Miracle-dz/UniFAR-FTUs huggingface dataset:
Outage Performance for Satellite-Assisted Cooperative NOMA Systems With Coordinated Direct and Relay Transmission

In this letter, the outage performance of a satellite-assisted cooperative non-orthogonal multiple access (NOMA) system is studied, where a terrestrial source communicates with one terrestrial destination directly while the other terrestrial destination is assisted by a regenerative satellite. We consider the satellite channels and the terrestrial channels undergo shadowed-Rician fading and Nakagami- $m$ fading, respectively. Based on this, we derive the exact closed-form expressions for the outage probabilities. In addition, the asymptotic expressions at high signal-to-noise ratio are provided to gain further insights. Simulation results validate the accuracy of the analytical results and show the superiority over other conventional schemes.
Experimental Results on Customer Reviews Using Lexicon-Based Word Polarity Identification Method

Determining the polarities of words in a given context has been in existence since the inception of computational linguistics, text mining, and sentiment analysis. Due to its fundamental role in determining the overall semantic orientation of natural language expressions, it is considered one of the most challenging issues facing these areas of research. This paper introduces a new implementation of the lexicon-based word polarity identification method on several customer reviews datasets. Herein, we use a variation of a lexicon-based word polarity identification method that operates by computing the semantic relatedness between the context expansion set of the target word and a synonym expansion set comprising the synonyms of all words surrounding the target word within the original text fragment. The polarity of the target word is determined as that for which the semantic relatedness between these two meaningful sets is the highest. Unlike most existing lexicon-based multi-polarity word identification methods, the used method is not based on estimating pairwise relatedness at term-level, but instead, it is based on measuring semantic relatedness at the fragment-level. This enables the exploration and capture of a higher degree of semantic and sentimental information, and is more consistent with people’ understanding through the consideration of the larger context in which the word appears. Its performance can be further improved by incorporating an initial step in which the relative negation scope of words in the given text fragment is managed while determining their sentiment orientation. The implementation results demonstrate that the used variation of the lexicon-based word polarity identification method performs favourably against compared methods, as evaluated on numerous benchmark datasets through stand-alone and end-to-end evaluation models.
Pathogen and its biological characteristics of the marigold leaf spot

The morphology and biological characteristics of the pathogen of marigold leaf spot was studied. The results indicated that the pathogen of marigold leaf spot was Alternaria tenuissima.The optimum growth condition of the pathogen were 25 ℃,pH 6.04,RH above 98 % respectively.Under such conditions,the pathogens grew quickly, the sporulation quantity was large and the spore germination rate was high.
IEEE 802.11be: Throughput and Reliability Enhancements for Next Generation WI-FI Networks

The IEEE 802.11be Task Group (TG) was created in May 2019 to develop the Extremely High-Throughput (EHT) 802.11be amendment for Wireless Local Area Networks (WLANs). This paper analyses the throughput, capacity and reliability improvements due to two candidate technologies forecasted in the Project Authorization Request (PAR): the increase of maximum number of spatial streams from 8 to 16 and introduction of Hybrid Automatic Repeat Request (HARQ) retransmission protocols [1]. The simulation results, validated using a first-order approach, for single-user multiple-input multiple output (SU-MIMO) with transmit beamforming (TxBF), downlink (DL) and uplink (UL) multi-user MIMO (MU-MIMO) technologies show expressive gains on the throughput and reliability due to the implementation of Chase combining HARQ in systems with 16 antenna ports in the 802.11ax/be physical layer (PHY).
Continual Human Value Analysis in Software Development: A Goal Model Based Approach

