Miracle-dz/UniFAR-FTUs huggingface dataset:
Force Estimation for Prosthetic Hands Using Surface Electromyography

In order to improve amputees quality of life, electromyogram (EMG) prosthetic hands have been developed to compensate for some daily activities. A force estimation method for prosthetic hands using surface electromyotraphy is proposed in the paper to help amputees. One hand of the subject is tied to imitate amputees. The subjects would grip the force sensor with his healthy hand, while doing the same thing with the tied hand. Meanwhile, EMG signals and force are acquired by LABVIEW. Then a muscle-force model based on stepwise regression method is established . The experiments are carried out to evaluate the grasping force on a single degree of freedom prosthetic hand. The experimental results show that the proposed method is effective. Keywords-prosthetic hand; muscle-force mode; stepwise regression
Secured Authentication for De-Duplication byUsing Hybrid Cloud Approach

Data de-duplication is one in every of vital information compression techniques for eliminating duplicate copies of continuance information and has been wide employed in cloud storage to scale back the quantity of space for storing and save information measure to guard the confidentiality of sensitive information whereas supporting de-duplication, the confluent cryptography technique has been planned to encipher the info before outsourcing to higher shield information security, this paper makes the primary plan to formally address the matter of approved information de-duplication. Completely different from ancient de-duplication systems, the differential privileges of users are more thought of in duplicate check besides the info itself. We conjointly gift many new de-duplication constructions supporting approved duplicate sign in a hybrid cloud design. Security analysis demonstrates that our theme is secure in terms of the definitions per the planned security model. As an indication of construct, we tend to implement a model of our planned approved duplicate check theme and conduct test bed experiments victimization our model. We tend to show that our planned approved duplicate check theme incurs nominal over head compared to traditional operations.
ILC-based model reference neuro-adaptive technique for stochastic distribution control

The stochastic distribution control is important for certain industrial applications and cases where non-Gaussian noises exist. The problem has been initially solved by controlling the dynamical system formed by neural networks which approximate the output probability density function (PDF). Also, a modified version of iterative learning control (ILC) has been previously introduced by the authors to solve the output PDF shaping problem for linear weight dynamical systems. Looking into unknown non-linear weight dynamics, this paper presents a model reference neuro-adaptive control (MRNAC) approach for PDF shaping in non-Gaussian stochastic systems. The method is based on ILC and employs a neural network framework for modelling and controller. The time domain is first split up to batches. Then the proposed ILC method is implemented in two main domains namely within each batch and between any two adjacent batches. The design is carried out in three stages: a) NN-based non-linear dynamic system identification; b) MRNAC of the weight control loop within each batch; c) tuning the NN centres and widths between any two adjacent batches. Simulations confirm the effectiveness of the method.
Electrical method for on-wafer modal gain characterization of semiconductor optical amplifiers

1.Introduction The generic foundry model reduces the prototyping costs of Photonic Integrated Circuits (PIC) dramatically. One of the main Building Blocks (BB) within the generic foundry approach is the Semiconductor Optical Amplifier (SOA). It is the core element in every integrated laser source. Therefore, its accurate characterization in terms of modal gain is fundamental to the overall performance of the PIC. The main methods proposed for measuring modal gain are the Hakki-Paoli, the Thomson, and the fitting algorithm method. The draw-back of the Hakki-Paoli method is the need to resolve with very high spectral resolution the longitudinal modes of a laser cavity which includes an SOA and the cleaved facets. For typical chip lengths of several mm this method is not practical since a high resolution spectrometer is needed. The fitting algorithm method makes use of a non linear least square fitting algorithm over the Amplified Spontaneous Emission (ASE) of many SOAs and calculates the modal gain. The draw-back of this method lays in the large number of SOAs needed. The Thomson method in turn needs only two SOAs with length L and 2L to determine the modal gain. Our approach is based on the Thomson method. Its novelty lies in the integration of the SOAs with an optical filter and an array of integrated detectors. The integration of the SOAs with the optical filter and a detector array allows for electrical on-wafer characterization without the need to couple optical signals out of the chip.
Performance of TCP over radio link with adaptive channel coding and ARQ

The performance of transmission control protocol (TCP) over wireless links could degrade due to handoff, high bit error rate and long roundtrip delay on the air interface. Radio link protocol (RLP) uses channel coding and ARQ to mitigate impairment over wireless channels. In this paper, we study the performance of TCP over adaptive RLP. We investigate this problem in the context of the TDMA (IS-136 and IS-130) wireless network, where the wireless data is transmitted through the reliable RLP. The RLP is modified with an adaptive channel coding scheme. First, we analyze the throughput of RLP with combination of ARQ and fixed channel codes. Second, we consider an adaptive channel coding scheme using punctured convolutional codes and ARQ that maximizes the throughput under variable channel conditions. Third, we simulate the effect of radio environment and compare the performance of TCP over RLP with fixed and adaptive channel coding. Our simulation results indicate significant improvement in throughput performance for TCP over adaptive RLP.
Graphomotor Evolution in the Handwriting of Bengali Children Through Sigma-Lognormal Based-Parameters: A Preliminary Study

