Miracle-dz/UniFAR-FTUs huggingface dataset:
Traffic Shaping to Optimize Ad Delivery

Web publishers must balance two objectives: how to keep users engaged by directing them to relevant content, and how to properly monetize this user traffic. The standard approach is to solve each problem in isolation, for example, by displaying content that is tailored to the user’s interests so as to maximize clickthrough rates (CTR), and also by building a standalone ad serving system that displays ads depending on the user’s characteristics, the article being viewed by the user, and advertiser-specified constraints. However, showing the user only those articles with highest expected CTR precludes the display of some ads; if the publisher had previously guaranteed the delivery of a certain volume of impressions to such ads, then underdelivery penalties might have to be paid. We propose a joint optimization of article selection and ad serving that minimizes underdelivery by shaping some of the incoming traffic to pages where underperforming ads can be displayed, while incurring only minor drops in CTR. In addition to formulating the problem, we design an online optimization algorithm that can find the optimal traffic shaping probabilities for each new user using only a cache of one number per ad contract. Experiments on a large real-world ad-serving Web portal demonstrate significant advantages over the standalone approach: a threefold reduction in underdelivery with only 10% drop in CTR, or a 2.6-fold reduction with a 4% CTR drop, and similar results over a wide range.
Communications of the Association for Information Systems

: Few studies have synthesized accumulated scholarly knowledge on software piracy across the disciplines that study this phenomenon. We contribute to understanding the intellectual and social development on software piracy by performing a cross-disciplinary literature search. We used 17 research questions to address five specific areas of inquiry on software piracy research: 1) what makes up software piracy’s intellectual substance? , 2) do theoretical contributions on software piracy suggest a cross-disciplinary research community on the topic? , 3) what changes have occurred in software piracy research across the seven measured periods? , 4) what are the top IS journals’ publishing patterns on software piracy research? , and 5) who has contributed to software piracy research? To address these questions, we classified 179 software research studies. We found that: 1) over 50 percent of the studies focused on an individual level of analysis, 2) most papers examined software piracy in North America and Asia Pacific regions, although other regions also have major problems, and 3) the distribution of theoretical and methodological contributions show a pattern of leaning towards positivism. The findings point to several research opportunities including expanding research: 1) at organizational levels with particular emphasis on organizations’ role as consumers and or intermediaries, 2) in Latin America and Africa, which are areas with high incidence of software piracy, and 3) on approaches beyond positivism.
A novel real-coded quantum-inspired genetic algorithm and its application in data reconciliation

Data reconciliation techniques play a significant role in the industrial manufacture process, especially in the petrochemical industry. Different heuristic optimization methods have been proposed to solve this problem in previous study. In this paper, a novel real-coded quantum-inspired genetic algorithm (RLCQGA) is proposed, which has stronger search ability and quicker convergence speed, not only because of the introduction of real number coding method, but also due to interval division technique. The proposed approach is tested with five standard benchmark functions and two industrial process cases. Detailed comparisons with similar approaches are given and discussed. The promising results illustrate the efficiency of the proposed method and show that it could be used as a reliable tool for solving nonlinear data reconciliation problems.
Heavy metal movement through insect food chains in pristine thermal springs of Yellowstone National Park

Yellowstone National Park thermal features regularly discharge various heavy metals and metalloids. These metals are taken up by microorganisms that often form mats in thermal springs. These microbial mats also serve as food sources for invertebrate assemblages. To examine how heavy metals move through insect food webs associated with hot springs, two sites were selected for this study. Dragon-Beowulf Hot Springs, acid-sulfate chloride springs, have a pH of 2.9, water temperatures above 70 °C, and populations of thermophilic bacterial, archaeal, and algal mats. Rabbit Creek Hot Springs, alkaline springs, have a pH of up to 9, some water temperatures in excess of 60 °C, and are populated with thermophilic and phototrophic bacterial mats. Mats in both hydrothermal systems form the trophic base and support active metal transfer to terrestrial food chains. In both types of springs, invertebrates bioaccumulated heavy metals including chromium, manganese, cobalt, nickel, copper, cadmium, mercury, tin and lead, and the metalloids arsenic, selenium, and antimony resulting from consuming the algal and bacterial mat biomass. At least two orders of magnitude increase in concentrations were observed in the ephydrid shore fly Paracoenia turbida, as compared to the mats for all metals except antimony, mercury, and lead. The highest bioaccumulation factor (BAF) of 729 was observed for chromium. At the other end of the food web, the invertebrate apex predator, Cicindelidia haemorrhagica, had at least a 10-fold BAF for all metals at some location-year combinations, except with antimony. Of other taxa, high BAFs were observed with zinc for Nebria sp. (2180) and for Salda littoralis (1080). This accumulation, occurring between primary producer and primary consumer trophic levels at both springs, is biomagnified through the trophic web. These observations suggest trace metals enter the geothermal food web through the microbial mat community and are then transferred through the food chain. Also, while bioaccumulation of arsenic is uncommon, we observed five instances of increases near or exceeding 10-fold: Odontomyia sp. larvae (13.6), P. turbida (34.8), C. haemorrhagica (9.7), Rhagovelia distincta (16.3), and Ambrysus mormon (42.8).
Developing a resilience assessment framework for the Urban Land–Water System

