Miracle-dz/UniFAR-FTUs huggingface dataset:
UIMigrate: Adaptive Data Migration for Hybrid Non-Volatile Memory Systems

Byte-addressable, non-volatile memory (NVRAM) combines the benefits of DRAM and flash memory. Its slower speed compared to DRAM, however, makes it hard to entirely replace DRAM with NVRAM. Hybrid NVRAM systems that equip both DRAM and NVRAM on the memory bus become a better solution: frequently accessed, hot pages can be stored in DRAM while other cold pages can reside in NVRAM. This way, the system gets the benefits of both high performance (from DRAM) and lower power consumption and cost/performance (from NVRAM). Realizing an efficient hybrid NVRAM system requires careful page migration and accurate data temperature measurement. Existing solutions, however, often cause invalid migrations due to inaccurate data temperature accounting, because hot and cold pages are separately identified in DRAM and NVRAM regions.Based on this observation, we propose UIMigrate, an adaptive data migration approach for hybrid NVRAM systems. The key idea is to consider data temperature across the whole DRAM-NVRAM space when determining whether a page should be migrated between DRAM and NVRAM. In addition, UIMigrate adapts workload changes by dynamically adjusting migration decisions as workload changes. Our experiments using SPEC 2006 show that UIMigrate can reduce the number of migrations and improves performance by up to 90.4% compared to existing state-of-the-art approaches.
Gait Classification of Healthy Young and Elderly Adults Using Micro-Doppler Radar Remote Sensing

This paper presents a radar-based technique for the gait classification of healthy young and elderly adults based on the difference in their balance ability. We propose a method for extracting the velocity parameters related to the balance ability during walking via micro-Doppler radar gait measurement. The experimental results show that significant gait differences between young and elderly adults exist in the extracted parameters. In particular, the effectiveness of the parameters related to leg motions in both stance and swing phases is verified. By using the extracted parameters, a support vector machine-based approach shows that two groups can be effectively classified.
Citation characteristics of research published in Emergency Medicine versus other scientific journals.

STUDY OBJECTIVE We sought to examine how a cohort of published emergency medicine research is cited in scientific journals. METHODS Data were collected on all research submitted to the 1991 Society for Academic Emergency Medicine meeting and subsequently published. Outcome measures included all citations of these studies found in journals listed in the Science Citation Index, as well as the impact factors (citations per manuscript per year) of citing journals. RESULTS Two hundred four of the 493 submitted studies were published and met study entry criteria; the average article was cited 2.04 times a year during the study period. Twelve percent were never cited, and 39% were cited only once or twice. Thirty percent were published in non-emergency medicine journals, and these were cited at least twice as often (and by almost 3 times as many journals) as apparently similar studies published in emergency medicine journals. The percentage of studies never cited by anyone was about threefold higher when published in emergency medicine journals. Forty-two percent of the citations of research published in emergency medicine journals came from within the specialty. Emergency medicine journals provided only 16% of the citations of emergency medicine research published in non-emergency medicine journals because these studies were cited 3 times as often by authors in other disciplines. Rejection of research for presentation at the meeting did not predict the number or quality of citations or citing journals. CONCLUSION Research submitted to the Society for Academic Emergency Medicine meeting and subsequently published is cited about as often as the average scientific journal article but receives more impact, is cited more widely, and is more likely to be cited by a broader range of authors when published by non-emergency medicine journals. The ability of emergency medicine journals to compete with larger non-emergency medicine journals for their larger audiences may help shape perceptions of the specialty.
Theory of mind and cognitive processes in aging and Alzheimer type dementia: a systematic review

Objectives: Theory of mind (ToM) performance in aging and dementia of the Alzheimer type (DAT) has been a growing interest of researchers and recently, theoretical trends in ToM development have led to a focus on determining the cognitive skills involved in ToM performance. The aim of the present review is to answer three main questions: How is ToM assessed in aging and DAT? How does ToM performance evolve in aging and DAT? Do cognitive processes influence ToM performance in aging and DAT? Method: A systematic review was conducted to provide a targeted overview of recent studies relating ToM performance with cognitive processes in aging and DAT. Results: Results suggest a decrease in ToM performance, more pronounced in complex ToM tasks. Moreover, the review points up the strong involvement of executive functions, especially inhibition, and reasoning skills in ToM task achievement. Conclusion: Current data suggest that the structure of ToM tasks itself could lead to poor performance, especially in populations with reduced cognitive abilities.
Effects of mechanical and chemical stimulation of fine muscle afferents upon primate spinothalamic tract cells.

