Miracle-dz/UniFAR-FTUs huggingface dataset:
Is it 5G or not? Investigating doubts about the 5G icon and network performance

Following the rollout of the first 5G networks in 2018, press reports in the US began to emerge that the 5G icon on smartphones was not depicting 5G connectivity. Such reports about ‘fake’ 5G icon reverberated across the industry, exposing a mismatch between the icon on the phone and the actual experience of users. Between 2018 - early 2020, 3GPP and the GSMA sought to provide industry guidance on what and when the 5G icon should be used and how 5G performance can differ from 4G. In this paper, we introduce an intuitive four stage investigation framework to explore the technical considerations that ultimately confirm the veracity of the 5G connectivity. Then, following the launch of 5G in the UK in late 2019, we set out to explore if there were similar confusion on 5G notification and performance in the country. We conducted field measurements at the five busiest train stations in the UK, during rush hour, using a Samsung 5G S10 and a Samsung S6 Edge+ 4G device to compare 5G notifications and perceived network performance on 4G and 5G networks. We observe confusing messages to the user - device icon says 5G but Android’s TelephonyManager API says 4G; worst cases for latency and uplink/downlink speeds were minimised but best case performance was the same on 4G and 5G devices. Based on our observations, and while we expect any lingering concerns to be ironed out as 5G deployment and adoption matures, we draw lessons that should guide the industry to avoid doubts about the icon and connectivity in 6G.
Integrating a Voice Analysis-Synthesis System with a TTS Framework for Controlling Affect and Speaker Identity

This paper reports an experiment exploring how a voice analysis-synthesis system, GlórCáil, can be used to add expressiveness to the synthetic voice in text-to-speech (TTS) systems. This implementation focuses on the Irish ABAIR TTS voices, where such voice control would facilitate many current/envisaged applications. GlórCáil allows voice control of synthesized speech, and for this experiment was integrated into a DNN-based TTS framework. Utterances were generated with f0, voice quality and vocal tract parameter manipulations targeting shifts in speaker identity and in the affective coloring of utterances. Scaling factors used for the manipulations were suggested in an earlier study. They involved global changes without sentence-internal dynamic variation, with a view to ascertain whether such global shifts might alter listeners’ perception of speaker identity and affect. Results demonstrate affect shifts compatible with expectations. However, there were confounding factors. The female/child voices were poorly differentiated, which was expected given the similarity in the scaling factors used. The affect transformations suggest the baseline voice used had an intrinsically sad quality so that there is weak differentiation between the sad and no emotion stimuli. Male angry voice was the least successful, suggesting that dynamic, within-utterance variation is essential for the signaling of certain affects.
Face Liveness Detection Competition (LivDet-Face) - 2021

Liveness Detection (LivDet)-Face is an international competition series open to academia and industry. The competition’s objective is to assess and report state-of-the-art in liveness / Presentation Attack Detection (PAD) for face recognition. Impersonation and presentation of false samples to the sensors can be classified as presentation attacks and the ability for the sensors to detect such attempts is known as PAD. LivDet-Face 2021 * will be the first edition of the face liveness competition. This competition serves as an important benchmark in face presentation attack detection, offering (a) an independent assessment of the current state of the art in face PAD, and (b) a common evaluation protocol, availability of Presentation Attack Instruments (PAI) and live face image dataset through the Biometric Evaluation and Testing (BEAT) platform. The competition can be easily followed by researchers after it is closed, in a platform in which participants can compare their solutions against the LivDet-Face winners.
Design of Multiband dipole antenna for 4×4MIMO in LTE Application

The Multiband dipole antenna for 4×4 MIMO for LTE Application of indoor small cell base station is proposed. The proposed antenna can provide two wide operating bands of 1710–2690 and 3400–3600MHz that the resonant modes generated by the coupling stub and silt. This planar 4-port Multiband MIMO antennas are placed symmetrically on the four edges of the substrate which achieve the pattern and polarization diversity characteristics. The envelope correlation coefficient (ECC) is less than 0.1 in the all status for 4×4 MIMO applications.
On the Complete Radiation Pattern of a Vertical Hertzian Dipole Above a Low-Loss Ground

