nils-herrmann/clean_scirepeval huggingface dataset:
COTS Integration: Plug and Pray?

135 Management F or most software applications, the use of commercial off-the-shelf products has become an economic necessity. Gone are the days when upsized industry and government information technology organizations had the luxury of trying to develop—and, at greater expense, maintain—their own database, network, and user-interface management infrastructure. Viable COTS products are climbing up the protocol stack, from infrastructure into applications solutions in such areas as office and management support, electronic commerce , finance, logistics, manufacturing, law, and medicine. For small and large commercial companies, time-to-market pressures also exert a strong pressure toward COTS-based solutions. However, most organizations have also found that COTS gains are accompanied by frustrating COTS pains. Table 1 summarizes a great deal of experience on the relative advantages and disadvantages of COTS solutions. 1 One of the best COTS integration gain-and-pain case studies 2 summarizes the experiences of David Garlan's group at CMU. Garlan's group tried to integrate four COTS products into the Aesop software architecting environment—the OBST object management system, the Mach RPC Interface Generator, the SoftBench tool integration framework, and the InterViews user interface manager—only to find a number of architectural mis-matches among the products' underlying assumptions. For example, three of the four products are event based, but each has different event semantics, and each assumes it is the sole owner of the event queue. Resolving such model clashes escalated the original two-person, six-month project into a five-person, two-year project: a factor of four increase in schedule and a factor of five increase in effort. Such experiences, and the more general technical and business issues shown in Table 1, indicate that COTS integration differs significantly from traditional software development and requires significantly different approaches to its management. At the USC Center for Software Engineering COTS Integration Affiliates' Workshop, we identified four key COTS integration issues: functional-ity and performance, interoperability, product evolution, and vendor behavior. You have no control over a COTS product's functionality or performance. If you modify the source code, it's not really COTS—and its future becomes your responsibility. Even as black boxes, big COTS products have formidable complexity; Windows 95, for example, has roughly 25,000 entry points. Let the buyer beware COTS-based projects cannot make blanket assumptions about system requirements or embrace traditional process models. One mistake developers can make is to use the waterfall model on a COTS integration project. With the waterfall model, you specify requirements and these determine the …
On Creative Self-Driving Cars: Hire the Computational Logicians, Fast

3 Creativity in What Sense? 3 3.1 Lovelace-Test Creativity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.2 Creative Formal Thought? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.3 Creative Musical Thought? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.4 Creative Literary Thought? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.5 But what about MacGyveresque creativity? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Spectral Hashing

Semantic hashing[1] seeks compact binary codes of data-points so that the Hamming distance between codewords correlates with semantic similarity. In this paper, we show that the problem of finding a best code for a given dataset is closely related to the problem of graph partitioning and can be shown to be NP hard. By relaxing the original problem, we obtain a spectral method whose solutions are simply a subset of thresholded eigenvectors of the graph Laplacian. By utilizing recent results on convergence of graph Laplacian eigenvectors to the Laplace-Beltrami eigenfunctions of manifolds, we show how to efficiently calculate the code of a novel datapoint. Taken together, both learning the code and applying it to a novel point are extremely simple. Our experiments show that our codes outperform the state-of-the art.
Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization

Can one parallelize complex exploration– exploitation tradeoffs? As an example, consider the problem of optimal highthroughput experimental design, where we wish to sequentially design batches of experiments in order to simultaneously learn a surrogate function mapping stimulus to response and identify the maximum of the function. We formalize the task as a multiarmed bandit problem, where the unknown payoff function is sampled from a Gaussian process (GP), and instead of a single arm, in each round we pull a batch of several arms in parallel. We develop GP-BUCB, a principled algorithm for choosing batches, based on the GP-UCB algorithm for sequential GP optimization. We prove a surprising result; as compared to the sequential approach, the cumulative regret of the parallel algorithm only increases by a constant factor independent of the batch size B. Our results provide rigorous theoretical support for exploiting parallelism in Bayesian global optimization. We demonstrate the effectiveness of our approach on two real-world applications.
Anomaly Detection in Elderly Daily Behavior in Ambient Sensing Environments

