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With additive manufacturing (AM) processes such as Wire Arc Additive Manufacturing (WAAM), components with complex shapes or with functional properties can be produced, with advantages in the areas of resource conservation, lightweight construction, and load-optimized production. However, proving component quality is a challenge because it is not possible to produce 100% defect-free components. In addition to this, statistically determined fluctuations in the wire quality, gas flow, and their interaction with process parameters result in a quality of the components that is not 100% reproducible. Complex testing procedures are therefore required to demonstrate the quality of the components, which are not cost-effective and lead to less efficiency. As part of the project "3DPrintFEM", a sound emission analysis is used to evaluate the quality of AM components. Within the scope of the project, an approach was being developed to determine the quality of an AM part dependent not necessarily on its geometry. Samples were produced from WAAM, which were later cut and milled to precision. To determine the frequencies, the samples were put through a resonant frequency test (RFM). The unwanted modes were then removed from the spectrum produced by the experiments by comparing it with FEM simulations. Later, defects were introduced in experimental samples in compliance with the ISO 5817 guidelines. In order to create a database of frequencies related to the degree of the sample defect, they were subjected to RFM. The database was further augmented through frequencies from simulations performed on samples with similar geometries, and, hence, a training set was generated for an algorithm. A machine-learning algorithm based on regression modelling was trained based on the database to sort samples according to the degree of flaws in them. The algorithm's detectability was evaluated using samples that had a known level of flaws which forms the test dataset. Based on the outcome, the algorithm will be integrated into an equipment developed in-house to monitor the quality of samples produced, thereby having an in-house quality assessment routine. The equipment shall be less expensive than conventional acoustic equipment, thus helping the industry cut costs when validating the quality of their components. [ABSTRACT FROM AUTHOR]

The modular multilevel converter (MMC) has many advantages of low switching losses, good harmonic performance and high modularity structure in state-of-the-art HVDC applications. The full-bridge submodules (FBSMs) of the hybrid MMC can inherently output negative voltage to absorb fault currents, and consequently the hybrid MMC can ride through severe DC faults without blocking. During the DC fault-ride-through process, the submodule capacitor voltage and arm current of the MMC will be temporarily increased. These characteristics limit the proportion of the FBSMs, which should not be too low and thus increase the cost and operating losses of the hybrid MMC. In this paper, an improved sorting algorithm of SM capacitor voltage is established, and a novel virtual damping control strategy is proposed that can effectively suppress the increase in submodule capacitor voltage and arm current of the hybrid MMC during the DC fault-ride-through process. By adopting this optimization control, the proportion of FBSMs can be reduced significantly without deteriorating the fault-ride-through capability or safety of the MMC. The effectiveness of the proposed control is verified by careful theoretical analysis and detailed simulation results. [ABSTRACT FROM AUTHOR]

BACKGROUND: The gangue content in coal seriously affects the calorific value produced by its combustion. In practical applications, gangue in coal needs to be completely separated. The pseudo-dual-energy X-ray method does not have high sorting accuracy. OBJECTIVE: This study aims to propose a novel multi-dimensional coal and gangue X-ray sorting algorithm based on CdZnTe photon counting detectors to solve the problem of coal and gangue sorting by X-ray. METHODS: This complete algorithm includes five steps: (1) Preferred energy bins, (2) transmittance sorting, (3) one-dimensional R-value sorting, (4) two-dimensional R-value sorting, and (5) three-dimensional R-value sorting. The output range of each step is determined by prior information from 65 groups of coal and gangue. An additional 110 groups of coal and gangue are employed experimentally to validate the algorithm's accuracy. RESULTS: Compared with the 60% sorting accuracy of the Pseudo-dual-energy method, the new algorithm reached a sorting accuracy of 99%. CONCLUSIONS: Study results demonstrate the superiority of this novel algorithm and its feasibility in practical applications. This novel algorithm can guide other two-substance X-ray sorting applications based on photon counting detectors. [ABSTRACT FROM AUTHOR]

