Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Energy-efficient Sensor Networks by Minimizing Sensors Numbers with a Machine Learning Model

With the increasing demand to construct sensor networks for a smart IoT (Internet of Things) world, numerous sensors with sensing and communication capabilities are expected to be deployed in the future. Thanks to the development of hardware manufacture technology, relatively small IoT smart sensors are now commercially available and cost-effective. However, the total power required by operating these sensors is expected to be enormous, due to their large number and frequent activity. Removing “unneeded sensors” is the most direct way to reduce the power consumption of sensor networks. Here, “unneeded sensors” refers to those that can be placed in sleep mode, or even be removed from the network topology entirely, without serious impact on the overall networks data processing performance. In this paper, we report the development of an energy-efficient sensor network by using a machine learning model to determine the actual necessity of all the sensors in a sensor network. Machine learning model is introduced to identify unneeded sensors by comparing the data from neighboring sensors to that from the potentially unneeded ones. For identifying unneeded sensors, different strategies with different computational complexity are also proposed. Numerical experiments conducted in two real indoor environments verify that our proposed scheme can reduce the total number of active sensors by around 1/3, while maintaining more than 90% of the original high monitoring performance of the sensor network.
Comparative Analysis for Performance Evaluation of Full Adders Using Reversible Logic Gates

Reversible logic is becoming more prominent logic for Power and Delay optimization. From last few years it has been incorporated in number of applications such as Bioinformatics, Quantum computing, DNA computing, Nanotechnology and low power VLSI. In Conventional digital circuits, the main cause of power dissipation is the disposal of bits of information while the logical operations are being carried out, So if these circuits are designed with reversible logic, the bit loss can be preserved. As 1-bit Full Adder is the elementary unit in almost all the digital circuits, So this paper gives the Comparative Analysis of 1 bit Full Adder circuit using reversible logic in order to find out the most efficient circuit in comparison to existing ones as in terms of Dynamic Power, Leakage Power, Area and Delay. All the circuits were designed with Verilog HDL and has been simulated Using NC-SIM. The RTL analysis was carried out with RTL compiler 14.01 by Cadence for Power, Area and Delay at 90nm and 45nm technology for both fast and slow library.
#Euromaidan: Quantitative Analysis of Multilingual Framing 2013–2014 Ukrainian Protests on Twitter

In this paper we investigate the use of social media for framing the Euromaidan protests in Ukraine. Using automatic classification of a large set of Twitter data, we investigate how the online representation of protests changed between different stages of the protest campaign; furthermore, we question how the framing of Euromaidan varied between different language streams. Our findings suggest that framing of Euromaidan on social media evolved from a peaceful movement to revolutionary force and then to existential danger to the Russophone population, prompting the continuation of political crisis in Ukraine and the annexation of Crimea.
Physiological Impact of Vibro-Acoustic Therapy on Stress and Emotions through Wearable Sensors

Stress represents one of the dominant factors of young adults’ health, negatively affecting emotional, mental and physical aspects. There are several works in the literature aimed at detecting stress levels and conditions through the use of wearable devices. In this paper we investigated the effects of vibro-acoustic therapy (VAT) on physiological signals in a small group of young adults, trying to detect its positive effect on their stress condition. VAT has its origin in 1980s with basic instruments able to transmit music and vibrations. Here, we exploited AcusticA, an innovative VAT solution represented by a wooden chaise longue developed by following the principles of a big soundboard, and thus implementing a whole-body approach. Therapeutic sessions are accompanied by selected relaxing melodies, appropriately composed by a music therapist. We recruited 8 volunteer subjects, working in the same environment and characterised by similar stress conditions. We analysed the main components of ECG and GSR signals in order to highlight physiological responses and their variations between a rest baseline phase and a 20 minute therapy. Results show a general decreasing trend in HR, SCRs and their amplitude, confirming the relaxing component of the therapy.
A Semiparametric Model for Time Series Based on Fuzzy Data

