bluuebunny/crossref_metadata_2025 huggingface dataset:
SCRAPS: Speech Contrastive Representations of Acoustic and Phonetic Spaces
Authors: Valles-Perez Ivan , Beringer Grzegorz , Bilinski Piotr , Cook Gary , Barra-Chicote Roberto
Published: September 2023

Numerous examples in the literature proved that deep learning models have the ability to work well with multimodal data. Recently, CLIP has enabled deep learning systems to learn shared latent spaces between images and text descriptions, with outstanding zero- or few-shot results in downstream tasks. In this paper we explore the same idea proposed by CLIP but applied to the speech domain, where the phonetic and acoustic spaces usually coexist. We train a CLIP-based model with the aim to learn shared representations of phonetic and acoustic spaces. The results show that the proposed model is sensible to phonetic changes, with a 91% of score drops when replacing 20% of the phonemes at random, while providing substantial robustness against different kinds of noise, with a 10% performance drop when mixing the audio with 75% of Gaussian noise. We also provide empirical evidence showing that the resulting embeddings are useful for a variety of downstream applications, such as intelligibility evaluation and the ability to leverage rich pre-trained phonetic embeddings in speech generation task. Finally, we discuss potential applications with interesting implications for the speech generation and recognition fields.
On the Learning Dynamics of Attention Networks
Authors: Vashisht Rahul , Ramaswamy Harish G.
Published: September 2023

Attention models are typically learned by optimizing one of three standard loss functions that are variously called – soft attention, hard attention, and latent variable marginal likelihood (LVML) attention. All three paradigms are motivated by the same goal of finding two models– a ‘focus’ model that ‘selects’ the right segment of the input and a ‘classification’ model that processes the selected segment into the target label. However, they differ significantly in the way the selected segments are aggregated, resulting in distinct dynamics and final results. We observe a unique signature of models learned using these paradigms and explain this as a consequence of the evolution of the classification model under gradient descent when the focus model is fixed. We also analyze these paradigms in a simple setting and derive closed-form expressions for the parameter trajectory under gradient flow. With the soft attention loss, the focus model improves quickly at initialization and splutters later on. On the other hand, hard attention loss behaves in the opposite fashion. Based on our observations, we propose a simple hybrid approach that combines the advantages of the different loss functions and demonstrates it on a collection of semi-synthetic and real-world datasets.
How Does Diffusion Influence Pretrained Language Models on Out-of-Distribution Data?
Authors: Wang Huazheng , Cheng Daixuan , Sun Haifeng , Wang Jingyu , Qi Qi , Liao Jianxin , Wang Jing , Liu Cong
Published: September 2023

Transformer-based pretrained language models (PLMs) have achieved great success in modern NLP. An important advantage of PLMs is good out-of-distribution (OOD) robustness. Recently, diffusion models have attracted a lot of work to apply diffusion to PLMs. It remains under-explored how diffusion influences PLMs on OOD data. The core of diffusion models is a forward diffusion process which gradually applies Gaussian noise to inputs, and a reverse denoising process which removes noise. The noised input reconstruction is a fundamental ability of diffusion models. We directly analyze OOD robustness by measuring the reconstruction loss, including testing the abilities to reconstruct OOD data, and to detect OOD samples. Experiments are conducted by analyzing different training parameters and data statistical features on eight datasets. It shows that finetuning PLMs with diffusion degrades the reconstruction ability on OOD data. The comparison also shows that diffusion models can effectively detect OOD samples, achieving state-of-the-art performance in most of the datasets with an absolute accuracy improvement up to 18%. These results indicate that diffusion reduces OOD robustness of PLMs.
VMBRL3: A Simple Visual Model-Based Reinforcement Learning Framework for Continuous Control
Authors: Wang Jian , Wang Haitao , Wu Hejun
Published: September 2023

Unsupervised pre-training has demonstrated its potential for accurately constructing world models in visual model-based reinforcement learning (MBRL). However, such MBRL approaches exhibit limited generalizability, thereby limiting their practicality in diverse scenarios. These methods produce models that are restricted to the specific task they were trained on, and are not easily adaptable to other tasks. In this work, we introduce a powerful unsupervised pre-training reinforcement learning (RL) framework called VMBRL3, which improves the generalization ability of visual MBRL. VMBRL3 employs task-agnostic videos to pre-train both the autoencoder and world model without access to actions or rewards information. The fine-tuned world model can then be applied to a range of downstream reinforcement learning tasks, allowing for rapid adaptation to diverse environments and facilitating policy learning. We demonstrate that our framework significantly improves generalization ability in a variety of manipulation and locomotion tasks. Furthermore, VMBRL3 doubles the sample efficiency and overall performance compared to previous visual methods of MBRL.
Attention Based Models for Cell Type Classification on Single-Cell RNA-Seq Data
Authors: Wang Tianxu , Fan Yue , Ma Xiuli
Published: September 2023

