Reviewerly/exHarmony huggingface dataset:
A Hybrid Optimization Algorithm for Multi-Agent Dynamic Planning with Guaranteed Convergence in Probability

To solve the problem of multi-agent path planning in complex environment, a new method is proposed based on the whale optimization algorithm, combining the chaotic initialization, the reverse search and the differential evolution methods. It is theoretically proved that this algorithm is globally convergent in probability. When applied to path planning problems, the proposed optimization algorithm can effectively find a globally optimal and smoother path. Through simulation experiments with multi-UAVs, it is demonstrated that the proposed algorithm has better performance than the state-of-the-art methods in environment with both static and dynamic obstacles, reflecting the global convergence and robustness of the proposed algorithm.
Message Hygiene and Security

Ten or fifteen years ago, the Exchange Transport server was used for message hygiene services. It was in the organization’s perimeter network, and software like Forefront Protection for Exchange was installed on it. And in those days, it did a decent job.
Exchange 2019 Introduction

Exchange Server 4.0 was introduced in 1996, more than 25 years ago! Now, in 2023, Exchange Server is still around and still alive, despite the massive migrations to Exchange Online.
Managing Emotional Dialogue for a Virtual Cancer Patient: A Schema-Guided Approach

In this paper, we describe a general-purpose dialogue management framework used to design SOPHIE (Standardized Online Patient for Healthcare Interaction Education). SOPHIE simulates a virtual standardized cancer patient that allows physicians to practice skills such as empathy and patient empowerment in end-of-life communication. To provide the user with an opportunity to practice these skills, SOPHIE must produce a natural, emotionally appropriate conversation, yet handle topic shifts and open-ended questions from the user. To accomplish this, our approach to dialogue management loosely follows <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">schemas</i> – explicit representations of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">typical</i> flows of dialogue in end-of-life communication – while also using flexible pattern-driven methods for interpretation and generation. We conduct a crowdsourced evaluation of conversations between medical students and SOPHIE. Our agent is judged to produce responses that are natural, emotionally appropriate, and consistent with her role as a cancer patient. Furthermore, it significantly outperforms an end-to-end neural model fine-tuned on a human standardized patient corpus, attesting to the advantages of a schema-guided approach in this domain. However, the system is currently limited in its ability to generate responses that are judged to demonstrate deep understanding of the user, suggesting that future work should place focus on integrating this framework with robust natural language understanding and commonsense reasoning methods.
Psychological stability of the personality in the light of the psychology of values: The dialectic of constancy and variability

THe issues of value transformations today come to the fore in educational practices and psychological research, includes different levels of cognition, forms a common problem field in the social sciences and the humanities, where a person’s value priorities are considered as prerequisites for his behavioral strategies, subjective preferences and political choices. However, the problem of relationship between values and psychological stability of a person in a transitive society remains insufficiently studied. THe purpose of the article is to discuss the psychological stability of a person in the context of the psychology of values. It has been established that reliance on values in a situation of sociocultural changes, awareness and self-reflexivity are prerequisites for the psychological stability of a person, which, depending on different research angles, can be interpreted in two ways: on the one hand, as self-determination, an internal locus of control, adherence to independently chosen life guidelines, on the other hand, adaptability, flexibility, readiness to situationally respond to changes and rebuild behavioral strategies. In this regard, the dialectic of constancy and variability becomes a methodological basis for interpreting the psychological stability of a person as a complex and antinomic process. Values connect subjective and objective, emotional and conceptual, existential and cognitive content, acting as a kind of bridge between the studies of personality and society, the methodology of psychology and social sciences. THe transdisciplinary approach is consistently used as a methodological strategy aimed at generalizing in a single conceptual framework the relationship between personality development, the evolution of society and culture, the dynamics of values changing in the course of sociocultural transformations. In this context of transdisciplinary discourse, a construct is introduced and substantiated — the axiological space of socialization. THe construct makes it possible to combine both directed influences on a person from the side of his social environment and educational institutions, as well as dispersed, diffuse, latent influences due to current changes in everyday life and the peculiarities of the modern way of life. It is assumed that in methodological terms, the axiological space of socialization contributes to the integration of research into the psychology of personality, the psychology of subject, the psychology of everyday life in the field of social sciences.
Cronus: Computer Vision-based Machine Intelligent Hybrid Memory Management

