The ACL-2019 Business meeting ended with a discussion of reviewing. Conferences are experiencing a success catastrophe. They are becoming bigger and bigger, which is not only a sign of success but also a challenge (for reviewing and more). Various proposals for reducing submissions were discussed at the Business meeting. IMHO, the problem is not so much too many submissions, but rather, random reviewing. We cannot afford to do reviewing as badly as we do (because that leads to even more submissions). Negative feedback loops are effective. The reviewing process will improve over time if reviewers teach authors how to write better submissions, and authors teach reviewers how to write more constructive reviews. If you have received a not-ok (unhelpful/offensive) review, please help program committees improve by sharing your not-ok reviews on social media.

It is widely accepted that acoustic and digital musical instruments shape the cognitive processes of the performer on both embodied and conceptual levels, ultimately influencing the structure and aesthetics of the resulting performance. In this article we examine the ways in which computer music languages might similarly influence the aesthetic decisions of the digital music practitioner, even when those languages are designed for generality and theoretically capable of implementing any sound-producing process. We examine the basis for querying the non-neutrality of tools with a particular focus on the concept of idiomaticity: patterns of instruments or languages which are particularly easy or natural to execute in comparison to others. We then present correspondence with the developers of several major music programming languages and a survey of digital musical instrument creators examining the relationship between idiomatic patterns of the language and the characteristics of the resulting instruments and pieces. In an open-ended creative domain, asserting causal relationships is difficult and potentially inappropriate, but we find a complex interplay between language, instrument, piece and performance that suggests that the creator of the music programming language should be considered one party to a creative conversation that occurs each time a new instrument is designed.

There is an increasing demand for humanitarian aid around the world. At the same time, the number of makerspaces has been growing exponentially. Recently, the humanitarian sector has become interested in how these new design spaces can help crisis-affected populations. Despite the emergence of humanitarian makerspaces, there is little research to date that documents their outcomes and impacts. A multi-case study approach is taken to analyze three makerspaces that support migrants, refugees, and asylum seekers in Greece. A maturity grid tool is used to show that humanitarian makerspaces are driving impact in six key areas. The study underlines how these makerspaces support different design activities and have different outcomes. It also considers the challenges which are preventing humanitarian makerspaces from achieving their ultimate goals, drawing attention to the need for an enabling ecosystem in both the local and humanitarian context. This research brings clarity to the poorly understood phenomenon of humanitarian makerspaces and highlights the important role of design in humanitarian interventions. It also reveals practical insights for humanitarian organizations who are considering setting up makerspaces in crisis-affected communities.

This paper proposes an intelligent model-based optimization methodology for optimizing the production cost and material removal rate subjected to surface quality constraint in turning operation of hardened AISI D2. Unlike traditional approaches, this paper deals with finding optimum cutting parameters considering the real condition of the cutting tool. Tool flank wear is predicted by the model obtained using genetic programming. On the basis of the predicted flank wear value, the surface roughness of work piece is estimated by neural networks. Applying the particle swarm optimization algorithm, the optimum machining parameters are determined. The simulation and experimental results show that machining with proposed intelligent optimization methodology has higher efficiency than conventional techniques with constant optimized cutting parameters.

This article considers the interval availability and instant availability of the k-system. A certain relationship between the two types of availability is established. Some lower and upper bounds to interval availability are derived. It also provides a couple of conditions under which the availability of two systems can be compared. Several examples are given to show the complexity of comparisons of availability.

We study decision procedures for two knowledge problems critical to the verification of security protocols, namely the intruder deduction and the static equivalence problems. These problems can be related to particular forms of context matching and context unification. Both problems are defined with respect to an equational theory and are known to be decidable when the equational theory is given by a subterm convergent term rewrite system (TRS). In this work, we extend this to consider a subterm convergent TRS defined modulo an equational theory, like Commutativity. We present two pairs of solutions for these important problems. The first solves the deduction and static equivalence problems in rewrite systems modulo shallow theories such as Commutativity. The second provides a general procedure that solves the deduction and static equivalence problems in subterm convergent systems modulo syntactic permutative theories, provided a finite measure is ensured. Several examples of such theories are also given.

This paper discusses stochastic comparisons for the residual and past lifetimes of coherent systems with dependent and identically distributed (d.i.d.) components under random monitoring in terms of the hazard rate, the reversed hazard rate, and the likelihood ratio orders. Some stochastic comparisons results are also established on the residual lifetimes of coherent systems under random observation times when all of the components are alive at that time. Sufficient conditions are established in terms of the aging properties of the components and the distortion functions induced from the system structure and dependence among components lifetimes. Numerical examples are provided to illustrate the theoretical results as well.

Typical wireless power transfer (WPT) systems on the market charge only a single receiver at a time. However, it can be expected that the need will arise to charge multiple devices at once by a single transmitter. Unfortunately, adding extra receivers influences the system efficiency. By impedance matching, the loads of the system can be adjusted to maximize the efficiency, regardless of the number of receivers. In this work, we present the analytical solution for achieving maximum system efficiency with any number of receivers for capacitive WPT. Among others, we determine the optimal loads and the maximum system efficiency. We express the efficiency as a function of a single variable, the system kQ-product and demonstrate that load capacitors can be inserted to compensate for any cross-coupling between the receivers.

