Miracle-dz/UniFAR-FTUs huggingface dataset:
Channel Estimation Algorithm Based on the Block Sparsity in Massive MIMO-OFDM Systems

The channel matrix of massive MIMO-OFDM systems is sparse in the delay domain. The channel estimation based on compressed sensing uses the sparsity of the channel matrix to improve the channel estimation accuracy and reduce the pilot overhead. A channel estimation algorithm based on block compressive sampling match pursuit (B-CoSaMP) is proposed. The proposed algorithm combines the spatial correlation of the MIMO channel caused by multi-antenna propagation with the close antenna spacing at the base station, and generates an equivalent channel impulse response based on block sparsity to improve the channel estimation performance. The simulation results show that the proposed algorithm has low bit error rate and small normalized mean square error (NMSE), which is suitable for channel estimation of massive MIMO-OFDM systems.
Matching of Business Data in a Generic Business Process Warehousing

Quick response times, ad-hoc queries, and reduction the load on existing productive systems are, among others, the most important reasons for using enterprise data warehouse systems (DWH). The fixed-structured multi-dimensional data model such as Star schema allows OLAP functionalities to be pre-programmed and executed by an OLAP engine without the need to any programming activities in runtime. In opposite, structures of business processes are dynamic. Business process analysts focus on the analysis of changing of processes over the time and their behavior. Therefore, it is not sufficient using traditional OLAP Engine of DWH just to investigate information about aggregates key performance indicators related to business processes like total execution time or process cost. This paper presents a conceptual generic data model for matching business data of business objects in a standardized business processes.
Forensic Detection of JPEG Compressed Image

For the detection of JPEG compression (JC) forensics, this paper proposes the feature vector that extracted using the Hu invariant moment of the forged image. The defined seven dimensionality feature vector is trained in an SVM (Support Vector Machine) classifier for the JC detection (JCD) of the forged images. The performance of the proposed JCD is measured with several types of images: unaltered, JPEG compressed, JPEG double compressed and rotated, respectively. Subsequently, the AUC (Area Under Curve) results of the JC classification are 0.9 over on the trained SVM classifier. Thus, it confirmed that the grade evaluation of the proposed scheme is 'Excellent (A)'.
A Cloud-Based Solution for Testing Applications' Compatibility and Portability on Fragmented Android Platform

Testing is a vital activity in software development. The ISO/IEC has defined a standard for system and software quality models called ISO/IEC 25010:2011 to be a guideline and scope for testing any applications. Testing of mobile applications according to this standard, however, is more challenging than other types of software. The diversity of Android devices and various versions of Android operating system, for example, has created a large fragmentation of the Android platform. This fragmentation hinders testing of Android applications especially in relation to portability and compatibility. Existing solutions are either neglecting portability and compatibility issues or lack flexibility in fulfilling needs of the different organizations. We propose a cloud testing model to address the fragmentation of Android platform and provide automated application testing services on the actual devices. The model can be configured in the public, private or hybrid setups to suit individual organizations' needs and budget. A prototype was built based on the model. 10 Android testers used the prototype and the Android Emulator to perform mobile application testing. Results show that the model has the potential to manage the challenging portability and compatibility testing on the Android platform in a flexible and scalable manner.
Performance Enhancement of 3-D NAND Flash Featuring a Two-Step Dummy Wordline Program Waveform and Pair-Bitline Program Scheme

In this work, we report two performance enhancement schemes for single-gate vertical-channel (SGVC) 3-D NAND Flash. The first one features a programming (PGM) waveform where the bias of the dummy wordline (DWL) is raised in a two-step manner so that the resultant disturbance that the DWL and edge WL suffer is appreciably alleviated. The second scheme takes advantage of a unique behavior termed “self-boosting-enhanced-PGM” mechanism in the pair- bitline PGM method to deal with the slow PGM bits and achieve a much lower bit error rate as a consequence. By using these two approaches, the bit error rate after multilevel cell (MLC) operation can be substantially improved by 82%.
Investigating Single Channel Source Separation Using Non-Negative Matrix Factorization and Its Variants for Overlapping Speech Signal

A pre-processor to speech recognition, audio source separation may mitigate the problem of quality degradation of individual signal recognition in scenarios like cock-tail party environment. The same may be used for various other applications like audio forensics, speaker verification, instrument identification, hearing aids, etc. There are various techniques available for single channel audio source separation, but the technique based on Non-negative Matrix Factorization (NMF) is widely used. Several research studies have shown considerable performance improvement of signal separation using NMF on different mixture of audio signals like speech with noise, speech with music, speech with speech taken from different audio databases. In this paper, single channel source separation using Non-Negative Matrix Factorization and its variants for two-speaker mixed signal is investigated using same speech database, the GRID speech corpus. The separation performances of phase-aware algorithms are compared with phase-unaware approaches based on NMF and its variants. The quality of separated speech was judged by varying parameters such as number of bases and analysis window size.
Study of Acoustic Correlates Between Prosodic Features and Emotions in Marathi Language