This paper proposes a semiparametric autoregressive integrated moving average model for those real-world applications whose observed data are reported by fuzzy numbers. To this end, a hybrid method including nonparametric kernel-based method, least absolute deviations, and cross-validation method is suggested, which allows estimating parameters of the model including the autoregressive order <inline-formula><tex-math notation="LaTeX">$p$</tex-math> </inline-formula>, optimal value of the smoothing parameter <inline-formula><tex-math notation="LaTeX">$h$</tex-math> </inline-formula>, and fuzzy smooth function of the innovations, simultaneously. A correlation concept is also developed for fuzzy time series data and its main properties are investigated. Some common goodness-of-fit criteria are employed to examine the performance of the proposed fuzzy semiparametric time series model. A potential application of the proposed method is represented through simulated fuzzy time series data. To illustrate utility of this approach, it is applied to a set of real-life house price data in fuzzy environment. The results indicate that the proposed method is potentially effective for predicting fuzzy time series data in real applications.
A Four-channel Time Domain Passivity Approach for Bilateral Teleoperator

In this paper, a modified four-channel time domain passivity approach is proposed for stable bilateral control of time-delay teleoperations. The passivity of the proposed approach has been analyzed theoretically and then proved by the simulation results. Compared with the two-channel time domain passivity approach, simulation results illustrate that the proposed approach has a better transparency.
Discovery of Bacterial Deaminases That Convert 5-Fluoroisocytosine Into 5-Fluorouracil

Cytosine is one of the four letters of a standard genetic code, found both in DNA and in RNA. This heterocyclic base can be converted into uracil upon the action of the well-known cytosine deaminase. Isocytosine (2-aminouracil) is an isomer of cytosine, yet the enzymes that could convert it into uracil were previously mainly overlooked. In order to search for the isocytosine deaminases we used a selection strategy that is based on uracil auxotrophy and the metagenomic libraries, which provide a random pool of genes from uncultivated soil bacteria. Several genes that encode isocytosine deaminases were found and two respective recombinant proteins were purified. It was established that both novel deaminases do not use cytosine as a substrate. Instead, these enzymes are able to convert not only isocytosine into uracil, but also 5-fluoroisocytosine into 5-fluorouracil. Our findings suggest that novel isocytosine deaminases have a potential to be efficiently used in targeted cancer therapy instead of the classical cytosine deaminases. Use of isocytosine instead of cytosine would produce fewer side effects since deaminases produced by the commensal E. coli gut flora are ten times less efficient in degrading isocytosine than cytosine. In addition, there are no known homologs of isocytosine deaminases in human cells that would induce the toxicity when 5-fluoroisocytosine would be used as a prodrug.
Multistate Satellite System Reliability Optimization Based on Improved Compression Inference Algorithm and Bayesian Network

No doubt that the proper design of satellite system reliability is one of the most important issues in satellite system engineering. In order to optimize the satellite reliability, the reliability optimization method is studied in this paper based on compression algorithm, Bayesian Network (BN) and Particle Swarm Optimization (PSO). Firstly, the improved compression inference algorithm (ICIA) is proposed to model the BN reliability model of multistate system based on the existing compression and inference algorithms. Then, the reliability optimization problem is formulated, which is a typical discrete optimization problem with the discrete reliability measured in the number of each component's units as design variables. The process of optimization, based on the BN reliability model of multistate satellite system will be achieved by PSO. The efficacy of the proposed method is demonstrated in a microsatellite system reliability optimization, which verifies the importance of satellite reliability optimization in decreasing the cost of satellite development.
Application of SynRM Driving CVT System Using Blend Recurrent Gegenbauer OPNNAPSO Control