Finding methods to teach sorting algorithms is a challenge for most Computer Science teachers, but also for students who are open to learn and search for information. Because nowadays students are very receptive to educational software, we want to introduce our instrument named ALSort – a software designed for teachers and students interested in the instructional process of sorting algorithms. ALSort is an educational software based on gamification and modelling. It is built on six stages of challenges related to the six levels of learning from the Revised Bloom Taxonomy and the version from this paper is a prototype. [ABSTRACT FROM AUTHOR]

• A new event-driven sorting algorithm-based merging Monte Carlo (SAMMC) method is developed for solving aerosol dynamics. • Neighbour merging method is proposed to maintain a constant-number and constant-volume scheme, and population information. • Both absolute volume difference (AVD) and relative volume difference (RVD) are used as the crucial merging criteria. • The stochastic errors and computational time of SAMMC method are quantitatively compared with previous MC methods. • The AVD- and RVD-based SAMMC methods show very high computational accuracy and efficiency in all aerosol dynamic processes. A new event-driven sorting algorithm-based merging Monte Carlo (SAMMC) method is proposed and developed for solving the general dynamic equation in aerosol dynamics. A neighbour merging method is proposed to maintain a constant-volume and constant-number scheme with minimal interference to the numerical particle population, where absolute volume difference (AVD) and relative volume difference (RVD) are used as the crucial merging criteria. The SAMMC method can be used for simulating all aerosol dynamic processes with very high computational accuracy, especially effective in those aerosol dynamic processes generating additional numerical particles. In the present study, comprehensive computational conditions are used to study their impacts on computational accuracy and efficiency by comparing the SAMMC method to previous MC methods and analytical solutions. Numerical results show that the SAMMC method has excellent agreement with analytical solutions for all specified cases of different aerosol dynamic processes and shows higher computational accuracy than equal-weight-based MC methods. In addition, the computational accuracy of the SAMMC method in the total particle number concentration is much higher than those of the weighted fraction Monte Carlo (WFMC) method and sorting algorithm-based merging weighted fraction Monte Carlo (SAMWFMC) method in non-homogeneous coagulation. The SAMMC method can also achieve the same computational precision as the multi-Monte Carlo (MMC) method at only slightly higher computational cost in homogeneous coagulation. More importantly, the SAMMC method can deal with breakage-related processes and simultaneous coagulation and nucleation with very high computational accuracy and efficiency, while the numerical results of the MMC method may significantly deviate from analytical solutions due to the introduction of systematic errors. Furthermore, the RVD can achieve higher computational accuracy in multi-breakage modelling than AVD, but AVD and RVD have almost the same computational efficiency and accuracy in other aerosol dynamic processes. [ABSTRACT FROM AUTHOR]

The order-of-addition (OofA) experiment has received a great deal of attention in the recent literature. The primary goal of the OofA experiment is to identify the optimal order in a sequence of m components. All the existing methods are model-dependent and are limited to small number of components. The appropriateness of the resulting optimal order heavily depends on (a) the correctness of the underlying assumed model, and (b) the goodness of model fitting. Moreover, these methods are not applicable to deal with large m (e.g., m ≥ 7 ). With this in mind, this article proposes an efficient adaptive methodology, building upon the quick-sort algorithm, to explore the optimal order without any model specification. Compared to the existing work, the run sizes of the proposed method needed to achieve the optimal order are much smaller. Theoretical supports are given to illustrate the effectiveness of the proposed method. The proposed method is able to obtain the optimal order for large m (e.g., m ≥ 20 ). Numerical experiments are used to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

