United Institute of Informatics Problems

Importance: Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Objective: Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin-stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists' diagnoses in a diagnostic setting. Design, Setting, and Participants: Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Exposures: Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. Main Outcomes and Measures: The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. Results: The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). Conclusions and Relevance: In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting.

Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge-the largest histopathology competition to date, joined by 1,290 developers-to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted κ, 95% confidence interval (CI), 0.840-0.884) and 0.868 (95% CI, 0.835-0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials.

New sets of CMS underlying-event parameters ("tunes") are presented for the pythia8 event generator. These tunes use the NNPDF3.1 parton distribution functions (PDFs) at leading (LO), next-to-leading (NLO), or next-to-next-to-leading (NNLO) orders in perturbative quantum chromodynamics, and the strong coupling evolution at LO or NLO. Measurements of charged-particle multiplicity and transverse momentum densities at various hadron collision energies are fit simultaneously to determine the parameters of the tunes. Comparisons of the predictions of the new tunes are provided for observables sensitive to the event shapes at LEP, global underlying event, soft multiparton interactions, and double-parton scattering contributions. In addition, comparisons are made for observables measured in various specific processes, such as multijet, Drell-Yan, and top quark-antiquark pair production including jet substructure observables. The simulation of the underlying event provided by the new tunes is interfaced to a higher-order matrix-element calculation. For the first time, predictions from pythia8 obtained with tunes based on NLO or NNLO PDFs are shown to reliably describe minimum-bias and underlying-event data with a similar level of agreement to predictions from tunes using LO PDF sets.

We address the problem of scheduling n jobs on a batching machine to minimize regular scheduling criteria that are non-decreasing in the job completion times. A batching machine is a machine that can handle up to b jobs simultaneously. The jobs that are processed together form a batch, and all jobs in a batch start and complete at the same time. The processing time of a batch is equal to the largest processing time of any job in the batch. We analyse two variants: the unbounded model, where b⩾n; and the bounded model, where b<n. For the unbounded model, we give a characterization of a class of optimal schedules, which leads to a generic dynamic programming algorithm that solves the problem of minimizing an arbitrary regular cost function in pseudopolynomial time. The characterization leads to more efficient dynamic programming algorithms for specific cost functions: a polynomial algorithm for minimizing the maximum cost, an O(n3) time algorithm for minimizing the number of tardy jobs, an O(n2) time algorithm for minimizing the maximum lateness, and an O(n log n) time algorithm for minimizing the total weighted completion time. Furthermore, we prove that minimizing the weighted number of tardy jobs and the total weighted tardiness are NP-hard problems. For the bounded model, we derive an O(nb(b−1)) time dynamic programming algorithm for minimizing total completion time when b>1; for the case with m different processing times, we give a dynamic programming algorithm that requires O(b2m22m) time. Moreover, we prove that due date based scheduling criteria give rise to NP-hard problems. Finally, we show that an arbitrary regular cost function can be minimized in polynomial time for a fixed number of batches. © 1998 John Wiley & Sons, Ltd.

Recent years have seen tremendous progress towards therapy of many previously incurable neuromuscular diseases. This new context has acted as a driving force for the development of novel non-invasive outcome measures. These can be organized in three main categories: functional tools, fluid biomarkers and imagery. In the latest category, nuclear magnetic resonance imaging (NMRI) offers a considerable range of possibilities for the characterization of skeletal muscle composition, function and metabolism. Nowadays, three NMR outcome measures are frequently integrated in clinical research protocols. They are: 1/ the muscle cross sectional area or volume, 2/ the percentage of intramuscular fat and 3/ the muscle water T2, which quantity muscle trophicity, chronic fatty degenerative changes and oedema (or more broadly, "disease activity"), respectively. A fourth biomarker, the contractile tissue volume is easily derived from the first two ones. The fat fraction maps most often acquired with Dixon sequences have proven their capability to detect small changes in muscle composition and have repeatedly shown superior sensitivity over standard functional evaluation. This outcome measure will more than likely be the first of the series to be validated as an endpoint by regulatory agencies. The versatility of contrast generated by NMR has opened many additional possibilities for characterization of the skeletal muscle and will result in the proposal of more NMR biomarkers. Ultra-short TE (UTE) sequences, late gadolinium enhancement and NMR elastography are being investigated as candidates to evaluate skeletal muscle interstitial fibrosis. Many options exist to measure muscle perfusion and oxygenation by NMR. Diffusion NMR as well as texture analysis algorithms could generate complementary information on muscle organization at microscopic and mesoscopic scales, respectively. 31P NMR spectroscopy is the reference technique to assess muscle energetics non-invasively during and after exercise. In dystrophic muscle, 31P NMR spectrum at rest is profoundly perturbed, and several resonances inform on cell membrane integrity. Considerable efforts are being directed towards acceleration of image acquisitions using a variety of approaches, from the extraction of fat content and water T2 maps from one single acquisition to partial matrices acquisition schemes. Spectacular decreases in examination time are expected in the near future. They will reinforce the attractiveness of NMR outcome measures and will further facilitate their integration in clinical research trials.

