Reviewerly/exHarmony huggingface dataset:
TEACHING STRATEGIES EMPLOYED BY ENGLISHTEACHERS IN BETA ENGLISH COURSEAT SMKN 1 POGALAN TRENGGALEK TO ENHANCE STUDENTS’ SPEAKING SKILLS

ABSTRACTRahmawati, Ana. Students Registered Number 17203163141. 2020.Teaching Strategies Employed by English Teacher in BETA EnglishCourse at SMKN 1 Pogalan Trenggalek to Enhance Students’Speaking Skills.Sarjana Thesis. English Education Department,Faculty of Tarbiyah and Teacher Training, State Islamic Institute(IAIN) Tulungagung. Guided by Dr. Nurul Chojimah, M.Pd.Keywords: Teaching Strategies, English Course, Speaking SkillsSpeaking is the most important skills should be mastered by thestudents. By having good speaking skills students will be able tocommunicate each other in teaching-learning practice and daily life. If theformal class are not enough, school might create an extra program tosupport students. Such as English course program in SMKN 1 PogalanTrenggalek.The statements of the research problem in this study are: (1) Whatstrategies are employed by the English teacher of BETA English CourseSMKN 1 Pogalan Trenggalek? (2)Is there any problem faced by the Englishteacher during the teaching-speaking in BETA English Course SMKN 1Pogalan Trenggalek? (3) How is the teacher way to overcome the problemin teaching speaking BETA English Course SMKn 1 Pogalan Trenggalek?The objective of the study are: (1) To find out the strategies employedby the English teacher of BETA English Course SMKN 1 PogalanTrenggalek? (2) To find out the problem faced by the English teacherduring teaching speaking in BETA English Course SMKN 1 PogalanTrenggalek? (3) To find out the way teacher overcome the problem inteaching speaking BETA English Course SMKN 1 Pogalan Trenggalek?This study used descriptive qualitative research method. Theresearcher collected the data by doing observation, interview, anddocumentation. The techniques of analyzing data were data reduction, datadisplay and drawing conclusion/verification..Based on the data, the teacher were employed various strategies inteaching learning process: (1) Cognitive: drilling, (2) Social : games, groupdiscussions, competition (3) Metacognitive: roleplay, outdoor activities (4)Affective: giving students motivation, games. The problem faced by theteacher in teaching speaking BETA English Course SMKN 1 PogalanTrenggalek were: (1) Classroom Management, (2) Learners Differences, (3)Problem in Motivating Students. Then, the possible solution to overcomethe problem: (1) give no response to the students who running through theclass, (2)different strategies for different type and need, (3) quiz/games andsong.
Dimensionality Reduction Techniques for High-dimensional Data in Precision Agriculture

High-dimensionality of data refers to a situation in which each data point lies in a high-dimensional space. A high-dimensional space is the one with a large number of coordinates (e.g., &gt;100). When dealing with high-dimensional data, machine learning algorithms may fail due to two major challenges. First, high-dimensional datasets usually exhibit high correlations among variables, which can cause severe model overfitting and high out-sample generalization errors if not adequately treated. Second, in many cases the number of available samples are small and are not enough to perform sensible learning without particular consideration. The second problem is known as the small N, large p p problem, where N refers to the sample size and p refers to the number of variables. These aforementioned problems are tightly related. The first problem if treated appropriately is the blessing of dimensionality and provides a solution to both challenges. That is, the correlation among variables in a high-dimensional dataset can be exploited to significantly reduce the dimension of data to a level that it is smaller than the sample size. At the same time, it alleviates the overfitting problem as a smaller number of model parameters is needed to be learned. Algorithms and techniques that are mapping high-dimensional data to a smaller space are called dimensionality reduction algorithms. These algorithms have massive applications in different areas, including manufacturing, healthcare, and agriculture.
Data Warehouse Implementation Techniques In Data Processing (Case Study Data Sales at PT Spirit Sejahtera Bersama): Data Warehouse Implementation Techniques In Data Processing (Case Study Data Sales at PT Spirit Sejahtera Bersama)

