of images. The group convolution achieves model compression and multibranch fusion. Using the main parts, the proposed network enables efficient plankton classification on mobile devices. The performance of the proposed network is evaluated on the Plankton dataset collected by Oregon State University’s Hatfield Marine Science Center. The results show that TANet outperforms other deep models in speed (31.8 ms per image), size (648 kB, the size of the hard disk space occupied by the model), and accuracy (Top-1 76.5%, Top-5 96.3%).

Temporal stochastic linear encoding networks

Convolutional Neural Networks (CNNs) have achieved great success for action recognition. Technically, extracting effective long-range temporal dynamics is critical for such temporal tasks. This paper proposes a temporal stochastic linear encoding (TSLE) to construct the global video representations for action recognition, which can be embedded inside of CNN as a layer. The advantages of temporal stochastic linear encoding networks (TSLEN) are: (a) Compared with algorithms focusing on the short-term motions it can implement an easy yet robust manipulation of long range temporal clues. (b) We propose an arbitrarily directional motion boundary (ADMB) unit, which can save the training time and hard disk space. (c) The proposed TSLE unit maps the highly-dimensional videos to the compact spatio-temporal representations. On the efficiency and recognition accuracy experimental results demonstrate that the proposed TSLENs achieve competitive performance among the effective algorithms.

Baobab Laboratory Information Management System: Development of an Open-Source Laboratory Information Management System for Biobanking.

A laboratory information management system (LIMS) is central to the informatics infrastructure that underlies biobanking activities. To date, a wide range of commercial and open-source LIMSs are available and the decision to opt for one LIMS over another is often influenced by the needs of the biobank clients and researchers, as well as available financial resources. The Baobab LIMS was developed by customizing the Bika LIMS software (www.bikalims.org) to meet the requirements of biobanking best practices. The need to implement biobank standard operation procedures as well as stimulate the use of standards for biobank data representation motivated the implementation of Baobab LIMS, an open-source LIMS for Biobanking. Baobab LIMS comprises modules for biospecimen kit assembly, shipping of biospecimen kits, storage management, analysis requests, reporting, and invoicing. The Baobab LIMS is based on the Plone web-content management framework. All the system requirements for Plone are applicable to Baobab LIMS, including the need for a server with at least 8 GB RAM and 120 GB hard disk space. Baobab LIMS is a server–client-based system, whereby the end user is able to access the system securely through the internet on a standard web browser, thereby eliminating the need for standalone installations on all machines.

REVIEW ON IMAGE AND VIDEO COMPRESSION STANDARDS

Nowadays, the number of photos taken each day is growing exponentially on phones and the number of photos uploading on Internet is also increasing rapidly. This explosion of photos in Internet and personal devices such as phones posed a challenge to the effective storage and transmission.Multimedia files are the files having text, images, audio, video, and animations, which are large and require lots of hard disk space. Hence, these files take more time to move from one place to another place over the Internet. Image compression is an effective way to reduce the storage space and speedup the transmission. Data compression is used everywhere on the internet, that is, the videos, the images, and the music in online. Even though many different image compression schemes exist, current needs and applications require fast compression algorithms which produce acceptable quality images or video with minimum size. In this paper, image and video compression standards are discussed.

