Non-conventional advertising formats in television versus spots: An analysis based on the generated recall

Advertising investment and audience figures indicate that television continues to lead as a mass advertising medium. However, its effectiveness is questioned due to problems such as zapping, saturation and audience fragmentation. This has favoured the development of non-conventional advertising formats. This study provides empirical evidence for the theoretical development. This investigation analyzes the recall generated by four non-conventional advertising formats in a real environment: short programme (branded content), television sponsorship, internal and external telepromotion versus the more conventional spot. The methodology employed has integrated secondary data with primary data from computer assisted telephone interviewing (CATI) were performed ad-hoc on a sample of 2000 individuals, aged 16 to 65, representative of the total television audience. Our findings show that non-conventional advertising formats are more effective at a cognitive level, as they generate higher levels of both unaided and aided recall, in all analyzed formats when compared to the spot.

NETCODE: an XOR-based warning dissemination scheme for vehicular wireless networks

The next generation of vehicles will be equipped with automated Accident Warning Systems (AWSs) capable of warning neighbouring vehicles about hazards that might lead to accidents. The key enabling technology for these systems is the Vehicular Ad-hoc Networks (VANET) but the dynamics of such networks make the crucial timely delivery of warning messages challenging. While most previously attempted implementations have used broadcast-based data dissemination schemes, these do not cope well as data traffic load or network density increases. This problem of sending warning messages in a timely manner is addressed by employing a network coding technique in this thesis. The proposed NETwork COded DissEmination (NETCODE) is a VANET-based AWS responsible for generating and sending warnings to the vehicles on the road. NETCODE offers an XOR-based data dissemination scheme that sends multiple warning in a single transmission and therefore, reduces the total number of transmissions required to send the same number of warnings that broadcast schemes send. Hence, it reduces contention and collisions in the network improving the delivery time of the warnings. The first part of this research (Chapters 3 and 4) asserts that in order to build a warning system, it is needful to ascertain the system requirements, information to be exchanged, and protocols best suited for communication between vehicles. Therefore, a study of these factors along with a review of existing proposals identifying their strength and weakness is carried out. Then an analysis of existing broadcast-based warning is conducted which concludes that although this is the most straightforward scheme, loading can result an effective collapse, resulting in unacceptably long transmission delays. The second part of this research (Chapter 5) proposes the NETCODE design, including the main contribution of this thesis, a pair of encoding and decoding algorithms that makes the use of an XOR-based technique to reduce transmission overheads and thus allows warnings to get delivered in time. The final part of this research (Chapters 6--8) evaluates the performance of the proposed scheme as to how it reduces the number of transmissions in the network in response to growing data traffic load and network density and investigates its capacity to detect potential accidents. The evaluations use a custom-built simulator to model real-world scenarios such as city areas, junctions, roundabouts, motorways and so on. The study shows that the reduction in the number of transmissions helps reduce competition in the network significantly and this allows vehicles to deliver warning messages more rapidly to their neighbours. It also examines the relative performance of NETCODE when handling both sudden event-driven and longer-term periodic messages in diverse scenarios under stress caused by increasing numbers of vehicles and transmissions per vehicle. This work confirms the thesis' primary contention that XOR-based network coding provides a potential solution on which a more efficient AWS data dissemination scheme can be built.

Steno cipher to provide data confidentiality and tampered data recovery for RFID tag

Radio Frequency Identification (RFID) is an emerging wireless object identification technology with many potential applications such as supply chain management, personnel tracking and healthcare. However, security vulnerabilities of the RFID system have been a serious concern for its wide adoption in many applications. Although much work has been done to provide privacy and anonymity, little focus has been given to ensure RFID data confidentiality, integrity and to address the tampered data recovery problem. To this end, we propose a lightweight stenographic-based approach to ensure RFID data confidentiality and integrity as well as the recovery of tampered RFID data. © 2013 Springer-Verlag Berlin Heidelberg.

Security framework and protocols for the internet of things

This study was conducted to protect security of human beings and businesses from intruders in the context of IoT which is next generation internet. We have developed a universal framework and a number of communication protocols to provide security that will make IoT cyber world safer for all t users.

