Reviewerly/exHarmony huggingface dataset:
التأثيرات السياسية في استدامة الدين العام في موازنة العراق 2019

This study clarifies the analysis of the reality of the financial policy in the budget of Iraq 2019, and that analysis is evaluated by tracking the elements of the public budget from public expenditures and public revenues, and the study focuses on the size of the political impact on the path of public spending, as well as the analysis of public spending and revenues in various sectors and sections of the public budget. This study also shows the size of the risks resulting from the continuation of the financial deficit, as well as the risks of public debt according to the indicators of its sustainability analysis within the financial and economic indicators that express the risks of public debt. The study emphasized that public spending is still based on the political decision and does not achieve the principles and objectives of the economic budget that achieve the public benefit. The necessity requires efficient spending and fair distribution in order to avoid future public debt risks and their impact on future generations
LibGuides: Website Feedback: Home

The libraries have a new website. Tell us what you think, sign up for usability testing, submit your questions, report bugs, and describe missing information .
Searching for the Cat: Effects of Variable Spatial Association between Objects and Scenes

Sometimes objects are not where you expect them, but sometimes objects can be found where ever: think of a cat. In the current study, we investigated the effects of the variability of spatial associations between objects and scenes. Based on the Surface Guidance Framework, during search attention is deployed to relevant scene surfaces at a specific vertical position in the scene (i.e., upper, middle and lower surfaces; Pereira & Castelhano, 2019). However, as strength of the spatial associations between objects and scene are variable, the focus of attentional deployment may vary with it. In the current study, we examined the effect of the expected spatial variability of target objects on search performance. For each trial, participants’ eye movements were tracked while they searched for one of two types of target objects: (1) Fixed Targets, which were associated with a specific surface (animal head mount, flower vase, boots); (2) Variable Targets, which were not associated with a specific region (fan, basket, cat). Results showed not only a slower reaction time for variable than fixed targets, but also an interesting pattern across eye movement measures. Attentional guidance measures showed longer times and many more fixations to get to variable than fixed targets. Interestingly, differences were not immediately apparent as the direction of the first saccade and fixations to the relevant scene region did not differ. When looking at the pattern of fixations over the course of the trial, the differences were apparent during the latter half of the search trial. This suggests that the influence of spatial expectations for variable vs. fixed targets on attentional deployment may not be immediate. We will further explore the deployment of attention over the course of the trial to address these differences in strategy implementation.
최근 40년간(1980-2019) 중국에서 텍스트 언어학의 연구 현황과 연구 동향

The purpose of this paper is to see how text linguistic theories can be applied in the analysis and interpretation of texts, by surveying how the concept and theories of text linguistics have been applied in the field of Chinese linguistics and its adjacent academic fields.There are three levels of text linguistics which have been studied in China for 40 years. The first step was the introduction of text linguistics in the 1980s. Text linguistics was introduced to China during this period, and has been studied mainlyintranslationandtheoryintroduction.Th esecondstage was the growth of text linguistics in the 1990s, and as the theory and system of text linguistics were organized in China, which developed its own research result that targeted Chinese text. The third stage was the study’s maturity of text linguistics in the 2000s, varying methods and perspectives on how to study text. Through these steps, I will describe the trend that has developed into the study of text linguistics in China.
Game Edukasi Pengenalan Rumah dan Pakaian Adat Untuk Anak Sekolah Dasar Berbasis Android

Inactivity of students in participating in learning is a classic problem in schools.Based on observations and interviews conducted at SD Muhammadiyah 16Surakarta, teaching teachers still use traditional methods in delivering material.The purpose of this study is to provide a new interactive learning media for theintroduction of traditional Indonesian homes and clothing, with material packagedin the form of an android-based educational game. The method used in thisresearch is Research and Development (R&D) using the ADDIE developmentmodel (Analysis, Design, Development, Implementation, Evaluation). As well aspaying attention to the assessment of media experts and material experts, thesubjects of this study were students of class IV-1 SD Muhammadiyah 16 Surakarta.From the research results, material experts with 96.52% results with Very decentquality, media experts with 97.65% results with Very decent quality, and UserTest with 89.21% results with Very decent quality . And the results shown fromthe pre-test and post-test get an increase of 14.70%.
Intra-Camera Supervised Person Re-ID by Tracklet Level Classifier

In this work, we propose a novel method to perform intra-camera supervised person re-ID by Tracklet Level Classifier (TLC). The key idea of our method is to train classifiers for every intra-camera ID, which is tracklet level, compared with camera level of previous works. By training tracklet level classifiers, we make the backbone learned to extract intra-camera invariant representations. With the fine-trained classifiers, we mine and exploit latent inter-camera ID matching pairs easily. Previous works needs two stages and relies on complicated rules to match inter-camera pairs while we simplify the training strategy to only one stage and do not need a complex design to match tracklet over cameras. Extensive experiments and ablation studies on three large re-ID datasets show that our simple and effective TLC method achieve state-of-the-art among all the intra-camera supervised person re-ID methods.
Semantic Entity Enrichment by Leveraging Multilingual Descriptions for Link Prediction.

