Advanced Programming Language Research Articles

Wind speed prediction

With the help of wind farms, wind energy is a vital renewable energy source that contributes significantly to the worlds energy balance. The lifespan and maintenance costs of wind turbines will be reduced with an accurate wind speed prediction. On the other hand, wind speed is highly volatile and unpredictable. Thus, it is essential to do research into creating complex models and algorithms for precise wind speed prediction. So far, some of the most promising models include Support Vector Machine (SVM), Artificial Neural Networks (ANN), and Autoregressive Moving Average (ARMA). Python, as an advanced and versatile programming language, is exceptionally suited for scripting the algorithms of these sophisticated models. This paper will use the data from Austin Texas and apply a Support Vector Machine (SVM) for wind speed prediction involves several stages, including data collection, data preprocessing, model selection, model training, parameter optimization, model validation, and prediction. Wind energy resource optimisation, maintenance cost reduction, and total wind farm efficiency can all be significantly improved by incorporating these models into predictive analytics and continuously improving them against changing data.

Dockerized Application with Web Interface

Developing an application can be a task if any kind of conflict arises during deploying the code or while running them and it can be due to the storage or the code being not supported by the other party’s system. Thus to provide a solution for this matter, we are introducing the project concept of Dockerized application deployment through a web interface. This proposed project combines the efficiency of Docker containers with a web interface to create a platform for running and managing applications easily. When a programmer or a developer or anyone in the field of programming has conflict in uploading, running or deploying their application code from another programmer’s system to their own due to the inefficiency or lack of facilities in their system, they can use this web interface as a solution. Especially during the time of any rush, they can opt for this web interface as it does not require the installation of a local Docker software and any extra dependency management, as installation of Dockers are a bit time lagging. One of the main factors of this project is that this web interface can be run in any kind of computer system without any extra facilities being added to it. Whether the system is less efficient or high efficient regardless of the type of the system, this web interface is easy to access for the users. Users can upload their application code, build Docker images, and run them directly from the web interface. With the advantage of Docker’s utility methodologies for shipping, testing and deploying code, you can reduce the delay between writing codes and running applications .It has additional features like users can define environment variables for their applications, configure network settings for container communication ,mount persistent volumes to store application data with help of virtual cloud, implement user roles and permissions for secure access control .The front end of the web page is created using NEXT Programming Language meanwhile the backend is applied using NEXT, Docker and Python Flask API. About NEXT Programming Language that in this language, when the front-end is applied the backend function gets directly deployed making us use less effort in creating the webpage. It's a newly created advanced programming language. Overall, this Dockerized application deployment web-interface offers a user-friendly and efficient solution for developers, system administrators, and DevOps teams, streamlining the application development and deployment process.

E-GVD: Efficient Software Vulnerability Detection Techniques Based on Graph Neural Network

INTRODUCTION: Vulnerability detection is crucial for preventing severe security incidents like hacker attacks, data breaches, and network paralysis. Traditional methods, however, face challenges such as low efficiency and insufficient detail in identifying code vulnerabilities. OBJECTIVES: This paper introduces E-GVD, an advanced method for source code vulnerability detection, aiming to address the limitations of existing methods. The objective is to enhance the accuracy of function-level vulnerability detection and provide detailed, understandable insights into the vulnerabilities. METHODS: E-GVD combines Graph Neural Networks (GNNs), which are adept at handling graph-structured data, with residual connections and advanced Programming Language (PL) pre-trained models. RESULTS: Experiments conducted on the real-world vulnerability dataset CodeXGLUE show that E-GVD significantly outperforms existing baseline methods in detecting vulnerabilities. It achieves a maximum accuracy gain of 4.98%, indicating its effectiveness over traditional methods. CONCLUSION: E-GVD not only improves the accuracy of vulnerability detection but also contributes by providing fine-grained explanations. These explanations are made possible through an interpretable Machine Learning (ML) model, which aids developers in quickly and efficiently repairing vulnerabilities, thereby enhancing overall software security.

