Miracle-dz/UniFAR-FTUs huggingface dataset:
A −117dBc THD (−132dBc HD3) and 126dB DR Audio Decoder with Code-Change-Insensitive RT-DEM Algorithm and Circuit Technique for Relaxing Velocity Saturation Effect of Poly Resistors

Three major distortion sources in high-fidelity audio decoders are 1) DAC inter-symbol interference (ISI) [1], [2]; 2) 3rd-order harmonic distortion (HD3) due to the 2nd-order nonlinearity of poly resistors; and 3) Cross-over distortion (COD) arising from limited amplifier inner-loop gain due to high output load capacitance (CL) [3], [4]. First, to alleviate the ISI, [1] presents a Real-Time Dynamic-Element-Matching (RT-DEM) algorithm to realize mismatch shaping for DAC cells, achieving 115dB SFDR without complex digital hardware as in [2]. However, the constraint of 1-LSB change with the RT-DEM limits dynamic range (DR) of the $\Delta\Sigma$ modulator. Moreover, a high clock rate of 181 MHz causes a high power consumption. Second, with a large signal swing, the total harmonic distortion (THD) of current-to-voltage (I2V) amplifiers is frequently dominated by the HD3 in [1]–[5]. The potential cause of this HD3 is due to the velocity saturation effect (VSE) of poly resistors [6]. Lastly, for a large load capacitance, the damping-factor-control frequency compensation (DFCFC) is commonly applied in multi-stage amplifiers to enhance the stability [4], [5]. However, it degrades the amplifier inner-loop gain and causes severe COD. In [4], a compensation scheme inserts a gain stage inside the inner loop to boost the loop gain over the audio band (20Hz to 20kHz), suppressing the peak COD below −111 dBc. In this work, three techniques are presented to eliminate the aforementioned distortion sources: 1) a code-change-insensitive RT-DEM (CCI-RT-DEM) algorithm is introduced to dynamically select the new start index of rotated DAC cells for the next code, instead of the fixed index at the first one [1], thus allowing for more than 1-LSB change; 2) a poly-resistor linearization scheme is presented to suppress HD3 by mitigating the VSE of resistors; and 3) a 2nd-order DFCFC for multi-stage amplifiers is introduced that allows a high inner-loop gain to suppress the COD, thus enhancing the amplifier linearity even with a large CL. Combining these solutions, the DAC and amplifier together achieve −117dBc THD (−132dBc HD3) and 126dB DR.
Evaluation of Experimental Implementations of Optimal Controllers for Underactuated Systems

Inverted pendulum control systems are widely employed benchmarking purposes as they offer similar challenges to those faced when designing controllers for underactuated systems. In this paper, an LQR-based control system consisting of an inverted pendulum on a cart is presented and used in a comparative experimental study on hardware controller implementation. The paper focuses on studying, comparing, and evaluating the performance of two options of controller implementations ranging from a low-cost microcontroller based embedded system, namely the Arduino DUE, to a relatively high-end, high-cost controller prototyping system, the dSpace DS1104. Derivation of the modeling equations of motion of the inverted pendulum on a cart based on the Lagrangian formulation is also presented
User Interface and Usability Assessment of mobile- based Smart City using Webqual 4.0 Approach: an insight of Madura Island Districts

User Interface and Usability is one of the essential factors that must be well-thought-out in designing and implementing mobile-based smart city services. This is done to ensure the usability and convenience aspects of the system to be carried out by clients in using smart city services. However, the application of smart city services still does not pay much attention to user interface and usability factors, affecting mobile-based smart city services to be inaccessible and causes user motivation to use the system to become very low. This study aims to conduct an assessment of mobile-based smart city services as of the perspective of stakeholders of smart city service users. The method used in this study is WEBQUAL 4.0, with data collection using stratified random sampling conducted on 328 stakeholder respondents who use mobile-based smart city services. Data analysis was performed with the help of AMOS software version 23.0. The result is a significant correlation between the variables in the Webqual model. This research contributes to the confirmation of modelling in the study of technology adoption in mobile-based smart cities and offers references to the government to give more thought to the factors that are important in the realization of smart city adoption.
Thermo-mechanical analysis of a glass-ceramic piston for potential use in combustion engines

