Miracle-dz/UniFAR-FTUs huggingface dataset:
From Cloud to Edge: Seamless Software Migration at the Era of the Web of Things

The Web of Things (WoT) standard recently promoted by the W3C constitutes a promising approach to devise interoperable IoT systems able to cope with the heterogeneity of software platforms and devices. The WoT architecture envisages interconnected IoT scenarios characterized by a multitude of Web Things (WTs) that interact according to well-defined software interfaces; at the same time, it assumes static allocations of WTs to hosting devices, and it does not cope with the intrinsic dynamicity of IoT environments in terms of time-varying network and computational loads. In this paper, we extend the WoT paradigm for cloud-edge continuum deployments, hence supporting dynamic orchestration and mobility of WTs among the available computational resources. Differently from state-of-art Mobile Edge Computing (MEC) approaches, we heavily exploit the W3C WoT, and specifically its capability to standardize the software interfaces of the WTs, in order to propose the concept of a Migratable WoT (M-WoT), in which WTs are seamlessly allocated to hosts according to their dynamic interactions. Three main contributions are proposed in this paper. First, we describe the architecture of the M-WoT framework, by focusing on the stateful migration of WTs and on the management of the WT handoff process. Second, we rigorously formulate the WT allocation as a multi-objective optimization problem, and propose a graph-based heuristic. Third, we describe a container-based implementation of M-WoT and a twofold evaluation, through which we assess the performance of the proposed migration policy in a distributed edge computing setup and in a real-world IoT monitoring scenario.
A Wideband Circularly Polarized Dipole Antenna Based on Asymmetric Feeding Technology

A new wideband circularly polarized (CP) dipole antenna with low profile is investigated. By using off-center-fed (OCFD) with coaxial probe, the dipole antenna generates different modes, thus expanding the bandwidth. Different lengths of two dipoles make the antenna produce two polarization waves with equal amplitude and orthogonal phase, which further realizes better circular polarization performance. The impedance bandwidth of it is 55.17% (3.36-5.92 GHz) and the bandwidth of 3-dB axial ratio (AR) is 27.94% (3.88-5.14 GHz). With simple structure, the antenna can achieve wide circular polarization.
Design and Analysis of a Novel 3-DOF Deployable Grasping Mechanism

In this paper, a novel 3-DOF deployable grasping mechanism consisting of two fingers and a palmar mechanism is proposed, in which each finger is made up of a series of basic modules. Firstly, specific design of the grasping mechanism is introduced. In order to realize the deployment motion, two groups of scissor-shaped elements are used in design of basic module, special revolute joint of the scissor-shaped element is designed to form grasping angle when the basic module carries out deployment motion. Secondly, the grasping angle and the deploy/fold ratio are discussed, from which the method to adjust grasping angle is also proposed. Thirdly, kinematics and workspace of the proposed grasping mechanism are analyzed, analysis result shows that the proposed grasping mechanism has quite large reachable workspace. Fourthly, the shape adaptability and grasping simulation are conducted, in which four types of objects with different shapes are grasped by the proposed grasping mechanism. The results prove that the proposed grasping mechanism has good grasping performance.
Very long Detection Times after High and repeated intake of Heroin and Methadone, measured in Oral Fluid

Abstract When detection times for psychoactive drugs in oral fluid are reported, they are most often based on therapeutic doses administered in clinical studies. Repeated ingestions of high doses, as seen after drug abuse, are however likely to cause positive samples for extended time periods. Findings of drugs of abuse in oral fluid might lead to negative sanctions, and the knowledge of detection times of these drugs are important to ensure correct interpretation. The aim of this study was to investigate the detection times of opioids in oral fluid. 25 patients with a history of heavy drug abuse admitted to a detoxification ward were included. Oral fluid and urine were collected daily and, if the patient gave consent, a blood sample was drawn during the first five days after admission. Morphine, codeine and/or 6-monoacetyl morphine (6-MAM) were found in oral fluid and/or urine from 20 patients. The maximum detection times in oral fluid for codeine, morphine and 6-MAM were 1, 3 and 8 days, respectively. Positive oral fluid samples were interspersed with negative samples, mainly for concentrations around cut off. Elimination curves for methadone in oral fluid were found for two subjects, and the detection times were 5 and 8 days. Oral fluid is likely to become a good method for detection of drug abuse in the future
Sensitivity-Aware Bit Allocation for Intermediate Deep Feature Compression

