Reviewerly/exHarmony huggingface dataset:
Keep Your AI-es on the Road: Tackling Distracted Driver Detection with Convolutional Neural Networks and Targeted Data Augmentation.

According to the World Health Organization, distracted driving is one of the leading cause of motor accidents and deaths in the world. In our study, we tackle the problem of distracted driving by aiming to build a robust multi-class classifier to detect and identify different forms of driver inattention using the State Farm Distracted Driving Dataset. We utilize combinations of pretrained image classification models, classical data augmentation, OpenCV based image preprocessing and skin segmentation augmentation approaches. Our best performing model combines several augmentation techniques, including skin segmentation, facial blurring, and classical augmentation techniques. This model achieves an approximately 15% increase in F1 score over the baseline, thus showing the promise in these techniques in enhancing the power of neural networks for the task of distracted driver detection.
library.SCOTCH: The Book Thief: Related Reading

This research guide has been created for Year 11 students studying The Book Thief. Through close reading, students develop the ability to analyse and evaluate the purpose, stylistic qualities and conventions of texts.
A comparison of training algorithms when training a Convolutional Neural Network for classifying road signs

This thesis is a comparison between three dierent training algorithms when training a Convolutional Neural Network for classifying road signs. The algorithms that were compared were Gradient Descen ...
SENTIMENTAL ANALYSIS USING TWITTER

With the abrupt growth in technology the use of social media increases day by day, users share and exchange their emotions and opinions on day to day basis on the social websites. Twitter is one of the social websites where daily users post tweets with their emotions and opinions which are necessary for the development. To express the correct sentiment and overall opinion of a large number of tweets the process of sentiment analysis is done. It analyses the sentiment of each tweet and gives the overall output whether the sentiment of the person about the tweet is positive, neutral or negative. It identifies the correct sentiment of each word and analyses the emotions and opinion from the text. It explores how text analysis techniques can be used to dig some data on different trends of tweet languages. The data collected from the tweets is filtered according to the userÂs requirement. So, content filtering is done to show only interest related posts. The continuous analysis of live and latest tweets is analyzed correctly which gives a highly accurate model with respect to the latest reviews. By gathering a large number of tweets, live data is processed and correct sentiment of the data is analyzed which expresses the opinion of the mass in this huge platform. Usually, words with the same meaning all the variants of the label rather than the exam same label are not classified accurately, therefore the label within the data set is analyzed by Naive Bayes which improves the classification of the tweets considerably.
Genetic Algorithms in Action

This chapter illustrates the use of genetic algorithms by solving a number of difficult algorithmic problems. Most of the problems presented in this chapter involve some arithmetic operations and therefore have a mathematical flavor.
Labeling Explicit Discourse Relations using Pre-trained Language Models.

Labeling explicit discourse relations is one of the most challenging sub-tasks of the shallow discourse parsing where the goal is to identify the discourse connectives and the boundaries of their arguments. The state-of-the-art models achieve slightly above 45% of F-score by using hand-crafted features. The current paper investigates the efficacy of the pre-trained language models in this task. We find that the pre-trained language models, when finetuned, are powerful enough to replace the linguistic features. We evaluate our model on PDTB 2.0 and report the state-of-the-art results in the extraction of the full relation. This is the first time when a model outperforms the knowledge intensive models without employing any linguistic features.
Development Of Competencies Through Non-Formal Activities

Nonformal activities are based on student-centered educational strategy objectives. The used content, methods and instruments are student-centered, differentiated according to the children's capacities and interest. Activities are flexible, optional and complementary to formal education and help to develop personality, creativity and competencies. The residence area, drop-out, assessments' results, nonformal activities are factors influencing the students' progress, personality and key competencies development. Extracurricular student-centered activities within the Children's Palace focus on developmental aspect of learning by identification of the efficient organizational ways of the students' activities. Choosing the appropriate extracurricular activities in order to acquire knowledge, to form skills, abilities and attitudes that should help with the integration in a modern society has a close relationship with the children's gender and residence area. Present questionnaire researches the role, importance and complementarity of extracurricular activities seen from the children's perspective. Through the answers we can realize a correlation between the results, drop-out and extracurricular activities. These activities assist the children to develop personality, research the learners' opinion on the interactive student-centered extra school activities. The study has been realized with an online questionnaire on a national level among primary, secondary, upper secondary children (N=3945). The results show us the importance of non-formal activities that besides formal education help to improve the results and to develop competencies. The study helps in analysing the strengths and weaknesses of non-formal education, the results enlighten us about the requirements of children and about the use of the student-centered educational strategy in obtaining better results.
Automatic Pilot Ship Route Planning Based on A RRT Guided Genetic Algorithm

