Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictive Model for SSVEP Magnitude Variation: Applications to Continuous Control in Brain-Computer Interfaces

The steady-state visual-evoked potential-based brain-computer interface (SSVEP-BCI) is a typically recognized visual stimulus frequency from brain responses. Each frequency represents one command to control a machine. For example, multiple target stimuli with different frequencies can be used to control the moving speeds of a robot. Each target stimulus frequency corresponds to a speed level. Such a conventional SSVEP-BCI is choice selection paradigm with discrete information, allowing users to discretely control the speed of a movable object. This can result in non-smooth object movement. To overcome the problem, in this study, a conceptual design of a SSVEP-BCI with continuous information for continuous control is proposed to allow users to control the moving speed of an object smoothly. A predictive model for SSVEP magnitude variation plays an important role in the proposed design. Thus, this study mainly focuses on a feasibility study concerning the use of SSVEP magnitude prediction for BCI. A basic experiment is therefore conducted to gather SSVEP responses from varying stimulus intensity using times with a fixed frequency. Random Forest Regression (RF) is outperformed by simple regression and neural networks in these predictive tasks. Finally, the advantages of the proposed SSVEP-BCI is demonstrated by streaming real SSVEP responses from ten healthy subjects into a brain-controlled robotic simulator. The results from this study show that the proposed SSVEP-BCI containing both frequency recognition and magnitude prediction is a promising approach for future continuous control applications.
Graphical representations and transfer of ideas between multi-draft pre-writing stages

Learning Sciences and Technology National Institute of Education In this study, 36 engineering students who were taking a course on effective communication used graphic organizers to prepare their draft for a writing task. This was followed by a review by peers and the teacher. As students often have difficulties constructing knowledge across representations, this study aims to uncover the factors that influence students’ cognitive decision-making when transferring information between pre-writing stages. The findings show that the factors were: the level of elaboration of the main ideas, the link between the writing goal of each pre-writing stage, and the level of importance of the main ideas. Furthermore, the redundant information in the pre-writing stages helped rather than hindered them from transferring ideas between the pre-writing stages. In addition, the students were more ready to accept feedback from the teacher than their peers. These findings highlight the importance of factoring in the function of the information in the representations in instructional design using multiple representations. Keywords: graphical representations, transfer of ideas, redundant information, writing
Research on Model Checking Based Source Code Analysis

A model checking-based source code analysis method is proposed and implemented in this paper. The main steps include translating C/C++ source code into Kripke structure that is equivalent to control flow graph,describing properties of source code in CTL formula and verifying the source code using model checker NuSMV. The experiments show that this approach is able to achieve the goal of source code analysis.
Modeling and control of flexible link manipulators for unmodeled dynamics effect

Flexible link manipulators are mostly prefered in applications where energy consumption and faster operation are critically important. Since distributed nature of flexibility makes the system depend on not only time variable but also a spatial variable, the dynamics of flexible structures are expressed by partial differential equations. In the virtue of this kind of modeling, the designers encounter with infinite dimensional systems which means that the system has an infinite number of degrees of freedom. To cope with infinite dimensional systems, one of the most relevant techniques is to truncate the model into a definite order. However, this may yield the unmodeled dynamics that cause performance degradation and even instability. In this paper, the main motivation is to propose control techniques to compensate unwanted effects of unmodeled dynamics which may occur in truncation process. In order to achieve this goal, the linear quadratic Gaussian and the weighted H ∞ controller design are adopted. The performances of the designed controllers are demonstrated on the experimental setup. Besides this motivation, traditional lumped parameter model of the flexible link manipulator which is widely seen in the literature is considered and the superiority of the partial differential equation model is shown on the experimental setup.
Region-Based Compressive Networked Storage with Lazy Encoding

