Miracle-dz/UniFAR-FTUs huggingface dataset:
TCAD Simulation, Small-Signal and Noise Modeling of Si Based Bandgap Engineered Semiconductor Device for Near THz Applications

In this paper high frequency small-signal model is presented for optimization of device parameters of SiGe HBT with 0. 1μm base-width which is based on the technique of direct parameter extraction. For this purpose, we use process simulator ATHENA and device simulator ATLAS from SILAVCO International. Further, a model is proposed to portray the noise in SiGe HBT with uniform Ge concentration in base. The results of the SiGe HBTs are advanced to those of III-V semiconductor devices.
Query Representation and Understanding July 28 , 2011 , Beijing , China Organizers

Understanding the user needs underlying a query can be very difficult, even for a human relevance judge. When evaluating our algorithms, particularly those with a sophisticated query model, it may be wise to use real queries and a notion of relevance that is aligned with real user needs. I will present two lines of work in this area. One is the TREC Web Track, where we attempt to incorporate real Web tasks, real queries and a diverse set of user intents for each query. Click-based clustering or crowdsourcing have been used to identify possible intents. The other line of work is click-based experimentation using result interleaving. Compared to TREC methods, interleaving can detect more subtle and personalized preferences. It is sensitive enough to get significant results from tens of users who install a browser toolbar. Analysis of these different approaches is according to statistical power, ease/availability of use, and fidelity to real user preferences. 10:00 – 10:30 Coffee Break 10:30 – 11:00 Accepted Talks I Using Web Snippets and Query-logs to Measure Implicit Temporal Intents in Queries. 1 Ricardo Campos (LIAAD – INESC Porto, LA) Alípio Mário Jorge (LIAAD – INESC Porto, LA) Gaël Dias (HULTIG, University of Beira Interior) Complex Network Analysis Reveals Kernel-Periphery Structure in Web Search Queries. 5 Rishiraj Saha Roy (IIT Kharagpur, Kharagpur, India) Niloy Ganguly (IIT Kharagpur, Kharagpur, India) Monojit Choudhury (Microsoft Research India, Bangalore, India) Naveen Kumar Singh (NIT Durgapur, Durgapur, India) Investigation of Web Query Refinement via Topic Analysis and Learning with Personalization. 9
Smart Grid Architecture Model use case management in a large European Smart Grid project

On European level the EU Mandate M/490 including the final reports of the respective working groups are gaining momentum in the community. Two of the mandate's core results deal with architecture description and use case management. As a response to the mandate, among other deliverables, the Smart Grid Architecture Model (SGAM) has been developed to provide a framework for Smart Grid architectures. Additionally, use case templates as well as a comprehensive methodology for use case management have been specified. The focus of this contribution is to demonstrate how use case management and the SGAM, and thus recommended by the EU, can be applied together in practice to specific use cases provided by the DISCERN project. The very purpose of the SGAM application is to share information among projects that implement similar use cases based on different technical solutions. Finally, open issues and research gaps to be addressed in order to utilize the SGAM will be presented.
Scheduling Arrivals to a Stochastic Service Delivery System Using Copositive Cones

In this paper we investigate a stochastic appointment-scheduling problem in an outpatient clinic with a single doctor. The number of patients and their sequence of arrivals are fixed, and the scheduling problem is to determine an appointment time for each patient. The service durations of the patients are stochastic, and only the mean and covariance estimates are known. We do not assume any exact distributional form of the service durations, and we solve for distributionally robust schedules that minimize the expectation of the weighted sum of patients' waiting time and the doctor's overtime. We formulate this scheduling problem as a convex conic optimization problem with a tractable semidefinite relaxation. Our model can be extended to handle additional support constraints of the service durations. Using the primal--dual optimality conditions, we prove several interesting structural properties of the optimal schedules. We develop an efficient semidefinite relaxation of the conic program and show that we can still obtain near-optimal solutions on benchmark instances in the existing literature. We apply our approach to develop a practical appointment schedule at an eye clinic that can significantly improve the efficiency of the appointment system in the clinic, compared to an existing schedule.
Lack of Evidence for Vesicular Glutamate Transporter Expression in Mouse Astrocytes

