Reviewerly/exHarmony huggingface dataset:
Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation

Referring video object segmentation aims to predict foreground labels for objects referred by natural language expressions in videos. Previous methods either depend on 3D ConvNets or incorporate additional 2D ConvNets as encoders to extract mixed spatial-temporal features. However, these methods suffer from spatial misalignment or false distractors due to delayed and implicit spatial-temporal interaction occurring in the decoding phase. To tackle these limitations, we propose a Language-Bridged Duplex Transfer (LBDT) module which utilizes language as an intermediary bridge to accomplish explicit and adaptive spatial-temporal interaction earlier in the encoding phase. Concretely, cross-modal attention is performed among the temporal encoder, referring words and the spatial encoder to aggregate and transfer language-relevant motion and appearance information. In addition, we also propose a Bilateral Channel Activation (BCA) module in the decoding phase for further denoising and highlighting the spatial-temporal consistent features via channel-wise activation. Extensive experiments show our method achieves new state-of-the-art performances on four popular benchmarks with 6.8% and 6.9% absolute AP gains on A2D Sentences and J-HMDB Sentences respectively, while consuming around 7x less computational overhead.
THE BRAILLE SYSTEM: THE WRITING AND READING SYSTEM THAT BRINGS INDEPENDENCE TO THE BLIND PERSON

The braille System is the most adopted writing and reading process in relief worldwide and includes the writing of the alphabet and of mathematical, chemical, phonetic, computer, and musical symbols. This text aims to explain what the braille System is and its importance for the independence of the blind person. In addition to demonstrating the appropriate distance between the points and proving that writing on the conventional slate is the best resource for correct writing in braille, the main objective of the research is to emphasize the importance of using the braille System and to value the conventional slate as a braille writing instrument. From the reading of theoretical texts and writings performed using both slates, the result is even more evident that writing on the conventional slate meets the tactile reading of the blind person, who uses the pad of the index finger to feel the braille dots.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0941/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
ZTA: Never Trust, Always Verify

Zero Trust Architecture (ZTA) deployments are growing in popularity, widely viewed as a solution to historical enterprise security monitoring that typically finds attackers months after they have gained system access. ZTA design incorporates multiple industry security advisories, including assuming network compromise, using robust identity management, encrypting all traffic, thwarting lateral movement, and other security best practices. Collectively, these features are designed to detect and prevent attackers from successfully persisting in the environment. These features each offer solutions to various ongoing security problems but individually are not comprehensive solutions. When designed for cloud services ZTA holds the promise of outsourcing security monitoring. However, some observations about ZTA suggest that the component solutions themselves have flaws potentially exposing systems to additional undetected vulnerabilities, providing a false sense of security. This paper addresses vulnerable paths using a bottom-to-top approach, listing problem areas and mapping them to attacker goals of deny, deceive, disrupt, deter, and destroy. The paper then addresses residual risk in the architecture. Based on the findings the paper suggests realistic countermeasures, offering insights into additional detection and mitigation techniques.
A Protection Layer over MapReduce Framework for Big Data Privacy

In many organizations, big data analytics has become a trend in gathering valuable data insights. The framework MapReduce, which is generally used for this purpose, has been accepted by most organizations for its exceptional characteristics. However, because of the availability of significant processing resources, dispersed privacy-sensitive details can be collected quickly, increasing the widespread privacy concerns. This article reviews some of the existing research articles on the MapReduce framework's privacy issues and proposes an additional layer of privacy protection over the adopted framework. The data is split into bits and processed in the clouds, and two other steps are taken. Hadoop splits the file into bits of a smaller scale. The task tracker then allocates these bits to several mappers. First, the data is split up into key-value pairs, and the intermediate data sets are generated. The efficiency of the suggested approach may then be effectively interpreted. Overall, the proposed method provides improved scalability. The following figures compare execution time with relation to file size and the number of partitions. As privacy protection technique is used, the loss of data content can be appropriately handled. It has been demonstrated that MRPL outperforms current methods in terms of CPU optimization, memory usage, and reduced information loss. Research reveals that the suggested strategy creates significant advantages for Big Data by enhancing privacy and protection. MRPL can considerably solve the privacy issues in Big Data.
Menggali Narasi, Melestarikan Tradisi: Warisan Konsep Water Preservation Pada Makam Sunan Muria

