Minimum Number Research Articles

SPECIFICS OF VERBAL VALENCE IN TERMS OF ITS PERCEPTION BY SPEAKERS (PSYCHOLINGUISTIC EXPERIMENT)

The article provides an in-depth study of the valence of verbal vocabulary in terms of selection of positions that are open to distributors. The purpose of the article is to outline the specifics of valence of actional and processual verbs in and out of context, to establish the minimum and maximum number of open verb positions in different contexts through a targeted associative experiment. The object of analysis are the verbs of actional and processual semantics, which appear in personal and impersonal meanings or combine these properties: вирувати (to eddy), заливати (to flood), зацвітати (to bloom), икати (to hiccup), казати (to say), клекотіти (to roar), котитися (to roll), переконувати (to persuade), ревіти (to howl), розливатися (to spill), свистіти (to whistle), сніжити (to snow), чавкати (to smack). It has been established that verbs of processual semantics require more dependent components, and this trend is observed with verbs that have lost their actional seme and moved to the class of processual ones. A small number of open valence positions has been established, which corresponds to the traditional scientific division, in particular, of the verb світати (to dawn), but most reactions suggest the presence of an additional number of distributors compared to the scientific division by valence characteristics. Verbs that scientists mainly classify as monovalent with a wide potential for transformation into divalent, respondents ranked as divalent or trivalent, which makes it possible to finally change the traditional division of verbs into groups based on valence features. A small number of the identified open fourth position of verb lexemes indicates the inconsistency of its allocation for direct communication.

Sulfated disaccharide protects membrane and DNA damages from arginine-rich dipeptide repeats in ALS.

Hexanucleotide repeat expansion in C9ORF72 (C9) is the most prevalent mutation among amyotrophic lateral sclerosis (ALS) patients. The patients carry over ~30 to hundreds or thousands of repeats translated to dipeptide repeats (DPRs) where poly-glycine-arginine (GR) and poly-proline-arginine (PR) are most toxic. The structure-function relationship is still unknown. Here, we examined the minimal neurotoxic repeat number of poly-GR and found that extension of the repeat number led to a loose helical structure disrupting plasma and nuclear membrane. Poly-GR/PR bound to nucleotides and interfered with transcription. We screened and identified a sulfated disaccharide that bound to poly-GR/PR and rescued poly-GR/PR-induced toxicity in neuroblastoma and C9-ALS-iPSC-derived motor neurons. The compound rescued the shortened life span and defective locomotion in poly-GR/PR expressing Drosophila model and improved motor behavior in poly-GR-injected mouse model. Overall, our results reveal structural and toxicity mechanisms for poly-GR/PR and facilitate therapeutic development for C9-ALS.

Sensor placement algorithm for faults detection in electrical secondary distribution network using dynamic programming method: focusing on dynamic change and expansion of the network configurations

Modern power grids are developing toward smartness through the use of sensors in gathering data for situation awareness, visibility, and fault detection. In most developing countries, fault detection in the electrical secondary distribution network (SDN) is very challenging due to the lack of automated systems for network monitoring. Systems for monitoring faults require sensor placement on each node, which is not economically feasible. Hence, optimal placement algorithms are required to ensure that the network is observable with few sensors possible. The existing sensor placement methods based on mathematical and heuristic approaches are efficient for transmission and primary distribution networks which are mostly static in size and layout. Such methods may not be efficient in SDN which is dynamic in size and have a relatively large number of nodes. This study proposes an enhanced dynamic programming method for sensor placement to enhance fault detection in SDN. The proposed algorithm employs the depth search concepts and the parent–children relationship between nodes to determine sensor types and locations considering the optimal cost. The proposed algorithm was compared with other methods including particle swarm optimization, genetic algorithm, and chaotic crow search algorithm using different network configurations. The results revealed that the proposed algorithm suggested the minimum number of sensors and shortest convergence time of 1.27 min. The results also revealed that, on network expansion, maintaining the location of the existing sensors is more cost-effective by 20% than reallocating the existing sensors. Furthermore, the results revealed that an average of 30% of nodes, need sensors to observe the entire network, hence cost optimization.

