Reviewerly/exHarmony huggingface dataset:
Abstract 1396: Detection and local histological staging of prostate cancer foci in H&E whole slide images using convolutional neural networks

A pathologist’s histological diagnosis is the gold standard of prostate cancer diagnostic measures. In addition to cancer grade, the stage of cancer determines the follow-up and possible adjuvant therapies after surgery. Not only glandular pattern recognition but also the assessment of three-dimensional extent and size of cancer, in relation to the whole organ, are parts of the subjective diagnosis, which may vary among pathologists. Furthermore, evaluation of lymph nodes for any possible metastases is time-consuming and missing cancer in lymph nodes can lead to undertreatment of the patient. For the abovementioned reasons, our team is developing an algorithm that calculates the amount of cancer tissue objectively, assisting the pathologist in the diagnostic procedure. In addition, we are creating an assistant for cancer detection in lymph nodes, which are removed for histological evaluation. All in all, we aim to create a tool that will help pathologists to a better, faster, more secure and more accurate diagnosis. Our material consists of full sets of scanned whole slide images from 302 prostates that were retrieved by radical prostatectomy. After supervised learning procedure, convolutional neural networks were employed for the classification of cancerous and non-cancerous regions in the images. A tiling based approach was used in which a slide was divided into square shaped small tiles. Millions of cancerous and non-cancerous tiles were sampled from the dataset for training and validation. During the convolutional neural network training, several different tile sizes were used, i.e., 256x256, 512x512, 1024x1024 pixels. Four different types of architectures were fine-tuned and trained for the task of tile-wise binary classification, namely InceptionV3, Xception, ResNet50 and a custom convolutional neural network architecture. In our preliminary assays for cancer detection, in both pixel-wise and tile-wise evaluation, InceptionV3 performed outstandingly well with an AUC score of 0.97 and 0.951, respectively. In conclusion, our algorithm has developed very well thus far with an accuracy in cancer detection of 97%. It is not only a versatile assisting tool, aiding pathologists to a more objective, standardized and accurate diagnosis, but also serves as a second opinion in difficult and challenging diagnostic cases. Citation Format: Carolin Sturenberg, Umair Khan, Kevin Sandeman, Oguzhan Gencoglu, Adrian Malen, Andrew Erickson, Timo Heikkinen, Antti Rannikko, Tuomas Mirtti. Detection and local histological staging of prostate cancer foci in HE 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1396.
A URL with Image-based Feature Extraction for Preventing Phishing Attacks

Currently, Phishing is a type of attack in which cyber criminals tricks the victims to steal their personal and financial data. It has become an organized criminal activity. Spoofed emails claiming to be from legitimate source are crafted in a way to lead victims to reveal their personal, financial data by misdirecting them to the counterfeit website. We compared previous password protection solutions, some of the presented solutions use specialized equipment or additional servers to protect passwords. Other solutions are prone to spoofing and phishing attacks as well as introduce usability issues. Also these solutions do not address the challenge of protecting passwords against the adversary who can, for instance, exploit server-side software vulnerabilities. Our goal is enhancing the best solution to prevent phishing by alerting the users from phishing websites when detected based on URL with image-based feature extraction method.
IMPROVING STUDENTS’ VOCABULARY MASTERY USING ENGLISH SONG

This research is a Classroom Research Action. The research aims to improve the tenth grade students of SMK Wirasaba Karawang in mastering vocabulary using English songs. Songs can be trusted to help remember vocabulary and used the songs are interested in learning English. Memorizing song can be used to develop English vocabulary mastery so that the purpose of learning English as a communication tool can be achieved optimally. It can be seen from the students’ score on vocabulary test which increased from three vocabulary tests given in the Cycle I and Cycle II. In the students’ achievement Cycle I was 67.33 and Cycle II was 83.7. It can be concluded that songs have a significant impact on improving students’ vocabulary mastery. Keywords: English song, vocabulary mastery, CAR
An Analysis of Maintainability Index Influencing Metrics and Their Behavior on Similar Open Source Gaming Application Developed in C, C++ and, JAVA

Gaming is a major entertainment to the world.It plays an important role in reducing the stress of many people.Constructing a game with high Quality is an important aspect.The quality of gaming software depends on many factors such as reliability, usability, maintainability, and other factors.Maintainability is a predominant factor among them as it affects the cost of open source gaming projects.It is important to forecast the consequence of such a crucial factor ahead of releasing the games as they are nonprofitable to the developers.In this paper, we collected 25 open source gaming application developed in various programming languages with the help of visualization and statistical approach to examine the maintainability of gaming applications.OSS gaming has an acceptable level of maintainability with a vast behavioral difference between metrics.
DEVELOPING SENTENCE–BASED WRITING SYLLABUS AND INSTRUCTIONALMATERIALS FOR ENGLISH DEPARTMENT STUDENTS

