Reviewerly/exHarmony huggingface dataset:
RT-YOLO: A Residual Feature Fusion Triple Attention Network for Aerial Image Target Detection

In recent years, target detection of aerial images of unmanned aerial vehicle (UAV) has become one of the hottest topics.However, target detection of UAV aerial images often presents false detection and missed detection.We proposed a modified you only look once (YOLO) model to improve the problems arising in object detection in UAV aerial images: (1) A new residual structure is designed to improve the ability to extract features by enhancing the fusion of the inner features of the single layer.At the same time, triplet attention module is added to strengthen the connection between space and channel and better retain important feature information.(2) The feature information is enriched by improving the multi-scale feature pyramid structure and strengthening the feature fusion at different scales.(3) A new loss function is created and the diagonal penalty term of the anchor frame is introduced to improve the speed of training and the accuracy of reasoning.The proposed model is called residual feature fusion triple attention YOLO (RT-YOLO).Experiments showed that the mean average precision (mAP) of RT-YOLO is increased from 57.2% to 60.8% on the vehicle detection in aerial image (VEDAI) dataset, and the mAP is also increased by 1.7% on the remote sensing object detection (RSOD) dataset.The results show that the RT-YOLO outperforms other mainstream models in UAV aerial image object detection.
Empirical Evaluation of ECC Batch Verification Algorithms of Digital Signature in Wireless Sensor Network

Wireless sensor network (WSN) is an emerging topic in wireless communication where various sensor nodes are connected over the internet for data exchange. Exchanging the information over the WSN is very critical; therefore, it requires authentication and security mechanisms to ensure integrity and confidentiality. To avoid unauthorized use of WSN, the authentication through a digital signature turns into an essential task in WSN. Verification of individual signature is taking too much time and it is not suitable for wireless sensor network. Digital signature verification time can be reduced by using batch verification techniques in WSN. Therefore, the goal of this research is to examine and analyze the different type of batch verification algorithm based on Elliptic Curve Cryptography (ECC). With respect to security, the entire algorithm is identical to the standard Elliptic Curve Digital Signature Algorithm (ECDSA) verification algorithm. These algorithms are effectively limited to small batch sizes.
A Short Review of Python Libraries and Data Science Tools

The features of Python and its modules are compared in this paper against those of other programming languages like R. The article also delves into the characteristics and motivations that have contributed to Python and its modules' meteoric rise in favour among data scientists and app developers. Their value and importance in solving real-world problems and making meaningful advancements in existing applications are also not to be underestimated.
PENGARUH JUMLAH FUNGSI KEANGGOTAAN PADA METODE FUZZY LOGIC TERHADAP HASIL PERAMALAN BEBAN LISTRIK JANGKA PANJANG

Electric load in Sumbawa Besar Regency from 2011 - 2018 experienced an average increase of ± 6.6%. The electric load for the following year is not yet known, so forecasting is needed. Electric load forecasting has an important role in the energy management system. Many methods can be used for forecasting, one of them is the fuzzy logic method. Fuzzy logic method consists of 3 components, those are Fuzzification, Fuzzy Inference System, and Defuzzification. Fuzzification is an important component of the fuzzy logic method, so the proper configuration is needed in order to produce forecasting that is close to the actual data. The simulation was carried out in 3 conditions, those are the first conditions (3 membership functions), the second condition (5 membership functions), and the third condition (7 membership functions). The third condition obtained a MAPE value of 2,42%, while the second condition was 3,34%, and the first condition was 6,51%. The third condition obtained the simulation results in 2026 at 24,75MW, while the second condition was at 23,26 MW, and the first condition was at 20,97MW. The third condition is the best condition in this study, because it has the smallest MAPE value.
(NON)AUTONOMOUS SUBORDINATION OF ACADEMIC TEACHERS

The aim of the foregoing study is to show that the subordination of academic teachers employed on the basis of an employment relationship is not at all autonomous, although it is generally accepted that their work is characterized by a high level of independence and does not display elements of classical subordination. It turns out that the traditional paradigm of subordinate work also works well in relation to those pursuing creative careers, including academic teachers. Using the example of academic teachers, the author tries to prove that despite the changes in socio-economic conditions, progressive technological development and new forms of work, the role of subordination as an essential feature distinguishing the employment relationship from other legal employment relationships is still crucial, making this criterion a necessary, most important structural feature of the employment relationship which should not be abandoned in any case.
Application of Utility Mining using Frequent Itemset and Association Rules: A Survey

