Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Multi-parameter Performance Modeling

Tuning large applications requires a clever exploration of the design and configuration space. Especially on supercomputers, this space is so large that its exhaustive traversal via performance experiments becomes too expensive, if not impossible. Manually creating analytical performance models provides insights into optimization opportunities but is extremely laborious if done for applications of realistic size. If we must consider multiple performance-relevant parameters and their possible interactions, a common requirement, this task becomes even more complex. We build on previous work on automatic scalability modeling and significantly extend it to allow insightful modeling of any combination of application execution parameters. Multi-parameter modeling has so far been outside the reach of automatic methods due to the exponential growth of the model search space. We develop a new technique to traverse the search space rapidly and generate insightful performance models that enable a wide range of uses from performance predictions for balanced machine design to performance tuning.
The “male” privilege of White women, the “White” privilege of Black women, and vulnerability to violence: an intersectional analysis of Peace Corps workers in host countries

ABSTRACT This article is an intersectional analysis of race, gender, and nationality in development work. Using interview, document, and observational data, I situate this inquiry in the context of US women’s work in the Peace Corps, an organization within a field marked by colonialism. I find that White women and women of color have similar and yet instructively different experiences of their gendered identities in field sites, because race and gender differently affect their identities and relative privilege abroad. Specifically, White women volunteers are often afforded some degree of “male” privilege because of their race (though their race may render them vulnerable to sexual violence), while some volunteers of color are afforded a degree of “White” privilege because of their nationality (although their race may also render them vulnerable to violence). However, because the Peace Corps does not challenge conventional race and gender privileges, it lacks the organizational orientation and capacity to effectively address safety and assault among its women volunteers.
Blending realities in game space

Modes of representation in digital games are explored in terms of game aesthetics, structure, and logic. A model for “world-making” is developed that identifies key components of digital media language and their relationship to shifting modes of representation. These ideas are demonstrated through three art works created by the Idea-ON>! , Iconica, and Semiomorph. The final work, Semiomorph, combines the theory of “semiotic morphism” with gameplay to create a digital game that generates blended realities. This work is described and analyzed in detail to illustrate the proposed model.
Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems

Big deep neural network (DNN) models trained on large amounts of data have recently achieved the best accuracy on hard tasks, such as image and speech recognition. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. To enable training of extremely large DNNs, models are partitioned across machines. To expedite training on very large data sets, multiple model replicas are trained in parallel on different subsets of the training examples with a global parameter server maintaining shared weights across these replicas. The correct choice for model and data partitioning and overall system provisioning is highly dependent on the DNN and distributed system hardware characteristics. These decisions currently require significant domain expertise and time consuming empirical state space exploration. This paper develops performance models that quantify the impact of these partitioning and provisioning decisions on overall distributed system performance and scalability. Also, we use these performance models to build a scalability optimizer that efficiently determines the optimal system configuration that minimizes DNN training time. We evaluate our performance models and scalability optimizer using a state-of-the-art distributed DNN training framework on two benchmark applications. The results show our performance models estimate DNN training time with high estimation accuracy and our scalability optimizer correctly chooses the best configurations, minimizing the training time of distributed DNNs.
Development of power control module in RFID reader circuit: A Mentor Graphic simulation approach

As the technology of automatic identification using radio frequency called RFID which is expected to be the alternative of the next generation barcode improves, concerns to the privacy infringement grow harder. In recent years, there has been growing interest in the development of communication systems for the localization and the identification of objects. This paper concerns the development of power splitter design for power control module in RFID reader circuit. In this work, a noble transformer type Wilkinson unequal power splitter was developed using Mentor Graphic. In order to extract the best RF performance from the power splitter, it was optimally designed using a newly proposed method. The power splitter supported highly improved RF characteristics in industrial scientific and medical (ISM) band gigahertz regions. It exhibited a bandwidth that extended from 2.5 GHz to 3 GHz, return loss 19.6 dB and isolation values 5.4 dB.
Caregivers in China: Knowledge of Mild Cognitive Impairment

This study aimed to examine the experience and knowledge of mild cognitive impairment (MCI) among Chinese family caregivers of individuals with MCI. The sample was recruited from memory clinics in Zhongnan Hospital in Wuhan, China. In-depth semi-structured interviews were used. Thirteen family members of individuals diagnosed with MCI participated in the study. Data analysis revealed three themes: 1) initial recognition of cognitive decline; 2) experience of the diagnosis of MCI; 3) perception of cognitive decline as a normal part of aging. While family members recognized the serious consequences of memory loss (e.g. getting lost), they would typically not take their family members to see a doctor until something specific triggered their access to the medical care system. The Chinese traditional perception of dementia as part of normal aging may serve to lessen the stigma of individuals with MCI, while the term “laonian chidai” which literally translates to “stupid, demented elderly” may exacerbate the stigma associated with individuals with MCI. It is suggested that family members’ worries may be relieved by improving their access to accurate knowledge of the disease, community-based and institutional care services, and culturally appropriately words are needed for MCI.
TEXT SUMMARIZATION EVALUATION: CORRELATING HUMAN PERFORMANCE ON AN EXTRINSIC TASK WITH AUTOMATIC INTRINSIC METRICS

