Search

The paper provides an equivalent circuit model and parametric analysis of the filter characteristics along with circuit simulation studies. The paper titled "A Miniaturized Band-Reject Filter Using Metamaterial Structures on Silicon Substrate for X-Band Application" gives the design of a band-reject filter in the X-band based on series connected complementary split ring resonators. The paper reports the electrostatic analysis of GNR and compares the delay of the radial point interpolation method (RPIM) with other analysis method I viz. i reproducing kernel particle method (RKPM). [Extracted from the article]

This paper presents a miniature-size band-reject filter on a Coplanar Waveguide (CPW) transmission line using series connected complementary split ring resonators (CSRRs) and series capacitive gaps for X-band applications. The band-reject filter has highly miniaturized dimensions and is capable of solving almost all the basic limitations to which the conventional band-reject filters are mostly susceptible. The series connected CSRRs are etched on the signal planes of the CPW transmission line on silicon substrate enabling CMOS compatibility with planar IC technology. It is a concept resulting in higher bandwidth, low insertion loss of 0.5 dB with high rejection of 40 dB in the stop bands better than similar designs. The optimized design of the proposed device is performed using the parametric study of filter characteristics. The proposed devices RF analysis and circuit model are simulated using Ansoft High-Frequency Structural Simulator (HFSS) v13® and Agilent Advanced Design System (ADS) 2009. Measured results are in good agreement with their simulated counterparts and the measured performance is encouraging in all respects. [ABSTRACT FROM AUTHOR]

Radio Frequency IDentification (RFID) is one of the prominent wireless technologies for implementing a complete smart environment and is preferred over magnetic tapes, bar codes and smart cards due to its low cost and high speed. RFID networks provide identification, location tracking and record management and consist of tags, readers and backend storage devices. In these networks, it is very common to see tag-to-tag or reader-to-reader collisions. For avoiding these collisions and hence to improve the overall system performance many probabilistic and deterministic anti-collision protocols have been proposed, but the majority of these protocols were found to be inefficient in channel distribution. In this work, based on simulation annealing, a novel and efficient reader-to-reader and tag-to-tag anti-collision protocol is proposed by uniformly distributing the available channels among different readers, which reduces reader-to-reader collisions to zero. For a better performance tag state parameters have been preferred over fixed scheduling. Improvement of tag identification ratio from 1% to 12.5%, successful interrogation cycles by up to 25% for a maximum of 1000 readers and reduction in the number of cycles required for interrogation by a minimum of 13.3% and a maximum of 25.5% and reader-to-reader collisions up to 24% for 100 K tags make the proposed protocol much suited to a heavily loaded network. Compared to other contemporary protocols performance gain in the range of 2% to 30% has been observed for the total number of sent/received packets, delay, number of collisions, idle cycles and time cycles. [ABSTRACT FROM AUTHOR]

In this study, a fractional capacitor order of α-based new fractional multivibrator topology is proposed. The new proposed circuit consists of a multioutput current follower transconductance amplifier (MO-CFTA) and a grounded fractional capacitor. The proposed topology offers electronically and independently control of output waveform amplitude, trigger levels, and oscillation period via relevant bias currents. The proposed circuit provides higher oscillation frequency in comparison with normal multivibrator. The proposed circuit is simulated via SPICE and 0.18 µm TSMC technology parameters. Furthermore, the introduced concepts are also verified experimentally. [ABSTRACT FROM AUTHOR]

This paper presents current-mode multi-input m:3 (4 ≤ m ≤ 7) counters based on carbon nanotube FET (CNTFET). Two different approaches are considered for these designs. In the first approach, a current mode m:3 (4 ≤ m ≤ 7) counter is achieved by means of current-mirrors in the output paths. The second proposed current-mode m:3 (4 ≤ m ≤ 7) counter is designed without requiring current-mirrors. This leads to lower number of transistors and lower power dissipation in comparison with the first approach. All of the designs are simulated using the Stanford CNTFET HSPICE model at 32 nm feature size. The results indicate that the second proposed designs are consistently faster and consume lower power than the first designs. Therefore, our PDP figure is improved by 35%, 30%, 36% and 26% as compared to those of current-mode logic (CML) counter 4:3, CML counter 5:3, CML counter 6:3 and CML counter 7:3, respectively. [ABSTRACT FROM AUTHOR]

This paper presents an experimental validation of, phase-lock loop less modified control strategy for single-phase shunt active power filter (APF) to compensate current harmonics and reactive power in single-phase distribution system under distorted supply voltage. The control technique is divided into two parts: first associated with selected frequency signal extraction by using Hilbert transform-based adaptive tuned filter from distorted supply voltage followed by reference current signal generation using DC-link energy balance method. Second deals with an improved pulse width modulation technique which reduces switching ripple and switching frequency for voltage source inverter used as a shunt APF. The overall control scheme is simulated using MATLAB/Simulink environment in the steady state and transient condition of the load. A detailed hardware design and other parameters of proposed system have been presented. A laboratory prototype has been developed using dSPACE DS1104 controller card having TMS320F240 as a slave DSP to verify the simulation results. Simulated and experimental results show that the proposed control technique gives a flexible and fast dynamic response in single-phase distribution system. The harmonic spectral performance of the proposed technique is as per the recommendation of IEEE-519 standards. [ABSTRACT FROM AUTHOR]

To overcome current difficulties in target extraction from high resolution Synthetic Aperture Radar (SAR) and in heterogeneous image registration, new extraction and registration methods are proposed in this paper according to two typical targets: airport and road targets. For airport targets, Otsu segmentation method is firstly used to obtain potential Region of Interest (ROI). Secondly, Fuzzy C-means Clustering Method (FCM) and HU Invariant Moments are jointed to describe regional features of ROI. Finally, Euclidean distance similarity and nearest neighbor distance ratio (NNDR) are jointly used to complete image registration (between optical and SAR image); for road targets, self-adaptive threshold segmentation method is firstly used to obtain ROI. Secondly, the ratio of average (ROA) and Hough transformation are jointed to get the directions of ROI. Thirdly, opening operators using linear operators based on these directions are used to obtain better ROI. Finally, a new method called Triangle Mesh Angle Method (TMAM) is proposed to complete image registration. Experimental results demonstrate the proposed methods have good matching accuracy and robust registration results, and own research value and promising applications. [ABSTRACT FROM AUTHOR]

