Black-box Method Research Articles

IoT-based Smart Piggy Bank Design Implementation Using RFID and Telegram Notification

Saving is one of the most important things in financial management. Saving is beneficial for the long term for life. In the conventional way, people can save in a closed container or generally use an object called a piggy bank. However, there are still many shortcomings of the current conventional piggy bank, such as having to be disassembled to take the money and it is difficult to monitor the amount of savings in it so that it can only be used once. With the help of technology, these conventional tools can be used better and more efficiently. This smart piggy bank can be integrated with the Telegram when money is inserted so that it becomes more monitored in saving. The money inserted is detected by infrared sensors and color sensors which are then accumulated and sent via Telegram. Previously, there has been similar research in using sensors to detect money and send notifications based on the Internet of Things. This research aims to develop the existing research by integrating some of its features. Testing was conducted using the Black Box method, focusing on the functionality of the device. As a result, the money inserted into the piggy bank can be accumulated properly and monitored via Telegram with a calculation according to the amount of money inserted and can be used by many people because it uses an RFID card that contains user data and savings so that it becomes more efficient and recorded.

Bifurcation tracking on moving meshes and with consideration of azimuthal symmetry breaking instabilities

We present a black-box method to numerically investigate the linear stability of arbitrary multi-physics problems. While the user just has to enter the system's residual in weak formulation, e.g. by a finite element method, all required discretized matrices are automatically assembled based on just-in-time generated and compiled C codes. Based on this method, entire phase diagrams in the parameter space can be obtained by bifurcation tracking and continuation at low computational costs. Particular focus is put on problems with moving domains, e.g. free surface problems in fluid dynamics, since a moving mesh introduces a plethora of complicated nonlinearities to the system. By symbolic differentiation before the code generation, however, these moving mesh problems are made accessible to bifurcation tracking methods. In a second step, our method is generalized to investigate symmetry-breaking instabilities of axisymmetric stationary solutions by effectively utilizing the symmetry of the base state. Each bifurcation type is validated on the basis of results reported in the literature on versatile fluid dynamics problems, for which we subsequently present novel results as well.

A new parameterization of the DFT/CIS method with applications to core-level spectroscopy.

Time-dependent density functional theory (TD-DFT) within a restricted excitation space is an efficient means to compute core-level excitation energies using only a small subset of the occupied orbitals. However, core-to-valence excitation energies are significantly underestimated when standard exchange-correlation functionals are used, which is partly traceable to systemic issues with TD-DFT's description of Rydberg and charge-transfer excited states. To mitigate this, we have implemented an empirically modified combination of configuration interaction with single substitutions (CIS) based on Kohn-Sham orbitals, which is known as "DFT/CIS." This semi-empirical approach is well-suited for simulating x-ray near-edge spectra, as it contains sufficient exact exchange to model charge-transfer excitations yet retains DFT's low-cost description of dynamical electron correlation. Empirical corrections to the matrix elements enable semi-quantitative simulation of near-edge x-ray spectra without the need for significant a posteriori shifts; this should be useful in complex molecules and materials with multiple overlapping x-ray edges. Parameter optimization for use with a specific range-separated hybrid functional makes this a black-box method intended for both core and valence spectroscopy. Results herein demonstrate that realistic K-edge absorption and emission spectra can be obtained for second- and third-row elements and 3d transition metals, with promising results for L-edge spectra as well. DFT/CIS calculations require absolute shifts that are considerably smaller than what is typical in TD-DFT.

Pembangunan Sistem Manajemen Data Wisata pada Dinas Pariwisata, Pemuda, dan Olahraga Kabupaten Madiun

The tourism sector in Madiun Regency has significant development potential, highlighted by 75 tourist destinations. However, inadequate management of tourism data has led to suboptimal growth. To address this issue, a tourism data management system is proposed to facilitate efficient data handling for various stakeholders, including Destination Managers, Tourism Industry Managers, and Service Verifiers. The system manages data on tourist destinations, the tourism industry, and visitor information. The results of system testing using the black box method show that all features are functioning properly. The system was tested using usability testing, it showed a score of 87% from a total of 53 respondents, indicate that the developed system is both functional and user-friendly.

