Handwriting in Forensic Investigations

The process of automatic handwriting investigation in forensic science is described. The general scheme of a computer-based handwriting analysis system is used to point out at the basic problems of image enhancement and segmentation, feature extraction and decision-making. Factors that may compromise the accuracy of expert’s conclusion are underlined and directions for future investigations are marked.

Analogical Reasoning Techniques in Intelligent Counterterrorism Systems

The paper develops a set of ideas and techniques supporting analogical reasoning throughout the life-cycle of terrorist acts. Implementation of these ideas and techniques can enhance the intellectual level of computer-based systems for a wide range of personnel dealing with various aspects of the problem of terrorism and its effects. The method combines techniques of structure-sensitive distributed representations in the framework of Associative-Projective Neural Networks, and knowledge obtained through the progress in analogical reasoning, in particular the Structure Mapping Theory. The impact of these analogical reasoning tools on the efforts to minimize the effects of terrorist acts on civilian population is expected by facilitating knowledge acquisition and formation of terrorism-related knowledge bases, as well as supporting the processes of analysis, decision making, and reasoning with those knowledge bases for users at various levels of expertise before, during, and after terrorist acts.

Интегрированный Моделирующий Комплекс Поддержки Принятия Решений в Комплексной Корпоративной Системе Управления Магистральной Газотранспортной Сетью

The approach to construction, structuring class of tasks, technology of the use and stages of modernization systems support of decision-making in composition the operative-dispatch control computer-based system by the gas-transport system of Ukraine is considered.

An Approach to Variable Aggregation in Efficiency Analysis

In the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.

The challenges of developing an online tool to measure the quality of the passenger experience in a PanEuropean context

METPEX is a 3 year, FP7 project which aims to develop a PanEuropean tool to measure the quality of the passenger's experience of multimodal transport. Initial work has led to the development of a comprehensive set of variables relating to different passenger groups, forms of transport and journey stages. This paper addresses the main challenges in transforming the variables into usable, accessible computer based tools allowing for the real time collection of information, across multiple journey stages in different EU countries. Non-computer based measurement instruments will be used to gather information from those who may not have or be familiar with mobile technology. Smartphone-based measurement instruments will also be used, hosted in two applications. The mobile applications need to be easy to use, configurable and adaptable according to the context of use. They should also be inherently interesting and rewarding for the participant, whilst allowing for the collection of high quality, valid and reliable data from all journey types and stages (from planning, through to entry into and egress from different transport modes, travel on public and personal vehicles and support of active forms of transport (e.g. cycling and walking). During all phases of the data collection and processing, the privacy of the participant is highly regarded and is ensured. © 2014 Springer International Publishing.

Application of ensemble averaging to the analysis of electromyography recordings under whole body vibratory stimulation

The aim of this study is to evaluate the application of ensemble averaging to the analysis of electromyography recordings under whole body vibratory stimulation. Recordings from Rectus Femoris, collected during vibratory stimulation at different frequencies, are used. Each signal is subdivided in intervals, which time duration is related to the vibration frequency. Finally the average of the segmented intervals is performed. By using this method for the majority of the recordings the periodic components emerge. The autocorrelation of few seconds of signals confirms the presence of a pseudosinusoidal components strictly related to the soft tissues oscillations caused by the mechanical waves. © 2014 IEEE.

Understanding Computing through Defining its Lexicon

Бойко Банчев - Понятието пресмятане в широкия му смисъл и неговото присъствие в природата, науката, технологията и други области е свързано с редица неизяснени въпроси. Дори в по-тесните рамки на програмирането и използването на компютри то не е адекватно разбрано. Представяме тезата, че един начин за приближаване към такова разбиране е разкриването на дълбинните структури и отношения, свързани с пресмятането, и на тази основа построяване на речник на пресмятането.

Компютърна система за обучение по програмиране

Hristo Krushkov, Mariana Krushkova, Victor Atanasov, Margarita Krushkova - The rising of the Bulgarian Higher educational standard is one of the strategic purposes of our country as a member of the European family. The implementation of new scientific methods and modern technological means in the process of education is a precondition for fulfilling this purpose. The study of informatics is making a significant contribution to the creation of a knowledge-based economy. In view of this the informatics has been studied in several departments of the Plovdiv University “Paisii Hilendarski”. However, due to different reasons the majority of the students have difficulties in mastering this discipline. The present report offers an architecture of computer-based system for helping the whole process of education in informatics.

