Comparison Of Distances Research Articles

Comparison of Inverse Distance Weighted and Thin Plate Spline Interpolation Methods in Projecting the Strength of the West Sumatra Earthquake

The Indonesian archipelago is situated in a highly active geological zone, making it prone to frequent earthquakes. West Sumatra, located on the west coast of central Sumatra, comprises lowland coastal areas and volcanic plateaus formed by the Barisan Mountains, covering a land area of 42,297.30 km² (2.17% of Indonesia's territory). This research aims to determine which interpolation method—Inverse Distance Weighted (IDW) and Thin Plate Spline (TPS)—provides more accurate predictions of earthquake strength in West Sumatra. The dataset consists of 229 earthquake events, divided into 90% for training (206 points) and 10% for testing (23 points). The training data was further subdivided into 80% training data 2 (164 points) and 20% validation data (42 points). The interpolation processes using the IDW and TPS methods were repeated 100 times, with the training 2 and validation data randomly shuffled in each iteration. Visualization of the interpolation results indicated that the earthquake magnitudes ranged from 2.0 to 4.5. Although the Mean Absolute Percentage Error (MAPE) values for the TPS method on the test and validation datasets were 16.42 and 14.29, respectively—slightly lower than the MAPE values for the IDW method—the t-test results showed no statistically significant difference between the two methods. Statistically, there is no significant difference between IDW and TPS in terms of predictive accuracy. However, researchers prefer the IDW method due to its computational efficiency and simplicity. Therefore, IDW is considered the most suitable method for analyzing earthquake strength in the West Sumatra region

Comparison of Upper Lip Bite Test and Thyromental Distance with Other Airway (Malampatti and Inter Incisor Distance) Assessment Tests for Predicting Difficult Endotracheal Intubation

Objective: To study the ability of upper lip bite test and thyromental distance to predict difficult endotracheal intubation when compared to standard assessment tests such as Mallampati and inter incisor distance. Study Design: Cross-sectional validation study. Place and Duration of Study: Department of Anesthesiology, Pak-Emirates Military Hospital, Rawalpindi, Pakistan, Sep 2020 to Mar 2021. Methodology: We studied a total of 50 patients who reported for the administration of general anesthesia. All patients underwent evaluation with modified Mallampati test, upper lip bite test and thyromental distance test. All participants underwent subsequent intubation according to a standard protocol. The researcher documented difficult intubations. Results: We found the upper lip bite test to have a sensitivity of 75.7%, a specificity of 84.2%, and a diagnostic accuracy of 78.6%. Thyromental distance had a sensitivity, specificity, and diagnostic accuracy of 51.4%, 78.9% and 60.7%, respectively while the modified Mallampati had a sensitivity of 64.9%, 89.5%, specificity and a diagnostic accuracy of 73.2%. Conclusion: Upper lip bite test is a useful bedside assessment tool with which to predict the probability of a difficult endotracheal intubation. Height to thyromental distance ratio test is also acceptable for rapid assessment.

Indiscernible noise determination of a military system equipped with an internal combustion engine

The main objective of this paper is to explore the non-detectability criteria of military systems and to determine the indiscernible noise of military systems equipped with internal combustion engines. Non-detectability is one of the critical requirements evaluated for military defense systems and it is defined strictly in MIL-STD-1474E standard. Furthermore, this standard specifies the limits of sound pressure levels conservatively for 1/3 octave bands. Though, the standard does not define indiscernible or inaudible noise levels for events in the presence of background noise. It is also not explicitly well-defined in the existing literature. This study presents a comparison of non-detectability distance defined in MIL-STD-1474E standard and indiscernible noise of a military system extracted from the measured octave band sound levels, which are processed based on sound propagation theory. In this study, several parameters such as atmospheric absorption, geometric spreading, ground effect, terrain type, obstacle existence are included to determine the indiscernible noise level of the military system of interest. The results are compared with the non-detectability distance limits given in the MIL-STD-1474E standard, and it is observed that the proposed method of indiscernible noise, which is defined as extracted sound level should be lower than the background noise, is well-correlated.

