Miracle-dz/UniFAR-FTUs huggingface dataset:
Coherent multicarrier/DS-CDMA and MC-CDMA for broadband packet wireless access

This paper compares the packet error rate (PER) performance levels of 3 access schemes, i.e., single-carrier (SC)/DS-CDMA, multi-carrier (MC)/DS-CDMA, and MC-CDMA assuming an over 100-MHz bandwidth for broadband packet wireless access. In a broadband propagation channel, severe multipath interference degrades the accuracy of path search and channel estimation for coherent detection. Computer simulation results show that, in the reverse link, SC/DS-CDMA achieves better performance than MC/DS-CDMA because the pilot signal power in one sub-carrier for path search and channel estimation decreases as the number of sub-carriers increases. The superiority of MC-CDMA to MC(SC)/DS-CDMA is demonstrated, and the results show that, in the forward link, frequency Rake diversity with MC-CDMA is more effective than time Rake diversity with DS-CDMA in a broadband multipath fading channel due to a large amount of multipath interference.
A multivariate auto-regressive method to estimate cortico-muscular coherence for the detection of movement intent

In this work a time-frequency approach to estimate the Cortico-Muscular Coherence for the detection of the movement intent is presented, assessed on simulated data, and evaluated experimentally during different motor tasks performed by healthy subjects and patients suffering from different types of tremor. Cortico-Muscular Coherence is an index of the coupling of EEG signal in the cortical area with sEMG activity in the frequency domain, and its contributions in the beta band 15--30 Hz have been associated to the movement intent. Cortico-Muscular Coherence estimation is here achieved by considering a closed-loop representation of the signals under analysis obtained through Multivariate Auto Regressive modeling. Significance levels for Cortico-Muscular Coherence are assessed by means of a surrogate data analysis approach. The detection technique is able to reveal significant Cortico-Muscular Coherence changes in 79% of the experimental trials, with a mean anticipation of 1.35 s with respect to movement onset. Time-frequency estimation of Cortico-Muscular Coherence can provide an insight for the development of a multimodal BCI able to integrate information from the brain activity in the functioning of assistive devices.
On the use of Nauta's transconductor in low-frequency CMOS gm-C bandpass filters

This paper discusses the use of a transconductor, first proposed by Nauta for high frequency applications, in low frequency CMOS g/sub m/-C bandpass filters. The behavior of the transconductor is examined in detail, showing that the robust implementation of higher-order low-voltage filters is possible for center frequencies in the lower megahertz region. The experimental results are presented of the realization of two prototypes, a 0.6-/spl mu/m CMOS 18th-order real bandpass filter and a 0.35-/spl mu/m CMOS 7th-order complex (14th-order bandpass) filter, both with a center frequency of 3 MHz and a passband of 1 MHz. These filters comply with the specifications for the channel-select stage of the Bluetooth short-range radio receiver.
Service differentiation of variable bit rate voice in AAL2 multiplexers

Many of the voice codecs in use today employ silence-suppression techniques to suppress packet generation during silence periods, resulting in output voice traffic that is variable bit rate (VBR) in nature. ATM Adaptation Layer Type 2 (AAL2) is recommended for use as the basic switching and multiplexing technology for third generation mobile access networks since it allows for efficient and low delay transport for these VBR streams. We give quantifiable quality of service (QoS) description of the requirements for real time signal transfer and explore the possibility of service differentiation within the AAL2 multiplexer for different classes of voice calls. It has been found that a 9% increase in trunking; bandwidth efficiency can be obtained when employing service differentiation and priority queuing techniques-over the more common first in first out (FIFO) single queue system.
A new architecture of adaptive line enhancer

Adaptive line enhancer (ALE) is widely used for enhancing the sinusoids corrupted by noise or estimating and tracking the unknown frequencies of the sinusoids This paper presents a new architecture of ALE, called ALECA. It is shown that the new processor possesses the equivalent ARMA structure. Better convergence and lower sensitivity to the adaptive parameter of the adaptive transversal filter are observed in the ALECA. The hardware implementation shows that it substantially improves the processing gain of conventional ALE. <<ETX>>
Palmprint Verification by Scene Matching Approaches

This paper presents two novel approaches for palmprint verification by scene match- ing. In a sense, the process of palmprint verification can be regarded as matching one palmprint template with another palmprint sample taken under conditions of different illumination, sensor pose geometry, or types of sensor, and making a decision of whether they belong to the same person or not. Enlightened by the idea of scene matching algorithms, two efficient approaches by scene matching are presented for palmprint verification. A sub-image from the user’s training palmprint is intentionally extracted, and stored as a template. In the verification stage, the sample image is directly matched with the template without the step of ROI (Region of Interest) extraction. Whether the sample image and the template are from the same person or not is decided by their matching scores. Experimental evaluation results on two databases clearly demonstrate the effectiveness of the proposed approaches.
An Efficient and Verifiable Privacy-Preserving Data Aggregation Scheme for Wireless Sensor Networks

