Program Code Research Articles

Development of an algorithm for code clone detection in source code based on abstract syntax tree

The object of research of this work is the algorithm for searching for duplicates in the program code based on the Abstract Syntaxes Tree (AST). The main tasks solved within the framework of this study are the detection of duplicate code and the search for vulnerabilities in the program code. The obtained results showed that the proposed algorithm is resistant to type 1 and 2 clones, which means its effectiveness in detecting similar code fragments with identical or variant text. However, for type 3 and 4 clones, the algorithm may show less efficiency due to the change in the AST structure for these types of clones. Experimental studies of the proposed algorithm showed that the algorithm can detect matches between unrelated files due to the presence of typical AST chains present in many programs. This can lead to a certain level of false positives in the detection of duplicates. Testing of the algorithm in the task of finding vulnerabilities showed that: The best recognition is observed for the «SQL injection» vulnerability, but it also has the highest number of false positives. Memory leak and null pointer dereferencing vulnerabilities are detected with equal effectiveness and false positives. «Buffer overflow» has the lowest recognition rate but fewer false positives compared to «SQL injection». The study showed that the use of AST allows for the effective detection of duplicate code and vulnerabilities in the software code. The developed tool can help software developers reduce maintenance efforts, improve code quality, and ensure software product security.

ВДОСКОНАЛЕНА МАТЕМАТИЧНА МОДЕЛЬ ТРИОБМОТКОВОЇ АСИНХРОННОЇ МАШИНИ

In phase coordinates, a mathematical model of a three-winding asynchronous machine with two windings on the stator as a structural element of electric drives and asynchronous generators with inverter and inverter-capacitor excitation for autonomous electric power plants, oriented to explicit methods of numerical integration of the system of differential equations, has been developed. The model takes into account the displacement angle between two stator windings in the range of 360º and other important factors affecting the course of electromagnetic processes occurring in the machine. On the basis of the mathematical model, a program code was developed as a means of computer verification of machine operation modes. The results of computer study performed with the help of the code confirm the suitability of the mathematical model of a three-winding asynchronous machine to take into account the influence of the displacement angle between the stator windings and their simultaneous and single power supply during the operation of the machine in motor mode. References 11, figures 10.

A Modified Approach for Forecasting Relative Humidity in Indoor Premises

In order to forecast certain microclimatic parameters in a room, such as relative humidity, it is necessary to collect a large amount of data. For this reason, an electronic system for providing comfortable conditions in a room has been developed, which is based on the becoming largely popular Internet of Things (IoT) technology. On the basis of the obtained data, the future change of the relative humidity in a room can be forecasted, which aims to ensure the health and well-being of its inhabitants. It should be noted that working with large datasets requires more sophisticated methods for prediction, and for this reason, this paper presents results obtained from a modified ordinary differential equation approach for forecasting relative humidity. For the purposes of the study, a program code was developed in Matlab. The resulting predicted relative humidity values are comparable to actual measured values, which would help to improve indoor air quality and provide thermal comfort to occupants.

Time and Energy Benefits of Using Automatic Optimization Compilers for NPDP Tasks

In this article, we analyze the program codes generated automatically using three advanced optimizers: Pluto, Traco, and Dapt, which are specifically tailored for the NPDP benchmark set. This benchmark set comprises ten program loops, predominantly from the field of bioinformatics. The codes exemplify dynamic programming, a challenging task for well-known tools used in program loop optimization. Given the intricacy involved, we opted for three automatic compilers based on the polyhedral model and various loop-tiling strategies. During our evaluation of the code’s performance, we meticulously considered locality and concurrency to accurately estimate time and energy efficiency. Notably, we dedicated significant attention to the latest Dapt compiler, which applies space–time loop tiling to generate highly efficient code for the NPDP benchmark suite loops. By employing the aforementioned optimizers and conducting an in-depth analysis, we aim to demonstrate the effectiveness and potential of automatic transformation techniques in enhancing the performance and energy efficiency of dynamic programming codes.

Smart vision-based analysis and error deduction of human pose to reduce musculoskeletal disorders in construction

PurposeThis pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.Design/methodology/approachUsing a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).FindingsResults show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.Research limitations/implicationsLiterature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.Practical implicationsThe theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.Social implicationsBy using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.Originality/valueHuman pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.