Mining on data reveals patterns that provide useful information for analysis, decision making and forecasting in various domains. Association Rule Mining (ARM) identifies patterns on itemsets which are either frequent or have interesting relationship amongst them based on strong rules and conceptually form a basis for Frequent Itemset mining (FIM) problems. FIM extracts binary values from transaction databases to identify frequently bought items but provides insufficient information for identifying infrequent items that generate maximum profit. So a latter problem, High utility itemsets (HUI) mining was developed to focus on the itemsets that generate huge profit to the business. Even though HUI is related to Business Intelligence, its application extends to Web Server Logs, Biological Gene Databases, Network Traffic Measurements and many other fields. This paper presents a survey on the algorithms from different aspects and perspectives based on Utility mining, Frequent Itemset generation and Association Rule Mining
Integration of Repository System in Optimization Data for Graduates’ Scientific Paper

Academic libraries manage collections and offer the community the best services possible, one of which is library-free services. In the free management of a library, an institutional repository is an essential aspect because, with it, graduates can publish their writings to the public. However, the number of graduates and repository data from various universities differ. It requires integration, automation, and graduation registration systems, so everything is interrelated. As a result, everything is interconnected and cannot proceed if the first stage is not completed. So it is necessary to create an online library free submission system that can combine these three systems. The study shows that the three systems can be integrated, providing maximum data optimization between graduate and repository data.&#x0D; &#x0D;
Categorising Virtual Reality Content

The current second wave of Virtual Reality (VR) initiated after the advent of the Oculus Rift in 2012 has led to millions of head-mounted displays (HMDs) being sold worldwide and to a vast and varied amount of content being produced. In addition, as it happened with the VR’s first wave a few decades ago, an exciting body of research has emerged. During both such waves, much of such research has described VR’s pivotal terminology ambiguously, which among other things has led to a lack of agreement on the nomenclature of VR content types. This paper proposes to consider VR as a medium with its own set of core elements, shedding light on its specificities. The text offers a taxonomy of VR content types taking into consideration such core elements and in particular, the concept of embodied interactivity, proposing possible directions to further advance the medium.
Integrated Color and Intensity MSF Scheme for Image Retrieval Systems

Markov Stationary Features (MSF) based on homogeneous Markov chain model, for content-based image analysis, is getting popularity nowadays. It not only considers the distribution of colors, just as the histogram method does, but also characterizes the spatial co-occurrence of histogram patterns. However, handling a large-scale database of images with a degree of heterogeneity, a simple MSF method is not sufficient to discriminate the images as one requires. In this paper, an Integrated Color and Intensity MSF (ICI-MSF) based on non-homogeneous Markov Chain is proposed to overcome this shortcoming. By incorporating spatial co-occurrence of image intensities with the spatial co-occurrence information of colors and exploiting time inhomogeneous Markov chain concept, it is possible to improve certain aspects of the existing methods. Without compromising effectiveness and robustness, the method proposed in this paper keeps the feature level simplicity. Widely recognized databases namely WANG1000 and Corel10800, are used to evaluate and compare the performance of the proposed algorithm with the existing methods. The experimental results justify the effectiveness of the proposed method.
Digital Transitions in Higher Education: European Dimension

In the article, the trends and approaches to digital transitions in higher education in the context of quality assurance are revealed based on the analysis and synthesis of the strategies of the global and European dimension, presented in the documents of the UN and the European Commission, as well as in the analytical and guiding documents of the EHEA. The global social development goals of the UN and the European Education Area are agreed primarily in terms of equal access to quality higher education for vulnerable populations, modernization of higher education institutions to create an inclusive educational environment, and are required the introduction of digitalization in higher education in order to achieve them. A trend towards the spread of digitally enhanced learning and teaching (DELT) in the EHEA covering both the traditional format of providing higher education and distance education has been revealed. The main approaches to providing digital higher education have been determined. A partnership approach to assuring high-quality and inclusive digital higher education requires the consolidation of public efforts based on the partnership of various stakeholders, and national policies and legislation should provide for such partnership and mechanisms for its implementation. The investment approach to financing the resource provision of quality digital higher education involves attracting appropriate investments in connectivity, equipment, and organizational potential and skills for successful digital transition in higher education. Digitally competency approach to the development of professional standards for University teachers and their professional development, re-training and professional excellence in the context of digital transition. An open approach to creating digital courses on platforms available for obtaining degree qualifications, partial qualifications and micro-credentials. A systematic approach to the creation and development of digital study programmes, which provides for high-quality educational content and quality assurance of digital higher education, in particular digital teaching, learning and assessment. It is emphasized that national strategic and other documents in higher education should be harmonized with international documents and strategies regarding digital transition in higher education to effectively introduce high-quality digital higher education in Ukraine and overcome the challenges of the state of war.
Color Image Encryption and Decryption by Using Optical Scanning Cryptography Method

