Reviewerly/exHarmony huggingface dataset:
การศึกษาและทดสอบประสิทธิภาพของ N-TiO2 โฟโตคะตะไลติก เพื่อยับยั้งการเจริญเติบโตของเชื้อ Mycobacterium tuberculosis

The purpose of the study was to develop a method for inhibition of Mycobacterium Tuberculosis (MTB), which is a major global public health problem. An advanced oxidation reaction with a photocatalytic process was conducted. The method could breakdown or eliminate molecules of an organic and inorganic substance to be stable molecules. The research examined the inhibition efficiency of MTB (H37Rv) by using N-TiO2 as a photocatalyst prepared by a sol-gel process and formed by a dipping process with a sponge substrate. The inhibition of tuberculosis was tested under ultraviolet light (UVC) and visible light irradiation with an N-TiO2 photocatalyst at room temperature in a negative pressure room. The results showed that N-TiO2 catalysts could inhibit MTB under visible light irradiation at three and five hours (60% and 100%) respectively. Besides, irradiation by using visible light and ultraviolet light together about 30 minutes inhibited MTB 100%.Keywords: MTB growth inhibition, N-TiO2, photocatalytic process, sol-gel process, dipping process
Perbandingan Metode Klasifikasi Naive Bayes dan K-Nearest Neighbor

Classification is a technique to build a model and assess an object to put in a particular class. Naive Bayes is one of algorithm in the classification based on the Bayesian theorem, which assumes the independencies of one class with another class. K-nearest neighbor is an algorithm in the classification method for classifiying based on data that has a closest distance between one object and another object. Naive Bayes and k-nearest neighbor methods are used in classification of the employment status of citizen in Kutai Kartanegara regency because has a good accuracy and produce a small error rate when using large data sets. This research aim to compared optimal performance accuracy of  both methods on the classifiying of the employment status of  citizen. The data used are employment status of citizen in Kutai Kartanegara Regency based on SAKERNAS of East Kalimantan Province in 2018 and used 5 factors namely age, sex, status in the household, marital status, and education to predict employment status of citizen. Based on the analysis, classification the employment status of citizen with naive Bayes method has accuracy of 90,08% and in the k-nearest neighbor has accuracy of 94,66%. To evaluate the accuracy of classification used calculation of Press’s Q. Based on Press’s Q value showed that both of classification methods are accurate. From that analysis, can be concluded that the k-nearest neighbor method works better compared with the naive Bayes method for the case of the employment status of citizen in Kutai Kartanegara Regency.
High-performance Block Cipher Using Flexible Architecture

Light weight cryptography has been a prominent sector in exploring the cryptanalytics in contemporary world. In this paper, an elevated production capable structure and pliant implementations of hardware by SPECK, which is a lightly weighted block cipher is presented. This lightly weighted SPECK can be accustomed to diminish the retardation of critical path, a tree structure for the realization of Sklansky adder which is an efficient parallel prefix adder operation is used.
SQL Server on Linux

I started my IT career working with Unix systems and databases. That includes databases and applications on platforms like System V Release 4, IBM AIX, HP-UX, Sun Solaris, and of course Linux. Back in 1991, I was using Unix on minicomputers, and I was always wondering how I could run Unix on less expensive hardware, such as a PC, so I could better test and learn how it works. Then I discovered Linux while reading a personal computing magazine article.
Random Oracle Schemes in Practice

In the following we give an overview about cryptographic schemes in practice and standards which rely on the random oracle methodology. In all cases the power of random oracles facilitates the design of very efficient solutions, usually combined with suitable number-theoretic primitives such as the discrete-logarithm-based one-way function or the RSA trapdoor function.
Metric for evaluating difference between seismic gathers

Summary When building machine learning (ML) models for specific tasks having a good metric is of crucial importance. Constructing a good metric that is relevant to the problem domain is a difficult task. We consider a problem of noise attenuation on seismic data, specifically ground roll attenuation problem. The methods of quality control that are used by experts who perform the denoising task manually can not be directly transferred to machine learning setting. A generalization of such a method is proposed to obtain a formal computable metric that allows to compare denoised gathers with respect to their “proximity” to a ground truth cleaned data, and consequently to compare ML models for ground roll attenuation.
The Rhetorical Adjunct Wh mwue(-l) ‘what’ in Korean

