title: Pornography and attitudes supporting violence against women: revisiting the relationship in nonexperimental studies

abstract: ::::::::::::: :::::::::::::::: :::::::::::: A meta-analysis was conducted to determine whether nonexperimental studies revealed an association between men’s pornography consumption and their attitudes supporting violence against women. The meta-analysis corrected problems with a previously published meta-analysis and added more recent findings. In contrast to the earlier meta-analysis, the current results showed an overall significant positive association between pornography use and attitudes supporting violence against women in nonexperimental studies. In addition, such attitudes were found to correlate significantly higher with the use of sexually violent pornography than with the use of nonviolent pornography, although the latter relationship was also found to be significant. The study resolves what appeared to be a troubling discordance in the literature on pornography and aggressive attitudes by showing that the conclusions from nonexperimental studies in the area are in fact fully consistent with those of their counterpart experimental studies. This finding has important implications for the overall literature on pornography and aggression. Aggr.


title: Quality-biased ranking of web documents

abstract: Many existing retrieval approaches do not take into account the content quality of the retrieved documents, although link-based measures such as PageRank are commonly used as a form of document prior. In this paper, we present the quality-biased ranking method that promotes documents containing high-quality content, and penalizes low-quality documents. The quality of the document content can be determined by its readability, layout and ease-of-navigation, among other factors. Accordingly, instead of using a single estimate for document quality, we consider multiple content-based features that are directly integrated into a state-of- the-art retrieval method. These content-based features are easy to compute, store and retrieve, even for large web collections. We use several query sets and web collections to empirically evaluate the performance of our quality-biased retrieval method. In each case, our method consistently improves by a large margin the retrieval performance of text-based and link-based retrieval methods that do not take into account the quality of the document content.


title: Computational thinking: what it might mean and what we might do about it

abstract: Computational thinking has been promoted in recent years as a skill that is as fundamental as being able to read, write, and do arithmetic. However, what computational thinking really means remains speculative. While wonders, discussions and debates will likely continue, this article provides some analysis aimed to further the understanding of the notion. It argues that computational thinking is likely a hybrid thinking paradigm that must accommodate different thinking modes in terms of the way each would influence what we do in computation. Furthermore, the article makes an attempt to define computational thinking and connect the (potential) thinking elements to the known thinking paradigms. Finally, the author discusses some implications of the analysis.


title: Modeling and animating eye blinks

abstract: Facial animation often falls short in conveying the nuances present in the facial dynamics of humans. In this article, we investigate the subtleties of the spatial and temporal aspects of eye blinks. Conventional methods for eye blink animation generally employ temporally and spatially symmetric sequences; however, naturally occurring blinks in humans show a pronounced asymmetry on both dimensions. We present an analysis of naturally occurring blinks that was performed by tracking data from high-speed video using active appearance models. Based on this analysis, we generate a set of key-frame parameters that closely match naturally occurring blinks. We compare the perceived naturalness of blinks that are animated based on real data to those created using textbook animation curves. The eye blinks are animated on two characters, a photorealistic model and a cartoon model, to determine the influence of character style. We find that the animated blinks generated from the human data model with fully closing eyelids are consistently perceived as more natural than those created using the various types of blink dynamics proposed in animation textbooks.


Problems in Multi-Modal Scheduling Theory for Thermal-Resilient Multicore Systems


title: Combining Shape-Changing Interfaces and Spatial Augmented Reality Enables Extended Object Appearance

abstract: We propose combining shape-changing interfaces and spatial augmented reality for extending the space of appearances and interactions of actuated interfaces. While shape-changing interfaces can dynamically alter the physical appearance of objects, the integration of spatial augmented reality additionally allows for dynamically changing objects' optical appearance with high detail. This way, devices can render currently challenging features such as high frequency texture or fast motion. We frame this combination in the context of computer graphics with analogies to established techniques for increasing the realism of 3D objects such as bump mapping. This extensible framework helps us identify challenges of the two techniques and benefits of their combination. We utilize our prototype shape-changing device enriched with spatial augmented reality through projection mapping to demonstrate the concept. We present a novel mechanical distance-fields algorithm for real-time fitting of mechanically constrained shape-changing devices to arbitrary 3D graphics. Furthermore, we present a technique for increasing effective screen real estate for spatial augmented reality through view-dependent shape change.


title: On the Key Generation Rate of Physically Unclonable Functions

abstract: In this paper, an algebraic binning based coding scheme and its associated achievable rate for key generation using physically unclonable functions (PUFs) is determined. This achievable rate is shown to be optimal under the generated-secret (GS) model for PUFs. Furthermore, a polar code based polynomial-time encoding and decoding scheme that achieves this rate is also presented.


title: From emotion perception to emotion experience: Emotions evoked by pictures and classical music

abstract: Most previous neurophysiological studies evoked emotions by presenting visual stimuli. Models of the emotion circuits in the brain have for the most part ignored emotions arising from musical stimuli. To our knowledge, this is the first emotion brain study which examined the influence of visual and musical stimuli on brain processing. Highly arousing pictures of the International Affective Picture System and classical musical excerpts were chosen to evoke the three basic emotions of happiness, sadness and fear. The emotional stimuli modalities were presented for 70 s either alone or combined (congruent) in a counterbalanced and random order. Electroencephalogram (EEG) Alpha-Power-Density, which is inversely related to neural electrical activity, in 30 scalp electrodes from 24 right-handed healthy female subjects, was recorded. In addition, heart rate (HR), skin conductance responses (SCR), respiration, temperature and psychometrical ratings were collected. Results showed that the experienced quality of the presented emotions was most accurate in the combined conditions, intermediate in the picture conditions and lowest in the sound conditions. Furthermore, both the psychometrical ratings and the physiological involvement measurements (SCR, HR, Respiration) were significantly increased in the combined and sound conditions compared to the picture conditions. Finally, repeated measures ANOVA revealed the largest Alpha-Power-Density for the sound conditions, intermediate for the picture conditions, and lowest for the combined conditions, indicating the strongest activation in the combined conditions in a distributed emotion and arousal network comprising frontal, temporal, parietal and occipital neural structures. Summing up, these findings demonstrate that music can markedly enhance the emotional experience evoked by affective pictures.


title: Credit and Debit Card Usage and Cash Flow Management Control by Customers: Evidences from Commercial Banks Customers in Kisumu City, Kenya

abstract: In the recent past, the banking sector in Kenya has witnessed a rapid growth, issuing thousands of credit cards and millions of debit cards to their customers. The frequency in which customers use these cards for various transactions raised concerns of whether customers had lost control over their finances. Previous studies on this area have provided very little understanding on the impact of use of debit and credit cards on customers‟ cash flow management control. This study sought to determine the extent of use of debit and credit cards in cash deposits, withdrawals and purchase transactions at retail outlets and to determine its effects on cardholder‟s cash flow management. Data was collected through a structured questionnaire administered to a sample of 35 debit and credit cardholders each, drawn from customers of 7 main commercial banks in Kisumu city, Kenya. The study revealed that both debit and credit cards usage increases cash outflows compared to cash inflows and that use of these cards has increased consumption levels as opposed to investments. As a premier study in Kenya, this study will greatly help in the understanding of the impact debit and credit cards in developing countries which are yet to advance in technology. Key words: Debit cards, credit cards, commercial banks, Kenya.


title: Adjuvant hyperthermic intraperitoneal chemotherapy (HIPEC) in patients with colon cancer at high risk of peritoneal carcinomatosis; the COLOPEC randomized multicentre trial

abstract: BACKGROUND ::: The peritoneum is the second most common site of recurrence in colorectal cancer. Early detection of peritoneal carcinomatosis (PC) by imaging is difficult. Patients eventually presenting with clinically apparent PC have a poor prognosis. Median survival is only about five months if untreated and the benefit of palliative systemic chemotherapy is limited. Only a quarter of patients are eligible for curative treatment, consisting of cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CR/HIPEC). However, the effectiveness depends highly on the extent of disease and the treatment is associated with a considerable complication rate. These clinical problems underline the need for effective adjuvant therapy in high-risk patients to minimize the risk of outgrowth of peritoneal micro metastases. Adjuvant hyperthermic intraperitoneal chemotherapy (HIPEC) seems to be suitable for this purpose. Without the need for cytoreductive surgery, adjuvant HIPEC can be performed with a low complication rate and short hospital stay. ::: ::: ::: METHODS/DESIGN ::: The aim of this study is to determine the effectiveness of adjuvant HIPEC in preventing the development of PC in patients with colon cancer at high risk of peritoneal recurrence. This study will be performed in the nine Dutch HIPEC centres, starting in April 2015. Eligible for inclusion are patients who underwent curative resection for T4 or intra-abdominally perforated cM0 stage colon cancer. After resection of the primary tumour, 176 patients will be randomized to adjuvant HIPEC followed by routine adjuvant systemic chemotherapy in the experimental arm, or to systemic chemotherapy only in the control arm. Adjuvant HIPEC will be performed simultaneously or shortly after the primary resection. Oxaliplatin will be used as chemotherapeutic agent, for 30 min at 42-43 °C. Just before HIPEC, 5-fluorouracil and leucovorin will be administered intravenously. Primary endpoint is peritoneal disease-free survival at 18 months. Diagnostic laparoscopy will be performed routinely after 18 months postoperatively in both arms of the study in patients without evidence of disease based on routine follow-up using CT imaging and CEA. ::: ::: ::: DISCUSSION ::: Adjuvant HIPEC is assumed to reduce the expected 25 % absolute risk of PC in patients with T4 or perforated colon cancer to a risk of 10 %. This reduction is likely to translate into a prolonged overall survival. ::: ::: ::: TRIAL REGISTRATION NUMBER ::: NCT02231086 (Clinicaltrials.gov).