Most Knowledge Graphs (KGs) contain textual descriptions of entities in various natural languages. These descriptions of entities provide valuable information that may not be explicitly represented in the structured part of the KG. Based on this fact, some link prediction methods which make use of the information presented in the textual descriptions of entities have been proposed to learn representations of (monolingual) KGs. However, these methods use entity descriptions in only one language and ignore the fact that descriptions given in different languages may provide complementary information and thereby also additional semantics. In this position paper, the problem of effectively leveraging multilingual entity descriptions for the purpose of link prediction in KGs will be discussed along with potential solutions to the problem.
Spoken Moments: A Large Scale Dataset of Audio Descriptions of Dynamic Events in Video

When people observe events they are able to abstract key information and build concise summaries of what is happening. These summaries include contextual and semantic information describing the important high-level details (what, where, who and how) of the obseved event and exclude background information that is deemed unimportant to the observer. With this in mind, the descriptions people generate for videos of different dynamic events can greatly improve our understanding of the key information of interest in each video. They provide expanded attributes for video labeling (e.g. actions/objects/scenes/sentiment/etc.) while allowing us to gain new insight into what people find important or necessary to summarize specific events. In this vein, we present a new dataset of audio descriptions collected for a set of 500K different short videos depicting a broad range of different events. We collect our descriptions using audio recordings to ensure that they remain as natural and concise as possible and provide verified text transcriptions of each recording. We additionally present a multi-modal audio-visual model for jointly learning a shared representation between the video and the audio descriptions and show how this learned representation can be applied to a number of different tasks in video understanding.
Ensuring Better Privacy of Cloud Storage Using Elliptic Curve Cryptography

Cloud technology is very profitable for the business evolution. In cloud computing, the data is mostly outsourced. The security and integrity of the data in the cloud system is always a main worry. Because of rapid development of adaptable cloud services, it becomes increasingly vulnerable to use cloud services to share data in a friend circle in the environment of cloud computing. The user privacy is also an important concern. Many systems and technique are being developed to address these issues, but still there is always a scope of improvement. While addressing the issues related to the user privacy and data security and integrity, we must consider the efficiency of the system while accessing and searching for the data. In this paper, we discuss about the major challenges in cloud environment. Also, presented is a brief overview on proposed system with elliptical curve cryptography is a public key encryption technique uses the properties of elliptic curve in order to generate keys instead of using the traditional methodology of generation of keys.
Cinema Sound: Characteristics and 3D Acoustic Measurements

Abstract In 2014, an SMPTE report stated that sound consistency between dubbing stages and performance venues was not respected. SMPTE technical commission studied this issue in 3 commercial cinemas and 3 dubbing stages in Hollywood using the impulse response method. This lack in sound consistency is probably imputable to the use of a wrong calibration system (RTA + Pink Noise Method) that is time-blind and does not mimic the perceptual listening of the human being. A campaign of measurements has been conducted in Rome to test the acoustic properties of a dubbing stage room and a cinema performance room. Two measurement systems were implemented: One for the extraction of ISO 3382 parameters (Omni, Binaural, Soundfield) and one for studying the spatial distribution of sound in the room (Eigenmike TM ).
Discover the Library of Congress: An Evaluation About Digital Collection

In contemporary knowledge-based society the novel developments mainly triggered by the advancement in information and communication technologies, intensely influenced the way of accessing, preserving, conserving and information, and thereby paved innovative way of archiving information resources through digital platform. In this milieu, current study attempts to analyse the collection archived by Library of Congress to highlight its varied features based on chosen parameters. The analysis evidently divulges that Library of Congress attempts to archive a wide variety of information resources ranging from Books collection to Software/E-resource covering wide range of time-periods. Moreover, items in library of Congress covers wide range of subjects which vary from one collection format to another, indicating that each collection format has its unique range of subjects. However, the geographical distribution of collection reveals that United States emerges as predominant location with English as most preferred language. In view of the fact, it appears that the Library of Congress has emerged as prospective digital platform, which ensures access to information for present as well as future generations by offering access to wide variety of collection through integration of technological advancements.
Perceptual and conceptual representations of objects in the human brain

