nils-herrmann/clean_scirepeval huggingface dataset:
Towards a next generation data center architecture: scalability and commoditization

Applications hosted in today's data centers suffer from internal fragmentation of resources, rigidity, and bandwidth constraints imposed by the architecture of the network connecting the data center's servers. Conventional architectures statically map web services to Ethernet VLANs, each constrained in size to a few hundred servers owing to control plane overheads. The IP routers used to span traffic across VLANs and the load balancers used to spray requests within a VLAN across servers are realized via expensive customized hardware and proprietary software. Bisection bandwidth is low, severly constraining distributed computation Further, the conventional architecture concentrates traffic in a few pieces of hardware that must be frequently upgraded and replaced to keep pace with demand - an approach that directly contradicts the prevailing philosophy in the rest of the data center, which is to scale out (adding more cheap components) rather than scale up (adding more power and complexity to a small number of expensive components).
 Commodity switching hardware is now becoming available with programmable control interfaces and with very high port speeds at very low port cost, making this the right time to redesign the data center networking infrastructure. In this paper, we describe monsoon, a new network architecture, which scales and commoditizes data center networking monsoon realizes a simple mesh-like architecture using programmable commodity layer-2 switches and servers. In order to scale to 100,000 servers or more,monsoon makes modifications to the control plane (e.g., source routing) and to the data plane (e.g., hot-spot free multipath routing via Valiant Load Balancing). It disaggregates the function of load balancing into a group of regular servers, with the result that load balancing server hardware can be distributed amongst racks in the data center leading to greater agility and less fragmentation. The architecture creates a huge, flexible switching domain, supporting any server/any service and unfragmented server capacity at low cost.
Experience-Aware Item Recommendation in Evolving Review Communities

Current recommender systems exploit user and item similarities by collaborative filtering. Some advanced methods also consider the temporal evolution of item ratings as a global background process. However, all prior methods disregard the individual evolution of a user's experience level and how this is expressed in the user's writing in a review community. In this paper, we model the joint evolution of user experience, interest in specific item facets, writing style, and rating behavior. This way we can generate individual recommendations that take into account the user's maturity level (e.g., recommending art movies rather than blockbusters for a cinematography expert). As only item ratings and review texts are observables, we capture the user's experience and interests in a latent model learned from her reviews, vocabulary and writing style. We develop a generative HMM-LDA model to trace user evolution, where the Hidden Markov Model (HMM) traces her latent experience progressing over time -- with solely user reviews and ratings as observables over time. The facets of a user's interest are drawn from a Latent Dirichlet Allocation (LDA) model derived from her reviews, as a function of her (again latent) experience level. In experiments with four realworld datasets, we show that our model improves the rating prediction over state-of-the-art baselines, by a substantial margin. In addition, our model can also give some interpretations for the user experience level.
A Comparison of the Cell Phone Driver and the Drunk Driver

The objective of this research was to determine the relative impairment associated with conversing on a cellular telephone while driving.



Epidemiological evidence suggests that the relative risk of being in a traffic accident while using a cell phone is similar to the hazard associated with driving with a blood alcohol level at the legal limit. The purpose of this research was to provide a direct comparison of the driving performance of a cell phone driver and a drunk driver in a controlled laboratory setting.



We used a high-fidelity driving simulator to compare the performance of cell phone drivers with drivers who were intoxicated from ethanol (i.e., blood alcohol concentration at 0.08% weight/volume).



When drivers were conversing on either a handheld or hands-free cell phone, their braking reactions were delayed and they were involved in more traffic accidents than when they were not conversing on a cell phone. By contrast, when drivers were intoxicated from ethanol they exhibited a more aggressive driving style, following closer to the vehicle immediately in front of them and applying more force while braking.



When driving conditions and time on task were controlled for, the impairments associated with using a cell phone while driving can be as profound as those associated with driving while drunk.



This research may help to provide guidance for regulation addressing driver distraction caused by cell phone conversations.
Positioning the role of the enterprise architect: An independent study in a mobile telecommunications organisation

Advances in technology bring some challenges to the organisation, for example within Information Systems (IS), organisations are facing challenges in dealing with the increased complexity posed by digitisation, distributed systems and business processes. Enterprise architecture (EA) was created to deal with these challenges, and the introduction of the EA discipline brought with it a new type of job, the enterprise architect, whose roles need clarity. The goal of this study was to investigate the role of enterprise architects in a mobile telecommunications organisation in South Africa. Following the interpretive epistemology and using the qualitative research approach, a case study was conducted using interviews as the data gathering technique. The research findings on the role of the enterprise architect revealed that the role of the enterprise architect is both managerial and technological in nature.
The complete nucleotide sequence and genome organization of tomato infectious chlorosis virus: a distinct crinivirus most closely related to lettuce infectious yellows virus

