Miracle-dz/UniFAR-FTUs huggingface dataset:
Smart Waste Management System using Internet of Things and RFID Technology

More recently the government’s massive fundraising campaign has been working to separate the garbage. The Indian government has invested a lot of money and energy in this work. To separate the garbage the government also needs sophisticated high-energy equipment. These machines also required maintenance costs from time to time. Health illness also affects when manual workers. The government also works to raise awareness of the separation of dry and wet waste through campaigns, banners, posters and celebrity campaigns. To overcome and alleviate the above problem our smart garbage dissection program will educate and name the user to make the best use of the dustbin. A micro-controller, sensors, servo motors, DC motor, RFID and Wi-Fi technology that will be used to build this great garbage disposal system. The main purpose of this paper is to educate and reward the various users who dump garbage on a daily basis. This program will have an RFID learning module that can monitor user identification with the RFID tag and the Wi-Fi system will send user data to an IOT-enabled application. At this point the IOT app user can check their bonus points. This bonus point can be adjusted for another discount offer.
Interobserver Reliability of Schatzker, AO Foundation-Orthopaedic Trauma Association, and Luo Classifications for Tibial Plateau Fractures: Does Three-Dimensional CT Improve Outcomes?

Objective To assess the interobserver agreement of the most widely used classification systems (Schatzker, AO Foundation-Orthopaedic Trauma Association (AO-OTA), and Luo) and investigate the impact of multiplane CT scans on their reliability. Methods Twelve raters (seven consultants and five senior trainees) were invited to classify 25 cases of tibial plateau fracture randomly selected out of a large database. Initially, they were asked to classify the fracture according to Schatzker, AO-OTA, and Luo based on plain anteroposterior (AP) X-ray and axial CT images. This procedure was applied for 25 cases consecutively. Next, the raters are given access to the multiplanar CT views of the same cases and were requested to reclassify each case. The interobserver agreement was calculated using the Fleiss kappa coefficient. Results An overall fair inter-rater agreement was observed for the Schatzker classification based on the plain AP X-ray (k=0.361) with a slight improvement after three-dimensional (3D) plane CT views (X-ray: k=0.361; 3D CT: k=0.364). For the AO-OTA classification, the relevant values were 0.204 and 0.231 based on plain X-ray and multiplanar CT, respectively. Finally, the Luo classification achieved the highest scores among the three classification systems (k=0.498), but its inter-rater agreement can still be characterized as moderate. No statistically significant improvement in the interobserver agreement was found for any classification even if only the consultants’ subgroup was included in the data analysis. Conclusion All three classification systems failed to achieve a substantial agreement among the raters, with only a nonsignificant improvement after providing advanced imaging. This finding reflects the intrinsic weaknesses of the classification systems themselves rather than the disagreement on the fracture pattern due to unsatisfactory imaging.
Mechanical reinforcement of granular hydrogels

Granular hydrogels are composed of hydrogel-based microparticles, so-called microgels, that are densely packed to form an ink that can be 3D printed, injected or cast into macroscopic structures. They are frequently used as tissue engineering scaffolds because microgels can be made biocompatible and the porosity of the granular hydrogels enables a fast exchange of reagents, waste products, and if properly designed even the infiltration of cells. Most of these granular hydrogels can be shaped into appropriate macroscopic structures, yet, these structures are mechanically rather weak. The poor mechanical properties prevent the use of these structures as load-bearing materials and hence, limit their field of applications. The mechanical properties of granular hydrogels depend on the composition of microgels and the interparticle interactions. In this review, we discuss different strategies to assemble microparticles into granular hydrogels and highlight the influence of inter-particle connections on the stiffness and toughness of the resulting materials. Mechanically strong and tough granular hydrogels have the potential to open up new fields of their use and thereby to contribute to fast advances in these fields. In particular, we envisage them to be well-suited as soft actuators and robots, tissue replacements, and adaptive sensors.
Discussion on the development of new Gambiered canton gauze product

Gambiered Canton gauze,also called Gambiered Canton silk is a silk product which is manually dyed by use of natural dyes.It is of cool,smooth,sweat absorptive and wrinkle-resistant so that it is an ideal material for summer clothes.Yet the designs and categories of Gambiered Canton gauze clothes on the market are so limited.The features,creative design and development trend of Gambiered Canton gauze clothes are studied in this paper to provide some references for the designers and consumers.
Dynamic measurement with in-cycle process excitation of HCCI combustion: The key to handle complexity of data-driven control?