In this paper, we systematically investigated the DC and RF behaviour of the novel Enhancement-Mode (E-Mode) Double-Gate High Electron Mobility Transistors (DGHEMTs) using Sentaurus-TCAD software. The scalability of the novel DGHEMT is also studied by analysing the short channel effects. The attractive features of the proposed DGHEMT are intrinsic In0.80Ga0.20As/InAs/In0.80Ga0.20As channel, dual silicon delta doping sheets and platinum (Pt) buried gate technology. The proposed DGHEMT with Lg = 20 nm exhibits a gm_max of 3970 mS/mm and IDS_max of 1650 mA/mm at VGS = 0.6 V and VDS = 0.8 V. The proposed DGHEMT exhibits a threshold voltage of 20 mV which indicates its E-Mode behaviour. The sub-threshold swing (SS) and DIBL values obtained for Lg = 20 nm DGHEMT at VDS = 0.5 V are 74 mV/dec and 78 mV/V respectively. The Lg = 20 nm proposed E-Mode DGHEMT also exhibit a fT and fmax of 826 and 1615 GHz respectively at VDS = 0.6 V. The computed logic gate delay for the Lg = 20 nm DGHEMT is 31.25 fS with an electron velocity under the gate of 6.4 × 107 cm/S. This excellent RF and DC behaviour of the proposed DGHEMT makes them an excellent choice for future sub-millimetre wave and THz frequency applications. [ABSTRACT FROM AUTHOR]

This paper discourses the variations in methods of fabrication and modeling of Through-Silicon Vias (TSVs) in chronological order. Three-dimensional (3D) integration is an emerging technology that forms multi-functioning high-performance ICs by vertically stacking of disparate technologies and components altogether. TSV has the potential to become an essential component in integration and packaging of 3D ICs. However, the limited information about TSV technologies brings the challenge in selecting the appropriate filler material of TSVs. This review paper overviews the copper (Cu)- and carbon nanotube (CNT)-based TSVs and their pros and cons to be established as suitable filler material for 3D TSVs. The equivalent electrical models of both Cu and CNT-based TSVs are discussed addressing their advantages and disadvantage to reason out the most promising method for the modeling of TSVs. [ABSTRACT FROM AUTHOR]

Flexible alternating current transmission system devices and energy storage devices have great potential to support frequency regulation in power system. Hence, the impact of interline power flow controller unit and redox flow battery unit in the load frequency control (LFC) of six-area power system having different power plant units has been investigated in this paper. The multi-verse optimizer (MVO) is proposed to tune the parameters of the proportional–integral and derivative (PID) controller. Further, the efficacy of the multi-verse optimizer tuned proportional–integral (PI) controller is also equated with the recently developed sine-cosine algorithm tuned PI controller in the investigated power system. The encouraging role of interline power flow controller (IPFC) unit and redox flow battery (RFB) unit has been confirmed for system frequency and tie-line power regulation. The investigation validated that multi-verse optimizer based proportional–integral–derivative controller with an interline power flow controller unit and redox flow battery unit give better dynamic response during sudden load disturbances. [ABSTRACT FROM AUTHOR]

This paper proposes the usage of an adaptive meshless method – radial point interpolation method (RPIM) for the analysis of armchair graphene nano ribbon (GNR) to be used for interconnect applications. The validity and efficiency of the proposed method are demonstrated using the following three examples: one-dimensional problem, two-dimensional problem and the cantilever beams under various forces and boundary conditions. Electrostatic analysis of the GNR is performed using RPIM. The delay of the GNR is calculated using the quasi-static capacitance. It is found that the delay is reduced compared to the RKPM analysis, making it as a suitable candidate for RF interconnects. [ABSTRACT FROM AUTHOR]

This paper aims at combining some of the best features of an available induction motor (IM) drive system while introducing a simplified adaptive flux estimation algorithm for sensorless operation. The use of a matrix converter (MC) is proposed to achieve improved source side power quality and input power factor correction of an IM drive. Direct torque control (DTC) of an IM is realized through appropriate switching of the MC and the control strategy is implemented with speed-sensorless operation by using a relatively simplified adaptive flux observer. DTC through speed and flux estimation is realized in the stationary reference frame. Primarily, three objectives are achieved, viz. speed regulation while directly controlling the motor torque (and flux), improved source side power quality owing to the use of MC, and substantially simplified sensorless estimation strategy. Additionally, economic benefits are also achieved owing to negligible energy storage requirements of the drive and sensorless operation. [ABSTRACT FROM AUTHOR]

In this work, we have performed numerical simulations of normally-off AlGaN/GaN recessed Metal–Insulator-Semiconductor or MIS-HEMTs. A double-gate double-channel device design is proposed and analyzed using calibrated TCAD models. The dual-gate geometry is shown to provide an enhanced gate control over the double-channel, thereby suppressing the short-channel effects. The proposed device exhibits 72-mV/decade subthreshold slope, which is 50% improvement compared to the single-gate single-channel device with 3 µm gate length. Both the double-gate double-channel and single-gate single-channel structures are compared for their ability to counter short-channel effects in aggressively scaled MIS-HEMT devices. It is shown that, double-gate design is superior to single-gate single-channel device with 80% improvement in drain-induced barrier lowering at sub-micrometer gate lengths. [ABSTRACT FROM AUTHOR]

Flush Air Data Sensing System (FADS) is an important subsystem required for a winged re-entry vehicle. It essentially makes use of surface pressure measurements located at a suitable position in the vehicle for deriving the air data parameters of the vehicle such as angle of attack, angle of sideslip, Mach number, etc. These air data parameters are used by the control and guidance system for carrying out gain scheduling, trim scheduling of control surfaces and overall flight management. The accuracy of the pressure sensors used in FADS is critical in achieving the targeted accuracy of the air data parameters. In the FADS system considered in this paper, piezoresistive MEMS-based pressure sensors are used. The FADS system is located in the nosecone of the vehicle which is a region prone to vibration during transportation as well as during flight. It is essential that the pressure sensors perform with the desired accuracies in spite of the vibration environment. Sine and random vibration testing are carried out as part of qualification testing of the vibration sensors of FADS. Analysis of the test results shows that the accuracies demanded by the system are provided by the pressure sensors under the vibration environment. [ABSTRACT FROM AUTHOR]