title: Touch Panel-type Dementia Assessment Scale: a new computer-based rating scale for Alzheimer's disease

abstract: Background: The Alzheimer's Disease Assessment Scale (ADAS) was designed as a rating scale for the severity of dysfunction in the cognitive and non-cognitive behaviours that are characteristic of persons with Alzheimer's disease. Its subscale, the ADAS-cog, is a cognitive testing instrument most widely used to measure the impact of the disease. However, the ADAS-cog takes more than 45 min to administer and requires a qualified clinical psychologist as the rater. A more comprehensive rating battery is therefore required. In the present study, we developed a computerized test battery named the Touch Panel-type Dementia Assessment Scale (TDAS), which was intended to substitute for the ADAS-Cog, and was specifically designed to rate cognitive dysfunction quickly and without the need of a specialist rater. ::: ::: ::: ::: Methods: The hardware for the TDAS comprises a 14-inch touch panel display and computer devices built into one case. The TDAS runs on Windows OS and was bundled with a custom program made with reference to the ADAS-cog. Participants in the present study were 34 patients with Alzheimer's disease. Each participant was administered the ADAS-cog and the TDAS. The test scores for each patient were compared to determine whether the severity of cognitive dysfunction of the patients could be rated equally as well by both tests. ::: ::: ::: ::: Results: Pearson's correlation coefficient showed a significant correlation between the total scores (r= 0.69, P < 0.01) on the two scales for each patient. The Kendall coefficients of concordance obtained for the three corresponding pairs of tasks (word recognition, orientation, and naming object and fingers) showed the three TDAS tasks can rate symptoms of cognitive decline equally as well as the corresponding items on the ADAS-cog. ::: ::: ::: ::: Conclusions: The TDAS appears to be a sensitive and comprehensive assessment battery for rating the symptoms of Alzheimer's disease, and can be substituted for the ADAS-cog.


title: DNA sequence based data classification technique

abstract: DNA sequence is a well established means for species classification and it motivated us to use DNA sequence for the purpose of data mining and knowledge discovery. In this work, we have considered different entities of DNA signature for the construction of an efficient classification algorithm. The proposed DNA sequence based data classification algorithm has been tested over three datasets namely: iris, wine and new-thyroid and its performance is observed satisfactory. Further, the performance of proposed algorithm has been compared with different variants of differential evolution (DE) and we observed the superiority of proposed method. These DE variants are used for optimizing the positioning of prototypes in nearest neighbour classification. We used the 1- NN rule as a baseline limit of performance.


title: Hashtags and followers An experimental study of the online social network Twitter

abstract: We have conducted an analysis of data from 502,891 Twitter users and focused on investigating the potential correlation between hashtags and the increase of followers to determine whether the addition of hashtags to tweets produces new followers. We have designed an experiment with two groups of users: one tweeting with random hashtags and one tweeting without hashtags. The results showed that there is a correlation between hashtags and followers: on average, users tweeting with hashtags increased their followers by 2.88, while users tweeting without hashtags increased 0.88 followers. We present a simple, reproducible approach to extract and analyze Twitter user data for this and similar purposes.


title: Incentive mechanism for peer-to-peer media streaming

abstract: We propose a rank-based peer-selection mechanism for peer-to-peer media streaming systems. The mechanism provides incentives for cooperation through service differentiation. Contributors to the system are rewarded with flexibility and choice in peer selection, resulting in high quality streaming sessions. Free-riders are given limited options in peer selection, if any, and hence receive low quality streaming. Through simulation and wide-area measurement studies, we verify that the mechanism can provide near optimal streaming quality to the cooperative users until the bottleneck shifts from the sources to the network.


title: Strata: layered coding for scalable visual communication

abstract: Existing code designs for display-camera based visual communication all have an all-or-nothing behavior, i.e., they assume the entire code must be decoded. However, diverse operational conditions due to device hardware diversity (in camera resolution and frame rate) and distance range motivate more scalable designs. In this paper, we borrow the notion of hierarchical modulation from traditional RF communication, and design Strata, a layered coding scheme for visual communication. Strata can support a range of frame capture resolutions and rates, and deliver information rates correspondingly. Strata embeds information at multiple granularity into the same code area spatially or the same frame interval temporally. It ensures all layers are decodable independently, by controlling the amount of interference between adjacent layers. Further, our design is recursive and extends readily to generate more layers. Compared with existing codes, it significantly extends the operational range, though at the expense of less capacity than a single-layer code.


title: Evolutionary Search in the Space of Rules for Creation of New Two-Player Board Games

abstract: Games have always been a popular test bed for artificial intelligence techniques. Game developers are always in constant search for techniques that can automatically create computer games minimizing the developer's task. In this work we present an evolutionary strategy based solution towards the automatic generation of two player board games. To guide the evolutionary process towards games, which are entertaining, we propose a set of metrics. These metrics are based upon different theories of entertainment in computer games. This work also compares the entertainment value of the evolved games with the existing popular board based games. Further to verify the entertainment value of the evolved games with the entertainment value of the human user a human user survey is conducted. In addition to the user survey we check the learnability of the evolved games using an artificial neural network based controller. The proposed metrics and the evolutionary process can be employed for generating new and entertaining board games, provided an initial search space is given to the evolutionary algorithm.


title: Occlusion Coherence: Localizing Occluded Faces with a Hierarchical Deformable Part Model

abstract: The presence of occluders significantly impacts performance of systems for object recognition. However, occlusion is typically treated as an unstructured source of noise and explicit models for occluders have lagged behind those for object appearance and shape. In this paper we describe a hierarchical deformable part model for face detection and keypoint localization that explicitly models occlusions of parts. The proposed model structure makes it possible to augment positive training data with large numbers of synthetically occluded instances. This allows us to easily incorporate the statistics of occlusion patterns in a discriminatively trained model. We test the model on several benchmarks for keypoint localization including challenging sets featuring significant occlusion. We find that the addition of an explicit model of occlusion yields a system that outperforms existing approaches in keypoint localization accuracy.


title: Glucomannan and obesity: a critical review.

abstract: Glucomantian (GM) is a soluble, fermentable, and highly viscous dietary fiber derived from the root ofthe elephant yam or konjac plant, which is native to Asia. Preliminary evidence suggests that GM may promote weight loss. This review summarizes studies using GM for weight loss as well as studies investigating its mechanisms of action. At doses of 2-4 g per day, GM was well-tolerated and resulted in significant weight loss in overweight and obese individuals. There is some evidence that GM exerts its beneficial effects by promoting satiety and fecal energy loss. Additionally, GM has been shown to improve lipid and lipoprotein parameters and glycemic status. Further investigation of safety, efficacy, and mechanisms of action is needed to determine whether GM can help to decrease the high prevalence of overweight and obesity in the United States. {Altern Ther Health Med. 2005;ll(6):30-34.)


title: Linear ubiquitination-mediated NF- B regulation and its related disorders

abstract: Ubiquitination is a post-translational modification involved in the regulation of a broad variety of cellular functions, such as protein degradation and signal transduction, including nuclear factor-κB (NF-κB) signalling. NF-κB is crucial for inflammatory and immune responses, and aberrant NF-κB signalling is implicated in multiple disorders. We found that linear ubiquitin chain assembly complex (LUBAC), composed of HOIL-1L, HOIP and SHARPIN, generates a novel type of Met1 (M1)-linked linear polyubiquitin chain and specifically regulates the canonical NF-κB pathway. Moreover, specific deubiquitinases, such as CYLD, A20 (TNFAIP3) and OTULIN/gumby, inhibit LUBAC-induced NF-κB activation by different molecular mechanisms, and several M1-linked ubiquitin-specific binding domains have been structurally defined. LUBAC and these linear ubiquitination-regulating factors contribute to immune and inflammatory processes and apoptosis. Functional impairments of these factors are correlated with multiple disorders, including autoinflammation, immunodeficiencies, dermatitis, B-cell lymphomas and Parkinson's disease. This review summarizes the molecular basis and the pathophysiological implications of the linear ubiquitination-mediated NF-κB activation pathway regulation by LUBAC.


title: Domain Generalization with Adversarial Feature Learning

abstract: In this paper, we tackle the problem of domain generalization: how to learn a generalized feature representation for an "unseen" target domain by taking the advantage of multiple seen source-domain data. We present a novel framework based on adversarial autoencoders to learn a generalized latent feature representation across domains for domain generalization. To be specific, we extend adversarial autoencoders by imposing the Maximum Mean Discrepancy (MMD) measure to align the distributions among different domains, and matching the aligned distribution to an arbitrary prior distribution via adversarial feature learning. In this way, the learned feature representation is supposed to be universal to the seen source domains because of the MMD regularization, and is expected to generalize well on the target domain because of the introduction of the prior distribution. We proposed an algorithm to jointly train different components of our proposed framework. Extensive experiments on various vision tasks demonstrate that our proposed framework can learn better generalized features for the unseen target domain compared with state-of-the-art domain generalization methods.


title: Multiple vehicles based new landmark feature mapping for highly autonomous driving map

abstract: A highly autonomous driving (HAD) map can improve the perception and localization performance of autonomous cars. However, when the HAD map cannot represent the real world precisely as a result of changes in the environment, reliability of autonomous cars may be decreased; therefore, it is essential that up-to-date map information is maintained. In order to keep the HAD map up-to-date, new landmark features must be updated continuously. This paper focuses on new landmark feature mapping in the HAD map based on multiple cars equipped with low-cost sensors. The features can be accurately mapped in the HAD map by matching between sensor information and the HAD map information, and by integrating multiple features estimated from various cars. The proposed algorithm is composed of three steps: data acquisition, new landmark feature map estimation using the HAD map, and feature integration. The algorithm is evaluated by means of certain simulation scenarios and experiments.