Aplikasi Multiplatform Sayur Kita untuk Meningkatkan Efisiensi Pedagang Pasar

Markets are an essential part of the economic ecosystem, often facing various challenges for traders. One of the issues they encounter is the limited time for conducting transactions with both consumers and suppliers. This condition significantly impacts business performance and the quality of stock, influenced by various factors such as weather, time constraints, and the shipping process. This research aims to determine and analyze the development of applications that make buying and selling easier between traders and suppliers online, which can be accessed at any time. This application is integrated into various platforms, both via mobile and web, to enable traders to carry out transactions quickly, effectively and efficiently in terms of time, ef-fort and cost. Apart from that, this research is to facilitate transactions between market traders and suppliers, as well as expand the reach of online markets, especially regarding time con-straints and stock availability. By adopting an integrated multiplatform application develop-ment approach, this research aims to facilitate transactions between market traders and suppli-ers, as well as expand the market reach online, particularly addressing time limitations and stock availability. The development method used is the Waterfall method, which includes re-quirements analysis, system design, implementation, testing, and maintenance. The result of this research is an application called "Sayur Kita," a cross-platform application that helps traders con-duct transactions quickly and efficiently through mobile and web platforms, usable on various devices. Testing was conducted using the black box method, and the results showed that all fea-tures operated as expected. Therefore, this application can help improve the efficiency of market traders in conducting transactions with suppliers and traders online.

Implementasi E-Katalog IKM Berbasis Website Pada Dinnakerind Di Kabupaten Demak

In this digital era, information technology is very important to develop small and medium industries (SMEs). The Department of Labor and Industry of Demak Regency seeks to improve the competitiveness of SMEs through a website-based e-catalog. The aim of this research is to create and implement an e-ICM catalogue that can be accessed online by the public as well as to evaluate how effective the catalogue is in promoting local products. Needs analysis, system design, implementation, and testing are the measures used in this research. This research aims to design and implement an SMEs e-catalog that can be accessed online by the community, and evaluate its effectiveness in promoting local products. The research method includes needs analysis, system design, implementation, and testing. The result is an e-catalog website that displays complete information about SMEs products in Demak Regency, including product descriptions, images, and manufacturer contacts. This website also has a search feature and product categories to facilitate users. Using the black-box testing method, the test was conducted with a usability survey of 22 respondents, which yielded a score of 86.8%. It is expected that the system will help develop small and medium-sized industries (SMEs) in Demak district, improve product visibility, and support the local economy.

DBI-Attack: Dynamic Bi-Level Integrated Attack for Intensive Multi-Scale UAV Object Detection

Benefiting from the robust feature representation capability of convolutional neural networks (CNNs), the object detection technology of intelligent high-altitude UAV remote sensing has been developed rapidly. In this field, the adversarial examples (AEs) pose serious security risks and vulnerabilities to deep learning-based systems. Due to the limitation of object size, image degradation, and scene brightness, adding adversarial disturbances to small and dense objects is extremely challenging. To study the threat of AE for UAV object detection, a dynamic bi-level integrated attack (DBI-Attack) is proposed for intensive multi-scale UAV object detection. Firstly, we use the dynamic iterative attack (DIA) method to generate perturbation on the classification level by improving the momentum iterative fast gradient sign method (MIM). Secondly, the bi-level adversarial attack method (BAAM) is constructed to add global perturbation on the decision level for completing the white-box attack. Finally, the integrated black-box attack method (IBAM) is combined to realize the black-box mislabeling and fabrication attacks. We experiment on the real drone traffic vehicle detection datasets to better evaluate the attack effectiveness. The experimental results show that the proposed method can achieve mislabeling and fabrication attacks on the UAV object detectors in black-box conditions. Furthermore, the adversarial training is applied to improve the model robustness. This work aims to call more attention to the adversarial and defensive aspects of UAV target detection models.

Sistem Informasi Akademik SMA Negeri 1 Kintap Berbasis Web

SMA Negeri 1 Kintap is one of the educational institutions located in Kintap District. Until now, there are still many educational institutions that have not implemented an academic information system, one of which is SMA Negeri 1 Kintap. Data management still uses processes that refer to documents in the form of files or archives, still uses Microsoft Excel and Microsoft Word applications, without a database. In addition, the principal is also difficult to put together academic reports. This study aims to build an academic information system to streamline time and make it easier for related parties to process and display. The method used in building this system is the waterfall method using the PHP and MySQL programming languages. This study uses data collection methods through literature study and interviews. The method used for testing or evaluation is the black box method. The black box method focuses on the function of a system. The result of this research is the web-based academic information system of SMA Negeri 1 Kintap.

