Miracle-dz/UniFAR-FTUs huggingface dataset:
A Wireless Multifunctional SSVEP-Based Brain–Computer Interface Assistive System

Several kinds of brain–computer interface (BCI) systems have been proposed to compensate for the lack of medical technology for assisting patients who lose the ability to use motor functions to communicate with the outside world. However, most of the proposed systems are limited by their nonportability, impracticality, and inconvenience because of the adoption of wired or invasive electroencephalography acquisition devices. Another common limitation is the shortage of functions provided because of the difficulty of integrating multiple functions into one BCI system. In this paper, we propose a wireless, noninvasive and multifunctional assistive system which integrates steady state visually evoked potential-based BCI and a robotic arm to assist patients to feed themselves. Patients are able to control the robotic arm via the BCI to serve themselves food. Three other functions: 1) video entertainment; 2) video calling; and 3) active interaction are also integrated. This is achieved by designing a functional menu and integrating multiple subsystems. A refinement decision-making mechanism is incorporated to ensure the accuracy and applicability of the system. Fifteen participants were recruited to validate the usability and performance of the system. The averaged accuracy and information transfer rate achieved is 90.91% and 24.94 bit per min, respectively. The feedback from the participants demonstrates that this assistive system is able to significantly improve the quality of daily life.
Methods and systems for translating from one language to another

FIELD: information technology. SUBSTANCE: present invention relates to translation from one language to another. Wireless mobile device service is provided with a service for selective downloading information from the server. The downloaded information includes the architecture of the translation, which has means of translating, independent of language, and at least one language dependent translation database. The translation data base which depends on the language includes translation templates and dictionary translations. It can also load specialised database for the chosen city or cities in the world. Translation between languages is carried out through the application of translation database in the means of translating which depends on the language and translation database, specific to a particular city. For simplification of translation process the means of translation implements a user controlled scheme for replacing terms. EFFECT: invention increases quality and convenience of text translation in a natural language. 24 cl, 5 dwg
Compariso no fOnlin eSocia lRelation si nTerm sof Volume vs. Interaction: A Case Study of Cyworld

Online social networking services are among the most popular Internet services according to Alexa.com and have become a key feature in many Internet services. Users interact through various features of online social networking services: making friend relationships, sharing their photos, and writing comments. These friend relationships are expected to become a key to many other features in web services, such as recommendation engines, security measures, online search, and personalization issues. However, we have very limited knowledge on how much interaction actually takes place over friend relationships declared online. A friend relationship only marks the beginning of online interaction. Does the interaction between users follow the declaration of friend relationship? Does a user interact evenly or lopsidedly with friends? We venture to answer these questions in this work. We construct a network from comments written in guestbooks. A node represents a user and a directed edge a comments from a user to another. We call this network an activity network. Previous work on activity networks include phone-call networks [34, 35] and MSN messenger networks [27]. To our best knowledge, this is the first attempt to compare the explicit friend relationship network and implicit activity network. We have analyzed structural characteristics of the activity network and compared them with the friends network. Though the activity network is weighted and directed, its structure is similar to the friend relationship network. We report that the in-degree and out-degree distributions are close to each other and the social interaction through the guestbook is highly reciprocated. When we consider only those links in the activity network that are reciprocated, the degree correlation distribution exhibits much more pronounced assortativity than the friends network and places it close to known social networks. The k-core analysis gives yet another This work was conducted while Ahn was at KAIST.
Information technology, knowledge management and human resource management

