Reviewerly/exHarmony huggingface dataset:
FIR-based Future Trajectory Prediction in Nighttime Autonomous Driving

The performance of the current collision avoidance systems in Autonomous Vehicles (AV) and Advanced Driver Assistance Systems (ADAS) can be drastically affected by low light and adverse weather conditions. Collisions with large animals such as deer in low light cause significant cost and damage every year. In this paper, we propose the first AI-based method for future trajectory prediction of large animals and mitigating the risk of collision with them in low light. In order to minimize false collision warnings, in our multi-step framework, first, the large animal is accurately detected and a preliminary risk level is predicted for it and low-risk animals are discarded. In the next stage, a multi-stream CONV-LSTM-based encoder-decoder framework is designed to predict the future trajectory of the potentially high-risk animals. The proposed model uses camera motion prediction as well as the local and global context of the scene to generate accurate predictions. Furthermore, this paper introduces a new dataset of FIR videos for large animal detection and risk estimation in real nighttime driving scenarios. Our experiments show promising results of the proposed framework in adverse conditions. Our code is available online.
TC-VAE: Uncovering Out-of-Distribution Data Generative Factors

Uncovering data generative factors is the ultimate goal of disentanglement learning. Although many works proposed disentangling generative models able to uncover the underlying generative factors of a dataset, so far no one was able to uncover OOD generative factors (i.e., factors of variations that are not explicitly shown on the dataset). Moreover, the datasets used to validate these models are synthetically generated using a balanced mixture of some predefined generative factors, implicitly assuming that generative factors are uniformly distributed across the datasets. However, real datasets do not present this property. In this work we analyse the effect of using datasets with unbalanced generative factors, providing qualitative and quantitative results for widely used generative models. Moreover, we propose TC-VAE, a generative model optimized using a lower bound of the joint total correlation between the learned latent representations and the input data. We show that the proposed model is able to uncover OOD generative factors on different datasets and outperforms on average the related baselines in terms of downstream disentanglement metrics.
Analysis of Total Electron Content Over the African Low-Latitude Region During the Maximum of Solar Cycle 24 (2012-2014)

This study examined the ionospheric variation over the African low-latitude region using Total Electron Content (TEC) and its wavelet power spectrum (WPS). TEC data were obtained from five Global Positioning System (GPS) stations located in the trough and crests of the equatorial ionization anomaly (EIA) in both hemispheres during quiet periods of the maximum phase of solar cycle 24 (2012-2014). Our results revealed a striking equinoctial asymmetry with stronger TEC in September equinox than March equinox of 2012 to 2013 with the reverse being the case in 2014. This equinoctial asymmetry might have been driven by the difference in the ExB drift velocity, O/N2 and thermospheric temperature. Furthermore, we found a hemispheric asymmetry in TEC with higher value towards the crest in the northern hemisphere (southern hemisphere) in September equinox (March equinox) of 2012 to 2013. In 2014, nevertheless, TEC was strikingly higher towards the crest located in the southern hemisphere in September equinox only. This hemispheric asymmetry during equinox may have been modulated by the direction of meridional wind in addition to the location of the magnetic equator in the northern hemisphere over Africa. The chaotic time series methods were used to examine the TEC variation. It was observed that ADIS within the magnetic equator exhibit minimum value of Lyapunov exponents (LE) during the quiet days of the ionosphere. The variations in the internal dynamics of the ionosphere have impacts on chaotic behavior. The ionospheric conductivity and ionospheric vortices might have impact on low latitudes due to the atmospheric heating effects.
Additional Learning for Joint Probability Distribution Matching in BiGAN

Bidirectional Generative Adversarial Networks (BiGANs) is a generative model with an invertible mapping between latent and image space. The mapping allows us to encode real images into latent representations and reconstruct input images. However, from preliminary experiments, we found that the joint probability distributions learned by the generator and the encoder are inconsistent, leading to poor-quality mapping. Therefore, to solve this issue, we propose an architecture-agnostic additional learning method to make the two joint probability distributions closer. In the experiments, we evaluated the reconstruction quality on synthetic and natural image datasets and found that our additional learning improves the invertible mapping of BiGAN.
Code Switching and Code Mixing in the Teaching Process: A Case Study at Rainbow School of Joy in Medan

