Test Path Research Articles

Developing and Field Testing Path Planning for Robotic Aquaculture Water Quality Monitoring

Marine food chains are highly stressed by aggressive fishing practices and environmental damage. Aquaculture has increasingly become a source of seafood which spares the deleterious impact on wild fisheries. However, continually monitoring water quality to successfully grow and harvest fish is labor intensive. The Hybrid Aerial Underwater Robotic System (HAUCS) is an Internet of Things (IoT) framework for aquaculture farms to relieve the farm operators of one of the most labor-intensive and time-consuming farm operations: water quality monitoring. To this end, HAUCS employs a swarm of unmanned aerial vehicles (UAVs) or drones integrated with underwater measurement devices to collect the in situ water quality data from aquaculture ponds. A critical aspect in HAUCS is to develop an effective path planning algorithm to be able to sample all the ponds on the farm with minimal resources (i.e., the number of UAVs and the power consumption of each UAV). Three methods of path planning for the UAVs are tested, a Graph Attention Model (GAM), the Google Linear Optimization Package (GLOP) and our proposed solution, the HAUCS Path Planning Algorithm (HPP). The designs of these path planning algorithms are discussed, and a simulator is developed to evaluate these methods’ performance. The algorithms are also experimentally validated at Southern Illinois University’s Aquaculture Research Center to demonstrate the feasibility of HAUCS. Based on the simulations and experimental studies, HPP is particularly suited for large farms, while GLOP or GAM is more suited to small or medium-sized farms.

Creep Characteristics and Creep Model of Coal Based on Pore Water Pressure

Anthracite in a specific area of Shanxi Province is the subject of this essay’s research. In the creep studies, different porosity intervals and pore water pressures were employed to evaluate the mechanical properties of creep under various test paths. The conventional Burges model was coupled in series with the nonlinear viscous elements and plastic elements. The key parameters in the equation are fitted, and a creep model is created to describe the nonlinear viscosity-elastic-plastic characteristics of coal under the influence of pore water pressure with varying porosities. The creep tests used varied porosity intervals, pore water pressures, and test paths to study the mechanical properties of creep. The conventional Burges model was coupled in series with the nonlinear viscous element and plastic element. To represent the nonlinear viscosity-elastic-plastic properties of coal under the effect of pore water pressure with variable porosities, the main parameters in the equation are fitted, and a creep model is developed. The results show that the porosity and strength of the coal sample are negatively correlated. In comparison to coal samples with a porosity of 5–10%, the uniaxial compressive strength of coal samples with a porosity of 10–15% and 15–20% reduced by 9.6% and 22.3%. Throughout the creep process, instantaneous strain rises with porosity, and changes in pore water pressure and porosity have an effect on instantaneous creep under low-stress loading, resulting in different creep curve starting strain values. The duration from stress loading to the accelerated creep stage in the failure stage and the time from the deceleration creep stage to the accelerated creep stage are both gradually shortened with an increase in porosity and pore water pressure. For regression analysis and parameter identification, a creep constitutive model was developed to describe the creep characteristics of coal samples with varying porosity under varying pore water pressure. The creep parameters of the new constitutive model were obtained, and they could very well reflect the creep characteristics of specimens with varying porosity intervals under the influence of pore water pressure.

Research on the comprehensive Literacy test and evaluation of English course students based on cloud education big data

In the innovation and development of modern education, the Internet, big data, cloud computing and so on have had a profound impact on the implementation of college English education curriculum. Especially after the development trend of economic globalization, college English courses pay more attention to optimizing the comprehensive quality of students in the face of the new talent training requirements put forward by the development of social and economic construction. Through the questionnaire survey, the main problems in the field of education are to study the current content of college students' comprehensive English quality test and evaluation, actively explore the test and evaluation path of students' comprehensive English quality under the background of big data, and clarify the implementation countermeasures of future college English courses according to the development trend of cloud education big data technology. On the basis of understanding the development status of cloud education big data technology, this paper constructs the testing and evaluation system of students' comprehensive quality from various aspects, such as motivation, attitude and quality, according to the requirements of English course students' comprehensive literacy training, and finally puts forward clear education management measures.