Existing work on distributed networked storage, although extensive, has generally focused on the recovery of global data field covering the entire network. This, while demanded by a broad range of applications, has ignored cases where only a subset of the data are needed, for example, from a local region of the network. Based on this observation and the fact that the sensor readings are correlated, this paper proposes a compressive networked storage solution. Specifically, by employing the compressive sensing (CS) theory, we present a lazy-encoding algorithm with local dissemination and a region-based reconstruction algorithm. Utilizing our local dissemination strategy, sensor readings only have to be disseminated and stored in their respective regions, which makes the dissemination cost decrease significantly. With the lazy-encoding algorithm, the readings in specified local regions are capable of being encoded individually, dramatically reducing the decoding ratio. The region-based reconstruction algorithm is introduced to explore the inter-region correlation, aiming at offering improved data accuracy. We further provide the mathematical foundation that our reconstruction algorithm could ensure efficient CS recovery. Experimental results using real sensor readings show that the proposed scheme is especially beneficial to the recovery of local data. At the same time, our scheme can recover the global data field as well without increasing reconstruction error.
Security Analysis of the LED Lightweight Cipher in the Internet of Things

LED,proposed in CHES 2011,is a new lightweight cipher which is applied in the Internet of Things to provide security for RFID tags and smart cards etc.On the basis of the half byte-oriented fault model and the differential analysis,a differential fault analysis on the LED cipher by inducing faults is proposed.Simulating experiment shows that our attack could recover its 64-bit secret key by introducing 3 faulty ciphertexts,and recover 128-bit secret key by introducing 6 faulty ciphertexts,respectively.Our method extends the attacking scope of faults,thereby increasing the efficiency of fault injection and decreasing the number of faulty ciphertexts.Thus,the results in this study will also be beneficial to the analysis of other lightweight ciphers.
Locating inspection facilities in traffic networks: an artificial intelligence approach

Abstract In order for traffic authorities to attempt to prevent drink driving, check truck weight limits, driver hours and service regulations, hazardous leaks from trucks, and vehicle equipment safety, we need to find answers to the following questions: (a) What should be the total number of inspection stations in the traffic network? and (b) Where should these facilities be located? This paper develops a model to determine the locations of uncapacitated inspection stations in a traffic network. We analyze two different model formulations: a single-objective optimization problem and a multi-objective optimization problem. The problems are solved by the Bee Colony Optimization (BCO) method. The BCO algorithm belongs to the class of stochastic swarm optimization methods, inspired by the foraging habits of bees in the natural environment. The BCO algorithm is able to obtain the optimal value of objective functions in all test problems. The CPU times required to find the best solutions by the BCO are found to be acceptable.
The interaction between task goals and the representation of choice options in decision-making

Most decision-making studies will focus on the value and uncertainty of each choice option but do not focus on the importance of the representation of the choice option itself. This thesis presents the effects that task goals have on creating the appropriate cognitive representation to achieve those goals and how these representations are dependent on the informational input within a given task. The overall hypothesis for this work is that cognitive representations reveal a trade-off between accommodating task goals and the format of the information sampled from the environment of the task. For example, ordering books in a stand in alphabetical order, to facilitate the task of retrieving a relevant one when necessary, reveals a material implication of such cognitive representations. As in many situations, the internal representations constructed by the agent embody the remaining degrees of freedom that map the input to successful task completion. The first two chapters in this work present how uncertain beliefs about ourselves and our preferences are either integrated or compared to fixed information about other agent’s beliefs. The third chapter presents the direct manipulation of representations of choice options by changing both the stimuli and controlling for the decision strategy used by the decision-makers. The fourth chapter presents how choice options themselves are represented in the human brain. The findings related to 1) the adaptation of personal preferences and beliefs to the (fixed) preferences and beliefs of other agents, 2) observed reduction in decision strategy compliance contingent on stimulus format, and 3) the task-contingent results for similarities between brain states of choice options, support the general trade-off hypothesis. The conclusion that can be drawn is that the study of choice option representations is underdetermined unless both informational input and task goals are accounted for.
On and Off-Policy Deep Imitation Learning for Robotics