Handwriting has a natural evolution throughout child development. It is expected that the higher their educational level, the more fluent their handwriting. This paper is the first study in graphomotor evolution in Bengali children. This study is focused on the handwriting of the first five letters learnt in Bengali (Bangla) schools in Kolkata, India. We selected between three and six participants within three different classrooms and applied the Sigma-Lognormal model to their handwriting by using the iDeLog method. We present conventional and novel parameters extracted from the lognormality analysis of their handwriting. An assessment of extracted parameters is carried out with meaningful statistical differences observed within their handwriting evolution. Our results adds to the growing list of evidence supporting the lognormality principle of graphomotor evolution in children.
Do Code Smells Hamper Novice Programming

Recently, block-based programming languages like Alice, Scratch and Blockly have become popular tools for programming education. There is substantial research showing that block-based languages are suitable for early programming education. But can block-based programs be smelly too? And does that matter to learners? In this paper we explore the code smells metaphor in the context of block-based programming language Scratch. We conduct a controlled experiment with 61 novice Scratch programmers, in which we divided the novices into three groups. One third receive a non-smelly program, while the other groups receive a program suffering from the Duplication or the Long Method smell respectively. All subjects then perform the same comprehension tasks on their program, after which we measure their time and correctness. The results of the experiment show that code smell indeed influence performance: subjects working on the program exhibiting code smells perform significantly worse, but the smells did not affect the time subjects needed. Investigating different types of tasks in more detail, we find that Long Method mainly decreases system understanding, while Duplication decreases the ease with which subjects modify Scratch programs.
Creating a Data-Informed Culture in Community Colleges: A New Model for Educators.

Nancy Johnson is a community college president. She considers herself an effective educational leader. Faculty and staff generally like what the college is doing, and the governing board has just renewed her contract. Nevertheless, Nancy believes that the college could be better serving its students and the community. She has a good understanding of its performance based on local, state, and national reports, but when she talks about the data, her words seem to fall on deaf ears. Each month, a new report on some aspect of student success is presented to the governing board, but although the board has made student success a priority, members tend to make only perfunctory comments, often not related to the data presented. Nancy feels there is more that needs to be done to get the message across, but is unsure of what to do to make that happen.
N EW M ETRIC FOR HWMP PROTOCOL (NMH)

The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi -hop technology increasing the coverage of IEEE 802.11 Wireless Network and providing Internet access. Recently, many researchers proposed several metric routing protocols for wireless mesh networks(WMNs). Some metrics consider the interferences and other study the channel diversity of the distant links along the path between the source and the destination. In order to provide the best path between the source and the destination, this paper proposes a new routing metric named (NMH) New Metric for Hybrid Wireless Mesh Protocol(HWMP). NMH is based on two hop channel diversity and hop delay. The simulation results show that NMH out performs WCETT in terms of average network throughput, end -to-end delay and number of flows.
Control and Design of LCD Display Based on DSP

A display program of LCD display module controlled by DSP has been adopted,and the system's hardware and software are analyzed.This display program lies in timing simulation of writing and reading by using general I/O port.Using specific implementation methods of C language,and rich display of LCD module,a better interface between DSP and LCD display module is realized,and has been applied in the actual workplace.Test shows that the display system is stable,and has better display quality and faster refresh rate,can achieve the desired objectives.
Enhanced Magneto-Optical Activities of Modulated 
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 Multilayer Metamaterials

1 Graduate School of Science and Technology, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0192, Japan 2 Graduate School of Materials Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0192, Japan 3 CIC nanoGUNE, E-20018 Donostia-San Sebastian, Spain 4 Departamento de Física de la Materia Condensada, Universidad del País Vasco, UPV/EHU, E-48080 Bilbao, Spain
Reversible Watermarking using Differential Expansion on IPCM Macroblocks in H.264/AVC

This paper proposes a reversible watermarking technique that utilizes the IPCM macroblocks generated by the H.264/AVC encoder. The technique applies the concept of Differential Expansion (DE) to the pixels of the luminance and the chrominance components within the IPCM macroblocks of the P-frames. The performance of the proposed algorithm was tested for a number of video sequences and compared to similar techniques. The results show that the watermark thus embedded is of a high capacity while at the same time ensured minimal bitrate increase and negligible degradation of PSNR values.
Neurotechnology for Imagery Analysis