Coastal areas of China have experienced rapid land development accompanied by an increase of impervious surface area often, leading to considerable environmental degradation, particularly for water quantity and quality. This land–water interaction within an urban milieu, called an Urban Land–Water System, involves critical ecosystem function loss and undesirable resilience change. With the purpose of identifying changes in spatial–temporal resilience of an Urban Land–Water System, we formulated an innovative quantitative method for resilience assessment based on the concept of critical functionality and Hooke's Law. The resilience assessment method contextualizes critical functionality of complex systems by integrating subsystems of impervious surface area with subsystems of water quantity and water quality. The method was applied in a study area named Lianyungang, whereby we compared different contributions of three subsystems within two scenarios, Scenario a (one‐fourth of impervious surface area, one‐half of water quantity, and one‐fourth of water quality) and Scenario b (one‐third for each subsystem). Overall, resilience degrades for the Urban Land–Water System from 2005 to 2010 to a relatively lower state with significantly increasing areas (from 62.88 to 281.50 km2) of low‐value resilience. Impervious surface area and water quantity were the main contributors to resilience change. In particular, the loss of resilience within Lianyungang was mostly due to the loss of evapotranspiration and increased built‐up land in both urban and rural areas. The resilience assessment method developed herein identifies areas of significant influences on nested and overlapping resilience change, thereby offering a practical approach for identifying hotspots for managing balances between different spatial–temporal subsystems.
How does personality affect trust in B2C e-commerce?

Trust is a critical component of successful e-Commerce. Given the impersonality, anonymity, and automation of transactions, online vendor trustworthiness cannot be assessed by means of body language and other environmental cues that consumers typically use when deciding to trust offline retailers. It is therefore essential that the design of e-Commerce websites compensate by incorporating circumstantial cues in the form of appropriate trust triggers. This paper presents and discusses the results of a study which took an initial look at whether consumers with different personality types (a) are generally more trusting and (b) rely on different trust cues during their assessment of first impression vendor trustworthiness in B2C e-Commerce.
CardioVinci: building blocks for virtual cardiac cells using deep learning

Recent advances in high-throughput microscopy imaging have made it easier to acquire large volumes of cell images. Thanks to electron microscopy (EM) imaging, they provide a high-resolution and sufficient field of view that suits imaging large cell types, including cardiomyocytes. A significant bottleneck with these large datasets is the time taken to collect, extract and statistically analyse 3D changes in cardiac ultrastructures. We address this bottleneck with CardioVinci.
Towards Automatic Generation of Peer-Targeted Science Talk in a Curiosity-Evoking Virtual Agent Leave

Curiosity is a critical skill that spurs learning, but is often found to decline with age and schooling. Recent research has shown that peer interaction may serve a special role in inducing curiosity through increased uncertainty and conceptual conflicts, since peers have similar knowledge and ability. For a virtual agent to stimulate curiosity in peer-interaction contexts , the virtual peer should be able to engage in curiosity-scaffolding behaviors such as argumentation and hypothesis formulation. Consequently, the agent must be capable of on-task and open-ended reasoning required to express these verbal behaviors, while also exhibiting peer-like cognitive abilities. Automatic data-driven generation of curiosityscaffolding behaviors for virtual peers is important given the spontaneity of child-child conversations, their latent reasoning processes and open-endedness required of curiosity-scaffolding interaction. In this paper, we design and implement a virtual peer that can carry out curiosity-stimulating verbal behaviors while engaged in discussion during multi-party board game play. We use a combination of child knowledge-graph construction and child-child interaction driven modeling to generate game-context appropriate behaviors that are compatible with 9-14 year old children. Encouraging human evaluation of the generated behaviors and generalizeability of the generation framework to other tasks opens up new directions in incorporating open-endedness and science talk in virtual agents that will make them truly play a peer role in learning.
WatchIT: Who Watches Your IT Guy?