The temperature of combustion engine pistons, e.g., 370 °C, along with their high thermal coefficient of expansion, are limiting design factors. The use of ceramic in the majority of the present literature is directed toward exploring its potential as a coating only, i.e., a thermal barrier. This work, however, investigates the applicability of glass-ceramic as a construction material for the engine piston in replacement of its metallic conventional candidates. Firstly, in attempts to find the most suitable ceramic material, a selection screening of several grades is performed using ANSYS Granta Edupack software. Secondly, a thermo-mechanical analysis is performed to compare between glass-ceramic, Aluminum and stainless steel that can best fit the piston application. It was found that the maximum induced Von-Mises stresses are reduced by more than 200% when glass-ceramic was used. Similarly, the maximum deformation was seen to be extremely lower compared to Aluminum and stainless steel. Different other possible high-strength glass-ceramic materials are also discussed. Overall, the FEA outcomes in conjunction with the findings of high-strength glass-ceramics present an attractive foundation as future candidates to pistons potentially used in aerospace applications.
The New Models of Financial Industry Development under the Background of Big Data

In the current era of big data, the development of Internet finance is facing opportunities while also facing challenges in all aspects. In the digital economy, data is the financial industry's core assets, and analyzing vast amounts of information through the use of big data technology, is the main direction of the current development of the financial industry. This paper by the status of the current financial market integration and the development of big data, analyzes the potential for development and the integration of the two major challenges currently facing, on how to deal with the financial relationship between the Internet and big data technologies, financial risk control, precision marketing, etc. Think about the difficult problems, and further explore the development path of Internet finance under the background of big data.
A 28nm 6GHz 2b Continuous-Time $\Delta\Sigma$ ADC with −101 dBc THD and 120MHz Bandwidth Using Digital DAC Error Correction

Ultra-highly linear ADCs, based on continuous-time $\Delta\Sigma$ modulators with a (theoretically) linear 1b DAC, have demonstrated better than −100dBc THD in a bandwidth range from tens of kHz for audio to tens of MHz for broadband AM/FM radio [1]. To achieve both a large bandwidth and high dynamic range with a 1 b $\Delta\Sigma$ modulator, a high OSR and multi-GHz-rate sampling frequency are required. But there is a limit to the maximum sampling frequency of a $\Delta\Sigma$ modulator, being a negative feedback system, in order to maintain loop stability and sufficiently low metastability, for a given technology node. To date, the maximum achievable bandwidth of a high-resolution 1 b $\Delta\Sigma$ modulator is limited to a few tens of MHz. To achieve a bandwidth exceeding 100MHz with a single-loop $\Delta\Sigma$ modulator, multi-bit quantization is essential [3]–[5]. When employing multi-bit quantization, the inherently linear property of a 1b DAC that consists of only a single unit element is lost, due to processing imperfections that cause mismatch errors between the multiple unit elements of a multi-bit DAC. The impact of static and dynamic mismatch errors can be effectively reduced with calibration, dynamic matching and analog/digital compensation techniques. State-of-the-art ADCs with bandwidths exceeding 100MHz have reported excellent linearity numbers up to −83dBc THD [4]–[5], but this is far off from the <-100dBc THD achieved by the ultra-highly linear 1b ADCs. This paper demonstrates a 28nm CT $\Delta\Sigma$ ADC that achieves −101 dBc THD in a 120MHz bandwidth, exceeding the state-of-the-art by 17.5dB and 4.8 times, respectively [2]–[5]. The 120MHz bandwidth is realized by employing an offset-calibrated 2b quantizer sampled at 6GHz, and the linearity performance is achieved with a high precision, digitally corrected 2b DAC and has been validated over PVT and local mismatch variation.
Nested Multiband Hysteresis Current Control of Master-Slave Scheme for Reliable Microgrid

The master-slave control/operational scheme proves to be very efficient for operating any microgrid in different modes: Islanded and grid-connected modes. The master-slave schemes prove to be competitive compared to the droop control schemes because of their admirable characteristics for the control/operation of AC microgrids. This presented paper employs the master-slave scheme as a control scheme for the operation of the microgrid. The adopted microgrid contains three multilevel (five-level diode-clamped) inverters. Two of them are operated as slave units, and the remaining unit is employed as a master unit. The slave units are operated in a current-controlled mode using developed multiband hysteresis current control. At the same time, the master inverter is operated in a voltage-controlled mode, which is responsible for maintaining both frequency and voltage at a certain level. In addition, the redundancy of the slave units is checked in case one slave unit is disconnected. The simulation results prove that master control and hysteresis current control perform well at different operating conditions.
A View Planning Method for 3D Reconstruction with Unknown Feature Prediction

