Miracle-dz/UniFAR-FTUs huggingface dataset:
Fine-Pitch $30\ \mu \mathrm{m}$ Cu-Cu Bonding using Electroless Nano-Ag

The development of direct Cu-to-Cu bonding technologies has attracted increasing attention due to the increased requirement for advanced high-density packaging. For Cu-Cu bonding, the main issue is that the surface roughness of the Cu pad is not uniform, and the uneven surface induces the partial-bonding, void, and delamination during bonding process. Thus, the Cu pad is needed to use the chemical machine polishing (CMP) to vanish the above-mentioned defects. Alternatively, R. Liu's study observed that the plating nano-Ag film was coated on the surface of the Cu pad to make the interconnect area more uniform [1]. However, if the Ag concentration was too high, it would occur the dendrites on the Cu pad, and the roughness became larger. In this study, the nano-Ag layer is formed using a replacement reaction during the electroless plating process, to decrease costs. Moreover, to compare with CMP, using electroless nano-Ag can lessen the probability of damage on the surface. This study further examined the optimum Ag concentration mixed with the additive for Ag coating on the Cu pad. The function of the additive is to contribute to the flatter Ag layer deposition on Cu pad. In addition, the sintering mechanism of Ag layer is observed with annealed temperature at 190°C, 220 °C, and 250°C, respectively. From atomic-force microscopy (AFM) results, the surface roughness of Ag layer is increased at 190°C compared with the initial surface morphology which can be attributed to the Ag agglomerates to form the Ag nodule. Contrarily, the roughness is decreased as annealing treatment changed from 190°C to 250 °C, which might be attributed to the surface diffusion and grain boundary diffusion of Ag nanoparticles during sintering process [2]. The tensile test is conducted after Cu-Ag-Cu bonding samples by using blanket and patterned metal bonding wafers. There're two failure modes, one is fracture on the electroless Ag-to-Cu joint interface, and the other is fracture on the Ag layer. Furthermore, electroless Nano-Ag was applied on the chip-to-wafer metal bonding process under 220°C, 1MPa and 5min of bonding condition. In daisy-chain electrical resistance verification, Nano-Ag assisted Cu-Ag-Cu bonding has 20 % improvement of yield compared with CMP assisted Cu-Cu bonding. In summary, electroless nano-Ag with the additive cannot only enlarge the process window, but also is strongly adhesive on the Cu part well. Therefore, Cu-Ag-Cu bonding using electroless nano-Ag is the competitive application compared to direct Cu-Cu bonding for applying the fine-pitch IC package under low-temperature.
A New Adhesive for CoW Cu-Cu Hybrid Bonding with High Throughput and Room Temperature pre-Bonding

In this report, a new approach to high throughput, low-temperature chip on wafer hybrid bonding processes by using a unique adhesive is described. In our process, a bonding layer consisting of cured adhesive and slightly recessed Cu pads is fabricated on the chip surface, and the chip is bonded to another bonding layer consisting of SiO2 and Cu pads fabricated on the target wafer. The chip is pre-bonded to the target wafer under compression for 1 second at room temperature by contacting the adhesive and SiO2. By using the slight film shrinkage of the adhesive in the Cu-Cu bonding process, the two facing Cu contact and compressed. As a result, batch annealing process without chip compression becomes possible. Experimental results for the proof of our process are reported.
New heuristic and PSO algorithm for Tchebychev distance facility Location problems with a probabilistic line barrier in the plane

One of the well established research areas within Operations Research is and has been facility location. Considering barriers in weber location problem is a relatively new research direction within location analysis that takes into account barrier’s traits and its prohibited region for finding location of new facility in the plane. we propose and design an efficient heuristic algorithm and particle swarm optimization (PSO) for solving tchebychev distance facility Location problems with a probabilistic line barrier in the plane. Finally, these algorithms were evaluated by solving some different size of test-problem and their results were compared. Keywords: PSO, Operations Research, distance facility;
WOMBAT: A fully Bayesian global flux-inversion framework