System administrators have unlimited access to system resources. As the Snowden case shows, these permissions can be exploited to steal valuable personal, classified, or commercial data. In this work we propose a strategy that increases the organizational information security by constraining IT personnel's view of the system and monitoring their actions. To this end, we introduce the abstraction of perforated containers -- while regular Linux containers are too restrictive to be used by system administrators, by "punching holes" in them, we strike a balance between information security and required administrative needs. Our system predicts which system resources should be accessible for handling each IT issue, creates a perforated container with the corresponding isolation, and deploys it in the corresponding machines as needed for fixing the problem. Under this approach, the system administrator retains his superuser privileges, while he can only operate within the container limits. We further provide means for the administrator to bypass the isolation, and perform operations beyond her boundaries. However, such operations are monitored and logged for later analysis and anomaly detection. We provide a proof-of-concept implementation of our strategy, along with a case study on the IT database of IBM Research in Israel.
SRDE: an improved differential evolution based on stochastic ranking

In this paper, we propose a methodology to improve the performance of the standard Differential Evolution (DE) in constraint optimization applications, in terms of accelerating its search speed, and improving the success rate. One critical mechanism embedded in the approach is applying Stochastic Ranking (SR) to rank the whole population of individuals with both objective value and constraint violation to be compared. The ranked population is then in a better shape to provide useful information e.g. direction to guide the search process. The performance of the proposed approach, which we call SRDE (Stochastic Ranking based Differential Evolution) is investigated and compared with standard DE with two variants of mutation strategies. The experimental results show that SRDE outperforms, or at least is comparable with standard DE in both variants in all the tested benchmark functions.
Urban Ornithology

This book offers the first quantitative long-term historical analysis of the migratory, winter, and breeding avifaunas of any New York City natural area—Van Cortlandt Park and the adjacent Northwest Bronx—and spans the century and a half from 1872 to 2016. Only Manhattan’s Central and Brooklyn’s Prospect Parks have published even lightly annotated cumulative species lists, last updated in 1967, and the most recent book addressing the birdlife of the New York City area was published more than 50 years ago. Addressed are the 301 Bronx, New York City and New York City area species known to have occurred within the study area, plus another 70 potential additions. These are contrasted with their status in adjacent Riverdale, the entire Bronx, Central and Prospect Parks, New York City, plus Long Island, Westchester, and Rockland Cos. The history of the 123 known study area breeding species are tracked from 1872—only 20 years after Audubon’s death in Manhattan—complemented by unique quantitative breeding data from Van Cortlandt Park censuses from 1937 to 2015. Gains and losses of breeding species are tracked and discussed as an expanding New York City inexorably extinguished unique habitat, offset only slightly by addition of two large reservoirs. Comparisons are provided with analogous data from heavily monitored Central and Prospect Parks. The tradeoffs in attempting to managing an urban park area for mass recreation at the same time as conserving its natural resources are highlighted.
Humpback Whales and Humans: A Multi-Disciplinary Approach to Exploring the Whale-Watching Industry in Juneau, Alaska

A booming whale-watching industry in Juneau, Alaska is leading to complicated resource management challenges. Juneau’s growing commercial whale-watching industry includes over 60 vessels and generates more than $25 million in annual revenue. As this industry has increased, so too have concerns for the welfare of humpback whales (Megaptera novaeangliae) exposed to this vessel traffic. However, we lack a fundamental understanding of long-term impacts, if any, that vessel disturbance has on humpback whales. Further, we have insufficient data on local abundance and seasonal attendance of humpback whales that are necessary to detect potential future changes. The aim of this project is to investigate Juneau area humpback whales and their interactions with whale-watching tourism to set a foundation for sustainable management of this resource and industry. To reach this objective, three studies were employed. 1) Methods for monitoring humpback whale population parameters through a citizen science program were developed and tested. Photo­ identification data were collected on whale-watching platforms and compared to data from dedicated surveys to objectively evaluate the citizen science data collection methods and identify biases. 2) Physiological markers were evaluated for signs of a chronic stress response in blubber of Juneau-area humpback whales compared with humpback whales from other areas in Alaska with far less vessel traffic. The concentrations of several steroid hormones, including cortisol, were measured from biopsy samples and used to infer a relative cumulative stress response in whales exposed to Juneau’s tourism fleet. 3) Community perceptions toward Juneau’s whale-
Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications –

1. PROPENSITY SCORED LOSSES This section provides proofs for all the theorems stated in Section 4 of the paper. Theorem 4.1. The loss function L(y, ŷ) evaluated on the observed ground truth y is an unbiased estimator of the true loss function L∗(y∗, ŷ) evaluated on complete ground truth y∗. Thus, Ey[L(y, ŷ)] = Ey∗ [L∗(y∗, ŷ)], for any P (y∗) and P (y) related through propensities pl and any fixed ŷ. Proof. Ey[L(y, ŷ)] = ∑
A deep hierarchy of predictions enables assignment of semantic roles in online speech comprehension

