Task-based annotation and retrieval for image information management

Continuing advances in digital image capture and storage are resulting in a proliferation of imagery and associated problems of information overload in image domains. In this work we present a framework that supports image management using an interactive approach that captures and reuses task-based contextual information. Our framework models the relationship between images and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. During image analysis, interactions are captured and a task context is dynamically constructed so that human expertise, proficiency and knowledge can be leveraged to support other users in carrying out similar domain tasks using case-based reasoning techniques. In this article we present our framework for capturing task context and describe how we have implemented the framework as two image retrieval applications in the geo-spatial and medical domains. We present an evaluation that tests the efficiency of our algorithms for retrieving image context information and the effectiveness of the framework for carrying out goal-directed image tasks. © 2010 Springer Science+Business Media, LLC.

Applying Information Foraging Theory to understand user interaction with content-based image retrieval

The paper proposes an ISE (Information goal, Search strategy, Evaluation threshold) user classification model based on Information Foraging Theory for understanding user interaction with content-based image retrieval (CBIR). The proposed model is verified by a multiple linear regression analysis based on 50 users' interaction features collected from a task-based user study of interactive CBIR systems. To our best knowledge, this is the first principled user classification model in CBIR verified by a formal and systematic qualitative analysis of extensive user interaction data. Copyright 2010 ACM.

Supply chain optimisation of pyrolysis plant deployment using goal programming

This paper presents a goal programming model to optimise the deployment of pyrolysis plants in Punjab, India. Punjab has an abundance of waste straw and pyrolysis can convert this waste into alternative bio-fuels, which will facilitate the provision of valuable energy services and reduce open field burning. A goal programming model is outlined and demonstrated in two case study applications: small scale operations in villages and large scale deployment across Punjab's districts. To design the supply chain, optimal decisions for location, size and number of plants, downstream energy applications and feedstocks processed are simultaneously made based on stakeholder requirements for capital cost, payback period and production cost of bio-oil and electricity. The model comprises quantitative data obtained from primary research and qualitative data gathered from farmers and potential investors. The Punjab district of Fatehgarh Sahib is found to be the ideal location to initially utilise pyrolysis technology. We conclude that goal programming is an improved method over more conventional methods used in the literature for project planning in the field of bio-energy. The model and findings developed from this study will be particularly valuable to investors, plant developers and municipalities interested in waste to energy in India and elsewhere. © 2014 Elsevier Ltd. All rights reserved.

A multihop peer-communication protocol with fairness guarantee for IEEE 802.16-based vehicular networks

Wireless-communication technology can be used to improve road safety and to provide Internet access inside vehicles. This paper proposes a cross-layer protocol called coordinated external peer communication (CEPEC) for Internet-access services and peer communications for vehicular networks. We assume that IEEE 802.16 base stations (BS) are installed along highways and that the same air interface is equipped in vehicles. Certain vehicles locating outside of the limited coverage of their nearest BSs can still get access to the Internet via a multihop route to their BSs. For Internet-access services, the objective of CEPEC is to increase the end-to-end throughput while providing a fairness guarantee in bandwidth usage among road segments. To achieve this goal, the road is logically partitioned into segments of equal length. A relaying head is selected in each segment that performs both local-packet collecting and aggregated packets relaying. The simulation results have shown that the proposed CEPEC protocol provides higher throughput with guaranteed fairness in multihop data delivery in vehicular networks when compared with the purely IEEE 802.16-based protocol.

Task-based image annotation and retrieval

In order to address problems of information overload in digital imagery task domains we have developed an interactive approach to the capture and reuse of image context information. Our framework models different aspects of the relationship between images and domain tasks they support by monitoring the interactive manipulation and annotation of task-relevant imagery. The approach allows us to gauge a measure of a user's intentions as they complete goal-directed image tasks. As users analyze retrieved imagery their interactions are captured and an expert task context is dynamically constructed. This human expertise, proficiency, and knowledge can then be leveraged to support other users in carrying out similar domain tasks. We have applied our techniques to two multimedia retrieval applications for two different image domains, namely the geo-spatial and medical imagery domains. © Springer-Verlag Berlin Heidelberg 2007.

Manometry-Based Cough Identification Algorithm

Gastroesophageal reflux disease (GERD) is a common cause of chronic cough. For the diagnosis and treatment of GERD, it is desirable to quantify the temporal correlation between cough and reflux events. Cough episodes can be identified on esophageal manometric recordings as short-duration, rapid pressure rises. The present study aims at facilitating the detection of coughs by proposing an algorithm for the classification of cough events using manometric recordings. The algorithm detects cough episodes based on digital filtering, slope and amplitude analysis, and duration of the event. The algorithm has been tested on in vivo data acquired using a single-channel intra-esophageal manometric probe that comprises a miniature white-light interferometric fiber optic pressure sensor. Experimental results demonstrate the feasibility of using the proposed algorithm for identifying cough episodes based on real-time recordings using a single channel pressure catheter. The presented work can be integrated with commercial reflux pH/impedance probes to facilitate simultaneous 24-hour ambulatory monitoring of cough and reflux events, with the ultimate goal of quantifying the temporal correlation between the two types of events.