Low binder content bricks: a regolith-based solution for sustainable surface construction on the Moon

This work proposes a composite construction material made by a blend of lunar regolith and thermoplastic binders in dry powder form. This solution offers advantages over regolith sintering or melting by requiring lower power consumption and simplifying the manufacturing process. However, its sustainability depends on minimizing the content of the binder material. Drawing from validated concepts used on Earth, such as polymeric concrete and compressed Earth bricks, this paper suggests that binder optimization can be achieved by simplifying and streamlining the manufacturing process, targeting parts with predefined shapes. Standardized elements like bricks or tiles ease production and assembly automation, especially when incorporating interlocking features, simplifying the payload concept transition. After drafting the process with a minimum number of basic steps, this work studies the effects of some process parameters to minimize the weight percentage of the matrix while maintaining reasonable mechanical properties. The compressive and the flexural strength are the targets of an orthogonal array Design of Experiment. Through comparison with reference values for civil engineering, the process demonstrates promising results within an organic phase as low as 10 wt%.

Tumor de células de la granulosa tipo juvenil tras la menopausia

Granulosa cell tumors are rare ovarian tumors. There are two histological types: adult and juvenile. Juvenile granulosa cell tumors account for 5%, with only 3% occurring in people over 30 years of age. Given the suspicion, the definitive intraoperative diagnosis is complex given its rarity and its easy confusion with other ovarian neoplasms. The cystic pattern with immature granulosa cells, with frequent mitosis, the absence of Call-Exner bodies and the immunocystic study confirm this. Its low prevalence makes it difficult to diagnose. The stage of the disease is the most important prognostic factor, and complete resection is essential. The role of complementary therapy is not well established, and the available studies include only a minimal number of cases, which do not differentiate between adult women. Adequate follow-up for the early detection of a possible late recurrence is a clinical challenge. Keywords: Granulosa cell tumor, Juvenile granulosa cell tumor, Ovarian neoplasms, Menopause.

Assessment of the importance of platelet transfusion in patients with severe dengue: a systematic review

Introduction: Dengue is one of the most important vector-borne viral diseases in subtropical and tropical regions. The World Health Organization (WHO) 2009 classified dengue into three groups: dengue without alarm signs, dengue with alarm signs, and severe dengue. According to the type of dengue, various managements have been proposed. The authors suggest that a predictive factor to avoid a poor prognosis in this disease is to keep platelet levels stable in the patient to prevent a fatal outcome. The aim of this paper is to analyze the efficacy of transfusion of platelet agents in the outcome of patients with severe dengue and thrombocytopenia. Material and methods: A bibliographic search was carried out in the Medline, OVID, and Scielo databases from January 1, 2008, to April 31, 2023, using the MeSH terms. Results: 7 articles were included in the systematic review. A wide range in age was found (18 to 79 years). A minimal number of studies detail the comorbidities of patients in their enrollment. Regarding platelet transfusion, the average number of platelet units used in the transfusion case was 5 (2 - 14). Transfusions of ABO identical and compatible pooled platelets transfusion were found to be more successful in increasing platelets. Almost all of the patients included in the studies had platelets <20,000 at enrollment. One study found a significant increase in platelets after transfusion, while the rest did not find it compelling. No mortality associated with platelet transfusion was recorded. Conclusions: Prophylactic platelet transfusion is not recommended as a routine measure in patients with severe dengue and thrombocytopenia. The uncertainty highlights need to reach a specific consensus establishing the appropriate indications for platelet transfusion and what type of patients with dengue virus would be beneficial.

Metatarsals and foot phalanges from the Sima de los Huesos Middle Pleistocene site (Atapuerca, Burgos, Spain).