COMBAT DANCE:A CREATIVELY HOLISTIC APPROACH TO MOVEMENT PERFORMANCE ART

COMBAT DANCE: A CREATIVELY HOLISTIC APPROACH TO MOVEMENT PERFORMANCE ART By Raymont Lee Anderson, M.F.A. A thesis in partial fulfillment of the requirements for the degree of Master of Fine Arts at Virginia Commonwealth University Virginia Commonwealth University, 2003 Major Director. Dr. Noreen Barnes-McLain, Director of Graduate Studies Department of Theatre “Combat Dance” is an eclectic blend of combat and dance art forms combined and taught from the Fall 2001 to Spring 2003. As defined here, combat dance is a blend of techniques and principles gleaned from both unarmed and armed aspects of stage combat, martial arts (such as aikido and kung fu), modern dance and other expressive movements used to tell a story of conflict. Its primary purpose is to provide both actors and non-actors greater awareness and control of their bodies and to provide a range of creative avenues of expression. Combat dance gives the performers a unique and v holistic set of exercises and skills that leave no part of the body, mind, or even deeper the spirit uninfluenced. The thesis begins with the vision and birth of the class, a description of the preparatory research, an analysis of the reasons for the class, and reflection, revelations, and realizations gained through teaching the class. The ultimate focus of this thesis is to aid anyone interested in any type of combat or dance-related movements: dancers, non-dancers, actors, non-actors, movement coaches, and even those in the fields of dance or drama therapy. Thesis was saved using Microsoft® Works Suite 2002 Requirements To use Microsoft® Works Suite version 2002, you need: Computer/Processor Multimedia PC with a Pentium 200MHz or higher processor Memory 64 MB of RAM Hard Disk 1045 MB of available hard-disk space for typical installation of all applications. Custom installation may require more or less hard-disk space. Drive Quad speed CD ROM drive or higher Display Super VGA monitor, 1 MB of VRAM Operating System Microsoft Windows 98, Me, 2000 or XP operating system Peripherals Microsoft mouse or compatible pointing device Miscellaneous Microsoft® Internet Explorer 5.5 software required and included. Up to an additional 80 MB of hard disk space may be required for Internet Explorer upgrade. This installation will not replace your primary browser. Modem (28.8 baud or faster recommended), access to the Internet, Audio card with headphones or speakers, Microphone required for voice recording.

A Technical Cost Effective Network-Domain Hosting through Virtualization: a VMware ESXi and vSphere Client Approach

ABSTRACT In today‟s fast advancing technology, virtualization has presented the possibility of consolidating unused/underutilized resources into one physical component. This comes with benefits such as saving costs, hardware independence and improving security by isolation; it is no wonder virtualization is gradually being implemented in every aspect of the technology world. A virtualized system is able to run several separate Operating Systems (OSs) in parallel and in one Central Processing Unit (CPU) without the need to reboot. Unlike in a dual boot system, where only a single OS can run at a time requiring rebooting in order to switch to the other OS. Server virtualization is a term used to describe the abstraction of a physical server resource i.e. server consolidation. The VMware integrated Elastic Sky X (ESXi) is a bare metal hypervisor which provides the illusion of a real hardware to the guest (OS). This in turn simplifies underlying hardware by abstraction and therefore promoting better utilization of needed resources. Prior virtualization, server sprawl never presented itself to organizations as a shock, an event where one physical server performs only one function such as printer server, email server to mention but just a few which required a lot of money to maintain in the form of cooling devices and space. This study focuses on server virtualization using the cost effective VMware ESXi and its manager, vSphere client to host a network domain, a case of the Department of Computer Science (CSC), University of Fort Hare. The rationale behind this research project was to consolidate all physical servers into one physical machine without immense consumption of hard disk space since resources are only allocated when needed in a virtualized environment.

A Mobile Agent-Based System for Server Resource Monitoring

Abstract Mobile agent technology has become an important approach for the design and development of distributed systems. Currently, there is little research regarding the efficiency of mobile agent-based monitoring of the server resource. Based on the Mobile-C library, a mobile agent-based system called Mobile Agent- Based Server Resource Monitoring System (MABSRMS) is presented. In MABSRMS mobile agents can call low level functions in binary dynamic or static libraries, and thus can monitor server resource conveniently and efficiently. The experiment was conducted in a university computer center with hundreds of computer workstations and 15 server machines. The experiment uses the MABSRMS to detect system resources, such as available hard disk space, CPU usage and main memory usage. The experiment shows that the mobile agent-based monitoring system is a practical way to monitor server resources in large scale distributed computer centers.

Assembling a Three‐Dimensional Computed Tomography Database

Objectives: It is important for surgery to keep up with new technologies. Current skull-base techniques use stereotactic navigation, assisted by magnetic resonance (MRI) and computed tomography (CT) compilation. Our objective is to assemble a normalized CT database for three-dimensional (3D) endocranial renderings. This database can provide preoperative information for assistive mapping and intraoperative land marking during procedures. Methods: 222 CT studies were pooled between October 2011and December 2012. These studies were then deidentified and loaded into third party software, Osirix (Pixmeo, Switzerland), and reconstructed into 3D renderings. The Osirix program is a freeware-based Apple-only-program capable of volumetric analysis, metrics, and 3D space manipulation. The database was then encrypted for patient information protection. Results: A total of 179 studies(101 males and 78 females) were ultimately used. Two-hundred gigabytes of hard-disk space was used. An Apple (Cuptertino, CA) laptop, running Mac OSX, was used for computation. The Osirix software was downloaded as freeware, requiring no payment. The hard-disk was purchased at a local electronics store for $100.00 USD. The computer was approximately $1300. Conclusions: Radiologic imaging drives preoperative surgical planning. This can be augmented by new technology and creative applications of current innovations. There has not been an explanation process on how to assemble this data for departments and individuals. We provide a simple, reproducible, and inexpensive guide to CT head databases. Once the database is assembled, it may be used for such projects as mapping the parapharyngeal carotid, estimating endocranial volumes, and surgical diagrams.