Neural Network Based Approach for Developing the Enterprise Strategy

Modern enterprises work in highly dynamic environment. Thus, the developing of company strategy is of crucial importance. It determines the surviving of the enterprise and its evolution. Adapting the desired management goal in accordance with the environment changes is a complex problem. In the present paper, an approach for solving this problem is suggested. It is based on predictive control philosophy. The enterprise is modelled as a cybernetic system and the future plant response is predicted by a neural network model. The predictions are passed to an optimization routine, which attempts to minimize the quadratic performance criterion.

Linked knowledge sources for topic classification of microposts:a semantic graph-based approach

Short text messages a.k.a Microposts (e.g. Tweets) have proven to be an effective channel for revealing information about trends and events, ranging from those related to Disaster (e.g. hurricane Sandy) to those related to Violence (e.g. Egyptian revolution). Being informed about such events as they occur could be extremely important to authorities and emergency professionals by allowing such parties to immediately respond. In this work we study the problem of topic classification (TC) of Microposts, which aims to automatically classify short messages based on the subject(s) discussed in them. The accurate TC of Microposts however is a challenging task since the limited number of tokens in a post often implies a lack of sufficient contextual information. In order to provide contextual information to Microposts, we present and evaluate several graph structures surrounding concepts present in linked knowledge sources (KSs). Traditional TC techniques enrich the content of Microposts with features extracted only from the Microposts content. In contrast our approach relies on the generation of different weighted semantic meta-graphs extracted from linked KSs. We introduce a new semantic graph, called category meta-graph. This novel meta-graph provides a more fine grained categorisation of concepts providing a set of novel semantic features. Our findings show that such category meta-graph features effectively improve the performance of a topic classifier of Microposts. Furthermore our goal is also to understand which semantic feature contributes to the performance of a topic classifier. For this reason we propose an approach for automatic estimation of accuracy loss of a topic classifier on new, unseen Microposts. We introduce and evaluate novel topic similarity measures, which capture the similarity between the KS documents and Microposts at a conceptual level, considering the enriched representation of these documents. Extensive evaluation in the context of Emergency Response (ER) and Violence Detection (VD) revealed that our approach outperforms previous approaches using single KS without linked data and Twitter data only up to 31.4% in terms of F1 measure. Our main findings indicate that the new category graph contains useful information for TC and achieves comparable results to previously used semantic graphs. Furthermore our results also indicate that the accuracy of a topic classifier can be accurately predicted using the enhanced text representation, outperforming previous approaches considering content-based similarity measures. © 2014 Elsevier B.V. All rights reserved.

An intervention encouraging planned self-regulation and goal setting in drivers across the lifespan:testing an extended theory of planned behaviour

Previous work has demonstrated that planning behaviours may be more adaptive than avoidance strategies in driving self-regulation, but ways of encouraging planning have not been investigated. The efficacy of an extended theory of planned behaviour (TPB) plus implementation intention based intervention to promote planning self-regulation in drivers across the lifespan was tested. An age stratified group of participants (N=81, aged 18-83 years) was randomly assigned to an experimental or control condition. The intervention prompted specific goal setting with action planning and barrier identification. Goal setting was carried out using an agreed behavioural contract. Baseline and follow-up measures of TPB variables, self-reported, driving self-regulation behaviours (avoidance and planning) and mobility goal achievements were collected using postal questionnaires. Like many previous efforts to change planned behaviour by changing its predictors using models of planned behaviour such as the TPB, results showed that the intervention did not significantly change any of the model components. However, more than 90% of participants achieved their primary driving goal, and self-regulation planning as measured on a self-regulation inventory was marginally improved. The study demonstrates the role of pre-decisional, or motivational components as contrasted with post-decisional goal enactment, and offers promise for the role of self-regulation planning and implementation intentions in assisting drivers in achieving their mobility goals and promoting safer driving across the lifespan, even in the context of unchanging beliefs such as perceived risk or driver anxiety.

Privacy and the City:user identification and location semantics in location-based social networks

With the advent of GPS enabled smartphones, an increasing number of users is actively sharing their location through a variety of applications and services. Along with the continuing growth of Location-Based Social Networks (LBSNs), security experts have increasingly warned the public of the dangers of exposing sensitive information such as personal location data. Most importantly, in addition to the geographical coordinates of the user’s location, LBSNs allow easy access to an additional set of characteristics of that location, such as the venue type or popularity. In this paper, we investigate the role of location semantics in the identification of LBSN users. We simulate a scenario in which the attacker’s goal is to reveal the identity of a set of LBSN users by observing their check-in activity. We then propose to answer the following question: what are the types of venues that a malicious user has to monitor to maximize the probability of success? Conversely, when should a user decide whether to make his/her check-in to a location public or not? We perform our study on more than 1 million check-ins distributed over 17 urban regions of the United States. Our analysis shows that different types of venues display different discriminative power in terms of user identity, with most of the venues in the “Residence” category providing the highest re-identification success across the urban regions. Interestingly, we also find that users with a high entropy of their check-ins distribution are not necessarily the hardest to identify, suggesting that it is the collective behaviour of the users’ population that determines the complexity of the identification task, rather than the individual behaviour.