The objectives of this study were to find out the types and factors of code-switching and code-mixing done by the teachers in the teaching process and to reveal why teachers switched and mixed the utterances. It was conducted using a descriptive qualitative research method. The objects of this study were Mathematics, Science and English teachers at Rainbow School of Joy in Medan. The data were collected by video recording the teachers' utterances during the learning to find out types and factors of code-switching and code-mixing and by interviewing the teachers to reveal why they switched and mixed the codes. Data were analysed by using Cohen's technique (2018). The study's findings showed the teachers' most frequent types of code-switching were inter-sentential. The total is 46 types with a percentage of 18%. The most frequent types of code mixing were insertion (word phrase). The accommodation is 49 types, with a rate of 19%. The most frequent factor of the teachers doing the code-switching and mixing was talking about a particular topic. The total is 52, with a percentage of 21%. Finally, the most frequent reason was the genre. The accommodation is 12, with a rate of 27.2%.
A simplified approach for the design and implementation of Handmade ceramic product with a distinctive historical identity

This research can be summarized as a serious attempt to a strategy for obtaining handmade ceramics with distinctive features of historical ceramics in different historical eras, which in turn confirmed the identity. Research problem: The research problem is the following: 1- Are handmade products with a distinctive character for identity available? 2- How to obtain handmade ceramic products of a historical nature.
Selected Topics of Artificial Intelligence in Robotics

The paper is focused on the selected area of artificial intelligence (AI) applications, and presents only two examples relating to robotics and robotic systems. It is particularly interested in swarm intelligence method applied to path planning problems, and machine and deep learning approaches to anomaly detection. Based on existing methods of AI, we discuss important aspects for the application of AI technologies to view some research problems from robotics perspective.
Feature Extraction for Big Data Using AI

Internet around the world is producing loads of data every second in different ways, the speed of this information is being spread across the corners of the globe in very few seconds. A multi-feature information retrieval approach is utilized, and predicated on this, an ai - powered big data MFE scheme is intended, with the regular news framework as an application example, where it would be expanded, and necessary analysis is performed. This method is taken to the algorithm design of hot event identification using a news article as the sender. As a result, a twostage multi-function fusion clustering l. To analyze keywords, a multi-functional fusion model is created in the first step, which combines word frequency and a part of speech attribute. We use it to extract keywords that describe current events and news.
Learning to Learn Task Transformations for Improved Few-Shot Classification

Meta-learning has shown great promise in few-shot image classification where only a small amount of labeled data is available in each classification task. Many training tasks are provided to train a meta-model that can quickly learn new and similar concepts with few labeled samples. Data augmentation is often used to augment training tasks to avoid overfitting. However, existing data augmentation methods are often manually designed and fixed during training, ignoring training dynamics and the difference between various meta-learning settings specified by meta-model architectures and meta-learning algorithms. To address this problem, we add a task transformation layer between a training task and a meta-model such that the right amount of perturbation is added to training tasks for a certain meta-learning setting at a certain training stage. By jointly optimizing the task transformation layer and the meta-model, we avoid the risk of providing tasks that are either too easy or too difficult during training. We design the task transformation layer as a stochastic transformation function, adding the flexibility in how a training task can be transformed. We leverage differentiable data augmentations as the building blocks of the task transformation function for efficient optimization. Extensive experiments show that our method can consistently improve the few-shot generalization performance of various meta-models trained with different meta-learning algorithms, meta-model architectures, and datasets.
Formalizing Requirements Through Use Cases

When you get ready to leave on a vacation, you may run through a mental or written checklist to make sure that you’ve properly prepared for your departure. Did you pack everything you need to take? Did you pack too much? Did you arrange to have the appropriate services (newspaper, mail delivery, etc.) stopped? Did you arrange for someone to water the plants and feed your pet rat? Once you depart on your trip, you want to enjoy yourself and know that when you arrive home again, you won’t find any disasters waiting for you.
Rancang Bangun E-Learning Pelajaran Produktif Multimedia Dan Pemasaran Pada Smk Karsa Mulya Kota Palangka Raya

The Electronic E-learning System for Productive Multimedia and Marketing Lessons at Karsa Mulya Vocational High School, Palangkaraya City, was built for convenience for teachers and students who during this time the learning process is always limited when studying in the room. In the process of designing an E-learning system for productive lessons in Multimedia and Marketing at SMK Karsa Mulya, Palangkaraya City, using the Waterfall Method according to Sommerville (2011: 29-30) which is divided into several stages, namely Analysis and definition of needs, system design and software, implementation and unit testing, system integration and testing, operation and maintenance. In the analysis and design stage the writer conducted a survey, interview and discussion with the school to find options and solutions for what features would be designed next and this analysis stage also made a flowchart, then used the programming language THML, PHP, CSS, Bootstrap, JavaScript and MySQL as the database creation. Then implemented into an E-learning website, which is carried out in the testing phase using a Blackbox. From the results of research that has been carried out by the author implementing the results of this study in the E-learning system of Productive Multimedia and Marketing lessons at SMK Karsa Mulya, Palangka Raya city. The output produced by this system is in accordance with the expected criteria and objectives, obtained an accuracy of 72.7% with a system error value of 27.2% in testing system results.
Aplikasi Sistem Pencatatan Keuangan Berbasis Website

