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Автор: Grafiati

Опубліковано: 14 листопада 2023

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1

Wagner, Larry. "Failure Analysis Challenges." EDFA Technical Articles 6, no. 2 (May 1, 2004): 28–30. http://dx.doi.org/10.31399/asm.edfa.2004-2.p028.

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Abstract Semiconductor trends, as embodied in the International Technology Roadmap for Semiconductors (ITRS), provide a guide for the challenges facing the failure analysis community. This process is a risk assessment of key features forecast for the impact of future technologies on failure analysis. The technical challenges fall primarily into two categories: failure site isolation and physical analysis. The failure site isolation challenges are largely driven by the device complexity and reduced accessibility of circuit nets. Additional challenges arise due to the increase in device operating speed and pin count. The challenges in physical analysis are driven primarily by smaller device feature sizes and by the host of new materials being introduced. In addition to the technical challenges, infrastructure changes are also likely to occur. The industry paths for addressing these challenges are discussed.

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2

Conti, J. P. "Analysis: Chile's challenges." Engineering & Technology 5, no. 5 (March 27, 2010): 14–15. http://dx.doi.org/10.1049/et.2010.0500.

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3

Roelofs, Freek, Lindy Blackburn, Greg Lindahl, Sheperd S. Doeleman, Michael D. Johnson, Philipp Arras, Koushik Chatterjee, et al. "The ngEHT Analysis Challenges." Galaxies 11, no. 1 (January 10, 2023): 12. http://dx.doi.org/10.3390/galaxies11010012.

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The next-generation Event Horizon Telescope (ngEHT) will be a significant enhancement of the Event Horizon Telescope (EHT) array, with ∼10 new antennas and instrumental upgrades of existing antennas. The increased uv-coverage, sensitivity, and frequency coverage allow a wide range of new science opportunities to be explored. The ngEHT Analysis Challenges have been launched to inform the development of the ngEHT array design, science objectives, and analysis pathways. For each challenge, synthetic EHT and ngEHT datasets are generated from theoretical source models and released to the challenge participants, who analyze the datasets using image reconstruction and other methods. The submitted analysis results are evaluated with quantitative metrics. In this work, we report on the first two ngEHT Analysis Challenges. These have focused on static and dynamical models of M87* and Sgr A* and shown that high-quality movies of the extended jet structure of M87* and near-horizon hourly timescale variability of Sgr A* can be reconstructed by the reference ngEHT array in realistic observing conditions using current analysis algorithms. We identify areas where there is still room for improvement of these algorithms and analysis strategies. Other science cases and arrays will be explored in future challenges.

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4

Hovardaoglu, Ozan. "Turkey's demographic challenges for urbanization: a quantitative analysis." International Journal of Academic Research 6, no. 6 (November 30, 2014): 165–73. http://dx.doi.org/10.7813/2075-4124.2014/6-6/a.20.

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5

Kozikoğlu, İshak, and Nuray Senemoğlu. "Challenges Faced By Novice Teachers: A Qualitative Analysis." Journal of Qualitative Research in Education 6, no. 3 (November 28, 2018): 1–31. http://dx.doi.org/10.14689/issn.2148-2624.1.6c3s16m.

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6

Fetzer, Anita. "Challenges in contrast." Languages in Contrast 9, no. 1 (March 24, 2009): 73–97. http://dx.doi.org/10.1075/lic.9.1.05fet.

