Benzylammonium-Mediated Formamidinium Lead Iodide Perovskite Phase Stabilization for Photovoltaics

There is an ongoing surge of interest in the use of formamidinium (FA) lead iodide perovskites in photovoltaics due to their exceptional optoelectronic properties. However, thermodynamic instability of the desired cubic perovskite (α-FAPbI₃) phase at ambient conditions leads to the formation of a yellow non-perovskite (δ-FAPbI₃) phase that compromises its utility. A stable α-FAPbI₃ perovskite phase is achieved by employing benzylammonium iodide (BzI) and the microscopic structure is elucidated by using solid-state NMR spectroscopy and X-ray scattering measurements. Perovskite solar cells based on the FAPbI₃(BzI)_0.25 composition achieve power conversion efficiencies exceeding 20%, which is accompanied by enhanced shelf-life and operational stability, maintaining 80% of the performance after one year at ambient conditions.     

Detecting and Classifying Darknet Traffic Using Deep Network Chains

The anonymity of the darknet makes it attractive to secure communication lines from censorship. The analysis, monitoring, and categorization of Internet network traffic are essential for detecting darknet traffic that can generate a comprehensive characterization of dangerous users and assist in tracing malicious activities and reducing cybercrime. Furthermore, classifying darknet traffic is essential for real-time applications such as the timely monitoring of malware before attacks occur. This paper presents a two-stage deep network chain for detecting and classifying darknet traffic. In the first stage, anonymized darknet traffic, including VPN and Tor traffic related to hidden services provided by darknets, is detected. In the second stage, traffic related to VPNs and Tor services is classified based on their respective applications. The methodology of this paper was verified on a benchmark dataset containing VPN and Tor traffic. It achieved an accuracy of 96.8% and 94.4% in the detection and classification stages, respectively. Optimization and parameter tuning were performed in both stages to achieve more accurate results, enabling practitioners to combat alleged malicious activities and further detect such activities after outbreaks. In the classification stage, it was observed that the misclassifications were due to the audio and video streaming commonly used in shared real-time protocols. However, in cases where it is desired to distinguish between such activities accurately, the presented deep chain classifier can accommodate additional classifiers. Furthermore, additional classifiers could be added to the chain to categorize specific activities of interest further.     

An Approximate Numerical Methods for Mathematical and Physical Studies for Covid-19 Models

The advancement in numerical models of serious resistant illnesses is a key research territory in different fields including the nature and the study of disease transmission. One of the aims of these models is to comprehend the elements of conduction of these infections. For the new strain of Covid-19 (Coronavirus), there has been no immunization to protect individuals from the virus and to forestall its spread so far. All things being equal, control procedures related to medical services, for example, social distancing or separation, isolation, and travel limitations can be adjusted to control this pandemic. This article reveals some insights into the dynamic practices of nonlinear Coronavirus models dependent on the homotopy annoyance strategy (HPM). We summon a novel sign stream chart that is utilized to depict the Coronavirus model. Through the numerical investigations, it is uncovered that social separation of the possibly tainted people who might be conveying the infection and the healthy virus-free people can diminish or interrupt the spread of the infection. The mathematical simulation results are highly concurrent with the statistical forecasts. The free balance and dependability focus for the Coronavirus model is discussed and the presence of a consistently steady arrangement is demonstrated.     

Low-Cost IMU Sensors for Satellite Maturity Improvement

The satellite technology proves its impact in the modern era with its wide benefits and applications. However, the cost of the development in this field presents gaps in many countries, almost the developed countries. Therefore, this paper provides a rich platform around low-cost sensors in order to improve maturity in space technology, mostly the system of attitude determination and control. The development of this knowledge turns out to be very interesting in order to achieve a space mission which leads to the progression of the spatial technology readiness level (TRL) defined by the international measurement scale which is able to estimate the technological maturity. Thus, the idea is carried out for the development of low-cost sensors’ system for attitude determination around an Arduino board. A sensor fusion method was applied on three types of sensors: accelerometer, magnetometer, and gyroscope in order to detect the reliable orientation. It is aimed to apply quaternion based Kalman filter on different platform than previous systems. It is succeeded therefore to improve measurement accuracy around low-cost sensor to achieve the main goal of this paper.     

Experimental evaluation of various register‐pressure‐reduction heuristics

Minimizing the amount of spill code is still an open problem in code generation and optimization. The amount of spill code depends on both the register allocation algorithm and the pre‐allocation instruction scheduling algorithm that controls the register pressure. In this paper, we focus on the impact of pre‐allocation instruction scheduling on the amount of spill code. Many heuristic techniques have been proposed to do instruction scheduling with the objective of minimizing register pressure and consequently the amount of spill code. However, the performance of these heuristic techniques has not been studied relative to optimality on real large‐scale programs. In this paper, we present an experimental study that evaluates the performance of several pre‐allocation scheduling heuristics. The evaluation involves computing an experimental lower bound on the size of gap between each heuristic's performance and optimal performance. We also propose a simple heuristic technique based on a specific permutation of two basic priority schemes and experimentally evaluate the performance of this technique compared with other heuristics, including the heuristics implemented in the LLVM open‐source Compiler. The evaluation is carried out by running SPEC CPU2006 on real x86‐64 hardware and measuring both the amount of spill code and the execution time. The results of our study show that the proposed heuristic technique gives better overall performance than LLVM's best heuristic on x86‐64, although it produces slightly more spilling. The proposed heuristic has better overall performance, because it achieves a better balance between register pressure and instruction‐level parallelism (ILP). This result shows the importance of ILP in pre‐allocation scheduling even on out‐of‐order machines. Furthermore, the results of the study show that there is a large gap between the performance of any of the studied heuristics and optimal performance; even the best heuristic in the study produces significantly more spill code than the optimal amount. This experimental result quantifies the intuitive belief that it is unlikely to find a heuristic that works well in all cases, thus showing the need for more rigorous solutions using combinatorial approaches. The paper discusses the challenges and complexities that are involved in developing such rigorous solutions. Copyright © 2014 John Wiley & Sons, Ltd.     

