Miracle-dz/UniFAR-FTUs huggingface dataset:
A Memory-Efficient Approach to the Scalability of Recommender System With Hit Improvement

With the rapid increase of users and resources on the Internet, the scale of the recommender system becomes larger and larger. There are three major challenges facing in recommender system: sparsity, scalability, and cold start. In this paper, we mainly focus on the scalability issue and propose a recommender system based on the memory-efficient recurrent neural network. First, we allocate an item table for items and use a pair of embedding vectors to represent each item. Thus, we can use a few vectors to represent numerous items and decrease the memory used for the storage of embedding vectors. Second, we present a similarity-based initialization method for the item table to get a better representation of items. Third, we further design the loss function and the adjustment method to adjust the placement of items in the item table to speed up the training procedure of the model and get a better performance. The experimental results demonstrate the effectiveness of our approach. It can clearly improve the performance of recommendation, such as hit rate and normalized discounted cumulative gain, when compared to the state-of-the-art recommender algorithm. In addition, our approach can also handle the cold start problem and supply new users with the same quality of service as the old users.
Deep Reinforcement Learning for Mobile Edge Caching: Review, New Features, and Open Issues

Mobile edge caching is a promising technique to reduce network traffic and improve the quality of experience of mobile users. However, mobile edge caching is a challenging decision making problem with unknown future content popularity and complex network characteristics. In this article, we advocate the use of DRL to solve mobile edge caching problems by presenting an overview of recent works on mobile edge caching and DRL. We first examine the key issues in mobile edge caching and review the existing learning- based solutions proposed in the literature. We also discuss the unique features in the application of DRL in mobile edge caching, and illustrate an example of DRL-based mobile edge caching with trace-data-driven simulation results. This article concludes with a discussion of several open issues that call for substantial future research efforts.
Impacts of Viewing Conditions on HDR-VDP2

HDR (High Dynamic Range) and WCG (Wide Color Gamut) increase significantly quality of viewing experience by rendering impressive images and videos. Automatic assessing the quality of these HDR WCG images is one crucial objective in broadcast process. Full-reference HDR metrics have been designed in the last years to achieve this objective: HDR- VDP2, HDR-VQM, PU-encoding metrics. Recent studies have pointed out that HDR-VDP2 is one of the best metric. Unfortunately, HDR-VDP2 is quite complex to use due to numerous and sometimes hard-to-know parameters such as display emission spectrum, surround luminance and angular resolution. In this paper, we show that HDR-VDP2 does not require an accurate knowledge of the viewing condition parameters. For that, we not only test the impact of these parameters on existing image databases of subjective quality scores, but also we propose a new and complementary image database made with a different HDR display.
Optimal Frequency Reuse in HetNets With In-Band Relays

In-band relay nodes can be utilized to enhance the coverage of heterogeneous networks in a cost-effective way. However, the wireless backhaul links of in-band relay nodes also consume the limited spectrum resources. Appropriate spectrum resource management/cooperation is necessary to ensure the balanced resource usages between the macro base stations and the relay nodes. In this paper, we derive an optimal spectrum reuse strategy in a heterogeneous network with in-band relay nodes to maximize the overall proportional fairness metric. We first provide one distributed resource allocation algorithm based on the alternating direction method of multipliers for the heterogeneous network with in-band relay nodes. Even though the number of feasible spectrum reuse patterns increases exponentially with the total number of base stations and relay nodes, we further prove that we can achieve the optimal network performance by only activating a limited number of spectrum reuse patterns, which is just in the order of the total number of mobile stations and relay nodes. According to this finding, we put forth an algorithm to refine the set of active reuse patterns in a soft manner by employing the re-weighted $\ell _{1}$ -norm algorithm. Numerical simulations demonstrate the superiority and effectiveness of our proposed algorithms.
Automatic Speech Translation System Selecting Target Language by Direction-of-Arrival Information

