Reviewerly/exHarmony huggingface dataset:
Dynamic Windows Scheduling for Virtual Machine Placement

We consider applying Windows Scheduling (WS) to VirtualMachine(VM) placement in cloud computing. In brief, the problem is to schedule the use of Physical Machines(PM) in terms of mips, processing elements, ram, storage and/or bandwidth to clients. Each client is characterized by an active cycle and a broker which is acting on behalf of that client. The broker hides virtual machine management, as VMcreation, submission of cloudlets to VM and destruction of VMs. During the period of time that any given client is active, there must be transmissions from the broker to the cloud resource provider, for example, a Data Center, for VM creation and destruction. The goal of the Data Center Virtual Machine Allocation Policy is to minimize the numberof PMs used for VM placement. With this online model, decisions are dynamic, we assume that VMs may be reallocated at some cost. We assume that such cost is a constant amount paid per reallocation. That is, we also aim to minimize the number of reallocations. We will present several online reallocation algorithms for VM placement. We will eval-uate experimentally these policies showing that, in practice, all achieve constant amortized reallocations with close to optimal PM usage. Our simulations will also expose interesting trade-offs between reallocations and PM usage. We are developing the simulation model termed Virtual-MachinePlacementSim (VMPSim) based on CloudSim to perform theexperiments.
Applying Vocabularies to a Large, Historic Geoscience Collection

Geoscience collections have data needs that are broadly consistent with, but differ in important ways from, biology collections. Non-paleontology geoscience collections have received particularly little attention because they do not fit easily into the biodiversity framework that encompasses most natural history collections. Here we describe efforts to apply controlled vocabularies to the rock, mineral, and meteorite collections of the Department of Mineral Sciences in the Smithsonian Institution's National Museum of Natural History. Controlled vocabularies encourage consistency in usage of terms, connect related terms and concepts, and simplify discovery and re-use of data. Developing and implementing vocabularies for geoscience collections is a key step in better integrating these collections into the broader natural history landscape. The Mineral Sciences collections contain approximately 450,000 specimens collected over 150 years. Specimen records therefore contain a large number of archaic terms and vary widely in the quality and amount of descriptive metadata available. We targeted four fields judged most likely to benefit from using a vocabulary: rock/mineral classification (using terms from the British Geological Survey Rock Classification Scheme, the International Mineralogicial Association's list of minerals, and other sources); rock microstructure (using terms from GeoScience Markup Language, or GeoSciML); stratigraphy (using MacroStrat); and collection locality (using terms from GeoNames and the Global Volcanism Program). This process highlighted many of the challenges of grafting vocabularies onto existing data of varying age and quality, including: A lack of comprehensive, widely used vocabularies for geosciences Ambiguities in usage between the specimen database and the controlled vocabulary Widespread use of archaic terms that must be defined or replaced Difficulty shoehorning vocabularies into databases not designed to accommodate them Tension between the needs of data management and collection management A lack of comprehensive, widely used vocabularies for geosciences Ambiguities in usage between the specimen database and the controlled vocabulary Widespread use of archaic terms that must be defined or replaced Difficulty shoehorning vocabularies into databases not designed to accommodate them Tension between the needs of data management and collection management Even with these difficulties, implementing vocabularies has made it easier to retrieve and interpret specimen data, especially for queries of rock/mineral classification and locality information, and is a useful step in encouraging wider use of data from the collections.
Partnering with Senior Engineering Students: Design & Prototype building of Document Encapsulator

Encapsulation of flat paper collection items, such as documents, between polyester film is standard practice preservation strategy. Equipment currently available on the market for encapsulation either employ heat or an ultrasonic welder to create the seams in the polyester film. This equipent is only produced by limited sources and can be cost-prohibitive. Each year, the Engineering College calls for project proposals for Capstone projects, a senior class project designed to have students work with a client to design and complete, mimicking the real world. The Preservation unit submitted an open proposal to design and build an encapsulator and was selected by a mechanical engineering team.Working with a team of five senior students, the project took place in two phases, over the course two semesters. The TAMU Encapsulator design includes several innovations including an off-the-shelf removable ultrasonic welder locally sourced, an interchangable welder tip, a digital control box to adjust percent strength of the weld, and additional seam types.With a budget of $15k provided by the Library, these students were able to build a working prototype from off-the-shelf components and came in under budget. The prototype was presented in the Annual Senior Showcase, competeing with all Enginneering specialties and awarded Second Place.
21세기 문식성 계발을 위한 내용문식성과 읽기 과제 모형 탐색