ABSTRACT The TB Portals program is an international consortium of physicians, radiologists, and microbiologists from countries with a heavy burden of drug-resistant tuberculosis working with data scientists and information technology professionals. Together, we have built the TB Portals, a repository of socioeconomic/geographic, clinical, laboratory, radiological, and genomic data from patient cases of drug-resistant tuberculosis backed by shareable, physical samples. Currently, there are 1,299 total cases from five country sites (Azerbaijan, Belarus, Moldova, Georgia, and Romania), 976 (75.1%) of which are multidrug or extensively drug resistant and 38.2%, 51.9%, and 36.3% of which contain X-ray, computed tomography (CT) scan, and genomic data, respectively. The top Mycobacterium tuberculosis lineages represented among collected samples are Beijing, T1, and H3, and single nucleotide polymorphisms (SNPs) that confer resistance to isoniazid, rifampin, ofloxacin, and moxifloxacin occur the most frequently. These data and samples have promoted drug discovery efforts and research into genomics and quantitative image analysis to improve diagnostics while also serving as a valuable resource for researchers and clinical providers. The TB Portals database and associated projects are continually growing, and we invite new partners and collaborations to our initiative. The TB Portals data and their associated analytical and statistical tools are freely available at https://tbportals.niaid.nih.gov/ .

