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Research on consumer in-store shopping behavior does not account for the existence of different types of display locations (e.g. storefront, store rear, secondary, front end cap, rear end cap, and shelf displays). This article focuses on accounting for and understanding the impact of various displays on consumer purchase behavior based on the Stimulus-Organism-Response (SOR) theory. Specifically, we study how displays closer to and farther from the main location of the focal category influence consumer purchase behavior. Furthermore, within the different types of displays we investigate the impact of specific types of displays on consumer's category purchase and brand choice and the moderating role of price and discounts. A hierarchical Bayesian model is estimated using scanner panel data for a large U.S. grocery chain that contains unique information on the number of product facings at multiple display locations within a store. We find that displays closer to the focal category have a larger impact, with front end cap displays having the largest impact on category purchase and shelf displays having the largest impact on brand choice. We also demonstrate the synergistic impact of price and discounts in enhancing the impact of displays on consumer purchase behavior and brand choice. Equipped with these findings we propose a display allocation optimization that results in an average increase in revenue of about 11.15% and a strategy to distribute displays across all locations in the store rather than letting one location dominate.

Indoor localization with high accuracy and efficiency has attracted much attention. Due to visible light communication (VLC), the LED lights in buildings, once modulated, hold great potential to be ubiquitous indoor localization infrastructure. However, this entails retrofitting the lighting system and is hence costly in wide adoption. To alleviate this problem, we propose to exploit modulated LEDs and existing unmodulated lights as landmarks. On this basis, we present a novel inertial-aided visible light positioning (VLP) system for lightweight indoor localization on resource-constrained platforms, such as service robots and mobile devices. With blob detection, tracking, and VLC decoding on rolling-shutter camera images, a visual front end extracts two types of blob features, i.e., mapped landmarks (MLs) and opportunistic features (OFs). These are tightly fused with inertial measurements in a stochastic cloning sliding-window extended Kalman filter (EKF) for localization. We evaluate the system by extensive experiments. The results show that it can provide lightweight, accurate, and robust global pose estimates in real time. Compared with our previous ML-only inertial-aided VLP solution, the proposed system has superior performance in terms of positional accuracy and robustness under challenging light configurations, such as sparse ML/OF distribution.

Visual-inertial odometry (VIO) is widely studied and used in autonomous robots. This article proposes a novel tightly coupled monocular VIO system based on point-line constraints (PLC-VIO). In the front end, PLC-VIO presents a line segment extraction and merging algorithm based on the EDLines method and achieves real-time feature tracking based on the geometric constraints between feature points and lines. In the back end, PLC-VIO reconstructs new 3-D landmarks of feature lines through points on the line and optimizes the states by minimizing a cost function that combines the preintegrated inertial measurement unit (IMU) error term together with the point and line reprojection error terms in a sliding window optimization framework. A loop closure module is also integrated, which enables relocalization and drift elimination. The corresponding experimental evaluations are conducted using public datasets to validate the effectiveness and robustness of the proposed system, and the results show that PLC-VIO can achieve good performance when compared with other state-of-the-art systems and, at the same time, with no compromise to real-time performance.

Detailed detection of geological hazard sources is an important and yet challenging problem that remains unsolved. In this letter, we propose a whole closed space intrinsically safe Ground Penetrating Radar (GPR) system for geological hazard detection in coal mine roadway. Compared with many existing GPRs for half-space, this GPR system is characterized by achieving a stable radiation pattern and improved gain throughout the bandwidth. The improved performance for the system is achieved by the newly microwave front end design, adding round corners on the antenna radiation surface to improve radiation efficiency, designing resistive loading for better impedance matching, and optimizing shielding cavity dimensions to eliminate environmental interference. For design validation, a field experiment in mine roadway conditions is conducted, and the results show that the developed system has a good performance in mining roadway with depth detection accuracy at 0.5 m and direction detection accuracy at 1.5 m.

Chapter 13 led us into the “front end” of the product development process, with a perspective that focused on the market. Readers should have left that chapter understanding how firms can interpret market needs and come up with a concise description of the product and of the market segment to address.