This study provides a complete, updated and illustrated inventory, as well as a comprehensive study, of the metatarsals and foot phalanges (forefoot) recovered from the Middle Pleistocene site of Sima de los Huesos (SH, Atapuerca, Spain) in comparison to other Homo comparative samples, both extant and fossils. This current updated review has established a minimum number of individuals (MNI) of 17, which represent 58.6% of the 29 dental individuals identified within the SH sample. An exclusive or autoapomorphic combination of traits can be recognized within the SH hominin foot sample. A few traits appear primitive or plesiomorphic when compared with earlier Homo individuals and other recent modern humans. There are other metrical and morphological traits that SH hominins and Neandertals have in common that sometimes represent shared derived traits in this evolutionary line, most of which are probably related to robusticity. Furthermore, some exclusive autoapomorphic traits are observed in the SH sample: a very broad first metatarsal, long and broad hallucal proximal foot phalanges and possibly extremely robust lateral distal foot phalanges compared to those of Neandertals and modern humans. In these last traits, the SH metatarsals and pedal phalanges are even more robust than in Neandertals. They are herein named as "hyper-Neandertal" traits, which could suggest a slight gracilization process in this evolutionary line, at least in the hallux toe. Finally, some paleobiological inferences are made in relation to body size (stature and body mass) and some associations are proposed within the SH sample.

Motion intention recognition of the affected hand based on the sEMG and improved DenseNet network

The key to sEMG (surface electromyography)-based control of robotic hands is the utilization of sEMG signals from the affected hand of amputees to infer their motion intentions. With the advancements in deep learning, researchers have successfully developed viable solutions for CNN (Convolutional Neural Network)-based gesture recognition. However, most studies have primarily concentrated on utilizing sEMG data from the hands of healthy subjects, often relying on high-dimensional feature vectors obtained from a substantial number of electrodes. This approach has yielded high-performing sEMG recognition systems but has failed to consider the considerable inconvenience that the abundance of electrodes poses to the daily lives and work of patients. In this paper, we focused on transradial amputees and used sEMG data from the Ninapro DB3 database as our dataset. Firstly, we introduce a STFT (Short-Time Fourier Transform)-based time-frequency feature fusion map for sEMG. This map includes both time-frequency features and the time-frequency localization of sEMG signals. Secondly, we propose an Improved DenseNet (Dense Convolutional Network) model for recognizing motion intentions in the affected hand of amputees based on their sEMG signals. Finally, addressing the issue of optimizing the number of electrodes carried by amputees, we introduce the PCMIRR (Pearson Correlation and Motion Intention Recognition Rate) algorithm. This algorithm optimizes the number of channels by considering the Pearson correlation between the sEMG channels of amputees and the recognition rate of motion intentions in the affected hand based on single-channel sEMG data. The experimental results reveal that the recognition accuracy, recall, and F1 score achieved by the Improved DenseNet model were 93.82%, 93.61%, and 93.65%, respectively. When the number of electrodes was optimized to 8, the recognition accuracy reached 94.50%. In summary, this paper ultimately attained precise recognition of motion intentions in amputees' affected hands while utilizing the minimum number of sEMG channels. This method offers a novel approach to sEMG-based control of bionic robotic hands.

Dual independent pathway‐densely connected residual network with dilated convolution‐based arterial spin labeling MRI image reconstruction with minimum label‐control pairs