This study explores theories of content literacy and disciplinary literacy in search of implications for reading content development, building on the reading competency concept and assessment framework of the Programme for International Student Assessment (PISA) 2018 that reflects the orientation of literacy education in the 21st century. Common Core State Standards(CCSS) emphasized literacy education, focusing on close reading, complex texts, and multiple-document reading. The effects of generic literacy skills have been widely questioned by secondary subject teachers. A new disciplinary literacy theory asserts the need to balance content and literacy, going so far as to suggest unique literacy skills for subject content. PISA trends and advanced literacy instruction in disciplinary literacy theory, underlying readers’ roles and goals and authentic reading tasks, suggest models for content-area reading and content literacy instruction. In Korea, the psychological approach to reading competency, which still adheres to the 2015 curriculum and textbooks, should be converted to a social constructivist perspective and text-based reading tasks with multiple documents. To do so requires empirical studies for reading task development based on collaboration between disciplinary specialists and literacy experts.
A Tight Analysis of Greedy Yields Subexponential Time Approximation for Uniform Decision Tree

Decision Tree is a classic formulation of active learning: given $n$ hypotheses with nonnegative weights summing to 1 and a set of tests that each partition the hypotheses, output a decision tree using the provided tests that uniquely identifies each hypothesis and has minimum (weighted) average depth. Previous works showed that the greedy algorithm achieves a $O(\log n)$ approximation ratio for this problem and it is NP-hard beat a $O(\log n)$ approximation, settling the complexity of the problem. However, for Uniform Decision Tree, i.e. Decision Tree with uniform weights, the story is more subtle. The greedy algorithm's $O(\log n)$ approximation ratio was the best known, but the largest approximation ratio known to be NP-hard is $4-\varepsilon$. We prove that the greedy algorithm gives a $O(\frac{\log n}{\log C_{OPT}})$ approximation for Uniform Decision Tree, where $C_{OPT}$ is the cost of the optimal tree and show this is best possible for the greedy algorithm. As a corollary, we resolve a conjecture of Kosaraju, Przytycka, and Borgstrom. Leveraging this result, for all $\alpha\in(0,1)$, we exhibit a $\frac{9.01}{\alpha}$ approximation algorithm to Uniform Decision Tree running in subexponential time $2^{\tilde O(n^\alpha)}$. As a corollary, achieving any super-constant approximation ratio on Uniform Decision Tree is not NP-hard, assuming the Exponential Time Hypothesis. This work therefore adds approximating Uniform Decision Tree to a small list of natural problems that have subexponential time algorithms but no known polynomial time algorithms. All our results hold for Decision Tree with weights not too far from uniform. A key technical contribution of our work is showing a connection between greedy algorithms for Uniform Decision Tree and for Min Sum Set Cover.
Security Implications Of Compiler Optimizations On Cryptography -- A Review

When implementing secure software, developers must ensure certain requirements, such as the erasure of secret data after its use and execution in real time. Such requirements are not explicitly captured by the C language and could potentially be violated by compiler optimizations. As a result, developers typically use indirect methods to hide their code's semantics from the compiler and avoid unwanted optimizations. However, such workarounds are not permanent solutions, as increasingly efficient compiler optimization causes code that was considered secure in the past now vulnerable. This paper is a literature review of (1) the security complications caused by compiler optimizations, (2) approaches used by developers to mitigate optimization problems, and (3) recent academic efforts towards enabling security engineers to communicate implicit security requirements to the compiler. In addition, we present a short study of six cryptographic libraries and how they approach the issue of ensuring security requirements. With this paper, we highlight the need for software developers and compiler designers to work together in order to design efficient systems for writing secure software.
Genetic Network Architecture Search

We propose a method for learning the neural network architecture that based on Genetic Algorithm (GA). Our approach uses a genetic algorithm integrated with standard Stochastic Gradient Descent(SGD) which allows the sharing of weights across all architecture solutions. The method uses GA to design a sub-graph of Convolution cell which maximizes the accuracy on the validation-set. Through experiments, we demonstrate this methods performance on both CIFAR10 and CIFAR100 dataset with an accuracy of 96% and 80.1%. The code and result of this work available in GitHub:https://github.com/haihabi/GeneticNAS.
Interactive-Predictive Neural Machine Translation through Reinforcement and Imitation

We propose an interactive-predictive neural machine translation framework for easier model personalization using reinforcement and imitation learning. During the interactive translation process, the user is asked for feedback on uncertain locations identified by the system. Responses are weak feedback in the form of "keep" and "delete" edits, and expert demonstrations in the form of "substitute" edits. Conditioning on the collected feedback, the system creates alternative translations via constrained beam search. In simulation experiments on two language pairs our systems get close to the performance of supervised training with much less human effort.
Responsible Sourcing via Blockchain in Mineral Supply Chains