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Challenges express the speaker’s intention not to comply with a proposition, force or presupposition communicated in and through a prior conversational contribution. This may be a directly adjacent contribution, some less directly adjacent contribution, or a conversational contribution uttered in some prior discourse. As for its sequential status, a challenge is a responsive contribution, and from an interpersonal perspective, it tends to carry a high degree of face-threatening potential. A felicitous analysis of a challenge thus needs to go beyond a single conversational contribution, not only accommodating context but also the nature of a challenge’s embeddedness in context. The contribution is organized as follows: The first section systematizes the necessary and sufficient contextual constraints and requirements for a conversational contribution to be assigned the status of a challenge. The second part argues for a challenge to be conceptualized as a particularized contextual configuration, which may serve as a tertium comparationis in contrastive pragmatics. The third section exemplifies the frame of reference with a contrastive analysis of British and German challenges adopted from a corpus of political interviews. In both sets of data, challenges tend to be realized implicitly, and in both sets, challenging the content of a contribution is more frequent than challenging its force or presuppositions. While the British data display a wider variety of challenges, the German data prefer the content-based, implicitly realized challenge.

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7

Bickford, John Holden, and Devanne R. Lawson. "Examining Patterns within Challenged or Banned Primary Elementary Books." Journal of Curriculum Studies Research 2, no. 1 (May 25, 2020): 16–38. http://dx.doi.org/10.46303/jcsr.02.01.2.

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Public schools and public libraries often receive challenges—suppression or removal requests—to particular books, which can lead the book being banned. Research has examined challenges to books with multicultural themes and individuals, noted that authors of color are disproportionally targeted, and recognized the remarkable number of challenges to books deemed to be classic. This qualitative content analysis research utilized both with inductive and deductive elements—open coding and axial coding—to examine challenged books intended for primary elementary students. The theoretical framework blended critical multiculturalism, gay and lesbian identity, and radical politics in children’s literature. Findings included patterns based on era, frequency and location of challenge, demography of challenger, and oft-challenged themes, specifically sexuality (sexual reproduction and diverse sexualities), inappropriate humor, danger, death, racial and religious diversity, mysticism and wizardry, racially or culturally insensitive elements, concerning interpersonal dynamics, and evolution. Meaning is extracted for teachers, librarians, administrators, and researchers.

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8

Haslett, John. "Spatial Data Analysis-Challenges." Statistician 41, no. 3 (1992): 271. http://dx.doi.org/10.2307/2348549.

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9

Concato, John. "Challenges in prognostic analysis." Cancer 91, S8 (2001): 1607–14. http://dx.doi.org/10.1002/1097-0142(20010415)91:8+<1607::aid-cncr1174>3.0.co;2-j.

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10

Nikravesh, Parviz E., and Adrijan P. Ribaric Omid Kazemi. "CHALLENGES IN MULTIBODY DYNAMIC ANALYSIS OF VEHICLES(Keynote Lectures)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _KeynoteLe. http://dx.doi.org/10.1299/jsmeacmd.2010.5._keynotele_1.

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11

Banday, Mehroush. "Deep learning and Big Data Analysis: Challenges, Opportunities and Applications." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 2216–22. http://dx.doi.org/10.31142/ijtsrd12710.

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12

Ferris, Tom. "Challenges for Regulatory Impact Analysis." Volume 1 Issue 1 (2009) 1, no. 1 (January 1, 2009): 51–65. http://dx.doi.org/10.33178/ijpp.1.1.4.

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Regulations are important in achieving economic and social goals. Governments must ensure that their legislation is as up-to-date as possible, while reflecting current issues of public concern. At the same time, governments need to have processes in place to review the extent to which existing regulations are achieving their objectives. Techniques, such as Regulatory Impact Analysis (RIA), are used to help produce better regulations at minimum cost. While RIA is relatively new in Ireland, it has already gained widespread acceptance in developed economies and throughout the EU. This article outlines what RIA involves, where it is being applied, describes the Irish experience of RIA, and offers suggestions as to how it can be made more robust in its application.

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13

Degtyarev, N. Yu, G. P. Zhigulin, R. A. Shakirova, and S. A. Bondarev. "ANALYSIS OF CLOUD SECURITY CHALLENGES." Scientific and Technical Volga region Bulletin 6, no. 3 (June 2016): 104–6. http://dx.doi.org/10.24153/2079-5920-2016-6-3-104-106.