AbstractArterial spin labeling (ASL) is a non‐invasive MRI technique widely used to measure cerebral blood flow (CBF), but it suffers from poor SNR, requiring the acquisition of a large number of multiple Label‐Control (L‐C) pairs at the expense of prolonged acquisition time. This work proposed a novel deep learning network to reconstruct the ASL CBF map using the minimum number of L‐C pairs. A dataset comprising 72 normal ASL raw images with 52 L‐C pairs is obtained from ADNI2. The mean CBF map, derived from 52 L‐C pairs with Gaussian smoothing and outlier cleaning, serves as the reference. The mean CBF images obtained from randomly selected 10 pairs per subject, without preprocessing, are employed as input for the proposed model. A novel data augmentation technique for model training, leveraging the characteristics of ASL L‐C pairs, is implemented. The accuracy and reproducibility of the reconstructed ASL CBF map were assessed with various state‐of‐the‐art methods on both normal and Alzheimer's Disease (AD) data. The proposed model surpasses state‐of‐the‐art methods, yielding PSNR = 23.9542, SSIM = 0.81499, and Lin's CCC = 0.9168 for the ASL CBF map with 10 L‐C pairs in normal data. For AD patients, the model achieves PSNR of 22.5932, SSIM of 0.80923, and Lin's CCC of 0.9078. The Bland–Altman plot, using the radiologist's manual GMCBF ROI, consistently aligns the estimated and reference CBF values. The novel data augmentation technique improved the ASL CBF map quantification accuracy with Lin's CCC >0.9. The proposed work is a promising approach to reconstructing the ASL CBF map using a minimum number of ASL LC pairs that can lead to low image acquisition time with a reduction in motion artifacts. The use of a novel data augmentation approach, utilizing the properties of ASL L‐C pairs, allows for the generation of a large dataset for further experimentation and analysis.

Energy‐efficient hybrid beamforming for millimeter‐wave‐based massive multiple‐input multiple‐output system

SummaryThe advanced wireless communication system requires abridged energy consumption, enhanced data rate, and good signal coverage. The massive MIMO technology for 5G systems has been developed to accommodate several users simultaneously with superior throughput. The claim for high data rate wireless communication services is expanding quickly as time goes. Thus, the key difficulty is that as the number of users grows, the number of phase shifters grows as well, causing the system to consume more power; as a result, the system's energy efficiency decreases. Hybrid beamforming has recently emerged as an attractive technique for millimeter‐wave (mmWave) communication systems. The analog beamformer in the RF domain and digital beamformer in the baseband are coupled through a minimal number of RF chains in hybrid beamforming architecture. Hybrid beamforming utilizes fewer RF (radio frequency) chains than the total number of antennas to have a lower energy consumption design. The hybrid beamforming for a mmWave‐based massive MIMO system through different phase shifter selection mechanisms is proposed to achieve the highest energy efficiency for mmWave communications systems. The fully connected with phase shifter selection, sub‐connected with phase shifter selection (SPSS), and fully connected and sub‐connected with phase shifter selection with halved and doubled switches are considered for this research. The simulation results show the SPSS with halved switch outperforms on energy efficiency.

A new submodule‐based generalized multilevel inverter topology with reduced switches and DC sources

SummaryMultilevel inverters are known as essential converters in renewable sources. First, in this paper, a new submodule is presented, and based on it, a new sub‐multilevel inverter is presented. The proposed sub‐multilevel inverter consists of several unidirectional and bidirectional switches and DC voltage sources. Then, the generalized topology, developed in two modular and cascaded modes, is presented to increase production levels. The proposed submodules are connected in series in the modular topology, increasing production levels. The proposed topology to produce the maximum output levels has the minimum number of IGBTs, drivers, DC voltage sources, etc. Mathematical analyses for conduction and switching losses are provided, and mathematical analyses for the number of devices and voltage across the switches are also presented. In addition to the mathematical analysis of losses, the simulation results are also presented. A general comparison of proposed topology components is presented to demonstrate their advantages. This comparison shows that the proposed topology has the minimum number of power electronic devices. In this paper, nearest level modulation is used to control the proposed topology. The simulation and experimental results of the proposed sub‐multilevel verify the performance of the proposed topology.

