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Learning Assistance by Demonstration (LAD) is concerned with using demonstrations of a human agent to teach a robot how to assist another human. The concept has previously been used with smart wheelchairs to provide customised assistance to individuals with driving difficulties. A basic premise of this technique is that the learned assistive policy should be able to generalise to environments different than the ones used for training; but this has not been tested before. In this work we evaluate the assistive power and the generalisation capability of LAD using our custom teleoperation and learning system for smart wheelchairs, while seeking to improve it by experimenting with different combinations of dimensionality reduction techniques and machine learning models. Using Autoencoders to reduce the dimension of laserscan data and a Gaussian Process as the learning model, we achieved a 23% improvement in prediction performance against the combination used by the latest work on the field. Using this model to assist a driver exposed to a simulated disability, we observed a 9.8% reduction in track completion times when compared to driving without assistance.

The basic premise of Internet of Things (IoT) is to have intelligent devices that can communicate and cooperate directly without human involvement and to deliver a new class of applications such as Bio stamps, Wearable things, Smart City, Smart Toll Plaza etc. For the purpose, the key focus of IoT is on four key components, namely, enabling technologies, standard protocols, technological barriers and application areas. Some IoT architectures like SOA, ROA, NEBULA FIA, NDN, CASAGRAS and AKARI have been proposed by different researchers and are discussed in this article. The paper not only narrow down the promising research domains like identification technology, energy optimization, hardware and software solutions with their major research issues, but also discusses the technological tradeoffs of applications.

In our article we discuss the design of the onboard anti-collision system. The basic premise of creating an anti-collision system is that all flying objects (FO) work in the aviation communications network and each of the flying objects transmits their location information. An important condition for the operation of the proposed anti-collision system is a synchronous communication network. We expect that communication messages to be broadcast by every user at a specified time. All network participants are informed when another network participant is broadcasting. The principle of relative navigation is based on this. We have designed an anti-collision system using this principle.

The established view on massive IoT access is that the IoT devices are activated randomly and independently. This is a basic premise also in the recent information-theoretic treatment of massive access by Polyanskiy. In a number of practical scenarios, the information from IoT devices in a given geographical area is inherently correlated due to a commonly observed physical phenomenon. We introduce a model for massive access that accounts for correlation both in device activation and in the message content. To this end, we introduce common alarm messages for all devices. A physical phenomenon can trigger an alarm causing a subset of devices to transmit the same message at the same time. We develop a new error probability model that includes false positive errors, resulting from decoding a non-transmitted codeword. The results show that the correlation allows for high reliability at the expense of spectral efficiency. This reflects the intuitive trade-off: an access from a massive number can be ultra-reliable only if the information across the devices is correlated., Comment: Extended version of conference submission

This paper provides an overview of the Internet of Things (IoT) with emphasis on enabling Architecture, protocols, and application issues. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper starts by providing a horizontal overview of the IoT. Then, we give an overview of some technical details that pertain to the IoT enabling protocols, and applications.

More email is opened on mobile devices today than on other platforms [1]. At the same time, enterprises are constantly investing in approaches to improve employee productivity. In this paper, we consider the problem of automated information suggestions to assist in reply construction. The basic premise of the work is that a significant portion of the information content of a reply is likely to be present in prior emails. We first show that the premise is valid by analyzing both public and private email datasets. We then present a simple algorithm that relies on inverse document frequency (IDF) and keyword matching to provide relevant suggestions during reply construction. Through prototype evaluations done using the Email datasets, we show that the proposed algorithm has attractive benefits.

Emerging Internet of Things represents a paradigm shift in our understanding of modern communication networks. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications having far reaching consequences for all aspects of human life. In particular Internet of Things revolution is transforming the modern connected healthcare. However, ubiquitous nature and increased autonomy of the IoT devices raise serious concerns about the ethical complicity of connected smart healthcare applications. In this paper we present a novel method to incorporate ethics in IoT driven connected smart healthcare so that the services provided do not unwittingly infringe on the ethical rights of its beneficiaries.

