Reviewerly/exHarmony huggingface dataset:
Information on How to Interact and Love Dogs for Children Through Illustration Books

Violence in animals, especially dogs, is increasing every day. The lack of education and knowledge about loving dogs is also less given to the wider community. For dog owners will understand more about how to interact and treat dogs, but for those who do not have or get used to the existence of dogs it will be very difficult to love dogs. With the rapid development of age and technology, violence against animals, especially dogs, is becoming increasingly visible by uploading to social media for the purpose of having fun. The rise in violence against animals has led the rest of the world to denounce by making laws that ensnare perpetrators. In reality the community itself does not care about this troubling behavior and ignores the current law. Providing education about dogs can be done early so that when growing up the child does not hurt and love the dog. Therefore, this design was created with the aim of providing information to the public on how to interact and love dogs for children. Giving an education to the child can go through a pleasant thing so as not to feel burdened. Educating through an illustration book will make it easier for the child to learn, this can be done when the child will go to sleep, because the information will be absorbed faster and remembered longer when given at night.
Grammatical Errors Found in Articles' Abstracts of Indonesian Scholarly Journals

This study is aimed to know the grammatical errors found in the articles’ abstracts of scholarly journals published by one of Indonesian Islamic State Colleges in 2008-2010. The theory used to analyze the data in this case study is Burt and Kiparsky’s theory, namely Surface Strategy Taxonomy. This theory devides errors into errors of omission,errors of addition, errors of misformation and errors of misordering. This results of the study show that there are 172 items of grammatical errors. The most frequent type of grammatical error is omission with the total number is 72 items or 41.9%. The second is errors of misformation which consist of 57 items or 33.1%. The next is errors of addition (27 items or 15.7%) and finally is errors of misordering as the least number of errors with 16 items or 9.3%.
AethelmE, HTML5 Game Engine with Multiple Canvas Elements

Game engine is software which ease the game development. As the processor power technology evolved and the HTML5 (HyperText Markup Language 5) specification are developed, browsers nowadays can natively (without any need for external plug-in) display animations and multimedia files (audio and video) using JavaScript as the programming language. Some of the features which are used in this research are HTML5‘s canvas and audio elements. The problem is that none of the existing free HTML5 game engines is able to support multiple canvas elements. This research will create a game engine, called AethelmE, which support multiple canvas elements as its unique feature. This game engine is also able to support sprite transformation, browsers compatibility, external asset loading, and audio format compatibility. This research successfully resulted in creating an HTML5 game engine which supports multiple canvas elements. It also supports all the scopes, with a small exception on sound format compatibility. Moreover, this research conducted a performance comparison testing of multiple HTML5 game engines, from which can be concluded that multiple canvas elements does not give significant performance gain compared to a single canvas.
You, Too, Can Find That Job You Want!

Finding the 'right' job in the 'right' location and the 'right' time by already employed technical personnel can be an overwhelming task.If any student desires a job change or a career move, and is employed, he/she just does not have the time and is usually lacking the know-how to find 'that' job.At Purdue University, Organizational Leadership and Supervision Department, a Professional Development course is offered to help equip these students with the necessary knowledge and skills to locate and obtain the job of their choice.All this is accomplished without having to travel or miss work.The students learn how to use today's computer technology to its fullest.Their "text" is a workbook identifying over twenty current Job Search World Wide Web (WWW) addresses, the www addresses of the Forbes 500 companies, and other documents covering pertinent www addresses and techniques for submitting resumes.Even, Chat-based expectations and techniques are included as key elements of this course.This Professional Development course is primarily self-learning and self-directed in which each student generates a learning contract.Individually, the students determine exactly what he/she wants to learn and accomplish.The specific course content is then customized around their identified needs.They currently may not be pursuing a job change or career move but all of the students will be thoroughly versed and skilled in finding and getting that 'right' job in the future.They learn how to research a company and possible locations so they will be totally prepared for any opportunity which may be presented to them.
Human Computer Interaction Closes The Software Engineering Gap

With the pervasiveness of computers throughout our environment, there is a growing demand for diligent Human Computer Interaction (HCI) education of graduate and undergraduate students to close the gap left by software engineering education.This paper describes one approach to teaching HCI while requiring students to develop systems for various city, school, and university organizations.The benefits derived by the students and the clients receiving their services are many.There is a wide range of opportunities for community-based HCI education.The various client applications provide a plethora of learning scenarios that don't fit into the software engineering paradigm.The process, experience, and results of HCI education that closes the gap are presented in this paper.
Development Of A Pc Controlled Autonomous Aerial Robot

