Reviewerly/exHarmony huggingface dataset:
Sistem Informasi Proses Transaksi Tamara Laundry

Currently, the information system technology is developing very quickly. This makes every business process carried out by a company computerized so that all activities ranging from services to reports can be carried out effectively and efficiently. Tamara Laundry is a company that runs its business in the field of laundry services. Based on the survey that has been conducted so far, Tamara Laundry has not used an information system, so all activities are still done manually. it causes business processes to take a long time and are very susceptible to human error. To overcome these problems, a desktop-based information system was designed using the Java language. This application will assist employees in managing data, storing transactions, and making reports. This application is expected to facilitate and speed up business processes and minimize errors in data management so that, in the end, business processes can run effectively and efficiently.
Monitoring activity and detecting unexpected events in surveillance footage using Deep CNN

Security is always a primary concern in any domain, because there is an increasing in crime rate and illegal activities. Computer vision learning places a premium on abnormal detection and monitoring, which has numerous applications for dealing with a wide range of issues. We are all aware that there is a high demand for safety protection, personal properties and security, in recent years, video surveillance in systems has become a major focus in people's lives, particularly in government agencies and businesses. The technique we are employing is anomaly detection, which aids in distinguishing various patterns and identifying unusual patterns in a short period of time; these patterns are referred to as outliers. Surveillance videos provide real-time output of unusual events. Anomaly detection in video surveillance entails breaking the process down into three layers: video labelers, image processing, and activity detection. As a result, it detects abnormalities in videos for video surveillance, providing an application by providing accurate results in real-time scenarios. In this proposed work, abnormal events are detected with 98.5 percent accuracy using images and videos. To prevent virus transmissions across the world the government forced to announce the lockdown due to COVID-19 pandemic. As a result, production at manufacturing plants in most areas was halted, resulting in the cessation of all economic activity. There is an even greater need to ensure the safety of youngsters. While there is a pressing need to revive workforce production. The work helps in maintaining social distance and wearing face masks while at work clearly reduces the risk of transmission. Monitor activity decided to identify violations using computer vision (Not Wearing Mask) Real-time alerts that send a trigger and an email with a photo of a rule violation to the appropriate authority as evidence of a rule violation
Role Models in Cognitive Psychology: Jerome Bruner as Exemplar

An examination of Jerome Bruner’s intelectual ontogenesis elucidates how cognitive psychologists can generate both good theory and practice during their careers. Bruner challenges psychologists to expand what they see as the focus of their discipline and to actively work for social change. In his early work Bruner challenged the behaviorists. Today he challenges the cognitive psychologists. His challenges are not just about theoretical concerns but about the basic nature of science itself. He calls for a compassionate view of science.
Regular Expressions for Web Advertising Detection based on an Automatic Sliding Algorithm

This paper presents the automation of a Web advertising recognition algorithm, using regular expressions. Currently, the use of regular expressions, optical character recognition, Databases, and automation tests have been critical for multiple Software implementations. The tests were carried out in three Web browsers. As a result, the detection of advertisements in Spanish, that distract attention and that above all extract information from users was achieved. The main feature of the algorithm is that automatic and versatile execution does not require access to the code of the page in question and that in the future it can be an application with background operation. In addition, being supported by optical character recognition gives us acceptable efficiency in detecting advertising.
2-D histogram Based Multilevel Thresholding for Image Segmentation by Hybrid Bacterial Foraging Optimization and Particle Swarm Optimization

The objective of image segmentation is to extract meaningful clusters in given image. Meaningful clusters are possible with perfect threshold values which are optimized by assuming Renyi entropy as an objective function. A 1-D histogram based multilevel thresholding is computationally complex and segmented image visual quality comparatively low because of equal distribution of energy over the entire histogram plan. To overcome the problem, a 2-D histogram based multilevel thresholding is proposed in this paper by maximizing the Renyi entropy with a novel Hybrid Bacterial Foraging Optimization Algorithm and Particle Swarm Optimization (hBFOA-PSO) and the obtained results are compared with state of art optimization techniques. The results of the proposed model have been evaluated on a standard image dataset. The results obtained after implementing a 2-D histogram suggest hBFOA-PSO can be effectively used won multilevel thresholding problems resulting in a high accuracy.
An improved flower pollination algorithm for solving nonlinear system of equations

