Miracle-dz/UniFAR-FTUs huggingface dataset:
Scheduling space-sharing for internet advertising

This paper provides the first in-depth study of the algorithmic questions involved in the scheduling of space-sharing for Internet advertising. We consider the scheduling problem where each advertisement is specified by a geometry and a display frequency. Given a set of ads, a schedule of the ads specifies which ads are to be displayed at the same time. The objective is find a schedule of the ads such that (1) each ad is displayed with the correct frequency, (2) each ad is allocated enough space for the specified geometry, (3) all the ads to be displayed simultaneously can be arranged in the space available for advertising. We demonstrate that an optimal schedule can be determined by finding a solution to a new variant of the bin packing problem that we introduce. In this new variant, there are a number of copies of each item to be placed into the bins. In addition to the usual bin packing requirements, all copies of an item must be placed in different bins. In this paper, we provide an efficient algorithm that finds the optimal solution to a restricted version of the new bin packing problem. This algorithm also provides a 2-approximation for the unrestricted case. We then apply this approximation to the problem of scheduling space-sharing for Internet advertising. We obtain a 2-approximation to the problem of minimizing the space requirements of a given set of ads, as well as to the problem of determining the best subset of the ads that can be scheduled with a given space constraint. We also consider an on-line version of the ad scheduling problem, where requests to purchase ad space arrive sequentially and after each request arrives, a decision must be made whether or not to sell the requested space without knowledge of future requests. We provide an algorithm that makes these decisions in a manner that is the best possible for any on-line algorithm. Copyright © 2002 John Wiley & Sons, Ltd.
Mass of Clusters in Simulations

We show that dark matter halos in N-body simulations have a boundary layer (BL), which neatly separates dynamically bound mass from unbound materials. We define T(r) and W(r) as the differential kinetic and potential energy of halos and evaluate them in spherical shells. We notice that in simulated halos such differential quantities fulfill the following properties: (1) the differential virial ratio ℛ = -2T/W has at least one persistent (resolution-independent) minimum , such that, close to , (2) the function w = -d log W/d log r has a maximum, while (3) the relation ℛ() ≃ w() holds. BLs are set where these three properties are fulfilled, in halos found in simulations of "tilted" Einstein-de Sitter and ΛCDM models, run ad hoc, using the ART and GADGET codes; their presence is confirmed in larger simulations of the same models with a lower level of resolution. Here we find that ~97% of the ~300 clusters (per model) we have with M > 4.2 × 1014 h-1 M☉ own a BL. Those clusters that appear not to have a BL are seen to be undergoing major merging processes and to grossly violate spherical symmetry. The radius ≡ rc has significant properties. First of all, the mass Mc it encloses almost coincides with the mass Mdyn, evaluated from the velocities of all particles within rc, according to the virial theorem. Also, materials at r > rc are shown not be in virial equilibrium. Using rc we can then determine an individual density contrast Δc for each virialized halo, which we compare with the "virial" density contrast Δv ≃ 178Ω (where Ωm is the matter density parameter) obtained assuming a spherically symmetric and unperturbed fluctuation growth. As expected, for each mass scale, Δv is within the range of values Δc. However, the spread in Δc is wide, while the average Δc is ~25% smaller than the corresponding Δv. We argue that the matching of properties derived under the assumption of spherical symmetry must be a consequence of an approximate sphericity, after violent relaxation destroyed features related to ellipsoidal nonlinear growth. On the contrary, the spread of the final Δc is an imprint of the different initial three-dimensional geometries of fluctuations and of the variable environment during their collapse, as suggested by a comparison of our results with the Sheth & Tormen analysis.
Primal space sparse kernel partial least squares regression for large scale problems

Kernel based methods suffer from exceeding time and memory requirements when applied on large datasets since the involved optimization problems typically scale polynomially in the number of data samples. As a remedy we propose both working on a reduced set (for fast evaluation) and at the same time keeping the number of model parameters small (for fast training). Departing from the Nystrom based feature approximation we describe fixed-size least squares support vector machine in the context of primal space least squares regression, to extend it with a supervised counterpart, sparse kernel partial least squares. The model is illustrated on a large scale example.
Unsupervised Data Driven Taxonomy Learning

The ability to effectively organize textual information is a big challenge in intelligent text processing. With the increase in the amount of textual data being generated, this task is becoming more and more essential. In this paper we present an unsupervised computer-aided tool for automatically building classification schemes and taxonomies for enhancing the process of automated text classification. The tool utilizes the Wikipedia knowledge base and its categorization system to achieve its goal. Validation of the tool was done using a subset of a large language dataset obtained from the Google moderator series (Egypt 2.0) idea bank. The output of the tool was evaluated by comparing the similarity between the results obtained automatically from the tool, and those manually annotated by three different human evaluators, verifying the effectiveness of the tool. The tool showed effectiveness with a precision of 88.6% and recall of 81.2%.
Sustainable Levels of Human Impact for Hector's Dolphin