In this paper we propose a novel real time video sailency detection algorithm based on disorder in Motion Field. The proposed algorithm operates on the basic premise that higher disorder pertains to higher information in the scene. Based on the quantified value of the disorder, salient areas in the video frame are demarcated. In order to achieve real time operational capability, the algorithm operates in compressed H.264 domain rather than in pixel domain. The proposed algorithm has been evaluated on standard video sequences and results on real time video surveillance data are also presented.

We present the tests results of the first phase of a multi-phase study to combat deteriorating adolescent fitness, reflected in the growth in adolescent obesity rates, by creating a fitness game deployed on mobile devices. The objective of this first phase was to test an initial mobile fitness prototype's efficacy in generating positive attitudinal changes towards fitness activity using strong socialization components within the game. The basic premise being that game play with a strong social aspect is an attractive support mechanism for sustained interest and providing positive reinforcement to users within our fitness application. Such sustained interest and positive reinforcement is vital for producing long-term fitness improvements. Our mobile fitness game prototype included 13 exercises with functionality to socialize with friends regarding exercise progress and collaboration. A subject pool of 12 adolescents aged 15 to 17 used the prototype for a six week period. Results indicate that the application's socialization features were able to improve subjects' views on fitness activities. Increasing online social networking tendency correlated with improving views on the fitness exercises that were most often engaged in with the application.

Determining the size of candidate matching areas (CMAs) is the basic premise for matching suitability analysis in geomagnetic aided navigation (GAN), and this problem is investigated from the viewpoint of inertial navigation system (INS) precision here. Through the analysis of the influencing factors of the size, the mathematical model is constructed from the perspective of statistics, which makes sure that both the real track and the INS track are included in the CMA with a probability of 99.74%. Experimental results show that the proposed model is effective for determining the size of CMAs, and the conclusions can pave the way for the following matching suitability analysis.

The basic premise of Radio Frequency Identification (RFID) is that objects are marked with "tags" which emit unique "serial numbers" obtainable by "readers" using radio signals. An increasingly popular RFID standard, Class-One Generation-Two (ISO 18000-6c), is expected to play an important role in the widespread adoption of the technology. However, tags of this standard can have their serial numbers easily duplicated or "cloned". Consequently, clone tags, and the objects they are attached to (e.g. counterfeit goods) are assumed to be the original tag and hence object. To address this threat, this work offers a new solution to detect "clones": when multiple tags are active at a reader, "anti-collision algorithm" may expose the implausibility of tags which contain duplicate EPC values. This work begins with an exploration of simulation results from previous work that suggested a possible way to expose clone tags at the reader, and proceeds to confirm these results as a solution to tag cloning exposure using EPC Class One Generation Two hardware. The new solution reported here has the advantage of being relatively simple and implementable on existing hardware making it an additional security solution and therefore an important contribution to RFID security.

We begin from the basic premise that the primary enemies of PV modules are heat, light and moisture, plus numerous other possible stressors which may or may not be participants, depending upon the specific location of the module. We have adopted a Coffin-Manson model to estimate what the effects of thermal cycling might be upon the PV module in support of empirical observations. It describes part of the environmental durability to be anticipated from subject modules (1). Although this model ignores the effects of humidity, solar irradiance, voltage variation and other mechanical and chemical stresses, it does offer us an estimate of the equivalence of a test methodology to a part of the real world environment. A realistic example of its use is described and calculated.

This paper presents the salient aspects of a holistic approach to engineering education. At the heart of holistic education is the basic premise that education addresses the various dimensions of the personality of the whole person, i.e., physical, emotional, intellectual and spiritual personalities of the individual. Transformation is a movement that is primarily from being to becoming. Holistic education values and encourages learning both inside and outside the classroom, enables the development of confident, well-rounded graduates who are prepared to serve as the next generation of creative thinkers and leaders.

The traditional intellectual property diffusion theory is take the law, the administrative protection as the basic premise, But many developed countries started to abandon this theory, and start to study the proliferation effectiveness under the weak constraints. This article based on the weak restraint's basic supposition and the definition, gives the "the proliferation balance condition" of proprietary intellectual property rights, and unifies the intellectual property rights diffusion equation, we discuss two basic proliferation way that is the stable and the unstable way under the weak constraints the proprietary intellectual property rights.

