Biosignal controlled recommendation in entertainment systems

With the explosive growth of the entertainment contents and the ubiquitous access of them via fixed or mobile computing devices, recommendation systems become essential tools to help the user to find the right entertainment at the right time and location. I envision that by integrating the bio signal input into the recommendation process, it will help the users not only to find interesting contents, but also to increase one’s comfort level by taking into account the biosginal feedback from the users. The goal of this project was to develop a biosignal controlled entertainment recommendation system that increases the user’s comfort level by reducing the level of stress. As the starting point, this project aims to contribute to the field of recommendation systems with two points. The first is the mechanism of embedding the biosignal non-intrusively into the recommendation process. The second is the strategy of the biosignal controlled recommendation to reduce stress. Heart rate controlled in-flight music recommendation is chosen as its application domain. The hypothesis of this application is that, the passenger's heart rate deviates from the normal due to unusual long haul flight cabin environment. By properly designing a music recommendation system to recommend heart rate controlled personalized music playlists to the passenger, the passengers' heart rate can be uplifted, down-lifted back to normal or kept within normal, thus their stress can be reduced. Four research questions have been formulated based on this hypothesis. After the literature study, the project went mainly through three phases: framework design, system implementation and user evaluation to answer these research questions. During the framework design phase, the heart rate was firstly modeled as the states of bradycardia, normal and tachycardia. The objective of the framework is that, if the user's heart rate is higher or lower than the normal heart rate, the system recommends a personalized music playlist accordingly to transfer the user’s heart rate back to normal, otherwise to keep it at normal. The adaptive framework integrates the concepts of context adaptive systems, user profiling, and the methods of using music to adjust the heart rate in a feedback control system. In the feedback loop, the playlists were composed using a Markov decision process. Yet, the framework allows the user to reject the recommendations and to manually select the favorite music items. During this process, the system logs the interactions between the user and the system for later learning the user’s latest music preferences. The designed framework was then implemented with platform independent software architecture. The architecture has five abstraction levels. The lowest resource level contains the music source, the heart rate sensors and the user profile information. The second layer is for resource management. In this layer are the manager components to manage the resources from the first layer and to modulate the access from upper layers to these resources. The third layer is the database, acting as a data repository. The fourth layer is for the adaptive control, which includes the user feedback log, the inference engine and the preference learning component. The top layer is the user interface. In this architecture, the layers and the components in the layers are loosely coupled, which ensures the flexibility. The implemented system was used in the user experiments to validate the hypothesis. The experiments simulated the long haul flights from Amsterdam to Shanghai with the same time schedule as the KLM flights. Twelve subjects were invited to participate in the experiments. Six were allocated to the controlled group and others were allocated to the treatment group. In addition to a normal entertainment system for the control group, the treatment group was also provided with the heart rate controlled music recommendation system. The experiments results validated the hypothesis and answered the research questions. The passenger's heart rate deviates from normal. In our user experiments, the passenger's heart rate was in the bradycardia state 24.6% of time and was in the tachycardia state 7.3% of time. The recommended uplifting music reduces the average bradycardia state duration from 14.78 seconds in the control group to 6.86 seconds in the treatment group. The recommended keeping music increases the average normal state duration from 24.66 seconds in the control group to 29.79 seconds in the treatment group. The recommended down-lifting music reduces the average tachycardia state duration from 13.89 seconds in the control group to 6.53 seconds in the treatment group. Compared to the control group, the stress of the treatment group has been reduced significantly

A strategic planning methodology for aircraft redesign

Due to a progressive market shift to a customer-driven environment, the influence of engineering changes on the product's market success is becoming more prominent. This situation affects many long lead-time product industries including aircraft manufacturing. Derivative development has been the key strategy for many aircraft manufacturers to survive the competitive market and this trend is expected to continue in the future. Within this environment of design adaptation and variation, the main market advantages are often gained by the fastest aircraft manufacturers to develop and produce their range of market offerings without any costly mistakes. This realization creates an emphasis on the efficiency of the redesign process, particularly on the handling of engineering changes. However, most activities involved in the redesign process are supported either inefficiently or not at all by the current design methods and tools, primarily because they have been mostly developed to improve original product development. In view of this, the main goal of this research is to propose an aircraft redesign methodology that will act as a decision-making aid for aircraft designers in the change implementation planning of derivative developments. The proposed method, known as Strategic Planning of Engineering Changes (SPEC), combines the key elements of the product redesign planning and change management processes. Its application is aimed at reducing the redesign risks of derivative aircraft development, improving the detection of possible change effects propagation, increasing the efficiency of the change implementation planning and also reducing the costs and the time delays due to the redesign process. To address these challenges, four research areas have been identified: baseline assessment, change propagation prediction, change impact analysis and change implementation planning. Based on the established requirements for the redesign planning process, several methods and tools that are identified within these research areas have been abstracted and adapted into the proposed SPEC method to meet the research goals. The proposed SPEC method is shown to be promising in improving the overall efficiency of the derivative aircraft planning process through two notional aircraft system redesign case studies that are presented in this study.Ph.D.Committee Chair: Prof. Dimitri Mavris; Committee Member: Dr. Elena Garcia; Committee Member: Dr. Neil Weston; Committee Member: Mathias Emeneth; Committee Member: Prof. Daniel P. Schrag

A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments

In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique was to maintain a balance between user comfort and energy requirements such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gap in the literature is due to the advancements in the technology and drawbacks of the optimization algorithms and the introduction of different new optimization algorithms. Further, many newly proposed optimization algorithms which have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. The detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes

