Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving the quality of the police interview: Can training in the use of cognitive techniques help?

Previous research on the Cognitive Interview (CI) has suggested that it is an effective procedure to use when interviewing witnesses. Much of the research however, has used college students as interviewers and provided little information about the quality of training. The aim of this research was to pilot a CI training procedure using thirty‐eight British police officers with varying levels of field experience. An armed robbery was staged and interviews were conducted with witnesses. Analysis of results did not reveal any differences in witness performance with the CI as compared to a control technique. Feedback from interviewers and a study of interview transcripts suggested that the CI training (which had been successful in previous studies) had little impact on the interviewing style of these experienced officers and that the CI techniques were not used appropriately. The implications of these results for police training in the CI are discussed.
Personality Traits and Social Inequality

During many decades, sociologists have downplayed the role that personality traits play in shaping individual’s lives. However, recent studies, mostly in economics, have shown the influence of these traits on a several educational and occupational outcomes. This thesis is an attempt to shed more light on this topic. By using longitudinal data from the German Socio-Economic Panel, it first investigates how the Big Five personality traits affect two important labor market outcomes: unemployment incidence and job mobility. The results from these first two articles show two things. First, personality traits contribute importantly to processes of job mobility and job loss. Second, models including personality traits fit better compare to models that exclude them. Additionally, the inclusion of personality traits also improves our understanding of the underlying process in the labor market. The second part of this thesis focuses on how personality traits are transmitted from parents to their children. My results show that socialization processes are extremely important in the transmission and development of personality traits. Higher educated parents are more successful in promoting socially desirable and success-enhancing traits than lower educated ones. While there is a direct influence of the parent’s education on the development of children’s personality traits, the effect is mediated by different childrearing practices and by the use of external daycare.
Some remarks about OO teaching

This paper summarizes experiences gained with OO teaching for several years at the Warsaw University. We start with description of students being taught and the impact of their skills and motivation on the chosen teaching approach. Then we sketch the adopted teaching program. Finally we discuss how the teaching may be improved by using modern teaching tools like the Moodle system.
Bio-Inspired Pedestrian Detection and Tracking

Pedestrian detection and tracking remains a popular issue in computer vision, spawning many applications in robotics, surveillance and security, biometrics and human- computer interaction. In this paper we present a biological framework for detecting and tracking pedestrians by using a monocular moving camera. This framework is based on visual cortex cells, namely complex and end-stopped cells, the last being used to extract keypoints. By employing a modified HOG descriptor combined with the responses of complex cells and a linear SVM, pedestrians can be detected. By combining the above information with keypoints, motion information and tracked features, persons can be tracked in complex scenarios where partial occlusions exist. This paper presents an extension of a biologically inspired model based on cortical cells to pedestrian detection and tracking in crowded environments with partial occlusions and using a moving camera. The model employs responses of cortical complex cells as HOG-like descriptors to code a pedestrian's shape, within a detection window to be classified as either pedestrian or non-pedestrian with a linear SVM. After detection, the detection window and features (keypoints) from detected pedestrians are tracked using the camera's and keypoints' motions during a few frames. This two-step process helps to reduce the tracking problems due to classification errors of the classifier, and alleviates the computational burden of detecting pedestrians in every frame, speeding up the overall process. The proposed method was trained and evaluated on the well-known INRIA pedestrian dataset (3), and compared to Dalal and Triggs' popular HOG-based pedestrian detector for performance comparison. The main contribution of the paper is the bio-inspired model, i.e., the model for the detection and tracking of pedestrian in crowded environments.
A Multi-Cell MMSE Detector for Massive MIMO Systems and New Large System Analysis

In this paper, a new multi-cell MMSE detector is proposed for massive MIMO systems. Let K and B denote the number of users in each cell and the number of available pilot sequences in the network, respectively, with B = βK, where β ≥ 1 is called the pilot reuse factor. The novelty of the multi-cell MMSE detector is that it utilizes all B channel directions that can be estimated locally at a base station, so that intra-cell interference, parts of the inter-cell interference and the noise can all be actively suppressed, while conventional detectors only use the K intra-cell channels. Furthermore, in the large- system limit, a deterministic equivalent expression of the uplink SINR for the proposed multi-cell MMSE is derived. The expression is easy to compute and accounts for power control for the pilot and payload, imperfect channel estimation and arbitrary pilot allocation. Numerical results show that significant sum spectral efficiency gains can be obtained by the multi-cell MMSE over the conventional single-cell MMSE and the recent multi-cell ZF, and the gains become more significant as β and/or K increases. Furthermore, the deterministic equivalent is shown to be very accurate even for relatively small system dimensions.
An Efficient Cooperative Spectrum Sensing Algorithm Based on BP Neural Network