Structure of data in cell biology research

Bioinformatics is a scientific field on the border between informatics and biology where problems in the field of biology are solved using statistical methods. Another part of it are database systems which serve to store data necessary for meta-analysis. In recent years, there has been a boom mainly thanks to enabling technologies that make it possible to obtain big data about the functioning of living cells of organisms. Bioinformatics tools are necessary to process these data and form an integral part of research in modern biological and medical sciences. Scientific research focused on molecular biology, as well as medicine, is increasingly focusing on data storage. It is understood that the correct structure of the database is important for the correct interpretation of the results of their research activities. For communication between tables in the database, it is essential to set the data type, assign Primary key and Foreign key, ensure data integrity, remove data plurality and understand the research logic. Based on these needs, we created a relational database using SQL Server 2017 and Microsoft SQL Server Management Studio 2017 (SSMS). We created the source code for programming the database and filling it with data in Structured Query Language (SQL) and T-SQL on the Microsoft platform. Of the data types, we used float for numbers with a floating decimal line, integer values were assigned an integer (int), date had a date data type, and text strings had a defined nvarchar data type. Our results bring new information in the field of bioinformatics about the creation of a database structure for data storage in cell biology research. These new insights will help big data in meta-analyses of data and applying scientific results to medical and scientific practice. The database will store data obtained in real time, which will ensure relevance in pointing out biological trends, regularities, relationships and links between cellular structures. All these aspects are very important for the spatial modeling of data and the creation of models of interactions of cell structures with use for applications in medical and biological practice.

Techno-economic optimization of hybrid-electric power plants onboard cruise ships

This work aims at assessing energy, environmental and economic performances of hybrid-electric plants installed onboard large-size cruise vessels fuelled by Liquefied Natural Gas. Specifically, hybrid-electric power plants coupling combined gas electric and steam plants, reciprocating engines and lithium-ion battery pack are considered. By adopting cogeneration efficiency, carbon dioxide emissions, nitrogen oxide emissions and costs as objective functions, optimal performances were assessed by a Mixed Integer Linear Programming code, following a two-step procedure. First, the MILP code has been applied considering 8-days long, phase-mean operating profiles to identify an optimal design of the engine room. Second, power plant performances have been investigated by applying MILP code to hourly demand profiles, in order to provide more detailed insight on working schedule. Overall, as main outcome of the phase-mean analysis, the potential of combined gas electric and steam plants and lithium-ion batteries in promoting a more efficient energy utilization, reduced environmental impact and enhanced cost savings is proved. Specifically, combined gas electric and steam plant was shown to optimize objective functions during navigation and maneuvering, whereas batteries improved energy and environmental performances in the most demanding ship operating conditions. Furthermore, optimal sizing of lithium-ion battery pack was determined at 40 MWh, despite its economic competitiveness resulted to deeply rely on carbon tax. On the other hand, the hourly analysis showed that controlling the combined gas electric and steam plant and batteries according to a mixed spinning reserve-peak shaving strategy optimizes the performance of power plant even in port conditions, with almost no role played by reciprocating engines. In detail, in comparison to a reference non-hybrid electric power plant, batteries are shown to improve cogeneration efficiency and greenhouse gas emission savings by nearly 2%, whereas nitrogen oxide emissions and costs were reduced by 12% and 2%, respectively.

Simple, Efficient, and Universal Energy Decomposition Analysis Method Based on Dispersion-Corrected Density Functional Theory.

Energy decomposition analysis (EDA) is an important class of methods to explore the nature of interaction between fragments in a chemical system. It can decompose the interaction energy into different physical components to understand the factors that play key roles in the interaction. This work proposes an EDA strategy based on dispersion-corrected density functional theory (DFT), called sobEDA. This method is fairly easy to implement and very universal. It can be used to study weak interactions, chemical bond interactions, open-shell systems, and interactions between multiple fragments. The total time consumption of sobEDA is only about twice that of conventional DFT single-point calculation for the entire system. This work also proposes a variant of the sobEDA method named sobEDAw, which is designed specifically for decomposing weak interaction energies. Through a proper combination of DFT correlation energy and dispersion correction term, sobEDAw gives a ratio between dispersion energy and electrostatic energy that is highly consistent with the symmetry-adapted perturbation theory, which is quite popular and robust in studying weak interactions but expensive. We present a shell script sobEDA.sh to implement the methods proposed in this work based on the very popular Gaussian quantum chemistry program and Multiwfn wavefunction analysis code. Via the script, theoretical chemists can use the sobEDA and sobEDAw methods very conveniently in their study. Through a series of examples, the rationality of the new methods and their implementation are verified, and their great practical values in the study of various chemical systems are demonstrated.

Sex differences in fetal kidney reprogramming: the case in the renin-angiotensin system.

