Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards an ontology framework for the integrated design of modular assembly systems

Next generation manufacturing companies have to become highly responsive in order to succeed in an ever more rapidly changing global market. The ability to effectively develop and adapt their assembly facilities (systems) to changing requirements on demand plays a crucial role in achieving high responsiveness since the assembly process has to deal with the full inherent complexity of increasingly mass-customised products. This work was motivated by the current lack of a holistic assembly system design theory that would enable design environments to address the need for rapid system development and adaptation. The challenge is to create a common environment where domain experts can effectively collaborate while taking advantage of the best practices of their diverse domains. This thesis investigates how a domain ontology can help to overcome those challenges. The approach is taking advantage of the higher levels of standardisation inherent in the modular assembly system paradigm which is considered to be one of the fundamental enabling factors to achieve a high level of adaptation. A new ontology framework has been developed to support the design and adaptation of modular assembly systems (ONTOMAS). The ONTOMAS framework is based on engineering ontology principles structuring the domain using formalisms for aggregation, topology, taxonomies, and system theory principles. A number of design patterns have been identified and formalised to support key design decision-making tasks during the design of modular assembly systems. Furthermore, the function-behaviour-structure paradigm has been applied to capture the characteristics of modular assembly equipment at different levels of abstraction that reflect the specific needs of the engineering design process. The proposed ONTOMAS framework provides a sound foundation for computer based support tools to reduce the assembly system design effort and time while maintaining a high level of quality. An integrated design framework for the requirements driven specification of assembly processes and configuration of modular assembly system has been developed. The design approach applies the new formalisms of ONTOMAS to support the design decision-making activities. The developed ONTOMAS framework has been applied in several industrial and synthetic use cases to verify its applicability and appropriateness. Furthermore, the new ontology and design framework have been used as foundation for the development of a prototype collaborative design environment which allows different domain experts to participate in the design of modular assembly systems.
Comparison of elegance of Japanese and European jackets

Purpose – The purpose of this paper is to investigate factors affecting the impression of elegance of a jacket’s appearance. Design/methodology/approach – A questionnaire survey on the impression of jacket appearance was conducted using images of jackets of Japanese and European brands. A paired comparison and sensory test were carried out for four Japanese and European jackets. To explain different jacket appearances, the jacket patterns and silhouettes were investigated from an engineering point of view. Findings – Most Japanese subjects responded that European jackets in images were more elegant and characteristic of European style. In a comparison of jacket silhouettes, Jacket 1 (European brand) was evaluated as the most elegant. The waist and bust parts of Jacket 1 had three-dimensional shape whereas the Japanese jackets had planar and rectilinear shapes. This was due to the difference in the waist darts and curved lines in the patterns. Jacket appearance in terms of elegance is thus mainly affected .
A parallel multi-objective optimization procedure for protein structure prediction

Proteins are chains of amino acids whose sequence determines its 3D structure after a folding process. As the 3D structure of a protein exclusively determines its functionality (transport and transduction of biological signals, the possible enzymatic activity of some proteins, etc.), there is a high interest in the determination of the structure of any given proteins. Experimental methods such as X-ray crystallography and nuclear magnetic resonance (NMR) allow the determination of the 3D structure of a protein although they are complex and expensive. Thus, only about the 2% of the known proteins has known structures currently. The so called, protein structure prediction (PSP) problem is the approach to find the 3D structures of proteins by using computers. This work proposes an approach to the protein structure prediction (PSP) problem: PITAGORAS-PSP (Parallel Implemented procedure with Template information, Ab initio Global Optimization, and Rotamer Analysis and Statistics for Protein Structure Prediction). This way, taking into account its name, our procedure represents a hybrid approach that takes advantage of previous knowledge about the known protein structures to improve the effectiveness of an ab initio procedure for the PSP problem. Moreover, the procedure benefits from a parallel and distributed implementation of a multi-objective evolutionary approach that allows faster and wider exploration of the conformation space. The experimental results obtained from the present implementation of our procedure show improvements with respect to previously proposed procedures in the proteins selected as benchmarks from the CASP set (up to 28% of RMSD improvement with respect to one of the best procedures known at this moment in some proteins). We also present a new method to extract better torsion angles from protein structures, it can be used to build an improved data base for torsion angles that aids in the knowledge extraction from the known structures. Our hybrid approach can be used as the main method to predict protein structures, but it can be also used to refine predictions of other methods, due to its capabilities to take advantage of results from other approaches.
Visual Odometry Based on K-Nearest Neighbor Matching and Robust Motion Estimation