title: Socio-economic factors related to moral reasoning in childhood and adolescence: the missing link between brain and behavior

abstract: Neuroscientific and psychological research on moral development has until now developed independently, referring to distinct theoretical models, contents and methods. In particular, the influence of socio-economic and cultural factors on morality has been broadly investigated by psychologists but as yet has not been investigated by neuroscientists. The value of bridging these two areas both theoretically and methodologically has, however, been suggested. This study aims at providing a first connection between neuroscientific and psychological literature on morality by investigating whether socio-economic dimensions, i.e. living socio-geographic/economic area, immigrant status and SES, affect moral reasoning as operationalized in moral domain theory (a seminal approach in psychological studies on morality) and in Greene and colleagues’ (2001) perspective (one of the main approaches in neuroethics research). Participants were 81 primary school (M = 8.98 yrs.; SD = 0.39), 72 middle school (M = 12.14 yrs.; SD = 0.61) and 73 high school (M = 15.10 yrs.; SD = 0.38) students from rural and urban areas. Participants’ immigrant status (native vs. immigrant) and family SES level were recorded. Moral reasoning was assessed by means of a series of personal and impersonal dilemmas based on Greene and colleagues' (2001) neuroimaging experiment and a series of moral and socio-conventional rule dilemmas based on the moral domain theory. Living socio-geographic/economic area, immigrant status and SES mainly affected evaluations of moral and, to a higher extent, socio-conventional dilemmas, but had no impact on judgment of personal and impersonal dilemmas. Results are mainly discussed from the angle of possible theoretical links and suggestions emerging for studies on moral reasoning in the frameworks of neuroscience and psychology.


title: Augmented Reality-based Mimicry Attacks on Behaviour-Based Smartphone Authentication

abstract: We develop an augmented reality-based app that resides on the attacker's smartphone and leverages computer vision and raw input data to provide real-time mimicry attack guidance on the victim's phone. Our approach does not require tampering or installing software on the victim's device, or specialized hardware. The app is demonstrated by attacking keystroke dynamics, a method leveraging the unique typing behaviour of users to authenticate them on a smartphone, which was previously thought to be hard to mimic. In addition, we propose a low-tech AR-like audiovisual method based on spatial pointers on a transparent film and audio cues. We conduct experiments with 31 participants and mount over 400 attacks to show that our methods enable attackers to successfully bypass keystroke dynamics for 87% of the attacks after an average mimicry training of four minutes. Our AR-based method can be extended to attack other input behaviour-based biometrics. While the particular attack we describe is relatively narrow, it is a good example of using AR guidance to enable successful mimicry of user behaviour---an approach of increasing concern as AR functionality becomes more commonplace.


title: Shuffle Index: Efficient and Private Access to Outsourced Data

abstract: Data outsourcing and cloud computing have been emerging at an ever-growing rate as successful approaches for allowing users and companies to rely on external services for storing and managing data. As data and access to them are not under the control of the data owner, there is a clear need to provide proper confidentiality protection. Such requirements concern the confidentiality not only of the stored data (content) but also of the specific accesses (or patterns of them) that users make on such data. In this article, we address these issues and propose an approach for guaranteeing content, access, and pattern confidentiality in a data outsourcing scenario. The proposed solution is based on the definition of a shuffle index structure, which adapts traditional B +-trees and, by applying a combination of techniques (covers, caches, and shuffling), ensures confidentiality of the data and of queries over them, protecting each single access as well as sequences thereof. The proposed solution also supports update operations over the data, while making reads and writes not recognizable as such by the server. We show that the shuffle index exhibits a limited performance cost, thus resulting effectively usable in practice.


title: Using optical communication for remote underwater robot operation

abstract: Underwater vehicles are typically operated using a tether or a slow acoustic link. We present an underwater optical communication system that enables a high-throughput and low-latency link to an underwater robot. The optical link allows the robot to operate in cluttered environments without the need for a tether. We demonstrate the performance of the system in a number of experiments which characterize the optical link and demonstrate remote control of the robot using a human input device.


title: Visual Social Relationship Recognition

abstract: Social relationships form the basis of social structure of humans. Developing computational models to understand social relationships from visual data is essential for building intelligent machines that can better interact with humans in a social environment. In this work, we study the problem of visual social relationship recognition in images. We propose a dual-glance model for social relationship recognition, where the first glance fixates at the person of interest and the second glance deploys attention mechanism to exploit contextual cues. To enable this study, we curated a large scale People in Social Context dataset, which comprises of 23,311 images and 79,244 person pairs with annotated social relationships. Since visually identifying social relationship bears certain degree of uncertainty, we further propose an adaptive focal loss to leverage the ambiguous annotations for more effective learning. We conduct extensive experiments to quantitatively and qualitatively demonstrate the efficacy of our proposed method, which yields state-of-the-art performance on social relationship recognition.


title: A Review of Studies on Neuromarketing: Practical Results, Techniques, Contributions and Limitations

abstract: This article surveyed the main neuromarketing techniques used in the world and the practical results obtained. Specifically, the objectives are (1) to identify the main existing definitions of neuromarketing; (2) to identify the importance and the potential contributions of neuromarketing; (3) to demonstrate the advantages of neuromarketing as a marketing research tool compared to traditional research methods; (4) to identify the ethical issues involved with neuromarketing research; (5) to present the main neuromarketing techniques that are being used in the development of marketing research; (6) to present studies in which neuromarketing research techniques were used; and (7) to identify the main limitations of neuromarketing. The results obtained allow an understanding of the ways to develop, store, retrieve and use information about consumers, as well as ways to develop the field of neuromarketing. In addition to offering theoretical support for neuromarketing, this article discusses business cases, implementation and achievements.


An Impossible Dialogue! Nominal Utterances and Populist Rhetoric in an Italian Twitter Corpus of Hate Speech against Immigrants


title: When Should Sellers Use Auctions

abstract: A bidding process can be organized so that offers are submitted simultaneously or sequentially. In the latter case, potential buyers can condition their behavior on previous entrants' decisions. The relative performance of these mechanisms is investigated when entry is costly and selective, meaning that potential buyers with higher values are more likely to participate. A simple sequential mechanism can give both buyers and sellers significantly higher payoffs than the commonly used simultaneous bid auction. The findings are illustrated with parameters estimated from simultaneous entry USFS timber auctions where our estimates predict that the sequential mechanism would increase revenue and efficiency.


title: Technology roadmapping—A planning framework for evolution and revolution

abstract: Abstract Technology roadmapping is a flexible technique that is widely used within industry to support strategic and long-range planning. The approach provides a structured (and often graphical) means for exploring and communicating the relationships between evolving and developing markets, products and technologies over time. It is proposed that the roadmapping technique can help companies survive in turbulent environments by providing a focus for scanning the environment and a means of tracking the performance of individual, including potentially disruptive, technologies. Technology roadmaps are deceptively simple in terms of format, but their development poses significant challenges. In particular the scope is generally broad, covering a number of complex conceptual and human interactions. This paper provides an overview of the origins of technology roadmapping, by means of a brief review of the technology and knowledge management foundations of the technique in the context of the fields of technology strategy and technology transitions. The rapidly increasing literature on roadmapping itself is presented in terms of a taxonomy for classifying roadmaps, in terms of both organizational purpose and graphical format. This illustrates the flexibility of the approach but highlights a key gap—a robust process for technology roadmapping. A fast-start method for technology roadmapping developed by the authors is introduced and described. Developed in collaboration with industry, this method provides a means for improved understanding of the architecture of roadmaps and for rapidly initiating roadmapping in a variety of organizational contexts. This paper considers the use of the roadmaps from two main perspectives. The first is a company perspective: roadmaps that allow technology developments to be integrated with business planning, and the impact of new technologies and market developments to be assessed. The second perspective is multiorganizational: roadmaps that seek to capture the environmental landscape, threats and opportunities for a particular group of stakeholders in a technology or application area. Two short illustrative cases show the fast-start method in use in the context of disruptive technological trends from these two perspectives.


title: Scratch vs. Karel: impact on learning outcomes and motivation

abstract: This paper presents the results of an experiment regarding the effects of using one of two different programming environments in secondary schools. Both "Scratch" and "Karel the Robot" have been successfully used in these settings previously. These two environments are also representative for two classes of programming environments for beginners. One is more graphically oriented and may therefore alleviate the steep learning curve of programming while the other is text-based and therefore more akin to "real" programming. Also, one places more emphasis on the visualization of program structure and the other emphasizes visualizing program flow. The experiment has been conducted in parallel in two school classes, each using one of the two approaches. The abilities of the students were tested before and after the experiment as well as their intrinsic motivation and the perceived self-regulation. The results show, that the class using Scratch has higher intrinsic motivation and performs better, however the Karel class shows a higher identified regulation.


