Miracle-dz/UniFAR-FTUs huggingface dataset:
One Size Does Not Fit All: A Longitudinal Analysis of Brazilian Financial Malware

Malware analysis is an essential task to understand infection campaigns, the behavior of malicious codes, and possible ways to mitigate threats. Malware analysis also allows better assessment of attacker’s capabilities, techniques, and processes. Although a substantial amount of previous work provided a comprehensive analysis of the international malware ecosystem, research on regionalized, country, and population-specific malware campaigns have been scarce. Moving towards addressing this gap, we conducted a longitudinal (2012-2020) and comprehensive (encompassing an entire population of online banking users) study of MS Windows desktop malware that actually infected Brazilian bank’s users. We found that the Brazilian financial desktop malware has been evolving quickly: it started to make use of a variety of file formats instead of typical PE binaries, relied on native system resources, and abused obfuscation technique to bypass detection mechanisms. Our study on the threats targeting a significant population on the ecosystem of the largest and most populous country in Latin America can provide invaluable insights that may be applied to other countries’ user populations, especially those in the developing world that might face cultural peculiarities similar to Brazil’s. With this evaluation, we expect to motivate the security community/industry to seriously considering a deeper level of customization during the development of next generation anti-malware solutions, as well as to raise awareness towards regionalized and targeted Internet threats.
Ultra Low Power Photometry for Pulse Oximetry Applications*

Removing patient cables from the hospital environment, through the use of wireless sensors, improves hygiene, convenience and standard-of-care [1] [2]. In the drive to eliminate cable clutter, vital signs monitoring (VSM) is "going wireless. " This, in turn, is driving a trend for battery powered VSM sensors such as Saturation of Peripheral Oxygen (SpO2), Blood Pressure (BP), and Electro-cardiogram (ECG) sensors with a resultant demand for ultra-low-power circuits and algorithms. The architecture of the optical SpO2 pulse oximeter, which measures blood oxygenation and heartrate, is described with a focus on the drivers and contributors to system power. Two concepts for reduction of power in the pulse oximeter are explored. Firstly, an algorithm which modulates LED current according to the instantaneous heartbeat pulse phase is demonstrated in hardware and software. Secondly, an inductor centric LED driver, which provides the power efficiency of a switched mode current source and the system accuracy of a linear current source is introduced with feasibility demonstrated by circuit and system simulation.Clinical Relevance— The techniques discussed enable longer battery life for the SpO2 wireless VSM which, in turn, improves hygiene, convenience and, most importantly, mobility of the patient in the clinical setting.
A Modular System for the Harmonic Analysis of Musical Scores using a Large Vocabulary

The harmonic analysis of a musical composition is a fundamental step towards understanding its structure. Central to this analysis is the labeling of segments of a piece with chord symbols and local key information. In this work, we propose a modular system for performing such a harmonic analysis, incorporating spelled pitches (i.e., not treating en-harmonically equivalent pitches as identical) and using a very large vocabulary of 1540 chords (each with a root, type, and inversion) and 70 keys (with a tonic and mode), leading to a full harmonic characterization similar to Roman numeral analysis. Our system’s modular design allows each of its components to model an aspect of harmony at an appropriate level of granularity, and also aids in both ﬂexibility and interpretability. We show that our system improves upon a state-of-the-art model for the task, both on a previously available corpus consisting mostly of pieces from the Classical and Romantic eras of Western music, as well as on a much larger corpus spanning a wider range from the 16th through the 20th centuries.
ALGORITHM FOR POSITIONING OF ROTARY ACTUATORS BASED ON SHAPE MEMORY Cu-Al-Ni TENSILE FORCE ELEMENTS

This paper considers positioning algorithms for rotary actuators based on shape memory Cu-Al-Ni crystals. The actuator function scheme is provided. An algorithm for positioning of the actuator based on an actual rotary angle has been developed. Experimental results on the control algorithm and the actuator are presented. The functional characteristics of the actuator (rotation speed and positioning accuracy) are considered.
Cardiac Disease Representation Conditioned by Spatio-temporal Priors in Cine-MRI Sequences Using Generative Embedding Vectors