The complete nucleotide sequence of tomato infectious chlorosis virus (TICV) was determined and compared with those of other members of the genus Crinivirus. RNA 1 is 8,271 nucleotides long with three open reading frames and encodes proteins involved in replication. RNA 2 is 7,913 nucleotides long and encodes eight proteins common within the genus Crinivirus that are involved in genome protection, movement and other functions yet to be identified. Similarity between TICV and other criniviruses varies throughout the genome but TICV is related more closely to lettuce infectious yellows virus than to any other crinivirus, thus identifying a third group within the genus.
Reduced-order model of a half-bridge series resonant inverter for power control in domestic induction heating applications

When modeling resonant inverters considering the harmonic balance method, the order of the obtained transfer functions is twice the state variables number. This is explained because two components are considered for each state variable. In order to obtain a simpler transfer function model of a halfbridge series resonant inverter, different techniques of model order reduction have been considered in this work. Thus, a reduced-order model has been obtained by residualization providing much simpler analytical expressions than the original model. The proposed model has been validated by simulation and experimentally. The validity range of the proposed model is extended up to a tenth of the switching frequency. Taking into account the great load variability of induction heating applications, the proposed reduced-order model will allow the design of advanced controllers such as Gain-Scheduling.
The use of simulated patients in medical education: AMEE Guide No 42.

Medical training has traditionally depended on patient contact. However, changes in healthcare delivery coupled with concerns about lack of objectivity or standardization of clinical examinations lead to the introduction of the 'simulated patient' (SP). SPs are now used widely for teaching and assessment purposes. SPs are usually, but not necessarily, lay people who are trained to portray a patient with a specific condition in a realistic way, sometimes in a standardized way (where they give a consistent presentation which does not vary from student to student). SPs can be used for teaching and assessment of consultation and clinical/physical examination skills, in simulated teaching environments or in situ. All SPs play roles but SPs have also been used successfully to give feedback and evaluate student performance. Clearly, given this potential level of involvement in medical training, it is critical to recruit, train and use SPs appropriately. We have provided a detailed overview on how to do so, for both teaching and assessment purposes. The contents include: how to monitor and assess SP performance, both in terms of validity and reliability, and in terms of the impact on the SP; and an overview of the methods, staff costs and routine expenses required for recruiting, administrating and training an SP bank, and finally, we provide some intercultural comparisons, a 'snapshot' of the use of SPs in medical education across Europe and Asia, and briefly discuss some of the areas of SP use which require further research.
Adaptive Strassen's matrix multiplication

Strassen's matrix multiplication (MM) has benefits with respect to any (highly tuned) implementations of MM because Strassen's reduces the total number of operations. Strassen achieved this operation reduction by replacing computationally expensive MMs with matrix additions (MAs). For architectures with simple memory hierarchies, having fewer operations directly translates into an efficient utilization of the CPU and, thus, faster execution. However, for modern architectures with complex memory hierarchies, the operations introduced by the MAs have a limited in-cache data reuse and thus poor memory-hierarchy utilization, thereby overshadowing the (improved) CPU utilization, and making Strassen's algorithm (largely) useless on its own.
 In this paper, we investigate the interaction between Strassen's effective performance and the memory-hierarchy organization. We show how to exploit Strassen's full potential across different architectures. We present an easy-to-use adaptive algorithm that combines a novel implementation of Strassen's idea with the MM from automatically tuned linear algebra software (ATLAS) or GotoBLAS. An additional advantage of our algorithm is that it applies to any size and shape matrices and works equally well with row or column major layout. Our implementation consists of introducing a final step in the ATLAS/GotoBLAS-installation process that estimates whether or not we can achieve any additional speedup using our Strassen's adaptation algorithm. Then we install our codes, validate our estimates, and determine the specific performance.
 We show that, by the right combination of Strassen's with ATLAS/GotoBLAS, our approach achieves up to 30%/22% speed-up versus ATLAS/GotoBLAS alone on modern high-performance single processors. We consider and present the complexity and the numerical analysis of our algorithm, and, finally, we show performance for 17 (uniprocessor) systems.
Inter-Rater Reliability of Cognitive-Behavioral Case Formulations of Depression: A Replication

