Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Menus to Access Computers via Phone-Based Interfaces

Phone-based interfaces allow users easy access to information stored in distant computers. Applications include gaining credit card information, information about financial aid and registration at universities, and banking services. One interface tool that is often used in these applications is the menu. Unfortunately, the use of menus in these types of interfaces is not well investigated. The current study was developed to investigate issues related to the use of menus in auditory interfaces using computer synthesized speech as the output medium. Variables of interest included: 1) menu-page configuration (organized versus random); 2) menu-hierarchy configuration (top-down versus bottom-up); 3) individual differences in short-term memory capabilities; and 4) user anxiety. Subjects performed 20 menu selection trials from one of four menu arrangements. Subjects were given a digit-span task to assess short-term memory capacity and a Sternberg task to assess speed of recall from short-term memory. Finally, subjects were given the State-Trait Anxiety Inventory to assess subject trait and state anxiety. Results suggest that menu performance is a more complex process than VDT menu performance. Short-term memory abilities contributed a major portion of the variance in menu performance. User interest in the menu task also accounted for a good deal of the variance in menu performance and interest was found to be correlated with user anxiety. These results and the results of the menu configuration variables are discussed in terms of possible implications for phone-based menu use and design.
Mixed Display Platform to Expand Comfortable Zone of Stereoscopic 3D Viewing

Common stereoscopic three‐dimensional (3D) display has a convergence and accommodation conflict that violates the natural human cognitive process of viewing. This weakness exposes the challenge in supporting fun factors while eliminating safety problems in the 3D viewing experience. Thus, human factors have become a major research topic. In this letter, we propose a 3D stereoscopic visualization platform that can expand the sense of a 3D space by fusing organically mixed stereoscopic displays to provide a continuous feeling of 3D depth. In addition, we present pilot test results to show the possibility of the technical implementation of the proposed platform and note ongoing research issues to be addressed.
MacVisSTA: A System for Multimodal Analysis of Human Communication and Interaction

The study of embodied communication requires access to multiple data sources such as multistream video and audio, various derived and meta-data such as gesture, head, posture, facial expression and gaze information. This thesis presents the data collection, annotation, and analysis for multiple participants engaged in planning meetings. In support of the analysis tasks, this thesis presents the multimedia Visualization for Situated Temporal Analysis for Macintosh (MacVisSTA) system. It supports the analysis of multimodal human communication through the use of video, audio, speech transcriptions, and gesture and head orientation data. The system uses a multiple linked representation strategy in which different representations are linked by the current time focus. MacVisSTA supports analysis of the synchronized data at varying timescales for coarse-to-fine observational studies. The hybrid architecture may be extended through plugins. Finally, this effort has resulted in encoding of behavioral and language data, enabling collaborative research and embodying it with the aid of, and interface to, a database management system.
A method of real-time detection for distant moving obstacles by monocular vision

In this paper, we propose an approach for detection of distant moving obstacles like cars and bicycles by a monocular camera to cooperate with ultrasonic sensors in low-cost condition. We are aiming at detecting distant obstacles that move toward our autonomous navigation car in order to give alarm and keep away from them. Method of frame differencing is applied to find obstacles after compensation of camera’s ego-motion. Meanwhile, each obstacle is separated from others in an independent area and given a confidence level to indicate whether it is coming closer. The results on an open dataset and our own autonomous navigation car have proved that the method is effective for detection of distant moving obstacles in real-time.
Engineering design of a virtual reality simulator for gynaecological endoscopy

Endoscopic surgeons have identified the need for a system that enables them to practice a range of complex 3D surgical procedures that involve the use of a video endoscopic instrument system. Physical simulators have been developed to enable the evaluation of skills required in endoscopic surgery and a VR surgical simulator is being developed that incorporates the ability of virtual instruments to interact with virtual anatomical structures, and for the operator to feel virtual anatomy as it resists movement. The emphasis of this work is to use available graphics tools to visually represent the anatomy, to represent instrument/anatomy interactions in a visually convincing way, and to represent instrument resistance to movement in a tactile sensory convincing way.
A digitally controlled on-chip clock multiplier for globally asynchronous locally synchronous systems

For large high-speed globally synchronous ASICs, designing the clock distribution net becomes a troublesome task. Besides problems caused by clock skew, the clock net also is a major source of power consumption. Partitioning the design into locally clocked blocks reduces clock skew problems and if handled correctly it also helps reducing power consumption. However, to achieve these positive effects, the blocks need on-chip clocks having properties as small area and low power consumption. Therefore, a low power small area digitally controlled on-chip clock generator is designed.
A Personalized Recommendation Model Based on Contextual Information

