Miracle-dz/UniFAR-FTUs huggingface dataset:
The Application of Association Rules Mining in the Analysis of Students' Test Scores

Data mining from large amounts of data to extract efficient, implicit, potential useful knowledge and information, it has in many other areas has been successfully applied. However, the application in the field of education is relatively less. The central work of institutions of higher learning is teaching, the focus is to improve the quality of education, but students are precisely the basis for measuring the quality of teaching. The characteristic of this paper is to apply association rule mining method of university students' grades, previously unknown effects on student achievement factors of mining, to provide some valuable reference for teachers and administrators, to provide the necessary decision support for teaching and student management, to better carry out teaching, in order to improve the quality of teaching in Colleges and universities.
A Cross-Domain Approach to Designing an Unobtrusive System to Assess Human State and Predict Upcoming Performance Deficits

Many work environments are fraught with highly variable demands on cognitive workload, fluctuating between periods of high operational demand to the point of cognitive overload, to long periods of low workload bordering on boredom. When cognitive workload is not in an optimal range at either end of the spectrum, it can be detrimental to situational awareness and operational readiness, resulting in impaired cognitive functioning (Yerkes and Dodson, 1908). An unobtrusive system to assess the state of the human operator (e.g., stress, cognitive workload) and predict upcoming performance deficits could warn operators when steps should be taken to augment cognitive readiness. This system would also be useful during testing and evaluation (T&E) when new tools and systems are being evaluated for operational use. T&E researchers could accurately evaluate the cognitive and physical demands of these new tools and systems, and the effects they will have on task performance and accuracy. In this paper, we describe an approach to designing such a system that is applicable across environments. First, a suite of sensors is used to perform real-time synchronous data collection in a robust and unobtrusive fashion, and provide a holistic assessment of operators. Second, the best combination of indicators of operator state is extracted, fused, and interpreted. Third, performance deficits are comprehensively predicted, optimizing the likelihood of mission success. Finally, the data are displayed in such a way that supports the information requirements of any user. The approach described here is one we have successfully used in several projects, including modeling cognitive workload in the context of high-tempo, physically demanding environments, and modeling individual and team workload, stress, engagement, and performance while working together on a computerized task. We believe this approach is widely applicable and useful across domains to dramatically improve the mission readiness of human operators, and will improve the design and development of tools available to assist the operator in carrying out mission objectives. A system designed using this approach could enable crew to be aware of impending deficits to aid in augmenting mission performance, and will enable more effective T&E by measuring workload in response to new tools and systems while they are being designed and developed, rather than once they are deployed.
Human resource strategies, mature workers and competitive advantage : a resource-based view

The recent growth of the Australian economy has created labour and skills shortages. A key point is, however, that labour shortages in many areas, particularly service industries, could be filled by mature workers. Many of these workers will delay retirement or return to the workforce after retirement. One argument is that mature workers’ experience should be highly valued. Moreover, this cohort possesses superior knowledge to younger workers. Among other things, this relates to corporate knowledge, mature judgment, lower absenteeism, greater work ethic and reliability. Generally, mature workers are noted for their loyalty. Against a background of the resource-based view (RBV) at firm level, this paper seeks to demonstrate the increased benefits of utilising mature workers. We argue that when combined with superior HRM practices, it is possible for an organisation to improve its competitive advantage and increase productivity. We suggest, however, that organisations need to increase their focus on age-neutral attraction, retention and development policies.
Optimized Ge channel profiles for VLSI compatible Si/SiGe p-MOSFET's

Theoretical and experimental support is provided to demonstrate that, with the design constraint of a fixed Ge dose, the effective hole mobility and carrier confinement in SiGe MOSFET's are maximized by employing positively graded triangular Ge profiles in the channel. Hole mobilities in excess of 400 cm/sup 2/Vs were obtained experimentally for transistors with 0-50% triangular Ge channel profiles. When compared to devices with rectangular Ge profiles, the MOSFET's with triangular profiles demonstrated 30-40% improvement in mobility, transconductance and cutoff frequency. These results were observed for both MBE- and CVD-grown wafers. <<ETX>>
Do Manufacturing Firms Profit from Intraregional Innovation Linkages? An Empirical Based Answer

Nowadays, inter-firm linkages in the form of regional networks are seen as growth-promoting and important prerequisites for successful innovation activities in firms. Beginning with this hypothesis, the paper sets out to answer the question, whether manufacturing businesses with strong intraregional ties are more successful with respect to growth rates and innovative activities than those firms with little connection to their region. From a survey carried out in 10 European regions, the results verify that in spite of numerous network relationships on the national and international level small businesses are most likely to cooperate with others in their vicinity. In addition, the more knowledge-intensive innovation activities of businesses are, the more important is the relevance of spatial proximity in particular and networking in general.
“Let Our Ballots Secure What Our Bullets Have Won”: Union Veterans and the Making of Radical Reconstruction

