Miracle-dz/UniFAR-FTUs huggingface dataset:
Computer analysis of transient voltages in large grounding systems

A computer model for transient analysis of a network of buried and above ground conductors is presented. The model is based on the electromagnetic field theory approach and the modified image theory. Validation of the model is achieved by comparison with field measurements. The model is applied for computation of transient voltages to remote ground of large grounding grid conductors. Also computation of longitudinal and leakage currents, transient impedance, electromagnetic fields, and transient induced voltages is possible. This model is aimed to help in EMC and lightning protection studies that involve electrical and electronic systems connected to grounding systems.
Process development: a theoretical framework

There have already been a number of review articles that focus on product development, but none on process development. Process development is technically difficult, time-critical and competitively important, thus worth being explored as a distinct unit of analysis. This paper develops a theoretical framework to fill this gap in knowledge based on a comprehensive literature review. Five objectives for process development are summarised to align with the goal of product realisation, and 12 enablers (including intra-functional enablers, inter-functional enablers, and learning enablers) are identified and discussed. The authors first locate process development in the product realisation process (including product design, process design, process execution and process improvement) and draw necessary parallel factors between product design and process design as a foundation. Then the attributes of all relevant literature are organised and general principles for successful performance of development projects are used to infer the enablers. The developed framework offers opportunities to further verify the new enablers and theoretical links in future studies. One implication is that process development should be viewed as a strategic function for competitive edge and as such specific measures should be set to create an environment that is conducive to successful performance.
Optimisation, design and characterisation of a piezoelectric micro suspension

A piezoelectric micro active suspension device has been developed for the application of active isolation of sensitive electronic devices such as frequency generators or inertial sensors. The developed strategy is based on a classical skyhook active damper but adapted and optimised to allow robust implementation onto an adaptive microelectromechanical systems (MEMS). The micro suspension is a silicon beam structure etched in a silicon on insulator (SOI) wafer and is equipped with a pair of piezoelectric transducers obtained from a lead zirconate titanante thin film sandwiched between pairs of electrodes. High performance transducers allow application of the active isolation strategy and demonstrate the possibility to implement skyhook damping with low-voltage control level.
Dinamika Masyarakat Tradisional Kampung Naga di Kabupaten Tasikmalaya

The dynamics of the Kampung Naga at District Tasikmalaya community is controlled by the custom. Generally, the aim of this research is to analyze the traditional dynamic community of Kampung Naga, especially to: (1) identify the custom of Kampung Naga community; (2) identify the dynamic of the society; and (3) recommend employing society strategy. The research design is using qualitative approach with descriptive method. Researcher as human instrument with the aid of interview guide, observation guide and field note. The subject of this research consists of 5 respondents. The data validity is through triangulation, probing, peer debriefing, and members check. The data analyze through data display, data reduction, verification and conclusion. The result of the research are: (1) the custom consists of testament tradition, mandating, prohibition and consequence; (2) the society dynamic consists of technology changing, occupation, income and life facility ownership; and (3) employing strategy is recommended through adaptive innovation concerning the custom.
Application of artificial neural network in bridge deck condition rating

Currently bridges are evaluated either a visual inspection process or structural analysis. When bridge evaluation is conducted by visual inspection a subjective rating is assigned to the bridge components with analytical evaluation. The rating is computed based on the load applied and the resistance capacity of bridge component visual inspection is subjective and depends primarily on the experience of the inspector in assigning the rating. analytical rating unable to represent the condition of bridge component since the rating is computed based on the load and bridge capacity only. If a relationship between analytical rating and subjective rating can be found. The estimation of bridges condition can be made only by determining the bridge analytical rating. Several attempts to correlate both methods using the conventional statistical analyses. As well as fuzzy logic have not been very succesful in providing the relationship between those rating methods. However, an attempt to utilize Artificial Neural Network (ANN) to correlate the analytical rating for railroad and bridge parameter with bridge subjective rating in Chicago has produced succesful results. This study describes the application of ANN in developing the correlation between load rating and subjective rating as well as bridge parameter for highway bridges. The subjective rating in this study is limited to deck rating only. The data provided by California Department of Transportation (CALTRAN) is utilized for training and testing session. The results obtained in the first part showed that additional variables are needed along with load rating variable to provide acceptable prediction performance. After several rounds of improvement process the best reults obtained exhibits 77% of the data used for testing are predicted within the acceptable range. Generally, this study showed that the ANN has a potential to be used to predict the subjective rating if the proper input variables are applied.
Sustainable Agricultural Groundwater Management for New Reclaimed Areas in Farafra Oasis, Western Desert of Egypt