Software failures that demonstrate violations of human values can result in financial losses, reputation damages and social implications. Therefore, integrating human values into software is vital to satisfy stakeholder needs. However, developing methodological approaches that allow systematic integration of human values throughout the software development life cycle is an open challenge. This paper proposes the Continual Value(s) Assessment (CVA) framework that uses extended goal and feature modeling techniques to support systematic integration, tracing and evaluation of human values in software systems. The CVA framework prescribes (i) brainstorming of value implications of system features based on conventional system artefacts and (ii) the expansion of the existing set of system features to better serve stakeholder values expectations. In a pilot study, we use an emergency alarm system for the elderly to demonstrate the feasibility of the framework. We further discuss the challenges we faced while applying the framework and present the lessons learned from the pilot study.
Inband Full-Duplex D2D Communications Underlaying Uplink Networks with Mutual SIC NOMA

This paper studies the combination of full-duplex (FD) and half-duplex (HD) device-to-device (D2D) communications while underlaying a cellular system. Non-orthogonal multiple access (NOMA) is used to manage the interference between devices and cellular users using mutual successive interference cancellation (SIC) and to boost the performance of D2D underlay systems, which are mainly interference-limited. For this purpose, we derive the conditions allowing for the application of mutual SIC in FD-D2D and HD-D2D systems. We compare the performance of the proposed strategy against state-of-the-art, where SIC is not applied between D2D devices and cellular users. The results show that important gains can be achieved by using NOMA in this context and highlight the importance of self-interference (SI) cancellation factors for determining the best transmission mode.
Beyond Fresh Update: Packet Management for Real-Time Feedback Control

In real-time feedback control systems, the freshness of the packet is crucial to control performance, where packet management is vital to keep data fresh. Recently, age of information (AOI) has been used to measure the freshness of the update information, where minimizing AOI becomes popular in system designs. In this paper, we find that minimizing AOI is not always equivalent to maximizing the control performance. In particular, we define a metric, called the age of stale information (AOSI), to link the instability of the control system to AOI. By minimizing AOSI, we can maximize the control performance, and also reduce the communication cost.
PPO-CPQ: A Privacy-Preserving Optimization of Clinical Pathway Query for E-Healthcare Systems

With the help of patients’ health data, e-healthcare providers can offer reliable data services for better medical treatment. For example, the clinical pathway provides optimal detailed guidance for the clinical treatment. However, the e-healthcare providers are incompetent with the huge volumes of e-healthcare data, and a popular and feasible solution is used to outsource the medical data to powerful cloud servers (CSs). Because the medical data are very sensitive yet the outsourced servers are not fully trusted, the straightforward execution of clinical pathway query service will inevitably bring huge privacy risks to patients’ data. Apart from the privacy issues, the efficiency issues also need to be taken into consideration, such as the communication overhead and computational cost between servers and providers. Considering the above issues, this article proposes a privacy-preserving optimization of clinical pathway query scheme (PPO-CPQ) to achieve the secure clinical pathway query under e-healthcare CSs without revealing neither the private information of patients, such as name, gender, age, and physical index, nor the sensitive information of hospitals, such as treatment, medication, and expense. In our proposed scheme, it first designs secure and privacy-preserving several subprotocols, such as privacy-preserving comparison, privacy-preserving clinical comparison, privacy-preserving stage selection, and privacy-preserving stage update protocol, to ensure privacy in the e-healthcare system, then it adopts the greedy algorithm in a secure manner to perform the query and the min-heap technology to improve efficiency. The experimental result shows that our scheme is practical and efficient in terms of computational cost and communication overhead.
Late Breaking Results: Automatic Adaptive MOM Capacitor Cell Generation for Analog and Mixed-Signal Layout Design

This paper introduces the first problem formulation in the literature for automatic MOM capacitor cell generation with adaptive capacitance. Given an expected capacitance value and available metal layers, the proposed capacitor cell generation method can produce a compact MOM capacitor cell with minimized area and matched capacitance. Compared with MOM capacitor cells with non-adaptive capacitance in the previous work, the experimental results show that the proposed adaptive MOM capacitor cell generation method can reduce 25% chip area and 20% power consumption of the capacitor network in successive-approximation-register analog-to-digital converters (SAR ADC).
Indoor Localization with Wi-Fi Fine Timing Measurements Through Range Filtering and Fingerprinting Methods