After the Civil War, congressional Republicans used sweeping powers to expand and enforce civil rights for African Americans. Though the electoral benefits of African American suffrage were clear, Republicans had to overcome party divisions and racist voters. This paper argues that the war imbued Northern veterans with the belief that true victory required renewing the Union by abolishing slavery and establishing (imperfect) legal equality. This made veterans more receptive to Radical Reconstruction and ignited activism for it from below. Using difference-in-differences, I show that greater enlistment increased Republican vote share, particularly in pivotal postwar elections. Moreover, “as-if” random exposure to combat deaths increased Republican partisanship among soldiers after the war. Finally, I show that veterans became more likely to vote for African American suffrage. The paper concludes that Union veterans, through their votes and their activism, were a decisive part of the white coalition that backed America’s “Second Revolution. ”
to Corporate

Socially responsible activities done by the food-service companies increase corporate their competitiveness and can be used as a marketing strategy for the preparation for their future corporate image through positive word of consumer mouth. Food-service companies will lose competitiveness if they overlook socially responsible activities, which risks their long term sustainability. For one month, June 1 to June 30, 2014, after explaining the purpose and validity to staff and customers, the researcher asked them to complete a questionnaire via Self-administered Questionnaire Survey Method and gathered it.532 questionnaires out of 540 were returned and, excluding 22 insincerely replied questionnaires, 510 questionnaires were used for empirical analysis of the research material. he summary analysis for the research hypotheses are as follows :First, socially responsible activities(economic, charity and environmnetal responsibility) had a positive(+) effect on corporate image. Second, socially responsible activities had a positive(+) effect on long-term orientation.Third, socially responsible activities had a positive (+) effect on word of mouth. This study is worthwhile because it empirically confirms that food-service companies carry out socially responsible activities. his study confirms that socially responsible activities and business operations that fulfill this responsibility can be used as a marketing strategy, which reveals consumers’ value of social responsibility.
Optimization of Units Movement in Turn-Based Strategy Game

Each game has an artificial intelligence that is used to fight the player, which will provide more challenge. But in some strategy games, unit movements are usually done using simple considerations. For example the rest of unit lives, unit strength, and so forth. In this study, a turn based strategy game is designed using genetic algorithm to control the movement of the enemy armies. In each turn, the enemy will move based on the potential level of produced damage to and from the opponent, the distance between the units, and the distance to the opponent’s building. The genetic algorithm’s chromosome for each unit contains the following information: the position where the unit will move, who is the target, and the distance to the armies’ centroid. Distance to centroid (midpoint) is used to force the units to remain in the set. The genetic algorithm process is used to control when and where the units will move or attack. From the test results, the genetic algorithm can create a more powerful enemy than the randomly moving enemy because it creates a higher winning chance of enemy units and acts more efficiently, in terms of the usage of money, the damage produced to the opponent, and the received damage.
EFFECT OF TUBE DIAMETER AND SURFACE ROUGHNESS ON FLUID FLOW FRICTION FACTOR

Experiments have been performed to investigate the effect of channel roughness and diameter on fluid friction. Three different diameters and roughness of tubes were used to examine the friction factor. The first tube made of stainless steel with an inner diameter of 1.14 mm was investigated at Brunel University, whilst the others made of PVC with diameters of 17 mm and 15.5 mm rough were tested at Mataram University. The stainless steel was equipped with a 200 mm calming section and smooth one. The 15.5 mm diameter tube was coated internally with sand that had an average grain size of 0.5 mm so that the tube had a relative roughness of 0.032. The last tube with a diameter of 17 mm was smooth as explained in the H408 Fluid Friction Experimental Apparatus manual. The results indicate that the flow in the stainless steel tube still obeys the theory and in the 17 mm tube shows a deviation in friction factor with the theory. However, this was due to no calming section installed in the test rig. Flow in the rough tube (15.5 mm diameter) demonstrates that the Reynolds number does not affect the friction factor in turbulent regimes and the experimental friction factors were reasonably in a good agreement with the theory or Moody diagram. Hence, the effect of decreasing in diameter of channels on friction factor is insignificant.
ScholarWorks at WMU ScholarWorks at WMU Extraction Studies of Toxic Multiply Charged Oxoanions from Extraction Studies of Toxic Multiply Charged Oxoanions from Aqueous Media Using Nanojars Aqueous Media Using Nanojars