Hector's dolphin is endemic to New Zealand, and listed as endangered on the IUCN Red List and equivalent New Zealand list of threatened species. The main threat to the species is entanglement in fishing gear, in particular gill- nets. The Potential Biological Removal (PBR) method developed by the US National Marine Fisheries Service is a com- monly used standard for determining a level of bycatch for marine mammal populations which, if exceeded, is likely to cause population decline. For Hector's dolphin, PBRs are less than one individual per year for most populations and the total for the whole species is less than 10 per year. Current estimated bycatch is on the order of 10-35 times higher than these PBRs. This is consistent with several Population Viability Analyses indicating that under current management Hec- tor's dolphin populations are declining rapidly.
Dynamic carbon 13 breath tests for the study of liver function and gastric emptying

In gastroenterological practice, breath tests (BTs) are diagnostic tools used for indirect, non-invasive assessment of several pathophysiological metabolic processes, by monitoring the appearance in breath of a metabolite of a specific substrate. Labelled substrates originally employed radioactive carbon 14 (14C) and, more recently, the stable carbon 13 isotope (13C) has been introduced to label specific substrates. The ingested 13C-substrate is metabolized, and exhaled 13CO2 is measured by mass spectrometry or infrared spectroscopy. Some 13C-BTs evaluate specific (microsomal, cytosolic, and mitochondrial) hepatic metabolic pathways and can be employed in liver diseases (i.e. simple liver steatosis, non-alcoholic steato-hepatitis, liver fibrosis, cirrhosis, hepatocellular carcinoma, drug and alcohol effects). Another field of clinical application for 13C-BTs is the assessment of gastric emptying kinetics in response to liquids (13C-acetate) or solids (13C-octanoic acid in egg yolk or in a pre-packed muffin or the 13C-Spirulina platensis given with a meal or a biscuit). Studies have shown that 13C-BTs, used for gastric emptying studies, yield results that are comparable to scintigraphy and can be useful in detecting either delayed- (gastroparesis) or accelerated gastric emptying or changes of gastric kinetics due to pharmacological effects. Thus, 13C-BTs represent an indirect, cost-effective and easy method of evaluating dynamic liver function and gastric kinetics in health and disease, and several other potential applications are being studied.
Image Retrieval with a Visual Thesaurus

Current state-of-art of image retrieval methods represent images as an unordered collection of local patches, each of which is classified as a "visual word" from a fixed vocabulary. This paper presents a simple but innovative way to uncover the spatial relationship between visual words so that we can discover words that represent the same latent topic and thereby improve the retrieval results. The method in this paper is borrowed from text retrieval, and is analogous to a text thesaurus in that it describes a broad set of equivalence relationship between words. We evaluate our method on the popular Oxford Building dataset. This makes it possible to compare our method with previous work on image retrieval, and the results show that our method is comparable to more complex state of the art methods.
Non-Euclidean metrics for similarity search in noisy datasets

In the context of classification, the dissimilarity between data elements is often measured by a metric defined on the data space. Often, the choice of the metric is often disregarded and the Euclidean distance is used without further inquiries. This paper illustrates the fact that when other noise schemes than the white Gaussian noise are encountered, it can be interesting to use alternative metrics for similarity search.
EIM: Efficient online interference measurement in wireless sensor networks

In wireless sensor networks, knowing real signal interference (received signal strength or RSS) from other sensors to cared sensor is critically important for protocol design and for many applications. However, the real interferences generally differ much from those calculated by theoretical or empirical models, because these models cannot capture the dynamic impacts of the environments. This paper presents EIM, an efficient method for sensors to online measure their interference vectors, where the interference vector of a sensor indicates the real interferences from other sensors to it when other sensors are transmitting packets. EIM conducts interference vector measurement passively during the natural working process of the sensor network. Because a sensor may be interfered by quite a few neighbors and the environments may change over time, the efficiency i.e. latency for real-time interference vector estimation is a very challenging issue. EIM exploits three facts to improve the efficiency of interference vector calculation. First, by exploiting the additivity property of the received signal strenth, a linear interference vector reconstruction model is developed. Secondly, EIM exploits not only the received and overheard packets from other sensors, but also the collided packets to construct the observation matrix of the linear model. Third, compressive sensing technologies are developed to recover the interference vector even when the observation matrix is partly determined. These methods help sensors much reduce the latency for calculating real-time interference vectors. Extensive simulations were carried out to verify the effectiveness and efficiency of the proposed methods.
Precise network monitoring for high quality live streaming