This work presents a K-NN feature matching for monocular visual odometry (VO) system that can perform in realtime. By feeding a monocular video sequence, the proposed method continuously determines the instantaneous 6-DOF camera pose. After obtaining binary descriptors for image features, we adopt k-nearest neighbor algorithm with Hamming distance calculation as a novel method for feature matching. Then, with our designed robust motion estimation, the system can operate in real-time scenario for a large-scale outdoor environment without utilizing GPU or reducing input image size. The experimental result shows a successfully built trajectory path without non-linear optimization and loop closure for a challenging video sequences of KITTI dataset. Moreover, the comparison in terms of root mean square error with ORB-SLAM and Semidirect Visual Odometry (SVO) are also presented.
A novel synchronous rectifiers based ZVS-PWM DC-DC power converter with extended soft-switching operation range

In this paper, a full bridge edge-resonant zero voltage mode based soft-switching PWM DC-DC power converter with a high frequency transformer link is presented. Active power MOSFETs operating as synchronous rectifier are implemented in the rectifier stage to reduce conduction losses and also to extend ZVS commutation area of the primary side power MOSFETs from rated to zero load without requirement of a magnetizing current. The operation of this phase-shift PWM controlled converter is described in comparison with conventional ZVS phase-shifted PWM DC-DC power converter with diodes rectifier. Moreover, the experimental results of the switching power losses analysis are discussed in this paper. The practical effectiveness of the power DC-DC power converter treated here is proved from a practical point of view by using 2.5 kW, 32 kHz breadboard circuit. An actual efficiency 97% of this converter is measured in the experiment.
Cryptosporidium parvum GP60 subtypes present in diarrheic dairy calves of two biogeographical regions of Chile

Background Cryptosporidium is an apicomplexan zoonotic pathogen primary causing diarrhea in vertebrate hosts notably bovines and humans. Here, we characterized Cryptosporidium isolates by using the GP60 gene fragment of C. parvum to observe the dynamics of cryptosporidiosis transmission in dairy calves from two distant biogeographical regions of Chile (Metropolitan and Los Rios Regions). We collected 72 fecal samples from diarrheic calves screening the parasite carried out microscopy of an acid-fast staining smear and molecular characterization employing PCR to directly detect the Sanger GP60 C. parvum subtype and simultaneously in one selected sample the NGS profile of the GP60 same gene fragment to determine same and/or others Cryptosporidium subtypes Results The IIaA15G2R1 subtype was present in the 100% of the bovine fecal samples studied from Los Rios Region. Along with this same subtype, another two were observed in the Metropolitan Region, IIaA17G2R1 and IIaA17G4R1. The NGS analysis of a single selected GP60 PCR amplicon of one selected sample of our study showed similarly the Sanger sequencing determined subtype, the IIaA17G4R1 in 90% of readable sequences observed. By using this approach another multiple low frequency IIa subtypes of C. parvum were observed confirming that in an infected host multiple subtypes of the parasite can be present. Conclusions Cryptosporidiosis in these dairy farms calves in Chile is produced by C. parvum limited number of subtypes, being IIaA15G2R1 the most frequent. The IIa subtype family is considered prevalent in calves in South America. Subtypes IIaA17G2R1 and IIaA17G4R1 had been worldwide distribution. As all C. parvum subtypes observed in calves in Chile were isolated from diarrheic animals, so, it can be possible to relate its presence with the pathogenic role in the bovine host and with a potential digestive disease risk for humans.
Scene Recognition Method by Bag of Objects Based on Object Detector

The scene recognition is one of the most important tasks for estimating ambient attributes from the image data. The ambient attributes are scene traits for specifying the meanings of human activities. We consider that the estimation of ambient attributes is required for understanding human activities in various scenes. Thus this paper proposes a novel method of the scene recognition by the object detector. The proposed method estimates a scene using a histogram of objects, which is called Bag of Objects, based on the result of object detection. To evaluate the proposed method, a simulation experiment has been done with a lot of image data we collected from the web. As the result, we show that the average of scene recognition accuracy is 0.58 for 26 scene categories.
A Cross-Cultural Comparison of Younger and Older Adults’ Simulated Highway Driving Performance Under Single and Dual Task Conditions

Driving is a complex psychomotor task that is often interrupted by secondary activities that divert attention away from the roadway. The risk of inattentive driving is known vary with age. The degree to which culture impacts these changes is less established. To study the impact of age and culture on drivers’ capacity to manage dual task demands, we developed a parallel driving simulation in the US and Korea. We assessed the performance of 135 drivers divided into two age groups, younger (20–29) and older (60-69). Both age and cultural group differences in basic highway driving performance measures were observed. However, the relative impact of the dual task demands on driving performance was largely consistent across cultures.
Design of Low Power P-Gated Schmitt Trigger SRAM in 65nm CMOS Technology

