Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Reinforcement Learning-Aided Bidding Strategies for Transactive Energy Market

The concept of transactive energy market (TEM) has been introduced to efficiently balance supply and demand across the electrical networks in a distributed manner. TEM allows consumers to sell/purchase a portion of their excess/lack of energy to/from other local consumers. In this article, a transactive framework is proposed for a distribution network in which transactive agents participate in a local market and submit their bids to local TEM for day-ahead planning. However, due to complexity of the market and effects of a multitude of factors in the market outcome, deriving the optimal bid is not a trivial task. In order to learn the optimal bidding strategy in such a complex system with incomplete information, soft actor-critic method is utilized. Two scenarios are analyzed and compared. The first scenario assumes only one agent uses the learning method, while in the second scenario a number of residents form a coalition with a representative learning agent. Then, allocation of power assigned to the whole coalition between its residents is discussed. Comprehensive simulations are conducted for the 37-bus IEEE distribution system in two different scenarios to compare nonlearner agents with learner agents in both scenarios.
Digital Media in the Classroom: A Study on How to Improve Guidance for Successful Collaboration and Learning in Student Teams

Digital video technologies provide a variety of functions to support collaborative knowledge construction. Yet, for novice learners, positive outcomes also depend on effective guidance of group interactions. In this paper, we present empirical evidence for the use of web-based video tools to support students’ collaborative learning in a history class. In an experiment with 16-year old learners (N=148) working with a history topic, we compared two contrasting types of guidance for student collaboration in dyads (cognitive task-related guidance or social interaction-related guidance). We also compared two types of video tools. Both types of guidance and tools were aimed at supporting students’ active, meaningful learning and critical reflection. Results indicate that social interaction-related guidance was more effective in terms of learning outcome (e.g., critical reflection skills) than cognitive taskrelated guidance. The different tools did not yield significant differences in learning. The practical implications of these results are discussed.
Factors influencing field performance: Utilizing the Drug Evaluation and Classification (DEC) program to identify suspected impaired drivers as reported by selected certified police officers in Texas

Factors Influencing Field Performance: Utilizing the Drug Evaluation and Classification (DEC) Program to Identify Suspected Impaired Drivers as Reported by Selected Certified Police Officers in Texas. (December 2008) Melissa Noggle Walden, B.S., The University of Alabama; M.S. Texas A&M University Co-Chairs of Advisory Committee: Dr. Homer Tolson Dr. Susan A. Lynham This study examined how decision-making training related to the Drug Evaluation and Classification (DEC) Program was transferred to law enforcement officers, referred to as drug recognition experts (DRE), for use in identifying and assessing impaired drivers. Specifically, this study explored how particular factors observed as part of the DEC Program’s decision-making process influence the DRE’s prediction of a drug category that was impairing a suspected impaired driver in the enforcement environment. Quantitative and qualitative methods were utilized to better understand the complexity of the DRE’s decision-making. Factors observed from 199 drug influence evaluations (DIE) were used as a basis for the quantitative analysis. In addition, feedback gleaned from the interviews conducted with six DREs was analyzed to identify themes that described the perceptive influence of those same factors on the DRE’s prediction of a drug category.
Resume Classification System using Natural Language Processing and Machine Learning Techniques

The selection of a suitable job applicant from the pool of thousands applications is often daunting job for an employer. The categorization of job applications submitted in form of Resumes against available vacancy(s) takes significant time and efforts of an employer. Thus, Resume Classification System (RCS) using the Natural Language Processing (NLP) and Machine Learning (ML) techniques could automate this tedious process. Moreover, the automation of this process can significantly expedite and transparent the applicants’ screening process with mere human involvement. This experimental study presents an automated NLP and ML-based RCS that classifies the Resumes according to job categories with performance guarantees. This study employs various ML algorithms and NLP techniques to measure the accuracy of RCS and proposes a solution with better accuracy and reliability in different settings. To demonstrate the significance of NLP and ML techniques for RCS, the extracted features were evaluated on nine ML classification models namely Support Vector Machine - SVM (Linear, SGD, SVC and NuSVC), Naïve Bayes (Bernoulli, Multinomial & Gaussian), K-Nearest Neighbor (KNN), and Logistic Regression (LR). The Term-Frequency-Inverse-Document-Frequency (TF-IDF) feature representation scheme was proved suitable for RCS. The developed models were evaluated using the Confusion Matrix, F-Score, Recall, Precision, and overall Accuracy. The experimental results indicate that using the One-Vs-Rest-Classification strategy for this multi-class Resume classification task, the SVM class of Machine Learning classifiers performed better on the study dataset of over nine hundred sixty plus parsed resumes with more than 96% accuracy. The promising results suggest that NLP and ML techniques employed in this study could be used for developing an efficient RCS.
Differential Trajectories of Fathers’ Postpartum Depressed Mood: A Latent Class Growth Analysis Approach