We are adopting, in the present work, a cooperative transmission procedure for an in-home communication system as a solution to meet the contemporary needs of the smart grids and smart home. It is composed of a Low Voltage PL channel assisted by a relay station in the presence of an impulsive noise. Our contribution consists of using the Decode and Forward (DF) relaying protocol while adapting the Joint Modulation (JM) technique to the PLC context. The benefits of this integration are highlighted in a comparative study of the system capacities using the DF-JM and the Amplify and Forward (AF) relaying protocols. The transmission channel is affected by an impulsive noise of type Middleton class-A. The evaluation is based initially on signal attenuation model and eventually on Transmission Line Theory. For the latter, a multi-branched cable with loads at the ends is considered when keeping the relay at the optimal selected position. Simulations and mathematical proofs show that the DF JM relaying technique offers more capacity over the AF independently of cable configuration. Furthermore, in the current study, we analyse the effect of load impedance and branch density on the DF-JM PLC as well as their contribution to the system performance while varying the class-A model parameters. [ABSTRACT FROM AUTHOR]

A new reconfigurable band-notched ultra-wideband (UWB) dielectric resonator antenna (DRA) has been designed and fabricated for cognitive radio (CR) applications. The UWB antenna design comprises a dielectric resonator as a radiation element, a ground plane, and a microstrip feed line. The frequency band's rejection mechanism is achieved by cutting two slots and adding an L-shaped stub on the ground plane. The reconfigurable function is created by PIN diode switches to change the current distribution path on the ground plane. A preliminary model of the DRA was fabricated, and its efficiency was verified. The proposed antenna occupies an area of 40 × 40 × 7.3 mm. The simulated and measured results have demonstrated suitable radiation patterns attained by the proposed antenna, which operates within the UWB frequency range of 3–11 GHz. Moreover, the antenna has shown an ability by rejecting switchable bands to achieve the WiMAX (3.2–3.65 GHz), WLAN 5 GHz (4.8–6 GHz), and ITU 8 GHz (8–8.3 GHz). Also, this antenna can be operated as dual and triple band-notched antennas. [ABSTRACT FROM AUTHOR]

Volume restriction, low battery capacity and low focal length camera in Wireless Capsule Endoscopy (WCE) result in images being of lower contrast, darkness, un-even brightness and image degradations. In this paper, a Laplacian pyramid based Image fusion of Contrast Limited Adaptive Histogram Equalization (CLAHE) and Multi-Scale Retinex with Colour Restoration (MSRCR) to integrate information of both techniques have been proposed. The proposed technique combines the information from CLAHE and MSRCR, reduces uncertainties, redundancy and maximizes the information. Experimental evaluation reveals that the proposed method outperforms existing methods in terms of Peak Signal to Noise Ratio and Structural Similarity Index Measure. [ABSTRACT FROM AUTHOR]

In this paper, a modified compact ultra-wide band (UWB) monopole antenna possessing U-shaped slots and multi-band rejection characteristics are presented. The dimensions of the presented antenna are 30 × 30 × 1 mm3, and it is fed by the coplanar waveguide (CPW). Inverted U-shaped slots produce three notched frequency bands at 2.5, 3.5 and 5.5 GHz. The lengths of the slots are modified for adjusting the frequency bands. The results of measurement and simulation show a VSWR of ≤2 for the antenna. The presented antenna is a perfect candidate for applications in UWB because of its omnidirectional radiation patterns. The antenna shows a radiation efficiency of above 85%. [ABSTRACT FROM AUTHOR]

The main goal of this article is to design a low-profile wide band Rectangular Dielectric Resonator Antenna (RDRA). The proposed "S" shaped rectangular DRA is excited by means of a popular microstrip line feeding. By using "S" shaped design, our proposed DRA yields an impedance bandwidth of 32% from 9.2 to 12.48 GHz, covering "X" band frequency. The proposed antenna has a wide impedance bandwidth, extremely low profile with the volume of 447 mm3, and a thickness equal to 2.5 mm. This design provides stable radiation patterns and high radiation efficiency. The proposed design is compared with some other designs in the literature in order to emphasize its significance. The proposed RDRA was fabricated and its characteristics were tested. Excellent agreement between simulated and measured ones was obtained. [ABSTRACT FROM AUTHOR]

In this paper, a simple 2 × 2 polarization reconfigurable planar microstrip array antenna is presented. It is based on electrical switching technology using PIN diodes. Each element of the array is excited with the aid of the corporate feed technique. Each element of the proposed structure consists of a corner truncated square patch connected to parasitic triangular conductors by means of PIN diodes. The array element is configured to facilitate linear polarization (LP), right-hand circular polarization (RHCP) or left-hand circular polarization (LHCP) by means of 4 independently biased PIN diodes. The proposed antenna is designed and simulated using electromagnetic simulation software CST Microwave Studio. In order to experimentally validate the design, a prototype is fabricated on a 1.6 mm thick RT Duroid substrate of relative permittivity ϵr = 2.2. The performance of the antenna is validated experimentally using 16 PIN diodes. The simulation and measured results for all the polarization states of the array antenna are found to be in good agreement. The measured results have established the polarization reconfigurable ability of the antenna for 5.7–6.0 GHz operating band. The proposed antenna is suitable for C-band point-to-point communication applications. [ABSTRACT FROM AUTHOR]

In this research, determination of the applicable ultrasonic sensors based on the wall thickness of the metal pipe for the purpose of transmission tomography is studied. The range of applicable ultrasonic frequencies according to the thickness of the metal pipe is investigated. For the study of the behaviour of ultrasonic wave propagation in various metal pipes of different thicknesses, two-dimensional (2D) modelling of the system with COMSOL software is utilized. The paper presents an exploration of the effect of variation of the wall thickness on the propagation of ultrasonic waves, including a frequency analysis in order to find the maximum applicable frequency. The simulation results are compared to experimental data and are shown to provide key insight for this well-defined experimental case by explaining the signals obtained from the experimental setup. Finally, the experimental results which are useful for further investigation for the application of ultrasonic transmission tomography in the industry are illustrated. [ABSTRACT FROM AUTHOR]