The concept of a tripartite synapse including a presynaptic terminal, a postsynaptic spine, and an astrocytic process that responds to neuronal activity by fast gliotransmitter release, confers to the electrically silent astrocytes an active role in information processing. However, the mechanisms of gliotransmitter release are still highly controversial. The reported expression of all three vesicular glutamate transporters (VGLUT1–3) by astrocytes suggests that astrocytes, like neurons, may release glutamate by exocytosis. However, the demonstration of astrocytic VGLUT expression is largely based on immunostaining, and the possibility of nonspecific labeling needs to be systematically addressed. We therefore examined the expression of VGLUT1–3 in astrocytes, both in culture and in situ. We used Western blots and single-vesicle imaging by total internal reflection fluorescence microscopy in live cultured astrocytes, and confocal microscopy, at the cellular level in cortical, hippocampal, and cerebellar brain slices, combined with quantitative image analysis. Control experiments were systematically performed in cultured astrocytes using wild-type, VGLUT1–3 knock-out, VGLUT1Venus knock-in, and VGLUT2-EGFP transgenic mice. In fixed brain slices, we quantified the degree of overlap between VGLUT1–3 and neuronal or astrocytic markers, both in an object-based manner using fluorescence line profiles, and in a pixel-based manner using dual-color scatter plots followed by the calculation of Pearson's correlation coefficient over all pixels with intensities significantly different from background. Our data provide no evidence in favor of the expression of any of the three VGLUTs by gray matter protoplasmic astrocytes of the primary somatosensory cortex, the thalamic ventrobasal nucleus, the hippocampus, and the cerebellum.
Predictors of Reoperations in Deep Inferior Epigastric Perforator Flap Breast Reconstruction

Background: The deep inferior epigastric perforator (DIEP) procedure is regarded a safe option for autologous breast reconstruction. Reoperations, however, may occur, and there is no consensus in the literature regarding the risk factors. The aim of this study was to identify factors associated with reoperations in DIEP procedure. Patients and Methods: A retrospective study of consecutive patients undergoing DIEP breast reconstruction 2007 to 2014 was performed and included a review of 433 medical charts. Surgical outcome was defined as any unanticipated reoperation requiring return to the operating room. Multivariate regression analysis was utilized to identify predictors of reoperation. The following factors were considered: age, body mass index, comorbidity, childbearing history, previous abdominal surgery, adjuvant therapy, reconstruction laterality and timing, flap and perforator characteristics, and number and size of veins. Results: In total, 503 free flaps were performed in 433 patients, 363 (83.8%) unilateral and 70 (16.2%) bilateral procedures. Mean age was 51 years; 15.0% were obese; 13.4% had hypertension; 2.3% had diabetes; 42.6% received tamoxifen; 58.8% had preoperative radiotherapy; 45.6% had abdominal scars. Reoperation rate was 15.9% (80/503) and included flap failure, 2.0%; partial flap loss, 1.2%; arterial thrombosis, 2.0%; venous thrombosis, 0.8%; venous congestion, 1.2%; vein kinking, 0.6%. Other complications included bleeding, 2.2%; hematoma, 3.0%; fat necrosis, 2.8%, and infection, 0.2%. Factors negatively associated with reoperation were childbearing history (odds ratio [OR]: 3.18, P = 0.001) and dual venous drainage (OR: 1.91, P = 0.016); however, only childbearing remained significant in the multivariate analyses (OR: 4.56, P = 0.023). Conclusions: The history of childbearing was found to be protective against reoperation. Number of venous anastomoses may also affect reoperation incidence, and dual venous drainage could be beneficial in nulliparous patients.
Higher accuracy and lower run time: efficient mutation analysis using non‐redundant mutation operators

Mutation analysis is a powerful but computationally expensive method to measure the effectiveness of a testing or debugging technique. The high cost is due, in part, to redundant mutants generated by commonly used mutation operators. A mutant is said to be redundant if its outcome can be predicted based on the outcome of other mutants. The execution of those redundant mutants is unnecessary and wastes CPU resources. Moreover, the inclusion of redundant mutants may lead to a skewed mutant detection rate and therefore misrepresent the effectiveness of the assessed testing or debugging technique. This paper extends previous work and makes the following contributions. First, it defines and provides non‐redundant versions of the conditional operator replacement, unary operator insertion, and relational operator replacement mutation operators. Second, it reports on a conducted empirical study using 10 real‐world programmes that comprise a total of 410 000 lines of code. The empirical study used developer‐written and generated test suites. The results show how prevalent redundant mutants are and how their elimination improves the efficiency and accuracy of mutation analysis. In summary, the total mutation analysis run time decreased by more than 20% by removing redundant mutants, and the inclusion of redundant mutants led to an overestimated mutation score for all analysed test suites. Copyright © 2014 John Wiley & Sons, Ltd.
Natural language processing for unmanned aerial vehicle guidance interfaces