This paper investigates the grammatical roles of the adjunct wh-word mwue(-l) ‘what-ACC’ occurring in both interrogative and declarative sentences. Thus far, the function of mwue(-l) in declarative sentences has been mainly focusing on its use as an exclamative interjection marking a humble statement. In this paper, narrowing down to its distribution in the clauses containing a copula and a stative adjective, our novel claim is that mwue(-l) can be analyzed as a rhetorical question marker. We will explore its empirical dimensions and investigate how the distinct functions of the ordinary question marker and the rhetorical question marker relate to each other in terms of syntactic and semantico-pragmatic dimensions. Specifically, we will show that the meaning of the rhetorical mwue(-l) is not associated with the core property of the question marker at the at-issue level, but with the negative expressive content which gives rise to the speaker’s negative attitude towards reading on the proposition at the multi-dimentional level.
THE EFFECT OF USING DISCUSSION METHOD IN STUDENTS’ SPEAKING ABILITY AT THE TENTH GRADE STUDENTS OF SMK SWASTA HKBP PEMATANGSIANTAR

This study is focus on the effect of using discussion method in students’ speaking abilility at the tenth grade students of SMK Swasta HKBP Pematangsiantar. According to Schmuck, Discussion Method is a strategy for achieving instructional objectives that involves a group of persons, usually in the roles of moderator and participant, who communicate with each other using speaking, nonverbal, and listening processes.The populations in this study are 80 students of 3 classes. The choosing of sample is done by using purposive sampling thus gotten the sample as big as 52 students ( 2 classses)The data analysis is done by counting the Mean (????) and the Standart Deviation (S) and the hypothesis will be proved by testing the significant of coleration statistic students or testing-t . The Mean of Pre Test Experimen Class is 3,78 and the Mean of Post Test Experiment Class is 8,05. The Mean of Pre Test Control Class is 3,74 and the Mean of Post Test Control Class is 6,55.The testing of hypothesis for pre test between experiment class and control class is gotten ????ℎ????????????????????(2,45 ) < ???????????????????????? (7,14). So ????0 is received and ???????? is rejected, it means that there is any effect of using discussion method in students’ speaking ability.
Simple online and real-time underwater multiple object tracking

For underwater videos, the effects of object tracking becomes more challenging since videos taken are greatly influenced by blurry background, illumination condition and occlusion. Hence, this paper explores an effective approach for underwater multiple object tracking where the main advantage lies in associating objects effectively for online and real-time applications. It is a remarkable fact that detection quality is a key factor for tracking effects, where changing the detector improves the result of tracking. In the process, the whole model consists of detection, Kalman Filter and Hungarian Algorithm. While the detection method applied is yolov3 as it has an excellent performance in terms of speed and accuracy. Consequently, yolov3 can be perfectly embedded in the model. The model embraces an impressive tracking result on underwater dataset. Tracking results have been analyzed using Multiple Object Tracking Accuracy (MOTA) and Multiple Object Tracking Precision (MOTP).
Alignment Completeness for Relational Hoare Logics

Relational Hoare logics (RHL) provide rules for reasoning about relations between programs. Several RHLs include a rule, Sequential-Product, that infers a relational correctness judgment from judgments of ordinary Hoare logic (HL). A variety of other rules have been found useful in practice, but Sequential-Product is relatively complete on its own (with HL). As a more satisfactory way to evaluate RHLs, a notion of alignment completeness for rules is introduced, in terms of the inductive assertion method and product automata. Alignment completeness results are given to account for several different sets of rules. Applying alignment completeness to richer languages and product notions may serve to guide the design of RHLs.
Pedagogical conditions for the formation of managerial competencies of future teachers through practice-oriented educational tasks

The relevance of the issues of the formation of future teachers’ managerial competencies is due to the increased requirements for the quality of training and complication of the conditions for organizing the educational process, which determines the strengthening of requirements for professional competence and the need to prepare for a new role – a teacher-manager. When analyzing the problem, a complex of theoretical and empirical methods is used: a systematic analysis of scientific and methodological works, generalization of pedagogical experience, observation and analysis of the results of pedagogical activity, allowing the authors to consider this problem taking into account many factors that affect the process of forming the managerial competencies of future teachers.
Under control: Audio/Video Conferencing Systems Feed “Surveillance Capitalism” with Students' Data

This paper analyses to what extent the choice of audio and video conferencing systems in university teaching can be described as part of an overarching “surveillance capitalism” in the course of the corona lockdowns.
Anonymisation of Image Data Using Deep Learning

