Reviewerly/exHarmony huggingface dataset:
Adaptive Steganographic Scheme using a Variable Matrix Embedding

Steganography is the art of concealing secret information within digital media. In this paper, an adaptive steganographic scheme based on Faber-Schauder discrete wavelet transform (DWT) is proposed. Data is hidden in the details coefficients, which are divided into smooth and complex areas. In the smooth area, we hide one bit in every coefficient via a variable matrix embedding that hides 2n bits of data into 2n+1 coefficients while modifying at most n coefficients. In the complex area, data is hidden by substituting the least significant bits (LSBs) of the coefficients, and the optimal pixel adjustment procedure (OPAP) is utilised to minimise the modification. The performance is tested through experiments and comparison to literature. We obtain a good imperceptibility and embedding rate that respect the complexity of the cover image. We also reach a high level of security by using a correcting procedure that preserves the histogram in the smooth area.
A Human-Centered Data-Driven Planner-Actor-Critic Architecture via Logic Programming.

Recent successes of Reinforcement Learning (RL) allow an agent to learn policies that surpass human experts but suffers from being time-hungry and data-hungry. By contrast, human learning is significantly faster because prior and general knowledge and multiple information resources are utilized. In this paper, we propose a Planner-Actor-Critic architecture for huMAN-centered planning and learning (PACMAN), where an agent uses its prior, high-level, deterministic symbolic knowledge to plan for goal-directed actions, and also integrates the Actor-Critic algorithm of RL to fine-tune its behavior towards both environmental rewards and human feedback. This work is the first unified framework where knowledge-based planning, RL, and human teaching jointly contribute to the policy learning of an agent. Our experiments demonstrate that PACMAN leads to a significant jump-start at the early stage of learning, converges rapidly and with small variance, and is robust to inconsistent, infrequent, and misleading feedback.
Mutex Graphs and Multicliques: Reducing Grounding Size for Planning.

We present an approach to representing large sets of mutual exclusions, also known as mutexes or mutex constraints. These are the types of constraints that specify the exclusion of some properties, events, processes, and so on. They are ubiquitous in many areas of applications. The size of these constraints for a given problem can be overwhelming enough to present a bottleneck for the solving efficiency of the underlying solver. In this paper, we propose a novel graph-theoretic technique based on multicliques for a compact representation of mutex constraints and apply it to domain-independent planning in ASP. As computing a minimum multiclique covering from a mutex graph is NP-hard, we propose an efficient approximation algorithm for multiclique covering and show experimentally that it generates substantially smaller grounding size for mutex constraints in ASP than the previously known work in SAT.
PENGEMBANGAN MEDIA MAKET RUMAH ADAT UNTUK KETERAMPILAN BERBAHASA PEMELAJAR BIPA

The Indonesian Language for Foreign Speakers (BIPA) is one of the effective effort to internationalize The Indonesian language. To help students understand Indonesian, either language or culture, this research develop media traditional house mockups to be used in BIPA learning. By using three steps: Defining, Designing and Developing, this research is hoped to result learning products. From the validation stage, the results are obtained: validator (V1) = 4. According to the validity criteria, it is classified as a valid category with an achievement score of E = 4. The final stage, namely the assessment, includes trials on two BIPA students in Darma Persada University. The response of the learners to the media was good, with the number of students' questionnaire responses 116. The results illustrate that the learners positively accepted the learning media of traditional house mockups so that they were more motivated in learning Indonesian language skills. Therefore, it can be concluded that the developed traditional house media mockups can be used to train BIPA learners' language skills.
Modern Aspects of the Interpretation of the Term ‘Reprography’

There is interpretation of the term ‘reprografy’ on the basis of modern technologies receive fax copies of the images, texts, various documents. Analyses the most famous work of the ways and methods of copying by means of hardware-software complexes that have pulled together these and systematize scientific and practical experience in the world of inventors, scientists, engineers, which gave impetus and developed modern technologies of reprography, which are used for industrial needs and to address scientific and technological experimental tasks. There was analised understanding reprography as fax (not printing) copy the information direct or indirect reproduction on the photo- or sensitive material.The structural scheme, which explains the essence of modern technology as reprography facsimile copy (reproduction) information the direct or indirect method from the originals (analog or digital ID) at photo- or sensitive materials and documents (products) by means of simulation, nano-printing, 3D-printing. The modern means of the hardware-software complexes that provide high accuracy and frequency of reproduction information in a visual-, audio- and material forms.On the basis of an understanding of the world of intellectual property as a source of production of printed and electronic publications, the term ‘Reprography’ is treated as a branch of science, technology and industry, covering a set of methods, processes and means of reproduction copies the originals. Reprography is based on the use of media, changing physical and physico-chemical properties under the action of the corresponding radiation or other type of energy and can be seen as a component of digital technologies ‘is a modern system of registration and dissemination of information by means of reproduction’.
Proxy Functions for Approximate Reinforcement Learning