We developed a model of cognitive-behavioralcase formulation and tested several hypotheses abouttherapists' ability to use it to obtaincognitive-behavioral formulations of cases of depressedpatients. We tested whether clinicians, using measures wedeveloped, could correctly identify patients' overtproblems and agree on assessments of patients'underlyingschemas. Clinicians offered cognitive-behavioralformulations for three cases after listening to audiotapesof initial interviews with depressed women conducted bythe first author in her private practice. Therapistsidentified 67% of patients' overt problems. When schema ratings were averaged over five judges,interrater reliability was good (inter-rater reliabilitycoefficients averaged 0.72); single judges showed poorinter-rater agreement on schema ratings (inter-rater reliability coefficients averaged 0.37).Providing therapists with a specific context in which tomake ratings did notimprove schema agreement.Ph.D.-trained therapists were more accurate thannon-Ph.D.-trained therapists in identifying patients' problems.Most findings replicated those obtained in an earlierstudy.
Optimizing Ontology Mapping Using Genetic Algorithms ( OOMGA )

Aarti Singh Department of Computer Science, Guru Nanak Girls College, Yamuna Nagar, Haryana, India Email: singh2208@gmail.com -------------------------------------------------------------------ABSTRACT---------------------------------------------------------Ontologies play a vital role in knowledge representation in artificial intelligent systems. With emergence and acceptance of semantic web and associated services offered to the users, more and more ontologies have been developed by various stack-holders. Different ontologies need to be mapped for various systems to communicate with each other. Ontology mapping is an open research issue in web semantics. Exact mapping of ontologies is rare to achieve so it’s an optimization problem. This work presents and optimized ontology mapping mechanism which deploys genetic algorithm.
Visualizing and Comparing Convolutional Neural Networks

Convolutional Neural Networks (CNNs) have achieved comparable error rates to well-trained human on ILSVRC2014 image classification task. To achieve better performance, the complexity of CNNs is continually increasing with deeper and bigger architectures. Though CNNs achieved promising external classification behavior, understanding of their internal work mechanism is still limited. In this work, we attempt to understand the internal work mechanism of CNNs by probing the internal representations in two comprehensive aspects, i.e., visualizing patches in the representation spaces constructed by different layers, and visualizing visual information kept in each layer. We further compare CNNs with different depths and show the advantages brought by deeper architecture.
CODEN : IJPNL 6 FORMULATION AND EVALUATION OF SUSTAINED RELEASE MATRIX TABLETS OF

The aim of the present study was to prepare and characterize the Sustained release matrix tablets of Ranolazine using Kollidon® SR. Kollidon® SR is a polyvinyl acetate based excipient. Three different strengths i.e 375mg, 500mg and 750mg of ranolazine SR tablets were prepared by direct compression method and by using common blend. The influence of compression force was studied on the dissolution release profile of Ranolazine SR tablets. In vitro release studies were performed for all the formulations using USP type II apparatus (paddle method) in 900 ml of 0.1N hydrochloric acid at 50 rpm for 24 hours and analyzed by UV spectrophotometer at 272nm. Further, in-vitro release pattern of drug from the optimized formulation was compared with innovator formulation and it was found to be super imposable with the Innovator product RANEXA based on dissimilarity and similarity factors.
Object detection algorithm for segregating similar coloured objects and database formation

Recent advancement in the processing power of onboard computers has encouraged engineers to impart visual feedbacks into various systems like mechatronics and internet of things. Applications ranging from CCTV surveillance to target detection and tracking using UAVs, there is a wide variety of demand on image processing techniques in terms of computational time and quality. In this scenario, developing generalised algorithms which gives a freedom to user in choosing the trade-off between quality and quick response is a challenging task. In this paper a novel boundary detection algorithm for segregating similar coloured objects in an image is presented, which accommodates a degree of freedom in choosing resolution of object detection to the detection time. This method uses colour based segmentation as preprocessing technique to reduce overall computational complexity. It is independent of the shape (convex or non-convex) and size of the object. Algorithm is developed using Open-CV libraries and implemented for separating similar coloured vehicles from an image of different vehicles on road. Implementation results showing different choices of boundary tightness and computation times are showcased.
Noninvasive brain-actuated control of a mobile robot by human EEG

Brain activity recorded noninvasively is sufficient to control a mobile robot if advanced robotics is used in combination with asynchronous electroencephalogram (EEG) analysis and machine learning techniques. Until now brain-actuated control has mainly relied on implanted electrodes, since EEG-based systems have been considered too slow for controlling rapid and complex sequences of movements. We show that two human subjects successfully moved a robot between several rooms by mental control only, using an EEG-based brain-machine interface that recognized three mental states. Mental control was comparable to manual control on the same task with a performance ratio of 0.74.
A secure steganography for privacy protection in healthcare system