title: CLIP-Q: Deep Network Compression Learning by In-parallel Pruning-Quantization

abstract: Deep neural networks enable state-of-the-art accuracy on visual recognition tasks such as image classification and object detection. However, modern deep networks contain millions of learned weights; a more efficient utilization of computation resources would assist in a variety of deployment scenarios, from embedded platforms with resource constraints to computing clusters running ensembles of networks. In this paper, we combine network pruning and weight quantization in a single learning framework that performs pruning and quantization jointly, and in parallel with fine-tuning. This allows us to take advantage of the complementary nature of pruning and quantization and to recover from premature pruning errors, which is not possible with current two-stage approaches. Our proposed CLIP-Q method (Compression Learning by In-Parallel Pruning-Quantization) compresses AlexNet by 51-fold, GoogLeNet by 10-fold, and ResNet-50 by 15-fold, while preserving the uncompressed network accuracies on ImageNet.


title: Trust and Satisfaction, Two Stepping Stones for Successful E-Commerce Relationships: A Longitudinal Exploration

abstract: Trust and satisfaction are essential ingredients for successful business relationships in business-to-consumer electronic commerce. Yet there is little research on trust and satisfaction in e-commerce that takes a longitudinal approach. Drawing on three primary bodies of literature, the theory of reasoned action, the extended valence framework, and expectation-confirmation theory, this study synthesizes a model of consumer trust and satisfaction in the context of e-commerce. The model considers not only how consumers formulate their prepurchase decisions, but also how they form their long-term relationships with the same website vendor by comparing their prepurchase expectations to their actual purchase outcome. The results indicate that trust directly and indirectly affects a consumer's purchase decision in combination with perceived risk and perceived benefit, and also that trust has a longer term impact on consumer e-loyalty through satisfaction. Thus, this study extends our understanding of consumer Internet transaction behavior as a three-fold (prepurchase, purchase, and postpurchase) process, and it recognizes the crucial, multiple roles that trust plays in this process. Implications for theory and practice as well as limitations and future directions are discussed.


title: Convolutional Networks with Adaptive Computation Graphs.

abstract: Do convolutional networks really need a fixed feed-forward structure? Often, a neural network is already confident after a few layers about the high-level concept shown in the image. However, due to the fixed network structure, all remaining layers still need to be evaluated. What if the network could jump right to a layer that is specialized in fine-grained differences of the image's content? In this work, we propose Adanets, a family of convolutional networks with adaptive computation graphs. Following a high-level structure similar to residual networks (Resnets), the key difference is that for each layer a gating function determines whether to execute the layer or move on to the next one. In experiments on CIFAR-10 and ImageNet we demonstrate that Adanets efficiently allocate computational budget among layers and learn distinct layers specializing in similar categories. Adanet 50 achieves a top 5 error rate of 7.94% on ImageNet using 30% fewer computations than Resnet 34, which only achieves 8.58%. Lastly, we study the effect of adaptive computation graphs on the susceptibility towards adversarial examples. We observe that Adanets show a higher robustness towards adversarial attacks, complementing other defenses such as JPEG compression.


title: Addressing perception uncertainty induced failure modes in robotic bin-picking

abstract: We present a comprehensive approach to handle perception uncertainty to reduce failure rates in robotic bin-picking. Our focus is on mixed-bins. We identify the main failure modes at various stages of the bin-picking task and present methods to recover from them. If uncertainty in part detection leads to perception failure, then human intervention is invoked. Our approach estimates the confidence in the part match provided by an automated perception system, which is used to detect perception failures. Human intervention is also invoked if uncertainty in estimated part location and orientation leads to a singulation planning failure. We have developed a user interface that enables remote human interventions when necessary. Finally, if uncertainty in part posture in the gripper leads to failure in placing the part with the desired accuracy, sensor-less fine-positioning moves are used to correct the final placement errors. We have developed a fine-positioning planner with a suite of fine-motion strategies that offer different tradeoffs between completion time and postural accuracy at the destination. We report our observations from system characterization experiments with a dual-armed Baxter robot, equipped with a Ensenso three-dimensional camera, to perform bin-picking on mixed-bins. HighlightsApproach to handle perception uncertainty to reduce failures in robotic bin-picking.Method to characterize pose estimation uncertainty of an automated perception system.Mechanism for rationalized basis to detect failures and invoke human interventions.User interface that allows remote human to provide cues to reduce pose uncertainty.Singulation planner that incorporates uncertainty into plan evaluation.Fine positioning planner for correcting errors in destination part posture.


title: A Single-Inductor Multiple-Output Auto-Buck–Boost DC–DC Converter With Tail-Current Control

abstract: A single-inductor multiple-output (SIMO) auto-buck–boost dc–dc converter with proposed tail-current control to achieve fast and robust reference tracking of inductor current is proposed in this paper. Moreover, the proposed backward– $V_{x1}$ control algorithm and frequency-control loop enable the proposed SIMO dc–dc converter to operate at a fixed switching frequency and achieve high power-conversion efficiency in both the buck-dominated and boost-dominated cases. The proposed SIMO auto-buck–boost dc–dc converter has four output channels and is implemented in a standard 0.35-μm CMOS process. Measurement results show that the proposed dc–dc converter achieves a peak efficiency of more than 91% at a total output power of about 0.5 W and load transient response time of less than 80 μs.


title: An interview with Peter H. Buschang

abstract: Dr. Peter Buschang is regent professor and director of orthodontic research. He has been at Texas A&M University Baylor College of Dentistry since 1988. Dr. Buschang received his PhD in 1980 from the University of Texas at Austin; he spent 3 years as a NIDR postdoctoral fellow at the University of Connecticut, and five years as a FRSQ scholar at the University of Montreal. Every year, Dr. Buschang teaches in 16 different courses, 7 of which he directs. In addition to more than 100 lecture hours per year, he spends hundreds of hours mentoring students. For his teaching efforts, Dr. Buschang was awarded the Robert E. Gaylord Award of Excellence in Orthodontic education in 1992, 1998, 2004, and 2010. He also gives 1-2 day evidence-based CE courses throughout the world. The residents he has taught recently honored him by pledging to fund the Peter H. Buschang Endowed Professorship of Orthodontics. His research interests pertain to craniofacial growth and assessment of treatment effects. Dr. Buschang has been funded regularly over the years by the Medical Research Council of Canada, Fonds de le Recherche en Santé du Québec, the NIH, and the American Association of Orthodontics Foundation. He has mentored over 140 Master's and PhD students, and 49 dental students. Dr. Buschang has published over 250 peer-reviewed articles, 15 book chapters and 198 abstracts. He has given over 150 invited talks and lectures in 14 different countries. For his work with the American Board of Orthodontics, Dr. Buschang was awarded the Earl E. and Wilma S. Shepard Award. Dr. Buschang is the only non-orthodontist ever to have been made an honorary member of both the American Association of Orthodontics (2005) and the Edward H. Angle Society of Orthodontics (2009), the two most prestigious orthodontic groups.


title: IT Governance Frameworks and COBIT - A Literature Review

abstract: IT governance is one of the central areas of IS research. This study examines research on Control Objectives for Information and Related Technology (COBIT), a popular governance framework. COBIT is a comprehensive IT governance framework that provides guidelines to IT managers in managing and governing enterprise IT. This paper compiles and analyses extant research on COBIT. Our findings suggest that researchers have examined COBIT through multiple perspectives and that most papers either concentrate on overall framework development/comparison or certain pockets of interest within COBIT such as security, risk management, systems development, effectiveness and internal control. Our survey also indicates that many of the published papers are in the accounting domain. COBIT’s scope has increased over the years and now it encompasses many of the mainstream IS related areas. Hence, suggestions for future research in IS with regard to COBIT is also articulated in this study.


title: Generating Missions and Spaces for Adaptable Play Experiences

abstract: This paper investigates strategies to generate levels for action-adventure games. For this genre, level design is more critical than for rule-driven genres such as simulation or rogue-like role-playing games, for which procedural level generation has been successful in the past. The approach outlined by this article distinguishes between missions and spaces as two separate structures that need to be generated in two individual steps. It discusses the merits of different types of generative grammars for each individual step in the process. Notably, the approach acknowledges that the online generation of levels needs to be tailored strictly to the actual experience of a player. Therefore, the approach incorporates techniques to establish and exploit player models in actual play.


title: Abel inversion using total-variation regularization

abstract: In the case of radiography of a cylindrically symmetric object, the Abel transform is useful for describing the tomographic measurement operator. The inverse of this operator is unbounded, so regularization is required for the computation of satisfactory inversions. We introduce the use of the total variation seminorm for this purpose, and prove the existence and uniqueness of solutions of the corresponding variational problem. We illustrate the effectiveness of the total-variation regularization with an example and comparison with the unregularized inverse and the H1 regularized inverse.


title: Modeling and simulation of data center networks

abstract: Data centers are integral part of cloud computing that support Web services, online social networking, data analysis, computation intensive applications and scientific computing. They require high performance components for their inter-process communication, storage and sub-communication systems. The performance bottleneck that used to be the processing power has now been shifted to communication speed within data centers. The performance of a data center, in terms of throughput and delay, is directly related to the performance of the underlying internal communication network. In this paper, we introduce an analytical model that can be used to evaluate the underlying network architecture in data centers. The model can further be used to develop simulation tools that extend the scope of performance evaluation beyond what it can be achieved by the theoretical model in terms of various network topologies, different traffic distributions, scalability, and load balancing. While the model is generic, we focus on its implementation for fat-tree networks that are widely used in data centers. The theoretical results are compared and validated with the simulation results for several network configurations. The results of this analysis provide a basis for data center network design and optimization.


