Constraint Factor Research Articles

The Impact of Financing Constraints on the Efficiency of Investment and Construction: Evidence from Municipal Infrastructure in China

Imperfect external capital market and internal soft budget constraints are important reasons for the issue of enterprise financing constraints. This paper studies the impact of financing constraints and influencing factors of financing constraints in municipal infrastructure investment and construction for local governments by using the panel data from 2003 to 2018 in China. The results show that, first, there are great financing constraints in municipal infrastructure investment and construction for local government in China. Second, the increase of self-financing capacity and external financing capacity can reduce the level and uncertainty of financing constraints, thus improving the efficiency of municipal infrastructure investment and construction. Third, the expansion of the city scale may reduce the uncertainty of financing constraints, but improve the level of financing constraints thus reducing the efficiency of municipal infrastructure investment and construction.

신중년 여성의 커뮤니티 참여 의의와 제약요인의 탐색

신중년 여성의 커뮤니티 참여 의의와 제약요인의 탐색

A semantic SLAM-based method for navigation and landing of UAVs in indoor environments

Autonomous navigation and landing of Unmanned aerial vehicles (UAVs) are critical functions towards full intelligence in unknown environments. However, current methods heavily rely on positioning devices or geometric maps, leading to two limitations: (1) UAVs fail to work normally indoors when signals are blocked, and (2) Navigation systems are not capable of achieving high-level decision-making missions. In this paper, we propose a novel and complete framework to realize the autonomous landing of UAVs in unknown indoor scenes based on visual SLAM, semantic segmentation, terrain estimation, and a decision-making model. Firstly, our 3D map is built on top of the visual SLAM system with semantic features, and then multiple types of maps (e.g., texture map, octo-map, grid-map, and semantic topology) are created for different function requirements. To achieve high-level scene understanding, we design a data association rule to fuse semantic features extracted by a deep learning model into the mapping process of topology structure. Next, a terrain estimation strategy is performed in the lightweight grid-map, which is modeled only via low-level elevation representation. Through multiple terrain constraints factor, a few optimized landing sites are selected in safe regions via clustering algorithm. Finally, based on the guidance of semantic topology, we construct a decision-making model for UAV landing that effectively integrates terrain safety, environment perception, and path planning. We perform extensive autonomous landing experiments on multiple indoor scenes from the TUM RGB-D dataset, and the full unknown environment maps are created simultaneously. The experiment proves that the proposed framework can select an optimal landing site for the advanced mission of UAVs effectively.

Investigation of the dynamical structures of double-chain deoxyribonucleic acid model in biological sciences

The present research investigates the double-chain deoxyribonucleic acid model, which is important for the transfer and retention of genetic material in biological domains. This model is composed of two lengthy uniformly elastic filaments, that stand in for a pair of polynucleotide chains of the deoxyribonucleic acid molecule joined by hydrogen bonds among the bottom combination, demonstrating the hydrogen bonds formed within the chain’s base pairs. The modified extended Fan sub equation method effectively used to explain the exact travelling wave solutions for the double-chain deoxyribonucleic acid model. Compared to the earlier, now in use methods, the previously described modified extended Fan sub equation method provide more innovative, comprehensive solutions and are relatively straightforward to implement. This method transforms a non-linear partial differential equation into an ODE by using a travelling wave transformation. Additionally, the study yields both single and mixed non-degenerate Jacobi elliptic function type solutions. The complexiton, kink wave, dark or anti-bell, V, anti-Z and singular wave shapes soliton solutions are a few of the creative solutions that have been constructed utilizing modified extended Fan sub equation method that can offer details on the transversal and longitudinal moves inside the DNA helix by freely chosen parameters. Solitons propagate at a consistent rate and retain their original shape. They are widely used in nonlinear models and can be found everywhere in nature. To help in understanding the physical significance of the double-chain deoxyribonucleic acid model, several solutions are shown with graphics in the form of contour, 2D and 3D graphs using computer software Mathematica 13.2. All of the requisite constraint factors that are required for the completed solutions to exist appear to be met. Therefore, our method of strengthening symbolic computations offers a powerful and effective mathematical tool for resolving various moderate nonlinear wave problems. The findings demonstrate the system’s potentially very rich precise wave forms with biological significance. The fundamentals of double-chain deoxyribonucleic acid model diffusion and processing are demonstrated by this work, which marks a substantial development in our knowledge of double-chain deoxyribonucleic acid model movements.