Introduction: An Automatic Speech Recognition (ASR) system enables to recognize the speech utterances and thus can be used to convert speech into text for various purposes. These systems are deployed in different environments such as clean or noisy and are used by all ages or types of people. These also present some of the major difficulties faced in the development of an ASR system. Thus, an ASR system need to be efficient, while also being accurate and robust. Our main goal is to minimize the error rate during training as well as testing phases, while implementing an ASR system. Performance of ASR depends upon different combinations of feature extraction techniques and back-end techniques. In this paper, using a continuous speech recognition system, the performance comparison of different combinations of feature extraction techniques and various types of back-end techniques has been presented Methods: Hidden Markov Models (HMMs), Subspace Gaussian Mixture Models (SGMMs) and Deep Neural Networks (DNNs) with DNN-HMM architecture, namely Karel’s, Dan’s and Hybrid DNN-SGMM architecture are used at the back-end of the implemented system. Mel frequency Cepstral Coefficient (MFCC), Perceptual Linear Prediction (PLP), and Gammatone Frequency Cepstral coefficients (GFCC) are used as feature extraction techniques at the front-end of the proposed system. Kaldi toolkit has been used for the implementation of the proposed work. The system is trained on the Texas Instruments-Massachusetts Institute of Technology (TIMIT) speech corpus for English language Results: The experimental results show that MFCC outperforms GFCC and PLP in noiseless conditions, while PLP tends to outperform MFCC and GFCC in noisy conditions. Furthermore, the hybrid of Dan’s DNN implementation along with SGMM performs the best for the back-end acoustic modeling. The proposed architecture with PLP feature extraction technique in the front end and hybrid of Dan’s DNN implementation along with SGMM at the back end outperforms the other combinations in a noisy environment. Conclusion: Automatic Speech recognition has numerous applications in our lives like Home automation, Personal assistant, Robotics etc. It is highly desirable to build an ASR system with good performance. The performance Automatic Speech Recognition is affected by various factors which include vocabulary size, whether system is speaker dependent or independent, whether speech is isolated, discontinuous or continuous, adverse conditions like noise. The paper presented an ensemble architecture that uses PLP for feature extraction at the front end and a hybrid of SGMM + Dan’s DNN in the backend to build a noise robust ASR system Discussion: The presented work in this paper discusses the performance comparison of continuous ASR systems developed using different combinations of front-end feature extraction (MFCC, PLP, and GFCC) and back-end acoustic modeling (mono-phone, tri-phone, SGMM, DNN and hybrid DNN-SGMM) techniques. Each type of front-end technique is tested in combination with each type of back-end technique. Finally, it compares the results of the combinations thus formed, to find out the best performing combination in noisy and clean conditions

Recently emerging applications in the millimeter-wave (mm-wave) frequency range, such as automotive radar, satellite communications, 5G, 6G, and beyond, have brought new and significant challenges to the implementation of microwave circuits and systems. Many of these, such as speed, power consumption, signal-handling capability, linearity, integration possibilities, and cost, are directly related to the choice of the semiconductor process technology. For the implementation of a sophisticated mm-wave front end, different technology options are available, mainly the group III–V semiconductors, silicon–germanium (SiGe) heterojunction bipolar transistor/bipolar CMOS (BiCMOS), or CMOS processes in their multiple variants [1] – [3] .

Continuous Learning is seen as the key to remain competitive and effective at work. Very often, this also takes place outside the walls of a classroom. Nowadays Digital Badges and microcredentials are pathways to acknowledge and recognize achievements and specific skills of a learner. In this research, the different techniques used in existing blockchain-based educational systems have been reviewed and in the end, a novel web-based digital badge and microcredentials system which helps the learners to acquire the desired skills is proposed. For the Blockchain, Ethereum has been used and to develop the front end ReactJS has been used. A digital badging and micro-credential system consisting of quizzes and digital badges was built with Ethereum blockchain together with ipfs to store the badge image and firebase for examination, registration, and storing courses. The proposed system proved to be very much beneficial and addressed the inherent limitations of traditional learning content management systems (LCMS).

In this work, theoretical and experimental results of solid-state resonant circuits for the transmission and reception of wireless electrical energy, for applications in mobile devices are presented. Analytical expressions are found to calculate the voltage range as a function of the distance between the emitter and the load, as well as the current at the front end of an electromagnetic wave receiver. These expressions show the parameters to be varied to achieve a greater range in the transmission of wireless electrical energy. The transmitted voltage and current are measured by an electromagnetic wave receiver and compared with theoretical values, finding an excellent correspondence between the two.

A front-end bidirectional symmetric bipolar outputs (SBOs) LLC dc-transformer (DCX) for half bridge class-D audio amplifier (HB-CDAA) system is proposed and studied in this article. The bidirectional SBO LLC DCX provides SBOs for the HB-CDAA without producing voltage pumping on the outputs of the SBO LLC DCX. The operation of the proposed bidirectional SBO LLC DCX is analyzed, and the effects of the HB-CDAA on the operation of its front-end bidirectional SBO LLC DCX are studied. Soft switching of the proposed bidirectional SBO LLC DCX can be realized both in the positive and negative audio frequency cycles, which improves efficiency of the proposed HB-CDAA system. A 100-W prototype is built up to verify the analysis results. The experimental results show that SBOs are obtained and soft switching of all switches are achieved.

A high-efficiency 27–30 GHz 0.13- ${{\mu } \text {m}}$ BiCMOS transmitter front end for mobile satellite communication (SATCOM) phased arrays is presented. A system-level analysis for determining the key parameters of the RF front end for the case of a SATCOM user terminal for geostationary Earth orbit (GEO) is presented. The building blocks of the beamformer, consisting of a phase shifter, variable attenuator, and power amplifier, are fully characterized. A 360° phase shifter with an accuracy of 7 bits and amplitude error of ±1.5 dB is integrated with a variable attenuator that provides a gain variation of 16 dB with phase error of ±5°. The chip has a measured transducer gain of 23 dB and a power consumption of 45 mW at OP1dB of 10.8 dBm. The power-added efficiency (PAE) of 26.7% is measured for the entire channel at OP1dB. An error vector magnitude (EVM) of −28 dB at Pout,avg of 6 dBm and PAEavg of 12% is measured for a 400-MHz bandwidth 64-QAM modulated signal. The overall size of the chip is ${1.18} \times {2.23}\,\,\text {mm}^{{2}}$ .

