Miracle-dz/UniFAR-FTUs huggingface dataset:
Research Challenges in Building a Voice-based Artificial Personal Shopper - Position Paper

Recent advances in automatic speech recognition lead toward enabling a voice conversation between a human user and an intelligent virtual assistant. This provides a potential foundation for developing artificial personal shoppers for e-commerce websites, such as Alibaba, Amazon, and eBay. Personal shoppers are valuable to the on-line shops as they enhance user engagement and trust by promptly dealing with customers’ questions and concerns. Developing an artificial personal shopper requires the agent to leverage knowledge about the customer and products, while interacting with the customer in a human-like conversation. In this position paper, we motivate and describe the artificial personal shopper task, and then address a research agenda for this task by adapting and advancing existing information retrieval and natural language processing technologies.
A rail‐to‐rail low‐power latch comparator with time domain bulk‐tuned offset cancellation for low‐voltage applications

Low‐voltage high‐precision comparators are the main building blocks of many low‐power mixed‐mode electronic devices. In this paper, a rail‐to‐rail high‐precision comparator is introduced. The proposed comparator uses 2 parallel input P‐type metal‐oxide‐semiconductor pairs with a dynamic level shifter to ensure rail‐to‐rail operation. Moreover, the proposed circuit incorporates a rail‐to‐rail offset cancellation circuit. The offset cancellation circuit works based on a time domain bulk‐tuned negative feedback loop. The proposed comparator and offset cancellation circuits are designed to work correctly when the input common mode voltage varies from rail to rail. The rail‐to‐rail scheme allows the use of the proposed comparator in nanometer technologies, where the acceptable input range is limited. The proposed circuit was simulated in a standard 180 nm complementary metal‐oxide‐semiconductor technology, and the results proved the rail‐to‐rail comparison ability in addition to the rail‐to‐rail offset cancellation function. The overall power consumption of the comparator was only increased by 11% compared with the conventional non–rail‐to‐rail approach. The maximum clock frequency of the proposed circuit is 833 MHz, which is slightly more than its counterpart at similar operation conditions.
Control Interventions Can Impact Alveolarization and the Transcriptome in Developing Mouse Lungs

There is currently much interest in understanding the mechanisms of normal and aberrant lung alveolarization, particularly in the context of bronchopulmonary dysplasia, a common complication of preterm birth where alveolarization is impeded. To this end, the parenteral administration of pharmacological agents that modulate biochemical pathways, or facilitate modulation of gene expression in transgenic animals, has facilitated the discovery and validation of mechanisms that direct lung development. Such studies include control interventions, where the solvent vehicle, perhaps containing an inactive form of the agent applied, is administered; thereby providing a well‐controlled point of reference for the analysis of the partner experiment. In the present study, the impact of several widely used control interventions in developing C57Bl/6J mouse pups was examined for effects on lung structure and the lung transcriptome. Parenteral administration of scrambled microRNA inhibitors (called antagomiRs) that are used to control in vivo microRNA neutralization studies, impacted lung volume, septal thickness, and the transcriptome of developing mouse lungs; with some effects dependent upon nucleotide sequence. Repeated intraperitoneal isotonic saline injections altered lung volume, with limited impact on the transcriptome. Parenteral administration of the tamoxifen solvent Miglyol accelerated mouse pup growth, and changed the abundance of 73 mRNA transcripts in the lung. Tamoxifen applied in Miglyol—in the absence of Cre recombinase—decreased pup growth, lung volume, and lung alveolarization and changed the abundance of 298 mRNA transcripts in the lung. These data demonstrate that widely used control interventions can directly impact lung alveolarization and the lung transcriptome in studies on lung development. Anat Rec, 302:346–363, 2019. © 2018 Wiley Periodicals, Inc.
BackPocketDriver - A Mobile App to Enhance Safe Driving for Youth (S)

Young drivers are one of the highest risk groups for being involved in car accidents. BackPocketDriver (BPD) is an Android application that aims at encouraging young drivers to adopt and hone safe driving skills. Smartphone sensors are used to monitor driver behaviour, including speed, turning, acceleration and braking. The journey data is analysed for unsafe behaviour with user feedback, which includes journey review, positive reinforcement using textual messages, goal setting and points scoring. To achieve this, behavioural change techniques were studied in relation to gamification, and several features were implemented into BackPocketDriver including achievements, leader board, quizzes, friends system, etc. Evaluations in terms of functional comparisons with related tools were conducted to measure the advantages of the proposed solution. The BPD app provides effective improvements to youth driving.
Congestion avoidance and control