Cognitive radio (CR) is a promising paradigm proposed to cope with the spectrum scarcity problem by reusing the authorized idle spectrum resource. Accurate spectrum sensing of CR is important for raising the utilization efficient of spectrum resource meanwhile avoiding interference to authorized users. In this paper, a new efficient cooperative spectrum sensing algorithm based on the BP neural network is proposed. This algorithm adjusts iteratively the parameters of BP neural network to raise the sensing accuracy. Simulation results show that the detection accuracy is improved and the consumption of energy is reduced by the new cooperative spectrum sensing algorithm.
Dimensional Analyses of Taxonic Data

Principal component analysis (PCA) and common factor analysis are often used to model latent data structures. Typically, such analyses assume a single population whose correlation or covariance matrix is modelled. However, data may sometimes be unwittingly sampled from mixed populations containing a taxon (nonarbitrary subpopulation) and its complement class. One derives relations between values of PCA parameters within subpopulations and their values in the mixed population. These results are then extended to factor analysis in mixed populations. As relationships between subpopulation and mixed-population principal components and factors sensitively depend on within-subpopulation structures and between-subpopulation differences, naive interpretation of PCA or factor analytic findings can potentially mislead. Several analyses, better suited to the dimensional analysis of admixture data structures, are presented and compared.
Structured Composition of Semantic Vectors

Distributed models of semantics assume that word meanings can be discovered from "the company they keep. " Many such approaches learn semantics from large corpora, with each document considered to be unstructured bags of words, ignoring syntax and compositionality within a document. In contrast, this paper proposes a structured vectorial semantic framework, in which semantic vectors are defined and composed in syntactic context. As such, syntax and semantics are fully interactive; composition of semantic vectors necessarily produces a hypothetical syntactic parse. Evaluations show that using relationally-clustered headwords as a semantic space in this framework improves on a syntax-only model in perplexity and parsing accuracy.
3 D joint inversion of seismic traveltime and gravity data : a case study

Joint inversion of different geophysical datasets is an effective way to eliminate non-uniqueness in geophysical inversion problems. In this paper, we focus on a case study of joint inversion of seismic traveltime and gravity observations. The results are encouraging and we can have confidence that, comparing traveltime tomography alone, joint inversion of seismic traveltime and gravity data improved resolution, reduced velocity biases, formed the basis for successful statics solutions, and imaged geologic structure. The final 3D velocity model provided sufficient resolution and accuracy as the input for successful prestack depth-migration velocity analyses.
Early multilinguals have smaller gray matter volumes in language processing areas

Poster: "ECR 2012 / C-2318 / Early multilinguals have smaller gray matter volumes in language processing areas" by: "L. S. Eppenberger1, R. Smieskova1, A. Kaiser2, E. Kuenzli1, S. Borgwardt1, E. W. Radue1, K. Bendfeldt1, C. Nitsch1; 1Basel/CH, 2Berlin/DE"
Time-varying Nairu and real interest rates in the Euro Area

This paper analyses the Nairu in the Euro Area and the influence that monetary policy had on its development. Using the Kalman-filter technique we find that the Nairu has varied considerably since the early seventies. The Kalman-filter technique is applied here for the first time using explicit exogenous variables. In particular real interest rates were found to explain a quarter of the increase in the Nairu between 1980 and 1995. This indicates the possibility of a long-run non-superneutrality of monetary policy. JEL Classification: C32, E32, E52.
Face Processing on Low-Power Devices

The research on embedded vision-based techniques is considered nowadays as one of the most interesting matters of computer vision. In this work we address the scenario in which a real-time face processing system is needed to monitor people walking through some locations. Some face detection (e.g., Viola-Jones face detector) and face recognition (e.g., eigenfaces) approaches have reached a certain level of maturity, so we focused on the development of such techniques on embedded systems taking into account both hardware and software constraints. Our goal is to detect the presence of some known individuals inside some sensitive areas producing a compact description of the observed people. Captured data can then be used for online or offline behavioural analysis. In order to obtain system scalability and efficient resource allocation, Wireless Multimedia Sensor Networks (WMSNs) are used. Each node is based on the low-power Imote2 platform extended with a multimedia board that integrates a VGA camera and a PIR motion sensor. Tests have been performed on a WMSN prototype deployed for the monitoring of a laboratory at the University of Palermo and experimental results are very encouraging.
Investigation of upper limb kinematics and corticospinal pathway activity early after stroke

