Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents

User interaction with voice-powered agents generates large amounts of unlabeled utterances. In this paper, we explore techniques to efficiently transfer the knowledge from these unlabeled utterances to improve model performance on Spoken Language Understanding (SLU) tasks. We use Embeddings from Language Model (ELMo) to take advantage of unlabeled data by learning contextualized word representations. Additionally, we propose ELMo-Light (ELMoL), a faster and simpler unsupervised pre-training method for SLU. Our findings suggest unsupervised pre-training on a large corpora of unlabeled utterances leads to significantly better SLU performance compared to training from scratch and it can even outperform conventional supervised transfer. Additionally, we show that the gains from unsupervised transfer techniques can be further improved by supervised transfer. The improvements are more pronounced in low resource settings and when using only 1000 labeled in-domain samples, our techniques match the performance of training from scratch on 10-15x more labeled in-domain data.Comment: To appear at AAAI 201

Diversity, Assortment, Dissimilarity, Variety: A Study of Diversity Measures Using Low Level Features for Video Retrieval

In this paper we present a number of methods for re-ranking video search results in order to introduce diversity into the set of search results. The usefulness of these approaches is evaluated in comparison with similarity based measures, for the TRECVID 2007 collection and tasks [11]. For the MAP of the search results we find that some of our approaches perform as well as similarity based methods. We also find that some of these results can improve the P@N values for some of the lower N values. The most successful of these approaches was then implemented in an interactive search system for the TRECVID 2008 interactive search tasks. The responses from the users indicate that they find the more diverse search results extremely useful

Enhancing Cybersecurity Awareness for Students at Haaga Helia University of Applied Sciences

In the current digital era, cybersecurity knowledge is crucial for preserving the confidentiality of personal data and safe online conduct, especially in institutions of higher learning that hold enormous volumes of sensitive data. To uncover knowledge gaps and develop a customised instructional handbook to meet these needs, this research examines the cybersecurity aware-ness of students at Haaga Helia University of Applied Sciences. The Social Cognitive Theory (SCT), which prioritises behavioural reinforcement, self-efficacy, and observational learning, served as the theoretical framework for the study. Semi-structured interviews were used as part of a qualitative technique to investigate the attitudes, behaviours, and experiences of students with cybersecurity. Common awareness gaps, misunderstandings, and real-world difficulties encountered by students were identified by the analysis. This thesis concludes by suggesting that thorough, approachable instructional materials, like the created handbook, can be extremely helpful in closing the knowledge gap in cybersecurity among students. To encourage improved cybersecurity practices and provide a safer online environment for all students, it is advised that educational institutions include this handbook in their resources

Performance Enhancement of Power Line Communication Using OFDM and CDMA

Power line communication has been emanated as one of the most enduring means of communication for smart grid applications especially while considering the biggest advantage i.e. an already established infrastructure, therefore sending out the control information over the same network will add only a little cost and hence opens the door for a plethora of applications. The communication over Power Line is not so new when we are concerned about generation, transmission or deliverance of power but here our main concern is control and management of power rather than transmission or deliverance of power and this purpose can only be accomplished if we are utilizing the available resources in an efficient manner which in turn is dependent on the fast and effective transmission of data or control information over these channels. To ensure the fulfilment of these requisites there is a requirement to analyse the basic topological connections and the circuit modelling and thus determined the various control and traffic problems associated with the transmission of this information which usually varies according to applications. Therefore OFDM (BPSK, QPSK, and QAM) has been utilized for the purpose of analysis of the channel performance while ensuring the speed and robustness of the channel to be the main criteria for any kind of services or applications .Moreover there usually arises a problem of power failure and reliable communication over remote locations and therefore the solution for it is an interfacing between wired and wireless communication technologies and hence in the thesis work, a comparison of the bit error probability had been shown between the performance of the channel while using OFDM and CDMA and this comparison provides an solution to choose the technology according to the requirement of application

DEVELOPMENT AND VALIDATION OF A NOVEL METHOD FOR CAUSALITY ASSESSMENT USING SUSPECTED ADVERSE DRUG REACTIONS TO ANGIOTENSIN-CONVERTING ENZYME INHIBITORS

Objectives: The study has been designed to develop, test reliability, and construct validity of a novel versatile causality assessment tool (VCAT) method.Methods: The study included 427 literature case reports of angiotensin-converting enzyme inhibitors with suspected adverse drug reactions from 1990 to February 25, 2016. The causality of these cases was assessed independently by 3 raters in 3 phases of the study. Kappa (k) and intra-class correlation Intraclass Correlation Coefficient (ICC) were used to test reliability and validity of the VCAT method.Results: Intra-rater reliability was high between Phase I and Phase III (k=0.84–0.93; % agreement: 92.3–96.3%). Inter-rater agreement was good in Phase I (k=0.87–0.89, % agreement: 93.7–94.1%, ICC: 0.975) and Phase III (k=0.85–0.89, % agreement: 93–94.4%, ICC: 0.973). Validity was proved by the high agreement observed between Phase I and Phase II (k=0.78–0.94; % agreement: 89.7–97.2%; p<0.001); and between Phase II and Phase III (k=0.8–0.9; % agreement: 90.2–94.8%; p<0.001).Conclusion: VCAT method is a standardized causal assessment tool that gives valid and reproducible results. It has shown good agreement with the expert judgment method. This method may overcome the limitations enthralled with existing methods of causality assessment

Computational Fermi level engineering and doping-type conversion of Ga2O3 via three-step synthesis process

Ga2O3 is being actively explored for high-power and high-temperature electronics, deep-ultraviolet optoelectronics, and other applications. Efficient n-type doping of Ga2O3 has been achieved, but p-type doping faces fundamental obstacles due to compensation, deep acceptor levels, and the polaron transport mechanism of free holes. However, aside from achieving p-type conductivity, plenty of opportunity exists to engineer the position of the Fermi level for improved design of Ga2O3 based devices. We use first-principles defect theory and defect equilibrium calculations to simulate a 3-step growth-annealing-quench synthesis protocol for hydrogen assisted Mg doping in beta-Ga2O3, taking into account the gas phase equilibrium between H2, O2 and H2O, which determines the H chemical potential. We predict Ga2O3 doping-type conversion to a net p-type regime after growth under reducing conditions in the presence of H2 followed by O-rich annealing, which is a similar process to the Mg acceptor activation by H removal in GaN. For equilibrium annealing there is an optimal temperature that maximizes the Ga2O3 net acceptor density for a given Mg doping level, which is further increased in the non-equilibrium annealing scenario without re-equilibration. After quenching to operating temperature, the Ga2O3 Fermi level drops below mid-gap down to about +1.5 eV above the valence band maximum, creating a significant number of uncompensated neutral MgGa0 acceptors. The Fermi level reduction down to +1.5 eV and suppression of free electron density in this doping type converted (NA > ND) Ga2O3 material is of significance and impact for the design of Ga2O3 power electronics devices