Miracle-dz/UniFAR-FTUs huggingface dataset:
Relating Random Telegraph Signal Noise in Metal Oxide Semiconductor Transistors to Interface Trap Energy Distribution

In this work, we study random telegraph signal (RTS) noise in metal-oxide-semiconductor field effect transistors when the device is periodically and rapidly cycled between an "on" and an "off" bias state. We derive the effective RTS time constants for this case using Shockley-Read-Hall statistics applied under transient conditions. In this way, we show that the oft-observed reduction in RTS noise under such bias conditions can be explained by a nonuniform (e.g., U-shaped) distribution in energy of interface traps.
Architecture-Aware Packing and CAD Infrastructure for Field-Programmable Gate Arrays

Architecture-Aware Packing and CAD Infrastructure for Field-Programmable Gate Arrays Jason Luu Doctor of Philosophy Graduate Department of Electrical and Computer Engineering University of Toronto 2014 As technology scaling, human creativity, and other factors open new markets for FPGAs, the architectures of such chips must continue to evolve to meet changing demands. However, public domain software tools available to explore future FPGA architectures have not kept pace with advances in the field. Furthermore, these tools often have strong architectural assumptions embedded within the source code itself. Thus, short of major software rewriting, this limits the use of these tools to simple variations of particular architectures. In this thesis, we describe contributions to a large open-source collaborative project, called Verilog-to-Routing (VTR), that relaxes such limitations by providing an extensive software infrastructure for FPGA architecture exploration and CAD research. This infrastructure includes modern benchmarks, sample architecture description files, and a CAD flow that can target a broad space of architectures. We then describe new techniques in the packing stage of the CAD flow, which allow the packer to both target FPGAs with modern architectural features, as well as adjust computational effort based on architectural complexity. Finally, we conduct an architecture experiment on hard adders and carry chains to show the new capabilities of the software infrastructure and to quantitatively answer questions about the actual effectiveness of these classical architectural features.
The Development Status of Underwater Positioning and Navigation Technology Used on Deep Tow System

The methods of the geophysical navigation and acoustic navigation are outlined in this paper. And this paper focuses on the applications of acoustic positioning used on deep tow system. The advantages and disadvantages of three traditional acoustic positioning systems, especially for USBL system, are respectively summarized. Some typical products are listed to illuminate the performance and application of acoustic navigation system. And this paper pointed out the key technical problems to be solved and its development of underwater navigation. Combined acoustic navigation and integrated navigation will become a research hotspot.
Beyond Doubt: The Case Against ‘Not Proven’

Scotland,unusually,has three verdicts in criminal trials:guilty,not guilty,and not proven.The not proven verdict, regarded by many as an intermediate option between the other two, has been the subject of a long-running debate as to whether it should be abolished. In this article we argue that it should. Drawing on empirical evidence from two recent studies, we cast doubt on the arguments most often made in its favour – that it serves a valuable communicative function, protects against wrongful conviction, and/or increases juror satisfaction. There is no consensus on its meaning or appropriate application in any given case, and it risks both stigmatising an acquitted accused and diminishing complainers’ opportunities for closure. It is doubtful that it prevents wrongful conviction,but even if it does,there are more effective measures in this regard.
Reliability of the Ginzburg–Landau Theory in the BCS-BEC Crossover by Including Gaussian Fluctuations for 3D Attractive Fermions

We calculate the parameters of the Ginzburg–Landau (GL) equation of a three-dimensional attractive Fermi gas around the superfluid critical temperature. We compare different levels of approximation throughout the Bardeen–Cooper–Schrieffer (BCS) to the Bose–Einstein Condensate (BEC) regime. We show that the inclusion of Gaussian fluctuations strongly modifies the values of the Ginzburg–Landau parameters approaching the BEC regime of the crossover. We investigate the reliability of the Ginzburg–Landau theory, with fluctuations, studying the behavior of the coherence length and of the critical rotational frequencies throughout the BCS-BEC crossover. The effect of the Gaussian fluctuations gives qualitative correct trends of the considered physical quantities from the BCS regime up to the unitary limit of the BCS-BEC crossover. Approaching the BEC regime, the Ginzburg–Landau equation with the inclusion of Gaussian fluctuations turns out to be unreliable.
Use of data fusion to optimize contaminant transport predictions