Abstract The nuclear modification factors of $${\mathrm {J}/\psi }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>J</mml:mi> <mml:mo>/</mml:mo> <mml:mi>ψ</mml:mi> </mml:mrow> </mml:math> and $$\psi \text {(2S)}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>ψ</mml:mi> <mml:mtext>(2S)</mml:mtext> </mml:mrow> </mml:math> mesons are measured in $$\text {PbPb}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mtext>PbPb</mml:mtext> </mml:math> collisions at a centre-of-mass energy per nucleon pair of $$\sqrt{\smash [b]{s_{_{\text {NN}}}}} = 5.02\,\text {Te}\text {V} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msqrt> <mml:mpadded> <mml:msub> <mml:mi>s</mml:mi> <mml:msub> <mml:mrow/> <mml:mtext>NN</mml:mtext> </mml:msub> </mml:msub> </mml:mpadded> </mml:msqrt> <mml:mo>=</mml:mo> <mml:mn>5.02</mml:mn> <mml:mspace/> <mml:mtext>TeV</mml:mtext> </mml:mrow> </mml:math> . The analysis is based on $$\text {PbPb}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mtext>PbPb</mml:mtext> </mml:math> and $$\mathrm {p}\mathrm {p}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>p</mml:mi> <mml:mi>p</mml:mi> </mml:mrow> </mml:math> data samples collected by CMS at the LHC in 2015, corresponding to integrated luminosities of 464 $$\,\mu \mathrm {b}^{-1}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mspace/> <mml:mi>μ</mml:mi> <mml:msup> <mml:mrow> <mml:mi>b</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> and 28 $$\,\text {pb}^\text {-1}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mspace/> <mml:msup> <mml:mtext>pb</mml:mtext> <mml:mtext>-1</mml:mtext> </mml:msup> </mml:mrow> </mml:math> , respectively. The measurements are performed in the dimuon rapidity range of $$|y | &lt; 2.4$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>|</mml:mo> <mml:mi>y</mml:mi> <mml:mo>|</mml:mo> <mml:mo>&lt;</mml:mo> <mml:mn>2.4</mml:mn> </mml:mrow> </mml:math> as a function of centrality, rapidity, and transverse momentum ( $$p_{\mathrm {T}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>p</mml:mi> <mml:mi>T</mml:mi> </mml:msub> </mml:math> ) from $$p_{\mathrm {T}} =3$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>p</mml:mi> <mml:mi>T</mml:mi> </mml:msub> <mml:mo>=</mml:mo> <mml:mn>3</mml:mn> </mml:mrow> </mml:math> $${\,\text {Ge}\text {V}/}\text {c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mspace/> <mml:mtext>GeV</mml:mtext> <mml:mo>/</mml:mo> </mml:mrow> <mml:mtext>c</mml:mtext> </mml:mrow> </mml:math> in the most forward region and up to 50 $${\,\text {Ge}\text {V}/}\text {c}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mspace/> <mml:mtext>GeV</mml:mtext> <mml:mo>/</mml:mo> </mml:mrow> <mml:mtext>c</mml:mtext> </mml:mrow> </mml:math> . Both prompt and nonprompt (coming from b hadron decays) $${\mathrm {J}/\psi }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>J</mml:mi> <mml:mo>/</mml:mo> <mml:mi>ψ</mml:mi> </mml:mrow> </mml:math> mesons are observed to be increasingly suppressed with centrality, with a magnitude similar to the one observed at $$\sqrt{\smash [b]{s_{_{\text {NN}}}}} = 2.76\,\text {Te}\text {V} $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msqrt> <mml:mpadded> <mml:msub> <mml:mi>s</mml:mi> <mml:msub> <mml:mrow/> <mml:mtext>NN</mml:mtext> </mml:msub> </mml:msub> </mml:mpadded> </mml:msqrt> <mml:mo>=</mml:mo> <mml:mn>2.76</mml:mn> <mml:mspace/> <mml:mtext>TeV</mml:mtext> </mml:mrow> </mml:math> for the two $${\mathrm {J}/\psi }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>J</mml:mi> <mml:mo>/</mml:mo> <mml:mi>ψ</mml:mi> </mml:mrow> </mml:math> meson components. No dependence on rapidity is observed for either prompt or nonprompt $${\mathrm {J}/\psi }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>J</mml:mi> <mml:mo>/</mml:mo> <mml:mi>ψ</mml:mi> </mml:mrow> </mml:math> mesons. An indication of a lower prompt $${\mathrm {J}/\psi }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>J</mml:mi> <mml:mo>/</mml:mo> <mml:mi>ψ</mml:mi> </mml:mrow> </mml:math> meson suppression at $$p_{\mathrm {T}} &gt; 25$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>p</mml:mi> <mml:mi>T</mml:mi> </mml:msub> <mml:mo>&gt;</mml:mo> <mml:mn>25</mml:mn> </mml:mrow> </mml:math> $${\

An infection represents a highly dynamic process involving complex biological responses of the host at many levels. To describe such processes at a global level, we recorded gene expression changes in mouse lungs after a non-lethal infection with influenza A virus over a period of 60 days. Global analysis of the large data set identified distinct phases of the host response. The increase in interferon genes and up-regulation of a defined NK-specific gene set revealed the initiation of the early innate immune response phase. Subsequently, infiltration and activation of T and B cells could be observed by an augmentation of T and B cell specific signature gene expression. The changes in B cell gene expression and preceding chemokine subsets were associated with the formation of bronchus-associated lymphoid tissue. In addition, we compared the gene expression profiles from wild type mice with Rag2 mutant mice. This analysis readily demonstrated that the deficiency in the T and B cell responses in Rag2 mutants could be detected by changes in the global gene expression patterns of the whole lung. In conclusion, our comprehensive gene expression study describes for the first time the entire host response and its kinetics to an acute influenza A infection at the transcriptome level.

This paper provides a literature review and an analysis of the studies related to workforce reconfiguration strategies as a part of workforce planning for various production environments. The survey demonstrates that these strategies play a crucial role in the resilience and flexibility of manufacturing systems since they help industrial companies to quickly adapt to frequent changes in demand both in terms of volume and product mix. Five strategies are considered: the use of utility, temporary, walking, cross-trained workers, and bucket brigades. They are analysed in the context of mixed and multi-model manual assembly lines, dedicated, cellular, flexible, and reconfigurable manufacturing systems. The review shows that most of the researches on these reconfiguration strategies focus on multi- or mixed-model assembly lines. At the same time, few studies consider workers team reconfiguration in flexible and reconfigurable manufacturing systems. Finally, this paper reveals several promising research directions in workforce reconfiguration planning, namely, the use of both machine and workforce reconfigurations, consideration of the ergonomic aspects, the combination of multiple workforce reconfiguration strategies, the study of workforce reconfiguration in human-robot collaborative systems, and the use of new technologies in human-machine industrial environments.

