Miracle-dz/UniFAR-FTUs huggingface dataset:
Volatility and Spillover Risks in Cryptocurrency Market: A VAR and GARCH Processes Perspective

-In this analysis; we study the four major cryptocurrency returns that are Bitcoin, Ethereum, XRP, and Litecoin, where the dynamics of volatility spillover are observed for a span of 7 years – 2013 to 2020; wherein the total number of sample observations collected and analyzed were 10,953 (Data Points). This paper investigates the behaviour and responses of cryptocurrency assets with respect to each other by using VAR Granger Causality and Bayesian VAR Model, we find that Ethereum and Litecoin prove to be independent in the cryptocurrency market. Whereas Bitcoin, XRP, and Binance coins tend to be the recipient of the spillover effect. Our study indicates that there is a conditional variance in these cryptocurrency assets and Bitcoin & Binance coins are more adversely affected due to the bad news in the market, leading to rigorous fluctuations in volatility. While approaching for the analysis, we conducted a GARCH (1,1), T-ARCH, and E-GARCH analysis along with a univariate GARCH model which we used to estimate and quantify the nature of volatility spillovers. Given the overall cryptocurrency bull-run in the first quarter of 2017-18 we have analyzed the saturation of the cryptocurrency markets; where investors sought to invest in Bitcoin and Ethereum, vehemently and this resulted in extremely high volatility during the December 17’ period. Keywords--Cryptocurrency; Spillovers; Time-varying volatility; VAR Granger Causality; Bayesian VAR; GARCH; Static Forecasting JEL CLASSIFICATIONS: C46, C53, C58, G15, G17
Design and development of monolithic microwave integrated amplifiers and coupling circuits for telecommunication systems applications

Recent advances in printed circuit and packaging technology of microwave and millimeter wave circuits result to the increasing use of MMICs in telecommunication systems. At Microwave and Fiber Optics Lab of NTUA several designs of various MMICs were conducted using the HP Eesof CAD Tool and FET and HEMT models of F20 and H40 GaAs foundry process of GEC Marconi. The designed MMICs are constructed in Europractice Organization while on-wafer probe measurements are performed in the Lab. In that framework, MMIC technologies are employed in the design of power and low noise amplifiers and couplers to be used for mobile and wireless communications as well as remote sensing and radar applications. A medium power linear FET amplifier has been designed with combining techniques on a single chip. The circuit operates at 14.4–15.2 GHz with an input power of −15 dB m, a 36 dB total gain, while the input and output VSWR is less than 1.6. Due to high cost of MMIC fabrication only the first subunit was manufactured and tests verified the simulation results. Additionally, novel techniques have been used for the design of two coupling networks at 10 GHz in order to minimize the area occupied. A meander-kind design as well as shunt capacitors were implemented for a 90° quadrature coupler and a Wilkinson one in order to reduce size. Finally, a two stages low noise amplifier was designed with the use of H40 GaAs process in order the differences between the relevant designs to be explored. The key specifications for this MMIC LNA include operation at 10 GHz with a total gain of 17 dB while the noise figure is less than 1.5 dB.
Design and Fabrication of a Three-Axis Force Sensor for Underwater Robot Fingers and a Method for Decreasing Error

In this paper, we present a new mathematical model of three-axis force sensor for underwater robot fingers. We designed a kind of sensor based on this model which has a simple structure and can be miniaturized easily. By this model, they can be calculated that the magnitude, direction of finger force. Moreover, we present a new compensating method to decrease the error caused with the variation of temperature and pressure of water and caused with bending of the beams by symmetrical electronic circuits. We proposed compensation block method to solve the problem of heavy lead wire which affecting finger moving in underwater. Finally, an experiment is performed to verify the proposed model.
ELECTRIC FIELD MAPPING IN HIGH VOLTAGE SUBSTATION USING THE FINITE ELEMENTS METHOD

This paper aimed to study the behaviour of electric field and its influence within and in the vicinity of a high voltage substation, since the presence of electric fields intense can produce interactions with living organisms from harmful effects by long-term exposure. The study was performed by means of computer simulation using the software COMSOL Multiphysics ® , which is based on Finite Element Method (FEM). With results of the simulations was possible to weigh if the values obtained meets the levels of electric field recommended by legislation. Was also possible to determine the voltage induced in a metallic tube in soil and in one human, the touch voltage and step voltage on the patio of the substation. The results of simulations were shown to be coherent, and they may serve as an aid in the evaluation process of electric field of complex structures.
Radiophysical methods for modelling frozen soils dielectric permittivity in the southern Vitim plateau (Eastern Siberia, Russia)

