Miracle-dz/UniFAR-FTUs huggingface dataset:
Information leakage through passive timing attacks on RSA decryption system

The threat of timing attacks is especially serious when an attacker actively controls the input to a target program. Countermeasures are studied to deter such active attacks, but the attacker still has the chance to learn something about the concealed information by passively watching the running time of the target program. The risk of passive timing attacks can be measured by the mutual information between the concealed information and the running time. However, the computation of the mutual information is hardly possible except for toy examples. This study focuses on three algorithms for RSA decryption, derives formulas of the mutual information under several assumptions and approximations, and calculates the mutual information numerically for practical security parameters.
Graph Partition Based on Dimensionless Similarity and Its Application to Fault Diagnosis

In order to improve the efficiency of fault diagnosis, a novel granular computing algorithm is developed to reduce computational cost. It is realized by extracting and partitioning on the complete graphs, and in the process of graph generation, the dimensionless similarity method is proposed to overcome the influence of attributes with different dimensions. So, the algorithm is named graph partition based on dimensionless similarity (GPDS). Moreover, similarity threshold determination method based on frequency distribution histogram is proposed to reduce the dependency on the experiences of experts. Finally, different characteristic data are applied to verify the theories. The experimental results indicate that the compressed training samples can maintain the classification accuracy. Furthermore, the elapsed time can be obviously reduced. Therefore, the GPDS method can be used in fault diagnosis properly.
Mining Customer Satisfaction on B2B Online Platforms using Service Quality and Web Usage Metrics

In order to distinguish themselves from their competitors, software service providers constantly try to assess and improve customer satisfaction. However, measuring customer satisfaction in a continuous way is often time and cost intensive, or requires effort on the customer side. Especially in B2B contexts, a continuous assessment of customer satisfaction is difficult to achieve due to potential restrictions and complex provider-customer-end user setups. While concepts such as web usage mining enable software providers to get a deep understanding of how their products are used, its application to quantitatively measure customer satisfaction has not yet been studied in greater detail. For that reason, our study aims at combining existing knowledge on customer satisfaction, web usage mining, and B2B service characteristics to derive a model that enables an automated calculation of quantitative customer satisfaction scores. We apply web usage mining to validate these scores and to compare the usage behavior of satisfied and dissatisfied customers. This approach is based on domain-specific service quality and web usage metrics and is, therefore, suitable for continuous measurements without requiring active customer participation. The applicability of the model is validated by instantiating it in a real-world B2B online platform.
A 22nm 4Mb 8b-Precision ReRAM Computing-in-Memory Macro with 11.91 to 195.7TOPS/W for Tiny AI Edge Devices

Battery-powered tiny-AI edge devices require large-capacity nonvolatile compute-in-memory (nvCIM), with multibit input (IN), weight (W), and output (OUT) precision to support complex applications, high-energy efficiency (EF$_{{\mathrm {MAC}}})$, and short computing latency $(t_{{\mathrm {AC}}})$ for multiply-and-accumulate (MAC) operations. Due to the low read-disturbfree voltage of nonvolatile memory (NVM) devices and the large parasitic load on the bitline, most existing Mb-level nvCIM macros use a current-mode read scheme [1–5] and only achieve a low IN-W precision (binary to 4b).
Factors Influencing the Implementation of IT Governance in Public Universities

Information Technologies are the key assets within any public or private organization, these assets should be governed by a senior executive or a special body in the higher hierarchical level of the organization. Public universities need to create an IT governance body that allows direct, evaluate, monitor all the management process of the projects and services operations with TI dependence to improve the performance, generate the adequate information for the decision-making of the senior executives, and achieve the desired objectives within of the university. In reality, this does not happen on a day-to-day basis in many universities, because the decisions made by senior executives are empirical, without taking into account the appropriate information. The objective of the article is to collect and show the different factors that influence the correct implementation of an IT Governance model in universities. For the elaboration of the article, a literature review methodology was used, where different scientific articles from the last years were reviewed. As a result, 20 factors were found that influence the implementation of IT governance in public universities, which must be taken into account and receive special attention for the implementation of an IT governance framework.
Inphasing Signal Component Separation for an X-Band Outphasing Power Amplifier