title: LCR-Net++: Multi-Person 2D and 3D Pose Detection in Natural Images

abstract: We propose an end-to-end architecture for joint 2D and 3D human pose estimation in natural images. Key to our approach is the generation and scoring of a number of pose proposals per image, which allows us to predict 2D and 3D poses of multiple people simultaneously. Hence, our approach does not require an approximate localization of the humans for initialization. Our Localization-Classification-Regression architecture, named LCR-Net, contains 3 main components: 1) the pose proposal generator that suggests candidate poses at different locations in the image; 2) a classifier that scores the different pose proposals; and 3) a regressor that refines pose proposals both in 2D and 3D. All three stages share the convolutional feature layers and are trained jointly. The final pose estimation is obtained by integrating over neighboring pose hypotheses, which is shown to improve over a standard non maximum suppression algorithm. Our method recovers full-body 2D and 3D poses, hallucinating plausible body parts when the persons are partially occluded or truncated by the image boundary. Our approach significantly outperforms the state of the art in 3D pose estimation on Human3.6M, a controlled environment. Moreover, it shows promising results on real images for both single and multi-person subsets of the MPII 2D pose benchmark and demonstrates satisfying 3D pose results even for multi-person images.


title: Dynamics of Driver's Gaze: Explorations in Behavior Modeling and Maneuver Prediction

abstract: The study and modeling of driver's gaze dynamics are important because, if and how the driver is monitoring the driving environment is vital for driver assistance in manual mode, for takeover requests in highly automated mode and for semantic perception of the surround in fully autonomous mode. We developed a machine vision-based framework to classify driver's gaze into context rich zones of interest and model driver's gaze behavior by representing gaze dynamics over a time period using gaze accumulation, glance duration, and glance frequencies. As a use case, we explore the driver's gaze dynamic patterns during maneuvers executed in freeway driving, namely, left lane change maneuver, right lane change maneuver, and lane keeping. It is shown that condensing gaze dynamics into durations and frequencies leads to recurring patterns based on driver activities. Furthermore, modeling these patterns show predictive powers in maneuver detection up to a few hundred milliseconds a priori .


title: A Microwave Microfluidic Sensor Based on a Dual-Mode Resonator for Dual-Sensing Applications

abstract: In this paper, we propose a novel microwave microfluidic sensor with dual-sensing capability. The sensor is based on a dual-mode resonator that consists of a folded microstrip line loaded with interdigital lines and a stub at the plane of symmetry. Due to the specific configuration, the resonator exhibits two entirely independent resonant modes, which allows simultaneous sensing of two fluids using a resonance shift method. The sensor is designed in a multilayer configuration with the proposed resonator and two separated microfluidic channels—one intertwined with the interdigital lines and the other positioned below the stub. The circuit has been fabricated using low-temperature co-fired ceramics technology and its performance was verified through the measurement of its responses for different fluids in the microfluidic channels. The results confirm the dual-sensing capability with zero mutual influence as well as good overall performance. Besides an excellent potential for dual-sensing applications, the proposed sensor is a good candidate for application in mixing fluids and cell counting.


Unsupervised morpheme segmentation and morphology induction from text corpora using Morfessor 1.0


title: Resilient Universities: Confronting Changes in a Challenging World

abstract: Resilience is ostensibly acknowledged as a cross-disciplinary issue, yet resilience has seldom been applied to the understanding of universities and the academic world. The contributions to this volume aim to fill this gap through the presentation of both theoretical and empirical studies. The book's title reflects the desire to extend the debate in new directions and to assemble a fresh set of models and tools for thinking about resilient universities. Bringing together a range of experts in the field, this collection marks a novel departure towards establishing a holistic approach to future university governance and adaptation.


title: Six-Port Radar Sensor for Remote Respiration Rate and Heartbeat Vital-Sign Monitoring

abstract: A novel remote respiration and heartbeat monitoring sensor is presented. The device is a monostatic radar based on a six-port interferometer operating a continuous-wave signal at 24 GHz and a radiated power of less than 3 $\mu\hbox{W}$ . Minor mechanical movements of the patient's body caused by the respiration as well as hearbeat can be tracked by analyzing the phase modulation of the backscattered signal by means of microwave interferometry with the six-port network. High-distance measurement accuracy in the micrometer scale as well as low system complexity are the benefits of the six-port receiver. To verify the performance of the system, different body areas have been observed by the six-port radar. The proposed system has been tested and validated by measurement results.


title: Efficient architecture of variable size HEVC 2D-DCT for FPGA platforms

abstract: Abstract This study presents a design of two-dimensional (2D) discrete cosine transform (DCT) hardware architecture dedicated for High Efficiency Video Coding (HEVC) in field programmable gate array (FPGA) platforms. The proposed methodology efficiently proceeds 2D-DCT computation to fit internal components and characteristics of FPGA resources. A four-stage circuit architecture is developed to implement the proposed methodology. This architecture supports variable size of DCT computation, including 4 × 4, 8 × 8, 16 × 16, and 32 × 32. The proposed architecture has been implemented in System Verilog and synthesized in various FPGA platforms. Compared with existing related works in literature, this proposed architecture demonstrates significant advantages in hardware cost and performance improvement. The proposed architecture is able to sustain 4 K@30 fps ultra high definition (UHD) TV real-time encoding applications with a reduction of 31–64% in hardware cost.


title: bh_tomo - a Matlab borehole georadar 2D tomography package

abstract: bh_tomo is an open source borehole georadar data processing and ray-based 2D tomography software package developed at the Ecole Polytechnique of Montreal. bh_tomo runs under Matlab version 7.0 and above, and is therefore portable between computer operating systems supported by Matlab. To perform the tomographic inversions, bh_tomo includes an implementation of the classical LSQR algorithm, as well as an implementation of the recent geostatistical inversion scheme developed at the Ecole Polytechnique of Montreal. One important motivation behind the development of bh_tomo was to ease the data processing sequence necessary to perform tomographic inversion of georadar amplitude data, especially when measured between many adjacent boreholes. The software package relies on a mini database and comprises interactive modules to manage, process and interpret the data.


title: Optimal Design of IPM Motors With Different Cooling Systems and Winding Configurations

abstract: Performance improvement of permanent magnet (PM) motors through optimization techniques has been widely investigated in the literature. Oftentimes the practice of design optimization leads to derivation/interpretation of optimal scaling rules of PM motors for a particular loading condition. This paper demonstrates how these derivations vary with respect to the machine ampere loading and ferrous core saturation level. A parallel sensitivity analysis using a second-order response surface methodology followed by a large-scale design optimization based on evolutionary algorithms are pursued in order to establish the variation of the relationships between the main design parameters and the performance characteristics with respect to the ampere loading and magnetic core saturation levels prevalent in the naturally cooled, fan-cooled, and liquid-cooled machines. For this purpose, a finite-element-based platform with a full account of complex geometry, magnetic core nonlinearities, and stator and rotor losses is used. Four main performance metrics including active material cost, power losses, torque ripple, and rotor PM demagnetization are investigated for two generic industrial PM motors with distributed and concentrated windings with subsequent conclusions drawn based on the results.


title: A Scientific Workflow Approach to Distributed Geospatial Data Processing using Web Services

abstract: Geospatial analyses of distributed data from surveys and sensors are often stored and managed in diverse regional, national and global repositories. The nature of scientific processes requires composition of these resources in a meaningful order to solve a specific geoscience problem. These tasks can be viewed as scientific workflows. Web based interfaces allow access to remote data and tools, and enable running computational experiments using different online resources. However, it requires manual processing to combine multiple resources in pipelines and scientists still need IT experts to automate their large-scale scientific workflows. The challenging problem is how to enable the scientists to harvest online data and models for designing and executing experiments in a seamless manner. A solution becomes feasible by the introduction of Web Services in a variety of scientific domains. These services can be discovered and composed through generic visual interfaces and scientific workflow tools. For this purpose, we present a complete framework for registering, discovering, composing and executing Web Services to support online science.


title: New technique for inter-implant papilla reconstruction between two or more implants in patients with variably reabsorbed ridges and flat anatomy. Preliminary results of a 9 consecutive clinical case series

abstract: The aim of the work: Interimplant papilla reconstruction is difficult because the biologic width around an implant is apical to the implant-abutment connection and because the biologic width creates subcrestally. The aim of this study is to investigate whether the reconstruction of the interimplant papilla can be achieved by the use of an innovative surgical technique combined with scalloped implants, in the most severe surgical conditions, i.e. in variably reabsorbed ridges with flat anatomy. ::: Materials and method: Nine surgical sites, in eight consecutive patients, were treated with at least two adjacent scalloped implants and fixed prosthesis. 23 scalloped implants were placed using this new surgical technique on bone and soft tissue structures. One flat platform implant was also placed between two other scalloped implants. A total of 15 interimplant papillae were examined. ::: Results: 100% of papilla reconstruction at first prosthesis insertion. 13.3% failed to maintain interimplant papillae after 6 months and 20% after 12 months. Also, papilla reconstruction was maintained for 12 months in the mesial and distal embrasure spaces of the flat platform implant. ::: Conclusion: The combination of the use of adjacent scalloped implants with this surgical approach, even in reabsorbed ridges with flat anatomy, may reform inter-implant bone peaks as support for the papillae.


