Earticle

Amid the acceleration of digital transformation and the increasing demand for rapid application development, No-Code and Low-Code (NCLC) development platforms have emerged as an important development approach that enables broader user participation. This study aims to identify the key factors influencing the adoption and intention to use NCLC development platforms. To achieve this objective, this study proposes and empirically tests an integrated research model that combines the Technology-Organization-Environment (TOE) framework and the Unified Theory of Acceptance and Use of Technology (UTAUT). Data were collected through an online survey of developers, designers, and general users, and analyzed using partial least squares (PLS) structural equation modeling. The results indicate that relative advantage, cost-effectiveness, competitive environment, compatibility, top management support, and organizational capability significantly influence either performance expectancy or effort expectancy. Furthermore, performance expectancy, effort expectancy, and social influence were found to positively affect usage intention. This study contributes to the literature by integrating organizational and individual perspectives on technology adoption and provides practical implications for organizations considering the adoption of NCLC platforms in digital transformation.

전 세계적으로 에너지 전환이 이루어지고 있는 가운데, 배터리의 효율적인 관리를 위해 배터리 정보 전송 기법들이 연구되고 있다. 배터리 정보를 전송하기 위한 BLE(Bluetooth Low Energy) 기술은 저전력 소비와 실시간 데이터 전송 의 장점을 제공하고 이를 통해 배터리의 성능 및 상태 모니터링이 가능하다. 하지만 현재의 정보 전송 방법의 경우 디 바이스의 정보를 노출시키며 사용자 조작에 의한 연결로 인해 비인가 접근이 발생할 수 있다. 따라서 본 논문에서는 이 러한 문제를 해결하기 위해 QR Code와 BLE 통신 기술을 활용한 데이터 검증 프로세스를 도입하여 보다 안전한 전송 기법을 제안한다.

Battery information transmission techniques are being studied for efficient management of batteries amid energy conversion around the world. Bluetooth low energy (BLE) technology for transmitting battery information provides the advantages of low power consumption and real-time data transmission, enabling battery performance and status monitoring. However, current information transmission methods expose device information, and unauthorized access may occur due to connection by user manipulation. Therefore, in order to solve this problem, this paper proposes a safer transmission technique by introducing a data verification process using QR Code and BLE communication technology.

This paper is about environment-based low-code and no-code execution platform and execution method that combines hybrid and native apps. In detail, this paper describes the Low-Code/No-Code execution structure that combines the advantages of hybrid and native apps. It supports the iPhone and Android phones simultaneously, supports various templates, and avoids developer-oriented development methods based on the production process of coding-free apps and the produced apps play the role of Java virtual machine (VM). The Low-Code /No-Code (LCNC) development platform is a visual integrated development environment that allows non-technical developers to drag and drop application components to develop mobile or web applications. It provides the functions to manage dependencies that are packaged into small modules such as widgets and dynamically loads when needed, to apply model-view-controller (MVC) pattern, and to handle document object model (DOM). In the Low-Code/No-Code system, the widget calls the AppOS API provided by the UCMS platform to deliver the necessary requests to AppOS. The AppOS API provides authentication/authorization, online to offline (O2O), commerce, messaging, social publishing, and vision. It includes providing the functionality of vision.

The amount of digital text data is growing exponentially, and many machine learning solutions are being used to monitor and manage this data. Artificial intelligence and machine learning are used in many areas of our daily lives, but the underlying processes and concepts are not easy for most people to understand. At a time when many experts are needed to run a machine learning solution, no-code machine learning tools are a good solution. No-code machine learning tools is a platform that enables machine learning functions to be performed without engineers or developers. The latest No-Code machine learning tools run in your browser, so you don't need to install any additional software, and the simple GUI interface makes them easy to use. Using these platforms can save you a lot of money and time because there is less skill and less code to write. No-Code machine learning tools make it easy to understand artificial intelligence and machine learning. In this paper, we examine No-Code machine learning tools and compare their features.

Recently, Artificial Intelligence (AI) has been emerging as a technology that has transformed and revolutionized various industries around the world. In recent years, businesses in Vietnam have also started to embrace AI applications to enhance their operations and gain a competitive edge in the market. As AI technologies continue to evolve rapidly, their impact on Vietnamese businesses is becoming increasingly profound. As artificial intelligence continues to progress across various fields, the need to democratize AI technology becomes increasingly clear. In a rapidly growing market like Vietnam, leveraging AI offers significant opportunities for businesses to improve operational efficiency, customer engagement, and overall competitiveness. However, significant barriers to AI adoption in Vietnam are the scarcity of skilled developers and the high cost of implementing traditional AI. No-code/low-code platforms offer an innovative solution that can accelerate AI adoption by making these technologies accessible to a wider audience. This article analyzes and understands the benefits of no-code/low-code solutions and proposes a roadmap for implementing no-code/low-code solutions in promoting AI applications in Vietnamese businesses.