Cardiac cine-MRI is one of the most important diagnostic tools for characterizing heart-related pathologies. This imaging technique allows clinicians to assess the morphology and physiology of the heart during the cardiac cycle. Nonetheless, the analysis on cardiac cine-MRI is highly dependent on the observer expertise and a high inter-reader variability is frequently observed. Alternatively, the ejection fraction, a quantitative heart dynamic measure, is used to identify potential cardiac diseases. Unfortunately, this type of measurement is insufficient to distinguish among different cardiac pathologies. This quantification does not exploit all the heart functional information conveyed by cine-MRI sequences. Automatic image analysis might help to identify visual patterns associated with cardiac diseases in the cine-MRI sequences and highlight potential biomarkers. This paper introduces a conditional generative adversarial network that learns a mapping between the latent space and a generated cine-MRI data distribution involving information from five different cardiac pathologies. This net is guided from the left ventricle segmentation and the velocity field that is computed as prior information to focus on the deep representation of salient cardiac patterns. Once the deep neural networks are trained, a set of validation cine-MRI slices is represented in the embedding space. The associated embedding descriptor, in the latent space, is found by minimizing a reconstruction error in the generator output. We evaluated the obtained embedded representation as a disease marker by using different classification models in 16000 pathological cine-MRI slices. The representation retrieved by using the best conditional generative model configuration was used on the classifier models yielding an average accuracy of 90.04% and an average F1-score of 89.97% in the classification task.Clinical relevance—Construction of a topological embedding space, from generative representation, that fully exploits hidden relationships of cine-MRI and represent cardiac diseases.
Investigation of optimized topology for AC/DC Power supply unit in telecom in- dustry

Nowadays most power electronics converters are becoming more efficient and cost effective, and yet there is always a room left for improvement. This Master thesis deals with AC/DC power supply units in telecom industry which is implemented by a two-stage approach, which includes a power factor correction (PFC) stage followed by an isolated DC/DC stage. A literature study has been conducted to choose suitable topology candidates for telecom industry for power levels around 500W, 1kW and 2kW. The topology selection has been done considering efficiency, power density and cost. Active boost/classical boost, interleaved and bridgeless PFC are chosen to be suitable for further studies. Similarly, half bridge, full bridge and interleaved half bridge LLC resonant converters have also been selected for further study. This study indicates that, the bridgeless PFC converter, at 230V input, shows high efficiency across the given power range and has a peak efficiency of 98.5%. The half bridge LLC resonant converter is chosen to be efficient and cost effective for around 500W with a peak efficiency of 97.5%. The full bridge LLC resonant converter is chosen for power levels around 1kW with a peak efficiency of 97.5%. For a power range around 2kW, the interleaved half bridge LLC resonant converter is chosen with a peak efficiency of 97.7%. The combination of the PFC stage and LLC stage gives the AC/DC power supply unit (PSU). With the selected topology combinations, this converter can achieve a peak efficiency of 96.0%, 95.9% and 95.6% around 500W, 1kW and 2kW respectively.
On the application of accelerating moving walkways to support passenger processes in Amsterdam Airport Schiphol

Plans for the expansion of Amsterdam Airport Schiphol (AAS) are likely to cause longer walking distances inside the Schiphol Centrum passenger terminal. This can increase the risk in maintaining established time schedules and minimum connecting times for performing passenger processes. However, the currently installed Conventional Moving Walkways (CMWs) are not always capable of providing short travel times. In this paper, we investigate the application of Accelerating Moving Walkways (AMWs) to support passenger processes in AAS, particularly in terms of reducing travel times and walking distances. The current situation in Schiphol Centrum is analysed with regard to walking distances, passenger processing times and the time schedules and connecting times. The application of AMWs in the terminal is evaluated with regard to planning considerations such as location and transport capacity, as well as the expected contribution and benefit from the proposed systems in comparison to the current CMWs.
Fusion of Multi-Model Biometric Authentication Systems Using Iris and Palmprint

This paper presents fusion of two biometric traits, i.e., iris and palmprint, at matching score level architecture using weighted sum of score technique. The features are extracted from the pre-processed images of iris and palmprint. These features of a query image are compared with those of a template database image to obtain matching scores. The individual scores generated after matching are passed to the fusion module. This module consists of three major steps i.e., normalization, generation of similarity score and fusion of weighted scores. The final score is then used to declare the person as genuine or an impostor. The system is tested on template databases collected by the authors for 1250 samples and gives an overall accuracy of 97.04% with FAR of 0.58% and FRR of 4.34%.
Genetic analysis of resistance to stripe rust in cross of commercial bread wheat cv. Aflak × Avocet