Cell type classification serves as one of the most fundamental analyses in bioinformatics. It helps recognizing various cells in cancer microenvironment, discovering new cell types and facilitating other downstream tasks. Single-cell RNA-sequencing (scRNA-seq) technology can profile the whole transcriptome of each cell, thus enabling cell type classification. However, high-dimensional scRNA-seq data pose serious challenges on cell type classification. Existing methods either classify the cells with reliance on the prior knowledge or by using neural networks whose massive parameters are hard to interpret. In this paper, we propose two novel attention-based models for cell type classification on single-cell RNA-seq data. The first model, Cell Feature Attention Network (CFAN), captures the features of a cell and performs attention model on them. To further improve interpretation, the second model, Cell-Gene Representation Attention Network (CGRAN), directly concretizes tokens as cells and genes and uses the cell representation renewed by self-attention over the cell and the genes to predict cell type. Both models show excellent performance in cell type classification; additionally, the key genes with high attention weights in CGRAN indicate and identify the marker genes of the cell types, thus proving the model’s biological interpretation.
Adversarial Erasing with Pruned Elements: Towards Better Graph Lottery Tickets
Authors: Wang Yuwen , Liu Shunyu , Chen Kaixuan , Zhu Tongtian , Qiao Ji , Shi Mengjie , Wan Yuanyu , Song Mingli
Published: September 2023

Graph Lottery Ticket (GLT), a combination of core subgraph and sparse subnetwork, has been proposed to mitigate the computational cost of deep Graph Neural Networks (GNNs) on large input graphs while preserving original performance. However, the winning GLTs in exisiting studies are obtained by applying iterative magnitude-based pruning (IMP) without re-evaluating and re-considering the pruned information, which disregards the dynamic changes in the significance of edges/weights during graph/model structure pruning, and thus limits the appeal of the winning tickets. In this paper, we formulate a conjecture, i.e., existing overlooked valuable information in the pruned graph connections and model parameters which can be re-grouped into GLT to enhance the final performance. Specifically, we propose an adversarial complementary erasing (ACE) framework to explore the valuable information from the pruned components, thereby developing a more powerful GLT, referred to as the ACE-GLT. The main idea is to mine valuable information from pruned edges/weights after each round of IMP, and employ the ACE technique to refine the GLT processing. Finally, experimental results demonstrate that our ACE-GLT outperforms existing methods for searching GLT in diverse tasks. Our code is available at https://github.com/Wangyuwen0627/ACE-GLT.
Online Privacy Preservation for Camera-Incremental Person Re-Identification
Authors: Wu Sheng , Ge Wenhang , Wu Jiong , Meng Jingke , Zhang Huang
Published: September 2023

Task-incremental person re-identification aims to train a model with consecutively available cross-camera annotated data in the current task and a small number of saved data in preceding tasks, which may lead to individual privacy disclosure due to data storage and annotation. In this work, we investigate a more realistic online privacy preservation scenario for camera-incremental person re-identification, where data storage in preceding cameras is not allowed, while data in the current camera are intra-camera annotated online by a pedestrian tracking algorithm without cross-camera annotation. In this setup, the missing data of previous cameras not only results in catastrophic forgetting as task-incremental learning, but also makes the cross-camera association infeasible, which further leads to the incapability of person matching across cameras due to the camera-wise domain gap. To solve these problems, we propose an Online Privacy Preservation (OPP) framework based on the generated exemplars of previous cameras by DeepInversion, where generated exemplars used as supplements to alleviate forgetting and enable cross-camera association to be feasible for camera-wise domain shift mitigation, meanwhile further improving the cross-camera matching capability. Specifically, we propose to mine underlying cross-camera positive pairs between samples of the current camera and exemplars of previous cameras by similarity cues. Furthermore, we introduce a mixup learning strategy to handle the domain gap with mixed samples and labels. Finally, intra-camera incremental learning and cross-camera incremental learning are aggregated into the OPP framework. Extensive experiments on Re-ID benchmarks validate the superiority of the OPP framework as compared with state-of-the-art methods.
DPBERT: Efficient Inference for BERT Based on Dynamic Planning
Authors: Wu Weixin , Zhuo Hankz Hankui
Published: September 2023

Large-scale pre-trained language models such as BERT have contributed significantly to the development of NLP. However, those models require large computational resources, making it difficult to be applied to mobile devices where computing power is limited. In this paper we aim to address the weakness of existing input-adaptive inference methods which fail to take full advantage of the structure of BERT. We propose Dynamic Planning in BERT, a novel fine-tuning strategy that can accelerate the inference process of BERT through selecting a subsequence of transformer layers list of backbone as a computational path for an input sample. To do this, our approach adds a planning module to the original BERT model to determine whether a layer is included or bypassed during inference. Experimental results on the GLUE benchmark exhibit that our method reduces latency to 75% while maintaining 98% accuracy, yielding a better accuracy-speed trade-off compared to state-of-the-art input-adaptive methods.
Fingerprint Attack: Client De-Anonymization in Federated Learning
Authors: Xu Qiongka , Cohn Trevor , Ohrimenko Olga
Published: September 2023

Federated Learning allows collaborative training without data sharing in settings where participants do not trust the central server and one another. Privacy can be further improved by ensuring that communication between the participants and the server is anonymized through a shuffle; decoupling the participant identity from their data. This paper seeks to examine whether such a defense is adequate to guarantee anonymity, by proposing a novel fingerprinting attack over gradients sent by the participants to the server. We show that clustering of gradients can easily break the anonymization in an empirical study of learning federated language models on two language corpora. We then show that training with differential privacy can provide a practical defense against our fingerprint attack.
Data-Free Class-Incremental Learning with Implicit Representation of Prototypes
Authors: Yang Tianwen , Huang Leixiong , Luo Ronghua
Published: September 2023