Sustainable groundwater management is an important practice of water resources engineering, especially, in case of deserts and oases where there is no source of surface water and precipitation rarely occurs. The importance increases when the only source of groundwater is a nonrenewable aquifer. This is the case of new reclaimed areas in Farafra Oasis, Western Desert of Egypt. The only source of irrigation water is groundwater extracted from the nonrenewable Nubian Sandstone Aquifer (NSA). There is a great agricultural development in Farafra Oasis as a part of the 1.5 million feddan mega project. Agricultural development, for new areas, is a must for Egypt to fulfil the increasing food demand accompanied with the increasing population growth rate. However, this development has to consider the sustainability of groundwater usage along with the social, economic, and national security aspects. Groundwater extraction rate from NSA has increased. As it is a nonrenewable aquifer, there is no groundwater recharge. Consequently, the groundwater potentiometric level (GPL) decreases with time. The traditional sustainability concept of safe yield or discharge equals recharge is not applicable on such cases. The Ministry of Water Resources and Irrigation (MWRI) of Egypt set the groundwater sustainability criteria for groundwater-dependent new reclaimed areas in Farafra Oasis, Western Desert of Egypt. Both duration and economic lifting depth, have been considered. This paper presents groundwater sustainability assessment for extraction rates, Qwell = -1000, -2000, -3000, -4000, and -5000 m3 /d, to obtain the most beneficial sustainable extraction rate according to the MWRI sustainability criteria. A new groundwater-dependent reclaimed area of 10,000 feddan in Sahl Baraka, Farafra oasis, was taken as a case study area. GIS functions were used to obtain the values of unknown data and develop the initial groundwater potentiometric map. MODFLOW was used to construct a numerical model for groundwater extraction rate simulation for the case study area. This model was calibrated and used to obtain the depression cone drawdown (DCD) associated with different extraction rates. All NSA regional drawdown rates at Farafra oasis were considered. Benefit –Deficit analysis for duration and economic lifting depth criteria are presented and show that the extraction rate of Qwell = -3000 m3 /d is the most beneficial sustainable extraction rate according to the MWRI adopted sustainability criteria
An Overview Current Application of Artificial Neural Network in Concrete

This paper presents the overview of aArtificial Neural Network (ANN) in the scope of civil engineering application. ANN is one of the artificial intelligence (AI) applications which are currently one of the effective methods used by engineers and researchers to solve technical problems in many scopes of engineering field. One of the explicit criteria of ANN is the ability of the network to deal with the incomplete data and have the capability of learning from experience. This network is also able to adapt to new and changing situation or environment.
Arc-Fault Detection Method Research Based on Wavelet Transformation

The arc-fault is the main reason that cause electric fires. The technology of arc-fault circuit interrupters (AFCI) is the new circuit protection technology and it could avoid arc-fault causing fire effectively. The appearance of arc-fault can not be predicted. The traditional time domain or frequency domain analysis method for arc-fault signal processing is not ideal because it’s inaccurate and not in time. This paper bases on characteristics of arc-fault signals and analyzes the series connection arc-fault signal by Daubechies wavelet transform in 4 orders. As a result, it can provide the characteristics of arc-fault and detect arc-fault effectively and timely. This method is confirmed reliability by the simulation result and provides the theoretical basis of the development of AFCI.
A new family of isolated zero-voltage-switched converters

A family of isolated, zero-voltage-switched converters which utilizes the magnetizing inductance of the transformer to achieve zero voltage turn-on of the primary switches is proposed. In addition, by employing saturable inductors on the secondary side, soft turn-off of the output rectifiers is obtained with a minimum circulating energy flowing through the converter. The proposed converters can operate either with a variable or constant switching frequency. A complete DC analysis and design guidelines for the half-bridge topology are described, and the performance of a 100 W experimental converter is presented. <<ETX>>
An Improved SNR-Based Cooperative Spectrum Sensing in Cognitive Radio Networks

Spectrum sensing is a new technology in cognitive radio network, whose main purpose is to design an optimal detector. This paper studies a soft linear cooperative spectrum sensing method. We propose a SNR-based algorithm for weight setting at fusion center to improve the detector performance. Simulation results shows that the SNR-based method has better detector performance than the others.
Multiple line-segments regression for stock prices and long-range forecasting system by neural network