In this paper, we propose an automatic speech translation system that selects its target language on the basis of the direction-of-arrival (DOA) information. The system uses two microphones to detect speech signals arriving from specific directions. The target language for speech recognition is selected on the basis of the DOA. Both the speech detection and target language selection relieves users from operations normally required for individual utterances, without serious increase in computational costs. In a speech-recognition evaluation of the proposed system, 80 % word accuracy was achieved for utterances recorded with two microphones that were 40cm distant from speaker positions. This accuracy is nearly equivalent to that in which the time frame and target language of a user's speech are given in advance.
Prediction Of Cloud Computing Resource Utilization

Efficient resource utilization leads cloud provider to low cost and high performance. Cloud Computing is a dynamic environment that provides on-demand services over the internet on pay as you go model. Cloud platform has a dynamic resource usage as it is shared among large number of users. Resource allocator provisions resources to dynamic demands of user from finite set of resources. There should be no over and under provisioning of resources. Underutilized resources causes resource wastage and more cost whereas over utilized resource can lead to service degradation. If Resource allocators can presume future resource usage they can take resource provisioning decision efficiently. A resource utilization prediction mechanism is required to assist resource allocator for optimum resource provisioning.Accurate prediction is a challenge in such a dynamic resource usage. Machine learning techniques can help in creating a model that yields accurate prediction results. In machine learning, Ensemble mechanisms are renowned for improving the prediction accuracy which uses a combination of learners rather than a single learner. In this study, an “Ensemble based workload prediction mechanism” is proposed that is based on stack generalization. Experiments are conducted in order to compare the proposed model with the individual and baseline prediction models. For comparison with baseline model, we have used Root Mean Square Error(RMSE) as results of baseline model were given in RMSE. Proposed mechanism has shown 6% and 17% reduction in RMSE in CPU usage and in Memory usage prediction respectively. For comparing our proposed ensemble with independent learner(K Nearest Neighbor, Neural Network, Decision Tree, Support Vector Machine and Naïve Bayes), we have used accuracy as evaluation parameter. The proposed ensemble has improved the prediction accuracy by $\approx 2$%.
Unilateral Left-Tail Anderson Darling Test Based Spectrum Sensing with Laplacian Noise

This paper focuses on spectrum sensing under Laplacian noise. To remit the negative effects caused by heavy-tailed behavior of Laplacian noise, the fractional lower order moments (FLOM) technology is employed to pre-process the received samples before spectrum sensing. Via exploiting the asymmetrical difference between the distribution for the FLOM of received samples in the absence and presence of primary users, we formulate the spectrum sensing problem under Laplacian noise as a unilateral goodness-of-fit (GoF) test problem. Based on this test problem, we propose a new GoF-based detector which is called unilateral left-tail Anderson Darling (ULAD) detector. The analytical expressions for the theoretical performance, in terms of false-alarm and detection probabilities, of the ULAD are derived. Moreover, a closed-form expression for the optimal detection threshold is also derived to minimize the total error rate. Simulation results are provided to validate the theoretical analyses and to demonstrate the superior performance of the proposed detector than others.
Analysis of Programs for GPGPU Architectures

Over the past decade, General Purpose Graphics Procesing Units i.e. GPGPUs emerged as a platform for general purpose and scientific computing applications. Languages used for programming GPGPUs are CUDA, OpenCL, DirectCompute etc. As GPUs are widely being used in scientific computing, optimization of programs has become a major concern. Producing accurate results in reduced time is increasingly becoming an important factor in the usability of GPU applications in concerned domains. Program optimization requires analysis of program to find the program features or parameters that impact its execution and storage efficiency. In this work, we analyze GPGPU programs written in CUDA to extract important features in them which will be useful for further optimization.
Impedance Influence Analysis on Multi Spectral Capacitive Sensor