Methodology for Creating of Objective and Balanced Linear Tests Based on the Item Response Theory

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

Does spatial locative comprehension predict landmark-based navigation?

In the present study we investigated the role of spatial locative comprehension in learning and retrieving pathways when landmarks were available and when they were absent in a sample of typically developing 6- to 11-year-old children. Our results show that the more proficient children are in understanding spatial locatives the more they are able to learn pathways, retrieve them after a delay and represent them on a map when landmarks are present in the environment. These findings suggest that spatial language is crucial when individuals rely on sequences of landmarks to drive their navigation towards a given goal but that it is not involved when navigational representations based on the geometrical shape of the environment or the coding of body movements are sufficient for memorizing and recalling short pathways.

Goal orientation and its relationship to the business family, and family business performance, within the UK’s family owned and managed mid-sized businesses

Mid-Sized Businesses (MSBs) are defined by the Department for Business, Innovation and Skills (BIS) as having a sales turnover of between £25 million and £500 million. A key gap in family firm/business research and literature to date is, understanding the role and importance of non-financial objectives (such as family harmony, tradition and business longevity), and the role the family plays in creating a wide set of business performance objectives (both financial and non-financial) in these businesses. This dissertation contributes to filling this knowledge gap by drawing on Family Systems Theory applied in a business context, and within an overarching Resource Based View (RBV) of the firm.

Computational model of bladder tissue based on its measured optical properties

Urinary bladder diseases are a common problem throughout the world and often difficult to accurately diagnose. Furthermore, they pose a heavy financial burden on health services. Urinary bladder tissue from male pigs was spectrophotometrically measured and the resulting data used to calculate the absorption, transmission, and reflectance parameters, along with the derived coefficients of scattering and absorption. These were employed to create a "generic" computational bladder model based on optical properties, simulating the propagation of photons through the tissue at different wavelengths. Using the Monte-Carlo method and fluorescence spectra of UV and blue excited wavelength, diagnostically important biomarkers were modeled. Additionally, the multifunctional noninvasive diagnostics system "LAKK-M" was used to gather fluorescence data to further provide essential comparisons. The ultimate goal of the study was to successfully simulate the effects of varying excited radiation wavelengths on bladder tissue to determine the effectiveness of photonics diagnostic devices. With increased accuracy, this model could be used to reliably aid in differentiating healthy and pathological tissues within the bladder and potentially other hollow organs.

Szolgálatosodás Nyugat-Európában és Magyarországon. Hol tartunk és merre haladunk? – Egy nemzetközi felmérés nyomán (Servitization in Western Europe and Hungary – Based on an international survey)

A szerző tanulmányában nyugat-európai és magyarországi termelővállalatok szolgálatosodását vizsgálta. A cél a szolgálatosodás mértékének és megtérülésének elemzése volt. A vizsgálatokat az IMSS kérdőíves felmérés adatain végezte el, stratégiai, operatív és eredményességi dimenziók mentén. Munkájában nemcsak Nyugat-Európa és Magyarország vállalatainak szolgálatosodásáról ad képet külön-külön, hanem az adatok közvetlen összehasonlításával megbízható összehasonlító elemzést is végzett a két térség között, melyet a tanulmány legfőbb hozzáadott értékének tekint. Nyugat-Európában a szolgáltatások kiemelkednek a versenycélok közül, míg Magyarországon gyenge helyezést érnek el a stratégiai prioritási sorrendben. Működési szinten mindkét helyen átlagosnak mondható a szolgáltatások nyújtását támogató akcióprogramokba fektetett erőfeszítés nagysága. Ez azonban nem feltétlenül mond ellent a stratégiai szintnek Nyugat-Európában, hiszen az is mondható, hogy a szolgáltatásokkal kapcsolatos programok nem zárják ki azt, hogy más területen is fejlesszenek (pl. lean programok). Az eredmények mindkét térségben a szolgálatosodás paradoxonát mutatják. ______ The paper focuses on the servitization of manufacturing companies in Western Europe and Hungary. The author's goal was to analyse the degree and the returns of servitization. The investigations were conducted using data of the IMSS, considering the dimensions of strategy, operations and returns. Besides giving a picture of the servitization of Western European and Hungarian companies, the paper also offers a reliable comparative analysis between the two regions, which can be considered as main value added of the paper. Services are among the most important competitive goals in Western Europe, but have a low ranking in Hungary. Regarding the operational level, programs supporting the offering of services are in the average in both places. This does not necessarily contradict the high strategic level in Western Europe, because we can say that programs related to servitization do not rule out improvement initiatives in other areas (e. g. lean programs). The service paradox is experienced in both territories.