Class-incremental learning (CIL) has attracted much attention in deep learning due to the challenge problem of catastrophic forgetting. Various methods have been proposed for CIL, including exemplar-based class-incremental learning (EBCIL), non-exemplar class-incremental learning (NECIL) and data-free class-incremental learning (DFCIL). Without storing any information (such as examples and prototypes) about the old classes, DFCIL is obviously the most challenging one. To address the problem of lacking information in DFCIL and with the assumption that the learned representations are not linearly separable, we propose a method called IRP. We use the L2-similarity classifier instead of the FC classifier, where each weight vector represents a prototype that implicitly records information about the classes. We use representation-prototype distance minimization (RPDM) to solve the problem of loose representation caused by overfitting. To alleviate the excessive deviation of old prototypes under long-term CIL, we add prototype changing limitation (PCL) and prototype momentum updating (PMU) in incremental stages. In addition, we design a method for resampling around old prototypes (RAOP) to maintain the decision boundary of the old classes. Numerous experiments on three benchmarks have shown that IRP is significantly superior to other DFCIL methods and performs comparably to NECIL and partial EBCIL methods.
CERM: Context-Aware Literature-Based Discovery via Sentiment Analysis
Authors: Young Julio Christian , Akujuobi Uchenna
Published: September 2023

Driven by the abundance of biomedical publications, we introduce a sentiment analysis task to understand food-health relationship. Prior attempts to incorporate health into recipe recommendation and analysis systems have primarily focused on ingredient nutritional components or utilized basic computational models trained on curated labeled data. Enhanced models that capture the inherent relationship between food ingredients and biomedical concepts can be more beneficial for food-related research, given the wealth of information in biomedical texts. Considering the costly data labeling process, these models should effectively utilize both labeled and unlabeled data. This paper introduces Entity Relationship Sentiment Analysis (ERSA), a new task that captures the sentiment of a text based on an entity pair. ERSA extends the widely studied Aspect Based Sentiment Analysis (ABSA) task. Specifically, our study concentrates on the ERSA task applied to biomedical texts, focusing on (entity-entity) pairs of biomedical and food concepts. ERSA poses a significant challenge compared to traditional sentiment analysis tasks, as sentence sentiment may not align with entity relationship sentiment. Additionally, we propose CERM, a semi-supervised architecture that combines different word embeddings to enhance the encoding of the ERSA task. Experimental results showcase the model’s efficiency across diverse learning scenarios.
Revisiting the Efficiency-Accuracy Tradeoff in Adapting Transformer Models via Adversarial Fine-Tuning
Authors: Zhang Minjia , Naresh Niranjan Uma , He Yuxiong
Published: September 2023

Adversarial fine-tuning (i.e., training on adversarial perturbed inputs) has demonstrated promising results in improving the accuracy of natural language understanding tasks. However, the improved accuracy does not come for free but is accompanied by a significantly prolonged training time, limiting their applicability to larger and more complex models. This work revisits the efficiency-accuracy trade-off in adversarial fine-tuning by systematically analyzing if adversarial fine-tuning methods, in conjunction with several efficiency optimizations, are suitable for adapting pre-trained Transformer models for natural language understanding tasks. Our results show that multiple design choices are crucial in determining the efficiency-accuracy trade-off, and we introduce a method, ScaLA, that achieves better accuracy-vs-speed trade-off than prior methods. We show in experiments that our proposed method attains up to 14.7× adaptation speedups on BERT, RoBERTa, and T5, while achieving comparable accuracy to existing methods.
XFed: Improving Explainability in Federated Learning by Intersection Over Union Ratio Extended Client Selection
Authors: Zhao Juan , Zhang Yuankai , Li Ruixuan , Li Yuhua , Wang Haozhao , Yi Xiaoquan , Deng Zhiying
Published: September 2023

Federated Learning (FL) allows massive clients to collaboratively train a global model without revealing their private data. Because of the participants’ not independently and identically distributed (non-IID) statistical characteristics, it will cause divergence among the client’s Deep Neural Network model weights and require more communication rounds before training can be converged. Moreover, models trained from non-IID data may also extract biased features and the rationale behind the model is still not fully analyzed and exploited. In this paper, we propose eXplainable-Fed (XFed) which is a novel client selection mechanism that takes both accuracy and explainability into account. Specifically, XFed selects participants in each round based on a small test set’s accuracy via cross-entropy loss and interpretability via XAI-accuracy. XAI-accuracy is calculated by Intersection over Union Ratio between the heat map and the truth mask to evaluate the overall rationale of accuracy. The results of our experiments show that our method has comparable accuracy to state-of-the-art methods specially designed for accuracy while increasing explainability by 14%-35% in terms of rationality.
Fuzzy based self-tuned move lengths for enhanced performance of gas source localization algorithm
Authors: Gaurav Kumar
Published: September 2023