Data Warehouse is a technique that can provide a facility for the storage and management of historical data from various internal and external sources so that it can be used in making strategic decisions for the company. A characteristic that distinguishes ordinary data warehouse database was largely on the data source that can not necessarily uniform and comes from one source as happened in PT Sejahtera Bersama spirit. The company is engaged in the sale of medical equipment, up to now has more than 70 showrooms and is divided in 12 regions, of which the sales information system used by the company in each region has a separate database in excel format, this is what makes firms difficulty in the process analyzing the sales data of the company. This research aims to design and build a data warehouse system to support marketing performance assessment and achievement of sales at PT Sejahtera Bersama spirit. Data modeling methods used in the design of data warehouse in this study is the dimensional modeling star schemas. Results from this study is a web-based dashboard application that will display sales data from the data warehouse is equipped with charts and reports, and the results of tests with the method of black box testing can be seen that the system has been going well as expected. Data modeling methods used in the design of data warehouse in this study is the dimensional modeling star schemas. Results from this study is a web-based dashboard application that will display sales data from the data warehouse is equipped with charts and reports, and the results of tests with the method of black box testing can be seen that the system has been going well as expected. Data modeling methods used in the design of data warehouse in this study is the dimensional modeling star schemas. Results from this study is a web-based dashboard application that will display sales data from the data warehouse is equipped with charts and reports, and the results of tests with the method of black box testing can be seen that the system has been going well as expected.
Pengaruh Metode Permainan Crossword Puzzle Terhadap Minat Siswa Kelas XI IPS Mata Pelajaran Sejarah

The purpose of this study was to determine the positive effect of the crossword puzzle method on student interest in the history subjects of the eleventh grade social student at Xaverius Pringsewu 2018/2019 Academic Year. This research uses the experimental method. The population in this study were eleventh grade Xaverius Pringsewu High School Year 2018/2019. The sample used is the entire eleventh grade social student selected using random sampling techniques. Quantitative data analysis techniques. Data analysis test uses simple linear regression test and correlation formula. Based on the results of research and discussion it can be concluded that there is a positive influence on the crossword puzzle method of student interest in the history subjects of social students at Xaverius Prinsewu High School Year 2018/2019. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh positif pada metode permainan crossword puzzle terhadap minat siswa pada mata pelajaran sejarah kelas XI IPS di SMA Xaverius Pringsewu Tahun Pelajaran 2018/2019. Peneitian ini menggunakan metode eksperimen. Populasi dalam penelitian ini adalah siswa kelas XI IPS SMA Xaverius Pringsewu Tahun Pelajaran  2018/2019. Sampel yang digunakan adalah seluruh kelas XI IPS dipilih menggunakan teknik random sampling . Teknik analisis data menngunakan kuantitatif. Uji analisis data menggunakan uji regresi liner sederhana dan rumus korelasi.Berdasarkan hasil penelitian dan pembahasan dapat disimpulkan bahwa ada pengaruh positif pada metode permainan crossword puzzle terhadap minat siswa pada mata pelajaran sejarah kelas XI IPS DI SMA Xaverius Prinsewu Tahun Pelajaran 2018/2019. Kata kunci : crossword puzzle , minat belajar, pengaruh
XBOOK book borrowing system

The most basic library operation system, especially in school uses manila card for the borrowing and returning book. This operation seems obsolete, as the world is moving towards digitalize system. Also, the personnel to handle the operation is sometimes insufficient. With XBook Book Borrowing System, we created a concept to change the obsolete system. With the usage of usual computer parts, open-source softwares and inexpensive equipment, XBook is the economical alternatives compared to the other available book borrowing system. XBook ensures that the operation for borrowing and returning book is self-service, meaning that book borrower handle the operation themselves. We chose to use open­source softwares, compliments with web service for the operation. The system also theoretically secure, as we deployed several applications to secure it.
Are synthetic a priori propositions informative

According to rationalists, synthetic a priori propositions convey new knowledge, whereas analytic propositions are non-informative or vacuous conceptual truths. However, as we argue in this article, each a priori proposition is necessarily true because of its semantic constituents and the way they are combined, and hence can be transformed into its equivalent analytic form. So each synthetic a priori proposition conveys only non-informative conceptual truths like analytic propositions.
Gerakan Npc Pada Game Pengenalan Huruf Menggunakan Algoritma Dijkstra Dengan Perbedaan Ketinggian Pada Obstacle

Game is a play used as a medium of entertainment or for learning. In the game certainly there is a character that can not be played but the role to continue the story in the game that is NPC (Non Player Character). From previous research with the theme of NPC movement using algorithm dijkstra in game introduction of letters there is a problem if the environment obtained there is obstacle or commonly called obstacle NPC can not do the next movement if there is obstacle with a certain height. From the problem then the author intends to develop to add NPC movements with actions can pass an obstacle with the provision that the NPC can jump if the obstacle height is ¼ of the height of the NPC. In managing the NPC movement to go to the target is usually often experienced constraints as if there are various kinds of obstacles that exist around the environment sometimes NPC is difficult to determine the movement to be done. Pathfinding is a very supportive method to ease the NPC movement in finding the main target. The pathfinding accompanied by the dijkstra algorithm is perfect for giving Artificial Intelligence to the NPC. Calculate the exact algorithm with the whole area to find the closest distance to the target.
Investigating the Syntactic Structures of Patient Information Leaflets