During the early stages of the development of the living multiorgan systems, genome modifications other than sequence variation occur that guide cell differentiation and organogenesis. These modifications are known to operate as a fetal programming code during this period, and recent research indicates that there are some tissue-specific codes in organogenesis whose effects may persist after birth until adulthood. Consequently, the events that disrupt the pre-established epigenetic pattern could induce shifts in organ physiology, with implications on health from birth or later in adult life. Chronic kidney disease (CKD) is one of the main causes of mortality worldwide; its etiology is multifactorial, but diabetes, obesity, and hypertension are the main causes of CKD in adults, although there are other risk factors that are mainly associated with an individual's lifestyle. Recent studies suggest that fetal reprogramming in the developing kidney could be implicated in the susceptibility to kidney disease in both childhood and adulthood. Some epigenetic modifications, such as genome methylation status, dysregulation of miRNA, and histone coding alterations in genes related to the regulation of the renin-angiotensin axis, a common denominator in CKD, may have originated during fetal development. This review focuses on epigenetic changes during nephrogenesis and their repercussions on kidney health and disease. In addition, the focus is on the influence of environmental factors during pregnancy, such as maternal metabolic diseases and dietary and metabolic conditions, as well as some sex differences in fetal kidney reprogramming during which dysregulation of the renin-angiotensin system is involved.

Tank Battle And Trivia Quiz Games Development Using Construct 2 To Improve Critical Thinking Ability

Game is something that is fun and entertaining 'of all time' and will always be in this world and can be enjoyed by both children, and adults. There are various types of games that are often played, including shooting and quiz games. Shooting Game has the main theme of shooting where players will beat each other to become the winner. While Quiz Game or often called Trivia Quiz is a game where players try to answer the questions given to get various kinds of prizes and become a winner. Construct 2 is a program for making games without writing programming code, because most of the game's logic can be arranged via the menu.This study aims to create a game design that is a combination of Shooting Game and Trivia Quiz where players can play both types of games simultaneously. While the program used is construct 2. And the sample used is 16 years and over. The methodology used is object-oriented design methodology. The modeling tools used are use case diagrams, activity diagrams and class diagrams. The results of making this game show that combining more than one type of game can be done and make a game more interesting.

Application Design of Newton-Rapshon method in Proving Maximum Wavelength on Wien’s Displacement Law

The Calculation of the maximum wavelength (?m) of radiation emitted by a black body can be determined from the Wien displacement law, which states the ratio between the Wien constant and the absolute temperature (T). Wien's displacement law can be derived analytically from the Energy Density equation (U?) in Plank's law. The solution for U? is obtained by calculating the first derivative of the function with respect to ? or dU?/d?, and then proceeding with finding a solution to the equation for the derivative. The solution of dU?/d? is the value of ? that makes dU?/d? equal to zero. The resulting wavelength is the maximum wavelength ?m, which is the wavelength value that makes the value in the equation U? the maximum value. The final result of this calculation is the Wien’s displacement law, namely the multiplication of ?m with T equals the Wien constant. So basically, the derivation of Wien's displacement law is to find the maximum value of the function f(x). The maximum value of the function f(x) can be done numerically. Solving numerically can be done with the Modified Newton-Rapshon method. The modified Newton-Rapshon method is usually implemented in the form of computer program code. In this research, the results of the calculation of the maximum wavelength ?m analytically are very close to the results of numerical calculations (modified NR). This can be seen from the results of linear regression with gradient values (m), regression constants (c) and coefficient of determination (R2) close to the ideal values of 1, 0 and 1, respectively.

The disjoint path cover in the data center network HSDC with prescribed vertices in each path

The n-dimensional HSDC with the logic graph Hn is one of the most attractive server-centric data center networks for high incremental scalability. The routing design in network topology is very important for information transmission. In particular, the application of disjoint path covers can solve various problems such as program code optimization and mapping parallel programs to parallel structures. Hn consists of 2n cliques and each two vertices in a clique are adjacent. For any vertex sets {x,u} and {y,v} in W and B, respectively, and any two disjoint vertex sets A1,A2 in some clique, where (W,B) is a bipartition of Hn, in this paper, we prove that, when |Ai|≠1 and Ai∩{x,y,u,v}=∅ for i=1,2, if |A1∪A2|≤n−3, then there exists an (x,y)-path P1 and a (u,v)-path P2 in Hn passing through A1 and A2, respectively, such that P1 and P2 have no common vertices and P1∪P2 contains all vertices of Hn. Then P1∪P2 is called the 2-disjoint path cover in Hn and we propose the efficient algorithms for the path design. Furthermore, we prove that our main result is optimal.