Abstract Reach-to-grasp is an essential part of activities of daily living (ADL’s); despite rehabilitation reach-to-grasp often impaired after a stroke contributing to disability. Upper limb rehabilitation interventions need improvement. A deeper understanding of underlying kinematic characteristics and the neural correlates of movement can be achieved through neuro-biomechanical assessment. This would provide knowledge of the interaction of the nervous and musculoskeletal system, which may contribute to development of improved targeted upper limb interventions. A systematic review and meta-analysis was conducted investigating the kinematic differences in reach-to-grasp between stroke survivors and neurologically intact adults. The results indicate stroke survivors consistently demonstrate different kinematics to neurologically intact adults during reach-to-grasp in the central and ipsilateral workspace. There was heterogeneity of the reach-to-grasp task, and included studies demonstrated unclear or high potential risk of bias. A test-retest reliability study investigated transcranial magnetic stimulation (TMS) measures of corticospinal pathway excitability in the bilateral biceps, extensor carpi radialis (ECR), and abductor pollicis brevis (APB) in neurologically intact adults. The results demonstrate variable reliability; the lower end of the confidence interval was below acceptable reliability (ICC < 0.70) for many measures. The 95% confidence intervals (CI) and 95% limits of agreement (LOA) were wide, further indicating imprecision in measurement. A test-retest reliability study investigated TMS measures of corticospinal pathway excitability in the bilateral biceps, ECR and APB in stroke survivors within three months after stroke. The results demonstrate variable reliability; and the lower end of the confidence interval was below the range of acceptable reliability (ICC < 0.70) for many measures. The 95% CI and 95% LOA were wide, further indicating imprecision in measurement. Investigations into the variability of TMS measures in sub-acute stroke survivors and neurologically intact adults; as well as specificity of TMS measurement warrant future investigations to determine the use of TMS within these populations.
Finite-time attitude regulation control for a rigid spacecraft under input saturation

The problem of attitude regulation for a rigid spacecraft under input saturation is studied in this paper. Based on the technique of finite-time control and the model structural features, a novel finite-time attitude controller is proposed. The bound of a proposed finite-time controller can be adjusted to any small level to accommodate the actuation bound in practical implementation. A simulation example is given to demonstrate the efficiency of the proposed method.
Improved Representation of Boundary Layer Clouds over the Southeast Pacific in ARW-WRF Using a Modified Tiedtke Cumulus Parameterization Scheme*

AbstractA modified Tiedtke cumulus parameterization (CP) scheme has been implemented into the Advanced Research Weather Research and Forecasting model (ARW-WRF) to improve the representation of marine boundary layer (MBL) clouds over the southeast Pacific (SEP). A full month simulation for October 2006 was performed by using the National Centers for Environmental Prediction (NCEP) final analysis (FNL) as both the initial and lateral boundary conditions and the observed sea surface temperature (SST). The model simulation was compared with satellite observations and with results from an intense ship-based campaign of balloon soundings during 16–20 October 2006 at 20°S, 85°W.The model with the modified Tiedtke scheme successfully captured the main features of the MBL structure and low clouds over the SEP, including the geographical distribution of MBL clouds, the cloud regime transition, and the vertical structure of the MBL. The model simulation was repeated with the various CP schemes currently provided as.
The GAP arginine finger movement into the catalytic site of Ras increases the activation entropy

Members of the Ras superfamily of small G proteins play key roles in signal transduction pathways, which they control by GTP hydrolysis. They are regulated by GTPase activating proteins (GAPs). Mutations that prevent hydrolysis cause severe diseases including cancer. A highly conserved “arginine finger” of GAP is a key residue. Here, we monitor the GTPase reaction of the Ras·RasGAP complex at high temporal and spatial resolution by time-resolved FTIR spectroscopy at 260 K. After triggering the reaction, we observe as the first step a movement of the switch-I region of Ras from the nonsignaling “off” to the signaling “on” state with a rate of 3 s−1. The next step is the movement of the “arginine finger” into the active site of Ras with a rate of k2 = 0.8 s−1. Once the arginine points into the binding pocket, cleavage of GTP is fast and the protein-bound Pi intermediate forms. The switch-I reversal to the “off” state, the release of Pi, and the movement of arginine back into an aqueous environment is observed simultaneously with k3 = 0.1 s−1, the rate-limiting step. Arrhenius plots for the partial reactions show that the activation energy for the cleavage reaction is lowered by favorable positive activation entropy. This seems to indicate that protein-bound structured water molecules are pushed by the “arginine finger” movement out of the binding pocket into the bulk water. The proposed mechanism shows how the high activation barrier for phosphoryl transfer can be reduced by splitting into partial reactions separated by a Pi-intermediate.
Evaluation on geospatial information extraction and retrieval: Mining thematic maps from web source

The World Wide Web easily becomes the largest repository of natural language text data. We are particularly interested in state-of-the-art methods in exploiting geospatial information the web. The survey is done in the context of its extraction methods, retrieval, visualization, and further possible mining or knowledge discovery scenarios in order to produce thematic maps automatically from the web corpus. We found that Web-based Geographic Information Retrieval (GIR) methods that returns selected relevant area instead of points is still lacking, even though area modeling is common in GIS. We also found that most GIR methods is still focused on places and buildings instead of theme or information around some area. Thus it indicates that the state of the art GIR methods are not yet sufficient for thematic extraction and retrieval to generate thematic maps from web corpus. Bayesian topic models such as Latent Dirichlet Allocation may serve as a good basis to serve such use cases.
An approach to minimize false positive in SQLI vulnerabilities detection techniques through data mining