Abstract The reasonable and optimized navigation for an automatic pilot ship is one of the key technologies in ship bridge system. In this paper, a genetic algorithm based path planning method is introduced for this kind of problem. In order to build efficient chromosome to improve the searching efficiency, before the planning procedure of the GA, a traditional but efficient fast searching method - RRT is utilized to give a clue to build the chromosomes. In this paper, at first, a searching area is constructed based on the result of RRT and secondly, a GA based planning algorithm is proposed for the ship to find a path from the start to a target. The fitness function and genetic operator are selected by roulette to ensure the robustness of genetic algorithm. The diversity of population is enhanced by two point crossover operators. Finally, the simulation results show the effectiveness of the proposed algorithm.
Dissecting Deep Networks into an Ensemble of Generative Classifiers for Robust Predictions.

Deep Neural Networks (DNNs) are often criticized for being susceptible to adversarial attacks. Most successful defense strategies adopt adversarial training or random input transformations that typically require retraining or fine-tuning the model to achieve reasonable performance. In this work, our investigations of intermediate representations of a pre-trained DNN lead to an interesting discovery pointing to intrinsic robustness to adversarial attacks. We find that we can learn a generative classifier by statistically characterizing the neural response of an intermediate layer to clean training samples. The predictions of multiple such intermediate-layer based classifiers, when aggregated, show unexpected robustness to adversarial attacks. Specifically, we devise an ensemble of these generative classifiers that rank-aggregates their predictions via a Borda count-based consensus. Our proposed approach uses a subset of the clean training data and a pre-trained model, and yet is agnostic to network architectures or the adversarial attack generation method. We show extensive experiments to establish that our defense strategy achieves state-of-the-art performance on the ImageNet validation set.
An Amorphous 2-Dimensional Barcode

Most existing 2-dimensional barcodes are designed with a fixed shape and clear area. Having a fixed shape and clear area makes the barcode difficult to lay out with other text and pictures. To solve this problem, an amorphous 2-dimensional barcode is presented in this paper. The barcode uses encoding graph units to encode data. There are two key points in a 2-dimensional barcode: One is the encoding graph unit, the other is its encoding rules. Because encoding graph units of a 2-dimensional barcode are surrounded by other graphics, the units should be self-positioned and distinguished from other units. This paper presents an encoding graph unit generation algorithm, which is based on genetic algorithms. Encoding rules of the barcode are also given in this paper. Those rules include data encoding rules and encoding graph unit sequence arrangement rules. Data encoding rules are used to encode data to an encoding graph unit sequence. Encoding graph unit sequence arrangement rules are used to embed the unit sequence in the target picture. In addition to those rules, it also discussed the steps to restore encoding graph unit sequence from a picture. In the experiments section of this paper, an example is provided to encode a string and embed it in a car ad picture by the barcode. According to encoding rules of the barcode, those encoding graphic units can be scattered and embedded in a picture with other graphics, so amorphous 2-dimensional barcode has no fixed shape. Take advantage of this, designer can present a more elegant design to lay out barcodes with other graphic elements.
Thresholding Comparison Display Using Graphical User Interface (GUI) with Mobile Notification

Abstract Thresholding is a sort of image division that separates protest apportioning an image into a closer view and foundation. The fundamental utilization of image division are medical imaging, object discovery and recognition tasks, content-based image recovery, video surveillance, and automatic traffic control systems. The objective of the thresholding method is to simplify an image into something that is easier to examine. By using MATLAB R2017b as its core programming software, the image will be separated by unused background with uncertainty. This project will describe a few selected thresholding methods such as Fuzzy C-Mean Algorithm’s method, Wolf’s method, Bradley’s method, Bernsen’s method, Triangle’s Method and Deghost’s Method. Each method will experiment with medical and document images. The thresholding method will undergo image quality analysis such as Sensitivity and Specificity. This process is using Graphical User Interface (GUI) and sending messages to phones with Global System for Mobile Notification (GSM) modems is implemented with the aim of allowing researchers to know the best methods by the ease in a convenient manner. This message can send the receiver any time, users only insert telephone number to send their message.
APLIKASI ROF TOTAL VARIATION MENGGUNAKAN SPLIT BREGMAN UNTUK MENGURANGI NOISE PADA GAMBAR PEMBULUH DARAH KAPILER DALAM JARI MANUSIA

An image might have noises that could lose important information on that image. As a consequence, we need a consistent method to reduce the noise without erasing the important information. In this paper, ROF Total Variation using Split Bregman is applied to the image to reduce the noise. We choose the monochrome image of the human capillaries on the fingertips.
Rancang Bangun Sistem Informasi Registrasi Dan Keanggotaan Komunitas Motor XMAN Kuningan Menggunakan PHP Dan MYSQL