Data aggregation is an important techniques to save energy consumption in wireless sensor networks. However, the compromised aggregators may forge fake values as the aggregated results of their child nodes. In this paper, we proposed an efficient secure data aggregation scheme to overcome the problem. Integrated with the privacy homomorphism and the aggregate message authentication code techniques, our proposal can provide both end-to-end privacy and data integrity in data aggregation for sensor networks. The performance analysis shows that compared with other existing secure data aggregation schemes, the proposed scheme has remarkable advantages in terms of computation and communication overhead.
Portable orientation estimation device based on accelerometers, magnetometers and gyroscope sensors for sensor network

In this paper, we developed a portable orientation estimating device equipped with the Bluetooth network module. Accelerometers and magnetometers are used to measure absolute orientation against the Earth. Gyroscope sensors are used to measure the local angular velocity. By integrating the measured absolute orientation with the local angular velocity using an unscented Kalman filter (UKF), the stability and robustness of estimating absolute orientation are improved over either sensor alone. Since this device has the Bluetooth module, we can easily construct sensor networks.
Graph theory application to deregulated power system

This paper presents a methodology using graph theory to determine the specific generator contributions to different loads and the transmission system usage of different utilities. Starting from a power load flow solution, the method first identifies the buses as load buses or generation buses by getting the net power. Then a directed graph is formed with vertices representing buses and the edges representing transmission lines. Second, it constructs all possible directed and rooted subgraphs of the system from its generator vertices. Notice that the union of these subgraphs is the original directed graph. Using proportionality and average assumptions, it is possible to calculate the specific generator contributions to different loads and the transmission system usage of different utilities.
An ensemble approach to diagnose breast cancer using fully complex-valued relaxation neural network classifier

This paper presents a new improved classification technique using Fully Complex-Valued Relaxation Networks (FCRN) based ensemble technique for classifying mammogram images. The system is developed based on three stages of breast cancer, namely normal, benign and malignant defined by the MIAS database. Features like binary object features, RST invariant features, histogram features, texture features and spectral features are extracted from the MIAS database. Extracted features are then given to the proposed FCRN-based ensemble classifier. FCRN networks are ensembled together for improving the classification rate. Receiver Operating Characteristic (ROC) analysis is used for evaluating the system. The results illustrate the superior classification performance of the ensembled FCRN. The resultant ensembled FCRN approximates the desired output more accurately with a lower computational effort.
Intrusion detection using neural networks and support vector machines

Information security is an issue of serious global concern. The complexity, accessibility, and openness of the Internet have served to increase the security risk of information systems tremendously. This paper concerns intrusion detection. We describe approaches to intrusion detection using neural networks and support vector machines. The key ideas are to discover useful patterns or features that describe user behavior on a system, and use the set of relevant features to build classifiers that can recognize anomalies and known intrusions, hopefully in real time. Using a set of benchmark data from a KDD (knowledge discovery and data mining) competition designed by DARPA, we demonstrate that efficient and accurate classifiers can be built to detect intrusions. We compare the performance of neural networks based, and support vector machine based, systems for intrusion detection.
Fast Shading and Shadowing of Virtual Objects Using Shadowing Planes in Mixed Reality

We have developed a fast shading and shadowing method that uses the shadowing planes and the basis images in mixed reality (MR). The method is model-based and computable in real time by using a standard graphics processing unit (GPU) making it particularly effective when used with an outdoor MR application. To express the shadows of objects, we map the shadow images that are synthesized from the basis images rendered offline with the basis lights onto the shadowing planes, and we compute alpha blending with the objects. The shadowing planes are generated from convex hulls of objects. We obtain the radiance parameters of the real scene from an omnidirectional image and compute the linear sum of the radiance parameters and the basis images on the GPU. We applied this shadowing method to both an indoor and outdoor MR application and found it to be effective.
Randomness analysis on grain - 128 stream cipher

In this work, the randomness analysis of Grain-128 stream cipher algorithm by using NIST Statistical Test Suite is introduced. The NIST Statistical Test Suite is applied to determine the randomness of this algorithm. The Grain - 128 is based on LFSR, NLFSR and Boolean function with suitable for limited resources like gate count, power consumption and area chip. It uses 128-bit key and 96-bit initial value (IV). Based on our result of conducting the analysis, we obtained that this algorithm is not random at the 1% significance level.
A model for determining 3-D upper extremity net joint forces and moments during wheelchair propulsion