Previous research reported high-level object representations in the visual ventral stream (VS) at the interface between perception and semantics, reflecting behavioural similarity judgements. Here we used representational similarity analysis (RSA) to investigate object recognition (36 objects including bodies, faces, objects and scenes) comparing three behavioural tasks with functional magnetic resonance imaging (fMRI, 3T, n=20) and electroencephalography (EEG, 128 channels, n=20). In an attempt to capture implicit similarity representations, we used a novel discriminability task. As a measure of explicit similarities, we collected behavioural judgments using the multiple-arrangements (MA) task. Finally, to capture semantic representations, we obtained human-derived caption labels. We predicted that implicit similarity judgements would better capture perceptual representations, while explicit and semantic judgments would extend to higher-level, semantic or conceptual brain processes. Representational dissimilarity matrices (RDMs) were estimated using drift-rates for the discriminability task, using pixel euclidean distances for the multi-arrangements task, and using sentence embeddings of the human captions for the semantic labelling task (Figure 1A). We relate these behavioural RDMs to time-resolved RDMs (EEG, Figure 1B) and searchlight-defined RDMs (fMRI, all statistics are reported with p<0.001 corr., Figure 1C). The EEG-RDMs showed large and early peak correlations with the discriminability task, and weaker correlations for the semantic and multi-arrangement tasks (later in time). In fMRI, we see all three behavioural tasks strongly mapping (t values reaching 48.9) on the visual ventral stream (strongest for the discriminability task). The multi-arrangement and semantic tasks additionally involved higher-order regions of the medial temporal lobes and prefrontal cortices. Our results suggest that implicit similarity judgements better capture representational geometries in visual cortex but fail to predict higher-order representations. In contrast, multi-arrangements and semantic judgements account for higher-level representations. Therefore, we propose that accounting for behaviourally relevant information processes in the brain should rely on a battery of behavioural metrics.
Feature-based attention induces location transfer in perceptual learning

[Goal] Perceptual learning (PL), experience-induced improvement in perception, is typically highly specific to the trained location and feature. However, location specificity can be alleviated by particular training protocols. Manipulating exogenous (Donovan, Szpiro & Carrasco, 2015) or endogenous (Donovan & Carrasco, 2018) spatial attention during training facilitates learning transfer more efficiently than other protocols that require a secondary training task. Here we investigated whether feature-based attention (FBA), which enhances the representation of particular features throughout the visual field, facilitates location and/or feature transfer in PL. [Methods] To investigate the effects of FBA on specificity in PL, we implemented an orientation discrimination task in which observers were first presented with two reference angles simultaneously, then asked to discriminate whether the orientation of a Gabor stimulus was clockwise or counter-clockwise to either reference. In Experiment 1, we confirmed that FBA improved accuracy in this task. In Experiment 2, two groups of observers participated in a six-day PL study; the Attention group trained with a feature attention cue, indicating on a trial-by-trial basis which of the two reference angles was relevant for the discrimination, and the Neutral group trained with a neutral cue, indicating both reference angles. Observers were presented with neutral cues during both the pre-test (before training) and post-test (after training) sessions. [Results] For both groups of observers, performance improved for the trained feature at the trained location. Notably, training with FBA enabled complete learning transfer to the untrained location, but not to the untrained orientation. In contrast, the Neutral group exhibited both location and orientation specificity. [Conclusion] Our results show a perceptual benefit of FBA in an orientation discrimination task, and reveal a remarkable spatial-transfer of learning induced by FBA, reminiscent of its global effect across the visual field. This study has possible translational implications for perceptual training in visual rehabilitation.
Identification and Prioritization of Factors Contributing in Cloud Service Selection Using Fuzzy Best-worst Method (FBWM)

The introduction of cloud computing techniques revolutionized the current of information processing and storing. Cloud computing as a competitive edge provides easy and automated access to the vast ocean of resources through standard network mechanisms to businesses and organizations. Due to the vast diversity of service providers and their respective variety of available services with different qualities, top managements often face difficulty for choosing the best available option. So, considering the growing significance of the mentioned issue, this study aims to identify and rank contributing factors in selection of cloud service providers. In that attempt, this research approaches its goal by going through three major phases. Firstly, in phase one, prior studies are reviewed for extracting related elements of selection. Secondly, by employing Fuzzy Delphi method and obtaining results by interviewing experts in this field such as IT managers and technicians, this study tries to finalize the list of contributing factors. Lastly, by utilizing Fuzzy best-worst multi-criteria decision-making method, which is one of the most recent techniques employed to statistically rank variables, this research introduces a list of vital factors for cloud service selection. Based on the findings of this study, there are five major categories involved in the selection process which are: performance, security, data management, personal data protection and environmental-organizational. The finalized result of ranking shows that, performance related factors such as accessibility, response time and capacity are the first priority. The runner-up is security with reliability and governance. Environmental-organizational variables lands in the third place by considering rental and network costs.
MACHINE LEARNING TECHNIQUES AND THEIR PROBLEM-SPECIFIC DOMAINBASEDEXCELLENCE