Medical image detection and classification play an important role in medical research. Tumour detection is a process of crucial importance in oncology. The aim of this paper is to devise an approach for efficient image enhancement, tumour detection, and classification on computed tomographic lung images. Three different application-related methods on computed tomography (CT) images have been designed and implemented in this work. The first method, which was based on image quality, enhances the performance of the medical images. Generally, the CT images are very sensitive to noise and are difficult to handle. Proper care may be taken by introducing some preprocessing algorithms like enhancement algorithms and filters. According to this, an image enhancement algorithm, Wavelet Shrinkage adaptive histogram Equalization (WSAHE), with anisotropic diffusion filter (ADF) was introduced to improve the contrast of the CT images and denoising. In the second method Seed Region growing with Random walk segmentation algorithm (SRGWRWS) is proposed for lung tumour segmentation. In the third method GLCM features, FOS features, structural features, and combinational features are calculated from the segmented lung images. After segmentation, the tumour classification is done by Multi-class support vector machine (MCSVM) and Descend RUSBOOST classifiers. Here, MCSVM classifier was used to find whether the input CT tumour image is suspicious, benign or malignant. Overall accuracy of 92% is obtained using Descend RUSBOOST classifier with GLCM features, FOS features, structural features, combinational features and overall accuracy of 97% is obtained using MCSVM classifier with GLCM feature in MATLAB 2017a software. [ABSTRACT FROM AUTHOR]

The carrier transport in uniaxial strained Si N channel metal oxide semiconductor field effect transistor (NMOSFET) irradiated by gamma rays is analysed. Based on the total dose irradiation effect, an analytical model for differential capacitance of uniaxial strained Si Nano NMOSFET is established. Based on this model, numerical calculation is carried out by MATLAB. The influence of geometric parameters and total dose on differential capacitance is simulated. Meanwhile, the simulation results match the calculation results very well, which validate the accuracy of the model. Therefore, the model provides a good reference for the irradiation reliability of uniaxial strained Si nano NMOSFET and the application of strained integrated circuits. [ABSTRACT FROM AUTHOR]

Electrocardiography is one of the vital physiological signals which gives information about the different phases of cardiac activity. Monitoring the activity of the heart plays a major role in timely treatment and thereby reduces the number of deaths due to cardiac diseases. As there are several problems posed by the conventional ECG monitoring system for long term applications, a contactless ECG monitoring system can be used as an alternative. But there are several downsides to contactless ECG monitoring system as well, which prevent it from reaching the standards required for clinical use. Hence, an analysis of the different factors that can possibly affect the quality of the ECG signal being acquired using the contactless system is required, in order to understand the problems better and to overcome them. The different factors that are considered in the present analysis are change in dielectric material, change in thickness of the dielectric, effect of motion artefacts, and effect of stray and cable capacitances. [ABSTRACT FROM AUTHOR]

This paper presents an approach of neural modeling for the diagnosis of fetus abnormality using ultrasound (US) images. The proposed algorithm is a hybrid approach wherein image processing methods have been used for preprocessing the image data, and an artificial neural network has been used as a classifier to extract fetus abnormality. Initially, 350 US images were collected in DICOM format directly from the radiologist and were preprocessed to extract the fetal biometric parameters using a morphological operator and a gradient vector flow algorithm. The extracted parameters were labeled as normal and abnormal fetal parameters. The extracted parameters were then applied to a Feed-Forward Back-propagation Neural Network (FFNN) for the training and validation purpose. These neural networks are capable to provide excellent performance in the critical cases especially in the field of pattern recognition. The result found from the proposed FFNNs was in closed confirmation with the real-time results. This modeling will help radiologist to take appropriate decisions in the boundary line cases. [ABSTRACT FROM AUTHOR]

This paper clarifies the optimal control strategy of Hybrid Renewable Energy System (HRES), which has the parallel execution of Lightning Search algorithm with Artificial Neural Network and Recurrent Neural Network (PLSANN). The projected system is composed of Photovoltaic (PV), Wind Turbine (WT), Fuel Cell (FC), and Battery, which can associate DC link and competent to balance the real and reactive power. The introduction of wind/PV power within an electric grid origin the PQ troubles are considered. At this point, the recompense policy of DC/DC converter is examined by PLSANN/RNN technique to provide the optimal power flow management of HRES. Here, LSA is exploited for the optimization process of real power and the Recurrent Neural Network (RNN) is utilized for the optimal reactive management. The projected process recognizes the finest control pulses of the DC/DC converter derived from the foundation part and load part limitation. The projected system is competent to establish the active power into the grid and additionally it is capable of enhancing the PQ. With proper control, HRES significantly enhance the dynamic security of the power system. The proposed method is implemented in MATLAB/Simulink working platform and analyzed their performances. The statistical analysis of proposed method is analyzed in terms of mean, median and standard deviation factors. In order to prove the effectiveness, the proposed method is compared with current techniques such as Combined Modified Bat Search algorithm–artificial neural network (CMBSNN) technique, Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and PI controller. [ABSTRACT FROM AUTHOR]

Data mining technology is an effective way to solve the problem of rich data and poor knowledge. Cluster analysis is an important content of data mining, including analysis ideas based on partition, hierarchy, density, grid and model. Neural network clustering is a typical clustering method based on model thinking. It is an organic combination of brain cognitive science and data mining. It has a strong theoretical connection with actual brain processing knowledge. This paper uses the K-means algorithm to optimize the neural network clustering data mining algorithm, and designs experiments to verify the neural network data mining clustering optimization algorithm proposed in this paper. The experimental research results in this paper show that on four UCI datasets, the mean MP values of the neural network data mining clustering optimization algorithms are 77.9 and 87.72, respectively, which are greater than the values of the other two algorithms. This paper also applies the algorithm to the study of the distribution of remaining oil. The algorithm has achieved obvious results in the cluster analysis of the degree of flooding. [ABSTRACT FROM AUTHOR]