Workers' demands for new applications, especially mobile applications, are increasing. Many industry analysts, researchers and corporate executives say the demand for mobile applications is becoming increasingly difficult to follow in the IT department. Gartner predicts that by 2021, the demand for mobile application development within the enterprise will increase about five times faster than IT can deliver applications. The purpose of this paper is to provide an environment where non-developers who are in charge of business development can develop apps and webs for their work. The basic concept of a new innovative App development tool, Smart Maker Authoring Tool is to develop Apps on the level using easy-to-learn Word or Excel in a computer. The main feature is that the app is developed by a non-developer worker. The coding technology is perfectly optimized to the structure and operation mechanism of the IT Infra such as hardware devices and operating system, which are the targets for implementing a desired function. Rather, it shows excellent software productivity. The most important feature of future business development is that it is developed by a non-developer worker. In this paper, we propose a no-code and low-code platform for non - developers to develop their business. In the future, we will link the IoT based Arduino system and artificial intelligent interpretation system

The subchannel analysis was performed to verify the behavior of hot channel characteristics and obtain the information to support the core thermal-hydraulic behavior at post-trip steam line break with low flow condition. During this postulated accident, buoyancy-induced cross flow occurs, and the coupled nuclear and thermal-hydraulic interactions become important. The code predictions with TORC are in good agreement with the test data. Under such conditions, the mass flow increase in the hot channel by buoyancy-induced cross flow depends on the parameter $GR^{*}\;/\;Re^2$, and buoyancy effect becomes more noticeable as $GR^{*}\;/\;Re^2$ increases.

A partial matched filter (PMF) for semi-coherent correlation code acquisition of the DSSS-CPFSK signal is proposed. It is a calculation-reduced structure of the hard-limited signal based FIR filter, yet its code acquisition time is equal to that of the hard-limited signal based FIR filter. The PMF eliminates duplicate calculations by utilizing the characteristic that the hard-limited DSSS-CPFSK signal has same value in several consecutive samples. For example, the PMF can achieve about 95% reduction in gate size, as compared to the hard-limited signal based FIR filter, when the modulation index of the DSSS-CPFSK signal is equal to 1.5 and the sample rate is equal to 40 sample/chip.

Carrier interferometry code is considered as a promising scheme that provides significant performance improvement via frequency diversity effect. Space-time coding is commonly employed to achieve a performance gain through space diversity. The combination of these techniques and forward error correction coding will lead to enhanced system capacity and performance. This paper presents a low-density parity check (LDPC) coded space-time orthogonal frequency division multiplexing (OFDM) transmission scheme with carrier interferometry code for high-capacity and high-performance mobile multimedia communications. Computer simulations demonstrate that the proposed mobile multimedia transmission system offers a considerable performance improvement of approximately 9dB in terms of Eb/No in the Rayleigh fading channel with relatively low delay spread, in comparison with space-time OFDM. Performance gains are further increased, comparing with traditional OFDM systems.

Various test data compression techniques have been developed to reduce the test costs of system-on-a-chips. In this paper, a scan chain reordering algorithm for code-based test data compression techniques is proposed. Scan cells within an acceptable relocation distance are ranked to reduce the number of conflicts in all test patterns and rearranged by a positioning algorithm to minimize the routing overhead. The proposed method is demonstrated on ISCAS '89 benchmark circuits with their physical layout by using a 180 nm CMOS process library. Significant improvements are observed in compression ratio and test power consumption with minor routing overhead.

Hierarchical modulation has been considered for achieving higher data rates in Terrestrial-DMB(T-DMB) systems. And for achieving a higher data rates transmission, the low-priority (LP) data, which is used to carry additional data, such as video data, audio data and textual data, should be perfectly decoded in a certain value of $E_b/N_o$. Unfortunately, the man-made noise badly affects the high-priority (HP) symbol, which is used to carry the conventional data in the existed T-DMB system; and since the advanced T-DMB system is proposed to fit for the legacy T-DMB receivers, the low-priority symbols in the hierarchical modulation are much worse affected by the neighbors, who are both in the same quadrant. Because of the feature that mentioned previously, the turbo code has been considered to deal with the LP data. And due to the degradation which caused by the shortened symbol distance, the error performance of LP data is not sufficient by only using the turbo code. In this paper, we propose a Reed-Solomon code used outside of turbo code, and with the turbo code, it becomes a concatenated code. In this paper, there are some simulation results, within the comparison of those performances, we can see how a Reed-Solomon code is utilized for degradation of error performance which is caused by the hierarchical constellation, and how to design a Reed-Solomon code which is suitable for improving the degradation of error performance.