It is difficult to solve a system of nonlinear equations, especially for higher-order nonlinear equations when we do not have an efficient and reliable algorithm, even though much work has been done in this area. Newton's method and its improved form are widely used at present, but their convergence and performance characteristics can be highly sensitive to the initial guess of the solution, and the methods fail if the initial guess of the solution is inopportune. It is difficult to select a good initial guess for most systems of nonlinear equations. For this reason, it is necessary to find an efficient algorithm for systems of nonlinear equations. Metaheuristic optimisation algorithms have been proposed by many researchers to solve systems of nonlinear equations. The flower pollination algorithm (FPA) is a novel metaheuristic optimisation algorithm with quick convergence, but its population diversity and convergence precision can be limited in some applications. To enhance its exploitation and exploration abilities, in this paper, an elite opposition-based flower pollination algorithm (EFPA) has been applied for solving systems of nonlinear equations. The results show that the proposed algorithm is robust, has high convergence rate and precision, and can give satisfactory solutions of nonlinear equations.
AFRICA – ISRAEL: Spyware Allegations

Africa Research Bulletin: Political, Social and Cultural SeriesVolume 58, Issue 7 p. 23249A-23250C Nations Overseas AFRICA – ISRAEL: Spyware Allegations First published: 19 August 2021 https://doi.org/10.1111/j.1467-825X.2021.10110.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume58, Issue7August 2021Pages 23249A-23250C RelatedInformation
Bacterial Expression of Chimeric <i>Escherichia coli</i> and <i>Trypanosoma brucei</i> DNA Methyltransferases

Our laboratory is interested in DNA and RNA methylation in E. coli and T. brucei as little is known about this form of epigenetic regulation in microorganisms. One methyltransferase being studied at this time is a putative DNA methyltransferase (TbDmt) from Trypanosoma brucei . The exact function of TbDmt is unknown but the protein strongly resembles bacterial DNA methyltransferases such as DNA cytosine methyltransferase (EcDcm) from E. coli . To test our hypothesis that TbDmt is a DNA methyltransferase, we expressed TbDmt in bacteria and created two chimeric protein sequences switching the DNA binding domain and enzymatic domain of EcDcm and TbDmt. Exchanging the DNA binding domain and enzymatic domain of TbDmt with a known methyltransferase may help us discover the function of the enzyme and, if it is a methyltransferase, what DNA sequence is targeted for methylation. Plasmids were made containing the sequences for EcDcm, TbDmt, and both chimeric proteins where the genes are adjacent to the lac operator. E. coli were transformed with the plasmids and expression was induced with IPTG. All four proteins were produced at 20°C, but the proteins with the TbDmt enzymatic domain were less soluble than those with the EcDcm enzymatic domain. The plasmids were re‐isolated after three hours of growth in the presence of IPTG. The plasmids were then digested with eight restriction enzymes blocked by methylation. Each digestion was run on an agarose gel with DNA from uninduced cells and unmethylated phage lambda DNA as controls. EcDcm methylated at its expected site, 5′CCWGG3′, as determined by resistance to PspGI. In addition, there is partial resistance to HpaII in cells containing EcDcm indicating methylation at 5′CCGG3′ or related sequences. The proteins were denatured using guanidium HCl, isolated and analyzed by SDS‐PAGE with Coomassie blue staining. EcDcm and the chimeric protein with the EcDcm enzymatic domain and TbDmt DNA binding domain were successfully purified and were then purified using partial denaturing conditions. These proteins will be tested for methyltransferase activity. TbDMT and the chimera with the TbDMT enzymatic domain were not able to be purified using the guanidium HCl denaturing method so stronger denaturants will be tested in attempt to purify the proteins. Further work will be done in purifying the proteins using both denaturing and nondenaturing conditions to produce functional enzymes for use in methylation assays. This work will contribute to the limited knowledge of methyltransferases in bacteria and protists. Support or Funding Information NIH grant 1R15AI133428‐01 to KTM
Segmentation and Identification of Bilingual Offline Handwritten Scripts (Devanagari and Roman)

Hand written text acknowledgment field has been considered as one of the hardest issues in the digital word. The multifaceted nature dimension of this exploration zone is high due to the reasons like diverse method for writing pursued by the clients, auxiliary independences, age elements of people and so on. This paper shows a novel procedure for the recognition of handwritten scripts, for example division of words and characters. In this paper, we have used two different scripts :”Devanagari” and “Roman” scripts. For which three Convolution Neural Networks(CNN) models are applied on different types of classification: one for language classification for which we have achieved 98% accuracy, second one for Devanagari character classification for which we have achieved 89% and third one for Roman character classification for which have achieved 97% respectively
Deixis used in the novel entitled the good muslim by tahmima anam