The original data fusion workstation, as envisioned by Coleman Research Corp., was constructed under funding from DOE (EM-50) in the early 1990s. The intent was to demonstrate the viability of fusion and analysis of data from various types of sensors for waste site characterization, but primarily geophysical. This overall concept changed over time and evolved more towards hydrogeological (groundwater) data fusion after some initial geophysical fusion work focused at Coleman. This initial geophysical fusion platform was tested at Hanford and Fernald, and the later hydrogeological fusion work has been demonstrated at Pantex, Savannah River, the US Army Letterkenny Depot, a DoD Massachusetts site and a DoD California site. The hydrogeologic data fusion package has been spun off to a company named Fusion and Control Technology, Inc. This package is called the Hydrological Fusion And Control Tool (Hydro-FACT) and is being sold as a product that links with the software package, MS-VMS (MODFLOW-SURFACT Visual Modeling System), sold by HydroGeoLogic, Inc. MODFLOW is a USGS development, and is in the public domain. Since the government paid for the data fusion development at Coleman, the government and their contractors have access to the data fusion technology in this hydrogeologic package for certain computer platforms, but would probably have to hire FACT (Fusion and Control Technology, Inc.,) and/or HydroGeoLogic for some level of software and services. Further discussion in this report will concentrate on the hydrogeologic fusion module that is being sold as Hydro-FACT, which can be linked with MS-VMS.
Optimization of the Activated Sludge Process

AbstractThis paper presents a multiobjective model for optimization of the activated sludge process (ASP) in a wastewater-treatment plant (WWTP). To minimize the energy consumption of the activated sludge process and maximize the quality of the effluent, three different objective functions are modeled [i.e., the airflow rate, the carbonaceous biochemical oxygen demand (CBOD) of the effluent, and the total suspended solids (TSS) of the effluent]. These models are developed using a multilayer perceptron (MLP) neural network based on industrial data. Dissolved oxygen (DO) is the controlled variable in these objectives. A multiobjective model that included these objectives is solved with a multiobjective particle swarm optimization (MOPSO) algorithm. Computation results are reported for three trade-offs between energy savings and the quality of the effluent. A 15% reduction in airflow can be achieved by optimal settings of dissolved oxygen, provided that energy savings take precedence over the quality of the .
R.F. induction furnace for silica-fibre drawing

An r.f. induction furnace is described to be used in a standard-type machine for drawing silica fibres for optical communication. The furnace consists of a small induction-heated graphite element which is fitted in a `concentrator? (stepdown transformer) placed directly in the tank coil of the r.f. generator, thus allowing one to maximise the matching efficiency between the generator and the heating element. The small dimensions of the graphite element make the furnace quickly responsive to input-power variations, so that it can be brought to a maximum temperature of 2180 K in 10 s. An argon atmosphere and an additional argon laminar flow are provided to avoid fibre contamination by the sublimated graphite, as well as to preserve the graphite susceptor. Successful tests of furnace operation have been carried out.
An empirical study of evolutionary techniques for multiobjective optimization in engineering design