Parental psychological well-being is essential to the wellness of the family. However, longitudinal investigations into fathers’ postpartum depressed mood are limited. This study aimed to identify the typologies of depressed mood trajectories over the first year postpartum among Taiwanese fathers and to examine the factors associated with such typologies. We retrieved data from a nationwide longitudinal study on child development and care in Taiwan. A total of 396 fathers, who completed at least one of the three interviews when their children were 3, 6, and 12 months old between 2016 and 2017, were included in this analysis. Conditional latent class growth analysis was conducted to identify the classifications of the fathers’ depressed mood trajectories in the first year postpartum and to estimate the effects of covariates on individuals’ membership of a trajectory class. Three classes of depressed mood trajectories were identified. The high increasing group consisted of 11% of the participants; the moderate increasing and the low decreasing groups consisted of 28% and 61% of the participants, respectively. Financial stress was associated with the fathers’ likelihood of being in the high increasing group compared with their likelihood of being in the low decreasing group (OR = 2.28, CI = 1.16–4.47). The result may be related to the difference in gender roles and social expectations.
Effect of Manufacturing Inaccuracies on the Wake Past Asymmetric Airfoil by PIV

The effect of manufacturing geometry deviations on the flow past a NACA 64(3)-618 asymmetric airfoil is studied. This airfoil is 3D printed according to the coordinates from a public database. An optical high-precision 3D scanner, GOM Atos, measures the difference from the idealized model. Based on this difference, another model is prepared with a physical output closer to the ideal model. The velocity in the near wake (0–0.4 chord) is measured by using the Particle Image Velocimetry (PIV) technique. This work compares the wakes past three airfoil realizations, which differ in their similarity to the original design (none of the realizations is identical to the original design). The chord-based Reynolds number ranges from 1.6×104 to 1.6×105. The ensemble average velocity is used for the determination of the wake width and for the rough estimation of the drag coefficient. The lift coefficient is measured directly by using force balance. We discuss the origin of turbulent kinetic energy in terms of anisotropy (at least in 2D) and the length-scales of fluctuations across the wake. The spatial power spectral density is shown. The autocorrelation function of the cross-stream velocity detects the regime of the von Karmán vortex street at lower velocities.
The Expression of TP53-Induced Glycolysis and Apoptosis Regulator (TIGAR) Can Be Controlled by the Antioxidant Orchestrator NRF2 in Human Carcinoma Cells

Hyperactivation of the KEAP1-NRF2 axis is a common molecular trait in carcinomas from different origin. The transcriptional program induced by NRF2 involves antioxidant and metabolic genes that render cancer cells more capable of dealing with oxidative stress. The TP53-Induced Glycolysis and Apoptosis Regulator (TIGAR) is an important regulator of glycolysis and the pentose phosphate pathway that was described as a p53 response gene, yet TIGAR expression is detected in p53-null tumors. In this study we investigated the role of NRF2 in the regulation of TIGAR in human carcinoma cell lines. Exposure of carcinoma cells to electrophilic molecules or overexpression of NRF2 significantly increased expression of TIGAR, in parallel to the known NRF2 target genes NQO1 and G6PD. The same was observed in TP53KO cells, indicating that NRF2-mediated regulation of TIGAR is p53-independent. Accordingly, downregulation of NRF2 decreased the expression of TIGAR in carcinoma cell lines from different origin. As NRF2 is essential in the bone, we used mouse primary osteoblasts to corroborate our findings. The antioxidant response elements for NRF2 binding to the promoter of human and mouse TIGAR were described. This study provides the first evidence that NRF2 controls the expression of TIGAR at the transcriptional level.
On the comparison between compound louvered-vortex generator fins and X-shaped louvered fins

A recent evolution in heat exchanger design is the use of compound designs. One of the designs under study is a combination between a louvered fin and vortex generators. Several possible placements of the vortex generators are studied. These compound designs are compared with the X-shaped louvered fin, which maximizes the louvered area. It is shown that the X-shaped louvered fin exhibits the same heat transfer enhancement mechanism as the compound design, with respect to the rectangular louvered fin. The X-shaped louvered fin outperforms all of the compound designs.
TAF2-Net: Triple-Branch Attentive Feature Fusion Network for Ultrasonic Flaw Detection

