Programming Procedure Research Articles

Qualitative to Quantitative Non-Destructive Evaluation: A Concept for D-Sight Inspections of Aircraft Structures

Non-destructive evaluation of structures is a key procedure in operation of aircraft structures, necessary to maintain their quality and integrity. Numerous non-destructive testing (NDT) techniques have been adapted to inspect aircraft structures and are currently used according to appropriate protocols. However, many of them provide only qualitative results, such as the D-Sight optical NDT technique used for inspections in aviation. In this study, a concept of improvement of the D-Sight technique is proposed by means of appropriate experimental program and processing procedures applied to the resulting images from inspection. It was demonstrated that appropriately selected processing methods may allow assessing damage quantitatively and improve the overall sensitivity and applicability of a given NDT technique.

Data and model hybrid-driven virtual reality robot operating system

To realize efficient remote human-computer interaction of robots, a robot remote operating system based on virtual reality and digital twin is proposed. The system builds a digital twin model based on the Unity 3D engine to establish a connection with the robot entity, assisting the online remote programming and real-time manipulation of the robot unit. The system uses HTC VIVE to build a virtual reality framework. To actualize the mutual drive between the real space and the virtual space, a mathematical model of the robot is constructed through the forward and inverse kinematics of the robot. Through the combination of eye-tracking-based eye movement interaction and the unique controller interaction of virtual reality system, a multi-sensory multi-input collaborative interaction method is accomplished. The method realizes the robot joints driving of users using multiple interaction methods simultaneously, simplifies the robot programming and control procedure, and optimizes the operation experience. Tests demonstrate that the system is capable of effectively providing monitoring, teleoperation and programming services for remote interaction of robots.

Evaluating simplified macromodeling approaches of simulating infilled reinforced concrete frames with openings

AbstractSimulating the contribution of masonry infills on the reaction of reinforced concrete (RC) frames have been the concentration point of numerous numerical studies. However, the effects of openings are often neglected by technical codes, which may lead to sensible errors in predicting the seismic behavior of masonry infilled frames. In this study, the simplified macromodeling approaches of equivalent diagonal strut model (EDSM) and two‐dimensional discrete macroelement model (DMEM) compared to a finite element model (FEM) and the influence of the modeling approach on the lateral response of infilled frames, with different percentages of openings, was investigated. A nonlinear static pushover analysis for conveying the terms of the monotonic loading procedure of the benchmark experimental program has been employed. Concerning the results, the stiffness of the masonry infilled frames by increasing the amount of opening was decreasing. The outcomes of this study may increase the knowledge of comparing the possible methods for modeling masonry infilled frames with openings.

Admissible Region of Renewable Generation Ensuring Power Flow Solvability in Distribution Networks

The uncertainty of renewable generation makes the operating status of distribution systems more volatile, as fully controllable resource at the distribution level is rare. A dispatchable region refers to the set that consists of all admissible patterns of nodal renewable power injections under which the power flow is solvable without violating security bound constraints. This article studies the dispatchable region in distribution networks under alternating current power flow model. A rank minimization problem is proposed to test power flow solvability under a fixed nodal power injection pattern, providing basic operation to construct the exact dispatchable region. A sequential low-order semidefinite programming procedure is developed to solve the problem. Furthermore, based on a global outer approximation of the second-order conic relaxation of the distflow model, a linear programming-based polyhedral projection algorithm is developed to calculate an outer approximation of the dispatchable region. The projection algorithm is also applied to the traditional linearized distflow model. Combining the feasibility test procedure, it is shown that the intersection of the respective dispatchable regions obtained from two linearized power flow models produces a fairly accurate approximation for the true dispatchable region under the exact nonlinear distflow model. The proposed method is an extension of existing studies on security assessment for distribution systems under uncertainty.

Probabilistics Design and Analysis of Metal Interference Fits

This paper presents the press fit calculation that depends on different methods, the sizes of holes and shafts are quantities distributed according to the normal law, so the tolerance of the joint between the shaft and the hub is also distributed according to the normal law with two parameters: the mean value and the standard deviation. The paper also demonstrates the procedure and computer program for calculating the metal interference joints given by the probability method, thereby giving a chart of choosing tolerance depending on the applied load, simultaneously calculating the interference joints by the min-max method, and comparing it with the probability method, etc. Calculation by the probability method gives more reasonable working parameters. Along with the interference fit parameters, the consideration of materials is mentioned as well.