The currently employed autonomous aerial robot uses a complex system of GPS(Global Positioning System), INS(Inertial Navigation System), pressure meter, and so on.Also, the aerial robot carries the control algorithm in FCC(Flight Control Computers).However, in the case of a small aerial robot or MAV(Micro Air vehicle), it is impossible to load these bulky payloads due to the physical limitations.Therefore, this research sets its objectives on making the simplest and smallest autonomous aerial robot.For this project, we tried to build a PC-Controlled Autonomous Aerial Robot.The project provides an opportunity for the high school student to perform a broad range of engineering activities with guidance of trained graduate students.
The Clarkson Common Experience Curriculum: Graduation Requirements Based On Student Learning Outcomes

Traditional graduation requirements have been composed of required and elective courses in a student's major together with courses selected to meet a "general education" requirement.With the growing emphasis on student learning outcomes, Clarkson University has adopted an outcomes based set of graduation requirements..The Clarkson Common Experience unifies each student's learning in a major field of study with learning expectations that broaden the student's understanding of our modern world.Graduates are expected to meet outcomes in fundamental academic abilities, in personal and social development, and in prescribed areas of knowledge.While some outcomes may be achieved in a single course, the Common Experience Curriculum identifies four components that serve as common threads through multiple courses.These are: (a) learning to communicate effectively, (b) developing an appreciation for diversity in both working and living environments, (c) recognizing the importance of personal, societal, and professional ethics, and (d) understanding how technology can be used to serve mankind.Each of these components is introduced early in the curriculum, reinforced in subsequent courses, and emphasized in upper division courses.This curriculum also emphasizes professional development through outcomes in professional responsibility and ethics, and by engaging the student in a professional experience such as co-op, internship, directed research or other experiential learning activity related to the student's professional goals.This paper presents a brief summary of the development process that led to the Clarkson Common Experience Curriculum.We discuss the relationship of this process to other curricular developments in higher education.The implementation of this curriculum, including the measures we have taken to ensure that the curriculum is sustainable and kept current, is described.Assessment of outcomes-based learning is vital to determining the overall success of this curricular change.We have just begun implementation during the 2006-07 academic year, and our plan will be phased over four years.We discuss our initial efforts and results of assessment.
Robust domain-adaptive discriminant analysis

In domain adaptation, classifiers with information from a source domain adapt to generalize to a target domain. However, an adaptive classifier can perform worse than a non-adaptive classifier due to invalid assumptions, increased sensitivity to estimation errors or model misspecification. Our goal is to develop a domain-adaptive classifier that is robust in the sense that it does not rely on restrictive assumptions on how the source and target domains relate to each other and that it does not perform worse than the non-adaptive classifier. We formulate a conservative parameter estimator that only deviates from the source classifier when a lower risk is guaranteed for all possible labellings of the given target samples. We derive the classical least-squares and discriminant analysis cases and show that these perform on par with state-of-the-art domain adaptive classifiers in sample selection bias settings, while outperforming them in more general domain adaptation settings.
Use Of Python In Teaching Discrete Mathematics

Discrete structures class is among the foundational classes in computer science since it includes materials that are highly pervasive in other areas of computer science such as data structures and algorithm design.A course in discrete structures typically starts with an introduction to logic and mathematical proof techniques then the focus is placed on graph theory with algorithm design and analysis techniques.These topics tend to be difficult to teach and hard to grasp students since materials are often abstract and at times disconnected.In this study we examine the impact of using Python programming language as an aid in teaching a discrete structures class to computer science students.Python is a programming language that supports both objectoriented and functional programming paradigms.It is easy to read and understand with syntax suitable for algorithm development.Python can run in an interactive mode which provides an efficient environment for students to experiment with abstract ideas in order to better understand the concepts.
Reporting on the Use of a Software Development Case Study in Computing Curricula

The use of case studies is an effective method for introducing real-world professional practices into the classroom.Case studies have become a proven and pervasive method of teaching about professional practice in such fields as business, law, and medicine.The term "case study" is used in a variety of ways.In its most naive form, it simply refers to a realistic example used to illustrate a concept or technique.Although the use of case studies in education has shown success in the above mentioned disciplines, it is yet to be adopted in any significant way in the computing education.In this work, we re-introduce the DigitalHome Case Study, and report on our use of one of the case modules of this case study.
Lessons From Industry Applied To A Software Project Course