Manufacturers and suppliers in the tech industry, trading and utilizing minerals, are often unable to conduct substantial supply chain due diligence, due to reasons such as lack of competence, the ...
Integration of Imitation Learning using GAIL and Reinforcement Learning using Task-achievement Rewards via Probabilistic Graphical Model

Integration of reinforcement learning and imitation learning is an important problem that has been studied for a long time in the field of intelligent robotics. Reinforcement learning optimizes policies to maximize the cumulative reward, whereas imitation learning attempts to extract general knowledge about the trajectories demonstrated by experts, i.e., demonstrators. Because each of them has their own drawbacks, methods combining them and compensating for each set of drawbacks have been explored thus far. However, many of the methods are heuristic and do not have a solid theoretical basis. In this paper, we present a new theory for integrating reinforcement and imitation learning by extending the probabilistic generative model framework for reinforcement learning, {\it plan by inference}. We develop a new probabilistic graphical model for reinforcement learning with multiple types of rewards and a probabilistic graphical model for Markov decision processes with multiple optimality emissions (pMDP-MO). Furthermore, we demonstrate that the integrated learning method of reinforcement learning and imitation learning can be formulated as a probabilistic inference of policies on pMDP-MO by considering the output of the discriminator in generative adversarial imitation learning as an additional optimal emission observation. We adapt the generative adversarial imitation learning and task-achievement reward to our proposed framework, achieving significantly better performance than agents trained with reinforcement learning or imitation learning alone. Experiments demonstrate that our framework successfully integrates imitation and reinforcement learning even when the number of demonstrators is only a few.
Operation labeling algorithm within Xamtanga sentences

The objective of this article was to look at the operation of the Labeling Algorithm within Xamtanga sentences. A descriptive research design was used to examine the research objective.&nbsp;The proposed sentences were gathered from Xamtanga&nbsp;college lecturers (3 males, 1 female) who teach the intended language. By expert sampling, eleven (11) sentences were chosen, prearranged, and portrayed. The method of data analysis working in this research was Labeling Algorithm {XP, YP}. Thus, results designated that simple sentences in Xamtanga&nbsp;have barely single Verbal heads. On the other hand, compound, complex, and compound-complex sentence structures have more than one verbal head. Regarding sentence appearances, Syntactic Object representations they enclose were dissimilar. Alternatively, every sentence types share Syntactic&nbsp;Object representations like Noun Phrase (NP), Verb Phrase (VP), Determiner Phrases (DP), Prepositional phrase (PP), Tense Phrase (TP), Adverbial Phrase (ADVP), and Adjectival Phrase (AP). Lastly, the study suggested that additional research on how {XP, H}, and {X, Y} employed to explain Xamtanga sentences. &nbsp; &nbsp
Fitting Probability Distribution Function to Malaria Incidence Data

Abstract: Malaria remains a major infectious disease that affects millions of people. Once infected with Plasmodium parasites, a host can develop a broad range of clinical presentations, which result from complex interactions between factors derived from the host, the parasite and the environment. Malaria has historically been a very serious health problem and currently poses the most significant threat to the health of Masinde Muliro University of Science and Technology students, data shows that more than 70% percent of pediatric cases are due to malaria.&#x0D; Methodology: Hence, the study aimed to fit malaria incidences dataset for the period 1st January, 2013 to 31st December, 2015. Data on monthly malaria incidence was obtained from the Masinde Muliro University of Science and Technology health service. Gamma, Weibull and Lognormal Distributions were employed to fit the malaria incidence dataset using R-software.&#x0D; Results: High malaria incidences were observed in the months of August, September and November. AIC values results showed that lognormal distribution had the lowest AIC value of 185.9875 followed by the Gamma distribution with a value of 187.8815 and then the Weibull distribution with a value of 188.7271. This confirmed the lognormal distribution to be the best fitting distribution for the malaria incidence dataset&#x0D; Conclusion: The Poisson regression model did not accurately fit the data on malaria incidences due to over dispersion in the data but lognormal distribution was a better fit compared to gamma and Weibull distribution.
FORMATION OF REFLEXIOUS ACTIVITIES OF ADOLESCENTS ON LITERATURE PRESENTATIONS