The world has witnessed a lot of catastrophes in recent times due to chemical gas leaks. The core problem is untimely or sudden happenings of calamity for which humans are not prepared to take appropriate actions. Hence robotic gas source localization can be considered as an alternative to prevent such catastrophes. This paper presents an improved approach to an existing chemotactic plume tracing algorithm with self-tuned move length/step size. The technique uses the proposed fuzzy inference model to produce the move lengths for the next walk based on the input of gas concentration magnitude in the present state. The move lengths correspond to either the plume finding or plume tracing stage with which a mobile robot surges for the next step. Dynamic plumes under eight different simulated environments are created to evaluate the proposed approach rather than plumes in laminar flow for a more realistic case. Performance analysis of the algorithm is based on success rate with self-tuned move length compared with fixed move length. In addition, there is an analysis of step size parameters that vary concerning a particular environmental condition. Results show that adaptive step size can increase the success rate of the plume tracing algorithm and consequently improve search performance and efficiency.
Exploration on vehicle target detection technology based on wireless networks and its application in intelligent traffic
Authors: Xu Zhaosheng , Liao Zhongming , Xu Xiuhong , Ahmad Suzana , Mat Diah Norizan
Published: September 2023

In the current development of intelligent traffic in many regions, vehicle target detection has always been the focus of attention and research in the field, which can further enhance the overall performance of multiple system modules such as the security module in intelligent traffic system (ITS). This article first analyzed traditional vehicle target detection techniques, which mainly used computer vision (CV) to recognize vehicle targets on the road. However, it was often susceptible to multiple factors such as the environment, and the efficiency and universality of vehicle target detection based on CV were also low. This article also conducted research on vehicle target detection technology based on wireless networks. In this process, both cloud computing and edge computing technologies were used to further improve the efficiency of vehicle target detection based on wireless network, and reduce the use requirements of vehicle target detection. This article selected 100 images to test the accuracy of two vehicle detection technologies that do not combine wireless network technology and wireless network technology. Among the 100 sample images, 50 included vehicles and 50 did not. Through experiments, it was found that the detection accuracy of cars and trucks without wireless network technology was 79% and 84%, respectively, while the detection accuracy of cars and trucks with wireless network technology was 92% and 89%, respectively. The wireless network-based vehicle detection technology improved the real-time performance of vehicle detection on the road with the help of cloud computing and edge computing technology, and enabled the vehicle detection technology to respond quickly according to system commands. The improvement of real-time performance and the implementation of rapid response have helped vehicle target detection technology achieve better performance in intelligent traffic.
Small RNA Profiles of Brain Tissue-Derived Extracellular Vesicles in Alzheimer’s Disease
Authors: Huang Yiyao , Driedonks Tom A.P. , Cheng Lesley , Turchinovich Andrey , Pletnikova Olga , Redding-Ochoa Javier , Troncoso Juan C. , Hill Andrew F. , Mahairaki Vasiliki , Zheng Lei , Witwer Kenneth W.
Published: September 2023

Background: Extracellular vesicles (EVs) and non-coding RNAs (ncRNAs) are emerging contributors to Alzheimer’s disease (AD) pathophysiology. Differential abundance of ncRNAs carried by EVs may provide valuable insights into underlying disease mechanisms. Brain tissue-derived EVs (bdEVs) are particularly relevant, as they may offer valuable insights about the tissue of origin. However, there is limited research on diverse ncRNA species in bdEVs in AD. Objective: This study explored whether the non-coding RNA composition of EVs isolated from post-mortem brain tissue is related to AD pathogenesis. Methods: bdEVs from age-matched late-stage AD patients (n = 23) and controls (n = 10) that had been separated and characterized in our previous study were used for RNA extraction, small RNA sequencing, and qPCR verification. Results: Significant differences of non-coding RNAs between AD and controls were found, especially for miRNAs and tRNAs. AD pathology-related miRNA and tRNA differences of bdEVs partially matched expression differences in source brain tissues. AD pathology had a more prominent association than biological sex with bdEV miRNA and tRNA components in late-stage AD brains. Conclusions: Our study provides further evidence that EV non-coding RNAs from human brain tissue, including but not limited to miRNAs, may be altered and contribute to AD pathogenesis.
Peran Kepemimpinan Perempuan Dalam Sistem Ketatanegaraan Pada Pemerintahan Di Kota Metro Perspektif Siyasah Syar'iyyah
Authors: ‎    ‎ Aziza Aziz Rahmaningsih , Murdiana Elfa , Selviana Umniyatus
Published: September 2023

Perempuan menjadi isu yang sering menjadi perbincangan publik. Peran perempuan dalam kehidupan bermasyarakat bukan hanya sebagai proses pembangunan, tetapi juga sebagai fondasi berstruktur kuat,Pemimpin adalah seorang yang memimpin sebuah Wilayah. Di dalam memimpin Wilayah seorang pemimpin harus mempunyai ilmu kepemimpinan. Hasil dari Penelitian menunjukan peran kepemimpina n perempuan di Kecamata n Metro Pusat adalah memberika n pelayana n da n Kebijaka n yang bai k kepada masyarakat sesuai denga n visi-misi Kecamata n Metro Pusat terutama tentang E-service yang memberika n pelayana n secara elektroni k dala m artia n bahwa kecamata n Metro Pusat suda h dapat memberika n pelayana n yang bebas berbasis elektroni k sehingga memudahka n masyarakat untu k mendapatka n pelayana n yang cepat da n tepat yaitu sesuai dengan tujuan Siyasa h syar’iyya h yaitu kepemimpina n yang menuju pada kemaslahata n bai k dunia maupu n di akhirat.
Problematika Pengembalian Kerugian Negara Akibat Tindak Pidana Korupsi Melalui Mekanisme Perampasan Aset
Authors: Azkia Ashfa
Published: September 2023