This research investigated Deixis used in the novel entitled The Good Muslim by Tahmima Anam.This study was conducted to find out; (1) types of deixis contained in utterances of the novel entitled the Good Muslim by Tahmima Anam, (2) types of deixis were used most in the Novel entitled The Good Muslim by Tahmima Anam. Therefore, it gived significant to the author herself, the learners, other researchers and english teachers. The writer used levinson’s theory in analyzing the data. The methodology of this research was qualitative descriptive study. The technique used to collect the data was documentation. The data was taken from 1.972 utterances of the novel entitled the Good Muslim by Tahmima Anam. From the data have been analyzed, it was found that there were five types of deixis, they were person deixis occured 1.723 times (87.4%), place deixis occured 53 times (2.7%), time deixis occured 68 times (3.4%), discourse deixis occured 83 times (4.2 %), person deixis occured 45 times (2.3 %). The most commonly used types of deixis was person deixis occuring 1.723 times (87.4%).
Machine Learning Based Track Classification and Estimation using Kalman Filter

Classification of target from a mixture of multiple target information is quite challenging. In This paper we have used supervised Machine learning algorithm namely Linear Regression to classify the received data which is a mixture of target-return with the noise and clutter. Target state is estimated from the classified data using Kalman filter. Linear Kalman filter with constant velocity model is used in this paper. Minimum Mean Square Error (MMSE) analysis is used to measure the performance of the estimated track at various Signal to Noise Ratio (SNR) levels. The results state that the error is high for Low SNR, for High SNR the error is Low.
Cyber Security 2020 Front Matters

Cyber Science is the flagship conference of the Centre for Multidisciplinary Research, Innovation and Collaboration (C-MRiC), a multidisciplinary conference focusing on pioneering research and innovation in Cyber Situational Awareness, Social Media, Cyber Security and Cyber Incident Response.It is an IEEE technically co-sponsored conference.Cyber Science aims to encourage participation and promotion of collaborative scientific, industrial and academic inter-workings among individual researchers, practitioners, members of existing associations, academia, standardisation bodies, and government departments and agencies.The purpose is to build bridges between academia and industry, and to encourage interplay of different cultures.Cyber Science invites researchers and industry practitioners to submit papers that encompass principles, analysis, design, methods and applications.It is an annual conference with the aim that it will be held in the future at various cities in different countries.Cyber Science as a multidisciplinary and co-located event is maturing a mainstream and notable conference, first, for its quality, second, for its uniqueness, and finally, for its structure, contributions and originality; something existing mainstream conferences do not normally possess.A testament to the significant interest Cyber Science has thus so far gained.
Internet of Things Security Failures

Privacy and information security are distinct but related fields.1 Security focuses on questions surrounding the extent to which related products, systems, and processes can effectively defend against “attacks on confidentiality, integrity and availability of code and information.”2 The field of information security often involves inquiries about the legal consequences of security failures.3 In 2018, The Economist reported that “more than ninety percent of the world’s data appeared in just the past two years.”4 In the last decade there have been multiple large-scale data breaches and inadvertent data exposures that have resulted in the disclosure of millions of our data.
What's in the R- Stars for Korea?

Korea's stars tell of an economy saddled with a real neutral rate (r-star) that has declined significantly in recent decades and is currently below zero.This reflects a significant decline in trend growth, and two large financial crises that triggered significant shifts in the savinginvestment balance.Larger fiscal deficits and frothy financial conditions since 2012 have helped offset rising demand for safer assets, preventing the neutral rate from falling further.Nonetheless, the fall in the neutral rate, coupled with its effects on asset returns, has complicated the task of monetary policy stabilization.Korea's neutral rate is likely to remain low over the medium-term and could fall further, reflecting a structural savings-investment imbalance owing to declining productivity and a rotation in demographics increasing the demand for precautionary saving and convenience yield, and widening the capital risk premia.The COVID pandemic risks magnifying these trends.
Data Mining Technique to Data Collection and Analysis for Cyber Forensic

In the world of Digital forensic the uncovered digital may contain vital information for digital data investigation for investigator. Digital data collected from the crime scene leads to find out the clue after performing analysis by the examiner. This process of data examination data collection and analysis plays important role in cyber world for the forensic investigator. The cybercrime is a part of computer forensics where the digital evidences are analyze by the investigator and to perform analysis special measurements and techniques are required in order to use this details that has to be accepted in court of law for law enforcement. The data collection of evidence is a key aspect for the investigator, such kind of digital data has to be collected from different sources at the crime scene and this process involves to collect each and every evidence of digital crime scene and later this gather data will be analyze by the experts to reach to the conclusion. In this paper the proposed method collected the data from the crime scene efficiently which includes log data, transactional data, physical drive data, and network data; later this collected data analyzed to find out the theft node in the network. In this paper FTK 4.0 digital forensic tool used to reduce plenty of time for data processing and later report will be produce that will be accepted tin the court of law. This paper also focuses the data collection method with in the network and reach to the faulty node and later this faulty node analyzed with all collected data for forensic analysis. For this standard algorithm used to analyze the performance of distinct features used for network attacks. Kmeans clustering methodology is used to create cluster of victim node and represent victim data in systematic manner for the ease of law enforcement.
Opinion Retrieval