In this paper, a computer simulation of optical encryption for color images are presented based on the optical scanning cryptography technique that T.C. Poon suggested in 2003. This method is based on using an encryption key; the color image is optically encrypted. The output is a signal at a radio frequency which it transmits to a receiver (secure site) via an antenna for digital storage and decryption. To create an electrical signal, the same optical scanning system is employed in the secure site, along with a decryption key. After that, the electrical signal is analyzed and transferred to a computer for decryption; a digital decryption unit performs a decryption algorithm. The electrical signal is then analyzed and delivered to a computer for decryption, where a decryption procedure is performed by a digital decryption unit. The decryption unit will decrypt the color image if the encryption and decryption keys are identical. To ensure the system’s effectiveness, by applying several image quality measures to measure the quality of the recovered image (after encryption). The encryption result indicates that the proposed technique produces a noise-like structure that reveals no useful information about the original image.
Development of Student Worksheets Based on Multiple Intelligence in Thematic Learning of Grade IV Elementary Schools

The various bits of intelligence of elementary school-age children can be explored and developed. This diverse intelligence is known as multiple intelligence. Student Worksheets based on multiple intelligences can be used for thematic learning so that students become more active and enthusiastic in participating in learning. The results of observations and interviews conducted before the research showed that the teacher had never made student worksheets and only used student worksheets in student thematic books. Students also never use multiple intelligence-based student worksheets in learning. This study aims to develop various intelligence-based student worksheets in thematic learning to improve students' numerous intelligence abilities. This study uses research and development (R&amp;D) methods. This research was conducted at MI Baitul Huda Semarang, Central Java, Indonesia, with a total of 65 students. The results showed that (1) multiple intelligence-based student worksheets in thematic learning were developed based on an analysis of the needs of teachers and students. (2) the results of the assessment of the two students worksheet validators were 90.4% and 92.3% on every feasible criterion. The assessment from psychologists was 93.8% with very appropriate criteria, (3) the effectiveness of multiple intelligence-based student worksheets was assessed from the N-gain test with a result of 0.83 with an effectiveness percentage of 83. The results of the hypothesis test showed that t count (17.957) &gt; t table (2.036), (4) the acceptability of multiple intelligence-based student worksheets is assessed based on teacher and student response questionnaires with a percentage of 87.5% and 97.5% on every feasible criterion. Keywords: Student Worksheets, Multiple Intelligence, Thematic Learning
PERANCANGAN PLTS ATAP DI GEDUNG GRAHA SEWAKA DHARMA

The utilization of renewable energy can be a solution to support the supply of electricalenergy, one of which is the use of solar energy with rooftop solar panels. In this study, the roofof the Graha Sewaka Dharma Building was used as a location for the design of rooftop solarpower plants to be able to help with electrical energy needs and support government programsin developing the use of solar energy. The total roof area of Graha Sewaka Dharma Building is1,616.37 m2. This design uses a battery-free On-grid PLTS system using a Solaria PowerXT-400R-PM solar module with a capacity of 400 Wp and a Ginlong Solis S5-GC36K-LV inverterwith a capacity of 36 kW. This design will calculate the capacity of solar modules that can beinstalled and the electrical energy produced with the limitation of the roof area and load profile inthe Graha Sewaka Dharma Building. Based on the results of the study, the capacity of therooftop PLTS installed in the Graha Sewaka Dharma Building is 188.8 kWp with a total of 472solar module units and 6 inverter units. The energy output produced per year (energy yield) is306,2 MWh/year. The investment feasibility study using the methods Net Present Value,Profitability Index, and Discounted Payback Period shows that this design investment isfeasible. Further research is recommended to study the impact of reducing carbon emissions onthe use of the PV grid.
An FPGA-Based Weightless Neural Network for Edge Network Intrusion Detection