In October of '86, the Internet had the first of what became a series of 'congestion collapses'. During this period, the data throughput from LBL to UC Berkeley (sites separated by 400 yards and three IMP hops) dropped from 32 Kbps to 40 bps. Mike Karels 1 and I were fascinated by this sudden factor-of-thousand drop in bandwidth and embarked on an investigation of why things had gotten so bad. We wondered, in particular, if the 4.3BSD (Berkeley UNIX) TCP was mis-behaving or if it could be tuned to work better under abysmal network conditions. The answer to both of these questions was “yes”. Since that time, we have put seven new algorithms into the 4BSD TCP: round-trip-time variance estimation exponential retransmit timer backoff slow-start more aggressive receiver ack policy dynamic window sizing on congestion Karn's clamped retransmit backoff fast retransmit Our measurements and the reports of beta testers suggest that the final product is fairly good at dealing with congested conditions on the Internet. This paper is a brief description of ( i ) - ( v ) and the rationale behind them. ( vi ) is an algorithm recently developed by Phil Karn of Bell Communications Research, described in [KP87]. ( viii ) is described in a soon-to-be-published RFC. Algorithms ( i ) - ( v ) spring from one observation: The flow on a TCP connection (or ISO TP-4 or Xerox NS SPP connection) should obey a 'conservation of packets' principle. And, if this principle were obeyed, congestion collapse would become the exception rather than the rule. Thus congestion control involves finding places that violate conservation and fixing them. By 'conservation of packets' I mean that for a connection 'in equilibrium', i.e., running stably with a full window of data in transit, the packet flow is what a physicist would call 'conservative': A new packet isn't put into the network until an old packet leaves. The physics of flow predicts that systems with this property should be robust in the face of congestion. Observation of the Internet suggests that it was not particularly robust. Why the discrepancy? There are only three ways for packet conservation to fail: The connection doesn't get to equilibrium, or A sender injects a new packet before an old packet has exited, or The equilibrium can't be reached because of resource limits along the path. In the following sections, we treat each of these in turn.
Canadian packaged gluten-free foods are less nutritious than their regular gluten-containing counterparts

Background A strict gluten-free (GF) diet is required for the management of celiac disease (CD). The nutritional adequacy of this diet has been questioned due to the elimination of wheat, an important vehicle for micronutrient fortification and source of fibre. While novel and/or reformulated packaged GF products have rapidly entered the marketplace, providing alternatives to wheat-based staples, it is unknown whether these new products are nutritionally comparable. Methods From a database of 3,851 foods collected across 21 grocery stores in Eastern Canada, we compared the nutrient content of 398 unique GF items with 445 gluten-containing (GC) equivalents. Wilcoxon rank tests were conducted on listed nutrient content (g, mg, µg) per 100 g of product and the nutrient contribution of iron, folate and fibre were evaluated using Health Canada’s nutrient claim regulations. Results GF staples (cereals, breads, flours, pastas) contained 1.3 times more fat and less iron (by 55%), folate (by 44%) and protein (by 36%), than GC counterparts (P < 0.0001). On average, GF pastas had only 37% of the fibre in GC pastas (P < 0.0001). Notably, GF and GC flours were equivalent in nutrient content. Despite GF and GC flours having similar nutritional content, the vast majority of the processed GF foods fell short in key nutrients. Discussion Packaged GF foods in Canada are generally less nutritious than their GC counterparts, suggesting that GF diets should not be promoted to those who do not require it. The use of nutrient-dense GF flours in homemade foods may improve nutrient intakes on the GF diet.
A traffic flow approach to early detection of gathering events

Given a spatial field and the traffic flow between neighboring locations, the early detection of gathering events (edge) problem aims to discover and localize a set of most likely gathering events. It is important for city planners to identify emerging gathering events which might cause public safety or sustainability concerns. However, it is challenging to solve the edge problem due to numerous candidate gathering footprints in a spatial field and the non-trivial task to balance pattern quality and computational efficiency. Prior solutions to model the edge problem lack the ability to describe the dynamic flow of traffic and the potential gathering destinations because they rely on static or undirected footprints. In contrast, in this paper, we model the footprint of a gathering event as a Gathering directed acyclic Graph (G-Graph), where the root of the G-Graph is the potential destination and the directed edges represent the most likely paths traffic takes to move towards the destination. We also proposed an efficient algorithm called SmartEdge to discover the most likely non-overlapping G-Graphs in the given spatial field. Our analysis shows that the proposed G-Graph model and the SmartEdge algorithm have the ability to efficiently and effectively capture important gathering events from real-world human mobility data. Our experimental evaluations show that SmartEdge saves 50% computation time over the baseline algorithm.
Accuracy of Perceiving Precisely Gazing Virtual Agents