1. Injections of algesic chemicals were made into the arterial circulation of the triceps surae muscles in anaesthetized monkeys. 2. The responses of a sample of primary muscle afferents suggest that what is known about the activation of muscle afferents in the cat by algesic agents applies also to the monkey. One exception to this is the activation of many group I afferents by KCl in the monkey, but not in the cat. 3. Many spinothalamic tract cells were powerfully excited by the intra‐arterial injection of algesic chemicals (bradykinin, 5‐hydroxytryptamine (5‐HT), KCl) in preparations in which the hind limb was denervated except for the nerves to the triceps surae muscles. The excitatory action of bradykinin had a slower time course than did that of 5‐HT or KCl. 4. A number of the spinothalamic tract cells which failed to respond to chemical activation of muscle afferents were located in lamina I of the spinal cord. 5. Repeated injections of bradykinin produced similar responses, whereas the effects of 5‐HT injections showed marked tachyphylaxis. 6. No evidence was obtained that activation of muscle spindle afferents by succinylcholine injections resulted in the excitation of spinothalamic tract neurones in the population sampled. 7. Injections of hypertonic NaCl into muscle or tendon produced a prolonged excitation of many spinothalamic tract cells. 8. It is concluded that a substantial proportion of primate spinothalamic tract cells receive a convergent input from cutaneous and muscle receptors. The muscle receptors involved appear to include primary afferents of group III and IV calibre. The possibility is suggested that such cells could play a role in the production of poorly localized pain.
THIS ARTICLE HAS BEEN RETRACTED Critical care nurse practitioners and clinical nurse specialists interface patterns with computer‐based decision support systems

Purpose: The purposes of this review are to examine the types of clinical decision support systems in use and to identify patterns of how critical care advanced practice nurses (APNs) have integrated these systems into their nursing care patient management practices. The decision‐making process itself is analyzed with a focus on how automated systems attempt to capture and reflect human decisional processes in critical care nursing, including how systems actually organize and process information to create outcome estimations based on patient clinical indicators and prognosis logarithms. Characteristics of APN clinicians and implications of these characteristics on decision system use, based on the body of decision system user research, are introduced. Data sources: A review of the Medline, Ovid, CINAHL, and PubMed literature databases was conducted using “clinical decision support systems,”“computerized clinical decision making,” and “APNs”; an examination of components of several major clinical decision systems was also undertaken. Conclusions: Use patterns among APNs and other clinicians appear to vary; there is a need for original research to examine how APNs actually use these systems in their practices in critical care settings. Because APNs are increasingly responsible for admission to, and transfer from, critical care settings, more understanding is needed on how they interact with this technology and how they see automated decision systems impacting their practices. Implications for practice: APNs who practice in critical care settings vary significantly in how they use the clinical decision systems that are in operation in their practice settings. These APNs must have an understanding of their use patterns with these systems and should critically assess whether their patient care decision making is affected by the technology.
Advanced Multi-Media Element for Simulating Distribution of Magnetic Flux Density Influenced by Narrow Crack

In order to calculate eddy current testing (ECT) signals due to a complex natural crack by using a regular mesh, the multi-media element (MME) was proposed by authors. In this paper, a new high-precision method for calculating the MME coefficient matrices is proposed and implemented in the finite-element method (FEM)–BEM hybrid code for ECT of narrow cracks. Through the comparison of the new MME solutions with those of the conventional FEM–BEM method, validity and efficiency of the new method and the corresponding numerical code are demonstrated. Eddy current perturbations and distributions of the magnetic flux density affected by a narrow crack of different directions are also numerically analyzed by using the new MME. In addition, the measurement results from the experiments give further support to the validity of the new MME method.
Aging-aware Lifetime Enhancement for Memristor-based Neuromorphic Computing

Memristor-based crossbars have been applied successfully to accelerate vector-matrix computations in deep neural networks. During the training process of neural networks, the conductances of the memristors in the crossbars must be updated repetitively. However, memristors can only be programmed reliably for a given number of times. Afterwards, the working ranges of the memristors deviate from the fresh state. As a result, the weights of the corresponding neural networks cannot be implemented correctly and the classification accuracy drops significantly. This phenomenon is called aging, and it limits the lifetime of memristor-based crossbars. In this paper, we propose a co-optimization framework combining software training and hardware mapping to reduce the aging effect. Experimental results demonstrate that the proposed framework can extend the lifetime of such crossbars up to 11 times, while the expected accuracy of classification is maintained.
On Biometric Identification Using Optical-Coherence-Tomography Data for Ophthalmic Patients