In order to reduce effect of nonlinear time-varying uncertainty for a continuously variable transmission (CVT) system driven by synchronous reluctance motor (SynRM), a blend recurrent Gegenbauer orthogonal polynomials neural network adaptive particle swarm optimization (OPNNAPSO) control system is proposed in this paper. The blend recurrent Gegenbauer OPNNAPSO control system consists of a censor control, a recurrent Gegenbauer OPNN control with adaptive law based on Lyapunov stability and a recompensed control. Furthermore, the adaptive particle swarm optimization (APSO) is proposed for regulating two varied learning rates of parameters in the recurrent Gegenbauer OPNN to obtain better dynamic response and faster convergence. Finally, comparative studies demonstrated by experimental results are illustrated to verify the effectiveness of the proposed control scheme.
Local Path Planning of Autonomous Vehicles Based on A* Algorithm with Equal-Step Sampling

Path planning is an important component in the study of autonomous vehicles. And local path planning is a pivotal issue, which will greatly influence the safety and comfort of the vehicle. On the premise of security, this paper proposes a novel A* algorithm with equal-step sampling based on vehicle kinematics model to improve the comfort of the path as much as possible. The algorithm is based on vehicle kinematics and introduces an enhanced cost function. The simulation results illustrate the feasibility of this approach on lane-keep and obstacle avoidance in different scenarios. In addition, the real vehicle test results of “Smart Driving” autonomous vehicle of Tianjin University demonstrate the capability of real-time implementation.
An exercise program for people with severe peripheral neuropathy and diabetic foot ulcers – a case series on feasibility and safety

Abstract Purpose: To examine a non-weightbearing exercise program for persons with severe peripheral neuropathy (PN) and a diabetic foot ulcer in terms of feasibility and safety. Materials and methods: Five men (mean (SD) age of 68.2 (7.1) years) with diabetes, severe peripheral neuropathy and an active foot ulcer, participated in a 10-week exercise program. Program adherence, patient satisfaction, healing of foot ulcers, adverse advents, ability to perform activities of daily life, and changes in muscle strength were assessed. Results: All participants completed the program with a session attendance from 85 to 95%, and with high satisfaction (≥9 points on a 10-point numeric rating scale). Only minor adverse events occurred, and ulcers were reduced for all participants, from a median of 1.9 (IQR, 1.1–7.3) cm2 to 0.0 (0.0–3.0) cm2. The distance on stationary bike was improved from a mean (SD) of 3.30 (1.1) to 5.36 (0.5) kilometers, and strength training loads were progressed. Ability to perform in self-selected activities of daily living improved from a median of 4.3 (2–5) to 6.7 (5–8) on the Patient Specific Functional Scale (0–10 points), while maximal isometric knee-extension muscle strength improved with 23%. Conclusions: A non-weightbearing exercise program for people with diabetes, severe peripheral neuropathy and foot ulcers seems feasible and safe. Further studies are needed to confirm these findings. Implications for rehabilitation An exercise program designed for people with severe peripheral neuropathy and diabetic foot ulcers can be safe by means of not compromising healing of foot ulcers. Feasible in terms of attendance and progression. An alternative to passive waiting for ulcer to heal in a population already deconditioned.
Multi-task Total Least-Squares Adaptation over Networks

Collaborative parameter estimation is a significant application of distributed multi-agent network. In practical scenarios, there are many multi-task oriented applications that the networks have multiple optimum parameter vectors to be estimated. Considering the condition that the input and output of agents are corrupted by additive noises, the network can be modeled as the multi-task errors-in-variables (M-EIV) problem. Total least-squares (TLS) method is a typical solution to the EIV problem for it can minimize the perturbation both in input and output data. In this paper, we study the problem of unbiased parameter estimation over multi-task networks whose nodes' inputs are corrupted by white noises. We propose a novel multi-task TLS (M-TLS) algorithm which can reach consistent unbiased estimation. Simulation results show that the proposed algorithms can achieve consistent and unbiased estimation.
A 0.19 mm2 10 b 2.3 GS/s 12-Way Time-Interleaved Pipelined-SAR ADC in 65-nm CMOS