For defective drilled lotus seeds, the inner bitter lotus plumule cannot be removed normally, leading to difficulties in subsequent nutrient extraction and food processing. There is an obvious difference in visibility of drilled hole between normal and defective drilled lotus seeds in the top view; thus, an online sorting method for drilled lotus seeds based on drilled hole detection is proposed in this study. First, a drilled hole detection model based on You Only Look Once (YOLOv3) is developed to detect the drilled hole features on the lotus seed surface. The model was tested and compared with the Faster Region-based Convolutional Neural Network (Faster R-CNN) and Single Shot MultiBox Detector (SSD) models, and it showed a better comprehensive performance in terms of accuracy and speed. A sorting control algorithm is also proposed to perform online sorting based on real-time drilled hole detection results. In addition, an auxiliary algorithm is proposed to prevent the boundary misjudgement of detected hole ownership between adjacent lotus seeds during continuous sorting. An online sorting system was designed, and sorting tests were performed. A sorting accuracy of 95.8% was achieved for the mixed defective and normal drilled lotus seed samples. The proposed method is expected to not only fulfil the practical requirements for the online sorting of drilled lotus seeds but also provide references for other agricultural products that require continuous online sorting based on the detection of local features. • Drilled lotus seeds can be sorted based on the detection of drilled hole. • An online sorting system for drilled lotus seeds was proposed. • A drilled hole detection model was developed based on YOLOv3. • The proposed sorting control algorithm can achieve online continuous sorting. • A sorting accuracy rate of 95.8% was achieved using the developed sorting system. [ABSTRACT FROM AUTHOR]

Featured Application: This study is useful for a series-integrated separation between good parts and defective ones via acoustic resonance testing. The work primarily relies on the simulation-based generation of mandatory and application-specific training data for defect detection. It also considers an optional use of additional structural component information in data evaluation. The given achievements may enable a time- and cost-optimized training procedure, allow for applying acoustic resonance testing despite a limited number of representative training parts, or provide a way to counter significant part-to-part variations for improved defect detection. Analyzing eigenfrequencies by acoustic resonance testing enables a fast screening of components regarding structural defects. The eigenfrequencies of each specific part depend on the general geometric and material properties, including tolerable part-to-part variations, as well as on possible structural flaws. Separating good parts from defective ones is not straightforward and each application-specific sorting algorithm is usually found from experimental training data. However, there are limitations and training data collection may be intricate. We worked on this challenge focusing on machine-made model parts varying slightly in geometry. The application objective was the eigenfrequency-based detection of parts featuring a through-hole test defect drilled into some of the parts and enlarged stepwise. The eigenfrequencies were measured concomitantly. Unlike the industry standard, our approach is based on synthetic training data created mainly by simulation techniques, which resulted in a principally satisfactory classification of the good and defective parts. However, the parts with small defects were not identified from the eigenfrequencies alone, due to overlaying geometric variations. In order to counteract such noise and to improve defect detection based on synthetic training data, the specific actual part geometry was used, in the sense of additional a priori information. A multimodal data evaluation model showed a clearly enhanced sorting power. [ABSTRACT FROM AUTHOR]

The manufacturing of solderless wrapped connections in traceable and reproducible high quality requires an automated manufacturing process. However, one key challenge for robot-based wiring is the definition of wiring sequence, as the proximity of the array-oriented wrapposts exacerbates tool accessibility. In this research, we optimize the wiring sequence by treating it as a constraint satisfaction problem, whereby a solution is indispensable, even if the constraints are not fulfilled. Experiments on a pilot plant for robot-based manufacturing of wrapped connections show that the percentage of automatically wired connections can be significantly increased with the developed approach. [ABSTRACT FROM AUTHOR]

Following the footprints of what has been done with other sorting devices, we study a popqueue and define an optimal sorting algorithm, called Cons. Our results include a description of the set of all the preimages of a given permutation, an enumeration of the set of the preimages of permutations with some specific properties and, finally, the exact enumeration of permutations having 0, 1 and 2 preimages, respectively, with a characterization of permutations having 3 preimages. [ABSTRACT FROM AUTHOR]

Consider the following partial “sorting algorithm” on permutations: take the first entry of the permutation in one-line notation and insert it into the position of its own value. Continue until the first entry is 1. This process imposes a forest structure on the set of all permutations of size n, where the roots are the permutations starting with 1 and the leaves are derangements. Viewing the process in the opposite direction towards the leaves, one picks a fixed point and moves it to the beginning. Despite its simplicity, this “fixed point forest” exhibits a rich structure. In this paper, we consider the fixed point forest in the limit n → ∞ and show using Stein’s method that at a random permutation the local structure weakly converges to a tree defined in terms of independent Poisson point processes. We also show that the distribution of the length of the longest path from a random permutation to a leaf converges to the geometric distribution with mean e − 1, and the length of the shortest path converges to the Poisson distribution with mean 1. In addition, the higher moments are bounded and hence the expectations converge as well.

