Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of Alzheimer’s Disease in MRI based on Dictionary Learning and Heavy Tailed Modelling

Diagnosis of brain diseases is considered one of the most challenging medical tasks to perform, even for medical experts who rely on high-resolution anatomical images to identify signs of abnormalities by visual inspection. However, new computational tools which assist to automate this diagnosis have the potential to significantly improve the speed and accuracy of this process. This work presents a model to aid in the task of classification of structural Magnetic Resonance Imaging scans. The classification is performed using a Support Vector Machine, whilst the features to analyze belong to a dictionary space. Such space was mainly built from a dictionary learning perspective, although a predefined one was also assessed. The results indicate that features learnt from the data of interest lead to improved classification performance. The proposed framework was tested on the ADNI dataset stage I.
A Memristor-based Scan Hold Flip-Flop

The scan based design-for-testability (DfT) has been widely adopted in modern integrated circuits (ICs) design to facilitate manufacture testing. However, the transitions in scan cells result in much test power consumption during testing. The scan hold flip-flop (SHFF) can insulate the transitions in scan chain from the circuit under test to reduce test power while incurring much area overhead. We propose to solve this problem by adopting a memristor-based D flip-flop (DFF) into SHFF. The new design breaks down the design structure of conventional CMOS scan cells and adopts memristors into SHFF to reduce the number of transistors and hence the chip area. The functionality of the proposed design is verified to be correct by HSPICE simulation. Compared with the conventional SHFF cells, the area overhead is reduced 26.5%
Unsupervised face anti-spoofing using dual cameras based feature matching

Face anti-spoofing is a crucial part of face recognition system to protect subject’s privacy and life safety. Most current face anti-spoofing algorithms are based on feature extraction and machine learning. The performance of machine learning based approaches depends on the quantity and quality of the training data. In this paper, we propose an unsupervised face anti-spoofing method based on feature extraction and matching of a dual camera setup, which does not require offline training. The principle of our method is simple, intuitive, and generally applicable. The core idea of our method is exploiting the fact that a 3D face has different feature representations in images from two cameras with different view angles, as compared to that of a 2D spoofing face (either printed in a paper or showing on a screen). The proposed method has been benchmarked on a dataset created by our dual camera setup and shows an accuracy of 94.2%.
Automatic detection of High Frequency Oscillations (80-500Hz) based on Convolutional Neural Network in Human Intracerebral Electroencephalogram *

Recently, high-frequency oscillations (HFOs) of range 80-500 Hz in electroencephalogram (EEG) recordings of epilepsy patients are considered as a reliable marker of epileptic seizure. In the present work, an automatic detection of HFOs represents an isolated peak (an ‘island’) in a time-frequency plot based on convolutional neural network (CNN) was proposed. Initially, three patients with medically intractable epilepsy were recruited. They underwent a presurgical monitoring individually with around 54-90 channels of intracranial electroencephalograph (iEEG). Then, a specific CNN with five layers was developed with a total of 18,400 time-frequency island pictures marked with a label of either a real HFO or a false HFO. They are in the range of 80-500 Hz in the recorded iEEGs of 312 hours. Besides, over 7940 pictures including 3970 real HFO events and 3970 false HFO events except the training set were used to evaluate the performance of the current proposed method. As a result, the obtained precision of HFO events, the value of the recall, and the F1 score of the proposed CNN were found to be 94.19%, 89.37%, and 91.71%, respectively. Additionally, the automatic detection time of each HFO event is limited within 1-3 seconds. In summary, the proposed HFOs detector with deep learning would be more efficient and useful in the diagnosis of epilepsy as compared with the current manual determination of each HFOs from a long-term multichannel iEEGs recordings.
Markerless tracking of micro-endoscope for optical biopsy in stomach

This paper presents a landmark-free approach to estimate the fiberscope pose during endoscopic exploration for in-vivo optical biopsy. The fiberscope pose is estimated by fitting the projection of a virtual 3D cylinder into the endoscopic images. The cylinder axis is estimated based on the apparent contours using Plücker coordinates and its insertion is estimated by maximizing the similarity between binary masks. The performance of the method is evaluated on simulations: the mean Euclidian distance of fiberscopic tip between estimated pose and ground truth is 0.158 ± 0.113 mm. The in-vivo performance is assessed in two endoscopic sequences by comparing automatic RCF and manual segmentations in terms of angular deviation of the axis and Euclidian distance between the tip location. The estimation of the relative position of both cameras allows to perform registration between the two image modalities.
Evaluation of electroencephalography analysis methods