This work investigates signal component separator design for an RF-input outphasing power amplifier (RFIO PA). In the RFIO architecture, the phase- and amplitude-modulated input signals to the outphasing power stage are realized using a nonlinear “inphasing” network, resulting in an outphasing system that operates on a single RF input. Previous RFIO work has demonstrated the feasibility of this approach, but the combined nonlinear effects of the inphasing and outphasing networks have resulted in overall poor linearity. In this work, we use a simplified transistor model to predict the inphasing network design requirements, and then compare three nonlinear components to synthesize the required transfer function. An $X$ -band monolithic microwave-integrated circuit (MMIC) in 150-nm GaN is used as the output stage, and its operation is characterized for hybrid inphasing networks based on three different technologies: diode-connected HEMT, p-i-n diode, and nonlinear GaN mesa resistor. The RFIO PA with mesa resistor inphasing network achieves a linearity-efficiency compromise with −27.9 dBc adjacent channel leakage ratio (ACLR) and 29% PAE at an average output power of 27.7 dBm for a 100-MHz long-term evolution (LTE) signal with 7.9 dB peak-to-average power ratio (PAPR) centered at 10 GHz.
30.4 A 1Tb 3b/Cell 3D-Flash Memory in a 170+ Word-Line-Layer Technology

This work demonstrates a novel 1Tb 3D Flash memory chip that has an area efficiency of 10.4Gb/mm2 in a 3b/cell technology. Using a circuit under array (CUA) design technique and over 170 word-line (WL) layers, the chip achieves 33% higher bit density than prior 3b/cell work [1], and better density than in 4b/cell technology [3]. This paper discusses the challenges advanced 3D Flash memories face: using over 100 WL layers results in large parasitic loads and decreases read/program speed, and its complicated operation increases test costs. On the other hand, as high bandwidth is also required, this chip supports a 2.0Gbps IO transfer rate, while maintaining signal integrity. This work introduces four new key technologies to address these difficulties. 1) Asynchronous independent plane read (AIPR), with a 4-plane architecture to improve system-level performance. 2) Enhanced sensing that enables faster read time $(t_{R})$. 3) IO-DCC (duty cycle correction) training for high-speed DDR operation. 4) A scan chain to improve test coverage and cost effectiveness.
Waveguide Integrated Magneto-Optical Isolators on Silicon Nitride Platforms

We report high-performance magneto-optical isolators and circulators on silicon nitride platforms for TM (TE) polarizations showing 32 dB(30 dB) isolation ratio, 2.3 dB(3 dB) insertion loss and -32 dB(-30 dB) minimum crosstalk. © 2020 The Author(s)
Time Series Load Forecasting using Multitask Deep Neural Network

This work presents a new framework based on multitasking with BiLSTM+dropout deep neural network for individual consumers’ load forecasting. The proposed framework quantifies the uncertainties of consumers’ load profiles in smart meter dataset. The hierarchical clustering algorithm is employed to group similar consumers based on consumption pattern. Furthermore, load profile pooling is carried out on each consumer group to increase the data diversity for addressing the overfitting issues. This framework is tested on 1031 randomly selected residential consumers’ of SGSC smart meter dataset, Australia and implemented through MATLAB platform. Compared to LSTM+dropout technique, the prediction accuracy of the proposed technique shows an improvement of 35.5% and 17.64% over RMSE and MAE respectively. In addition, in comparison to the pooling based LSTM technique, the enhancement in prediction accuracy is around 61.77% and 45.13% over RMSE and MAE respectively. The Experimental results show that the proposed model achieved high prediction accuracy by learning the shared features efficiently and account for stochastic environmental disturbances.
On the Effects of Channel Aging in D2D Two-Way Relaying with Space-Constrained Massive MIMO

This paper studies the spectral efficiency (SE) of a space-constrained multi-pair two-way massive multiple-input multiple-output (MIMO) decode-and-forward (DF) relay system with channel aging for device-to-device (D2D) communications in the Internet of Things (IoT) environments. Maximum ratio combininy-Maximum ratio transmission (MRC/MRT) processing is employed at the relay and imperfect channel estimation is assumed. With the consideration of the spatial correlation due to insufficiently spaced antennas, and the time correlation due to channel aging, we study the closed-form large-scale approximations of the SE performance. Our analytical studies and performance results demonstrate that a degree of both spatial correlation due to antenna proximity, and time correlation due to channel aging can be tolerated in the massive MIMO regime without significant performance degradation.
Comparative study of gated single crystal silicon and polysilicon field emitters

Both single crystal silicon and polysilicon are attractive emitter materials for displays using cold field emission. Although single crystal silicon has been under investigation for some time, by contrast, interest in polysilicon is more recent. Using state of the art fabrication techniques including high resolution electron beam lithography and plasma dry etch both single crystal silicon and polysilicon have been processed to fabricate sharp and uniform gated emitter arrays. We report in this article a comparative study of material aspects, processing, and emission properties of the two materials.
Power Sharing in an Islanded LV Distribution Network Fully Installed with PV-Battery Systems Based on Grid-Forming Control

