Reviewerly/exHarmony huggingface dataset:
Cervical cancer classification using convolutional neural network-support vector machine

Cervical cancer is the second most common cancer in women worldwide, and occurs when there are presences of abnormal cells in the cervix, which continue to grow uncontrollably. In the early stages, cervical cancer indications are not perceptible; however, it is easily detected with different forms of machine learning methods, such as the convolutional neural network (CNN). This is a popular method with a wide range of applications and known for its high accuracy value. Moreover, there is a support vector machine (SVM) with several kernel functions that is commonly used in the classification of diseases, and also known for its high accuracy value. Therefore, the combination of CNN–SVM with several linear kernels functions as classifier for the categorization of cervical cancer.
The Study of the Plight of Cyberterrorism and Its Way Out

After "9.11", terrorist attacks have been increasingly relying on cyberspace, posing an imminent threat to national security.This article introduces two types of cyberterrorism attack: target oriented and tool oriented.Target oriented attack means terrorists directly attack networking device, while tool oriented is the activity making use of Internet tools.Moreover, in the work, three countermeasures and five futures for cyberterrorism are also discussed.This article suggests that understanding cyberterrorism in a board sense, and do not underestimate the serious situation.
Biotechnology Patent Law Top Ten of 2019: Secret Sales, Denied Appeals, and the Promise of Coronavirus Cures

In the rarified realm of biotechnology patent law, 2019 was one of stasis, change, reaction, and challenges to practitioners, patentees, those discontented with patents, and the judiciary itself. The year saw a comeback of sorts for the doctrine of equivalents, which has been a quiet area of the law since the Supreme Court’s last word in Festo v. Shoketsu Kinzoku Kogyo Kabushiki Co. in 2002. In 2019 there were no fewer than seven cases decided by the Federal Circuit involving the doctrine, and its primary antithesis, the doctrine of prosecution history estoppel. The perennial issue of subject matter eligibility remained uncertain, with the Federal Circuit deciding that method of treatment claims were patent-eligible as being an application of a natural law (and the Supreme Court taking the Solicitor General’s advice and not granting certiorari to review the wisdom of this dichotomy). Diagnostic method claims were another matter, with the Federal Circuit maintaining its jurisprudence that claims to such methods are almost per se patent-ineligible. In doing so, however, its Athena Diagnostics, Inc. v. Mayo Collaborative Services LLC decision illustrated a court in frank internal disagreement (if not disarray) in denying patentee’s petition for rehearing en banc. The Supreme Court weighed in on the extent to which the Leahy-Smith America Invents Act changed the scope of novelty-destroying prior art (saying it didn’t, despite an amicus brief to the contrary by the Act’s co-author, Rep. Lamar Smith), and Section 112(a) came under scrutiny on both written description and enablement issues. Finally, as a fixed constant in an otherwise changing universe, the interference over CRISPR technology between the Broad Institute and its colleagues and the University of California, Berkeley and its collaborators maintained its measured pace to a determination of who was first to invent CRISPR, and, accordingly, who owns this important technology. Admittedly, choosing the top ten judicial decisions suffers from an inevitable degree of subjectivity. However, we believe these decisions are among the most important decisions of the year in biotechnology patent law even if others might prefer to substitute a case or two for those on our list. All of the decisions discussed in this article were delivered during the 2019 calendar year.
Kombinasi Algoritma Huffman dan Algoritma ROT 13 Dalam Pengamanan File Docx

Behind this is often the theft of very important files, where they look for the files they need that they want. With no security for a title or file name, they will be very easy to find the file title they want. With the security of a file that is very important where a lot of people who are not responsible for controlling or owning the file. So this will cause a loss for the file owner if the file is known by others. The huffman algorithm is an algorithm that can be used to compress files, so that the resulting file size becomes smaller than the actual size. Huffman algorithm is a lossless compression algorithm. lossless compression algorithm is a compression technique that does not change an information from the original file. ROT13 (rotate 13) is a encryption substitution cipher that is commonly used in UNIX operating systems. In the ROT13 encryption system a letter is replaced by a letter that is located in the top 13 positions of it. With the existence of an application that implements a combination of the huffman algorithm and the ROT 13 algorithm used in the security of a docx file, making it difficult for file thieves to find the desired file
Pengembangan Aplikasi Penelusuran Alumni STAI DDI Pangkajene Sidrap Berbasis Web