The article presents the results of applying the radiophysical method for modelling the dielectric permittivity on the example of Haplic Chernozem Molliglossic soils in the south of the Vitim plateau, depending on VHF and UHF wavelengths, temperature, and soil moisture. Depending on the heterogeneity of moisture reserves and heat content, the soil is considered as a three-layer medium with different soil characteristics. A difference in the frequency dispersion of the complex dielectric permittivity over the entire soil profile in the VHF and UHF ranges has been established.
A Novel Current Sensor less MPPT based Approach for PV Applications Using PSO Technique

As an increased demand in power resources and to reduce global warming, Renewable Energy Sources (RES) are preferred over the conventional sources. Among various available RES, solar energy is the effective and efficient one. The solar energy is also clean and free energy. The use of Maximum Power Point Tracking (MPPT) is the one of the techniques to get maximized output power from the Photo Voltaic (PV) system. The proposed method uses a voltage sensor by eliminating the need of current sensor based on selected technique using Partial Swarm Optimization (PSO) technique interfaced with DC-DC boost converter. PSO technique is one of the methods which has high conflux speed, to precisely track the maximum power. The result of the planned methodology is studied with the assistance of an acceptable simulation applied in MATLAB/Simulink setting for experiment to valid of microcontroller which is employed. The result obtained from the simulations studies showed that current sensor less methodology using PSO technique can extract the maximize power from PV systems.
Determination of physico-chemical parameters of coal mines water samples and their correlation establishment with WQI using python programming

The quality assessment of water is the need of the hour as water pollution has reached to an alarming level. The pollution of natural water bodies due to mine drainage system and mining activities is a major environmental concern worldwide. There are many potential reasons of water pollution such as agricultural, sewage, oil, radioactive materials, dumping & mining activities etc. Mining activities are responsible for the contamination of watercourses with metal and increment of sediment levels in it, however acid mine drainage can be viewed as the most lethal means of polluting watercourse. In this study an analysis was done on the water samples collected from different coal mines of Jharkhand and Telangana State. The WQI for each sample were calculated and correlated with their physico-chemical parameters. The lowest grades of the water samples are mainly due to the presence of the strongest correlated parameters. It was observed that the iron content in the samples has the strongest correlation with a Pearson coefficient of 0.9977 and highest significance with a P value lower than 0.001.
Dielectric metasurface for emission control of magnetic dipole in the near-IR wavelength range

Developing active dielectric systems is in high demand due to growing the internet of things. Such systems can control the optical properties of nanoemitters which leads to an increase in the performance of the telecommunication networks. Here we numerically investigate metasurface consists of all-dielectric erbium-doped silicon nanocylinders. We demonstrate that such a structure can effectively control and enhance 320-folds spontaneous emission in the near-IR wavelength range. The results of this paper can be used for creating new telecommunication systems.
The Brazilian gravitational wave detector Mario Schenberg: progress and plans

The Schenberg gravitational wave detector is almost completed for operation at its site in the Physics Institute of the University of São Paulo, under the full support of FAPESP (the São Paulo State Foundation for Research Support). We have been working on the development of a transducer system, which will be installed after the arrival of all the microwave components and the completion of the transducer mechanical parts. The initial plan is to operate a CuAl6% two-mode parametric transducer in a first operational run at 4.2 K with nine transducers and an initial target sensitivity of h ∼ 2 × 10−21 Hz−1/2 in a 50 Hz bandwidth around 3.2 kHz. Here we present details of this plan and some recent results of the development of this project.
Experimental analysis of microstructure and mechanical characteristics of LM6 & fly ash composite through stir casting method

Fly ash has received a lot of attention as a possible support for aluminium alloy composites (AMCs) to improve characteristics while lowering production costs. Al alloy MMC was made with different amounts of fly ash (2, 5, and 8%). The semi-solid state mould was gradually filled with reinforced particles. The optical microscope investigation of the microstructure of AMCs reveals homogenous fly ash dispensation. With the increase in fly ash particulate, the microstructure with refined composition displays reducing Si-needle structure and extending space of eutectic-Al grid space. While hardness increases by 88 percent, tensile strength increases by 57 percent and yield strength by 17 % of the AMCs with the increment of fly ash. The addition of fly ash particles improved the AMCs’ physical and mechanical qualities. As a result, it leads to upgrade the energy utilisation.
A risk-based optimisation for pavement preventative maintenance with probabilistic LCCA: a Chinese case