Research on the comprehensive Literacy test and evaluation of English course students based on cloud education big data

In the innovation and development of modern education, the Internet, big data, cloud computing and so on have had a profound impact on the implementation of college English education curriculum. Especially after the development trend of economic globalization, college English courses pay more attention to optimizing the comprehensive quality of students in the face of the new talent training requirements put forward by the development of social and economic construction. Through the questionnaire survey, the main problems in the field of education are to study the current content of college students' comprehensive English quality test and evaluation, actively explore the test and evaluation path of students' comprehensive English quality under the background of big data, and clarify the implementation countermeasures of future college English courses according to the development trend of cloud education big data technology. On the basis of understanding the development status of cloud education big data technology, this paper constructs the testing and evaluation system of students' comprehensive quality from various aspects, such as motivation, attitude and quality, according to the requirements of English course students' comprehensive literacy training, and finally puts forward clear education management measures.

Experimental study on failure characteristics of single-sided unloading rock under different intermediate principal stress conditions

Investigation of unloading rock failure under different σ2 facilitates the control mechanism of excavation surrounding rock. This study focused on single-sided unloading tests of granite specimens under true triaxial conditions. The strength and failure characteristics were studied with micro-camera and acoustic emission (AE) monitoring. Furthermore, the choice of test path and the effect of σ2 on fracture of unloading rock were discussed. Results show that the increased σ2 can strengthen the stability of single-sided unloading rock. After unloading, the rock's free surface underwent five phases, namely, inoculation, particle ejection, buckling rupture, stable failure, and unstable rockburst phases. Moreover, at σ2≤30 MPa, the b value shows the following variation tendency: rising, dropping, significant fluctuation, and dropping, with dispersed damages signal. At σ2≥40 MPa, the tendency shows: a rise, a decrease, a slight fluctuation, and final drop, with concentrated damages signal. After unloading, AE energy is mainly concentrated in the micro-energy range. With the increased σ2, the micro-energy ratio rises. In contrast, low, medium and large energy ratios drop gradually. The increased tensile fractures and decreased shear fractures indicate that the failure mode of the unloading rock gradually changes from tensile-shear mode to tensile-split one. The fractional dimension of the rock fragments first increases and then decreases with an inflection point at 20 MPa. The distribution of SIF on the planes changes as σ2 increases, resulting in strengthening and then weakening of the rock bearing capacity.

General temporal ghost imaging model with detection resolution and noise.

Improving imaging quality while reducing the sampling time simultaneously is a crucial challenge that limits the practical application of temporal ghost imaging (TGI). To improve the performance of TGI, various methods have been proposed and verified. However, a work analyzing in detail the influence of intensity accuracy and detection noise of TGI is still absent. Here, we establish an evaluation model to quantify the imaging quality of TGI and differential TGI (DTGI). Our model considers the intensity detection accuracy, threshold, and noise of the test path during image reconstruction and quantifies their influences by developing general imaging formulas of (D)TGI. We also simulate the imaging of (D)TGI numerically. The evaluation demonstrates that (D)TGI is relatively not sensitive to detection accuracy and thresholds of the test path, and image quality is degraded slightly even when those parameters turn much worse. (D)TGI is relatively robust to detection noise but will be unable to reconstruct the object when noise is too strong. DTGI does not show clear advantages over TGI. Our work develops an effective model to quantify the image quality with practical parameters and is significant to real applications of (D)TGI.

SPIDER: Speeding up Side-Channel Vulnerability Detection via Test Suite Reduction

Side-channel attacks allow adversaries to infer sensitive information, such as cryptographic keys or private user data, by monitoring unintentional information leaks of running programs. Prior side-channel detection methods can identify numerous potential vulnerabilities in cryptographic implementations with a small amount of execution traces due to the high diffusion of secret inputs in crypto primitives. However, because non-cryptographic programs cover different paths under various sensitive inputs, extending existing tools for identifying information leaks to non-cryptographic applications suffers from either insufficient path coverage or redundant testing. To address these limitations, we propose a new dynamic analysis framework named SPIDER that uses fuzzing, execution profiling, and clustering for a high path coverage and test suite reduction, and then speeds up the dynamic analysis of side-channel vulnerability detection in non-cryptographic programs. We analyze eight non-cryptographic programs and ten cryptographic algorithms under SPIDER in a fully automated way, and our results confirm the effectiveness of test suite reduction and the vulnerability detection accuracy of the whole framework.