Techno-economic-environmental assessment and AI-enhanced optimization of a gas turbine power plant with hydrogen liquefaction

Most of the power plants in the world are based on gas turbines and many researchers tried to improve their efficiencies. This goal can be attained by the optimum utilization of heat losses. The authors of the present study aim to design, model, and optimize a gas turbine-based multigeneration power plant that uses the maximum possible of input energy to boost the products capacity and improve the efficiency. To decline the hydrogen storage and transportation costs, a hydrogen liquefaction process is applied to liquified the produced hydrogen at the same time. Besides, the power plant stack containing a substantial amount of energy is employed to operate a multi-effect desalination unit. To solve the main functions of the model, a programming code is developed. Then, the objective functions of the model are optimized using a machine learning model coupled with a genetic algorithm. Sensitivity analysis reveals that the fuel mass flow rate plays a pivotal role on total cost rate and hydrogen production rate; however, does not affect the exergy efficiency. Applying such a design for heat recovery, leads to 3.27% improvement in exergy efficiency rather than similar studies. The optimization results indicates that the LCOE is declined by 8.16% and normalized emission of CO2 is mitigated by 5.82 kg/GJ.

Photoproton reactions on molybdenum

The yields of (γ, p)-reactions for bremsstrahlung γ-quanta with boundary energies of 20, 40, and 55 MeV on a natural mixture of molybdenum isotopes targets were measured as well as the activity of the resulting 91m, 95mg, 96, 97Nb isotopes. The weighted average yields of these isotopes formed in (γ, p)-reactions on molybdenum were measured for the first time. The experimental values were compared with the theoretical yields calculated using the TALYS1.96 program code and the method of the consideration of the giant dipole resonance isospin splitting.

Numerical Solutions of Casson-Nano Fluid Flow Past an Isothermal Permeable Stretching Sheet: MHD, Thermal Radiation and Transpiration Effects

The Runge-Kutta Shooting Technique may be used to discover numerical solutions by the absence of magnetic field, thermal radiation, then transpiration consequence for viscous, incompressible, electrically conducting with combination of Casson and Nano-fluids that approach an isothermal permeable non-linearly stretched sheet. The governing equations for this fluid flow were transformed keen on non-linear ODEs using the similarity quantities. Visualizations of velocities, temperatures, and concentrations illustrate the mathematics behind the issue. According to tabular data, these flow regulating factors affect the coefficient of friction for skin-friction, heat transfer, and mass flow coefficients. Program code validation literature has been compared to the new numerical findings. It has been shown that flow characteristics are greatly affected by the amount of air that is exhaled. The study’s applications include industrial Nano-technological manufacturing processes. In this current work, the speed profiles are diminishing growing values of Casson fluid limitation as well as decreases by growing values of Magnetic field & Suction/Injection parameters. With increasing effects Brownian motion and Thermophoresis temperature profiles are increase. As the values of Thermal radiation of limitation enhances, the temperature profiles are also increases. The concentration profiles are increasing with increasing values of Thermophoresis parameter and reverse effect observed in case of Brownian motion effect. Also, concentration profiles decreases with increasing values of Lewis number.

A Novel DGM(1, N) Model with Interval Grey Action Quantity and Its Application for Forecasting Hydroelectricity Consumption of China

This paper addresses the issue of the conventional DGM(1, N) model’s prediction results not taking into account the grey system theory pri1nciple of the “non-uniqueness of solutions”. Firstly, before presenting the interval grey action quantity, the practical significance of grey action quantity is examined. In the DGM(1, N) model, the grey action quantity is transformed into an interval grey action quantity. Then, the calculation of the parameters uses the least squares method. A DGM(1, N, ⊗c) model containing interval grey action is then built, and meanwhile, the program code for DGM(1, N, ⊗c) is provided. Lastly, the aforementioned model is used to forecast the hydroelectricity consumption of China. The findings indicate that it produces more rational outcomes than the traditional DGM(1, N) model. Overall, the research carries significant pragmatic implications for broadening the conceptual underpinnings of multivariate grey forecasting models and enhancing their structural arrangement.