A Memory-efficient Bounding Algorithm for the Two-terminal Reliability Problem

The terminal-pair reliability problem, i.e. the problem of determining the probability that there exists at least one path of working edges connecting the terminal nodes, is known to be NP-hard. Thus, bounding algorithms are used to cope with large graph sizes. However, they still have huge demands in terms of memory. We propose a memory-efficient implementation of an extension of the Gobien-Dotson bounding algorithm. Without increasing runtime, compression of relevant data structures allows us to use low-bandwidth high-capacity storage. In this way, available hard disk space becomes the limiting factor. Depending on the input structures, graphs with several hundreds of edges (i.e. system components) can be handled.

Image Compression of medical images using VQ-Huffman Coding Technique

Digital Medical Imaging has grown very fast in recent years and hence plays a vital role in diagnosis, treatment, and research area. All the radiological modalities such as CT scanners, MRI, US, PET, X-Ray made by multiple vendors and located at one or many sites can communicate by means of DICOM across an network. Now days, hospitals need to store large volume of data about the patients that require huge hard disk space and high bandwidth. This would employ the need to compress DICOM images for efficient storage and transmission over the internet. In this paper, a new compression algorithm combining the features of both lossy (DCT) and lossless (Huffman Coding) compression techniques has been designed and implemented. The performance of proposed algorithm is then improved using Vector Quantization technique in the context of increasing Compression Ratio as well as preserving the quality of compressed images. Different quality metrics like MSE, PSNR and CR are computed on various medical test images. The experimental results show that proposed compression technique performs better than the existing techniques in terms of performance parameters.

Numerical Simulation of Touchdown Dynamics of Thermal Flying-Height Control Sliders

With the advent of thermal flying-height control (TFC) technology the physical spacing in magnetic hard disk drives is now reduced to sub-1 nm. At this spacing the tribological flyability and reliability become critical issues for the performance of the read-write head. In this paper a numerical approach is applied to study the touchdown dynamics of TFC sliders by expanding a 3-degree-of-freedom slider dynamics model to a 250-degree-of-freedom head-gimbal assembly dynamics model and considering several significant tribological effects at this ultra-low clearance (adhesion, tribo-charge, friction, contact, etc.). The simulation results show that the slider's vibration amplitude increases substantially at the beginning of touchdown, and it gets suppressed with further reduction in flying height. Analysis in the frequency domain shows the excitation of the second air-bearing pitch mode when instability occurs. The expansion of the dynamic system to include a realistic model of the suspension is shown to be important in determining the frequency of the excited mode. Adhesion force is shown to play an essential role in exciting the second air-bearing pitch mode and causing instability, while electrostatic force and friction force affect only some details of the slider's dynamics at instability. Friction force is also shown to be related to the excitation of the first air-bearing pitch mode.

Head-disk interface design in magnetic data storage

Superior electrical conductivity and thermo-mechanical response of graphene can significantly improve areal density in magnetic data storage. The current head media spacing in hard disk drives (HDD) is 7.2 nm, and replacing conventional carbon overcoat (COC) with graphene will drastically reduce head media spacing, increasing areal density to eight times its present value. A paradigm shift in HDD systems can also be achieved via selection of a combination of new lubricants and unconventional architecture of COC systems. Here, we evaluate the feasibility of graphene overcoat (GOC), by understanding GOC-lubricant interactions. We further introduce new alternative head-disk interface (HDI) designs consisting of buffer/lubricant layers (i.e., graphene/carbon nanotube (CNT) or fullerene/perfluoropolyether (PFPE)). These hybrids could further enhance tribological performance including the reduction of wear and friction while drastically increasing areal density of data storage devices. Our study here will lead to vigorous investigation of HDI in magnetic data storage, including heat-assisted magnetic recording (HAMR), with tuned atomistic design criteria.