Approximate Reinforcement Learning (RL) is a method to solve sequential decisionmaking and dynamic control problems in an optimal way. This paper addresses RL for continuous state spaces which derive the control policy by using an approximate value function (V-function). The standard approach to derive a policy through the V-function is analogous to hill climbing: at each state the RL agent chooses the control input that maximizes the right-hand side of the Bellman equation. Although theoretically optimal, the actual control performance of this method is heavily influenced by the local smoothness of the V-function; a lack of smoothness results in undesired closed-loop behavior with input chattering or limit-cycles. To circumvent these problems, this paper provides a method based on Symbolic Regression to generate a locally smooth proxy to the V-function. The proposed method has been evaluated on two nonlinear control benchmarks: pendulum swing-up and magnetic manipulation. The new method has been compared with the standard policy derivation technique using the approximate V-function and the results show that the proposed approach outperforms the standard one with respect to the cumulative return.
Ontology-Schema Based Query by Example

The Web has evolved from a network of linked documents to one where both documents and data are linked, resulting in what is commonly known as the Web of Linked Data, that includes a large variety of data usually published in RDF from multiple domains. Intuitive ways of accessing RDF data become increasingly important since the standard approach would be to run SPARQL queries. However, this can be extremely difficult for non-experts users. In this paper, we address the problem of question answering over RDF. Given a natural language question or a keyword search string, our goal is to translate it into a formal query as SPARQL that captures the information needed. We propose Von-QBE which is a schema-based approach to query over RDF data without any previous knowledge about the ontology entities and schema. This is different from the-state-of-art since the approaches are instance-based. However, it can be unfeasible using such approaches in big data scenarios where the ontology base is huge and demands a large amount of computational resource to keep the knowledge base in memory. Moreover, most of these solutions need the knowledge base triplified, which can be a hard task for legacy bases. Von-QBE results are promising for the two real benchmarks evaluated, considering that only the ontology schema is used to generate SPARQL queries.
Universal Derivations v0.5

Universal Derivations (UDer) is a collection of harmonized lexical networks capturing word-formation, especially derivational relations, in a cross-linguistically consistent annotation scheme for many languages. The annotation scheme is based on a rooted tree data structure, in which nodes correspond to lexemes, while edges represent derivational relations or compounding.The current version of the UDer collection contains eleven harmonized resources covering eleven different languages.
"E. T. A. Hoffmann’s complex" in the cycle of stories and drama scenes "Earth Axis" by Valery Bryusov (1901-1907)

In this article we explore "E. T. A. Hoffmann’s complex", which includes real and imaginary worlds, the problem of the mechanisation of life and society, the duality, the romantic irony and grotesque in the series of short stories "Earth Axis" by Valery Bryusov. Following E. T. A. Hoffmann’s tradition, Velery Bryusov creates a special type of romantic the dual world based on the principle of mirror reflection of the real world. The dominance of the unreal world leads to the absorption of the main character. The problem of mechanisation of a life and a man in the series is manifested in the tendency of loss of spirituality in society and an attempt to fill the spiritual emptiness with "inanimate" objects ("Flat", "Defence"). Valery Bryusov creates a grotesque picture of a society ("Earth", "Rise of the Machines"), where the living changes are replaced by the nonliving (machines). Romantic irony and grotesque, which are destructive, become a stylistic device in the work of Valery Bryusov.
Vanishing-Error Approximate Degree and QMA Complexity.