In this paper, the potential of nanojars as extracting agents of chromate and arsenate from aqueous media into a non-polar organic medium is investigated. Nanojars are a class of compounds that consist of multiple [cis-Cu II (µ-OH)(µ-pz)] n cyclic polymerization isomers (n = 6, 8, 9, 10, 12, 14; pz = pyrazolato anion) that form from self-assembly reactions around a multiply-charged oxoanion core with capping counterions to render an overall neutral complex. This incarcerates the anion, preventing it from escaping the complex without the use of any covalent bonding, making it a potentially highly effective and unique extracting agent. We have concluded that our system is capable of extracting both arsenate and chromate from water to below their respective EPA limits of 10 ppb and 100 ppb, and they do so better than another extracting agent, trioctylammonium nitrate. It has also been demonstrated in past publications by our group that nanojars are indeed capable of incarcerating the multiply-charged oxoanions via mass spectrophotometric and X-ray crystallographic analysis.
Optimization and comparison of superconducting generator topologies for a 10 MW wind turbine application

A direct-drive superconducting generator (DDSCG) is proposed for 10 MW wind turbines in the INNWIND.EU project. To fit the generator into the ”king-pin” conceptual nacelle design, the generator structure with inner stationary superconducting (SC) field winding and outer rotating copper armature winding is investigated in the first research phase. This paper presents a method using 2D finite element (FE) methods to minimize the active material cost of the ”king-pin” fitted DDSCG by optimizing the geometrical variables. By implementing this method, three typical superconducting generator topologies are compared in terms of the active material cost and mass, the synchronous reactance and the phase resistance. The optimization method and the comparison results provide the DDSCG designers with a guideline for selecting a suitable machine topology.
An Efficient Valid Page Crawling Approach for Websites with Dynamic Scripts

In times of Web 2.0, more and more websites adopt dynamic scripts for user interaction, and the switches between pages are no longer all based on the " " tags and the URL is no longer the unique identification of a Web page. Traditional Web crawlers can't deal with Web pages containing dynamic scripts, as a result, search engines, such as Google, give up these Web pages. The research on crawling website with dynamic scripts is still in the early stage. This paper proposes an efficient valid page crawling approach for websites with dynamic scripts. Firstly, by training the paper can get the events and the Web elements that triggered the events, which would lead the people to desired Web pages. Then, the paper generates the XPath patterns of these elements and record the events the people need to trigger. During crawling, the paper only considers these event and element combinations for accelerating the crawling. Additionally, the paper demonstrates the efficiency and the effectiveness of the approach by extensive experimental evaluation.
Massive mitochondrial degeneration in motor neurons triggers Massive mitochondrial degeneration in motor neurons triggers the onset of amyotrophic lateral sclerosis in mice expressing a the onset of amyotrophic lateral sclerosis in mice expressing a mutant SOD1 mutant SOD1

Amyotrophic lateral sclerosis (ALS) involves motor neuron degeneration, skeletal muscle atrophy, paralysis, and death. Mutations in Cu,Zn superoxide dismutase (SOD1) are one cause of the disease. Mice transgenic for mutated SOD1 develop symptoms and pathology similar to those in human ALS. To under-stand the disease mechanism, we developed a simple behav-ioral assay for disease progression in mice. Using this assay, we deﬁned four stages of the disease in mice expressing G93A mutant SOD1. By studying mice with deﬁned disease stages, we tied several pathological features into a coherent sequence of events leading to motor neuron death. We show that onset of the disease involves a sharp decline of muscle strength and a transient explosive increase in vacuoles derived from degenerating mitochondria, but little motor neuron death. Most motor neurons do not die until the terminal stage, ; 9 weeks after disease onset. These results indicate that mutant SOD1 toxicity is mediated by damage to mitochondria in motor neurons, and this damage triggers the functional decline of motor neurons and the clinical onset of ALS. The absence of massive motor neuron death at the early stages of the disease indicates that the majority of motor neurons could be rescued after clinical diagnosis.
Diverging current fluctuations in critical Kerr resonators

The parametrically pumped Kerr model describes a driven-dissipative nonlinear cavity, whose nonequilibrium phase diagram features both continuous and discontinuous quantum phase transitions. We consider the consequences of these critical phenomena for the fluctuations of the photocurrent obtained via continuous weak measurements on the cavity. Considering both direct photodetection and homodyne detection schemes, we find that the current fluctuations diverge exponentially at the discontinuous phase transition. However, we find strikingly different current fluctuations for these two detection schemes near the continuous transition, a behaviour which is explained by the complementary information revealed by measurements in different bases. To obtain these results, we develop formulas to efficiently compute the diffusion coefficient -- which characterises the long-time current fluctuations -- directly from the quantum master equation, thus connecting the formalisms of full counting statistics and stochastic quantum trajectories. Our findings highlight the rich features of current fluctuations near nonequilibrium phase transitions in quantum-optical systems.
Intuitive method for constructing effective field theories