In this paper, we focus on compressing and trans-mitting deep intermediate features to support the prosperous applications at the cloud side efficiently, and propose a sensitivity-aware bit allocation algorithm for the deep intermediate feature compression. Considering that different channels’ contributions to the final inference result of the deep learning model might differ a lot, we design a channel-wise bit allocation mechanism to maintain the accuracy while trying to reduce the bit-rate cost. The algorithm consists of two passes. In the first pass, only one channel is exposed to compression degradation while other channels are kept as the original ones in order to test this channel’s sensitivity to the compression degradation. This process will be repeated until all channels’ sensitivity is obtained. Then, in the second pass, bits allocated to each channel will be automatically decided according to the sensitivity obtained in the first pass to make sure that the channel with higher sensitivity can be allocated with more bits to maintain accuracy as much as possible. With the well-designed algorithm, our method surpasses state-of-the-art compression tools with on average 6.4% BD-rate saving.
Low Power Low Voltage Current Mirror for Analog & Mixed Signal Applications

A “current mirror (CM)”, appropriate designed meant for activity on small voltage stages remains introduced. The reflect consumes high info then high yield voltage swipes. Adaptable existing biasing is presented designed for limiting the impacts of balance current. A pay method consumes remained utilized to expand the data transmission. These types the “CM structure” alluring meant for versatile, high recurrence circuit submissions. “P-SPICE” recreations, in light of representations for 1.2 innovations, approve the activity of the future present glass designed for movements as of 1 to 500@ through 1.2GHz data transfer capacity.
Essential oil composition of Syzygium aromaticum leaf from little Andaman, India

The cloves are grown as plantation crops in the agroclimatic conditions of the Indian island of Little Andaman. The dried leaves, on hydrodistillation, gave 4.8% of the oil. GC and GC-MS analysis of the oil resulted in the identification of 16 compounds. The major compound was eugenol (94.4%) followed by β-caryophyllene (2.9%). The clove oil from Little Andaman was found to be comparable with the best oil produced in south India in terms of its eugenol content. It is suggested that clove can be grown as an economically viable crop in the Andaman, Nicobar and Lakshdeep islands.
A Stochastic Coupling-Based Channel Impulse Response Matrix Model for Massive MIMO Channels

A novel stochastic channel impulse response matrix (CIRM) model for massive multiple input multiple output (MI-MO) channels is proposed in this papen Under the framework of this proposed model, the CIRM can be modeled as a sum of couplings between the steering vectors at the base station (BS) end and the eigenbases at the mobile station (MS) side. The fading of the coupling between the steering vector and the eigenbase is modeled as Nakagami distribution. Furthermore, the closed form of the capacity is derived based on the proposed framework. Compared with the traditional Weibchselberger model, the proposed model has lower complexity. To validate the proposed model, extensive massive MIMO channel measurements are carried out in an indoor environment The results show that the new model provides a better fit to the measured results than Weibchselberger model. Finally, the closed form and PDF are validated by Monte Carlo realizations of the proposed model. This CIRM model can be used for massive MIMO design in future fifth-generation communication system design.
LBFP: Logarithmic Block Floating Point Arithmetic for Deep Neural Networks