High-Precision Map Construction in Degraded Long Tunnel Environments of Urban Subways

In response to the demand for high-precision point cloud mapping of subway trains in long tunnel degradation scenarios in major urban cities, we propose a map construction method based on LiDAR and inertial measurement sensors. This method comprises a tightly coupled frontend odometry system based on error Kalman filters and backend optimization using factor graphs. In the frontend odometry, inertial calculation results serve as predictions for the filter, and residuals between LiDAR points and local map plane point clouds are used for filter updates. The global pose graph is constructed based on inter-frame odometry and other constraint factors, followed by a smoothing optimization for map building. Multiple experiments in subway tunnel scenarios demonstrate that the proposed method achieves robust trajectory estimation in long tunnel scenes, where classical multi-sensor fusion methods fail due to sensor degradation. The proposed method achieves a trajectory consistency of 0.1 m in tunnel scenes, meeting the accuracy requirements for train arrival, parking, and interval operations. Additionally, in an industrial park scenario, the method is compared with ground truth provided by inertial navigation, showing an accumulated error of less than 0.2%, indicating high precision.

Structure optimization of DTH hammer piston based on RBF neural network and WSO algorithm

To address the issue of piston fracture due to insufficient strength in the Down-The-Hole (DTH) hammer. The effect of the pressure state of the gas chamber on the piston motion is considered. A piston motion model is established based on the steady flow energy equation and the working principle of the piston. The finite element method is used to analyze the dynamic response of the piston during the impact of the drill bit. RBF neural network is employed to construct a surrogate model for the relationship between piston structural parameters (front-end diameter, front-end length, and center bore) and piston strength and performance (impact energy, frequency, and gas consumption). By combining this model with the white shark optimization search algorithm, the design of the DTH hammer’s piston structure parameters is optimized. The minimum piston mass is the objective function. Impact energy, frequency, air consumption and stress are constraint factors. The effect of piston life is considered while meeting rock drilling efficiency. The optimization results show that the stresses in the optimized piston structure are reduced by 13%. The proposed RBF performance prediction model combined with the optimal search algorithm can significantly improve the optimization efficiency.

Investigating the constraint role in J-CTOD relationship for compact tension (CT) specimen

The Crack Tip Opening Displacement (CTOD or δ) estimation from J-integral (J) defined by ASTM 1820 considers the CTOD dependency on material properties, and the constraint factor (m). The m in Compact Tension (CT) specimen is based on yield to tensile strength ratio (σys/σut) without taking into account of in-plane dimensions as in Single Edge Notch Bending (SENB). Hence, an attempt is made to understand the effect of crack length to specimen width (a/W), specimen thickness to specimen width (B/W) for different σys/σut on CTOD using CT specimen. A new method of estimating the CTOD from FE analysis is demonstrated and validated with 450-intercept method. It has been found that the ASTM 1820 based CTOD (δASTM) assessed values under-estimate the actual CTOD present in the CT specimen. The variation in a/W and B/W doesn’t affect the J-CTOD relationship as stated by ASTM 1820. However, the CTOD measured by FE analysis (δFE) are consistently higher than the δASTM. Therefore, an effort is made to correct the constraint factor, m based on present FE analysis by considering the effect of σys/σut. The proposed corrected constraint factor, mFE, can be employed in fracture applications that generally need both the J-integral and the CTOD.