WOMBAT (the WOllongong Methodology for Bayesian Assimilation of Trace-gases) is a fully Bayesian hierarchical statistical framework for flux inversion of trace gases from flask, in situ, and remotely sensed data. WOMBAT extends the conventional Bayesian-synthesis framework through the consideration of a correlated error term, the capacity for online bias correction, and the provision of uncertainty quantification on all unknowns that appear in the Bayesian statistical model. We show, in an observing system simulation experiment (OSSE), that these extensions are crucial when the data are indeed biased and have errors that are correlated. Using the GEOS-Chem atmospheric transport model, we show that WOMBAT is able to obtain posterior means and uncertainties on non-fossil-fuel CO$_2$ fluxes from Orbiting Carbon Observatory-2 (OCO-2) data that are comparable to those from the Model Intercomparison Project (MIP) reported in Crowell et al. (2019, Atmos. Chem. Phys., vol. 19). We also find that our predictions of out-of-sample retrievals from the Total Column Carbon Observing Network are, for the most part, more accurate than those made by the MIP participants. Subsequent versions of the OCO-2 datasets will be ingested into WOMBAT as they become available.
Quantum-accelerated multilevel Monte Carlo ewline methods for stochastic differential equations in mathematical finance

1Department of Mathematics, University of California, Berkeley, CA 94720, USA 2School of Mathematics, Fry Building, University of Bristol, BS8 1UG, UK 3Joint Center for Quantum Information and Computer Science, University of Maryland, MD 20742, USA 4Institute for Advanced Computer Studies, University of Maryland, MD 20742, USA 5Department of Mathematics, University of Maryland, MD 20742, USA 6Phasecraft Ltd, Quantum Technologies Innovation Centre, Bristol BS1 5DD, UK
Novel Music Genre Classification System Using Transfer Learning on a Small Dataset

Music is an essential "element" in our lives. With the rapid development of technology, the use of compact disks and tapes for listening various forms of music of different cultures has become obsolete. Because of the generation of considerable music data, the accurate classification of music data has become a critical topic of research, and the development of deep learning technology provides a solution for music classification. Transfer learning techniques are widely used in image recognition but are rarely used for music classification. In this study, a small music dataset is used for music classification using transfer learning.
Detection of Various Plant Leaf Diseases Using Deep Learning Techniques

To sustain healthy crop yields and avoid extensive plant disease damage, it is essential to diagnose plant leaves. Traditional diagnostic techniques, however, can be laborious and complicated. Deep learning methods like ResNet 34 have recently come to light as a potential strategy for automating plant leaf diagnosis. Deep convolutional neural network ResNet 34 is capable of correctly classifying photos of plant leaves based on patterns and characteristics. A ResNet 34 model may be taught to recognize different leaf illnesses and other anomalies with excellent accuracy by training it on a huge dataset of tagged plant leaf photos. The ResNet 34 model's output may be seen on a website, enabling users to upload pictures of plant leaves and get a diagnosis in a matter of seconds. Also, the website might include details on the particular ailment or issue found, along with suggested remedies and prevention actions. The way of identifying and treating plant illnesses may be completely altered by this method of diagnosing plant leaves, which would ultimately result in healthier crops and a more sustainable future. Farmers, agronomists, and other stakeholders will find it simpler to recognize and effectively treat plant diseases thanks to the usage of ResNet 34 and a website for output display, which offers an accessible and user-friendly interface for plant diagnostics.
Convergence of discrete and continuous unilateral flows for Ambrosio–Tortorelli energies and application to mechanics

We study the convergence of an alternate minimization scheme for a Ginzburg–Landau phase-field model of fracture. This algorithm is characterized by the lack of irreversibility constraints in the minimization of the phase-field variable; the advantage of this choice, from a computational stand point, is in the efficiency of the numerical implementation. Irreversibility is then recovered a posteriori by a simple pointwise truncation. We exploit a time discretization procedure, with either a one-step or a multi (or infinite)-step alternate minimization algorithm. We prove that the time-discrete solutions converge to a unilateral L2-gradient flow with respect to the phase-field variable, satisfying equilibrium of forces and energy identity. Convergence is proved in the continuous (Sobolev space) setting and in a discrete (finite element) setting, with any stopping criterion for the alternate minimization scheme. Numerical results show that the multi-step scheme is both more accurate and faster. It provides indeed good simulations for a large range of time increments, while the one-step scheme gives comparable results only for very small time increments.
Comparative Mechanical Behavior of Sn-Bi based Low Temperature Solder Alloys under Different Pretest Aging Conditions