Path Unselection for Path Delay Fault Test Generation

Path selection procedures identify path delay faults whose tests detect small delay defects. Path selection criteria are positive in the sense that they point to paths that should be selected, e.g., the longest paths. However, the longest paths are in many cases untestable, and the number of paths can be large when the longest testable paths are considered. For this scenario, it is advantageous to have a negative path selection procedure that excludes paths from consideration as targets for test generation. This provides the flexibility to identify detectable path delay faults among a reduced number of path delay faults. Such a procedure is developed in this article and referred to as a path unselection procedure. The procedure performs linear-time traversals of the circuit to unselect fan-out branches, and thus exclude from consideration paths that are shorter than the ones it keeps. It also uses available information about detectable and undetectable path delay faults to unselect fan-out branches or avoid unselecting them. To demonstrate its use, the procedure is applied to benchmark circuits as part of an iterative test generation procedure whose goal is to target manageable numbers of the longest path delay faults.

Governance of non-state-owned shareholders and corporate capital structure decision: A mechanism test from the opportunistic behavior of management.

It is an important measure in the reform of state-owned enterprises to improve the efficiency of capital operation by introducing non-state-owned shareholders. This paper explores the impact of non-state shareholder governance on capital structure decision-making by using the data of 2008-2021 A-share state-owned listed companies from the perspective of the speed and deviation of capital structure adjustment. The results reveal that only non-state shareholding has no significant impact on the capital structure adjustment of a company. However, the appointment of senior management by non-state shareholders can speed up the capital structure adjustment and lower the degree of capital structure deviation. Moreover, when the capital structure goes down, the appointment of non-state-owned shareholders plays a larger role in accelerating the capital structure adjustment, which makes the deviation from the actual capital structure and the target capital structure smaller. Further research shows that the above relationship between non-state shareholder governance and the optimization and adjustment of the capital structure only exists in local SOEs and competitive SOEs. In addition, the path test found that non-state shareholder governance affects the dynamic adjustment of capital structure by reducing opportunism behavior of management rather than by financing constraints.

Environmental pollution liability insurance and green innovation of enterprises: Incentive tools or self-interest means?

The existing theoretical research on environmental liability insurance mainly focuses on system construction, development status and other aspects, and mainly consists of normative research, with relatively little empirical research. This paper uses empirical research methods to explore the impact of environmental liability insurance on the green innovation of enterprises and examines the driving role of environmental liability insurance in green innovation from the perspective of green governance. This paper, based on the list of enterprises purchasing environmental pollution liability insurance (EPLI) as published by the Ministry of Ecology and Environment, explores the impact of EPLI on the green innovation of enterprises. It is found that purchasing EPLI can significantly improve the green innovation of enterprises. The effect path test shows that EPLI can promote the green innovation of enterprises by relaxing financing constraints and reducing agency costs. The heterogeneity scenario test shows that compared with non-state-owned enterprises, non-heavily polluting enterprises, and enterprises in regions with a lower intensity of environmental regulation, EPLI plays a stronger role in the promotion of green innovation of state-owned enterprises, heavily polluting enterprises and enterprises in regions with a higher intensity of environmental regulation. In addition, it is found that the promotion effect of EPLI on green innovation is mainly reflected in the significant improvement of high-quality green innovation and the optimization of the structure of the green patent output. This paper affirms the positive role of EPLI on the green operations of enterprises and provides empirical evidence that green insurance serves the development of the green innovation of enterprises.

Formal Verification of Robot Rotary Kinematics

With the widespread application of robots in aerospace, medicine, automation, and other fields, their motion safety is essential for the well-being of humans and the accomplishment of vital socially beneficial programs. Conventional robot hardware and software designs mainly rely on experiential knowledge and manual testing to ensure safety, but this fails to cover all possible testing paths and adds risks. Alternatively, formal, mathematically rigorous verifications can provide predictable and reliable guarantees of robot motion safety. To demonstrate the feasibility of this approach, we formalize the mathematical coordinate transformation of a robot’s rigid-body kinematics using the Coq Proof Assistant to verify the correctness of its theoretical design. First, based on record-type matrix formalization, we define and verify a robot’s spatial geometry by constructing formal expressions of the matrix’ Frobenius norm, trace, and inner product. Second, we divide rotary motion into revolution and rotation construct and provide their formal definitions. Next, we formally verify the rotational matrices of angle conventions (e.g., roll–pitch–yaw and Euler), and we complete the formal verification of the Rodriguez formula to formally verify the correctness of the motion theory in specific rotating kinematics problems. The formal work of this paper has a variety of essential applications and provides a generalizable kinematics analysis framework for robot control system verification. Moreover, it paves the way for automatic programming capabilities.