Semantic Storytelling, Cross-lingual Event Detection and other Semantic Services for a Newsroom Content Curation Dashboard.


title: "Right Time, Right Place" Health Communication on Twitter: Value and Accuracy of Location Information

abstract: Background: Twitter provides various types of location data, including exact Global Positioning System (GPS) coordinates, which could be used for infoveillance and infodemiology (ie, the study and monitoring of online health information), health communication, and interventions. Despite its potential, Twitter location information is not well understood or well documented, limiting its public health utility. Objective: The objective of this study was to document and describe the various types of location information available in Twitter. The different types of location data that can be ascertained from Twitter users are described. This information is key to informing future research on the availability, usability, and limitations of such location data. Methods: Location data was gathered directly from Twitter using its application programming interface (API). The maximum tweets allowed by Twitter were gathered (1% of the total tweets) over 2 separate weeks in October and November 2011. The final dataset consisted of 23.8 million tweets from 9.5 million unique users. Frequencies for each of the location options were calculated to determine the prevalence of the various location data options by region of the world, time zone, and state within the United States. Data from the US Census Bureau were also compiled to determine population proportions in each state, and Pearson correlation coefficients were used to compare each state’s population with the number of Twitter users who enable the GPS location option. Results: The GPS location data could be ascertained for 2.02% of tweets and 2.70% of unique users. Using a simple text-matching approach, 17.13% of user profiles in the 4 continental US time zones were able to be used to determine the user’s city and state. Agreement between GPS data and data from the text-matching approach was high (87.69%). Furthermore, there was a significant correlation between the number of Twitter users per state and the 2010 US Census state populations (r ≥ 0.97, P < .001). Conclusions: Health researchers exploring ways to use Twitter data for disease surveillance should be aware that the majority of tweets are not currently associated with an identifiable geographic location. Location can be identified for approximately 4 times the number of tweets using a straightforward text-matching process compared to using the GPS location information available in Twitter. Given the strong correlation between both data gathering methods, future research may consider using more qualitative approaches with higher yields, such as text mining, to acquire information about Twitter users’ geographical location. [J Med Internet Res 2012;14(6):e156]


title: Event Detection and Domain Adaptation with Convolutional Neural Networks

abstract: We study the event detection problem using convolutional neural networks (CNNs) that overcome the two fundamental limitations of the traditional feature-based approaches to this task: complicated feature engineering for rich feature sets and error propagation from the preceding stages which generate these features. The experimental results show that the CNNs outperform the best reported feature-based systems in the general setting as well as the domain adaptation setting without resorting to extensive external resources.


title: First- and Second-Order Methods for Learning: Between Steepest Descent and Newton's Method

abstract: On-line first-order backpropagation is sufficiently fast and effective for many large-scale classification problems but for very high precision mappings, batch processing may be the method of choice. This paper reviews first- and second-order optimization methods for learning in feedforward neural networks. The viewpoint is that of optimization: many methods can be cast in the language of optimization techniques, allowing the transfer to neural nets of detailed results about computational complexity and safety procedures to ensure convergence and to avoid numerical problems. The review is not intended to deliver detailed prescriptions for the most appropriate methods in specific applications, but to illustrate the main characteristics of the different methods and their mutual relations.


title: On the duality between firing rate and initial marking variations in TCPN

abstract: A performance measure which is often used when evaluating systems modeled by Petri nets is the throughput of a transition in steady-state, i.e., the number of firings per unit time in permanent regime if it exists. When fluid Petri nets are considered, such measure corresponds to the continuous flow of the transitions. Its value depends on the firing rates associated to transitions and also on the initial marking of the net. In this work two properties of the steady-state throughput, monotonicity and continuity, are studied under firing rate and initial marking variations. It is shown that in certain cases there exists a kind of duality between both type of changes, that is, some property eventually holds no matter if firing rate or initial marking is varied. These results are obtained in a structural framework using the P-flows, T-flows, and configurations of the net model.


title: Exploring Help Seeking Experiences of Male Victims of Female Perpetrators of IPV

abstract: Intimate partner violence (IPV) is a common phenomenon worldwide. However, there is a relative dearth of qualitative research exploring IPV in which men are the victims of their female partners. The present study used a qualitative approach to explore how Portuguese men experience IPV. Ten male victims (aged 35–75) who had sought help from domestic violence agencies or from the police were interviewed. Transcripts were analyzed using QSR NVivo10 and coded following thematic analysis. The results enhance our understanding of both the nature and dynamics of the violence that men experience as well as the negative impact of violence on their lives. This study revealed the difficulties that men face in the process of seeking help, namely differences in treatment of men versus women victims. It also highlights that help seeking had a negative emotional impact for most of these men. Finally, this study has important implications for practitioners and underlines macro-level social recommendations for raising awareness about this phenomenon, including the need for changes in victims’ services and advocacy for gender-inclusive campaigns and responses.


title: Cybersecurity situational awareness taxonomy

abstract: Ensuring cost-efficient cybersecurity for a networked system is a challenging task. In this task, cybersecurity situational awareness is a cornerstone to ensure that systems are protected in a meaningful way. However, cybersecurity situational awareness can be built in various ways. Firstly, several monitoring and analysing techniques can be applied, and secondly, a time window for the usage of situational awareness varies from short-term operational to long-term strategic decision making. Understanding differences and purposes of these aspects is an essential part to research and develop cybersecurity situational awareness. In this paper, we build a taxonomy of cybersecurity situational awareness. The taxonomy categorises terminology, makes it possible to recognise missing areas, and to understand the area in a uniform way. Moreover, the taxonomy helps to select the most effective techniques to be used in a specific situation awareness implementation.


title: Anomaly Detection for Temporal Data using Long Short-Term Memory (LSTM)

abstract: We explore the use of Long short-term memory (LSTM) for anomaly detection in temporal data. Due to the challenges in obtaining labeled anomaly datasets, an unsupervised approach is employed. We tra ...


title: Chemical crystal identification with deep learning machine vision

abstract: ObjectiveThis study was carried out with the purpose of testing the ability of deep learning machine vision to identify microscopic objects and geometries found in chemical crystal structures.ResultsA database of 6994 images taken with a light microscope showing microscopic crystal details of selected chemical compounds along with 180 images of an unknown chemical was created to train and test, respectively the deep learning models. The models used were GoogLeNet (22 layers deep network) and VGG-16 (16 layers deep network), based on the Caffe framework (University of California, Berkeley, CA) of the DIGITS platform (NVIDIA Corporation, Santa Clara, CA). The two models were successfully trained with the images, having validation accuracy values of 97.38% and 99.65% respectively. Finally, both models were able to correctly identify the unknown chemical sample with a high probability score of 93.34% (GoogLeNet) and 99.41% (VGG-16). The positive results found in this study can be further applied to other unknown sample identification tasks using light microscopy coupled with deep learning machine vision.


title: An Energy-Efficient Low Frequency-Dependence Switching Technique for SAR ADCs

abstract: This brief presents a highly energy-efficient switching scheme for successive approximation register (SAR) analog-to-digital converters that achieves a 95% reduction in switching energy over the conventional SAR. The switching energy has been calculated by taking into account both the power drawn from reference and the power consumed by the switches themselves. The frequency dependence of the switching energy has been studied and the proposed technique presents ways to maintain high energy efficiency over the entire frequency range of operation. The results have been verified through behavioral and SPICE simulations.


title: Noisy Or-based model for Relation Extraction using Distant Supervision

abstract: Distant supervision, a paradigm of relation extraction where training data is created by aligning facts in a database with a large unannotated corpus, is an attractive approach for training relation extractors. Various models are proposed in recent literature to align the facts in the database to their mentions in the corpus. In this paper, we discuss and critically analyse a popular alignment strategy called the “at least one” heuristic. We provide a simple, yet effective relaxation to this strategy. We formulate the inference procedures in training as integer linear programming (ILP) problems and implement the relaxation to the “at least one ” heuristic via a soft constraint in this formulation. Empirically, we demonstrate that this simple strategy leads to a better performance under certain settings over the existing approaches.


Clustering Approach to Stock Market Prediction


CHAPTER 3 Media Violence Effects and Violent Crime


Modeling the Non-Substitutability of Multiword Expressions with Distributional Semantics and a Log-Linear Model


Cluster ensemble extraction for knowledge reuse framework


title: User Perception of the Quality, Value, and Utility of User-Generated Content

abstract: User Generated Content (UGC) is a rapidly emerging growth engine of many Internet businesses and an important component of the new knowledge society. However, little research has been done on the mechanisms inherent to UGC. This research explores the relationships among the quality, value, and benefits of UGC. The main objective is to identify and evaluate the quality factors that affect UGC value, which ultimately influences the utility of UGC. We identify the three quality dimensions of UGC: content, design, and technology. We classify UGC value into three categories: functional value, emotional value, and social value. We attempt to characterize the mechanism underlying UGC value by evaluating the relationships between the quality and value of UGC and investigating what types of UGC value affect UGC utility. Our results show that all three factors of UGC quality are strongly associated with increases in the functional, emotional, and social values of UGC. Our findings also demonstrate that the functional and emotional values of UGC are critically important factors for UGC utility. Based on these findings, we discuss theoretical implications for future research and practical implications for UGC services.


title: High quality MELP coding at bit-rates around 4 kb/s

abstract: A number of coding techniques have been reported to achieve near toll quality synthesized speech at bit-rates around 4 kb/s. These include variants of code excited linear prediction (CELP), sinusoidal transform coding (STC) and multi-band excitation (MBE). While CELP has been an effective technique for bit-rates above 6 kb/s, STC, MBE, waveform interpolation (WI) and mixed excitation linear prediction (MELP) models seem to be attractive at bit-rates below 3 kb/s. We present a system to encode speech with high quality using MELP, a technique previously demonstrated to be effective at bit-rates of 1.6-2.4 kb/s. We have enhanced the MELP model producing significantly higher speech quality at bit-rates above 2.4 kb/s. We describe the development and testing of a high quality 4 kb/s MELP coder.


title: Big Data Pre-processing: A Quality Framework

abstract: With the abundance of raw data generated from various sources, Big Data has become a preeminent approach in acquiring, processing, and analyzing large amounts of heterogeneous data to derive valuable evidences. The size, speed, and formats in which data is generated and processed affect the overall quality of information. Therefore, Quality of Big Data (QBD) has become an important factor to ensure that the quality of data is maintained at all Big data processing phases. This paper addresses the QBD at the pre-processing phase, which includes sub-processes like cleansing, integration, filtering, and normalization. We propose a QBD model incorporating processes to support Data quality profile selection and adaptation. In addition, it tracks and registers on a data provenance repository the effect of every data transformation happened in the pre-processing phase. We evaluate the data quality selection module using large EEG dataset. The obtained results illustrate the importance of addressing QBD at an early phase of Big Data processing lifecycle since it significantly save on costs and perform accurate data analysis.


title: Criticism as an approach to interface aesthetics

abstract: In this paper we discuss the re-orientation of human-computer interaction as an aesthetic field. We argue that mainstream approaches lack of general openness and ability to assess experience aspects of interaction, but that this can indeed be remedied. We introduce the concept of interface criticism as a way to turn the conceptual re-orientation into handles for practical design, and we present and discuss an interface criticism guide.