Compared to major structural repair or even replacement, preventative preservation of in-service pavements has been more popular in engineering practices, but recently, pavement preventative maintenance (PPM) has become more complex in China as the competition for pavement preservation funds has grown and the need to justify decisions has increased. Therefore, the life cycle cost analysis (LCCA) has increasingly attracted attention from transportation agencies. However, most of previous studies were conducted deterministically or only focused on a single factor, while PPM is apparently affected by many potential sources of uncertainty. The risk-based analysis to investigate potential risks and combined effects of multiple factors is a necessary component of PPM. This paper aims at presenting a risk-based PPM with the probabilistic LCCA for a Chinese highway case. Major analysis variables of different range are examined to probe risks of different scenarios, investigate combined effects of multiple variables and identify an optimal preservation strategy.
Real-Time Evaluation of System Dynamics to Improve Network Performance in Akure Electric Power Distribution System in Nigeria

Real-t ime evaluation of the dynamics of Electric Power Distribution Net work was proposed and developed for Akure Electric Power Distribution System (EPDS ). The d iagnostic system is based on threshold trespassing algorith m using the current signatures. The algorithm is able to distinguish between overload and short circuit currents. The suitability of the algorith m was simu lated in MATALA B before field deploy ment. The hardware consists of embedded system that reports abnormal conditions to the distribution control centre using wireless communicat ion where analysis is carried out to establish the attribute of the disturbance for pro mpt restoration. The system is also capable of logging the transformer loading and reports to the control centre periodically. The effect of the system was studied by integrating it with a fault prone Feeders as defined by the performances of the Five feeders in Akure. The study was carried out to improve the delivery of power though reduction in mean-t ime -to repair. Fault reporting time of 2sec was achieved fro m the set-up with imp rovement in power availability fro m about 30% to 60%. The system shows engineering capability in improving the performance of EPDS in Nigeria.
Traceable and Intelligent Supply Chain based on Blockchain and Artificial Intelligence

Smart manufacturing focuses on maximizing the capabilities to increase multiple objectives, like cost, delivery, and quality, in manufacturing enterprises. This requires implementing product development lifecycle, production system lifecycle, and business cycle for supply chain management. In short, a considerable amount of data is generated in a given manufacturing enterprise. Likewise, progress has been made to adopt blockchain in financial industries, but the adoption is slow in non-financial sectors. The article elaborates a methodology for the realization of a traceable and intelligent supply chain. First, the methodology elaborates on the realization of traceability of enterprise entities, which are an integral part of the supply chain. In this case, each participating stakeholder of the supply chain is required internally to realize a smart manufacturing system with an extension to write critical control data to the blockchain (i.e., a subset of process data). Artificial Intelligence (AI) is being adopted in most industries. A supply chain stakeholder has access to its data and can employ AI to derive new insights. The data available with the stakeholder provides a narrow context. With blockchain, all the stakeholders have access to the data from other stakeholders. Subsequently, the insights derived by a stakeholder will be more meaningful. This will assist in realizing an intelligent supply chain.
Image Transformation for Digital Printing Machine

A computer monitor through mixing shades of red, green, and blue show pictures, that is named RGB color model. CMYK use the different color reproduction technologies and properties. A CMYK printer instead uses light-absorbing cyan, magenta and yellow ink. This paper discusses the conversion between RGB and CMKY color model. OpenCV was used for the verification of the effectiveness of the algorithm is proved to be feasible.
Supporting communication between product designers and engineering designers in the design process of branded products: a comparison of three approaches

The successful implementation of brand values and emotional concepts into physical products is critical in the design process of branded products and can be problematic when multidisciplinary project teams come from different backgrounds. This paper argues that lack of communication between product designers and engineering designers causes additional process iterations to assure that the initially intended brand values and emotional responses are preserved in the final product. This paper investigates the use of Annotations, Word Mappings and Multiple-Domain Matrices as three potential approaches to support the communication between product designers and engineering designers. The results of an evaluation study show the level of acceptability of these approaches among product designers, engineering designers and academics depending on the purpose of its use, the familiarity of users with the representation and the stage of the design process.
Research and application of bolt defects detection technology based on machine learning

With the development of computer technology, the technology based on computer machine learning plays an important role in various fields. Using drones for collecting image data and using machine learning to analyze the collected image data have become the current general method of intelligent detection technology. As the main machine learning method, deep learning is commonly used in image analysis, but it requires many high-quality training samples and high-performance embedded system. In the engineering quality and safety detection with few training samples, the detection effect of this method is not satisfactory. To solve this problem, computer vision and machine learning technology are introduced into image analysis of bolt, based on the analysis and mining of historical image samples, the recognition and judgment of new collected images can be realized by matching the newly collected image samples and historical samples. Taking the bolt on a steel structure bridge as an example, this method is used to recognize the bolt appearance image collected by UAV. The results show that the method can effectively identify the appearance state of bolts, with fast calculation speed and high recognition accuracy.
Finite Element Model for Predicting Static and Thermally Induced Bin Wall Pressures