Implicit personalization in driving assistance: State-of-the-art and open issues

In recent decades, driving assistance systems have been evolving towards personalization for adapting to different drivers. With the consideration of driving preferences and driver characteristics, these systems become more acceptable and trustworthy. This article presents a survey on recent advances in implicit personalized driving assistance. We classify the collection of work into three main categories: 1) personalized Safe Driving Systems (SDS), 2) personalized Driver Monitoring Systems (DMS), and 3) personalized In-vehicle Information Systems (IVIS). For each category, we provide a comprehensive review of current applications and related techniques along with the discussion of industry status, benefits of personalization, application prospects, and future focal points. Both relevant driving datasets and open issues about personalized driving assistance are discussed to facilitate future research. By creating an organized categorization of the field, we hope that this survey could not only support future research and the development of new technologies for personalized driving assistance but also facilitate the application of these techniques within the driving automation community</h2

Smart system for aircraft passenger neck support

Air travel is becoming increasingly more accessible to people due to the availability of low cost air travel. However, long distance air travel is not a normal activity for human. During air travel, people experience different levels of physiological and psychological discomfort. The discomfort may affect the passenger’s health and feeling. With the rapid development of technology, the comfort of service has become an important issue. Nowadays, comfort is an attribute which is highly demanded by aircraft passengers. The comfort of aircraft passengers depends on different features and the cabin environment during air travel. Seat is one of the important features for the passengers and in which a passenger spends almost all their time during air travel. Different seat aspects have to be seen and taken into account in the comfort model. The research has five goals. First goal, literature research starts with the study on the state of the art and recent development of vehicle seat design which is available in current literature and products. The literature review gives a general idea about the research and the measurement method related to seating comfort and discomfort. Second goal, four surveys were conducted to identify the comfort factor of economy class aircraft passenger, body discomfort for truck driver, body discomfort for economy class aircraft passenger and relationship between seat location and sitting posture. The first survey is to identify and investigate the comfort factors for economy class aircraft passenger seat. Subsequently, survey on the body back sitting discomfort over travel time was conducted for truck driver and economy class aircraft passenger. The third survey is to investigate the relationship of the seat location and sitting posture of passengers in the economy class aircraft cabin. The postures of subjects were observed and recorded based on seven predefined sitting postures. Third goal, we contributed to develop a smart neck support system for economy class aircraft passenger. Our system aims to support and reduce neck muscle stress. A functional and working prototype was built to demonstrate the design concept and to perform experimental validation. Forth goal, we developed a low cost aircraft cabin simulator and we utilized it to validate our developed smart neck support system. The aircraft cabin simulator was built with motion platform and it is able to simulate a broad range of flight procedures. Next, a calibration experiment was conducted to investigate SCM muscle stress in relation to different support conditions, time interval and head rotation angle. Fifth goal, a validation experiment was conducted in the aircraft cabin simulator to evaluate the smart neck support system. The objective and subjective results show that the smart neck support system is able to reduce SCM muscle stress adaptively in a fully automate manner

Modeling network traffic on a global network-centric system with artificial neural networks

This dissertation proposes a new methodology for modeling and predicting network traffic. It features an adaptive architecture based on artificial neural networks and is especially suited for large-scale, global, network-centric systems. Accurate characterization and prediction of network traffic is essential for network resource sizing and real-time network traffic management. As networks continue to increase in size and complexity, the task has become increasingly difficult and current methodology is not sufficiently adaptable or scaleable. Current methods model network traffic with express mathematical equations which are not easily maintained or adjusted. The accuracy of these models is based on detailed characterization of the traffic stream which is measured at points along the network where the data is often subject to constant variation and rapid evolution. The main contribution of this dissertation is development of a methodology that allows utilization of artificial neural networks with increased capability for adaptation and scalability. Application on an operating global, broadband network, the Connexion by Boeingʼ network, was evaluated to establish feasibility. A simulation model was constructed and testing was conducted with operational scenarios to demonstrate applicability on the case study network and to evaluate improvements in accuracy over existing methods --Abstract, page iii

ELVIS: Entertainment-led video summaries

© ACM, 2010. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Multimedia Computing, Communications, and Applications, 6(3): Article no. 17 (2010) http://doi.acm.org/10.1145/1823746.1823751Video summaries present the user with a condensed and succinct representation of the content of a video stream. Usually this is achieved by attaching degrees of importance to low-level image, audio and text features. However, video content elicits strong and measurable physiological responses in the user, which are potentially rich indicators of what video content is memorable to or emotionally engaging for an individual user. This article proposes a technique that exploits such physiological responses to a given video stream by a given user to produce Entertainment-Led VIdeo Summaries (ELVIS). ELVIS is made up of five analysis phases which correspond to the analyses of five physiological response measures: electro-dermal response (EDR), heart rate (HR), blood volume pulse (BVP), respiration rate (RR), and respiration amplitude (RA). Through these analyses, the temporal locations of the most entertaining video subsegments, as they occur within the video stream as a whole, are automatically identified. The effectiveness of the ELVIS technique is verified through a statistical analysis of data collected during a set of user trials. Our results show that ELVIS is more consistent than RANDOM, EDR, HR, BVP, RR and RA selections in identifying the most entertaining video subsegments for content in the comedy, horror/comedy, and horror genres. Subjective user reports also reveal that ELVIS video summaries are comparatively easy to understand, enjoyable, and informative

Human-Machine Interfaces for Service Robotics

L'abstract è presente nell'allegato / the abstract is in the attachmen