The massive amount of text is available online because of easy availability of Web technologies. This motivates users to post opinions and share their experiences on Web for decision-making process. Information can be searched easily on any topic using facts but searching opinions is difficult. Previous research and extraction systems are thoroughly analyzed for constructing an efficient retrieval system for opinion mining which will distinguish between constructive opinionated information.
Natural Language Learning

This thesis is a small step towards automated learning of natural languages. With the use of a parser that incorporates machine-learning algorithms, our algorithm is able to learn mean-ings of words representing relations in simple sentences, that describe relative positions of two points on a 2D plane. Our SentenceLearner program can create simple sentences describing rela-tions between two points on another 2D plane using data, collected by a statistical parser from sentences given for training, based on n-grams of five words. In this thesis I show that association of simple relations expressed in training sentences with the positional relations of a corresponding pair of points on a 2D plane is possible without the use of any machine-learning algorithm in some circumstances.
Fraud money intercepted

An Interpol-led multinational law enforcement operation has led to the seizure of $83m in funds that was being routed to cyber criminals operating a variety of online scams.
Proceedings of the 65&lt;sup&gt;th&lt;/sup&gt; General Meeting of the Showa University Society

Cardiovascular science emerged in the era of the late 19th and early 20th centuries.Advancements in medical treatment, as well as catheter and device-based interventions, have dramatically reduced the rate of cardiovascular mortality.In Japan, we have appreciated a superior insurance system and taken advantage of intravascular imaging devices, such as intravascular ultrasound and optical coherence tomography (OCT) .OCT has contributed to visualizing atherosclerotic plaques and defining lesion characteristics in vivo.OCT provides us detailed structural and morphological information on plaques, bringing their pathogenesis to light.This innovation has been applied to optimizing a revascularization procedure (percutaneous coronary intervention) and demonstration of anti-atherosclerotic drug efficacy, as well as the detection of vulnerable plaques.Following the successful management of acute phase coronary disease, elderly patients will become prone to develop valvular heart disease, such as aortic valve stenosis and functional mitral regurgitation, and manifest heart failure.Consequently, we are now facing the most aged society in the world with a prominent increase in heart failure patients ; a ʻheart failure pandemicʼ.We should prepare for this upcoming ʻresidual riskʼ.
The Village Library Movement in the 1960s and ‘70s, and the Peasants’ Autonomous activities

Agricultural areas of the 1960s in Korea have been perceived for a long time as a region where the time just stood still. It has also been a longstanding belief that such stagnance was overcome and faded away only after the government-led Saemaueul Movement was initiated and actively promoted by the regime in the 1970s. Quite a few recent studies, however, highlighted the fact that autonomous efforts for progress did take place in agricultural regions during the 1960s, and among those examples, a Book-reading Movement which was also called the “Village Library Movement” is particularly worth mentioning. This movement continued in Korean agricultural towns in the 1960s and ‘70s, and most importantly, such local voluntary activities reveal to us the autonomous nature of the peasant activities of the time.<BR> The Village Library Movement was launched as a civilian movement in 1961, and tried to organize all the existing book-reading activities by the peasants into a single grand movement. Peasants in various regions all autonomously operated book-reading communities of and on their own, officially under the banner of the Village Library Movement, and enhanced their own autonomous activities, by purchasing books the residents in their respective regions wanted to read and enjoy. The essence of this movement, the voluntary participation and autonomous nature of it, continued into the 1970s even when the movement was overtaken by the government and proceeded as a government-led project.<BR> Although the program came to serve as a portal through which books that the government felt necessary for the peasants’ education would flow into agricultural regions, peasants who continued to operate the book-reading communities did not give up their autonomous attitudes. The original ideals of the Village Library Movement was indeed compromised, but book-reading communities continued with many peasants’ participation, and some of them financially benefitted from the Saemaeul Movement, while some others inspired by the movement even joined anti-government peasant activities. We can see the voluntary and autonomous attitudes of the peasants cultivated through such activities involving book-reading communities actually enabled the peasants to set goals of their own for themselves, and to join the society in diverse capacities and roles.