Wireless communication has witnessed rapid developments in the last few decades. To further improve the performance of wireless radio-frequency (RF) systems, emphasis has been given to designing multifunctional modules. The front end of RF systems includes transmitting/receiving antennas integrated with bandpass filters (BPFs). These integrated units are commonly known as filtering antennas or filtennas . The techniques related to designing filtennas have been continuously upgraded in the last couple of years. However, different design constraints are encountered during filtenna implementation, which can be better described in terms of frequency selectivity, bandwidth, high gain, radiation efficiency, polarization, and so on. Therefore, an extensive review has been carried out on integrated filtering antenna structures that were introduced during the last decade. The objective of the article is to present an overview of various approaches adopted to deal with different design challenges. The authors hope that this review exercise will be helpful for RF engineers to get a better understanding on filtenna designs and will encourage young researchers who would like to work in this domain.

Despite the growing importance of using social media to leverage external knowledge for new product development (NPD) in innovation, few studies have examined firm capabilities that underpin this knowledge acquisition route. This paper provides an empirical examination of firm capabilities that leverage external knowledge, utilising social media for the fuzzy-front-end (FFE) phase of the NPD process. With evidence from 27 interviews conducted with executives’ from large fast moving consumer goods (FMCG) firms, a thematic analysis using NVivo 12 is used to develop a conceptual framework capturing the key capabilities for using social media in the FFE. The findings reveal that the utilisation of social media is an ongoing process of experimenting with new technologies within the NPD phase of a firm’s innovation efforts. Hence, the results of the study suggest FMCG firms may consider developing the following capabilities to help effectively acquire external knowledge via social media: use staff specialised in social media for external knowledge identification; dedicate an independent department for social media knowledge acquisition; and encourage an open innovation culture.

A concept of the front-end system of the XCELS (eXawatt Center for Extreme Light Studies) facility is presented. Its design is aimed at achieving high stability of laser radiation parameters and possibility of their control in a wide range. Optically synchronised chirped signal (wavelength 910 nm, bandwidth more than 100 nm, and duration ∼3 ns) and pump (wavelength 1054 nm, bandwidth ∼1 nm, and duration ∼4 ns) pulses for XCELS parametric amplifiers will be implemented at the output of the front-end system. Chirped femtosecond pulses with energies above 100 mJ [no more than 15 fs long after compression, with carrier-envelope phase (CEP) stabilisation] will have a repetition rate up to 100 Hz, which will allow one to implement active energy stabilisation and to minimise the angular jitter of the emitted beam at the XCELS output. The application of picosecond pumping in the parametric amplifier of the front-end system should provide a high contrast of femtosecond pulses. The pump pulse will be linearly frequency-modulated; this approach will not affect the parametric amplification efficiency but make it possible to use spectral methods to control the pump pulse shape in order to form a pulse of specified shape at the output of power amplifiers, even under conditions of their strong saturation.

In this paper, a development of low cost, miniature, highly integration broadband RF transceiver front-end using the high selectivity hybrid resonator RF bandpass filters, and diplexer integrated w...

This paper presents a fast configurable automatic gain control (AGC) with strong focus on fast acting control and low power consumption. This AGC includes two paths, main amplification path and gain adjusting path. Using the gain adjusting path through an extra amplifier provides a way for tracking and comparing the input signal with four adjusted thresholds to be judged for selecting the appropriate gain value for main amplification path. This mechanism of gain control is done by reorganization of input level and changing the resistance of feedback in main amplification path to generate smooth variation gain, without any interruption or delay in signal flow through the variable gain amplifier. Moreover, in order to protect the user from intense transients in variations of the input signal level, output level of variable gain amplifier is directly monitored using optimum threshold to reduce the overall gain using feedback control mechanism. The minimum power is consumed by gain adjusting path has almost no considerable on power consumption, it greatly improves hearing quality. Meanwhile, using a large size PMOS differential pair at the input improved the noise performance. Proposed AGC designed and simulated in TSMC 130-nm CMOS process. The post layout simulation results the maximal SNR is 84.6 dB in 100 Hz–19.6 kHz band-width and the total consumption power of this AGC is 78 μW at 1 V supply voltage. In addition, its gain is varied smoothly between 20 to 57 dB. Achieved results demonstrate that designed AGC meet the requirement of analog front end of hearing aids.

In high-energy physics experiments, front-end (FE) digitization modules are usually driven by a common clock. At the front-end electronics and digitization modules of the detector, a precise timing reference must be established in order to make a useful timing measurement. It would be very useful for the front-end digitization system to include a feature of redundant timing crosschecking. The inspiration for the timing crosschecking scheme came from the long-abandoned analog mean-timer schemes. In this scheme, several Front-end modules are connected together through a cable set with taps connected to the digitization modules. Pulses are driven from every FE module alternately without overlapping. The arrival times of pulses sent from FE modules are digitized at the timing crosschecking module. The mean times will change as temperature changes, but the difference between the two FE modules is canceled mathematically. This feature enables the easy achievement of good timing precision without the need for complex hardware.