The use of Low Temperature Solders (LTS) as an alternative to high temperature Sn-Ag-Cu (SAC) alloys has gained increasing interest owing to the benefits associated with low reflow temperatures such as decrease in warpage during as-sembly, nontoxicity, and lower operating and energy costs. Sn-Bi alloy system, with reduced reflow temperature of approximately 183°C, is a popular LTS alloy system. In addition to the existing literature on microstructural properties, there is a need to study and compare the mechanical properties of the new LTS solders. As part of this study, a baseline mechanical characterization of Sn3.0Ag0. 5Cu and Sn58Bi solder compositions is first performed. Several alloying elements have been suggested to improve the reliability of Sn-Bi system, of which Ag, In and Sb have been studied in this work. Mechanical behavior of Sn57BilAg, HRL3 (by MacDermid Alpha), L27 and L29 (by Senju Metal Industry) alloys are presented here. In addition, the effect of pretest aging (after reflow and aged to 10 days at 85°C/125°C) on the mechanical behavior is studied. A comprehensive comparison of the mechanical behavior of the four new LTS alloys against the baseline alloys is presented. A custom designed micro-precision mechanical tester is used to perform isothermal creep, monotonic and fatigue testing of the solder test specimen under shear at room temperature and an elevated temperature of 70° C.
G-Bench: Fair Benchmarking to Support Innovations in Streaming Graph Systems

In this work, we comment on the current practices for benchmarking streaming graph systems. We deduce that present practices can stifle future innovations in storage design, establish wrong precedents, lead to premature optimizations and complexity, and are a recipe for errors. We analyze why such benchmarking errors are prevalent and propose potential solutions. We further deliver a code base, G-Bench, that can be easily integrated with prior and future research prototypes to provide fair performance comparison metrics without compromising innovations. Our evaluations contradict results published in some recent works.
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs ( SUPPLEMENTARY ) 1 . Model Details

Voxelization. We pre-process input point clouds with voxelization subsampling by computing per-voxel mean positions and observations over a regular 3D grid (5 cm bins for Semantic3D and 3 cm bins for S3DIS dataset). The resulting semantic segmentation is interpolated back to the original point cloud in a nearest neighbor fashion. Voxelization helps decreasing the computation time and memory requirement, and improves the accuracy of the semantic segmentation by acting as a form of geometric and radiometric denoising as well (Table 4 in main paper). The quality of further steps is practically not affected, as superpoints are usually strongly subsampled for embedding during learning and inference anyway (Subsection 3.3 in the main paper).
Contamination-Free Cu/SiCN Hybrid Bonding Process Development for Sub- μm Pitch Devices with Enhanced Bonding Characteristics

Hybrid bonding has emerged as a promising 3D integration technology for the next generation stacking devices with advantages of higher performance and smaller form factor. As for the future devices with fine-pitch (sub-μm level) copper (Cu) interconnects, however, there are critical issues to consider for a successful application of hybrid bonding processes; (1) Cu diffusion with scaled Cu pads and (2) Cu re-sputtering and chamber contamination during plasma surface activation step that lead to fatal device failure (e.g. electrical shorts) even with a small amount. Here, we demonstrated robust connections for 0.4 to 0.7 μm-sized Cu pads of fine-pitch with wafer-to-wafer (W2W) Cu/SiCN hybrid bonding scheme through N2 plasma development and present comprehensive analyses for surface activation process. A computational work carried out by reactive molecular dynamics (MD) simulations was employed to propose an optimal N2 plasma condition that can enhance SiCN-SiCN bonding characteristics. The optimized N2 plasma condition reproduces SiCN-SiCN bonding strength of above 2.0 J/m2while suppressing oxidation of Cu pads below 2 nm. Cu/SiCN hybrid bonding characteristics using N2 plasma were confirmed to be void-free, well Cu-Cu interdiffused, and mechanically well aligned from the assessment involving SAT, TEM/EDS and FIB-SEM/EBSD analyses. Moreover, our optimal plasma condition meets the contamination- free criteria indicating that it is a preferable surface activation scheme without contaminating the plasma chamber regardless of continuous operations. The methodologies demonstrated in this work suggest that hybrid bonding can be applied to future fine- pitch device applications for successful 3D integration.
Stochastic Programming Versus Chance-Constrained Optimization for Optimal Rescheduling of Microgrids in Hierarchical Multi-Microgrid Systems