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14

Poirier, Patrick, Patrice Schwindenhammer, Alban Colder, Bernadette Domengès, Patrice Schwindenhammer, and Alban Colder. "Complex Systems Failure Analysis Challenges." EDFA Technical Articles 10, no. 4 (November 1, 2008): 6–14. http://dx.doi.org/10.31399/asm.edfa.2008-4.p006.

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Abstract This article presents a failure analysis workflow tailored for complex ICs and device packages. The FA flow determines the root cause of failures using nondestructive analysis and advanced sample preparation techniques. The nondestructive tests typically used are X-ray radiography, scanning acoustic microscopy, time domain reflectometry, and magnetic current imaging. To gain access to interconnect failures, laser ablation is used, typically in combination with chemical etching to finish the decapsulation process. Repackaging is also part of the FA flow and is briefly discussed.

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15

Knittel, Christopher R., and Konstantinos Metaxoglou. "Challenges in Merger Simulation Analysis." American Economic Review 101, no. 3 (May 1, 2011): 56–59. http://dx.doi.org/10.1257/aer.101.3.56.

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In this paper, we share our experience with merger simulations using a Random Coefficient Logit model on the demand side and assuming a static Bertrand game on the supply side. Drawing largely from our work in Knittel and Metaxoglou (2008), we show that different demand estimates obtained from different combinations of optimization algorithms and starting values lead to substantial differences in post-merger market outcomes using metrics such as industry profits, and change in consumer welfare and prices.

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16

Pultarova, T. "News Analysis: Challenges of 'Dronevolution'." Engineering & Technology 9, no. 12 (December 1, 2014): 16–17. http://dx.doi.org/10.1049/et.2014.1219.

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17

Fan, Jianqing, Fang Han, and Han Liu. "Challenges of Big Data analysis." National Science Review 1, no. 2 (February 5, 2014): 293–314. http://dx.doi.org/10.1093/nsr/nwt032.

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Abstract Big Data bring new opportunities to modern society and challenges to data scientists. On the one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This paper gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogenous assumptions in most statistical methods for Big Data cannot be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

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18

Namieśnik, Jacek. "Trace Analysis — Challenges and Problems." Critical Reviews in Analytical Chemistry 32, no. 4 (October 2002): 271–300. http://dx.doi.org/10.1080/10408340290765579.

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19

Grandi, C. "CMS distributed data analysis challenges." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 534, no. 1-2 (November 2004): 87–93. http://dx.doi.org/10.1016/j.nima.2004.07.065.

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20

Hay, Brian, Matt Bishop, and Kara Nance. "Live Analysis: Progress and Challenges." IEEE Security & Privacy Magazine 7, no. 2 (March 2009): 30–37. http://dx.doi.org/10.1109/msp.2009.43.

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21

Hutchinson, Nancy L. "The Challenges of Componential Analysis." Journal of Learning Disabilities 25, no. 4 (April 1992): 249–52. http://dx.doi.org/10.1177/002221949202500405.

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22

M, Mr Keshava Reddy, and Mr Senthil Thirusangu. "Viral Hepatitis – Disease Burden, Challenges and Gap Analysis with Existing Response." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 545–47. http://dx.doi.org/10.31142/ijtsrd22823.

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23

K, Anuradha, and Nirmala Sugirtha Rajini S. "Analysis of Machine Learning Algorithm in IOT Security Issues and Challenges." Journal of Advanced Research in Dynamical and Control Systems 11, no. 0009-SPECIAL ISSUE (September 25, 2019): 1030–34. http://dx.doi.org/10.5373/jardcs/v11/20192668.

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24

Silva, Jayawardena. "Development Prospects: An Analysis of Opportunities and Challenges of Sri Lanka." Asia Social Science Academy 10, no. 2 (April 30, 2023): 1–7. http://dx.doi.org/10.51600/jass.2023.10.2.1.