Electrochemical Impedance Spectroscopy (EIS) has been a well-known method that popularly used in creating a high sensitivity of the sensor. This detection method uses a multi-spectral approach, complex data analysis, a relatively fast and also accurate measurements. We describe the method of sensing using a multi spectral capacitive sensor (MSCS) which has based on the EIS principal. Results analyses were done for 150 data sets that have been taken from pure water using MSCS. The output of this sensor is shown in a 3D (Dimension) image which is known as HHF (High High-Fluctuation) and also represents the amplitude of fluctuation in noise spectral frequency. In this study, we manage to define the effect of impedance in the sensor system to the output with such qualitative and quantitative observation. There are two types of impedance used, which are 3.3 MΩ, and 8.2 MΩ, respectively. The result will reveal the amplitude values. Hence, it is easier to observe the fluctuation value and consistency value of the material measured.
A Capacitive Loading Method for Turning a Single-Band Antenna Into Dual-Band for Wireless Terminal Applications

This letter proposes a simple method to turn a single-band inverted-F antenna (IFA) or loop antenna into a dual-band antenna with a small frequency ratio and similar radiation patterns by simply adding a capacitor near the shorting end of a conventional single-band IFA or a loop antenna. Two demonstration examples imitating a mobile terminal application using IFA and loop antenna are present. The measured results show that the IFA and loop antenna with an added capacitor near the shorting end have comparable radiation patterns and total efficiencies in the two designed frequency bands compared with the antennas without the capacitor. The measured frequency ratio of the two resonances is 1.15 (2.23 and 2.56 GHz) for IFA and 1.19 (2.19 and 2.61 GHz) for loop antenna. And the two resonant frequencies can be easily controlled by tuning the added capacitor so that this method can be easily applied to frequency agility applications. To illustrate the physical mechanism, a transmission line model is presented and analyzed.
Image-Based Pedestrian Classification for 79 GHz Automotive Radar

Radar sensors have become an integral part of advanced driver assistance systems. Merely detecting targets will not, however, advance their contribution. Rather, an object classification capability is required to distinguish vulnerable road users from other objects, such as vehicles. In this paper, we present a novel pedestrian classification procedure, which uses image features from the range-Doppler-Matrix created by a 79 GHz chirp sequence radar. Experiments show single measurement success rates of 88% for a bandwidth of 1.6 GHz. Moreover, the robustness of the classification process is consolidated with a tracking algorithm. Implemented in vehicles, this can be a major contribution to protect vulnerable road users.
A Novel Propulsion Control Scheme of Long Stator Linear Synchronous Motor for Maglev Vehicle Considering the Influence of Suspension System

The long stator linear synchronous motor (LSLSM) for high-speed maglev vehicle is used not only for propulsion but also for suspension system. The performance of propulsion control will be affected by the suspension system. Therefore, this paper presents a novel propulsion control scheme to reduce the thrust fluctuations caused by the influence of the suspension system. The control scheme is proposed based on the estimation of mutual flux linkage between the excitation winding and the $d$ -axis stator winding of the LSLSM. By adding the flux linkage information to the outer speed loop and the inner current loop, the thrust fluctuations caused by the suspension system will be effectively suppressed. The simulation results show the effectiveness of the control scheme.
Silicon-Photonic Dense 8-Channel Multiplexer Using Auto-Regressive Moving-Average Filters

We propose and demonstrate an integrated 8-channel dense wavelength division multiplexer in silicon-on-insulator platform. The device layout comprises of 7 stages in a tree topology. Each stage is based on an unbalanced Mach-Zehnder interferometer with a nested ring resonator. The transfer function of each stage is that of an auto-regressive moving-average filter, characterized by a uniform passband, strong out-of-band rejection and sharp spectral transitions. The passband of each channel is extremely narrow: only 0.135 nm (16 GHz), and the worst-case crosstalk among channels is -22 dB. Individual phase delays within the device are trimmed through selective photo-removal of an upper cladding layer of photo-sensitive chalcogenide glass. The devices are suitable for integrated-photonic processing of radio-over-fiber and mm-wave communication.
Vehicle Control System for Cooperative Driving Coordinated Multi -Layered Edge Servers