Multi-microgrid systems (MMSs) can pave the way for the development of microgrids (MGs) in distribution networks (DNs), contributing to renewable energy exploitation and carbon footprint reduction. Notwithstanding, the emergence of MMSs complicates the day-ahead optimal energy management of DNs since both private MGs and distribution system operators (DSOs) are involved in the decision-making process compared to conventional DNs. Hence, hierarchical structures as practical solutions have attracted the attention of many researchers. Nevertheless, in those structures, MGs have to reschedule their generation and consumption patterns based on the orders received from DSOs. In this paper, two-stage stochastic and chance-constrained models for the rescheduling of an MG in an MMS are deployed and compared to embrace the uncertainties linked to demand and renewable energy generation. Results for the modified IEEE 33-bus test system showed that the proposed chance-constrained model can reduce the total cost by 6.68% compared to the stochastic one. Thus, the proposed model is well-suited for a fair rescheduling of the MG by avoiding excessive costs associated with extreme cases.
Distributed Cooperative Control of Multi Flywheel Energy Storage System for Electrical Vehicle Fast Charging Stations

Citation for published version (APA): Sun, B. , Dragicevic, T. , Quintero, J. C. V. , & Guerrero, J. M. (2015). Distributed Cooperative Control of Multi Flywheel Energy Storage System for Electrical Vehicle Fast Charging Stations. In Proceedings of the 2015 17th European Conference on Power Electronics and Applications (EPE'15 ECCE-Europe) (pp. 1-8). IEEE Press. https://doi.org/10.1109/EPE.2015. 7311762
Machine Learning Approach to Sentiment Recognition from Periodic Reports

We propose a novel indicator to measure fund managers’ sentiment, a topic of significant interest to both academia and the financial industry, as it relates to investor sentiment and stock volatility. As mutual funds continue to gain traction, fund managers have emerged as crucial players in the Chinese stock markets. Drawing upon a dataset comprising 4,142 mutual funds over a five-year period, we construct a fund manager sentiment index by analyzing periodic reports. Additionally, we examine the mediating effect of the investor sentiment index on stock volatility. This study contributes to the understanding of fund managers’ sentiment and its potential implications for stock market fluctuations.
REVISTA DE CONTABILIDAD SPANISH ACCOUNTING REVIEW

The low satisfaction of university accounting teachers with the mentoring process of the Final Year Dissertation (FYD) has motivated carrying out this study. Moreover, lecturers are very interested in knowing which factors are influencing this satisfaction. The aim of the study is to detect which factors explain this state of satisfaction and model this relation. The elements which have been able to influence this opinion have been identified and studied. Exploratory factor analysis has extracted 5 factors from them: the acceptation of the methodology, the perception of competence, generic competences, the importance of instrumental competences and the importance of systemic competences. The results reveal the relations between the constructs and satisfaction. In conclusion, if we wish to build a teaching strategy which reinforces university accounting teachers’ degree of satisfaction in their work mentoring the FYD, this should be centred on enhancing its generic competences. The development of these generic competences directly or indirectly impacts the mentors’ opinions concerning the importance of the instrumental and systemic competences and, consequently, their satisfaction. ©2021 ASEPUC. Published by EDITUM Universidad de Murcia. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Códigos JEL: A22 M40 M49 Palabras clave: Profesores de Contabilidad Trabajo Fin de Grado Competencias Satisfacción PLS Modelización, usando ecuaciones estructurales, del grado de satisfacción de los profesores universitarios de contabilidad sobre el trabajo fin de grado
REVISTA DE CONTABILIDAD SPANISH ACCOUNTING REVIEW