Live streaming of high quality media requires high quality network in terms of packet loss rate and jitter. However, the current IP or Ethernet network does not assure the bandwidth or jitter for streaming in general. In addition, the existing network monitoring system does not have the functionality to measure these network quality. My precise network monitoring is a packet-by-packet network monitoring to observe switching or routing latency inside of a switch, router, or network, and provide the statistics of a flow that is specified by user on-demand. We implemented this system, installed it in the existing network, and evaluated its functionality. It shows the impact of cross-traffic on a measured flow.
The eIF4G homolog DAP5/p97 supports the translation of select mRNAs during endoplasmic reticulum stress

DAP5/p97 is a member of the eIF4G family of translation initiation factors that has been suggested to play an important role in the translation of select messenger RNA molecules. We have shown previously that the caspase-cleaved form of DAP5/p97, termed p86, is required for the induction of the endoplasmic reticulum (ER)-stress-responsive internal ribosome entry site (IRES) of the caspase inhibitor HIAP2. We show here that expression of DAP5/p97 is enhanced during ER stress by selective recruitment of DAP5/p97 mRNA into polysomes via the DAP5/p97 IRES. Importantly, enhanced translation mediated by the DAP5/p97 IRES is dependent on DAP5/p97 itself, thus providing a positive feedback loop. In addition, we show that activation of DAP5/p97 and HIAP2 IRES during ER stress requires DAP5/p97. Significantly, the induction of DAP5/p97 during ER stress is caspase-independent, whereas the induction of HIAP2 requires proteolytic processing of DAP5/p97. Thus, DAP5/p97 is a translational activator that selectively modulates translation of specific mRNAs during conditions of cellular stress in both a caspase-dependent and caspase-independent manner.
Capturing tacit knowledge for assessing employees’ competency and productivity

Problem statement: Organization has to evaluate the competencies of their workers to improve organizational productivity. However, this is difficult because organizations have difficulties to capture and retain knowledge especially tacit knowledge of their employees. Approach: The study reviewed selected literature on management knowledge and employers competencies. It also reviewed existing frameworks in knowledge management focusing on the capturing and storing tacit knowledge. Results: Results of this study will include theoretical concept for capturing tacit knowledge and storing them besides developing a model for measuring employee’s competencies in the organization. Conclusion/Recommendation: This study contributes in assessing knowledge workers performance to improve their productivity in an organization.
Efficient and Accurate Path Cost Estimation Using Trajectory Data

Using the growing volumes of vehicle trajectory data, it becomes increasingly possible to capture time-varying and uncertain travel costs in a road network, including travel time and fuel consumption. The current paradigm represents a road network as a graph, assigns weights to the graph's edges by fragmenting trajectories into small pieces that fit the underlying edges, and then applies a routing algorithm to the resulting graph. We propose a new paradigm that targets more accurate and more efficient estimation of the costs of paths by associating weights with sub-paths in the road network. The paper provides a solution to a foundational problem in this paradigm, namely that of computing the time-varying cost distribution of a path. The solution consists of several steps. We first learn a set of random variables that capture the joint distributions of sub-paths that are covered by sufficient trajectories. Then, given a departure time and a path, we select an optimal subset of learned random variables such that the random variables' corresponding paths together cover the path. This enables accurate joint distribution estimation of the path, and by transferring the joint distribution into a marginal distribution, the travel cost distribution of the path is obtained. The use of multiple learned random variables contends with data sparseness, the use of multi-dimensional histograms enables compact representation of arbitrary joint distributions that fully capture the travel cost dependencies among the edges in paths. Empirical studies with substantial trajectory data from two different cities offer insight into the design properties of the proposed solution and suggest that the solution is effective in real-world settings.
Quantitative Understanding of Nanoparticle Uptake in Watermelon Plants

The use of agrochemical-nutrient fertilizers has come under scrutiny in recent years due to concerns that they damage the ecosystem and endanger public health. Nanotechnology offers many possible interventions to mitigate these risks by use of nanofertilizers, nanopesticides, and nanosensors; and concurrently increases profitability, yields, and sustainability within the agricultural industry. Aerosol based foliar delivery of nanoparticles may help to enhance nanoparticle uptake and reduce environmental impacts of chemical fertilizers conventionally applied through a soil route. The purpose of this work was to study uptake, translocation, and accumulation of various gold nanostructures, 30–80 nm, delivered by aerosol application to a watermelon plant. Cellular uptake and accumulation of gold nanoparticles were quantified by Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS). Observations suggested that nanoparticles could be taken up by the plant through direct penetration and transport through the stomatal opening. Observed translocation of nanoparticles from leaf to root shows evidence that nanoparticles travel by the phloem transport mechanism. Accumulation and transport of nanoparticles depend on nanoparticle shape, application method, and nature of plant tissues.
Induction of diapause and seasonal morphs in butterflies and other insects: knowns, unknowns and the challenge of integration