Understanding speech requires mapping fleeting and often ambiguous soundwaves to meaning. While humans are known to exploit their capacity to contextualize to facilitate this process, how internal knowledge is deployed on-line remains an open question. Here, we present a model that extracts multiple levels of information from continuous speech online. The model applies linguistic and nonlinguistic knowledge to speech processing, by periodically generating top-down predictions and incorporating bottom-up incoming evidence in a nested temporal hierarchy. We show that a nonlinguistic context level provides semantic predictions informed by sensory inputs, which are crucial for disambiguating among multiple meanings of the same word. The explicit knowledge hierarchy of the model enables a more holistic account of the neurophysiological responses to speech compared to using lexical predictions generated by a neural-network language model (GPT-2). We also show that hierarchical predictions reduce peripheral processing via minimizing uncertainty and prediction error. With this proof-of-concept model we demonstrate that the deployment of hierarchical predictions is a possible strategy for the brain to dynamically utilize structured knowledge and make sense of the speech input.
at UWindsor

To statistically model large data sets of knowledge processes during asynchronous, online forums, we must address analytic difficulties involving the whole data set (missing data, nested data and the tree structure of online messages), dependent variables (multiple, infrequent, discrete outcomes and similar adjacent messages), and explanatory variables (sequences, indirect effects, false positives, and robustness). Statistical discourse analysis (SDA) addresses all of these issues, as shown in an analysis of 1,330 asynchronous messages written and self-coded by 17 students during a 13-week online educational technology course. The results showed how attributes at multiple levels (individual and message) affected knowledge creation processes. Men were more likely than women to theorize. Asynchronous messages created a micro-sequence context; opinions and asking about purpose preceded new information ; anecdotes , opinions , different opinions , elaborating ideas, and asking about purpose or information preceded theorizing . These results show how informal thinking precedes formal thinking and how social metacognition affects knowledge creation.
High Throughput Route Selection in Multi-rate Ad hoc Wireless Networks

An ad hoc wireless network is an autonomous self-organizing system of mobile nodes connected by wireless links where nodes not in direct range communicate via intermediate nodes. Modern wireless devices, such as those implementing 802.11b, utilize multiple modulation schemes with different rates to accommodate changes in link quality. A common technique used by existing ad hoc routing protocols is to select theshortestpath, defined by the minimum number of hops, between the source and the destination. This typically results in a path composed predominantly of low rate links which has low effective throughput and high opportunity cost. We present an alternate technique for route selection which takes into account the diverse link rates present in multi-rate ad hoc wireless networks. This technique defines a link metric which is proportional to the time it takes to transmit a packet on that link. The path selected by this medium time metrichas both the lowest latency and highest effective capacity of any path in the network, and is thus dubbed thefastestpath. In this work we compute rate based link weights appropriate for 802.11b networks according to our medium time metric technique, and present the Destination Sequenced Distance Vector Rate Metric (DSDV-RM) routing protocol. DSDV-RM is an enhanced version of DSDV which uses the sum of rate based link weights instead of hop count as its distance metric. Finally, we show the throughput gains provided by fastest path DSDV-RM over shortest path DSDV in a variety of NS simulations of 802.11b ad hoc wireless networks.
A Java applet-based virtual environment as a usable interface to distributed services and collaborative applications on the Internet

In this paper we tackle the problem of implementing a user graphical interface that plays the role of an Internet distributed applications container. A Java applet-based DVE (Distributed Virtual Environment), named VERSA (Virtual Environment for Remote Services Access) has been conceived as a common users' platform for acceding to services and applications by means of virtual reality and multimedia communication. The user, that inhabits the "palace" in the semblance of an avatar, may move across rooms and corridors, interact with other avatars, communicate with them and join collaborative sessions of Internet applications by the simple action of entering special rooms. An inter-server communication protocol has been introduced for locating and acceding to such distributed services on the Internet. A widely distributed multi-server structure is implemented to ensure multi-user access and differentiated kinds of services.
Feature Selection Based on Genetic Algorithms for On-Line Signature Verification

Two different genetic algorithm (GA) architectures are applied to a feature selection problem in on-line signature verification. The standard GA with binary coding is first used to find a suboptimal subset of features that minimizes the verification error rate of the system. The curse of dimensionality phenomenon is further investigated using a GA with integer coding. Results are given on the MCYT signature database comprising 330 users (16500 signatures). Signatures are represented by means of a set of 100 features which can be divided into four different groups according to the signature information they contain, namely: i) time, ii) speed and acceleration, iii) direction, and iv) geometry. The GA indicates that features from subsets i and iv are the most discriminative when dealing with random forgeries, while parameters from subsets ii and iv are the most appropriate to maximize the recognition rate with skilled forgeries.