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This paper analyzes the development prospects of a country and identifies the opportunities and challenges that it faces in achieving sustainable economic growth. Specifically, this research focuses on the economic development prospects of Sri Lanka and examines the country's strengths and potential growth areas. Through a comprehensive analysis of Sri Lanka's economic history and current state, this paper identifies the key opportunities and challenges to Sri Lanka's economic development, including the tourism industry, agriculture, and manufacturing. The paper also discusses policy measures and initiatives that can support economic development in these areas. Finally, the paper concludes with a summary of key findings and implications for Sri Lanka's economic development prospects.

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25

M. Budd, John. "Higher Education’s Challenges: A Dialectical Analysis." Journal of Modern Education Review 5, no. 11 (November 15, 2015): 1027–38. http://dx.doi.org/10.15341/jmer(2155-7993)/11.05.2015/001.

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26

De Wolf, Ingrid. "3-D Technology: Failure Analysis Challenges." EDFA Technical Articles 18, no. 4 (November 1, 2016): 24–29. http://dx.doi.org/10.31399/asm.edfa.2016-4.p024.

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Abstract Chip-level 3D integration, where chips are thinned, stacked, and vertically interconnected using TSVs and microbumps, brings as many challenges as it does improvements, particularly in the area of failure analysis. This article assesses the capabilities of various FA techniques in light of the challenges posed by 3D integration and identifies current shortcomings and future needs.

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27

Le, Phong, Haruna Isah, Sajjad Dadkhah, Mohammad Mehdi Yadollahi, Xichen Zhang, and Ali A. Ghorbani. "Data Breach: Analysis, Countermeasures, and Challenges." International Journal of Information and Computer Security 1, no. 1 (2023): 1. http://dx.doi.org/10.1504/ijics.2023.10050154.

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28

IWASAKI, Mio, and Yasushi ISHIHAMA. "Challenges Facing Complete Human Proteome Analysis." CHROMATOGRAPHY 35, no. 2 (2014): 73–80. http://dx.doi.org/10.15583/jpchrom.2014.013.

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29

Ilk, D., D. M. M. Anderson, G. W. J. W. J. Stotts, L. Mattar, and T. A. A. Blasingame. "Production-Data Analysis—Challenges, Pitfalls, Diagnostics." SPE Reservoir Evaluation & Engineering 13, no. 03 (June 8, 2010): 538–52. http://dx.doi.org/10.2118/102048-pa.

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Summary The analysis of production data to determine reservoir characteristics, completion effectiveness, and hydrocarbons in place has become very popular in recent years. Although production analysis (PA) for reservoir characterization is approaching the popularity of pressure-transient analysis (PTA), there are few consistent diagnostic methods in practice for the analysis of production data. Many of the diagnostic methods for production-data analysis are little more than observation-based approaches—and some are essentially rules of thumb. In this work, we provide guidelines for the analysis of production data, as well as identify common pitfalls and challenges. Although PTA and production-data analyses have the same governing theory (and solutions), we must recognize that pressure transient data are acquired as part of a controlled experiment, performed as a specific event [e.g., a pressure-buildup (PBU) test]. In contrast, production data are generally considered to be surveillance/monitoring data—with little control and considerable variance occurring during the acquisition of the production data. We note that since both PA and PTA have the same governing relations, it is possible "in theory" that the same deliverables of PTA can be obtained using PA. This paper attempts to provide a state-of-the-technology review of current production-data-analysis techniques/tools—particularly tools to diagnose the reservoir model and assess the reservoir condition. The reservoir model is diagnosed mainly by examining the character exhibited by the data [that is the evidence of transient flow (e.g., quarter-slope might indicate a finite-conductivity fracture, or half-slope might indicate radial/pseudoradial flow)]. In addition, one can also assess the reservoir condition by inspecting the character of production data, which can confirm the evidence of boundary-dominated flow such that unit slope may indicate the boundary-dominated-flow regime and, therefore, in-place fluid volume can be estimated. This work also identifies the challenges and pitfalls of PA—and we try to provide guidance toward best practices and best tools. To complement this mission, we use relevant field examples to address specific issues, and we illustrate the value and function of production-data analysis for a wide range of reservoir types and properties. In this work, we propose the use of a sequence of raw and enhanced data plots for the diagnostic analysis of production data. We strongly believe that a comprehensive and systematic approach for production-data diagnosis has significant importance for the analysis and forecast of production performance.