Current state-of-the-art resource management systems leverage Machine Learning (ML) methods to enable the efficient use of heterogeneous memory hardware, deployed across emerging computing platforms. While machine intelligence can be effectively used to learn and predict complex data access patterns of modern analytics, the use of ML over the exploded data sizes and memory footprints is prohibitive for its practical system-level integration. For this reason, recent solutions use existing lightweight historical information to predict the access behavior of majority of the application pages, and train ML models over a small page subset. To maximize application performance improvements, the pages selected for machine learning-based management are identified with elaborate page selection methods. These methods involve the calculation of detailed performance estimates depending on the configuration of the hybrid memory platform. This paper aims to reduce such vast operational overheads, that further exacerbate the existing high overheads of using machine intelligence, in return for high performance and efficiency. To this end, we build Cronus, an image-based pipeline for selecting pages for ML-based management. We visualize memory access patterns and reveal spatial and temporal correlations among the selected pages, that current methods fail to leverage. We then use the created images to detect patterns and select page groups for machine learning model deployment. Cronus drastically reduces the operational costs, while preserving the effectiveness of the page selection and achieved performance of machine intelligent hybrid memory management. This work makes a case that visualization and computer vision methods can unlock new insights and reduce the operational complexity of emerging systems solutions.
Real-Time Hand Gesture Recognition

The automatic recognition of gestures enriches Human – Computer Interaction by offering a natural intuitive method of data input. Compared with the traditional interaction approaches, such as keyboard, mouse, pen etc. Vision based hand interaction is more natural and efficient. As this methodology is aided with cameras and computer vision techniques. And besides normal use for handling objects and manipulating tools, the hand of human being can be used as the mean of communication here. This paper presents a new method or technique for a real time static hand gesture recognition on plain uniform background, for the HCI, based on pattern recognition using K-nearest Neighbor (KNN). Major consideration here is the stable lighting condition. Here work is done to recognize 10 gestures from ASL. Concept of connected components or objects is used here for hand segmentation, canny edge detector is used for pattern creation and classification is done by using K-nearest Neighbor algorithm. This algorithm gives 84% accuracy with recognition time of 0.3s. Accuracy decreases as distance of hand from camera increases above 1.5feets. The gestures recognized here can be used further to develop an application of controlling the devices which will be very much helpful to the physically disabled and older persons who can’t move easily from one place to another.
Control, Security, and Risk in the Cloud

Abstract This chapter discusses the risks in cloud computing. Concerns are often raised about decreased customer control and increased provider control of data in clouds, particularly regarding data security (confidentiality, integrity, and availability), fuelled perhaps by the relative lack of information available to customers regarding details of providers' components, suppliers, and mechanics. Colocation risks may also exist. One concern is the leakage of data to others sharing the infrastructure. Another consideration is that if hardware thought to contain a third party's target data is seized by authorities, data of other tenants sharing that hardware may be exposed also. Ultimately, cloud services differ in the degree of control and flexibility afforded to customers (and accordingly in their responsibility for security), and the extent to which providers or sub-providers can access user data. Much depends on a service's type and design. Prospective cloud users may manage their cloud risks not just through technological or contractual means, but also through insurance.
Multisets in type theory

A multiset consists of elements, but the notion of a multiset is distinguished from that of a set by carrying information of how many times each element occurs in a given multiset. In this work we will investigate the notion of iterative multisets, where multisets are iteratively built up from other multisets, in the context Martin-L\"of Type Theory, in the presence of Voevodsky's Univalence Axiom. Aczel 1978 introduced a model of constructive set theory in type theory, using a W-type quantifying over a universe, and an inductively defined equivalence relation on it. Our investigation takes this W-type and instead considers the identity type on it, which can be computed from the Univalence Axiom. Our thesis is that this gives a model of multisets. In order to demonstrate this, we adapt axioms of constructive set theory to multisets, and show that they hold for our model.
Mathcad Functions For Thermodynamic Analysis Of Ideal Gases

Data from "The Chemkin Thermodynamic Data Base" were used to generate MathCAD functions for the molar specific enthalpy, internal energy, entropy, specific heat at constant volume, and the specific heat at constant pressure for twelve chemical species of the carbonhydrogen-oxygen-nitrogen system.The functions for oxygen and nitrogen were then used to generate ideal gas functions for air, including functions for relative pressure and relative volume.The MathCAD functions were made available for students in ME 242 Thermodynamics II and in ME 448/548 Internal Combustion Engines.The ideal gas functions were generated to ease the complication of using tabulated data for ideal gas properties, to allow parametric studies of thermodynamic systems using ideal gases, and to enable the students to generate relative pressure and relative volume functions for substances other than air.The details and usage of the ideal gas MathCAD functions are discussed, and specific examples of their application to problems in thermodynamics and combustion are presented.
Short and long-term impact of trade openness on financial development in Sub-Saharan Africa