Permasalahan tentang korupsi memang harus dibahas secara mendalam. Pelaku korupsi yang dirasa tidak jera dengan perbuatannya, menimbulkan gagasan untuk merampas aset yang dimiliiikinya untuk mengganti kerugian negara. Di Indonesia, sudah ada peraturan tentang perampasan aset, namun masih meninggalkan beberapa permasalahan yang harus segera ditanggulangi. Penelitian ini akan membahas mengenai problematika pengembalian kerugian negara akibat tindak pidana korupsi melalui mekanisme perampasan aset guna mengembalikan uang Negara yang dikorupsi. Penelitian ini merupakan penelitian normatif yang menggunakan pendekatan konseptual dan pendenkatan undang-undang. Objek penelitian ini adalah peraturan yang mengatur mengenai mekanisme perampasan aset dan teori kerugian negara dalam hukum administrasi negara. Analisis bahan bahan hukum pada penelitian ini disajikan secara kualitatif. Hasil dari penelitian ini adalah penerapan hukum yang berlaku saat ini dalam melaksanakan mekanisme perampasan aset, masih belum maksimal. Karena proses pelaksanaan perampasan aset harus menunggu putusan yang incracht, sehingga membutuhkan waktu yang lama. Hukuman bagi tidak pidana korupsi yang menyababkan kerugian negara, belum sepenuhnya fokus terhadap pengembalian kerugian negara. Ranah hukum administrasi negara, memberi gambaran bahwa dalam hal perbuatan yang mengkibatkan kerugian negara, maka hukumannya fokus terhadap pengembalian kerugian negara yang disebabkan perbuatan tersebut. RUU perampasan aset hasil tindak pidana harus segera disahkan menjadi undang-undang, sebagai jawaban dari problematika yang ada.
Information technologies for automation of hyddrophisical situation molelling and forecasting in the Black Sea region
Authors: Shyptsov Oleksandr A. , Gordeev Anton Yu. , Lebid Oleksii H. , Okhariev Viacheslav O. , Telychko Roman I. , Fedoseienkov Sergiy H. , Shundel Oleksiy I.
Published: September 2023

The article offers a solution to the scientific and applied problem of automating the acquisition and analysis of a certain set of hydrophysical indicators with the subsequent formation of a forecast of the hydrophysical situation in the Black Sea water area. This topic is of great relevance both in peacetime and in the conditions of the current armed aggression of the Russian Federation against Ukraine. The solved task is an important element of solving the more complex problem of operational obtaining of oceanographic data for highlighting the hydrographic situation in the Black Sea water area, collection, accumulation and visualization of oceanographic data in the interests of navigation and hydrographic support of users of such information. To solve this problem, a software environment was created for automatic search and selection of hydrophysical data, as well as their automatic input into specialized software for modeling and forecasting the hydrophysical situation with subsequent calculation of forecasts of hydrophysical fields. A set of the most important data was formed, which includes indicators of salinity, temperature, circulation. Automatic search and selection of meteorological and hydrophysical data takes place from international GFS and COPERNICUS profile databases. Also, to increase the effect of the simulations and forecasts, a specialized interface was developed for searching, visualization, and the possibility of downloading by the user the results of the forecast module of the mathematical modeling of the spatio-temporal variability of the hydrophysical fields of the northwestern part of the Black Sea. The developed scientific and practical approaches and toolkit are designed to function within the framework of the distributed and centralized Bank of Oceanographic Data of the National Academy of Sciences of Ukraine, part of which is an intellectual information system for highlighting the hydrographic situation in the Black Sea water area. The obtained results are also aimed at increasing the level of environmental safety in the Black Sea water area and can be used to monitor nature management in this region.
Testing a numerically-analytical method for prediction design maxima discharges of floods using plotting position formulas: the river Uzh case, the “Uzhhorod” gauging station data
Authors: Stefanyshyn Dmytro V.
Published: September 2023

There are a lot of analytical probability distributions that might be used to predict peak discharges of floods. However, there is no proper theoretical or another similar justification for choosing an appropriate parametric probability distribution to predict peak discharges of floods by using observed data. As a permissible hypothesis, any of recommended probability distributions can be considered providing it meets the given statistical criteria and other considerations for the adequacy of simulation are taken into account. In turn, more than seventeen plotting position formulas have been proposed. They provide a non-parametric means to estimate the observed data probability distribution. Using a plotting position formula, a plot of the estimated values from a theoretical parametric probability distribution can be compared with the observed data.The choice of a better plotting position formula for fitting the different probability distributions has been discussed many times in hydrology and statistical literature. However, no specific criterion for choosing these formulas has been proposed yet. Perhaps there is no need for such a criterion. Maybe, the diversity of estimates that can be obtained due to these formulas matters more. Due to the diversity of the different plotting position estimates, from the point of view of informational entropy, different plotting position formulas enable revealing epistemic (non-stochastic or subjective) uncertainty in predictions of hydrological extremes.Results of calculating empirical annual probabilities of exceedance observed maxima discharge employing various plotting position formulas show that increasing the predicting horizon toward low probable and more extreme events increases the divergence between the estimates obtained using the different plotting position formulas. Therefore, it is reasonable to assume that this divergence may be extrapolated to predict design maxima discharges of floods based on empirical estimates of plotting position probabilities.This paper proposes a numerically-analytical method using such an extrapolation. It is based on using different plotting position formulas, numerical calculations of plotting position probabilities, and extrapolation of the divergence between the obtained estimates. The method is tested in predicting the maxima discharges of 0.5% and 1% annual probability of exceedance for the Uzh River flowing in the Transcarpathia region, the hydrological station “Uzhhorod” data.
KYIV ARCHITECTURE OF THE SECOND HALF OF THE 20TH CENTURY: BIOGRAPHY OF THE ARCHITECT IN THE CONTEXT OF THE ERA (CREATIVE PATH OF ARCHITECT OLEKSANDR HORBYK)
Authors: Gorbyk Olena
Published: September 2023

