Miracle-dz/UniFAR-FTUs huggingface dataset:
Multimedia Tools for Teaching Basic Electronics

This paper presents the application of interactive multimedia courseware for teaching rectifiers in electrical engineering and electronics engineering courses. The aim of the study is to present a learning innovation using courseware on rectifier as an additional tool in teaching and studying EE 432 (Power Electronics) for Spring Semester of 2013-2014. The courseware was developed using Macromedia Authorware as the authoring language. Students gain hands-on experience, and also improve their skill in product development, selfdirected learning, teamwork, and project management. Practical projects increase the challenge for students and, hence, their interest level. Graphics and animations are used to give a more attractive and effective presentation. The courseware developed is also capable of producing graph simulation which agreed with the simulation using MATLAB program. Using this courseware the teaching and studying process will be more effective, attractive and interesting.
Emerging Risk Management in Industry 4.0: An Approach to Improve Organizational and Human Performance in the Complex Systems

Industry 4.0 in the contemporary operating context carries important sources of complexity. This context generates both traditional risks and emerging risks that must be managed. The management of these risks includes both industrial risks and occupational risks, since they are heavily interlinked. The human factor can be considered the main link between both types of risks. Thus, understanding risks originating from human errors and organizational weaknesses as causes of accidents and other disruptions in complex systems requires elaborating sophisticated modeling approaches. Therefore, the objective of this paper is to propose an organizational and human performance approach to improve the emerging risk management linked to the complex systems, like as Human-Machine Interactions (HMI) and Human-Robot Interaction (HRI). To fulfill this objective, we first introduce the concept of emerging risk linked to human factor. Then, we introduce the concept of emerging risk management in the Industry 4.0 context. Under this complex context, we expose the concept considering the current models of risk management. Finally, we discuss how enhancing human and organizational performance can be achieved through risk management in complex systems linked to Industry 4.0. Therefore, we conclude that while Industry 4.0 brings numerous advantages, it must contend with emerging risks and challenges associated with organizational and human factors. These emerging risks include industrial risks as well as occupational risks. Moreover, the human factor aspect of Industry 4.0 is directly linked to industrial emerging and occupational emerging via context of operations. To cope with these new challenges, it is necessary to develop new approaches. One of such approaches is Complex System Governance. This approach is discussed along with the need for adequate organizational and human performance models dealing with, for example, experience from other domains such as nuclear, space, aviation, and petrochemical.
H∞ Mixed Sensitivity Control for a Three-Port Converter

The three-port converter (TPC) obtains major attention due to its power density and ability to dispose different electric powers flexibly. Since the control models of the TPC are derived from particular steady state work point through small signal modeling method, the model parameters usually be deviated from their normal values with the change of operation and load conditions. Furthermore, there are couplings and interactions in power delivery between different ports, which have a significant influence in the dynamic control performance of the system. In this paper, the H∞ mixed sensitivity method is employed to design robust controllers for a TPC control system. Simulation results are given to demonstrate the effectiveness of the proposed scheme, and experimental studies are conducted on a prototype circuit to further validate the developed method. Compared to a traditional PI controller, it shows that a mixed sensitivity based robust controller manifest balanced performance in model parameters changes attenuation and dynamic control performance.
Analysis of students' generated questions in laboratory learning environments

In order to attain a reliable laboratory work assessment, we argue taking the Learning Environment as a core concept and a research paradigm that considers the factors affecting the laboratory as a particularly complex educational context. With regard to Laboratory Learning Environments (LLEs), a well known approach is the SLEI (Science Laboratory Environment Inventory). The aim of this research is to design and apply an alternative and qualitative assessment tool to characterize Laboratory Learning Environments in an introductory course of organic chemistry. An alternative and qualitative assessment tool would be useful for providing feed-back for experimental learning improvement; serving as a complementary triangulation tool in educational research on LLEs; and generating meaningful categories in order to design quantitative research instruments. Toward this end, spontaneous questions by students have been chosen as a reliable source of information. To process these questions, a methodology based on the Grounded Theory has been developed to provide a framework for characterizing LLEs. This methodology has been applied in two case studies. The conclusions lead us to argue for using more holistic assessment tools in both everyday practice and research. Likewise, a greater attention should be paid to metacognition to achieve suitable self-perception concerning students’ previous knowledge and manipulative skills.
ANALYSIS AND COMPARISON OF SYMMETRIC KEY CRYPTOGRAPHIC ALGORITHMS BASED ON VARIOUS FILE FEATURES