Inverse Markov decision processes with unknown transition probabilities

Inverse optimization involves recovering parameters of a mathematical model using observed values of decision variables. In Markov Decision Processes (MDPs), it has been applied to estimate rewards that render observed policies optimal. A counterpart is not available for transition probabilities. We study two variants of this problem. First, the decision-maker wonders whether there exist a policy and transition probabilities that attain given target values of expected total discounted rewards over an infinite horizon. We derive necessary and sufficient existence conditions, and formulate a feasibility linear program whose solution yields the requisite policy and transition probabilities. We extend these results when the decision-maker wants to render the target values optimal. In the second variant, the decision-maker wishes to find transition probabilities that make a given policy optimal. The resulting problem is nonconvex bilinear, and we propose tailored versions of two heuristics called Convex-Concave Procedure and Sequential Linear Programming (SLP). Their performance is compared via numerical experiments against an exact method. Computational experiments on randomly generated MDPs reveal that SLP outperforms the other two both in runtime and objective values. Further insights into SLP’s performance are derived via numerical experiments on inverse inventory control, equipment replacement, and multi-armed bandit problems.

MSEMT: An Advanced Modelica Library for Power System Electromagnetic Transient Studies

Electromagnetic Transient (EMT) simulation tools are typically developed using conventional procedural programming languages. On the other hand, modern high-level and equation-based programming languages, such as Modelica, are currently available. Modelica allows formulating models that are easy to develop, maintain and understand by expressing what needs to be computed without stating how it should be computed. This paper presents a Modelica-based simulator for electromagnetic transients. It is demonstrated that this approach offers significant advantages for developing sophisticated models. Computational performance and accuracy are compared to a conventional EMT-type simulation tool.

Creating a General-Purpose Procedural Language for Programming in Kannada

Abstract: To build a general-purpose procedural programming language in Kannada and the corresponding header file that understands the language and pre-processes the code typed in Kannada into C++ programming language which can then be compiled by a C++ compiler and produce corresponding output in Kannada. The entire compilation of the language will be built in a single and Integrated Development Environment (IDE) i.e. Microsoft Visual Studio which can be downloaded by anyone and start learning to code in Kannada by including the header file. Any programming logic can be typed entirely in Kannada, the syntax is created such that it is similar to C-syntax. Any person knowing Kannada and with little effort on understanding the language’s syntax can start coding in Kannada without any prior knowledge in English or programming. This paper aims mainly at providing its users a programming experience in a regional language “Kannada”. The users can edit, complier and thus observe the results also in Kannada. The user has to abide by a set of syntactic rules and thus program accordingly for better results.

A First-Order Complete Temporal Logic for Structured Context-Free Languages

The problem of model checking procedural programs has fostered much research towards the definition of temporal logics for reasoning on context-free structures. The most notable of such results are temporal logics on Nested Words, such as CaRet and NWTL. Recently, the logic OPTL was introduced, based on the class of Operator Precedence Languages (OPLs), more powerful than Nested Words. We define the new OPL-based logic POTL and prove its FO-completeness. POTL improves on NWTL by enabling the formulation of requirements involving pre/post-conditions, stack inspection, and others in the presence of exception-like constructs. It improves on OPTL too, which instead we show not to be FO-complete; it also allows to express more easily stack inspection and function-local properties. In a companion paper we report a model checking procedure for POTL and experimental results based on a prototype tool developed therefor. For completeness a short summary of this complementary result is provided in this paper too.

PENDIDIKAN DASAR SEBAGAI PERINTIS TERDEPAN DALAM PENGUATAN KARAKTER MUSLIM

Basic Education as a leading pioneer in Strengthening Muslim Character has a relationship with character education. The implementation of Strengthening Character Education is carried out with the principle of school-based management which is the responsibility of school principals and teachers, as the fulfillment of the workload of teachers and school principals (Article 6 paragraph 3,4,5 PP 87/2017). According to President Joko Widodo's directive, character education at the basic education level gets a larger portion than education that teaches knowledge, for Elementary Schools by 70% while for Junior High Schools by 60%. The point of this research is management of strengthening characters education in elementary schools are includes planning, implementation and evaluation. The research method is descriptive qualitative through observation, documentation and interview.The result of this research obtained depiction that the first,the reinforcement of character education students have been implemented well through the preparation of goals, strategy and policy mapping and procedure mapping and program improvement using RPP and syllabus design; second, the implementation of character education runs well through activities of religious activities, nationalism cultivation, social care and environmental awareness; third, evaluation of the strengthening of character education management students through supervision activities on the implementation of activities by carrying out reflections, analysis and follow-up plans.