The extraction of expressive features from an electroencephalography (EEG) signal is necessary for classification of movement and movement imagination of the limbs. We introduce different preprocessing and feature extraction algorithms for this purpose and develop an algorithm that selects features by their feature importance. This selection is used as an evaluation measure for features, their preprocessing algorithms and the EEG electrodes. Our results show that most influential features for signal interpretation are: common spatial patterns, fractal dimensions, as well as, variance and standard deviation of the preprocessed data. We show that preprocessing with continuous wavelet transforms outperforms the other tested preprocessing algorithms. Furthermore, we show that high gamma frequencies (70-90 Hz) contain more information than the lower µ-rhythms (8-12 Hz) where event-related-desynchronization (ERD) is known to occur. The important EEG electrodes for this classification task are located in the left and right back of the motor-cortex. The proposed algorithm can be further used to create subject-specific and performance models for real-time classification.
A Surface Electromyogram Evaluation of the Postural Freedom Effects in Laparoscopic Surgery

It has been demonstrated that laparoscopic procedures benefit patients in terms of recovery time, exposure to infections and trauma. Nevertheless, it increases the number of problems for the surgeons, including the frequency and duration of awkward postures for surgeons. The repetition of these movements is considered the main cause for musculoskeletal disorders in surgeons’ upper limbs. The goal of this study is to evaluate the muscular activity and muscular fatigue effect produced by both, a conventional instrument and an instrument provided with the Postural Freedom (PF) feature; which consists in a ball socket articulation that allows a variable handle-to-shaft angle, on a conventional laparoscopic pistol-grip handle. Seventeen participants were evaluated during a static simulation using both instruments. Surface electromyography was used to compare the instruments in terms of muscular activity in each target position and muscular fatigue produced in the muscles trapezius, deltoids, biceps, and flexor carpi radialis. Trapezius and deltoids were the muscles most affected. Entrance and exit targets and targets facing the participants showed the higher muscular activity values. The PF prototype reduced muscular activity in all the muscles and in the majority of the target positions showing a reduction greater than 70% of the activity required by the trapezius and deltoid muscles in comparison to the conventional tool. Muscular fatigue was produced by both instruments but it presented lower frequency values with PF prototype. The results indicated that the use of conventional instruments impacts negatively on muscular activity during laparoscopic procedures, in terms of positions adopted. The PF feature in laparoscopic instrumentation reduced the muscular activity and also decreased the signals of muscular fatigue in the muscles evaluated in comparison with the conventional tool.
An Approach for Automatic Identification of Fundamental and Additional Sounds from Cardiac Sounds Recordings

This paper presents an approach for automatic segmentation of cardiac events from non-invasive sounds recordings, without the need of having an auxiliary signal reference. In addition, methods are proposed to subsequently differentiate cardiac events which correspond to normal cardiac cycles, from those which are due to abnormal activity of the heart. The detection of abnormal sounds is based on a model built with parameters which are obtained following feature extraction from those segments that were previously identified as normal fundamental heart sounds. The proposed algorithm achieved a sensitivity of 91.79% and 89.23% for the identification of normal fundamental, S1 and S2 sounds, and a true positive (TP) rate of 81.48% for abnormal additional sounds. These results were obtained using the PASCAL Classifying Heart Sounds challenge (CHSC) database.
Genetic Algorithm- A Literature Review

Genetic Algorithm (GA) may be attributed as method for optimizing the search tool for difficult problems based on genetics selection principle. In additions to Optimization it also serves the purpose of machine learning and for Research and development. It is analogous to biology for chromosome generation with variables such as selection, crossover and mutation together constituting genetic operations which would be applicable on a random population initially. GA aims to yield solutions for the consecutive generations. The extent of success in individual production is directly in proportion to fitness of solution which is represented by it, thereby ensuring that quality in successive generations will be better. The process is concluded once an GA is most suitable for the issues that need optimization associated with some computable system. John Holland may be regarded as funding father of original genetic algorithm and is attributed to year 1970’s as funding date. Additionally a random search method represented by Charles Darwin for a defined search space in order to effetely solve a problem. In this paper, what is genetic algorithm and its basic workflow is discussed how a genetic algorithm work and what are the process is included in this is also discussed. Further, the features and application of genetic algorithm are mentioned in the paper.
Does repetitive Transcranial Magnetic Stimulation (rTMS) have therapeutic effects on Dynamic Balance of Children with Cerebral Palsy? *