The increasing penetration of renewables leads to the emergence of renewable-dominated low voltage (LV) distribution networks. Hybrid PV-battery systems owned by end users can be used to support islanded operations of such networks. In this paper, we argue that PV and batteries can be interfaced by a hybrid inverter to ensure the simultaneous implementation of MPPT and grid-forming control, whereby the power capacity from the DC side is extended. To that end, we propose a control strategy for the PV-battery interfaced converter based on matching control. The strategy consists of power sharing based on droop control in LV network and feed-forward power compensation for the DC-link capacitor. Simulations are based on the residential LV network scenario, and simulation results are provided to verify the feasibility of the proposed strategy.
Three-Phase Step-Up Multilevel Inverter With Self-Balanced Switched-Capacitor

This article presents a new three-phase multilevel inverter with boosting capability for low-voltage applications like electric vehicles and renewable energy sources. This inverter is fed by a single dc voltage source and each phase involves two low-voltage transistors, two high-voltage transistors, two diodes, and two capacitors. Except that the two high-voltage transistors withstand twice the dc input voltage, all other components are rated to the dc input voltage. With phase-disposition pulsewidth modulation, the two types of high- and low-voltage transistors operate in low and high switching frequencies, respectively. This is very beneficial for reducing switching losses and selecting semiconductor switches. The two capacitors are connected in parallel and series alternately with the dc source resulting in high ac output voltage with multiple levels, self-balanced capacitor voltages as well as low voltage ripples. The topology, operation principle, capacitors’ voltage ripples and power loss are analyzed in detail. Both simulation and experimental results are provided to demonstrate the feasibility of the proposed inverter.
Dual-Band Shared-Aperture High-Efficiency Reflectarray Antenna Based on Structure-Reuse Technique

A millimeter-wave dual-band shared-aperture high-efficiency reflectarray antenna (RA) based on the structure-reuse technique is proposed in this letter, which consists of two sets of elements with full 360° phase compensation ranges. The oblique dipole element excited by the substrate integrated waveguide (SIW) is employed for the lower frequency band. The equivalent metallic waveguide element with the unchanged periodic grid and transverse size is selected for the higher frequency band. To make full use of the radiating aperture and, then, improve the aperture efficiency of the dual-band RA, the SIW-fed dipole cells are used to replace a pair of symmetry walls of the metallic waveguide cell in the x-polarization direction. The measured gains of the proposed RA are 28.7 dBi with the aperture efficiency of 43.59% at 18 GHz and 35.8 dBi with the efficiency of 50.12% at 38 GHz. The simulated and measured results successfully validate the effectiveness of the proposed method in the design of a millimeter-wave dual-band shared-aperture RA.
Control of Solar PV System for Power Quality Improvement in AC Network and Islanded Operation

The harmonics currents drawn by the nonlinear loads distort the point of common coupling (PCC) voltages. It affects the performance of the solar PV system (SPVS) and other sensitive loads, connected at the same PCC. Moreover, it increases the line losses in the AC network. Hence, this paper presents an adaptive filter-based control algorithm for the SPVS to improve the power quality (PQ) in the AC network as par the IEEE standard 519 and to reduce its line losses. The presented adaptive filter algorithm effectively filters out the harmonics from the sensed voltages and currents and reduces the DC offset caused by the sensor circuitry. Moreover, in this paper, an adaptive DC-link control approach is presented to regulate the DC link voltage of the SPVS, which ensures that the modulation index remains less than 1. Hence, the harmonics currents injected by the SPVS at the PCC, are reduced. Moreover, the SPVS separates itself from the AC network to uphold the IEEE std. 1547, if any abnormality occurs in the AC network voltages. In this condition, it feeds power to the loads by changing its mode of operation to the islanded mode. Hence, the energy generated by the SPVS is effectively utilized and its payback period reduces. A Simulation study is carried out in various dynamics conditions to uphold the performance of the presented control algorithm.
Thermo‐kinetic analysis of reactions involved in the manufacture of o‐nitroaniline

Exothermic reaction processing must be concerned with potential consequences when heat released by the reaction exceeds that removed by the reactor coolant system, a situation known commonly as a runaway reaction. We have investigated a complicated reaction process in which two exotherms can occur—the process of making the desired product, o‐nitroaniline (o‐NA), from ammonia and o‐chloronitrobenzene (T Onset around 140°C), and the decomposition of the product, o‐NA (T Onset around 225°C). A severe industrial loss occurred in 1971 at a plant producing o‐nitroaniline, an incident that has been the subject of several AIChE loss prevention presentations and papers. In this article, we take a closer look at the chemistry involved, and the ability to use thermo‐kinetic analyses to understand the reactions involved, and how these influenced the accident that occurred. Further, we present the progress we've made towards predictive models for the kinetics and the pressure‐time data. Several useful generalizations have evolved. First, is the need to include experiments that use stoichiometric mixtures when assessing exothermic reactions. Second, is the need to understand the role of reaction intermediates, and how they may influence the operation of the plant.
Block Sizes Control For an Efficient Real Time Record Linkage