This research describes two types of summarization evaluation methods, intrinsic and extrinsic, and concentrates on determining the level of correlation between automatic intrinsic methods and human task-based extrinsic evaluation performance. Suggested experiments and preliminary ndings related to exploring correlations and factors aecting correlation (method of summarization, quality of summary, type of intrinsic method used, and genre of source documents) are detailed. A new measurement technique for task-based evaluations, Relevance Prediction, is introduced and contrasted with the current gold-standard based measurements of the summarization evaluation community. Preliminary experimental ndings suggest that the Relevance Prediction method yields better performance measurements with human summaries than that of the LDC-Agreement method and that small correlations are seen with one of the automatic intrinsic evaluation metrics and human task-based performance results.
A reforma administrativa em Portugal: em busca de um novo paradigma

Falar de reforma administrativa em Portugal é falar, principalmente, nas mudanças que ocorreram nas últimas três décadas com o regresso do regime democrático em Abril de 1974. Até então, as iniciativas de reforma foram esporádicas, algumas sem consequências visíveis. Pode-se mesmo afirmar que a grande reforma administrativa realizada antes do regime democrático ocorreu em 1935, a qual incidiu fundamentalmente sobre as questões do pessoal. Só na década de sessenta é que se esboçou novamente uma tentativa reformadora, enquadrada nos planos de desenvolvimento elaborados na altura, mas sem grande êxito. Apesar dos vários estudos, diagnósticos e propostas de reforma a forte resistência à mudança impediu a implementação da reforma (ARAÚJO, 2002). É com o advento da democracia que surge um grande impulso reformador despoletado pelas necessidades de democratização do país, de desenvolvimento económico e das concomitantes reformas económicas e sociais. Contudo, a definição do modelo de Estado e de Administração Pública que se pretendia para o país só assume contornos claros mais tarde, a partir de meados da década de oitenta. Nesta comunicação faz-se uma breve resenha da reforma administrativa e analisam-se as tendências da gestão pública em Portugal. A análise incidirá especialmente sobre a reforma da função pública e a evolução do modelo de gestão pública.
Impact of Changes in Length of Stay on the Demand for Residential Care Services in England: Estimates from a Dynamic Microsimulation Model

If you believe this document infringes copyright then please contact the KAR admin team with the take-down information provided at http://kar.kent. ac.uk/contact.html Citation for published version Fernández, José-Luis and Forder, Julien E. (2011) Impact of Changes in Length of Stay on the Demand for Residential Care Services in England: Estimates from a Dynamic Microsimulation Model. Project report. Personal Social Services Research Unit
Circulating cell-free DNA as a promising biomarker in patients with gastric cancer: diagnostic validity and significant reduction of cfDNA after surgical resection

Purpose The aim of this study is to determine whether levels of circulating free DNA (cfDNA) increase according to cancer progression, whether they are restored after surgical resection, and to evaluate cfDNA in gastric cancer patients as a useful biomarker. Methods A case-control study design was used. Thirty gastric cancer patients and 34 healthy subjects were enrolled from two hospitals in South Korea. The plasma cfDNA of patients with gastric cancer were obtained before surgery and 24 hours after surgery, and then analyzed by a quantitative, real-time polymerase chain reaction. Plasma samples were also obtained from the control group. Results The mean levels of cfDNA in the healthy control group, patients with early gastric cancer, and with advanced gastric cancer were 79.78 ± 8.12 ng/mL, 106.88 ± 12.40 ng/mL, and 120.23 ± 10.08 ng/mL, respectively (P < 0.01). Sensitivity was 96.67% and specificity was 94.11% when the cutoff value was 90 ng/mL. Variables representing the tumor burden such as tumor size, T stage, TNM stage, and curative resection are also associated with the levels of cfDNA. The levels of cfDNA in the 24-hour-after-surgery group decreased significantly (112.17 ± 13.42 ng/mL vs. 77.93 ± 5.94 ng/mL, P < 0.001) compared to the levels of cfDNA in the preoperation group. Conclusion The changes in the levels of cfDNA can act as reliable biomarkers to detect cancer early, to predict tumor burden, estimate curative resection and even prognosis.
Applying single processor algorithms to schedule tasks on reconfigurable devices respecting reconfiguration times