For designing intelligible and natural Text-to-Speech systems (TTS) researchers all over the world are studying relation between prosodic features and emotions in various languages. The objective of this research is to study acoustic correlates between prosodic features including duration, F0 and intensity for vowels and various emotions in Marathi language. Also, these prosodic features are analyzed for vowels in words non-final and final syllables. Pause durations occurring between words for various emotions are also studied. Marathi sentences spoken by a female speaker are recorded in five emotion styles: anger, fear, happy, sadness and neutral. For every sentence vowel mean duration, mean F0 and mean intensity are calculated. Long pauses, mid-pauses and short pauses for all the five emotions are analyzed. The ANOVA analysis for F0 and intensity with p<0.001 indicate that these parameters can be used as cue for various emotion styles for Marathi language. Short vowel duration and large number of short pauses are observed for angry emotion whereas long vowel duration and short, mid and long pauses are observed equally for happy emotion. Above observations related to prosodic features and pauses would be useful to model Marathi TTS system.
Novel Schmitt Trigger and Square-Wave Generator Using Single Current Amplifier

This paper presents an important missing building block for mixed-mode signal processing: a Schmitt trigger circuit based on the current amplifier. Schmitt trigger is used extensively in both the analogue and digital areas. The transfer characteristics of the proposed design are independent on the supply voltage. Unlike Schmitt triggers incorporating other types of amplifiers, the proposed design is totally active. It does not require passive resistors and hence it shall be more attractive for VLSI implementation. The proposed circuit is utilized to implement a novel current mode square-wave oscillator using a single current amplifier that provides differential current signals. The output amplitude can be controlled without additional circuitry. Current generators are particularly essential for bio-impedance measurement. Comparison with their counterparts using the operational amplifier, transconductance operational amplifier, transresistance operational amplifier, and current conveyor demonstrates several advantageous features of the proposed circuits. The experimental results obtained from primary prototypes fabricated using standard 150 nm CMOS process are provided. It is shown that the proposed Schmitt trigger and the square wave generator nominally consume $8~\mu \text{W}$ and $11~\mu \text{W}$ while working in the MHz range.
Intelligent Adaptive Data Transmission Strategy for CRNs

Due to the time-varying characteristics of the wireless channels in cognitive radio networks, how to set the length of data packets for transmission is a challenge. It’s because that the packet length is too large, which may cause link congestion and transmission failure, and the packet length is too small to make full use of the spectrum resources. To solve this problem, we propose an adaptive transmission strategy based on Multi Armed Bandit. We assume the packet length as the arm, and the transmitter as the player. The goal of our strategy is to improve data transmission efficiency as far as possible by choosing the suitable arm with the change of channel quality. Furthermore, in order to improve the convergence speed, we innovatively propose using the belief factor to balance the exploitation and exploration among arms, so as to avoid falling into local optimum. The experiments show that our strategy can select the optimal arm when the channel quality changes dynamically. It means that the packet length is intelligent adaptive in varying environment of cognitive radio networks. Compared with other traditional algorithms, our strategy has better throughput.
Improvement of Similarity Coefficients Based on Item Rating and Item Genre

Item-based collaborative filtering recommendation system has been widely used in many fields, which generates recommendations based on similarity between items. However, the conventional similarity calculation may produce inaccurate results because of data sparsity. To alleviate this problem, this paper proposes a new method of similarity calculation based on item rating and genre. Firstly, similarity calculation based on item rating are proposed, which reduces similarity between items with fewer co-rating users. Genre information is an inherent attribute of an item which could not be changed by user behavior. It reflects the common characteristics among items, then item similarity based on the item’s dependency on genre are calculated. Finally, a trade-off between rating and genre similarity are proposed to calaulate the similarity between items. Experimental results show that the proposed method can alleviate the issue of inaccurate similarity caused by sparse data and improve the recommendation quality.
Design and Implementation of a Cost-Efficient Smart Home System with Raspberry Pi and Cloud Services