For achieving faster communication most of confidential data is circulated through networks as electronic data. Cryptographic ciphers have an important role for providing security to these confidential data against unauthorized attacks. Though security is an important factor, there are various factors that can affect the performance and selection of cryptographic algorithms during the practical implementation of these cryptographic ciphers for various applications. This paper provides analysis and comparison of some symmetric key cryptographic ciphers (RC4, AES, Blowfish, RC2, DES, Skipjack, and Triple DES) on the basis of encryption time with the variation of various file features like different data types, data size, data density and key sizes.
Real-time classification of Fear / Panic emotion based on Physiological Signals

Fear/panic is one of the critical factors that could hinder a user to take proper actions in emergency situations. Therefore an automatic detection of users fear/panic states is crucial for enhancing safety in operating control rooms, driving vehicles, etc. In this paper, we address machine learning-based methods for real-time recognition of fear/panic states using physiological signals. We conducted a human factors experiment in order to collect physiological signals involving fear/panic or neutral states. A total of ten subjects participated in the experiment and each one was asked to see ten different movie clips to induce fear/panic and neutral states alternately. While he/she was seeing the ten movie clips, five physiological signals (skin conductance, blood The Eighth Pan-Pacific Conference on Occupational Ergonomics (PPCOE 2007) October 17-19, 2007, Bangkok, Thailand volume pressure, skin temperature, electromyography, and respiration) were collected and recorded. We applied ensemble learning methods to the real-time classification of fear/panic states, including Bagging, Boosting, and Adaboost, using features obtained from the physiological signals. The proposed methods provided more than 77% of real-time classification accuracy in the experiment. The real-time fear/panic recognition methods can be applied to safety-critical applications such as nuclear reactor control, driving, and aviation in order to enhance safety in emergency situations.
The Massively Parallel Processor

From the Publisher: The development of parallel processing, with the attendant technology of advanced software engineering, VLSI circuits, and artificial intelligence, now allows high-performance computer systems to reach the speeds necessary to meet the challenge of future complex scientific and commercial applications. This collection of articles documents the design of one such computer, a single instruction multiple data stream (SIMD) class supercomputer with 16,834 processing units capable of over 6 billion 8 bit operations per second. It provides a complete description of the Massively Parallel Processor (MPP), including discussions of hardware and software with special emphasis on applications, algorithms, and programming. This system with its massively parallel hardware and advanced software is on the cutting edge of parallel processing research, making possible AI, database, and image processing applications that were once thought to be inconceivable. The massively parallel processor represents the first step toward the large-scale parallelism needed in the computers of tomorrow. Orginally built for a variety of image-processing tasks, it is fully programmable and applicable to any problem with sizeable data demands. Contents: "History of the MPP," D. Schaefer; "Data Structures for Implementing the Classy Algorithm on the MPP," R. White; "Inversion of Positive Definite Matrices on the MPP," R. White; "LANDSAT-4 Thematic Mapper Data Processing with the MPP," R. O. Faiss; "Fluid Dynamics Modeling," E. J. Gallopoulas; "Database Management," E. Davis; "List Based Processing on the MPP," J. L. Potter; "The Massively Parallel Processor System Overvew," K. E. Batcher; "Array Unit," K. E.Batcher; "Array Control Unit," K. E. Batcher; "Staging Memory," K. E. Batcher; "PE Design," J. Burkley; "Programming the MPP," J. L. Potter; "Parallel Pascal and the MPP," A. P Reeves; "MPP System Software," K. E. Batcher; "MPP Program Development and Simulation," E. J. Gallopoulas. J. L. Potter is Associate Professor of Computer Science at Kent State University. The Massively Parallel Processor is included in the Scientific Computation Series, edited by Dennis Gannon.
Content-Based Emotional Semantic Recognition and Retrieval of Male T-Shirt Images

Emotional semantics identifying and retrieving of images is one of the hotspots in current research. It can provide certain basis for clothing design, clothing wearing and clothing matching. As a kind of male T-shirt, the recognition and retrieval of emotional semantics of images has also attracted much attention. On the basis of establishing the relationship between emotional semantic space and low-level features of T-shirt images based on the previous knowledge of clothing field, 40 T-shirt images were trained and a machine learning model was established by using support vector machine (SVM). The quantitative mapping relationship between emotional semantic space and low-level features of T-shirt images was established, which could be calculated automatically. The emotional semantics of the image is calculated to realize the emotional semantic recognition of the image. Similarity measure algorithm is also used to measure the emotional semantics of images, and image emotional semantic retrieval is realized. Through the experiment of software programming and development, a better recognition and retrieval effect have been achieved, thus verifying the feasibility and effectiveness of emotional semantic analysis of images combined with domain knowledge.
The Driving Forces for Design Project Effectiveness