This study aims (1) To develop a web-based application for tracing the alumni of the Sekolah Tinggi Agama Islam (STAI) DDI Pangkajene Sidrap. (2) To determine the application of the Web-based DDI Pangkajene Sidrap Alumni Tracing application. This type of research is research and development (R&D) using the waterfall software engineering development model, with four stages, namely analysis, design, coding, and testing. The research subjects were 35 alumni respondents. Data were analyzed using descriptive statistics in the form of data presentation with tables, calculation of means and percentages. The results of the study show that (1) the development of the application for Tracing of STAI DDI Pangkajene Sidrap alumni uses the waterfall model R&D method, the development stage begins with the analysis, design, coding, and testing stages. (2) The results of the small group trial show that the alumni tracing application is in a good category, thus it can be implemented on a larger scale. The application for tracing the alumni of STAI DDI Pangkajene Sidrap is very helpful in the process of managing alumni data and providing information about alumni data. The campus can process and coordinate its alumni.
Design of a low-cost prototype for the detection of falls in people with multiple sclerosis

Multiple sclerosis is a neurodegenerative disease that mainly affects the central nervous system, causing wear and tear on myelin in the spinal cord and manifesting itself in the form of inflammatory events, causing chronic mobility impairment and thus reducing the quality of life of people. Currently, the development of technologies for assistance is a fundamental part to improve the quality of life of people and their inclusion. Statistically, it is known that many people worldwide do not have access to technology for different reasons, such as politics and economics, the environment in which they live, which represents an obstacle to inclusion and therefore, in their development. This article presents the design of a low-cost prototype to detect possible falls, through a device to monitor sudden movements and send alerts, for people with gait disorders, mainly in advanced stages of the disease, since it is considered the moment with the most affectation and when the majority of those who suffer from it are limited to staying at home and where their personal dependence begins.
PERANCANGAN STEGANOGRAFI HIDDEN MESSAGE DENGAN METODE LEAST SIGNIFICANT BIT INSERTION (LSB) BERBASIS MATLAB

Steganography (steganography) is the science or technique of art to hide secret messages inother messages so that the existence of such secret messages can not be accessed by others who have noauthority. In terms of data security (, text or audio) should follow the appropriate 5 (five) main rules isthe factor of confidentiality, integrity, availability, authenticity, and non-repudiation. LSB algorithmmethod is a method used steganography where the process of combining messages containing text storedin a particular in this format made this research JPG and BMP with a certain pixel size. This researchresulted after the process of testing and analyzing using matrix based application (M-File, Matlab) thereis no significant change in quality (cover and stego) and text.
THE EFFECT OF GENRE-BASED APPROACH (GBA) TOWARDS STUDENTS’ NARRATIVE WRITING FOR THE 10TH GRADE OF VOCATIONAL HIGH SCHOOL 1 OF SERANG CITY (SMK PGRI 1 KOTA SERANG) (A Research of Quasi Experimental Study)

This study aims to find out the effect of genre-based approach (GBA) towards students’ narrative writing. Quantitative study, especially the nonequivalent group design (NEGD) was employed in this study. The samples were two classes of tenth grade of Vocational High School 1 of Serang City (SMK PGRI 1 Kota Serang); one class was selected as the experimental class and the other one as the control class in. The experimental class was taught by using genre-based approach, and the control class was taught by using expository learning. Pre-test and post-test were employed in this research. In the tests the students were required to write a narrative text about a fairy tale. To analyze the data T-test was used by using IBM SPSS Statistic 22 version. The hypothesis testing analysis revealed that the value of t-count at 0.05 level of significance with 68 degree of freedom was 5.682.  It means that t-count was higher than the t-table which was 2.000. It can be inferred that genre-based approach affected students’ writing in narrative text.
If you use too many H1 tags, could you harm your site’s SEO?