This note proposes a forecasting system for stock prices by neural network with reference to multiple line-segments regression after examining simulation results of our modified forecasting system. Our objective is to construct middle and long time range forecasting system, we consider the week summary data instead of the ending-value of one day. Thus we modify our forecasting system replacing the ending-values of stock prices per day by the week summary data with the week average which are inputs of our neural network. Usual back-propagation method is used for the learning. After the learning, the associative memory of our neural network gives forecasting values for stock prices with their time unit to be one week. Unfortunately, this modified system does not yield satisfactory forecasting values in our simulation study. Hence, instead of forecasting stock prices as an output of our neural network, we set the tangent and the length of the multiple line-segments regression as outputs of our new neural network. Usual back-propagation method is used for the learning. After the learning, the associative memory of our new neural network gives forecasting values for stock prices by the collection of tangents and lengths of the multiple line-segment regression. Several simulation results are also discussed.
40 GHz optical clock extraction from 160 Gbit/s data signals using PLL-based clock recovery

In summary, we have demonstrated 40 GHz optical clock extraction from 160 Gbit/s input data signals by introducing an optical multiplexer to an optical phase locked loop (PLL) based on a semiconductor laser amplifier in a loop mirror (SLALOM). We obtained RMS timing jitter of less than 0.3 ps for a wide range of data input powers. We also investigated 80 GHz and 160 GHz clock extraction and showed that the SLALOM operates as phase comparator for clock signals up to 160 GHz. Thus this clock recovery can also be applied for 160 Gbit/s 3R-regeneration.
Soft x-ray projection system for robust roundness measurements

When integrating optic measurement systems into or next to the production line for part inspection and control of the production process requirements for measurement devices like the measurement time and the measurement uncertainty have to be expanded by a requirement for the robustness of the measurement system. A novel optic measurement system will be presented which is designed for the robust measurement of roundness of shafts next to the production line which is not influenced by residues of the manufacturing process, e.g. cooling lubricant. The measurement system is based on projecting the shadow of a shaft onto a detector and measuring the cast edges to derive the roundness of the shaft. The main parts of the measuring system consist of a soft X-ray micro focus tube, a highly precise angle measurement system and a CCD-detector. In contrast to roundness measurement instruments which are based on visible light and a telecentric optical path, new algorithms to calibrate the soft X-ray measurement instrument are being developed because of the divergent ray distribution of the soft X-rays. This paper will introduce the design and the main elements of the novel soft X-ray projection system as well as algorithms needed to conduct the roundness measurements. An estimation of accuracy and precision for small diameter shafts is presented as well as possibilities to achieve the invariance up to residues of the manufacturing process.
Performance Prediction of Pre-Corroded Aluminum Alloy Using Genetic Algorithm-Neural Network and Fuzzy Neural Network

Genetic algorithm is introduced in the study of network authority values of BP neural network, and a GA-NN algorithm is established. Based on this genetic algorithm-neural network method, a predictive model for fatigue performances of the pre-corroded aluminum alloys under a varied corrosion environmental spectrum was developed by means of training from the testing dada. At the same time, a fuzzy-neural network method is established for the same purpose. The results indicate that genetic algorithm-neural network and fuzzy-neural network can both be employed to predict the underlying fatigue performances of the pre-corroded aluminum alloy precisely.
Anforderungs- und Testfall-Codesign

Durch den verstärkten Einsatz von Software in mechatronischen Systemen und die hohen Anforderungen an die Qualität derselben, müssen Entwicklungsprozesse bei der mechatronischen Produkt- beziehungsweise Geräteentwicklung angepasst werden, um dem interdisziplinären Charakter in der Entwicklung zu entsprechen. In diesem Beitrag wird eine Untersuchung von aktuellen Vorgehensweisen und den sich daraus ableitenden Herausforderungen an das Anforderungs- und Testmanagement vorgestellt. Ferner wird ein Konzept zur integrierten Modellierung und Spezifikation von Anforderungen und Testfällen vorgestellt. Fazit: Eine Formalisierung von Anforderungen bis hin zu semi-formalen Anforderungen ermöglicht bei der Spezifikation eine automatische Generierung von Testfällen.
New Algorithms for Predicting Conformational Polymorphism and Inferring Direct Couplings for Side Chains of Proteins