In this paper we study the setup where multiple cyber-physical applications are partitioned and mapped onto spatially distributed electronic control units (ECUs). Further, applications communicate over a mixed time-/event-triggered bus like FlexRay. Such a setting commonly arises in automotive and other distributed cyber-physical systems. All control messages mapped onto the time-triggered or static segment of the bus result in negligible/zero communication delays (viz., the bus and the ECUs can be perfectly synchronized) and hence good control performance. At the other extreme, all messages scheduled in the priority-driven dynamic segment often result in poor control performance because of the intrinsic timing non-determinism of priority-based protocols. In this paper we are concerned with the intermediate case — where messages are dynamically moved between the time- and event-triggered segments in order to meet performance requirements in the presence of disturbances — and formally study the schedulability analysis problem on the bus. In particular, we propose a novel scheduling strategy that considerably reduces the number of static time-triggered slots required in such a switching scheme to meet specified performance requirements. The basic premise of our work is that time-triggered slots are expensive and, hence, they should be used sparingly. We further demonstrate the benefits of our proposed scheme through a number of illustrative examples.

It has now been a decade since the term “Third Generation Photovoltaics” was coined as part of a new research initiative from the author's group. The basic premise was that, given unavoidable costs of encapsulants and mounting structures, energy conversion efficiency must determine the ultimate cost of photovoltaics and hence the likely extent of its adoption. A program was launched with the aim of accelerating the development of high efficiency cell conversion approaches consistent with the use of thin-film, abundant, non-toxic and durable materials. A decade since the program's conception, progress and lessons learnt are reviewed.

By analyzing Coal Mine Safety Supervision of information and process, this article put forward the problem of poor circulation of IFH. In order to adapt to the needs of coal mining enterprises, under the basic premise of the establishment of coal mine safety hidden danger treasury, this article attempts to build a coal mine safety monitoring of IVR systems, in order to deliver IFH information through all types of telephone voice communication equipment and other types of telephone equipments which are fast and convenient.

This paper proposes a hotel recommender system based on sales records. Basic premise under the research is that the sales records include the user's preference relations among hotels. The proposed system recommends hotels based on preference transition network when a user selects a hotel. This paper describes four steps procedure for building the preference transition network proposes in detail. The proposed recommender system is available for repeatable purchase without explicit product evaluation. The features of the prototype system are also illustrated.

The usage of K-anonymity to protect static data sets is well known, but when applied to real time data personal privacy may be breached. For example, a hospital that releases information on all current patients may begin to involuntarily disclose private information due to the presence of a long-term patient records which, when identified through time, reveal identifying information about other records contained in the same k-anonymous tuples. In this paper, we will give a feasible scenario, brief overview of the K-anonymization method, the flaws arising in real-time data, and a practical solution to counter the problems. The basic premise of the solution is to track the released k-anonymized tuples and, in the future, prevent the release of the same tuple at a decreased privacy level.

In this paper we present the design and theoretical analysis of a novel algorithm (LRV) that efficiently solves the problems of coverage, exploration and sensor network deployment at the same time. The basic premise behind the algorithm is that the robot carries network nodes as a payload, and in the process of moving around, emplaces the nodes into the environment based on certain local criteria. In turn, the nodes emit navigation directions for the robot as it goes by. Nodes recommend directions least recently visited by the robot, hence the name LRV. We formally establish the following two properties: 1. LRV is complete on graphs, and 2. LRV is optimal on trees. We present some experimental conjectures for LRV on regular square lattice graphs and compare its performance empirically to other graph exploration algorithms.

Nondiscriminatory transmission services are an essential requirement of open access and constitute a basic premise for the smooth functioning of competitive electricity markets. This requirement is particularly critical when there are bilateral transactions coexisting side-by-side with the centralized day-ahead electricity markets in which the so-called pool players participate as buyers and sellers. The nondiscriminatory allocation of transmission services to the pool players and the bilateral transactions is synonymous with the determination of the market outcomes and the provision of transmission services to the bilateral transactions. We propose the formulation of a generalized transmission scheduling problem (GTSP) to simultaneously accomplish this objective. The proposed GTSP formulation not only captures more appropriately the social welfare and market efficiency loss, but also results in more efficient market outcomes than the conventional transmission scheduling problem (TSP) formulations in the presence of transmission congestion. In addition, the GTSP solutions determine more appropriate locational marginal prices (LMPs) and, consequently, LMP differences for computing the congestion charges and the payoffs for the financial transmission rights (FTR). We assess the capabilities of the proposed GTSP formulation and quantify the improvements over conventional TSP solutions. These improvements become particularly important as the load served by the bilateral transactions constitute an increasingly large portion of the total load in the system. We illustrate quantifiable benefits of the GTSP solutions on a wide range of systems including the IEEE 118-bus network. The representative numerical results in the paper provide persuasive support for the effectiveness of the proposed formulation and the superiority of its solutions over those of the conventional TSP.