With the rapid development of microelectronics technology, digital image processing technology has deepened our lives. In the past, image processing mostly used software processing. Due to the large number of processing algorithms and the complexity of the algorithm, it could not meet the real-time requirements. Therefore, this paper proposes a method for parallel processing of ultrasound images based on fax by using a programmable logic device. Image fusion is to extract and synthesize complementary information from different sensors to obtain a more accurate, comprehensive and reliable description of the target or scene. The transmission of images and other images is achieved by the sound of various sensors, which is far from enough. This article presents the use of hardware description language to design image processing and drivers. The core of the print head, scan head and stepper motor can use the control interface to perform selective and parameter variable median filtering on the scanned graphic image through software. Edge sharpening, image field separation, binarization and other hardware processing are compared with a series of processing directly using software, and the optimal processing plan can be made well, and the processed image can be displayed and printed out on the. This design can produce practical results for designs in the fields of biomedicine, sports, and energy production. [ABSTRACT FROM AUTHOR]

Porcelain art is a classic art treasure in the history of human civilization. After thousands of years of development, it carries the wisdom and sweat of the ancients and draws us a masterpiece that spans thousands of years. China is the hometown of porcelain. As the essence of Chinese art, porcelain has retained the traditional artistic characteristics of our country for thousands of years. Porcelain design can not only capture people's living experience and cultural understanding, but also express the thoughts or feelings of predecessors. This thesis aims to study the application of Leizhou kiln porcelain pattern gene extraction and modern design in the secure Internet of Things. The extraction of Leizhou kiln porcelain patterns in this paper is a very rigorous technical work. First, a security IoT monitoring and early warning system must be established. Secondly, a field survey of Leizhou Museum and Zhanjiang City Museum will be carried out to take photos of Leizhou kiln porcelain from various angles, combined with literature. Sort out the first-hand porcelain materials and classify the porcelain according to the age of production. Then use software such as photoshop, Adobe illustrator, CorelDRAW and other software to extract unit patterns from the patterns on the Leizhou kiln porcelain in turn, use symmetry, exaggeration and other basic skeleton deformation processing, refer to the popular color matching, to form a modern and unique pattern. The results of the empirical analysis show that we must use the Internet of Things technology to take safety measures before Leizhou kiln porcelain pattern gene extraction, which can make the safety reach 91%, and we must also apply the extracted patterns to modern designs. It does not mean that the porcelain patterns are directly used. What we want to achieve is an innovative way of inheritance, so that these porcelain patterns will be presented to everyone with a brand-new mental outlook. [ABSTRACT FROM AUTHOR]

In today's era of Internet of Things (IoT) applications, Cognitive Radio (CR) is recognized as the most promising technology to access the unused spectrum. Such CR networks can be easily built using Wide-band spectrum sensing. However, the processing of wide-band signals involves a high sampling rate. In such scenario, Compressed Spectrum Sensing (CSS) overcomes the challenges of real-time signal recovery and sampling. CSS uses Sparse signals which are widely used in many applications as they aid in processing large data. Beyond sparsity, all the real-world signals will have special structures (like Restricted Isometric property, Null space property). Moreover, it is very hard to determine the domain in which the signal is sparse. To find this we need a random measurement matrix which plays an important role in extracting the sparse coefficients of the signal. In this paper, a customized neural network is employed to identify the peculiar structures of sparse signals for efficient recovery in real time. The neural network learns and trains an adaptive measurement matrix from the sparse signals to reduce the sensing overhead. The transmitter and receiver systems are configured using Universal Software Radio Peripheral (USRP) boards with LabVIEW® and MATLAB® extensions for peer to peer communications. The implementation results depict the superior performance of neural network based recovery in assimilating the additional structures of real-time signals. [ABSTRACT FROM AUTHOR]

Providing safety, security, operational convenience and energy savings are some of the vital goals of a home automation system. A single unified point of interaction for the user is also an important consideration. Each feature requires a different sensor, powering scheme and mounting arrangement. To address each requirement, custom node development is to be prepared with all nodes being part of a personal area network for data transfer. A central node with Internet connectivity can push data to the cloud and the user can be provided access to data on a mobile app. This paper presents the practical implementation of such a distributed home automation scheme with custom-designed microcontroller-based ZigBee enabled hardware nodes for liquid petroleum gas leak detection, window open detection, lights switching control based on occupancy and intrusion detection. Messages are triggered by events and are not periodic to avoid traffic congestion. A central node built around a Raspberry Pi with a ZigBee dongle will serve as a data aggregator which sends messages to our own MQTT (Message Queuing Telemetry Transport) broker. An android mobile app will work as an MQTT client, helps the user to connect the MQTT broker, subscribe to the topics published and makes alerts to the user as soon as an event occurs. The mobile app will also enable the user to switch on lights and other appliances through command messages sent to the MQTT broker and subscribed to Raspberry Pi. [ABSTRACT FROM AUTHOR]

The present study analysed the performance of an integrated settler based anaerobic biofilm reactor (ISBABR) for domestic wastewater treatment at two hydraulic loading conditions as an onsite sanitation system. The ISBABR is designed on the basic concept of conventional septic tanks and anaerobic biofilm reactors. The ISBABR was run on actual sewage after inoculating it with digested sludge, whose COD (Chemical oxygen demand) and VSS (Volatile suspended solids) values were 9.65 and 7.13 g/l respectively. The system was operated on steady and non-steady hydraulic loading conditions while maintaining 24 h HRT for 4 consecutive months. The average removal efficiency of the system in terms of TSS (Total suspended solids), BOD (Biochemical oxygen demand) and COD was found to be 90.09 ± 4.5%, 89.89 ± 3.2% and 87.89 ± 5.2% respectively, under both the hydraulic loading conditions. In bacterial analysis, the removal efficiency of the system in terms of TC (Total coliform) and FC (Fecal coliform) was found to be 85.5 ± 4.9% and 96.36 ± 1.5% respectively. The morphology of the sludge showed the presence of anaerobes, which was a good indicator for the system. The results of the present study prove that the ISBABR is perfect system for onsite sanitation. [ABSTRACT FROM AUTHOR]