Algorithms for mobile networking are increasingly being moved from centralized servers towards the edge in order to decrease latency and improve the user experience. While much of this work is traditionally done using ASICs, 6G emphasizes the adaptability of algorithms for specific user scenarios, which motivates broader adoption of FPGAs. In this paper, we propose the FPGA-based Weightless Intrusion Warden (FWIW), a novel solution for detecting anomalous network traffic on edge devices. While prior work in this domain is based on conventional deep neural networks (DNNs), FWIW incorporates a weightless neural network (WNN), a table lookup-based model which learns sophisticated nonlinear behaviors. This allows FWIW to achieve accuracy far superior to prior FPGA-based work at a very small fraction of the model footprint, enabling deployment on small, low-cost devices. FWIW achieves a prediction accuracy of 98.5% on the UNSW-NB15 dataset with a total model parameter size of just 192 bytes, reducing error by 7.9x and model size by 262x vs. LogicNets, the best prior edge-optimized implementation. Implemented on a Xilinx Virtex UltraScale+ FPGA, FWIW demonstrates a 59x reduction in LUT usage with a 1.6x increase in throughput. The accuracy of FWIW comes within 0.6% of the best-reported result in literature (Edge-Detect), a model several orders of magnitude larger. Our results make it clear that WNNs are worth exploring in the emerging domain of edge networking, and suggest that FPGAs are capable of providing the extreme throughput needed.
From Instance to Metric Calibration: A Unified Framework for Open-World Few-Shot Learning

Robust few-shot learning (RFSL), which aims to address noisy labels in few-shot learning, has recently gained considerable attention. Existing RFSL methods are based on the assumption that the noise comes from known classes (in-domain), which is inconsistent with many real-world scenarios where the noise does not belong to any known classes (out-of-domain). We refer to this more complex scenario as open-world few-shot learning (OFSL), where in-domain and out-of-domain noise simultaneously exists in few-shot datasets. To address the challenging problem, we propose a unified framework to implement comprehensive calibration from instance to metric. Specifically, we design a dual-networks structure composed of a contrastive network and a meta network to respectively extract feature-related intra-class information and enlarged inter-class variations. For instance-wise calibration, we present a novel prototype modification strategy to aggregate prototypes with intra-class and inter-class instance reweighting. For metric-wise calibration, we present a novel metric to implicitly scale the per-class prediction by fusing two spatial metrics respectively constructed by the two networks. In this way, the impact of noise in OFSL can be effectively mitigated from both feature space and label space. Extensive experiments on various OFSL settings demonstrate the robustness and superiority of our method. Our source codes is available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/anyuexuan/IDEAL</uri> .
Nigerian Film Industry and Screenplay Text: Historical and Linguo-Socio-Cultural Symbiosis

The issue of the development of the Nigerian film industry and the specifics of the screenplay text as a reflection of the linguocultural picture of the world is considered. The question is raised about identifying the linguo-socio-cultural features of the screenplay text formed during the contact interaction of British English and the indigenous languages and cultures of Nigeria. It is proved that the text of the Nigerian film script has all the key textual categories, like the texts of British and American films, but in the refraction of the Nigerian linguistic culture. The scientific novelty of the study is determined by the derived new properties of the Nigerian screenplay text in the process of linguocultural adaptation of British English to the realities of Nigerian culture. The author’s development of a model of linguocultural adaptation of the Nigerian screenplay text is presented and its unique properties at the level of vocabulary and grammar are revealed. Particular attention is paid to the aspect of the sociolinguistic differentiation of the Nigerian society and the identification of errors in the dialogic communication of the characters depending on their belonging to the sociolinguistic type — acrolect, mesolect, basilect. The results obtained can be used for researchers in the field of the theory of language contacts in the field of communicative syntax.
Classification of online school problems from tweets on Twitter using support vector algorithm

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation Derbi Wulan Fitri, Toha Saifudin, Nur Chamidah; Classification of online school problems from tweets on Twitter using support vector algorithm. AIP Conference Proceedings 25 January 2023; 2554 (1): 030016. https://doi.org/10.1063/5.0104576 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search
Semi-automatic Chatbot Generation for Web APIs

The Chatbot is a new and popular technology in recent years. With Web API technology becoming increasingly mature, how to integrate Web APIs and Chatbots has become an issue of great interest. Based on the concept of Model-Driven Engineering, this research proposes a semi-automatic generation method and its associated tool, called BOTEN, to allow application developers to build Chatbot interfaces with specified Web APIs quickly. To ensure that the Chatbot has sufficient NLU (natural language understanding) capability, we also propose a method, called SCASG (sentence coupling analysis and sentence generation), to evaluate the training sentences written by the developer based on TF-IDF, WordNet, and SpaCy techniques. SCASG provides the “coupling” analysis for sentences and warns the developer to modify the poor-quality training sentences. SCASG can also automatically increase the number of training sentences to improve the NLU capability of a Chatbot.