Mobility changes in older age: neuropsychological, neurophysiological and cognitive predictors of successful adaptation in a real world scenario

The aims of this thesis were to investigate the neuropsychological, neurophysiological, and cognitive contributors to mobility changes with increasing age. In a series of studies with adults aged 45-88 years, unsafe pedestrian behaviour and falls were investigated in relation to i) cognitive functions (including response time variability, executive function, and visual attention tests), ii) mobility assessments (including gait and balance and using motion capture cameras), iii) motor initiation and pedestrian road crossing behavior (using a simulated pedestrian road scene), iv) neuronal and functional brain changes (using a computer based crossing task with magnetoencephalography), and v) quality of life questionnaires (including fear of falling and restricted range of travel). Older adults are more likely to be fatally injured at the far-side of the road compared to the near-side of the road, however, the underlying mobility and cognitive processes related to lane-specific (i.e. near-side or far-side) pedestrian crossing errors in older adults is currently unknown. The first study explored cognitive, motor initiation, and mobility predictors of unsafe pedestrian crossing behaviours. The purpose of the first study (Chapter 2) was to determine whether collisions at the near-side and far-side would be differentially predicted by mobility indices (such as walking speed and postural sway), motor initiation, and cognitive function (including spatial planning, visual attention, and within participant variability) with increasing age. The results suggest that near-side unsafe pedestrian crossing errors are related to processing speed, whereas far-side errors are related to spatial planning difficulties. Both near-side and far-side crossing errors were related to walking speed and motor initiation measures (specifically motor initiation variability). The salient mobility predictors of unsafe pedestrian crossings determined in the above study were examined in Chapter 3 in conjunction with the presence of a history of falls. The purpose of this study was to determine the extent to which walking speed (indicated as a salient predictor of unsafe crossings and start-up delay in Chapter 2), and previous falls can be predicted and explained by age-related changes in mobility and cognitive function changes (specifically within participant variability and spatial ability). 53.2% of walking speed variance was found to be predicted by self-rated mobility score, sit-to-stand time, motor initiation, and within participant variability. Although a significant model was not found to predict fall history variance, postural sway and attentional set shifting ability was found to be strongly related to the occurrence of falls within the last year. Next in Chapter 4, unsafe pedestrian crossing behaviour and pedestrian predictors (both mobility and cognitive measures) from Chapter 2 were explored in terms of increasing hemispheric laterality of attentional functions and inter-hemispheric oscillatory beta power changes associated with increasing age. Elevated beta (15-35 Hz) power in the motor cortex prior to movement, and reduced beta power post-movement has been linked to age-related changes in mobility. In addition, increasing recruitment of both hemispheres has been shown to occur and be beneficial to perform similarly to younger adults in cognitive tasks (Cabeza, Anderson, Locantore, & McIntosh, 2002). It has been hypothesised that changes in hemispheric neural beta power may explain the presence of more pedestrian errors at the farside of the road in older adults. The purpose of the study was to determine whether changes in age-related cortical oscillatory beta power and hemispheric laterality are linked to unsafe pedestrian behaviour in older adults. Results indicated that pedestrian errors at the near-side are linked to hemispheric bilateralisation, and neural overcompensation post-movement, 4 whereas far-side unsafe errors are linked to not employing neural compensation methods (hemispheric bilateralisation). Finally, in Chapter 5, fear of falling, life space mobility, and quality of life in old age were examined to determine their relationships with cognition, mobility (including fall history and pedestrian behaviour), and motor initiation. In addition to death and injury, mobility decline (such as pedestrian errors in Chapter 2, and falls in Chapter 3) and cognition can negatively affect quality of life and result in activity avoidance. Further, number of falls in Chapter 3 was not significantly linked to mobility and cognition alone, and may be further explained by a fear of falling. The objective of the above study (Study 2, Chapter 3) was to determine the role of mobility and cognition on fear of falling and life space mobility, and the impact on quality of life measures. Results indicated that missing safe pedestrian crossing gaps (potentially indicating crossing anxiety) and mobility decline were consistent predictors of fear of falling, reduced life space mobility, and quality of life variance. Social community (total number of close family and friends) was also linked to life space mobility and quality of life. Lower cognitive functions (particularly processing speed and reaction time) were found to predict variance in fear of falling and quality of life in old age. Overall, the findings indicated that mobility decline (particularly walking speed or walking difficulty), processing speed, and intra-individual variability in attention (including motor initiation variability) are salient predictors of participant safety (mainly pedestrian crossing errors) and wellbeing with increasing age. More research is required to produce a significant model to explain the number of falls.

eBEST platform a KKV-klaszterek operatív és együttműködési folyamatainak támogatására (eBEST platform for supporting operational and cooperative processes of SME's clusters)