Eco-design modeling of home products in smart wellness environments

Abstract Intelligent recuperation mode represents a novel approach to elderly care, leveraging the capabilities of the Internet of Things (IoT) and big data. In this paper, based on the SOM-improved K-means algorithm, combined with association rule algorithm mining and analysis with time constraint factor, we establish an analysis model of elderly behavior recognition and make a preliminary judgment on the health status of older people based on the physiological parameters of the model. At the same time, an outlier detection algorithm based on normal distribution is being used to evaluate the abnormal behavior of elderly individuals and an intelligent recreational home ecosystem is being built and tested. In the evaluation of functional modules, except for the nutrition management and lighting control modules, which are rated as “average,” the evaluation values of the remaining eight modules are all in the range of [3,4], and their evaluation ratings are “good” and above. The evaluation values of all dimensions in the comprehensive evaluation of functions are all greater than 3, among which the evaluation values of the dimensions of perceived usefulness and tendency to use are 4.04 and 4.17, respectively, and the evaluation grade reaches the level of “excellent.” The average satisfaction value of the test experience is 3.77, which is 0.98 higher than the satisfaction value of using traditional household products.

Solution to the problem of low sensitivity of crack closure models to material properties

The paper focuses on differences between crack closure obtained by numerical models and by experimental fatigue crack growth rates, namely for three different steels (bainitic steel, predominantly pearlitic steel and additively manufactured austenitic stainless steel). The experimental data revealed a load ratio effect different from that predicted by the most used plasticity-induced crack closure (PICC) models. The term “irreversibility of plastic deformation” was proposed in this work to be used as a material property to estimate how strong the PICC effect would be in a material. Two basic phenomena, which are usually omitted in other models, were considered in the explanation: (i) cyclic softening/hardening, (ii) brittle microcracking at the maximum load. The strip-yield model has the ability of conducting fast and accurate simulations under the variable-amplitude loading. It was demonstrated that the results of this model are practically independent of the material properties. This is caused by the consideration of only monotonic elastic–plastic material properties. To simulate real load ratio effects, the parameter β in the strip-yield model (constraint factor in compression) is proposed to be used as a variable. It enabled a generation of different ratios of monotonic and cyclic plastic zones, which in turn helped to reproduce the crack closure values observed experimentally. Discussion and explanations were provided regarding the material microstructure. The proposed approach considers unequal tensile and compressive yield stresses caused by the different irreversibility of plastic deformation, which explains the dissimilarities in the load ratio effect observed in the investigated materials. It can also improve the accuracy of residual fatigue life estimations.

Identification of hub genes that variate the qCSS12-mediated cold tolerance between indica and japonica rice using WGCNA.

Cold-tolerant QTL qCSS12-regulated 14 hub genes are involved in the chloroplastic biological processes and in the protein synthesis and degradation processes in japonica rice. Low temperature is a main constraint factor for rice growth and production. To better understand the regulatory mechanisms underlying the cold tolerance phenotype in rice, here, we selected a cold-sensitive nearly isogenic line (NIL) NIL(qcss12) as materials to identify hub genes that are mediated by the cold-tolerant locus qCSS12 through weighted gene co-expression network analysis (WGCNA). Fourteen cold-responsive genes were identified, of which, 6 are involved in regulating biological processes in chloroplasts, including the reported EF-Tu, Prk, and ChlD, and 8 are involved in the protein synthesis and degradation processes. Differential expression of these genes between NIL(qcss12) and its controls under cold stress may be responsible for qCSS12-mediated cold tolerance in japonica rice. Moreover, natural variations in 12 of these hub genes are highly correlated with the cold tolerance divergence in two rice subspecies. The results provide deep insights into a better understanding of the molecular basis of cold adaptation in rice and provide a theoretical basis for molecular breeding.

Deep learning algorithm using bispectrum analysis energy feature maps based on ultrasound radiofrequency signals to detect breast cancer.