This research combined image alignment techniques with techniques for processing neurophysiological signals to find consistent classifiers of changed and unchanged aerial reconnaissance images. These physiological markers were independent of explicit responses, and in fact, can compensate for errors made by analysts. In addition, we found that measures of eye movements have significant potential for use in image triage. This research has applications not only to the Intelligence community but also in commercial applications, such as analysis of medical imagery, geological and environmental studies, and building construction and inspection.
Identifying Time-Varying Neuromuscular Response: Experimental Evaluation of a RLS-based Algorithm

Methods for identifying neuromuscular response commonly assume time-invariant neuromuscular dynamics. However, neuromuscular dynamics are likely to change during realistic control scenarios. In a previous paper we presented a method for identifying timevarying neuromuscular dynamics based on a Recursive Least Squares (RLS) algorithm. To date, this method has only been validated in a Monte Carlo simulation study. This paper presents an experimental validation of the same method. In the experiment, three different disturbance-rejection tasks were performed: a position task with the human instructed to minimize the stick deflection in front of an external force disturbance, a relax task with the instruction to relax the arm, and a time-varying task with the instruction to alternate between position and relax tasks. The position and relax tasks induce different time-invariant neuromuscular dynamics, whereas the time-varying task induces time-varying neuromuscular dynamics. The RLS-based method was used to estimate neuromuscular dynamics in the three tasks. The neuromuscular estimates were reliable both in time-invariant and time-varying tasks. These findings indicate that the RLS-based method can be used to estimate time-varying neuromuscular responses in human-in-the loop experiments.
NumCIL: Numeric Operations in the Common Intermediate Language

As multicore processors are now the standard for high performance machines, scientists must develop complex programs to fully utilize the processing power. In this article we present NumCIL, a new framework for expressing scientific and financial algorithms. By using n-dimensional arrays, a scientist can write sequential code without knowledge of parallel constructs. The library is a CIL library and can thus be used from languages as diverse as IronPython, F# and C#. As the ndimensional arrays are compatible with numpy ndarrays, it is possible to run some existing numpy programs unmodified on NumCIL. The NumCIL library can run entirely in CIL or offload computation to an external library. We compare NumCIL to numpy and show that the implementation is able to perform on par with numpy for a variety of problems taken from imaging, physics and financial computing domains.
A fully integrated 40-Gb/s clock and data recovery IC with 1: 4 DEMUX in SiGe technology

In this paper, a fully integrated 40-Gb/s clock and data recovery (CDR) IC with additional 1:4 demultiplexer (DEMUX) functionality is presented. The IC is implemented in a state-of-the-art production SiGe process. Its phase-locked-loop-based architecture with bang-bang-type phase detector (PD) provides maximum robustness. To the authors' best knowledge, it is the first 40-Gb/s CDR IC fabricated in a SiGe heterojunction bipolar technology (HBT). The measurement results demonstrate an input sensitivity of 42-mV single-ended data input swing at a bit-error rate (BER) of 10/sup -10/. As demonstrated in optical transmission experiments with the IC embedded in a 40-Gb/s link, the CDR/DEMUX shows complete functionality as a single-chip-receiver IC. A BER of 10/sup -10/ requires an optical signal-to-noise ratio of 23.3 dB.
Unassisted establishment of biological soil crusts on dryland road slopes

Abstract. Understanding patterns of habitat natural recovery after human-made disturbances is critical for the conservation of ecosystems under high environmental stress, such as drylands. In particular, the unassisted establishment of nonvascular plants such as biological soil crusts or biocrust communities (e.g., soil lichens, mosses and cyanobacteria) in newly formed habitats is not yet fully understood. However, the potential of biocrusts to improve soil structure and function at the early stages of succession and promote ecosystem recovery is enormous. In this study, we evaluated the capacity of lichen biocrusts to spontaneously establish and develop on road slopes in a Mediterranean shrubland. We also compared taxonomic and functional diversity of biocrusts between road slopes and natural habitats in the surroundings. Biocrust richness and cover, species composition, and functional structure were measured in 17 road slopes (nine roadcuts and eight embankments) along a 13 km highway stretch. Topography, soil properties and vascular plant communities of road slopes were also characterized. We used Kruskal–Wallis tests and applied redundancy analysis (RDA) to test the effect of environmental scenario (road slopes vs. natural habitat) and other local factors on biocrust features. We found that biocrusts were common in road slopes after ∼20 years of construction with no human assistance needed. However, species richness and cover were still lower than in natural remnants. Also, functional structure was quite similar between roadcuts (i.e., after soil excavation) and natural remnants, and topography and soil properties influenced species composition while environmental scenario type and vascular plant cover did not. These findings further support the idea of biocrusts as promising restoration tools in drylands and confirm the critical role of edaphic factors in biocrust establishment and development in land-use change scenarios.
Use and appropriation of new media technologies by teens: «The E-teen model» perspective