Automatically and accurately obtaining payload information from Load-Haul-Dump (LHD) vehicles is a typical application of information and intelligence technology in engineering equipment, which provides an important support for efficient and safe construction. In this paper, a novel comprehensive weighing model for LHD with high accuracy and adaptability is proposed by Newton-Euler method. The accuracy of the model has been greatly improved with the consideration of some critical factors such as materials randomness, driving cylinders coupling, dynamic characteristics of mechanism, system damping and working pavement. The effect of the critical factors on the accuracy of weighing model is deeply analysed through significance analysis and comparison tests, which provides an important basis for the improvement of weighing model. Validation shows that the novel model is superior to traditional models in accuracy and adaptability. In theory, the accuracy of novel model is at least 3 times higher than that of traditional models, and its accuracy can still achieve ±0.3% in complex velocity or acceleration motion, and the larger the load mass, the higher the accuracy. As a result, the novel comprehensive weighing model can provide accurate load information for LHD vehicles without affecting working efficiency. It is of great theory and application value to the development of information and intelligence technology in engineering equipment and contributes to efficient and safe construction.

The free bending forming (FBF) technology is a new die-less forming process suitable for bending complex-shaped thin-walled tubes with several bending radii. A new theoretical model of convoluted spiral tubes manufactured through FBF technology is proposed in this investigation for revealing and understanding the parameters of manufacturing the spiral tubes using FBF technology. After that, finite element modelling and experimentation were performed to verify the accuracy and reliability of the proposed theoretical model. The max error determined by comparing the experimental results with those acquired from the theoretical analysis is less than 7%. This verifies the reliability and the accuracy of the new theoretical analysis. Afterwards, the forming limit of a convolute spiral tube manufacturing by FBF technology is explored. It is realized that the spiral diameter (D) was affected by distance A which is the distance between the front end of the guide mechanism and the centre of bending die in Z direction; and eccentricity (U). In addition, it is detected that D is directly proportional with distance A and inversely proportional with distance U, where D increased by increasing distance A and decreasing U.

To overcome the limitations of critical path method (CPM) as a project network scheduling technique, various researchers have incorporated time–cost trade-off (TCT) to take care of the specified deadline and corresponding expenses. The results of an industry-wide questionnaire survey (Roofigari-Esfahan, N. (2011). Project Schedule Compression Considering Multi-objective Decision Environment (Doctoral dissertation, Concordia University).) revealed that despite the wide range of TCT analysis methods available in the literature; none of the respondents use these methods. The lack of specialized knowledge of mathematical modeling needed for defining objective function and constraint inequalities seems to be the main deterring in using these involved procedures. This necessitates developing a practical tool in the form of a simple user-friendly software capable of dealing with the rigor of optimization at the back end and entering a simple input at the front end. This paper presents a simple standalone software that requires input in the form of data defining the network precedence and activity time–cost relations. The objective function and constraints equations are automatically formed by the computer code and the mathematical model employing Linear/Integer programming is solved by an open-source solver integrated within the software itself. The program has been validated through implementing it on various case studies from the published literature. The implementation of developed software is illustrated with an example. The detailed results are then presented for a case study of small real-life project. The proposed software thus outweighs the current two stage procedure wherein a mathematical model is framed first and then some commercial solvers like Lingo (Zeinalzadeh in Aust. J. Basic Appl. Sci. 5:208–214, 2011), MATLAB are used to solve the model.

We use a database of over 15,000 teacher candidates from 15 teacher education programs in Washington state to investigate the connections between specific teacher preparation experiences and the likelihood that these candidates enter and stay in the state’s public teaching workforce. As has been found in prior research, candidates with endorsements in hard-to-staff subjects like math and special education are more likely to enter the public teaching workforce than other candidates. We also find large differences in hiring rates over time, as candidates who graduated in the years prior to and during the Great Recession are far less likely to be hired than candidates in recent years. Finally, teacher candidates hired into the same school type (elementary, middle, or high school) or into schools and classrooms with similar student demographics as their student teaching placement are more likely to stay in the teaching workforce than candidates who experience less alignment.

In this paper, we present a general target tracking and following architecture for multirotor unmanned aerial vehicles (UAVs), and provide pointers to related work. We restrict our discussions to tracking ground-based objects using a monocular camera that is not gimballed. Target tracking is accomplished using a novel visual front end combined with a recently developed multiple target tracking back end. The target following is accomplished using a novel, nonlinear control algorithm. We present an end-to-end target tracking and following architecture that uses a visual front end to obtain measurements and compute the homography, a tracking algorithm called Recursive Random Sample Consensus (R-RANSAC) to perform track initialization and tracking, a track selection scheme, and a target-following controller. Target tracking and following is accomplished using a monocular camera, an inertial measurement unit, an on-board computer, a flight control unit, a sensor to measure altitude, and a multirotor UAV under the assumption that the target is moving on fairly planar ground with nearly constant velocity.

A low-power 2.2–2.4-GHz receiver front end for Internet-of-Things (IoT) applications is presented. The front end consists of a capacitively cross-coupled common-gate low-noise amplifier (CC-CGLNA), with translational positive feedback from baseband to RF through a four-phase switching mixer, providing RF filtering and matching, in conjunction with a 1:4 transformer. A detailed analysis of the architecture is presented, highlighting the design tradeoffs between noise, out-of-band filtering, and power. A prototype integrated circuit, fabricated in 28-nm CMOS, consumes $580~\mu \text{W}$ of power for the entire receiver front end. With this submilliwatt power consumption, it achieves a noise figure (NF) of 11.9 dB, an in-band IIP3 of −6.5 dBm, and an out-of-band IIP3 of +3.3 dBm.

