Reviewerly/exHarmony huggingface dataset:
Active Heading Control Platform for Instruments Flown on High Altitude Balloons

Experiments flown on high-altitude balloons are typically free to spin without any control or information collected on the payload orientation during flight, limiting the scope of experiments that can be performed. Projects that include targeting (i.e. imaging the 2017 solar eclipse) have at best a random chance of succeeding, while video footage is often hard to watch due to high payload rotation rates. While passive stabilization reduces the rotation rate, active pointing control is necessary for continuous target acquisition. Here we discuss a project built by students at Wright College called the Controlled Heading Automation Device (CHAD) that actively controls the heading of other instruments (i.e. cameras) and has been proven to work in flight. This project is open-source, 3D printable, made from cheap DIY electronics, and has been made available online (http://physi.cz/chad) so the high-altitude ballooning community can create, use, and adapt it to their own projects. We show how to create an attitude and heading reference system (AHRS) that can be used to continuously record payload orientation, which can supplement experiments where pointing information is needed. We then show how to have CHAD use the AHRS to automatically control the heading of other instruments in real-time without any other inputs.
The Marginal: A Game for Modeling Players' Perceptions of Gradient Membership in Avatar Categories

We encounter the results of category formation every day, from demographic categories like race and gender, to role-playing-game classes like "fighter" or "mage". Category membership is often not simply based on the possession of discrete properties but instead constructed from and reflect the highly nuanced relationships (gradience) between members and best-example individuals called "prototypes". In this paper, we present The Marginal, an artificial intelligence (AI)-driven game that (1) computationally models the cognitive categories that players develop when customizing videogame avatars and (2) generates challenges for players to use their perception of visual, textual, and numerical data to progress in a game created using these models. We use archetypal analysis, an AI clustering approach for identifying boundary points in data, to generate tasks in The Marginal for its gameplay. It shows how AI can be combined with games to model and evaluate cognitive categorization phenomena.
Systems Architecting and Software Architecting - On Separate or Convergent Paths?

Systems Engineering is an overall method and discipline for building large-scale systems.It has been described as consisting of some twenty-five subordinate processes or an equivalent number of elements.Whatever the overall description, it is agreed that software engineering is a critical activity within the overall field of systems engineering.The success of our efforts at building large systems often depends upon how well we execute the software tasks within a systems engineering framework.The software development issue is high on our list of areas that require continuous improvement if we are to be successful at systems engineering.Both systems and software engineering have methods for architecting.In the former case, there are several approaches, all of which are rather definitive, and have well-known proponents and supporters.These include DoDAF, MoDAF, Enterprise Architecting, and others.In the case of software engineering, the approaches seem to be deep, varied and interesting, and not necessarily agreed upon.In this paper, the author provides an overview of both the fields of systems and software architecting, looking especially for areas of possible commonality.Conclusions are set forth including the possibility of a unified approach.Recommendations follow, suggesting future actions as well as research areas.These results have direct relevance to the structure and content of curricula, current and future, for systems and software engineering and architecting.
Calculating and Evaluating Trustworthiness of Certification Authority

In a public key infrastructure trust model, a trust is transferred along a set of certificates, issued by certificate authorities (CAs) considered as trustfully third parties, providing a trust chain among its entities. In order to deserve this trustworthiness, a CA should to apply the rigorous procedures for generating keys, checking the identities, and following reliable security practices. Any deficiency in these procedures may in?uence its trustworthiness. In this context, some authorities could be weaker than others. Then, relying parties (RPs) and certificate holders (CHs) need a mechanism to evaluate CA trustworthiness. In this paper, we provide them this mechanism to have information about its trustworthiness. In fact, we propose a trust level calculation algorithm that is based on three parameters which are the CA reputation, the quality of procedures described in the certi?cate policy and its security maturity level.
A New Polya Tree Construction Facilitating A Goodness-of-Fit Test

Polya tree, by embedding parametric families as a special case, provides natural suit to test goodness of fit of a parametric null with nonparametric alternatives.For this purpose, we present a new construction on Polya tree for random probability measure, which aims to perform an easy multiple χ 2 test for goodness of fit.Examples of data analyses are provided in simulation studies to highlight the performance of the proposed methods.
Teacher Preparedness to Utilize Emergent Literacy for Teaching Initial Literacy in Selected Schools of Mansa District