In the single machine environment, several scheduling algorithms exist that allow to quantify schedules with respect to feasibility, optimality, etc. In contrast, reconfigurable devices execute tasks in parallel, which intentionally collides with the single machine principle and seems to require new methods and evaluation strategies for scheduling. However, the reconfiguration phases of adaptable architectures usually take place sequentially. Run-time adaptation is realized using an exclusive port, which is occupied for some reasonable time during reconfiguration. Thus, we can find an analogy to the single machine environment. In this paper, we investigate the appliance of single processor scheduling algorithms to task reconfiguration on reconfigurable systems. We determine necessary adaptations and propose methods to evaluate the scheduling algorithms.
Identification of Mesenchymal Stem Cell Marker STRO-1 in Oral Reactive Lesions by Immunofluorescence Method

Statement of the Problem Stem cells are considered as new implement for tissue regeneration. Several niches in adult human body are colonized by multipotent stem cells but access to these potential reservoirs is often limited. Although human dental pulp stem cells isolated from healthy teeth have been extensively characterized, it is still unknown whether stem cells also exist in reactive lesions of oral cavity such as pyogenic granuloma and peripheral ossifying fibroma which are deliberated as inflammatory proliferation of different cell families. Purpose The aim of this study was to explore for clues to see whether pyogenic granuloma or peripheral ossifying fibroma contain dental mesenchymal stem cell (DMSC). Materials and Method Four pyogenic granuloma and four peripheral ossifying fibroma specimens were collected by excisional biopsy and preserved in PBS-EDTA at -86 °C. Then we cut them in 5µm diameter using Cryostat. Having been rinsed with PBS, the samples were stained with a primary mouse anti-human STRO-1 monoclonal IgM antibody. Afterward, a secondary goat anti-mouse IgM-FITC antibody was applied to detect STRO-1+ cells as probable stem cells by immunofluorescence technique. Results Immunofluorescence microscopy revealed presence of STRO-1+ cells in these lesions, particularly localized on perivascular zone. The negative control group was not glowing. Conclusion Based on these results, it was found that reactive lesions of pyogenic granuloma and peripheral ossifying fibroma have STRO-1 positive cells, which raises the possibility that these cells may be DMSCs.
Knowledge maintenance: the state of the art

In the software and knowledge engineering literature we can find maintenance strategies offered to maintain seven main types of knowledge: words; sentences; behavioral knowledge; and meta-knowledge. Meta-knowledge divides into problem solving methods, quality knowledge, fix knowledge, social knowledge and processing activities. There are five main ways in which these seven knowledge types are processed: acquire, operationalise, fault, fix and preserve. We review systems that contribute to these 7*5 = 35 types of knowledge maintenance to make the following conclusions. First, open issues with the current maintenance research are identified. These include (a) areas that are not being addressed by any researcher; (b) the recursive maintenance problem; and (c) drawbacks with rapid acquire systems and the operationalisation KM assumption. Secondly, a process is described for commissioning a new maintenance tool. Thirdly, a general common principle for maintenance (search-space reflection) is isolated.
Effect of cold clouds on satellite measurements near 183 GHz

[1] Near-global analysis of 183 GHz measurements from the NOAA-15 advanced microwave sounding unit (AMSU) B was conducted to investigate the impact of cold (< 240 K at 11 μm) clouds on upper tropospheric humidity (UTH) observations and in assessing the potential for deriving cloud microphysical properties. Collocated advanced very high resolution radiometer (AVHRR) data aided in identifying clouds and isolating the ice-cloud-scattering effect. This effect was determined by subtracting the measured AMSU-B brightness temperature (Tb) from a background Tb estimated using AVHRR-derived cloud optical depth data. Results for December 1999 over land and ocean show that nonprecipitating cold clouds have a measurable impact on 183 GHz Tbs although the average effect is rather weak (1.4 K). Cold clouds associated with precipitation had a much larger average effect (7 K); therefore only for these types of clouds is there sufficient information for potential quantitative estimation of cloud/precipitation physical properties. Nonprecipitating cold clouds bias estimates of UTH, on average, by 5% but can reach 20% for optically thick clouds. Precipitating clouds produce an 18% average bias. On the basis of these results it is recommended that UTH retrievals undergo filtering for precipitation (using combined microwave and infrared window channels) as well as for optically thick nonprecipitating cold clouds that fill a sensor's field of view, which may be screened using infrared split window techniques.
DIRECT QUANTILE ESTIMATION FOR LOCALLY STATIONARY TIME SERIES , WITH APPLICATIONS TO OZONE DATA