Current is an era of data analysis. The data is growing rapidly this time due to more followers ofdigitization. Such type of data dependency also needs predictions from informed data. Set of trained algorithms are alsorequired which may generate decision making results. Nowadays, researchers are trying to make the machinesintelligent. To accomplish it, Machine Learning (ML) is the suitable study stream. The objective of this paper is todiscuss various ML approaches and their issues under one umbrella. The algorithms describe about the variousbranches of advanced computer science in which ML can be applied and thus implemented. Domain-basedcategorization has also been done as it is always a big question as to which algorithm must be selected to deal with aparticular problem. Real life applications need predictions which accelerates any process like business planning forinvestment, recommendation systems, medical diagnosis, speech recognition, etc.
Production Results Forecasting Using Linier Regression Methods In UMKM KWT Suka Maju

Kelompok Wanita Tani (KWT) SUKAMAJU is a women's association in Palihan village, Bambanglipuro sub-district. The KWT activities include monthly social gatherings, savings, and loans, gardening by growing vegetables and family medicinal plants in the KWT Sukamaju garden, regular monthly meetings for agricultural extension agents, and food production. The community service team assists in the form of increasing production by supporting production equipment which is considered to be still long for large quantities of products and multimedia and internet-based marketing as a means of establishing marketing communications for the group of craftsmen for processing banana tree food made by KWT Sukamaju. Amid the physical distancing period of the Covid-19 pandemic, community visits to the field as the only marketing communication channel must stop. The use of internet marketing means to spur production to be fast and in large numbers. The difficulty of producing such large quantities is constrained by the tools and the processing time that must be fast due to a large number of orders from the internet.  Data retrieval is taken from the use of production equipment for 30 days. Every day with an intensity of 3 times every 3 until 4 hours for 6 months. The total sample is 180 data samples every three times to 540 data.  The test using linear regression before and after adding equipment for the production of KWT UMKM has an average result of 56.54% of the estimate after being given additional equipment of 55.63%. The result is between estimation and reality after using  production tool s,  after and before using the tool close to an accurate estimate of between 56, 5% with 55.6% have only a  0.9% difference in error. Based on the results of the prediction of KWT production rates using simple linear regression, it can be concluded that the addition of the data  production tools used to produce has a big effect, and predictions are close to accuracy using time series data, which greatly affect the accuracy of prediction calculations .
Fuzzy Clustering Models and Their Related Concepts

This chapter describes fuzzy clustering models. Fuzzy clustering models are typical examples of model-based clustering. The purpose of the model-based clustering is to obtain the optimal partition of objects by fitting the model to the observed similarity (or dissimilarity) of objects. The merit of model-based clustering is that we can obtain a mathematically clearer solution as the clustering result, because we know the mathematical features of the model. However, when we observe a large amount of complex data, it is difficult to fit the simple model to the data to obtain a useful result. In order to solve this problem, we have extended the model in the framework of fuzzy clustering models to adjust to the complexity caused from the recent variety of vast amounts of data. This chapter describes how we extend the fuzzy clustering models, along with the mathematical features of the several fuzzy clustering models. In particular, we describe the novel generalized aggregation operator defined on the product space of linear spaces and the generalized aggregation operator based nonlinear fuzzy clustering model.
FORMATION OF TEENAGERS’ COGNITIVE INTEREST TO POP MUSIC ART

This article discusses the problems of the teenagers’ cognitive interest formation concerning pop music art; the concept of this phenomenon as an integrative quality of a teenager's personality was clarified. From a gnoseological position by the example of rock music the authors reveal the specifics of pop music art and describe its main directions in different time periods, thereby forming cognitive interest in adolescents. Teenagers’ psychological and educational features were identified, contributing to the effective formation of cognitive interest in the best examples of rock music. The authors developed and described the criterion-assessment basis of the study; proposed diagnostic assessment of the formation of adolescents’ cognitive interest in rock music that was based on two criteria: motivational and taste preferences, which allowed identifying and describing four levels of this phenomenon formation in adolescents. The efficiency of the developed diagnostics on the ground of the criterion-assessment basis was proved. The article is intended for university teachers, graduate students, undergraduates, education professionals.