Creation of a virtual and interactive simulation environment in Excel for the study of Ohm's Law

The article highlights the growth of virtual laboratories as technological and pedagogical tools. It presents an example of a virtual laboratory in Excel® to assist in teaching and develop specific skills in users. The virtual laboratory of Ohm's Law includes multimeters, power supply, protoboard, and resistor for studying electrical measurements, resistance reading, ohmic behavior, and graphical analysis. It does not require an internet connection and does not use advanced programming languages, allowing the creation of customized virtual laboratories for various learning needs.

Challenges in the Geo-Processing of Big Soil Spatial Data

This study addressed a critical resource—soil—through the prism of processing big data at the continental scale. Rapid progress in technology and remote sensing has majorly improved data processing on extensive spatial and temporal scales. Here, the manuscript presents the results of a systematic effort to geo-process and analyze soil-relevant data. In addition, the main highlights include the difficulties associated with using data infrastructures, managing big geospatial data, decentralizing operations through remote access, mass processing, and automating the data-processing workflow using advanced programming languages. Challenges to this study included the reproducibility of the results, their presentation in a communicative way, and the harmonization of complex heterogeneous data in space and time based on high standards of accuracy. Accuracy was especially important as the results needed to be identical at all spatial scales (from point counts to aggregated countrywide data). The geospatial modeling of soil requires analysis at multiple spatial scales, from the pixel level, through multiple territorial units (national or regional), and river catchments, to the global scale. Advanced mapping methods (e.g., zonal statistics, map algebra, choropleth maps, and proportional symbols) were used to convey comprehensive and substantial information that would be of use to policymakers. More specifically, a variety of cartographic practices were employed, including vector and raster visualization and hexagon grid maps at the global or European scale and in several cartographic projections. The information was rendered in both grid format and as aggregated statistics per polygon (zonal statistics), combined with diagrams and an advanced graphical interface. The uncertainty was estimated and the results were validated in order to present the outputs in the most robust way. The study was also interdisciplinary in nature, requiring large-scale datasets to be integrated from different scientific domains, such as soil science, geography, hydrology, chemistry, climate change, and agriculture.

MODEL IMPLEMENTASI LOGIKA FUZZY UNTUK PENILAIAN KINERJA KARYAWAN IT SUPPORT

Human resources are the most valuable asset in a company. Employee performance is one of the company's benchmarks in assessing the productivity of these assets. Methods in measuring employee performance can be done in various forms, one of which is using the fuzzy logic method. Fuzzy Mamdani is a fuzzy inference method that provides rules that must be passed before carrying out the process of determining the final value. There are three main criteria that will be analyzed in this study, namely attendance, quality of work and communication. Each of these criteria has a value obtained from the average value of several elements. The final result after going through the employee data analysis process is the average weighted value. Conclusions that can be drawn as the basis for employee performance and the results can be seen from the order of values, starting from the highest to the lowest. MATLAB or what we call it (Matrix Laboratory) is a program for analyzing and computing numerical data, and MATLAB is also an advanced mathematical programming language, which was formed on the premise of using the properties and forms of matrices. Graphical User Interface (GUI) is a visual media that makes users give certain commands on the computer without typing the command, but using the available images.

텍스트 마이닝을 활용한 여자 대학생의 무용 관련 운동 트렌드 분석

This study aims to understand the weight of dance of exercise trends and motivations for choosing exercise using the text-mining method based on essays collected from 214 female college students who represent Generation MZ that leads social trends. For this purpose, word frequency, word cloud, and word keyword analyses were conducted. The results of the analyses are as follows. The female college students’ criteria for choosing exercise are the professionalism of the program, the efficiency of time utilization, the effect on the body, communication with people doing the exercise together, and appropriate tuition fees. Motivations for exercise included improving muscle and physical strength, promoting flexibility, correcting body shape and diet, and releasing stress. Various detailed keywords related to dance have been extracted. Hopefully, this study will be utilized as a material for the baseline research to expand the range of the utilization of dance as a consuming exercise, and numerous algorithms can be used in dance studies through more diverse and advanced programming languages in the future.