Timeline: The Evolution of Fellowship Training in Micrographic Surgery and Dermatologic Oncology.

The Accreditation Council for Graduate Medical Education (ACGME) granted accreditation to the first 5 Procedural Dermatology Fellowship Training Programs in 2004. The name of the training program was changed from Procedural Dermatology to Micrographic Surgery and Dermatologic Oncology by the ACGME/Residency Review Committee for Dermatology in 2014. The American Board of Dermatology/American Board of Medical Specialties conducted the first certification examination in Micrographic Dermatology Surgery in October 2021. This article chronicles the history and development of the subspecialty. J Drugs Dermatol. 2022;21(8):861-863.: doi:10.36849/JDD.6933.

A δ

Over the last decade, automatic differentiation (AD) has profoundly impacted graphics and vision applications --- both broadly via deep learning and specifically for inverse rendering. Traditional AD methods ignore gradients at discontinuities, instead treating functions as continuous. Rendering algorithms intrinsically rely on discontinuities, crucial at object silhouettes and in general for any branching operation. Researchers have proposed fully- automatic differentiation approaches for handling discontinuities by restricting to affine functions, or semi- automatic processes restricted either to invertible functions or to specialized applications like vector graphics. This paper describes a compiler-based approach to extend reverse mode AD so as to accept arbitrary programs involving discontinuities. Our novel gradient rules generalize differentiation to work correctly, assuming there is a single discontinuity in a local neighborhood, by approximating the prefiltered gradient over a box kernel oriented along a 1D sampling axis. We describe when such approximation rules are first-order correct, and show that this correctness criterion applies to a relatively broad class of functions. Moreover, we show that the method is effective in practice for arbitrary programs, including features for which we cannot prove correctness. We evaluate this approach on procedural shader programs, where the task is to optimize unknown parameters in order to match a target image, and our method outperforms baselines in terms of both convergence and efficiency. Our compiler outputs gradient programs in TensorFlow, PyTorch (for quick prototypes) and Halide with an optional auto-scheduler (for efficiency). The compiler also outputs GLSL that renders the target image, allowing users to interactively modify and animate the shader, which would otherwise be cumbersome in other representations such as triangle meshes or vector art.

Phase Transitions in Recovery of Structured Signals From Corrupted Measurements

This paper is concerned with the problem of recovering a structured signal from a relatively small number of corrupted random measurements. Sharp phase transitions have been numerically observed in practice when different convex programming procedures are used to solve this problem. This paper is devoted to presenting theoretical explanations for these phenomena by employing some basic tools from Gaussian process theory. Specifically, we identify the precise locations of the phase transitions for both constrained and penalized recovery procedures. Our theoretical results show that these phase transitions are determined by some geometric measures of structure, e.g., the spherical Gaussian width of a tangent cone and the Gaussian (squared) distance to a scaled subdifferential. By utilizing the established phase transition theory, we further investigate the relationship between these two kinds of recovery procedures, which also reveals an optimal strategy (in the sense of Lagrange theory) for choosing the tradeoff parameter in the penalized recovery procedure. Numerical experiments are provided to verify our theoretical results.

POp: Parameter Optimization of Differentiable Vector Patterns

AbstractProcedural materials are extensively used in computer graphics, since they provide editable, resolution‐independent representation of textures. However, tuning the parameters of procedural generators to achieve a desired result remains time‐consuming for users. Recently, inverse procedural material algorithms have been developed, exploiting differentiable rendering methods to find the parameters of a procedural model that match a target image. These approaches focus on raster textures. We propose pOp, a practical method for estimating the parameters of vector patterns, that are formed by collections of vector shapes arranged by an arbitrary procedural program. In our approach, patterns are defined as arbitrary programs, that control the translation, rotation and scale or vector graphics elements. We support elements typical of vector graphics, namely points, lines, circle, rounded rectangles, and quadratic Bèzier drawings, in multiple colors. We optimize the program parameters by automatically differentiating the signed distance field of the drawing, which we found to be significantly more reliable than using differentiable rendering of the final image. We demonstrate our method on a variety of cases, representing the variations found in structured vector patterns.