In this article it is reasoned that e-teens have different characteristics, attitudes, motivations and needs regarding new media use and appropriation. Consequently, teenagers have to be studied in a different context than any other group. We also argue that theories and models regarding uses, gratifications and appropriation of new media technologies are generalized and therefore cannot aptly be applied to the study of e-teens. Grounded in concepts from Uses and Gratifications, Model of Technology Acceptance, Technology Appropriation theories and a critical study of the developmental needs of e-teens, this study proposes a conceptual model that explains how e-teens use and appropriate new media technologies- the E-teen Model. Further, to test the model, the quantitative approach was used to select 300 teens from age 13 to 19 in senior high schools in the Greater Accra region of Ghana to answer questions in relation to the predictions in the E-teen Model. The results of the study show that educational, sociability and social inclusion, respectively, were the most popular gratifications sought and obtained by e-teens, s predicted in the model. The Correlation and Mann- Whitney U tests applied confirmed all three hypotheses formulated in the model. To provide support and substance to the e-teen model, other researchers are encouraged to test and extend it where necessary.
A transmit assignment algorithm for uplink flow control in WCDMA networks

We consider a distributed flow control algorithm which operates as part of the bandwidth management module of each cell in a multi-cellular wideband CDMA network. The algorithm controls the flow of packets time-slot by time-slot depending on the availability of radio resources as measured or predicted. A terminal's distance from the base station significantly influences the resources needed to transmit a packet, therefore terminals are grouped into spatial regions within which their resource requirements can be assumed equal. We formulate the position-based transmit assignment problem and propose a sub-optimal heuristic solution. Improvement in throughput and its trade-off with fairness among users in different regions is discussed. Results for average delay and throughput for a bursty packet arrival model are presented for two sets of radio resource conditions, an in-cell constrained system state and an out-of-cell constrained system state. The algorithm achieves high throughput and adapts easily to any desirable trade-off between throughput and fairness goals.
A Comparison Study on Machine Learning Algorithms Utilized in P300-based BCI

This study addresses Brain-Computer Interface (BCI) systems meant to permit communication for those who are severely locked-in. The current study attempts to evaluate and compare the efficiency of different translating algorithms. The setup used in this study detects the elicited P300 evoked potential in response to six different stimuli. Performance is evaluated in terms of error rates, bit-rates and runtimes for four different translating algorithms; Bayesian Linear Disciminant Analysis (BLDA), Linear Discriminant Analysis (LDA), Perceptron Batch (PB), and nonlinear Support Vector Machines (SVMs) were used to train the classifier whilst an N-fold cross validation procedure was used to test each algorithm. A communication channel based on Electroencephalography (EEG) is made possible using various machine learning algorithms and advanced pattern recognition techniques. All algorithms converged to 100% accuracy for seven of the eight subjects. While all methods obtained fairly good results, BLDA and PB were superior in terms of runtimes, where the average runtimes for BLDA and PB were 13 ± 2 and 15.6 ± 6 seconds, respectively. In terms of bit-rates, BLDA obtained the highest average value (22 ± 12 bits/minute), where the average bit-rate for all subjects, all sessions, and all algorithms was 18.76 ± 10 bits/minute.
Non contact shape and dimension measurements by LIDAR techniques of one of the biggest Italian caverns

Many measurements techniques have been proposed and used for the “digitalization of things”: laser scanner, high resolution camera, depth cam, structured light 3D scanner, hyper-spectral sensor, multi-spectral cam, photo modelling, etc. In this work LIDAR measurement techniques has been applied for the digitalization of a cave room of about 180 x 120 m and a height recently discovered up to 250 m, named Abisso Ancona in the Frasassi caves, in the municipality of Genga, Ancona province, Italy.
Box Counting Dimension of Red Blood Cells Samples when Filtered with Wavelet Transform

Automatic recognizing of different populations of several millions of red blood cells (RBCs) is a useful tool in Hematology and Clinical Diagnosis. In this work we studied samples of several millions of RBCs: on one hand healthy control RBCs and on the other hand control RBCs incubated with Trichinella spiralis larval parasites. The alteration on the cells membrane with the parasite can be studied with box-counting dimension on both samples. Previously we applied wavelet transform to all the samples in order to improve the results. The procedure to remove noise from an image is based on the decomposition of the observed signal in a set of wavelets and taking threshold values to select the appropriate coefficients through which the signal can be reconstructed. In our work we compared the results obtained when analyzing the raw signals and the ones obtained after applying wavelet transform, and the results were different and more clearly characterized when the signal were treated with wavelet transform. Finally, the present method using wavelet transform is suitable to optimize the characterization of the RBCs damage when incubated with the larval parasites.