The contextuality of the life and creative path of the architect's personality is emphasized in relation to the social-cultural and political-ideological conditions of the era, which are the framework of development. The political-economic, moral-worldview, and cultural changes in the society are considered and the corresponding stylistic changes in the architecture of Kyiv in the 50s-90s of the 20th century are characterized. It is shown how drastically and in connection with what the priorities in the architecture of Ukraine changed every ten years and how, in the fight against these challenges, the professional path of the generation that was born during the times of Stalinist repressions and war, grew up in the conditions of stable state-political regulation and culture of enlightenment, realized its life potential in the conditions of economic crisis and state collapse, grew old in the conditions of the new statehood, new social relations and technological transformations. The life and creative path of the Kyiv architect Oleksandr Horbyk is a revealing illustration of both realized opportunities and limitations created. The taste formed by the post-war historical center of Kyiv, the academic university education acquired at the Kyiv institute of Architecture had a limited opportunity to be realized in the practice of typical architecture - functional and combinatory in planning and constructive components. Such recreation centers in the Crimea and on the rivers and lakes of Ukraine, large-panel schools and kindergartens in Kyiv have proven the success of the architectural solution by the practice of functioning to this day. However, typical projects created certain ideological narratives of limitation and lack of freedom in the society of users, and the non-realization of creative futuristic and competitive projects belittled the creative potential of the architect. Attempts to diversify the professional path with teaching and scientific activities, artistic creativity, sports and travels, raising a dynasty of scientists were a certain compensator. The article contains data on the design practice of the Kyiv, list of scientific publications on the actual scientific topics of the second half of the 20th century.
WARM OLEKSII
Authors: Krivenko Olga , Ploskyi Vitalii
Published: September 2023

The article is devoted to the bright memory of Oleksii Leontiyovych Pidgorny. A talented artist, architect, poet, teacher, leader and, without a doubt, a world-renowned scientist. A specialist who not only created a unique scientific school, bringing geometric theories and methods to architecture and construction. Back in the seventies, he ingeniously predicted the innovative role of geometric tools in the tasks of architectural and building physics, energy efficiency and eco-architecture. Oleksiy Leontiyovych's profound kindness, warmth and humanity won over everyone who knew him. It was these features that were the basis on which our scientific father obtained his high achievements. To describe the life path of O.L. Podhorny's authors used poems and memories from his first and last author's collection of poetry and painting "Colors of Life". Poems-memoirs best illustrate the multifaceted personality and attitude to life of Oleksii Leontiyovych. They help us to once again feel the joy and warmth of communicating with him, which unfortunately remain with us now only in memory... And this memory will always be as warm as the bright spring holiday in honor of which our son was baptized scientific father.
Evaluation of the social and environmental quality of brazilian public squares
Authors: Jeveaux Passamani Amanda , Andara Ramos Larissa Leticia , Netto de Jesus Luciana Aparecida , Conde Karla Moreira
Published: September 2023

Objective: the article reflects on socio-environmental aspects that qualify the squares in the Greater Center Region, Vila Velha-ES, from the application of the tool “QualificaURB” and presents considerations on the squares with the best and worst evaluation. Methodology: the research is defined in three stages: contextualization; mapping; application of the tool and analyses. The squares were classified as “regular” in most of the evaluation criteria. Results: among the 19 squares evaluated, none obtained the best classification "excellent" and of these, one obtained the worst performance, considered "insufficient". Originality: The analyzes showed weaknesses and strengths that interfere with the quality of these spaces, and help guide proposals for urban interventions.
Uncovering the Fundamental Traits of Campus Culture in Chinese Vocational Institutions
Authors: Liu Fengcun , Li Shumei
Published: September 2023

A comprehensive understanding of the connotation and basic characteristics of campus culture in vocational colleges is a prerequisite for ensuring their sustainable development. Campus culture in vocational colleges is a concentrated reflection of their educational philosophy, ideal beliefs, and value pursuits. It possesses basic characteristics such as practicality, vocational orientation, ethics, contemporaneity, integration, and regionality.
Passing Strange: Radical Chic, Race, Sex, Song, and Dance in “Moanin’ Low”
Authors: Connolly Thomas F.
Published: September 2023

