120 research outputs found
Automatic eyeblink and muscular artifact detection and removal from EEG signals using k-nearest neighbor classifier and long hhort-term memory networks
No full textElectroencephalogram (EEG) is often corrupted with artifacts originating from sources such as eyes and muscles. Hybrid artifact removal methods often require human intervention for the adjustment of different parameters. We propose a robust method that can automatically detect and remove eyeblink and muscular artifacts from EEG using a k-nearest neighbor (kNN) classifier and a long short-term memory (LSTM) network. Our method adopts a sliding window of 0.5 s to detect and remove the artifacts from EEG. Features, such as the variance, peak-to-peak amplitude, and average rectified value, are calculated for each EEG segment to identify corrupted segments using the kNN classifier. The kNN classifier detects the presence of artifacts, after which the corresponding EEG window is forwarded to the LSTM network for artifact removal. The LSTM network is trained with the corrupted segments of 0.5 s as input and clean segments of 0.5 s as output. Our method achieved an accuracy of 97.4% in identifying corrupted EEG segments and an average correlation coefficient, structural similarity, signal-to-artifact ratio, and normalized mean squared error of 0.69, 0.76, 1.52 dB, and 0.0013, respectively, in cleaning the EEG. Our results outperformed other hybrid methods reported in the literature based on a combination of ensemble empirical mode decomposition and canonical correlation analysis, a combination of independent component analysis and wavelet decomposition, and tensor decomposition. The mean absolute error of our method is also better in comparison to other methods. Our method can be applied to single and multiple channels and does not require any tuning of parameters
Distributed Mechanisms for Multi-Agent Systems: Analysis and Design
Get PDFThere is an increasing need for multi-agent systems to operate under decentralised control regimes that support openness (individual components can enter and leave at will) and enable components representing distinct stakeholders with different aims and objectives to interact effectively. To this end, this thesis explores issues associated with using techniques from Game Theory and Mechanism Design to organise and analyse such systems. In particular, emphasis is given to distributed mechanisms in which there is distributed allocation (no single centre determines the allocation of the resources or the tasks) and distributed information (agents require information privately known by other agents in order to determine their own valuation or cost). Such mechanisms are important because, in comparison to their centralised counterparts, they are robust to a single-point failure, the computational burden can be potentially shared amongst many agents, and there is a reduction in bottlenecks since not all communication need pass through a single point. As a result, distributed mechanisms are better suited to many types of multi-agent application. To provide a grounding for the mechanisms we develop, the thesis contains a running example of a multi-sensor network scenario. In these systems, distributed allocation mechanisms are desirable since they are robust and reduce bottlenecks in the communication system. Furthermore, we show that distributed information naturally arises by deriving an information-theoretic valuation function. This scenario also gives rise to two additional requirements that are addressed within this thesis: (i) constrained capacity, whereby suppliers can only provide a limited amount of goods or services at any given time and (ii) uncertainty in task completion, whereby sensors potentially fail after they have been assigned tasks. Specifically, we focus on the \ac{vcg} mechanisms and investigate ways of extending it so as to address the requirements that arise within distributed setting in general and sensor networks. In particular, we choose the VCG as our point of departure since it is a mechanism that is efficient, individually rational and incentive compatible. Unfortunately, it is brittle in the sense that it does not conserve these desirable properties when considering the requirements that we outlined above. Therefore, we develop novel mechanisms that do. In more detail, the first part of this thesis considers two distributed allocation mechanisms --- a simultaneous auction environment and \ac{cda}. In the former, bidders place sealed bids in a number of selling auctions which are concurrently offering items. This results in a distributed allocation whereby the winner at each auction is determined by the seller conducting it. For this case, we derive the optimal strategy of the bidders using a game-theoretic approach. In the \acs{cda}, buyers and sellers, respectively, submit bids and asks continuously and the market clears when a bid is higher than an ask; meaning that the allocation is again determined in a distributed way. Furthermore, CDAs are known to yield close to efficient allocations, under certain conditions, even when utilising very simple strategies. However, in our case, we need to modify their format in order to deal with the requirement of constrained capacity. In both of these mechanisms, we study the system's loss in efficiency that ensues from distributing the allocation and find that it is in the simultaneous auction case and upto in the continuous