Eye gaze of is an informative social signal in interactions with other humans and also with virtual agents (VA). But for a successful communication, users have to accurately perceive the VA's point of gaze (POG). In our study, participants sitting opposite to a VA at a table indicated its POG by positioning a token on the table surface. We measured the perceptual accuracy within and between participants as well as the participants' response times and eye movements for five horizontally aligned gaze targets. We demonstrated that perceiving the VA met perceptual benchmarks from human lookers: a) variances within and between participants were only slightly larger, b) the VA's visual angle was linearly overestimated, and c) variances increased with the visual angle. Finally, participants showed large individual differences but were consistent in their own gaze behaviour and response times across trials and gaze targets.
Data Handling in Knowledge Infrastructures

Offshore oil exploration is concerned with subsea geological reservoirs that are numerous kilometers below the seabed. These reservoirs are knowable only through a knowledge infrastructure of interconnected technologies that are applied to diverse instrument-generated data. Noise, holes, and inaccuracies are inherent in the data, which depend on the technology producing it. We conducted an interpretative case study of data handling work in the exploration unit of a European oil company. Our findings show how data handling involves the skills needed for managing data identities and ownership, a variety of technologies, and contingent negotiations of data needs. We use the notion of repair to analyze this data handling work and discuss how the concept of repair in data handling involves keeping the knowledge infrastructure navigable and attending to countless details. Our research contributes to the literature on repairing infrastructures by considering how repair relates to data work.
Spacetime Characterization of Real-Time Collaborative Editing

Real-Time Collaborative Editing (RTCE) is a popular way of instrumenting cooperative work on documents, in particular on the Web. Little is known in the literature yet about RTCE usage patterns in the real world. In this paper we study how a popular RTCE editor (Etherpad) is used in the wild, digging into the edit histories of a large collection of documents (about 14 000 pads), retrieved from one of the most popular public instances of the platform, hosted by the Wikimedia Foundation. The pad analysis is supported by a novel conceptual model that allows to label edit operations as "collaborative" or not depending on their distance-in edit position (space), edit time, or spacetime (both)-from edits made by other authors. The model is applied to classify all edits from the pad corpus. Classification results are further used to characterize the collaboration behavior of pad authors. Findings show that: 1) about half of the pads have a single author and hence witnessed no collaboration; 2) collaboration on common document parts happens often, but it happens asynchronously with authors taking turns in editing; and 3) simultaneous editing of common document parts happens very rarely. These findings help in revisiting early RTCE design decisions (e.g., the granularity of conflict management in RTCE protocols) and give insights on how to address novel needs (e.g., end-to-end encryption and offline editing).
Linear algebra operators for GPU implementation of numerical algorithms

In this work, the emphasis is on the development of strategies to realize techniques of numerical computing on the graphics chip. In particular, the focus is on the acceleration of techniques for solving sets of algebraic equations as they occur in numerical simulation. We introduce a framework for the implementation of linear algebra operators on programmable graphics processors (GPUs), thus providing the building blocks for the design of more complex numerical algorithms. In particular, we propose a stream model for arithmetic operations on vectors and matrices that exploits the intrinsic parallelism and efficient communication on modern GPUs. Besides performance gains due to improved numerical computations, graphics algorithms benefit from this model in that the transfer of computation results to the graphics processor for display is avoided. We demonstrate the effectiveness of our approach by implementing direct solvers for sparse matrices, and by applying these solvers to multi-dimensional finite difference equations, i.e. the 2D wave equation and the incompressible Navier-Stokes equations.
Finding resource-release omission faults in Linux

The management of the releasing of allocated resources is a continual problem in ensuring the robustness of systems code. Missing resource-releasing operations lead to memory leaks and deadlocks. A number of approaches have been proposed to detect such problems, but they often have a high rate of false positives, or focus only on commonly used functions. In this paper we observe that resource-releasing operations are often found in error-handling code, and that the choice of resource-releasing operation may depend on the context in which it is to be used. We propose an approach to finding resource-release omission faults in C code that takes into account these issues. We use our approach to find over 100 faults in the drivers directory of Linux 2.6. 34, with a false positive rate of only 16%, well below the 30% that has been found to be acceptable to developers.
Generating “Visual Clouds” from Multiplex Networks for TV News Archive Query Visualization

Advances in multimedia analysis, enables access and indexing of huge and rich video content. However, delivering this heterogeneous content remains a challenge. We proposes the use of multiplex networks to combine both textual and visual semantic cues extracted from TV news videos for interactive search refinement on heterogeneous data. After preprocessing, the indexed videos can be queried, for which result space is summarized in a visual cloud helping query refinement with contextual information by combining visual and textual cues. We leverage on properties of multiplex networks to extract a hierarchy of layers, which not only contextualizes results, but also guides the construction of our visual cloud, and its interactions.
Optimisation of strategy placements for public good in complex networks