Non-volatile memory (NVM) has emerged as an alternative of the next-generation memory due to its non-volatility, byte addressability, high storage-density, and low-energy consumption. However, NVM also has some limitations, e.g. asymmetric read and write latency. Therefore, at present, it is not realistic to completely replace DRAM with NVM in computer systems. A more feasible scheme is to adopt the hybrid memory architecture composed of NVM and DRAM. Following the assumption of hybrid memory architecture, in this paper, we propose an NVM-friendly sorting algorithm called NVMSorting. Particularly, we introduce a new concept called Natural Run to improve the existing MONTRES algorithm. Further, we apply the proposed NVMSorting to database join algorithms to improve the performance of the existing sort-merge join. To verify the performance of our proposal, we implement six existing sorting algorithms as baselines, including the MONTRES algorithm, and conduct comparative experiments on real Intel Optane DC persistent memory. The results show that NVMSorting outperforms other sorting algorithms in terms of execution time and NVM writes. In addition, the results of the join experiment show that the NVMSorting algorithm achieves the highest performance among all schemes. Especially, in the partially ordered data, the execution time of NVMSorting is 2.9%, 2.7%, and 4.2% less than MONTRES, external sort, and quick sort, respectively. Also, the amount of NVM writes of the NVMSorting is 26.1%, 43.6%, 96.2% less than MONTRES, external sort, and quick sort, respectively. [ABSTRACT FROM AUTHOR]

Pollution of the marine environment by ship garbage is an urgent problem to be solved at home and abroad. The ship kitchen garbage vacuum collection system is a new environmental protection scheme for garbage disposal. It has many advantages, such as using a pipeline instead of manual operation, creating high-level sanitary conditions, realising completely closed garbage collection and transportation, eliminating cross-pollution, saving space and so on. In this paper, the system is modelled, and the calculation of pipeline pressure loss, the vacuum degree of the vacuum tank and the energy consumption of the system are briefly introduced. In order to reduce the energy consumption, an algorithm for the emptying and discharging port is presented. In order to solve the problem of optimising relevant parameters, the vacuum transport mechanism of garbage is studied based on an optimisation model of the pipe network, and the experimental platform of a simulation device is set up. In engineering, this is of great significance to the design of cruise ship garbage collection and treatment systems and the development of supporting technology.

This paper is devoted to the practical application of parallel sorting algorithms and parallel input-output methods for the problem of genome alignment. The paper considers different approaches to the implementation of such algorithms, taking into account the capabilities of high-performance systems. Main purpose of the work is to develop a genome sorting program, the efficiency of which significantly exceeds the efficiency of free software analogues. The genome sorting program is implemented for a supercomputer using the C++ language and the OpenMP and OpenMPI. The developed program demonstrates a significant increase in the speed of operation (up to 10 times) compared to free software analogues due to massive parallel data input and output. Different approaches for data input/output parallelization and data processing considered in the paper can be applied in other subject areas. [ABSTRACT FROM AUTHOR]

Sorting a set of items is a task that can be useful by itself or as a building block for more complex operations. That is why a lot of effort has been put into finding sorting algorithms that sort large sets as efficiently as possible. But the more sophisticated and complex the algorithms become, the less efficient they are for small sets of items due to large constant factors. A relatively simple sorting algorithm that is often used as a base case sorter is insertion sort, because it has small code size and small constant factors influencing its execution time. We aim to determine if there is a faster way to sort small sets of items to provide an efficient base case sorter. We looked at sorting networks, at how they can improve the speed of sorting few elements, and how to implement them in an efficient manner using conditional moves. Since sorting networks need to be implemented explicitly for each set size, providing networks for larger sizes becomes less efficient due to increased code sizes. To also enable the sorting of slightly larger base cases, we adapted sample sort to Register Sample Sort, to break down those larger sets into sizes that can in turn be sorted by sorting networks. From our experiments we found that when sorting only small sets of integers, the sorting networks outperform insertion sort by a factor of at least 1.76 for any array size between six and 16, and by a factor of 2.72 on average across all machines and array sizes. When integrating sorting networks as a base case sorter into Quicksort, we achieved far less performance improvements over using insertion sort, which is probably due to the networks having a larger code size and cluttering the L1 instruction cache. The same effect occurs when including Register Sample Sort as a base case sorter for IPS4o. But for x86 machines that have a larger L1 instruction cache of 64 KiB or more, we obtained speedups of 12.7% when using sorting networks as a base case sorter in std::sort, and of 5%–6% when integrating Register Sample Sort as a base case sorter into IPS4o, each in comparison to using insertion sort as the base case sorter. In conclusion, the desired improvement in speed could only be achieved under special circumstances, but the results clearly show the potential of using conditional moves in the field of sorting algorithms. [ABSTRACT FROM AUTHOR]