Ultrasonography is an important imaging method for clinical breast cancer screening. As the original echo signals of ultrasonography, ultrasound radiofrequency (RF) signals provide abundant tissue macroscopic and microscopic information and have important development and utilization value in breast cancer detection. In this study, we proposed a deep learning method based on bispectrum analysis feature maps to process RF signals and realize breast cancer detection. The bispectrum analysis energy feature maps with frequency subdivision were first proposed and applied to breast cancer detection in this study. Our deep learning network was based on a weight sharing network framework for the input of multiple feature maps. A feature map attention module was designed for multiple feature maps input of the network to adaptively learn both feature maps and features that were conducive to classification. We also designed a similarity constraint factor, learning the similarity and difference between feature maps by cosine distance. The experiment results showed that the areas under the receiver operating characteristic curves of our proposed method in the validation set and two independent test sets for benign and malignant breast tumor classification were 0.913, 0.900, and 0.885, respectively. The performance of the model combining four ultrasound bispectrum analysis energy feature maps in breast cancer detection was superior to that of the model using an ultrasound grayscale image and the model using a single bispectrum analysis energy feature map in this study. The combination of deep learning technology and our proposed ultrasound bispectrum analysis energy feature maps effectively realized breast cancer detection and was an efficient method of feature extraction and utilization of ultrasound RF signals.

Designing a simple and suitable laboratory test specimen for investigating the general mixed mode I/II/III fracture problem

A novel test specimen was designed for experimental investigations of pure and mixed mode fracture. This novel test configuration is called “modified edge notched disc bend” (M-ENDB) specimen. The M-ENDB specimen has a circular disc shape with an edge crack along its diameter that is loaded using asymmetric three-point bending. Different fracture parameters including: stress intensity factors (SIFs), geometry factors, T-stress, biaxiality ratio (BR), and out-of-plane constraint factor (Tz) were determined for the suggested disc bend specimen using the extensive finite element (FE) analyses. According to the obtained results, the proposed specimen can present all combinations of mode mixities, including pure modes I, II, and III as well as mixed-mode I/II, I/III, and I/II/III deformations. Afterwards, a large number of pure and mixed-mode fracture toughness experiments were carried out on polyurethane (PUR) foam to examine the capabilities of the suggested M-ENDB specimen. Fracture path, fracture surface, fracture toughness, work of fracture, and critical T-stress of broken foams under general mixed mode conditions were investigated. Mixed mode I/II/III fracture toughness value was smaller than the pure mode I fracture toughness (KIc) value showing the weakness of brittle materials against multi-axial fracture compared to pure tensile type fracture.

Juridic Analysis of Implementation of Resolving Criminal Acts of Fraud Through Restorative Justice (Study of Directorate of General Criminal Investigation of the Riau Islands Police)

The police are law enforcement agencies that are given the authority to carry out investigations and investigations of criminal acts which are then faced with legal developments in the form of the concept of resolving criminal cases using restorative justice which aims to provide legal certainty, benefit, and justice. Therefore, this study aims to find out how the legal arrangements, implementation, and constraint factors as well as solutions related to the application of a Restorative Approach to the Settlement of Criminal Cases by the Directorate of General Criminal Investigation of the Riau Islands Police are made. This study uses empirical legal research (field) using a normative juridical approach, namely in the form of an analysis of the legal arrangements that regulate matters that become problems to obtain secondary data, and a sociological juridical approach to obtain primary data through field research. The results of this study indicate that the legal arrangements in this writing are the Circular Letter of the Chief of Police Number SE/8/VII/2018 concerning the Application of Restorative Justice in the Settlement of Criminal Cases, the Regulation of the Chief of Police Number 6 of 2019 concerning Investigation of Criminal Acts Article 12 and the State Regulation of the Republic of Indonesia Number 8 2021 on Handling Crimes Based on Restorative Justice.