Game theory has long been used to model cognitive decision making in societies. While traditional game theoretic modelling has focussed on well-mixed populations, recent research has suggested that the topological structure of social networks play an important part in the dynamic behaviour of social systems. Any agent or person playing a game employs a strategy (pure or mixed) to optimise pay-off. Previous studies have analysed how selfish agents can optimise their payoffs by choosing particular strategies within a social network model. In this paper we ask the question that, if agents were to work towards the common goal of increasing the public good (that is, the total network utility), what strategies they should adapt within the context of a heterogeneous network. We consider a number of classical and recently demonstrated game theoretic strategies, including cooperation, defection, general cooperation, Pavlov, and zero-determinant strategies, and compare them pairwise. We use the Iterative Prisoners Dilemma game simulated on scale-free networks, and use a genetic-algorithmic approach to investigate what optimal placement patterns evolve in terms of strategy. In particular, we ask the question that, given a pair of strategies are present in a network, which strategy should be adopted by the hubs (highly connected people), for the overall betterment of society (high network utility). We find that cooperation as opposed to defection, Pavlov as opposed to general cooperator, general cooperator as opposed to zero-determinant, and pavlov as opposed to zero-determinant, strategies will be adopted by the hubs, for the overall increased utility of the network. The results are interesting, since given a scenario where certain individuals are only capable of implementing certain strategies, the results give a blueprint on where they should be placed in a complex network for the overall benefit of the society.
Postfault Control of Scalar (V/f) Controlled Asymmetrical Six-Phase Induction Machines

With the accelerated development in semiconductor power devices along with the dictated rigorous reliability standards in some industrial sectors, the application of a medium-voltage high-power multiphase induction machine with multiple three-phase windings is now considered as a leading technology in high-power safety-critical applications. This paper proposes a parameter-independent postfault control scheme for an asymmetrical six-phase induction machine based on simple scalar V/f control, which can successfully ensure the most common postfault scenarios used in this respect, namely, equal stator copper loss and minimum copper loss modes. Moreover, the proposed controller can effectively be used in either open-loop or closed-loop speed control modes. The proposed controller is experimentally validated using a 1.5-kW prototype induction machine. The effect of the neutral arrangement on the dynamic performance is also explored.
A linear-time heuristic for improving network partitions

An iterative mincut heuristic for partitioning networks is presented whose worst case computation time, per pass, grows linearly with the size of the network. In practice, only a very small number of passes are typically needed, leading to a fast approximation algorithm for mincut partitioning. To deal with cells of various sizes, the algorithm progresses by moving one cell at a time between the blocks of the partition while maintaining a desired balance based on the size of the blocks rather than the number of cells per block. Efficient data structures are used to avoid unnecessary searching for the best cell to move and to minimize unnecessary updating of cells affected by each move.
WordNet-feelings: A linguistic categorisation of human feelings

In this article, we present the first in depth linguistic study of human feelings. While there has been substantial research on incorporating some affective categories into linguistic analysis (e.g. sentiment, and to a lesser extent, emotion), the more diverse category of human feelings has thus far not been investigated. We surveyed the extensive interdisciplinary literature around feelings to construct a working definition of what constitutes a feeling and propose 9 broad categories of feeling. We identified potential feeling words based on their pointwise mutual information with morphological variants of the word `feel' in the Google n-gram corpus, and present a manual annotation exercise where 317 WordNet senses of one hundred of these words were categorised as `not a feeling' or as one of the 9 proposed categories of feeling. We then proceeded to annotate 11386 WordNet senses of all these words to create WordNet-feelings, a new affective dataset that identifies 3664 word senses as feelings, and associates each of these with one of the 9 categories of feeling. WordNet-feelings can be used in conjunction with other datasets such as SentiWordNet that annotate word senses with complementary affective properties such as valence and intensity.
Stylistically User-Specific Generation

Recent neural models for response generation show good results in terms of general responses. In real conversations, however, depending on the speaker/responder, similar utterances should require different responses. In this study, we attempt to consider individual user’s information in adjusting the notable sequence-to-sequence (seq2seq) model for more diverse, user-specific responses. We assume that we need user-specific features to adjust the response and we argue that some selected representative words from the users are suitable for this task. Furthermore, we prove that even for unseen or unknown users, our model can provide more diverse and interesting responses, while maintaining correlation with input utterances. Experimental results with human evaluation show that our model can generate more interesting responses than the popular seq2seqmodel and achieve higher relevance with input utterances than our baseline.