Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting Crowd-based Learning Method in Software Engineering Course

Software engineering is one of main major course for computer science. The main objective of this course is to improve the engineering capabilities of students to develop complex software systems. However, current course practice methods are teacher-centered and thus highly depend on the limited talents, experiences and efforts of teachers. Such methods greatly restrict students’ scopes to gain necessary skills and artifacts, and to draw on successful experiences to address various personalized engineering issues and therefore enhance abilities to tackle engineering complexity. This paper presents a crowd-based learning method and introduces our exploration to use the method to reform the software engineering course practice. The essence of our exploration is to exploit the wisdoms and artifacts of crowds over Internet to support students to accomplish their course projects. The former is the engineering knowledges shared in question and answering (Q&A) platforms such as StackOverflow, and the latter is the open source software (OSS) hosted in OSS sites such as GitHub. We use the method in two separate course practices that aim to improve students’ abilities to develop original, high-quality and large-scale software systems. The results of three-year explorations are positive and impressive and show that the crowd-based learning method is effective.
Evaluation of Add/Drop Flexibility Requirements in Future SDM-Enabled ROADMs

In this paper, we evaluate five different architectures for implementing the Add/Drop module of future Spatial Division Multiplexing (SDM)-enabled Re-configurable Optical Add & Drop Multiplexers (ROADMs) with different degrees of flexibility, from a completely static transponder to spatial channel assignment to a fully-flexible transceiver to fibre and spatial channel assignment. The performance of the proposed architectures is compared in a single SDM-enabled ROADM scenario, where local as well as bypass traffic is injected, supported by spectral super-channels at diverse bit-rates and employing different modulation formats. The obtained results illustrate the additional benefits attainable by more flexible Add/Drop architectures versus their increased hardware complexity.
Package-Integrated, Wideband Power Dividing Networks and Antenna Arrays for 28-GHz 5G New Radio Bands

Package-integrated and ultrathin power dividers with footprint smaller than unit $\lambda ~_{0}~^{\mathrm{ 2}}$ at the operating frequency of 28-GHz 5G new radio (NR) n257 and n258 bands are presented for the first time for small-cell applications. These power dividers are also configured as antenna arrays using endfire Yagi–Uda antenna elements. Utilizing minimal matching techniques, two-, three-, and four-element antenna arrays are designed without compromising on the bandwidth of operation or electrical performance. These thin-film power dividers exhibit a cross-sectional height of $147~\mu \text{m}$ and can be implemented in the top metal layer of front-end module packages. Panel-compatible semiadditive patterning (SAP) process is utilized to realize these structures, which yields precise line space dimensions required for millimeter-wave (mm-wave) applications. This results in power dividers with low added insertion loss, low VSWR, and minimal phase difference between output ports. The added insertion loss is 25% less than similar structures reported on integrated fan-out architectures. The antenna arrays exhibit high gain and efficiency. Excellent model-to-hardware correlation is observed with multiple coupons of the same structure. Package-integrated power dividers and antenna arrays based on ultrathin laminated glass substrate represent a major step toward realizing compact mm-wave antenna-in-package for 5G small-cell applications.
Thérapie génique cutanée : acquis et perspectives.

Les techniques de therapie genique, bien que trouvant aujourd'hui leurs limites dans les systemes de transfert et d'expression, ouvrent un champ prometteur de la recherche medicale. La peau, qui en offre un bon modele, a ete la cible d'un nombre croissant d'experimentations dans ce domaine. Dans le cas des genodermatoses, trois types de pathologies ont ete plus particulierement etudiees : les epidermolyses bulleuses, les ichtyoses recessives et le xeroderma pigmentosum. Plus generalement, les applications de la therapie genique cutanee trouvent leur prolongement dans bien d'autres domaines tels que la cicatrisation, la therapie des desordres systemiques, l'immunomodulation cutanee, et la therapie des cancers de la peau. L'avenir de ces approches diverses et attirantes repose sur la mise au point de methodes de transfert sures et efficaces, et sur des etudes complementaires utilisant des modeles animaux.
Effects of underfill thickness on mechanical properties and fracture behavior of Si/underfill/Si adhesion structures