Structural and Theoretical Assessment of Covalency in a Pu(III) Borohydride Complex.

Despite the discovery of actinide borohydride complexes over 80 years ago, no plutonium borohydride complexes have been structurally validated using single-crystal X-ray diffraction (XRD). Here we describe Pu2(H3BPtBu2BH3)6, the first example of a Pu(III) borohydride complex authenticated by XRD and NMR spectroscopy. Theoretical calculations (DFT, EDA, and QTAIM) and experimental comparisons of metal-boron distances suggest that metal-borohydride covalency in M2(H3BPtBu2BH3)6 complexes generally decreases in the order M = U(III) > Pu(III) > Ln(III).

Comparison of distance versus in-person laparoscopy training using a low-cost laparoscopy simulator—a randomized controlled multi-center trial

IntroductionSimulation training programs are essential for novice surgeons to acquire basic experience to master laparoscopic skills. However, current state-of-the-art laparoscopy simulators are still expensive, limiting the accessibility to practical training lessons. Furthermore, training is time intensive and requires extensive spatial capacity, limiting its availability to surgeons. New laparoscopic simulators offer a cost-effective alternative, which can be used to train in a digital environment, allowing flexible, digital and personalized laparoscopic training. This study investigates if training on low-cost simulators in a digital environment is comparable to in-person training formats.Materials and methodsFrom June 2023 to December 2023, 40 laparoscopic novices participated in this multi-center, prospective randomized controlled trial. All participants were randomized to either the ‟distance” (intervention) or the “in-person” (control) group. They were trained in a standardized laparoscopic training curriculum to reach a predefined level of proficiency. After completing the curriculum, participants performed four different laparoscopic tasks on the ForceSense system. Primary endpoints were overall task errors, the overall time for completion of the tasks, and force parameters.ResultsIn total, 40 laparoscopic novices completed digital or in-person training. Digital training showed no significant differences in developing basic laparoscopic skills compared to in-person training. There were no significant differences in median overall errors between both training groups for all exercises combined (intervention 3 vs. control 4; p value = 0.74). In contrast, the overall task completion time was significantly lower for the group trained digitally (intervention 827.92 s vs. control 993.42; p value = 0.015). The applied forces during the final assessment showed no significant differences between both groups for all exercises. Overall, over 90% of the participants rated the training as good or very good.ConclusionOur study shows that students that underwent digital laparoscopic training completed tasks with a similar number of errors but in a shorter time than students that underwent in-person training. Nevertheless, the best strategies to implement such digital training options need to be evaluated further to support surgeons’ personal preferences and expectations.

Comparison of linear distance of glenoid fossa to frontomaxillary nasal suture in skeletal Class-II and skeletal Class-I malocclusion.

To compare linear distance of glenoid fossa to frontomaxillary nasal suture in skeletal Class-I and II malocclusions. This cross-sectional study was conducted at the Department of Orthodontics, Altamash Institute of Dental Medicine, Karachi Pakistan. The duration of study was one year from January, 2019 to January, 2020. After taking informed consent from patient and hospital ethical committee a total of 60 patients were included in the study using WHO sample size calculator. Two groups comprising 30 patients each i.e., Skeletal Class-I malocclusion and Skeletal Class-II malocclusion with mandibular retrusion both having normal vertical relationship were included in the study. The cephalometric measurements SNA, SNB, SNMP, FHMP, GF-FMN, CO-GO, CO GN on lateral cephalograms were measured and compared between the two groups. Independent t test was applied and p value ≤ 0.05 was considered as significant. In skeletal Class-I malocclusion the mean linear distance of GF-FMN was 70.2 ± 4.02 mm and in skeletal Class-II malocclusion it was 73.4 ± 4.04 mm (p value .004). Glenoid fossa was 3.2 mm distally placed in patients with Class-II malocclusion. Glenoid fossa position is a diagnostic feature of Class-II malocclusion associated with mandibular retrusion. One of the effective cephalometric measurements to check glenoid fossa position is the distance from the glenoid fossa(GF) to the frontomaxillary nasal suture FMN (GF-FMN).