Effective teaching of initial literacy in Grade 1 demands more of the teacher’s attention to&#x0D; pupils’ emergent literacy skills and consideration of how they learn. The emergent literacy&#x0D; skills children acquire lay a firm foundation for their learning to read and write in the&#x0D; conventional sense. Some of the skills that children develop under emergent literacy&#x0D; include phonological awareness and phonological sensitivity, which give children the&#x0D; ability to hear, recognize, manipulate and distinguish the sounds of the language they have&#x0D; acquired. These are key language skills which teachers will need to utilize in their teaching&#x0D; of reading and writing skills to Grade 1 learners in the classroom.&#x0D; A study was carried out whose purpose was to investigate whether primary school teachers&#x0D; in Mansa District utilized emergent literacy skills in their teaching of conventional reading&#x0D; and writing skills to the learners in Grade 1 considering the fact that emergent literacy lays&#x0D; a firm and solid foundation for continuous development of the literacy skills. The study&#x0D; was a descriptive survey and qualitative in nature since it required the researcher to&#x0D; describe the state of affairs as found and observed in their natural setting in the research&#x0D; sites. The qualitative methods of data collection and analysis were used. The sample for&#x0D; this study comprised 62 Grade 1 teachers and 3,594 Grade 1 primary school pupils. Only&#x0D; those schools teaching initial literacy in the local familiar language using the Breakthrough&#x0D; to Literacy (BTL) methodology were targeted for this research.&#x0D; The findings indicated that: (1) Teachers lacked knowledge about emergent literacy and&#x0D; did not know how useful it was for continuous literacy development among the children.&#x0D; (2) Most of the teachers ignored pupils’ prior literacy knowledge and considered their&#x0D; learners as complete illiterates who knew nothing about literacy skills. (3) Teachers never&#x0D; designed extra teaching and learning materials for teaching literacy. Rather, they relied on&#x0D; the New Breakthrough to Literacy (NBTL) kit materials. (4) The class sizes were large and&#x0D; meaningful scaffolding was lacking in most of the classes.&#x0D; This study concluded that the Ministry of Education in Zambia should consider emergent&#x0D; literacy as the foundation for conventional literacy development in Grade 1. One&#x0D; recommendation was that teachers should be equipped with knowledge of emergent&#x0D; literacy through deliberate training. They need to understand and appreciate emergent&#x0D; literacy as an essential body of knowledge to be utilized for successful conventional&#x0D; literacy development among Grade 1 learners.
Machine Teaching as Search

Machine teaching (MT) studies the task of designing a training set. Specifically, given a learner (e.g., an artificial neural network or a human) and a target model, a teacher aims to create a training set which results in the target model being learned. MT applications include optimal education design for human learners and computer security where adversaries aim to attack learning-based systems. In this work, we formulate pool-based MT as a state space search problem. We discuss the properties and challenges of the resulting problem and highlight opportunities for novel search techniques. In our preliminary study we use a beam search approach, and find that training and evaluating empirical risk of models dominate the run time of the search. Toward the goal of better search techniques for future work, we develop optimizations ranging from implementation details for specific learners to algorithm changes applicable to general blackbox learners. We conclude with a discussion of open problems and research directions.
Detección de fraude financiero mediante redes neuronales de clasificación en un caso real español

This paper explores the possibilities offered by statistical tools based on artificial neural networks for pattern recognition in expert work for money-laundering detection. The data is provided by the Spanish Police Department and comes from a case in which is actually working at. Account information is provided, where some accounting entries are identified as fraud. Hence it is possible to use this information to train a classification model. In this analysis, after briefly describing methodology used and fitting strategy, it is presented a model with a promising predictive capacity, even with strongly unbalanced training data set. After applying balancing technique to the training data (SMOTE) the result is remarkably improved which would indicate the viability of those models as tool for police experts planification, providing a way to reduce the use of expensive research resources.
Numeric Planning via Search Space Abstraction (Extended Abstract)

Many real-world planning problems are best modeled as infinite search space problems, using numeric fluents. Unfortunately, most planners and planning heuristics do not directly support such fluents. We propose a search space abstraction technique that compiles a planning problem with numeric fluents into a finite state propositional planning problem. To account for the loss of precision resulting from the abstraction, we leverage a policy repair technique used for non-deterministic planning. We evaluate our approach on a set of benchmarks and compare it to state-of-the-art planners that deal with numeric fluents.
Recursive Constraint Manifold Subsearch for Multirobot Path Planning with Cooperative Tasks