In this study, two types of commercial underfill materials are used to prepare a simplified Si/underfill/Si adhesion structure with the decreasing underfill thickness of 200, 100 and 50 μm, respectively. The underfill thickness effects on the mechanical performance and fracture behavior of the underfilled Si/underfill/Si structures are studied comprehensively, in which the Si/underfill/Si adhesion structure is designed to mimic the die/underfill/interposer structure widely employed in actual 2.5D/3D integration packages. Results demonstrate that fracture mainly occurs in Si/underfill/Si adhesion structures by two modes, i.e., interface delamination and mixed mode of interface cracking and internal fracture in the underfill, and the probability of two fracture modes occurring in the adhesion structures does not seem to show obvious difference. The decrease in underfill thickness from 200 to 100 and then to 50 μm seems to have little influence on shear strength of the adhesion structures, but the adhesion structures with interface delamination mode show obviously higher shear strength than the structures with the mixed fracture mode. A comparison of the shear strength between the adhesion structures prepared by two underfills suggests that Tg may be the main factor affecting the adhesion performance of the underfill and its adhesion structures.
A 4-Kb 1-to-8-bit Configurable 6T SRAM-Based Computation-in-Memory Unit-Macro for CNN-Based AI Edge Processors

Previous SRAM-based computing-in-memory (SRAM-CIM) macros suffer small read margins for high-precision operations, large cell array area overhead, and limited compatibility with many input and weight configurations. This work presents a 1-to-8-bit configurable SRAM CIM unit-macro using: 1) a hybrid structure combining 6T-SRAM based in-memory binary product-sum (PS) operations with digital near-memory-computing multibit PS accumulation to increase read accuracy and reduce area overhead; 2) column-based place-value-grouped weight mapping and a serial-bit input (SBIN) mapping scheme to facilitate reconfiguration and increase array efficiency under various input and weight configurations; 3) a self-reference multilevel reader (SRMLR) to reduce read-out energy and achieve a sensing margin 2 $\times $ that of the mid-point reference scheme; and 4) an input-aware bitline voltage compensation scheme to ensure successful read operations across various input-weight patterns. A 4-Kb configurable 6T-SRAM CIM unit-macro was fabricated using a 55-nm CMOS process with foundry 6T-SRAM cells. The resulting macro achieved access times of 3.5 ns per cycle (pipeline) and energy efficiency of 0.6–40.2 TOPS/W under binary to 8-b input/8-b weight precision.
Exploring the Effects of Excessive Texting Through Mobile Applications on Students’ Technostress and Academic Writing Skills in the Arabic Language

This study aims to develop a model to examine the influence of excessive mobile application (app) texting on technostress and academic writing skills in the Arabic language among undergraduates in higher education. In this study, the person-technology (P-T) fit model was used as a means of exploring the effect of excessive mobile app texting on students’ levels of technostress and the influence of these factors on their academic writing skills. The sample was comprised of 235 undergraduate students who were selected by random sampling. The study proposed a model comprised of several factors that assist in answering the study questions. These factors are the following: ‘excessive mobile apps texting’, ‘techno-overload’, ‘techno-invasion’, ‘techno-complexity’, ‘accuracy’, ‘clarity’, ‘cohesiveness’, and ‘vocabulary’. A developed questionnaire was employed as the main data collection method to obtain relevant information regarding excessive mobile app texting, mobile technostress, and students’ academic writing skills. A quantitative research method via structural equation modeling (SEM) was used to analyze the data. The results showed that excessive mobile app texting and mobile technostress, including techno-overload, techno-invasion, and techno-complexity, have negative influences (through both direct and indirect effects) on students’ academic writing skills, including accuracy, clarity, cohesiveness, and vocabulary. Several pedagogical and technical implications are suggested at the end of this study.
Routing and Capacity Optimization Based on Estimated Latent OD Traffic Demand

This paper introduces a method to estimate latent traffic from its origin to destination based on the link packet loss rate and traffic volume. Using the estimated latent traffic, this paper also shows that we can compute the appropriate link capacity and route of packet transfer. Observed traffic might deviate from the original traffic demand and become latent when the traffic passes through congested links because of transmission control protocol (TCP) congestion control and behavioral change in the users and/or applications owing to a degraded quality of experience (QoE). The latent traffic is actualized when the congested link's capacity is improved. When link provisioning is based on observed traffic, actualized traffic might cause new congestion at other links. Thus, network providers need to estimate the origin-destination (OD) original traffic demand for network planning. Although estimation of original traffic has been researched, the estimation was only for links. In this paper, we propose a method to estimate latent origin-destination traffic by combining and expanding techniques. One approach estimates the actualized OD traffic and loss rate from the actualized traffic and packet loss rate of links. The other method estimates the latent traffic demand. Then, using the estimated value, the link capacity and routing matrix are optimized. We evaluated our method through simulation and confirmed that congestion could be avoided by capacity provisioning based on estimated latent traffic, while provisioning based on observed traffic retained the congestion. The combined method can avoid congestion with a 23% increment of capacity compared to capacity provisioning only.
A sensor fault detection scheme of DFIG-based wind turbine using deep auto-encoder approach