The article is devoted to one of the stages of educational activity in literature lessons - the formation of reflection. The main attention is focused on revealing the essence of the concept of "reflection" and its effectiveness. The forms and methods of reflection at different stages of employment are singled out. Reflection is aimed at understanding the path taken, in gathering information. Such activity stimulates the moral development of students, and this affects their selectivity regarding the content process of ethical knowledge, emotional and personal attitude to the forms and methods of its organization. Activating the ability to reflect allows teenagers more adequately and actively to know reality, to reveal in its phenomena general and special, to develop new knowledge. Conducting reflection in classes is a kind of monitoring where the teacher can and must see whether each student (student, student) has made certain knowledge, results, expectations, and the ability of participants in the learning process to evaluate themselves and the work of others. Reflection helps the teacher to see the learning process and find out at once what was clear, and what's left to refine. Reflection in the classroom is a joint activity of the students and the teacher, which allows to improve the educational process, focusing on the personality. At different stages, it has different functions: communicative, cognitive, motivational, corrective, and so on. Most psychologists and educators point out that written reflection is more important for the development of personality. One can distinguish several of the most well-known forms of written reflection: essay, free letter, mini-essay, on-board magazine.The realization of reflective activity in literature classes helps to more confident communication with peers and adults, reduce the level of unethical behavior of students, awareness of the acquired knowledge and skills, free expression of their feelings, development of the ability to reflect in real life, aware of their actions and to predict further steps, to compare their perception with thoughts, views, feelings of others, etc
THE ROLE OF LEADERSHIP AND SOCIAL TIES IN THE DEVELOPMENT OF HUMAN CAPITAL

The sociological aspects of studying human capital, leadership and social ties, are considered in this article. Sociological theories of human capital consider it in its connection with social capital that can be defined as an engagement in social relations, units and networks giving one some benefits. Social ties are the resource of development of human capital. The article shows that human capital can be evaluated from sociological perspective through the role of a creative class and new forms of ties that constitute integration on the intergroup level (weak ties). Such forms of communication significantly expand the sphere of opportunities for human development. The leadership acquires new functions of building nodes of networks that establish and develop social ties on different levels, and contribute to social transformation. Leadership networks demonstrate strength of weak ties that allows leaders to reach their goals through collaboration and sharing information with their own kind and to broad the scope of their activity. There are four types of leadership networks: peer leadership networks, organizational leadership networks, field-policy leadership networks, and collective leadership networks. Study of the leadership networks helps to research forms of communications, factors influencing their intensity, trust among the network’s actors etc. Analysis of the leadership networks includes such objectives as definition of network structure; their dynamics; evaluating ways of communications, and impacts of changes that occur as the result of their activity. Network analysis allows finding out the core and peripheral agents of network, and strong and weak ties between them.
학습몰입이 진로자기효능감, 교육만족도, 수업지속의도에 미치는 영향

This study attempted to analyze the effects of after-school learning commitment on career self-efficacy, educationalsatisfaction and intention to...
Deformable Mesh for Regularization of Three-Dimensional Image Registration

We demonstrate that the registration of three-dimensional medical images demands elastic transformation with limitation of scaling. Moreover, it should be performed on a limited number of feature points and within a specified volume of interest. The regularization term derived from locally estimated unimodal transformation meets these requirements. The term was implemented in the image registration routine in the way inspired by deformable models. The resulting algorithm is presented in detail and verified on time series of three-dimensional kidney images. The qualitative results are presented and compared with the registrations obtained by the reference state-of-the-art method.
The Development Research of Gesture Recognition Based on Human Interaction

Firstly, the paper discusses the concept and common direction of virtual reality human-computer interaction. On this basis, it focuses on the foundation of function realization, and proposes to verify the multi-channel gestures through simulation to help improve the human-computer interaction process. The ability to simulate gestures. On this basis, the paper focuses on the tracking algorithm of multi-feature gesture recognition in virtual reality human-computer interaction environment, combined with the actual system design analysis, in order to be more clearly analyze the direction of human-computer interaction development.
A Sound Algorithm for Asynchronous Session Subtyping (extended version).

Session types, types for structuring communication between endpoints in distributed systems, are recently being integrated into mainstream programming languages. In practice, a very important notion for dealing with such types is that of subtyping, since it allows for typing larger classes of system, where a program has not precisely the expected behavior but a similar one. Unfortunately, recent work has shown that subtyping for session types in an asynchronous setting is undecidable. To cope with this negative result, the only approaches we are aware of either restrict the syntax of session types or limit communication (by considering forms of bounded asynchrony). Both approaches are too restrictive in practice, hence we proceed differently by presenting an algorithm for checking subtyping which is sound, but not complete (in some cases it terminates without returning a decisive verdict). The algorithm is based on a tree representation of the coinductive definition of asynchronous subtyping; this tree could be infinite, and the algorithm checks for the presence of finite witnesses of infinite successful subtrees. Furthermore, we provide a tool that implements our algorithm and we apply it to many examples that cannot be managed with the previous approaches.