Application of mathematical model using advanced programming languages to estimate lake pollution

The goal of this article is to develop an online simulation of lake pollution. The mathematical model for detecting the load of various pollutants in a lake was developed earlier. Through this model, different pollutants are disseminated throughout the lake and their discharge is calculated. Manual arithmetic calculations were possible, but they had many limitations due to the logarithmic equations as well as the length of time it took. In order to accomplish this, C++ and Java were used to create the Lake Pollution Model. A manual scientific calculation has been used to calibrate this model, which has an error of 0.114 to 0.25 mg/L. Based on the results, it can generate lake pollution output in a very short amount of time without involving scientific calculations.

Backpropagation Model in Predicting the Location of Prospective Freshman Schools for Promotion Optimization

In carrying out promotions, it is also necessary to pay for the manufacture of brochures, banners and other promotional media to provide information to prospective students and attract prospective students to register. Determining the location of the promotion is one of the success factors in promotional activities. In this study, the Artificial Neural Network will be used to predict the location of the promotion. Backpropagation is one of the best artificial neural network methods used for prediction, this method is widely used by researchers in predicting a problem. The data analysis tool used is Matlab or what we call the (Matrix Laboratory) which is a program to analyze and compute numerical data, and Matlab is also an advanced mathematical programming language, which was formed on the premise of using the properties and forms of matrices. From the results of the algorithm used, it is expected to get good accuracy results with some architectural experiments later. So that this research can be an indicator to optimize promotions in the following year in order to attract prospective students to register for AMIK and STIKOM Tunas Bangsa Pematangsiantar

The Serological Basis of the Correlation between Iron Deficiency Anemia and Thyroid Disorders in Women: A Community Based Study

Objectives: Iron Deficiency Anemia (IDA), a global public health problem may have an inimical effect on thyroid function, especially in women and children. This study was conducted to inspect the correlation between IDA and thyroid disorders in women of Bangladesh.
 Methods: A cross-sectional study was conducted among 452 women of different age groups in particular regions of Bangladesh presenting anemic symptoms and were confirmed anemic after testing of serum hemoglobin levels less than 12 g/dL. To identify the correlation between iron deficiency anemia and thyroid disorders; serum samples were tested quantitatively through standardized methods considering serum iron, total iron-binding capacity (TIBC), ferritin, thyroid-stimulating hormone (TSH), free thyroxin (FT4), and vitamin D levels as parameters. Post clinical diagnosis statistical analysis, graphical presentations of the complex clinical data was generated using advanced computer programming language and bio-analytical tools. 
 Results: A positive correlation between hypothyroidism and IDA in women was discovered in this study as 24.69% of patients with IDA from 0-60 years were found suffering from hypothyroidism simultaneously; with the highest percentage (38.46%) amongst the 31-40 years of age and 26% of iron-deficient females of reproductive age (15-49 years) were suffering from hypothyroidism. Moreover, the association between congenital hypothyroidism and IDA was noticed in 50% of cases above all.
 Conclusion: Hypothyroidism was found quite common among the women of different age groups who were previously reported with acute to chronic anemia symptoms due to iron deficiency.

RETRACTED: Design of english video learning platform based on FPGA system and sobel algorithm

In order to improve the system performance of image processing and improve the efficiency of image processing, we can use some hardware running image processing algorithms. in practice, we introduce some reconfigurable devices and more advanced programming languages to use FPGA for image processing. following will briefly introduce the design of FPGA in the edge detection system.The design has integrated a 32-bit soft RISC processor as dedicated hardware peripheral micro development and EDK embedded system developed by the system generator. Input is detected from a real-time image obtained from the CMOS camera displayed on the DVI display on the screen.

Reflections on Ethics, Human Intelligence and Artificial Intelligence (AI)

The history of AI is very long, which began in the mid-50s of the last century, since the creation of the Internet for military purposes (Darpanet) which became due to its great utility in the commercial and application form in all the fields of knowledge and human endeavor. These programs that initially ran in the operating systems of the time in the primitive Internet, have evolved along with the technological advances in programming languages, operating systems and software with such innovation capabilities that it has allowed their architecture with transistors and increasingly smaller chips, high-speed processing of text, number and matrix tables with formulas; coupled with the speed of RAM and hard disk memory. In this platform, AI has grown to the unimaginable, until it becomes a program with codes and algorithms that learn and re-map themselves to carry out their pre-established task more efficiently, a situation that when it happens, means improvement of the program but results and type of programming with codes and algorithms that are no longer known by the programmer, so in view of the risk of deviation from the pre-established objectives and taking care of ethical laws and regulations, the programs of this software must install filters at the beginning, during the process and at the end, as signals alarm when there are deviations such that they have ethical implications for humans. This interaction of Human Intelligence (HI) with AI has had negative as well as positive disagreements, for which in principle, the adaptation of labor and human rights standards and laws was sufficient, but now with the great development of AI, The establishment of ethical standards in the development of such programs is mandatory. At the moment, the standard already formally exists: Barcelona Declaration for the Adequate Development and Use of Artificial Intelligence in Europe.