Multiobjective optimization of porous medium for efficient transpiration cooling of hypersonic vehicles using genetic algorithm

Transpiration cooling has been proven an effective method for reducing heat flux on the surfaces of high-speed vehicles. This study investigates the effects of porous medium properties, employing a black-box optimization method to determine the optimal length, thickness, and porosity for a porous medium in a transpiration cooling system on a flat plate under hypersonic laminar flow. The objectives include optimizing thermal effectiveness, coolant consumption, and the weight and cost of the porous material. A multiobjective genetic optimization algorithm is directly integrated with a Computational Fluid Dynamics (CFD) solver, and 1562 CFD simulations were conducted to identify the optimal configuration. The results demonstrate that the length and porosity of the porous medium more significantly impact thermal effectiveness than the thickness. Furthermore, the optimization identified a configuration for the porous medium that, when compared to the original case, shows reductions in length, thickness, and porosity of 3.5%, 11%, and 29%, respectively. Additionally, there were average improvements in thermal effectiveness and coolant consumption of 4.56% and 3.9%, respectively, while the weight and cost of the porous material increased by 3.73% and 3.65%, respectively.

TextJuggler: Fooling text classification tasks by generating high-quality adversarial examples

Deep neural networks are vulnerable to adversarial attacks, despite performing well in a variety of tasks. In the current black-box word-level text adversarial attacks on various classification tasks, the main problems are the relatively low success rate and the need to improve the quality of the adversarial examples generated. These problems mainly involve two aspects: first, the key to effectively conducting adversarial attacks is accurately determining the key words in a sentence that significantly affect the model’s judgment. Only by precisely finding these words can the attack be effectively performed. Second, to generate high-quality adversarial examples, it is essential to mislead the classification model while minimizing changes to words in the sentence. It is essential to ensure that adversarial examples are as semantically and grammatically similar to the original samples as possible. Therefore, accurately determining key words and minimally altering them to produce high-quality adversarial examples presents a significant challenge. To address these challenges, we introduce TextJuggler, a new black-box word-level text adversarial attack method, inspired by occlusion and language modeling concepts. By using the Bert model to sample and replace words in sentences, the key words that influence classifier decisions can be efficiently determined. To ensure efficiency in the search for key words, our method reduces queries via crafted locality-sensitive hashing. For the determined key words, we adopt the robust and optimized Bert model, to generate high-quality adversarial examples through insertion or substitution operations for different text classification tasks while ensuring semantic similarity and text fluency. Extensive experiments and API experiments show that TextJuggler outperforms the baselines in attack success rate, textual similarity, and fluency.

Measurement-based Dynamic Modelling in Levitated Active Magnetic Bearing Systems

Commissioning Active Magnetic Bearings (AMB) requires a well-designed control system to reject external disturbances while supporting process loads. An accurate dynamic model is essential for predicting responses to various excitations and disturbances, aiding in controller design. Current models for AMB commissioning are either nonparametric estimations, which provide limited information, or finite element models, which may not capture all system dynamics. This paper presents a black-box method to develop a parametric model that captures all dynamics within an AMB system using measurement data. Frequency domain measurement data was used to construct a segmental linear model to simulate dynamic interactions. The controller, actuation, and sensor components were derived from SKF Magnetic Mechatronics design calculations to isolate the rotor from the plant model and reconstruct the closed-loop system model. The frequency response of the identified rotor model was compared to direct measurements, and the resulting system model was compared to direct measurements of the closed-loop response. Results show that the proposed segmental AMB system model predicts frequency response with 97.9% accuracy compared to direct measurements. This model will be used to design control methods to improve AMB system performance.

Research Project Topic Recommender System Using Generative Language Model

Education has become a driver of a person's continuous innovation to improve their quality. Currently, the use of artificial intelligence determines progress in education. In this research, artificial intelligence technology was applied to develop a web-based recommendation system to help students at the Faculty of Computer Science, Klabat University, choose appropriate research topics for their final assignments. To provide personalized and contextually relevant suggestions, the recommendation system leverages deep learning and generative language models, specifically GPT-3. The Rapid Application Development process model is employed to develop the system. Its key components include semantic search, rapid engineering, and an advanced vector database for effective data management and retrieval. The functions provided by the system include user account registration, login, input of major subject grades and research preferences, and personalized recommendation results. Some additional features such as profile management, previous recommendation history, and password reset options are also provided. All these functions have been tested using the black box method.