The XMAN Kuningan community is a community of Yamaha NMAX motorcycle users in Kuningan Regency. The members of this community are Kuningan Regency people who own Yamaha XMAN Motorcycles. To be able to become a member of this community, prospective members must meet the predetermined requirements, that is, they are willing to obey the rules in this community, free from drugs and illegal drugs, and are willing to protect the good name of the community. Any community in Kuningan Regency who is a Yamaha NMAX motorbike driver can become a member of the Kuningan XMAN Motorcycle Community by registering themselves to the secretariat of the XMAN Kuningan Motorcycle Community. To register sometimes prospective members find it difficult to find the location of the XMAN Kuningan Motor Community secretariat. Likewise with prospective members who are far from the secretariat location will require time and money to come to the secretariat so that many Yamaha NMAX motorcycle owners are reluctant to come directly to the secretariat because they do not have enough time to come directly to the secretariat. a registration information system that is made web-based, using the programming language PHP and MySQL as its database and using the Waterfall system development method. This study aims to establish the process of recruiting members of the XMAN Kuningan Motor Community and facilitate the registration of registered members.Keywords: Waterfall, Management of registration registration, Web, PHP and MYSQL programming
ISSUES AND CHALLENGES IN THE USE OF GEOGEBRA IN TEACHING AND LEARNING OF MATHEMATICS IN SECONDARY SCHOOLS IN MAKURDI METROPOLIS

This research work examined the issues and challenges in the use of GeoGebra in teaching and learning of Mathematics in Secondary Schools in Makurdi metropolis. Survey research design was adopted for the study. The population of 190 students and 10 teachers were used as respondents for the study. The researcher used both primary and secondary sources obtained by the use of a well structured questionnaire. The data collected were analyzed using descriptive statistics such as frequency, simple percentages. Confirmatory factor analysis was used for to test the validity of the instrument while the Cronbach Alpha Coefficient was used to establish the reliability of the instrument. The result of the study showed that unavailability or no computer is the major challenges preventing teaching and learning of Mathematics in the selected Secondary Schools in the study area this is followed by low teacher competence as one of the challenges preventing the use of GeoGebra in the teaching and learning of Mathematics in the selected Secondary Schools in the study area. Unavailability of GeoGebra software and erratic power supply are some of the factors. It was concluded that with the availability of dynamic mathematics software, like GeoGebra, teachers will be able to make graphical representations of mathematics concepts and thus present difficult concepts in a very clear and unambiguous manner. It was recommended among others that Policy makers and school authorities should consider the acquisition of computer and GeoGebra software so that they can improve on the level of comprehension of mathematics being taught in school.
Research Guides: Marketing: Data Services

Access NYU Libraries' marketing and advertising resources. Data services and links to marketing analytics resources
Fingerprint Smoothing Using Different Interpolation Techniques

Classical fingerprint analysts use binary images in the minutiae recognition and extraction processes. These obtained images do not have a sufficient quality that allows the extraction of the robust primitives, either during the contours detection or during skeletonization. In this study, a mathematical approach for the fingerprint curves modeling have been performed. The adopted smoothing technique is based on two geometric interpolation types adapted to fingerprint images. The obtained results reveal that the Bezier curve method has an error lower than that by the cubic spline method. The Bézier curve method has a RMS value of 0.035 pixels and an average maximum error of the order of 0.33 pixels. On the other hand, the cubic spline method has a RMS value about of 0.043 pixels and an average maximum error about of 0.37 pixels. We can see that the proposed method facilitates the design process of real-world objects and makes the fingerprint curves smooth.
Proxy-Hedging of Bitcoin Exposures With Altcoins

The aim of this research is to explore the associated risks with hedging in cryptocurrencies markets. It focuses on finding the most effective proxy hedge instrument for the Bitcoin-USD market. Due to its particularities, this market does not exhibit the same features as traditional financial markets do. In appearance, it seems very related to other altcoins (alternative coins), but in reality, it exhibits unusual volatility clustering effects. This behaviour has a direct impact on the hedging strategies of business exposed to crypto-currencies, including the hedge funds, mining farms or ICO projects. The paper explores the econometric features of Bitcoin and other Altcoins and underlines the need for fat tail distributions and volatility clustering models. Also, it examines the density forecasting capacity of various proxy hedge instruments including Bitcoin, Bitcoin Cash and Ether exchange rates
LibGuides: ENG 101: Find Books

This course guide is designed to help students with their research in English 101 How to find books
Sosialisasi dan Simulasi Tanggap Bencana Gunung Meletus dan Banjir Desa Sumberagung Kecamatan Gandusari