Description of a new species of Andricus Hartig, 1840 (Hymenoptera: Cynipidae: Cynipini) from China

A new species of gall wasp, Andricus wugangensis Zeng, Liu, & Zhu sp. nov. is described and illustrated herein from Hunan Province, China. The new species is most similar to A. wuhanensis Ide, Abe, Su & Zhu and A. xishuangbanaensis Melika & Tang in morphology but can be easily distinguished by having 1) a large V-shaped carina on the lower face and 2) a broad transverse depression spanning the region between the inner margin of the eyes on the upper face. The results of a phylogenetic analysis and pairwise genetic distance comparison, based on COI sequences, were consistent with the conclusion of the comparative morphological assessment of the similar species: A. wuganensis, A. wuhanensis and A. xishuangbanaensis, although the morphological differences are more obvious than the small genetic distance of the COI sequences, which is 4.3% and 3% between the new species and A. wuhanensis and A. xishuangbanaensis, respectively. Additionally, a taxonomic key to the known species of Andricus from China is provided.

Unsupervised domain adaptation multi-level adversarial learning-based crossing-domain retinal vessel segmentation

BackgroundThe retinal vasculature, a crucial component of the human body, mirrors various illnesses such as cardiovascular disease, glaucoma, and retinopathy. Accurate segmentation of retinal vessels in funduscopic images is essential for diagnosing and understanding these conditions. However, existing segmentation models often struggle with images from different sources, making accurate segmentation in crossing-source fundus images challenging. MethodsTo address the crossing-source segmentation issues, this paper proposes a novel Multi-level Adversarial Learning and Pseudo-label Denoising-based Self-training Framework (MLAL&PDSF). Expanding on our previously proposed Multiscale Context Gating with Breakpoint and Spatial Dual Attention Network (MCG&BSA-Net), MLAL&PDSF introduces a multi-level adversarial network that operates at both the feature and image layers to align distributions between the target and source domains. Additionally, it employs a distance comparison technique to refine pseudo-labels generated during the self-training process. By comparing the distance between the pseudo-labels and the network predictions, the framework identifies and corrects inaccuracies, thus enhancing the accuracy of the fine vessel segmentation. ResultsWe have conducted extensive validation and comparative experiments on the CHASEDB1, STARE, and HRF datasets to evaluate the efficacy of the MLAL&PDSF. The evaluation metrics included the area under the operating characteristic curve (AUC), sensitivity (SE), specificity (SP), accuracy (ACC), and balanced F-score (F1). The performance results from unsupervised domain adaptive segmentation are remarkable: for DRIVE to CHASEDB1, results are AUC: 0.9806, SE: 0.7400, SP: 0.9737, ACC: 0.9874, and F1: 0.8851; for DRIVE to STARE, results are AUC: 0.9827, SE: 0.7944, SP: 0.9651, ACC: 0.9826, and F1: 0.8326. ConclusionThese results demonstrate the effectiveness and robustness of MLAL&PDSF in achieving accurate segmentation results from crossing-domain retinal vessel datasets. The framework lays a solid foundation for further advancements in cross-domain segmentation and enhances the diagnosis and understanding of related diseases.

Beyond mutations: Accounting for quantitative changes in the analysis of protein evolution

Molecular phylogenetic research has relied on the analysis of the coding sequences by genes or of the amino acid sequences by the encoded proteins. Enumerating the numbers of mismatches, being indicators of mutation, has been central to pertinent algorithms. Specific amino acids possess quantifiable characteristics that enable the conversion from “words” (strings of letters denoting amino acids or bases) to “waves” (strings of quantitative values representing the physico-chemical properties) or to matrices (coordinates representing the positions in a comprehensive property space). The application of such numerical representations to evolutionary analysis takes into account not only the occurrence of mutations but also their properties as influences that drive speciation, because selective pressures favor certain mutations over others, and this predilection is represented in the characteristics of the incorporated amino acids (it is not born out solely by the mismatches). Besides being more discriminating sources for tree-generating algorithms than match/mismatch, the number strings can be examined for overall similarity with average mutual information, autocorrelation, and fractal dimension. Bivariate wavelet analysis aids in distinguishing hypermutable versus conserved domains of the protein. The matrix depiction is readily subjected to comparisons of distances, and it allows the generation of heat maps or graphs. This analysis preserves the accepted taxa order where tree construction with standard approaches yields conflicting results (for the protein S100A6). It also aids hypothesis generation about the origin of mitochondrial proteins. These analytical algorithms have been automated in R and are applicable to various processes that are describable in matrix format.