A consideration of the genesis and performance of the number “Moanin' Low" from the first _Little Show _(1929) reveals an unusually problematic blackface number. Libby Holman and Clifton Webb, two white performers, enacted the roles of African-Americans, a prostitute and a pimp, respectively. Nevertheless, the song and the accompanying dance were ground-breaking for a number of reasons. It is one of, if not, the first instance(s) of characterization achieved exclusively through dance in a revue number. The performance was considered shockingly frank and was a reflection of the ongoing fascination with the otherness of the “New Negro." It signifies a cultural mutation and is a founding text of radical chic. Nevertheless, the black-face aesthetic of this performance signifies post-colonial power that now allows the subaltern free reign overs its presumed cultural imperatives such as ballet, opera, or classical theatre, while denying itself any further hegemony over any aspect of subaltern forms. Such essentializing noblesse oblige is of course patronizing. Reverse false consciousness does not equate to true consciousness, nor does projecting an affection or even adoration for the other completely mask cultural essentialism. It is a cultural product of radical chic.
Penerapan Algoritma Advance Encryption Standard (AES) Untuk Pengamanan File Pada Aplikasi Berbasis WEB
Authors: Bibiola Fifmianti , Kalsum Toibah Umi , Alamsyah Hendri
Published: September 2023

Tujuan dari penelitian ini yaitu untuk menerapkan algoritma Advanced Encryption Standard (AES) dalam mengamankan file sehingga informasi didalamnya menjadi aman dan tidak dapat dipahami oleh sembarang orang. Penerapan Algoritma Advanced Encryption Standard (AES) dibuat menggunakan Bahasa Pemrograman PHP dan database MySQL yang dapat diakses melalui link http://fifmiantiaes.online/. Dengan adanya Aplikasi pengamanan file menggunakan algoritma Advanced Encryption Standard (AES) berbasis web dapat meningkatkan keamanan file dari pihak yang tidak berwewenang. Berdasarkan hasil pengujian yang telah dilakukan diperoleh bahwa sistem berhasil melakukan proses enkripsi dan dekripsi menggunakan Algoritma AES, dimana file dokumen tersimpan di dalam server dalam bentuk enkripsi, dan waktu proses enkripsi tergantung dari ukuran file dokumen, semakin besar ukuran file, maka semakin lama proses enkripsi yang diperlukan.
Aspek Performasi Surah Yâsîn dalam Literatur Hadis
Authors: Sawaun Sawaun
Published: September 2023

Surah Yâsîn is one of the most popular and recited among other surah of the Koran. In several communities, there is a ritual called Yâsînan. The Yâsînan ritual is a routine ritual performed by Muslim communities, both individually and in groups. The reading of Surah Yâsîn is also often done in commemorations of someone's death. This activity called a performative reception of Qur’an, especially surah Yâsîn, where qur’anic verses (Yâsîn) are accepted and used as a medium for certain rituals, regardless of its informative meaning. This article examine the performance of the surah Yâsîn which are contained ini hadith literatures, both canonical and non-canonical, that appeared up to the fifth century of the hijriah. From this research, there are several forms of performance related to surah Yâsîn. First, surah Yâsîn is recited at the death ritual. Second, surah Yâsîn also recited at certain times. Third, Surah Yâsîn is considered to be the heart of the Qur'an, so reading surah Yâsîn has a quality equivalent to reading the Qur'an several times. Fourth, surah Yâsîn is often used as a medicine for psychic ailments. And fifth, there is a recommendation for reading Yâsîn in certain prayer rituals.
Pengaruh Kondisi Operasi terhadap Karakteristik Pengeringan Jahe Merah (Zingiber officinale Var. Rubrum) Menggunakan Tray Dryer dengan Udara Panas dari Proses Pirolisis
Authors: Hasibuan Rosdanelli , Hamdanah Hasibuan  , Yovani Nissi Madani  , Viqry Pramananda  , Risma Fazillah  , Vikram Alexander
Published: September 2023

Red ginger (Zingiber officinale Var. Rubrum) is a rhizome plant often used as a complementary spice, a mixed ingredient in the food and beverages, and herbal medicines. One of the post-harvest processing of red ginger is drying, which aims to reduce the water content of red ginger to a point where the growth of microorganisms and the activity of enzymes that can damage red ginger can be prevented. This study aims to evaluate the effect of tray height and drying air temperature on moisture content, drying rate, drying characteristics, and quality of red ginger dried using a tray dryer with hot air from a biomass pyrolysis process. The results showed that both tray height and drying temperature affected red ginger's water content and drying rate. The quality of red ginger that complies with SNI 1-3393-1994 was obtained at a tray height of 60 cm and a drying temperature of 70 °C, with distinctive aroma and taste characteristics, the water content of 8,9%; ash content of 5,5%; oil content of 4,93 mL/100 g; and no fungus on the red ginger.
Pengaruh Konsentrasi Pelarut NaOH dan Waktu Aging pada Pembuatan Silika Gel dari Fly Ash Batu Bara
Authors: Batubara Fatimah , Turmuzi Muhammad , Latifah Syam Zanni , Putri Yunita Trisna
Published: September 2023