The finance–openness debate has remained a complex one to date. Some studies argue that trade and capital account openness may promote financial development by enhancing foreign direct and portfolio investments. Other studies argue that financial development may improve trade policy and openness. Yet, one challenge faced by researchers in their quest to unravel the finance–openness debate is the lack of measures of trade openness that take a country's global interaction and interconnectedness into account. Our study addresses this challenge by extending a recently proposed index of trade openness to a panel data setting, and by examining the short- and long-term impact of trade openness on financial development for a panel of 43 sub-Saharan African (SSA) countries over the period 1996 to 2014. We test the performance of the pooled mean group (PMG) estimator against the dynamic fixed-effects (DFE) and the mean group (MG) estimators using the standard Hausman test, in order to ensure that the most appropriate estimator is used to estimate our dynamic, distributed lag model. We use the new measure of openness for the SSA countries to measure their interaction and interconnectedness with each other and find that openness is associated with significant financial development in the long term. In the short term, the effect of openness on financial development is not clear, but the results suggest that it may be negative. We then divide the sample into low- and middle-income countries and find that openness enhances financial development in the low-income countries. By contrast, openness is detrimental to financial development in the middle-income countries. This finding suggests a non-linear relationship between financial development and openness. We take the analysis a step further by examining the role of governance, human capital development, and infrastructural development, as these are major issues in SSA countries. We find that governance, human capital development, and infrastructure development are critical to financial development, particularly in the long term. In other words, these factors help to better explain the openness–finance relationship. Besides, they are important factors that policymakers should take into account when pursuing openness, financial development and a growth agenda.
PaperCraft3D: Paper-Based 3D Modeling and Scene Fabrication

A 3D modeling system with all-inclusive functionality is too demanding for a casual 3D modeler to learn. There has been a shift towards more approachable systems, with easy-to-learn, intuitive interfaces. However, most modeling systems still employ mouse and keyboard interfaces, despite the ubiquity of tablet devices and the benefits of multi-touch interfaces. We introduce an alternative 3D modeling and fabrication paradigm using developable surfaces, inspired by traditional papercrafting, and we implement it as a complete system designed for a multi-touch tablet, allowing a user to fabricate 3D scenes. We demonstrate the modeling and fabrication process of assembling complex 3D scenes from a collection of simpler models, in turn shaped through operations applied to virtual paper. Our fabrication method facilitates the assembly of the scene with real paper by automatically converting scenes into a series of cutouts with appropriately added fiducial markers and supporting structures. Our system assists users in creating occluded supporting structures to help maintain the spatial and rigid properties of a scene without compromising its aesthetic qualities. We demonstrate several 3D scenes modeled and fabricated in our system, and evaluate the faithfulness of our fabrications relative to their virtual counterparts and 3D-printed fabrications.
Intelligent digital image firewall system for filtering privacy or sensitive images

As the commonest part of social networks, sharing images in social network not only provides more information, but also gives more intuitive view than text. However, images also can leak out information more easily than text, so the audit of image content is particularly essential. The disclosure of a tiny image, which involves sensitive information about individual, society even the state, may trigger a series of serious problems. In this paper, we design a kind of intelligent image firewall to detect and filter sensitive or privacy images. Two different approaches of the firewall are proposed. In the first approach, we propose an image firewall based on joint sparse representation, which can provide accurate and robust privacy prediction, and also can provide rich spatial relationship information. In the second approach, we propose a method based on the deep learning (Faster RCNN), which can predict the privacy relationships or actions (like kiss, hug and hand in hand) among the persons of an image. Experimental results show the effectiveness of the two kinds of approaches.
Exact and heuristic methods for personalized display advertising in virtual reality platforms

