Miracle-dz/UniFAR-FTUs huggingface dataset:
Increasing the instruction fetch rate via multiple branch prediction and a branch address cache

"Increasing the Instruction Fetch Rate viaMultiple Branch Prediction and a Branch Address Cache" was the first paper to propose a highly accurate hardware mechanism for predicting and fetching multiple non-contiguous basic blocks using leading-edge aggressive branch predictors of the time. Prior to this paper, the methods to increase fetch bandwidth relied on software and compiler mechanisms to increase the size of the basic blocks themselves. The publication of our paper inspired an explosion of research to further improve the accuracy of multiple branch prediction, reduce complexity of fetching multiple basic blocks, or increase the fetch bandwidth in other ways. Our HPS research group defied conventional wisdom in a 1991 ISCA paper [1] that demonstrated instruction level parallelism (IPC) can be greater than two even for non-scientific workloads. This flew in the face of numerous "proofs" at the time. We showed that there was enough parallelism for an aggressive superscalar out-of-order execution engine to exploit to dramatically improve performance, provided that the penalties caused by incorrect branch predictions, cache misses, and TLB misses could be improved.
GestureMan: a mobile robot that embodies a remote instructor's actions

When designing systems that support remote instruction on physical tasks, one must consider four requirements: 1) participants should be able to use non-verbal expressions, 2) they must be able to take an appropriate body arrangement to see and show gestures, 3) the instructor should be able to monitor operators and objects, 4) they must be able to organize the arrangement of bodies and tools and gestural expression sequentially and interactively. GestureMan was developed to satisfy these four requirements by using a mobile robot that embodies a remote instructors actions. The mobile robot mounts a camera and a remote control laser pointer on it. Based on the experiments with the system we discuss the advantage and disadvantage of the current implementation. Also, some implications to improve the system are described.
NB-IoT: A Candidate Technology for Massive IoT in the 5G Era

The existing mobile network infrastructure is currently optimized to support the Narrow-Band Internet of Things (NB-IoT), which is meant to provide numerous services in poor coverage areas, with ultra-low power consumption. The question that arises is whether (and to what extent) NB-IoT can meet the requirement for massive Machine Type Communications (mMTC) in the 5G era. In view of this, we study coverage enhancement in NB-IoT. We describe the subframe structure for various physical channels of NB-IoT and explain the repetition mechanism used for downlink transmissions in poor coverage areas. Focusing on optimizing this mechanism, we analyze how the latency and user blockage can be reduced by a proper selection of the downlink radio resources.
Distributed computing column 42: game theory and fault tolerance in distributed computing

Game theory and fault tolerance offer two different flavors of robustness to distributed systems – the former is robust against participants attempting to maximize their own utilities, whereas the latter offers robustness against unexpected faults. This column takes a look at attempts to combine the two. It features a review of recent work that provides both flavors of robustness by Ittai Abraham, Lorenzo Alvisi, and Joe Halpern. Ittai, Lorenzo, and Joe discuss how game theory-style strategic behavior can be accounted for in fault-tolerant distributed protocols. They make a compelling case for bringing a game-theoretic perspective to distributed computing problems. Many thanks to Ittai, Lorenzo and Joe for their article!
Catching free-riders: in-network adblock detection with machine learning techniques

The rise of adblockers is creating lots of concerns to the online content publishing industry, as it severely affects the possibility to offer free-content to end-users by subsidizing the fruition costs with advertisements.While many detection techniques have been proposed as a countermeasure to the diffusion of adblocks, they either rely on the injection of code in the served web pages, or require to perform passive measurements for a long time, thus leading to high costs and delays before collecting the desired information. Motivated by these reasons, in this paper we propose a novel technique to conduct in-network adblock usage measurements, inspecting only few minutes of network traffic. Our approach relies on network traffic inspection, and classification with machine learning techniques to detect whether the user is blocking, or not, the advertisements.Key findings obtained show that by inspecting only few minutes of network traffic, we can reliably perform the detection with an accuracy up to 99%, with a negligible computational overhead.
Bone-Preserving Decompression Procedures Have a Minor Effect on the Flexibility of the Lumbar Spine