The potential to overuse H1 tags on a website is an SEO thought that really gained traction in the early days of the Internet when search engines did ...
Relationships between intergenerational support and the health information avoidance behavior of the elderly

Health information avoidance is prevalent amongst the elderly in China, making the understanding of the causes behind such behaviors crucial.In the face of the COVID-19 pandemic in 2020, people still lack systematic understanding and approaches to prevent the occurrence of the elderly's health information avoidance behaviors.This study groups the health information avoidance behavior of the elderly into six categories, including the trusting crisis, the behavior inertia of the elderly, the fear of uncertainty and unmeasurable risks, as well as technological barriers.It is proven through qualitative research that intergenerational support could successfully turn the elderly's information evasion into active acquisition, solving each of the six root causes of the elderly' health information avoidance behavior.Although the results in this work are collected only based on the elderly population in Shanghai, it is a thorough representation of the relationships between intergenerational support and the health information avoidance behavior of the elderly.It could serve as a reference for other cities in China as well.
Evanđeoski pristup Ivana Pavla II. migracijama kao izvoru blagostanja

Starting from the fundamental view that the Church exists in order to evangelize, John Paul II, in the light of evangelical philanthropy and solidarity, traces the Church's path in relation to the phenomenon of migration at the beginning of the third millennium. It is about pleading for the dignity of each particular man and his family, which springs from man's godlikeness. Such an attitude is uncompromisingly advocated by the Holy Father in his epistles for the World Day of Migrants. Accordingly, the Church and all its members, if they wish to remain faithful to Christ's mission, must not be blind to the cries and needs of migrants and their families, but must authentically live the truth of Christ, i.e. evangelically intervene and show solidarity, and thus in dialogue to bear witness and proclaim the fullness of salvation reserved to the Church through Christ. Migration in this sense is not a threat, but an opportunity for the progress and growth of the well-being of the human family. Consequently, the unavoidable path of the Church of the third millennium is the culture of life, i.e. the culture of welcome, family integration and humane pluralism.
On Transistor Radios and Authoritarianism

As the Philippines continues to grapple with the effects of the COVID-19 pandemic, new modalities of instruction are being devised by the administration of Rodrigo Duterte, through the Department of Education (DepEd). Among these are what the DepEd provided as self-learning modules (SLMs) combined with “alternative learning delivery modalities” which include radio-based instruction (DepEd 2020). The SLMs and radiobased instruction are the most common modalities of learning, being the most accessible especially for the poor students of the country. This paper will examine the pedagogical and political dimensions of a radio-based instruction. Coming from the tradition of philosophy of technology that emphasizes the political nature of technology, I will argue how the logic of radio broadcasting predetermines a specific pedagogy and form of communication. I will further argue how this predetermined form of communication carries the danger of being an effective support for authoritarianism.
Personalized Web Service Recommendation Method Based on Hybrid Social Network and Multi-Objective Immune Optimization

To alleviate the cold-start problem and data sparsity in web service recommendation and meet the personalized needs of users, this paper proposes a personalized web service recommendation method based on a hybrid social network and multi-objective immune optimization. The network adds the element of the service provider, which can provide more real information and help alleviate the cold-start problem. Then, according to the proposed service recommendation framework, multi-objective immune optimization is used to fuse multiple attributes and provide personalized web services for users without adjusting any weight coefficients. Experiments were conducted on real data sets, and the results show that the proposed method has high accuracy and a low recall rate, which is helpful to improving personalized recommendation.
PENYUSUNAN BUKU PENGAYAAN KELAS X BERBASIS PENELITIAN IDENTIFIKASI MAKRO INVERTEBRATE SEBAGAI BIOINDIKATOR KUALITAS AIR SUNGAI CATUR MADIUN

