Development of a typing behaviour recognition mechanism on Android

This paper proposes a biometric authentication system which use password based and behavioural traits (typing behaviours) authentication technology to establish user’s identity on a mobile phone. The proposed system can work on the latest smart phone platform. It uses mobile devices to capture user’s keystroke data and transmit it to web server. The authentication engine will establish if a user is genuine or fraudulent. In addition, a multiplier of the standard deviation “α” has been defined which aims to achieve the balance between security and usability. Experimental results indicate that the developed authentication system is highly reliable and very secure with an equal error rate is below 7.5%

Cationic aminooxy lipids : synthesis, liposome stabilization and applications.

This dissertation describes research focused on the synthesis, polymerization and applications of cationic aminooxy lipids. An efficient and convenient method was developed to stabilize liposomes using \u27click chemistry\u27. The \u27click stabilized liposomes\u27 are fortified via covalent crosslinks generated between aldehyde and aminooxy functionalities in the lipid bilayers. Compared to untreated liposomes (i.e., no lipid-lipid bonding), the \u27click\u27 stabilized liposomes are considerably more stable against surfactant-mediated liposome disruption or serum-mediated liposome aggregation. Stabilized liposomes also can react with \u27clickable\u27 targeted ligands on the liposome surface for specific organ (e.g. breast cancer cells or liver) targeting. In this thesis, I have explored the feasibility of using the click stabilized liposomes in three different applications: i) colonic targeted delivery ii) gene vector iii) enzyme nanoreactor. This dissertation is divided into six chapters. Chapter 1 gives a review of liposomes and liposome stabilization. Chapter 2 describes the synthesis and characterization of cationic aminooxy compounds 2.1 and 2.2 as the headgroup domains of prototype lipids. Chapter 3 describes the synthesis, characterization and hydrolysis of cationic aminooxy enol ether lipids 3.1 and 3.2. The liposomes formulated from lipid 3.2 were stabilized using a pH-triggered lipid polymerization strategy. Chapter 4 describes the synthesis and characterization of a variety of aminooxy lipids and dextran polyaldehydes (DPAs). The liposomes formulated from lipids 4.1 were stabilized by simply mixing with DPAs. The resultant \u27click\u27 stabilized liposomes have potential applications such as drug carriers for colonic targeted delivery and as nano-reactors. Chapter 5 focuses on applying \u27click\u27 stabilized liposomes as gene carriers. The initial results of in vitro gene transfection revealed that the stabilized lipoplexes formulated from lipid 4.1 successfully transfected MFC-7 cells, but with lower transfection potency. A liver-targeted ligand 5.2 based on lactose was synthesized for future in vivo gene transfection applications. Chapter 6 details all experimental procedures and approaches used for compound characterizations

Personalized Dialogue Generation with Diversified Traits

Endowing a dialogue system with particular personality traits is essential to deliver more human-like conversations. However, due to the challenge of embodying personality via language expression and the lack of large-scale persona-labeled dialogue data, this research problem is still far from well-studied. In this paper, we investigate the problem of incorporating explicit personality traits in dialogue generation to deliver personalized dialogues. To this end, firstly, we construct PersonalDialog, a large-scale multi-turn dialogue dataset containing various traits from a large number of speakers. The dataset consists of 20.83M sessions and 56.25M utterances from 8.47M speakers. Each utterance is associated with a speaker who is marked with traits like Age, Gender, Location, Interest Tags, etc. Several anonymization schemes are designed to protect the privacy of each speaker. This large-scale dataset will facilitate not only the study of personalized dialogue generation, but also other researches on sociolinguistics or social science. Secondly, to study how personality traits can be captured and addressed in dialogue generation, we propose persona-aware dialogue generation models within the sequence to sequence learning framework. Explicit personality traits (structured by key-value pairs) are embedded using a trait fusion module. During the decoding process, two techniques, namely persona-aware attention and persona-aware bias, are devised to capture and address trait-related information. Experiments demonstrate that our model is able to address proper traits in different contexts. Case studies also show interesting results for this challenging research problem.Comment: Please contact [zhengyinhe1 at 163 dot com] for the PersonalDialog datase

Unraveling Managerial Tangents in Firm Disclosure: Concealing Issues or Being Exposed?

Earnings calls influence stock prices and are traditionally analyzed using sentiment and linguistic traces. Our research introduces a "Topic-Switching Index," a novel metric quantified through the transformer model FinBERT, to measure managerial evasion during Q$\&$A sessions in earnings calls. We find a negative correlation between this index and subsequent stock prices, indicating that investors penalize managerial evasiveness. This study is the first to quantify such evasive tactics, adding a new dimension to how earnings calls are understood and suggesting that topic shifting is an overlooked but significant factor. We also show the predictability of the index under three different classifier models and it stands out in all circumstances

Design of Visual Feedback Tracking Algorithm for Nonholonomic Mobile Robots Based on Neural Network

With the rapid development of the computer and the electronic technique, the application of robots has been widen. The robot visual serving control system may mimic the human eyes. Then the vision information is used as a feedback to improve the ability of the robot adaption to the environment. However, traditional algorithms which need the calibration of visual parameters spend much time and become technical bottlenecks. This paper presents the development background of the robot and the concept of nonholonomic mobile robots with visual servoing feedback. Second, the deficiency exists in traditional algorithms and fuzzy controller. Third, BP neural network PID is proposed to design controller. Combining BP neutral network with PID controller is used to manipulate mobile robots firstly. The complex deduces of common tracking controllers is simplified and tracking control problem with non calibrated virtual parameters is solved. Finally, we program the simulation code. The simulation results show that the method is effective