Fly ash has the potential to be used as a raw material in the production of silica gel. This study aims to characterize fly ash and silica gel, determine the effect of NaOH concentration and aging time on the manufacture of silica gel, and determine the trapping power of silica gel. In this research, the production of silica gel begins with the washing of fly ash using HCl. Next, NaOH is added with varying concentrations of 1.5 N, 2.5 N, 3.5 N, and 4.5 N. The formed Na2SiO3 is then mixed with H2SO4 of 3 N concentration, with aging times of 12 hours, 15 hours, and 18 hours. The highest yield of silica gel is 49.61% at a NaOH concentration of 4.5 N and an aging time of 15 hours. The highest water vapor adsorption capacity of the silica gel is 883.00 mg/g at a NaOH concentration of 3.5 N and an aging time of 15 hours. SEM-EDX characterization results indicate a diverse morphology and size for both fly ash and silica gel. The SiO2 content in fly ash is 41.64%, while in silica gel, it is 41.42%. FTIR characterization of fly ash and silica gel reveals the presence of functional groups such as silanol (Si-O), siloxane (Si-O-Si), and hydroxyl (Si-OH) which are active sites in silica gel.
Duygusal Kas-Güçlü Ebeveynler, Güçlü Çocuklar
Authors: Yıldırım Saadet Aybeniz , Elagöz Yüksel Mine
Published: September 2023

Duygusal Kas-Güçlü Ebeveynler, Güçlü Çocuklar
ВПЛИВ СЕКТОРАЛЬНОЇ НАСИЧЕНОСТІ ІНОЗЕМНИМИ ІНВЕСТИЦІЯМИ НА ЕКОНОМІЧНИЙ РОЗВИТОК КРАЇН-ЧЛЕНІВ ОЕСР
Authors: Грамотнєв Віталій
Published: September 2023

У статті аналізуються питання впливу іноземного капіталу, залученого до певного сектору, на розвиток економік приймаючих країн. Високий рівень геополітичної напруги у світі, одночасна криза на ринку енергоносіїв та продовольства, волатильність світових цін на решту біржових товарів, висока ймовірність «охолодження» економіки світу та наслідки війни в Україні формують передумови для істотного зниження міжнародних потоків іноземних інвестицій. Через посилення конкуренції за них між державами світу зростає актуальність проблеми визначення тих секторів економіки приймаючої країни, функціонування в яких іноземного капіталу дає найбільший, порівняно з іншими секторами, імпульс розвитку всій національній економіці. Особливу гостроту це питання матиме для Української держави на етапі її повоєнного відновлення, беручи до уваги негативний вплив істотних масштабів руйнувань та безпекових ризиків на інвестиційну привабливість нашої країни. Виходячи з цього, в якості завдання дослідження було обрано проведення кількісної оцінки впливу насиченості секторів іноземними інвестиціями на економіку країн, рівень розвитку яких може слугувати для України орієнтиром в процесі післявоєнної відбудови. Для цього за допомогою загальнонаукових методів та статистичного аналізу досліджено щільність зв’язку між згаданими економічними явищами в країнах-членах ОЕСР. Отримані результати дозволили диференціювати сектори за силою впливу вкладеного у них іноземного капіталу на економічну активність приймаючої країни. Це дало змогу виокремити групи секторів, іноземні інвестицій в яких мають вагомий, помірний або слабко виражений ефект для зростання національних економік. Досвід функціонування іноземного капіталу в економіках країн-членів ОЕСР свідчить, що найбільший вплив на активність економічного розвитку приймаючої країни має залучення згаданого капіталу до сфери послуг, фінансів, а також у науково-дослідну діяльність. Наступною у цьому рейтингу за силою стимулюючого впливу є група секторів, що складається з IT, переробної промисловості, транспорту й торгівлі. Найменшим або малопомітним для економічного розвитку країн-членів ОЕСР виявився ефект діяльності іноземних інвесторів у секторах добувної промисловості, готельному й ресторанному бізнесі, секторах нерухомості та енергопостачання вищезгаданих країн.
ОСОБЛИВОСТІ ФІНАНСУВАННЯ ІННОВАЦІЙНИХ ПРОЕКТІВ МІЖНАРОДНОЇ ТЕХНІЧНОЇ СПІВПРАЦІ
Authors: Гнилянська Леся , Кісь Марʼяна , Білоус Юрій
Published: September 2023

Стаття присвячена актуальним питанням фінансування інноваційних проектів міжнародної технічної співпраці. Коли людина вирішує розпочати власний бізнес чи розширити вже існуючий, то однією з головних проблем стає капітал для втілення цієї ідеї. В цьому випадку на допомогу можуть прийти власні (збереження, нерозподілений прибуток), залучені (акціонування, розширення статутного фонду) або позичкові кошти (різні види кредитів, випуск облігацій тощо). Важливим при цьому є прийняти таке рішення щодо залучення коштів, яке буде найбільш ефективним, щоб структура джерел фінансування була якнайкраща. В статті визначено сутність та значення понять « фінансування» та «міжнародна технічна співпраця». Розглянуто особливості міжнародної технічної співпраці України. Визначено суть міжнародної технічної співпраці та фінансування інноваційних проектів. Вивчено сферу фінансування інноваційних проектів ТОВ «Окко-Драйв АЗС». Та розроблено рекомендації щодо здійснення фінансування інноваційних проектів ТОВ «Окко-Драйв» АЗС» в умовах міжнародної технічної співпраці.