Miracle-dz/UniFAR-FTUs huggingface dataset:
Proceedings of the 4th Nordic conference on Human-computer interaction: changing roles

NordiCHI is the main forum for human-computer interaction research in the Nordic countries. It is a biannual conference, and the three first conferences were held in Stockholm (2000), Arhus (2002) and Tampere (2004), respectively. This year's conference is held in Oslo and is hosted by the Norwegian Computing Society (NCS). It is a joint effort ("dugnad"), joining together a large portion of the Norwegian HCI community in academia, research and industry. Each fall for the last 8 years NCS has arranged a two-day conference on usability, user experience and documentation called Yggdrasil. NordiCHI incorporates this year's Yggdrasil conference. The most visible result of this is that NordiCHI 2006 has defined Industrial Experience Reports as a new contribution category.The main theme for this year's conference is "Changing roles". We currently see a reshaping of almost every aspect of society, which is caused by the forces of globalization and innovative uses of personal technologies in the networked society. Do we need to change our roles as developers, researchers and designers? How can we maintain focus on the user in this rapidly changing environment? Will the role of HCI change? The broad call for participation elicited excellent response in the HCI community, and we are happy to provide a high-quality technical program that combines the best of the Nordic tradition with emerging trends in interaction techniques and new approaches to study human-computer interaction. The technical program combines four different categories of submissions: Long papers, short papers, industrial experience reports and interactive events (demonstrations). We received 134 long papers, 123 short papers and 16 industrial experience reports. An international committee, totalling 98 reviewers, helped in the selection process. Each submission received at least 3 reviews. In the end we accepted 37 long papers, 28 short papers (18 for plenum presentation and 10 posters) and 8 industrial experience reports. The proceeding also includes documentation of interactive events. The acceptance rate for long papers was 28% and 23% for short papers. The submitted long papers represent 21 countries and the accepted papers came from 11 countries (about half of these from countries outside the Nordic region), and distributed as follows:Austria: 2Canada: 2Denmark: 3Finland: 3Germany: 2Iceland: 1Italy: 2Norway: 2Sweden: 8UK: 8USA: 4
Inside the Interrogation Room

This article takes the reader inside the interrogation room in order to analyze the characteristics, context and outcome of police interrogation practices in America. This study is the first in over twenty-five years to examine routine police interrogation practices in America through field research. The data is based on nine months of observation in a major, urban police department involving 122 interrogations and 45 detectives. It also relies on 60 videotaped custodial interrogations from two additional police departments. The article attempts to fill in the gap left by criminal interrogation scholars who have failed to employ empirical research on police interrogation practices in their studies. The article asserts that the techniques that Miranda was designed to address, such as undermining suspects' confidence in their denials and confronting suspects with fabricated evidence of their guilt, continue to be used in contemporary American police interrogations. It also suggests that interrogators have become increasingly successful at eliciting incriminating information from custodial suspects in the last thirty years. These findings confirm that interrogation methods exert a fateful effect on criminal cases at every subsequent stage in the criminal justice system.
HOW TO DISPLAY DATA BADLY

Methods for displaying data badly have been under development for many years, and a wide variety of interesting and inventive schemes have emerged. Presented here is a synthesis yielding the twelve most powerful techniques that seem to underlie many of the realizations found in the literature. These twelve (the dirty dozen) are identified and illustrated.
On time alignment and metric algorithms for speech recognition

An algorithm for comparing speech waveforms to decide if the spoken utterance is part of a given vocabulary of word waveforms or not, and if it is part of the vocabulary, to choose the matching word is presented. Our algorithm has been implemented in connection with our own vector interpolation alignment algorithm which is faster than dynamic time warping and yet as accurate as dynamic time warping. This vector interpolation, has a classification rate comparable to that of dynamic time warping. While vector interpolation is able to match dynamic time warping for recognition accuracy, it requires significantly less computation, making it much faster than DTW based algorithms. Both algorithms are presented and a comparison of the two is made. Also an alternative algorithm, where the number of intervals of the two utterances to be compared is the same, where the length of the intervals in one utterance is different than the length of the intervals in the other utterance, has been investigated. When appropriate adjustments are made so that the beginning and end of the two utterances match, this algorithm has a classification rate comparable to that of dynamic time warping. Furthermore an alternative to LPC analysis for utterance recognition is presented. Unlike LPC which is an extrapolation algorithm, our algorithm is an interpolation algorithm. Theoretically our algorithm has smaller variance and smaller mean square error than the LPC algorithm. Preliminary results show that our algorithm provides high probability of correct classification.
Using Evolutionary Algorithms for Optimization of Analogue Electronic Filters