The reliability of the wind turbine doubly-fed induction generator (DFIG) is of paramount concern for adequate power production. This paper investigates an effective fault detection scheme for DFIG using the deep auto-encoder (DAE) structure. The methods contain three main steps: first, the measurement of the stator currents and voltages directly presented to the DAE to capture the characteristics of the signals effectively. Second, using those features, a neural network model is used to detect faults affecting the stator immediately. Then, a binary decision logic proposed for isolation. The results confirm the method efficiency, rapidity, robustness against the occurrence of multiple faults in the presence of measurement noise and unknown inputs.
A brief review of FEM simulation techniques for IC packaging under impact load

In this paper, several key issues in FEM analysis of IC packaging under impact loading is discussed based on existing references, including IMC simulation, failure modes, and submodel method. Intermetallic compound (IMC) is widely observed in BGA packaging, the failure mode depends greatly on the IMC. As the solder is strengthened with the increase of the strain-rate, the failure mode turned from solder failure to IMC failure, the highest strain rate will even cause pad lift of the packaging. A popular way to simulate its failure procedure in FEM model is cohesive zone model(CZM), the theoretical foundation and the determination of parameters are summarized. Submodel technique is widely used in thermo-mechanical analysis of IC packaging, while few applications of this submodel method can be found in dynamic analysis. It’s suggested that the nonlinear properties can be ignored until the submodel was to be implemented, which decrease the computation complexity drastically.
Evaluation method of human-vehicle tactile interaction experience based on EEG

Aiming at the problem of human-vehicle tactile interaction experience evaluation, this paper proposed a method based on the combination of EEG signals and subjective scoring evaluation. Generally, the evaluation method of human-machine interaction experience is based on the user's subjective evaluation. This kind of method causes the inaccuracy of the evaluation because different people have different judgments on feelings. This paper built a simulated driving environment, collects the EEG signals of the subjects in the interaction process of a car touchpad in different modes, and preprocesses, extracts and analyzes the signals. Then combining the user's subjective score evaluation to achieve an effective combination of quantitative analysis and qualitative analysis. The experimental results show that different modes of the tactile interaction system will affect users to generate EEG signals with different characteristics. The method of subjective and objective fusion can make the evaluation of human-vehicle tactile interaction experience more comprehensive.
Effects of total flavonoids in Gingko Biloba on glucose and lipid metabolism and liver function in rats with insulin resistance

Objective To investigate the effects of total flavonoids in Gingko Biloba on glucose and lipid metabolism and liver function in rats with insulin resistance. Methods Forty SD rats were randomly divided into normal control group,model group,total flavonoids in Gingko Biloba group and rosiglitazone group(positive drug control group)(n=10). Models of insulin resistance were established by high glucose and high fat diet in model group,total flavonoids in Gingko Biloba group and rosiglitazone group.After treatment for 12 weeks,serum glucose,serum lipids,and parameters of insulin resistance,liver function and anti-oxidation capability were detected in each group,and histologic observations of liver tissues were conducted with adipose staining. Results The serum glucose,insulin resistance index(HOMA-IR),insulin action index(IAI),serum total cholesterol(TC),triglyceride(TG),liver malondialdehyde(MDA) and serum transaminase activity in total flavonoids in Gingko Biloba group were significantly lower than those in model group(P0.01),while high density lipoprotein-cholesterol(HDL),serum total anti-oxidation capacity(T-AOC) and liver superoxide dismutase(SOD) were significantly higher than those in model group(P0.01). Histologic observations revealed that there were smaller and less lipid droplets in liver cells in total flavonoids in Gingko Biloba group and rosiglitazone group than in model group. Conclusion Total flavonoids in Gingko Biloba can effectively regulate serum glucose and serum lipids levels,increase insulin sensitivity,decrease degree of adipose degeneration,and improve liver function and anti-oxidatin capacity in rats with insulin resistance.
Wireless Body-Area-Network Transceiver and Low-Power Receiver With High Application Expandability

In this article, a body channel communication (BCC) transceiver (TRX) and low-power receiver (RX) that can cover wide applications are proposed. The IEEE 802.15. 6 human body communication (HBC) physical layer (PHY) standard and high-speed data transmission are supported simultaneously with a single chip. First, the sinusoidal-modulated transmitter is proposed for the standard mode TRX, and it can reduce filtering power overhead 35%. Second, high-speed TRX is proposed that can support dual-band QPSK modulation to increase system data rate and bandwidth efficiency. Third, on-chip RC duplexer is proposed for full-duplex function in communication. Also, for the low-power RX, a wireless power transfer (WPT)-based wake-up receiver (WuRX) and a higher energy efficiency main RX is integrated into RX chip. The main HBC RX demodulates both ASK and frequency-shift keying (FSK) information with a sharing oscillator (OSC) with 31- $\mu \text{W}$ low-power consumption. The TRX and RX are implemented in 65-nm CMOS process.
Imprinting analysis by droplet digital PCR coupled with locked nucleic acid TaqMan probes

