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Communications of the ACM

111 - 120 of 3,913 for bentley

Deterministic Sparse Suffix Sorting in the Restore Model

Given a text T of length n, we propose a deterministic online algorithm computing the sparse suffix array and the sparse longest common prefix array of T in O(c √ lg n + m lg m lg n lg* n) time with O(m) words of space under the premise that the space of T is rewritable, where mn is the number of suffixes to be sorted (provided online and arbitrarily), and c is the number of characters with mcn that must be compared for distinguishing the designated suffixes.


Constraint handling in genotype to phenotype mapping and genetic operators for project staffing

Project staffing in many organisations involves the assignment of people to multiple projects while satisfying multiple constraints. The use of a genetic algorithm with constraint handling performed during a genotype to phenotype mapping process provides a new approach. Experiments show promise for this technique.


GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion

GECCO is the largest peer-reviewed conference in the field of Evolutionary Computation, and the main conference of the Special Interest Group on Genetic and Evolutionary Computation (SIGEVO) of the Association for Computing Machinery (ACM).


Communication vs Synchronisation in Parallel String Comparison

The longest common subsequence (LCS) problem is fundamental in computer science and its many applications. Parallel algorithms for this problems have been studied previously, in particular in the bulk-synchronous parallelism (BSP) model, which treats local computation, communication and synchronisation as independent scarce resources of a computing system. We consider primarily BSP algorithms running in either constant or polylogarithmic synchronisation. Based on our previous results on the algebraic structure and efficient algorithms for semi-local LCS, we present BSP algorithms for parallel semi-local LCS, improving on the existing upper bounds on communication and synchronisation; in particular we present the first constant-sync work-optimal LCS algorithm.


Project Us: A Wearable for Enhancing Empathy

Enhancing the empathy of our human interactions has been the object of intensive psychological studies for decades. The emergence of affective computing has opened the door towards technologically-enabled solutions. Yet, existing techniques struggle to attain their desired impact, often being difficult and expensive to deliver, and disconnected from daily life. Project Us' goal is to help overcome these challenges through a pair of wearable devices (in this case wristbands) that aim to trigger an empathy-enhancing effect, when being worn by two people during day-to-day conversations. The small-sized, wireless devices sense each person's electrodermal activity, associated with their level of emotional arousal, and share it to the other partner (when a threshold is exceeded) through a discreet, haptic nudge, creating a real-time feedback loop. The user study performed with 18 participants (nine romantically engaged couples) revealed that most of them found the wristbands to increase their level of awareness of the partner's emotional experience. Their interaction was analyzed based on interviews (qualitatively), and natural language processing techniques (quantitatively).


"All Rise for the AI Director": Eliciting Possible Futures of Voice Technology through Story Completion

How might the capabilities of voice assistants several decades in the future shape human society? To anticipate the space of possible futures for voice assistants, we asked 149 participants to each complete a story based on a brief story stem set in the year 2050 in one of five different contexts: the home, doctor's office, school, workplace, and public transit. Story completion as a method elicits participants' visions of possible futures, unconstrained by their understanding of current technological capabilities, but still reflective of current sociocultural values. Through a thematic analysis, we find these stories reveal the extremes of the capabilities and concerns of today's voice assistants---and artificial intelligence---such as improving efficiency and offering instantaneous support, but also replacing human jobs, eroding human agency, and causing harm through malfunction. We conclude by discussing how these speculative visions might inform and inspire the design of voice assistants and other artificial intelligence.


Using Remote Controlled Speech Agents to Explore Music Experience in Context

It can be difficult for user researchers to explore how people might interact with interactive systems in everyday contexts; time and space limitations make it hard to be present everywhere that technology is used. Digital music services are one domain where designing for context is important given the myriad places people listen to music. One novel method to help design researchers embed themselves in everyday contexts is through remote-controlled speech agents. This paper describes a practitioner-centered case study of music service interaction researchers using a remote-controlled speech agent, called DJ Bot, to explore people's music interaction in the car and the home. DJ Bot allowed the team to conduct remote user research and contextual inquiry and to quickly explore new interactions. However, challenges using a remote speech-agent arose when adapting DJ Bot from the constrained environment of the car to the unconstrained home environment.


Making Air Quality Data Meaningful: Coupling Objective Measurement with Subjective Experience through Narration

Air pollution causes several million deaths every year. Increasing public awareness through the deployment of devices that sense air quality may be a promising step in addressing the problem; however, these wholly objective device measurements may not capture the nuanced and lived experiences people have with the air, which are often colored by perceptions, histories, imaginations, and the sociopolitical context in which people live. The gap between objective environmental realities and individuals' subjective experiences of the environment may make it difficult to form meaning from data, hindering the positive policy outcomes that they are intended to produce. To bridge this gap, we conducted a two-phase design fieldwork to obtain an empirical understanding of the rich contours of experiences people have with the air and outline design strategies in making air quality data meaningful.