Miracle-dz/UniFAR-FTUs huggingface dataset:
Postal Automation ZIP + 4 Technology: A Decision Analysis

The US Postal Service recently decided to continue the nine-digit zip code ZIP + 4 for first class business mailers and to purchase additional capital equipment as part of postal automation. Prior to this decision, the Office of Technology Assessment OTA and its contractors performed technical and economic analyses and evaluations of the options available to the US Congress and the Postal Service. Postal automation options involved capital investments of over $350 million and annual maintenance and other costs that could escalate to over $300 million a year. However, potential annual savings of up to $1.5 billion from reduced clerk and carrier costs were possible but highly uncertain. This decision analysis was the basis for OTA's economic evaluations in the face of uncertainty.
Design, Manufacturing, and Acoustical Analysis of a Helmholtz Resonator-Based Metamaterial Plate

Acoustic metamaterials are materials artificially engineered to control sound waves, which is not possible with conventional materials. We have proposed a design of an acoustic metamaterial plate with inbuilt Helmholtz resonators. The plate is made of Polylactic acid (PLA) which is fabricated using an additive manufacturing technique. It consists of Helmholtz resonator-shaped cavities of different sizes. In this paper, we have analyzed the acoustic properties of the Helmholtz resonators-based metamaterial plate experimentally as well as numerically. The experimental results are in good agreement with the numerical results. These types of 3D-printed metamaterial plates can find their application where high sound transmission loss is required to create a quieter ambience. There is an additional advantage of being lightweight because of the Helmholtz resonator-shaped cavities built inside the plate. Thus, these types of metamaterial plates can find their application in the design sector requiring lighter materials with high sound transmission loss.
Restoration Strategy for Active Distribution Systems Considering Endogenous Uncertainty in Cold Load Pickup

Cold load pickup (CLPU) phenomenon is identified as the persistent power inrush upon a sudden load pickup after an outage. Under the active distribution system (ADS) paradigm, where distributed energy resources (DERs) are extensively installed, the decreased outage duration can induce a strong interdependence between CLPU pattern and load pickup decisions. In this paper, we propose a novel modelling technique to tractably capture the decision-dependent uncertainty (DDU) inherent in the CLPU process. Subsequently, a two-stage stochastic decision-dependent service restoration (SDDSR) model is constructed, where first stage searches for the optimal switching sequences to decide step-wise network topology, and the second stage optimizes the detailed generation schedule of DERs as well as the energization of switchable loads. Moreover, to tackle the computational burdens introduced by mixed-integer recourse, the progressive hedging algorithm (PHA) is utilized to decompose the original model into scenario-wise subproblems that can be solved in parallel. The numerical test on modified IEEE 123-node test feeders has verified the efficiency of our proposed SDDSR model and provided fresh insights into the monetary and secure values of DDU quantification.
Effect of Frequency Coupling on Stability Analysis of a Grid-Connected Modular Multilevel Converter System

Due to the internal dynamics of the modular multilevel converter (MMC), the coupling between the positive and negative sequences in impedance, which is defined as frequency coupling, inherently exists in MMC. Ignoring the frequency coupling of the MMC impedance model may lead to inaccurate stability assessment, and thus the multi-input multi-output (MIMO) impedance model has been developed to consider the frequency coupling effect. However, the generalized Nyquist criterion (GNC), which is used for the stability analysis of an MIMO model, is more complicated than the stability analysis method applied on single-input-single-output (SISO) models. Meanwhile, it is not always the case that the SISO model fails in the stability assessment. Therefore, the conditions when the MIMO impedance model needs to be considered in the stability analysis of an MMC system should be analyzed. This paper quantitatively analyzes the effect of frequency coupling on the stability analysis of grid-connected MMC, and clarifies the frequency range and grid conditions that the coupling effect required to be considered in the stability analysis. Based on the quantitative relations between the frequency coupling and the stability analysis of the grid-connected MMC system, a simple and accurate stability analysis method for the grid-connected MMC system is proposed, where the MIMO impedance model is applied when the frequency coupling has a significant effect and the SISO impedance model is used if the frequency coupling is insignificant.
Gear Fault Diagnosis Based on Variational Modal Decomposition and Wide+Narrow Visual Field Neural Networks