During several recent years, the performance of computer technology increased enough to enable the using of numerical methods in various branches more commonly then in the past when mainly analytical methods were used. Numerical methods are utilized both in a design and in optimization of various systems. One of the advantages of numerical methods is the possibility of meeting more requirements – they are able to solve multi-objective (multi-criteria) tasks. Of course, numerical methods are applied also in electronics while designing electronic circuits. Thanks to these methods, circuits can be designed with more aspect taken into account. The aspects are, naturally, primarily main circuit requirements, e.g., a magnitude frequency response, then other various features, e.g., a group delay frequency response, a dynamic range, consumption etc. However, in addition, also the parameters of used components – the tolerance and spread of their values, their real features, circuit characteristic sensitivities to their values, and so on – can be taken into consideration. If an analytical method shall be applied to satisfy so many requirements, the circuit design would become either unfeasible or so complicated that it would be unsuccessful or inaccurate. However, numerical methods are able to operate even with a low or at least acceptable complicacy rate. On the other hand, numerical methods have disadvantages as well. One of the most significant is a higher time consumption to obtain a result compared to analytical methods. Nevertheless, this is not such a problem mostly.
Predictive control of teleoperated constrained systems with unbounded communication delays

We present a control technique which allows the teleoperation of systems subject to input/state constraints through transmission channels with unbounded time-delays, such as Internet TCP/IP connections. The main idea is based on the fact that predictive controllers provide, as a by-product, command sequences which can be executed as emergency maneuvers whenever the communication channel is broken by excessive time-delays. We show how this idea can be exploited by equipping the predictive controller with some additional control logic which enables the synchronization between plant, predictive controller, and human operator.
Implementing mental health economic evaluation evidence: Building a bridge between theory and practice

Background: Interest in economic evaluation to support strategic decision-making for mental health policy has increased, but the capacity for such analysis remains limited. Aims: To reflect on challenges faced in the production of economic evaluations and the extent to which they are used for mental health policy across Europe. Method: A bespoke questionnaire and literature review were used to collect information on the use of economic evaluation in 17 European countries. Results: The number of evaluations for mental health continues to grow; albeit their quality is patchy. Most concentrate on medications; there are few evaluations outside the health and social care sector. Simple cost-effectiveness analyses dominate, with much less use of cost-utility or cost-benefit analysis. Few have been subject to economic evaluation as part of reimbursement procedures for new drugs and other interventions. Conclusions: There is much scope for practical and methodological development, in particular on outcome measurement and the evaluation of complex non-health system interventions. The variable quality of evaluations suggests that work to build capacity for both their conduct and interpretation is needed. Initiatives such as MHEEN might help promote understanding of the potentially powerful role that can be played by economic evaluation. Declaration of interest: The Mental Health Economics European Network Phase I was supported by a grant (SPC.2002397) from the European Commission, Health and Consumer Protection Directorate. There are no conflicts of interest.
COMPUTER ANALYSIS OF THREE-FACTOR INTERACTIONS IN CONTINGENCY TABLES

Abstract : Numerous methods have been proposed for testing the hypothesis of zero three-factor interaction in contingency tables. These methods are incorporated into a single computer program which is designed to calculate the test statistic by any or all of the proposed techniques, and which also provides estimators of the interactions and corresponding two-sided confidence intervals. The program is written in FORTRAN 63 for the CDC-3600 computer, and will analyze interactions in contingency tables of dimensions 2 r 5, 2 s 5, 2 t 16, for r s t.
Variability analysis of discrete event series and wavefront patterns in surface electrocardiogram: contributions to psychophysiological and clinical research

The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.
Hierarchic Normal Forms for Desynchronization