Our big goal in this research was to evaluate the therapeutic effects of repetitive Transcranial Magnetic Stimulation (rTMS) on cerebral palsy (CP) children with balance deficits. Four spastic hemiplegic CP children were participated; the experimental group received rTMS training 4 days a week for 3 weeks and then for the next 3 weeks they received typical occupational therapy just after rTMS therapy. The control group received placebo rTMS instead of real one accordingly. Their dynamic balance was evaluated before the start of the treatment and 6 weeks after it. Center of pressure (COP) and center of mass (COM) features were regarded as dynamic balance parameters. Our results showed that the peak to peak of COP, COM, COM-COP, COM-COP inclination angles all improved for both experimental (15-86%) and control group patients, though there was less improvement about 8-46% in features of the control patients. Our results demonstrate that intensive sessions of the rTMS training could have the potential to enhance the therapeutic effects of typical occupational therapy that can produce dynamic balance improvements in CP children compared to using the occupational therapy by itself.
Retinal Thickness Analysis in High Myopia based on Medial Axis Transforms

This paper presents a retinal thickness analysis method from 3D images acquired by optical coherence tomography (OCT). Given OCT images with segmented boundaries of retinal layers, medial axes of the layers are computed by medial axis transforms (MAT), and thickness is evaluated based on Euclidean distance fields. Since the MAT computes the closest points on the boundary of the layer, it can compute more correct thickness than conventional methods that evaluate Y-axis-aligned thickness. Experimental results show that our method can detect thin-parts around distorted regions, or a clue of high myopia. This is useful for early diagnosis of high myopia and other eye diseases.
Spatial resolution adaptation framework for video compression

This paper presents a resolution adaptation framework for video compression. It dynamically applies spatial resampling, trading off the relationship between spatial resolution and quantization. A learning-based Quantization-Resolution Optimization (QRO) module, trained on a large database of video content, determines the optimal spatial resolution among multiple options, based on spatial and temporal video features of the uncompressed video frames. In order to improve the quality of upscaled videos, a modified CNN-based single image super-resolution method is employed at the decoder. This super-resolution model has been trained using compressed content from the same training database. The proposed resolution adaptation framework was integrated with the High Efficiency Video Coding (HEVC) reference software, HM 16.18, and tested on UHD content from several databases including videos from the JVET (Joint Video Exploration Team) test set. Experimental results show that the proposed method offers significant overall bit rate savings for a wide range of bitrates compared with the original HEVC HM 16.18, with average BD-rate savings of 12% (based on PSNR) and 15% (based on VMAF) and lower encoding complexity.
Effect of Static Respiratory Volume on the Waveform of Cardiac-induced Sternal Vibrations

Cardio-respiratory activity originating in the chest creates vibrations that diffuse through the organs to the thoracic wall. The vibrational waves were detected in all six degrees of freedom by an inertial motion sensor at the xiphoid process of the sternum. Vibrational cardiography (VCG) combines the detection of vibrations via acceleration, termed as seismocardiography, and gyration, termed as gyrocardiography. The objective of this study was to determine the effect of static respiration volume on the morphology of cardiac-induced waveforms in the VCG signal. In this study, 24 subjects were tested while holding breath at peak inhalation, and at peak exhalation. Ensemble averages of the waveforms showed larger variations in the signal when the lungs were inhaled for both the primary and secondary heart sounds. Inter-subject variability was accounted for by averaging all waveforms and calculating the root mean squared value over a sliding window of 60 milliseconds. The peak amplitudes of both heart sounds were consistently larger for high lung volumes. However, the ratio of primary to the secondary heart sound was found to be inversely proportional to lung volume. These opposing effects offer a strong analysis tool for the determination of relative inhalation volume using VCG morphology alone.
An Optimization Based on General Airport of Complex Condition

With the development of general aviation transportation, general airports are gradually being built, one of the urgent problems to be solved is optimizing the site selection of general airports to improve flight safety and economy. In order to solve this problem, this paper studies the requirements of clearance and flight performance of the general airports, the factors which affect the optimization of airport site selection with the complex terrain are analyzed, the general airport site selection optimization model is established, and designs a multi-objective genetic algorithm to solve the problem. Based on the actual operation data of a general airport, a set of Pareto optimal solutions is obtained, which is better than the traditional method, the validity of the model is fully verified.
Creating a healthy working environment for older employees as part of social responsibility