Fixed-point quantization techniques have attracted considerable attention in deep neural network (DNN) inference acceleration. Nevertheless, they often require time-consuming fine-tuning or retraining to keep the accuracy of a quantized model. Besides, DNNs involve massive multiplication operations, which are of much higher computational complexities compared with addition operations. To deal with the two problems, we propose an improved numerical format named logarithmic block floating point (LBFP) for post-training quantization. Firstly, logarithmic arithmetic is employed to convert multiplication operations to addition and shift operations. Then, Kullback-Leibler divergence is used to determine the shared exponent before inference. Thus, LBFP can significantly reduce the hard-ware complexity with negligible performance loss. Moreover, an efficient hardware architecture is designed to support the computation of LBFP. Hardware synthesis results show that our 8-bit LBFP multiplier can reduce power and area by 53% and 45%, respectively, compared with the 8-bit traditional fixed-point multiplier. Finally, a software library is developed with the CUDA-C language to evaluate the inference accuracy of LBFP. Without retraining, the accuracy of the selected DNN models with the 8-bit LBFP representation is comparable to that of the corresponding 32-bit floating-point baselines, showing the great potential in efficient DNN inference acceleration.
Performance Analysis of Different Reduced Precision Redundancy based Full Adders

Many electronic devices may have manufacturing defects or internal failures which cause errors in the devices. These errors are called soft errors, which are hard to detect and remove. Reduced Precision Redundancy (RPR) is the most efficient technique to remove soft error with less area and power. In this technique, the RPR is combined with Triple Modular Redundancy (TMR) voter logic to remove soft errors with still lesser power and area overhead. There are different types of majority voter logic circuit designs which can be used in RPR based full adder design to remove soft errors. In this paper, different majority voter logic designs are surveyed and implemented in RPR based full adder. These RPR based full adders analyzed for area, power and delay. As per the analysis it is found that NOR gates based majority voter combined with RPR is having less area and NOR gates based majority voter combined with RPR is having the less power and the NAND gates based majority voter combined with RPR is having the less delay
Information Allocation for Transport Switched Systems With ADT Method

In this work, an output feedback controller based on adaptive backstepping technique is considered for a class of transport information switched systems. A modified adaptive neural network control method is successfully built by combining the general approximation capability and dynamic surface control technique with the improved mean discrete time scheme. More specifically, a switched observer is constructed to reduce the conservatism caused by the use of a common observer, and by adopting the common coordinate transformation of all subsystems, it is proved that the overall closed-loop system is stable in the sense of semi-globally uniformly ultimately bounded in mean square, and steers the output to a small neighborhood of the origin. Finally, mass-spring-damping system with controller switching simulation studies are provided to demonstrate the validity of the proposed control format.
Lipase-Catalyzed Transesterification of Aryl-Substituted Alkanols in an Organic Solvent

Lipase-catalyzed transesterifications of aryl-substituted alcohols with vinyl acetate in organic solvents have been investigated. Vmax of (R)-1-phenylethanol is much larger than its (S)-counterpart, although their Kms are similar each other. It is proposed that a lipase from Pseudomonas cepacia can form a complex easily with each enantiomer, although the complex with the (S)-enantiomer is abortive. Enantioselectivity for the ortho-substituted 1-phenylethanol is smaller than those for the others. A three-dimensional model for the active domain of the lipase has been proposed to explain the enantioselectivity and substrate selectivity of the lipase.
A low-cost Raspberry PI-based vision system for upper-limb prosthetics

To achieve human like stable grasp with prosthetic, the correct grasp type along with the appropriate grasp aperture need to be identified from the targeted object. In most of the advance myo-electric prosthetics, the problem has been solved by using computer vision system in addition with the prosthetics. The vision systems are placed over the prosthetic itself and it needs to move towards the target object. Upon reaching the target object, the system capture the object image and process it to generate the correct grasp type. The processing time delays the initiation of the grasp process. To reduce this time delay and make the grasp instant like normal human hand, we have developed a vision system with Raspberry PI along with the PI camera. The system moves toward the targeted object and captures images of the focused region at two intermediate positions. OpenCV DNN model was used to identify all the objects within the captured frame. The employed model provided the efficiency of deep learning models in object identification without using of any GPU. The width of the objects in terms of pixels were also estimated from the images. The distance travelled by the system was measured by the SensorHAT (integrated with the system) which recorded the acceleration and direction of the hand movement. The device was tested in the cluttered environment in recognising four different grasp types- Compliant, Lateral, Tripod closed and Wrist-flexion aided grasp.
Model Predictive Periodic Output Path Following