This paper presents a 2.3 GS/s 12-way time-interleaved pipelined-SAR ADC achieving 1.1 GHz input bandwidth with 47.4 dB signal-to-noise distortion ratio (SNDR). Here, we propose a hierarchical interleaving with passively shared sub-sampling front-end to eliminate the timing skews, thus avoiding the timing calibration for design simplicity as well as better area and power efficiency. To provide a fast signal transfer with good power efficiency to the sub-ADCs, the power and bandwidth trades off by using the passive sharing or active buffers are analyzed according to our developed mathematic model. The analysis is based on two scenarios: noise and matching limited sampling. Moreover, we propose a boosting-capacitor-sharing technique to enhance the compactness of the time-interleaved bootstrapped sampling front-end, which is particularly critical when omitted the time calibration in this design. Measurement results on a 65 nm CMOS prototype operated at 2.3 GS/s and 1.2 V supply show 31 mW total power consumption with a SNDR of 47.4 dB @Nyquist leading to a FOM of 69 fJ/conv.step.
A 18.5 nW 12-bit 1-kS/s Reset-Energy Saving SAR ADC for Bio-Signal Acquisition in 0.18- $\mu$ m CMOS

This paper presents three low-power design techniques for successive approximation registers (SAR) analog-to-digital converter (ADC) for bio-potential signal acquisition: skip-reset, delta (<inline-formula> <tex-math notation="LaTeX">$\Delta$ </tex-math></inline-formula>) readout with MSB-rounding, and tri-level split monotonic switching. The skip-reset scheme reduces not only reference energy but also digital switching energy for the ADC reset. The <inline-formula> <tex-math notation="LaTeX">$\Delta$ </tex-math></inline-formula>-readout process with the proposed MSB-rounding technique shifts the location of the resolvable range using the previous digital code to increase the hit-rate. Finally, the tri-level split monotonic switching scheme minimizes the CDAC switching activity in predictive residue generation for the <inline-formula> <tex-math notation="LaTeX">$\Delta$ </tex-math></inline-formula>-readout process. A prototype ADC was fabricated in a 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS technology and occupies an active area of 0.17 mm<sup>2</sup>. At a 1.5-V supply voltage and a 1-kS/s sampling-rate with the electrocardiogram signal input, the ADC power consumption could be reduced to 18.5 nW, corresponding to 71% power saving, and owing to the proposed techniques from a conventional SAR ADC consuming 63.5 nW.
An Innovative Syndicate Medium Ecosystem

At present, businesses and operators that provide Free Wi-Fi in the world almost emphasize the internet access function of Wi-Fi, while ignoring how to operate the media communication function via Wi-Fi. Users are lost or trapped in the WORLD WIDE WEB internet and classic free Wi-Fi with single channels and multiple clicks. This study explores how emoji Wi-Fi medium technology is creating a new medium in the bitesize internet and driving a technological innovation to turn normal Wi-Fi hotspots into radio stations or brand amplifiers by employing the power of hashtags and emojis. The article focuses on how minimally used Service Set Identifiers (SSIDs) are turned into great marketing assets via an innovative syndicate medium ecosystem, a Hashtags-Over-The-Air platform.
Interactive 3D Exploration of RDF Graphs through Semantic Planes

This article presents Tarsier, a tool for the interactive 3D visualization of RDF graphs. Tarsier is mainly intended to support teachers introducing students to Semantic Web data representation formalisms and developers in the debugging of applications based on Semantic Web knowledge bases. The tool proposes the metaphor of semantic planes as a way to visualize an RDF graph. A semantic plane contains all the RDF terms sharing a common concept; it can be created, and further split into several planes, through a set of UI controls or through SPARQL 1.1 queries, with the full support of OWL and RDFS. Thanks to the 3D visualization, links between semantic planes can be highlighted and the user can navigate within the 3D scene to find the better perspective to analyze data. Data can be gathered from generic SPARQL 1.1 protocol services. We believe that Tarsier will enhance the human friendliness of semantic technologies by: (1) helping newcomers assimilate new data representation formats; and (2) increasing the capabilities of inspection to detect relevant situations even in complex RDF graphs.
The effect of Triple helix and innovative local community on the sustainable entrepreneurship in resource dependent region of China