Drawing on dynamic capability view, this study aims to offer a conceptual framework to clarify the nature of the effects of firm’s information technology (IT) capability, knowledge management (KM) capability and human resource management (HRM) capability on organizational business performance. IT is the driver that changes all aspects of doing business in the digital era, while both knowledge and human resources (HR) are being increasingly regarded as key levers of competitive advantage in today’s global, dynamic and complex business environment. ,The survey methodology was used to collect data. To clarify the relationships between IT capability, KM capability and organizational business performance, the qualitative literature review has been conducted. This review has revealed the three structural models presenting possible interactions between observed constructs. Confirmatory factor analysis has been used for the evaluation of proposed measurement models while structural equation modeling has been used for structural models’ assessments and hypotheses testing. ,IT capability enhances HRM capability which enhances KM capability. As a result, KM capability together with IT capability enhances organizational business performance. In addition, there is an interaction effect of KM capability and HRM capability on business performance. ,First, the sample is based on the emerging economy firms. Second, the use of a self-rating performance measure may be a limitation of the study. Third, the data are not completely normally distributed. Fourth, specificities of different industries were not the subject of analysis in this paper. This should be considered in the interpretation and understanding of the results. ,From managerial point of view, the paper indicates what managers can do to master their dynamic capabilities, especially those relevant to the business in the digital era. Firms are urged to develop and improve their capabilities to face dynamic environment and intense competition, as well as business globalization. However, to improve certain capability, firms should develop others as well because of their interconnectedness. ,The main academic contribution of this study is reflected through the development of the integrative model which is aimed at identifying the interrelationships among IT, KM, HRM and business performance. The results indicate the importance of observing interconnections between the firms’ various capabilities to verify the premise of the dynamic capability view. This paper identified relationships between most prominent firm’s resources for the digital era: knowledge, HR and IT. The results show causes and effects of relationships between capabilities related to these resources.
Degree Programme in Information Technology

TAMPERE UNIVERSITY OF TECHNOLOGY Master's Degree Programme in Information Technology LUO, XINGHAN: Algorithms for Face and Facial Feature Detection Master of Science (Technology) Thesis, 58 pages, 5 Appendix pages December 2007 Major: Image and Video Signal Processing Examiners: Dr. Atanas Gotchev (TUT), Prof. Karen Egiazarian (TUT); Prof. Joern Ostermann (LUH)
Statistical issues related to semiquantitative food-frequency

Semiquantitative food-frequency (50FF) ques- tionnaires have been used by many epidemiological studies to collect dietary data. These methods arc especially attractive for use in large-scale studies because they are often self-administered and/on completed with minimal time or effort. This paper dis- cusses several statistical issues related to the use of dietary data collected by frequency methods. In particular, the paper ad- dresses Al) whether SOFF methods are well-validated dietary methods as suggested by many investigators and 2) whether data based on SOFF methods can be used to compare mean dietary intakes among different populations and to estimate the distri- bution of usual nutrient intakes in a national probability popu- lation. Data from several validation studies are used to evaluate the impact on statistical analyses of measurement error associated with certain 50FF methods. These examples help to illustrate the potential problems and clarify the interpretation of the results. In addition, concerns about the misuse of dietary data derived from SOFF questionnaires arc also discussed. Am J Clin Nutr 1994;59(suppl):262S-5S.
Let’s fix it? Cross-linguistic influence in word order patterns of Russian heritage speakers in Germany

The paper analyzes verb placement of heritage speakers of Russian in contexts where German has a fixed position of the finite verb: V2 in declarative main clauses and V-final in subordinate clauses. Russian exhibits a neutral SVO order in both cases, but verb placement is in general dependent on requirements of information structure. Verb placement in texts of 20 Russian-German bilinguals was compared to data from a monolingual control group. The analysis shows that the bilinguals maintain the pragmatic flexibility of verb placement in Russian. They did not exhibit an overuse of V2 structures in declarative main clauses. There is, however, a significant increase in V-final for subordinate and declarative main clauses, which may be due to transfer from German.
Efficient Preference-based Reinforcement Learning

Common reinforcement learning algorithms assume access to a numeric feedback signal. The numeric feedback contains a high amount of information and can be maximized efficiently. However, the definition of a numeric feedback signal can be difficult in practise due to several limitations and badly defined values may lead to an unintended outcome. For humans, it is usually easier to define qualitative feedback signals than quantitative. Hence, we want to solve reinforcement learning problems with a qualitative signal, potentially capable of overcoming several of the limitations of numeric feedback. Preferences have several advantages over other qualitative settings, like ordinal feedback or advice. Preferences are scale-free and do not require assumptions over the optimal outcome. However, preferences are difficult to use for solving sequential decision problems, because it is unknown which decisions are responsible for the observed preference. Hence, we analyze different approaches for learning from preferences and show the design principles that can be used, as well as the advantages and problems that occur. We also survey the field of preference-based reinforcement learning and categorize the algorithms according to the design principles. Efficiency is of special interest in this setting, as it is important to keep the amount of required preferences low, because they depend on human evaluation. Hence, our focus is on efficient use of the preferences. It can be stated that it is important to be able to generalize the obtained preferences, as this keeps the amount of required preferences low. Therefore, we consider methods that are able to generalize the obtained preferences to models not yet evaluated. However, this introduces uncertain feedback and the exploration/exploitation problem already known from classical reinforcement learning has to be considered with the preferences in mind. We show how to efficiently solve this dual exploration problem by interleaving both tasks, in an undirected manner. We use undirected exploration methods, because they scale better to high-dimensional spaces. Furthermore, human feedback has to be assumed to be error-prone and we analyze the problems that arise when using human evaluation. We show that noise is the most substantial problem when dealing with human preferences and present a solution to this problem.
Communication Optimization of Parallel Applications in the Cloud