Wi-Fi technology has been thoroughly studied for indoor localization. This is mainly due to the existing infrastructure inside buildings for wireless connectivity and the uptake of mobile devices where Wi-Fi location-dependent measurements, e.g., timing and signal strength readings, are readily available to determine the user location. To enhance the accuracy of Wi-Fi solutions, a two-way ranging approach was recently introduced into the IEEE 802.11 standard for the provision of Fine Timing Measurements (FTM). Such measurements enable a more reliable estimation of the distance between FTM-capable Wi-Fi access points and user-carried devices; thus, promising to deliver meter-level location accuracy. In this work, we propose two novel solutions that leverage FTM and follow different approaches, which have not been investigated in the literature. The first solution is based on an Unscented Kalman Filter (UKF) algorithm to process FTM ranging measurements, while the second solution relies on an FTM fingerprinting method. Experimental results using real-life data collected in a typical office environment demonstrate the effectiveness of both solutions, while the FTM fingerprinting approach demonstrated 1.12m and 2.13m localization errors for the 67-th and 95-th percentiles, respectively. This is a two to three times improvement over the traditional Wi-Fi signal strength fingerprinting approach and the UKF ranging algorithm.
High Power Efficiency and Dynamic Range Analog Photonic Link with Suppressed Dispersion-Induced Power Fading

An analog photonic link (APL) based on a dual-polarization dual-parallel Mach–Zehnder modulator (DP-DPMZM) is proposed and experimentally demonstrated. The proposed APL can suppress the nonlinearity of modulator, compensate the power fading induced by dispersion (PFID), and improve the power efficiency of link, leading to large dynamic range. The PFID and the nonlinearity are suppressed by adjusting the phase of optical carrier (OC) and polarization controller (PC), respectively. In addition, by optimizing the optical carrier to sideband ratio (OCSR) in the DP-DPMZM, the output RF power and the power efficiency of link can be significantly improved while the total optical power received by the photodetector (PD) remains constant. An experiments are performed to demonstrate the feasibility of the APL. The results show that an spurious free dynamic range (SFDR) of 103.2 dB·Hz4/5 for 13.73 GHz is achieved after compensating PFID and nonlinearity, which is 32 dB higher than that of a conventional double sideband (DSB) assisted APL. After OCSR optimizing, the output RF power achieves 13-dB improvement, and the SFDR is further raised to 114.1 dB·Hz4/5.
Via-based Redistribution Layer Routing for InFO Packages with Irregular Pad Structures

The integrated fan-out (InFO) wafer-level chip-scale package is introduced for modern system-in-package designs with larger I/O counts and higher interconnection density. A redistribution layer (RDL) in an InFO package is an extra metal layer for inter-chip connections. To achieve flexible and compact inter-chip connections, the RDL routing problem for InFO packages has become a crucial problem for modern electronic designs. In advanced high-density InFO packages, multiple RDLs with flexible vias are often adopted. On the other hand, to integrate chips of different technology nodes into one package, irregular pad structures need to be considered. To our best knowledge, however, there is no published work for RDL routing considering flexible vias or irregular pad structures. In this paper, we present the first work to handle the routing problem with pre-assigned pad pairs (i.e., the hardest pre-assignment routing problem) on the via-based multi-chip multi-layer InFO package with irregular pad structures. We first propose a layer assignment method based on a weighted maximum planar subset of chords algorithm to concurrently route as many inter-chip nets as possible. We then propose an octagonal tile model with a layout partitioning method to tackle increasingly popular irregular structures. Finally, we develop an efficient linear-programming-based layout optimization algorithm to find solutions with high-quality wirelength and via arrangements. Experimental results demonstrate the effectiveness and robustness of our algorithm.
A Study of the Spatial Auto-Correlation of Memory-Based Physical Unclonable Functions