Collecting and storing data is easier and more common than ever before.A lot of this data is personal data, which is problematic to store and use both for ethical reasons and because of legislations. In some scenarios the personal information in the data is not interesting or relevant for the given task but it is still collected and stored as a byproduct of the data collection. In these scenarios it would be much better if one could use anonymised data instead.This report presents a neural network approach for creating an anonymisation filter for image data, specifically for images depicting humans taken from above. A convolutional neural network is used as the filter. It is trained together with a person detector and ReID in order to generate images where it is possible to detect people in the images but impossible to identify them. The training process is similar to that of a generative adversarial network since the goal of the filter was to construct an anonymisation that makes it easy for the detector but hard for the ReID and the aim for the detector and ReID was to become as good as possible. Using the presented method a filter was created which succeeds in anonymising the images whilst almost maintaining the performance of the person detection. Using the metrics AP for the detector and AUC-ROC for the ReID this filter yielded the results 0.864 and 0.540 respectively. However, several of the parameters were very sensitive to changes, yielding results that varied widely when small changes were made, making the network fairly hard to train.
Seq2Biseq: Bidirectional Output-wise Recurrent Neural Networks for Sequence Modelling

During the last couple of years, Recurrent Neural Networks (RNN) have reached state-of-the-art performances on most of the sequence modelling problems. In particular, the sequence to sequence model and the neural CRF have proved to be very effective in this domain. In this article, we propose a new RNN architecture for sequence labelling, leveraging gated recurrent layers to take arbitrarily long contexts into account, and using two decoders operating forward and backward. We compare several variants of the proposed solution and their performances to the state-of-the-art. Most of our results are better than the state-of-the-art or very close to it and thanks to the use of recent technologies, our architecture can scale on corpora larger than those used in this work.
Cyber-Crime and Digital Forensic: Challenges Resolution

Cybercrime is an emerging kind of crime, which has to be faced and fight for mankind. When you go through news or any crime case authentic data source, you will easily analyze that number of crime cases with the help of technology, are getting climb drastically. To overcome this problem a new way of science originated known as digital/computer forensic. Here author is trying to hold forth about cybercrime and crime rate of different states of India. Furthermore, author will discuss some prevention measure to avoid risk of cybercrime. There are some law enforcement agencies like cybercrime cells fabricated by the government, to fight with this canker of society. Digital forensic needs new forensic tools in the war of crime because of enhanced technology and increase databaseKeywords- Cyber-crime, Digital forensic, Forensic tools, Computer  forensic.
Shaw University Library Guides: Other Lending Resources: Interlibrary Loans (ILL)

Guide to using Cooperating Raleigh Colleges (CRC) and Interlibrary Loan (ILL) lending options to supplement your research at Shaw University Libraries. An In-depth look at ILL Lending
A comparative study of professional music production methods in theage of streaming

Although Sweden is a small country, the Swedish music exports have been successful for many years. In our ongoing research project: Searching for Sophia in music production, we study how various as ...
Patent Enforcement in Cyberterritories

3D-printing technology has exposed a gap in patent protection. Thanks to 3D printers, physical products can be created and sold digitally in the form of CAD files, and consumers printing the products are effectively manufacturers. But current law would treat a product patent as being directly infringed only when the physical product is made, used, offered for sale, or sold, making it difficult to target the digital source of the infringement. While past scholarship has fashioned new legal constructs to close this gap (e.g., expanding patent eligibility or extending infringement case law) this article considers whether a proper, analogous framework already exists — the law of extraterritorial patent enforcement. National borders have long been thinning as a result of globalization, with manufacturing, sales, and operations increasingly being conducted, at least in part, abroad. When certain entities operated beyond the border to avoid infringement liability, Congress and the courts occasionally responded to expand the reach of U.S. law to deem such conduct infringing, provided that there was a sufficient nexus to the United States and harm to the patent owner.Now 3D printing has thinned the border between the digital and the physical such that the difference can be little more than the click of a button. As with national borders, businesses now have more choices as to which side of the digital-physical border to conduct their business activities. Just as the law bridged certain gaps in the national borders context, a similar reach into digital spaces may be appropriate. Beyond this analogy are similar analytical challenges. Both situations require some balancing of recognized jurisdiction with the reality that conduct outside the border often has substantial effects on the interests of U.S. patent owners. And in both situations imposing liability for some conduct can over-protect patent owners’ legitimate interests. There is even a statutory textual link, in that infringement is defined as certain acts “within the United States,” but that geographic scope has never been interpreted to encompass three-dimensional spaces that exist only as non-physical, conceptual constructs within digital storage devices.Applying patent extraterritoriality principles to such digital spaces, or cyberterritories, as if they were in fact outside “the United States,” closes the gap in patent protection in certain desirable respects but leaves the gap open in other desirable respects. Further, although cyberterritories are not sovereign, and thus no traditional conflict-of-law analysis can be done, future evidence of norms concerning the development and use of CAD files may suggest that the results of this analytical approach are consistent with comity-like considerations.
ANALISA BANDWIDTH DENGAN LIMIT, GROUPING, BURST DAN PRIORITY PADA MIKROTIK MENGGUNAKAN METODE SIMPLE QUEUE (Studi Kasus SMKN 1 Palasah)