The deployment of multi-insulator tunneling diodes has recently had more attention to be used as rectifiers in energy harvesting rectennas with good potentiality for a millimeter and terahertz range. However, with the rather complicated math to obtain the current–voltage relation, it is difficult to evaluate the design figures of merit (FOM)s such as asymmetry, nonlinearity, responsivity, and dynamic resistance and monitor the impact of changing physical parameters on them. This complicates the decision-making process for the required physical parameters. In this work, a heuristic optimization framework using genetic algorithm is suggested using the transfer matrix method to find the combination of physical parameters which satisfies the minimum required FOM set by users and weighted by their preference.

In this paper, a concise and universal method to calculate the maximum RF (radio frequency) power transfer efficiency between arbitrary multiple transmitters and multiple receivers wireless power transfer (MIMO-WPT) system is presented. The method is based on maximum Rayleigh quotient which can be deduced either from the multi-port impedance matrix Z or from the multi-port scattering matrix S. Moreover, without any limitation on the transmitting/receiving element's geometry, numbers, operating frequency, coupling method, and so on, the approach is capable to evaluate both the transfer efficiency and the maximum transfer efficiency (MTE) of any type of transmitting and receiving elements, and to obtain the optimum impedances for all transmitting or receiving ports as well. At the end of this paper, the MTEs of some typical MIMO-WPT systems will be calculated to validify the proposed method, and the effectiveness against the receiver's misalignment by using multiple transmitters will be demonstrated.

This study proposes the use of a series elastic actuator (SEA) in a Segway to improve the stability of the tires during linear and curved driving, thus improving the comfort of the driver and ensuring driving stability. Recently, Segway has been developed continuously for intelligent mobile vehicles and the performance of Segway is being enhanced. Therefore, safety factors during the Segway driving have been considered seriously. In most of the developments and studies on Segway, the optimization and improvement of the controller component have been tackled and there are few studies on the safety devices and the stability of driving. The impact and vibration generated from the ground due to uneven road surfaces considerably influence the force exerted on the tire, which further affects driving stability. This research focuses on the control of the SEA based on the tire model to improve the driving stability of Segway. The performance of the proposed algorithm to improve the stability of the driver has been verified by straight and curved paths driving experiments with the tire model.

This paper presents design considerations for an integrated wireless power transfer (WPT) and power line communication (PLC) system (e.g. WPT-PLC). The main goal is to enable wireless charging of mobile electronic products, along with high data rate communication over the shared wireless inductive resonant channel. Starting from a couple of resonant coils, characterized by the S-parameters matrix, the design of an impedance matching network and decoupling filters is carried out to better decouple power and data signals. A pulse-driven class-E power amplifier (PA) and a rectifier are first conceived based on the measured S-parameters and load-pull characterizations. Second, a sine-driven class-E power link, operating at 6.78 MHz, is proposed to reduce the total harmonic distortion of the integrated WPT-PLC system. These design steps aim to ensure high-power efficiency and low harmonic distortion of the class-E PA in order to mildly affect the channel capacity of the PLC. The harmonic interferences of the pulse-driven and sine-driven class-E power links are compared and discussed, together with the electromagnetic compatibility levels, the channel capacity, and the noise disturbances of the PLC channel in order to guarantee an optimized power and data transfer in the integrated WPT-PLC system.

This study documents historical trends of size and political diversity in Americans’ discussion networks, which are often seen as important barometers of social and political health. Contrasting findings from data drawn out of a nationally representative survey experiment of 1,055 Americans during the contentious 2016 U.S. presidential election to data arising from 11 national data sets covering nearly three decades, we find that Americans’ core networks are significantly smaller and more politically homogeneous than at any other period. Several methodological artifacts seem unlikely to account for the effect. We show that in this period, more than before, “important matters” were often framed as political matters, and that this association probably accounts for the smaller networks.

When collecting egocentric network data, visual representations of networks can function as a cognitive aid for depicting relationships, helping to maintain an overview of the relationships, and keeping the attention of the interviewees. Additionally, network maps can serve as a narration generator in qualitative and in mixed-methods studies. While varying visual instruments are used for collecting egocentric network data, little is known about differences among visual tools concerning the influence on the resulting network data, the usability for interviewees, and data validity. The article provides an overview of existing visually oriented tools that are used to collect egocentric networks and discusses their functions, advantages, and limitations. Then, we present results of an experimental study where we compare four different visual tools with regard to networks elicited, manageability, and the impact of follow-up questions. In order to assess the manageability of the four tools, we used the thinking aloud method. The results provide evidence that the decision in favor of a specific visual tool (structured vs. unstructured) can affect the size and composition of the elicited networks. Follow-up questions greatly affect the elicited networks and follow-up cues can level out differences among tools. Respondents tend to prefer the concentric circles tool, with some differences in preferences and manageability of tools between participants with low and those with high socioeconomic status. Finally, assets and drawbacks of the four instruments are discussed with regard to data quality and crucial aspects of the data collection process when using visual tools.

There is an implicit assumption in machine learning techniques that each new task has no relation to the tasks previously learned. Therefore, tasks are often addressed independently. However, in some domains, particularly reinforcement learning (RL), this assumption is often incorrect because tasks in the same or similar domain tend to be related. In other words, even though tasks are quite different in their specifics, they may have general similarities, such as shared skills, making them related. In this paper, a novel domain adaptation-based method using adversarial networks is proposed to do transfer learning in RL problems. Our proposed method incorporates skills previously learned from source task to speed up learning on a new target task by providing generalization not only within a task but also across different, but related tasks. The experimental results indicate the effectiveness of our method in dealing with RL problems.