Author(s): Laskey, Michael David | Advisor(s): Goldberg, Ken | Abstract: As an alternative to explicit programming for robots, Deep Imitation learning has two drawbacks: sample complexity and covariate shift. One approach to Imitation Learning is Behavior Cloning, in which arobot observes a supervisor and then infers a control policy. A known problem with this approach is that even slight departures from the supervisor’s demonstrations can compound over the policy’s roll-out resulting in errors; this concept of drift and resulting error is commonly referred to as covariate shift On-policy techniques reduce covariate shift by iteratively collecting corrective actions for the current robot policy. To reduce sample complexity of these approaches, we propose a novel active learning algorithm, SHIV (Svm-based reduction in Human InterVention). While evaluating SHIV, we reconsider the trade-off between Off- and On-Policy methods and find that: 1) On-Policy methods are challenging for humans supervisors and 2) performance varies with the expressiveness of the policy class. To make Off-Policy methods more robust for expressive policies we propose a second algorithm, DART (Disturbances Augmenting Robot Trajectories), which injects optimized noise into the supervisor’s control stream to simulate error during data collection. This dissertation contributes two aforementioned algorithms, experimental evaluation with three robots evaluating their performance on tasks ranging from grasping in clutter to singulation to bed-making, and the design of a novel first-order urban driving simulator (FLUIDS) that can fill gaps in existing benchmarks for Imitation Learning to rapidly test algorithm performance in terms of generalization.
Investigating the Effects of the Unified Protocol on Common and Specific Factors in a Comorbid Insomniac Sample: A Single-Case Experimental Design

Background: Insomnia and emotional disorders share common factors that underlie and perpetuate these disorders. The Uniﬁed Protocol (UP) for transdiagnostic treatment of emotional disorders is a new treatment approach designed to target core processes of emotional disorders. Objectives: The present study examined the eﬀects of UP on behavioral inhibition/behavioral activation, anxiety sensitivity, and emotion dysregulation as transdiagnostic factors, as well as cognition and behaviors speciﬁc to insomnia, in a small sample of patients (N = 6) with comorbid insomnia and emotional disorders. Methods: A multiple-baseline across subjects single-case experimental design with a 3-month follow-up was used. Participants were allocated to 2, 4, and 6 baseline periods and then received 14 weekly individual sessions of UP. The outcome measures were Behavioral Inhibition/Behavioral Activation Scales (BIS/BAS), Anxiety Sensitivity Index-3 (ASI-3), Diﬃculties in Emotion Regulation Scale (DERS), Dysfunctional Beliefs and Attitudes about Sleep Scale-10 (DBAS-10), and Sleep-Related Behaviors Questionnaire (SRBQ). Data were analyzed using visual inspection, mixed model analysis, and reliable change index (RCI). Results: Mixed model analysis showed signiﬁcant changes in BIS/BAS, ASI-3, DERS, DBAS-10, and SRBQ from pre-treatment to post-treatment. Most participants achieved a reliable change in BIS, ASI-3, DERS, DBAS-10, and SRBQ at a 3-month follow-up. Conclusions: Thispreliminarystudyprovidesempiricalevidenceontheutilityof UPforreducingcommonvulnerabilityandsleep-speciﬁc factors in chronic insomnia comorbid with emotional disorders. Further research is needed to test these ﬁndings in randomized controlled studies.
Corpus use by student writers: error correction by Thai learners of English

Researchers in corpus linguistics and applied linguistics have recommended the use of corpus data by language learners to promote independent learning (Bernardini, 2004; Yoon & Hirvela, 2004; O’Keeffe et al, 2007). However, it is not clear to what extent learners are able to use corpus resources independently, and how they can be trained to use a corpus more effectively. This thesis reports a study of learners using a corpus for error correction. The learners recorded their processes using a think-aloud protocol. The thesis records three main findings. Firstly, the learners found it easiest to spot and correct errors of clause structure, noun class, adjective pattern, and collocation; they found verb pattern the most difficult errors to correct. Secondly, the learners most frequently searched for information about colligation, collocation, acceptability/occurrence of strings in a corpus, and determiner-noun agreement; they searched for information about lexical pattern relatively infrequently. Finally, the learners worked most effectively with the corpus when they entered single words as the search terms and scrutinized the concordance lines for collocates and patterns; they worked least effectively with the corpus when they entered whole strings of words. The thesis also makes recommendations for facilitating corpus use in classrooms and specifies the training that learners need to use corpora effectively.
A New Semi-implicit Approach for the Periodic QZ Algorithm