Analyzing eigenfrequencies by acoustic resonance testing enables a fast screening of components regarding structural defects. The eigenfrequencies of each specific part depend on the general geometric and material properties, including tolerable part-to-part variations, as well as on possible structural flaws. Separating good parts from defective ones is not straightforward and each application-specific sorting algorithm is usually found from experimental training data. However, there are limitations and training data collection may be intricate. We worked on this challenge focusing on machine-made model parts varying slightly in geometry. The application objective was the eigenfrequency-based detection of parts featuring a through-hole test defect drilled into some of the parts and enlarged stepwise. The eigenfrequencies were measured concomitantly. Unlike the industry standard, our approach is based on synthetic training data created mainly by simulation techniques, which resulted in a principally satisfactory classification of the good and defective parts. However, the parts with small defects were not identified from the eigenfrequencies alone, due to overlaying geometric variations. In order to counteract such noise and to improve defect detection based on synthetic training data, the specific actual part geometry was used, in the sense of additional a priori information. A multimodal data evaluation model showed a clearly enhanced sorting power.

Nonvolatile random access memory (NVRAM) has been regarding a promising technology to replace DRAM as the main memory in embedded systems owing to its nonvolatility and low idle power consumption. However, due to the asymmetric read/write costs and limited lifetime of NVRAM, most of the existing fundamental algorithms are not NVRAM-friendly with their write pattern and write intensiveness. Thus, existing fundamental algorithms for NVRAM embedded devices has been revealed. For instance, as the sorting algorithm is one of the most fundamental algorithms, most of the existing sorting algorithms are not NVRAM-friendly because they impose heavy write traffic [i.e., $\mathcal {O}(n\lg {n})$ ] on main memory, where $n$ is the number of unsorted elements. To resolve this issue, this article proposes a write-once sorting algorithm, namely B*-sort, to reduce the amount of write traffic on NVRAM-based main memory. B*-sort adopts a brand-new concept, i.e., tree-based sort, inspired by the binary-search-tree structure to achieve the write-once property which can guarantee the optimal endurance during the sorting process. According to the experimental results, B*-sort can achieve significant performance improvement for sorting on NVRAM-based systems. [ABSTRACT FROM AUTHOR]

Modern nonvolatile memories (NVMs) are widely recognized as energy-efficient replacements of classical memory/storage media, such as SRAM, DRAM, and mechanical hard disk. Among the popular NVMs, the skyrmion racetrack memory (SK-RM) is well known for its high storage density and unique supports of insert/delete operations. However, the existing algorithms designed for classical media might experience serious performance degradation when working on the SK-RM, due to the distinct characteristics of SK-RM. Thus, the existing algorithms should be redesigned to adapt to the brand-new memory model based on the SK-RM, so as to fully reveal the potentials of SK-RM. In particular, many existing algorithms tend to access the in-memory data in a random-hopping fashion, which generates many time-consuming shift operations of SK-RM. It is therefore crucial for the existing algorithms to eliminate unnecessary shift operations of SK-RM to boost the performance of the algorithms. In many modern applications, such as multimedia and data analysis, it is a common operation to process two or more arrays/vectors of data to perform certain computation tasks. In the arrays/vectors, an appropriate data placement strategy is critical for avoiding unnecessary shift operations of SK-RM. The observation thus motivates this work in proposing a recursive back-to-back data placement manner to effectively reduces the shift operations of SK-RM. To demonstrate the back-to-back data placement, we take sorting algorithms as a case study, and propose a novel shift-limited sorting algorithm for SK-RM. Analytical studies show that the shift-limited sort effectively enhances the time complexity of classical merge sort from $\mathcal {O}(dn\lg n)$ to $\mathcal {O}(n\lg n)$ , where $d$ is the bit distance between adjacent access ports on the nanotracks of the SK-RM. After that, the efficacy of the proposed shift-limited sort is then verified by experimental studies, where the results are encouraging. [ABSTRACT FROM AUTHOR]