The trend of faster microprocessors at lower supply voltages demanded the need for a stable and less power consuming SRAM. This study answered these issues by implementing a 12T Power Gated Schmitt Trigger SRAM implemented in Full Custom 65nm CMOS technology. The read and write stability was accomplished without extra peripheral circuitry with more control signals per cell. The design schematic, layout, and results were obtained using SYNOPSYS Custom Designer. The Full Custom design resulted to 1.25 sq. mm. chip area, 2.43 mW power consumption, and 31.45 ns slack time. Results also show that most power consumption from the Full Custom design come from the banking and row decoders. The memory array has a 16-bit addressable word line, 512 byte memory capacity, simulated with 25–200 MHz operating frequency and under 1V supply voltage.
A Dual-Band Microstrip fed Monopole Quasi - Yagi Antenna

In this paper, a dual-band microstrip fed monopole and quasi-Yagi antenna is presented for using in dual-band Wiress Local Area Network (WLAN) access point. The propose antenna consists of a printed circular monopole etched with a rectangular slot antenna as the driver fed by a microstrip transmission line, five metal patch as the directors and one reflector. The final antenna design presents measured bandwidths Of $\pmb{2.09-2.07\ GH{z}}$ and 4.71-6.05 GHz which cover completely the two bands of WLAN. Meanwhile good end-fire radiation patterns and relatively high gain of 6.2 and 6.5dBi are also achieved in the operating bandwidth.
Media independent interface: concepts and guidelines

In the course of their efforts to upgrade the operating speed of Ethernet from 10 Mbps to 100 Mbps, the members of the IEEE 802.3~ 1OOBASE-T Task Force recognized that it was vital to preserve the media independent nature of Ethernet, but they also recognized that the mechanism by which this was accomplished at 10 Mbps was not up to the task. Thus, they set out to define a new Media Independent Interface (MII) which would allow the development of a family of specifications for operation over various types of network media.
Object Design: Roles, Responsibilities, and Collaborations

From the Publisher: If you create software using object-oriented languages and tools, then Responsibility-Driven Design has likely influenced your work. For over ten years Responsibility-Driven Design methodology has been the standard bearer of the behavioral approach to designing object-oriented software. Object Design: Roles, Responsibilities, and Collaborations focuses on the practice of designing objects as integral members of a community where each object has specific roles and responsibilities. The authors present the latest practices and techniques of Responsibility-Driven Design and show how you can apply them as you develop modern object-based applications. Working within this conceptual framework, Rebecca Wirfs-Brock and Alan McKean present how user requirements, system architecture, and design patterns all contribute to the design of an effective object model. They introduce a rich vocabulary that designers can use to discuss aspects of their designs, discuss design trade-offs, and offer practical guidelines for enhancing the reliability and flexibility of applications. In addition, case studies and real-world examples demonstrate how the principles and techniques of Responsibility-Driven Design apply to real-world software designs. You'll find coverage of such topics as: Strategies for selecting and rejecting candidate objects in an emerging design model Object role stereotypes and how to identify objects' behaviors How to characterize objects using role stereotypes Allocating responsibilities to appropriate objects Developing a collaboration model Strategies for designing application controlcenters Documenting and describing a design, focusing on use cases, design conversations, and annotations Strategies for enhancing reliability, including handling exceptions and recovering from errors How to characterize software variations and design to support them for greater flexibility How to categorize and treat various kinds of design problems As all experienced designers know, software design is part art and inspiration and part consistent effort and solid technique. Object Design: Roles, Responsibilities, and Collaborations will help all software designersfrom students to seasoned professionalsdevelop both the concrete reasoning skills and the design expertise necessary to produce responsible software designs.
A Leading Indicator for the Dutch Economy - Methodological and Empirical Revision of the Cpb System

Since 1990, CPB Netherlands Bureau for Economic Policy Analysis (CPB) has used a leading indicator in preparing short-term forecasts for the Dutch economy. This paper describes some recent methodological innovations as well as the current structure and empirical results of the revised CPB leading indicator. Special attention has been paid to the role and significance of IFO data. The structure of the CPB leading indicator is tailored to its use as a supplement to model-based projections, and thus has a unique character in several respects. The system of the CPB leading indicator is composed of ten separate composite indicators, seven for expenditure categories (‘demand’) and three for the main production sectors (‘supply’). This system approach has important advantages over the usual structure, in which the basis series are directly linked to a single reference series. The revised system, which uses 25 different basic series, performs quite well in describing the economic cycle of the GDP, in indicating the upturns and downturns, and in telling the story behind the business cycle.
SISTEM TELEMETRI Unmanned Aerial Vehicle (UAV) BERBASIS Inertial Measurement Unit (IMU)