This study aims to determine the diversity of macroinvertebrate species and the quality of the CaturMadiun River by using macroinvertebrates as bioindicators. Researchers used a qualitative descriptive study. The method used in this study was macroinvertebratebioindicators, the technique used in taking samples was purposive random sampling technique, sampling was carried out at three stations, namely the upstream middle part and the downstream part, sampling was carried out every 2 weeks for one month. The data analysis used was the Family Biotic Index (FBI) which was supported by physical and chemical parameters. Based on the research exploratory variety of macroinvertebrates in the Catur River, 7 orders from 8 macroinvertebrate families were found. At station I, it was found that FBI = 4, 76 with a good category, polluted with some organic matter, FBI station II = 6.44 with a bad category, very much polluted, and FBI station II = 6.50 with a bad category, very much polluted. The assessment of the feasibility of the enrichment book from the material expert validator was obtained with a percentage of 72, 91% with the criteria Enough, and from the media expert validator obtained a percentage of 65% with the criteria Enough. Keywords: Enrichment book preparation, bioindicators, macroinvertebrates
On Learning Continuous Pairwise Markov Random Fields.

We consider learning a sparse pairwise Markov Random Field (MRF) with continuous-valued variables from i.i.d samples. We adapt the algorithm of Vuffray et al. (2019) to this setting and provide finite-sample analysis revealing sample complexity scaling logarithmically with the number of variables, as in the discrete and Gaussian settings. Our approach is applicable to a large class of pairwise MRFs with continuous variables and also has desirable asymptotic properties, including consistency and normality under mild conditions. Further, we establish that the population version of the optimization criterion employed in Vuffray et al. (2019) can be interpreted as local maximum likelihood estimation (MLE). As part of our analysis, we introduce a robust variation of sparse linear regression a` la Lasso, which may be of interest in its own right.
LibGuides: Ask the Right Questions: Learning Module

When looking for information, one of the first steps is to develop a research question to figure out the scope of what exactly is needed. In this lesson, students will explore what it takes to narrow a search in order to find the best information.
Optimized Load-balancing in Cloud Computing based on Traffic and Workload-aware VM Migration

In cloud storage systems, Virtual Machine (VM) migration approaches play a major function in minimizing the power usage and balancing the tasks in the data centers. Owing to the massive amount of clients and applications trying to gain from cloud service, it makes it a complex process for the edge cloud servers to operate in an energy-saving mode. Also, while maximizing the bandwidth between VMs, the chance of traffic congestion presence is increased. To solve this problem, this article proposes an Osmotic Hybrid artificial Bee and Ant Colony with Future Utilization Prediction (OH-BAC-FUP) approach to lessen the number of VM migrations and enhance the load-balancing. First, both ongoing and upcoming resource consumption of PMs and VMs are determined using Linear Regression (LR) and Optimal Piecewise LR (OPLR) schemes. The determined values are given to the OH-BAC which computes the fitness value for choosing the optimal VM to be migrated to the optimal PM. Also, this is further enhanced by proposing a Multipath Traffic Routing (MTR) called OH-BAC-FUP-MTR approach which prevents the chance of congestion while migrating VM to the PM. If any congestion exists because of high bandwidth or traffic flows, then the flows are split into many segments and transfer them via multiple link-disjoint routes. Moreover, Merge-and-Split-based Coalitional Game-theoretic (MSCG) scheme is proposed with OH-BAC-FUP-MTR approach to achieve a proper tradeoff between task reliability and power conservation in heterogeneous data centers. This MSCG is used for splitting the PMs into many sets and choosing the members from those sets to generate effective coalitions. For each coalition, OH-BAC-FUP-MTR is executed which enhances the payoff of each coalition and sustains PMs to operate in a high energy-efficient state. Finally, the simulation results reveal the OH-BAC-FUP-MTR-MSCG accomplishes better efficacy than the classical VM migration approaches.
LibGuides: Database & Book Catalog Instruction: Proquest