Financial management is a company activity related to how to obtain funds, use funds, and manage assets in accordance with the overall company goals. Financial management is quite complicated because it contains calculations to support a more structured financial system. However, currently there are still many who use the financial system manually and do not use technology such as websites or applications. Waterfall software development method. For the manufacture of the software Sublime Text 3 software as the code. The DBMS (Database Management System) used in this application system is MySQL. The programming languages used are HTML, PHP, CSS, and JavaScript. Based on the results of testing using the blackbox method, it was found that this financial system application was running well.
Rancang Bangun Website Desa Sebagai Media Informasi Pengenalan Potensi Desa Tumbang Manjul

Tumbang Manjul Village is a remote village located in the forest in Seruyan Hulu District, Seruyan District, Central Kalimantan Province. Tumbang Manjul Village has a lot of potential that must be known by the community so that Tumbang Manjul Village can be recognized. With this potential, the village of Tumbang Manjul can also contribute to the community outside the village to take advantage of the results of the village. Based on the background provided, a Village Website Design was made as an Information Media for Introducing the Potential of Tumbang Manjul Village, Seruyan Hulu District, Seruyan Regency, Central Kalimantan Province so that it could facilitate the village of Tumbang Manjul to promote the village's potential. The methodology used in making this village website is the waterfall method with stages, namely Requirement Analysis described using a Flowchart, System Design described through DFD (Data Flow Diagram), ERD (Entity Relationship Diagram), and database. Implementation with the programming languages ​​used, namely HTML, PHP, CSS, Bootstrap Javascript, and MySQL. The final stage is Testing using the Blackbox Method. On this website there are several features, namely the village government, facilities, village potential, and contacts that can be accessed by website visitors with the aim that visitors can view information about the village of Tumbang Manjul. This website is also managed by an admin who has the right to manage data on the Tumbang Manjul village website.
OPTIMALISASI BUDAYA LITERASI MELALUI KOMUNITAS SASTRA ANAK DI SDK RUTENG 3, KECAMATAN LANGKE REMBONG, KABUPATEN MANGGARAI, NUSA TENGGARA TIMUR

Optimization of Literacy Culture through Children's Literature Community in SDK Ruteng 3 Langke Rembong, Manggarai, East Nusa Tenggara. The community service activities aim to optimize the literacy culture of reading and writing for students and students of SDK Ruteng 3. The subject and object of this service activity are school residents, principals, teachers, employees and students in SDK Ruteng 3. Meanwhile, the object of activity is perception, the activities and behavior of school citizens against literary literacy activities. The method of implementing this service activity is through strategic stages along with intensive assistance from the child literature ca re community (PEDUS). The stages of service activities in general are as follows. lecturer together with community students form a literary care group (Poetry) in partner schools and hold regular poetry writing training on a regular basis, the student work will be published on the partner school's wall magazine. The next stage, rearranging the library is comfortable, safe, child-friendly, fun, and safe, applying the obligation to read 10 minutes every day, reading corners, make wall magazines of partner schools, holding the best reader, organizing poetry writing competitions, and making poetry ontology on the work of students at partner schools. The results of this service activity show that there is a significant increase and change in learning climate.
Object Interactions

As you learned in Chapter 3 , objects are the building blocks of an object-oriented software system. In such a system, objects collaborate with one another to accomplish common system goals, similar to the ants in an anthill or the employees of a corporation or the cells in your body. Each object has a specific structure and mission; these respective missions complement one another in accomplishing the overall mission of the system as a whole.
Artificial Intelligent Decoding of Rare Words in Natural Language Translation Using Lexical Level Context

Artificial intelligence based Machine Translation is a Natural Language Processing, attaining significant attention to fully automate the system that can translate source language content into the target languages. The proposed method is a Neural Machine Translation, end-to-end system, with the lexical level context for converting German sentences to English sentences. The Transformer based Machine Translation is used for translation for handling the occurrence of rare words in the lexical level context. The FSR group rare words together and represent sentence level context as Latent Topic Representation. WMT En-De bilingual parallel corpus is used for translation handling the Out of Vocabulary words using clustering of tags. In the existing method there is a mismatch of translation but the proposed system is more superior due to the sentence context inclusion. The model performance is enhanced with hyper parameter optimization obtaining a BLEU score with a better translation of source to target language. Finally minimizing the TER score to attain a better translation rate
Several classes of new projective three-weight or four-weight linear codes and their applications in $ s $-sum sets