Objective To mitigate the risk of iatrogenic instability, new posterior decompression techniques able to preserve musculoskeletal structures have been introduced but never extensively investigated from a biomechanical point of view. This study was aimed to investigate the impact on spinal flexibility caused by a unilateral laminotomy for bilateral decompression, in comparison to the intact condition and a laminectomy with preservation of a bony bridge at the vertebral arch. Secondary aims were to investigate the biomechanical effects of two-level decompression and the quantification of the restoration of stability after posterior fixation. Methods A universal spine tester was used to measure the flexibility of six L2–L5 human spine specimens in intact conditions and after decompression and fixation surgeries. An incremental damage protocol was applied : 1) unilateral laminotomy for bilateral decompression at L3–L4; 2) on three specimens, the unilateral laminotomy was extended to L4–L5; 3) laminectomy with preservation of a bony bridge at the vertebral arch (at L3–L4 in the first three specimens and at L4–L5 in the rest); and 4) pedicle screw fixation at the involved levels. Results Unilateral laminotomy for bilateral decompression had a minor influence on the lumbar flexibility. In flexion-extension, the median range of motion increased by 8%. The bone-preserving laminectomy did not cause major changes in spinal flexibility. Two-level decompression approximately induced a twofold destabilization compared to the single-level treatment, with greater effect on the lower level. Posterior fixation reduced the flexibility to values lower than in the intact conditions in all cases. Conclusion In vitro testing of human lumbar specimens revealed that unilateral laminotomy for bilateral decompression and bone-preserving laminectomy induced a minor destabilization at the operated level. In absence of other pathological factors (e.g., clinical instability, spondylolisthesis), both techniques appear to be safe from a biomechanical point of view.
Tencent Neural Machine Translation Systems for WMT18

We participated in the WMT 2018 shared news translation task on English↔Chinese language pair. Our systems are based on attentional sequence-to-sequence models with some form of recursion and self-attention. Some data augmentation methods are also introduced to improve the translation performance. The best translation result is obtained with ensemble and reranking techniques. Our Chinese→English system achieved the highest cased BLEU score among all 16 submitted systems, and our English→Chinese system ranked the third out of 18 submitted systems.
The Social Roles of Bots

Bots, or programs designed to engage in social spaces and perform automated tasks, are typically understood as automated tools or as social "chatbots. " In this paper, we consider their place alongside users in the emerging social ecosystem of audience participation platforms, through the application of Structural Role Theory. We perform a large-scale analysis of activity levels of user-designed bots on Twitch, finding that they communicate at a much greater rate than any other type of user. We build on a classification scheme derived from prior literature on bot functionalities to identify the roles bots play on Twitch, how these roles vary across different types of Twitch communities, and how users engage with them and vice versa. We conclude with a discussion of what roles are missing and where opportunities lie to re-conceptualize and re-design bots as social actors who help communities grow and evolve.
Translation of Biomedical Documents with Focus on Spanish-English

For the WMT 2018 shared task of translating documents pertaining to the Biomedical domain, we developed a scoring formula that uses an unsophisticated and effective method of weighting term frequencies and was integrated in a data selection pipeline. The method was applied on five language pairs and it performed best on Portuguese-English, where a BLEU score of 41.84 placed it third out of seven runs submitted by three institutions. In this paper, we describe our method and results with a special focus on Spanish-English where we compare it against a state-of-the-art method. Our contribution to the task lies in introducing a fast, unsupervised method for selecting domain-specific data for training models which obtain good results using only 10% of the general domain data.
The effects of single-dominant organizational cultures on the innovativeness of a firm

The culture of a firm influences its ability to be innovative. A firm's culture can be diagnosed to be either clan, adhocracy, market or hierarchy cultures. The objective of the paper is to examine how single-dominant cultures influence a firm's innovativeness. Based on the literature review, some hypotheses were formulated and tested using hierarchical regression analysis with data collected from 172 financial institutions. The results show that clan, adhocracy, and market cultures have a positive link with product and process innovations. The practical implication is that managers of commercial firms should develop adhocracy or market cultures if they are to gain a sustained competitive advantage. The theoretical contribution of this paper is that organizational cultures that are externally-oriented foster innovation in the workplace.
The first-order logic of signals: keynote

Formalizing properties of systems with continuous dynamics is a challenging task. In this paper, we propose a formal framework for specifying and monitoring rich temporal properties of real-valued signals. We introduce signal first-order logic (SFO) as a specification language that combines first-order logic with linear-real arithmetic and unary function symbols interpreted as piecewise-linear signals. We first show that while the satisfiability problem for SFO is undecidable, its membership and monitoring problems are decidable. We develop an offline monitoring procedure for SFO that has polynomial complexity in the size of the input trace and the specification, for a fixed number of quantifiers and function symbols. We show that the algorithm has computation time linear in the size of the input trace for the important fragment of bounded-response specifications interpreted over input traces with finite variability. We can use our results to extend signal temporal logic with first-order quantifiers over time and value parameters, while preserving its efficient monitoring. We finally demonstrate the practical appeal of our logic through a case study in the micro-electronics domain.
PolyCleaner: Clean your Polynomials before Backward Rewriting to verify Million-gate Multipliers