Multivariate Genetic Analyses Unveil the Complexity of Grain Yield and Attributing Traits Diversity in Oryza sativa L. Landraces from North-Eastern India

In the North-Eastern region of India, rice stands as the predominant staple, with diverse cultivars evolving over the past six decades. This study systematically evaluated 20 rice landraces, analyzing eleven variables related to yield and its attributing traits. The aim was to identify promising genotypes for potential breeding programs and to ascertain the minimum number of components essential for explaining the total diversity. Among the eleven principal components (PCs) examined, four PCs exhibited eigenvalues surpassing 1.0, collectively contributing to 80.45% of the total variability in the traits. PC1, which explained 31.19% of the overall variance, was associated with plant height, days to 50% flowering, panicle length, grain breadth, and grain length-to-breadth ratio. Utilizing cluster analysis, the 20 rice landraces were categorized into seven distinct clusters. Maximum inter-cluster divergence was observed between clusters VI and I, as well as clusters VI and V, indicating greater genetic distinctiveness among genotypes in these clusters compared to others. Notably, rice landraces such as Borosolpana, Phougak, Satyaranjan, Kakcheng Phou, Moniram, Kanaklata, and Bahadur were identified as genetically divergent. These genotypes hold promise for generating segregating populations, serving as valuable source materials for targeted yield improvement through meticulous selection, as indicated by inter-cluster distances.

Optimization Algorithm for AoI-Based UAV-Assisted Data Collection

Regarding the issue of information freshness in systems that aid in data collection using unmanned aerial vehicles (UAVs), a data collection algorithm that is based on freshness and UAV assistance is proposed. Under the limitations of wireless sensor node communication distance and UAV parameters, the optimization problem of minimizing the average spatial correlation age of information (SCAoI) of all nodes in the area is set up. This problem is solved by optimizing the number of clusters, UAV flight trajectories, and the order of data collection from cluster member nodes. The maximum communication distance of the nodes is used as the cluster formation radius, and the maximum-minimum distance clustering algorithm is used to cluster the nodes in the region to obtain the minimum number of clusters. After it has been proven that the trajectory optimization problem in this study is NP-hard, the ant colony algorithm is applied to obtain the minimum flight time and the corresponding trajectory. By using the greedy algorithm to determine the member nodes in the sequence of data collection for a cluster, the instantaneous SCAoI of the UAV arriving at the cluster head is solved. Simulation results show that the proposed algorithm in this paper can effectively improve the freshness of data and reduce the average SCAoI of the system compared with the algorithm in the comparative literature, reducing the average SCAoI by about 61%.

Two Repetitions May Be Enough! Reliability of Movement Timing in Physical Fitness Exercises Performed by Young, Trained Adults Using Inertial Sensors

This study aimed to determine the minimum number of repetitions for a high reliability of movement timing in fundamental physical fitness exercises using inertial sensors. Fifteen young men and fifteen women performed eight exercises (two-leg hop, forward lunge, squat, sit-up, shoulder abduction, hip abduction, back extension, and push-up) (preferred tempo, 3 trials, 20 repetitions per trial). The movement timing (cycle of movement in seconds and its phases in seconds and %tcycle) was tested for intra- and inter-trial reliability (SPSS 28.0, p ≤ 0.05). Just two repetitions were adequate for excellent intra- and inter-trial relative reliability (ICCs ≥ 0.75, isolated exceptions only for durations expressed as %tcycle, in only three out of the eight exercises: hip abduction, back extension, and push-up), as well as for high absolute intra- and inter-trial reliability (average SEM% at 5.9%, respectively, and 6.8% and average MDC95% at 13.7% and 15.9%, respectively, which was consistently higher than the upper boundary limit of SEM%, and a rather low CV% ranging from 1.5% to 4.9% and averaging at 3.1%). A total of four repetitions, excluding the initial and the final one, appears adequate for high overall reliability of movement timing in the eight physical fitness exercises examined.