The game theory concept has been adapted for energy management between energy producers and consumers in the presence of renewable energy sources (RES) and electric vehicles (EVs). The objective of the paper is to increase the penetration of renewable energy sources and EVs by the Stackelberg game theory model with real-time pricing. RES are the energy generation sources located near load centers to manage the demand of consumers. The primary objective of EV is transportation, but for managing the energy demand, EV participate in grid operations as a back up source of energy. EV are charged during off-peak hours and discharged to the grid during peak hours. Consumers benefited in terms of higher payoffs to supply energy during peak hours. To increase the payoffs, consumers can shift their appliance operation from high price duration to low price duration and create a new peak energy consumption. To maintain the balance between consumers and utility, an optimization tool is essential. The Stackelberg game theory model is a one leader and N followers' game, the leader first declares the energy price and the follower respond by selecting their best response for energy consumption. The leader can update its strategy again by considering the follower best response to obtain maximum benefits. The process to achieve the best response of the follower and leader is called the Stackelberg nash equilibrium. Objective of energy producers is to supply maximum energy through renewable energy sources and the use of EVs as storage units. The prime objective of consumers is to minimize energy tariff by scheduling the appliances. [ABSTRACT FROM AUTHOR]

PROBLEM-Training programmes are conducted to increase competency of trainees but effectiveness is not known. In most of the already published papers on training effectiveness measurement is based on learning outcomes and there is no focus on inputs. For continuous improvement in deliverables feedback about inputs is necessary. PURPOSE – Quality depends on customer satisfaction & meeting the expectations of the customer. James Cowan stated the Effectiveness is the ratio of actual to ideal outcome. An ideal outcome from Quality Management perspective is meeting the expectations of the customers. Hence, the purpose of the research paper is to find whether the training programme on Design and Analysis of Machines using Motion view and MATLAB conducted at MNIT Jaipur in collaboration with ATAL(AICTE Training and Learning) Academy was effective in the eyes of the students for whom it was designed. The effectiveness of teaching components like Instruction Material, Teacher, Teaching Methodology, Classroom Environment have an impact on the learning effectiveness so the intention is to formulate a regression model of learning effectiveness. DESIGN/METHODOLOGY/APPROACH – Literature review method was used to find out the basic concepts related to teaching methodology, types of teaching levels general and psychological teaching principles, training methods etc. Infrastructure related environmental conditions required were studied. The research design was of descriptive type as a questionnaire was designed based on literature review to map the effectiveness of above programme in which 15 questions were asked. The sampling type was non random sampling where selection of participants was done by MNIT college and more than 40 participants were selected. On the final day of the training 27 participants were available in the last session who filled the questionnaire and sampling was quota sampling. FINDINGS – Detailed analysis reveals that there are different dimensions which contribute to training effectiveness. A training programme is effective if (a) it meets the expectations of the students (92.59% felt that) (b) it attains the goals of memory, understanding and reflective levels of teaching (80.16,71.07, 60.74 % from sample felt that goals are attained) (c) uniform assessment is there for all participants (37.04, 51.85, 70.37 % feel that diagnostic, formative, summative assessment was conducted) (d) General & Psychological principles of teaching are achieved (77.78 % & 62.96 % of students felt that all General & Psychological principles were attained) (e) Teacher, Instruction Material, Infrastructure, Teaching Methodology, Learning all are effective (85.43, 76.30, 86.17, 72.84, 77.04 % felt that) (f) All topics are covered (81.48% felt that). Note: Sample statistics are given in brackets. PRACTICAL IMPLICATIONS – Effectiveness is the most important measure to find out whether goals are accomplished. The measurement of effectiveness should be done considering inputs, process, output factors and by taking feedback about all the deliverables it can be improved. ORIGINALITY/VALUE – This paper studies factors which probably have an impact on participant expectation fulfilment and highlights many new probable dimensional measures of training effectiveness irrespective of the training subject. [ABSTRACT FROM AUTHOR]

Enhanced awareness about plastic cutlery pollution has brought a green transition in consumers' intentions. Through the lens of green offers by the food aggregators, this research investigates the relationship of the antecedents to green consumption intention. A conceptual model extending the stimulus-organism-response (S-O-R) theory is tested by Structural Equation Modeling (SEM) on the primary data of 622 green consumers. The significant relations between perceived consumer effectiveness to green brand trust, influencing green consumption intentions were established. Social Image partially mediates the relation of green brand trust to green consumption intention. The identified relationships among the variables provide practical and theoretical implications. [ABSTRACT FROM AUTHOR]

Flexible electronics is an imminent revolution in industry, where devices can be developed using sustainable materials and processes. Some of the criteria for sustainability are low cost, low energy consumption, recyclability, and biodegradability. Besides, this technology is bringing into existence electronic gadgets that are light weight, flexible, and conform to the human body. In this paper, we describe a prototype tactile array sensor (TAS) that can enhance the existing prosthetic gadgets. As an example, the sensor can be used to detect an approaching object or surface for a prosthetic foot. Finite element method simulations have been done to show the feasibility of the proposed approach. Flexibility is of importance for prosthetics used by children of growing age for better adaptability, reduced frequency of changes, and creativity in product design [Torres-Jara, Dexterous and Compliant Robotic US 8,662,552 B2,2014]. Once developed, this application for sustainable prosthesis is expected to complement the pioneering work done at the MIT Tata Center toward the development of affordable mobile-enabled diabetic foot analyzer that has enabled regular monitoring of detection of loss of sensation in the feet of diabetic patients avoiding foot ulcers and leg amputation. [ABSTRACT FROM AUTHOR]

This paper discusses the design and low-cost implementation of direction and speed controller for an electric wheelchair actuated using a permanent magnet direct current (PMDC) motor. Most of the works are performed either with the simulation of PMDC motor control with various techniques or studied the performance of a single type of controller in real-time with the wheelchair. In this work, the authors simulated the control of PMDC motor with three different controllers and tuned the parameters for real-time implementation of electric wheelchair control using PMDC motor. The authors attempted the simple solution using push button-based interface as well as a graphical user interface for the direction and speed control of electric wheelchair. The signal processing path of the controller, decode the user command input for the direction and desired speed. The controller generates necessary pulse width modulated signals to the H-bridge driver for directions forward, backward, left, and right direction as well as speed control of wheelchair. The user speed control commands low, slightly medium, medium, high, and very high speed are sensed to limit the speed of wheelchair. The performance capability of the intelligent neural network and fuzzy logic controller is studied and compared with proportional-integral-derivative (PID) controller with variations in speed. The PID, neural network and fuzzy logic controller are designed using Matlab-Simulink for PMDC motor and controller parameters are tuned for driving the wheelchair in the real-time implementation using the ATmega 328P microcontroller. The fuzzy logic controller in the electric wheelchair demonstrated the improved performance with less peak overshoot and faster settling with less oscillation compared to PID and neural network controller. [ABSTRACT FROM AUTHOR]