Formal method plays an important role in modeling large scale concurrent networks through its efficient model construction and analysis. Taking urban road networks and public transportation systems as examples, such models can be defined in a formal method in order to investigate the performance of current bus-line deployment based on a given road network. This paper considers how to efficiently build a formal model based on such an original prototype of the specified road network and transportation system. As the model prototype can be represented by a directed graph that is then transformed into a numerical incidence matrix, we proposed an algorithm, in this paper, to assist the construction of formal models by sorting all potential compositional structures and components based on the previously obtained numerical incidence matrix. Thereafter, a performance evaluation process algebra-based formal model can be automatically generated on the basis of sorted compositional structures, which extends the use of formal method for largescale and comprehensive network, and system modeling. The findings reveal that the proposed algorithm can efficiently find all potential compositional structures that include all potential components and related activity flows in models.

Sorting is an essential operation which is widely used and is fundamental to some very basic day to day utilities like searches, databases, social networks and much more. Optimizing this basic operation in terms of complexity as well as efficiency is cardinal. Optimization is achieved with respect to space and time complexities of the algorithm. In this paper, a novel left-field N-dimensional cartesian spaced sorting method is proposed by combining the best characteristics of bucket sort, counting sort and radix sort, in addition to employing hashing and dynamic programming for making the method more efficient. Comparison between the proposed sorting method and various existing sorting methods like bubble sort, insertion sort, selection sort, merge sort, heap sort, counting sort, bucket sort, etc., has also been performed. The time complexity of the proposed model is estimated to be linear i.e. O(n) for the best, average and worst cases, which is better than every sorting algorithm introduced till date. [ABSTRACT FROM AUTHOR]

Nowadays, mangoes and other fruits are classified according to human perception of low productivity, which is a poor quality of classification. Therefore, in this study, we suggest a novel evaluation of internal quality focused on external features of mango as well as its weight. The results show that evaluation is more effective than using only one of the external features or weight combining an expensive nondestructive (NDT) measurement. Grading of fruits is implemented by four models of machine learning as Random Forest (RF), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN). Models have inputs such as length, width, defect, weight, and outputs being mango classifications such as grade G1, G2, and G3. The unstructured data of 4983 of captured images combining with load-cell signals are transferred to structured data to generate a completed dataset including density. The data normalization and elimination of outliers (DNEO) are used to create a better dataset which prepared for machine learning algorithms. Moreover, an unbiased performance estimate for the training process carried out by the nested cross-validation (NCV) method. In the experiment, the methods of machine learning have high accurate over 87.9%, especially the model of RF gets 98.1% accuracy. [ABSTRACT FROM AUTHOR]

Sorting is a fundamental computing concept. As for today, it is taught at the secondary school level. However, this kind of algorithm is an obstacle for some students due to its high level of abstraction. To prevent discouragement as well as to incorporate a fun and challenging algorithmic task, a novel tabletbased digital game, Sorted, was created to serve the purpose. This research article embraces the neo- Piagetian framework of cognitive development and provides the theoretical-based explanation of how high school students establish sorting algorithms as a result of the digital gameplay. Twenty-three tenthgrade students, who have no proper knowledge of sorting algorithms, participated voluntarily in this study. They played the game with a multi-level design involving multiple unknowns. To later reflect on their operational reasoning and hence decision-making, the series of game actions were logged for individual empirical data. The sorting algorithm formation can be deduced from the logged sequential actions. They were coded and analyzed according to the neo-Piagetian framework to elicit the students' operational reasoning. The discovery of the relations between actions and schematic reasoning to solve sorting problems suggests the impact of a digital game on algorithmic thinking development, and, in general, the use of a game for self-learning of computing concepts. [ABSTRACT FROM AUTHOR]