The complete radiation field pattern of a vertical Hertzian dipole antenna on or above a lossless or low-loss dielectric half-space is studied using a rigorous Sommerfeld formalism. The reflected fields in the air above the interface and the subsurface fields transmitted into the dielectric are computed by numerical integration of the Sommerfeld integrals. Furthermore, to facilitate the physical interpretation of these results, a detailed asymptotic saddle-point integration method analysis is presented, which includes terms that vary in magnitude with the second power of the inverse distance from the dipole. It is shown that the second-order field constituents are dominant at the interface, where the first-order geometrical fields vanish. These second-order terms comprise an evanescent wave propagating along the interface in the upper half-space and a lateral wave, also known as the head wave, which propagates in the subsurface along the direction of the critical angle. The two waves only exist between two cones whose half-angles are equal to the critical angle, and their interference with the geometrical-optics fields determines the radiation pattern for elevation angles near the horizon. The far zone surface fields on either side of the interface comprise two second order waves that propagate along the interface, one with the phase velocity in the air, and the other with the phase velocity in the dielectric. Away from the interface, the leading field components vary with the first power of the inverse distance, which explains the sharp dip in the field pattern at the interface—a phenomenon known as the interface pattern extinction. Another distinctive phenomenon, observed in the subsurface field pattern, is the rippling that occurs in the angular range between the critical angle cone and the interface. The asymptotic analysis has shown that this pattern scalloping results from the interference of the lateral wave with the geometrical-optics spherical wave.
Periodic impulse feature separation by combination of bi-frequency map and non-negative matrix factorization

For the fault detection of rolling element bearings, generally, the periodic impulsive fault features would be mixed with other cyclic components in the spectral coherence map of the raw vibration signal. Authors aim to extract faint fault features from the bi-frequency map, especially in the incipient fault cases. To achieve this goal, this paper presents a novel method termed Double Spectrum (DS), where Non-negative Matrix Factorization (NMF) is used to analyze bi-frequency maps in two steps: firstly, the basis matrix helps identify the cyclic frequencies where the high-amplitude cyclic components locate, and secondly, the activation matrix is considered as a set of filter bands which are adopted for further demodulation and envelope analysis. We combine the information contained in the basis matrix and the activation matrix by multiplying the enveloped spectrum and the corresponding column of basis matrix to enhance the fault features. Tests on the experimental data and comparisons to the state-of-the-art diagnosis techniques have verified the performance of the proposed method.
Service Customization: Optimizing Value Creation and Capture by Designing the Customer Journey

Service customization is a central issue in sociotechnical service ecosystems, enabled and fueled by new data-driven approaches, and with the goal of increasing value creation for the customer, and value capture for the provider. In this paper, we address the question of how to design service customization within the provider-customer interaction. We propose a novel quantitative approach for modeling the relation between customization level at the various steps of the customer journey on the one hand, and its effect on the value created for customer and provider on the other hand. Combining this model with approaches from multi-objective optimization, optimum levels of customization from both the customer and the provider perspective can be determined. Thus, the proposed model allows the identification of service designs which are optimized in terms of their value creation and value capture.
An improved cepstrum analysis method to diagnose faults in bearings

Cepstrum analysis is suitable for decomposing and identifying fault features of different types. However, it is tough to find the weak fault frequencies from running mechanical systems in heavy background noises. In order to diagnose faults accurately, an improved version of cepstrum analysis is proposed. First, the cepstrum analysis is employed to separate and obtain the periodic parts of dense modulated signals. Second, the cepstrum line in associate with the lower periodic components is removed from cepstrum by carefully selecting the thresholding of cepstrum value. The signal-to-noise ratio (SNR) is enormously modified by filtering out the low-frequency terms interfered by the rotational speed and its harmonics. Finally, the traditional Hilbert envelope analysis is carried out for the reconstructed time-domain signal to extract bearing fault features. The experiment investigations of bearings with inner race faults are performed. The comparison results show that the present improved version of cepstrum analysis has higher performance to detect faults.
On The Behavior of Partial Oxidation of Methane in a Pd-Membrane Reactor under Periodic Operation Conditions

In the current study, a theoretical analysis of the behavior of the reaction of partial oxidation of methane performed in a palladium membrane reactor, operating under periodic conditions was carried out. The periodic operations in the pd-membrane reactor are supposed to be created by forcing some inputs cyclically using a sinusoidal function. The concerned inputs are the composition and mainly the steam and oxygen in the reactor inlet and the sweeping gas in the permeation side. It was found that the periodic operations applied to these inputs are beneficial since the predicted performance is improved. When the steam to methane ratio and the sweeping gas are running periodically both in phase, the conversion of methane and the pure hydrogen recovery can exceed the steady state levels and the H2/CO ratio is significantly reduced compared to the steady state operation.
A Blockchain Based Link-Flooding Attack Detection Scheme

Distributed Denial-of-Service (DDoS) attack is a long-lived attack that is hugely harmful to the Internet. In particular, the emergence of a new type of DDoS called Link Flooding Attack (LFA) makes the detection and defense more difficult. In LFA, the attacker cuts off a specific area by controlling large numbers of bots to send low-rate traffic to congest selected links. Since the attack flows are similar to the legitimate ones, traditional schemes like anomaly detection and intrusion detection are no longer applicable. Blockchain provides a new solution to address this issue. In this paper, we propose a blockchain-based LFA detection scheme, which is deployed on routers and servers in and around the area that we want to protect. Blockchain technology is used to record and share the traceroute information, which enables the hosts in the protected region to easily trace the flow paths. We implement our scheme in Ethereum and conduct simulation experiments to evaluate its performance. The results show that our scheme can achieve timely detection of LFA with a high detection rate and a low false positive rate, as well as a low overhead.
Qualification and Appointment of Staff for Project Work in Implementing IT Systems Under Conditions of Uncertainty