The ‘choice’ of whether to enter diapause or to develop directly has profound effects on the life histories of insects, and may thus have cascading consequences such as seasonal morphs and other less obvious forms of seasonal plasticity. Present knowledge of the control of diapause and seasonal morphs at the physiological and molecular levels is briefly reviewed. Examples, mainly derived from personal research (primarily on butterflies), are given as a starting point with the aim of outlining areas of research that are still poorly understood. These include: the role of the direction of change in photoperiod; the role of factors such as temperature and diet in modifying the photoperiodic responses; and the role of sex, parental effects and sex linkage on photoperiodic control. More generally, there is still a limited understanding of how external cues and physiological pathways regulating various traits are interconnected via gene action to form a co‐adapted complete phenotype that is adaptive in the wild despite environmental fluctuation and change.
Non-Commutative Extensions of the Standard Model

Four different extensions of the Standard Model to non-commutative space-time are considered. They all have the structure group U_Y(1) x SU_L(2) x SU_c(3) but differ through the way Yukawa interaction is implemented. Models based on non-commutative tensor products involve, in general several inequivalent Seiberg-Witten maps of some (Higgs or fermionic) matter field. The non-minimal Non-Commutative Standard Model, advocated by the Munich Group is reproduced at lowest order in the non-commutativity parameter by a particular model of this class. On the other hand, models based on hybrid Seiberg-Witten maps predict electromagnetic couplings of neutral particles like Z-boson, Higgs meson, or neutrino. The non-commutative contributions of the above Standard Model extensions at low energies are evaluated by integrating out all massive bosonic degrees of freedom.
A Finite Element Method for Density Estimation with Gaussian Process Priors

A variational problem characterizing the density estimator defined by the maximum a posteriori method with Gaussian process priors is derived. It is shown that this problem is well posed and can be solved with Newton's method. Numerically, the solution is approximated by a Galerkin/finite element method with piecewise multilinear functions on uniform grids. Error bounds for this method are given and numerical experiments are performed for one-, two-, and three-dimensional examples.
An Automatic Test Instrument for Dial Gauge Based on Computer Image Process

To solve the limitation of the current testing system for dial gauge, this paper proposes a machine vision-based automatic test instrument system. The system's test principle and structure are presented. Through the key image process algorithm, the dial gauge indicator automatic identification by machine is realized. By comparing the feed value provided by precision feeding mechanism with the actual reading of the instrument, it accomplishes the automatic examination. The experiment proves that this method can be applied in the production as its fast speed and high accuracy.
Impact of rotor winding and stator stepped end core on magnetic force distribution on stator end-winding of turbogenerators

Impact of the rotor end-winding on the force distribution of the stator end-winding using equivalent current sheets or a concentrated coil in each rotor slot has been so far considered in the literatures. However, the impact of the stator stepped end core on the force has not been studied yet. In this paper calculation methods for magnetic force exerted on the stator end-winding are first reviewed comprehensively; then the impact of some parameters on the magnetic force distribution on the stator end-winding of a 2-pole, 200 MVA turbo-generator under sudden three-phase short-circuit are studied. Three-dimensional finite element method (FEM) based on the reduced magnetic scalar potential formulation is used. The stator and rotor end-windings actual geometry is taken into account, except their cross section areas which are approximated by combination of straight line segments. To simplify the meshing process, stator stepped end core geometry is replaced by equivalent ramp geometry. Short-circuit currents of the generator windings are computed using two-dimensional transient FEM. It is shown that these parameters affect the stator end-winding magnetic force, particularly in the involutes part of the stator end-coils.
Embedding internet technology for home automation

As more and more digital appliances populate our homes, networking them to form a home automation (HA) system not only becomes an option, but almost a necessity. While comfort, security, and energy efficiency can be provided by many existing systems, they all remain complex islands that are difficult to expand and customize. We propose Internet technology to remedy the situation and to become the future solution for HA. For this, we analyze the feasibility of today's Internet technology with regard to traditional HA solutions. Furthermore, we present two case studies that substantiate the benefits of our proposal. As we will show, with IPv6 and 6LoWPAN, a single network serves the classical as well as emerging aspects of HA while concepts from the Web provide benefits for both, developers and users.
Cynical About Change? A Preliminary Meta-Analysis and Future Research Agenda

Cynicism about organizational change is often considered an important factor that influences employee acceptance of change initiatives. However, cynicism has been compared with several similar constructs with little conceptual or empirical differentiation. To provide a deeper understanding of change cynicism, we compare and contrast it with similar—yet distinct—constructs: organizational trust, resistance to change, and organizational cynicism. We begin with a narrative review of the conceptual distinctions and similarities among these constructs, followed by meta-analysis of the nomological network of change cynicism. In addition, we compare the nomological network of change cynicism with those of organizational cynicism and trust. We discuss the need for a refined conceptualization of cynicism and suggest new areas for future research.