Based on an earlier work, we present an in-depth discussion of the relationsh- ips between synchrony and asynchrony. Simple models of both paradigms are presented, and we state theorems which guarantee correct desynchronization- , meaning that the original synchronous semantics can be reconstructed from the result of this desynchronization. This theory can be used as a basis for correct distributed code generation. The present paper presents a new data structure, the hierarchic normal form for a transition relation, which is instrumental in implementing this theory. We illustrate this on a example. The whole approach is implemented in the Signal compiler.
HoloVision: a software package for reconstruction and analysis of digitally sampled holograms

HoloVision is a software package for performing digital holography on the Microsoft Windows platform. Basic theory for reconstruction of digitally sampled holograms is presented along with some more specific software implementation details. This includes the Fresnel method, the Convolution method and the Fourier method. A method involving a tilt of the reference wave and magnification through a numerical lens is presented to enlarge the visible region of the reconstructed image. Two different approaches for suppressing the undesired zero-order components are investigated. Examples are included for ordinary intensity images as well as for phase difference images from digital holographic interferometry.
Cutaneous lesions and visceral involvement of tuberous sclerosis: First report in North of Iran

Abstract Tuberous sclerosis (TS) is an autosomal dominant disorder with a significant range of clinical expressions. The involvement of vital organs, such as the brain, kidney, heart and lung is the main cause of death in patients with TS. The aim of this study is to summarize the characteristic cutaneous features and common extracutaneous involvement of TS, which are helpful to the early detection of visceral involvement. The analyzed clinical data from 10 patients with TS included those from detailed history, physical and dermatological examination, cranial computed tomography and magnetic resonance imaging, abdominal ultrasonography, chest roentgenography, and ophthalmologic examination. The skin, brain and electroencephalography were involved frequently in TS patients. Hypomelanotic macules were the most common and earliest cutaneous lesions. There were two facial angiofibromas and no Shagreen's patch in our patients. Cranial computed tomography showed a high positive rate including periventricular and Monro foramen calcification in TS patients. Hypsarrhythmia was the most common abnormality on electroencephalography background. Cutaneous features of TS are helpful in the early diagnosis of the disease. Hypomelanotic macules are especially important for patients with epilepsy or babies whose number of hypomelanotic macules is more than three. Cranial computed tomography is of great value in the diagnosis of TS. The involvement of visceral organs such as the brain and kidney should be considered in TS patients.
Comparing Propensity Score Methodologies for Analyzing High School Class Assignment

Students’ class assignment is extremely relevant to their academic achievement, but the problem of assigning a student to the correct classroom is difficult to assess. For example, it may not be readily clear whether a student should be placed in remedial, regular, or advanced math classes, but it could greatly affect how well a student does in school. Maybe a remedial-level student is placed in a regular-level class and does poorly as a result; or maybe an advanced-level student is placed in a regular-level class and doesn’t do as well as they could. How can we determine the classes that students should be assigned to? This is the question we will try to answer; and we will see that, as a result, we will have to thoroughly evaluate several statistical techniques in order to properly answer this question.
Spatial Temporal based Classification for Antebrachium and Carpus Movement of EEG Data Using Emotive Head set

Electroencephalographic (EEG) signals from test subjects are used for BCI analysis and classification of the four upper limb movements. Brain computer interface (BCI) system provides better neural control to the user, over two antebrachium and two carpus movement. This paper uses Epoc Emotiv head set with fourteen electrodes to acquire signal from the motor area of scalp. A particular protocol for data acquisition is followed. Our method is based on the time domain feature extraction techniques. Activity feature is applied on the signals. In order to discriminate between four upper limb movements within the data set, the paper uses Quadratic support vector machine, RBF SVM and Multilayer perceptron. The best classification accuracy of two antebrachium and two carpus movement is achieved by Quadratic SVM and RBF SVM when Gaussian window is used to calculate the activity feature vector. The number of correctly classified instants in term of percentage is 76.92% and 75.96% for quadratic SVM and RBF SVM. Current classifiers show promising results, where as to make conclusion more generalized and to enhance the classification accuracy, further experiments need to be carried out.
Automated skin lesion segmentation of dermoscopic images using GrabCut and k-means algorithms