Describes the implementation of a method for the estimation of kinetic parameters imposed on and developed by the upper extremity joints during the activity of wheelchair propulsion. To calculate estimates of the three-dimensional net reaction forces and moments acting at the wrist, elbow, and shoulder joints during wheelchair propulsion, measures of upper body segment kinematics, external kinetics, and body segment anthropometry are necessary. The external forces acting on the human system were measured using an instrumented wheelchair pushrim. The kinematic data were collected by video digitization of body segment markers. Body segment anthropometric data were also collected. An anthropometric model, taking into consideration the non-proportional mass distribution of this population, was used for the estimation of body segment inertial parameters. The calculations were implemented by the use of a recursive algorithm which was previously developed. Three dimensional kinematic, kinetic, and anthropometric data were collected for 15 subjects. A sample result of the net joint force and moment calculations for these subjects is presented here.
Model-Based Design of Scanning Input Communication Aids: State of the Art and Research Issues

Abstract Scanning input communication aids are used by people with speech and motor disabilities. These aids are typically in the form of on-screen matrix of alphanumeric characters. To compose communicative messages, disabled users select characters from the matrix with scanning input methods. The problem faced by designers of such systems is to choose the best design from a large number of design alternatives. The problem may be alleviated by automated design methods based on user models. We performed a critical analysis of the related work and found that the present user models do not consider several factors that are important for user-system interaction. These include (a) scanning interaction, (b) visual search, and (c) user errors. In this paper, we present review and analysis of existing models and suggest directions for future research.
3D Integrated Circuits: Liquid Cooling and Power Delivery

Abstract Three-dimensional (3D) integration of ICs provides unique opportunities to improve bandwidth, latency, and power dissipation bottlenecks of interconnects (both on- and off-chip). However, while 3D IC integration improves signal interconnection, it also presents new challenges, especially in power delivery and cooling ("thermal interconnects"). The focus of this paper is on some of the key challenges and promising technologies to address power delivery, cooling, and signaling in a 3D stack of logic ICs.
Perception of Constructivist Learning Environment: Gender and School Type Differences in Siaya County, Kenya

Aims: The study aimed at investigating gender and school type differences in perception of Biology constructivist learning environment. Study Design : The study adopted a survey design. Place and Duration of Study: The study was carried out in Siaya County in Kenya between October and November 2013 during the school term. Methodology: The study sampled 815 grade 12 students (466 boys, 349 girls, 399 high achieving students and 416 low achieving students). Two instruments were used viz. Learners Perception Questionnaire (LPQ) and Learners Interview Guide (LIG). The data were analyzed using descriptive statistics, independent sample t - tests, two - way MANOVA and two - way ANOVA. The qualitative data were used to explain quantitative data. Results: The findings show that there existed statistically significant difference in perception between the low achieving schools and high achieving schools in favor of the low achieving schools in all the subscales of SPQ ( p =.00) and statistically significant gende r (Hotelling’s trace = . 131, F =
The clinical impact of orthotic correction of lower limb rotational deformities in children with cerebral palsy: a randomized controlled trial

Objective:This study aimed to evaluate the effectiveness of a static ground reaction ankle foot orthosis and strapping system on improving gait parameters in children with spastic diplegic cerebral palsy.Setting:The current study was conducted at the physical therapy faculty of Cairo University, Egypt.Subjects:This study included 57 children of both sexes, aged 6 to 8 years.Study design:Three-armed randomized control trial.Intervention:Participants in all groups received a traditional neuro-developmental physical therapy program that included standing and gait training exercises. Children in group A performed the training program without any orthotic management, in group B with the TheraTogs™ strapping system, and in group C with the TheraTogs™ strapping system and static ground reaction ankle foot orthoses. Children underwent treatment for two hours daily, except on weekends, for twelve successive weeks.Main measure:Gait speed, cadence, stride length, and hip and knee flexion angles in the mid-stance pha.
A Target Tracking Algorithm Based on Internet of Things Spatial Meshing

The three-dimensional spatial target tracking based on wireless communication technology has attracted more and more attention due to its importance in the field of Internet of Things.However,there are still some problems including calculation overhead is too high and power consumption is too large.Thus,a distributed three-dimensional target tracking mechanism for the environment of the Internet of Things is proposed.The network structure in the algorithm uses spatial clustering structure, which includes two tier sleep scheduling mechanisms and unite cluster head mechanism. A spatial segmental linear fitting method is adopted to track the target,which have effectively reduced the network overhead and improved tracking efficiency. It also provides a scheduling strategy how to wake up the sensor node guarantee to continue tracking it,when the mobile target lost.Simulation results show that the algorithm is better than the existing target tracking algorithm in tracking efficiency and have a lower power consumption.
Deploying a speech‐based information system as a research platform for speech recognition research in real environments