A novel line balancing problem is considered. It differs from assembly line balancing problems in that the operations of each workstation are partitioned into blocks of simultaneously executed (parallel) operations. The blocks of each workstation are executed sequentially. For the line design stage considered in this paper, the compatibility (inclusion and exclusion) constraints for grouping operations into blocks and workstations as well as precedence constraints are known. The goal is to minimize a weighted sum of the number of workstations and the number of blocks while achieving a desired cycle time and satisfying all the constraints. The developed exact and heuristic methods are based on a mixed-integer programming approach. Experimental results are reported.

Non-deterministic lot-sizing models are considered which serve for an explicit determination of lot sizes in an uncertain environment. Taxonomy components for such models are suggested and a bibliography structured according to these components is presented. The taxonomy components are numeric characteristics of a lot-sizing problem, names of uncertain parameters and names of approaches to model the uncertainty. The bibliography covers more than 300 publications since the year 2000.

The time resolution of a scintillator-based detector is directly driven by the density of photoelectrons generated in the photodetector at the detection threshold. At the scintillator level it is related to the intrinsic light yield, the pulse shape (rise time and decay time) and the light transport from the gamma-ray conversion point to the photodetector. When aiming at 10 ps time resolution, fluctuations in the thermalization and relaxation time of hot electrons and holes generated by the interaction of ionization radiation with the crystal become important. These processes last for up to a few tens of ps and are followed by a complex trapping-detrapping process, Poole-Frenkel effect, Auger ionization of traps and electron-hole recombination, which can last for a few ns with very large fluctuations. This paper will review the different processes at work and evaluate if some of the transient phenomena taking place during the fast thermalization phase can be exploited to extract a time tag with a precision in the few ps range. A very interesting part of the sequence is when the hot electrons and holes pass below the limit of the ionization threshold. The only way to relax their energy is then through collisions with the lattice resulting in the production of optical and acoustic phonons with relatively high energy (up to several tens of meV) near the ionization threshold. As the rate of such electron/phonon exchange is about 100 events/ps/electron or hole and as the number of electrons/holes generated after mutiplication in a high light yield scintillator like LSO can be as high as 100,000 or more, we end up with an energy deposition rate of about 100 KeV/ps. This energy deposition rate contributes to many fast processes with a characteristic time in the ps range such as band-to-band luminescence, hot intraband luminescence, acoustic shock wave generation, fast local variation of index of refraction, etc. We will discuss if the part of the total energy which is released this way, and which can represent between 50% and 90% of the energy of the incoming ionization radiation, can be efficiently exploited to improve the time resolution of scintillators, presently limited to the 100 ps range.

The land cover classification has been an important task in remote sensing. With the development of various sensors technologies, carrying out classification work with multisource remote sensing (MSRS) data has shown an advantage over using a single type of data. Hyperspectral images (HSIs) are able to represent the spectral properties of land cover, which is quite common for land cover understanding. Light detection and ranging (LiDAR) images contain altitude information of the ground, which is greatly helpful with urban scene analysis. Current HSI and LiDAR fusion methods perform feature extraction and feature fusion separately, which cannot well exploit the correlation of data sources. In order to make full use of the correlation of multisource data, an unsupervised feature extraction-fusion network for HSI and LiDAR, which utilizes feature fusion to guide the feature extraction procedure, is proposed in this article. More specifically, the network takes multisource data as input and directly output the unified fused feature. A multimodal graph is constructed for feature fusion, and graph-based loss functions including Laplacian loss and t-distributed stochastic neighbor embedding (t-SNE) loss are utilized to constrain the feature extraction network. Experimental results on several data sets demonstrate the proposed network can achieve more excellent classification performance than some state-of-the-art methods.

