Reviewerly/exHarmony huggingface dataset:
The NTNU System for Formosa Speech Recognition Challenge 2020

This paper describes the NTNU ASR system participating in the Formosa Speech Recognition Challenge 2020 (FSR-2020) supported by the Formosa Speech in the Wild project (FSW). FSR-2020 aims at fostering the development of Taiwanese speech recognition. Apart from the issues on tonal and dialectical variations of the Taiwanese language, speech artificially contaminated with different types of real-world noise also has to be dealt with in the final test stage; all of these make FSR-2020 much more challenging than before. To work around the under-resourced issue, the main technical aspects of our ASR system include various deep learning techniques, such as transfer learning, semi-supervised learning, front-end speech enhancement and model ensemble, as well as data cleansing and data augmentation conducted on the training data. With the best configuration, our system takes the first place among all participating systems in Track 3.
Development of Control Drainage Operation Model and Utilization Planning of Post-Fire Peatlands

The research aimed to determine the monthly operational groundwater control and land use patterns in fire prevention efforts on peatlands. The research method was carried out using a detailed survey scale method in the representative sample area of 20-30 ha. Observations in the field included measuring the physical properties of soils and observing hydrological components. Group discussions with the community were conducted to explore information on the causes of fires, compilation of plans for operational activities in the field, and land use models. The research results showed that in the soil depth of 0-20 cm the level of peat maturity classified as Sapric (mature), at a depth of 20-50 cm is classified as hemic and at a depth of 50-100 cm belongs to fibric (immature). The effects of blocking canal construction were very significant in raising the water level in the channel and groundwater table. However, due to the low rainfall until December 2019, the groundwater level was not yet able to raise to the point of arrangement 40 cm. Till the end of December 2019, the groundwater level was at 70 cm, however there has been an increase in groundwater level of 30 cm since the beginning of December 2019. In the rainfall conditions &amp;lt; 2500 mm/year, blocking canal operations with a retention system have to begin in April. Agroforestry is the best model and &lt;em&gt;Albizia chinensis&lt;/em&gt; (Osbeck) Merr. (sengon) in combination with pineapple plants are the best land use pattern. In addition, some short-term proposals are to provide infrastructure for firefighting, the construction of a road embankment, normalization of main rivers and canals, providing boring wells, making security control posts, training, monitoring, and providing some incentives for farmers to clear land and firefighting teams at the village level.
Semantic Analysis of Verb-Noun Derivation in Princeton WordNet.

We present here the results of a morphosemantic analysis of the verb-noun pairs in the Princeton WordNet as reflected in the standoff file containing pairs annotated with a set of 14 semantic relations. We have automatically distinguished between zero-derivation and affixal derivation in the data and identified the affixes and manually checked the results. The data show that for each semantic relation an affix prevails in creating new words, although we cannot talk about their specificity with respect to such a relation. Moreover, certain pairs of verb-noun semantic primes are better represented for each semantic relation, and some semantic clusters (in the form of WordNet subtrees) take shape as a result. We thus employ a large-scale data-driven linguistically motivated analysis afforded by the rich derivational and morphosemantic description in WordNet to the end of capturing finer regularities in the process of derivation as represented in the semantic properties of the words involved and as reflected in the structure of the lexicon.
Interactive Learning Model to Increase Student Activities in Social Studies Learning About Natural Resources in Elementary Schools

The background of this research was a lack of activity and student learning outcomes in social studies learning. One of the reasons is that the way of learning that teachers do so far is still conventional in the sense that the dominant teacher is active in transferring knowledge to students. While students are less involved, their activities are only listening, taking notes and memorizing them. Based on this, a classroom action research (CAR) was carried out with the aim of increasing and improving teaching and learning activities in class IV SDN 1 Kedawung. The method used in this research is to use the PTK developed by Kemis and Mc.Taggart which consists of planning, action, observation and reflection. The research data collection technique was carried out using observation guidelines, field notes, interview sheets, process assessment tables, evaluation sheets (LKS). The data obtained were analyzed and reflected using qualitative descriptive methods. The results showed that student learning activities in learning natural resources using an interactive approach had increased. Student learning outcomes have also increased significantly in each cycle. The average score of students at the end of I reached 64.46, in cycle II the average score of students was 68.92 and in the third cycle the average score of students was 76.60. This shows that students' understanding is quite evenly distributed with the level of achievement that is classified as quite successful.
SPF-Net: Semantic Parsed Feature for Pedestrian Attribute Recognition