We have developed a speech-based information system for North Ikoma-shi Community Center, Takemuru-kun, as a platform for research into speech interfaces in real-life environments. The system consists of a single-question/single-answer-type speech interface based on large-vocabulary continuous speech recognition, and is capable of providing information regarding the community center and Ikoma-shi City. The system is located at the entrance to the community center and members of the public are free to communicate with the agent when the center is open. We conducted field tests over 5 months with the objective of observing how users interact with such a system and the collection of a log of user utterances. In this paper we first describe the structure of this system focusing on the speech interface component. As a result of the field tests we assembled around 1362 minutes of speech data from both male and female users of various ages. By analyzing these results, we show that although there are different trends in the content of utterances from adults and children, the system was effectively used. In experiments to evaluate the recognition performance of the baseline system on the actual user utterances, the system achieved a word recognition rate of 86% for adult utterances and a 76% correct response rate. However, we also confirmed that for reasons such as insufficient accuracy when used by children, there are still many issues remaining before such a speech interface can be deployed in practice. © 2005 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 88(12): 43–54, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.20232
A Bimodal Approach for Land Vehicle Localization

In this paper, we present a novel idea to integrate a low cost inertial measurement unit (IMU) and Global Positioning System (GPS) for land vehicle localization. By taking advantage of positioning data calculated from an image based on photogrammetry and stereo‐vision techniques, errors caused by a GPS outage for land vehicle localization were significantly reduced in the proposed bimodal approach. More specifically, positioning data from the photogrammetric approach are fed back into the Kalman filter to reduce and compensate for IMU errors and improve the performance. Experimental results are presented to show the robustness of the proposed method, which can be used to reduce positioning errors caused by a low cost IMU when a GPS signal is not available in urban areas.
Open Problems in Deadlock Control for Flexible Manufacturing Systems by Using Petri Nets

Deadlocks are a rather undesirable situation in a highly automated flexible manufacturing system. Their occurrences often deteriorate the utilization of resources and may lead to catastrophic results in safety-critical systems. This work surveys the open problems in deadlock control for automated manufacturing systems. The focus is deadlock prevention due to its large and continuing stream of efforts. A control strategy is evaluated in terms of computational complexity, behavioral permissiveness, and structural complexity of its deadlock-free supervisor. This study provides readers with a conglomeration of the open problems in this area and facilitates them in finding a suitable topic for their research.
Multiparametric analysis of non-invasive blood pressure variability including methods of nonlinear dynamics

The objective of this study was to determine the clinical feasibility of continuous, non-invasive blood pressure recordings for characterizing pathological changes in cardiovascular diseases. Tachograms (interbeat intervals and systolic pressure over the time) of two groups, one consisting of 26 cardiac patients with dilated cardiomyopathy (DCM) and the second group consisting of 24 healthy persons as a control group, were investigated. The tachograms were obtained from a Portapres noninvasive blood pressure monitor device. Artifacts and misclassifications were automatically detected and removed. From these corrected tachograms the authors extracted 41 parameters from different domains. Two (of 10) time domain, 4 (10) frequency domain and 4 (10) NLD parameters did separate significantly (p<0.01) the controls from the DCM patients. In this multiparametric and multidimensional approach the combination of 6 parameters from heart rate and mainly blood pressure variability improves the classification result of the discriminant function techniques to 90%. Furthermore, the authors confirmed the effectiveness of the measures from symbolic dynamics as a useful approach to classify the dynamics and intermittent variability change in blood pressure time series.
A 10-b 30-MS/s low-power pipelined CMOS A/D converter using a pseudodifferential architecture

A 10-b 30-MS/s low-power CMOS pipelined analog-to-digital converter (ADC) is described. The ADC using a pseudodifferential architecture and a capacitor cross-coupled sample-and-hold stage consumes 16 mW with a single 2-V supply. The chip is fabricated in a standard 0.3-/spl mu/m two-poly three-metal CMOS technology. The achieved low-power dissipation normalized by the sampling frequency of 0.52 mW/MHz is superior to other high-speed low-power ADCs reported. The ADC has a signal-to-noise-and-distortion ratio of 54 dB at an input frequency of 15 MHz. The maximum differential and integral nonlinearity are 0.4 and 0.5 LSB, respectively.
Synchronization considerations in meteor-burst communications

Consideration is given to the effect of frame synchronization on the performance of a meteor-burst communication system. It is shown that for a system which can tolerate a reasonable size frame synchronisation pattern on each packet, synchronization losses should not contribute much to overall performance degradation. That is, at the point where the probability of not synchronizing becomes significant, the number of errors in the packet due to random noise would be too large for satisfactory operation, even in the presence of perfect synchronization. <<ETX>>