Many end-to-end approaches have been proposed to detect predefined keywords. For scenarios of multi-keywords, there are still two bottlenecks that need to be resolved: (1) the distribution of important data that contains keyword(s) is sparse, and (2) the timestamps of the detected keywords are inaccurate. In this paper, to alleviate the first issue and further improve the performance of the end-to-end ASR front-end, we propose the biased loss function for guiding the recognizer to pay more attention to the speech segments containing the predefined keywords. As for the second issue, we solve this problem by modifying the force alignment applied to the end-to-end ASR front-end. To get the frame-level alignment, we utilize a Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) based acoustic model (AM) for auxiliary. The proposed system is evaluated in the OpenSAT20 held by the National Institute of Standards and Technology (NIST). The performance of our end-to-end KWS system is comparable to the conventional hybrid KWS system, sometimes even slightly better. With fusion results of the end-to-end and conventional KWS systems, we won the first prize in the KWS track. On the dev dataset (a part of SAFE-T corpus), the system outperforms the baseline by a large margin, i.e., our system with GMM-HMM aligner has a lower segmentation-aware word error rates (relatively 7.9–19.2% decrease) and higher overall Actual term-weighted values (relatively 3.6–11.0% increase), which demonstrates the effectiveness of the proposed method. For more precise alignments, we can use DNN-based AM as alignmentor at the cost of more computation.

In this article, a novel broadband millimeter-wave (mm-wave) front end (FE) based on the asymmetric switch network structure is proposed for multistandard fifth-generation (5G) applications. The asymmetric switch network consists of a bidirectional impedance transformation network and a T-type topology single-pole single-throw (SPST) switch. In the TX-mode, the bidirectional impedance transformation network serves as an output matching network to achieve a continuous-mode Class-F−1 power amplifier (PA) to expand the bandwidth. In the RX-mode, the OFF impedance of the PA can be transformed into a high-impedance region by the bidirectional impedance transformation network. Based on the proposed structure, a broadband mm-wave front end is implemented in the 0.13- $\mu \text{m}$ SiGe BiCMOS process, which occupies $906\,\,\mu \text{m}\,\,\times 997\,\,\mu \text{m}$ including pads. In the TX-mode, the −1-dB $P_{\mathrm {sat}}$ bandwidth of the FE covers 21–44 GHz with the maximum output power of 18.1–19 dBm and the peak power added efficiency (PAE) of 20.2%–26.8%. In the RX-mode, the FE achieves an 84.6% and −3-dB small-signal gain fractional bandwidth from 20.2 to 49.8 GHz with 38-mW power consumption. It achieves a measured noise figure (NF) of 7.62–11.64 dB over the frequency range of 24–48 GHz. To the best of our knowledge, this is the first FE that covers all the present 5G mm-wave bands without reconfiguration.

This research investigates the application of A3 Architecture Overviews (A3AOs) in subsea front-end engineering studies. A3AO is a valuable method to support multi-disciplinary communication and share architectural knowledge in complex engineering domains. The method captures key information of an overall system and displays the system overview in a standard A3 format. In this paper, we investigate the beneficial impact a global subsea supplier can gain by applying A3AO as part of their concept evaluation process in the early phase study. Through interviews and a survey, we identified company's main challenges in concept evaluation of tie-in and connection system. We then applied the A3AO method to investigate its mitigating effect in early phase concept evaluation. We found that the company resources found the A3AO to provide a holistic system overview and support knowledge sharing. Overall, our research supports the use of A3AO as a method to promote common understanding.

Continuous monitoring of vital bio-signals is crucial to track the well-being of patients and to allow for timelymedical intervention in cases of emergency. This paper presents a compact and wearable electrocardiogram (ECG) sensor using graphene-elastomer electrodes, which were characterised, first using an electronic patient simulator, then on a human subject. We demonstrate that the proposed electrodes are highly conductive, flexible and ultralight (weighing less than 10 mg). Their skin-impedance values are significantly lower than existing electrodes including other graphene-based sensors. In addition, we demonstrate that they can be applied on the skin in dry form without needing an intermediate gel layer, or excessivemechanical pressures, overcoming an important challenge for long term monitoring applications. The proposed configuration enables the design ofwearable devices that can outperformwell-refined commercial sensors, providing great potential for electronic/mobile health applications.

Major countries are globally facing difficult situations due to this pandemic disease, COVID-19. There are high chances of getting false positives and false negatives identifying the COVID-19 symptoms through existing medical practices such as PCR (polymerase chain reaction) and RT-PCR (reverse transcription-polymerase chain reaction). It might lead to a community spread of the disease. The alternative of these tests can be CT (Computer Tomography) imaging or X-rays of the lungs to identify the patient with COVID-19 symptoms more accurately. Furthermore, by using feasible and usable technology to automate the identification of COVID-19, the facilities can be improved. This notion became the basic framework, Res-CovNet, of the implemented methodology, a hybrid methodology to bring different platforms into a single platform. This basic framework is incorporated into IoMT based framework, a web-based service to identify and classify various forms of pneumonia or COVID-19 utilizing chest X-ray images. For the front end, the.NET framework along with C# language was utilized, MongoDB was utilized for the storage aspect, Res-CovNet was utilized for the processing aspect. Deep learning combined with the notion forms a comprehensive implementation of the framework, Res-CovNet, to classify the COVID-19 affected patients from pneumonia-affected patients as both lung imaging looks similar to the naked eye. The implemented framework, Res-CovNet, developed with the technique, transfer learning in which ResNet-50 used as a pre-trained model and then extended with classification layers. The work implemented using the data of X-ray images collected from the various trustable sources that include cases such as normal, bacterial pneumonia, viral pneumonia, and COVID-19, with the overall size of the data is about 5856. The accuracy of the model implemented is about 98.4% in identifying COVID-19 against the normal cases. The accuracy of the model is about 96.2% in the case of identifying COVID-19 against all other cases, as mentioned.