ABSTRACT Imprinted genes are differentially expressed in a parent-of-origin-specific manner. Parental origin of the alleles is discriminated by intragenic DNA polymorphisms. Comparisons of parental allelic expression have been analysed by semiquantitative RT-PCR. Here, we developed a novel quantitative method for allelic expression of the imprinted gene Ube3a, which inactivation and mutations cause Angelman syndrome and predominantly expressed by the maternal allele in neuronal tissues. In this method, cDNA was amplified by droplet digital PCR (ddPCR) coupled with allele-specific locked nucleic acid (LNA) TaqMan probes, which labelled by FAM and HEX were designed to detect the SNPs in the target regions. ddPCR assay demonstrated that the sense transcript of Ube3a was equally expressed from both parental alleles in adult tissues except neuronal tissues, where Ube3a expression from the paternal allele was about 10 to 14% of total Ube3a expression in adult brain, and 20% in spinal cord. The antisense transcript of Ube3a was expressed at 60% to 70% of the sense transcript of Ube3a in adult brain. Changes in the Ube3a transcripts during postnatal brain development were also evaluated by ddPCR. The ddPCR method is far more reliable and simpler to use than semiquantitative PCR to analyse skewed or faint allelic expression of imprinted genes.
Molecular dynamics simulation of melting and sintering process of multi-scale copper nanoparticles

With the advent of the information age, electronic packaging technology is developing in the direction of high power, high density, miniaturization, high reliability and green packaging. Because the third-generation semiconductor material has advantages over traditional semiconductors, it is considered to be a strategic technology with significant influence. Become a hot topic of research. However, due to the limitations of traditional packaging materials, it is difficult for third-generation semiconductor devices to take advantage of their low loss and high electrical performance, and the operating temperature range is narrow. Solder has become one of the technical bottlenecks of wide-sealed semiconductor device packaging and high-power device high-temperature packaging. In this paper, the molecular dynamics simulation software Lammps was used to simulate the copper nanoparticles with different nanometer sizes under low temperature and pressureless sintering conditions, and the interdiffusion sintering neck growth, radius of gyration and mixed size of the nanometer copper particles under different size conditions were discussed. The energy distribution of the atom in the particle model reveals the transformation tendency of the internal lattice of the nano-copper particles during the heating process. Provide a certain theoretical basis for the development of the experiment.
Analysis of Learning Behavior in an Automated Programming Assessment Environment: A Code Quality Perspective

Automated programming assessment systems are useful tools to track the learning progress of students automatically and thereby reduce the workload of educators. They can also be used to gain insights into how students learn, making it easier to formulate strategies aimed at enhancing learning performance. Rather than functional code which is always inspected, code quality remains an essential aspect to which not many educators consider when designing an automated programming assessment system. In this study, we applied data mining techniques to analyze the results of an automated assessment system to reveal unexpressed patterns in code quality improvement that are predictive of final achievements in the course. Cluster analysis is first utilized to categorize students according to their learning behavior and outcomes. Cluster profile analysis is then leveraged to highlight actionable factors that could affect their final grades. Finally, the same factors are employed to construct a classification model by which to make early predictions of the students’ final results. Our empirical results demonstrate the efficacy of the proposed scheme in providing valuable insights into the learning behaviors of students in novice programming courses, especially in code quality assurance, which could be used to enhance programming performance at the university level.
End-To-End KPI Analysis in Converged Fixed-Mobile Networks

The independent operation of mobile and fixed network segments is one of the main barriers that prevents improving network performance while reducing capital expenditures coming from overprovisioning. In particular, a coordinated dynamic network operation of both network segments is essential to guarantee end-to-end Key Performance Indicators (KPI), on which new network services rely on. To achieve such dynamic operation, accurate estimation of end-to-end KPIs is needed to trigger network reconfiguration before performance degrades. In this paper, we present a methodology to achieve an accurate, scalable, and predictive estimation of end-to-end KPIs with sub-second granularity near real-time in converged fixed-mobile networks. Specifically, we extend our CURSA-SQ methodology for mobile network traffic analysis, to enable converged fixed-mobile network operation. CURSA-SQ combines simulation and machine learning fueled with real network monitoring data. Numerical results validate the accuracy, robustness, and usability of the proposed CURSA-SQ methodology for converged fixed-mobile network scenarios.