Improving Library Services: A Web-Based Solution for Jember Regency Prosecutor's Office

In the era information technology advancement, adaptation and integration of technology have become essential needs for organizations across various sectors. This research endeavors to design and implement an efficient and modern web-based library system to the specific needs of the Jember Regency Prosecutor's Office. This study employs structured analysis to comprehensively understand existing library management processes, and it adopts the waterfall model for system development. This model entails sequential stages, including requirement analysis, system design, implementation, and testing using black box method, ensuring a systematic approach to system development. Data collection techniques involve interviews with key stakeholders and examination of existing systems and processes. Data analysis encompasses identifying challenges and requirements, which inform system design and development. The findings indicate that the newly developed web-based library system effectively addresses identified challenges, streamlining administrative processes and enhancing user experience. Its successful implementation is expected to significantly improve operational efficiency and resource accessibility at the Jember Regency Prosecutor's Office library, contributing to the modernization of library services in Indonesia and paving the way for future advancements in library technology development.

Sistem Informasi Pelaporan Perkembangan Pasien (SI-PELPASI) berbasis Mobile Android

The use of Android mobile applications in the healthcare sector as tools for patient progress reporting has become a significant innovation. The mobile Android-based patient progress reporting information system (SI-PELPASI) serves as a solution to enhance efficiency and accuracy in patient monitoring. This study aims to develop a mobile Android-based patient progress reporting information system at the Bukit doa rehabilitation centre, an Institution for Mandatory Reporting (IPWL). The system development in this study employs the System Development Life Cycle (SDLC) method, which consists of systematic stages: the planning stage aims to plan the system, the analysis stage involves reviewing existing and current systems and collecting data through interviews and observations, the design stage includes designing Unified Modelling Language (UML) diagrams and the user interface, the implementation stage uses the Kodular app creation platform, and the testing stage uses the black box method to test system functionality. Our findings resulted in the Patient Progress Reporting Information System in the form of a Mobile Android application named SI-PELPASI. The application runs smoothly and can be operated on Android-based mobile devices. With this application, the process of reporting patient progress becomes faster and real-time.

Sistem Informasi Penjualan Seprai Pada Toko Salsabila Seprai

Technological developments are needed in carrying out various sales activities. Currently, it has become a necessity that information technology can provide convenience in finding the desired information. Toko Salsabila Seprai started running its business through the Instagram platform but there were various problems such as the lack of monitoring of the transaction process and transaction reports which were still done manually because the sales system was not integrated. Therefore, the purpose of this research is to develop a website-based sales information system using the SDLC method. This system is used by the Salsabila Store as a media for sales and transaction data management. The design of this sales information system uses a structured method. Website implementation is made using the HTML, PHP and MySQL programming languages and using the Bootstrap framework so that the web appearance becomes responsive and attractive. The results obtained are a website-based bed sheet sales information system application that is equipped with main page menu features, login, customer registration, shopping cart, purchases, payments, sales reports and admin pages for data management. Based on the test results using the blackbox method, these features can function properly and are valid.

Calibration method for complex permittivity measurements using s-SNOM combining multiple probe tapping harmonics.

Scattering-type scanning near-field optical microscopy (s-SNOM) enables sub-diffraction spectroscopy, featuring high sensitivity to small spatial permittivity variations of the sample surface. However, due to the complexity of the near-field probe-sample interaction, the quantitative extraction of the complex permittivity leads to a computationally demanding inverse problem, requiring further approximation of the system to an invertible model. Black-box calibration methods, similar to those applied to microwave vector network analyzers, allow the extraction of the permittivity without detailed electromagnetic modeling of the probe-sample interaction. These methods, however, are typically designed for stationary setups. In contrast, the distance between the sample and the probe tip of the s-SNOM is periodically modulated to differentiate the near-field interaction from the far-field background via lock-in detection of the harmonics of the periodic motion. This paper proposes an improved black-box calibration method that takes account of the effects of the probe tapping, including its multiple harmonics, and far-field background. The method is validated for an s-SNOM operating in the mid-infrared spectral range by applying it to spectroscopic measurements of silicon microstructures of different but well characterized doping.

