Coalition structure generation over graphs

We give the analysis of the computational complexity of coalition structure generation over graphs. Given an undirected graph G = (N,E) and a valuation function v : P(N) → R over the subsets of nodes, the problem is to find a partition of N into connected subsets, that maximises the sum of the components values. This problem is generally NP-complete; in particular, it is hard for a defined class of valuation functions which are independent of disconnected members — that is, two nodes have no effect on each others marginal contribution to their vertex separator. Nonetheless, for all such functions we provide bounds on the complexity of coalition structure generation over general and minor free graphs. Our proof is constructive and yields algorithms for solving corresponding instances of the problem. Furthermore, we derive linear time bounds for graphs of bounded treewidth. However, as we show, the problem remains NP-complete for planar graphs, and hence, for any Kk minor free graphs where k ≥ 5. Moreover, a 3-SAT problem with m clauses can be represented by a coalition structure generation problem over a planar graph with O(m2) nodes. Importantly, our hardness result holds for a particular subclass of valuation functions, termed edge sum, where the value of each subset of nodes is simply determined by the sum of given weights of the edges in the induced subgraph

The Translation of English Passive Voice Into Indonesian

English and Indonesian have different grammatical patterns and cultural values. That is why, many problems that students studying translation subject have to face. One of them is how to translate English Passive Voice into Indonesian. That is the reason the writer aims to do the research. The research is to describe the translation of English passive voice into Indonesian by analyzing two novels, which are Kristan Higgins' Waiting on You and its translation Nina Andiana's Penantian Terpanjang. This research uses qualitative method. The writer collected, identified, the data concerning with the translation of English passive voice. The results of the research shows that there are two categories of translating English passive voice into Indonesian, namely English passive voice can be translated both into Indonesian passive voice and English passive voice can be translated into Indonesian active voice. English passive voice is translated into Indonesian passive voice by using prefixes di- and ter-, meanwhile English passive voice is translated into Indonesian active voice by using prefixes me-, men-, and ber-. From forty one data which are identified there are 32 data (78.04%) of English passive voices translated into Indonesian passive voices and 9 data (21.96%) of English passive voices translated into Indonesian active voices

Packetized-voice/data integrated transmission on a token passing ring local area network

This paper investigates the performance of a token passing ring network with packetized-voice/data mixed traffic through extensive simulations. Both data and voice users are modeled in the simulations. Data users produce bursty traffic. Voice traffic is modeled as having alternating talkspurts and silences, with generation of voice packets at a constant rate during talkspurts and no packet generation during silence periods.The network performance measures obtained include: the distribution of transmission delays for voice packets, the average transmission delay and loss probabilities for voice packets, the number of voice users allowed on a network while satisfying the real-time constraints of speech, and the average transmission delay for data packets.Token passing ring local area networks are shown to effectively handle both voice and data traffic. The effects of system parameters (e.g., voice packet length, talkspurt/silence lengths, data traffic intensity, and limited versus exhaustive service disciplines) on network performance are discussed

Continuous Authentication for Voice Assistants

Voice has become an increasingly popular User Interaction (UI) channel, mainly contributing to the ongoing trend of wearables, smart vehicles, and home automation systems. Voice assistants such as Siri, Google Now and Cortana, have become our everyday fixtures, especially in scenarios where touch interfaces are inconvenient or even dangerous to use, such as driving or exercising. Nevertheless, the open nature of the voice channel makes voice assistants difficult to secure and exposed to various attacks as demonstrated by security researchers. In this paper, we present VAuth, the first system that provides continuous and usable authentication for voice assistants. We design VAuth to fit in various widely-adopted wearable devices, such as eyeglasses, earphones/buds and necklaces, where it collects the body-surface vibrations of the user and matches it with the speech signal received by the voice assistant's microphone. VAuth guarantees that the voice assistant executes only the commands that originate from the voice of the owner. We have evaluated VAuth with 18 users and 30 voice commands and find it to achieve an almost perfect matching accuracy with less than 0.1% false positive rate, regardless of VAuth's position on the body and the user's language, accent or mobility. VAuth successfully thwarts different practical attacks, such as replayed attacks, mangled voice attacks, or impersonation attacks. It also has low energy and latency overheads and is compatible with most existing voice assistants

音声モーフィングにおける基準点付与の自動化

Automatic reference point placement method for voice morphing is reported in this paper. Voice morphing is one of fundamental voice editing methods to blend feature vector sequences of two voices based on corresponding reference points. Reference points are basically assigned by hands, and depends on the quality of voice morphing output. Moreover, assigning reference points is a time-consuming task. The proposed method realizes to assign reference points on spectrogram in time- and frequency-domain automatically based on temporal decomposition (TD) and line spectral frequency (LSF). As results of two-speakers’ voice morphing, the proposed method was worked well by using voice and its transcription as inputs