This study attempts to look at the internal and external factors which result in improved interior design project management through the proposal and empirical validation of a theoretical model. The model incorporates three major dimensions: users' technology readiness, their perceptions of information system quality, and project management effectiveness. Sample data collected from 50 interior design companies located in north, central and southern urban cities in Taiwan (n = 497) were analyzed using structural equation modeling (SEM). Results showed that both users' technology readiness and information system quality have positive effect on project effectiveness. Specifically, technology readiness influences project management effectiveness indirectly through information system quality, indicating that it is crucial for organizations to invest and enhance quality technological performance support tools in conjunction with fostering users' acceptance and readiness of technology adoption and application.
Brigitte Brabant Approach to Knowledge Management Learning in Health Care Organizations and Systems : An Alternative

This article presents, through the example of health care systems, a theoretically founded analysis of learning processes in the context of reform implementation. Following a critical assessment of the two most prominent approaches to knowledge management—mechanistic and organic—we propose another approach, which consists in coordinating the learning of interdependent actors. The potential of this approach is illustrated through an empirical case study of the implementation of a Quebec program to combat cancer.
A growing network classifier of 3D objects using multiple views

A system for the classification of real 3D objects is presented. Ten objects are presented in arbitrary orientation (and position, within limits). The perception of an object is achieved by the use of multiple stereo pairs of images taken from different view positions. Classification of the spectrum of distances between edge-points perceived on an object is achieved using a constructive algorithm. Convergence to zero errors on the set of training examples is guaranteed. The generalization capability was tested on a set of 10 novel presentations of each object. <<ETX>>
DRAFT : October 8 , 2017 1 Heterogeneous Climate Preferences of Migrants : Boiling Phoenix or Shivering Boston ?

This paper examines the influence of origin climate on migrants’ destination choice. Starting from a McFadden residential location choice model, we make use of a novel dataset of international migration from Mexico to the US from 1970 to 2010, controlling for economic and demographic destination characteristics. The unique dataset provides geographic information on both origin and destination locations, thereby enabling the estimation of a location choice model allowing for heterogeneous climate preferences determined by origin climate. We find Mexican emigrants to prefer migrating to areas with similar average temperatures as well as warmer summers compared to their home climate. If splitting the sample into migrants from different climatic origin areas in Mexico, we find the temperature parameters to be statistically different between the two sub-samples. Mexican immigrants from colder regions have stronger preferences over destination climate. In a fully interactive model of climate variables, the interaction term of mean temperatures is statistically significant. The findings suggest that migrant’s climate preferences differ by origin climate, thus providing evidence for the existence of heterogeneous climate preferences. While the effect size is small compared to economic factors, climate change will not only alter the attractiveness of locations to incoming migrants but also affect climate preferences by changing the origin climate. Furthermore, our findings suggest that exposure to extreme cold or heat reduces the amenity value of moderate climate. Consequently, locations currently perceived as less attractive might become more interesting in the future as the climate in origin communities deteriorates. ∗a.schwarz@sussex.ac. uk †This research was generously funded by the EU-COMPLEX project. We are grateful to Richard S. J. Tol, Alexander Moradi, Hector Elias Gutierrez Rufrancos, Ani Siwal, Tiziano Arduini. We thank the participants of the University of Sussex Economics PhD research seminars, as well as the 2015 SITEIDEAs conference. DRAFT: October 8, 2017 2
DESIGN OF STANDARD AND CUSTOM PERIPHERAL USING NIOS II PROCESSOR 1

Today, Field programmable gate arrays (FPGA) play a very vital role in realizing embedded systems which are used in the area of defence systems, bioinformatics, cryptography, and many more. The recent developments of soft-core processors like NIOS II have redefined the use of FPGA in embedded systems. In this project processing and realizing general purpose embedded system using soft-core Nios-II processor on Altera Cyclone II FPGA. Here, we are developing the test logic for every component in the system to debug the system efficiently and the user-logic will decide the application whose realization is done using Nios II IDE. KeywordsFPGA, Nios II Processor, Sopc Builder, Quartus II
A database and functional annotation of NF-κB target genes

Backgrounds: The previous studies show that the transcription factor NF-κB always be induced by many inducers, and can regulate the expressions of many genes. The aim of the present study is to explore the database and functional annotation of NF-κB target genes. Methods: In this study, we manually collected the most complete listing of all NF-κB target genes identified to date, including the NF-κB microRNA target genes and built the database of NF-κB target genes with the detailed information of each target gene and annotated it by DAVID tools. Results: The NF-κB target genes database was established (http://tfdb.seu.edu.cn/nfkb/). The collected data confirmed that NF-κB maintains multitudinous biological functions and possesses the considerable complexity and diversity in regulation the expression of corresponding target genes set. The data showed that the NF-κB was a central regulator of the stress response, immune response and cellular metabolic processes. NF-κB involved in bone disease, immunological disease and cardiovascular disease, various cancers and nervous disease. NF-κB can modulate the expression activity of other transcriptional factors. Inhibition of IKK and IκBα phosphorylation, the decrease of nuclear translocation of p65 and the reduction of intracellular glutathione level determined the up-regulation or down-regulation of expression of NF-κB target genes. Conclusion: Through the analysis of 1667 distinct NF-κB target genes, it can further perfect the NF-κB signaling pathways and provide the data for building the gene expression regulatory networks and the clinical targets of diagnosis and treatment.
Rainfall estimation over the Taiwan Island from TRMM / TMI data