research-article SPF-Net: Semantic Parsed Feature for Pedestrian Attribute Recognition Share on Authors: Qin Zixin Tsinghua University, China Tsinghua University, ChinaView Profile , Wang Han Tsinghua University, China Tsinghua University, ChinaView Profile , Wang Shengjin Tsinghua University, China Tsinghua University, ChinaView Profile Authors Info & Affiliations ICVIP 2020: 2020 The 4th International Conference on Video and Image ProcessingDecember 2020 Pages 110–115https://doi.org/10.1145/3447450.3447468Published:25 December 2020 0citation11DownloadsMetricsTotal Citations0Total Downloads11Last 12 Months11Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Cinematic Sequence For Video Blog Using Multimedia Development Life Cycle

There are so much video blog on internet. It already become a trend for now, where people can record and upload video to internet and can be watched by audiences. But because some video blog has boring visual, especially lack of cinematic content in the video blog. And with cinematic videos is actually can attract more audience. Therefore with this video blog can help people understand how to make cinematic sequence with some tips on this video blog. This video blog develop using Multimedia Development Life Cycle (MDLC), where is contain 6 steps which is, concept, design, material collecting, assembly, testing and distribution. Final result of this video blog contains tips on how to make cinematic sequence, which are compiled using Adobe Premiere Pro CC 2017. Final video are implemented on the youtube website, after implemented the video, this video able to provide some tips to audience about content in this video blog.
About how much miracles are we ready for preparation…

The material can be attributed to the genre of free review of the book of Philosophy recently published in Crimea sciences of Mikhail Kizilov, which, continuing and developing the connotation “Crimean text”, deduces from marginal discourse and includes in the scientific circulation, firstly, the name of Demokrit Terpinovich, and secondly, it still publishes the unknown text “Zoroad. Poem relating to Tauris…”, which was discovered by him in the collections of the Khoton library of Harvard University.
Organizational Culture, Job Satisfaction and performance: The Mediating Role of Innovation and Motivation: Evidence Form Workplaces in Pakistan

The core objective of this research is to study the interrelations between organizational culture, innovation, motivation, job satisfaction, and performance. We proposed a theoretical framework whereby organizational culture that can both stimulate or restrain innovation directly or through motivation. And these two factors play a mediatory role in job satisfaction. We also proposed a bidirectional effect running from job satisfaction to innovation. For this, we modified the Naranjo-Valencia et al (2016) model and Cameron and Quinn (1999) Competing values framework was adopted which differentiates organizational culture into four types i.e. clan, adhocracy, hierarchy, and market culture. We also establish empirical validity by collecting data from 200 respondents including males and females of different age groups working in different sectors of Pakistan. Data was collected by means of Likert scale type questionnaire and analyzed using PLS CFA and SEM techniques. The results show that the culture can foster innovation and ultimately improve job satisfaction and performance, or it can be an obstacle for both depending on the norms and values promoted by the culture. It has been found explicitly that adhocratic culture is the one that enhances innovation, job satisfaction and performance whereas the hierarchy culture inhibits them. Based on these results, it can be concluded that organizational culture type has a significant impact on innovation as well as a strong mediatory role of motivation and innovation has its effect on job satisfaction and performance. Moreover, Job satisfaction also seems to foster innovation. The findings provide useful insights for organizations operating in Pakistan, to achieve a competitive advantage through innovation. Organizations can use the result in favor of their organizational effectiveness by motivating the employees to embrace innovation in the culture which will ultimately lead to job satisfaction and increased employee performance. The overall result supports that the culture of organizations has a significant positive impact on employee job performance.
Application of Genre-Based Writing Models to Improve The Ability of Writing Personal Letters

This research was motivated by the problem of writing personal letters at SDN Ujungberung V. Based on the results of observations in the field, it was found that many students were less able to write personal letters, were still difficult to express ideas in making personal letters, and did not pay attention to spelling in writing. The purpose of this study was to describe the process and ability of students in writing personal letters. For this reason, researchers used a genre-based writing model to improve the processes and abilities of students in writing personal letters. The research method used is a classroom action research method (PTK) using Elliot's design. In this study, researchers used instruments in the form of observation sheets, field notes, interviews, documentation, and tests. Data analysis was performed using quantitative, qualitative and triangulation techniques. Based on the findings in the field, there were several important problems related to writing personal letters. Students are not familiar with the structure of personal letters, written personal letters are not in accordance with a predetermined theme and pay less attention to spelling in writing. Judging from the results of the ability to write personal letters, each cycle has increased. This is evident from the average value of the ability to write personal letters obtained by students from each cycle. Cycle I: 68.26, Cycle II: 81.58, and Cycle III: 89.94. Thus the researcher recommends the teacher to use a genre-based writing model as a solution to improving students' personal letter writing skills.
ASSOCIATIVE CLASSIFICATION APPROACH CAN PREDICT PROSTATE CANCER BASED ON THE EXTRACTED ASSOCIATION RULES