Telemetry is a process used to measure or record of a physical quantity in a location far away from thecentral processing of measurement results. Telemetry systems on unmanned aerial vehicles can provide information such as position, altitude, direction, and status in real time rides themselves during air vehicleis operated.The system consists of hardware and software. Hardware such as the IMU consisting of microcontrollers and sensors. For software consists of ground station systems that receive and process data from the IMU.On the software is equipped with aircraft instrumentation systems.On the test results, the system is able to provide information IMU slope rides, although there is still a noise at the output of each sensor. Instrumentation rides well it works exhibit a vehicle. Tracking can be performed by using a ground station.
Deterministic and Probabilistic Lifecycle Cost Assessment: Applications to Nebraska Bridges

AbstractThe main purpose of this paper is to utilize lifecycle cost analysis (LCCA) as a decision-support tool for three commonly encountered decisions in bridge management: bridge deck overlay decisions, expansion joint replacement decisions, and deck widening versus deck replacement decisions. Bridge management systems aim to assess investment decisions and identify the most cost-effective improvement alternatives to ensure the safety and serviceability of bridge networks. To achieve this goal, the recently developed deterioration models and cost data for highway bridges in the state of Nebraska are utilized in conducting LCCA using deterministic and probabilistic approaches. For deck overlay decisions, silica fume overlay, epoxy polymer overlay, and polyester overlay are compared with bare deck with respect to lifecycle cost and structural life. In expansion joint replacement decisions, two alternatives are compared: relocating abutment expansion joints at the grade beam and replacing abutment expansio.
Detecting P300 Potentials Using Weighted Ensemble Learning

The P300 is an event-related potential seen in electroencephalogram (EEG) waveforms. It is elicited by visual stimuli and used by a brain-computer interface (BCI) known as the P300 speller for character input. However, EEG traces are generally very noisy and can bury the characteristic component in the noise, so various feature extraction methods have been used to extract such features from EEG results. In this paper, we investigate the discriminating P300 potentials using a convolutional neural network (CNN), a widely-used image processing tool. We also consider weighted ensemble learning combining a CNN, stepwise linear discriminant analysis (SWLDA), and a support vector machine (SVM), with the aim of improving the P300 detection accuracy.
Transmitting power control in CDMA cellular systems

This report surveys the research in transmitting power control (TPC) in CDMA cellular systems with an emphasis on the controller design aspect. First of all, the problem is put in the standard framework of the control process. Quantities in TPC are treated as control system components. Most of the available control strategies are then reviewed, sometimes with a system theoretical justification or a stability proof, in the control system set-up. New research directions are pointed out.
Design Analysis of Boiler Header Inspection Robot MK-02

Boiler header and tube are considered as one on the main element in thermal power plant. The boiler header and tube are vulnerable to attack by internal and external corrosion and cracking due to high temperature and high pressure operating condition. The usage of inspection robot integrated with image acquisition and localization simplify the inspection procedure and provides better acquired image or video quality. In this paper, various design analysis in term of load and motor analysis for locomotion and lifting mechanism; and analysis on the critical components of boiler header inspection robot MK-02 are discussed in detailed.
A DC-500 Mb/s burst mode preamplifier for optical data links

A 30-k Omega transimpedance preamplifier IC for DC to 500 Mb/s, optical burst data reception is described. At 200 Mb/s, dynamic range is >or=26 dB, isolated pulse input sensitivity is -29.5 dBm, and pulsewidth distortion <or=1 ns for -5.5 dBm>
Reliability Models for Application Software in Maintenance Phase

With growing demand for zero defects, predicting reliability of software systems is gaining importance. Software reliability models are used to estimate the reliability or the number of latent defects in a software product. Most reliability models to estimate the reliability of software in the literature are based on the development lifecycle stages. However, in the maintenance phase, the software needs to be corrected for errors and to be enhanced for the requests from users. These decrease the reliability of software. Software Reliability Growth Models (SRGMs) have been applied successfully to model software reliability in development phase. The software reliability in maintenance phase exhibits many types of systematic or irregular behaviors. These may include cyclic behavior as well as long-term evolutionary trends. The cyclic behavior may involve multiple periodicities and may be asymmetric in nature. In this paper, SGRM has been adapted to develop a reliability prediction model for the software in maintenance phase. The model is established using maintenance data from a commercial shop floor control system. The model is accepted to be used for resource planning and assuring the quality of the maintenance work to the user.
Unmanned Aerial Vehicle for Human Tracking using Face Recognition System

Maintaining surveillance is no easy job, neither is chasing criminals nor looking for kids or elderly people who are lost in crowded areas. This report aims to propose a viable solution for the aforementioned issue. The proposal encompasses the working of an Unmanned Aerial Vehicle (UAV) with an add-on of face recognition software created by us. The process flow includes inputting the face of the person (either blacklisted or lost) into the software followed by drone run to scan for the inputted faces and providing live alerts when a match is found along with their location. The application of this project can be extended to look humans in closed environments- such as exhibition halls, pattern tracking, and public safety surveillance. UAVs are the future and using them for such applications help reduce the human efforts, thereby making things easier and human error-free.