In this paper, let q be a power of a prime, we construct several classes of new projective three-weight or four-weight linear codes over Fq from the defining sets construction, and determine their weight distributions by using additive character sums.Especially, these codes are suitable for applications in secret sharing schemes.Furthermore, basing on two classes of projective three-weight codes, we construct some s-sum sets for any odd s > 1.
Enhancing Customer Relationship Management through Sentiment Analysis and Social Media Data Mining

Customer Relationship Management (CRM) is a crucial aspect of modern business that enables companies to maintain healthy relationships with their customers. In today's digital age, customers interact with companies through multiple channels, including social media, email, and phone. Therefore, analyzing customer feedback and sentiment has become increasingly important in understanding their needs and improving the overall customer experience. To this end, this work proposes a new system that applies deep learning for sentiment analysis in a way that improves the performance of CRM by analyzing customer feedback from various sources, companies can gain valuable insights into customer needs and preferences and identify areas for improvement in their products and services. Then, we present a case study of a company that implemented the proposed system in its CRM strategy. The results showed that our system could improve customer satisfaction and retention rates and enable the company to identify and address customer concerns more efficiently.Our approach can be applied as a powerful tool to enable companies to gain valuable insights into customer needs and preferences, identify areas for improvement in their products and services, and develop targeted marketing campaigns and personalized communication strategies.
Sampo Karjalainen

Habbo is an MMO and virtual world in which users design rooms within the “Habbo Hotel” and an avatar that inhabits it. Users can also build and play games, embark on quests, have conversations, and buy and trade “furni” (furniture) with other avatars. Cofounded in 2000 by Sampo Karjalainen and Aapo Kyrölä, the game has since become one of the most visited social hangouts for teenagers worldwide. Habbo has amassed 316 million registered avatars and 500 million rooms. At present, it has over 800,000 active monthly users in 115 countries. It has raised over $35 million from VC investors and has been acquired twice for an undisclosed amount.
Stavovi i mišljenja odraslih o elementima promotivnog miksa i promociji programa obrazovanja odraslih

Following modern global trends in the commercialization of education and adopting the lifelong learning concept, as well as rapid development of adult education in Bosnia and Herzegovina, this research connects the adult education field with one of the vital management models in each organization/company's practice – marketing management. The number of adult education providers is increasing, but practical tools and research of their scope of work are in deficit. With the intention to contribute to the improvement of the theory and practice of adult education and marketing management and to help adult education providers adjust their promotional messages to their target groups, for the purpose of this research, the population of adults is divided into four generations: Baby Boom, X, Y and Z. This research aims to understand opinions and attitudes of the four generation's representatives on the elements of the promotional mix of educational institutions and determine whether changes between them exist or not. A qualitative research approach has been used in collecting primary data with focus groups as the main research method. The final result of this research is a projection of twenty recommendations to adult education providers (public and private schools, organizations and adult education centers), which are not only applicable in these education institutions. Other companies and organizations creating offers for age-segmented markets could also benefit greatly from these recommendations.
Abstraction and Modeling

As human beings, we’re flooded with information every day of our lives. Even if we could temporarily turn off all of the sources of “e-information” that are constantly bombarding us—emails, voicemails, podcasts, tweets, and the like—our five senses alone collect millions of bits of information per day just from our surroundings. Yet, we manage to make sense out of all of this information, typically without getting overwhelmed. Our brains naturally simplify the details of all that we observe so that these details are manageable through a process known as abstraction.
Traceability of Counterfeit Medicine Supply Chain Through Blockchain

The counterfeit medicine supply chain deals with a main issue on safety of drug. During the actual manufacture of drugs, it is a difficult process to trace the accurate pharmaceutical ingredients. Drugs that contain inactive ingredients and that do not contain calculated active ingredients can ultimately lead to harming the end consumer and also death of end consumer. Blockchain’s technology has the capability to completely trace the drugs, from manufacturer to end consumer, and provides the basis to identify counterfeit-drug. This paper aims to address the issue of drug safety using Blockchain and encrypted security. The methods used are SHA algorithm, AES Rijndael algorithm, Blockchain TCP Remoting concepts.
Quantum computer creates wormhole analogue

Quantum processors could put string theory and quantum gravity to the test, as Martijn Boerkamp reports.
Some Java Basics

What you’ll learn conceptually about objects in Part 1 of this book, and about object modeling in Part 2, is language neutral and thus could apply equally well to Java, Python, Ruby, or an as-yet-to-be-invented object-oriented (OO) language. Before diving into the basics of objects in Chapter 3 , however, I’d like to spend some time getting you comfortable with the basics of Java, as this is the programming language that I’ll use to illustrate object concepts as they are introduced throughout the rest of this book.