Current ubiquitous computing applications for smart homes aim to enhance people’s daily living respecting age span. Among the target groups of people, elderly are a population eager for “choices for living arrangements”, which would allow them to continue living in their homes but at the same time provide the health care they need. Given the growing elderly population, there is a need for statistical models able to capture the recurring patterns of daily activity life and reason based on this information. We present an analysis of real-life sensor data collected from 40 different households of elderly people, using motion, door and pressure sensors. Our objective is to automatically observe and model the daily behavior of the elderly and detect anomalies that could occur in the sensor data. For this purpose, we first introduce an abstraction layer to create a common ground for home sensor configurations. Next, we build a probabilistic spatio-temporal model to summarize daily behavior. Anomalies are then defined as significant changes from the learned behavioral model and detected using a cross-entropy measure. We have compared the detected anomalies with manually collected annotations and the results show that the presented approach is able to detect significant behavioral changes of the elderly.
Presence and Flow in Virtual Environments

Virtual environments (VEs) are thought to elicit a sense of presence to the user. The sense of presence is considered as a psychological experience of being in a world generated by the computer instead of using the computer from the outside. As a field of research the psychology of VE is quite new and not well explored. In this study the three components of the sense of presence are examined: spatial awareness, attention and the realness of the VE. The three components solution of presence is accused of following Cartesian tradition in separating perception from action. Interaction is considered an important part of the experience of presence. Some authors consider it as the only determinant of presence. The purpose of this study was to explore empirically this human experience. The idea was to integrate the presented presence components into a cognitive-emotional appraisal process from the environment. This type of an appraisal process in generating emotions dominates the field of modern psychological emotion theories. It has also been presented that similar appraisal process precedes optimal experience, i.e., flow. Flow has been used as a metrics to evaluate human computer interaction. However, there are only few studies in which both presence and flow has been measured. In this study the participants gained experiences while conducting a simple search task in a virtual CAVE. These experiences were measured with a questionnaire. Based on the results a three-dimensional framework was constructed. This framework integrated the experience of presence and interaction as well as an appraisal process from the environment based on one’s skills and challenges provided by the environment. In the appraisal process also personal relevance and evaluation of the interactivity of the VE are included. Framework also included two basic emotional dimensions arousal and control, which are considered important in producing the overall emotional experience. The framework was used to explain different endpoint experiences gained by the users. The results showed that the sense of presence is an integral part of the flow experience in VEs and in order to experience VE positively a user should experience both presence and flow in VE. Although, the framework needs more careful studying, it provides a fair depiction of the basic dynamics behind a subjective experience in VE.
Game Designers Training First Person Shooter Bots

Interactive training is well suited to computer games as it allows game designers to interact with otherwise autonomous learning algorithms. This paper investigates the outcome of a group of five commercial first person shooter game designers using a custom built interactive training tool to train first person shooter bots. The designers are asked to train a bot using the tool, and then comment on their experiences. The five trained bots are then pitted against each other in a deathmatch scenario. The results show that the training tool has potential to be used in a commercial environment.
A review: Information extraction techniques from research papers

Text extraction is a crucial stage of analyzing Journal papers. Journal papers generally are in PDF format which is semi structured data. Journal papers are presented into different sections like Introduction, Methodology, Experimental setup, Result and analysis etc. so that it is easy to access information from any section as per the reader's interest. The main importance on section extraction is to find a representative subset of the data, which contains the information of the entire set. Various approaches to extract sections from research papers include stastical methods, NLP, Machine Learning etc. In this paper we present review of various extraction techniques from a PDF document.
Streaming-LDA: A Copula-based Approach to Modeling Topic Dependencies in Document Streams

We propose in this paper two new models for modeling topic and word-topic dependencies between consecutive documents in document streams. The first model is a direct extension of Latent Dirichlet Allocation model (LDA) and makes use of a Dirichlet distribution to balance the influence of the LDA prior parameters wrt to topic and word-topic distribution of the previous document. The second extension makes use of copulas, which constitute a generic tools to model dependencies between random variables. We rely here on Archimedean copulas, and more precisely on Franck copulas, as they are symmetric and associative and are thus appropriate for exchangeable random variables. Our experiments, conducted on three standard collections that have been used in several studies on topic modeling, show that our proposals outperform previous ones (as dynamic topic models and temporal \LDA), both in terms of perplexity and for tracking similar topics in a document stream.
Network traffic characteristics of data centers in the wild

Although there is tremendous interest in designing improved networks for data centers, very little is known about the network-level traffic characteristics of data centers today. In this paper, we conduct an empirical study of the network traffic in 10 data centers belonging to three different categories, including university, enterprise campus, and cloud data centers. Our definition of cloud data centers includes not only data centers employed by large online service providers offering Internet-facing applications but also data centers used to host data-intensive (MapReduce style) applications). We collect and analyze SNMP statistics, topology and packet-level traces. We examine the range of applications deployed in these data centers and their placement, the flow-level and packet-level transmission properties of these applications, and their impact on network and link utilizations, congestion and packet drops. We describe the implications of the observed traffic patterns for data center internal traffic engineering as well as for recently proposed architectures for data center networks.
A Dual-Band Metasurface Antenna Using Characteristic Mode Analysis