Pyrolysis of municipal green waste: a modelling, simulation and experimental analysis

Pyrolysis is the thermo-chemical conversion of carbonaceous feedstock in the absence of oxygen to produce bio-fuel (bio-oil, bio-char and syn-gas). Bio-fuel production from municipal green waste (MGW) through the pyrolysis process has attracted considerable attention recently in the renewable energy sector because it can reduce greenhouse gas emissions and contribute to energy security. This study analyses properties of MGW feedstock available in Rockhampton city of Central Queensland, Australia, and presents an experimental investigation of producing bio-fuel from that MGW through the pyrolysis process using a short sealed rotary furnace. It was found from the experiment that about 19.97% bio-oil, 40.83% bio-char and 29.77% syn-gas can be produced from the MGW. Then, a four-stage steady state simulation model is developed for pyrolysis process performance simulation using Aspen Plus software. In the first stage, the moisture content of the MGW feed is reduced. In the second stage, the MGW is decomposed according to its elemental constituents. In the third stage, condensate material is separated and, finally, the pyrolysis reactions are modelled using the Gibbs free energy minimisation approach. The MGW's ultimate and proximate analysis data were used in the Aspen Plus simulation as input parameters. The model is validated with experimentally measured data. A good agreement between simulation and experimental results was found. More specifically, the variation of modelling and experimental elemental compositions of the MGW was found to be 7.3% for carbon, 15.82% for hydrogen, 7.04% for nitrogen and 5.56% for sulphur. The validated model is used to optimise the biofuel production from the MGW as a function of operating variables such as temperature, moisture content, particle size and process heat air-fuel ratio. The modelling and optimisation results are presented, analysed and discussed.

Heart failure following cancer therapy in patients with hematological malignancies aged 18 years and under : a linked health data analysis (1996-2009)

Introduction: The causal link between chemotherapy treatments and subsequent cardiotoxicity is well established, particularly for children with hematological malignancies. Little information exists on the characteristics and outcomes for patients with heart failure (HF) after chemotherapy. This study aimed to describe the characteristics, survival and mortality of patients who received chemotherapy for hematological cancer (leukemias, lymphomas and related disorders) before 18 years old and subsequently developed HF compared to those who did not.

Methods: Linked health data (1996-2009) from the Queensland Cancer Registry, Death Registry and Hospital Administration records for HF and chemotherapy admissions were reviewed. From all breast and hematological cancers patients (n=73,158), 15,987 received chemotherapy, including 819 patients aged ≤18 years at time of cancer diagnosis. Patients were categorized as those with an index HF admission (occurred after cancer diagnosis) and those without an index HF admission (non HF).

Results: Of the 819 patients, 3.7% (n=30) had an index HF admission. Median age of HF patients at time of cancer diagnosis was 5 years (IQR 3-12) compared to 7 years (IQR 3-14) in the non HF group (p=0.503). Median follow up from cancer diagnosis was 2.5 years in the HF group compared to 5.42 years in the non HF group (p<0.01). Of those who developed HF, 70% (n=21) had the index admission within 12 months of their cancer diagnosis. Of those with HF, 53.3% (n=16) died (all cause) compared to 14.6% (n=115) with no HF. On adjustment for age, sex and chemotherapy admissions, HF patients had an almost 5 fold increased mortality risk compared to non HF patients (HR 4.91 [95% CI, 2.88-8.36]) (Figure 1).

Conclusions: This study demonstrated that in children with hematological cancers the onset of HF occurred soon after chemotherapy and mortality risk is almost 5 times that of children who do not develop HF. Innovative strategies are still needed for the prevention and management of cardiotoxicity in this population.

Characteristics evaluation of a μ-Synthesis H∞ controller for a grid-connected three-phase photovoltaic system

This paper presents a μ-Synthesis H∞ Controller for regulating the switching signal of the inverter connected with a three-phase photovoltaic (PV) system. To facilitate the control design, the system is represented in terms of state space realization with uncertainties. The control design involves selecting proper weighting functions and performing synthesis. The controller order is reduced by Henkel-norm method. Simulations are carried out to evaluate the characteristics of the controller under parametric uncertainties. It is found out that the proposed controller is inherently stable, possesses significantly small tracking error, and preserves nominal performance, robust stability and robust performance for the grid-connected three-phase PV system.