Most real-world engineering optimization problems are multiobjective in nature, since they normally have several (possibly conflicting) objectives that must be satisfied at the same time. The word "optimum" has several interpretations within this context, and it is up to the designer to decide which fits better to his/her application. Currently, there are more than 20 mathematical programming multiobjective optimization techniques, each one corresponding to a different understanding of the term "optimum". On the other hand, genetic algorithms (GAs) have been viewed to be, since their early days, well suited for multiobjective optimization problems. Consequently, several GA-based techniques have been developed since then. The purpose of this research has been to develop a platform that allows the testing and comparison of existing and future multiobjective optimization techniques. Two new multiobjective optimization GA-based methods based on the notion of min-max optimum are proposed, showing that at least one of them is able to produce better results than any other technique tested. Also, a method for adjusting the parameters of the GA for single-objective numerical optimization is proposed, showing the suitability of the GA as a numerical optimization technique when used properly. Then, a brief study of the importance of population policies and proper niching parameters is included. This work tries to narrow the gap between theory and practice in the context of engineering optimization. Finally, some insights on the importance of choosing a good chromosomic representation and the use of a proper fitness function are provided, derived from the analysis of a more general design problem.
Adapting to climate-induced sea level rise on the Gold Coast: lessons from the Netherlands

Sea level rise poses significant risks to the Gold Coast, which is particularly vulnerable to coastal retreat, inundation and flooding. Drawing on policy transfer literature as the conceptual framework, this paper aims to draw lessons from the Netherlands, as an exemplar of adaptive flood management, to inform the future direction of adaptation to sea level rise on the Gold Coast. On both the Gold Coast and in the Netherlands, the traditional approach taken to adapt to sea level rise has been characterised by a structural approach to protect properties through flood defences. However, the Dutch Government has recently acknowledged the need to adopt a proactive approach to water management and accommodate water through spatial planning initiatives to minimise long-term risk from climate change. From the Dutch experience, three important lessons can be drawn: (1) the need to use spatial planning to accommodate water; (2) the need to adopt a proactive approach to climate adaptation; and (3) the importance of a strong centralised approach to water management. As the current adaptation framework in the Netherlands reflects centuries of experimenting with flood mitigation, these lessons should be of particular interest to Australian planners and policy-makers.
Product variety management: A synthesis of existing research

This article presents a systematic review of the literature on product variety management (PVM). The review examines publications between 2005 and 2010 found in the Elsevier electronic database. The review emphasises various internal and external pressures that encourage companies to increase or reduce the variety of products that they offer (that is, PVM input), different ways of dealing with these different pressures (that is, structure and processing), and the expected results of good management practices (that is, outputs). The framework also includes a fourth dimension that highlights the context in which the studies are grounded. The results highlight the main themes in PVM research, identify the key issues addressed in this research, and emphasise remaining gaps that deserve special attention in future research. Key words: Supply chain, business processes, information technology, mitigation strategies, metrics.
Stock Price Movement Prediction Using Sentiment Analysis and CandleStick Chart Representation

Determining the price movement of stocks is a challenging problem to solve because of factors such as industry performance, economic variables, investor sentiment, company news, company performance, and social media sentiment. People can predict the price movement of stocks by applying machine learning algorithms on information contained in historical data, stock candlestick-chart data, and social-media data. However, it is hard to predict stock movement based on a single classifier. In this study, we proposed a multichannel collaborative network by incorporating candlestick-chart and social-media data for stock trend predictions. We first extracted the social media sentiment features using the Natural Language Toolkit and sentiment analysis data from Twitter. We then transformed the stock’s historical time series data into a candlestick chart to elucidate patterns in the stock’s movement. Finally, we integrated the stock’s sentiment features and its candlestick chart to predict the stock price movement over 4-, 6-, 8-, and 10-day time periods. Our collaborative network consisted of two branches: the first branch contained a one-dimensional convolutional neural network (CNN) performing sentiment classification. The second branch included a two-dimensional (2D) CNN performing image classifications based on 2D candlestick chart data. We evaluated our model for five high-demand stocks (Apple, Tesla, IBM, Amazon, and Google) and determined that our collaborative network achieved promising results and compared favorably against single-network models using either sentiment data or candlestick charts alone. The proposed method obtained the most favorable performance with 75.38% accuracy for Apple stock. We also found that the stock price prediction achieved more favorable performance over longer periods of time compared with shorter periods of time.
Balanced antipodal Vivaldi antenna for wide bandwidth phased arrays