Abstract : Sentence-based Writing (SBW) course introduces the students to the skill of writing in which students are taught to make grammatical sentences in the level of clause structure. However, the syllabus and the materials for this course are considered ineffective. This present study employed Research & Development (R & D) cycles for developing syllabus and instructional materials. The theories adopted for syllabus and materials were Richard’s (2001) and Tomlinson & Masuhara’s (2004), respectively. The steps were mapping materials, developing criteria and framework for evaluation and development, selecting and adapting available materials, developing necessary original materials, and designing activities. Needs analysis was conducted prior to designing syllabus by using the following instruments: documentation, questionnaire, interview, and library research. The validation and try-out displayed positive results that the products of development were appropriate to be used in classroom activities of SBW course. Keywords : Sentence-based Writing, Syllabus, Instructional Materials
KENDALA DAN TANTANGAN PENDIDIKAN BERBASIS TEKNOLOGI

Education will develop more and more, of course, supported by the existence of information and communication technology so that it becomes digital education that can support the advancement of the world of education. However, this technology-based education is still experiencing various obstacles and challenges. For example, remote areas that still lack the introduction of digital technology and networks so that there is a delay in the development of technology-based education.
PRACTICE AND FORMATION MODELS OF PROFESSIONAL ORIENTATION OF SCHOOLCHILDREN

The lack of demand on fresh graduates on the labor market and inability to interact under conditions of market relations is one of the acute problems among young generation.Life requires the ability to choose the sphere of his professional and labor activity, focusing on the needs of society and taking into account the prospects of material well-being as well as individual and personal development, i.e. ability of professional self-determination.However, the education system is not ready to provide effective assistance to high school students in choosing a profession, since the content of professional self-determination as the goal of education has not been clarified from the perspective of governmental program, there is no scientific and pedagogical foundations, professional self-determination have not been developed in terms of updating the national school.Most of the problems of professional self-determination are investigated mainly within the framework of vocational guidance, which is often regarded as an object, rather than a means of scientific management.The main goal of the article is to cope with the use of a generalized model of choosing a profession without taking into account the individual characteristics of a high school student, the lack of a differentiated approach to students with different levels of readiness for professional self-determination, as well as informational supply in the world of professions.These circumstances make it necessary to develop a dynamic model for the development of professional self-determination for senior schoolchildren.During the research it was found that up-to-date graduates need to "to try on", that is, it is important to make them familiarize with profession's 'demo-version' before making a final decision.This allows us to offer more active project activities for high school students, as well as considering the possibility of short-term internships or entity visits for graduates.
GRAMMATICAL ERROR IN WRITING DESCRIPTIVE TEXT AT SEVENTH GRADE STUDENTS OF JUNIOR HIGH SCHOOL IN CIMAHI

The purpose of this research is to find the type of grammatical error in students’ writing descriptive text made by the seventh graders of junior high school in Cimahi.The population consists of five classes, and we took 20 students to be sample. The study found out that the types of grammatical error are: Omission, Addition,Misformation and Misordering. The total of each type of error are: Omission 39.34%, Misordering 28.68%, Addition 18.03%, and Misformation 13.93%. Based on the research, it can be assumed that students usually miss to put a word like to be must appear in a well-formed sentence. And the lowest frequently of error is misformation, it is because in descriptive text there are rarely use plural words.
IMPROVING STUDENTS NARRATIVE WRITING PROCESS THROUGH SERIES OF PICTURE CLASSROOM ACTION RESEARCH

Dealing with the difficulties in writing can be carried out by implementing strategies in teaching writing. This research is done to know the benefits of using series of pictures in the process of narrative writing. It is expected that the research can be interesting and enjoyable ways. It is also expected by the teacher to know that using series of picture, the students can be stimulated to think cratively in gaining the ideas and learning the narrative writing well. The method of the research was quantitative method, or more specifically quasi-experimental design to see the effectiveness series of picture toward students ’writing skill in narrative text. The population of this reserach was twelfth grade students of SMK Negeri 1 Cijati Cianjur and the sample was class XII. The form of instrument in this research was narrative text writing test. The data was collected by using pre-test and post-test measurement on the control and experiment class and comparing the gained scores between both classes. The result presented that the picture series as media in writing narrative text is effective towards students’writing skill in narrative text. The result of calculation presented that in the significance degree of 5%,the value of t-test (to) &gt;t-table (tt) (5.514&gt; 1.992).According to the criteria of the test, the result showed that there is a significant diferrence between students’writing skill in narrative text by using picture series as media and without picture series.it means that, the picture series is effective and applicable as the media in writing narrative text.
PENGENDALIAN KEPADATAN KENDARAAN PADA TRAFFIC LIGHT MENGGUNAKAN ATMEGA8535 DAN VISUAL BASIC