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30

Ortega-Ballesteros, Andrés, Francisco Manzano-Agugliaro, and Alberto-Jesus Perea-Moreno. "Water Utilities Challenges: A Bibliometric Analysis." Sustainability 13, no. 14 (July 10, 2021): 7726. http://dx.doi.org/10.3390/su13147726.

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The water utilities are under big pressure to guarantee water access to their customers with the right level of service and quality due to challenges such as climate change, aging infrastructure, water scarcity, and growing populations, which put pressure on their operations. The scientific community has worked intensively over the last years to propose solutions and alternatives for the utilities to improve their operation and management in order to overcome these challenges. This paper aims to review scientific contributions to this field. The result shows increasing awareness from the scientific community in this topic which translates into a growing number of publications since the beginning of the current century. This paper analyzes the evolution of the publications, identifies the main countries and institutions working in this field and their scientific relationships over time. It also identifies the main keywords in the literature, which are grouped into three main topics: water quality, water management, and water optimization. The development of smart technologies is accelerating the scientific production towards the topic of water optimization, which is acquiring more importance over the last years. Future trends of research are related to identifying specific challenges per country and the specific solutions proposed by the scientific community to address them and its feasibility to be applied in other places.

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31

Michael, L. Altland. "Transient Analysis Challenges in Force Mains." Proceedings of the Water Environment Federation 2016, no. 6 (January 1, 2016): 218–27. http://dx.doi.org/10.2175/193864716819715059.

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32

Honarpour, Mehdi M., Nizar F. Djabbarah, and Krishnaswamy Sampath. "Whole Core Analysis - Experience and Challenges." SPE Reservoir Evaluation & Engineering 8, no. 06 (December 1, 2005): 460–69. http://dx.doi.org/10.2118/81575-pa.

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Summary Whole-core analysis is critical for characterizing directional permeability in heterogeneous, fractured, and/or anisotropic rocks. Whole-core measurements are essential for heterogeneous reservoirs because small-scale heterogeneity may not be appropriately represented in plug measurements. For characterization of multiphase-flow properties (special core analysis) in heterogeneous rocks, whole-core analysis is also required. Few commercial laboratories are equipped to conduct routine measurements on whole cores up to 4 in. in diameter and up to 8 in. long and, importantly, under simulated reservoir net confining stress (NCS). Special whole-core analyses are rarely conducted because of the difficulties associated with establishing a representative water saturation in drainage capillary pressure experiments and measuring directional effective permeabilities. Electrical properties also can be measured on whole cores to determine porosity and saturation exponents for situations in which resistivity tools are used in horizontal or highly deviated wells. In this paper, we provide an overview of routine and special core-analysis measurements on whole cores. Results from selected heterogeneous sandstone and carbonate rocks will be discussed. We also will show how the results relate to data obtained from plug analysis, with particular emphasis on directional absolute permeability, trapped-gas and fluid saturations, and the effect of NCS. Finally, we will describe a novel apparatus for special core analysis on whole cores and provide examples of the capabilities of the system. In this paper, we will present:• Recommended techniques for the determination of directional absolute and effective permeability and for establishing initial water saturation in whole cores.• Improved understanding of the effect of scale (sample size) on the measured properties.• Description of a novel whole-core apparatus with measurement of fluid-saturation distribution using in-situ saturation monitoring. Introduction Reservoir rocks are heterogeneous, especially carbonate rocks, in which more than 50% of the world's hydrocarbon reserves are deposited. Fig. 1 shows an example of variability in rock characteristics as observed in a carbonate-rockout crop in Oman. The heterogeneous nature of these rocks tends to become more apparent as attempts are made to measure their petrophyscal properties at various scales. An example of permeability variation in a plug from a carbonate formation is shown in Fig. 2. Single-phase air permeability varies by three orders of magnitude over the distance of a few centimeters in this core plug. This dual-porosity behavior impacts the spontaneous-imbibition performance significantly (Fig. 3). Technology at Commercial Laboratories Selected commercial laboratories have capabilities to appropriately clean and prepare whole cores, perform core X-ray imaging, and measure basic properties such as directional permeability and porosity under a maximum confining stress of 5,000 psi. Available technologies for imaging, sample preparation, and routine core analysis are summarized in the following sections. Special-core-analysis capabilities at commercial laboratories are rare. Only one or two laboratories are capable of measuring primary-drainage gas/water capillary pressure and gas/water or oil/water electrical properties on whole cores at confining stress. Whole-Core Imaging and Screening Whole-core photography and X-ray imaging provide information about surface features and internal structure. The computed tomography (CT) scan provides evidence of fractures, vugs, and heterogeneities as indicated by the extent in the variation of CT density. X-ray fluoroscopy and CT are two of the most practical X-ray scanning techniques used to characterize core-level heterogenieties and to explain their effect on horizontal and vertical permeabilities. CT-scanning algorithms should often be modified to obtain images free of artifacts and with better than0.5-mm horizontal and 1-mm vertical resolutions.