Summary Presented is a model-based methodology identifying subsea field architectures that satisfy prespecified multiphysics constraints. The proposed methodology prioritizes the identified subsea system using a multiobjective optimization approach considering two objective functions, which are minimizing pressure drop reflecting the maximization of production flow rates and minimizing capital expenditures. The architecture solutions produce manifolds positioning and optimal pipeline routing/sizing. A convex combination approach creates the multiobjective optimization criterion enabling weighting among constraints such as hydraulic, topological, structural, and flow assurance, as well as technical issues and financial limitations. The optimization problem is computationally solved using a hybrid method with a global multistart algorithm that combines a scatter search process with a gradient-based local nonlinear problem solver. A case study is provided to test the proposed methodology including the effect of varying the weights among the constraints. This deep-dive analysis demonstrates the potential offered by the proposed methodology, illustrated by the ability to perform several investigations such as wells-grouping analysis and insulation effect on the overall optimization procedure, as well as to provide a tracking tool for flow-assurance factors, namely erosion and corrosion rates along the subsea layout. Hence, we present a demonstration of the capabilities of the proposed model-based subsea field layout optimization procedure.

This letter proposes an ultralow-power mixer-first front-end using voltage-mode boosting. The voltage gain is achieved passively by using capacitive stacking. By employing $N$ -path filtering technique, this front-end achieves high out-of-band (OOB) rejection which results in high in/OOB linearity. A prototype, composed of four-paths with six stages of switched capacitors, is fabricated in 28-nm CMOS technology, and achieves 29-dB gain, 5.7-dB noise figure (NF) and +10-dBm OOB-IIP3 while consuming less than $140~\mu \text{W}$ .

This article presents a power efficient 24–28-GHz four-element phased-array transceiver (TRX) front end (FE) for 5-G base stations and user equipment communications. A power efficient hybrid quadrature vector interpolation-based phase-shifting architecture is proposed to increase the TX and RX power efficiency and phase resolution. A transformer-based embedded T/R switch is proposed which minimizes TX and RX losses to ensure high TX output power and power efficiency while maintaining a low noise figure (NF) and extremely compact chip area. The 24–28-GHz four-element TRX FE is implemented in a 65-nm CMOS process (1P9M) for large-scale phased-array applications. The TX and RX paths achieve 0.8° phase resolution with $P_{\mathrm {sat}}$ with 21.1%/16.6% PAEpeak/OP1dB for each FE element while maintaining a minimum 4.4-dB NF in the full RX path (including combiner, T/R switch, and OFF-mode PA) at 28 GHz. Under the 64-/256-QAM modulation measurements, the full TX path achieves a state-of-the-art average output power of 13.5-/10.2-dBm per element (8.4%/3.5% full TX path PAE) with −26.4/−30.8 dB EVM and 27.8-/30.1-dB ACLR at 28 GHz, making the proposed TRX FE can be effectively deployed in both base stations and user equipment for 5-G communications. The chip size of the four-element TRX FE excluding I/O pads is only $3.4\times1.1$ mm2.

The efficacy of the deployment of backscatter networks in sensor networks and the internet of things has been severely limited by the maximum read range of backscatter radio frequency identification (RFID) tags. The work presented here demonstrates a low-power two-way repeater architecture capable of increasing the read range and extending the coverage of tags to non-line-of-sight (NLOS) scenarios. This is achieved through the use of a two-way frequency divided tunnel diode-based reflection amplifier optimized for use in backscattering channels. The system reports a more than 2X increase in the read range of a semi-passive RFID tag at 17 dBm output power. The work presented here shows a system capable of giving a comparable performance with the state of the art while consuming up to 1000X less power in a simple single-component front end.

This report presents a down-conversion method involving digital sideband separation for the Yuan Tseh Lee Array to double the processing bandwidth. The receiver consists of a MMIC HEMT LNA frontend operating at a wavelength of 3 mm, and sub-harmonic mixers that output signals at intermediate frequencies of 2 - 18 GHz. The sideband separation scheme involves an analog 90 degree hybrid followed by two mixers that provide down conversion of the IF signal to a pair of in phase (I) and quadrature (Q) signals in baseband. The I and Q baseband signals are digitized using 5 Giga sample per second analog to digital converters. A second hybrid is digitally implemented using field programmable gate arrays to produce two sidebands, each with a bandwidth of 1.6 GHz. The 2 x 1.6 GHz band can be tuned to cover any 3.2 GHz window within the aforementioned IF range of the array. Sideband rejection ratios (SRRs) above 20 dB can be obtained across the 3.2 GHz bandwidth by equalizing the power and delay between the I and Q baseband signals. Furthermore, SRRs above 30 dB can be achieved when calibration is applied., 8 pages, 12 figures

This study proposes a hybrid optimisation method integrating contribution analysis, Entropy weight Technique for Ordering Preferences by Similarity to Ideal Solution (E-TOPSIS), design of experimen...