Active reconstruction can be considered as an intelligent perception problem that seeks to optimize the efficiency of the modeling tasks by adjusting the configuration of vision system on robotic platform automatically. We consider a feature as several local surfaces that have the same kinds of characteristics. A standard geometry can be defined by attributes abstracted from a set of features. For the regular geometry of the same category, descriptions and topological relations about these objects’ features are known before modeling tasks. In order to maximize the acquisition of an object’s surface in a few views, knowledge of its features is employed as partial prior information that guides the view planning in active reconstruction. Since each reconstruction task may have a different type of object to be rebuilt, in order to make the view planning algorithm suitable for different tasks, we store the prior information of the object in a fixed-form database, so as to call the content of the library to perform verification and reasoning of all features, and make predictions on unknown local surface and rough shape of the object. The predicted unknown surface is discretized and then marked as predicted voxels in the voxel space, which are used to evaluate the priority of all candidate viewpoints, together with the detected voxels. A novel hybrid optimization function is proposed that takes the constraint on overlap, the accessibility of predicted surface, and the amount of unknown object surface into account. Simulated experiments are conducted and the results show that our method is efficient for reconstruction.
Greening the global classroom: Experiences using MOOCs to advance sustainability education

The proliferation of massive open online courses (MOOCs) has been a phenomenon in higher education but only recently the subject of academic literature. MOOCs combine the traditional ideas of cohort and guided learning with open access and a truly global classroom. With over twenty thousand learners attracted to such courses, we argue that they can be a powerful tool in advancing sustainability education in terms of global reach. Like traditional education, the quality of the education delivered by MOOCs is influenced by their design and this is also integral to their success in promoting deeper learning of sustainability topics. However, designing a quality course and ensuring genuine learning experiences in this open and massive context is not without challenges. We describe our practical experience with curriculum design, production and delivery of a MOOC with a wide sustainability focus of "Greening the Economy: Lessons from Scandinavia". The background of students taking the MOOC, motivations and reasons for seeking this type of sustainability education and perceived benefits from this MOOC and other MOOCs with topics related to sustainability are discussed. Combining pedagogical approaches in the form of teacher-led lectures and quizzes for basic understanding with more constructivist forum discussions and peer assessment created the opportunity for the MOOC to not only disseminate knowledge about sustainability issues, but also encourage discussion, peer interaction, and deeper engagement with these issues. An interesting aspect of this reciprocal learning was the collected insights from learners in the form of case studies and survey responses. The promise, as well as potential issues, of MOOCs in contributing to the goals of sustainability education and lifelong learning are discussed and reflected upon.
Flu Symptoms Detection and Sanitization System

Existing inspection and sanitization approaches were mostly manual, such as security personnel checking patrons' temperatures and custodians regularly cleaning public spaces. To that aim, an automated system that measures body temperature, detects flu symptoms, and sanitizes the environment is a more effective approach to control the infections in public places. This paper presents an automated system to detect flu symptoms and control the sanitization process in closed spaces, such as small hallways and elevators. The proposed method is cheap and effective in detecting flu symptoms. The cost is estimated around USD 283 with off the shelf components. The sneezing and coughing systems reached 86.6% training accuracy. This paper illustrates the proposed design of the system, its design implementation, and finally analysis the obtained results.
Pulsed Laser Synthesis of Bi-Metallic Nanoparticles for Biomedical Applications: A Review

Bi-Metallic Nanoparticles (BMNPs) have been extensively researched for applications in various fields of Nano-engineering, Nano-medicine, and Nano-biotechnology. Methods used in synthesizing them (top-down and bottom-up) have also been vastly explored. From the past reviews, extensive usage of chemical approaches (such as Sol-Gel, polymer precursor, micro-emulsion, hydrothermal, sonochemical, etc.) has been reported. However, by usage of pre-cursors, harmful and toxic chemical agents, longer reaction time, there is a limited or no contribution towards green environment. Producing BMNPs at a commercial scale in such a scenario would have detrimental effects which are still un-realized. Also, some of the biomedical applications, demand usage of pure and stable nanoparticles Therefore, the need immediately arises to opt for a greener synthesis method. One such available physical approach Laser-assisted synthesis (LASIS) gives effective control, as well as stable, pure BMNPs, is obtained. This review focuses on the recent work done in Laser-assisted synthesis of BMNPs with a focus on their properties and different nanostructures formed using this technique for bio-imaging, anticancer, and drug delivery applications and thereby its contribution in being an environment-friendly and green technology.
EEG Channel Selection Methods for Motor Imagery in Brain Computer Interface

EEG is widely applied in motor imagery because of its non-invasive and easy access. However, multi-channel EEG signals cause noise interference and redundant information. Channel selection can reduce the noisy signal to obtain more real signals. Therefore, many studies focus on the influence of channel selection algorithms on motion imagery decoding. This paper summarizes the characteristics of channel selection methods for decoding motion imagination tasks and compares their methods and results. One way to select the channel is based on neural network and takes the channel as the input parameter of the neural network; Another is an EEG classification method based on statistical information. Statistical information such as CSP rank, cross-correlation, and Pearson correlation coefficient is used to sort channels. In addition, we also discuss the relationship between the channel selection algorithm and high-density electrode design.
Combining Process Modeling and Requirements Engineering