In this paper, the traditional ant colony algorithm has a slow convergence rate for routing optimization of Mesh networks. A multi-path routing protocol based on improved ant colony algorithm, Fortified Ant protocol, is proposed. The protocol first adds a sorting algorithm based on the ant colony algorithm, and introduces the concept of elite ants to improve the speed of routing optimization. Secondly, this paper also studies the multipath transmission of self-organizing networks. The simulation results show that compared with ADOV, DSR and AOC routing algorithms, the algorithm can quickly find multiple paths with better quality, with fast convergence and overhead. Less advantage. [ABSTRACT FROM AUTHOR]

This study investigated the effects of respiratory motion, including unwanted breath holding, on the target volume and centroid position on four‐dimensional computed tomography (4DCT) imaging. Cine 4DCT images were reconstructed based on a time‐based sorting algorithm, and helical 4DCT images were reconstructed based on both the time‐based sorting algorithm and an amplitude‐based sorting algorithm. A spherical object 20 mm in diameter was moved according to several simulated respiratory motions, with a motion period of 4.0 s and maximum amplitude of 5 mm. The object was extracted automatically, and the target volume and centroid position in the craniocaudal direction were measured using a treatment planning system. When the respiratory motion included unwanted breath‐holding times shorter than the breathing cycle, the root mean square errors (RSME) between the reference and imaged target volumes were 18.8%, 14.0%, and 5.5% in time‐based images in cine mode, time‐based images in helical mode, and amplitude‐based images in helical mode, respectively. In helical mode, the RSME between the reference and imaged centroid position was reduced from 1.42 to 0.50 mm by changing the reconstruction method from time‐ to amplitude‐based sorting. When the respiratory motion included unwanted breath‐holding times equal to the breathing cycle, the RSME between the reference and imaged target volumes were 19.1%, 24.3%, and 15.6% in time‐based images in cine mode, time‐based images in helical mode, and amplitude‐based images in helical mode, respectively. In helical mode, the RSME between the reference and imaged centroid position was reduced from 1.61 to 0.83 mm by changing the reconstruction method from time‐ to amplitude‐based sorting. With respiratory motion including breath holding of shorter duration than the breathing cycle, the accuracies of the target volume and centroid position were improved by amplitude‐based sorting, particularly in helical 4DCT. [ABSTRACT FROM AUTHOR]

This paper proposes a new carrier-based modulation strategy for symmetrical cascaded multilevel converters denominated phase disposition with sorting (PDS). It deals with the issue of irregular distribution of PWM signals and power for each converter cell that occurs when using the conventional phase disposition (PD) modulation. Although some alternatives have been proposed in the literature for overcoming these problems, most of them do not consider operation of the converter under fault conditions on the power cells. Therefore, one of the contributions of the proposed PDS modulation strategy is the ability to evenly distribute the pulse signals for the converter semiconductor switches, resulting in the same power being processed by all cells, maintaining the good quality of the synthesized output voltages, even with faults in one or more power cells. In addition, it allows implementation in commercial digital signal processors, not requiring additional hardware. The good performance of the proposed modulation strategy is validated through experimental results for a three-phase symmetrical cascaded multilevel converter with three cells per phase, considering normal and faulty conditions on the power cells. [ABSTRACT FROM AUTHOR]

One important characteristic of modular multilevel converter (MMC) is the existence of circulating current, which consists of a dc component and a series of undesirable even-order (predominantly second-order) harmonics. However, only the dc part of the circulating current is required for power balance, the ac harmonics are unwanted. These undesirable harmonics should be suppressed to reduce device stress and power losses. Most state-of-the-art circulating current suppression techniques employ separate controllers to generate the arm reference voltage for circulating current suppression. This paper proposes an alternate approach, eliminating the need of any additional control loop. Generation of undesirable circulating current is prevented inherently in the modulation stage. Reduced switching frequency sorting algorithm based modulation framework is employed to ensure reduced switching loss. Suitability of the proposed method is validated by experiments performed on a three-phase laboratory prototype of MMC. Steady state and transient operation of the MMC in grid-connected condition is studied. [ABSTRACT FROM AUTHOR]