The periodic QZ (pQZ) algorithm is a basic tool in many applications, including periodic systems, cyclic matrices and matrix pencils, and solution of skew-Hamiltonian/Hamiltonian eigenvalue problems, which, in turn, is essential in optimal and robust control, and characterization of dynamical systems. This iterative algorithm operates on a formal product of matrices. The shifts needed to increase the convergence rate are implicitly defined and applied via an embedding of the Wilkinson polynomial. But the implicit approach may not converge for some periodic eigenvalue problems. A new semi-implicit approach is proposed to avoid convergence failures and reduce the number of iterations. The shifts, computed explicitly, but without evaluating the matrix product, are applied via a suitable embedding. The combination of the implicit and semi-implicit schemes improves the behavior of the pQZ algorithm. The numerical results in extensive tests have shown no convergence failures and a reduced number of iterations.
Soft robotic hand prosthesis using reverse engineering and fast prototyping

The present work aimed to develop a soft robotic prosthesis of the human hand using reverse engineering and fast prototyping. This project arises in response to some limitations of the current conventional prostheses, namely aesthetic, mechanical and cost, that fail to fulfil the needs of its users, for example with soft objects. The hand prosthesis design involved the acquisition and processing of a medical image of the user's hand, followed by a modelling process which proved to be highly complex, and finally the obtainment of a real model (by 3D printing) of the prosthesis. The results obtained proved to be satisfactory in the approximation of the hand morphology, low cost and the designed mechanical properties. However, due to some technological limitations (the used 3D printers), and more specifically in the physical conception of the model, its functionality is yet to be proved with the pneumatic control.
Childhood Amnesia: Factors Related to the Age of First Childhood Memory

ÖZ Çocukluk amnezisi, gelişimin erken evrelerinde üretilen otobiyografik anıların yetişkinlik döneminde tam olarak hatırlanamaması olarak tanımlanan bir durumdur. Genel olarak hatırlanan ilk anıların ortalama 34 yaşa ait olduğu kabul edilse de, ilk çocukluk anısının ait olduğu yaş tartışmalıdır. Bu çalışmada genç yetişkinlerde hatırlanan ilk çocukluk anısına ait yaşın belirlenmesi ve cinsiyet, anıya ilişkin faktörler, bağlanma stilleri ve çocukluk çağı travmatik olaylarının anı yaşı üzerindeki etkisinin incelenmesi amaçlanmıştır. Araştırmaya 137 üniversite öğrencisi katılmıştır. Katılımcılardan hatırladıkları ilk anıyı yazmaları ve anının yaşı ile sıradanlık düzeyi, netliği, emosyonel yoğunluğu, bütünlüğü gibi anı özelliklerini değerlendiren anketi doldurmaları istenmiştir. Buna ek olarak katılımcıların erken travmatik deneyimleri ve bağlanma stilleri de değerlendirilmiştir. Katılımcıların hatırladıkları ilk çocukluk anısına ait yaşın 24 ve 95 ay arasında değiştiği ve ortalamanın 52.44 (SS = 16.77) ay olduğu bulunmuştur. Kadın katılımcılarda ilk anı yaşının erkek katılımcılara kıyasla anlamlı düzeyde daha düşük olduğu saptanmıştır. Cinsiyete ek olarak, çocukluk çağında yaşanan ebeveynler arasındaki ilişkiye dair travmatik olayların varlığı ilk anı yaşı ile ilişkili bir diğer faktör olarak ön plana çıkmıştır. Çocukluk çağı amnezisi otobiyografik belleğin ortaya çıkışının bir işareti olarak düşünülmektedir. Bulgular cinsiyet gibi bireysel özelliklere ek olarak erken çocukluk çağı deneyimlerinin çocukluk çağı amnezisi ile ilişkili olduğunu öne sürmektedir. Anahtar Kelimeler: Bellek, çocukluk çağı, amnezi 1Dr. Öğr. Üyesi, Işık Üniversitesi, Fen Edebiyat Fakültesi, Psikoloji Bölümü, İstanbul, Türkiye 2Dr. Öğr. Üyesi, Yeditepe Üniversitesi, Fen Edebiyat Fakültesi, Psikoloji Bölümü, İstanbul, Türkiye 3Psikolog, Işık Üniversitesi, Fen Edebiyat Fakültesi, Psikoloji Bölümü, İstanbul, Türkiye
The use of the T-history method to estimate thermal capacity and latent heat for RT15 and RT18 materials