Omrani, A. , Khodarahmi, M. and Afshari, F. 2019. Genetic analysis of resistance to stripe rust in cross of commercial bread wheat cv. Aflak × Avocet. Crop Breeding Journal 9 (1 & 2): 61-70 Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is one of the most devastating wheat diseases worldwide. Identification of virulence factors of the pathogen as well as using resistant cultivars are effective approaches in controlling wheat strip rust. Knowledge of genetic basis of resistance to stripe rust in commercial wheat cultivars is an important objective to ensure that diverse resistance genes are deployed in breeding programs. Five bread wheat commercial cultivars were evaluated for stripe rust using 40 Pst races that were collected from different locations in Iran. Among them cultivar Aflak showed seedling resistance to all races and the other cultivars displayed field resistance at the adult plant stage. To study the heritability and genetic basis of resistance to stripe rust in bread wheat cv. Aflak, it was crossed with susceptible cultivar Avocet‘s’ and F1, F2, BC1 and BC2 generations were developed. The generations along with their parents were planted in Randomized Complete Block Design (RCBD) with three replications under greenhouse conditions. The seedlings were inoculated using the race 230E158A+, Yr27+ urediniospores. The resistance components including infection type, latent period, pustule size and pustule density were recorded on single plants of each generation. The results of the weighted analysis of variance showed that there were significant (p ≤ 0.01) differences among generations for each of the four traits. Generations mean analysis showed that in addition to additive and dominance effects, epistasis, particularly the additive × dominance epistasis also played a significant role in controlling resistance to stripe rust. For all traits, high broad-sense heritability was observed. Moderate to high narrow-sense heritability was estimated for resistance components
Extracting and visualizing geo-social semantics from the user mention network on Twitter

This paper introduces an approach for extracting and visualizing geo-social semantics of user mentions on Twitter. The approach consists of three steps. First, data filtering and processing is performed to construct a directed area-to-area mention network in which tweets are aggregated into flow bins between geographic areas. Second, using flow bins as documents, a probabilistic topic model is employed to detect a collection of topics, and classify each area-to-area flow into a mixture of topics with differing probabilities. Third, for each topic, a modularity graph of mentions is obtained and visualized using a flow map and a topic cloud to infer semantics from the set of frequently co-occurring words for each topic. To demonstrate, a dataset of 19 million geo-tagged mentions during the primary elections (Feb-Jun, 2016) in the U.S. were analyzed. The results highlight changing patterns of symmetry, distance and clustering of flows by the topic of content.
A SmartNIC-based Load Balancing and Auto Scaling Framework for Middlebox Edge Server

Edge Cloud servers running network functions for cellular carriers must provide both high performance and high resource efficiency. Recent research has focused on load balancing across multiple servers in a large data center, yet load balancing within a single host has been neglected. Multi-core servers make use of multi-queue NICs in order to distribute incoming packets to different CPUs; however, existing approaches can lead to an unfair distribution of work since different flows may have significant variations in size and processing time. While the NIC has the detailed information about incoming traffic, it lacks knowledge about the server’s resources which prevents the hardware from fully supporting auto scaling and load balancing features. These problems are exacerbated for edge middlebox servers running virtual network functions, where processing latency is critical.SmartNICs offer a unique opportunity to resolve this problem with their increased programmability and flexibility. In this paper we present SmartLB - a programmable hardware framework to explore how middlebox servers can work together with SmartNICs to provide a cross-layer solution. Our evaluation shows that SmartLB can increase flow-level fairness, reduces tail latency, and support auto scaling feature for high performance network functions.
Decomposition Formulas for Second-Order Quadruple Gaussian Hypergeometric Series by Means of Operators H (α, β) and H (α, β)

Numerous decomposition formulas for various hypergeometric functions of several variables have been offered. In this paper, we aim to establish symbolic operator identities and decomposition formulas for second-order quadruple Gaussian hypergeometric series associated with Appell functions and Saran hypergeometric functions by mainly using mutually inverse symbolic operators H (α, β) and H (α, β), which were introduced in an earlier work. Mellin-Barnes type contour integrals are employed for proofs of the operator identities. Also we determine the regions of convergence of the 14 quadruple Gaussian hypergeometric series.
Community Analysis of Brain Functional Networks Reveals Systems-Level Integration in Olfactory Hedonic Perception

Olfactory hedonic perception involves complex interplay among an ensemble of neurocognitive systems implicated in sensory, affective and reward processing. However, the mechanisms of these inter-system interactions have yet to be well-characterized. Here, we employ directed functional connectivity networks estimated from source-localized EEG to uncover how brain regions across the olfactory, emotion and reward systems integrate organically into cross-system communities. Using the integration coefficient, a graph theoretic measure, we quantified the effect of exposure to fragrance stimuli of different hedonic values (high vs low pleasantness levels) on inter-systems interactions. Our analysis focused on beta band activity (13-30 Hz), which is known to facilitate integration of cortical areas involved in sensory perception. Higher-pleasantness stimuli induced elevated integration for the reward system, but not for the emotion and olfactory systems. Furthermore, the nodes of reward system showed more outward connections to the emotion and olfactory systems than inward connections from the respective systems. These results suggest the centrality of the reward system—supported by beta oscillations—in actively coordinating multi-system interactivity to give rise to hedonic experiences during olfactory perception.
How Informal Social Control Affect the Integrity of Political Participation among Young People?

