Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning

Federated Learning (FL) is a novel privacy-protection distributed machine learning paradigm that guarantees user privacy and prevents the risk of data leakage due to the advantage of the client's local training. Researchers have struggled to design fair FL systems that ensure fairness of results. However, the interplay between fairness and privacy has been less studied. Increasing the fairness of FL systems can have an impact on user privacy, while an increase in user privacy can affect fairness. In this work, on the client side, we use fairness metrics, such as Demographic Parity (DemP), Equalized Odds (EOs), and Disparate Impact (DI), to construct the local fair model. To protect the privacy of the client model, we propose a privacy-protection fairness FL method. The results show that the accuracy of the fair model with privacy increases because privacy breaks the constraints of the fairness metrics. In our experiments, we conclude the relationship between privacy, fairness and utility, and there is a tradeoff between these.Comment: 17 pages, 3 figures, conferenc

A Focused Review on Structures and Ionic Conduction Mechanisms in Inorganic Solid-State Proton and Hydride Anion Conductors

Solid-state proton and hydride anion conductors are an important family of materials as electrolytes for solid state electrochemical cells such as fuel cells, batteries, sensors, and gas separation membranes. Searching for new proton and hydride-anion conductors has been an active research area for many decades. The focus of this article is on reviewing the types and mechanisms of each proton/hydride-anion conductor developed and their pros and cons. This review starts off with the most studied and most promising perovskite structured oxides as proton conductors, followed by other types of perovskite-related structures such as the Ruddlesden–Popper phase, pyrochlores and rare earth orthoniobates/orthotantalates. This review then moves to solid polyanionic compounds as proton conductors, including sulfates, nitrates, and phosphates, which is followed by hydrates and nanocomposites. This review finally discusses the types and conduction mechanisms of new hydride-anion conductors that emerged recently

A novel measurement method for SiPM external crosstalk probability at low temperature

Silicon photomultipliers (SiPMs) are being considered as potential replacements for conventional photomultiplier tubes (PMTs). However, a significant disadvantage of SiPMs is crosstalk (CT), wherein photons propagate through other pixels, resulting in secondary avalanches. CT can be categorized into internal crosstalk and external crosstalk based on whether the secondary avalanche occurs within the same SiPM or a different one. Numerous methods exist for quantitatively estimating the percentage of internal crosstalk (iCT). However, external crosstalk (eCT) has not been extensively studied. This article presents a novel measurement method for the probability of emitting an external crosstalk photon during a single pixel avalanche, using a setup involving two identical SiPMs facing each other, and without the need for complex optical designs. The entire apparatus is enclosed within a stainless steel chamber, functioning as a light-tight enclosure, and maintained at liquid nitrogen temperature. The experimental setup incorporates two Sensl J-60035 SiPM chips along with two 0.5-inch Hamamatsu Photonics (HPK) VUV4 S13370-6050CN SiPM arrays. The findings show a linear relationship between the probability of emitting an external crosstalk photon and the SiPM overvoltage for both SiPM samples. Surprisingly, this novel measurement method also rovides measurements of the SiPM photon detection efficiency (PDE) for eCT photons at low temperature

Preserving Flake Size in an African Flake Graphite Ore Beneficiation Using a Modified Grinding and Pre-Screening Process

As the high value and the scarcity of large-flake graphite ore resources, it is in the best interest to maximize the amount of large flakes and minimize any processing that will reduce flake sizes. In the study, the mineralogy of an African graphite ore was estimated using X-ray diffraction (XRD), X-ray fluorescence (XRF), and optical microscope analyses. The results indicated that it was a heavily weathered large flake graphite ore and the main gangue minerals were quartz and kaolinite. The graphite flakes were thick, bent, and fractured, and some clay minerals were embedded into the graphite interlayer, which made it difficult to prevent the large flakes from being destroyed using mechanical grinding methods. An approach of steel rod coarse grinding and pebble regrinding effectively reduced the destruction of graphite flakes and improved the grinding efficiency. In addition, comparing with the conventional process, a pre-screening process was applied and the content of large flakes in the final concentrate was significantly improved

SPECIES SPECIFIC CALIBRATION FOR THE CHLOROPHYLL METER FOR EIGHT TREE SPECIES IN NORTHEAST CHINA

We assessed the predictive capability of the optical meter for determining leaf pigment status of Quercus mongolica, Betula platyphylla, Phellodendron amurense, Juglans mandshurica, Fraxinus mandshurica, Acer mono, Tilia amurensis, and Ulmus propinqua during the growing season. The relationships between extractable Chl (a+b) concentration per unit of leaf area/content per unit of fresh leaf mass and the SPAD values generally followed a nonlinear function, and variations in the calibration line slope were markedly evident for eight tree species across sampling dates. Moreover, the relationships between the SPAD values and the concentration of Chl (a+b) were stronger than content both within and across dates in all tree species in most cases. Even though R2 values between Chl (a+b) content and SPAD meter readings were improved by incorporating leaf mass area (LMA) and leaf water content (LWC) as the independent variables into regression compared with those values showed in simple regression equations of eight tree species, which the content of Chl (a+b) were significantly negatively correlated with LMA, and mostly positively with LWC. Overall, our results indicated that the optical meter can accurately estimate leaf pigment during the growing season-but that the accuracy of the estimate varies across species throughout development. Precautions for using the meter are prescribed if unhealthy leaves are to be measured

ECCF: An Improved GNN CollaborativeFiltering Algorithm for Edge Computing

Abstract There are many relational data in edge computing They belong tonon-Euclidean spatial data. Graphical neural network can expand edgecomputing capabilities to extract features from non-Euclidean spatialdata, and thus is suitable for edge computing data classification and filtering. In IoT edge computing, there are many computing nodes anddata to be transmitted. Therefore, how to transmit the most needed datato the computing nodes is an important issue, and a better recommendation model is needed to filter t he e dge d ata. L ightGCN i s a superiorrecommendation model based on graph neural network, but there is stilla problem of over-smoothing when the user-item relationship extractionlayer is stacked with multiple layers. To solve this problem, this paperproposes an improved graph neural network collaborative filtering algorithm for edge computing (ECCF) to build a deeper graph neural networkto achieve better feature extraction, keep the purity of local features,and improve recommendation performance. ECCF uses hard negativemining method as a sampling method to improve recommendation accuracy and training efficiency, and uses IndRNN with long and short-termmemory with self-attention layer to capture valid information.The experimental results of the model using Gowalla, Yelp 2018 and AmazonBook show that ECCF performs better in NDCG and Recall evaluationmetrics than LightGCN, IMP-GCN and NGCF. ECCF improves the recommendation accuracy while minimizing the complexity of the model,which is well adapted to be applied to data filtering for edge computing.</jats:p