Objectives: To propose a crawler to visit websites for collecting information and create a search engine index for reference; To compare various crawler License, language used for creation, effectiveness with proposed DHEKTS crawler; To compare various characteristics, tasks and functions with proposed DHEKTS crawler; To identify the merits of the DHEKTS Crawler. Methods: A new Crawler called DHEKTS is developed to filter and synchronize documents like Images, Link, and HTML code from a given website. This Crawler is unique in nature since it returns all the details of a particular website having Images, Links, html code and contents. It can crawl through links in a specified website and crawl further to other links on the website. The DHEKTS Crawler is designed for Depth and Relevance crawling. The entire DHEKTS crawler has a few crawling mechanism supporting variety of information. The requirements are Operating System: Win 7 and higher, Front End: PHP, BackEnd: MySQL, RAM: Minimum 4GB and SERVER: High Speed Server with good storage Capacity. Findings: The DHEKTS Crawler has brought web related Links, Images, HTML Code, Information about to fifth level of crawling and Relevance Search giving relevant information. Multiple crawlers fulfill the major functions of crawling but DHEKTS CRAWLER is built to execute all functions in one crawler. Applications: This is applied in Crawling of various Websites and to retrieve valuable data. Keywords: Crawler; DHEKTS Crawler; License; tasks; functions; effectiveness; Comparison

This work presents the design of a front-end MEMS piezoresistive pressure sensor readout circuit along with a drug actuator model based on TSMC 0.18 μm CMOS technology. The overall system finds application in implantable systems based on micro-pressure sensing and actuation such as the closed loop automatic micturition chip. The system consists of high performance and ultra-low noise chopper stabilized differential amplifier front-end, a digitally programmable threshold generator and window comparator circuit for setting up the pressure thresholds for urination, and an actuator model that simulates drug delivery for micturition, overactive bladder control, and bladder closure. The system also has a novel core circuit enable for power savings mode. The corresponding sub-circuits have been designed to operate in low power that is suitable for implantation and be powered by energy harvesters.

Most of failures of startup application in many countries reached 75%, while the startup failures in Indonesia reached 90%. These failures were caused by non-technical or management factors in managing startup. The RPL (Software Engineering) Laboratory of FILKOM of Brawijaya University has a roadmap to develop an application to guarantee the success of a management software project. The data analysis had been performed on FILKOM student’s thesis work which generally develops software that has main obstacle in the management. A study solution which was developed through scientific SDLC and PMLC combined with Scrum method becomes an application named SPM-SCRUM. The results of analysis carried out on several software development projects refer to the Iterative SDPM process. Furthermore, the strategy of Iterative SDPM combined with Scrum method produces a system architecture design that separates the Front End and Back End

Cloud computing is new image of Information Technology and the way applications are available to end-users. Also, the applications available are gaining popularity as being able to demonstrate the flexibility of use of resources as in Multi-Scale Cloud-Based Applications. These applications on the cloud are hosted on remote virtual machines with multi-tenancy architecture. Multi-tenant cloud computing architecture helps cloud users and customers to share computing resources and still the individual tenant's data is stored separately so as to make it is invisible to other tenants. With this multi-tenancy architecture, the application is being used by multiple people at the same time. Also, the application resides in various copies across various servers situated at different geographical locations. Virtual Machines that are housed in multiple Data Centers are coupled by way of load balancers. These load balancers are responsible for the optimal distribution of load/demand/tenant requests and the size of the data held within the request. So in short, two areas need to be focused on when architecting such systems. Firstly, the load must be balanced optimally across data centers and virtual machines for seamless operation at the back end. Secondly, at the front end, it is imperative that every tenant enjoys optimal service speeds without any degradation of service request speed. In case the back-end virtual machines are unbalanced in their load then there is bound to be degradation of services. For this very purpose, various researchers/academicians, and practitioners in the cloud space have been working tirelessly towards developing optimal algorithms to get the best load balancing architecture to ensure that the objective of seamless back end and front end quality of service in terms of average response times. Multi-Scale applications consist of variable payload for time and often unpredictable i.e. load can be increased/decreased suddenly or gradually. Hence to balance these loads equally at any time, a new algorithm is proposed. This algorithm considers the characteristics of multiscale applications in terms of data size and runtime characteristics of VM in terms of capacity and availability. Finally, the performance of this method is analyzed qualitatively as well as quantitatively by performing simulation experiments of multiscale applications.

To collaboratively improve the lightweight and frontal collision safety performance of the automobile body, the material–structure–performance integrated multi-objective optimization design of the front-end structure was implemented in this study. The hybrid weight–grey relational analysis (HW–GRA) method was proposed to address the problem that the Pareto optimal compromise solution of multi-objective optimization cannot be easily selected. The design variables of the material and structural parameters were recorded through material type coding and model parameterization. To satisfy the basic static–dynamic performance constraints of the body, the RSM–Kriging surrogate model, design of experiments, and multi-objective particle swarm optimization algorithm were used to optimize the material and structural parameters to improve the lightweight and crashworthiness of the body. The Pareto optimal compromise solution was determined using the HW–GRA method. The decision result of the proposed method was more robust and rational than those of single weighting techniques combined with GRA and hybrid weighting approach combined with TOPSIS. After the multi-objective optimization and decision-making, the basic static–dynamic performance of the body demonstrated a change of less than 2.0%, which satisfied the constraint requirements. The mass of the body was reduced by 2.4 kg, and the frontal collision safety performance of the body was significantly improved.