A compact metasurface-based antenna is proposed for dual-band operations. The proposed metasurface is designed on a single-layered substrate including an array of modified  $3 \times 3$  squared patches. Each of the four corner patches is split into four fractional patches while the four edge patches are evolved into Malta crosses and the center patch is scaled. A substrate integrated waveguide-based Y-junction cavity-fed dual slot drives the metasurface with multiple impedance resonances. Based on the predicted modal behaviors of metasurface using a characteristic mode analysis (CMA), as an example, an antenna operating at three resonant modes at 28, 33, and 36 GHz, respectively is designed for the dual-band operation for the coming 5G. The proposed design shows that the measured impedance bandwidths (return loss larger than 10 dB) are 23.7–29.2 GHz and 36.7–41.1 GHz with the achieved gain of 4.8–7.2 dBi and 8.9–10.9 dBi, respectively. The proposed dual-band antenna features the advantages of low profile and wideband, suitable for the coming dual-band 5G applications.
Multimodal imaging of optic disc drusen.

To evaluate optic disc drusen, extracellular protein deposits known to contain numerous aggregates of mitochondria, using multimodal modalities featuring optical coherence tomography (OCT) and autofluorescence imaging.



Retrospective observational case series.



Eyes with optic nerve drusen were examined with enhanced depth imaging (EDI)-OCT, swept source OCT, and fundus autofluorescence using a fundus camera.



Twenty-six eyes of 15 patients with optic disc drusen were evaluated. EDI-OCT and swept source OCT showed multiple optic disc drusen at different levels; most were located immediately anterior to the lamina cribrosa. The drusen were ovoid regions of lower reflectivity that were bordered by hyperreflective material, and in 12 eyes (46.2%) there were internal hyperreflective foci. The mean diameter of the optic disc drusen as measured in OCT images was 686.8 (standard deviation ± 395.2) μm. There was a significant negative correlation between the diameter of the optic disc drusen and the global retinal nerve fiber layer thickness (r = -0.61, P = .001). There was a significant negative correlation between proportion of the optic disc drusen area occupied by optic nerve drusen as detected by autofluorescence imaging and the global retinal nerve fiber layer thickness (r = -0.63, P = .001).



Deeper-penetration OCT imaging demonstrated the internal characteristics of optic disc drusen and their relationship with the lamina cribrosa in vivo. This study also showed that both the larger the drusen and the more area of the optic canal occupied by drusen, the greater the associated retinal nerve fiber layer abnormalities.
Observing Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition

Interpretation of images and videos containing humans interacting with different objects is a daunting task. It involves understanding scene or event, analyzing human movements, recognizing manipulable objects, and observing the effect of the human movement on those objects. While each of these perceptual tasks can be conducted independently, recognition rate improves when interactions between them are considered. Motivated by psychological studies of human perception, we present a Bayesian approach which integrates various perceptual tasks involved in understanding human-object interactions. Previous approaches to object and action recognition rely on static shape or appearance feature matching and motion analysis, respectively. Our approach goes beyond these traditional approaches and applies spatial and functional constraints on each of the perceptual elements for coherent semantic interpretation. Such constraints allow us to recognize objects and actions when the appearances are not discriminative enough. We also demonstrate the use of such constraints in recognition of actions from static images without using any motion information.
Carotid Artery and Jugular Vein Tracking and Differentiation Using Spatiotemporal Analysis

We have derived and evaluated parameters from ultrasound images of the neck to permit a computer to automatically characterize and differentiate between the carotid artery and jugular vein at image acquisition time during vascular interventions, given manually placed seed points. Our goal is to prevent inadvertent damage to the carotid artery when targeting the jugular vein for catheterization. We used a portable 10 MHz ultrasound system to acquire cross sectional B-mode ultrasound images of these great vessels at 10 fps. An expert user identified the vessels in the first frame by touching the vessels on the screen with his fingertip, and the computer automatically tracked the vessels and calculated a best-fit ellipse for each vessel in each subsequent frame. Vessel location and radii were further analyzed to produce parameters that proved useful for differentiating between the carotid artery and jugular vein. These parameters include relative location of the vessels, distension of the vessel walls, and consistent phase difference between the arterial and venous pulsations as determined by temporal Fourier analysis.
Consumers ’ Perception on Online Shopping