ABSTRACT Asecond generation finite element model (FEM) was developed to predict static and thermal lateral pressures in grain storage bins. The en masse stress-strain behavior of the stored wheat was modeled using an elastoplastic theory. Interaction between the bin wall and wheat, and bin floor and wheat was described using an interface element. The relationship between shear stress-relative displacement for the interface was assumed to be exponential. The FEM was validated against the experimental data from a scaled model bin. Results showed that the FEM adequately predicted lateral static pressures with and without surcharge. The average difference between the FEM predicted and the mean measured lateral thermal pressures at 10°C temperature drop was 18.1% of the mean measured values. However, the FEM predicted thermal pressures are within the 95% confidence interval for the data for a 10°C temperature drop.
Optical Microfiber Sensor : A Review

Due to numerous benefits such as geometrical simplicity, compact size, high sensitivity, broad detection range, low noise, and high accuracy, optical devices have attracted a lot of interest for sensing applications. It is critical in a variety of sectors, including cultural relic preservation, warehouse products maintenance, manufacturing process control, semiconductor, agriculture, food production storage, environmental control, health industries, chemical and home improvement. It outperforms its electronic equivalent owing to its capacity to function in tough and demanding situations such as combustible surroundings, greater pressure and temperature levels, and the ability to send signals over long distances without electromagnetic interference. Optical fiber sensors are classified based on their operating principles such as interferometers, fiber Bragg gratings (FBG), resonators and whispering galleries modes (WGM). This paper presents a comprehensive review related to the optical microfiber sensor such as its properties, fabrication techniques, evanescent wave, optical micro resonators and recent study on the application of microfiber towards humidity sensing. This review could be beneficial to help other researchers to gain greater view in the field of optical microfiber sensor.
An efficient multi-channel communications scheme for wireless sensor network

This paper presents a multi-channel communications system for wireless sensor networks (WSNs), referred to as Load-adaptive practical multi-channel communications (LPMC). LPMC estimates the active load of a channel at the sink, and dynamically adds or removes channel based on the estimated load. The nodes in a path use the same channel; and therefore, they do not need to switch channels to receive or forward packets. Furthermore, LPMC updates the routing path to balance the loads of the channels. LPMC is evaluated by simulation in NS-2, and the results demonstrate that it can effectively increase the channel utilization and network throughput, and decrease the delay.
Development of an AFO with Dual-material using an FDM Printer

This paper presents a design and development of an Ankle Foot Orthosis (AFO) printed with a multi-extrusion Fused Deposition Modelling (FDM) printer. AFO is crucial in the healing of patients with ankle joint displacement. It helps to heal the foot easily. The model is designed to print with dual materials such as flex and polylactic acid (PLA). The critical problem in building a prototype is to obtain excellent bonding properties between the layers of different materials. The Flex material is softer than the PLA and both have different melting temperatures. Thus, successfully printing with an excellent adhesive is the key concern in multimaterial applications. The paper also presents the simulation results of an AFO to justify the mechanical properties and required materials for sustainable development.
Equivalent electric circuit of the P‐i‐N photodiode for the pulse incident excitation

An equivalent electric circuit of a P‐i‐N photodiode, for the case of the pulse‐light excitation, is derived and incorporated using SPICE. We consider only nonlinearity, which is the result of the change of the photodiode's reverse‐bias voltage. We compare our SPICE model with a previously published analytical model. The results obtained prove the superiority of the derived model, which has potential application in comprehensive OEIC modeling. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 41: 468–471, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20174
Your Microphone Array Retains Your Identity: A Robust Voice Liveness Detection System for Smart Speakers

Though playing an essential role in smart home systems, smart speakers are vulnerable to voice spooﬁng attacks. Passive liveness detection, which utilizes only the collected audio rather than the deployed sensors to distinguish between live-human and replayed voices, has drawn increasing attention. However, it faces the challenge of performance degradation under the different environmental factors as well as the strict requirement of the ﬁxed user gestures. In this study, we propose a novel liveness feature, array ﬁngerprint , which utilizes the microphone array inherently adopted by the smart speaker to determine the identity of collected audios. Our theoretical analysis demonstrates that by leveraging the circular layout of microphones, compared with existing schemes, array ﬁngerprint achieves a more robust performance under the environmental change and user’s movement. Then, to leverage such a ﬁngerprint, we propose A RRAY ID, a lightweight passive detection scheme, and elaborate a series of features working together with array ﬁn-gerprint. Our evaluation on the dataset containing 32,780 audio samples and 14 spooﬁng devices shows that A RRAY ID achieves an accuracy of 99.84%, which is superior to existing passive liveness detection schemes.