The Effect of Placement and Competence on Employee Performance through Motivation as an Intervening Variable (Bank Case study, Mandiri Gandaria Branch)

This study aims to determine the effect of job placement and competence on employee performance with work motivation as an intervening variable at PT. Bank Mandiri Gandaria Branch. The sample used in this study were 100 employees who worked at the Gandaria branch office by using a questionnaire to collect data. The sampling technique used a saturated sample. Data analysis technique using path analysis produces validity, reliability, classical assumption test using multicollinearity test, path test and hypothesis testing. The results showed that the variable placement and competence have a significant effect on employee performance variables through indirect motivation, placement variables affect employee performance through motivation, competence variables affect employee performance through motivation. The placement variable has a direct effect on employee performance, the competence variable has a significant effect on employee performance.

Does Internet Infrastructure Construction Improve Corporate Green Innovation? Evidence from China

Green technology innovation has become a breakthrough topic in the coordinated development of economic growth and environmental protection. Although the Internet is likely to become a key driver of transformative environmental change and innovation, studies on the impact of internet infrastructure on green innovation and analyses of the paths are still extremely scarce. Based on a sample of China’s listed companies from 2009 to 2019, this paper treats the Broadband China pilot strategy as a quasi-natural experiment and adopts the time-varying difference-in-differences (DID) model to explore the effect and the transmission path of internet infrastructure construction on green innovation. The study finds that Broadband China significantly promotes green innovation, and the result remains consistent after a series of robustness tests. The transmission path test proves that internet infrastructure construction affects green innovation by improving the degree of informatization, human capital, and internet media reports and by reducing financing constraints. Furthermore, considering the heterogeneity effect, the Broadband China strategy has a greater stimulating effect on state-owned, large-scale, high-tech enterprises; enterprises in low-competition industries; enterprises in growth and mature stages; and enterprises registered in the central and eastern regions. This paper systematically analyzes the effects of internet infrastructure on the green innovation of enterprises based on economic informatics theory, providing new insights for improving internet infrastructure and green innovation in practice.

Enhanced Multi-Verse Optimizer (TMVO) and Applying it in Test Data Generation for Path Testing

Data testing is a vital part of the software development process, and there are various approaches available to improve the exploration of all possible software code paths. This study introduces two contributions. Firstly, an improved version of the Multi-verse Optimizer called Testing Multi-Verse Optimizer (TMVO) is proposed, which takes into account the movement of the swarm and the mean of the two best solutions in the universe. The particles move towards the optimal solution by using a mean-based algorithm model, which guarantees efficient exploration and exploitation. Secondly, TMVO is applied to automatically develop test cases for structural data testing, particularly path testing. Instead of automating the entire testing process, the focus is on centralizing automated procedures for collecting testing data. Automation for generating testing data is becoming increasingly popular due to the high cost of manual data generation. To evaluate the effectiveness of TMVO, it was tested on various well-known functions as well as five programs that presented unique challenges in testing. The test results indicated that TMVO performed better than the original MVO algorithm on the majority of the tested functions.

The Influence of Cash Flow, Profitability, and Sales Growth on Stock Prices With Capital Structure as Intervening Variables in Banking Companies Listed on the Indonesia Stock Exchange 2015-2019

This study aims to determine the effect of cash flow, profitability and sales growth on share prices and analyze the effect of cash flow, profitability and sales growth on stock prices with a capital structure as a variable in banking companies listed on the Indonesia stock exchange for the 2015–2019 period. Sampling using purposive sampling so that the number of samples taken is 34 companies with 5 years of observation with a total sample of 170 samples. This study uses secondary data, data collection techniques using documentation studies and literature studies and the method used is path testing. The results of this study indicate that profitability has a significant effect on capital structure, while cash flow and sales growth have no significant effect on capital structure in banking companies listed on the IDX for the 2015–2019 period. Cash flow, sales growth and capital structure have a significant effect on stock prices, while profitability has no significant effect on stock prices in banking companies listed on the IDX for the 2015–2019 period. The capital structure can mediate the effect of cash flow, profitability and sales growth on stock prices in banking companies listed on the IDX for the 2015–2019 period.