Az Európai Bizottság jelentése szerint a magyar kis- és középvállalkozások helyzete 2005 óta stagnál. Bár ezek a vállalkozások adják a magyar vállalkozások 99%-át, mégis a közbeszerzési, valamint a növekvő piacokhoz való hozzáférés terén számos akadállyal kerülnek szembe. Az eBEST projekten (Empowering Business Ecosystems of Small Service Enterprises to Face the Economic Crisis) belül kialakított platform olyan funkcionalitással bír, ami mindamellett, hogy lehetővé teszi a vállalkozások szervezett csoportokba, azaz ökoszisztémákba rendeződését, hozzá tud járulni a fogyasztói igények kielégítése érdekében létrejövő ellátási lánc, illetve egyedi folyamatok mentén fellépő információszerzési, kommunikációs vagy együttműködési akadályok lebontásához. ____ It is widely recognised that the most important factor for increasing the productivity of small companies is a deep adoption of computer-based applications and services. The FP7 SME eBEST project proposed a new operational environment specifically conceived for net worked small companies, supported by an advanced suite of ICT services, the eBEST platform. The paper aims at presenting the projects achievements that are validated by a number of company clusters of different EU countries and industry sectors. The general objectives of the eBEST project are attracting customers to work with the clustered companies, facilitating companies to collaborate with each other, and enabling associations to foster the devised innovation.

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

Educating Parents on the Accelerated Reading Program

The Accelerated Reader Program was developed by Paul, VanderZee, Rue and Swanson at the Institute for Academic Excellence. The intention was to provide a computer-based reading program that would be recreational for students and that would provide information to teachers about the students. The majority of the research conducted to date targets the use of the program within the classroom. Results of the program only mention the participation of parents in the program as merely being informed of its existence. Parents are not necessarily included as active players in the daily routines. In fact, it is the lack of research found on the relationship between parent participation and student reading success and reading motivation that fueled the direction of this research. Thus, it created the perfect scenario to investigate the possible connection between parental involvement practices and the success of the Accelerated Reader Program.

Technology Integration and School Leadership

The No Child Left Behind Act of 2001 (NCLB) brought many significant changes to American schools including accessibility to technology. Through an extensive literature review of the relationship between technology leadership and student achievement, five major themes emerged from data that support the need for more effective computer-based education in schools.

Atividade eletroencefalográfica de pacientes com acidente vascular cerebral na aprendizagem motora de um jogo baseado em realidade virtual

Stroke is the leading cause of long-term disability among adults and motor relearning is essential in motor sequelae recovery. Therefore, various techniques have been proposed to achieve this end, among them Virtual Reality. The aim of the study was to evaluate electroencephalographic activity of stroke patients in motor learning of a virtual reality-based game. The study included 10 patients with chronic stroke, right-hande; 5 with left brain injury (LP), mean age 48.8 years (± 4.76) and 5 with injury to the right (RP), mean age 52 years (± 10.93). Participants were evaluated for electroencephalographic (EEG) activity and performance while performing 15 repetitions of darts game in XBOX Kinect and also through the NIHSS, MMSE, Fugl-Meyer and the modified Ashworth scale. Patients underwent a trainning with 45 repetitions of virtual darts game, 12 sessions in four weeks. After training, patients underwent reassessment of EEG activity and performance in virtual game of darts (retention). Data were analyzed using ANOVA for repeated measures. According to the results, there were differences between the groups (PD and PE) in frequencies Low Alpha (p = 0.0001), High Alpha (p = 0.0001) and Beta (p = 0.0001). There was an increase in alpha activation powers and a decrease in beta in the phase retention of RP group. In LP group was observed increased alpha activation potency, but without decrease in beta activation. Considering the asymmetry score, RP group increased brain activation in the left hemisphere with the practice in the frontal areas, however, LP group had increased activation of the right hemisphere in fronto-central areas, temporal and parietal. As for performance, it was observed a decrease in absolute error in the game for RP group between assessment and retention (p = 0.015), but this difference was not observed for LP group (p = 0.135). It follows then that the right brain injury patients benefited more from darts game training in the virtual environment with respect to the motor learning process, reducing neural effort in ipsilesionais areas and errors with the practice of the task. In contrast, patients with lesions in left hemisphere decrease neural effort in contralesionais areas important for motor learning and showed no performance improvements with practice of 12 sessions of virtual dart game. Thus, the RV can be used in rehabilitation of stroke patients upper limb, but the laterality of the injury should be considered in programming the motor learning protocol.

Predictive Risk Modelling for Integrated Care: a Structured Review

If patients at risk of admission or readmission to hospital or other forms of care could be identified and offered suitable early interventions then their lives and long-term health may be improved by reducing the chances of future admission or readmission to care, and hopefully, their cost of care reduced. Considerable work has been carried out in this subject area especially in the USA and the UK. This has led for instance to the development of tools such as PARR, PARR-30, and the Combined Predictive Model for prediction of emergency readmission or admission to acute care. Here we perform a structured review the academic and grey literature on predictive risk tools for social care utilisation, as well as admission and readmission to general hospitals and psychiatric hospitals. This is the first phase of a project in partnership with Docobo Ltd and funded by Innovate UK,in which we seek to develop novel predictive risk tools and dashboards to assist commissioners in Clinical Commissioning Groups with the triangulation of the intelligence available from routinely collected data to optimise integrated care and better understand the complex needs of individuals.