During recent years, resource dependent regions in China are facing great transitional challenges in transforming into new sustainable development. Entrepreneurship is considered to be vital vehicle in this process. Based on prior research, this research tries to provide deeper view about the effects of Triple Helix and innovative local community on sustainable entrepreneurship. A survey of 1224 university students joined in Entrepreneur Association was carried out to support this theorized model. The main findings of this research suggest that university undergraduates in resource dependent regions are improved to be risk seeking and fill with courage quotient in break away with market barriers. This process involves different collaboration, and should be carried out by the type of universities. For the non-science and engineering university, the marginal effect of different stakeholders on sustainable entrepreneurship are strengthened when adding in the trilateral interact effect among university, innovative local community and the government. When considering the science and engineering universities, triple cooperation mode is the most efficient way compared with other cooperation (bilateral and quadrilateral) modes in fostering sustainable entrepreneurship. These findings contribute to literature streams on both of sustainable entrepreneurship and sustainable transition. Finally, four kinds of special strategies for different stakeholders were recommended by extending our results.
Integrated Inverted-F and Open-Slot Antennas in the Metal-Framed Smartphone for  $2\times2$  LTE LB and  $4\times4$  LTE M/HB MIMO Operations

Six antennas placed on the short edges of the metal-framed smartphone for the long-term evolution (LTE) multi-input multi-output (MIMO) operation are presented. The six-antenna structure comprises three antennas placed on the top edge of the smartphone and three antennas placed on the bottom edge thereof. The three antennas on the bottom edge are identical to those on the top edge. Each three-antenna structure consists of one inverted-F antenna (IFA) that covers the LTE low band (LB) in 698–960 MHz and two open-slot antennas (OSAs) that cover the LTE middle/high bands (M/HB) in 1710–2690 MHz. The three-antenna structure is compactly integrated, with the IFA placed between two OSAs, to fit in one short edge of the smartphone. In addition, the presence of the IFA is able to decrease the mutual coupling between two OSAs in the LTE M/HB. Furthermore, two IFAs at opposite short edges can also show good decoupling to have decreased envelope correlation coefficients in the LTE LB. The six antennas at two short edges can, therefore, achieve good performances for <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula> LTE LB MIMO and <inline-formula> <tex-math notation="LaTeX">$4\times 4$ </tex-math></inline-formula> LTE M/HB MIMO operations.
A 2-MS/s, 11.22 ENOB, Extended Input Range SAR ADC With Improved DNL and Offset Calculation

A 12-bit successive approximation register analog-to-digital converter (ADC) with extended input range is presented. Employing an input sampling scaling technique, the presented ADC can digitize the signals with an input range of <inline-formula> <tex-math notation="LaTeX">$3.2\,\,V_{\mathrm {pp-d}}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\pm 1.33~V_{\text {REF}}$ </tex-math></inline-formula>). The circuit also includes a comparator offset compensation technique that results in a residual offset of less than 0.5 LSB. The chip has been designed and implemented in a 0.13-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process and demonstrates the state-of-the-art performance, featuring an SNDR of 69.3 dB and the SFDR of 79 dB without requiring any calibration. Total power consumption of the ADC is 0.9 mW, with a measured differential non-linearity of 1.2/−1.0 LSB and INL of 2.3/−2.2 LSB.
Cold-Source Noise Measurement of a Differential Input Single-Ended Output Low-Noise Amplifier Connected to a Low-Frequency Radio Astronomy Antenna

We present two methods for measuring the noise temperature of a differential input single-ended output low-noise amplifier (DISO LNA) connected to an antenna. The first method is the direct measurement of the DISO LNA and antenna in an anechoic chamber at ambient temperature. The second is a simple and low-cost noise parameter extraction of the DISO device using a coaxial long cable. The reconstruction of the DISO noise parameter from the noise wave measurements of the DISO LNA with one terminated input port is discussed in detail. We successfully applied these methods to the Murchison widefield array LNA and antenna.