The paper presents theoretical assumptions and implementation of the T-history method, which was used to estimate the thermal capacity and latent heat for phase change materials (PCMs). The research equipment, measurement system and obtained results were discussed. The T-history method was used to investigate the heating and cooling process of two PCMs, sold under the trade names of RT15 and RT18. Obtained results were compared with the manufacturer’s data. The analysis of the research results has led to the conclusion that the presented measurement method made it possible to perform a preliminary verification of the enthalpy–temperature dependency of the PCMs. The method can be also used for studying different commercial materials and estimating this dependency for materials of yet unknown properties.
Projection pursuit model for comprehensive evaluation of water quality

In order to test the evaluation criterions of water quality,to resolve the nonuniformity problem of evaluation results of water quality indexes,and to raise the resolution of water quality comprehensive evaluation,a new model projection pursuit(PP)model is suggested,where the evaluation results are real numbers.A scheme of PP modeling is also presented to reduce the computational amount,a new function of projection indexes is given,and it is suggested that both the function of projection indexes and the parameters of PP model can be optimized by using real coding based genetic algorithm.The calculation example shows that the scheme is effective and general,which can be applied to comprehensive evaluation of other environmental quality.
Comparisons of Different Seasonal Fused GF-1 Multispectral Images for Mapping Quasi-circular Vegetation Patches

Mapping the quasi-circular vegetation patches (QVPs) is the most basic and necessary step for studying the mechanisms of vegetation pattern formation, spontaneous plant colonization, and ecosystem maintenance and degradation in the Yellow River Delta (YRD), China. It is well known that the use of multi-seasonal image data may be expected to obtain better results for mapping the vegetation than the use of a single date image because of vegetation phenology and the contrasts between vegetation and background. Although the spring GF-1 images have been used to detect the QVPs, the potential of multi-seasonal fused GF-1 multispectral images for mapping the QVPs has not been well explored. With the objective to fill this gap, we evaluated the potential of the winter, spring, summer, and autumn fused GF-1 multispectral images for mapping the QVPs with object-based example-based feature extraction with support vector machine classification method to understand the seasonal effect on the QVPs mapping accuracy. The results showed that classification based on the spring data acquired on 6 April 2014 (OA=99.8%, kappa=0.988) was more accurate than the classification base on the other tree seasonal images. The lowest classification accuracy was obtained from the autumn data acquired on September 21 2015 (OA=93.1%, kappa=0.885). We recommend the he spring and winter images to map the QVPs in the YRD. In the future, more machine learning techniques should be applied to classify and compare the potential of the different seasonal fused GF-1 multispectral images for mapping the QVPs.
Application Study of Example Based Chinese Word Segmentation and Part-of-speech Tagging Method

The experiments in this paper proved that the example-base Chinese word segmentation and part-of-speech tagging(EBST for abbr.) system has very good performance on training corpus-relevant texts.The experiments show that the results of segmentation and part-of-speech given by the experiment EBST system have not only very high precision but also very good coherence with the training corpus.This makes EBST systems very suitable for the applications within example-base machine translation systems.An example of this kind application is also given in this paper,as well as its experiment results.