This article describes a 4 $\times $ 112 Gb/s digital receiver targeting long-reach (LR) channels. An SNR optimized approach is presented, which relaxes the ADC resolution requirement and the number of FFE taps without sacrificing BER. The discrete-time front end overcomes gain–BW limitations to provide 10+ dB gain at 28 GHz. A 56-GS/s ADC then converts the signal to 6-b digital consuming only 195 mW. The following DFE-FFE-based digital equalizer is capable of compensating 36-dB loss achieving a BER of 2e−5. Furthermore, TDC and ISI filter-based low-latency timing recovery meet jitter tolerance specs over a wide range of data rates from 10 to 112 Gb/s, including 28-Gb/s NRZ. The overall receiver consumes 338 mW with 3.18-pJ/bit energy efficiency.

One of the most significant goals of earthmoving equipment is to maximize productivity during loading cycles. A real-time knowledge of the forces exchanged between the machine implement and the surrounding, that is, while digging, can be used in different ways to increase productivity. It can be used to determine the amount of material moved by the machine; or to find the optimal bucket trajectory; moreover, as input to traction control systems. This article presents an online force estimation algorithm able to predict vertical and horizontal forces exchanged between the front-loader and the surrounding environment, as well as the reaction forces through the implement itself. Taking the case of a 14-ton wheel loader as reference, this article illustrates the development of a simulation model for the analysis of the machine digging system, along with the instrumentation and testing of the proposed estimation algorithm. The model is divided into two sections describing, respectively, system kinematic and system dynamics. The kinematic model of the front-loader is compared against measurements, and results show an average error lower than 1%. The dynamic model predicts both hydraulic and dynamic features of the machine implement, achieving an accuracy on the payload mass within 2%–3%, even during dynamic conditions. The estimated pushing force reflects the expected behavior when tested for various pushing efforts and in different ground conditions. Eventually, the algorithm was tested on a complete loading cycle and the results show good consistency considering the measured front-loader trajectory and vehicle speed. The proposed model overcomes some drawbacks of the currently used technologies. For example, it allows for an online estimation of the bucket forces for any position of the implement. Although the results discussed in this article pertain to a specific reference machine, the proposed method can be extended to most wheel loaders equipped with standard digging equipment.

Eye tracking je senzorska, hardverska tehnologija koja omogućava računarima ili drugim uređajima praćenje korisničkog pogleda. Eye tracker kamera može da detektuje prisustvo, pažnju i fokus korisnika. Omogućava jedinstven uvid u razumevanje ljudskog faktora prilikom korišćenja računara i olakšava izradu što prirodnijeg korisničkog interfejsa za širok spektar digitalnih uređaja. Takođe, mogućnost upravljanja računarom uz pomoć očiju predstavlja potencijalno olakšanje za korisnike kojima je onemogućen govor ili korišćenje ruku. Ovakav tip kamere je veoma skup, te je zbog toga nepristupačan većini populacije. Potencijalno rešenje ovog problema može da bude Gazepoint Eye Tracker simulator. U radu je detaljno opisan postupak implementacije softvera, način njegovog rada, kao i princip određivanja simuliranog korisničkog pogleda. Za izradu simulatora korišćen je radni okvir Angular, koji se odnosi na prezentacijski sloj aplikacije, dok će se za samu biznis logiku pobrinuti radni okvir Spring Boot u čijoj se osnovi nalazi programski jezik Java.

To satisfy the stringent requirements of the emerging wireless communication system, the dual-band operation and reconfigurability are both desired for the front end. However, few works can realize them simultaneously. In addition, the flexibility of the implemented reconfigurability is limited. In this article, a reconfigurable dual-band quadrature coupler with independently tunable characteristics at the lower band is proposed. Based on the investigation of an ideal model, the design requirements to achieve the previous reconfigurability can be obtained. Thus, the coupled line loaded with varactor is proposed on a patch coupler to implement the desired functionality. By varying the voltages applied on the varactors, the frequency and coupling coefficient at the lower band of the proposed coupler can be tuned independently with the characteristics at the upper band fixed. For validation, a prototype was designed, fabricated, and measured. Measured results show that the frequency of the coupler at the lower band can be tuned from 2.9 to 3.2 GHz. Meanwhile, the corresponding coupling coefficient can be tuned from 3 to 10 dB. During the lower band tuning, 3 dB coupling coefficient and quadrature phase difference can be always maintained for upper band, which is fixed at 4.7 GHz.

In this paper, we experimentally determine the drag coefficient when conical and cylindrical impactors penetrate into sandy soil. In the experiments, the half-opening angle of the conical tip of the penetrator (indenter) varied from 10° to 90°. The velocity of indenter movement varied in the range of 0.2–2.0 km/s. The average values of the drag coefficient are obtained for conical bodies during quasi-stationary supersonic motion in sandy soil with an average moisture content of 7–12% and for indenters with a flat front end in sandy soil with a moisture content of 0–16%. A significant dependence of the drag coefficient of thin cones (β < 25°) on the movement velocity and the absence of such a dependence (taking into account the experimental error) for obtuse cones and an indenter with a flat end were shown.