A Modified Form of Inertial Viscosity Projection Methods for Variational Inequality and Fixed Point Problems

This paper aims to introduce an iterative algorithm based on an inertial technique that uses the minimum number of projections onto a nonempty, closed, and convex set. We show that the algorithm generates a sequence that converges strongly to the common solution of a variational inequality involving inverse strongly monotone mapping and fixed point problems for a countable family of nonexpansive mappings in the setting of real Hilbert space. Numerical experiments are also presented to discuss the advantages of using our algorithm over earlier established algorithms. Moreover, we solve a real-life signal recovery problem via a minimization problem to demonstrate our algorithm’s practicality.

Effects of structured exercise program on severity of dizziness, kinesiophobia, balance, quality of sleep, activities of daily living and quality of life in bilateral vestibular hypofunction: case study

Background and Purpose. The vestibular rehabilitation is an exercise-based method, aiming to maximize central nervous system(CNS) compensation at vestibular nuclear and other CNS levels for vestibular pathology. A minimal number of studies have documented the impact of Vestibular rehabilitation on the recovery rate of patients with Bilateral Vestibular Hypofunction(BVH). The purpose of this study was to investigate the effectiveness of structured vestibular rehabilitation (VR) programs on severity of dizziness, kinesiophobia, balance, quality of sleep, activities of daily living(ADL) and quality of life(QoL) in subjects with chronic BVH. Case Description. Three participants diagnosed with BVH who suffered from severity of dizziness, kinesiophobia, balance, quality of sleep, ADL and QoL were included in the study. Intervention. A structured VR program was applied in 50-minute sessions once a week and as a home exercise program 3 days a week over 8 weeks. Outcomes. Participants were evaluated for severity of dizziness with the Visual Analog Scale (VAS), for kinesiophobia with the Tampa Scale of Kinesiophobia (TSK), for balance with the Semitandem, tandem, and standing tests, for quality of sleep with the Pittsburgh Sleep Quality Index (PSQI), for ADL with the Vestibular Disorders Activities of Daily Life (VADL) and for QoL with Dizziness Handicap Inventory (DHI) at the baseline (T0), at 4th week (T1), 8th week (T2), and 20th week (T3) after study started. Conclusion. In conclusion, a twelve-week structured VR program may enhance severity of dizziness, kinesiophobia, balance, quality of sleep, ADL and QoL in participants with chronic BVH.

Predicting building energy consumption in urban neighborhoods using machine learning algorithms

Assessing building energy consumption in urban neighborhoods at the early stages of urban planning assists decision-makers in developing detailed urban renewal plans and sustainable development strategies. At the city-level, the use of physical simulation-based urban building energy modeling (UBEM) is too costly, and data-driven approaches often are hampered by a lack of available building energy monitoring data. This paper combines a simulation-based approach with a data-driven approach, using UBEM to provide a dataset for machine learning and deploying the trained model for large-scale urban building energy consumption prediction. Firstly, we collected 18,789 neighborhoods containing 248,938 buildings in the Shanghai central area, of which 2,702 neighborhoods were used for UBEM. Simultaneously, building functions were defined by POI data and land use data. We used 14 impact factors related to land use and building morphology to define each neighborhood. Next, we compared the performance of six ensemble learning methods modeling impact factors with building energy consumption and used SHAP to explain the best model; we also filtered out the features that contributed the most to the model output to reduce the model complexity. Finally, the balanced regressor that had the best prediction accuracy with the minimum number of features was used to predict the remaining urban neighborhoods in the Shanghai central area. The results show that XGBoost achieves the best performance. The balanced regressor, constructed with the 9 most contributing features, predicted the building rooftop photovoltaics potential, total load, cooling load, and heating load with test set accuracies of 0.956, 0.674, 0.608, and 0.762, respectively. Our method offers an 85.5%-time advantage over traditional methods, with only a maximum of 22.75% of error.

Effects of combined exercise training with sleep education in older adults with obstructive sleep apnea: protocol for a randomized clinical trial.