Hierarchical modulation has been considered for achieving higher data rates in Terrestrial-DMB(T-DMB) systems. And for achieving a higher data rates transmission, the low-priority (LP) data, which is used to carry additional data, such as video data, audio data and textual data, should be perfectly decoded in a certain value of $E_b/N_o$. Unfortunately, the man-made noise badly affects the high-priority (HP) symbol, which is used to carry the conventional data in the existed T-DMB system; and since the advanced T-DMB system is proposed to fit for the legacy T-DMB receivers, the low-priority symbols in the hierarchical modulation are much worse affected by the neighbors, who are both in the same quadrant. Because of the feature that mentioned previously, the turbo code has been considered to deal with the LP data. And due to the degradation which caused by the shortened symbol distance, the error performance of LP data is not sufficient by only using the turbo code. In this paper, we propose a Reed-Solomon code used outside of turbo code, and with the turbo code, it becomes a concatenated code. In this paper, there are some simulation results, within the comparison of those performances, we can see how a Reed-Solomon code is utilized for degradation of error performance which is caused by the hierarchical constellation, and how to design a Reed-Solomon code which is suitable for improving the degradation of error performance.

This work presents a low complexity maximum-likelihood decoder for signal detection in VBLAST-STBC system, which employs non-square O-STBC code rate 3/4. Stacking received symbols from different symbol duration and applying QR decomposition result in the special format of upper triangular matrix R so that the proposed decoder is able to provide not only ML-like BER performance but also very low computational load. The low computational load and ML-like BER performance properties of the proposed decoder are verified by computer simulations.

This work presents a low complexity maximum-likelihood decoder for signal detection in VBLAST-STBC system, which employs non-square O-STBC code rate 3/4. By stacking received symbols from different received symbolduration and applying QR decomposition resulting the special format of upper triangular matrix R, the proposed decoder is able to provide not only ML-like BER performance but also very low computational load. The low computational load and ML-like BER performance properties of the proposed decoder are verified by computer simulations.

This work presents a low complexity maximum-likelihood decoder for signal detection in VBLAST-STBC system, which employs non-square O-STBC code rate 3/4. By stacking received symbols from different received symbolduration and applying QR decomposition resulting the special format of upper triangular matrix R, the proposed decoder is able to provide not only ML-like BER performance but also very low computational load. The low computational load and ML-like BER performance properties of the proposed decoder are verified by computer simulations.

This work deals with the assessment of the burnup capabilities of the Serpent Monte Carlo code to predict spent nuclear fuel (SNF) isotopic concentrations for low-enriched uranium (LEU) fuel at different burnup levels up to 47 MWd/kgU. The irradiation of six UO₂ experimental samples in three different VVER-1000 reactor units has been simulated and the predicted concentrations of actinides up to ²⁴⁴Cm have been compared with the corresponding measured values. The results show a global good agreement between calculated and experimental concentrations, in several cases within the margins of the nuclear data uncertainties and in a few cases even within the reported experimental uncertainties. The differences in the performances of the JEFF3.1.1, ENDF/B-VII.1 and ENDF/B-VIII.0 nuclear data libraries (NDLs) have also been assessed and the use of the newly released ENDF/B-VIII.0 library has shown an increased accuracy in the prediction of the C/E's for some of the actinides considered, particularly for the plutonium isotopes. This work represents a step forward towards the validation of advanced simulation tools against post irradiation experimental data and the obtained results provide an evidence of the capabilities of the Serpent Monte-Carlo code with the associated modern NDLs to accurately compute SNF nuclide inventory concentrations for VVER-1000 type reactors.

4차 산업혁명과 코로나19 영향으로 개발자 수요가 급증하며, 노코드 및 로우코드 플랫폼과 자연어 처리 기반 인공지능이 주목받고 있다. 본 연구는 프로그래밍 접근성 향상을 위한 노코드 플랫폼을 탐구하며, 사용자가 UI를 통해 직관적으로 프로젝트를 구축할 수 있는 설계 방식을 제시한다. 본 연구에서는 웹 크롤링과 자연어 처리 모델 학습에 기반한 아키텍처와 방향성을 제시한다. 사용자는 화면을 구성하고 프레임워크 선택 후 프로젝트를 간단하게 구축할 수 있다. 이 연구는 전문 지식 없이도 소프트웨어 개발에 쉽게 접근할 수 있는 방법론을 제시하며, 접근성과 포용성 강화에 기여한다.

The turbo code appropriate to IMT-2000 is known to have a good performance whenever the size of frame increases. But it is not appropriate to a sort of video service to need real time because of decoding complexity and long delay time by the size of frame. Therefore this paper proposes decoding decision algorithm of short frame in which soft output is weighted according to iteration number in turbo decoder. Performance of the proposed algorithm is analysed in the AWGN channel when short length of frame is 100, 256, 640. As the result. it is appeared that the proposed decoding decision algorithm has improved in BER other than in the existing MAP decoding algorithm.