double auction case. The second part of this thesis is concerned with designing mechanisms when agents have distributed information within the system. Such settings are more general than those more traditionally studied in that they encompass the fact that agents can potentially change their valuation or cost upon knowing a signal about the system (which they have not observed) that was hitherto unknown to them. Specifically, we first show that interdependent valuations arise naturally within a sensor network when we develop an information-theoretic valuation function. To account for this, we significantly extend the VCG mechanism in order to deal with these interdependent valuations. We then go on to develop a mechanism that can deal with uncertainty in task allocation. In both of these cases, our mechanisms are shown to be efficient, individually rational and incentive compatible. Moreover, their computational properties are studied and efficient algorithms are designed (based on linear and dynamic programming) in order to speed up the computation of the allocation problem which is generally -hard
A survey on denoising techniques of electroencephalogram signals using wavelet transform
Get PDFElectroencephalogram (EEG) artifacts such as eyeblink, eye movement, and muscle movements widely contaminate the EEG signals. Those unwanted artifacts corrupt the information contained in the EEG signals and degrade the performance of qualitative analysis of clinical applications and as well as EEG-based brain–computer interfaces (BCIs). The applications of wavelet transform in denoising EEG signals are increasing day by day due to its capability of handling non-stationary signals. All the reported wavelet denoising techniques for EEG signals are surveyed in this paper in terms of the quality of noise removal and retrieving important information. In order to evaluate the performance of wavelet denoising techniques for EEG signals and to express the quality of reconstruction, the techniques were evaluated based on the results shown in the respective literature. We also compare certain features in the evaluation of the wavelet denoising techniques, such as the requirement of reference channel, automation, online, and performance on a single channel
Market-Based Task Allocation Mechanisms for Limited Capacity Suppliers
No full textThis paper reports on the design and comparison of two economically-inspired mechanisms for task allocation in environments where sellers have finite production capacities and a cost structure composed of a fixed overhead cost and a constant marginal cost. Such mechanisms are required when a system consists of multiple self-interested stakeholders that each possess private information that is relevant to solving a system-wide problem. Against this background, we first develop a computationally tractable centralised mechanism that finds the set of producers that have the lowest total cost in providing a certain demand (i.e. it is efficient). We achieve this by extending the standard Vickrey-Clarke-Groves mechanism to allow for multi-attribute bids and by introducing a novel penalty scheme such that producers are incentivised to truthfully report their capacities and their costs. Furthermore our extended mechanism is able to handle sellers' uncertainty about their production capacity and ensures that individual agents find it profitable to participate in the mechanism. However, since this first mechanism is centralised, we also develop a complementary decentralised mechanism based around the continuous double auction. Again because of the characteristics of our domain, we need to extend the standard form of this protocol by introducing a novel clearing rule based around an order book. With this modified protocol, we empirically demonstrate (with simple trading strategies) that the mechanism achieves high efficiency. In particular, despite this simplicity, the traders can still derive a profit from the market which makes our mechanism attractive since these results are a likely lower bound on their expected returns
Girlhood and Masculinity in Rajdeep Paulus's Swimming Through Clouds: An Atypical "Masala" Young Adult Novel
No full textThe in-between identity, mainly female, has been the focus of most contemporary English-language Young Adult novels by Indian diaspora authors (Superle, 2011). The hybrid self illustrated in those texts is metaphorically characterised as “Masala”, referring to the blend of spices used to add flavour to the Indian cuisine. However, within the genre at hand, little focus has been given to psychologically rounded female protagonists and masculinities have been almost invisible. An atypical approach to bicultural identities and gender performance has been adopted by the award-winning Indo-American author of “Masala-marinated” fiction Rajdeep Paulus, whose representation of girlhood and masculinity is realistic and inspiring for a young audience.
After outlining the main features of Masala literature (Kumar, 2003), I will discuss to what extent Paulus departs from the standard portrayal of the “New Indian Girl” (Bohemer, 2005; Superle, 2011) in her novel Swimming Through Clouds (2013). I will then move on to the analysis of the masculinities presented in the novel (Connel, 2005; Sinha, 2016), thus showing how giving visibility to both positive and negative examples of masculinity is a necessary condition if socio-cultural needs are to be met (Priya, 2014).