This paper describes an upper level project course in which student teams identify and prototype software products.The course is designed for junior and senior computer science majors without previous software engineering training.The goals of the course are to: 1) give students experience working in teams on non-trivial projects; 2) help students develop skills in areas such as analysis, design, risk management, testing, and documentation; and 3) expose students to related topics, including organizational issues, marketing, and intellectual property.This course has evolved over several years, partly in reaction to the author's experiences consulting in industry.Many issues faced in the software industry have parallels in student projects; project courses that acknowledge and emphasize these similarities can better prepare students for the future.The paper describes the evolution and mechanics of the course, lessons learned from industry, resulting changes, and future plans.
RANCANG BANGUN SMART DOOR LOCK MENGGUNAKAN QR CODE DAN SOLENOID

Smart Door Lock is a development of home door lock or padlock conventional manual. This study aims to create an alternative technology at home by utilizing key technologies readily available. This study uses an Arduino Uno microcontroller as the brains of the solenoid, and Android as controller QR Code reader. QR Code reader on Android run using a third party application that is Barcode Scanner. Arduino programming is done using the Arduino IDE. Bluetooth HC 05 is used to connect a barcode scanner app on Android with Arduino. Testing tool is run on Jelly Bean Android platform and the hardware and software components can be run properly. The results of the studies described in the form perncangan home door lock tool automatically uses the QR Code with Barcode Scanner app and Arduino as a control solenoid.
Examining the Impact of Emojis on Disaster Communication: A Perspective from the Uncertainty Reduction Theory

In this paper, I examine design practices by contrasting the Cartesian view of separation with an ontological perspective and argue for a dynamic, multiple, and entangled world (namely, sociomateriality). In the digital era we live in, sociomateriality helps move design practices forward in order to embrace constant changes and re- configurations. The word interface manifests a worldview of separation. Researchers typically conceive an interface as belonging to an artifact; that is, the technology, the material. More so, [people] typically considers user interfaces as the layer that separates and connects the technology and the user, which enables interaction. I recognize the limitations of the well-established perspective of interface design and contrast two traditional HCI concepts (namely, usability and context) from a Cartesian versus a sociomaterial perspective. However, to embrace and capitalize on the emergent digital reality, we need a new vocabulary. I introduce helpful concepts that one can use when designing and talking about experiences, and I ground the concepts in a sociomaterial ontological perspective. The concepts and design approach presented in this paper invite and encourage researchers to focus on experiences as sociomaterial entanglements and re-configurations and not as separated social and material entities. By using Michel Serres’ (1980) term quasi-objects, I call attention to the complexity of sociomaterial entanglements that make up experiences and emphasize a holistic and inclusive design approach. In addition, introducing sociomaterial concepts, such as agential cuts and intra-actions, into the human-computer interaction domain invites researchers to think and act in new ways in the era of digitalized experiences. I examine the benefits of the sociomaterial design approach and present practical guidelines on how to approach experiential design with a sociomaterial take.
HyPED: Modeling and Analyzing Action Games as Hybrid Systems

Platformers and action-adventure games have high-dimensional state spaces with difficult, non-linear constraints on character movement; even worse, game environments often respond to the player in complex ways that can cause exponential expansion of the planning search space. Planning problems in these high-dimensional spaces generally require domain-specific knowledge and manually abstracted models of game rules to replicate the intuition of human designers or playtesters. In this work, we outline a system for modeling these complex games at a precise and low level in terms of hybrid automata. With this representation, standard incremental search algorithms can be used to answer reachable-region queries, taking advantage of the domain information embedded in the system.
Switching and information exchange in compressed estimation of coupled high dimensional processes

Compressed Estimation approaches, such as the Generalised Compressed Kalman Filter (GCKF), reduce the computational cost and complexity of high-dimensional and high-frequency data assimilation problems, usually without sacrificing optimality. Configured using adequate cores, such as the Unscented Kalman Filter (UKF), the GCKF could also treat certain high-dimensional non-linear cases. However, the application of a compressed estimation process is limited to a class of problems which inherently allow the estimation process to be divided, at certain intervals of time, into a set of lower-dimensional problems. This limitation prohibits applying the compressing techniques for estimating coupled high-dimensional processes. However, those limitations can be overcome by applying proper techniques. In this paper, the concepts of subsystem switching and information exchange architecture, namely ‘Exploiting Local Statistical Dependency’ (ELSD), have been derived and explored, allowing compressed estimators to mimic optimal full-Gaussian estimators. The performances of the methods have been verified through applications in solving usual types of Stochastic Partial Differential Equations (SPDEs). The computational advantages of using the proposed techniques have also been highlighted with a recommendation for its usage over the full filter when dealing with high-dimensional and high-frequency data assimilation.
Reasoning about proof and knowledge