Traffic light is a beacon used to arrange the traffic regularity of 4- way intersection by giving the road users some opportunities to take turn alternately. The density of vehicles in each 4-way intersection has difference level while the recent traffic lights uses the same waiting time at each intersection. It makes less effective. Ideally, the traffic lights as possible should be controlled easily and utilized efficiently to facilitate the flow of traffic at 4-way intersection. Solving the problem, the solution of traffic light optimization was provided in the form of a prototype by using the ATMEGA8535 microcontroller with two infrared laser modules and two photodiodes as a detection of the received reflection light in each intersection recently. These sensors served to determine the range of congestion levels based on the density of the vehicle. It made the waiting time be more efficient. The tools of setting programed by using Visual Basic. The results of this study were the optimizing traffic light that makes the waiting time at each intersection becomes more effective based on the density of the vehicle.
How to Prevent Bias in Self-Improving Models

One of the greatest advantages of machine learning is that models can build and update themselves without any human intervention, enabling them to respond to structural changes at the fastest possible pace. The very context requiring such self-improving algorithms (the fast change of the environment in which they operate) is also the source of a heightened risk of biases affecting the algorithm, be it self-reinforcing feedback loops like we experienced in the context of social media (Chapter 11 ) or new data that might enable the algorithm to develop a bias against a protected class.
LITERATURE REVIEW ON SENTIMENT ANALYSIS OF TWITTER DATA

Sentiment analysis is an evolving field of study which involves the process of evaluating and distinguishing the opinions or emotions expressed in a given text. Twitter promotes unregulated communication by providing an easily accessible medium where millions of people tweet everyday to contribute their thoughts and viewpoints to the world. This paper presents a review on the techniques of Sentiment Analysis on the Twitter Data. With this paper, we present a brief review of all the work done on twitter sentiment analysis so far and elaborate the models and their methodologies used. We have surveyed all the papers published in this field and focused on the recent approach so as to facilitate the development of promising avenues of future projects and research.
Hamiltonian, Lagrangian and Physical Laws

The significance of the correspondence between the classical limit of quantum theories and the laws of classical physics is explained.It is proved that this correspondence yields constraints on acceptable quantum theories.The variational principle is taken as the basis of the analysis.The discussion shows that the first order Dirac equation abides by these constraints, whereas second order quantum equations fail to do that.
Improved Multi-feature Computer Vision for Video Surveillance

Computer vision deals with automatic extraction, analysis, and understanding of information from image or video. Recent research in the area of computer vision mainly focused on developing intelligent systems for detecting and observing human behaviors. Human detection is the process of locating human automatically in an image or video sequence. This paper presents an efficient intelligent surveillance system using features, namely HAAR, local binary patterns, and histogram of oriented gradients to detect the presence of human being. Support vector machine is used to train the system. In most of the work in computer vision, researchers used different datasets and different features. This paper compares the result of the mentioned features using a common high-definition dataset. To reduce the time complexity of high-definition video, the proposed method normalized the extracted video frames into equal size. The experiments are performed on images and videos and the performance of the system is presented term of true positive rate, false positive rate, accuracy, and computation time.
Strengthening Gossip Protocols using Protocol-Dependent Knowledge

Distributed dynamic gossip is a generalization of the classic telephone problem in which agents communicate to share secrets, with the additional twist that also telephone numbers are exchanged to determine who can call whom. Recent work focused on the success conditions of simple protocols such as “Learn New Secrets” (LNS) wherein an agent a may only call another agent b if a does not know b’s secret. A protocol execution is successful if all agents get to know all secrets. On partial networks these protocols sometimes fail because they ignore information available to the agents that would allow for better coordination. We study how epistemic protocols for dynamic gossip can be strengthened, using epistemic logic as a simple protocol language with a new operator for protocol-dependent knowledge. We provide definitions of different strengthenings and show that they perform better than LNS, but we also prove that there is no strengthening of LNS that always terminates successfully. Together, this gives us a better picture of when and how epistemic coordination can help in the dynamic gossip problem in particular and distributed systems in general.
Strengthening Maritime Culture with Humanistic Value in Enrichment Books of Bahasa Indonesia