Business users have a problem in replacing existing business application systems. Well over 50% of all replacement projects fail. The systems have become much too complex and too much knowledge about them has been lost. It is nearly impossible to reconstruct the requirements. Therefore, this paper presents an incremental, integrative approach supported by bridging tools, which allows migrating without requirements. The basic premise is to first breakup the existing systems into separate, collaborating subsystems and then to either convert them, redevelop them or to wrap them one at a time. The key is the interaction of the subsystems with each other and with the database across platform boundaries. The new subsystems can coexist with the remaining old ones until such time that all of them have been replaced.

Platform-based design is one of the key strategies that is promoted for successfully coping with the most complex, system-on-chip designs. Its basic premise is that the levels of design productivity needed to counter the intrinsic complexity of such embedded systems will only be achieved by extensive, planned design re-use. The platform concept originated with ASICs but evolved rapidly to FPGAs. In this paper, we investigate the phenomenon of FPGA platforms using the Xilinx Virtex/spl trade/-II Pro series of Platform FPGAs as our reference model. We identify and categorize their principal characteristics and seek to differentiate them from their ASIC predecessors. We make the case for regarding Platform FPGAs as meta-platforms because of the extent to which they extend the original concept of platform-based design. Looking forward, we offer some conjectures as to the nature of future FPGA platforms and some of the challenges that researchers will face.

The long term goal of this study is to formulate a speech processing algorithm for analysis and classification of speech pathology due to vocal fold cancer. In this initial phase, a signal processing algorithm is proposed which attempts to quantify the change in production when vocal fold cancer is present. The basic premise is that exact glottal flow estimation is not needed to quantify the change in speech production when a stationary excitation pathology exists. The proposed method is based on maximum likelihood (ML) estimation, which allows for a separation of speech components under healthy and assumed pathology conditions. The method constitutes an iterative approach based on the estimation-maximization (EM) algorithm. An evaluation is performed on speech recordings from vocal fold cancer patients undergoing radiation treatment. An enhanced spectral pathology component (ESPC) results, which is shown to vary consistently between pre and post radiation conditions. It is suggested that general analysis of the ESPC feature can provide a quantitative, non-invasive approach for vocal fold pathology detection and characterization of speech production.

This paper describes a visual decision support system that supports marketers in the advertising field. The purpose of this system is to help users estimate the effect of advertising based on the extraction of expert knowledge when there is no fresh data to go on. This system includes the following functions: a) To check the dispersion of data and the behavior of models using 3D plot displays, and b) To make prediction models capable of estimating the effect of advertising using a constrained learning algorithm for neural networks. These functions have each of the following features: a) The ability to easily check the dispersion of data and the behavior of models in the various axes, allowing a marketer to delete unnecessary data in 3D spaces. b) The basic premise that the relationship between the input and output monotonously increases. This system is useful for domains where only deficient data is available like estimating the effect of advertising. Experimental simulations using real data have shown that experts can easily check the dispersion of data and the behavior of models, and have shown that the algorithm makes more reasonable models for estimating the effect of advertising than other conventional algorithms.

A basic premise of the DoD Global Broadcast Service (GBS) is the leveraging of commercial technology and the use of commercial off-the-shelf (COTS) components. Driven by the high cost associated with new development and "militarization", and the reality of decreasing defense budgets this trend is likely to continue and expand. It is important to ensure that military capability is not unduly compromised in this process, and that COTS equipment and components do not become a "weak link in the chain". This paper examines the use of COTS in the GBS program and draws conclusions regarding the appropriateness of these actions.