Information about how to use the library databases and book catalog. Information about how to use the Proquest databases
Design and Development of a Web-based Tool for Inpainting of Dissected Aortae in Angiography Images

Medical imaging is an important tool for the diagnosis and the evaluation of an aortic dissection (AD); a serious condition of the aorta, which could lead to a life-threatening aortic rupture. AD patients need life-long medical monitoring of the aortic enlargement and of the disease progression, subsequent to the diagnosis of the aortic dissection. Since there is a lack of 'healthy-dissected' image pairs from medical studies, the application of inpainting techniques offers an alternative source for generating them by doing a virtual regression from dissected aortae to healthy aortae; an indirect way to study the origin of the disease. The proposed inpainting tool combines a neural network, which was trained on the task of inpainting aortic dissections, with an easy-to-use user interface. To achieve this goal, the inpainting tool has been integrated within the 3D medical image viewer of StudierFenster (this http URL). By designing the tool as a web application, we simplify the usage of the neural network and reduce the initial learning curve.
Role of Literation in Post-Disaster Recovery

Indonesia is a country located in the Ring of or Ring of Fire on Pacific Rims, Indonesia has 13% of the total volcanoes in the world. As of 2000 various natural disasters have occurred in Indonesia. Trauma counseling is a very broad field of coverage, although professionals in systematic trauma, need to recognize the impact of trauma that contributes to the institution, culture, and society. Literacy has traditionally been understood as the ability to read and write, the ability to use language that can optimize all audio, visual and audio visual abilities. The development of language skills is reading, writing, listening, speaking, seeing, presenting, and critical thinking, linguistic intelligence skills can help carry out activities in the context of post-disaster traumatic recovery. Repairing and restoring all aspects of public or community services to an adequate level in post-disaster areas is an effort in post-disaster rehabilitation and reconstruction, apart from the physical injuries suffered by many victims of the disaster, emotionally damaged
kgbench: A Collection of Knowledge Graph Datasets for Evaluating Relational and Multimodal Machine Learning

Graph neural networks and other machine learning models offer a promising direction for machine learning on relational and multimodal data. Until now, however, progress in this area is difficult to gauge. This is primarily due to a limited number of datasets with (a) a high enough number of labeled nodes in the test set for precise measurement of performance, and (b) a rich enough variety of multimodal information to learn from. We introduce a set of new benchmark tasks for node classification on RDF-encoded knowledge graphs. We focus primarily on node classification, since this setting cannot be solved purely by node embedding models. For each dataset, we provide test and validation sets of at least 1000 instances, with some over 10000. Each task can be performed in a purely relational manner, or with multimodal information. All datasets are packaged in a CSV format that is easily consumable in any machine learning environment, together with the original source data in RDF and pre-processing code for full provenance. We provide code for loading the data into numpy and pytorch. We compute performance for several baseline models.
THE EFFECT OF YOUTUBE CONTENT MAKING ON STUDENTS’ SPEAKING SKILL

This research was aim ed to find out whether there is a significant effect of using YouTube content making on students' speaking skill. The research method of this research was experimental research in quantitative approach. The sample of this research was eleventh grade students of Madrasah Aliyah Swasta Yaspi , Labuhan Deli , w hich consisted of 80 students divided into two classes, the experimental class and the control class as sample consisting of 40 students in each class. The experimental group was taught using YouTube content making, while research involving control classes was taught using conventional techniques . Pre-test and post-test are research instruments used in collecting data . Then, the instrument used to collect data was oral test in the form of a short dialogue . The use of t-test is used to check data from research results. The significance value calculated 0.000 is smaller than 0.05 (P-value = 0.000 t table ) = (4,411>1,686). This means , that the alternative hypothesis (Ha) was accepted and the null hypothesis (Ho) was rejected . It can be concluded that the YouTube content making significantly influences students' speaking skill.