Pendampingan Penyusunan Standar Operasional Prosedur (SOP) Pengembangan Program Bapak Angkat Dinas PPKUKM DKI Jakarta

This assistance activity in the preparation of Standard Operating Procedures (SOP) of Foster Father's Program a community service activity that aims to produce a draft SOP of Foster Father's Program at the Industry and Trade Office of Small and Medium Enterprise Cooperatives (PPKUKM) of DKI Jakarta Province, as well as improving understanding related to the theory, principles, and techniques for preparing SOP in accordance with government regulations. A SOP is a written manual. Participants of this activity came from 5 private universities in Jakarta and one of them was Bakrie University which together with the PPKUKM Office actively participated in the SOP development socialization event in March 2021 using mentoring methods. The activity of preparing the SOP for the Development of Foster Father's Program begins with the activity of compiling and collecting materials, after which the material or material activities, then continued by formulating the Operational Standard of The Development Procedure of Development Foster Father's Program.

A Study on Application of Linear Programming on Product Mix for Profit Maximization and Cost Optimization

Objectives: This research aims to sneak into the retailer\'s perception about that customer segment and plan a product mix accordingly. The focus is on small players in small towns not having deep pockets to synergize the product mix decisions effectively. Methods: The data used in this research paper is from Hatchers, a medium-sized enterprise with zero budget for software for product mix decisions. The data was collected through face-to-face interviews with ten representatives and five supervisors in compliance with the existing documents and existing datasheet obtained from the production department, which was slightly updated to make the final output. The data was for one season, i.e., April to March. The data was analyzed to study pre-Linear Programming and post-Linear Programing profits. Findings: This examination distinguishes the current asset usage level and the benefit of every period of one of the apparel producing organizations, utilizing a linear programming procedure. Actual consumption of resources (product wise) was calculated to evaluate profit post applying Linear Programing to see the wastage and cost. There was a 54% increase post LP compared to the product-wise resource utilization. Similarly, the profit using Linear programming was more than double as wastage and costing were minimum, and revenue was high. Novelty: The article focused on the simple basic principle of linear programming for identifying product mix using Excel(Solver). LINGO. The software solutions become costlier for small firms, whereas Excel is more accessible and cost-efficient. There is a gap in existing literature as previous research has not focused on this aspect for small business houses where adapting software solutions is challenging. Keywords: Linear Programming, Profit maximization, Product Mix, Production, cost optimization

Switch-based hybrid beamforming for massive MIMO communications in mmWave bands

Switch-based hybrid networks provide a promising implementation for beamforming in large-scale millimeter wave (mmWave) antenna arrays by reducing both complexity and power consumption. However, the design of the optimum beamformer in the analog domain is a difficult task due to the binary nature of the switch-based structure. In this work, we tackle this problem, proposing a new approach that decouples the joint optimization of the analog and digital beamformers and confines the problem to a rank-constrained subspace to give an approximate solution. We then describe two algorithms for solving the resulting optimization: the first employs norm maximization and the second utilizes majorization. In the norm maximization method, we present a modified sequential convex programming(SCP) procedure that maximizes the mutual information while addressing the mismatch incurred from approximating the log-determinant by a Frobenius norm. The second method employs a lower bound on the mutual information by QR factorization. Furthermore, unlike previous approaches, we introduce a general strategy for dealing with partially-connected structures using linear constraints. We verify the effectiveness of the proposed methods through several numerical examples and show that they closely track the spectral efficiency provided by the unconstrained optimal beamformer while outperforming the switch-based design by unified greedy algorithm.

Fraction distribution and dynamic cycling of phosphorus in lacustrine sediment at Inexpressible Island, Antarctica.

