Exploiting Features and Logits in Heterogeneous Federated Learning

Due to the rapid growth of IoT and artificial intelligence, deploying neural networks on IoT devices is becoming increasingly crucial for edge intelligence. Federated learning (FL) facilitates the management of edge devices to collaboratively train a shared model while maintaining training data local and private. However, a general assumption in FL is that all edge devices are trained on the same machine learning model, which may be impractical considering diverse device capabilities. For instance, less capable devices may slow down the updating process because they struggle to handle large models appropriate for ordinary devices. In this paper, we propose a novel data-free FL method that supports heterogeneous client models by managing features and logits, called Felo; and its extension with a conditional VAE deployed in the server, called Velo. Felo averages the mid-level features and logits from the clients at the server based on their class labels to provide the average features and logits, which are utilized for further training the client models. Unlike Felo, the server has a conditional VAE in Velo, which is used for training mid-level features and generating synthetic features according to the labels. The clients optimize their models based on the synthetic features and the average logits. We conduct experiments on two datasets and show satisfactory performances of our methods compared with the state-of-the-art methods

Optimization of simultaneous production of waste cooking oil based-biodiesel using iron-manganese doped zirconia-supported molybdenum oxide nanopeprintss catalyst

Biodiesel derived from simultaneous esterification and transesterification of waste cooking oil has been attracting consideration as a replacement green fuel for diesel fuels, as it is economically feasible and circumvents the issue of energy versus food, which is estimated to take place with current biodiesel production techniques. In this optimization study, iron-manganese doped zirconia-supported molybdenum oxide catalyst has been prepared and used in the synthesis of waste cooking oil based biodiesel by a simultaneous esterification and transesterification method. The catalyst is prepared via an impregnation method and consequently characterized by XRD, TEM, TGA (thermogravimetric analysis), TPD-NH3, and Brunauer–Emmer–Teller (BET) techniques. The simultaneous process for biodiesel production has been assessed and improved statistically via response surface methodology in combination with the central composite design. It has been established that the process for synthesis of waste cooking oil based biodiesel achieved about 96.8% biodiesel yield at a best condition of 200 °C, waste cooking oil/ methanol molar ratio of 1:30 and 5.0 wt. % as loading of the catalyst. The highest ester yield of 96.8% has been obtained due to the improved physicochemical properties of zirconia-supported molybdenum oxide catalyst which accesses diffusion of the reactants to the active sites

Investigation of the nature of the oxidant (selective and unselective) in/on a vanadyl pyrophosphate catalyst

The anaerobic oxidation of CO by a (VO)2P2O7 catalyst has been used to investigate the nature of the oxidant (selective and unselective) in/on that material. Three peaks were observed in the rate of production of CO2 - at 993, 1073 and 1093 K. The temperature of the maximum in the rate of production of the first CO2 peak and the amount of oxygen associated with it are the same as that observed in the selective anaerobic oxidation of n-butane to butene and butadiene, but-1-ene to butadiene and furan and but-1,3-diene to dihydrofuran, furan and maleic anhydride. The interaction of CO with the (VO)2P2O7 catalyst forming CO2 at 993 K is therefore concluded to be with the selective oxygen. The total amount of oxygen removed by the CO from the (VO)2P2O7 lattice (>5 monolayers) is about six times greater than that of the selective oxygen. The higher activation energies for the removal of the unselective oxygen accounts for the high selectivities (~80%) encountered commercially for the anaerobic oxidation of n-butane to maleic anhydride. Re-oxidation of the CO reduced (VO)2P2O7 by N2O quantitatively replaces all of the lattice oxygen removed by the formation of CO2, but does not restore the original morphology

Synthesis of clamshell derived Ca(OH)2 nano-particles via simple surfactant-hydration treatment

Recently, calcium hydroxide (Ca(OH)2) nanoparticles derived from calcium oxide (CaO) has been getting attention from researchers as heterogeneous catalyst for several chemical reaction such as: transesterification, chemisorbents for toxic gases and cracking-decarboxylation process. Ca(OH)2 in nano-crystal structures exhibit superior characteristics which enhance the reaction. In Malaysia, clam species (Meretrix meretrix) are abundantly available in backwater and estuaries along the coast. It is a green material that composed of at least 95% of calcium for CaO production. In the present study, a green solid base Ca(OH)2 nanoparticles was prepared using waste clamshell (M. meretrix) via low cost wet-chemical route. The effects of wet-surfactant treatments (ethylene glycol (EG), diethyl ether (DE) and N-Cetyl-N,N,N-trimethylammonium bromide (CTAB)) on clamshell derived CaO (CS-CaO) were examined. Furthermore, the physicochemical properties of CS-CaO and surfactant treated Ca(OH)2 were analyzed using X-ray fluorescence spectrometer (XRF), X-ray diffraction spectroscopy (XRD), fourier transform spectroscopy (FT-IR), Brunauer–Emmett–Teller (BET) technique, temperature program desorption of carbon dioxide (TPD-CO2), scanning electron microscope (SEM) and transmission electron microscopy (TEM). The results showed that surfactant treatments are capable of enhancing properties of clamshell derived nano-Ca(OH)2 materials such as particle sizes, surface area and basicity. Among the surfactants, EG rendered the most significant effect on the clamshell-derived material, with surface area of 78.38 m2 g−1, basicity of 4658.8 μmol/g and nanoparticle sizes at 25–42 nm