Efficiency of inertial particle separators

An Inertial Particle Separator (IPS) is a non-barrier system installed at the inlet of a gas turbine to mitigate effects of particulate ingestion on the engine. This study presents experimental data for a wide range of flow path designs and test dusts. The experiments were conducted in a bifurcating wind tunnel with a rectangular cross-section and aggressive flow turning, injecting particles with a range of sizes and shapes. A new flow path geometry exhibited higher particle separation efficiency for a variety of test dusts over a range of operating conditions, including off-design cases. The new flow path used a smaller scavenge channel than previous designs in order to reduce flow separation, though not so small as to stop large particles from entering. Data postprocessing highlights the importance of particle Stokes number, scavenge mass flow ratio, and scavenge flow expansion ratio as key parameters in IPS design. • Inertial particle separators (IPS) can prevent sand and dust from entering gas turbines. • A large number of IPS sand ingestion tests have been performed. • Certain geometric parameters of the IPS have a strong effect on sand separation efficiency. • Arizona road dust, AFRL-03, and C-spec test dusts have been used to evaluate IPS designs.

The Effect of Tax Planning, Tax Avoidance and Earnings Management on Firm Value with Institutional Ownership as Moderating Variables in Consumer Goods Industry Sector Companies

The purpose of the study in this research is to find out the Effect of Tax Planning, Tax Avoidance and Earnings Management on Firm Value moderated by Institutional Ownership with the research period from 2017 to 2019. The population in this research is IDX companies engaged in the Goods Industry Sector. Consumption during 2017 to 2019. Purposive sampling is a sampling technique taken to determine the sample in this research so that this study found a sample of 25 companies so that the total sample taken for 3 years from 25 companies is 75 companies then secondary data which is the source the data in this study were tabulated and processed with the help of smartpls then a set of test tools to support the hypothesis. In accordance with the results of the first hypothesis test through analysis with the Structural Equaliting Model (path) test the effect of the moderating effect, the first gives the result that the effect of tax planning on firm value is not moderated by institutional ownership, the second gives the result that the relationship between tax avoidance and firm value is not moderated. by institutional ownership, the third gives the result that the relationship between earnings management and firm value is moderated by institutional ownership.

The Effect of Placement and Competence on Employee Performance through Motivation as an Intervening Variable (Bank Case study, Mandiri Gandaria Branch)

This study aims to determine the effect of job placement and competence on employee performance with work motivation as an intervening variable at PT. Bank Mandiri Gandaria Branch. The sample used in this study were 100 employees who worked at the Gandaria branch office by using a questionnaire to collect data. The sampling technique used a saturated sample. Data analysis technique using path analysis produces validity, reliability, classical assumption test using multicollinearity test, path test and hypothesis testing. The results showed that the variable placement and competence have a significant effect on employee performance variables through indirect motivation, placement variables affect employee performance through motivation, competence variables affect employee performance through motivation. The placement variable has a direct effect on employee performance, the competence variable has a significant effect on employee performance.

KINERJA PEGAWAI TRANSPORTASI UDARA BADAN PENELITIAN DAN PENGEMBANGAN PERHUBUNGAN DIPENGARUHI OLEH KEPEMIMPINAN MELALUI DISIPLIN KERJA

This study aims to determine the performance of employees in the air transportation of the Research and Development Agency for Transportation is influenced by leadership through work discipline. This study was conducted using the quantitative method by distributing questionnaires to air transportation employees Research and Development Agency. In this study the researcher used the saturated sample method where the sample used was all 46 employees of the population. For the analysis method the researcher uses a path analysis test (path analysis). The results showed that leadership had a positive and significant effect on employee performance. Work discipline has a positive and significant effect on employee performance. Leadership has a positive and significant effect on work discipline. And leadership influences employee performance through work discipline in air transportation research and transportation development agencies

A Hybrid Method for Test Data Generation for Unit Testing of C/C++ Projects

In recent years, automated test data generation from source code has gained a significantpopularity in software testing. This paper proposes a method, named Hybrid, to generate test datafor unit testing C/C++ projects. The method is a combination of two test data generation methodsnamed IBVGT and WCFT. In IBVGT method, the source code is analyzed to find simple conditions.Then, bases on these conditions, IBVGT generates test data for boundary values without having tosolve test paths constraints. This makes the method faster than BVTG method when generating testdata. In Hybrid method, while generating test data using WCFT, simple conditions are collected forboundary values test data generation. Test data generated by Hybrid are able to ensure both highsource code coverage and error detection ability. In addition, Hybrid is capable of finding infeasibleexecution paths and dead code. Experimental results with some popular unit functions show thatHybrid outperforms STCFG method in terms of test data generation time and boundary values relatederror detection. IBVGT is superior to BVTG in term of test data generation time whilst its boundaryvalues related error detection ability depends on the number of simple conditions inside each unitfunction.