The Histogram of Oriented Gradient (HOG) has been found to be an effective method for the face detection as well as the facial expression recognition. However, due to the large feature length of the facial expression, there is a challenge to decrease the size of the feature vector. A novel method is proposed using the graph signal processing (GSP) with the HOG to reduce the length of the feature vector and to increase the accuracy for recognizing the facial expression. The proposed method is demonstrated on CK+ and JAFFE database and the experimental performance is compared with the results of other methods using the same databases. The better recognition rate with the significant reduction in the feature length in the experimental results shows the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we present and compare two techniques of discriminating complex objects, using the electromagnetic scattering response in the time and frequency domains. The scattering in the time and frequency domains are computed using the Finite Difference Time Domain (FDTD) method and the Method of Moments (MoM), respectively. The dominant Natural Resonant Frequencies (NRFs) of the objects have been identified, using the Matrix Pencil of Function (MPoF) algorithm from the scattering response in the time domain, and the Vector Fitting (VF) method using the response in the frequency domain. The dominant NRFs in both cases have been identified after thresholding the power contribution of each pole. A "Risk" function using the dominant poles of any two scattering objects is then defined, which aids in quantifying the discrimination. Perfectly Electrically Conducting (PEC) objects with minor variations in their geometric shape have been discriminated using the risk function. It is shown that the techniques described in this paper are effective in discriminating targets. Both approaches, using the time and frequency domain scattering response are found to yield identical results. A single run of the FDTD algorithm is sufficient to compute the electromagnetic response required to determine the dominant natural resonances. Hence, the approach of using the time domain scattering response is computationally efficient. Thus a hybrid approach of computing the resonances from the time domain scattering response and discrimination using the risk function defined, is fast enough to apply to targets of realistic size such as an aircraft at operational radar frequencies. [ABSTRACT FROM AUTHOR]

This article presents an LLC resonant high-voltage DC–DC converter based on the hybrid symmetrical voltage multiplier that consists of the full-bridge inverter circuit, one resonant tank circuit, one power transformer, and the voltage multiplier circuit. The proposed converter operates below resonance on the negative slope region of DC characteristics curve for realization of zero voltage switching (ZVS) operation. Within this operating region, the power switches and output diodes of the converters generally operate under the ZVS and zero current switching (ZCS) conditions, respectively. The detail structure, design procedure, operation, and steady-state analysis of the proposed converter are thus described. Furthermore, an experimental prototype was built and tested with the input voltage of 100VDC. The results show that the proposed converter is capable to operate under soft-switching conditions, resulting in higher efficiency. The maximum efficiency of the proposed converter of about 96% was recorded at the output power of 550 W. [ABSTRACT FROM AUTHOR]

Nowadays, nanotechnology is gaining more advantages and widely used in many real-life applications including minute tumor detection and effective diagnosis. Nanoscale imaging technique significantly increases the precision, accuracy of tumor detection, and classification of tumor into benign and malignant. Computerized tomography (CT) scan is important for lung cancer diagnosis and research, because it gives accurate segmentation results in lung tumor. In the proposed NBDS method, nanotechnology based detection scheme is used to detect the lung tumors in nanoscale range. Pulmonary nodules are symptoms of lung cancer. The shape and size of these pulmonary nodules are used to diagnose lung cancer in CT images. In the early stages, nodules are very small, and radiologist has to refer to many CT images to diagnose the disease, causing operator mistakes. Image processing algorithms are used as an aid to detect and localize nodules. Here, the input nanoimage is enhanced by using the technique of unsharp masking with the anisotropic filter. By using toboggan algorithm, lung cancer images are segmented. Nano measuring tool for graphical user interface is developed in MATLAB software to detect the lung tumor area or lung lesion in the body (in nanometers). Image classification and feature extraction are done by K-nearest neighbor (KNN) and support vector machine (SVM) with Bag of Visual Words (BoVW) classifiers. The overall accuracy of 97% is obtained using GLCM and FOS features in MATLAB software. The convolutional neural network (CNN) classifier gives the maximum accuracy of 98.19% in MATLAB 2017a software, and hence, this classifier does not need the feature extraction step. Furthermore, the average time consumption for one lesion segmentation was under 4 s using our proposed method. The self-assembled biocompatible nano technique is created to detect the tumor area (in nanometers), and it automatically evaluates the disease. This novel nanotechnology-based tumor area detection schemes achieve robust, efficient, and accurate lung lesion segmentation in nano CT images. [ABSTRACT FROM AUTHOR]

The paper presents a design and quantitative analysis for an efficient light-trapping structure (LTS) based on Photonic Crystals (PhC) to enhance the performance of thin-film GaAs solar cells. LTS consists of single planar Anti-Reflection coating (ARC) layer at the top assisted by 2D PhC diffraction grating and Distributed Bragg Reflector (DBR) having alternate dielectric layers at the back of the active layer. The structure has been optically analyzed for various absorption layer thicknesses and compared with Lambertian limits, and it has been shown that with optimization of the design carefully, significant enhancement in the cell efficiency will take place for the presented LTS, especially for the devices with very thin absorption layers (typically less than 1000 nm). Further, it is demonstrated that this efficiency enhancement is attributed to the improvement in photon absorption in the wavelength range for which active layer thickness itself is not sufficient for absorption. According to the simulation analysis, the proposed cell efficiency can be enhanced 3.5 times for a 100 nm cell with LTS, and this enhancement shrinks only to 1.5 times for 1500 nm cell. The analysis has shown that for thin cells, the contribution by the optimized LTS is the main reason behind efficiency enhancement whereas the contribution from ARC remains almost constant. The evaluation of the performance of the proposed structure concerning the angle of incident light and fabrication tolerances has also been done, indicating improved performance. The paper also presents the quantitative and comparative analysis of the proposed design with different compatible designs such as a cell having double layer ARC and a cell having pyramidal ARC with PhC as BR design. Their analysis also predicts that the LTS especially BR are more important for thinner active layer cells and the cell with a pyramidal ARC with PhC outperforms the other designs. [ABSTRACT FROM AUTHOR]