Geographically, Sumberagung Village is located near an active volcano, Kelud Mountain. With such geographical conditions, it is very possible that natural disasters occur, ranging from volcanic natural disasters and cold lava floods in the Kali Putih River Region. With the frequent occurrence of disasters it is necessary to increase the readiness in dealing with disasters in the Sumberagung Village community, it is very necessary to conduct socialization to provide insight and knowledge to the community. The method used is to conduct direct socialization in the field, giving questionnaires, and coupled with literature studies from various sources, to conduct socialization to elementary / MI students in Sumberagung Village, Gandusari District, Blitar Regency. To improve disaster response and be smart in absorbing information on elementary / MI children as an early step, it is very necessary to socialize and simulate the SD / MI children in Sumberagung Village. The entire community and SD / MI students in Sumberagung Village have a very good response to the socialization activities and disaster response simulations that have been carried out, so that they are ready to assist and support the installation of placards for evacuation routes in Sumberagung Village, Gandusari District, Blitar Regency.
Proof Complexity of Substructural Logics

In this paper, we investigate the proof complexity of a wide range of substructural systems. For any proof system $\mathbf{P}$ at least as strong as Full Lambek calculus, $\mathbf{FL}$, and polynomially simulated by the extended Frege system for some infinite branching super-intuitionistic logic, we present an exponential lower bound on the proof lengths. More precisely, we will provide a sequence of $\mathbf{P}$-provable formulas $\{A_n\}_{n=1}^{\infty}$ such that the length of the shortest $\mathbf{P}$-proof for $A_n$ is exponential in the length of $A_n$. The lower bound also extends to the number of proof-lines (proof-lengths) in any Frege system (extended Frege system) for a logic between $\mathsf{FL}$ and any infinite branching super-intuitionistic logic. We will also prove a similar result for the proof systems and logics extending Visser's basic propositional calculus $\mathbf{BPC}$ and its logic $\mathsf{BPC}$, respectively. Finally, in the classical substructural setting, we will establish an exponential lower bound on the number of proof-lines in any proof system polynomially simulated by the cut-free version of $\mathbf{CFL_{ew}}$.
PEMBUATAN GAME RUNAWAY FROM CULIK DENGAN ALGORITMA FUZZY MAMDANI

The game comes from an English word that has the basic meaning of the game. Games have a type or can be called a genre, the function of the game genre is used to classify a game based on how the interaction of the game. Endless runner is a genre in the game. Endless runner games generally have a game system where players must avoid an obstacle and get as many scores as possible. At this time many games are endless runners, but there are no endless runner games with a kidnapper theme and a speed system that uses algorithms. Mamdani fuzzy algorithm is a Fuzzy inference method for rules represented in the form of If-Then where the system output is not a Fuzzy set but a constant or linear equation. In this study, the Mamdani fuzzy algorithm is applied to the conditions at which obstacles appear. With the Mamdani fuzzy algorithm a speed system can be made. In making games a game development method is also needed, so that the stages of development are clearer and as expected. For this research, the game development method used is the Game Development Life Cycle (GDLC) development model. GDLC is a game development process that adopts an iterative approach consisting of 6 development phases, starting from the initialization / concept making phase, preproduction, production, Testing (Alpha testing, Beta testing), and realease. From the 6 phases it can be grouped into 3 main processes, namely: Initialization Process which consists of concepts and designs, Production process consists of Pre Production, Production, and Testing consisting of Alpha Testing and Beta Testing, the last is Realease. Keywords : Games, Endless runner, Fuzzy Mamdani Algorithm, Game Development Life Cycle (GDLC).
Library Anxiety Among Students: A Descriptive Study

Students generally experience library anxiety related to library collections and staffs, application of library technologies, atmosphere around the library, and process of finding information. This phenomenon occurs due to the limitations of knowledge. This study aims to determine the description of library anxiety among students by using the MLAS (Multidimensional Library Anxiety Scale). This study used quantitative methods with survey descriptive research format. Data were collected through observation and interviews using questionnaire. The research sample was 84 students that were selected using purposive sampling. The variables that were studied were: comfort and confidence when using the library, the information search process and general Library Anxiety, perceived barriers with staff, perceived importance of understanding how to use the library, comfort with technology with applications to using the library, and comfort level while inside the library building. Data analysis used descriptive quantitative research analysis. The results showed that the dimension of comfort and confidence when using the library had an average of 2.46. From the dimension of perceived barriers with staff, an average of 2.69 was obtained. Meanwhile, the dimension of perceived importance of understanding how to use the library had a low average score, which was 2.52. The dimension of comfort level with technology with applications to using the library also obtained low average score (2.50). Furthermore, the dimension of the comfort level while inside the library building had an average of 2.14.
Virtual reality, augmented reality and mirror therapy for musculoskeletal pain: a systematic review

Key-Words: virtual reality, mirror therapy, MSK pain