In modern industrial production, rotating machinery plays an important role. The gears in this machinery adjust the speed and transmission of torque. Therefore, when the gear fails, it is very important to be able to diagnose the fault quickly and accurately. Gear vibration signals are often used in gear fault diagnosis, but the fault signal is often overwhelmed by noises. To enable the scientific and efficient detection of faults, this study proposes a gear fault diagnosis method based on variational modal decomposition (VMD) and wide+narrow visual field neural networks (WNVNNs), namely VMD-WNVNN. VMD-WNVNN consists of two stages. In the feature extraction stage, VMD and Pearson correlation coefficients are used to decompose and reconstruct the original data to obtain the features of these data in the frequency domain. In the classification stage, WNVNN is used to classify the data based on features. The final results of the gear fault diagnosis experiments show that this method not only has higher classification accuracy but also has higher classification stability than other recently proposed methods. Note to Practitioners—The gearbox is composed of many mechanical parts, such as gears, shafts, and bearings. Therefore, the vibration signal collected by the vibration sensor on the gearbox housing will contain the vibration signal of each part and the noise caused by processing errors. Therefore, if some methods can be used to efficiently extract the characteristic signals required for diagnosis in the data processing stage, the efficiency of fault diagnosis will be greatly improved. This article takes the health of gears as the research object and proposes a method that combines adaptive signal decomposition and deep learning technology. Experimental results show that this method has higher classification accuracy and classification stability than other methods proposed recently.
Ultra-lightweight true random number generators

A series of ultra-lightweight digital true random number generators (TRNGs) are presented. These TRNGs are based on the observation that, when a circuit switches from a metastable state to a bi-stable state, the resulting state may be random. Four such circuits with low hardware cost are presented: one uses an XOR gate; one uses a lookup table; one uses a multiplexer and an inverter; and one uses four transistors. The three TRNGs based on the first three circuits are implemented on a field programmable gate array and successfully pass the DIEHARD RNG tests and the National Institute of Standard and Technology (NIST) RNG tests. To the best of the authors' knowledge, the proposed TRNG designs are the most lightweight among existing TRNGs.
A Fuzzy Controller for Space Manipulator Systems

In this paper, a robust robotic controller algorithm is developed using a fuzzy logic structure. A general rule base is formulated using quantization tables in conjunction with traditional PID control. This hybrid fuzzy controller has an advantage in that a broader range of uncertainties, including unknown initial conditions, may still be addressed and stabilized using this structure. An off-line tuning approach has been investigated using phase portraits to gain further insight into the algorithm. The approach has been tested in simulation on a threedegree of freedom revolute manipulator model as well as other system dynamics.
Appending Global to Local features for Skin Lesion Classification on Dermoscpic Images

Skin cancer is the deadliest diseases compared with all other kinds of cancer. In this paper various pre- and post-treatments are proposed for improving automated melanoma diagnosis of dermoscopy images. At first pre-processing have done to exclude unwanted parts, a new triple-A segmentation proposes to extract lesion according to their histogram patterns. Lastly, suggest appending process with testing many factors for superior detection decision. This paper offers a novel approach with testing different detection rules: first system used fuzzy rules based on a different features, a second test has been done by modeled local colours with bag-of-features classifier. Then proposed adding lesion shape on two previous systems as their global form in the first one, while distributing it and appending with local colour patches in the second system. For each case, different features; various colour models, and many other parameters are examined to decide which settings are more discriminating. Evaluates performance of each method has carried out on (ISIC2019 Challenge) dermoscopic database. The novel processes with their a specific parameters are rising the classification accuracy to 98.26%.
“You’re not here for the right reasons!” From The Bachelorette to Instagram Influencer

ABSTRACT Despite vast research on reality television (RTV) and The Bachelor (2002) franchise specifically, most scholarship focuses on its appeal or negative impact on viewers. The inclusion of social media analysis is under-used in research on the series or any of its offshoots. Our work, however, analyzes how the women of The Bachelorette make the transition to influencer status on Instagram. Through critical visual analysis, we build on the theoretical concept of postfeminist nirvana, and show how this idealized, gendered state manifests across platforms. Our findings indicate that postfeminist nirvana has evolved in its aesthetic output and the women’s digital labor practices. This research demonstrates how postfeminist ideas are perpetuated across media platforms and intersects with studies of RTV, social media influencers, and postfeminist media texts.
Performance feedback in a group contest: A field experiment on electricity conservation

We conduct a field experiment to study whether revealing both the competitive state and the social state in a group contest affects individual beliefs and efforts. Our experiment randomizes group composition, participation in the contest, and types of information received in the contest. We find that contestants without feedback about relative performance had difficulty assessing their group’s competitive status, and laggards within a group tended to be overconfident about their relative contribution. In addition, we find that contestants receiving both competitive and social information were more likely to have correct beliefs about their positions during the contest and exerted the most effort, while contestants receiving no performance feedback did not behave differently from those who did not participate in the contest. Our results support the notion that providing feedback matters in a group contest.
Designing filters for polyphase filter banks