With the advent of the Internet of Things (IoT), a large number of devices are being connected to each other every day. Each connectivity opens the door to new possibilities to make a person's life easier and convenient. A smart home is one such area impacted by IoT which greatly improves a person's life by helping them create a secure environment for his family and carry out his day-to-day activities with ease. Focusing primarily in the context of Nepal where available smart systems are either expensive or lack basic features, this paper essentially deals with the design and implementation of a cost-efficient smart home system focusing on remote surveillance, monitoring different aspects (movement detections, surveillance and temperature and humidity) of a home with notification alerts. Furthermore, the system also aims to reduce electricity usage and minimize energy consumption by helping a person automate their everyday tasks such as turning on/off lights, thermostats, etc. by detecting their presence. Raspberry Pi is the heart of the home system managing all of these services. In addition, Amazon Cloud Services, Simple Email Service (SES) and Simple Notification Service (SNS) are used for notifying users/home-owners. The product could further be regarded as a prototype and additional features could be added on top of it to create one's own version of “smart home”.
Analysis of Contention-Based SCMA in mMTC Networks

Massive Machine Type Communication (mMTC) is one of the three new applications of fifth-generation (5G) networks. Users in mMTC applications have different patterns of transmission and requirements than traditional LTE applications; they are massively deployed and transmit small packets of data sporadically. Grant-based access scheme is inefficient to satisfy the mMTC requirements; therefore, grant-free contention-based access (CBA) is appointed as a promising solution to this problem. In this paper, we analyze the performance of contention-based sparse code multiple access (SCMA) concerning the probability of success of transmission and the area spectral efficiency. We derive closed-form expressions for both performance metrics and validate them with numerical simulations. Furthermore, we compare the results with an OFDMA contention-based approach.
Suppression of chaotic behaviors in a complex biological system by disturbance observer-based derivative-integral terminal sliding mode

Coronary artery systems are a kind of complex biological systems. Their chaotic phenomena can lead to serious health problems and illness development. From the perspective of engineering, this paper investigates the chaos suppression problem. At first, nonlinear dynamics of coronary artery systems are presented. To suppress the chaotic phenomena, the method of derivative-integral terminal sliding mode control is adopted. Since coronary artery systems suffer from uncertainties, the technique of disturbance observer is taken into consideration. The stability of such a control system that integrates the derivative-integral terminal sliding mode controller and the disturbance observer is proven in the sense of Lyapunov. To verify the feasibility and effectiveness of the proposed strategy, simulation results are illustrated in comparison with a benchmark.
Optimal Control of Ascent Trajectory for Launch Vehicles: A Convex Approach

This paper presents an online ascent trajectory optimization algorithm based on optimal control and convex optimization without accurate initial guesses. Due to the high complexity of space systems, exceptional cases such as engine failures may happen during the flight. In these cases, the dynamical model greatly changes and the nominal trajectory is infeasible. Thus, online trajectory optimization and replan should be considered when accurate initial guesses cannot be given. In this paper, the ascent trajectory optimization problem of launch vehicles is formulated as a Hamilton two-point boundary value problem (TPBVP) according to the optimal control theory. The control vector is expressed as a function of costate variables and the terminal condition is given according to the orbital constraint of the launch mission. In order to solve the TPBVP rapidly and accurately without accurate initial guesses, a convex approach is presented. Firstly, the flip-Radau pseudospectral method is applied to convert the continuous-time TPBVP into a finite-dimensional equality constraint. Then, successive linearization is applied to formulate the problem as a series of iteratively solved second-order cone programming (SOCP) subproblems. Considering the accuracy and robustness of the algorithm, trust-region and relaxation strategy are applied. The convex trajectory optimization can be solved by Interior Point Method (IPM) automatically. Simulation results in the case of thrust loss are presented to show the accuracy, efficiency and robustness of the algorithm.
Transfer Function Optimization for Band-Pass and Band-Stop Filters

In this study, optimization of transfer functions of band-pass and band-stop filters are performed by using honey bee mating optimization and firefly optimization algorithms. In the conventional methods, the transfer functions of band-pass, band-stop and high-pass filters are obtained by means of frequency transformations using transfer functions of low pass filters. During this process, firstly, the transfer function approaching the ideal low-pass filter characteristic is obtained. Then with frequency conversion and frequency translation process; the transfer function is brought to the desired type and the desired frequency region. In this study, it is shown that transfer functions of band-pass and band-stop filters can be obtained by using evolutionary algorithms without frequency conversion.
OFDM-Subcarrier Power Modulation With Two Dimensional Signal Constellations