*Although the research described in this article has been funded wholly or in part by the United States Environmental Protection Agency through STAR Cooperative Agreem ent #R-82940201-0 to The University of Chicago, it has not been subjected to the Agency’s required peer and policy review and therefore does not necessarily reflec t the v iews of the Agency, and no o fficial endorsement shou ld be inferred. The University of Chicago Center for Integrating Statistical and Environmental Science www.stat.uchicago.edu/~cises
Quantum Bio-inspired Invariant Object Recognition Model on System-on-a-Chip (SoC)

This paper presents the first attempt of designing a physical quantum-like `brain' for humanoid and experimentally proves a 2D invariant object recognition model inspired by the image processing along the human visual pathway: retina, lateral geniculate nucleus (LGN) and primary visual cortex (V1). It also describes storing the output of the model in quantum holographic memory (a hologram) and the method to reconstruct the visual representation. The work is implemented as system-on-a-chip in field-programmable gate array (FPGA).
Viewing sentence boundary detection as collocation identification

The detection of abbreviations is an important step in the process of sentence boundary detection. We describe a flexible, languageindependent and accurate method based on the idea that an abbreviation can be viewed as a collocation. As such, it can be identified by using methods for collocation detection such as the log likelihood ratio. Although the log likelihood ratio is known to show a good recall, its precision is poor. We employ scaling factors that lead to a strong improvement of precision. Experiments with English and German corpora show that abbreviations can be detected with high accuracy. We also show that inaccurate tokenization leads to a considerably higher error rate during tagging.
Trust Building via Risk Taking: A Cross-Societal Experiment

The role of risk taking in building trust relations has largely been overlooked in the burgeoning literature on trust in the social sciences; yet it is central to understanding how trust develops. We argue that a series of risk-taking behaviors is indispensable to building a trust relation. We conducted experiments in Japan and the United States to examine the independent and cross-cultural effects of risk taking on trust building. The results of these experiments indicate that the American participants took more risks than did the Japanese, supporting the general claim that Americans are inclined toward risk taking and trust building. Even so, the Americans were no better than the Japanese at improving the level of cooperation. The cumulative results of these experiments imply that risk taking is a critical element in trust building for Americans, but less so for the Japanese. Our results show clearly that it is important to distinguish trusting behavior from cooperation and to measure them separately if we are to study trust and trust building in relation to social cooperation.
Adjoint-driven Russian roulette and splitting in light transport simulation

While Russian roulette (RR) and splitting are considered fundamental importance sampling techniques in neutron transport simulations, they have so far received relatively little attention in light transport. In computer graphics, RR and splitting are most often based solely on local reflectance properties. However, this strategy can be far from optimal in common scenes with non-uniform light distribution as it does not accurately predict the actual path contribution. In our approach, like in neutron transport, we estimate the expected contribution of a path as the product of the path weight and a pre-computed estimate of the adjoint transport solution. We use this estimate to generate so-called weight window which keeps the path contribution roughly constant through RR and splitting. As a result, paths in unimportant regions tend to be terminated early while in the more important regions they are spawned by splitting. This results in substantial variance reduction in both path tracing and photon tracing-based simulations. Furthermore, unlike the standard computer graphics RR, our approach does not interfere with importance-driven sampling of scattering directions, which results in superior convergence when such a technique is combined with our approach. We provide a justification of this behavior by relating our approach to the zero-variance random walk theory.
An exploratory study on China's software engineers' unpaid overtime working

Unpaid Overtime Working widely exists in current China's software industry. However, there are few empirical studies on this issue. In this paper, we describe an ongoing exploratory study on the unpaid overtime working of the China's software engineers. We use semi-controlled interview as our major research method and some preliminary results are presented. We describe the software engineers' attitudes, current unpaid overtime working situations and summarize six reasons that motivate them accept unpaid overtime working. The influence of the unpaid overtime working is also presented from both the individual and organizational levels.
Impact of job deadlines on the QoS performance of cloud data centers

Job scheduling affects the performance of a cloud data center in terms of essential Quality-of-Service (QoS) metrics such as the blocking probability and the system's response time. This paper's first contribution lies in the proposal of a novel job Deadline-Aware Scheduling Scheme (DASS) with the objective of improving a data center's QoS in term of the above-mentioned metrics. An analytical queueing model is developed for the purpose of capturing the data center's behavioral dynamics and evaluating its performance when operating under DASS. The model's results and their accuracy are verified through extensive simulations. Furthermore, the performance of the data center achieved under DASS is compared to its counterpart achieved under the more widely adopted First-In-First-Out (FIFO) scheme. Results indicate that DASS outperforms FIFO by 11% to 58% in terms of the blocking probability and by 82% to 89% in terms of the system's response time.