The Cooperative Path Planning (CPP) problem seeks to determine a path for a group of robots which form temporary teams to perform tasks. The multi-scale effects of simultaneously coordinating many robots distributed across the workspace while also tightly coordinating the members of teams increases the difficulty of planning. Previous research produced the Constraint Manifold Subsearch (CMS) algorithm that can find minimal length paths to the CPP problem. However, CMS as currently formulated cannot handle more general cost functions, such as minimizing energy expenditure, and cannot handle task schedules that require multiple input teams to merge to form a set of multiple output teams. Furthermore, as CMS must couple planning for all interacting teams, it does not scale well to very large environments. In this paper, we rederive the CMS algorithm using a task graph to reason about inter-team dependencies, allowing the use of more general cost functions and task schedules. We then introduce the recursive CMS (rCMS) algorithm that exploits the reformulation to split the CPP into independent subproblems, significantly reducing computational complexity. Simulation studies show that rCMS can solve substantially larger problems than CMS.
Sentiment-Based Topic Suggestion for Micro-Reviews

Location-based social sites, such as Foursquare or Yelp, are gaining increasing popularity. These sites allow users to check in at venues and leave a short commentary in the form of a micro-review. Micro-reviews are rich in content as they offer a distilled and concise account of user experience. In this paper we consider the problem of predicting the topic of a micro-review by a user who visits a new venue. Such a prediction can help users make informed decisions, and also help venue owners personalize users’ experiences. However, topic modeling for micro-reviews is particularly difficult, due to their short and fragmented nature. We address this issue using pooling strategies, which aggregate micro-reviews at the venue or user level, and we propose novel probabilistic models based on Latent Dirichlet Allocation (LDA) for extracting the topics related to a user-venue pair. Our best topic model integrates influences from both venue inherent properties and user preferences, considering at the same the sentiment orientation of the users. Experimental results on real datasets demonstrate the superiority of this model compared to simpler models and previous work; they also show that venue-inherent properties have higher influences on the topics of micro-reviews.
Unsupervised Learning of HTNs in Complex Adversarial Domains

While Hierarchical Task Networks are frequently cited as flexible and powerful planning models, they are often ignored due to the intensive labor cost for experts/programmers, due to the need to create and refine the model by hand. While recent work has begun to address this issue by working towards learning aspects of an HTN model from demonstration, or even the whole framework, the focus so far has been on simple toy domains, which lack many of the challenges faced in the real world such as imperfect information and continuous environments. I plan to extend this work using the domain of real-time strategy (RTS) games, which have gained recent popularity as a challenging and complex domain for AI research.
Sleep Sets Meet Duplicate Elimination

The sleep sets technique is a path-dependent pruning method for state space search. In the past, the combination of sleep sets with graph search algorithms that perform duplicate elimination has often shown to be error-prone. In this paper, we provide the theoretical basis for the integration of sleep sets with common search algorithms in AI that perform duplicate elimination. Specifically, we investigate approaches to safely integrate sleep sets with optimal (best-first) search algorithms. Based on this theory, we provide an initial step towards integrating sleep sets within A* and additional state pruning techniques like strong stubborn sets. Our experiments show slight, yet consistent improvements on the number of generated search nodes across a large number of standard domains from the international planning competitions.
Image Restoration Based on Structure and Texture Decomposition

A new method for structure and texture filling-in of complex images with missing information is proposed. The presented algorithm relies on edge-based region segmentation. The segmented regions are used both to reconstruct a structure component and to guide the restoration of a texture component. The contributions of this paper are two-fold. Firstly, we propose an efficient method to prevent the edge-blur in filling-in complex image. Secondly, the texture can be quickly and nicely fixed in our method. Examples with real images show the advantages of the proposed scheme.
An Enhanced Non-Cryptographic Hash Function

How to store information for it to be searched and retrieved efficiently is one of the fundamental problems in computer science.There exists sequential search that support operation such as INSERT, DELETE and RETRIVAL in O (n log (n)) expected time in operations.Therefore in many applications where these operations are needed, hashing provides a way to reduce expected time to O (1).There are many different types of hashing algorithms or functions such as cryptographic hash functions, non-cryptographic hash function, checksums and cyclic redundancy checks.Non-cryptographic hash functions (NCHFs) take a string as input and compute an integer output (hash index) representing the position in memory the string is to be stored.The desirable property of a hash function is that the outputs are evenly distributed across the domain of possible outputs, especially for inputs that are similar.Noncryptographic hash functions have an immense number of applications, ranging from compilers and databases to videogames, computer networks, etc.A suitable hash function and strategy must be used for specific applications.This will help efficient use of memory space and access time.The most essential features of non-cryptographic hash functions is its % distribution, number of collisions, performance, % avalanche and quality which are the properties of the hash function.Basing on the properties assessed using a test suite; the results clearly demonstrated that: the proposed hash function that was developed had better properties as compared to other hash functions.
Accessible Design Issues And Principles In The Undergraduate Engineering Curriculum