In this paper, a new model predictive controller for path following of periodic references is proposed. This controller combines trajectory planning and tracking stages in a single optimization problem for a given periodic parametric path. In addition, the constraints of the optimization problem solved by the controller do not depend on the reference, allowing for sudden changes in the reference without losing feasibility. To illustrate the performance of the approach we discuss the example of ball and plate system.
Piezoelectric Array Configuration Technique into Enhance Power Catchment for Sound Energy Harvester System

The objective of this study is to explore the harvest maximum output changes occurs in piezoelectric transducer when connected in different configuration to produce highest electricity consumption and generate sound energy harvesting system. Acoustic energy is a type of environmental energy source that can be extracted and converted into electrical energy for small-scale energy applications. In this study, the corresponding load resistance for single piezoelectric transducer is 4.5 k$\Omega$, together with a constant vibration source at a frequency of 68 Hz and a 1-g acceleration. The performance of output voltage and power of piezoelectric are evaluated and the optimum output is measured by depending on the connection of the piezoelectric transducer arrangement into series, parallel and series, and parallel which stimulated using Proteus software. The experiment result presented that, when have single piezo, 5 piezo connected in series, and 5 piezo connected in parallel, the output powers are 1.664 mW, 1.671mW and 7.676 mW, respectively. During the combination series and parallel connections, the output power of 3S1P piezo increases to 5.05mW. In a parallel configuration, the output voltage that produced is much higher than a piezoelectric transducer arrangement connected in series connection. The piezoelectric transducer that connected in parallel configurations increases its voltage output from 2.83 V to 13.05 V with the same polarity. The arrangement of piezoelectric transducer in parallel configuration is affordable, with its higher production of a higher power output compared to the arrangement of piezoelectric transducer in series connection. Whereas in terms of power output, the maximum power remains constant in the range of 1.665 to 1.671 mW when three transducers are in series configuration connection with the same polarity. In conclusion, the proper implementation of the piezoelectric array configuration is needed in order to operate the minimum energy for low load devices and promise to accomplish generated optimum power output in harvester system.
Fourth-Order Buck-Boost Converters Exhibiting Minimum Phase by Reverse Inductor Coupling

Three fourth-order buck-boost converters with improved dynamic response are proposed. The improved dynamic response is achieved starting from the uncoupled inductors topologies and performing reverse coupling. This leads to the shift of the right half plane (RHP) zeros to the left half plane (LHP). The state-space small signal model is developed and the control-to-output transfer functions are derived. A comparison is made to the uncoupled and direct coupled topologies revealing the RHP zeros elimination. The simulations confirm that also with reverse coupling the input and output currents still maintain their smooth nature.
An Incentive Mechanism Based on Bertrand Game for Opportunistic Edge Computing

In a real edge network, many nodes may be selfish and unwilling to forward messages for other nodes. In this case, an incentive mechanism is needed to encourage the selfish nodes to participate in message forwarding. In this paper, we analyze the interaction between the source node and the relay node in edge opportunistic networks, and propose an incentive mechanism based on game theory to encourage the cooperation between nodes. Firstly, we define the interaction steps between the source and the relay node, which include that the source node decides the price of forwarding a message, the relay node responses the forwarding plan to the source node, and all nodes can get reward for their participant in message forwarding. We provide two-stage incentives to nodes, that is, the nodes can get reward from both receiving and forwarding messages. Since the nodes may be selfish, both the source node and the relay node want to maximize their utilities. Then, we model the cooperation between the source and the relay node as Bertrand Game, and the utility functions of the source and the relay node are defined. Furthermore, we find that the Nash Equilibrium is existed and unique, and present the best pricing scheme for the source node and the best forwarding plan for the relay node. The simulation results show that the proposed incentive mechanism can encourage the cooperation between selfish nodes, and improve the performance of routing algorithm in terms of delivery ratio and delay.
Joint Computation Offloading and Resource Allocation in UAV Swarms with Multi-access Edge Computing