In conclusion, as a powerful ideological tool, Masala Young Adult fiction should provide a realistic description of the deep problematic identity transition of bicultural selves as well as a thorough representation of masculinities alongside femininities in order to stimulate the young adult audience to explore and create their own identities and develop a positive attitude towards the norms of gender equality
{Girlhood and Masculinity in Rajdeep Paulus{\textquoteright}s Swimming Through Clouds: An Atypical "Masala" Young Adult Novel}
No full textThe in-between identity, mainly female, has been the focus of most contemporary English-language Young Adult novels by Indian diaspora authors (Superle, 2011). The hybrid self illustrated in those texts is metaphorically characterised as “Masala”, referring to the blend of spices used to add flavour to the Indian cuisine. However, within the genre at hand, little focus has been given to psychologically rounded female protagonists and masculinities have been almost invisible. An atypical approach to bicultural identities and gender performance has been adopted by the award-winning Indo-American author of “Masala-marinated” fiction Rajdeep Paulus, whose representation of girlhood and masculinity is realistic and inspiring for a young audience. After outlining the main features of Masala literature (Kumar, 2003), I will discuss to what extent Paulus departs from the standard portrayal of the “New Indian Girl” (Bohemer, 2005; Superle, 2011) in her novel Swimming Through Clouds (2013). I will then move on to the analysis of the masculinities presented in the novel (Connel, 2005; Sinha, 2016), thus showing how giving visibility to both positive and negative examples of masculinity is a necessary condition if socio-cultural needs are to be met (Priya, 2014). In conclusion, as a powerful ideological tool, Masala Young Adult fiction should provide a realistic description of the deep problematic identity transition of bicultural selves as well as a thorough representation of masculinities alongside femininities in order to stimulate the young adult audience to explore and create their own identities and develop a positive attitude towards the norms of gender equality
Forecasting international movements of RTI
No full textThesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, First author, 2017.Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, Second author, 2017.Cataloged from PDF version of thesis.Includes bibliographical references (pages 60-61).Returnable Transport Items (RTI) are a critical component of domestic and international trade. The large variability in the geographic supply and demand of goods shipped using RTI impacts the items overall availability at different locations within a network. This research focuses on improving our partner firm's RTI inventory supply in the United States and Canada by developing a one-month-ahead forecasting model to predict the net monthly international flows. To develop the model, six years of historical time series data was decomposed into key elements: level, trend, and seasonality. The results of the decomposition method were used to narrow the forecasting models considered to state space seasonal exponential, SARIMA, state space Holt-Winters, and multivariate regression methods. These four methods were then used to predict the pallet flows using two different approaches. In the first approach, two separate forecasting models were developed, one for the United States-to-Canada flows and the other for the Canada-to-United States flows. The derived Canada-to-United States value was then subtracted from the corresponding United States-to-Canada forecast to calculate the predicted net international movement. In the second approach, we forecasted the net pallet flows between the two countries utilizing only historical values of net international movements. Ultimately, 36 unique models were created using both approaches. The naive forecasting method served as a performance benchmark to the developed models. The performances of the 36 models were then compared using multiplicative and mean composite scores, both of which were based on three accuracy metrics: MAPE, MASE and MAD. Our research found that out of the 36 forecasting models, only seven models outperformed the baseline naive forecasting method. These seven forecasting models were further filtered by qualitative metrics such as ease of implementation and software platform dependence. The state space seasonal exponential model was ultimately recommended due to its superior performances on both the quantitative and qualitative metrics.by Patrick A. Jacobs and Rajdeep Singh Walia.M. Eng. in Supply Chain ManagementM. Eng. in Logistic
Budhan Stories S1E1: What is Corona?
No full textEpisode 1 of Season 1 is based on information regarding Covid-19 and how community is coping with it. People from Rajasthan, Ahmedabad and Maharashtra spoke about conditions they are facing in their regions. Dakxin Chhara gave detailed context of making video podcast and its need for the community.Directed (Author) by: Budhan Theatre Team. Participants: Dakxin Chhara, Atish Indrekar, Ruchika Kodekar, Chetna Rathod, Kushal Batunge, Keyur Bajrange, Anish Garange, Siddharth Garange, Rajdeep Ghamande, Manoj Tamaychi, Raman Chakravat, Akshay Khanna, Yashodara Udupa Supplementary materials include interviews, short clips, stills and poster. </p
Operator scheduling revisited: a multi-objective perspective for fine-grained DVS architecture
No full textFunctional units supporting dynamic voltage and frequency scaling are being used today for fine grained power managed digital integrated circuits. The stringent power budget of these low power circuits have driven chip designers to optimize power at the cost of area and delay, which were the traditional cost criteria for circuit optimization. The emerging scenario motivates us to revisit the classical operator scheduling problem under the availability of DVFS enabled functional units that can trade-off cycles with power. We study the design space defined due to this trade-off and present a branch-and-bound(B/B) algorithm to explore this state space and report the pareto-optimal front with respect to area and power. Experimental results show that the algorithm that operates without any user constraint is able to solve the problem for most available benchmarks, and the use of power budget or area budget constraints leads to significant performance gain
A MULTI-OBJECTIVE PERSPECTIVE FOR OPERATOR SCHEDULING USING FINEGRAINED DVS ARCHITECTURES
No full textThe stringent power budget of fine grained power managed digital integrated circuits have driven chip designers to optimize power at the cost of area and delay, which were the traditional cost criteria for circuit optimization. The emerging scenario motivates us to revisit the classical operator scheduling problem under the availability of DVFS enabled functional units that can trade-off cycles with power. We study the design space defined due to this trade-off and present a branch-and-bound(B/B) algorithm to explore this state space and report the pareto-optimal front with respect to area and power. The scheduling also aims at maximum resource sharing and is able to attain sufficient area and power gains for complex benchmarks when timing constraints are relaxed by sufficient amount. Experimental results show that the algorithm that operates without any user constraint(area/power) is able to solve the problem for mostavailable benchmarks, and the use of power budget or area budget constraints leads to significant performance gain
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