This study examines the legacy of Sunan Muria's thoughts on conserving water sourced from the sign and symbol around the graves The existence of water plays an important role in the religious studies. Islam, Christianity, Judaism, Hinduism and Buddhism use water as an important component in every religious ritual. Therefore, one of the contemporary issues in Islamic studies that has attracted the attention of scholars is water conservation. Based on initial observations, researchers found a water jar that is sacred by the local community. Social, religious, and cultural narratives about sacred concepts are the main points of this research. In addition, based on extensive field research, various interviews and literature studies on related topics, the researcher explores the complexity of the heritage of water conservation thought in Sunan Muria's perspective through the identification of signs and symbols on their tombs from the concepts of eco-theology; bi'ah al-hudry.
Practice-Oriented Approaches in Professional Orientation of Schoolchildren

A number of state documents in the field of education emphasize the importance of organizing an effective system of career guidance for students. The relevance of this work is due to several reasons, one of which is the strengthening of the dynamics of the labor market and the market of professions. Today, futurologists find it difficult to say which of the professions will be in demand in the future. Today's students should have a clear understanding of what the expression "lifelong education" means and be ready to change their profession.&#x0D; One of the modern approaches to creating an effective career guidance system is the actual approach, that is, the orientation of the student to the choice of a profession for the "here and now", but at the same time, teachers should warn about a possible reorientation. All this determines the acuteness of the problem of pedagogical support of professional self-determination of students.&#x0D; In addition, it is quite obvious that the socio-economic development of the country depends on the correct choice of a profession by school graduates, since this choice determines the motivation to receive a quality professional education.&#x0D; The authors of the article believe that for effective career guidance, an educational organization should use all resources (resource approach), in particular, the resources of additional education.&#x0D; The authors' material may be useful for teachers working on the creation of a career guidance system based on modern practice-oriented approaches.
STIP: A SpatioTemporal Information-Preserving and Perception-Augmented Model for High-Resolution Video Prediction

Although significant achievements have been achieved by recurrent neural network (RNN) based video prediction methods, their performance in datasets with high resolutions is still far from satisfactory because of the information loss problem and the perception-insensitive mean square error (MSE) based loss functions. In this paper, we propose a Spatiotemporal Information-Preserving and Perception-Augmented Model (STIP) to solve the above two problems. To solve the information loss problem, the proposed model aims to preserve the spatiotemporal information for videos during the feature extraction and the state transitions, respectively. Firstly, a Multi-Grained Spatiotemporal Auto-Encoder (MGST-AE) is designed based on the X-Net structure. The proposed MGST-AE can help the decoders recall multi-grained information from the encoders in both the temporal and spatial domains. In this way, more spatiotemporal information can be preserved during the feature extraction for high-resolution videos. Secondly, a Spatiotemporal Gated Recurrent Unit (STGRU) is designed based on the standard Gated Recurrent Unit (GRU) structure, which can efficiently preserve spatiotemporal information during the state transitions. The proposed STGRU can achieve more satisfactory performance with a much lower computation load compared with the popular Long Short-Term (LSTM) based predictive memories. Furthermore, to improve the traditional MSE loss functions, a Learned Perceptual Loss (LP-loss) is further designed based on the Generative Adversarial Networks (GANs), which can help obtain a satisfactory trade-off between the objective quality and the perceptual quality. Experimental results show that the proposed STIP can predict videos with more satisfactory visual quality compared with a variety of state-of-the-art methods. Source code has been available at \url{https://github.com/ZhengChang467/STIPHR}.
Comprehension Strategies: Its Influence on the Applied Reading Skills of Grade 11 students of San Bartolome Integrated High School

This study aimed to determine the Influence of Comprehension Monitoring Strategies on the Applied Reading Skills among Grade 11 students of San Bartolome Integrated High School S.Y. 2021-2022.Specifically, it sought to answers the following questions: (1) .What is the level of Comprehension Strategies of the respondents in terms of; Visualizing, Self-Questioning, and Drawing Conclusions (2) What is the level of Reading Skills of the respondents in terms of; Generalizing, Comparing, Recommending and Suggesting, Decision-Making and Create Alternative Endings and Is there a significant difference in the respondents' pre-test and post-test scores after being exposed to their comprehension strategies?The experimental design was used in the study to determine the comprehension monitoring strategies on the Applied Reading Skills of Grade 11 students of San Bartolome Integrated High School.The questionnaire via google form was used in garnering data.The statistical treatment used was average score or mean.The T-test formula was used to determine the Influence of Comprehension Monitoring Strategies on the Applied Reading Skills of Grade 11 students of San Bartolome Integrated High School S.Y. 2021-2022.The following are significant findings of the study: The pretest scores on the Applied reading Skills indicate that the respondents already fared well in Generalizing.Respondents exhibited a fairly satisfactory score in Comparing, Recommending and Suggesting, Decision-Making, and Creating Alternative Endings.The respondents showed 142 www.ijrp.org
Persons facial image synthesis from audio with Generative Adversarial Networks