Ultrasound-based visualization measurement of hyoid-mandibular motion for assessing the efficacy of acupuncture in treating post-stroke dysphagia: A clinical study

ObjectiveThe objective of this study was to utilize ultrasonography to measure the movement-related characteristics of the hyoid bone-mandible in patients with dysphagia in order to quantitatively evaluate the clinical efficacy of acupuncture as a treatment for dysphagia following brain infarction. MethodsA total of 63 patients with dysphagia following a brain infarction were randomly assigned into two groups: one receiving meridian point treatments and the other receiving non-meridian and non-point treatments. The meridian point group received routine treatment using the meridian point acupuncture method, and the true acupuncture intervention mode of qi arrival plus swift pricking blood therapy was utilized. The non-meridian and non-acupoint group received conventional treatment using the pseudo-acupuncture mode of non-acupoint without qi arrival. Both groups received treatment once daily, five times per week, for a duration of four weeks. Video fluoroscopic swallowing study (VFSS) was used to diagnose dysphagia in all patients, and FOIS and PAS were also used for clinical assessment. Results(i) Clinical efficacy comparison: After 4 weeks of treatment, the meridian group showed superior efficacy compared to the non-meridian and non-acupuncture group (P < 0.05). The FOIS score of the meridian acupoint group was also higher than that of the non-meridian and non-acupoint group (P < 0.05). In addition, the dilute fluid food PAS score in the meridian acupoint group was lower than that in the non-meridian and non-acupoint group (P < 0.05). (ii) Comparison of ultrasonography: The hyoid-mandibular comparison of the shortening distance, shortening rate, and movement speed of the bone movement were measured in both groups after 2 weeks and 4 weeks of treatment. The results indicated that the improvement in the meridian group was better than that in the non-meridian and non-acupoint group in all measurements (P < 0.05). ConclusionPatients with swallowing disorders exhibit impaired hyoid-mandibular movement. However, the implementation of true acupuncture intervention can enhance hyoid-mandibular movement function, ultimately leading to an improvement in swallowing function.

Differentiating Everyday Map Tasks: Unique Attention-Related Eye Movements and Electrophysiological Signatures of Map Use

Cartographic maps are ubiquitous in spatial activities such as localization, navigation, and travel exploration. Understanding how the map users interact with maps remains a challenge, however. Research to date has focused on the overt aspects of map users’ cognitive processes, using conventional empirical methods and eye tracking, but the covert aspects (e.g., brain activity) have been largely neglected. In this study, participants used Google Maps for four everyday tasks: global search, distance comparison, route following, and route planning. We recorded and analyzed users’ attention-related visual (eye movement measures by eye tracking) and electrophysiological (fixation-evoked P3-ERP and task-induced alpha/theta ERD/ERS by scalp electroencephalograms) responses. Results demonstrated efficient visual processing and expanded spatial exploration in global search and distance comparison tasks. Interestingly, more attentional resources were devoted to recognizing whether information matches or not in global search tasks, as shown by the larger P3 component for the map target. In contrast, route following and route planning tasks required intensified attention for information decoding and complicated cognitive processes, focusing predominantly on pertinent narrow map regions. Our findings highlight that the visual and electrophysiological signatures effectively capture the heterogeneity of user attention during different map tasks.