This study aims to measure the influence of social control which consists of the dimensions of attachment, belief and commitment with the integrity of political participation of young people in social media. The study was conducted on 400 students in four for Higher Education Institutions (HEI) in Melaka, namely Universiti Teknikal Malaysia, Melaka (UTeM, Universiti Teknologi MARA, Melaka (UiTM), Universiti Multimedia (MMU), and Kolej Universiti Islam Melaka (KUIM). 400 questionnaires were distributed, only 388 were returned for analysis. Empirical results via the structural equation modeling (SEM) approach revealed a significant relationship between the dimensions of attachment, belief, and commitment to the integrity of political participation. The study found that social control is important to the integrity of political participation, which means that social control through the dimensions of attachment, belief, and commitment gives influence on the behavior of young people with integrity in social media. Furthermore, the integrity of political participation is widely influenced by belief, it showed that most of them believe that God will provide rewards in the form of wealth, status, and power in return. Direction for future research is presented.
The Ethics of Sustainability for Artificial Intelligence

Sustainability is widely considered a good thing and is therefore a matter of ethical significance. This paper analyzes the ethical dimensions of existing work on AI and sustainability, finding that most of it is focused on sustaining the environment for human benefit. The paper calls for sustainability that is not human-centric and that extends into the distant future, especially for advanced future AI as a technology that can advance expansion beyond Earth.
Hydraulic Characteristics of Rills

Rill density and rill flow rates were determined during rainfall simulation tests conducted at 11 sites located throughout the eastern United States. A mean rill density of 1.0 rills/m was found for the study locations. From measurements of the relative distribution of flow rates, a procedure is identified for partitioning flow between individual rills. Regression equations were developed for relating rill width and hydraulic roughness coefficients to flow rate. Equations were also derived for predicting mean flow velocity from visually determined measurements of advance velocity. Information reported in this study can be used to estimate hydraulic characteristics of rills.
A Machine Learning-based Neural Implant Front End for Inducing Naturalistic Firing

Despite being able to restore speech perception with 99% success rate, cochlear implants cannot successfully restore pitch perception or music appreciation. Studies suggest that if auditory neurons were activated with fine timing closer to that of natural responses pitch would be restored. Predicting the timing of cochlear responses requires detailed biophysical models of sound transmission, inner hair cell responses, and outer hair cell responses. Performing these calculations is computationally costly for real time cochlear implant stimulation. Instead, implants typically modulate pulse amplitude of fixed pulse rate stimulation with the band-limited envelopes of incoming sound. This method is known to produce unrealistic responses, even to simple step inputs. Here we investigate using a machine learning algorithm to optimize the prediction of the desired firing patterns of the auditory afferents in response to sinusoidal and step modulation of pure tones. We conclude that a trained network that consists of 25 GRU nodes can reproduce fine timing with 4.4 percent error on a test set of sines and steps. This trained network can also transfer learn and capture features of natural sounds that are not captured by standard CI algorithms. Additionally, for 0.5 second test inputs, the ML algorithm completed the sound to spike rate conversion in 300x less time than the phenomenological model. This calculation occurs at a real-time compatible rate of 1 ms for 1 second of spike timing prediction on an i9 microprocessor. This suggests that this is a feasible approach to pursue for real-time CI implementation.
Study on Optimal Position and Covering Pressure of Wearable Neck Microphone for Continuous Voice Monitoring

Vocal cord disorder is one of the important health problems, especially in noisy industrial sites where excessive voice is required. A convenient and reliable communication method is required in a noisy environment to prevent the related disorders. However, the signal sensitivity of previous neck microphones is still insufficient to accurately convey the voice. In this study, we developed a skin-attachable neck microphone with a lightweight and flexible form factor. Also, we optimized the attachment position and covering pressure to maximize the signal sensitivity. As a result, we obtained the optimal position near the thyroid cartilage and confirmed that the signal sensitivity is the highest when the covering pressure is approximately 4 mmHg.Clinical Relevance— People can measure the voice status using a wearable neck microphone at the optimal position and covering pressure. It provides a solution to keep the vocal cords in good health even in a noisy environment.
40-GHz/150-ns versatile pulsed measurement system for microwave transistor isothermal characterization

A versatile pulsed I(V) and 40-GHz RF measurement system is described with all the know-how and methods to perform efficient, safe, and reliable nonlinear transistor measurements. Capability of discrimination between thermal and trapping effects with a pulse setup is demonstrated. Capture and emission constant times of trapping effects are measured. A method to electrically measure the thermal resistance and capacitance of transistors with a pulse setup is proposed.