An original modulation technique has been recently proposed for wireless communication systems known as OFDM- SPM (OFDM with Subcarrier Power Modulation). This technique utilizes a characteristic of the subcarriers of the OFDM block to carry extra data, this is the power of the subcarriers. Where the power level of each subcarrier conveys additional data bits. Presented here, the concept of OFDM-SPM is extended to the case of using two-dimensional signal constellations that consist of both in-phase and quadrature components such as QPSK Symbol modulation. Its performance is investigated over an AWGN (additive white Gaussian noise) channel. The adoption of this proposed scheme in future modulation techniques is studied by presenting OFDM-SPM with QPSK as a case of OFDM-SPM with higher order modulation schemes. The performance of the scheme in terms of the metrics of throughput and bit error rate (BER) of the system are discussed and analyzed. The results show that OFDM-SPM with QPSK vastly improves spectral efficiency especially when comparing with other techniques such as OFDM-SEM and OFDM-SNM which add a third data carrying dimension. The results show that OFDM-SPM, unlike many other proposed schemes, can be used with higher order modulation schemes to provide the perceived gains consistently regardless of the modulation scheme order. Specifically, it is found out that the spectral efficiency can be doubled compared to conventional benchmark schemes available in the literature at the expense of a slight degradation in the BER.
Towards an Influence Model for Cybersecurity and Information Warfare

Interactions between multiple individuals and organizations are integral to the operation of society at all levels. However, the same conduits that these critical activities occur over can also be used for nefarious purposes. In this article, a model for identifying and exploring influence transactions is presented. A classification scheme for the characterization of the influence events, consisting of one or more influence transactions, is also proposed. Examples are provided of the use of these two systems and their efficacy is qualitatively assessed.
Position Control of Flexible Manipulator using PSO-tuned PID Controller

Flexible manipulators have been tried to use due to their advantages such as the requirement of low drive power because of low weight, low power consumption, higher load capacity, high-speed operation, small actuators and low production costs. These advantages of flexible manipulators are due to their structural flexibility in joints or links. However, the flexibility causes vibrations in the end effector both on the move and after the force that causes the movement is removed. It takes some time to dampen these vibrations. In this study, particle swarm optimization (PSO)-tuned PID controller is used to control the position of the flexible manipulator directly and indirectly to reduce the vibration of the manipulator. The fitness function selected for the PSO includes parameters related to both the desired time response and vibration. Thus, the optimal PID parameters found with PSO control the position of the flexible manipulator and ensure low vibration.
mdspan in C++: A Case Study in the Integration of Performance Portable Features into International Language Standards

Multi-dimensional arrays are ubiquitous in high-performance computing (HPC), but their absence from the C++ language standard is a long-standing and well-known limitation of their use for HPC. This paper describes the design and implementation of mdspan, a proposed C++ standard multidimensional array view (planned for inclusion in C++23). The proposal is largely inspired by work done in the Kokkos project— a C++ performance-portable programming model de- ployed by numerous HPC institutions to prepare their code base for exascale-class supercomputing systems. This paper describes the final design of mdspan af- ter a five-year process to achieve consensus in the C++ community. In particular, we will lay out how the design addresses some of the core challenges of performance-portable programming, and how its cus- tomization points allow a seamless extension into areas not currently addressed by the C++ Standard but which are of critical importance in the heterogeneous computing world of today’s systems. Finally, we have provided a production-quality implementation of the proposal in its current form. This work includes several benchmarks of this implementation aimed at demon- strating the zero-overhead nature of the modern design.
Program Slicing Method of LLVM IR Based on Information-Flow Analysis

Program slicing is one of the important methods for program analysis and understanding, which has been widely used in the actual production and research. Currently there is an information flow analysis method that uses information flow relationships to define slices. The information-flow method can analyze intra-procedures precisely, but not inter-procedures. Therefore, the inter-procedural slicing technology based on information flow analysis needs further study. In order to further improve the information-flow analysis method, an inter-procedural slicing algorithm based on information-flow analysis is proposed in this paper. An information-flow slicer is implemented based on this algorithm, named as InfoSlicer. The object language of this paper is LLVM IR, which can better meet full development of the applications when compared with other front-end languages.
Modeling of Voltage-Controlled Spin–Orbit Torque MRAM for Multilevel Switching Application

Magnetic tunnel junction (MTJ) has emerged as a viable candidate for next-generation memory and logic applications. Manipulation of the magnetic and electric field can control the spin and charge state variables that are of utmost importance in spintronics devices. In this article, the modeling of voltage-controlled spin–orbit torque (VCSOT)-based magnetic random access memory (MRAM) is demonstrated. VCSOT MRAM is an ultrafast device owing to a magnetic switching time of 0.7 ns. It is more energy-efficient as compared to spin–orbit torque (SOT) MRAM. VCSOT MRAM has been exemplified for multilevel cell (MLC) application to enhance the memory integration density. Two-bit serial MLC (sMLC) and parallel MLC (pMLC) designs are proposed using VCSOT MRAM. These MLCs are more energy-efficient as compared to SOT-MLCs. Moreover, 2-bit sMLC and pMLC VCSOT-MRAM significantly reduce average write energy by 91.5% and 49.6%, respectively, as compared to SOT-based MLC. Performance metrics for these devices have been illustrated, which shows the negligible read disturbance and write error rates.