Temperature dependence of pressure sensitive flow in bulk metallic glass composites

The constraint factor, C, defined as hardness, H, to the yield strength, σy, ratio, is an indirect measure of the pressure sensitivity in materials. Previous investigations determined that while C is less than 3 for crystalline materials, and remains invariant with change in temperature, it is greater than 3 for bulk metallic glasses (BMGs) and increases with increasing temperature, below their glass transition temperature, Tg. In this study, the variations in C for two BMG composites (BMGCs), which have an amorphous matrix and in situ precipitated crystalline β-Ti dendrites, which in one case transforms under stress to α”-Ti and deforms by slip in the other, as a function of temperature are examined and compared with that of a BMG. For this purpose, instrumented indentation tests, with a Berkovich tip, and uniaxial compression tests were performed to measure the H and σy, respectively, on all alloys and their constituents at temperatures in the range of 0.48Tg and 0.75Tg. σy and H of the BMGC with transforming dendrites (BMGC-T) increase and remain invariant with increasing temperature, respectively. Alternately, in BMG and the BMGC with non-transforming dendrites (BMGCNT), the same properties decrease with increasing temperature. BMGC-T has the highest C of ∼4.93 whereas that of BMGCNT and BMG are ∼3.72 and ∼3.28, respectively, at 0.48Tg. With increasing temperature, C of the BMG and BMGCNT increases with temperature, but that of the BMGC-T decreases. The values of C and their variations as a function of temperature were explained by studying the variation of pressure sensitivity of the amorphous phase and concluding that the plastic flow in BMGCs under constrained conditions, such as indentation, is controlled by the flow resistance of the amorphous matrix whereas that in uniaxial compression, which is only partially constrained, is controlled by plasticity in both the dendrites and matrix.

Three-dimensional computer-generated holography based on the hybrid iterative angular spectrum algorithm.

This paper proposes a novel three-dimensional hologram calculation method based on the angular spectrum approach, with the aim of reducing the noise generated during the hologram reconstruction process. The proposed algorithm divides the spatial domain into multiple layers and employs the angular spectrum method to propagate the image between these layers, thus avoiding the paraxial approximation. To enhance the quality of the hologram, an error iteration algorithm is utilized to alleviate the occurrence of aliasing errors when directly superimposing holograms. Moreover, constraint factors are introduced between different layers within the same region to effectively utilize spatial resources for multi-image reconstruction, thereby mitigating the noise caused by inter-layer crosstalk. The feasibility of the proposed method is demonstrated through numerical simulations and optical experiments, highlighting its potential applicability to a wide range of three-dimensional reconstruction algorithms.

NHC-LIO: A Novel Vehicle Lidar-Inertial Odometry (LIO) With Reliable Nonholonomic Constraint (NHC) Factor

NHC-LIO: A Novel Vehicle Lidar-Inertial Odometry (LIO) With Reliable Nonholonomic Constraint (NHC) Factor

The impact of ambient pressure on the gas temperature near the ceiling and air entrainment caused by two fires in a tunnel

The tunnel is a typical underground building. Estimating the heat released by the fire sources to the surrounding environment, as well as providing rapid emergency response, requires a thorough comprehension of the properties of gas temperature and air entrainment beneath tunnel ceilings. Numerical works are performed to explore the impact of pressure on the gas distribution, velocity field distribution, temperature field distribution, and air entrainment rate induced by dual interacting fires with various heat release rates in a tunnel building. The findings indicate that as the distance between fires increases, two flames undergo a transition from merging together to not merging (S/D ≥ 2). The rise in atmospheric pressure leads to an augmentation in the air intake of two fires, ultimately diminishing the intensity at which the flames merge. As the spacing or pressure decreases, the area of flame expansion on the tunnel ceiling grows. The oxygen level in the extra space between the two flames gradually rises as the ambient pressure rises. This leads to a reduction in the local gas speed and temperature. The constraint factor is utilized to describe the maximum strength of air entrainment, revealing that the air entrainment constraint factor (β) for two tunnel fires ranges from 0 to 0.2. The maximum temperature rise of ceiling gas (ΔTmax) is reached at zero fire spacing, which is about 900 °C. For two fires with large spacings (S/D ≥ 2), ΔTmax is mainly determined by ambient pressure and heat release rate. Given that less cryogenic air entrainment into the ceiling gas, a higher ΔTmax is achieved at lower ambient pressure. A segmented correlation to correlate ΔTmax of two fires is developed and well-verified using literature data, and the forecast error is within ±30%.