Homogeneous Charge Compression Ignition (HCCI) is a low temperature combustion technique with a high potential for reducing emissions while simultaneously improving fuel consumption. However, the high sensitivity to changing boundary conditions and low combustion stability at the edges of the operating range has lead to implementation challenges. Additionally, cyclic coupling through internal exhaust gas recirculation causes cyclic variations of the process, resulting in incomplete combustion, or even misfiring. Thus, consecutive cycles must be decoupled to increase the process stability. To achieve an accurate description of the coupling effects on a cycle-to-cycle and an inner-cyclic timescale, a novel measurement methodology is presented to generate data with a high variance. For this purpose, an active process excitation is performed to capture all relevant interactions between operating and feedback variables to enable modeling of the coupling effects on both timescales. To demonstrate the potential of the methodology, the generated data is used to design multiple input, multiple output (MIMO) models for both cyclic and inner-cyclic timescales. Artificial neural networks are then utilized to address the highly nonlinear process by taking advantage of the large amount of training data. Inverse process models are then used to implement a pure cycle-to-cycle and a multiscale MIMO closed-loop controller. Compared to state-of-the-art rule-based control approaches, the process stability and its thermodynamic efficiency are significantly improved. For the multiscale MIMO controller, a reduction of the standard deviation of the indicated mean effective pressure and the combustion phasing of more than 65% is achieved. In particular, the additional inner-cyclic feedback loop achieves a remarkable reduction of the standard deviation of approximately 35% and a 1.2% higher indicated efficiency compared to the cycle-to-cycle MIMO controller. The dynamic measurement with active in-cycle process excitation has proven to be an enabler for data-driven MIMO control of HCCI on multiple timescales.
Study on Optimal Location of Flow Measurement Station in Urban Water System

Using the topological model of water distribution system, accounting the flow influence degree of each tube to the node discharge variety, inducting the concept of effective monitoring scope and calculating effective detection matrix under the setting level of service, a method of optimal locating of flow measurement stations is presented in water system by utilizing computational methods of irredundant dominant set and minimum covering set. This method provides a valid basis for water system to adjust, supervise and control the trouble of water system, which the credibility and the usefulness has been verified by example.
Physical and numerical modelling in low-head structures design

Physical and numerical modelling may be combined within so-called composite or hybrid modelling. This enables to optimally take benefit of the respective strengths of each modelling approach, while compensating for their specific drawbacks. Different types of composite modelling may be identified, such as embedding a detailed physical model within a broader scale numerical model, interconnecting different physical and numerical models focusing each on specific processes, or validating a numerical model from experimental data before exploiting the numerical model to generate more results than available from the experimental facility. Besides, specifically in more basic research, composite modelling may also be used to improve in-depth understanding of the relative importance of different processes which act simultaneously in the experimental test and may be artificially separated in numerical simulations.
Five optimized designs of comparator

Comparators contribute a significant role to analog to digital converters (ADC). Considering the comparator design, several performances should be deal with. Several optimizing methods for comparator design in recent years are reviewed in this work. Based on the traditional amplifiers, FIA (Floating Inverter Amplifier) technology is used to improve the preamplifier, thus achieving low power consumption. Triple-Latch Feedforward Dynamic Comparator by adding a feedforward path to reduce delay and a Rail-to-Rail Dynamic Voltage Comparator combines NAND logic circuit and NOR logic circuit to enable the comparator to operate in full scale of input voltage also proposed especially for low-input applications.
A quadrature-based scheme for numerical solutions to Kirchhoff transformed Richards' equation

In this work we propose a new numerical scheme for solving Richards' equation within Gardner's framework and accomplishing mass conservation. In order to do so, we resort to Kirchhoff transformation of Richards' equation in mixed form, so to exploit specific Gardner model features, obtaining a linear second order partial differential equation. Then, leveraging the mass balance condition, we integrate both sides of the equation over a generic grid cell and discretize integrals using trapezoidal rule. This approach provides a linear non-homogeneous initial value problem with respect to the Kirchhoff transform variable, whose solution yields the sought numerical scheme. Such a scheme is proven to be \begin{document}$ l^{2} $\end{document}-stable and convergent to the exact solution under suitably conditions on step-sizes, retaining the order of convergence from the underlying quadrature formula.
A Lightweight and Privacy-Friendly Data Aggregation Scheme against Abnormal Data