Mechanized relational verification of concurrent programs with continuations

Concurrent higher-order imperative programming languages with continuations are very flexible and allow for the implementation of sophisticated programming patterns. For instance, it is well known that continuations can be used to implement cooperative concurrency. Continuations can also simplify web server implementations. This, in particular, helps simplify keeping track of the state of server’s clients. However, such advanced programming languages are very challenging to reason about. One of the main challenges in reasoning about programs in the presence of continuations is due to the fact that the non-local flow of control breaks the bind rule, one of the important modular reasoning principles of Hoare logic. In this paper we present the first completely formalized tool for interactive mechanized relational verification of programs written in a concurrent higher-order imperative programming language with continuations (call/cc and throw). We develop novel logical relations which can be used to give mechanized proofs of relational properties. In particular, we prove correctness of an implementation of cooperative concurrency with continuations. In addition, we show that that a rudimentary web server implemented using the continuation-based pattern is contextually equivalent to one implemented without the continuation-based pattern. We introduce context-local reasoning principles for our calculus which allows us to regain modular reasoning principles for the fragment of the language without non-local control flow. These novel reasoning principles can be used in tandem with our (non-context-local) Hoare logic for reasoning about programs that do feature non-local control flow. Indeed, we use the combination of context-local and non-context-local reasoning to simplify reasoning about the examples.

A New Digital Solution Helps Automatic Voice Recognition

This scientific work concerning an examination on automatic speech recognition (ASR) frameworks connected with the home automation and to express the importance of this academic work, an itemized investigation of the engineering of speech recognition frameworks was completed. Our goal in Information Systems Engineering Research Group ofAbdelmalekEssaadi University is to choose a speech recognition programming that must work in remote speech conditions and in a rowdy area.The proposed framework is using atoolbox called Kaldi, which must correspond as aclient created by an advanced programming language, with any home automation framework.

Based on the BP Neural Network Optimization Application Research of the Construction Site

Artificial neural network (ANN) is a discipline which is used to calculate the nonlinear problem in the late 1980s. The BP neural network is widely used. It has been widely used in engineering because of its nonlinear mapping ability, self-learning ability, associative memory ability, parallel information processing mode and its excellent fault tolerance ability. The main functions of the system are pattern recognition, function approximation, data compression and prediction. Because of the huge amount of computation in the practical calculation of BP neural network model to help launch by the American Mathwork company MATLAB software, MATLAB software and BP neural network toolbox, can efficiently complete the project tasks. MATLAB software package BP tools function in mathematical calculation, graphic calculation, computer simulation and other aspects to provide a convenient tool for the research and design of neural network, to overcome the complexity of the problem, the advanced computer language programming language is simple, convenient debugging program, high operation efficiency, has very important application prospect.

PreX: A predictive model to prevent exceptions

The exception handling mechanism has been one of the most used reliability tools in programming languages in the last decades. However, this model has not changed much with time, in spite of advances in programming languages, which include concurrent programming and a shift towards more reactive paradigms, the basic principle remains the same - an exception occurs, and the mechanism reacts. We propose a new paradigm, inspired by Online Failure Prediction (OFP), to predict exceptions and possibly avert them by triggering the execution of preventive actions. The proposed model - PreX - is, thus, proactive, operating in a much finer-grained level than any other form of online failure prediction. OFP has shown promising results in predicting failures at a higher level, but has never been available to the developer, being mainly a system level technique. Thus, PreX will offer developers a new range of revitalization strategies. In this work, we describe the model and evaluate its performance by applying it to a real e-commerce solution, demonstrating how it is capable of predicting and preventing exceptions at run-time. Furthermore, we also show that PreX increases the overall availability and performance of the system under the same conditions.