This paper proposes to build a framework with Generative Adversarial Network (GANs) to synthesize a person's facial image from audio input. Image and speech are the two main sources of information exchange between two entities. In some data intensive applications, a large amount of audio has to be translated into an understandable image format, with automated system, without human interference. This paper provides an end-to-end model for intelligible image reconstruction from an audio signal. The model uses a GAN architecture, which generates image features using audio waveforms for image synthesis. The model was created to produce facial images from audio of individual identities of a synthesized image of the speakers, based on the training dataset. The images of labelled persons are generated using excitation signals and the method obtained results with an accuracy of 96.88% for ungrouped data and 93.91% for grouped data.
ENSURING CONSUMER SATISFACTION WITH CHATBOTS IN THE BALTIC STATES

Within the framework of this work, the authors want to study the theoretical foundations of consumer satis-faction, to understand the peculiarities of consumer satisfaction using chatbots. The artificial intelligence and its use is an integral part of modern business development, enabling companies to operate successfully in a competitive environ-ment. This study identifies factors that influence consumer satisfaction with the use of chatbots to enable businesses to improve their use and become more competitive. The study uses both secondary data analysis and expert interviews, as well as a survey of chatbot users. The study describes the situation in the field of the use of chatbots in the Baltic States. The study finds that personalized chatbots provide a higher level of consumer satisfaction. In order to achieve the goal of the research, three tasks were set: 1) to analyze the theoretical basis of consumer satisfaction and the introduction of chatbots; 2) describe the use of chatbots and their contribution to consumer satisfaction; 3) Explore user satisfaction with chatbots. A monographic or descriptive method was used to analyse the theoretical aspects of chatbots and their use, secondary data analysis and expert interviews were used to describe the situation, but user survey was conducted to study consumer attitudes using chatbots.
Discrete State-Action Abstraction via the Successor Representation

While the difficulty of reinforcement learning problems is typically related to the complexity of their state spaces, Abstraction proposes that solutions often lie in simpler underlying latent spaces. Prior works have focused on learning either a continuous or dense abstraction, or require a human to provide one. Information-dense representations capture features irrelevant for solving tasks, and continuous spaces can struggle to represent discrete objects. In this work we automatically learn a sparse discrete abstraction of the underlying environment. We do so using a simple end-to-end trainable model based on the successor representation and max-entropy regularization. We describe an algorithm to apply our model, named Discrete State-Action Abstraction (DSAA), which computes an action abstraction in the form of temporally extended actions, i.e., Options, to transition between discrete abstract states. Empirically, we demonstrate the effects of different exploration schemes on our resulting abstraction, and show that it is efficient for solving downstream tasks.
The Effect Of Using Jakarta Post Headlines And Sub Headlines as Teaching Media Towards The Students Vocabulary Mastery

This research is about the effect of using Jakarta post headlines as teaching mediatowards the students’ vocabulary mastery. The objective of the study is to find outwhether Jakarta post headlines and sub headlines affects students’ vocabulary mastery.This study was conducted by applying experimental quantitative research. The subject ofthe study was the second year students of SMP N.17 Medan. The researcher took VIII-4which consists of 30 students as experimental group using Jakarta post headlines and subheadlines media and VIII-1 which consists of 30 students as control group usedconventional method or without Jakarta post headlines and sub headlines. The populationof this research was 60 students which consist of two parallel classes. The researcher tookboth groups as total sampling to see the effect of using Jakarta post headlines and subheadlines as teaching media towards the students’ vocabulary mastery. The data weretaken by giving vocabulary test which consists of word completion and matching. Thetests were divided into two tests: pre-test and post-test for both experimental and controlgroup. The mean score of pre-test in experimental group is 53.73 and the post-test is79.86. The mean score of pre-test in control group is 43.86 and the post test is 58.667. Itis concluded that the mean score of experimental group is higher than control group. Theresult that t-calculated &gt; t-table at the level of significance p = 0.01 (3.095&gt;2.660). Thealternative hypothesis (Ha) is accepted and null hypothesis (Ho) is rejected. It means thatJakarta post headlines and sub headlines can be used as teaching media as alternative toenrich students’ vocabulary mastery at the second year students of Junior High School.key words: Jakarta post headlines and sub headlines, Vocabulary
THE GAIT OF THE FORUM LINGKAR PENA (FLP) IN REALIZING READING AND WRITING LITERACY IN THE SOUTH SUMATRA REGION