Enhanced differential evolution-Rao optimization with distance comparison method and its application in optimal sizing of truss structures

A new decision-making approach based on distance measures is established in this study to effectively reduce unnecessary structural analyses in performing truss optimization by metaheuristic algorithms. This approach termed distance comparison (DiC) judges a new design candidate as worth evaluating by using its distance from the best solution. The new candidate solution will be omitted without evaluating it if it is not closer to the best solution than the one being compared. The DiC method is integrated with a novel hybrid metaheuristic based on differential evolution (DE) and the Rao algorithm. In the proposed hybrid strategy, a modified Rao algorithm and an enhanced DE are applied adaptively based on the population diversity to utilize the advantage of each one for a specific stage of the optimization process. Six truss sizing examples with continuous variables, including the 10-bar and 200-bar planar trusses and the 25-bar, 72-bar, 120-bar, and 942-bar spatial trusses, are examined to evaluate the effectiveness of the proposed method. Numerical results demonstrate that DiC significantly reduces the number of structural analyses. Moreover, the performance of the proposed hybrid metaheuristic algorithm conducted on the examples is better than that of some state-of-the-art metaheuristic algorithms.

Physics-Informed Machine Learning Using Low-Fidelity Flowfields for Inverse Airfoil Shape Design

Physics-informed neural networks (PINNs) are a class of scientific machine learning that utilizes differential equations in loss formulations to model physical quantities. Despite recent developments, complex phenomena such as high-Reynolds-number (high-Re) flow remain a modeling challenge without the use of high-fidelity inputs. In this study, a low-fidelity-influenced physics-informed neural network (LF-PINN) is proposed as a surrogate aerodynamic analysis model for inverse airfoil shape design at Re=1.0×106. The LF-PINN is developed in a hybrid approach using low-fidelity flowfields approximated from a viscous-inviscid coupled airfoil analysis tool (mfoil) and physics residuals from the steady, incompressible, two-dimensional Navier–Stokes (NS) equations. The approach is designed to alleviate offline computational costs by avoiding high-fidelity simulations and sustain predicting accuracy using corrections by the physics residuals. The LF-PINN is able to correct the low-fidelity flowfield quantities toward the ground truth, with a mean improvement of about 19% in pressure and about 5% in total velocity based on Euclidean distance comparisons. Evaluation of the airfoil surface pressure coefficient Cp distributions shows corrections by the LF-PINN at the suction peak, which largely contributes to lifting forces. Inverse airfoil shape design is conducted using target Cp distributions in the objective function, whereby the LF-PINN can approach the expected target shapes while reducing online computational time by at least an order of magnitude compared to direct airfoil analysis tools.

PERANCANGAN TATA LETAK RELOKASI LANTAI PRODUKSI DENGAN METODE SYSTEMATIC LAYOUT PLANNING, BLOCPLAN, DAN FLAP

In the development of the industrial revolution 4.0, in carrying out production at small, medium, and large levels, there has been a fairly large and significant increase. Factors that influence the goal of successful production are not only about investment, capital, suppliers, machines, skills, and distributors but also one that must be observed is the layout planning and placement of factory facilities. PT. Eworx Indonesia is a company engaged in the processing industry, especially manufacturing in the metal processing sector. PT. Eworx Indonesia intends to relocate the production floor in order to increase production productivity. In this study, the proposed layout design on the new production floor was carried out using the SLP, Blocplan, and FLAP methods. The design is done by collecting direct observation data and interviews with the operator on duty. It was found that the initial layout had problems with operator movement that was not optimal and the placement of several machines and facilities that did not pay attention to material flow resulting in a slowdown in production time. Therefore, in order to get the best layout, a comparison is made on the results of the three alternative layouts with the smallest displacement distance comparison so that the production process will run more optimally. The best proposed layout is the systematic layout planning (SLP) method with the smallest material displacement distance of 147.4 meters and material handling costs Rp. 223,958 per day. Flexsim simulations show this layout can increase production output by 15%-34%.

Validation of deep amplicon sequencing of Dicrocoelium in small ruminants from Northern regions of Pakistan.