Role of Virtual Water Trade Under the Generalized Trade Framework in Xinjiang’s Economic Sustainable Development

Xinjiang had been suffering from acute water scarcity, which is an important constraint factor for its economic sustainability. Virtual water plays an important role in its sustainable development, and this paper tries to re-investigate the role of virtual water trade among the generalized trade framework in its sustainable development. The term generalized trade encompasses both physical and virtual trade. Physical trade refers to the transfer of commodities in monetary or barter form, and virtual trade refers to the transfer of inputs embodied in physical form (e.g., virtual water, energy, or land). It was in the water-scarce status, but it transported a net volume of about 13.1 billion tons of water to other economies, 94.6% of which was transported to other provinces. This phenomenon is contradictory to the comparative advantage theory. Water is a critical input in the production of commodities, but it is only one factor from the perspective of generalized trade. It is rich in energy resources but imports a large amount of external virtual energy from other provinces. Many labors come to Xinjiang both in physical and virtual senses. This situation indicates that generalized trade plays a more important role, and suggests that it should continue to improve its industrial system and optimize its business environment.

Operation scheduling strategy of battery energy storage system with the integration of differenced power constraint factor

The battery energy storage system (BESS) as a flexible resource can effectively achieve peak shaving and valley filling for the daily load power curve. However, the different load power levels have a differenced demand on the charging and discharging power of BESS and its operation mode. For further improving the efficiency of BESS in a demand response process, the differenced power demand should be incorporated into the BESS operation schedule. Therefore, this paper proposes a BESS operation scheduling strategy to satisfy the differenced demand based on the control of the power constraint factor. Firstly, a boundary moving method is used to solve the charging and discharging thresholds of BESS to determine the optimal charging and discharging periods. Secondly, a charging and discharging demand degree model is constructed based on the hourly charging and discharging demand. Thirdly, a BESS scheduling model with a minimum standard deviation of daily load curve is established for enhancing the peak shaving and valley filling. Finally, the case study shows that the proposed strategy can further improve the efficiency of BESS participating in demand response, improve the smoothness of the load power curve, and decrease the peak-valley difference.

Implementation of Land Acquisition Policy for the Construction of the Sumatra Barat - Riau Province Toll Road

Land acquisition is a sensitive issue that concerns the livelihood of the community. The problem of land acquisition for public interest is always feared by the community, which is carried out by the government by means of eviction. As a result, the rights of the community are threatened, because the problem of land acquisition is more sensitive, in which there are two conflicting interests, namely: the interests of the government on the one hand and the interests of the community on the other hand. Therefore, in obtaining land, an approach that is understood and accepted by both parties is needed.The purpose of this study was to determine, analyze the factors of constraints and support, and the appropriate and correct strategies for implementing land acquisition policies for the construction of toll roads. The research method used was a qualitative approach with descriptive that systematically describes the facts, characteristics of objects and subjects of empirical observation carried out concretely, accurately, clearly, and measurable by considering the variation of problems in implementing land acquisition policies for the construction of toll roads in West Sumatra Province - Riau Province.The results of the study showed that the implementation of land acquisition policies for the construction of toll roads in West Sumatra Province - Riau Province, although it has been implemented, has not been effective and tends to be slow from various factors that inhibit and support the involvement of stakeholders in carrying out land acquisition that is directly affected.