The supply chain is composed of parties that directly or indirectly fulfill customer needs, including not only manufacturers and suppliers, but also transporters, warehouses, retailers, and even customers themselves. The supply chain includes all functions to accept and meet customer needs. This article aims to study the application of intelligence based on the Internet of Things in supply chain adaptive operation decision technology and optimization algorithm models. This paper proposes a supply chain information system based on the Internet of Things technology, operational decision-making model algorithms, Web service technology and information management and support systems, multi-level structure model construction of port logistics supply chains, collaborative supply chain theory and models, and port supply under the Internet of Things Chain service quality evaluation index system, and then analyze the working capital management status and inventory decision value of the production link to explore the application research of the Internet of Things applied to the supply chain decision-making technology. This paper uses 14 standard calculation formulas, and the final experimental results show that through the use of a supply chain information system based on the Internet of Things technology, the supply chain operation decision-making technology can operate efficiently. [ABSTRACT FROM AUTHOR]

An important goal of computer vision research is to give computers human-like cognitive abilities so that the computer can recognize the environment in the visual field, understand the content of emotions, and take appropriate actions. Most of the information that people can perceive is obtained through vision. It is the human goal to make computers have the same visual functions as humans. At present, although computers do not have efficient, flexible, and intelligent human vision, with the joint efforts of researchers, people are gradually achieving their goals. The purpose of this thesis is to study the application of human movement and movement scoring technology in computer vision features in sports training. In this paper, the support vector machine (SVM) method is used to recognize the human movement in the video. After the recognition, the score is then performed, which can help sports athletes to carry out standardized training. The results of this paper show that the use of SVM method can basically achieve a recognition accuracy of more than 80% of human motion actions, so that motor actions can be scored better and more conveniently. Computer vision technology for action scoring can help athletes standardize various sports skills and improve their ability to compete by improving various sports skills. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid development of 5G technology, computer technology, communication technology, and the financial industry, people have paid more and more attention to financial information security issues. This article aims to use PCA technology and optimized BP neural network, and merge the two together to build a financial information security model and conduct in-depth research. This paper proposes the PCA technology, the principal component analysis technology, which uses the concept of dimensionality reduction to convert multiple indexes into partially integrated indexes. It is a data set simplification technology and the reverse propagation algorithm training according to a certain error. The BP neural network with many levels and multiple feedbacks carried out a financial information security model simulation experiment, and finally obtained experimental data to support the model. The experimental results of this article show that in 2020, my country has become the country with the highest network coverage in the world, reaching 64.3%, and the number of denizens has reached 632 million. In this experiment, there are a total of 13,896 pieces of useful data, including 4 types. Therefore, current research attaches great importance to the field of financial information security. [ABSTRACT FROM AUTHOR]

Emotion has always been a complex psychological and physiological phenomenon of people. In order to solve the problem of emotional calculation and emotional measurement methods, it will make people's research and understanding of emotion more meaningful in the future. This article aims to study the research of emotional computing and emotional measurement methods based on intelligent algorithms for wireless network communication. This paper proposes a modelling algorithm of physiological signal emotion based on random forest and LDA. After extracting the general features and proprietary features of the signal, the random forest algorithm is used to calculate the importance of these features under different labels, and the effective features are selected from all the features according to the order of importance. This article also realizes the process of establishing a complete emotional material database and physiological emotional database. Through multiple steps such as signal screening, material selection, emotion annotation and physiological data collection, the problem of missing physiological emotion database is solved. Experimental data shows that compared with other low-level feature classification, the recognition rate of the fusion method in this paper is 57.37% higher than other algorithms, the recognition rate of other behaviours is increased by 4.35%. [ABSTRACT FROM AUTHOR]

In this paper, a new compact dual-band filter based on closed-loop rectangular ring resonator is presented. Two passbands are designed to operate at L1 and L2 global positioning system (GPS) bands, respectively. The first passband is established by utilizing the dimension of square ring resonator that resonates at L1 band. Then, a perturbation mode element is applied to the upper and lower sides of the ring to separate the other degenerate mode and allocate the second passband of the filter at L2 GPS band. The dual passband can be adjusted to meet the designer requirements. The frequency selectivity of the filter is improved by using two symmetric parallel-coupled 0-degree feed structure that introduce a pair of transmission zeros around the passband. A practical dual-band bandpass filter is fabricated and measured. The measured results show good agreement with the simulated ones. [ABSTRACT FROM AUTHOR]

Reversible ternary circuit design is now being taken into consideration for its application within the quantum computer and other technologies associated with the nanotechnology domain, in addition to the advantages of the ternary logic application as opposed to binary logic. Multiplier circuit is one of the most important computing circuit in the ALU. Therefore, the circuit optimization for the multiplication will lead to efficient processor. In this paper, the reversible circuit for multiplication of two unsigned two-digit ternary numbers has been proposed. To construct reversible ternary multiplier, a new component termed TPPG with the quantum cost of 13 for partial product generation was proposed. In addition, we have introduced four new blocks of reversible ternary adder with the quantum cost of 11, 10, 7, 5 and one constant input, which can be used in the proposed multiplier circuit. We attempted to optimize the design of the circuits in terms of quantum cost, a number of primitive gates, constant inputs, and garbage outputs as far as possible. To realize all proposed circuits, one-qutrit shift gates and two-qutrit Muthukrishnan-Stroud gates were used. [ABSTRACT FROM AUTHOR]

A direct sequence spread spectrum is employed together with a lattice coding scheme to enhance physical layer security and efficiency of a wireless communication system against the denial of service attacks, due to the presence of deliberate unwanted interferences. Based on the results, using a direct sequence spread spectrum together with a random "construction A" lattice coding scheme named "DSSS/RCA" can highly improve the error performance compared with similar methods. Regarding a typically large block code length, some constraints on the coding rate and average signal to noise ratio are drawn to guarantee a block error probability which is asymptotically close to zero. Also, the secrecy capacity of DSSS/RCA is investigated and the achievability of perfect secrecy is verified. [ABSTRACT FROM AUTHOR]