Private data in healthcare system require confidentiality protection while transmitting. Steganography is the art of concealing data into a cover media for conveying messages confidentially. In this paper, we propose a steganographic method which can provide private data in medical system with very secure protection. In our method, a cover image is first mapped into a 1D pixels sequence by Hilbert filling curve and then divided into non-overlapping embedding units with three consecutive pixels. We use adaptive pixel pair match (APPM) method to embed digits in the pixel value differences (PVD) of the three pixels and the base of embedded digits is dependent on the differences among the three pixels. By solving an optimization problem, minimal distortion of the pixel ternaries caused by data embedding can be obtained. The experimental results show our method is more suitable to privacy protection of healthcare system than prior steganographic works.
Pili annulati associated with hair fragility: cause or coincidence?

Pili annulati is a disorder that produces a spangled appearance to the hair, caused by alternating light and dark banding of hair shafts. This phenomenon is created by abnormal cavities in the cortex of the hair shaft, which produces lighter bands seen on clinical examination. Complications of pili annulati are limited; the most noteworthy complication is increased breakage secondary to weathering of the abnormal hair shafts. We report a case of a 14-year-old adolescent girl with pili annulati and progressive hair loss of 2 months' duration. Most of her hairs were notably short, spangled, and lusterless with light and dark banding observed with handheld magnification. Light microscopy demonstrated alternating light and dark bands, and the dark bands had the typical appearance of air-filled spaces. Gentler hair grooming practices were recommended, and at a follow-up visit, the appearance of the hair had improved with darker and longer shafts. This case should alert clinicians to look for pili annulati when hair fragility is present.
Cube: A 512-FPGA cluster

Cube, a massively-parallel FPGA-based platform is presented. The machine is made from boards each containing 64 FPGA devices and eight boards can be connected in a cube structure for a total of 512 FPGA devices. With high bandwidth systolic inter-FPGA communication and a flexible programming scheme, the result is a low power, high density and scalable supercomputing machine suitable for various large scale parallel applications. A RC4 key search engine was built as an demonstration application. In a fully implemented Cube, the engine can perform a full search on the 40-bit key space within 3 minutes, this being 359 times faster than a multi-threaded software implementation running on a 2.5GHz Intel Quad-Core Xeon processor.
A New Randomness Test Based on Linear Complexity Profile

Linear complexity can be used to detect predictable nonrandom sequences, and hence it is included in the NIST randomness test suite. But, as shown in this paper, the NIST test suite cannot detect nonrandom sequences that are generated, for instance, by concatenating two different M-sequences with low linear complexity. This defect comes from the fact that the NIST linear complexity test uses deviation from the ideal value only in the last part of the whole linear complexity profile. In this paper, a new faithful linear complexity test is proposed, which uses deviations in all parts of the linear complexity profile and hence can detect even the above nonrandom sequences. An efficient formula is derived to compute the exact area distribution needed for the proposed test. Furthermore, a simple procedure is given to compute the proposed test statistic from linear complexity profile, which requires only O(M) time complexity for a sequence of length M. key words: randomness test, linear complexity profile, NIST SP800-22
Biomechanics of Schlemm's canal endothelium and intraocular pressure reduction

Ocular hypertension in glaucoma develops due to age-related cellular dysfunction in the conventional outflow tract, resulting in increased resistance to aqueous humor outflow. Two cell types, trabecular meshwork (TM) and Schlemm's canal (SC) endothelia, interact in the juxtacanalicular tissue (JCT) region of the conventional outflow tract to regulate outflow resistance. Unlike endothelial cells lining the systemic vasculature, endothelial cells lining the inner wall of SC support a transcellular pressure gradient in the basal to apical direction, thus acting to push the cells off their basal lamina. The resulting biomechanical strain in SC cells is quite large and is likely to be an important determinant of endothelial barrier function, outflow resistance and intraocular pressure. This review summarizes recent work demonstrating how biomechanical properties of SC cells impact glaucoma. SC cells are highly contractile, and such contraction greatly increases cell stiffness. Elevated cell stiffness in glaucoma may reduce the strain experienced by SC cells, decrease the propensity of SC cells to form pores, and thus impair the egress of aqueous humor from the eye. Furthermore, SC cells are sensitive to the stiffness of their local mechanical microenvironment, altering their own cell stiffness and modulating gene expression in response. Significantly, glaucomatous SC cells appear to be hyper-responsive to substrate stiffness. Thus, evidence suggests that targeting the material properties of SC cells will have therapeutic benefits for lowering intraocular pressure in glaucoma.