Purpose The purpose of this paper is to present the importance of a healthy working environment and approaches to establish a healthy working environment of older employees and their impact on work engagement of older employees. The working environment that is not suitable and adapted for older employees presents a big challenge for Slovenian and other companies in which the work force is getting older. Hence, this paper develops a model of a healthy working environment for older employees, in which they could feel well because of its positive affect on their health. Design/methodology/approach The research method in this paper was the descriptive-correlative type. After a systematic review of literature, which relates to this topic, the authors used the compilation method. In addition to descriptive statistics, factor analysis and regression analysis were used in this paper. Findings Considering the demographic changes and active ageing in the workplace, age diversity of employees has to become a part of the general strategy of a company to ensure equality and diversity. Adequate working conditions, which should exist in every company, contribute to the improvement of healthy working environment for older employees and their work-engagement. This paper presents that approaches to establish a healthy working environment of older employees have a positive impact on work-engagement of older employees. Practical implications The stated findings will help companies to better understand and manage their older employees and the importance of establishing a healthy working environment for older employees with which the work-engagement of older employees can be improved. Socially responsible behavior benefits all in this way, too. Originality/value This paper is based on forming a research model for creating a healthy working environment for older employees as a part of social responsibility. The main objective of this paper is to examine the impact of establishment of a healthy working environment for older employees on the work engagement of older employees in Slovenia.
The adoption of Web 2.0 technologies in academic libraries: A comparative exploration

This paper addresses the adoption and non-adoption of communication methods such as social media and explores the implementation of Web 2.0 technologies and their use in academic libraries. I interviewed 16 library employees from six academic university libraries in the Flanders region of Belgium and in South Africa. I explored five academic university libraries in the urban regions of Flanders and South Africa and one situated in a rural region of South Africa. This article discusses the benefits of using social media as a communication tool to engage with students. The results demonstrate that ‘ease of use’ was portrayed as a beneficial construct and has a positive influence on behavioural intention and use of Web 2.0 technologies. A comparison on the adoption of social media between the two countries indicate that financial resources, infrastructure and management support are crucial determining factors in service delivery.
Potential Biases in Big Data: Omitted Voices on Social Media

While big data offer exciting opportunities to address questions about social behavior, studies must not abandon traditionally important considerations of social science research such as data representativeness and sampling biases. Many big data studies rely on traces of people’s behavior on social media platforms such as opinions expressed through Twitter posts. How representative are such data? Whose voices are most likely to show up on such sites? Analyzing survey data about a national sample of American adults’ social network site usage, this article examines what user characteristics are associated with the adoption of such sites. Findings suggest that several sociodemographic factors relate to who adopts such sites. Those of higher socioeconomic status are more likely to be on several platforms suggesting that big data derived from social media tend to oversample the views of more privileged people. Additionally, Internet skills are related to using such sites, again showing that opinions visible on these sites do not represent all types of people equally. The article cautions against relying on content from such sites as the sole basis of data to avoid disproportionately ignoring the perspectives of the less privileged. Whether business interests or policy considerations, it is important that decisions that concern the whole population are not based on the results of analyses that favor the opinions of those who are already better off.
Prediction of average mobility of ions from corona discharge in air with respect to pressure, humidity and temperature

Pressure, temperature and humidity are the basic parameters of air, which affect the average mobility of ions in it. In this paper a series of the average mobilities of ions in corona discharge in air at different pressures, temperatures and humidities are measured using an apparatus for generating parallel plane ion flow field in a climatic test cabinet. The pressure, relative humidity, and temperature is from 80 to 110 kPa, 20 to 85%, and −10 to 40°C, respectively. The variation of the average mobility of ions in corona discharge in air, with respect to pressure, humidity and temperature, is discussed and calculated from the fundamental mobility equation.
Nonlinear Control of a Boost DC/DC Converter for Photovoltaic MPPT Systems Using a TMS320F28379D Microcontroller

This work presents a nonlinear controller of a boost dc/dc power converter for photovoltaic (PV) maximum power point tracking (MPPT) systems. The scheme of the proposed controller consists of the design of a nonlinear controller for the duty cycle generation. For this purpose, a simple and low- cost voltage-oriented controller is proposed in this study. In fact, this control algorithm is suitable to efficiently track fast irradiance changes. Consequently, the efficiency of the overall MPPT system is improved by avoiding loss of PV power caused by i) oscillatory responses due to varying irradiance conditions and ii) load disturbances. In addition, by assuming passivity properties of the constitutive relationship of the load element, internal stability of the closed-loop system is guaranteed for different load conditions, which are applicable for most PV applications. Besides, the internal stability allows to consider load scenarios affected by bounded disturbances. Finally, the proposed MPPT control system is implemented by using a proportional-integral-derivative controller, thereby providing a low-cost solution, which is programmed in the TMS320F28379D DSC Board. Experimental results by considering several scenarios, i.e., i) irradiance changes, ii) changes of setpoint and iii) load disturbances are illustrated to validate the effectiveness of the proposal.