In the South Sumatra region, one of the organizations whose members are active in writing is Forum Lingkar Pena Â (FLP). It is interesting to research so that the work carried out by FLP can be an example for other literacy groups. The method used in this research is a descriptive qualitative method using a field research approach. Techiques of collecting data use observation instruments,interview and documentary. The results of this study indicate that in realizing literacy in literacy, FLP holds coaching classes specifically carried out by regions as well as by branches with various creative ideas. This routine activity presents competent writers through seminars, trainings and webinars. The use of print and electronic media to monitor members' works is also carried out. The factors that support the success of realizing literacy in literacy are because there are members who already have literacy skills before becoming members and there are also members who really make literacy a part of their life. Meanwhile, the inhibiting factors are the difficulty in coordinating with the board and members if the contact number is lost and the lack of priority for members to write.
Transformer-based Personalized Attention Mechanism for Medical Images with Clinical Records

In medical image diagnosis, identifying the attention region, i.e., the region of interest for which the diagnosis is made, is an important task. Various methods have been developed to automatically identify target regions from given medical images. However, in actual medical practice, the diagnosis is made based not only on the images but also on a variety of clinical records. This means that pathologists examine medical images with some prior knowledge of the patients and that the attention regions may change depending on the clinical records. In this study, we propose a method called the Personalized Attention Mechanism (PersAM), by which the attention regions in medical images are adaptively changed according to the clinical records. The primary idea of the PersAM method is to encode the relationships between the medical images and clinical records using a variant of Transformer architecture. To demonstrate the effectiveness of the PersAM method, we applied it to a large-scale digital pathology problem of identifying the subtypes of 842 malignant lymphoma patients based on their gigapixel whole slide images and clinical records.
Unitary Evolutions Sourced By Interacting Quantum Memories: Closed Quantum Systems Directing Themselves Using Their State Histories

We propose, formulate and examine novel quantum systems and behavioral phases in which momentary choices of the system's memories interact in order to source the internal interactions and unitary time evolutions of the system. In a closed system of the kind, the unitary evolution operator is updated, moment by moment, by being remade out of the system's `experience', that is, its quantum state history. The `Quantum Memory Made' Hamiltonians (QMM-Hs) which generate these unitary evolutions are Hermitian nonlocal-in-time operators composed of arbitrarily-chosen past-until-present density operators of the closed system or its arbitrary subsystems. The time evolutions of the kind are described by novel nonlocal nonlinear von Neumann and Schrödinger equations. We establish that nontrivial Purely-QMM unitary evolutions are `Robustly Non-Markovian', meaning that the maximum temporal distances between the chosen quantum memories must exceed finite lower bounds which are set by the interaction couplings. After general formulation and considerations, we focus on the sufficiently-involved task of obtaining and classifying behavioral phases of one-qubit pure-state evolutions generated by first-to-third order polynomial QMM-Hs made out of one, two and three quantum memories. The behavioral attractors resulted from QMM-Hs are characterized and classified using QMM two-point-function observables as the natural probes, upon combining analytical methods with extensive numerical analyses. The QMM phase diagrams are shown to be outstandingly rich, having diverse classes of unprecedented unitary evolutions with physically remarkable behaviors. Moreover, we show that QMM interactions cause novel purely-internal dynamical phase transitions. Finally, we suggest independent fundamental and applied domains where the proposed `Experience Centric' Unitary Evolutions can be applied natuarlly and advantageously.
Analisis Performansi Dua Sistem Operasi Server CentOS 8 dan Oracle Linux 8 Menggunakan Metode Levene Dengan SysBench

&#x0D; CentOS 8 is a popular operating system for servers, but will discontinue. The Oracle Linux 8 operating system was chosen as a replacement because this operating system has many similarities with CentOS 8 and is distributed by the same party, namely RHEL (Red Hat Enterprise Linux). This study aims to compare the stability of the two server operating systems, as well as provide a reference for operating system users to choose a server operating system. CPU and memory tests were performed using SysBench software with the same number of threads, which were then recorded and compared. Cacti software is also used to compare CPU and memory performance in real time. The results showed that Oracle Linux 8 and CentOS 8 are two operating systems with different variances, although the kernels used by both operating systems are the same. Oracle Linux 8 can serve clients faster than CentOS 8 with a difference of 0.26 seconds.&#x0D;
Problems оf Improving the Quality оf Educational Services in The Republic of North Macedonia

Given the rapid pace of developments during and after the coronavirus, changes in the education system are inevitable. The fact that R.N.Macedonia has been regressing over decades requires a radical change in the education system. This article presents the results of a survey at the state level, as well as an overview of an interview with a professor of higher education in Macedonia. Also, if we consider the problem from several sides, we come to the conclusion that there are a lot of shortcomings.