Dicrocoelium lancet flukes cause significant production loss in ruminant livestock. Although co-infection with multiple Dicrocoelium species within a host is common, techniques for studying the composition of these complex parasite communities are lacking. The pathogenicity, epidemiology, and therapeutic susceptibility of different helminth species vary, and little is known about the interactions that take place between co-infecting species and their hosts. Here, we describe the first applicationof metabarcoding deep amplicon sequencing method to studythe Dicrocoelium species in sheep and goats. First, rDNA ITS-2 sequences of four Dicrocoelium species (Dicrocoelium dendriticum, Dicrocoelium hospes, Dicrocoelium orientalis, and Dicrocoelium chinensis) were extracted from the NCBI public database. Phylogenetic analysis revealed separate clades of Dicrocoelium species; hence, molecular differentiation between each species is possible in co-infections. Second, 202 flukes belonging to seventeen host populations (morphologically verified as belonging to the Dicrocoelium genus) were evaluated to determine the deep amplicon sequencing read threshold of an individual fluke for each of the four species. The accuracy of the method in proportional quantification of samples collected from single hosts was further assessed. Overall, 198 (98.01%) flukes were confirmed as D. dendriticum and 1.98% produced no reads. The comparison of genetic distances between rDNA ITS-2 revealed 86% to 98% identity between the Dicrocoelium species. Phylogenetic analysis demonstrated a distinct clustering of species, apart from D. orientalis and D. chinensis, which sit very close to each other in a single large clade whereas D. hospes and D. dendriticum are separated into their own clade. In conclusion each sample was identified as D. dendriticum based on the proportion of MiSeq reads and validated the presence of this group of parasites in the Gilgit Baltistan and Khyber Pakhtunkhwa provinces of Pakistan. The metabarcoding deep amplicon sequencing technology and bioinformatics pathway have several potential applications, including species interactions during co-infections, identifying the host and geographical distribution of Dicrocoelium in livestock, drug therapy response evaluation and understanding of the emergence and spread of drug resistance.

An improved MOEA/D for multi-objective flexible job shop scheduling by considering efficiency and cost

To achieve cost reduction and efficiency improvement in the production process of the aerospace industry, this study establishes a mathematical model for the multi-objective flexible job shop scheduling problem (MOFJSP). The model comprehensively considers four optimisation objectives: completion time, tool number, machine load, and machine energy consumption. For solving the MOFJSP, an improved MOEA/D (IMOEA/D) algorithm is proposed. To improve the quality of solutions, the algorithm introduces another global update strategy in addition to the original substitution operation. The population is initialised using four allocation rules, and the neighbourhood is dynamically updated based on the degree of population evolution. The simulation results on a single instance indicate that the simulation time of IMOEA/D has decreased by 10.5% and machine energy consumption has reduced by 9.5%. Moreover, when compared to various classic multi-objective algorithms on 25 benchmark instances, the IMOEA/D algorithm achieved optimal results in 19 instances for inverted generational distance comparisons, 15 instances for hypervolume comparisons and nearly all instances for set coverage comparisons. The results reveal that the proposed IMOEA/D is effective and competitive in solving MOFJSP.

Time-series analysis of rhenium(I) organometallic covalent binding to a model protein for drug development.

Metal-based complexes with their unique chemical properties, including multiple oxidation states, radio-nuclear capabilities and various coordination geometries yield value as potential pharmaceuticals. Understanding the interactions between metals and biological systems will prove key for site-specific coordination of new metal-based lead compounds. This study merges the concepts of target coordination with fragment-based drug methodologies, supported by varying the anomalous scattering of rhenium along with infrared spectroscopy, and has identified rhenium metal sites bound covalently with two amino acid types within the model protein. A time-based series of lysozyme-rhenium-imidazole (HEWL-Re-Imi) crystals was analysed systematically over a span of 38 weeks. The main rhenium covalent coordination is observed at His15, Asp101 and Asp119. Weak (i.e. noncovalent) interactions are observed at other aspartic, asparagine, proline, tyrosine and tryptophan side chains. Detailed bond distance comparisons, including precision estimates, are reported, utilizing the diffraction precision index supplemented with small-molecule data from the Cambridge Structural Database. Key findings include changes in the protein structure induced at the rhenium metal binding site, not observed in similar metal-free structures. The binding sites are typically found along the solvent-channel-accessible protein surface. The three primary covalent metal binding sites are consistent throughout the time series, whereas binding to neighbouring amino acid residues changes through the time series. Co-crystallization was used, consistently yielding crystals four days after setup. After crystal formation, soaking of the compound into the crystal over 38 weeks is continued and explains these structural adjustments. It is the covalent bond stability at the three sites, their proximity to the solvent channel and the movement of residues to accommodate the metal that are important, and may prove useful for future radiopharmaceutical development including target modification.