Exploratory Text Analysis using Lexical Episode Plots


title: Intuitionistic Fuzzy Aggregation Operators

abstract: An intuitionistic fuzzy set, characterized by a membership function and a non-membership function, is a generalization of fuzzy set. In this paper, based on score function and accuracy function, we introduce a method for the comparison between two intuitionistic fuzzy values and then develop some aggregation operators, such as the intuitionistic fuzzy weighted averaging operator, intuitionistic fuzzy ordered weighted averaging operator, and intuitionistic fuzzy hybrid aggregation operator, for aggregating intuitionistic fuzzy values and establish various properties of these operators.


title: Antioxidant Vitamin Supplements and Cardiovascular Disease

abstract: The American Heart Association (AHA) has had a long-standing commitment to provide information about the role of nutrition in cardiovascular disease (CVD) risk reduction. Many activities have been and are currently directed toward this objective, including issuing AHA Dietary Guidelines periodically (most recently in 20001) and Science Advisories and Statements on an ongoing basis to review emerging nutrition-related issues. The objective of the AHA Dietary Guidelines is to promote healthful dietary patterns. A consistent focus since the inception of the AHA Dietary Guidelines has been to reduce saturated fat (and trans fat) and cholesterol intake, as well as to increase dietary fiber consumption. Collectively, all the AHA Dietary Guidelines have supported a dietary pattern that promotes the consumption of diets rich in fruits, vegetables, whole grains, low-fat or nonfat dairy products, fish, legumes, poultry, and lean meats. This dietary pattern has a low energy density to promote weight control and a high nutrient density to meet all nutrient needs. ::: ::: As reviewed in the first AHA Science Advisory2 on antioxidant vitamins, epidemiological and population studies reported that some micronutrients may beneficially affect CVD risk (ie, antioxidant vitamins such as vitamin E, vitamin C, and β-carotene). Recent epidemiological evidence3 is consistent with the earlier epidemiological and population studies (reviewed in the first Science Advisory).2 These findings have been supported by in vitro studies that have established a role of oxidative processes in the development of the atherosclerotic plaque. Underlying the atherosclerotic process are proatherogenic and prothrombotic oxidative events in the artery wall that may be inhibited by antioxidants. The 1999 AHA Science Advisory2 recommended that the general population consume a balanced diet with emphasis on antioxidant-rich fruits, vegetables, and whole grains, advice that was consistent with the AHA Dietary Guidelines at the time. In the absence of …


title: Observations on the biology of Afrotropical Hesperiidae (Lepidoptera). Part 6. Hesperiinae incertae sedis: palm feeders

abstract: Partial life histories for 12 Hesperiinae incertae sedis that feed on palms (Arecaceae) are described and illustrated. The genera dealt with are: Perrotia (part), Ploetzia, Zophopetes, Gretna (part), Pteroteinon, Leona, and Caenides (part) (all from Evans' Ploetzia genera group). Although Gamia spp. have been reported to feed on palms, these records are considered to be in error, as caterpillars of this genus feed on Dracaena spp. (Asparagaceae). The life histories of the species documented are fairly uniform, in that caterpillars of most species have rounded brown heads, wider basally, with or without limited black markings, smooth bodies and make simple shelters by rolling leaves. Variation in caterpillar markings and male genitalia of Zophopetes dysmephila (Trimen) and caterpillar and adult markings of Gretna carmen Evans merit further study. In G. carmen, G. waga (Plötz) and G. balenge (Holland), the caterpillars' head and body are covered with hair-like setae, and develop an extensive covering of white waxy powder, which in G. balenge also covers the long setae. Furthermore, the pupa of G. balenge is unusual in having a pair of large, elaborate processes frontally on the head; when disturbed, the pupa vibrates violently and rattles noisily against the sides of the shelter. Ploetzia amygdalis (Mabille) and Pteroteinon laufella (Hewitson) have gregarious caterpillars, whereas the remaining species are solitary. After eclosion, the first instar caterpillars of Gretna spp. moult to the second instar without feeding. The implications of a palm-feeding life-style are discussed, and economic damage and plant quarantine risks to coconut, oil palm and ornamental palms pointed out. The known life histories suggest that all Afrotropical palm-feeding Hesperiidae will belong in the same tribe when the incertae sedis section is further elucidated, although the affinities of Gretna deserve further consideration.


title: E2MD for reduction of motion artifacts from photoplethysmographic signals

abstract: Most of the intensive care units (ICU) are equipped with commercial pulse oximeters for monitoring arterial blood oxygen saturation (SpO2) and pulse rate (PR). Photoplethysmographic (PPG) data recorded from pulse oximeters usually corrupted by motion artifacts (MA), resulting in unreliable and inaccurate estimated measures of SpO2. In this paper, a simple and efficient MA reduction method based on Ensemble Empirical Mode Decomposition (E2MD) is proposed for the estimation of SpO2 from processed PPGs. Performance analysis of the proposed E2MD is evaluated by computing the statistical and quality measures indicating the signal reconstruction like SNR and NRMSE. Intentionally created MAs (Horizontal MA, Vertical MA and Bending MA) in the recorded PPGs are effectively reduced by the proposed one and proved to be the best suitable method for reliable and accurate SpO2 estimation from the processed PPGs.


title: A SURVEY OF MODELS AND ALGORITHMS FOR SOCIAL INFLUENCE ANALYSIS

abstract: Social influence is the behavioral change of a person because of the perceived relationship with other people, organizations and society in general. Social influence has been a widely accepted phenomenon in social networks for decades. Many applications have been built based around the implicit notation of social influence between people, such as marketing, advertisement and recommendations. With the exponential growth of online social network services such as Facebook and Twitter, social influence can for the first time be measured over a large population. In this chapter, we survey the research on social influence analysis with a focus on the computational aspects. First, we present statistical measurements related to social influence. Second, we describe the literature on social similarity and influences. Third, we present the research on social influence maximization which has many practical applications including marketing and advertisement.


title: Heartbeat and Respiration Detection From Optical Interferometric Signals by Using a Multimethod Approach

abstract: In this paper, a multimethod approach for heartbeat and respiration detection from an optical interferometric signal is proposed. Optical interferometer is a sensitive device that detects physical changes of optical-fiber length due to external perturbations. When in direct or indirect contact with human body (e.g., hidden in a bed mattress), mechanical and acoustic activity of cardiac muscle and respiration reflect in the interferometric signal, enabling entirely unobtrusive monitoring of heartbeat and respiration. A novel, two-phased multimethod approach was developed for this purpose. The first phase selects best performing combinations of detection methods on a training set of signals. The second phase applies the selected methods to test set of signals and fuses all the detections of vital signs. The test set consisted of 14 subjects cycling an ergometer until reaching their submaximal heart rate. The following resting periods were analyzed showing high efficiency (98.18 ± 1.40% sensitivity and 97.04 ± 4.95% precision) and accuracy (mean absolute error of beat-to-beat intervals 22±9 ms) for heartbeat detection, and acceptable efficiency (90.06 ± 7.49% sensitivity and 94.21 ± 3.70% precision) and accuracy (mean absolute error of intervals between respiration events 0.33 ± 0.14 s) for respiration detection.


title: Average Case Analysis of Multichannel Sparse Recovery Using Convex Relaxation

abstract: This paper considers recovery of jointly sparse multichannel signals from incomplete measurements. Several approaches have been developed to recover the unknown sparse vectors from the given observations, including thresholding, simultaneous orthogonal matching pursuit (SOMP), and convex relaxation based on a mixed matrix norm. Typically, worst case analysis is carried out in order to analyze conditions under which the algorithms are able to recover any jointly sparse set of vectors. However, such an approach is not able to provide insights into why joint sparse recovery is superior to applying standard sparse reconstruction methods to each channel individually. Previous work considered an average case analysis of thresholding and SOMP by imposing a probability model on the measured signals. Here, the main focus is on analysis of convex relaxation techniques. In particular, the mixed l 2,1 approach to multichannel recovery is investigated. Under a very mild condition on the sparsity and on the dictionary characteristics, measured for example by the coherence, it is shown that the probability of recovery failure decays exponentially in the number of channels. This demonstrates that most of the time, multichannel sparse recovery is indeed superior to single channel methods. The probability bounds are valid and meaningful even for a small number of signals. Using the tools developed to analyze the convex relaxation technique, also previous bounds for thresholding and SOMP recovery are tightened.