In this thesis, I address the opportunities and challenges involved in applying natural language processing techniques to the control of unmanned aerial vehicles (UAVs). The problem of controlling an unmanned aircraft via natural language inputs is formulated as a feedback control problem, and notions of state, controllability, and observability are defined under this model. An implementation of such a system is also described. The phraseology of the existing air traffic control language is used as a base command set; to form this command set, a corpus of air traffic control commands was gathered from recorded exchanges between pilots and controllers at Boston’s Logan Airport, as well as Hanscom Field in Bedford, MA, and these were used as the “target language” for this implementation. Knowledge of air traffic control and airport operations, combined with existing natural language processing techniques, is used to achieve a higher recognition success rate than a traditional natural language processor designed for a more general domain of discourse would. This is the first known attempt at formalizing air traffic control phraseology for use in an unmanned system. Thesis Supervisor: Eric Feron Title: Associate Professor Department of Aeronautics and Astronautics Thesis Supervisor: Robert C. Berwick Title: Professor Department of Electrical Engineering and Computer Science
Rare-event Simulation Techniques : An Introduction and Recent Advances

In this chapter we review some of the recent developments for efficient estimation of rareevents, most of which involve application of importance sampling techniques to achieve variance reduction. The zero-variance importance sampling measure is well known and in many cases has a simple representation. Though not implementable, it proves useful in selecting good and implementable importance sampling changes of measure that are in some sense close to it and thus provides a unifying framework for such selections. Specifically, we consider rare events associated with: 1) multi-dimensional light-tailed random walks, 2) with certain events involving heavy-tailed random variables and 3) queues and queueing networks. In addition, we review the recent literature on development of adaptive importance sampling techniques to quickly estimate common performance measures associated with finite-state Markov chains. We also discuss the application of rare-event simulation techniques to problems in financial engineering. The discussion in this chapter is non-measure theoretic and kept sufficiently simple so that the key ideas are accessible to beginners. References are provided for more advanced treatments.
An Adaptive Noise-Filtering Algorithm for AVIRIS Data With Implications for Classification Accuracy

This paper describes a new algorithm used to adaptively filter a remote-sensing data set based on signal-to-noise ratios (SNRs) once the maximum noise fraction has been applied. This algorithm uses Hermite splines to calculate the approximate area underneath the SNR curve as a function of band number, and that area is used to place bands into ldquobinsrdquo with other bands having similar SNRs. A median filter with a variable-sized kernel is then applied to each band, with the same size kernel used for each band in a particular bin. The proposed adaptive filters are applied to a hyperspectral image generated by the airborne visible/infrared imaging spectrometer sensor, and results are given for the identification of three different pine species located within the study area. The adaptive-filtering scheme improves image quality as shown by estimated SNRs. Classification accuracies of three pine species improved by more than 10% in the study area as compared to that achieved by the same discriminant method without adaptive spatial filtering.
Qualitätsentwicklung in der Hochschullehre

Ausgehend von einem normativen Konzept von Lehrqualität und einem Modell guter Lehre werden Möglichkeiten erörtert, Hochschullehre zu verbessern. Massnahmen aufseiten der Lehrenden, der Studierenden und der Rahmenbedingungen haben das Ziel, die Lehre in ihrer intendierten Förderung von Wissen, Kompetenzen und Einstellungen zu unterstützen. Als wichtig werden hierfür erachtet: Lehrevaluation gekoppelt an Beratung und Weiterbildung; Auswahl von Studierenden nach Kompetenz; Sicherung basaler Bedingungen wie ein günstiges quantitatives Lehrenden-Studierenden-Verhältnis.
Validity and diagnostic accuracy of a measure of parental stress in parents with typically developing children

ABSTRACT The Parental Stress and Coping Inventory (PSCI), a 5-point, 18-item questionnaire was evaluated and validated as a screening measure for parental stress in the current sample of 126 mostly low income and ethnic minority parents with typically developing children. One hundred twenty-six participants contributed data to the current receiver-operating characteristics (ROC) analysis. ROC analyses were conducted to determine the cutoff scores of PSCI parental distress, social support, and family-based support measures. We found an optimal parental distress cutoff point of 14.5 with an associated sensitivity of 73% and 82% specificity. The optimal cutoff point of social support measure was 23.5 associated with 76% sensitivity and 49% specificity. And, the optimal cutoff point of family-based support measure was 13.5 associated with 79% sensitivity and 56% specificity. This study not only provided evidence for the reliability and validity of PSCI, but also proved the inventory to be a simple, sensitive, and specific battery for screening for parental stress and coping.
The Small Field Parabolic Flow for Bosonic Many-body Models: Part 4 - Background and Critical Field Estimates