The main criterion for the implementation of information systems in enterprises is the quality of all project work. The quality of the whole project depends on the professionalism of the team, the competent distribution of employees to work, which corresponds to the professional qualification parameters of each representative. The article considers the problems of determining the competence of staff who are the executors of tasks on the project, algorithms for certification and assessment of staff qualifications. The matrix for the formation of an estimation of compensations of the employees who are engaged in software development, according to qualification needs of the companies whose main activity is development of software products - information systems is presented. Each member of the team meets the criteria of competence of the work for which he will be assigned, taking into account the assessments received. The main parameters of personnel evaluation are determined, which include not only the available knowledge and experience, but also the personal qualities of the employee. The algorithm of division of employees on project works in the conditions of uncertainty depending on the level of professional competence and necessary qualification values of tasks of the project is resulted. This is an important factor in the implementation of design work on modern flexible methodologies. Prospects for the development of this area in the field of project management for the implementation of information systems and the development of a subsystem for automated personnel evaluation.
DeepSynthBody: the beginning of the end for data deficiency in medicine

Limited access to medical data is a barrier on developing new and efficient machine learning solutions in medicine such as computer-aided diagnosis, risk assessments, predicting optimal treatments and home-based personal healthcare systems. This paper presents DeepSynthBody: a novel framework that overcomes some of the inherent restrictions and limitations of medical data by using deep generative adversarial networks to produce synthetic data with characteristics similar to the real data, so-called DeepSynth (deep synthetic) data. We show that DeepSynthBody can address two key issues commonly associated with medical data, namely privacy concerns (as a result of data protection rules and regulations) and the high costs of annotations. To demonstrate the full pipeline of applying DeepSynthBody concepts and user-friendly functionalities, we also describe a synthetic medical dataset generated and published using our framework. DeepSynthBody opens a new era of machine learning applications in medicine with a synthetic model of the human body.
Malware Detection and Classification Using fastText and BERT

Among the types of cyber-attacks, malware that causes high financial losses for institutions and individuals is the biggest threat to computer systems. Kinds of malware increase day-by-day and new types are released, which can easily infect our computers through injection vectors such as e-mail, websites, web applications that we use constantly. It is very important to automatically detect them and protect our computer systems against malware threats. Analysis methods are available to protect our computer systems against malware threats. Dynamic analysis is highly effective in obtaining behavioral information of the software on the computer system and can obtain the API call sequence information of the malware. However, the API call sequence can be too long and difficult to understand. This paper proposes subjects the API call sequence to the purification and optimization process. This behavior information is used for the automatic classification task and then used for classification and word representation tasks using the fastText and BERT algorithms. It was used on three different open data sets to see the success of the method. The fastText model performed better than the BERT model in classification and detection tasks.
Dynamically controlled double-well optical potential for colloidal particles

This study presents a simple modulation scheme to dynamically create time-averaged optical potentials to trap colloidal particles using acousto-optical modulation. The method provides access to control experimentally relevant parameters of a tunable double-well potential. We show experimental data successfully adjusting the trapping distance in the range 20–2000 nm and discuss situations arising when reconstructing time-averaged optical potentials from trapped particle data. This is the first step towards studying colloidal particles in dynamically modulated optical potentials to explore the stochastic thermodynamics of mesoscopic systems and small-scale thermo-mechanical machines.
Improving accuracy of an existing semantic word labelling tool using word embeddings

Annotated corpora allow researchers to carry out studies that include linguistic phenomenona such as grammatical categories or even knowledge by means of semantic annotation. Semantic annotation in corpus linguistics is often included into every lexical unit of the corpus using a word labelling tool. Resources such as lexicons or ontologies are very useful for this purpose. However, current sizes of these resources for languages different from English are not always appropriate. This paper proves that an updated version of an existing NLP baseline can be extended for different domains and, as a consequence, it is able to improve Spanish token accuracy by up to 30% in comparison with using only a small lexicon.
Task Caching in Vehicular Edge Computing

Vehicular edge computing combines mobile edge computing with vehicular ad hoc networks and endeavors to mitigate the workloads of vehicles. Inspired by the content-centric mobile edge caching, we in this paper propose a cache enabled task offloading in the vehicular edge computing in hope to jointly optimize the response delay and the energy consumption at the road side unit. To be specific, both the communication and computation models are refined and a greedy algorithm is then put forward to solve the optimization problem. Numeric results have shown the advantages of the algorithm with regards to response latency and energy consumption in comparison with other related strategies.
HID 2021: Competition on Human Identification at a Distance 2021