In this work, we examine the spatial auto-correlation exhibited in the responses of memory-based Physical Unclonable Functions (PUFs). In particular, we examine the responses of an SRAM PUF, a DRAM decay-based PUF, and a disturbance-based Flash PUF. For the evaluation, we use three different metrics that have already been employed in the relevant literature for measuring the spatial correlation of other PUF responses. Our results prove that the examined PUF responses exhibit little, if any, spatial auto-correlation. Thus, these PUFs can be considered as security mechanisms of high entropy, which can be utilised to enhance the security of the Internet of Things (IoT).
A Generative Modelling Technique for 3D Reconstruction from a Single 2D Image

3D Object Reconstruction is the task of predicting the 3D model of an object given a set of 2D images. In this paper, we propose an approach to solving this problem, given a single 2D image. We attempt to make use of several deep learning techniques. Our model consists of two parts. The first part generates multiple images having different viewpoints. We have included this part because reconstructing 3D object directly from a single 2D image is quite difficult, but the same task would be a lot easier given multiple images which capture different views of that same object. Also, predicting an image having a different viewpoint is much easier than predicting the whole 3D object, given an input image. The second part uses a network consisting of an Encoder, a Decoder (or Generator), and a Discriminator to predict the complete 3D voxel grid of the object. In this way, we achieve significant improvements in the results as compared to the existing techniques.
Dual-Polarized Generalized Spatial Modulation for Wireless Terabit System

In this paper, we address multiple-input multiple-output (MIMO) communication technique based on generalized spatial modulation (GSM) and dual-polarized (DP) antennas in sub-TeraHertz (sub-THz) bands to improve the Spectral Efficiency (SE) and to reduce the spatial correlation effect, and the space occupancy. The proposed system adds the polarization dimension to the conventional GSM scheme and enhance the SE. Moreover, the joint Maximum Likelihood (ML) detector and a Modified Ordered Block Minimum Mean-Squared Error (MOB-MMSE) detector algorithm is proposed to detect jointly the complex symbols and the virtual bits conveyed by the activated polarization and the transmit antenna combination index. MOB-MMSE can achieve near-ML performance with low complexity. The performance of DP-GSM system over (un)correlated Rayleigh/Rician fading and sub-THz channels has been studied and the results show that DP-GSM system is robust against channel deficiency such as Rician fading and spatial correlation. Moreover, the Dual polarized Spatial Multiplexing (DP-SMX) and the Uni-Polarized GSM (UP-GSM) are compared with the DP-GSM system. The results reveal that DP-GSM with low order modulation schemes as QPSK outperforms the DP-SMX at high spatial correlations, and thus it is a promising candidate for ultra-high wireless data rates communication in sub-THz band.
Variable Length Coding for Asynchronous Communication

We consider a problem of asynchronous communication over a discrete memoryless channel (DMC). A transmitter seeks to communicate <inline-formula> <tex-math notation="LaTeX">$B$ </tex-math></inline-formula> bits of information to a receiver at a random time <inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>. For a general distribution of <inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>, we propose an asymptotically error-free variable length coding scheme that adapts the codeword length and distribution based on the arrival probabilities in a slot. For a simple class of L-step arrival distributions, we characterize the capacity of the DMC, and also show that the variable length coding scheme achieves higher rates and lower cost of communication in comparison with the fixed length coding scheme studied in prior works. Using numerical work, we illustrate our results for a binary symmetric channel in a number of interesting scenarios.
PIM-Prune: Fine-Grain DCNN Pruning for Crossbar-Based Process-In-Memory Architecture