Personalized recommendation offers a new way to solve the problem of information overload. In order to effectively build user model and improve the effect of personalized recommendation, this paper proposes a novel model for mining contextual information of non-structure text, and insects the contextual information into user model, which enriches user model. The experiment results shown that the model can greatly improve the recommendation performance when the model is applied to contextual data of the recommender system in hotel.
Topological transition from magnetic networks to the electric equivalent ones when iron losses are present

After presenting, based on Cherry rule, the classical deduction of the electric equivalent network of a transformer magnetic circuit, the authors introduce the extension of this topological approach when hysteresis losses are present. Specific considerations related to the matrix properties associated to the use of ideal transformers are also given. The method can be extended to the rotating machinery analysis. This allows to deduce the hysteresis torque.
Virtual Effort: An Advanced User Interface that Combines Various Visual Information with a Kinetic System for Virtual Object Manipulations

The present day virtual environments are very advanced and have the ability to display complex representations of simulated objects together with their surroundings. Each virtual object can be endowed with multiple physical properties; in this way the entire virtual environment tends to become very real. However, human interaction with objects in virtual environments is forced from the user perspective and very different from how humans interact with objects in physical world. In this paper, a research that allows a more natural human-computer communication is presented. This is realized by combining visual information that is displayed to a user with kinetic information captured from the user hand by utilizing a sensor to capture depth data. The presented method is used in order to perform experiment that consist in grasping, moving and dropping a virtual object and analyze the hand trajectory compared with the virtual object trajectory.
Practical implementation and analysis of hyper-encryption

The security of modern cryptographic schemes relies on limits on computational power and assumptions about the difficulty of certain mathematical problems, such as integer factorization. This thesis describes hyper-encryption in the limited access model, a system that provides perfect secrecy and authentication against an adversary who possesses unbounded computational power, but who is limited in the ability to eavesdrop on more than a fraction of computers in a large network, such as the Internet. This thesis also presents an implementation of hyper-encryption in the limited access model, discusses areas where the theoretical system differs from the practical implementation, and analyzes their impact on the security of the system. Thesis Supervisor: Ronald L. Rivest Title: Viterbi Professor of Electrical Engineering and Computer Science Thesis Supervisor: Michael O. Rabin Title: T.J. Watson Sr. Professor of Computer Science, Harvard SEAS
Statistical integrated circuit design

Several statistical design methods that have been developed to minimize the effects of IC manufacturing process disturbances on circuit performance are reviewed. It is shown that statistical design problems can be expressed as optimization problems in which either the objective function or the constraint functions depend on expectations of random variables. The effectiveness of the most recent such method, the boundary integral method is illustrated with several circuit design examples. >
Pseudobinary detection processes for a 9600 bit/s modem

In the Viterbi-algorithm detection of a multilevel digital signal having a large alphabet (many levels), such as a 16-level QAM signal, very considerable equipment complexity is involved, even when the sampled impulse response of the channel has only a few components. A recent development of the Viterbi-algorithm detector, known as the pseudobinary Viterbi-algorithm detector, effectively recodes the received multilevel data signal into a binary signal and implements the conventional Viterbi-algorithm detection process for the corresponding binary signal, thus very greatly reducing the complexity of the detector. Since there is only a small loss in tolerance to noise as a result of the given modification, a potentially useful detection process is obtained. The paper describes two novel detection processes in which the given pseudobinary technique is applied to two different near-maximum-likelihood detectors. The particular application studied is that of a synchronous serial 9600 bit/s modem transmitting a 16-level QAM signal over a telephone circuit in the public switched telephone network. Results of computer simulation tests are presented, comparing the tolerances to additive white Gaussian noise of various arrangements of each detector, when operating over models of two different telephone circuits.
A case study on the effects of a haptic interface on human arm movements with implications for rehabilitation robotics

Many different studies have proposed models for human arm trajectories, almost all of them agreed on invariant feature of these movements, such as smooth trajectories with straight line and uni-modal velocity profiles. We observed these characteristics in contact with a haptic interface that might modify the movement features. Significantly, our result showed similar characteristics for the human reaching and returning movement for one subject. We also used the data in comparison with the model based on the minimum jerk theory. The results obtained from our experiments are consistent with the model based on this theory, which suggests that our virtual trajectory is a good model of human arm movements. Further investigation, with more number of subjects are needed to prove these consistencies.
Sentiment Analysis of Chinese Micro Blog Using Machine Learning and an Improved Feature Selection Method