The majority of the Malaysian people consider the Patient Information Leaflets (PILs) of their medications difficult to read and understand because of their linguistic complexity. Clear and comprehensive PILs will help the users/readers gain the benefits of these PILs. Poor and complex PILs will cause lack of adherence to the medications being used. The current study aims first, to investigate the use of command, passive voice and negation currently used in the Malaysian PILs, their frequent occurrence and their effect on readers’ comprehension. A total of 10 leaflets of the most common disease in Malaysia, which is diabetes, were tested. The analysis was done first, by applying statistical descriptive analysis to show the frequency and percentage of each syntactic structures. Second, a comprehension questionnaire was carried out with 210 participants to evaluate the reading comprehension of the users/readers based on two texts. The original text which consists of sentences taken from the PILs and the revised text, which consists of the revised sentences of the original ones. Based on the results, command scored the highest mean value than passive and negation. Additionally, the results of conducting the comprehension questionnaire showed that most of the participants chose the revised text for command, passive and negation, respectively. These results revealed that most of the participants consider the revised text easier to read and understand than the original text. In conclusion, the linguistic complexity of the PILs will prevent users/readers from utilizing the benefits of the medical information provided by these PILs.
Traffic Foreground Detection at Complex Urban Intersections Using a Novel Background Dictionary Learning Model

In complex urban intersection scenarios, due to heavy traffic and signal control, there are many slow-moving or temporarily stopped vehicles behind the stop lines. At these intersections, it is difficult to extract traffic parameters, such as delay and queue length, based on vehicle detection and tracking due to the dense and severe occlusion of vehicles. In this study, a novel background subtraction algorithm based on sparse representation is proposed to detect the traffic foreground at complex intersections to obtain traffic parameters. By establishing a novel background dictionary update model, the proposed method solves the problem that the background is easily contaminated by slow-moving or temporarily stopped vehicles and therefore cannot obtain the complete traffic foreground. Using the real-world urban traffic videos and the PV video sequences of <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>i</mi> </math> -LIDS, we first compare the proposed method with other detection methods based on sparse representation. Then, the proposed method is compared with other commonly used traffic foreground detection models in different urban intersection traffic scenarios. The experimental results show that the proposed method performs well in keeping the background model being unpolluted from slow-moving or temporarily stopped vehicles and has a good performance in both qualitative and quantitative evaluations.
Learning Generative Deception Strategies in Combinatorial Masking Games

Deception is a crucial tool in the cyberdefence repertoire, enabling defenders to leverage their informational advantage to reduce the likelihood of successful attacks. One way deception can be employed is through obscuring, or masking, some of the information about how systems are configured, increasing attacker’s uncertainty about their targets. We present a novel game-theoretic model of the resulting defender-attacker interaction, where the defender chooses a subset of attributes to mask, while the attacker responds by choosing an exploit to execute. The strategies of both players have combinatorial structure with complex informational dependencies, and therefore even representing these strategies is not trivial. First, we show that the problem of computing an equilibrium of the resulting zero-sum defender-attacker game can be represented as a linear program with a combinatorial number of system configuration variables and constraints, and develop a constraint generation approach for solving this problem. Next, we present a novel highly scalable approach for approximately solving such games by representing the strategies of both players as neural networks. The key idea is to represent the defender’s mixed strategy using a deep neural network generator, and then using alternating gradient-descent-ascent algorithm, analogous to the training of Generative Adversarial Networks. Our experiments, as well as a case study, demonstrate the efficacy of the proposed approach.
Do It by Yourself: An Instructional Derivation of the Laplacian Operator in Spherical Polar Coordinates

For scientists and engineers, the Laplacian operator is a fundamental tool that has made it possible to carry out important frontier studies involving wave propagation, potential theory, heat conduction, the distribution of stresses in a deformable solid and quantum mechanics. Knowing, understanding, and manipulating the Laplacian operator allows us to tackle complex and exciting physics, chemistry, and engineering problems. In this paper, contained in the Special Issue “Mathematics as the M in STEM Education”, we present an instructional derivation of the Laplacian operator in spherical coordinates. Our derivation is self-contained and employs well-known mathematical concepts used in all science, technology, engineering, and mathematics (STEM) disciplines. Our lengthy but straightforward procedure shows that this fundamental tool in mathematics is not intractable but accessible to anyone who studies any of the STEM disciplines. We consider that this work may be helpful for students and teachers who wish to discuss the derivation of this vital tool from an elementary approach in their courses.
Towards understanding privacy trade-off in an epidemic