Clustering Method for Signals in the Wideband RF Spectrum Using Semi-Supervised Deep Contrastive Learning

This paper presents the application of self-supervised deep contrastive learning in clustering signals detected in the wideband RF spectrum, presented in the form of spectrograms. Radio clustering is a method of searching for similar signals within the analyzed part of the radio spectrum. Typically, it is based on one or several specific parameters processed from the signal in a given channel. The authors propose a slightly different, innovative approach; thanks to the self-supervised learning of neural networks, there is no need to define specific parameters, and the feature vector, enabling comparison of Euclidean distances between signals, is generated by a deep neural network trained using a contrastive loss function on a dataset containing different radio modulations. The authors describe self-supervised solutions based on contrastive learning and the methods of signal segmentation and augmentation. The training process utilizes a custom database and the Resnet-50 network with a contrastive cost function. Radio clustering is used for autonomous spectrum analysis across wide frequency ranges and enables, among other things, the detection of tactical radio stations operating with widely dispersed frequency-hopping or a significant reduction in computational power required for real-time analysis of a large number of radio signals.

Efficacy of Learning Disorder Treatment for Reading or Mathematics Disorders: An Open Study.

This study aimed to identify the effectiveness of treatment programs for children with reading (RD) or mathematics disorders (MD). Structured treatment programs were developed to improve phonological awareness and number sense among children and adolescents with RD or MD, respectively, and the effectiveness of the learning disorder treatment programs were evaluated. We used standardized, objective diagnostic, and evaluation tools not only to recruit participants with RD, MD, or comorbid attention deficit and hyperactivity disorder, but also to assess the effectiveness of the treatments regarding both improved core neurocognitive deficits of RD or MD and academic achievement. Forty children with RD or MD received one-on-one treatments from therapists. In the RD group, treatment effects were observed in all subtests. In the word and paragraph reading tests, the accuracy rates and fluency improved. The results of the phonological working memory test, word-sound correspondence test, and rapid automatic naming tests also improved. In the MD group, the accuracy rate and fluency on the arithmetic test improved. An increase in the accuracy rate in the size and distance comparison tests and a decrease in the error rate in the estimation test were also observed. However, there were no improvements in reaction time in these subtests. Learning disorder treatment programs that focus on improving phonological awareness or number sense in children with RD or MD improved achievement, phonological awareness, and number sense.

Coupled simulation-optimization model for pedestrian evacuation guidance planning

Effective evacuation guidance can guarantee people's safety by facilitating their swiftly exit hazardous areas during an emergency. However, pre-determined guidance plans based solely on distance comparisons to exits may not always be the most effective due to unstable accessibility conditions and uneven crowd distribution. Therefore, it is imperative to incorporate real-time optimal guidance information in the plan. Coupling simplified CTM (Cell Transmission Model)-based simulation, this study proposed a computationally efficient DRF (Directed Rooted Forest)-encoded planning for developing evacuation guidance plan. Taking them as a holistic model, the simulator predicts evacuation dynamics at a constant computational cost regardless of crowd size, while the planning module optimizes the guidance plan directionally by leveraging the simulation's intermediate and final outputs. Numerical tests have demonstrated that the tight coupling between optimization and simulation module has substantially enhanced the model's capacity to fine-tune the guidance plan and optimization efficiency. The proposed model may serve as the foundation for developing real-time evacuation guidance plans for large-scale crowded buildings, either on the premise of accelerated simulation or as an efficient generator of training data for machine learning models.