The Vivaldi antenna, a form of tapered slot radiator, has been shown to produce good performance over a wide bandwidth, limited only by the traditionally used slotline to microstrip feed transition. The authors present a new antenna, the balanced antipodal Vivaldi, which incorporates an ultrawide bandwidth transition and overcomes the poor polarisation performance of the antipodal form. Good performance over a 1 to 40 frequency range has been obtained. The use of the antenna in a linear phased array has also been investigated using elements constructed on high permittivity substrate. Wideband wide angle scanning with good cross-polarisation levels is obtained.
Calibration of On-Board Energy Measurement Systems Installed in Locomotives for AC Distorted Current and High Voltage Waveforms and Determination of Its Uncertainty Budget

Periodic calibrations of Energy Measurement Systems (EMS) installed in locomotives must be carried out to demonstrate the required accuracy established in the EN 50463-2 standard according to European Parliament and Council Directive 2008/57/EC on the interoperability of rail systems within the Community. As a result of the work performed in the “MyRailS” EURAMET project an AC calibration facility was developed consisting of a fictive power source was developed. This fictive power source can generate distorted sinusoidal voltages up to 25 kV-50 Hz and 15 kV-16.7 Hz as well as distorted sinusoidal currents up to 500 A with harmonic content up to 5 kHz or phase-fired current waveform stated in EN50463-2 standard. These waveforms are representative of those that appear during periods of acceleration and breaking of the train. Reference measuring systems have been designed and built consisting of high voltage and high current transducers adapted to multimeters, which function as digital recorders to acquire synchronized voltage and current signals. An approved procedure has been developed and an in-depth uncertainty analysis has been performed to achieve a set of uncertainty formulas considering the influence parameters. Different influence parameters have been analyzed to evaluate uncertainty contributions for each quantity to be measured: rms voltage, rms current, active power, apparent power and non-active power of distorted voltage and current waveforms. The resulting calculated global expanded uncertainty for the developed Energy Measuring Function calibration set up has been better than 0.5% for distorted waveforms. This paper is focused on presenting the complete set of expressions and formulas developed for the different influence parameters, necessary for uncertainty budget calculation of an Energy Measuring Function calibration.
Aplicação do método de mapeamento de fluxo de valor no setor de engenharia de uma empresa têxtil

Este artigo apresenta e discute a aplicacao de uma ferramenta da Manufatura Enxuta em um ambiente multiprojetos de desenvolvimento de produtos. A aplicacao se deu em uma empresa do setor textil do estado de Santa Catarina onde foi utilizado o metodo de mapeamento de fluxo de valor com a finalidade de identificar os desperdicios nas atividades desse processo e realizar melhorias de forma estruturada e objetiva. Portanto, sera que esse metodo aplicado na empresa estudada, realmente possibilita identificar a existencia de excessos nos inventarios de informacoes, retrabalhos, e inconsistencias nos fluxos de informacoes e materiais? Como resultado dessa aplicacao obteve-se a reducao de dois dias no lead time total do desenvolvimento de produtos no setor de engenharia, o que sinaliza o potencial de utilizacao desse metodo para a melhoria de ambientes caracterizados pelo elevado mix de produtos desenvolvidos num curto espaco de tempo.
Structure-Function Characteristics of SARS-CoV-2 Proteases and Their Potential Inhibitors from Microbial Sources