Session types for safe Web service orchestration

We address the general problem of interaction safety in Web service orchestrations. By considering an essential subset of the BPEL orchestration language, we define SeB, a session based style of this subset. We discuss the formal semantics of SeB and present its main properties. We take a new approach to address the formal semantics which is based on a translation into so-called control graphs. Our semantics accounts for BPEL control links and addresses the static semantics that prescribes the valid usage of variables. We also provide the semantics of service configurations.During a session, a client and a service can engage in a complex series of interactions. By means of the provided semantics, we define precisely what is meant by interaction safety. We then introduce session types in order to prescribe the correct orderings of these interactions. Service providers must declare their provided and required session types. We define a typing algorithm that checks if a service orchestration behaves according to its declared provided and required types.Using a subtyping relation defined on session types, we show that any configuration of well-typed service partners with compatible session types are interaction safe, i.e., involved partners never receive unexpected messages.     

Reducing covariate factors of gait recognition using feature selection and dictionary-based sparse coding

Human gait recognition is a behavioral biometrics method that aims to determine the identity of individuals through the manner and style of their distinctive walk. It is still a very challenging problem because natural human gait is affected by many covariate factors such as changes in the clothing, variations in viewing angle, and changes in carrying condition. This paper evaluates the most important features of gait under the carrying and clothing conditions. We find that the intra-class variations of the features that remain static during the gait cycle affect the recognition accuracy adversely. Thus, we introduce an effective and robust feature selection method based on the gait energy image. The new gait representation is less sensitive to these covariate factors. We also propose an augmentation technique to overcome some of the problems associated with the intra-class gait fluctuations, as well as if the amount of the training data is relatively small. Finally, we use dictionary learning with sparse coding and linear discriminant analysis to seek the best discriminative data representation before feeding it to the Nearest Centroid classifier. When our method is applied on the large CASIA-B gait data set, we are able to outperform existing gait methods by achieving the highest average result.     

A complete multi-robot path-planning algorithm

In the domain of multi-robot path-planning problems, robots must move from their start locations to their goal locations while avoiding collisions with each other. The research problem that we addressed is to find a complete solution for the multi-robot path-planning problem. Our first contribution is to recognize the solvable instances of the problem with our solvability test; the theoretical analysis has already been provided to show the validity of this test. Our second contribution is to solve this problem completely, in polynomial time, with the Push and Spin (PASp) algorithm. Once the problem was solved, we found decisions within the complete solution that may improve the performance of the complete algorithm. Hence, our third contribution is to improve the performance by selecting the best path from the set of complete paths. We refer to the improved version of our algorithm as the improved PASp algorithm. In terms of the completeness evaluation, the mathematical proofs demonstrate that the PASp is a complete algorithm for a wider class of problem instances than the classes solved by the Push and Swap (PAS), Push and Rotate (PAR), Bibox or the tractable multi-robot path-planning (MAPP) algorithms. Moreover, PASp solves any graph recognized to be solvable without any assumptions. In addition, the theoretical proof of the PASp algorithm showed completive polynomial performance in terms of total-path-lengths and execution time. In our performance evaluation, the experimental results showed that the PASp performs competitively, in reasonable execution time, in terms of number of moves compared to the PAS, PAR, Bibox and MAPP algorithms on a set of benchmark problems from the video-game industry. In addition, the results showed the scalability and robustness of PASp in problems that can be solved only by PASp. Such problems require high levels of coordination with an efficient number of moves and short execution time. In grid and bi-connected graphs with too many cycles, PASp required more moves and more time than the PAS, PAR and Bibox algorithms. However, PASp is the only algorithm capable of solving such instances with only one unoccupied vertex. Furthermore, adding heuristic search and smooth operation to the improved PASp showed significant further improvement by reducing the number of moves for all problem instances. PASp produced the best plans in a bit higher time. Finally, the PASp algorithm solves a wider class of problems and performs more completely in very complex/crowded environments than other state-of-art algorithms. Additionally, the Spin operation introduces a novel swapping technique to exchange two items and restore others in a graph for industrial applications.     

Modeling low mach number reacting flow with detailed chemistry and transport

An efficient projection scheme is developed for the simulation of reacting flow with detailed kinetics and transport. The scheme is based on a zero-Mach-number formulation of the compressible conservation equations for an ideal gas mixture. It relies on Strang splitting of the discrete evolution equations, where diffusion is integrated in two half steps that are symmetrically distributed around a single stiff step for the reaction source terms. The diffusive half-step is integrated using an explicit single-step, multistage, Runge-Kutta-Chebyshev (RKC) method. The resulting construction is second-order convergent, and has superior efficiency due to the extended real-stability region of the RKC scheme. Two additional efficiency-enhancements are also explored, based on an extrapolation procedure for the transport coefficients and on the use of approximate Jacobian data evaluated on a coarse mesh. We demonstrate the construction in 1D and 2D flames, and examine consequences of splitting errors. By including the above enhancements, performance tests using 2D computations with a detailed C₁C₂ methane-air mechanism and a mixture-averaged transport model indicate that speedup factors of about 15 are achieved over the starting split-stiff scheme.