The authors are concerned the filter design problem for a recently-proposed polyphase filter bank with an arbitrary number of subband channels. They have developed an analytical formula for the design of a prototype filter used in the polyphase filter bank. Compared with direct numerical design methods, this formula-based method allows the design of the required FIR lowpass prototype filter with a much lower complexity of operation and better filter bank performance. The theoretical results are further extended to two dimensions. Examples are also presented.
Exploring the Influence of Beliefs of Instructors on Adoption of Technology in Teaching

The implementation of Emergency Remote Teaching (ERT) due to Covid-19 pandemic resulted in classes being taught online. This research study examines computer-mediated instruction as it is influenced by beliefs of English-language instructors, and how those instructors make sense of their beliefs regarding computer-mediated online instruction tools. An Interpretative Phenomenological Analysis (IPA) research design was used. English-language instructors employed full-time in universities in Tokyo participated in this study. It appeared that each instructor’s beliefs interacted in a complex manner to technology which impacted instructors’ teaching practices related to the use of computer-mediated instruction. It revealed a multifaceted relationship between what instructors’ think and what they do in class in relation to computer-mediated tasks. Findings of this study suggest that English language instructors are navigating competently, yet cautiously in the digital age. This study suggests technology integration into the English language curriculum will require a greater collaborative effort by relevant stakeholders in recognizing instructors’ beliefs as vital to technology acceptance
Effective fault localization and context‐aware debugging for concurrent programs

Concurrent programs are difficult to debug because concurrency faults usually occur under specific inputs and thread interleavings. Fault localization techniques for sequential programs are often ineffective because the root causes of concurrency faults involve memory accesses across multiple threads rather than single statements. Previous research has proposed techniques to analyse passing and failing executions obtained from running a set of test cases for identifying faulty memory access patterns. However, stand‐alone access patterns do not provide enough contextual information, such as the path leading to the failure, for developers to understand the bug. We present an approach, Coadec, to automatically generate interthread control flow paths that can link memory access patterns that occurred most frequently in the failing executions to better diagnose concurrency bugs. Coadec consists of two phases. In the first phase, we use feature selection techniques from machine learning to localize suspicious memory access patterns based on failing and passing executions. The patterns with maximum feature diversity information can point to the most suspicious pattern. We then apply a data mining technique and identify the memory access patterns that occurred most frequently in the failing executions. Finally, Coadec identifies faulty program paths by connecting both the frequent patterns and the suspicious pattern. We also evaluate the effectiveness of fault localization using test suites generated from different test adequacy criteria. We introduce and have evaluated Coadec on 10 real‐world multithreaded Java applications. Results indicate that Coadec outperforms state‐of‐the‐art approaches for localizing concurrency faults and that Coadec's context debugging can help developers understand concurrency fault by inspecting a small percentage of code.
Power aware floorplanning in multiple supply voltage domain

Floorplanning in this nano‐scale era involves consideration of various other objectives apart from minimizing wirelength in a fixed outlined region. In recent era of electronic devices, reducing power consumption is an important objective which can be achieved by multiple supply voltage island aware floorplanning. Optimizing power routing resource to simplify power planning while reducing voltage drop or IR drop (represented by maximum power length) is the major goal of the proposed work. Moreover, it has been observed that locations of blocks and power pads are important considerations for IR drop optimization. The proposed work hence concentrates on generating efficient floorplan with respect to wirelength, power routing resource, and IR drop. The proposed technique uses effective heuristics along with a SAT (Boolean satisfiability)‐based framework to generate efficient floorplan considering all factors. The experimental validation depicts good results with respect to power resource, wirelength, and voltage drop in a fixed outline framework.
Selling, buying and eating – a synthesis study on dietary patterns across language regions in Switzerland

PurposeCross-cultural studies on differences in eating and consumer behavior have several limitations due to differences between countries, for example, in national health policies. Switzerland combines cultural diversity between the language regions, but with a common national health policy. Therefore, Switzerland provides an ideal framework to investigate cross-cultural eating and consumer behavior. The aim of this study was to combine food consumption, purchase data and sales data to obtain a more comprehensive understanding of cultural dietary differences.Design/methodology/approachSix national Swiss studies on food consumption, one study of food sales from the largest supermarket chain in Switzerland and one national study of food purchasing were included. The estimated marginal mean of each food category in each language region was calculated using linear regression and respective linear random effect models.FindingsIn the French- and Italian-speaking regions more fish was sold, bought and consumed than in the German-speaking region of Switzerland. In contrast, in the German-speaking region, more milk and dairy products were sold, bought and consumed. Language regions explained sales, purchase and consumption of foods, but the findings were only consistent for fish and milk and dairy products.Originality/valueIf possible limitations of cross-culture studies between countries are eliminated, cultural eating and consumer differences are still visible, even in a small country like Switzerland. For the first time, the complexity of studying food consumption, purchasing and sales is shown in one study. This indicates the importance of further studies which consider these three perspectives to better understand cultural differences in eating and consumption behavior.
Developmental Trajectories of Justice System-Involved Friendship Proportion: Relevance for Predicting Continued Offending Risk in Emerging Adulthood