Establishement for regional pelvic trauma database in Hunan Province

To establish a database for pelvic trauma in Hunan Province, and to start the work of multicenter pelvic trauma registry. Methods: To establish the database, literatures relevant to pelvic trauma were screened, the experiences from the established trauma database in China and abroad were learned, and the actual situations for pelvic trauma rescue in Hunan Province were considered. The database for pelvic trauma was established based on the PostgreSQL and the advanced programming language Java 1.6. Results: The complex procedure for pelvic trauma rescue was described structurally. The contents for the database included general patient information, injurious condition, prehospital rescue, conditions in admission, treatment in hospital, status on discharge, diagnosis, classification, complication, trauma scoring and therapeutic effect. The database can be accessed through the internet by browser/servicer. The functions for the database include patient information management, data export, history query, progress report, video-image management and personal information management. Conclusion: The database with whole life cycle pelvic trauma is successfully established for the first time in China. It is scientific, functional, practical, and user-friendly.

Research on Intelligent Flight Software Robot Based on Internet of Things

2010 China Internet of Things Application Promotion Union pointed out that the robot is one of the 100 leading edge technology. 2015, the forefront of the field of robot top10 technology, including Internet of things embedded technology, simulation technology, large data technology, cloud computing robot, robot autonomy technology and so on. The robot uses the sensor technology in the key technology of the Internet of Things. In order to make life better and more convenient, the research of Internet of Things technology and application, focusing on research based on the Internet of intelligent flight spherical monitoring software robot technology. In this paper, you can use mat lab simulation robot and programming algorithm, the use of advanced programming language to develop intelligent flight robots. The research results of intelligent flight monitoring software robot technology can be applied in academia and industry and medical transportation. This paper studies the intelligent flight monitoring software robot under the Internet of Things.

结构量计算机——三值光学计算机的应用特点

In this paper, a novel technology for processing simple data via the hardware of a ternary optical (TOC) is investigated, and the natural sources of this powerful processing ability-massive quantity of data bits of the ternary photo-electronic processor, reconstruction bit by bit, and carry-free adder-are described. It is also discussed that how to use these characteristics to reconstruct a ternary optical processor into a composite one with many data bits and several different functions. Furthermore, this paper details how to apply this kind of composite processor to process vast amounts of different types of data in the hardware within one operation instruction. Apparently, when a TOC is applied to process data, which is composed of different types of simple data, only one instruction is needed. Thus, its overwhelming superiority is revealed. We call this kind of a structured data computer for its application features. At the beginning of this paper, a technique outline applying a TOC to process simple data is detailed, which includes the SZG file format, a method for generating the SZG file automatically, and the extension for advanced programming languages. Next, an example is given of processing data with four components of different types through the data computer. In conclusion, the strong capacity of the TOC for processing data is exhibited by analyzing the computational process of 1000 pairs of data.

Development of an ophthalmological clinical information system for inpatient eye clinics

In times of increased digitalization in healthcare, departments of ophthalmology are faced with the challenge of introducing electronic clinical health records (EHR); however, specialized software for ophthalmology is not available with most major EHR sytems. The aim of this project was to create specific ophthalmological user interfaces for large inpatient eye care providers within a hospitalwide EHR. Additionally the integration of ophthalmic imaging systems, scheduling and surgical documentation should be achieved. The existing EHR i.s.h.med (Siemens, Germany) was modified using advanced business application programming (ABAP) language to create specific ophthalmological user interfaces for reproduction and moreover optimization of the clinical workflow. A user interface for documentation of ambulatory patients with eight tabs was designed. From June 2013 to October 2014 a total of 61,551 patient contact details were documented. For surgical documentation a separate user interface was set up. Digital clinical orders for documentation of registration and scheduling of operations user interfaces were also set up. A direct integration of ophthalmic imaging modalities could be established. An ophthalmologist-orientated EHR for outpatient and surgical documentation for inpatient clinics was created and successfully implemented. By incorporation of imaging procedures the foundation of future smart/big data analyses was created.