Nowadays, a variety of multipliers are used in different computationally intensive industrial applications. Most of these multipliers are highly parallelized and structurally complex. Therefore, the existing formal verification techniques fail to verify them. In recent years, formal multiplier verification based on Symbolic Computer Algebra (SCA) has shown superior results in comparison to all other existing proof techniques. However, for non-trivial architectures still a monomial explosion can be observed. A common understanding is that this is caused by redundant monomials also known as vanishing monomials. While several approaches have been proposed to overcome the explosion, the problem itself is still not fully understood. In this paper we present a new theory for the origin of vanishing monomials and how they can be handled to prevent the explosion during backward rewriting. We implement our new approach as the SCA-verifier PolyCleaner. The experimental results show the efficiency of our proposed method in verification of non-trivial million-gate multipliers.
Finding a needle in a haystack of reviews: cold start context-based hotel recommender system demo

Online hotel searching is a daunting task due to the wealth of online information. Reviews written by other travelers replace the word-of-mouth, yet turn the search into a time consuming task. Users do not rate enough hotels to enable a collaborative filtering based recommendation. Thus, a cold start recommender system is needed. This demo describes briefly our cold start hotel recommender system, which uses the text of the reviews as its main data. We define context groups based on reviews extracted from TripAdvisor.com and Venere.com. We introduce a novel weighted algorithm for text mining. We implemented our system which was used by the public to conduct 150 trip planning experiments. We compare our solution to the top suggestions of the mentioned web services and show that users were, on average, 20% more satisfied with our hotel recommendations. We outperform these web services even more in cities where hotel prices are high.
UWB at IEST 2018: Emotion Prediction in Tweets with Bidirectional Long Short-Term Memory Neural Network

This paper describes our system created for the WASSA 2018 Implicit Emotion Shared Task. The goal of this task is to predict the emotion of a given tweet, from which a certain emotion word is removed. The removed word can be sad, happy, disgusted, angry, afraid or a synonym of one of them. Our proposed system is based on deep-learning methods. We use Bidirectional Long Short-Term Memory (BiLSTM) with word embeddings as an input. Pre-trained DeepMoji model and pre-trained emoji2vec emoji embeddings are also used as additional inputs. Our System achieves 0.657 macro F1 score and our rank is 13th out of 30.
A Hexagonal Grid Based Human Blockage Model for the 5G Low Terahertz Band Communications

Users continuously demand higher connection speeds and data traffic from wireless communication networks. The newly required network capacity should be provided by higher frequency bands, because legacy sub-6 GHz bands are already operating using advanced communication techniques that provide very high spectral efficiencies. Consequently, millimeter wave communication standards are either complete or ongoing, and general submillimeter wave applications are next in line. Accordingly, this paper proposes a motion model in hexagonal grid of a person carrying a user equipment. Electromagnetic wave blockage analyses by utilizing channel characteristics of the low-THz band are presented. Lastly, the communication and blockage probabilities of an exemplary system are both theoretically examined and numerically simulated.
Learning Comment Controversy Prediction in Web Discussions Using Incidentally Supervised Multi-Task CNNs

Comments on web news contain controversies that manifest as inter-group agreement-conflicts. Tracking such rapidly evolving controversy could ease conflict resolution or journalist-user interaction. However, this presupposes controversy online-prediction that scales to diverse domains using incidental supervision signals instead of manual labeling. To more deeply interpret comment-controversy model decisions we frame prediction as binary classification and evaluate baselines and multi-task CNNs that use an auxiliary news-genre-encoder. Finally, we use ablation and interpretability methods to determine the impacts of topic, discourse and sentiment indicators, contextual vs. global word influence, as well as genre-keywords vs. per-genre-controversy keywords – to find that the models learn plausible controversy features using only incidentally supervised signals.
Host Differentiation and Compartmentalization of Microbial Communities in the Azooxanthellate Cupcorals Tubastrea coccinea and Rhizopsammia goesi in the Caribbean

We investigated the microbial communities associated with surface layer mucus, tissue and gastrovascular cavity of two azooxanthellate Caribbean cup corals (Tubastrea coccinea and Rhizopsammia goesi) to explore potential differences in microbial community composition within and among these azooxanthellate scleractinian corals. Using next-generation sequencing of the V3-V6 region of the 16S rRNA gene we found that while alpha-diversity was overall very similar, the relative abundance of microbial taxa differed between host species and among locations within a polyp (i.e., compartments). The distinct microbial assemblages between species is only challenged by the relatively high similarity among mucus samples of both species. This suggests a stronger signal of the surrounding environment and weaker host control over the mucus compartment compared with the tissue and gastrovascular cavity. Tubastrea coccinea harboured four indicator OTUs (including a Pseudoalteromonas species, an unidentified Gammaproteobacteria, an unidentified OTU in the family Comamonadaceae and one in the genus Burkholderia). The single indicator for R. goesi was another undetermined OTU in the Comamonadaceae. The microbial communities of the gastrovascular cavity and the mucus overlapped substantially in indicator OTUs. None of these were exclusive of the gastrovascular cavity or mucus, while an OTU of the order Thiohalorhabdales occurred uniquely in the tissue. In contrast to the gastrovascular cavity and mucus, the tissue of both coral species was rich in chloroplasts of different algal taxa (mainly Ulvophyceae and Stramenopiles), and an OTU of the genus Roseivirga (family Flammeovirgaceae). The two coral species shared most indicator OTUs for microbial communities residing in their mucus and tissue, but not in their gastrovascular cavities. However, Endozoicomonadaceae occurred in the tissue of both coral species. The genus Pseudomonas was found in R. goesi but was virtually absent in T. coccinea. This study demonstrates the influence of coral compartments and species identities on the composition of microbial communities associated with azooxanthellate cup corals and emphasizes the important effects of within-polyp microhabitats in structuring the coral microbiome.
FlashPatch: spreading software updates over flash drives in under-connected regions