We derive a novel method for constructing effective field theories. Physically, the method is very close to the intuition behind effective field theories: One can integrate out the heavier scale directly from the path integral. We give a detailed recipe for the effective field theory construction, which is nearly identical to the construction of the so-called 1PI effective action. We also demonstrate the equivalence of the novel method to the commonly used procedure of matching Green's functions.
M2R2: Missing-Modality Robust Emotion Recognition Framework With Iterative Data Augmentation

This article deals with the utterance-level modalities missing problem with uncertain patterns on emotion recognition in conversation (ERC) task. Present models generally predict the speaker's emotions by its current utterance and context, which is degraded by modality missing considerably. Our work proposes a framework missing-modality robust emotion recognition (M2R2), which trains emotion recognition model with iterative data augmentation by learned common representation. First, a network called party attentive network (PANet) is designed to classify emotions, which tracks all the speakers' states and context. Attention mechanism between speaker with other participants and dialogue topic is used to decentralize dependence on multitime and multiparty utterances instead of the possible incomplete one. Moreover, the common representation learning (CRL) problem is defined for modality-missing problem. Data imputation methods improved by the adversarial strategy are used here to construct extra features to augment data. Extensive experiments and case studies validate the effectiveness of our methods over baselines for modality-missing emotion recognition on two different datasets.
Performance and Design Comparison of a Bulk Thermoelectric Cooler with a Hybrid Device Architecture

ANTONIK, MARGARET. Performance and Design Comparison of a Bulk Thermoelectric Cooler with a Hybrid Device Architecture. (Under the direction of Dr. Scott Ferguson). This thesis compares the economic viability and performance outcomes of two different thermoelectric device architectures to determine the advantages and appropriate use of each configuration. Hybrid thermoelectric coolers employ thin-film thermoelectric materials sandwiched between a plastic substrate and formed into a corrugated structure. Roll-to-roll manufacturing and low-cost polymer materials offer a cost advantage to the hybrid architecture at the sacrifice of performance capabilities while conventional bulk devices offer increased performance at a higher cost. Performance characteristics and cost information are developed for both hybrid and conventional bulk single-stage thermoelectric modules. The design variables include device geometry, electrical current input, and thermoelectric material type. The trade-offs between cooling performance and cost will be explored and the thermoelectric system configuration analyzed for both hybrid and conventional bulk thermoelectric coolers. © Copyright 2015 Margaret Antonik All Rights Reserved Performance and Design Comparison of a Bulk Thermoelectric Cooler with a Hybrid Device Architecture
Neural 3D Scene Reconstruction with the Manhattan-world Assumption

This paper addresses the challenge of reconstructing 3D indoor scenes from multi-view images. Many previous works have shown impressive reconstruction results on textured objects, but they still have difficulty in handling low-textured planar regions, which are common in indoor scenes. An approach to solving this issue is to incorporate planer constraints into the depth map estimation in multiview stereo-based methods, but the per-view plane estimation and depth optimization lack both efficiency and multiview consistency. In this work, we show that the planar constraints can be conveniently integrated into the recent implicit neural representation-based reconstruction methods. Specifically, we use an MLP network to represent the signed distance function as the scene geometry. Based on the Manhattan-world assumption, planar constraints are employed to regularize the geometry in floor and wall regions predicted by a 2D semantic segmentation network. To resolve the inaccurate segmentation, we encode the semantics of 3D points with another MLP and design a novel loss that jointly optimizes the scene geometry and semantics in 3D space. Experiments on ScanNet and 7-Scenes datasets show that the proposed method outperforms previous methods by a large margin on 3D reconstruction quality. The code and supplementary materials are available at https://zju3dv.github. io/manhattan_sdf.
MMINR: Multi-frame-to-Multi-frame Inference with Noise Resistance for Precipitation Nowcasting with Radar

Precipitation nowcasting based on radar echo maps is essential in meteorological research. Recently, Convolutional RNNs based methods dominate this field, but they cannot be solved by parallel computation resulting in longer inference time. FCN based methods adopt a multi-frame-to-single-frame inference (MSI) strategy to avoid this problem. They feedback into the model again to predict the next time step to get multi-frame nowcasting results in the prediction phase, which will lead to the accumulation of prediction errors. In addition, precipitation noise is a crucial factor contributing to high prediction errors because of its unpredictability. To address this problem, we propose a novel Multi-frame-to-Multi-frame Inference (MMI) model with Noise Resistance (NR) named MMINR. It avoids error accumulation and resists precipitation noiseś negative effect in parallel computation. NR contains a Noise Dropout Module (NDM) and a Semantic Restore Module (SRM). NDM deliberately dropout noise simple yet efficient, and SRM supplements semantic information of features to alleviate the problem of semantic information mistakenly lost by NDM. Experimental results demonstrate that MMINR can attain competitive scores compared with other SOTAs. The ablation experiments show that the proposed NDM and SRM can solve the aforementioned problems.