E-commerce is emerging as a great level given that organized retail is still not ubiquitous across the length and breadth of the country with large retail chains making up less than 10% of the market.E-commerce is helping people in smaller towns in India access quality products and services similar to what people in the larger cities have access to. It being forecast that close to 60% of online shoppers would come from beyond the top eight large cities by end of this year.Increasing internet penetration has helped to expand the potential customer pool. Internet penetration is only about 10% (or about 121 million users) as against about 81% in the US and 36% in China. However this number continues to rise at a consistent pace because of falling prices for broadband connections. The first World Wide Web server and browser, created by Tim Berners-Lee in 1990, opened for commercial use in 1991. Thereafter, subsequent technological innovations emerged in 1994: online banking, the opening of an online pizza shop by Pizza Hut, Netscape's SSL v2 encryption standard for secure data transfer, and inter-shop’s first online shopping system. Immediately after, Amazon.com launched its online shopping site in 1995 and eBay was introduced in 1996. In the past decade, there has been a dramatic change in the way consumers have altered their way of shopping. Although consumers continue to purchase from a physical store, consumers feel very convenient to shop online since it frees the customer from personally visiting the store. Internet shopping has its own advantages and it reduces the effort of travelling to a physical store. Decisions can be made from home at ease looking at various choices and prices can be easily compared with the competitor’s products to arrive at a decision. This study highlights student’s attitude towards online shopping and their product preference on online shopping. This enable the e-retailers to support their online customer better by developing suitable marketing strategy in order to attract and convert potential customer as an active customers by encouraging them in an efficient way to make a purchase decision.
An Analytical Solution to the Stance Dynamics of Passive Spring-Loaded Inverted Pendulum with Damping

The Spring-Loaded Inverted Pendulum (SLIP) model has been established both as a very accurate descriptive tool as well as a good basis for the design and control of running robots. In particular, approximate analytic solutions to the otherwise nonintegrable dynamics of this model provide principled ways in which gait controllers can be built, yielding invaluable insight into their stability properties. However, most existing work on the SLIP model completely disregards the effects of damping, which often cannot be neglected for physical robot platforms. In this paper, we introduce a new approximate analytical solution to the dynamics of this system that also takes into account viscous damping in the leg. We compare both the predictive performance of our approximation as well as the tracking performance of an associated deadbeat gait controller to similar existing methods in the literature and show that it significantly outperforms them in the presence of damping in the leg.
A Multiphase Buck Converter With a Rotating Phase-Shedding Scheme For Efficient Light-Load Control

Mobile devices need to minimize their power consumption in order to maximize battery runtime, except during short extremely busy periods. This requirement makes dc-dc converters usually operate in standby mode or under light-load conditions. Therefore, implementation of an efficient regulation scheme under a light load is a key aspect of dc-dc converter design. This paper presents a multiphase buck converter with a rotating phase-shedding scheme for efficient light-load control. The converter includes four phases operating in an interleaved manner in order to supply high current with low output ripple. The multiphase converter implements a rotating phase-shedding scheme to distribute the switching activity concentrated on a single phase, resulting in a distribution of the aging effects among the phases instead of a single phase. The proposed multiphase buck converter was fabricated using a 0.18 μm bipolar CMOS DMOS process. The supply voltage ranges from 2.7 V to 5 V, and the maximum allowable output current is 4.5 A.
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions

The driving force behind deep networks is their ability to compactly represent rich classes of functions. The primary notion for formally reasoning about this phenomenon is expressive efficiency, which refers to a situation where one network must grow unfeasibly large in order to realize (or approximate) functions of another. To date, expressive efficiency analyses focused on the architectural feature of depth, showing that deep networks are representationally superior to shallow ones. In this paper we study the expressive efficiency brought forth by connectivity, motivated by the observation that modern networks interconnect their layers in elaborate ways. We focus on dilated convolutional networks, a family of deep models delivering state of the art performance in sequence processing tasks. By introducing and analyzing the concept of mixed tensor decompositions, we prove that interconnecting dilated convolutional networks can lead to expressive efficiency. In particular, we show that even a single connection between intermediate layers can already lead to an almost quadratic gap, which in large-scale settings typically makes the difference between a model that is practical and one that is not. Empirical evaluation demonstrates how the expressive efficiency of connectivity, similarly to that of depth, translates into gains in accuracy. This leads us to believe that expressive efficiency may serve a key role in the development of new tools for deep network design.