Abstract Computer network users must invest a lot to access the Internet. The Internet has had a huge influence on the dissemination of information, so that more and more people access data through the Internet. These problems can be overcome using MikroTik as a regulator of Internet data traffic and share bandwidth on computer network users. Mikrotik includes a full range of features for wireline and wireless. In this implementation, the researcher took a case study at school, namely SMK Negeri 1 Palasah. At the school, the distribution of bandwidth using the PCQ method has been carried out, where all clients get the same limit of 512Kbps, but after conducting field studies, many teachers are not satisfied with the internet access. So here the researcher tries to apply bandwidth with limits, grouping, burst and priority in the proxy on the simple queue so that the distribution of bandwidth can be adjusted to the needs of the user. The results of this study that the distribution of bandwidth given is in accordance with the needs of the client, where the grouping priority technique is applied to the teacher's room, for the limit technique in all student practice rooms and bursts in the special counseling guidance room and the result is that 80% of teachers and students have met access. internet at SMK Negeri 1 Palasah. . Keywords:  computer network, bandwidth, mikrotik, PCQ, Simple Queue.
Mixed impulse and Gaussian noise removal using L0 sparse regularization

This paper considers the problem of denoising the image corrupted by mixed impulse and Gaussian noise. We propose a two-stage approach based on impulse detectors and L0 sparse regularization. We first employ the impulse detectors to identify the locations of impulse noise, and then restore the noisy image by solving a constrained minimization model. The objective function of the proposed model uses the L0 norm to promote the sparsity of the resulting image in a tight framelet system. To overcome the algorithmic difficulty caused by the L0 norm, we use proximal block coordinate descent method to solve an approximate model. The global convergence of the algorithm is proved. We also develop an adaptive strategy on approximation parameter selection and a FISTA-like iterative scheme to speed up the algorithm. Numerical results show that our method performs favorably in comparison to several existing algorithms.
A new regularization term based on second order total generalized variation for image denoising problems

Variational models are one of the most efficient techniques for image denoising problems. A variational method refers to the technique of optimizing a functional in order to restore appropriate solutions from observed data that best fit the original image. This paper proposes to revisit the discrete total generalized variation (TGV ) image denoising problem by redefining the operations via the inclusion of a diagonal term to reduce the staircasing effect, which is the patchy artifacts usually observed in slanted regions of the image. We propose to add an oblique scheme in discretization operators, which we claim is aware of the alleviation of the staircasing effect superior to the con ventional TGV method. Numerical experiments are carried out by using the primal-dual algorithm, and numerous real-world examples are conducted to confirm that the new proposed method achieves higher quality in terms of rel ative error and the peak signal to noise ratio compared with the conventional TGV method.
Global Node Attentions via Adaptive Spectral Filters

Graph neural networks (GNNs) have been extensively studied for prediction tasks on graphs. Most GNNs assume local homophily, i.e., strong similarities in local neighborhoods. This assumption limits the generalizability of GNNs, which has been demonstrated by recent work on disassortative graphs with weak local homophily. In this paper, we argue that GNN's feature aggregation scheme can be made flexible and adaptive to data without the assumption of local homophily. To demonstrate, we propose a GNN model with a global self-attention mechanism defined using learnable spectral filters, which can attend to any nodes, regardless of distance. We evaluated the proposed model on node classification tasks over six benchmark datasets. The proposed model has been shown to generalize well to both assortative and disassortative graphs. Further, it outperforms all state-of-the-art baselines on disassortative graphs and performs comparably with them on assortative graphs.
Modern Techniques for Ancient Games

Games potentially provide a wealth of knowledge about our shared cultural past and the development of human civilisation, but our understanding of early games is incomplete and often based on unreliable reconstructions. This paper describes the Digital Ludeme Project, a five-year research project currently underway that aims to address such issues using modern computational techniques.
La dignità della vita ed il “diritto di morire” in Francia. Ratio, fisionomia e trasformazione della morte come parte integrante della vita

Expressions like “decisions on termination of life”, “right to die with dignity”, “euthanasia”, “assisted suicide” have found room not only on the pages of case law, of jurisprudence and in the political discussions, but in ordinary speech, too. The right to a life full of dignity, which implies the right to die with dignity or rather the refusal of an existence with no more dignity has become related with one person’s autonomy. This thinking takes uncertain bounds, it goes beyond the juridical context, it involves ethical, philosophical, theological aspects, it goes so far as to put limits to scientific research itself. After a brief analysis of the constitutional and legislative regulations in France, the role CCNE has assumed especially as to the law on bioethics is emphasized.