With the rapid development of Internet and occurrence of social media services, many users are becoming the creators of social information. However, the normal manual work can't deal with a large number of subjective messages. As a new kind of social media service, micro blog has been widely accepted and can be used for sentiment analysis. This paper compared performances of three machine learning methods on sentiment analysis of Chinese micro blog. We also proposed an improved feature selection method that increases the accuracy of classification. Experiment results show that SVM is closed to Naïve Bayes and they are better than logistic regression in most cases.
Fully automatic assessment of programming exercises

Automatic assessment of programming exercises has become an important method for grading students' exercises and giving feedback for them in mass courses. We describe a system called Scheme-robo, which has been designed for assessing programming exercises written in the functional programming language Scheme. The system assesses individual procedures instead of complete programs. In addition to checking the correctness of students' solutions the system provides many different tools for analysing other things in the program like its structure and running time, and possible plagiarism. The system has been in production use on our introductory programming course with some 300 students for two years with good results.
Toward High Utilization of Heterogeneous Computing Resources in SNP Detection

As the amount of re‐sequencing genome data grows, minimizing the execution time of an analysis is required. For this purpose, recent computing systems have been adopting both high‐performance coprocessors and host processors. However, there are few applications that efficiently utilize these heterogeneous computing resources. This problem equally refers to the work of single nucleotide polymorphism (SNP) detection, which is one of the bottlenecks in genome data processing. In this paper, we propose a method for speeding up an SNP detection by enhancing the utilization of heterogeneous computing resources often used in recent high‐performance computing systems. Through the measurement of workload in the detection procedure, we divide the SNP detection into several task groups suitable for each computing resource. These task groups are scheduled using a window overlapping method. As a result, we improved upon the speedup achieved by previous open source applications by a magnitude of 10.
La herramienta de tests de usabilidad a distancia Loop11

Las herramientas de usabilidad a distancia son muy valiosas y utiles para el diseno y la administracion de tests de usabilidad. Nos pueden servir para simplificar y agilizar los procesos. Se describe la aplicacion Loop11 en detalle y se comenta nuestra experiencia con ella en dos de estos tests.
Enhanced concept for control systems of electric power networks

This paper presents a hard- and software concept for the integration of modern condition monitoring devices into electric power network control and management systems. The concept is based on a distributed database and on a central system definition, which describes the entire setup. A system definition language is proposed, where all aspects of data such as location within the system, permission of access, interfaces, statistical and economical evaluation, storage and visualization can be defined. The system definition language is hierarchical and object oriented. An experimental setup for online monitoring purposes is described, where the methods proposed are applied.
Shift invariance algorithms for the angle/delay estimation of multipath space-time channel

In time-division CDMA systems the angle/delay of the multipath propagation channel can be estimated jointly by exploiting the invariance of angles/delays across multiple slots regardless of fast-variation in faded amplitudes. The joint angle/delay estimation (JADE) is reduced to the estimation of frequency of 2D sinusoids, here the shift-invariance method (2D-ESPRIT) is used. Application of JADE to 3/sup rd/ generation mobile communication system (TDD-UTRA standard) and to realistic propagation environments demonstrates the advantage of the proposed method. Linear multiuser detection that exploits angle/delay estimates shows a meaningful improvement (approx. 2/spl divide/4 dB in signal to noise ratio) with respect to the conventional least square estimate.
VLSI theory and parallel supercomputing

Abstract : Since its inception, VLSI theory has expanded in many fruitful and interesting directions. One major branch is layout theory which studies the efficiency with which graphs can be embedded in the plane according to VLSI design rules. In this survey paper, I review some of the major accomplishments of VLSI layout theory and discuss how layout theory engendered the notion of area and volume-universal networks, such as fat-trees. These scalable networks offer a flexible alternative to the more common hypercube-based networks for inter-connecting the processors of large parallel supercomputers. Keywords: Integrated circuits; Interconnection networks; Parallel computing; Super-computing; Universality; Thompson's model; Tree of meshes.
Efficient statistical tolerance analysis for general distributions using three-point information

The experimental design technique in the literature, which has been limited only to normally distributed random variables, is extended to handle non-normal cases. It is easy to implement and provides good results for the moments of system response functions compared with other traditional methods. It is based on the three-level Taguchi method, and optimum levels and weights to handle non-normal distributions are derived. A systematic procedure for tolerance analysis is then proposed by using the Pearson system. Numerical results for non-linear examples are shown to be very accurate in comparison with those from Monte Carlo simulations and the first-order reliability method.
An Effective Recognition Method of Quick Response Barcode in Complex Image Conditions Based on Multi-Constraint Hough Transform