Using IT development efforts for achieving new business goals is a challenging task. Optimally, IT projects and solutions should be aligned to answer the real requirements of actual business development targets. Process modeling has been widely applied as a tool for business process and IT development. The goal of this study is to investigate how to combine process modeling and requirements engineering (RE) in software development projects. We studied the use of process modeling focused Business-driven development (BDD) method and other modeling techniques to support complex large projects in the outsourced environment. The results presented here are based on 17 interviews, a study of 4 projects implemented with the BDD method and the experiences gathered from 11 other large projects at the case study organization. This report outlines the results of combining process modeling to use case, business rule and other requirements and architecture modeling. To a large extent, the results were positive and indicate the benefits for using business process modeling as a visual tool for combining business and IT development, and as a part of the requirements. However, the perspective and abstraction level for process modeling should be carefully selected. Our study concludes also that requirements modeling should cover different aspects from both project and enterprise context in a comprehensive manner.
A novel EWMA mean chart with its extensions

The EWMA chart is an advanced process monitoring tool because of its sensitive nature against small and moderate shifts that occur in the process parameter(s). In this paper, with a transformation related to the Brownian motion, we propose novel EWMA, double EWMA, triple EWMA, and quadruple EWMA charts for monitoring the mean of a process that follows a normal distribution. The Monte Carlo simulations are used to compute the run length properties of the proposed charts. Based on a comparative study, it is found that the newly proposed charts are uniformly and substantially better than their existing counterparts when detecting different kinds of shifts in the process mean. Real datasets are also considered to demonstrate the implementation of the proposed charts.
Computationally Efficient Methods for Shift-variant Image Restoration in Two and Three Dimensions

We, the dissertation committee for the above candidate for the Doctor of Philosophy degree, hereby recommend acceptance of this dissertation. 2011 Shift-variant image restoration/deblurring is useful in many applications including machine vision, image processing, 3D microscopy, medical image analysis, etc. Currently, several shift-variant restoration approaches exist. However, they are either computationally expensive or inaccurate leading to poor image quality. This thesis proposes and investigates computationally efficient techniques that produce high quality restoration, even in the presence of noise. The methods presented here are general in that they are not limited to certain types of kernels to be computationally efficient. Detailed analysis and computational algorithms for implementing the methods are provided. This thesis addresses linear shift-variant imaging systems in both two and three dimensions. Image restoration in this case corresponds to solving the Fredholm Integral iv Equation of the Fist Kind. In the two dimensional case, computational efficiency is achieved through localization. In the case of three dimensions, a new domain transformation is applied to achieve computational efficiency. These results are presented in two parts. In the first part, three image restoration algorithms are discussed. The first algorithm is a localized approach to restore highly defocused images. It is based on an existing method called the single interval RT (SRT) method. The SRT method is found to restore only small to medium levels of blur. It is first analyzed and then extended to restore images blurred with large shift-variant point spread functions (PSFs). The new method is called the multi interval RT (MRT) method. In the MRT technique a region around the pixel with size comparable to the support domain of the blurring kernel is divided into several smaller regions (intervals). The blurred image in each interval is modeled separately by truncated Taylor-series polynomials. A linear system is derived by differentiating the polynomial with respect to spatial variables. A vector of blurred image derivatives is then expressed as sum of such linear systems. An iterative update formula is obtained that is evaluated to improve focused image estimate. Experimental results for the MRT technique in 1D on analytic functions and in 2D on simulation data and real images are presented. The results show that MRT technique is effective for restoring highly defocused images but at a modest increase in computation cost compared to SRT. The next two restoration algorithms are iterative versions of SRT. One of them is the RT Iterative (RTI) …
Bestimmung von substrat-inhibierten stationären Zuständen zur Validierung von Modellen des Schadstoffabbaus

Prof. Dr.-Ing. Clemens Posten ist Professor für Bioverfahrenstechnik am Inititut für Mechanische Verfahrenstechnik und Mechanik der Universität Karlsruhe (TH). Arbeitsgebiete: Integrierte Bioprozeßentwicklung, Modelierung und Regelung von Bioprozessen (Stoffwechsel von Mikroorganisnen, Fermentationen, mechanische Aufarbeitungs-Prozesse), Anwendung îeuer mathematischer Methoden in der Bioverfahrenstechnik.
Study on the optimization of energy consumption as part of implementation of a ship energy efficiency management plan (SEEMP)

Executive summary: This document provides at annex the report of a Study on the optimization of energy consumption as part of implementation of a ship energy efficiency management plan (SEEMP), undertaken to identify best practice developed by the shipping industry, particularly since 1 January 2013 with the introduction of the mandatory requirement for ships to keep on board a ship-specific SEEMP