Phosphorus (P) chemistry and its dynamic cycling are essential for understanding aquatic primary productivity and ecosystem structure. However, there is a lack of knowledge on P chemistry in pristine aquatic ecosystems, such as in Antarctica. Here, we applied the Standards, Measurements and Testing Program (SMT) procedure and nuclear magnetic resonance spectroscopy (NMR) to reveal P speciation in two types of lacustrine sediment cores collected from Inexpressible Island, Ross Sea, East Antarctica. The Positive Matrix Factorization Model and Generalized Additive Models were applied to quantitatively identify the P sources and estimate relative effects of various environmental factors on the speciation. Our results demonstrate that orthophosphate, mainly as Ca-P, is the major component and the ortho-monoesters are the predominant organic phosphorus (OP) form in lacustrine sediments. Ornithogenic lacustrine sediments have a higher content of P as Ca-P than sediments with little or no penguin influence. Our model further suggests that penguin guano is the most important source for Ca-P, accounting for 80%, while detrital input is the predominant source for Fe/Al-P (up to 90%). The content of ortho-monoesters, as revealed by NMR, declines with depth, reflecting mineralization process of OP in the sediments. Moreover, we observed higher relative proportions of organic P in the sediments with little guano influence and the deposition of organic P are likely facilitated by microbial mats. Overall, our data suggest that burial of P in Antarctic lakes is sensitive to different P sources and sedimentary environments. The relatively higher bioavailable phosphorus in lacustrine sediments largely controls growth of aquatic microbial mats in oligotrophic lakes and ponds in Antarctica. The sediment profile data also indicate that P burial increased during the Medieval Climate Anomaly period, and climate warming is more conducive to P burial through the expansion of penguin populations and productivity of microbial mats. Our findings represent the first systematic understanding of natural P cycling dynamics and its main controlling factors in pristine ponds with different organic sources in Antarctica.

Frequency stability-based controlled islanding scheme based on clustering algorithm and electrical distance using real-time dynamic criteria from WAMS data

This paper presents online criteria of frequency stability-based controlled islanding scheme based on the density-based clustering algorithm and the system electrical distance from wide-area measuring system (WAMS) data. For this issue, at each time window, based on evaluating the correlation coefficient criteria between all two pairs of synchronous generators (SGs), the possible coherent generator groups are identified. Next, by using clustering algorithm, the identified coherent SGs are clustered and sorted through online working mode. In this case, an online index is proposed which and developed index in the form of mixed-integer linear programming (MILP) which through real-time evaluations, the system frequency stability is evaluated. In the use of MILP processes, the network electrical distance is considered as the main objective function (OF) which by solving the proposed OF through minimum criteria, proper islanding locations are identified. Finally, at the post-islanding period, a nonlinear programming (NLP) procedure is performed through each individual islands where corresponding proper operational feasibilities are satisfied. In this case of transient stability criteria, based on the coherent SGs located at each island, the stability criteria is preserved through coherent groups as the core of islands. Also, by allocating proper load buses based on the SGs governor capacities, the islands frequency stabilities are controlled through acceptable regions. The effectiveness of the proposed scheme is carried through two IEEE 39-bus test system and Iran practical power grid. Results present the effectiveness of the proposed approach through different islanding conditions.

Improving Estimates Accuracy of Voter Transitions. Two New Algorithms for Ecological Inference Based on Linear Programming

The estimation of RxC ecological inference contingency tables from aggregate data is one of the most salient and challenging problems in the field of quantitative social sciences, with major solutions proposed from both the ecological regression and the mathematical programming frameworks. In recent decades, there has been a drive to find solutions stemming from the former, with the latter being less active. From the mathematical programming framework, this paper suggests a new direction for tackling this problem. For the first time in the literature, a procedure based on linear programming is proposed to attain estimates of local contingency tables. Based on this and the homogeneity hypothesis, we suggest two new ecological inference algorithms. These two new algorithms represent an important step forward in the ecological inference mathematical programming literature. In addition to generating estimates for local ecological inference contingency tables and amending the tendency to produce extreme transfer probability estimates previously observed in other mathematical programming procedures, these two new algorithms prove to be quite competitive and more accurate than the current linear programming baseline algorithm. Their accuracy is assessed using a unique dataset with almost 500 elections, where the real transfer matrices are known, and their sensitivity to assumptions and limitations are gauged through an extensive simulation study. The new algorithms place the linear programming approach once again in a prominent position in the ecological inference toolkit. Interested readers can use these new algorithms easily with the aid of the R package lphom.