Record Linkage (RL) is the process of detecting duplicates in one or several datasets. The main important phase during the RL process is blocking, it reduces the quadratic complexity of the RL process by dividing the data into several blocks, in which, matching between the records is done. Several blocking techniques were proposed in the literature, but most of them do not have a mechanism of controlling the generated block sizes, which is a very important condition in the field of real-time RL or privacy-preserving RL. In this paper, we propose a mechanism to control the block sizes generated by the K-Modes based Record Linkage. The experiments done on three real-world datasets show satisfying results where most of the duplicates records were detected while respecting the specified block sizes.
Machine learning and datamining methods for hybrid IoT intrusion detection

By 2025 Internet of things will reach over 75 billion devices which would exceed number of humans about 8.1 billion. These devices need to be secured from many threats by implementing secure and interoperable solutions in order to guarantee a proper functioning of the infrastructures and systems using the IoT. This is why we proposed a hybrid intrusion detection system installed on the cloud powering another online and real time intrusion detection system on the fog to monitor the communication and detect attacks before it spreads over the network as in the case of Mirai botnet. We will provide details of the different algorithms used to implement this distributed system so as to detect attacks against IoT devices.
FlexArch: Flexible Controller Placement Architecture for Hypervisor Assisted vSDN-enabled 5G Networks

The next-Generation wireless network revolution (e.g. 5G & Beyond) is primarily focusing on mitigating the end-user demands that possess random and uncertain characteristics. The TNOs (Telecommunication Network Operators) are looking to provide optimum QoNS (Quality of Network Services) in URLL (Ultra-Reliable Low Latency) environment. The Hypervisor assisted vSDN (virtualized Software Defined Network) is one of the key technology enablers that envisions a flexible and realistic network topology to fulfill the never-ending user demands. Identifying the potential positions of Controllers and Hypervisors inside such a dynamic networking environment is a challenging task. So, in this work, we have proposed a MILP based Joint HPP-CPP (Hypervisor Placement Problem & Controller Placement Problem) that considers different network latency matrices and gives the best geographical arrangements depending upon user load and latency thresholds for real network topology. Our dynamic network framework utilizes a Greedy algorithmic approach that quantifies the parametric values when they have been used as objectives. The simulation result validates our proposed approach, and this approach can be applied in other similar types of critical and dynamic localization problems.
Searching for valid path set under the condition of urban rail transit network failure

When the subway station and the sector failed, the train will use the nearest turn line to form temporary train operation plan. Therefore, it is not reasonable that removing the failed subway station and the sector to rebuild the rail transit network. In this paper, the directed weighted transit network is reconstructed by removing the nodes and edges in the affected scope. The subway network is consisted of nodes and edges. The station and the sector are presented for the node, the edge, respectively. There are more transfer stations with the more perfect subway network. Passengers consider transfer impedance in the path selection. So, transfer station is split into the turn-back station and normal station which belongs to the respective line. And these stations are connected with edge between them. Then valid routes are searched by Breadth-First Search algorithm based on the reconstruction of the rail transit network.
Upper and Lower Estimates of Frame Error Rate for Convolutional Codes

In this paper, we suggest a new approach for frame error rate (FER) evaluation for the convolutional codes. We consider binary symmetric channel and Viterbi decoding of convolutional codes. Convolutional codes we studied here have code rate one half and recursive encoder. We precisely define active distances and their distance spectrum for the code. Unique distance properties allow us to construct estimates for error bursts probabilities and for the probability of erroneous decoding of the convolutional code. We derive upper and lower estimates for error burst probabilities. Based on these expressions we suggest upper and lower bounds for FER performance.
On the Capacity of Gaussian Multiple-Access Wiretap Channels with Feedback

Two-user Gaussian multiple-access wiretap channel models with feedback are investigated. First, we show that the secrecy capacity regions of both the Gaussian multiple-access wiretap channel (GMAC-WT) with feedback and the GMAC-WT with noncausal channel state information at the transmitters (GMAC-WT-NCSIT) and feedback equal the capacity region of the Gaussian multiple-access channel (GMAC) with feedback and without the secrecy constraint and the state corruption. Next, we derive inner and outer bounds on the secrecy capacity region of the GMAC-WT with degraded message set and feedback. Our numerical results show that the perfect secrecy of the private message can be achieved without loss of any reliable transmission rate.