With the emergence of multi-access edge computing (MEC) paradigm, mobile users who have computation-intensive and low-latency tasks can exploit computing resources of network edge MEC servers or other computing nodes. For a multi-user and multi-helper coexisting system (e.g., a cluster of UAVs), when computation offloading occurs, an efficient computation offloading scheme which can reduce users’ energy consumption or latency is required. In this paper, we study the computation offloading scheme in a multi-user UAV system in which UAVs with missions can offload part of the missions to helpers nearby to meet the delay constraint. And we minimize the total energy consumption of all devices by optimizing users’ strategy of offloading objects, transmission channel, and offloading rate. To solve the difficult problem of optimization variable coupling, we proposed a two-stage resource allocation scheme that exploits the convex optimization method and stochastic learning automata (SLA) algorithm respectively. Finally, simulation results indicate that our proposed schemes can effectively decrease energy consumption compared to several benchmark schemes.
High Q Toroidal Resonances In Planar Terahertz Metamaterials

Metamaterials pave an effective way to realize the toroidal dipole resonances, which is difficult to observe in nature. The new toroidal dipole metamaterials were proposed, which consists of two split ring resonators (SRRs) with left and right gaps merging together designed on polyimide substrate. The effect of gap on the electromagnetic characteristics was discussed deeply. The high Q toroidal dipole metamaterials is obtained, which could be broaden the family of terahertz devices.
Synthesis of polymer–clay nanocomposites of some vinyl monomers by surface-initiated atom transfer radical polymerization

The surface of Cloisite 30 B clay was treated with bromopropionyl bromide to form the clay Br-ended initiator needed for surface-initiated atom transfer radical polymerization (SI-ATRP). Several homo- and co-(SI-ATRP) polymerizations were conducted on the cured surface of the Cloisite 30 B clay using vinyl monomers, such as methyl methacrylate, styrene (St), and 2-(dimethylaminoethyl) methacrylate, along with the ligands 2,2′-bipyridine (bpy) and 1,1,4,7,10,10-hexamethyltriethylene tetraamine, and CuBr, as a catalyst. These grafted polymer–clay nanocomposites were characterized by X-ray diffraction, Thermal gravimetric analysis, differential scanning calorimetry, and Transmission electron microscopy. Most of the prepared nanocomposites displayed semi-exfoliated to exfoliated structures.
Robust Secure Beamforming in Cognitive MIMO Wiretap Channels With Bounded Channel Errors

This paper studies a cognitive multiple-input multiple-output (MIMO) network, in which a secondary transmitter aims to send confidential messages to its receiver in the presence of one multi-antenna eavesdropper, while has the interference temperature limit (ITL) for the primary user. Assuming that all the channels are imperfect and the errors are modeled by deterministically bounded model, we consider robust secure beamforming (RSB) design problem and our goal is to maximize the worst-case achievable secrecy rate subject to the total transmit power constraint and the ITL for the primary user. The formulated optimization problem is non-convex while the channel uncertainties make it more difficult to cope with. To address it, an inexact block coordinate descent (IBCD) approach is proposed to obtain the near-optimal solution, where we firstly linearize the two log-det terms of the objective function and then, the semi-infinite constraints with the bounded channel uncertainties are reformulated as linear matrix inequalities (LMIs). Finally, numerical results validate the performance of our proposed RSB algorithm.