Cooperative driving, where multiple vehicles are remotely and automatically operated and controlled through low-latency communication, has caught much attention recently. To achieve cooperative driving systems, cloud-based and/or Mo-bile/Multi Access Edge Computing (MEC)-based vehicle control systems have been proposed. They have a trade-off between the feedback latency in terms of controlling and capacity defined as the number of vehicles for which the cloud or edge-server can accommodate sensor information via the network. To take advantage of both systems, we have proposed a vehicle control system corrdinated an Upper Edge Server (UpES) that has a large capacity and a Lower Edge Server (LoES) that executes remote control with low latency. The previous system, however, does not consider autonomous control by the vehicle. When burst packet loss occurs, the previous system collapses. Furthermore, the previous system cannot be sufficiently evaluated using actual latency information in the real world. In this paper, we propose the coordination of the previous system and autonomous control. By considering autonomous control, the proposed system achieves a more flexible deployment of edge servers than the previous system. To evaluate the proposed system, we simulate the control time ratio between autonomous and remote control using the measured latency between various cloud services and carriers. From the simulation, we show the following. Multi-layered edge servers are required for cooperative driving systems. Our proposed system can solve the trade-off among the capacity, number of required edge servers, and control time ratio.
Iterative Reconstruction of Spectrally Sparse Signals from Level Crossings

This paper considers the problem of sparse signal reconstruction from the timing of its Level Crossings (LC)s. We formulate the sparse Zero Crossing (ZC) reconstruction problem in terms of a single L-blt Compressive Sensing (CS) model. We also extend the Smoothed LO (SLO) sparse reconstruction algorithm to the I-bit CS framework and propose the Binary SLO (BSLO) algorithm for iterative reconstruction of the sparse signal from ZCs in cases where the number of sparse coefficients is not known to the reconstruction algorithm a priori. Similar to the ZC case, we propose a system of simultaneously constrained signed-CS problems to reconstruct a sparse signal from its Level Crossings (LC)s and modify both the Binary Iterative Hard Thresholding (BIHT) and BSLO algorithms to solve this problem. Simulation results demonstrate superior performance of the proposed LC reconstruction techniques in comparison with the literature.
Performance Analysis of Grid- Tie Inverter for Reactive Power Injection Mode in Hybrid Wind Solar Energy System

Though the average lifespan of a wind turbine is 20−25 years, the power is being generated in the wind generating stations even after the average life span. But, when the wind turbine is used after this average life span the maximum power that can be generated will be reduced due to aging of mechanical parts and maintenance factors. Also, the other equipments like transformer and switchgear can be operated with reasonable efficiency even after the maximum working life span of the wind turbine. Hence utilization of a wind generating station can be improved by connecting a solar power system with the existing transformer and switch gear setup which forms hybrid wind-solar energy system. The various possible features that can be added in the hybrid system are discussed and analyzed in this paper. This work mainly focuses on the solar array and grid connected inverter and its performance. The solar irradiation is available only during the day time (i.e., 6 to 8 hours per day). In the absence of solar radiations, the PV system and grid connected inverter will be idle. To increase the utilization of the grid-tie inverter for a day, it can also be operated at reactive power injection mode when the PV power is unavailable. The inverter that can be operated at both active and reactive power injection mode is simulated in this paper. Results and effective analysis are carried out to enhance the operation of grid connected inverter used in the hybrid power station.
Thrust Ripple Reduction in Permanent Magnet Synchronous Linear Motor Based on Electromagnetic Damping-Spring System