This paper examines the economic consequences associated with an audit failure in the field of statutory auditing services, by analyzing changes in the audit firm’s market share around the time of the investigation process undertaken by the Spanish Public Oversight Board. We explore the variations in audit market share by applying the difference in differences method to a treatment group of 70 sanctioned audit firms and a matched control group of 70 non-sanctioned audit firms. The period of analysis covers the years from 1999 to 2015. Our results show that the sanctioned audit firms suffered a significant decrease in their relative number of clients. Moreover, this measure of market share decreased not only after the publication of the sanction disclosure (which may be attributed to reputational losses) but also after the initiation of the investigation (which may be attributed to the firm’s reluctance to audit risky clients). Findings are similar for both small and large firms when the market share is measured in terms of clients, whereas the evidence is weak concerning variations in their turnover-based market share. Our conclusions could be of interest for audit firms and also for audit regulators when designing disciplinary systems. ©2022 ASEPUC. Published by EDITUM Universidad de Murcia. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Códigos JEL: C23 C51 H83 M42 M48 Palabras clave: Sanción Fracaso de la auditoría Cuota de mercado Pérdidas económicas Diferencia en diferencias El impacto económico de los fallos de auditoría
REVISTA DE CONTABILIDAD SPANISH ACCOUNTING REVIEW

This study investigates whether some audit quality attributes are capable to restrict earnings management in a developing country, Jordan, whose cultural, economic and institutional context is very different from most previously analyzed countries context. Generalized least square regression (GLS) was used to study the association between two audit quality attributes (auditor size and audit fees) and discretionary accruals, as a proxy of earnings management, for a sample of industrial firms listed on the Amman Stock Exchange during the period 2012 2016. The findings are consistent with the expectation that in emerging countries external audit can function differently from that in Anglo-Saxon and West-European countries with regard to its role in restricting earnings management and indicate that, given the institutional environment in Jordan, auditor size and audit fees have no significant effect on earnings management. This study provides readers with information about if and how the institutional setting influences the relationship between audit quality and earnings management. Furthermore, it presents new evidence regarding the moderating effect of the level of audit fees on their relation with earnings management. This studys findings could provide valuable information to regulators and standards setters, both in Jordan and other countries with a similar economic and institutional environment, which can help in preventing earnings management practices. ©2020 ASEPUC. Published by EDITUM Universidad de Murcia. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Códigos JEL: M42 G30 Palabras clave: Calidad de la auditoría Tamaño del auditor Honorarios de auditoría Manipulación de resultados Devengos discrecionales Jordania ¿Influye la calidad de la auditoría en la gestión de resultados en los mercados emergentes? Evidencia de Jordania
ProvSec: Cybersecurity System Provenance Analysis Benchmark Dataset

System provenance forensic analysis has been studied by a large body of research work. This area needs fine granularity data such as system calls along with event fields to track the dependencies of events. While prior work on security datasets has been proposed, we found a useful dataset of realistic attacks and details that can be used for provenance tracking is lacking. We created a new dataset of eleven vulnerable cases for system forensic analysis. It includes the full details of system calls including syscall parameters. Realistic attack scenarios with real software vulnerabilities and exploits are used. Also, we created two sets of benign and adversary scenarios which are manually labeled for supervised machine-learning analysis. We demonstrate the details of the dataset events and dependency analysis.
Centralized Operation of Multi-Energy Microgrids

This paper presents a centralized model for operating multi-energy microgrids. The proposed model is based on a linearized optimal power flow (OPF) model for handling the network constraints in the distribution networks. It is assumed that each local microgrid is self-sustaining and can be operated independently from the other microgrids. However, the network access provides more flexibility to the multi-energy microgrid operators to supply their loads. The network-based electrical energy transactions are accepted in this study, while energy transformation from electricity to the other carriers is an asset to minimize the overall operating cost of the centralized multi-energy microgrid operation. The proposed model is tested and verified on the modified IEEE 33-bus test system.