In previous work [15], we presented a hierarchy of classical modal systems, along with algebraic semantics, for the reasoning about intuitionistic truth, belief and knowledge. Deviating from Gödel's interpretation of IPC in S4, our modal systems contain IPC in the way established in [13]. The modal operator can be viewed as a predicate for intuitionistic truth, i.e. proof. Epistemic principles are partially adopted from Intuitionistic Epistemic Logic IEL [4]. In the present paper, we show that the S5-style systems of our hierarchy correspond to an extended Brouwer–Heyting–Kolmogorov interpretation and are complete w.r.t. a relational semantics based on intuitionistic general frames. In this sense, our S5-style logics are adequate and complete systems for the reasoning about proof combined with belief or knowledge. The proposed relational semantics is a uniform framework in which also IEL can be modeled. Verification-based intuitionistic knowledge formalized in IEL turns out to be a special case of the kind of knowledge described by our S5-style systems.
Scheduling Live Interactive Narratives with Mixed-Integer Linear Programming

A live interactive narrative (LIN) is an experience where multiple players take on fictional roles and interact with real-world objects and actors to participate in a pre-authored narrative. Temporal properties of LINs are important to its viability and aesthetic quality and hence deserve special design consideration. In this paper, we tackle the largely overlooked problem of scheduling a multiplayer interactive narrative and propose the Live Interactive Narrative Scheduling Problem (LINSP), which handles reasoning under temporal uncertainty, resource scheduling, and non-linear plot choices. We present a mixed-integer linear programming formulation of the problem and empirically evaluates its scalability over large narrative instances.
Studying the Effects of Training Data on Machine Learning-Based Procedural Content Generation

The exploration of Procedural Content Generation via Machine Learning (PCGML) has been growing in recent years. However, while the number of PCGML techniques and methods for evaluating PCG techniques have been increasing, little work has been done in determining how the quality and quantity of the training data provided to these techniques effects the models or the output. Therefore, little is known about how much training data would actually be needed to deploy certain PCGML techniques in practice. In this paper we explore this question by studying the quality and diversity of the output of two well-known PCGML techniques (multi-dimensional Markov chains and Long Short-term Memory Recurrent Neural Networks) in generating Super Mario Bros. levels while varying the amount and quality of the training data.
Buying the Haystack: New Roles for Academic Business Libraries

For decades academic libraries have been buying databases to support classroom instruction and faculty research.The library market for these resources is well established, with specialized salespeople who know what libraries want and understand how to deliver the information.Data resources are made widely available for use, usually to the whole campus.Librarians customarily purchase database subscriptions with the intention of renewing them annually for perpetuity.Examples of web-based business databases in the academic market include Mergent Online and Capital IQ.Some, such as CRSP or TAQ, use platforms like WRDS to make their products available to libraries.The largest information producers use a mixed approach.For example, Thomson Reuters and Standard & Poor's both sell an array of information products across platforms.Academic decision-makers have commonly considered the library's information purchases to be community resources.Librarians purchased data that were widely in demand and readily available to a wide cross-section of users and declined to purchase resources that were available to only a small group or an individual.Even when influential faculty researchers requested specific databases, in most cases librarians made purchase decisions based on overall demand for the resource.Assistance with using specialized data was limited.But now user needs for data are changing, and use of libraries' web-based and WRDS-accessible databases is declining.With increasing frequency, faculty members are requesting a different kind of resource-stand-alone data sets that are not widely available to the library market and not available through WRDS.The seller often withholds university-wide use, and in many cases is not set up to offer it.Librarians who recognize the change in faculty data needs and want to stay relevant in the university research ecosystem are now purchasing and licensing these unique data sets to make them available to individual researchers or small groups of faculty.These stand-alone data sets are usually custom extracts, often one-time purchases of specific data that an individual or small group of faculty members needs for their research.These data sets involve a number of licensing, hosting, curating, and funding issues that librarians must resolve if they want to serve their institutional research agenda.