Performance and control of a reverse osmosis unit integrated with Pelton Wheel to supply emergency electric loads under various operating conditions

Nowadays, the whole world is moving very quickly into the field of seawater desalination. This is because the world suffers from a lack of potable water. Water and energy are adjoining linked fields. The present work aims at investigating the performance of a reverse osmosis (RO) plant integrated with Pelton Wheel under various operating conditions. The main reason for using Pelton turbine instead of the pressure exchanger (PX) is the low cost of Pelton compared to that of PX. The RO system integrated with the Pelton Wheel was tested under various operating pressures of 650, 700, 750, 800, and 850 kPa. Changing the feed water pressure affects the pressure of the reject entering the Pelton wheel and this, in turn, affects the velocity of the water jet. Also, the impact of varying the feed water salinity (total dissolved solids (TDS) = 400, 500, 600, 700, and 850 ppm) and temperature (20–39 °C) on the permeate and reject of RO was tested. In addition, a theoretical modeling was built to predict the performance of the RO system. The permeate flow rate was increased by raising the RO operating pressures. The permeate flow rate was augmented from 2.5 to 4.3 L min−1 when increasing the operating pressure from 650 to 850 kPa, respectively. Therefore, the permeate flow rate is enhanced by around 72% when increasing the operating pressure by only 30%. Besides, increasing the pressure by 30% (from 650 to 860 kPa) decreased the generated power of the Pelton Wheel by approximately 72% (from 960 to 270 W, respectively). Also, increasing the feed water salinity leads to raise the salinity of RO permeate, and vice versa. The RO permeate salinity is raised from 165 to 285 ppm when increasing the operating pressure from 650 to 850 kPa, respectively. As well, the more the increase in feed water temperature, the more improve in the permeate flux and salinity. The permeate TDS was decreased from 140 ppm at feed-water temperature 20 °C to 56 ppm at feed water temperature 39 °C. In this study, the Arduino program circuit was used to supply the required emergency loads by controlling the pressure values of high-pressure pump due to easy and open code program. Finally, the theoretical modelling results are in good correspondence with the experimental results. The average deviation among the theoretical and experimental results was 3.5%.

Research of models and methods for routing and practical implementation of autonomous movement by unmanned transport systems for cargo delivery

Modern challenges in the field of transport logistics associated with the need to increase the speed of cargo transportation and reduce the cost of transportation require the development of solutions that will allow the introduction of unmanned vehicles to solve logistics problems. Within the framework of this paper, a new problem of routing an unmanned transport system through delivery points using annealing simulation methods and an ant colony algorithm is considered. These methods are chosen taking into account the real situation of complication of the conditions of possible delivery, the emergence of closed areas for delivery, obtaining a large number of points for delivery, or the emergence of other features. The selected algorithms are relatively simple to implement and, at the same time, form acceptable routes of movement, taking into account the initial data. These algorithms are studied in the software simulation environment Gazebo for the possibility of their application in unmanned transport systems and their effectiveness in constructing alternative traffic routes. In the software simulation, a program code for the autonomous movement of an unmanned vehicle is developed and a simulation environment is formed taking into account the test data. In the test environment, the results of the ant colony algorithm are checked against the test data, and special attention is paid to the study of the speed and accuracy of the selected algorithms. It is worth noting that the annealing simulation algorithm allows you to quickly optimize a given route, however, to obtain more accurate results, you should additionally use other optimization methods, such as the ant colony algorithm. As a result of the proposed methods application, it is concluded that it is possible to form the optimal route of movement relative to the initial data within the length of the path and the speed of the generated route.

Applying a Situational Analysis Solver to Problems Involving Umbra/Sunlit Model

The search for optimal time intervals for satellite operations performance is based on verifying specific conditions of geometric or physical nature. Several conditions are combined in a situational problem. To be able to solve different situational problems, it is necessary to develop program codes for verifying different situational conditions in advance. Two situational conditions for determining if the satellite is in the sunlit zone or the umbra based on the conical models of the Earth's shadow are presented. Problems with one or more conditions are solved by a developed parallel solver for situational analysis. Conditions checking the position of a satellite relative to the Earth's shadow can be combined with other situational conditions.

DETECTION OF SQL INJECTION VULNERABILITY IN CODEIGNITER FRAMEWORK USING STATIC ANALYSIS

SQL Injection attacks are still one type of attack that often occurs in web-based applications. The causes and ways to prevent SQL Injection have been widely explained in various sources. Unfortunately, until now, SQL Injection vulnerabilities are still often found in multiple applications. Web-based application frameworks that already have functions to protect against attacks are often not used optimally. This is inseparable from the role of programmers, who often forget the rules for writing program code to prevent SQL Injection attacks. We conducted this research to detect SQL Injection vulnerabilities in source code using a case study of the PHP CodeIgniter framework. We compared this research with static analysis tools like RIPS, Synopsys Coverity, and Sonarqube. The tool we have developed can detect SQL Injection vulnerabilities that cannot be detected by the two tools with an accuracy of 88.8%. The results of our research can provide suggestions for programmers so that they can improve the code they write.