Quick Response (QR) barcodes are being used in a wide variety of applications. But the discrimination rate won’t be high because the collected bar codes (form a camera or scanner) are in various imaging conditions. Obtaining and correcting the QR barcode inclination angle is the basis of the QR barcode recognition technique. In this paper, using the characteristics of QR barcodes, we propose to recognize the QR barcodes in complex image conditions by multi-constraint Hough transform method, which combines the inclination angle constraint and edge-point constraint to obtain and correct the QR barcode inclination angle efficiently. The proposed method was evaluated on three data sets. The experimental results indicate that the transform time of our method is 0.3% of the transform time of the classic Hough transform. In particular, the proposed method provides a valuable QR barcode recognition solution in complex image conditions.
Interconnect optimization using asymptotic waveform evaluation (AWE)

The asymptotic waveform evaluation (AWE) technique is utilized for performance evaluation and optimization of interconnect circuits consisting of both lumped and distributed elements. An efficient method for distributed element sensitivity, a gradient based optimization scheme, and several techniques to enhance both efficiency and accuracy of simulation performance are presented and evaluated in this paper. <<ETX>>
Stereoselective Additions of Chiral, Functionalized Organozinc Reagents to Achiral and Chiral Aldehydes: A Matched-Mismatched Case in Organozinc Chemistry.

The additions of the enantiomerically pure organozinc reagents 17 and 33 to the THF-aldehyde 1 in the presence of the monodentate Lewis acid boron trifluoride -ether give the nonchelation-controlled addition products 7 and 36, respectively (stereoselectivity 95:5, 86: 14). These results provide a route to oligo(tetrahydrofuran)s with the relative stereochemistry trans-syn-cis. A stereodirecting effect of the chiral center in the organozinc reagent 17 is found, leading to simple diastereoselectivies in the reaction with achiral aldehydes and to a matched-mismatched case in the reaction with the chiral aldehyde 1
Towards 3D thermal models standardisation for human body in motion

In this paper, a novel multi-resolution real-time 3D thermal imaging system as potential solution for a human body 3D thermal models standardisation is presented. The system consists of a high-resolution offline 3D scanner and a real-time low-resolution 3D scanner, both of them paired together with a thermal imaging camera. The emphasis of this paper is the presentation of the novel concept of the standardisation of human body 3D thermal models, captured by the multi-resolution real-time 3D thermal imaging system. The standardisation procedure utilises skeleton detection, skeleton transformation, mesh optimisation and texture mapping. The presented concept enables novel and practical methods for human body 3D thermal models comparison and analysis.
A generalized RAKE receiver for DS-CDMA systems

In this paper, a generalized RAKE receiver for interference suppression and multipath mitigation is proposed. The receiver exploits the fact that time dispersion significantly distorts the interference spectrum from each base station in the downlink of a CDMA system. Compared to the conventional RAKE receiver, this generalized RAKE receiver may have more fingers and has different combining weights. The weights are derived from a maximum likelihood formulation, modeling the intracell interference as colored Gaussian noise. For a wideband CDMA (W-CDMA) system and a realistic mobile radio channel, capacity gains on the order of 100% are shown.
Hidden Markov Model with Information Criteria Clustering and Extreme Learning Machine Regression for Wind Forecasting

This paper proposes a procedural pipeline for wind forecasting based on clustering and regression. First, the data are clustered into groups sharing similar dynamic properties. Then, data in the same cluster are used to train the neural network that predicts wind speed. For clustering, a hidden Markov model (HMM) and the modiﬁed Bayesian information criteria (BIC) are incorporated in a new method of clustering time series data. To forecast wind, a new method for wind time series data forecasting is developed based on the extreme learning machine (ELM). The clustering results improve the accuracy of the proposed method of wind forecasting. Experiments on a real dataset collected from various locations conﬁrm the method’s accuracy and capacity in the handling of a large amount of data.
A New Similarity Measure Based on Intraclass Statistics for Biometrie Systems

A biometric system determines the identity of a person by measuring physical features that can distinguish that person from others. Since biometric features have many variations and can be easily corrupted by noises and deformations, it is necessary to apply machine learning techniques to treat the data. When applying the conventional machine learning methods in designing a specific biometric system, however, one first runs into the difficulty of collecting sufficient data for each person to be registered to the system. In addition, there can be an almost infinite number of variations of non‐registered data. Therefore, it is difficult to analyze and predict the distributional properties of real data that are essential for the system to deal with in practical applications. These difficulties require a new framework of identification and verification that is appropriate and efficient for the specific situations of biometric systems. As a preliminary solution, this paper proposes a simple but theoretically well‐defined method based on a statistical test theory. Our computational experiments on real‐world data show that the proposed method has potential for coping with the actual difficulties in biometrics.