Although the COVID-19 is still as complicated as ever, it is a significant job for private networks across the globe to gather and share data in the light of the battle against coronavirus. The sca...
Design and implementation of efficient Learning platform based on SpringBoot Framework

With the development of Internet technology, the demand for people's information exchange is getting higher and higher, and the traditional way of communication can no longer meet the needs of students. In order to improve the efficiency of information exchange, this paper uses a progressive framework, such as SpringBoot and Vue framework, these frameworks are easy to develop and maintain. According to these technologies, this paper designs a learning exchange community system for college students to learn and communicate. First of all, we analyze the research background and research status of learning community. Then, we analyzed the requirements of the system, including system function, performance and security requirements, and carried out the overall design of the system. The whole system is divided into several modules for development, and the specific module content is designed in detail, and the corresponding system functions are realized by using development tools. Finally, we use the black box to test the function, performance and security of the system.
Subword Mapping and Anchoring across Languages.

State-of-the-art multilingual systems rely on shared vocabularies that sufficiently cover all considered languages. To this end, a simple and frequently used approach makes use of subword vocabularies constructed jointly over several languages. We hypothesize that such vocabularies are suboptimal due to false positives (identical subwords with different meanings across languages) and false negatives (different subwords with similar meanings). To address these issues, we propose Subword Mapping and Anchoring across Languages (SMALA), a method to construct bilingual subword vocabularies. SMALA extracts subword alignments using an unsupervised state-of-the-art mapping technique and uses them to create cross-lingual anchors based on subword similarities. We demonstrate the benefits of SMALA for cross-lingual natural language inference (XNLI), where it improves zero-shot transfer to an unseen language without task-specific data, but only by sharing subword embeddings. Moreover, in neural machine translation, we show that joint subword vocabularies obtained with SMALA lead to higher BLEU scores on sentences that contain many false positives and false negatives.
The Relation of Investment Incentives and Inflow of FDI: Case of Developing Countries and Ethiopia

For economic, Social, or foreign direct investment promotion reasons, tax exemptions or incentives are common under tax laws of legal system of different nations.Under Ethiopian stamp duty laws, some areas of foreign investments are exempted from the liability of payment of same; documents that are exempted in accordance with international agreements and conventional treaties approved by Ethiopian government.The objective of this study article is to show the relationship between incentives and foreign direct investment inflows in developing countries and the Ethiopian context.The thesis employs research methodology that follows conceptual and legal analyses and interpretation in a comparative manner.The meaning and nature of investment incentives under Ethiopian investment laws and other jurisdiction, determinant factors driving and influencing the inflows of FDI under developing counties and Ethiopia are discussed.The dominant model of low income countries/developing countries investment incentive i.e. tax exemption and tax holiday's contribution and effectiveness in the attracting of FDI, and various economics researchers findings on the relationship between income tax incentives and FDI inflows are critically analyzed with the various laws and Ethiopian investment laws.Finally from the findings of different data we can conclude that weak investment climate cannot back up by providing tax incentives to attract FDI in developing countries and Ethiopia.The findings of the study revealed that tax incentive packages that are employed to attract FDI in developing countries are not in a position to accommodate and fulfill the comprehensive driving factors of the FDI and the interest of investors and host states.
Condenser: a Pre-training Architecture for Dense Retrieval.

Pre-trained Transformer language models (LM) have become go-to text representation encoders. Prior research fine-tunes deep LMs to encode text sequences such as sentences and passages into single dense vector representations for efficient text comparison and retrieval. However, dense encoders require a lot of data and sophisticated techniques to effectively train and suffer in low data situations. This paper finds a key reason is that standard LMs’ internal attention structure is not ready-to-use for dense encoders, which needs to aggregate text information into the dense representation. We propose to pre-train towards dense encoder with a novel Transformer architecture, Condenser, where LM prediction CONditions on DENSE Representation. Our experiments show Condenser improves over standard LM by large margins on various text retrieval and similarity tasks.
PGD-Optimized Patch and Noise Joint Embedded Adversarial Example for Faster RCNN and YOLOv4

Faster RCNN and YOLO have stable and outstanding performance as the state of the art and widely used object detectors in real applications. However, some researches and security incidents show that Faster RCNN and YOLO can be attacked by adversarial examples, resulting in errors or invalid detection results. According to the existing attack methods on computer vision, the imperceptible perturbations embedded into the initial images can be categorized into noise disturbance and patch disturbance. In this paper, we proposed an attack method that combines the advantages of the two categories. Our attack is based on PGD iterative attacks and patch optimization. We can attack Faster RCNN and YOLOv4 successfully in less time. And the adversarial examples generated are similar to the original images, which make the attack more stealthy.