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33

Wang, Bin, and Yaguang Xi. "Challenges for MicroRNA Microarray Data Analysis." Microarrays 2, no. 2 (March 25, 2013): 34–50. http://dx.doi.org/10.3390/microarrays2020034.

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34

Crossno, Patricia. "Challenges in Visual Analysis of Ensembles." IEEE Computer Graphics and Applications 38, no. 2 (March 2018): 122–31. http://dx.doi.org/10.1109/mcg.2018.021951640.

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35

Gotelli, Nicholas J., and Werner Ulrich. "Statistical challenges in null model analysis." Oikos 121, no. 2 (November 29, 2011): 171–80. http://dx.doi.org/10.1111/j.1600-0706.2011.20301.x.

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36

Maxwell-Reid, Corinne. "The Challenges of Contrastive Discourse Analysis." Written Communication 28, no. 4 (September 23, 2011): 417–35. http://dx.doi.org/10.1177/0741088311421890.

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37

Street, R. A. "Challenges in Timeseries Analysis from Microlensing." Proceedings of the International Astronomical Union 12, S325 (October 2016): 253–58. http://dx.doi.org/10.1017/s1743921316012886.

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AbstractDespite a flood of discoveries over the last ~ 20 years, our knowledge of the exoplanet population is incomplete owing to a gap between the sensitivities of different detection techniques. However, a census of exoplanets at all separations from their host stars is essential to fully understand planet formation mechanisms. Microlensing offers an effective way to bridge the gap around 1–10 AU and is therefore one of the major science goals of the Wide Field Infrared Survey Telescope (WFIRST) mission. WFIRST’s survey of the Galactic Bulge is expected to discover ~ 20,000 microlensing events, including ~ 3000 planets, which represents a substantial data analysis challenge with the modeling software currently available. This paper highlights areas where further work is needed. The community is encouraged to join new software development efforts aimed at making the modeling of microlensing events both more accessible and rigorous.

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38

Liu, Xiaohui. "Intelligent data analysis: issues and challenges." Knowledge Engineering Review 11, no. 4 (December 1996): 365–71. http://dx.doi.org/10.1017/s0269888900008055.

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Two phenomena have probably affected modern data analysts' lives more than anything else. First, the size of real-world data sets is getting increasingly large, especially during the last decade or so. Second, modern computational methods and tools are being developed which add further capability to traditional statistical analysis tools. These two developments have created a new range of problems and challenges for analysts, as well as new opportunities for intelligent systems in data analysis.

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