This paper proposes an electromagnetic damping-spring system (ED-SS) to reduce the thrust ripple of permanent magnet synchronous linear motor (PMSLM), which is applied to the laser cutting machine. This approach uses restraining force of ED-SS that offsets the ripple force to decrease the thrust ripple. First, the ED-SS is designed with the structure and motion characteristics of PMSLM. The equivalent magnetization method is used to analyze the PMSLM thrust. Simultaneously, the ripple force is obtained and acted as the excitation of ED-SS. Next, the equivalent surface current method and the virtual work principle are utilized to express the restraining force characteristics and the relationship among the designed parameters of ED-SS. The standard deviation of PMSLM thrust is selected as an index to evaluate the magnitude of thrust ripple. Finally, simulation is performed to verify the validity of the theory analysis. The prototype of PMSLM with ED-SS is manufactured and three prototype experiments are conducted. The experimental results verify the validity of the proposed approach.
Comparative Study of Perturb & Observe and Look -Up Table Maximum Power Point Tracking Techniques using MATLABISimulink

The need and trend of using Renewable Energy Sources for electricity generation has increased worldwide and solar PV technology is found to be a most promising alternative amongst the renewable energy technology. Solar energy is one of the most promising renewable energy sources. Solar cell has non-linear characteristics, since the output power of solar PV is a function of the intensity of the light falling on it and atmospheric temperature. Maximum Power Point Tracking (MPPT) controllers are introduced in solar PV system for maximum power extraction under all weather conditions. In this paper, comparative study of Perturb and Observe (P&O) and Look-Up MPPT based stand alone solar PV system is presented. The performance of the selected algorithms are compared and analyzed in terms of tracking performance such as tracking speed, oscillation at steady state and response under drastic changes in weather. Solar PV system is developed and simulated in MATLAB/Simulink with the P&O and LUT MPPT.
LED Drivers: The Role of the Rectifier on Flicker Immunity in ELV DC Environment

Within dc operated networks, the ac-dc conversion stage in various appliances is not needed anymore and may be excluded from the design, thus increasing overall efficiency. Previous research showed that removing the diode bridge rectifier from the LED driver design can sometimes worsen and sometimes enhance the overall immunity of the LED lamp to supply voltage distortion in terms of produced luminous flicker (flicker immunity). This paper aims to explain this behavior by performing simulations of the analyzed drivers. It is found that: firstly, the voltage reference inside the driver integrated circuit is not affected by the voltage perturbations; secondly, the removal of the rectifier will not worsen the flicker immunity if the driver is properly loaded and the common mode rejection ratio is not too high in case high side current sensing is used; thirdly, the size of the smoothing capacitor does not affect the flicker immunity when dc supply is used.
Realization of High Speed Low Power MCC Adder using Dynamic CMOS Transistors

Using multioutput domino CMOS logic, a cost effective implementation of Manchester carry chain (MCC) adder for 8-bit is designed in this paper. From this adder carries are generated parallelly employing two main carry chains of 4-bit. The suggested 8-bit adder module comprise confined length of carry chain. As a result of this ability, it is applied to realize broader adders and as well it guides to betterments in functioning rate equated to the related adders established upon the classical 4-bit MCC adder module.
An Improved Battery Charger for Electric Vehicle with High Power Factor

The incorporation of active power factor correction (PFC) converter reshapes the line current proportional to the input voltage and reduces the line current harmonics to the recommended IEC 61000-3-2 power quality (PQ) standard for the electric vehicle (EV) battery charger. However, modern vehicle charger with incorporated PFC, incurs additional high conduction loss owing to the use of rectification diode at the input end of the charger. This study discusses a simplified bridgeless (BL) topology for EV battery charger, depending upon the buck-boost configuration, which reduces the conduction loss, considerably, due to reduced number of semiconductor components conducting over one switching cycle during charging operation. The proposed bridgeless converter precedes a flyback converter to manage the charging of 48V/100Ah battery throughout the constant current (CC)/ constant voltage (CV) profile as well as built-in PFC capability at the mains side is inherited. An 850W prototype is designed and developed to support the enhanced performance of the battery charger by reconstructing the line current waveform and significantly reducing the input harmonics distortion to the recommended IEC 61000-3-2 standard.