One of the most important aspects that influences the performance of parallel applications is the speed of communication between their tasks. To optimize communication, tasks that exchange lots of data should be mapped to processing units that have a high network performance. This technique is called communication-aware task mapping and requires detailed information about the underlying network topology for an accurate mapping. Previous work on task mapping focuses on network clusters or shared memory architectures, in which the topology can be determined directly from the hardware environment. Cloud computing adds significant challenges to task mapping, since information about network topologies is not available to end users. Furthermore, the communication performance might change due to external factors, such as different usage patterns of other users. In this paper, we present a novel solution to perform communication- aware task mapping in the context of commercial cloud environments with multiple instances. Our proposal consists of a short profiling phase to discover the network topology and speed between cloud instances. The profiling can be executed before each application start as it causes only a negligible overhead. This information is then used together with the communication pattern of the parallel application to group tasks based on the amount of communication and to map groups with a lot of communication between them to cloud instances with a high network performance. In this way, application performance is increased, and data traffic between instances is reduced. We evaluated our proposal in a public cloud with a variety of MPI-based parallel benchmarks from the HPC domain, as well as a large scientific application. In the experiments, we observed substantial performance improvements (up to 11 times faster) compared to the default scheduling policies.
Assessment of ergonomically designed handle shapes for low-frequency vibration responses

Hand-operated tool handles transmit a large magnitude of vibration to the hand-arm system during low-frequency operations. Therefore, the precise design of a hand tool is very important to overcome musculoskeletal disorders, hand-arm vibration, etc. This study was aimed at developing optimal tool handles with an increased contact area and to overcome the contact pressure, which causes discomfort and pain. Six different human hand-based optimal handles (handles B to G) and one optimal cylindrical handle (handle A) were designed and fabricated using 3D printing technology, in order to assess the effect of low-frequency vibrations. The effect of handle shapes was evaluated with objective and subjective measurements using 15 subjects. Objective measurements were performed to assess the vibration transmissibility by experimental study at the frequency range of 0–100 Hz, and subjective measurements were performed to rate the handles based on comfort descriptors and overall comfort of the handles. Root mean square vibration accelerations were recorded at the wrist, elbow, and shoulder of each subject and at the base of the handle fixture to evaluate the vibration transmissibility for each handle. The mean vibration transmissibility was found to be minimum for handle B and was rated to be more comfortable by the subjects. The results indicated that all the human hand-based handles transmit less vibration and were rated to be more comfortable than the optimal cylindrical handle.
Meta-level pattern analysis for target tracking

Classical target tracking operates on a fast time-scale (order of seconds) during which target dynamics are constrained by the physical laws of motion. This dissertation is motivated by pattern analysis on a meta-level (order of minutes or larger) during which the intent of a target manifests. On such a coarse time-scale, Markovian models quantifying the physical laws of motion are not useful in detecting anomalous behavior. This is due to the hierarchical nature of plans and goaloriented targets. In this dissertation, several novel stochastic models are devised to capture long-range dependencies within target trajectories for the joint purpose of classification and enhanced tracking. The behavior of targets on the meta level is captured through both positional features (destination) as well as movement patterns (shape). Such features are used with context-free grammar models and reciprocal Markov models (one dimensional Markov random fields) for modeling spatial trajectories with a known end point. The intent of a target is assumed to be a function of the shape of the trajectory it follows and its intended destination. The stochastic grammar models developed are concerned with trajectory shape classification while the reciprocal Markov models are used for destination prediction. Towards this goal, Bayesian signal processing algorithms with polynomial complexity are also presented. The versatility of such models is illustrated with tracking applications in radar-based and optical surveillance.
Development of an efficient level set framework for the full field modeling recrystallization in 3D