This paper is a contribution to a program to see symmetry breaking in a weakly interacting many Boson system on a three dimensional lattice at low temperature. It is part of an analysis of the "small field" approximation to the "parabolic flow" which exhibits the formation of a "Mexican hat" potential well. Here we prove the existence of and bounds on the background and critical fields that arise from the steepest descent attack that is at the core of our renormalization group step anaylsis of these models.
OmTCP: Increasing Performance in Server Farms

Normal TCP/IP operation is for the routing system to select a best path that remains stable for some time, and for TCP to adjust to the properties of this path to optimize throughput. By executing TCP's congestion control algorithms on multiple paths at the same time, a multipath TCP can shift its traffic to a less congested path, thus maximizing both the throughput for the multipath TCP user and leaving more capacity available for other traffic on more congested paths. And when a path fails, this can be detected and worked around by multipath TCP much more quickly than by waiting for the routing system to repair the failure. This paper proposes a one-ended multipath TCP that is implemented on the sending host only, without requiring modifications on the receiving host, for the purposes of maximizing performance in transmissions from multiply connected large servers towards singly connected end-users and recovering from failures more quickly.
SJM: an SCM-based journaling mechanism with write reduction for file systems

Considering the unique characteristics of storage class memory (SCM), such as non-volatility, fast access speed, byte-addressability, low-energy consumption, and in-place modification support, we investigated the features of over-write and append-write and propose a safe and write-efficient SCM-based journaling mechanism for a file system called SJM. SJM integrates the ordered and journaling modes of the traditional journaling mechanisms by storing the metadata and over-write data in the SCM-based logging device as a write-ahead log and strictly controlling the data flow. SJM writes back the valid log blocks to the file system according to their access frequency and sequentiality and thus improves the write performance. We implemented SJM on Linux 3.12 with ext2, which has no journal mechanisms. Evaluation results show that ext2 with SJM outperforms ext3 with a ramdisk-based journaling device while keeping the version consistency, especially under workloads with large write requests.
Determining the top-k nodes in social networks using the Shapley value

In this paper, we consider the problem of selecting, for any given positive integer k, the top-k nodes in a social network, based on a certain measure appropriate for the social network. This problem is relevant in many settings such as analysis of co-authorship networks, diffusion of information, viral marketing, etc. However, in most situations, this problem turns out to be NP-hard. The existing approaches for solving this problem are based on approximation algorithms and assume that the objective function is sub-modular. In this paper, we propose a novel and intuitive algorithm based on the Shapley value, for efficiently computing an approximate solution to this problem. Our proposed algorithm does not use the sub-modularity of the underlying objective function and hence it is a general approach. We demonstrate the efficacy of the algorithm using a co-authorship data set from e-print arXiv (www.arxiv.org), having 8361 authors.
Filter based backward elimination in wrapper based PSO for feature selection in classification

The advances in data collection increase the dimensionality of the data (i.e. the total number of features) in many fields, which arises a challenge to many existing feature selection approaches. This paper develops a new feature selection approach based on particle swarm optimisation (PSO) and a local search that mimics the typical backward elimination feature selection method. The proposed algorithm uses a wrapper based fitness function, i.e. the classification error rate. The local search is performed only on the global best and uses a filter based measure, which aims to take the advantages of both filter and wrapper approaches. The proposed approach is tested and compared with three recent PSO based feature selection algorithms and two typical traditional feature selection methods. Experiments on eight benchmark datasets show that the proposed algorithm can be successfully used to select a significantly smaller number of features and simultaneously improve the classification performance over using all features. The proposed approach outperforms the three PSO based algorithms and the two traditional methods.
Design and development of a biomimetic leg using hybrid actuators

Research on legged locomotion has encountered its limits in human-made actuation technology. Building a structure and an actuation system capable of performing like a biological muscle for the dynamic locomotion of a mid- to large-sized machine is prohibitive. Novel technologies are being explored with the aim of improving actuator performance. This paper describes the development of a robotic leg for agile locomotion. The main aim is to imitate the multidisciplinary performance of the natural muscle by means of hybridizing conventional and new technologies for the development of large power, large force, lightweight, force-controlled, compliant robotic legs. A preliminary leg prototype has been developed. The actuation system is based on the hybrid use of series elasticity and magneto-rheological dampers which provides variable compliance for natural-looking motion and improved interaction with the ground. Experiments with the real leg prototype provide a positive assessment of the target leg features.