Automatic defect detection is a critical task in the industrial production process. At present, many detection methods based on deep learning have been successfully applied in industrial defect detection systems. However, due to the complexity of the specimen defects, the data collected in practice are imbalanced and have intraclass differences and interclass similarities. These problems may reduce the accuracy of defect detection. This article proposes an ultrasonic defect detection system, which uses a novel triple-branch attentive feature fusion network (TAF2-Net) architecture to detect and classify the defects of specimens. We introduce the multiscale feature extraction (MSFE) module to extract multiscale features from the 1-D ultrasonic echo signal and 2-D time–frequency diagram in two branches and design the deep multimodal feature fusion (DMF2) module to enhance the features at different abstract levels. The fused features are unified through a sequential feature pyramid network (SFPN) and fed into gated recurrent unit (GRU) to extract global sequential features in the third branch. Finally, the features extracted from the multiscale feature extract-1-D (MSFE-1-D) module, multiscale feature extract-2-D (MSFE-2-D) module, and GRU are fused to obtain the final prediction results. Experimental results show that the TAF2-Net is superior to the most advanced method, with the accuracy of 96.54%. Meanwhile, to meet the requirement of hardware systems that lack of computing resources, we also propose a lightweight TAF2-small Net that can still achieve a classification accuracy of 93.6%.
Compact CPW UWB diversity slot antenna with dual band‐notched characteristics

A compact coplanar waveguide (CPW) fed ultrawideband (UWB) slot antenna for multiple‐input‐multiple‐output (MIMO)/diversity applications is presented in this letter. The antenna consists of two coplanar waveguides (CPWs) feeding circular radiating elements and a protruded stub, which is placed at 45° between them. The circular radiating elements are arrange orthogonally and fed perpendicularly to obtain polarization diversity. Notched band at X‐band communication downlinks is achieved by etching split ring resonator slots in the radiators and the other notched band at WLAN system is achieved by the collaboration of arc‐shaped strips and the protruded stub. The protruded stub not only can help to achieve band rejection but also can reduce mutual coupling between two ports. As all of the structures are printed in one layer, it can be very easily to be integrated with RF front‐end circuits. Simulated and measured results show that the proposed antenna meets the 10‐dB impedance bandwidth from 3.4 to 12 GHz and isolation better than 15 dB at most of the band. Good diversity performance in terms of envelope correlation coefficient and the ratio of mean effective gain demonstrates that the antenna is quite suitable for MIMO UWB applications. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:989–994, 2016
Evolutionary Computing based Web Service Composition Technique for Scheduling of Workload under Cloud Environment

Objectives: The objective of this model is to design a technique to schedule the workload for the computation of web services in the heterogeneous cloud environment. As the Web Service Composition (WSC) for the execution of scientiﬁc workload in a heterogeneous cloud computing environment is a challenging task. Modern workload requires dynamic resource provisioning technique as there exist parallelization among sub-tasks and diﬀerent task demands diﬀerent Quality of Service (QoS) requirement. Methods: This study presents an Evolutionary Computing based Web Service Composition (EC-WSC) technique to execute a large-scale scientiﬁc workload in a heterogeneous cloud environment. A multi-objective metric for improving energy eﬃciency and resource utilization is modelled. Then, an improved searching mechanism for the dragonﬂy evolutionary computing algorithm is modelled. Findings: Experiment outcomes show EC-WSC
INFORMATION THEORETIC AND SPECTRAL METHODS OF TEST POINT, PARTIAL-SCAN AND FULL-SCAN FLIP-FLOP INSERTION TO IMPROVE INTEGRATED CIRCUIT TESTABILITY

OF THE THESIS Information Theoretic and Spectral Methods of Test Point, Partial-Scan and Full-Scan Flip-Flop Insertion to Improve Integrated Circuit Testability by Raghuveer Ausoori Thesis Director: Prof. Michael L. Bushnell We present a radically new design for testability (DFT) algorithm, which inserts test points (TPs) and scanned flip-flops (SFFs) into large circuits to make them testable. The algorithm measures testability using Shannon’s entropy measure (from information theory), which will be shown to be a vastly superior way to measure testability, and spectral co-efficients. The spectral measures are superior in measuring fault coverage (FC) improvement. The algorithm can determine the DFT candidates using a gradient descent method or using an integer linear program (ILP). The optimal insertion of the TPs and SFFs reduces the amount of DFT hardware, since the algorithm trades off inserting a TP versus inserting a SFF. Various other derived measures are used and found to be effective in making the circuit testability better at various stages. The integer linear program finds the optimal solution to the optimization, and the testability measures are used to maximize information flow through the circuit-under-test (CUT). The result, on full-scan designs with test points, is a 40.05% reduction in test volume (TV)
Surviving downsizing