Skin cancer is the most common type of cancer in the world and the incidents of skin cancer have been rising over the past decade. Even with a dermoscopic imaging system, which magnifies the lesion region, detecting and classifying skin lesions by visual examination is laborious due to the complex structures of the lesions. This necessitates the need for an automated skin lesion diagnosis system to enhance the diagnostic capability of dermatologists. In this study, the authors propose an automatic skin lesion segmentation method which can be used as a preliminary step for lesion classification. The proposed method comprises two major steps, namely preprocessing and segmentation. In the preprocessing step, noise such as illumination, hair and rulers are removed using filtering techniques and in the segmentation phase, skin lesions are segmented using the GrabCut segmentation algorithm. The k-means clustering algorithm is then used along with the colour features learnt from the training images to improve the boundaries of the segments. To evaluate the authors' proposed method, they have used ISIC 2017 challenge dataset and PH 2 dataset. They have obtained Dice coefficient values of 0.8236 and 0.9139 for ISIC 2017 test dataset and PH 2 dataset, respectively.
SKEPRID

Currently, the surveillance camera-based person re-identification is still challenging because of diverse factors such as people’s changing poses and various illumination. The various poses make it hard to conduct feature matching across images, and the illumination changes make color-based features unreliable. In this article, we present SKEPRID,1 a skeleton-based person re-identification method that handles strong pose and illumination changes jointly. To reduce the impacts of pose changes on re-identification, we estimate the joints’ positions of a person based on the deep learning technique and thus make it possible to extract features on specific body parts with high accuracy. Based on the skeleton information, we design a set of local color comparison-based cloth-type features, which are resistant to various lighting conditions. Moreover, to better evaluate SKEPRID, we build the PO8LI2 dataset, which has large pose and illumination diversity. Our experimental results show that SKEPRID outperforms state-of-the-art approaches in the case of strong pose and illumination variation.
Ergodic Capacity and SNR Analysis for Dual Hop Amplify and Forward Cooperative Communication Systems Over <inline-formula><tex-math notation="LaTeX">$\alpha$</tex-math></inline-formula><inline-formula><tex-math notation="LaTeX">$-$</tex-math></inline-formula><inline-formula><tex-math notation="LaTeX

Dual-hop communication systems are known to extend coverage and reduce transmit power in scenarios where one-hop communication is not possible. The <inline-formula><tex-math notation="LaTeX">$\alpha -\eta -\mu$</tex-math></inline-formula> fading distribution is a general fading distribution that can be reduced to other fading distributions like Rayleigh, Nakagami-<inline-formula><tex-math notation="LaTeX">$m$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$\alpha$</tex-math></inline-formula>-<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>, and <inline-formula><tex-math notation="LaTeX">$\eta$</tex-math></inline-formula>-<inline-formula><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>. In this paper, we study the statistics of the end-to-end signal to noise ratio (SNR) of a dual-hop amplify and forward system with semi-blind relay over independent but not necessarily identical <inline-formula><tex-math notation="LaTeX">$\alpha -\eta -\mu$</tex-math></inline-formula> fading channels. Specifically, we derive an expression for the <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula>th moment of the end-to-end SNR. The derived expression is then utilized to find the average value, the amount of fading, and the ergodic capacity of the end-to-end SNR. Numerical results are provided and compared to simulations to validate the derived expressions.
Atomicity and Non-Anonymity in Population-Like Games for the Energy Efficiency of Hybrid-Power HetNets

In this paper, the user–base station association problem is addressed to reduce grid consumption in heterogeneous cellular networks powered by hybrid energy sources (grid and renewable energy). This paper proposes a novel distributed control scheme inspired by population games and designed considering both atomicity and non-anonymity, i.e., describing the individual decisions of each agent. The controller performance is considered from an energy-efficiency perspective, which requires the guarantee of appropriate quality-of-service levels according to renewable energy availability. The efficiency of the proposed scheme is compared with other heuristic and optimal alternatives in two simulation scenarios. Simulation results show that the proposed approach inspired by population games reduces grid consumption by 12% when compared to the traditional best-signal-level association policy.