In this paper, motivated from a real problem faced by an online Virtual Reality (VR) platform provider, we study a personalized advertisement assignment problem. In this platform users log in/out and change their virtual locations. A number of advertisers are willing to pay for ad locations to reach these users. Every time a user visits a new location, the company displays one of the ads. At the end of a fixed time horizon, a reward is collected which depends on the number of ads of each advertiser displayed to different users. The objective is to assign ads dynamically to maximize the expected reward. The problem is studied in a framework where the behaviors of users are modeled with two-state continuous-time Markov processes. We describe two exact and four heuristic algorithms. We compare these algorithms and conduct a sensitivity analysis over problem and algorithm specific parameters. These are the main contributions of the current paper. Exact algorithms suffer from the curse of dimensionality, hence, heuristic methods might be considered instead in some cases. However, exact methods can also be used as part of heuristics since the experimental analysis demonstrates that they are robust for parameters that influence the computational requirements.
Mitigating the One-Use Restriction in Attribute-Based Encryption

We present a key-policy attribute-based encryption scheme that is adaptively secure under a static assumption and is not directly affected by an attribute “one-use restriction”. Our construction improves upon the only other such scheme (Takashima ’17) by mitigating its downside of a ciphertext size that is dependent on the maximum size of any supported attribute set.
Low-Resolution Face Recognition with Single Sample per Person via Domain Adaptation

Numerous low-resolution (LR) face images are captured by a growing number of surveillance cameras nowadays. In some particular applications, such as suspect identification, it is required to recognize an LR face image captured by the surveillance camera using only one high-resolution (HR) profile face image on the ID card. This leads to LR face recognition with single sample per person (SSPP), which is more challenging than conventional LR face recognition or SSPP face recognition. To address this tough problem, we propose a Boosted Coupled Marginal Fisher Analysis (CMFA) approach, which unites domain adaptation and coupled mappings. An auxiliary database containing multiple HR and LR samples is introduced to explore more discriminative information, and locality preserving domain adaption (LPDA) is designed to realize good domain adaptation between SSPP training set (target domain) and auxiliary database (source domain). We perform LPDA on HR and LR images in both domains, then in the domain adaptation space we apply CMFA to learn the discriminative coupled mappings for classification. The learned coupled mappings embed knowledge from the auxiliary dataset, thus their discriminative ability is superior. We extensively evaluate the proposed method on FERET, LFW and SCface database, the promising results demonstrate its effectiveness on LR face recognition with SSPP.
Augmented Mitotic Cell Count Using Field of Interest Proposal

Histopathological prognostication of neoplasia including most tumor grading systems are based upon a number of criteria. Probably the most important is the number of mitotic figures which are most commonly determined as the mitotic count (MC), i.e. number of mitotic figures within 10 consecutive high power fields. Often the area with the highest mitotic activity is to be selected for the MC. However, since mitotic activity is not known in advance, an arbitrary choice of this region is considered one important cause for high variability in the prognostication and grading. In this work, we present an algorithmic approach that first calculates a mitotic cell map based upon a deep convolutional network. This map is in a second step used to construct a mitotic activity estimate. Lastly, we select the image segment representing the size of ten high power fields with the overall highest mitotic activity as a region proposal for an expert MC determination. We evaluate the approach using a dataset of 32 completely annotated whole slide images, where 22 were used for training of the network and 10 for test. We find a correlation of r=0.936 in mitotic count estimate.
oTree: Implementing experiments with dynamically determined data quantity

oTree (Chen et al., 2015) provides an excellent platform and device independent open-source software environment for creating experiments. In some scenarios, namely when dealing with a large or dynamic quantity of data, oTree’s design makes it hard to avoid error-prone repetitive coding. This article presents a way of realizing dynamic and flexible data collection that is easy to implement and follows the principles of good software engineering. A market scenario is used as an example and basis for an illustrative implementation which is also provided along with this article. A software package is presented that extends oTree’s capabilities of live data monitoring and data export of dynamically collected data.
The multi-individuality of handwriting

The scientific research conducted so far as well as rich practical expert experience point to the fact that handwriting is individual to each person. On the other hand, there are quite infrequent cases of developing two or more different styles of writing by the same person, during learning-to-write process. These various styles of handwriting are used interchangeably, either spontaneously or intentionally; the effect being as if different persons can be attributed to authorship. The Author proposes to refer to this barely known phenomenon as “the multi-individuality of handwriting”. The identification of writer of this type of handwriting is possible, however may pose serious problems. Variations of handwriting of the same person may lead forensic examiners to faulty expert opinion, if a known sample does not reflect the writing style of a questioned entry. The purpose of this paper is to present the results of study of multi-individual handwriting.