The Taiwan is a mountainous island, recent overdevelopment of hill slope has made the water and soil conservation more difficult. In the advent of storm’s heavy rainfall, mudslide is likely to strike the upstream mountainous regions, leading to serious mud accumulation or flood in rivers and reservoirs or even water and soil loss against national economy and national security. Therefore, it is the focus for the meteorology community to improve weather forecasting technology for storm’s heavy rainfall and minimize or prevent the loss from catastrophic rainfall in an efficient way. With rapid development of satellite technology in recent years, satellite microwave data has become a major tool for rainfall research on an international basis. This is because meteorological satellite is a simplest method to monitor and track effectively all catastrophic rainfall systems from surrounding sea areas. And, this helps to understand the process and strength of rainfall systems, thereby providing all information required for flood prevention. This laboratory once applied satellite microwave image data to study rainfall over the ocean and obtain good results (Chen and Li, 2000; Chen and Li, 2002; Hu, 2002; Chen, 2004). To have a further observation and deeper understanding of rainfal system’s development over Taiwan land, microwave image data shall be applied to study the features and retrieval of land rainfall. Now, it is the first time that Scattering Index Method is applied to research of rainfall over Taiwan land. It is expected to set up a mechanism for monitoring and tracking catastrophic rainfall system. This paper aimed to study rainfall retrieval over Taiwan land using Scattering Index Method developed by Grody (1991), with the entire flow process shown in Fig. 1. The steps include: data collection and processing, land rainfall retrieval and verification of retrieval results. Firstly, the cases of TRMM/TMI (Tropical Rainfall Measuring Mission/TRMM Microwave Imager) passing through Taiwan land and the corresponding data of land rainfall observation stations (ARMTS, rain gauge data of Automatic Rainfall and Meteorological Telemetry System measurements of Taiwan) were collected and interpolated into the grid points in the region of Taiwan. Infrared (IR) satellite cloud figures were used to determine cloud-free cases in Taiwan (representing non-scattering atmospheric structure), while the data in this time interval were applied for analysis of surface characteristics. By substituting the data into Scattering Index Method (SI) developed by Grody (1991), the equation was shown in Eq (1). Through simulation of high-frequency Tb85V by low-frequency Tb19V and Tb22V channels, coefficients A1, A2, A3 and A4 could be obtained from SI equation via linear regression, thereby setting up a scattering index equation (SIL) of Taiwan land.
Design of an automated magnetic wheeled robot for crack inspection of overhead cranes by using NDT & GMR sensor

Overhead crane plays a vital role in almost all industries, and work under many harsh environmental conditions. Repetitive heavy loading and harsh environmental situations cause structural failure of overhead crane bridges. Corrosion is one of the major causes of structural failures. Regular and effective monitoring can contribute to minimizing the structural failures. This research work proposed an automated robot MILA3D for the inspection of steel structures, particularly for overhead crane bridges. MILA3D can perform crack detection and corrosion detection by using NDT technique and 16 channel GMR (Giant Magneto-Resistance) sensor array. Designed magnetic wheel not only provides adhesion forces to climb on a vertical surface but also contribute to the detection of defects & flaws into steel surface by emitting a magnetic field. The MILA3D robot have some special features like compact & flexible structure, fully autonomous, collects data and send back to the remote location station for real-time monitoring as well as also enables to create a 3D map of the inspection area. The proposed method provides a noticeable contribution in deprecating the limitations of recent overhead crane bridges inspection methods by providing a cost economical and effective solution by using the GMR sensor and
Bus Voltage Regulation of DC Home Grid with PV-Battery-Ultracap

Recently, there is an increasing interest towards an effective power management system incorporating grid, load, storage, and renewable sources in DC bus based systems [1], [2]. One indicating benchmark to measure the performance of the power management is the regulation of the DC bus voltage. In this paper, a DC home grid with PV-battery-ultracap is modeled. The modeling is developed using simplified circuits rather than using switching circuits of the converters. Then, an improved bus voltage regulation using feedforward variables is proposed. The validity of the approach is verified by simulation results.