There is limited research which has examined the developmental nature of friendships and their relevance for offending. This study examined heterogeneity in the development of justice system-involved friendship proportionality and its relevance for predicting offending continuity in emerging adulthood. Having a greater proportion of such peers within a friendship collective as individuals exit adolescence may lead to continued risk of offending in adulthood. The Pathways to Desistance data were used in analyses. Group-based trajectory modeling was used to identify developmental patterns of justice system-involved friendship proportionality during adolescence and emerging adulthood. Logistic regression was used to assess the relevance of trajectory group assignment for predicting offending risk in emerging adulthood. Findings indicated that a six-group trajectory model best fit the data. All other trajectory groups in the model indicated a lower risk of offending in emerging adulthood than the High Chronic justice system-involved friendship proportionality group. Sensitivity analyses indicated that separation from criminal peers following adolescence may be a more conservative predictor of offending risk in emerging adulthood.
Variable speed control: state-of-the-art and synthesis

In its policy to fight congestion, the Dutch Ministry of Transport in 1996 launched a program of measures, called Samen werken aan bereikbaarheid (go-operation for accessibility), to be implemented in the short term. In this program, special interest is directed towards a group of measures in the area of dynamic traffic management. One of these measures is the dynamic control of speed limits on motorways. In addition, variable speed control on motorways has also attained interest as a measure to improve traffic safety and reduce environmental pollution. In order to achieve the required short term implementation of the variable control of speed limits on motorways, the ministry has set up a three stage plan. The respective stages of this plan are: investigation of available knowledge; pilot application; and implementation. This paper presents the results of the investigation stage - the state-of-the-art of variable speed control on motorways.
Control of grid side converter in wind power based PMSG with PLL method

Wind power is one of the most promising renewable energy sources. Due to a constantly increasing penetration rate in power grids in order to comply with interconnection requirements. This article targets the impact of a permanent magnet synchronous generator (PMSG) which is the subject of most attention due to low cost and maintenance requirements, driven by a wind turbine with the necessary power electronic converters that allow wind turbines to operate at variable speed, and connected to the grid for power generation more efficiently by the phase-locked loop (PLL) method in order to synchronize it. Thus, the proposed control technicals are based on vector control (VC) to achieve maximum power point tracking (MPPT), keep the DC link voltage constant, and control the speed and current at the generator side and grid side in PMSG which provides controllability of the reactive power supplied to the network. Therefore, the response of the PLL is analyzed and the simulation results of the dynamic model of the system is developed in Matlab / Simulink. The study results exhibit the excellent performance with high robustness, by improving the system efficiency to 98.72%.
An Efficient Method of Deadlock Detection and Recovery for Flexible Manufacturing Systems by Resource Flow Graphs

Deadlocks are a highly undesirable situation in flexible manufacturing systems (FMSs). This article presents a direct and novel method to detect such markings by constructing the resource flow graph of a Petri net that models an FMS and to recover such markings by adding a set of recovery transitions. First, an algorithm is developed to build a new kind of directed graph called the resource flow graph of a Petri net. Resource flow graphs can well represent the competition for shared resources by different processes. Second, based on the resource flow graph, loop graphs can be found. Furthermore, partial deadlock markings can be easily detected due to their relationship with loop graphs. Then, we propose an algorithm to design a set of recovery transitions for loop graphs that are enabled at partial deadlock markings. The proposed approach can detect partial deadlock markings without generating a complete reachability graph of a Petri net and the resulting net is deadlock-free with all reachable markings by adding the obtained recovery transitions. Finally, some widely used examples are provided to demonstrate the proposed approach. Note to Practitioners—The occurrence of deadlocks in an FMS tends to cause unnecessary productivity costs and even catastrophic results. In the framework of Petri nets, reachability graph analysis can usually obtain a maximally permissive supervisor of a plant. However, it is rather inefficient since it suffers from the state explosion problem. In this particular research, we develop an off-line deadlock detection and recovery policy by setting a group of virtual events that are not present in a physical model. The proposed approach is computationally efficient since it does not require to generate a reachability graph. It guarantees that the resulted system is deadlock-free with its all original reachable markings.