Protein crystals populate diverse conformational ensembles. Despite much evidence that there is widespread conformational polymorphism in protein side chains, most of the xray crystallography data are modelled by single conformations in the Protein Data Bank. The ability to extract or to predict these conformational polymorphisms is of crucial importance, as it facilitates deeper understanding of protein dynamics and functionality. This dissertation describes a computational strategy capable of predicting side-chain polymorphisms. The applied approach extends a particular class of algorithms for side-chain prediction by modelling the side-chain dihedral angles more appropriately as continuous rather than discrete variables. Employing a new inferential technique known as particle belief propagation (PBP), we predict residue-specific distributions that encode information about side-chain polymorphisms. The predicted polymorphisms are in relatively close agreement with results from a state-of-the-art approach based on x-ray crystallography data. This approach characterizes the conformational polymorphisms of side chains using electron density information, and has successfully discovered previously unmodelled conformations. Furthermore, it is known that coupled fluctuations and concerted motions of residues can reveal pathways of communication used for information propagation in a molecule and hence, can help in understanding the “allostery” phenomenon in proteins. In order to characterize the coupled motions, most existing methods infer structural dependencies among a protein’s residues. However, recent studies have highlighted the role of coupled side-chain fluctuations alone in the allosteric behaviour of proteins, in contrast to a common belief that the backbone motions play the main role in allostery. These studies and the aforementioned recent discoveries about prevalent alternate side-chain conformations (conformational polymorphism) accentuate the need to devise new computational approaches that acknowledge side chains’ roles. As well, these approaches must consider the polymorphic nature of the side chains, and incorporate effects of this phenomenon (polymorphism) in the study of information transmission and functional interactions of residues in a molecule. Such frameworks can provide a more accurate understanding of the allosteric behaviour. Hence, as a topic related to the conformational polymorphism, this dissertation addresses the problem of inferring directly coupled side chains, as well. First, we present a novel approach to generate an ensemble of conformations and an efficient computational method to extract direct couplings of side chains in allosteric proteins. These direct couplings are used to provide sparse network representations of the coupled side chains. The framework is based on a fairly new statistical method, named graphical lasso (GLASSO),
ADVANCED CHASSIS CONTROL SYSTEMS FOR VEHICLE HANDLING AND ACTIVE SAFETY

SUMMARY In this paper chassis controls for vehicle handling and active safety have been reviewed. In particular, we have observed the effectiveness and limit of 4WS and DYC. It is pointed out that DYC is more effective in vehicle motion with larger side-slip and/or higher lateral acceleration and taking the nonlinearity of tire and vehicle dynamics into consideration is essential for introducing the control law for the chassis controls and their integration/coordination. We wish to emphasize that there is a need to further propose control laws based on deeper observation and understanding on the tire and vehicle dynamics.
Multistage PV conversion using nanostructured multi-interface Si components: experimental evidence

Completing one-step PV conversion by additional new low-energy mechanisms is one of the most important challenges of modern photovoltaics. Si is a basic PV material which is not efficient enough to convert the light into electricity in its bulk or thin-film form because of its indirect bandgap. Progress in conversion efficiency requires breakthroughs. One way has been indicated by low-dimensional or nanostructured Si materials such as, for example, nanoscale Si-layered systems combined with an active interface with its crystalline defects. We have demonstrated low-energy carrier multiplication experimentally under attenuated solar excitation in nanostructured Si in both the optical and electronic approaches. This paper gives results, among others, concerning: 1) a simulation based on previously determined parameters and 2) experiments using a reference cell. In the simulation, the nanolayer thicknesses are 5 nm for a-Si (estimation based on TEM images) and 20 nm for (estimation based on EELS data). To be simple and directly useful in the future development, the project has been limited to comparative measurements of the short-circuit currents of our test cells relative to the new generation photovoltaics. The ratio of short-circuit currents shows steps which allow estimating a characteristic energy Eδ = 0.274 eV, previously determined by us from spectral response and modeling. The effect is particularly visible under weak incident beams. Thanks to these investigations, the fabrication of a very highly efficient Si solar cell becomes more realistic. The results suggest scientific and technological prospectives.
Efficiency of TCP-friendly window adjustment strategies in wired/wireless networks

TCP(a,b) protocols parameterize the congestion window increase value and decrease ratio , motivated by the QoS requirements of multimedia applications for smooth rate adjustments. Based on a projection of the expected throughput of standard TCP(1,.5), modified versions of the protocol have been designed to generate smoother traffic patterns and to maintain a friendly behavior. In this paper, we study the design assumptions of TCP(a,b) and we discuss the impact of equation-based modulation of a and b on application efficiency. We confirm experimentally that, in general, smoothness and responsiveness constitute a tradeoff; however, we uncover undesirable dynamics of the protocols when the network is heterogeneous (wired/wireless) or the flow characteristics do not follow a prescribed and static behavior. For example, we show that smooth backward adjustments confine the protocol's capability to exploit resources that become available rapidly after a handoff in mobile network, and embarrass the fair and efficient growth of incoming flows. Furthermore, we show that in the context of wireless networks with high error rate, a low a dictates a conservative behavior that degrades the protocol performance with both best-effort and real-time applications; and in the context of high contention of heterogeneous flows, a low a does not contribute to efficiency and friendliness.