Obstructive sleep apnea (OSA) is a common disorder that affects approximately 1 billion people worldwide. Advanced age is a significant risk factor. Various treatment options have been explored to reduce the severity of OSA symptoms and physical exercise has emerged as a potential alternative therapy. Therefore, this study aims to investigate the effects of a combined exercise program with sleep education on sleep quality and on the severity of OSA in older adults. This is a randomized clinical trial with two parallel groups that will involve individuals of both genders aged between 60 and 79 years who have an apnea-hypopnea index (AHI) of more than 15 events per hour and who have not received or are currently undergoing treatment for OSA. Older adults who have engaged in regular exercise in the last six months and individuals with contraindications to exercise will be excluded. The study will assess outcomes related to OSA, including AHI, oxygen desaturation index, minimum and mean oxyhemoglobin saturation, sleep efficiency, sleep latency, and the type of respiratory events. Additionally, sleep quality-related outcomes, daytime sleepiness, physical activity, physical fitness, aerobic capacity, cognitive status, anthropometric measures, and health-related quality of life will be analyzed. Participants will be randomized to two groups: a combined exercise group (involving both resistance and aerobic training) with sleep education, and a control group that will receive only educational recommendations for managing OSA. The intervention will last 12 weeks and will consist of three sessions per week, totaling 36 exercise sessions. Sample size calculation indicates a minimum number of 36 participants. If the hypothesis is confirmed, this clinical trial will indicate an effective non-pharmacological intervention for treating OSA in older adults. This intervention could be used as an adjunct to existing approaches designed to improve OSA management. Brazil Clinical Trials Registry (ReBEC), identifier RBR-9hk6pgz.

3D object tracking using integral imaging with mutual information and Bayesian optimization

Integral imaging has proven useful for three-dimensional (3D) object visualization in adverse environmental conditions such as partial occlusion and low light. This paper considers the problem of 3D object tracking. Two-dimensional (2D) object tracking within a scene is an active research area. Several recent algorithms use object detection methods to obtain 2D bounding boxes around objects of interest in each frame. Then, one bounding box can be selected out of many for each object of interest using motion prediction algorithms. Many of these algorithms rely on images obtained using traditional 2D imaging systems. A growing literature demonstrates the advantage of using 3D integral imaging instead of traditional 2D imaging for object detection and visualization in adverse environmental conditions. Integral imaging’s depth sectioning ability has also proven beneficial for object detection and visualization. Integral imaging captures an object’s depth in addition to its 2D spatial position in each frame. A recent study uses integral imaging for the 3D reconstruction of the scene for object classification and utilizes the mutual information between the object’s bounding box in this 3D reconstructed scene and the 2D central perspective to achieve passive depth estimation. We build over this method by using Bayesian optimization to track the object’s depth in as few 3D reconstructions as possible. We study the performance of our approach on laboratory scenes with occluded objects moving in 3D and show that the proposed approach outperforms 2D object tracking. In our experimental setup, mutual information-based depth estimation with Bayesian optimization achieves depth tracking with as few as two 3D reconstructions per frame which corresponds to the theoretical minimum number of 3D reconstructions required for depth estimation. To the best of our knowledge, this is the first report on 3D object tracking using the proposed approach.

Algorithmic Complexity and Bounds for Domination Subdivision Numbers of Graphs

Let G=V,E be a simple graph. A subset D⊆V is a dominating set if every vertex not in D is adjacent to a vertex in D. The domination number of G, denoted by γG, is the smallest cardinality of a dominating set of G. The domination subdivision number sdγG of G is the minimum number of edges that must be subdivided (each edge can be subdivided at most once) in order to increase the domination number. In 2000, Haynes et al. showed that sdγG≤dGv+dGv−1 for any edge uv∈EG with dGu≥2 and dGv≥2 where G is a connected graph with order no less than 3. In this paper, we improve the above bound to sdγG≤dGu+dGv−NGu∩NGv−1, and furthermore, we show the decision problem for determining whether sdγG=1 is NP-hard. Moreover, we show some bounds or exact values for domination subdivision numbers of some graphs.