The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is considered the greatest challenge to the global health community of the century as it continues to expand. This has prompted immediate urgency to discover promising drug targets for the treatment of COVID-19. The SARS-CoV-2 viral proteases, 3-chymotrypsin-like protease (3CLpro) and papain-like cysteine protease (PLpro), have become the promising target to study due to their essential functions in spreading the virus by RNA transcription, translation, protein synthesis, processing and modification, virus replication, and infection of the host. As such, understanding of the structure and function of these two proteases is unavoidable as platforms for the development of inhibitors targeting this protein which further arrest the infection and spread of the virus. While the abundance of reports on the screening of natural compounds such as SARS-CoV-2 proteases inhibitors are available, the microorganisms-based compounds (peptides and non-peptides) remain less studied. Indeed, microorganisms-based compounds are also one of the potent antiviral candidates against COVID-19. Microbes, especially bacteria and fungi, are other resources to produce new drugs as well as nucleosides, nucleotides, and nucleic acids. Thus, we have compiled various reported literature in detail on the structures, functions of the SARS-CoV-2 proteases, and potential inhibitors from microbial sources as assistance to other researchers working with COVID-19. The compounds are also compared to HIV protease inhibitors which suggested the microorganisms-based compounds are advantageous as SARS-CoV2 proteases inhibitors. The information should serve as a platform for further development of COVID-19 drug design strategies.
The public and a radiological or nuclear emergency event: threat perception, preparedness, and anticipated response - findings from a preliminary study in Sydney, Australia

This paper presents selected findings from a preliminary study that sought to assess the impacts of a radiological or nuclear emergency event on an Australian population, and their anticipated responses to such an event. The questionnaire was wide-ranging and included sections on threat perception, preparedness, use of media sources and trusted organisations, as well as socio-demographic, personal resilience and health-related data. Survey data were collected from samples of the general public living in Sydney, Australia during the period May-June 2008 using a mixed convenience sample approach (n=324). In general, data suggest that the public is not highly concerned about terrorism involving radiological or nuclear materials and is unprepared for such an event. First Responders (Fire, Police, Ambulance) and the Australian Nuclear Science and Technology Organisation (ANSTO) were the authorities the public had most confidence in to respond to such incidents and these were also the agencies the public was most likely to trust for credible information. When respondents were prompted with a series of possible behaviours they might elicit in the event of a radiological or nuclear emergency incident, their immediate most likely responses included calling family members to check they are OK, washing off radioactive material, seeking shelter indoors, calling emergency services, covering their mouth to prevent inhalation of dust, and trying to get back home. Longer-term behaviours included having more frequent health checks. These findings suggest that there would be high demand on telecommunication services soon after such an event, and the general lack of preparedness of the public suggests that there would be a high degree of confusion and uncertainty in their responses. This emphasises the importance of timely communication and direction following such an event, preferably delivered by one of the authorities most trusted by the public.
Optimization of a right-angle piezoelectric cantilever using auxiliary beams with different stiffness levels for vibration energy harvesting

This paper presents experiments and models of a piezoelectric cantilever generator with a right-angle structure. Analysis shows that the extended part provides a large torque to the main beam, which can dramatically smoothen the strain distribution of the main beam. The auxiliary beam was fabricated with half the length of the main beam. When the auxiliary beam has a stiffness which is 0.02 times that of the main beam the piezoelectric element has a highly uniform strain distribution; in addition, its relative utilization efficiency (RUE) is 93% at the initial resonant frequency, whereas it is 50% for a conventional rectangular piezoelectric cantilever. The performances of three right-angle generators with auxiliary beams having different levels of stiffness, but constant-stiffness main beams are studied. The RUE of the piezoelements increases as the auxiliary beam’s stiffness decreases. A model based on the Rayleigh–Ritz method is established to demonstrate the principle of the strain-smoothing effect. The voltage and power outputs of the generators are measured. Finite element method simulations are also presented, and the result fits the experiments well.
Extremely reduced nonlinear K-factor in high-speed strained layer multiquantum well DFB lasers

The nonlinear damping K-factor value in a strained layer multiquantum well (MQW) DFB laser has drastically decreased to 0.13ns, about half of that for unstrained MQW lasers. This is mainly due to the increase in differential gain by about a factor of two. The estimated intrinsic maximum bandwidth is 68 GHz.