Exchange rate regimes and fiscal discipline: the role of trade openness

This study revisits the relationship between exchange rate regime (ERR) choice and fiscal discipline focusing on the role of trade openness. The conventional theoretical view is that fixed regimes bring about more fiscal discipline, while the recent literature argues that flexible regimes are more disciplinary. Empirical studies have provided mixed evidence. Using a panel dataset for a large number of developing and developed countries, as well as pooled panel OLS and instrumental variables (IV) estimation techniques, we find support for both views. We document that a fixed ERR is disciplinary at low levels of trade openness, while a flexible regime produces a greater fiscal discipline above a certain level of trade openness. Moreover, this relationship applies to only developing countries. These findings remain robust across different measures of fiscal outcomes, a number of controls, across different sub-samples, and are supported by both annual and five-year averaged panel data.

Characteristics evaluation of an LMI-synthesis H∞ controller for a superconducting magnetic energy systems applied in power systems

© 2015 IEEE.This paper presents an H« controller synthesised based on linear matrix inequalities (LMI) for a current source converter based superconducting magnetic energy systems (SMESs) connected to a node of power systems where the regulation of grid current has considered as a control objective. To facilitate the control design, the system is represented in terms of state space realization with uncertainties. The control design involves selecting proper weighting functions and performing LMI-synthesis. The controller order is reduced by Henkel-norm method. Simulations are carried out to evaluate the characteristics of the controller under parametric uncertainties. It is found out that the proposed controller is inherently stable, possesses significantly small tracking error, and preserves robust performance for the SMES.

Modeling, parameter measurement and sensorless speed estimation of IPM synchronous generator for direct drive variable speed wind turbine application

This paper presents simple methods of determining parameters of interior permanent magnet (IPM) synchronous generator such as magnet flux (λM), d-axis inductance (Ld) and q-axis inductance (Lq) of IPM synchronous generator, which are used to control the wind turbine generator. These methods are simple and do not require any complex theory, signal injection or special equipment. Moreover, a sensorless speed estimator is proposed to estimate the speed of the generator without using speed sensor. The measured parameters are used in this speed estimator. The elimination of speed sensor will enhance the system robustness and reduce the design complexity and system cost for a small-scale wind turbine considered in this paper. The effectiveness of parameter measurement methods and sensorless speed estimator is demonstrated by experimental results. Experimental results show that the proposed speed estimator that uses the measured parameters can estimate the generator speed with a small error.

Multi-layer attribute selection and classification algorithm for the diagnosis of cardiac autonomic neuropathy based on HRV attributes

Cardiac autonomic neuropathy (CAN) poses an important clinical problem, which often remains undetected due difficulty of conducting the current tests and their lack of sensitivity. CAN has been associated with growth in the risk of unexpected death in cardiac patients with diabetes mellitus. Heart rate variability (HRV) attributes have been actively investigated, since they are important for diagnostics in diabetes, Parkinson's disease, cardiac and renal disease. Due to the adverse effects of CAN it is important to obtain a robust and highly accurate diagnostic tool for identification of early CAN, when treatment has the best outcome. Use of HRV attributes to enhance the effectiveness of diagnosis of CAN progression may provide such a tool. In the present paper we propose a new machine learning algorithm, the Multi-Layer Attribute Selection and Classification (MLASC), for the diagnosis of CAN progression based on HRV attributes. It incorporates our new automated attribute selection procedure, Double Wrapper Subset Evaluator with Particle Swarm Optimization (DWSE-PSO). We present the results of experiments, which compare MLASC with other simpler versions and counterpart methods. The experiments used our large and well-known diabetes complications database. The results of experiments demonstrate that MLASC has significantly outperformed other simpler techniques.

Acetylacetonato chelated ruthenium organometallics incorporating imine-phenol function: spectroscopic, structural, electrochemical and cytotoxicity studies