Accessible design seeks to ensure physical accessibility through the use of sound human factors principles.In addition to physical accessibility, the design must facilitate cognitive accessibility-that is, reduce memory requirements, computational demands, possibly eliminate reading requirements, or in short, to keep things as simple as possible.Accessible design needs to reduce the variability associated with processes, jobs, and device performance.Jobs, processes or device operations that are not predictable, consistent or reliable lead to errors, frustrations, and accidents.Accessible design must build in error-proofing and error-handling capabilities and designers must take into account the many possible causes of human error and design for error prevention, protection and recovery.
Careerme: Encouraging An Advanced Manufacturing Worker Pipeline

Department (since 1995), teaching industrial engineering and quality engineering curriculum.As an independent quality professional in Dayton, Ohio since 2004, She provides consultation and training to manufacturing and service organizations for performance improvement initiatives in the quality system.Over the past 25 years, Sandy has held engineering,
Businesses And Education Cooperation Through Classroom Projects

This paper describes the incorporation of projects supplied by local businesses/industries into computer software courses in an attempt to provide students with an opportunity to develop collaborative problem solving skills, teamwork, professional responsibility, and most importantly an exposure to design and development situations very difficult to reproduce from textbook projects.Our paper describes the projects, discusses implementation problems, assessment procedures, students' attitude toward the experience, and instructors' reflections on the process.
Assessing And Refining Ec 2000

The goal of this paper is to consider the impact on engineering programs of various aspects of EC 2000 such as the focus on well-specified processes for defining and evaluating program objectives, or the requirement of well-defined assessment and feedback mechanisms; and possible ways to refine and further improve EC 2000, in particular Criteria 2 and 3, so that the impact on engineering education is as positive as it can be.Criterion 2 requires, in part, that the program have educational objectives that are determined and periodically evaluated based on the needs of various constituencies.Constituents typically include current and prospective students, alumni, local industry, etc.These constituents, in the experience of the author's program as well as that of others, often tend to be more interested in relatively short-term skills of immediate value and less interested in ideas and concepts that are likely to form the basis of engineering practice over the long run; similarly, these constituents may also not value highly the importance of a broad education including social and ethical issues underlying engineering.This contrasts sharply with the importance that most engineering faculty attach to these issues, and the stress that even EC 2000 (for example, outcome (3.h)) places on these issues.Possible ways of addressing this conflict are considered in the paper.Given the importance of assessment in EC 2000, most programs use a range of assessment instruments such as alumni surveys and employer surveys in an attempt to measure how well the objectives and outcomes of the program are being achieved.However, the reliability of these surveys is not entirely clear.The paper considers these issues and presents some alternative assessment and feedback mechanisms to address these concerns.
Bringing Cellular Phone Software Industry Practices To The Software Development Classroom

University computer science and software engineering curricula are oriented to conventional hardware platforms.This presents an obstacle to teaching students how to develop software for mobile devices.Industry certification practices provide an insight into what is important in teaching software development for a particular class of mobile devices, cellular phones.Adapting such practices to classroom use can aid in bridging the learning gap between traditional and non-traditional platforms.1.The problem: how to teach cellular phone software development Cellular phones have become indispensable tools for providing computation resources in a highly mobile package.An estimated 1.5 billion phones are in use today, with the number expected to grow to two billion by 2006 1 .These devices are so pervasive that many developed nations now have cellular communications infrastructures that are more reliable than their legacy land lines.In developed nations, particularly among students and young professionals, cellular phones are increasingly replacing traditional wired phones because they offer mobility, attractive calling rates, and digital services such as messaging and Internet facilities.Although phone calls are still the primary function of cell phones, these devices are increasingly viewed as mobile computers in their own right.They are equipped with processors that have the computational horsepower to organize address books, manage camera images, run games, and support a wide range of software applications once deemed the unique realm of the Personal Digital Assistant.Over 100,000 jobs in the American software industry involve writing software for mobile devices, with the number expected to triple in the next two years to a significant 11% of the software workforce 2 .The facts are plain: cell phones are a technology to be reckoned with.What are universities doing to equip their computer science and software engineering majors with skills necessary for developing software for such mobile devices?The answer is equally plain: very little 3 .Colleges teach students the principles of software development, but that instruction is oriented mostly to traditional hardware platforms.Developing software for mobile computers requires specific knowledge in working with hardware that is limited in speed, memory, power, and user interfaces.Mobile device software development is still very much a novelty; conventional university curricula do not address these areas to any depth.