title: Predicting flow in aortic dissection: Comparison of computational model with PC-MRI velocity measurements

abstract: Abstract Aortic dissection is a life-threatening process in which the weakened wall develops a tear, causing separation of wall layers. The dissected layers separate the original true aortic lumen and a newly created false lumen. If untreated, the condition can be fatal. Flow rate in the false lumen is a key feature for false lumen patency, which has been regarded as one of the most important predictors of adverse early and later outcomes. Detailed flow analysis in the dissected aorta may assist vascular surgeons in making treatment decisions, but computational models to simulate flow in aortic dissections often involve several assumptions. The purpose of this study is to assess the computational models adopted in previous studies by comparison with in vivo velocity data obtained by means of phase-contrast magnetic resonance imaging (PC-MRI). Aortic dissection geometry was reconstructed from computed tomography (CT) images, while PC-MRI velocity data were used to define inflow conditions and to provide distal velocity components for comparison with the simulation results. The computational fluid dynamics (CFD) simulation incorporated a laminar–turbulent transition model, which is necessary for adequate flow simulation in aortic conditions. Velocity contours from PC-MRI and CFD in the two lumens at the distal plane were compared at four representative time points in the pulse cycle. The computational model successfully captured the complex regions of flow reversal and recirculation qualitatively, although quantitative differences exist. With a rigid wall assumption and exclusion of arch branches, the CFD model over-predicted the false lumen flow rate by 25% at peak systole. Nevertheless, an overall good agreement was achieved, confirming the physiological relevance and validity of the computational model for type B aortic dissection with a relatively stiff dissection flap.


title: Fusing Iris, Palmprint and Fingerprint in a Multi-biometric Recognition System

abstract: This paper presents a trimodal biometric recognition system based on iris, palmprint and fingerprint. Wavelet transform and Gabor filter are used to extract features in different scales and orientations from iris and palmprint. Minutiae extraction and alignment is used for fingerprint matching. Six different fusion algorithms including score-based, rank-based and decision-based methods are used to combine the results of three modules. We also propose a new rank-based fusion algorithm Maximum Inverse Rank (MIR) which is robust with respect to variations in scores and also bad ranking from a module. CASIA datasets for iris, palmprint and fingerprint are used in this study. The experiments show the effectiveness of our fusion method and our trimodal biometric recognition system in comparison to existing multi-modal recognition systems.


title: Real-World Interaction with Camera-Phones

abstract: With the integration of cameras, mobile phones have evolved into networked personal image capture devices. Camera phones can perform image processing tasks on the device itself and use the result as an additional means of user input and a source of context data. In this paper we present a system that turns such phones into mobile sensors for 2-dimensional visual codes. The proposed system induces a code coordinate system and visually detects phone movements. It also provides the rotation angle and the amount of tilting of the camera as additional input parameters. These features enable applications such as item selection and interaction with large-scale displays. With the code coordinate system, each point in the viewed image – and therefore arbitrarily shaped areas – can be linked to specific operations. A single image point can even be associated with multiple information aspects by taking different rotation and tilting angles into account.


title: Solving Asymmetric Decision Problems with Influence Diagrams

abstract: While influence diagrams have many advantages as a representation framework for Bayesian decision problems, they have a serious drawback in handling asymmetric decision problems. To be represented in an influence diagram, an asymmetric decision problem must be symmetrized. A considerable amount of unnecessary computation may be involved when a symmetrized influence diagram is evaluated by conventional algorithms. In this paper we present an approach for avoiding such unnecessary computation in influence diagram evaluation.


title: Converting meet-in-the-middle preimage attack into pseudo collision attack: application to SHA-2

abstract: In this paper, we present a new technique to construct a collision attack from a particular preimage attack which is called a partial target preimage attack. Since most of the recent meet-in-the-middle preimage attacks can be regarded as the partial target preimage attack, a collision attack is derived from the meet-in-the-middle preimage attack. By using our technique, pseudo collisions of the 43-step reduced SHA-256 and the 46-step reduced SHA-512 can be obtained with complexities of 2126 and 2254.5, respectively. As far as we know, our results are the best pseudo collision attacks on both SHA-256 and SHA-512 in literature. Moreover, we show that our pseudo collision attacks can be extended to 52 and 57 steps of SHA-256 and SHA-512, respectively, by combined with the recent preimage attacks on SHA-2 by bicliques. Furthermore, since the proposed technique is quite simple, it can be directly applied to other hash functions. We apply our algorithm to several hash functions including Skein and BLAKE, which are the SHA-3 finalists. We present not only the best pseudo collision attacks on SHA-2 family, but also a new insight of relation between a meet-in-the-middle preimage attack and a pseudo collision attack.


title: Active Travel Co-Benefits of Travel Demand Management Policies that Reduce Greenhouse Gas Emissions

abstract: In this study, California’s activity-based travel demand model (ABM) is applied to demonstrate how such travel models can be used to produce the active travel data (age and sex distributions) required by comparative risk assessment models to estimate health outcomes for alternative land use and transport plans. It also shows how to identify the magnitude of change in active travel that may be possible from land use, transit, and vehicle pricing policies for California and its five major regions over the next 20 years. The results of this study suggest that distance-based vehicle pricing may increase walking by about 10% and biking by about 17%, and concurrently greenhouse gas emissions (GHG) from vehicle miles of travel (VMT) may be reduced by about 16%. Transit expansion and supportive development patterns may increase active travel by about 2% to 3% for both walk and bike modes while also reducing VMT by about 4% on average. The combination of all three policies may increase time spent walking by about 13% and biking by about 19%, and reduce VMT by about 19%.


title: A literature review on the prosthetic treatment of structurally compromised teeth.

abstract: PURPOSE ::: This article presents a review of the literature on biomechanical factors affecting the treatment outcome of prosthetic treatment of structurally compromised dentitions, with the main emphasis on often-compromised endodontically treated teeth. ::: ::: ::: MATERIALS AND METHODS ::: Articles cited in a MEDLINE/PubMed search were reviewed with a focus on factors influencing the risk for fatigue failures. ::: ::: ::: RESULTS ::: Technical failures in connection with fixed prosthodontics are often caused by fatigue fractures. The abutments, cement, and reconstruction are all subjected to stress caused by occlusal forces, and fatigue fracture may occur at the weakest point or where the maximum stress occurs. The weakest point is frequently in connection with endodontically treated teeth restored with posts and cores. ::: ::: ::: CONCLUSION ::: The literature points to nonaxial forces as a risk for fatigue fracture of teeth, cement, and restorative material. Favorable occlusal prosthesis design is probably more important for survival of structurally compromised endodontically treated teeth than is the type of post used.


title: Release engineering practices and pitfalls

abstract: The release and deployment phase of the software development process is often overlooked as part of broader software engineering research. In this paper, we discuss early results from a set of multiple semi-structured interviews with practicing release engineers. Subjects for the interviews are drawn from a number of different commercial software development organizations, and our interviews focus on why release process faults and failures occur, how organizations recover from them, and how they can be predicted, avoided or prevented in the future. Along the way, the interviews provide insight into the state of release engineering today, and interesting relationships between software architecture and release processes.


Monocular SLAM for Real-Time Applications on Mobile Platforms


title: Manganese Oxide–Silica Aerogels: Synthesis and Structural and Catalytic Properties in the Selective Oxidation of NH3

abstract: Manganese oxide–silica mixed oxide aerogels with different morphological and chemical properties were prepared using the sol–gel method and ensuing extraction of the solvent with supercritical CO2. Two types of manganese precursor, varying hydrolysis conditions of the silica and manganese precursors, influence of base addition for gelation, and calcination temperatures were investigated. Base addition had a strong effect on textural properties, producing high-surface-area, mesoporous aerogels, whereas these properties were only marginally affected by kind of manganese precursor used. The presence of different manganese oxide species was evidenced by X-ray diffraction, Raman and diffuse reflectance infrared Fourier transform spectroscopy, and temperature-programmed reduction. Mn4+, Mn3+, and Mn2+ oxide species were found after calcination at 600°C in air. Sol–gel processing with manganese(II) nitrate resulted in highly dispersed mixed oxides. Basic gelation of these sols strongly influenced the state of the manganese, leading to crystallites of hausmannite and to amorphous Mn5O8 in the calcined samples. Aerogels derived from the less reactive Mn(III) (acac)3 did not contain any manganese oxide crystallites when prepared under the same basic conditions. The catalytic performance of the aerogels in the selective oxidation of ammonia strongly depended on the state of the manganese. Samples containing crystalline Mn3O4 were more active than amorphous aerogels with dispersed manganese oxide species and afforded high selectivity to N2O. The presence of amorphous Mn5O8 further increased the activity and the selectivity to nitrous oxide, reaching 74% at 360°C. Nitrogen formation was found to be related to the amount of strongly Lewis-bound ammonia. The amorphous aerogels showing more Lewis-bound ammonia produced mainly nitrogen below 480°C, affording a selectivity of 78% at 360°C.


title: A Pooling Approach to Modelling Spatial Relations for Image Retrieval and Annotation

abstract: Over the last two decades we have witnessed strong progress on modeling visual object classes, scenes and attributes that have significantly contributed to automated image understanding. On the other hand, surprisingly little progress has been made on incorporating a spatial representation and reasoning in the inference process. In this work, we propose a pooling interpretation of spatial relations and show how it improves image retrieval and annotations tasks involving spatial language. Due to the complexity of the spatial language, we argue for a learning-based approach that acquires a representation of spatial relations by learning parameters of the pooling operator. We show improvements on previous work on two datasets and two different tasks as well as provide additional insights on a new dataset with an explicit focus on spatial relations.