The heterogeneous phase reaction of Ru(η²-RL)(PPh₃)₂(CO)Cl, 1 with lithium acetylacetonate (Liacac) afforded the complexes of the type Ru(η¹-RL)(PPh₃)₂(CO)(acac), 2 in excellent yield where η²-RL is C₆H₂O-2-CHNHC₆H₄R(p)-3-Me-5 and η¹-RL is C₆H₂OH-2-CHNC₆H₄R(p)-3-Me-5 and R is H, Me, Cl. The chelation of acac is attended with the cleavage of Ru-O and Ru-Cl bonds and iminium-phenolato → imine-phenol prototropic shift. A sterically controlled change in rotational conformation is involved in the 1 → 2 conversion. The conversion is irreversible and the type 2 species are thermodynamically more stable than the carboxylate, nitrite and nitrate complexes of 1. The crystal structures of Ru(η¹-MeL)(PPh₃)₂(CO)(acac), 2(Me) and Ru(η¹-ClL)(PPh₃)₂(CO)(acac), 2(Cl) are reported. Spectral (UV-Vis, IR, ¹H NMR) and electrochemical data of the complexes are also reported. The electronic structure and the absorption spectra of the complexes are scrutinized by the density functional theory (DFT) and time-dependent density functional theory (TD-DFT) analyses. The complexes were also screened in vitro for their antiproliferative properties against the MCF-7 breast cancer cell lines by using the MTT assay. Flow cytometric analysis showed that the complexes arrested the cell cycle in the sub G0 phase.

Stability enhancement of DFIG wind turbine using LQR pitch control over rated wind speed

A novel pitch control design method is proposed for the doubly fed induction generator (DFIG) wind turbine (WT) using linear quadratic regulator (LQR). A seven-order model represents the DFIG WT which is linearized by truncated Taylor series expansion. A systematic approach is adopted to determine the weighting matrices in LQR design for the optimal solution. Simulations have been carried out to compare the performance of the proposed LQR pitch control method against a PI pitch control for small and large disturbances. It is shown that the proposed control method enhances low-voltage ride-through capability and improves system damping under large disturbances.

Multilayer hybrid strategy for phishing email zero-day filtering

The cyber security threats from phishing emails have been growing buoyed by the capacity of their distributors to fine-tune their trickery and defeat previously known filtering techniques. The detection of novel phishing emails that had not appeared previously, also known as zero-day phishing emails, remains a particular challenge. This paper proposes a multilayer hybrid strategy (MHS) for zero-day filtering of phishing emails that appear during a separate time span by using training data collected previously during another time span. This strategy creates a large ensemble of classifiers and then applies a novel method for pruning the ensemble. The majority of known pruning algorithms belong to the following three categories: ranking based, clustering based, and optimization-based pruning. This paper introduces and investigates a multilayer hybrid pruning. Its application in MHS combines all three approaches in one scheme: ranking, clustering, and optimization. Furthermore, we carry out thorough empirical study of the performance of the MHS for the filtering of phishing emails. Our empirical study compares the performance of MHS strategy with other machine learning classifiers. The results of our empirical study demonstrate that MHS achieved the best outcomes and multilayer hybrid pruning performed better than other pruning techniques.

Characteristics of patients with haematological and breast cancer (1996-2009) who died of heart failure-related causes after cancer therapy

Aims To describe the characteristics and time to death of patients with breast or haematological cancer who died of heart failure (HF) after cancer therapy. Patients with an index admission for HF who died of HF-related causes (IAHF) and those with no index admission for HF who died of HF-related causes (NIAHF) were compared.

Methods and results We performed a linked data analysis of cancer registry, death registry, and hospital administration records (n = 15 987). Index HF admission must have occurred after cancer diagnosis. Of the 4894 patients who were deceased (30.6% of cohort), 734 died of HF-related causes (50.1% female) of which 279 (38.0%) had at least one IAHF (41.9% female) post-cancer diagnosis. Median age was 71 years [interquartile range (IQR) 62–78] for IAHF and 66 years (IQR 56–74) for NIAHF. There were fewer chemotherapy separations for IAHF patients (median = 4, IQR 2–9) compared with NIAHF patients (median = 6, IQR 2–12). Of the IAHF patients, 71% had died within 1 year of the index HF admission. There was no significant difference in HF-related mortality in IAHF patients compared with NIAHF (HR, 1.10, 95% CI, 0.94–1.29, P = 0.225).

Conclusions The profile of IAHF patients who died of HF-related causes after cancer treatment matched the current profile of HF in the general population (over half were aged ≥70 years). However, NIAHF were younger (62% were aged ≤69 years), female patients with breast cancer that died of HF-related causes before hospital admission for HF-related causes—a group that may have been undiagnosed or undertreated until death.