This study is aimed at (1) investigating the need for developing enrichment books of Bahasa Indonesia based on maritime culture with humanistic value; (2) developing enrichment books of Bahasa Indonesia based on maritime culture with humanistic value;and(3)presentingtheexperts’judgementontheprototypeofenrichmentbooks of Bahasa Indonesia based on maritime culture with humanistic value. This research employed Research and Development (R&amp;D) done in ﬁve steps. The results of this study are the enrichment books of Bahasa Indonesia based on the maritime culture withhumanisticvalue.Thedevelopedproductcanbeusedastheaccompanyingbook which can help the students improve their language skills.
Native Language Identification by Human Judges

This paper reports the results of two studies involving native language identification (NLI) by human judges (see Jarvis, 2012; Malmasi, Tetreault, & Dras, 2015; Odin, 1996). The first study includes six Finnish speakers who were asked to read a set of essays written in English and decide as quickly as possible whether each text was written by a Finnish or Swedish speaker. The second study includes the same six Finnish raters and an additional group of 10 Spanish-speaking raters. Both sets of raters were given 40 essays from the International Corpus of Learner English. The raters were asked to read each text carefully and indicate which texts they believed were written by native speakers of their own native languages. The results of both studies show that some of the raters were remarkably accurate in identifying the correct L1s of the writers, with accuracy rates above 80% for the top Finnish raters and over 90% for the top Spanish raters. A brief qualitative analysis of the data describes the types of features in the texts that allowed the raters to achieve such high accuracy rates. The paper concludes with a discussion of the theoretical, methodological, and pedagogical implications of these findings.
Emails and Email Crime

Email was invented way back in the 1960s but was used to a limited capacity and in a restricted manner; it only became popular by 1993. Email communication sparked the business revolution as it connected the world. Although many modern forms of communications have been invented, email still remains the most popular in the corporate world. As email communication flourished, it became an important part of our personal and professional lives. Email is an important part of e-discovery and forensic investigation, especially with the rise of cybercrime.
Using Open Source Tools to Improve DSpace Statistics

DSpace provides usage data on page views and downloads, but the accuracy of that data has been called into question. Library staff at UT Austin, despite a challenging budget, have sought to improve the communication of usage data produced in DSpace. We will discuss our use of RAMP (Repository Analytics and Metrics Portal) to improve the accuracy of the usage data gathered from DSpace and Google Analytics. We will also describe the script we wrote to aggregate RAMP statistics in spreadsheet format as well as a deep dive into our usage data. Participants will learn the pros and cons of repository usage data tools, and the skills and resources required to implement similar workflows.
Software Metrics Quality Testing (SMQT) Prediction using Logit Regression Model

Software testing is always a hot field in software engineering for both industry and academia.Traditional research focused on software quality instead of quality testing which can be evaluated through organization software testing.Previously, software testing management was based on statistical methods completely.In recent years, machine learning algorithms are developing rapidly for software quality testing management.In this reference, Logit regression (LR) model used widely in various domains like book classification, credit card investigation etc.In this research paper, the objective is to implement the Logit regression model in software testing quality management.Here, a latest metrics framework methodology is implemented for matrix testing management.Finally, the Logit regression model is testing on a financial unit data set.
THE USE OF PREDICTIONS STRATEGY IN IMPROVING STUDENTS’ READING COMPREHENSION

AbstractMany student judge that an English text is very difficult to understand. Consequently they fail to try comprehending a written text and finally they treat reading as the most avoidable activity. Based on the researcher’s observation, the students’ problem through reading comprehension appears because of some factors. The English subject is not easy for them ; they often complain when face it. This condition supports the researchers to make some appropriate learning material and good strategy to improve students’ reading comprehension. This research is aimed to improving students’ reading comprehension on the seventh grade of students at SMP Darussurur Cimahi through the use of prediction strategy. This research used quantitative research design. The population of the research was 194 students from 6 classes and the sample was 36 students from 1 class. The instrument is reading test which consist of 10 items multiple choice, and 10 items of essay. The collected data were analyzed by used SPSS. The result of the analysis showed that the mean score of pretest was 52.36. the mean score of posttest was 76.42. The result of paired samples test for t-test, the value of sig is 0. It is less than 0.05 as the significant level. Therefore, Ho (null hypothesis) is rejected. It means that predictions strategy has significant impact on students’ reading comperhension. The teacher should consider predictions strategy as the alternative technique for teaching reading.Keywords : reading comprehension,predictions strategy, quasi experimental
Improved Safety with a Distributed Routing Strategy for UAVs

This paper presents a routing strategy for UAVs that can be applied in conjunction with lower level collision avoidance methods. The strategy allows individual UAVs to route themselves in 2D space in order to avoid areas of high-density traffic. The proposed approach is explored in simulation. The results demonstrate a safer system operation when the routing strategy is used, compared with just a simple collision avoidance method.