Synthesis and catalytic activity of hydrationdehydration treated clamshell derived CaO for biodiesel production

Biodiesel has gained interest of most researchers recently as an alternative for fossil diesel fuels in promoting environmentally sustainable fuels. With the presence of base catalyst, biodiesel can be easily produced via transesterification of triglyceride with alcohol under mild reaction conditions. Utilization of green catalysts from natural waste shells for biodiesel synthesis is capable of reducing the cost of catalyst which is beneficial to overall production cost. In this study, we have developed a modified CaO catalyst from natural waste clamshell (Meretrix meretrix) via hydration–dehydration treatment for transesterification process. The effects of hydration duration on clamshell were investigated to achieve the most optimum characteristic and catalytic activity. The surface area and the basicity of the treated catalyst increased extensively with prolonged hydration duration technique. By prolonging the water treatment process, it shall allow more formation of Ca(OH)2 which then has promoted the formation of Bronsted base sites for higher basicity. The catalytic activity of hydration–dehydration treated catalysts were found increased in the following order CS-CaO12h > CS-CaO9h > CS-CaO6h > CS-CaO3h > CS-CaO1h. The triglyceride conversion was as high as 98% when utilizing CS-CaO12h under reflux conditions of methanol: oil molar ratio of 9:1, catalyst amount is 1 wt% and 2 h of reaction time

On the mechanism of the selective oxidation of n-butane, but-1-ene and but-1,3-diene to maleic anhydride over a vanadyl pyrophosphate catalyst

The mechanism of the selective partial oxidation of n-butane, but-1-ene and but-1,3-diene over a vanadyl phosphate catalyst has been investigated by temperature-programmed desorption (TPD) and by anaerobic temperature-programmed oxidation (TPO). TPD showed lattice oxygen to be desorbed in two states at 998 and 1023 K. The anaerobic TPO of n-butane produced butene and butadiene at 1020 K; anaerobic TPO of but-1-ene produced butadiene and furan at 990 K and dehydrofuran at 965 K, while anaerobic TPO of but-1,3-diene produced dehydrofuran at 970 K, furan at 1002 K and maleic anhydride at 1148 K. The total amount of oxygen removed from the lattice in these anaerobic selective partial oxidations was the same as that evolved from the vanadyl phosphate catalyst by TPD. This, and the fact that the selective oxidation reactions occurred at the same temperature at which the oxygen evolves from the lattice, suggests that the lattice oxygen is uniquely selective when it appears at the surface of the catalyst. (Under identical conditions of flow rate, weight of catalyst, heating rate etc., the reaction of n-butane or of but-1,3-diene in air produced only CO2 and H2O.

Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel

Sediment transport is a prevalent vital process in uvial and coastalenvironments, and \incipient motion" is an issue inseparably bound to this topic. Thisstudy utilizes a novel hybrid method based on Group Method of Data Handling (GMDH)and Genetic Algorithm (GA) to design GMDH structural (GMDH-GA). Also, SingularValue Decomposition (SVD) was utilized to compute the linear coefficient vectors. Inorder to predict the densimetric Froude number (Fr), the ratio of median diameter ofparticle size to hydraulic radius (d=R) and the ratio of sediment deposit thickness tohydraulic radius (ts=R) are utilized as e ective parameters. Using three di erent sources ofexperimental data and GMDH-GA model, a new equation is proposed to predict incipientmotion. The performance of development equation is compared using GMDH-GA andtraditional equations . The results indicate that the presented equation is more accurate(RMSE= 0:18 andMAPE= 6:48%) than traditional methods. Also, a sensitivityanalysis is presented to study the performance of each input combination in predictingincipient motion (15) Development of Group Method of Data Handling based on Genetic Algorithm to predict incipient motion in rigid rectangular storm water channel