The Competition on Human Identification at a Distance 2021 (HID 2021) is to promote the research in human identification at a distance and to provide a benchmark to evaluate different methods. HID 2021 is the second follow-up from the first one, HID 2020. The dataset size and the evaluation protocal are the same with the previous competition, but the data in the test set has been changed. The paper firstly introduces the dataset and the evaluation protocol, then describes the methods from the top teams and their results. The methods show how to achieve state-of-the-art performance on gait recognition. The results in HID 2021 are better than those in HID 2020. From the comparisons and analysis, some useful conclusions can be drawn. We hope more improvements can be achieved by better followup competitions.
Stealth Evaluation of the OFDM Communication System

The necessity of increase the stealth of the digital radio communication systems is showed in the paper. Functional principles, advantages and application fields of communication systems with OFDM modulation are reviewed. The possibilities of using application of signals with OFDM modulation in the stealthy command radio network is also analyzed. For this purpose, simulated the “shape” of the OFDM-signal in pseudo-phase space and visually evaluated that its structure is close to regular processes. The stealth of the systems with OFDM-modulation using BDS-statistic in comparison with “white” noise is estimated. The ways to increase the stealth of OFDM signals by using chaotic processes and sequences are proposed. At the summary are defined the directions of further researches.
Completing the Configuration of Digital Eco-Dynamic to Improve the Innovation Performance of SMEs

Entrepreneurship development is about the presence of strategic postures through business organizations so that risk-taking is at the organizational level, capable of developing competitive, proactive, and innovative behavior. This study is designed to reveal a theoretical model that best describes how to improve the innovation performance of SMEs in Indonesia. The model suggested at the end of this paper will picture the complete configuration of digital eco-dynamic to improve the performance of e-business SMEs in Indonesia seems promising. However, the author argues that amid the new normal era and besides the digital eco-dynamic, the innovation performance of SMEs in Indonesia is influenced by psychometric factors.
Improved Clamp-Switch Boost Converter with Extended ZVS range

In this article, a boost converter with a new modified clamp-switch network is proposed. An additional capacitor in parallel to the clamp diode is employed to extend the zero voltage switching (ZVS) range. In this way, the required difference between the converter's input and output voltage to achieve ZVS is reduced. The basic operation of the modified clamp-switch network is described, and the effect of the added capacitor on the ZVS operation is analyzed. Validation of the proposed converter structure and operating principle is carried out using simulations and measurements on a low-power (75 W) prototype converter. Experimental results indicate that high efficiency (> 98 %), together with a low-complexity control operation, can be achieved using the approach presented here.
Kinetics and Equilibrium Studies on the Removal of Victoria Blue Using Prosopis juliflora-Modified Carbon/Zn/Alginate Polymer Composite Beads

This article describes the removal of triarylmethane compound Victoria Blue (VB dye) from an aqueous medium using Prosopis juliflora-modified carbon/Zn/alginate polymer bead. The experimental conditions of the adsorption process chosen in this study are dye concentration (4·10–3 mg·kg–1 to 2.0·10 mg·kg–1), pH (3 to 10), adsorbent dose (0.5 g to 2.5 g), contact time (0.6 s to 5.4·103 s) and temperature (303 K to 343 K). The efficiency of the adsorption process was determined by kinetic, equilibrium, and thermodynamic parameters. The equilibrium uptake capacity of the adsorption process was obtained from Freundlich and Langmuir adsorption isotherm equations and the equilibrium uptake capacity of adsorption was compared with dimensionless separation factor (RL). The kinetics of adsorption process was estimated with pseudo-first-order and pseudo-second-order Lagergren’s equations. The diffusion of adsorption was confirmed using an intraparticle diffusion model. The feasibility of the adsorption process was as.
A Deep Subelectron Temporal Noise CMOS Image Sensor With Adjustable Sinc-Type Filter to Achieve Photon-Counting Capability

This letter introduces a Gm-cell-based CMOS image sensor (CIS) achieving deep subelectron noise performance. The CIS presents a new compensation block and low-noise current source to improve the performance of the Gm pixel. Furthermore, an optional first-order IIR filter is implemented to improve the output swing. The conversion gain, full well capacity, and dynamic range of the CIS can be easily adjusted by the charging time and the filter mode for different applications. The prototype chip is fabricated in a standard 180 nm CIS process and has a deep subelectron read noise of 0.31e-rms at minimum (of the noise distribution) and 0.42e-rms at peak (of the noise distribution). A smooth and clear photon-counting histogram is observed.