To resolve the phylogeny of certain mitochondrial DNA (mtDNA) haplogroups in eastern Europe and estimate their evolutionary age, a total of 73 samples representing mitochondrial haplogroups U4, HV*, and R1 were selected for complete mitochondrial genome sequencing from a collection of about 2,000 control region sequences sampled in eastern (Russians, Belorussians, and Ukrainians) and western (Poles, Czechs, and Slovaks) Slavs. On the basis of whole-genome resolution, we fully characterized a number of haplogroups (HV3, HV4, U4a1, U4a2, U4a3, U4b, U4c, U4d, and R1a) that were previously described only partially. Our findings demonstrate that haplogroups HV3, HV4, and U4a1 could be traced back to the pre-Neolithic times ( approximately 12,000-19,000 years before present [YBP]) in eastern Europe. In addition, an ancient connection between the Caucasus/Europe and India has been revealed by analysis of haplogroup R1 diversity, with a split between the Indian and Caucasus/European R1a lineages occurring about 16,500 years ago. Meanwhile, some mtDNA subgroups detected in Slavs (such as U4a2a, U4a2*, HV3a, and R1a1) are definitely younger being dated between 6,400 and 8,200 YBP. However, robust age estimations appear to be problematic due to the high ratios of nonsynonymous to synonymous substitutions found in young mtDNA subclusters.

Parallel machine problems with a single server are generalizations of classical parallel machine problems. Immediately before processing, each job must be loaded on a machine, which takes a certain set-up time. All these set-ups have to be done by a single server which can handle at most one job at a time. In this paper we continue studying the complexity aspects of server problems begun in Hall et al. (Discrete Appl. Math. 2000; 102: 223) and Kravchenko and Werner (Math. Comput. Model. 1997; 26: 1). New complexity results are derived for special cases. Copyright © 2002 John Wiley & Sons, Ltd.

As SAT-algorithms become more and more complex, there is little chance of writing a SAT-solver that is free of bugs. So it is of great importance to be able to verify, the information returned by a SAT-solver. If the CNF formula to be tested is satisfiable, solution verification is trivial and can be easily done by the user. However, in the case of unsatisfiability, the user has to rely on the reputation of the SAT-solver. We describe an efficient procedure for checking the correctness of unsatisfiability proofs. As a by-product, the proposed procedure finds an unsatisfiable core of the initial CNF formula. The efficiency of the proposed procedure was tested on a representative set of large "real-life" CNF formulas from the formal verification domain.

Infrared spectroscopy hampered by physical distortions from scattering and instrumental effects. Therefore, it is generally accepted that spectra should be pre-processed before further data analysis. Deep learning community offers augmentation techniques as an alternative approach to deal with variability in the data. In this paper we propose an Extended Multiplicative Signal Augmentation (EMSA) method for augmenting physical distortions in infrared spectra. In order to study the effect of pre-processing and augmentation techniques we combine them with a wide range of classifiers from chemometrics, machine learning and statistics for four different spectral data sets. While the conventional pre-processing strategies perform well with all classifiers evaluated, augmentation can replace pre-processing when combined with Deep Convolutional Neural Networks and is especially successful when applied to small data sets.

A measurement is presented of the effective leptonic weak mixing angle (sin 2 eff ) using the forwardbackward asymmetry of Drell-Yan lepton pairs ( and ee) produced in proton-proton collisions at s = 8 TeV at the CMS experiment of the LHC. The data correspond to integrated luminosities of 18.8 and 19.6 fb -1 in the dimuon and dielectron channels, respectively, containing 8.2 million dimuon and 4.9 million dielectron events. With more events and new analysis techniques, including constraints obtained on the parton distribution functions from the measured forward-backward asymmetry, the statistical and systematic uncertainties are significantly reduced relative to previous CMS measurements. The extracted value of sin 2 eff from the combined dilepton data is sin 2 eff = 0.23101 0.00036 (stat) 0.00018 (syst) 0.00016 (theo) 0.00031 (parton distributions in proton) = 0.23101 0.00053.

Increasing the noise immunity of complex signal processing systems is the main problem in various areas of signal processing. At the present time there are many books and periodical articles devoted t

A fully polynomial approximation scheme for the problem of scheduling n jobs on a single machine to minimize total weighted earliness and tardiness is presented. A new technique is used to develop the scheme. The main feature of this technique is that it recursively computes lower and upper bounds on the value of partial optimal solutions. Therefore, the scheme does not require any prior knowledge of lower and upper bounds on the value of a complete optimal solution. This distinguishes it from all the existing approximation schemes.