Downsizing is a trend that is likely to be with us and characterize management's response to ever increasing world competition until well after the turn of the century. Much has been written about the efficacy of this approach as to whether it is a viable, moral instrument to save and enhance organizations. Some would say that organizations become bloated and inefficient thus calling for radical surgical type operations to remove the excess "fat". Advocates of downsizing may see organizations as collections of employees-people-much like a crowd. By removing a few, the crowd is thinned out and the organization becomes more efficient. Those who question the appropriateness of this approach to management prefer to see the organization as a living organic, social institution. They say that the organization consists of many vital social networks. Downsizing they say devastates these social networks. This results in lowering of morale and loss of organizational memory. Both of these are important to the long range vitality of an organization. Much has been written and reported about the devastation that downsizing heaps upon the first victims, those whose employment is terminated from the organization. The New York Times featured this phenomenon the week that this paper was being written. The ratio of written word reporting on the outplaced victim to that written about the survivors was easily ten to one, if not more. Survivors of downsizing struggle to revitalize what is left of the organizations after downsizing is over. The author recently survived a downsizing and restructuring of his organization. He addresses first hand experiences about that situation.
Amateur translation and the development of a participatory culture in China : a netnographic study of The Last Fantasy fansubbing group

Triggered by globalisation and the increasing media convergence enabled by digital communication technologies, fansubbing has become one of the most observable aspects of Chinese participatory culture, both domestically and internationally. Informed by concepts drawn from the science of complexity and drawing on social self-organisation theory (Fuchs 2002), this study adopts a systems perspective and the method of netnography (Kozinets 2010) to bring to light the dynamics of collective identity formation in The Last Fantasy (TLF) fansubbing group, one of the most influential fansubbing networks in China. In particular, this study aims to reveal how TLF? s fansubbers deploy digital technologies to facilitate their daily subtitling activities, build and maintain their relationships, and express a collective voice in relation to the specific media context in China. Findings from this study are used to evaluate the role played by amateur translation, as exemplified by fansubbing activities carried out by TLF? s fansubbers, in China? s participatory culture. It is hoped that this study will enrich our understanding of the phenomenon of amateur translation in an increasingly networked society.
Semi-Automatic Town-Scale 3D Mapping using Building Information from Publicly Available Maps

The three-dimensional (3D) maps are used for self-positioning estimation and path planning for the autonomous navigation of robots in cities. This paper presents a framework for generating globally consistent 3D maps of urban areas. Our approach corrects consistent 3D maps by performing a 3D alignment with building information on publicly available maps. The framework automatically finds an appropriate anchor pose for the alignment and optimizes the pose graph according to the constraints obtained by the alignment. However, there are situations where it is difficult to automate 3D alignment because of measurement errors as well as errors in publicly available maps. To minimize operational costs, the proposed framework incorporates a user interface (UI) that allows users to check the results of 3D map alignment and make simple corrections. The framework was evaluated by conducting 3D mapping experiments in an urban area in Japan, and 3D mapping was performed over a distance of approximately 15 kilometers. The experimental results showed that the framework could automatically select anchor poses with high probability and generate a large-scale 3D city map with an average of approximately five manual operations per km by the user. The accuracy of the 3D mapping was evaluated by comparing it with a manually corrected reference trajectory based on an accurate 3D map from a commercial mobile mapping system (MMS). The 3D maps had an average absolute position error of 5.5, which is the lowest error compared to the maps generated by other open source software (OSS) SLAM methods.
Color Picture Tubes Life Test Bench

In this paper the particularities of color picture tubes life testing and test bench design are considered. The testing system and subsystems structures and engineering solutions are given. The software characteristics are discussed. The hardware and software of modern test bench must be flexible, as are shown. Ill. 5, bibl. 4 (in Lithuanian; summaries in Lithuanian, English and Russian).
Identification of a Five-Gene Panel to Assess Prognosis for Gastric Cancer

Methods Two datasets were used as training and validation cohorts to establish the predictive model. We used three types of screening criteria: background analysis, pathway analysis, and functional analysis provided by the cBioportal website. Fisher's exact test and multivariable logistic regression were performed to screen out related genes. Furthermore, we performed receiver operating characteristic (ROC) and Kaplan–Meier curve analyses to evaluate the correlation between the selected genes and overall survival. Result We screened five genes (KNL1, NRXN1, C6, CCDC169-SOHLH2, and TTN) that were highly related to recurrence of GC. The area under the receiver operating characteristic (ROC) curve was 0.813, which was much higher than that of the baseline model (AUC = 0.699). This result suggested that the mutation of five selected genes had a significant effect on the prediction of recurrence compared with other factors (age, stages, history, etc.). Furthermore, the Kaplan-Meier estimator also revealed that the mutation of five genes positively correlated with patient survival. Conclusions The patients who have mutations in these five genes may experience longer survival than those who do not have mutations. This five-gene panel will likely be a practical tool for prognostic evaluation and will provide another possible way for clinicians to determine therapy.