Mechanical and functional properties of metallic materials are strongly related to their microstructures, which are themselves inherited from thermal and mechanical processing. Being able to accurately predict and simulate the microstructure and its heterogeneities after complex forming paths recently became crucial for the metallurgy industry. This is also a real challenge from a numerical point of view which highlights the importance of digital materials in new modeling techniques. In this work, we focus on a recent front-capturing full field model based on the level set (LS) method within a finite element (FE) framework to model recrystallization mechanisms.The strengths of this approach comparatively to the state of the art have motivated the development of a software package called DIGIMU® by the company TRANSVALOR with the support of major industrial companies. However, the main drawback of this approach, common with other front-capturing full field approaches working on unstructured FE meshes, is its important computational cost, especially in 3D.Main purpose of this work was finally to drastically improve the numerical cost of the considered LS-FE formulation in context of unstructured FE meshes. New generic numerical developments have been proposed to improve the global efficiency of the model. The existing 2D LS formulation, already used to model grain growth, static recrystallization and the Smith-Zener pinning effect, has been extended and improved in order to model these mechanisms in 3D for large-scale polycrystals with reasonable computational costs.
An Empirical Foundation for Design Patterns in Parametric Design

This paper presents the results from exploring the impact of using a parametric design tool on designers’ behaviour in terms of us-ing design patterns in the early conceptual development stage. It is based on an empirical cognitive study in which eight architectural designers were asked to complete two architectural design tasks with similar complexity respectively in a parametric design environment (PDE) and a Geometric modelling environment (GME). Protocol analysis was employed to study the designers’ behaviour. To explore the development of design patterns during the design process, we utilise the technique of Markov model analysis. Through Markov models analysis of the PDE and GME results, we found that there are significantly more Function to Structure transitions in PDE than in GME. During this transition process, designers select an existing structure/solution for the particular function/design problem based on their experience or knowledge, which is a process of applying an existing design pattern to the problem. From this result we can infer that when architects apply programming and scripting in their design, such as in a PDE, they exhibit the characteristic of using design patterns.
UNSUPERVISED JOINT PART-OF-SPEECH TAGGING AND STEMMING FOR AGGLUTINATIVE LANGUAGES

Unsupervised Joint Part-of-Speech Tagging and Stemming For Agglutinative Languages Necva BÖLÜCÜ Master of Science,Computer Engineering Department Supervisor: Asst. Prof. Dr. Burcu CAN BUĞLALILAR June 2017, 108 pages Part of Speech (PoS) tagging is the task of assigning each word an appropriate part of speech tag in a given sentence regarding its syntactic role such as verb, noun, adjective etc. Various approaches have already been proposed for this task. However, the number of word forms in morphologically rich and productive agglutinative languages is theoretically infinite. This variety in word forms causes sparsity problem in the tagging task for agglutinative languages. In this thesis, we aim to deal with this problem in agglutinative languages by performing PoS tagging and stemming simultaneously. Stemming is the process of finding the stem of a word by removing its suffixes. Joint PoS tagging and stemming reduces sparsity by using stems and suffixes instead of words. Furthermore, we incorporate semantic features to capture similarity between stems and their derived forms by using neural word embeddings. In this thesis, we present a fully unsupervised Bayesian model using Hidden Markov Model (HMM) for joint PoS tagging and stemming for agglutinative languages. The results indicate that using stems and suffixes rather than full words outperforms a simple word-based Bayesian HMM model for especially agglutinative languages. Combining semantic features yields a significant improvement in stemming.
Experimental Investigation into Honeycomb Paperboard Vibration Transmissibility Property and Nonlinear Parameters Identification

Abstract The vibration transmissibility property of honeycomb paperboard is investigated by experiments, the experimental results indicate that both the resonance frequency and resonance peak are sensitive to the altitude of excitation force. We can assume that both the damping and stiffness properties are nonlinear, and they can be expressed as the combination of the linear part with the cubic nonlinear part. An experimental system are formulated to record the experimental data, a system parameter identification procedure is presented base on harmonic balance method and total least square method. The system parameters under different static load and different excitation force amplitude conditions are identified and presented in this paper, the system model along with the identified can be used to simulate Tr-f curves, the comparison between the simulated curves with experimental data indicates the model is accurate to predict the vibration transmissibility property, which is important for proper use of honeycomb paperboard and anti-vibration packaging design.