In this paper, a personal identification method is presented for patients visiting departments of ophthalmology. The proposed method prepares data from 32×256-sized matrices, which are inspection results measured by Optical Coherence Tomography, both at the stage of the registration and at that of the collation. It considers a three-tuple with one of top largest Pachymetry values and coordinates specifying its position in the matrix to be a characteristic point, and calculates degree of similarity between any couple of a three-tuple in the registered data and that in the collation data. It employs the sum of the above degrees to determine some subject with registered data as a person to be identified. In addition, it defines some threshold values associated with Instantaneous Keratometric, Reflective Keratometric, and Pachymetry, to eliminate false acceptance as much as possible. Experimental results establish that the proposed method can improve a false acceptance rate while keeping a high identification rate.
Implementation-aware design of image-based control with on-line measurable variable-delay

Image-based control uses image-processing algorithms to acquire sensing information. The sensing delay associated with the image-processing algorithm is typically platform-dependent and time-varying. Modern embedded platforms allow to characterize the sensing delay at design-time obtaining a delay histogram, and at run-time measuring its precise value. We exploit this knowledge to design variable-delay controllers. This design also takes into account the resource configuration of the image processing algorithm: sequential (with one processing resource) or pipelined (with multiprocessing capabilities). Since the control performance strongly depends on the model quality, we present a simulation benchmark that uses the model uncertainty and the delay histogram to obtain bounds on control performance. Our benchmark is used to select a variable-delay controller and a resource configuration that outperform a constant worst-case delay controller.
Enhancing the Additive Manufacturing process for spare parts by applying Agile Hardware Development principles

The availability of spare parts can turn into an issue, when those components are out of stock and cannot be reproduced easily. In this article, the German Federal Armed Forces serves as a prime example, since the equipment used is several decades old and due to that extended lifespan, its availability can turn into a significant problem, especially when the original documentation is unavailable. This article further develops the design process of manufacturing spare parts by means of additive manufacturing (AM), using a component of the military industry as a case study. The design of spare parts by means of AM is a complex task, which designers must face and in order to encounter the issues arising, it is possible to use principles and practices of agile hardware development to clarify and promote the robustness of that process. Using the concept of iterations and increments, the traceability and the quality of the spare parts produced is improved as well as the readiness of the overall process.
Design of Ergonomic Bipang Molding Tool to Increase Production of Bipang

Humans are a central point in a work system because basically humans are not only acting as planners and designers of work systems, but also as executors and controllers. Human limitations become a guideline in designing an ergonomic work system, where the focus of ergonomics involves three components, namely humans, machines / equipment and the environment that interact with each other which results in an inseparable work system. This study aims to determine the risk of skeletal muscle injury that is potentially experienced by bipang production operators, especially in bipang grading and filling activities. The method used to analyze the operator’s work posture is the quick exposure check (QEC) and rapid entire body assessment (REBA) methods, this research is carried out by direct observation of the research object, filling out the operator and observer questionnaires and conducting literature studies to collect data related to research. Based on the QEC method, the work posture of Bipang IKM employees on the flatten section has an exposure level of 66.67% while slicing bipang has an exposure level of 60.49% which means that further research and changes are needed. While using the REBA method, the bipang flatten activity obtained by the final score is 10, which means it is at a high level and immediate handling is needed, while the bipang slicing production process is at level 2 which means that immediate handling is needed, the position can cause muscle injury so it requires work improvement. By proposing improvements to work facilities so that the bipang flatten and slicing activities are carried out simultaneously, with a more efficient processing time of 10 minutes to 2 minutes and more optimal work productivity. Based on the REBA method, there is an action level 1 which means that the work posture can be accepted and there is no need for improvement. So that the increase in production when using bipang molding tool is 9,572 piece /day.
FIFOrder MicroArchitecture: Ready-Aware Instruction Scheduling for OoO Processors

The number of instructions a processor’s instruction queue can examine (depth) and the number it can issue together (width) determine its ability to take advantage of the ILP in an application. Unfortunately, increasing either the width or depth of the instruction queue is very costly due to the content-addressable logic needed to wakeup and select instructions out-of-order.This work makes the observation that a large number of instructions have both operands ready at dispatch, and therefore do not benefit from out-of-order scheduling. We leverage this to place such ready-at-dispatch instructions in separate, simpler, in-order FIFO queues for scheduling. With such additional queues, we can reduce the size and width of the expensive out-of-order instruction queue, without reducing the processor’s overall issue width and depth.Our design, FIFOrder, is able to steer more than 60% of instructions to the cheaper FIFO queues, providing a 50% energy savings over a traditional out-of-order instruction queue design, while delivering 8% higher performance.
M to 1 Joint Source-Channel Coding of Gaussian Sources via Dichotomy of the Input Space Based on Deep Learning