Deep Convolution Neural network (DCNN) pruning is an efficient way to reduce the resource and power consumption in a DCNN accelerator. Exploiting the sparsity in the weight matrices of DCNNs, however, is nontrivial if we deploy these DC-NNs in a crossbar-based Process-In-Memory (PIM) architecture, because of the crossbar structure. Structural pruning-exploiting a coarse-grained sparsity, such as filter/channel-level pruning-can result in a compressed weight matrix that fits the crossbar structure. However, this pruning method inevitably degrades the model accuracy. To solve this problem, in this paper, we propose PIM-PRUNE to exploit the finer-grained sparsity in PIM-architecture, and the resulting compressed weight matrices can significantly reduce the demand of crossbars with negligible accuracy loss.Further, we explore the design space of the crossbar, such as the crossbar size and aspect-ratio, from a new point-of-view of resource-oriented pruning. We find a trade-off existing between the pruning algorithm and the hardware overhead: a PIM with smaller crossbars is more friendly for pruning methods; however, the resulting peripheral circuit cause higher power consumption. Given a specific DCNN, we can suggest a sweet-spot of crossbar design to the optimal overall energy efficiency. Experimental results show that the proposed pruning method applied on Resnet18 can achieve up to 24.85× and 3.56× higher compression rate of occupied crossbars on CifarlO and Imagenet, respectively; while the accuracy loss is negligible, which is 4.56× and 1.99× better than the state-of-art methods.
A 506Gbit/s Polar Successive Cancellation List Decoder with CRC

Polar codes have recently attracted significant attention due to their excellent error-correction capabilities. However, efficient decoding of Polar codes for high throughput is very challenging. Beyond 5G, data rates towards 1Tbit/s are expected. Low complexity decoding algorithms like Successive Cancellation (SC) decoding enable such high throughput but suffer on errorcorrection performance. Polar Successive Cancellation List (SCL) decoders, with and without Cyclic Redundancy Check (CRC), exhibit a much better error-correction but imply higher implementation cost. In this paper we in-depth investigate and quantify various trade-offs of these decoding algorithms with respect to error-correction capability and implementation costs in terms of area, throughput and energy efficiency in a 28nm CMOS FD-SOI technology. We present a framework that automatically generates decoder architectures for throughputs beyond 100Gbit/s. This framework includes various architectural optimizations for SCL decoders that go beyond State-of-the-Art. We demonstrate a 506Gbit/s SCL decoder with CRC that was generated by this framework.
Online Ranking of Physicians with Perishable Resources

For the online healthcare platform, it is essential to recommend a list of physicians to arrived patients dynamically, in order to satisfy patients’ varied demands, improve the overall matching degree between patients and physicians as well as the resource allocation efficiency, since each physician only has limited registration capacity. In this paper we construct a general model to describe this dynamic ranking problem with patients’ rank-based choice behavior and limited resources. Under the framework of Markov Decision Process(MDP), the dynamic problem can be decomposed into a series of static problems as long as the marginal value of each physician’s registration resource can be approximated. To deal with the problem that at the cold-start stage the platform does not have available data to capture patients rank-based choice behavior specifically, we design a model-free LP-based method which can efficiently approximate the marginal value without requiring patients’ choice models as the input. We conduct a case study based on the data collected from the online healthcare platform to show how to apply this general framework in a real application and verify the capability of our methods.
A metaheuristic approach to optimize maintenance productivity of Indian railway coach and bogie

Indian Railways being one of the largest functioning units of India employs a huge amount of manual unorganized labor. Maintenance of railway coaches and bogies is provided from part of this labor. It has always been a great challenge to find an optimal operating scenario for maximized productivity. In this work, we aimed to model and maximize maintenance productivity of Indian Railway coach and bogie . Taking into consideration the volatility of the circumstances and uncorrelated behavior of different human factors affecting productivity, to obtain the best scenario five of the most critical human factors were identified that are expected to affect the maintenance of the coaches and bogies most. Cobb-Douglas production function was used to model maintenance productivity with the chosen human factors. The main goal after designing the model for productivity is to maximize it. To get the optimal productivity Differential Evolution algorithm is used. Finally, the Cuckoo search algorithm is applied to validate the results.
Jitter Reduction of Mode-Locked Hybrid Silicon Laser With Intra Cavity Filter

We study the influence of the intra-cavity ring on dynamics, phase noise and timing jitter of a long-ring-cavity colliding pulse mode-locked laser using a delay differential equation (DDE) model. The results of dynamic show that the intra-cavity filter can suppress harmonics of 2 GHz cavity. We also find a reduction of phase noise and timing jitter compared to the fundamental 20 GHz ring laser, which is in good agreement with experimental result.