Dependence on web applications is increasing very rapidly in recent time for social communications, health problem, financial transaction and many other purposes. Unfortunately, the presence of security weaknesses in web applications allows malicious user's to exploit various security vulnerabilities and become the reason of their failure. Currently, SQL Injection (SQLI) attacks exploit most dangerous security vulnerabilities in various popular web applications i.e. eBay, Google, Facebook, Twitter etc. Research on taint based vulnerability detection has been quite intensive in the past decade. However, these techniques are not free from false positive and false negative results. In this paper, we propose an approach to minimize false positive in SQLI vulnerability detection techniques using data mining concepts. We have implemented a prototype tool for PHP, MySQL technologies and evaluated it on six real world applications and NIST Benchmarks. Our evaluation and comparison results show that proposed technique detects SQLI vulnerabilities with low percentage of false positives.
Learning in a hierarchical control system: 4D/RCS in the DARPA LAGR program

The Defense Applied Research Projects Agency (DARPA) Learning Applied to Ground Vehicles (LAGR) program aims to develop algorithms for autonomous vehicle navigation that learn how to operate in complex terrain. Over many years, the National Institute of Standards and Technology (NIST) has developed a reference model control system architecture called 4D/RCS that has been applied to many kinds of robot control, including autonomous vehicle control. For the LAGR program, NIST has embedded learning into a 4D/RCS controller to enable the small robot used in the program to learn to navigate through a range of terrain types. The vehicle learns in several ways. These include learning by example, learning by experience, and learning how to optimize traversal. Learning takes place in the sensory processing, world modeling, and behavior generation parts of the control system. The 4D/RCS architecture is explained in the paper, its application to LAGR is described, and the learning algorithms are discussed. Results are shown of the performance of the NIST control system on independently‐conducted tests. Further work on the system and its learning capabilities is discussed. © 2007 Wiley Periodicals, Inc.
Under consideration for publication in Formal Aspects of Computing An Algebraic Theory for Web Service Contracts

We study a natural notion of compliance between clients and services in terms of their bpel (abstract) descriptions. The induced preorder shows interesting connections with the must preorder and has normal form representatives that are parallel-free finite-state activities, called contracts. The preorder also admits the notion of least service contract that is compliant with a client contract, called dual contract, and exhibits good precongruence properties when choreographies of Web services are considered. Our framework serves as a foundation of Web service technologies for connecting abstract and concrete service definitions and for service discovery.
A 6q14.1-q15 microdeletion in a male patient with severe autistic disorder, lack of oral language, and dysmorphic features with concomitant presence of a maternally inherited Xp22.31 copy number gain

We report on a male patient with severe autistic disorder, lack of oral language, and dysmorphic features who carries a rare interstitial microdeletion of 4.96 Mb at chromosome 6q14.1‐q15. The patient also harbors a maternally inherited copy number gain of 1.69 Mb at chromosome Xp22.31, whose pathogenicity is under debate.
Crowdsourced Mobile Sensing for Smarter City Life

This paper introduces the ongoing project that aims to develop a mobile sensing framework to collect sensor data reflecting personal-scale, or microscopic, roadside phenomena by crowd sourcing and also using social big data, such as traffic, climate, and contents of social network services like Twitter. To collect them, smartphone applications are provided. One of the typical applications is a driving recorder that collects not only sensor data, such as acceleration, gyro, compass, and speed, but also recorded videos from the driver's view. To extract specific roadside phenomena, collected data are integrated and analyzed at the service platform. The framework also provides tools for interactive analysis to support city administration.
Three-dimensional modeling and simulation of wideband MIMO mobile-to-mobile channels

A three-dimensional (3-D) geometrical propagation model for wideband multiple-input multiple-output (MIMO) mobile-to-mobile (M-to-M) communications is proposed. Based on the geometrical model, a 3-D parametric reference model for wideband MIMO M-to-M multipath fading channels is developed. From the reference model, the corresponding space-time-frequency correlation function is derived for a 3-D non-isotropic scattering environment. It is shown that the time and frequency dispersion of a wide sense stationary uncorrelated scattering channel cannot be treated independently, contrary to common practice. From the space-time-frequency correlation function, the space-Doppler power spectral density and the power space-delay spectrum are derived and compared with measured data. Finally, a new sum-of-sinusoids based simulation model for wideband MIMO M-to-M Ricean fading channels is proposed. The statistics of the simulation model are verified by simulation. The results show that the simulation model is a good approximation of the reference model.