Abnormal electricity data, caused by electricity theft or meter failure, leads to the inaccuracy of aggregation results. These inaccurate results not only harm the interests of users but also affect the decision-making of the power system. However, the existing data aggregation schemes do not consider the impact of abnormal data. How to filter out abnormal data is a challenge. To solve this problem, in this study, we propose a lightweight and privacy-friendly data aggregation scheme against abnormal data, in which the valid data can correctly be aggregated but abnormal data will be filtered out during the aggregation process. This is more suitable for resource-limited smart meters, due to the adoption of lightweight matrix encryption. The automatic filtering of abnormal data without additional processes and the detection of abnormal data sources are where our protocol outperforms other schemes. Finally, a detailed security analysis shows that the proposed scheme can protect the privacy of users’ data. In addition, the results of extensive simulations demonstrate that the additional computation cost to filter the abnormal data is within the acceptable range, which shows that our proposed scheme is still very effective.
Hybrid Optimization for Machinability Enhancement during Green Machining of Stainless Steel

Stainless steel 304 is one of the most promising materials for many industrial applications. Its machinability is poor whether machined in any environment. Conventional machining causes environmental degradation as well. In this paper, sustainable machining of SS304 using green lubricant is presented. Experiments have been conducted on Taguchi’s robust design of experiment technique. For machinability enhancement, a hybrid optimization technique VIKOR-Regression-PSO is employed. Machinability indicators that have been considered are tool wear, surface roughness, and chip reduction coefficient. Cutting speed, depth of cut, and feed rate have been considered as the variable machining parameters in this work. The hybrid optimization has been found very effective and provided a set of optimum machining parameters i.e. cutting speed-70m/min; feed rate-0.1mm/rev; depth of cut-0.5mm for the best values of machinability indicators i.e. tool wear-249.22 μm, roughness-11.08 μm, chip reduction coefficient-2.26.
3D Printing of Pediatric Medication: The End of Bad Tasting Oral Liquids?—A Scoping Review

3D printing of pediatric-centered drug formulations can provide suitable alternatives to current treatment options, though further research is still warranted for successful clinical implementation of these innovative drug products. Extensive research has been conducted on the compliance of 3D-printed drug products to a pediatric quality target product profile. The 3D-printed tablets were of particular interest in providing superior dosing and release profile similarity compared to conventional drug manipulation and compounding methods, such as oral liquids. In the future, acceptance of 3D-printed tablets in the pediatric patient population might be better than current treatments due to improved palatability. Further research should focus on expanding clinical knowledge, providing regulatory guidance and expansion of the product range, including dosage form possibilities. Moreover, it should enable the use of diverse good manufacturing practice (GMP)-ready 3D printing techniques for the production of various drug products for the pediatric patient population.
Condition Monitoring of Aeroengine Based on Wavelet Process Neural Networks

Aiming at the problem of aeroengine condition monitoring,a wavelet process neura l network (WPNN) model is proposed.Its hidden layer and output layer are compose d of process neuron and the hidden layer function consists of wavelet function.T he network has not only the capability to deal with the continuous input signals , but also the time-frequency local property of the wavelet analysis.The learni ng ability of WPNN is better and the predictive precision is higher.The correspo nding learning algorithm is given and the network is compared with three layers feedforward process neural network (PNN) by predicting the exhaust gas temperatu re (EGT). The result exhibits good convergence and simple architecture of the net work.The prediction capability is superior to PNN.This provides an effective way for the problem of aeroengine condition monitoring.
Structure of Agricultural, Forestry and Fishery Sector in the Vietnam Economy: An Input – Output Analysis

As coming to Vietnamese culture, it refers to the culture of agriculture. Every country has agriculture, but the culture of agriculture is only in some Asian countries, including Vietnam. In the soul of the Vietnamese is always a pure soul and pure. In recent decades it seems that people are trying to change this with the "industrialization and modernization" movement, trying to force the Vietnamese people instead of using the advantages of cultivation, breeding become workers. When Vietnamese people's strengths are not used and promoted, they have to try or be forced to use their weakness. Thus, the failure is almost inevitable. In Vietnam, the importance of an industry or group of industries is usually measured by the share of the value added of the industry (or group of industries) in GDP. This can lead to misunderstandings about the importance of that sectors group, So, this study examines the change in the interactions between agriculture, forestry and fisheries with other sectors of the economy based on the structure of the 2012 and 2016 Input Output (I/O) tables of Vietnam.
Research on broadband microwave electromagnetic antireflection effect based on angle-insensitive electromagnetically induced transparent metamaterials