Transferable adversarial attack based on sensitive perturbation analysis in frequency domain

Recently, transferable adversarial attacks on deep neural networks (DNNs) have attracted significant attention. Although existing adversarial attacks have achieved high attack success rates in white-box scenarios, they perform poorly in black-box attack scenarios. To address the issue of low transferability in black-box adversarial attacks, we propose a frequency-sensitive perturbation-based black-box adversarial attack method to enhance transferability performance from the perspective of Fourier domain sensitivity. Initially, the Fourier sensitivity heatmaps of multiple substitute models are integrated to identify the common sensitive frequency region. Subsequently, the perturbations in the frequency domain are optimized through joint loss, thereby constraining the sensitive region and limiting the perturbations in the non-sensitive region. Finally, in each iteration, a spectral model enhancement is performed to simulate additional substitute models and reduce the spectral discrepancy between the substitute and target models. Extensive experimental results on benchmark datasets demonstrated the effectiveness of the proposed method. Compared to existing black-box adversarial attack methods, the proposed approach generates targeted and non-targeted adversarial samples with higher transfer success rates and good invisibility, thereby confirming its superiority.

SUETA: Speaker-specific utterance ensemble based transfer attack on speaker identification system

With the widespread application of speaker identification (SI) systems in security-related tasks, the robustness of SI systems against adversarial examples has garnered increasing attention. Existing works have demonstrated the vulnerability of SI systems to transfer-based black-box attacks, wherein attackers generate adversarial examples with a surrogate model and then transfer them to attack the target system. However, the attack success rate (ASR) of transfer-based black-box attacks is limited by the transferability of adversarial examples. As far as we know, few works have investigated enhancing the transferability of adversarial examples for speech utterances to attack SI systems. Furthermore, existing works only utilize a single utterance in the attack process, but in practical situations, an attacker can usually collect multiple utterances of a speaker. In this paper, we propose a novel transfer-based black-box attack method, called speaker-specific utterance ensemble based transfer attack (SUETA), to attack SI systems. To the best of our knowledge, SUETA is the first transfer-based black-box attack method that utilizes multiple utterances instead of a single one. Furthermore, we also propose an improved variant of SUETA, called SUETA+, by sharing gradients of utterances at the speaker-embedding level. Empirical results show that both SUETA and SUETA+ improve the ASR compared to the baselines under the classical cross-model situation. SUETA+ further shows additional improvement over SUETA, especially in the case of the untargeted attack. SUETA+ also outperforms the baselines in cross-dataset and cross-preprocessor situations, although the ASR for all transfer-based attacks decreases compared to that in the cross-model situation. Moreover, SUETA+ can significantly improve the ASR against commercial APIs (iFlytek and TalentedSoft) and the voice assistant (Tmall Genie) for the untargeted attack compared to the baselines.

User Acceptance Test Aplikasi Mobile SI CANTIK BANGSA untuk Pencatatan Kesetaraan Gender dalam Pembangunan Desa

Gender equality is a complex issue that is difficult to eliminate in a society with a strong patriarchal culture. The Gender Empowerment Index (IDG) of Kebumen Regency decreased from 66.89% in 2021 to 66.86. The Kebumen Regency Government together with Institut Teknologi Telkom Purwokerto adopted the Si Cantik Bangsa Platform to support the activities of WANI LEmPER program cadres. This study aims to test the SI CANTIK BANGSA Mobile Application for recording gender equality in village development using the User Acceptance Test (UAT) method, namely alpha testing and beta testing. The results of alpha testing with the black box method show that all application modules are functioning properly. Beta testing using the System Usability Scale (SUS) resulted in an average score of 78.25, which means the application is acceptable with a grade C and an adjective rating of "Good". In conclusion, the Si Cantik Bangsa Mobile Application can be accepted by users, but it needs system improvement. The analysis showed the 6th question had the lowest score of 2.9 and the 9th question a score of 3.1, indicating areas in need of improvement

Aplikasi Sistem Presensi Karyawan Secara Online Pada PT Svarna Dipa Green Garden Jakarta Barat Berbasis Web dengan Metode Location Based Service menggunakan PHP

The advancement of information technology has provided various facilities that positively impact organizational activities. Rapidly evolving information technology is expected to facilitate users in obtaining information. This information is used by companies as a basis for future planning and decision-making. PT Svarna Dipa Green Garden, a major company in Indonesia located in Cengkareng, West Jakarta, was established in 2018 and operates as an electronic distribution agent. Despite being a large company, the employee attendance system at PT Svarna Dipa Green Garden remains manual, using WhatsApp for communication between employees and supervisors. This manual system causes issues such as unstructured attendance data recording and difficulties in creating summary reports of attendance, leave, and overtime data. This study aims to develop a web-based employee attendance application with Location Based Service (LBS) using PHP framework Laravel and MySQL. The application will be tested using the black-box method to identify and evaluate errors. The implementation of this application aims to simplify attendance activities, leave applications, and data management, as well as facilitate report creation at PT Svarna Dipa Green Garden, West Jakarta.