In this paper, we propose a deep neural network framework for Joint Source-Channel Coding of an m dimensional i.i. d. Gaussian source for transmission over a single additive white Gaussian noise channel with no delay. The framework employs two neural encoder-decoder pairs that learn to split the input signal space into two disjoint support sets. The encoder and the decoder are jointly trained to minimize the mean square error subject to a power constraint on the signal transmitted across the channel. The proposed method achieves results as good as the state of the art for m=3,4 and is easily extendable to higher dimensions. The trained model, we discovered, assigns almost equal probability to the disjoint support sets. The results show that the scheme performance is within 1.9dB of the Shannon optimal limit over a wide range of Channel Signal to Noise Ratios (CSNR) from 0dB to 30dB for various values of m. The method is also robust, i.e. employing a model trained at CSNR+/-5dB is only 0.6dB worse than a model trained specifically for that CSNR.
Scrub Unleveling: Achieving High Data Reliability at Low Scrubbing Cost

Nowadays, proactive error prediction, using ma-chine learning methods, has been proposed to improve storage system reliability by increasing the scrubbing rate for drives with higher error rates. Unfortunately, the majority of works incur non-trivial scrubbing cost and ignore the periodic characteristic of scrubbing. In this paper, we aim to make the prediction guided scrubbing more suitable for practical use. In particular, we design a scrub unleveling technique that enforces a lower rate scrubbing to healthy disks and a higher rate scrubbing to disks subject to latent sector errors (LSEs). Moreover, a voting-based method is introduced to ensure prediction accuracy. Experimental results on a real-world field dataset have demonstrated that our proposed approach can achieve lower scrubbing cost together with higher data reliability than traditional fixed-rate scrubbing methods. Compared with the state-of-the-art, our method can achieve the same level of Mean-Time-To-Detection (MTTD) with almost 32% less scrubbing.
ESD Reliability Study of a-Si:H Thin-Film Transistor Technology: Physical Insights and Technological Implications

In this paper, we present the detailed physical insights into the electrostatic discharge (ESD) behavior of hydrogenated amorphous silicon (a-Si:H)-based thin-film transistor (TFT) technology. Device failure under ESD conditions is studied in detail using electrical and optical techniques. Device degradation under ESD timescales is studied using real-time capacitance–voltage and a spatially variant degradation behavior is reported. Variations in material properties are studied before and after device failure using Raman spectroscopy. Device dimension-dependent failure mechanism is explored. Impact of stressing conditions and presence of top passivation on failure behavior is also explored. Failure physics of technologically relevant device architectures including diode-connected transistors (gated diodes) and drain underlap TFTs and their increased ESD robustness is discussed. Finally, ESD behavior of a-Si:H-based TFTs is discussed.
Notch-Filter Active Damping of LCL Filter Resonance in a Grid-connected Inverter with Variable Grid Inductance

The problem of LCL filter resonance is prominent in grid-connected voltage source converters with LCL filters. Various methods of damping the resonance have been proposed. This paper presents a simple but robust active damping solution based on a notch filter which is able to effectively damp the filter resonance for a range of grid impedance values. This scheme does not require measurement of the filter capacitor current, and therefore, does not increase the number of current sensors in the system. The notch filter active damping scheme is implemented in a grid-voltage sensorless virtual-flux based direct power control scheme, therefore, the only sensors required are grid current sensors. The model is created and analyzed in Matlab/Simulink and simulation results show that the system is stable, with a grid current THD of less than 5 % which met the grid requirements set by standard organizations.
Taming Data Caches for Predictable Execution on GPU-based SoCs

Heterogeneous SoCs (HeSoCs) typically share a single DRAM between the CPU and GPU, making workloads susceptible to memory interference, and predictable execution troublesome. State-of-the art predictable execution models (PREM) for HeSoCs prefetch data to the GPU scratchpad memory (SPM), for computations to be insensitive to CPU-generated DRAM traffic. However, the amount of work that the small SPM sizes allow is typically insufficient to absorb CPU/GPU synchronization costs. On-chip caches are larger, and would solve this issue, but have been argued too unpredictable due to self-evictions. We show how self-eviction can be minimized in GPU caches via clever managing of prefetches, thus lowering the performance cost, while retaining timing predictability.