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.

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, the use of storage space in industrial IoT systems using blockchain architecture will become a major challenge. Since the blockchain itself is based on the concept of a peer-to-peer network, 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 addition, newly added working nodes must also copy the original complete blockchain information, and will increase in expansion costs. In order to solve the above problems, this paper proposed a blockchain structure to reduce the space and network transmission costs. The 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, it 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.

Essential Skills for Working with Developers

There are specific technical resources that developers use that composers should also understand in order to have a productive workflow and to function as part of the team. One example of such a resource is version control, a system used to organize and track a team’s work by storing each change on a server. Though this is a surprisingly difficult resource to work with, it is discussed in this chapter in a concise and understandable manner. The optimization of audio is also a critical concept to understand when creating sound for a game. Each game has only a certain amount of hard disk space and memory allocated to the audio. Optimization is the technique of using this space as efficiently as possible so that one can achieve the desired sound without overloading the game’s resources. This chapter covers a variety of creative ways that composers can optimize their music without sacrificing quality.

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.

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%).

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.

A Mobile Agent-Based System for Server Resource Monitoring

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.

Online Computer Lab Security

Before an online computer lab is ready for students to perform hands-on practice, security measures need to be enforced to protect the computer lab and even more importantly to protect the university’s network. Since the computer lab is online, it is exposed to hundreds of malicious viruses. Once a computer is infected by viruses, the viruses will damage files, multiply themselves to occupy the memory and hard disk space, or to take away the CPU process power and make the computer run very slowly.

An Efficient Implementation of Polymer Viscoelastic Behavior Through a Pseudo Viscoelastic Model

Modeling of viscoelastic relaxation of polymer materials is important to understand the thermo-mechanical behavior of organic microelectronic systems. However, incorporation of viscoelastic behavior into numerical models makes the models compute-intensive. This paper presents a different technique to incorporate the polymer viscoelastic behavior into the numerical models such that the computation time is not adversely affected without compromising the accuracy of the results obtained. In the proposed “pseudo viscoelastic” modeling technique, the modulus of the viscoelastic material is computed as a function of time and temperature loading history outside of the finite-element simulation, and is then input into the simulation as a thermo-elastic material incorporating the viscoelastic relaxation of the material. This paper compares the warpage results obtained through the proposed technique against a complete viscoelastic simulation model and experimental data, and it is seen that the maximum warpage predicted using the proposed technique agree within 10% compared with the results obtained from a “full” viscoelastic model. Also, it is shown through some of our simulations that the proposed technique could result in a computational time saving of more than 50% and hard disk space saving of 65%.