We present the design and implementation of FlashPatch, a system which exploits the ubiquity of USB drives---normally a vector for virus transmission---to facilitate the distribution of software updates. Our system spreads software updates to offline machines by having the updates "piggy-back" on the existing circulation of USB flash drives. We discuss the techncial and ethical issues involved in the deployment of such a system and we describe the results of preliminary field testing in rural Ghana.
Nutrition risk among an ethnically diverse sample of community-dwelling older adults

Abstract Objective To assess the prevalence of nutritional risk among an ethnically diverse group of urban community-dwelling older adults and to explore if risk varied by race/ethnicity. Design Demographic characteristics, Katz’s activities of daily living and health-care resource utilization were ascertained cross-sectionally via telephone surveys with trained interviewers. Nutrition risk and nutrition symptomology were assessed via the abridged Patient Generated Subjective Global Assessment (abPG-SGA); scores of ≥6 points delineated ‘high’ nutrition risk. Descriptive statistics and logistic regression analyses were conducted. Setting Urban. Participants White, Black or Hispanic community-dwelling adults, ≥55 years of age, fluent in English or Spanish, residing in the city limits of Chicago, IL, USA. Results A total of 1001 participants (37 % white, 37 % Black, 26 % Hispanic) were surveyed. On average, participants were 66·9 years old, predominantly female and overweight/obese. Twenty-six per cent (n 263) of participants were classified as ‘high’ nutrition risk with 24, 14 and 31 % endorsing decreased oral intake, weight loss and compromised functioning, respectively. Black respondents constituted the greatest proportion of those with high risk scores, yet Hispanic participants displayed the most concerning nutrition risk profiles. Younger age, female sex, Black or Hispanic race/ethnicity, emergency room visits, eating alone and taking three or more different prescribed or over-the-counter drugs daily were significantly associated with high risk scores (P<0·05). Conclusions One in four older adults living in an urban community prone to health disparities was classified as ‘high’ nutrition risk. Targeted interventions to promote healthy ageing are needed, especially for overweight/obese and minority community members.
What we care about now, what we'll care about in the future

A SIGCSE is the oldest and best-known organization supporting computing education in the world today. Over 1700 attendees participated in the 2018 SIGCSE Technical Symposium, an indication of the importance of SIGCSE. SIGCSE’s 50 years almost perfectly matches the history of computing education. SIGCSE has defined the focus of computing education for the last 50 years. Predicting the future of SIGCSE is predicting the future of computing education.
Differential Vulnerabilities and a Diversity of Tactics

We investigate cybersecurity toolkits, collections of public facing materials intended to help users achieve security online. Through a qualitative analysis of 41 online toolkits, we present a set of key design dimensions: agentive scale (who is responsible for security), achievability (can security be achieved), and interventional stage (when are security measures taken). Recognizing toolkits as socially and culturally situated, we surface ways in which toolkits construct security as a value and, in so doing, how they construct people as (in)secure users. We center the notion of differential vulnerabilities, an understanding of security that recognizes safety as socially contingent, adversaries as unstable figures, and risk as differentially applied based on markers of relational position (e.g. class, race, religion, gender, geography, experience). We argue that differential vulnerabilities provides a key design concern in future security resources, and a critical concept for security discourses.
Developing Production-Level Conversational Interfaces with Shallow Semantic Parsing

We demonstrate an end-to-end approach for building conversational interfaces from prototype to production that has proven to work well for a number of applications across diverse verticals. Our architecture improves on the standard domain-intent-entity classification hierarchy and dialogue management architecture by leveraging shallow semantic parsing. We observe that NLU systems for industry applications often require more structured representations of entity relations than provided by the standard hierarchy, yet without requiring full semantic parses which are often inaccurate on real-world conversational data. We distinguish two kinds of semantic properties that can be provided through shallow semantic parsing: entity groups and entity roles. We also provide live demos of conversational apps built for two different use cases: food ordering and meeting control.