Aim: This study aims to classify the diagnosis status of prostate cancer and determine the related factors by applying the associative classification method, one of the data mining methods, to the open-access prostate cancer data set. Materials and Methods: In the current study , an open-access data set named Prostate Cancer is used for classification. The performance of the associative classification model is evaluated using the classification performance metrics such as sensitivity, selectivity, accuracy, balanced accuracy, negative predictive value, positive predictive value, and F1-score. Results: According to the prostate cancer classification results obtained from the associative classification model, the accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score values were obtained as 0.968, 0.789, 0.9, 0.879, 0.938, 0.882 and 0.923, respectively. Conclusion: In the analysis of the open-access data set, the proposed associative classification model has distinctively successful results in classifying prostate cancer on the performance metrics.
Study of Photography Result using Blind Test Method

Skripsi ini bertujuan untuk mengetahui apakah menggunakan metode blind test dapat menyatakan bahwa user awam dapat membedakan foto yang diambil dengan kamera DSLR, kamera mirrorless, dan kamera smartphone. Selain menggunakan metode blind test, penelitian ini juga menggunakan metode penelitian kualitatif dimana kami mengumpulkan data melalui distribusi online dengan menggunakan google form dan aplikasi media sosial yang disebut line dalam mendistribusikan kuesioner ke grup media sosial UIB jurusan Sistem Informasi angkatan 2015 yang diperkirakan sekitar 140 orang. Dalam mengisi kuesioner ada 30 siswa yang mengisi kuesioner online yang telah didistribusikan. Hasil penelitian ini adalah bahwa responden masih tidak dapat membedakan perbedaan foto yang diambil oleh kamera DSLR, kamera mirrorless, dan kamera smartphone. Mayoritas orang masih belum dapat menunjukkan secara khusus untuk memahami hasil dari ketiganya. Ini bisa jadi hasil dari kemajuan teknologi alat fotografi yang sudah berkembang sejauh ini, sehingga alat umum dapat menghasilkan hasil yang tidak dapat dilihat dari alat profesional.**********************************************************************This study aims to determine whether using blind test method able to tell that the average person can differentiate the photos that were taken with DSLR camera, mirrorless camera, and smartphone camera.Aside from using blind test method, this research also used qualitative research method where we collected the data through online distribution by utilizing google form and social media application called line in distributing questionnaires to the social media line group chat of UIB majoring in Information System class of 2015 which were estimated about 140 people. In filling out the questionnaire there were 30 students who fill out the online questionnaire that had been distributed. The result of this research is that the respondents still cannot distinguish the difference of photos taken by DSLR camera, mirrorless camera, and smartphone camera. Majority of people are still unable to point out distinctively to understand the results of those three. This could be the result of the technological advancement of photography tools already advanced so far, so that common tool can produce results that can’t be discerned from professional tool.
A novel artificial intelligence model for color image quality assessment for security enhanement weighted by visual saliency

Artificial Intelligence (AI) is the enhancement and method of computer system that handles tasks which requires human like intelligence such as recognition, language translation and visual interpretation. Subjective image quality assessment (IQA) is difficult to be implemented in real-time systems, methodology for enhancing the involvement in producing IQA model is to improve the quality of image by significant evaluation. Intuitively, human eyes are not sensitive to the distortion and damage from the area with lesser visual saliency (VS), VS is closely related to IQA. With this consideration, an effective IQA was proposed, which involved two processes. The local quality map of a distorted image was computed using the structural similarity function of its feature attributes, such as brightness, chrominance and gradient. Second, the local quality map was weighted with visual saliency (VS) to get the objective evaluation of image quality. The VS was modeled by extracting the saliency of low-level features of the image, wiping off the molestation information from these saliency based on an apriori threshold, and combining the effective information to construct the saliency map. Image processing using fuzzy is gathering features and segments as fuzzy set while processing images. The experiments on the two largest database for six classical IQA metrics demonstrate that performance of weighted-VS IQA metrics is superior to the performance of no weighted-VS IQA metrics, and the proposed IQA method has higher computational accuracy than the other IQA metrics under a moderate computational complexity, especially for two types of distortion images, such as local block-wise (Block) and fast-fading (FTF).
A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.
Public Service Oriented Data Warehouse Architecture in Public Security Field