Metamaterials have unlocked a number of unique optical properties for manipulating the electric and magnetic dipole resonances have drawn much attention over the past decades. It has been recognized that a metamaterial could provide a new approach to excite electromagnetic behaviors leading to potential applications in the fields of sensing, energy, and information The low-loss conformal processing integration of multi-band wide-angle electromagnetic antireflection metamaterials, functional layers and radome is a challenging research. In this paper, a high-permeability metamaterial with similar electromagnetically induced transparency (EIT) characteristics is constructed around the metal split ring, and the equivalent dielectric constant and equivalent permeability of the split ring meta-unit are analyzed based on the equivalent medium parameter inversion model. Analyze the regulation mechanism of array structure parameters on electromagnetic characteristics. The research results show that this EIT wave-transmitting material has the characteristics of wide working frequency, high transmission rate, and insensitive to electromagnetic wave incident angle and polarization direction. In view of this, a multi-band broadband electromagnetic antireflection metamaterial with a multi-layer nested coupling structure (open resonant ring-chiral spiral ring-cross symmetrical structural unit) is designed, which is continuous in different polarized electromagnetic waves from 0 degrees to 80 degrees. Large-angle oblique incidence 11GHz, 15GHz, 33Ghz three-band high transmission rate, bandwidth up to 1.3GHz, 1.02GHz and 1.678GHz.
Designing with Video: Focusing the user-centred design process

Digital video for user-centred co-design is an emerging field of design, gaining increasing interest in both industry and academia. It merges the traditions of design ethnography, participatory design, interaction analysis, scenario-based design, and usability studies into an integrated approach, which values the designers capacity to study and change the world creatively. Designing with Video: Focusing the User-centred Design Process covers the whole user-centred design project. The book illustrates in detail how digital video can be utilised throughout a design process, from the early user studies, through making sense of the video content and envisioning the future with video scenarios, to provoking change with video artefacts. A must-read for those wishing to create more value through insightful design, the text builds upon a wealth of real, first-hand case studies both in academic and industrial contexts, and is complemented by video excerpts. Teachers, students and professionals in design will all benefit from this approach for developing new ways of enhancing their design processes.
Compressed image transmission in precoded OFDM VLC systems

In this paper, a compressed image transmission scheme is proposed in a precoded orthogonal frequency division multiplexing (OFDM)-based visible light communication (VLC) system. First, an image is divided into sub-block images; then, each block image is sampled by block-based compressive sensing (BCS) based on the Hadamard sparse basis matrix with a partial DCT measurement matrix. The resulting data are transformed into bit stream, which is transmitted in a DFT precoded OFDM-based VLC. We propose an integrated end-to-end OFDM-based VLC system platform, including BCS, quantization, VLC link, and OFDM transmission. The simulation results prove the effectiveness of the proposed simulation platform. The bit error rate (BER) and peak signal-to-noise ratio (PSNR) performances of the simulation platform are evaluated as well. The simulation results show that different images result in different BER and PSNR performances in the proposed precoded OFDM-VLC system. The larger the information entropy of images, the better the PSNR and BER performances. In addition, the PAPR of the DFT precoded OFDM can be significantly reduced compared to that of the conventional OFDM for compressed image data.
In regression testing without code

Software products are often built from commercial-off-the-shelf (COTS) components. When new releases of these components are made available for integration and testing, source code is usually not provided by the COTS vendors. Various regression test selection techniques have been developed and have been shown to be cost effective. However, the majority of these test selection techniques rely on source code for change identification and impact analysis. This dissertation presents a regression test selection (RTS) process called Integrated - Black-box Approach for Component Change Identification (I-BACCI) for COTS-based applications. The I-BACCI process reduces the test suite based upon changes in the binary code of the COTS component using the firewall analysis regression test selection method. This dissertation also presents Pallino, the supporting automation that statically analyzes binary code to identify the code change and the impact of these changes. Based on the output of Pallino and the original test suit, testers can determine the regression test cases needed that execute the application glue code which is affected by the changed areas in the new version of the COTS component. Five case studies were conducted on ABB internal products written in C/C++ to determine the effectiveness and efficiency of the I-BACCI process. The total size of application and component for each release is about 340∼930 KLOC. The results of the case studies indicate this process can reduce the required number of regression test by as much as 100% if there are a small number of changes in the new component in the best case. Similar to other RTS techniques, when there are many changes in the new component the I-BACCI process suggests a retest-all regression test strategy. With the help of Pallino, RTS via the I-BACCI process can be completed in about one to two person hours for each release of the case studies. Depending upon the percentage of test cases reduction determined by the I-BACCI process, the total time cost of the whole regression testing process can be reduced to 0.0003% of that by retest-all strategy in the best case. Pallino is extensible and can be modified to support other RTS methods for COTS components. Currently, Pallino works on components in Common Object File Format or Portable Executable formats.