The storage data of each application system in public security field is distributed and heterogeneous. However, the traditional knowledge discovery system and data warehouse based on homogeneous data source can not meet the needs of public security knowledge discovery. Therefore, the construction of data warehouse architecture in the public security field is the key to the successful application of knowledge discovery technology in the public security field. According to the characteristics of the public security industry, this paper designs a public security data warehouse architecture in detail. This paper focuses on the design of data warehouse system architecture, data extraction, transformation and loading, the establishment of multi-dimensional model and the display of data warehouse front-end application. In view of the deficiency of the public security organs in decision support, a public security decision support platform based on data warehouse is proposed. At the same time, this paper analyzes the design and structure of decision support system, and studies the key technologies of data warehouse, OLAP and data mining used in the process of system implementation. Finally, an example is given to show the function of the system.
Improved RSA lossy trapdoor function and applications

Kakvi and Kiltz (EUROCRYPT'12) proposed the first tight security reduction for RSA full domain hash signature scheme (RSA-FDH) with public exponent e < N1/4 in the random oracle (RO) model, and they left an open problem which called for a tightly secure RSA-FDH for N1/4 < e < N. In this paper, we consider the improved RSA (iRSA) trapdoor functions, introduced by Cao (Science in China'01), are functions that the security can be strictly proved to be equivalent to the factoring. We show that iRSA-FDH has a tight security reduction for e < N. Technically we construct iRSA lossy trapdoor functions, and then we apply the lossiness of the iRSA trapdoor functions to obtain tight security reductions for iRSA-FDH in the RO model. Finally, we propose a tightly secure blind signature scheme based on our iRSA lossy trapdoor functions in the RO model.
Comparative Analysis of Web Frameworks (Angular JS, React JS, Vue JS)

Having new technologies in web ,the need for having better ways to rapidly develop and deploy interactive web applications here comes JavaScript frameworks in the picture. These frameworks provide the backbone for single page web applications development and provide powers the plain HTML, JavaScript. ReactJS, AngularJS and Vue JS are the three most commonly used java script frameworks in today’s web development. Both of these mentioned frameworks are used to build interactive single page application(SPA).This research paper will help in understanding AngularJS , ReactJS and Vue JS.Keywords: Web, Java script frameworks ,Single page applications, Web application development.
Performance Prediction for Hardware-Software Configurations: A Case Study for Video Games

Performance prediction for hardware-software configurations is a relevant and practically important problem. With an increasing availability of data in the form of performance measurements, this problem becomes amenable to machine learning, i.e., the data-driven construction of predictive models. In this paper, we propose a learning method that is specifically tailored to the task of performance prediction and takes two important characteristics of this problem into account: (i) prior knowledge in the form of monotonicity constraints, suggesting that certain properties of hard- or software can influence performance only positively or negatively, and (ii) strong differences in the precision and reliability of performance measurements available as training data. We evaluate our method on a real-world dataset from the domain of performance prediction in video games, which we specifically collected for this purpose.
Image Super Resolution Reconstructed By Coupling Dictionary And Clustered Image Blocks

This paper focuses on the reconstruction of high resolution image blocks through low resolution image blocks, the reconstruction process takes advantage of the sharpness value of image has the property of scale invariance [1]. The image blocks with the same sharpness value are grouped into one class. For classes that are higher than a certain sharpness value will train coupling dictionary, then the sparse representation coefficient of the block is obtained by using the mapping function, Coupling dictionary and image feature blocks. Image super-resolution reconstruction will utilize coupling dictionary, mapping function and sparse representation coefficient. The class of have no training coupling dictionary, the corresponding block is reconstructed directly by using the same location of MR (middle resolution) image, MR image is obtained by the double cubic interpolation amplification of LR (lower resolution) image. The proposed algorithm is improved on the basis of [2]. With the image reconstruction performance basically unchanged, the time of image reconstruction is greatly reduced and the complexity of the algorithm is reduced.