The $\epsilon$-approximate degree of a function $f\colon X \to \{0, 1\}$ is the least degree of a multivariate real polynomial $p$ such that $|p(x)-f(x)| \leq \epsilon$ for all $x \in X$. We determine the $\epsilon$-approximate degree of the element distinctness function, the surjectivity function, and the permutation testing problem, showing they are $\Theta(n^{2/3} \log^{1/3}(1/\epsilon))$, $\tilde\Theta(n^{3/4} \log^{1/4}(1/\epsilon))$, and $\Theta(n^{1/3} \log^{2/3}(1/\epsilon))$, respectively. Previously, these bounds were known only for constant $\epsilon.$ We also derive a connection between vanishing-error approximate degree and quantum Merlin--Arthur (QMA) query complexity. We use this connection to show that the QMA complexity of permutation testing is $\Omega(n^{1/4})$. This improves on the previous best lower bound of $\Omega(n^{1/6})$ due to Aaronson (Quantum Information & Computation, 2012), and comes somewhat close to matching a known upper bound of $O(n^{1/3})$.
Modeling the Network of Municipal Solid Waste Separation Factors using Fuzzy Cognitive Mapping: A Case Study in Tehran

Municipal solid waste management is a major challenge, especially in metropolises. This research focuses on a non-technical issue in municipal solid waste management named municipal solid waste separation at the source and seeks to find the best policy in terms of model results. Source separation for recycling has been recognized as a way to achieve sustainable municipal solid waste (MSW) management. The research questions are what factors affect municipal solid waste separation at the source, what are the relationships between them, and which is the best policy to increase municipal solid waste separation at the source. In this research delphi analysis and fuzzy cognitive mapping are used. After identifying 29 factors affecting the waste separation at the source and adjusting them to 9 factors according to the experts' opinions, due to direct causal relationships between the factors and their analysis with the fuzzy cognitive mapping, the factors network affecting the generation of waste were designed. By delphi analysis and expert gathering, three policies were applied to increase waste separation at the source. After analyzing each of the policies, the percentage of change in waste separation was calculated using fuzzy cognitive mapping and the most favorable policy, respectively, was the second policy (Emphasis on culturing), the first policy (Emphasis on encouragement and fines) and, ultimately, The third policy (Emphasis on physical infrastructure) was identified.
An encoder-decoder based grapheme-to-phoneme converter for Bangla speech synthesis

This paper proposes an encoder-decoder based sequence-to-sequence model for Grapheme-to-Phoneme (G2P) conversion in Bangla (Exonym: Bengali). G2P models are key components in speech recognition and speech synthesis systems as they describe how words are pronounced. Traditional, rule-based models do not perform well in unseen contexts. We propose to adopt a neural machine translation (NMT) model to solve the G2P problem. We used gated recurrent units (GRU) recurrent neural network (RNN) to build our model. In contrast to joint-sequence based G2P models, our encoder-decoder based model has the flexibility of not requiring explicit grapheme-to-phoneme alignment which are not straight forward to perform. We trained our model on a pronunciation dictionary of (approximately) 135,000 entries and obtained a word error rate (WER) of 12.49% which is a significant improvement from the existing rule-based and machine-learning based Bangla G2P models.
Memory Management in Resource-Bounded Agents.

In artificial intelligence, multi agent systems constitute an interesting typology of society modeling, and have in this regard vast fields of application, which extend to the human sciences. Logic is often used to model such kind of systems as it is easier to verify the explainability and validation, so for this reason we have tried to manage agents' memory extending a previous work by inserting the concept of time.
A New Structure of Stereo Algorithm Using Pixel Based Differences and Weighted Median Filter

This paper proposed a new algorithm for stereo vision system to obtain depth map or disparity map. The proposed stereo vision algorithm consists of three stages, matching cost computation, disparity optimization and disparity refinement. The first stage starts with matching cost computation, where pixel based differences methods are used. The matching methods are the combination of Absolute Difference (AD) and Gradient Matching (GM). Next, the second stage; disparity optimization utilizes Winner-Takes-All (WTA) technique to normalize the disparity values of each pixel of the image. Finally, for disparity refinement stage, weighted median (WM) filter is added to reduce and smother the noise on the disparity map.
Matching Capabilities of Prediction to Communication and Computing for Proactive VR Video Streaming.

Proactive tile-based video streaming can avoid motion-to-photon latency of wireless virtual reality (VR) by computing and delivering the predicted tiles to be requested before playback. All existing works either focus on the task of tile prediction or on the tasks of computing and communications, overlooking the facts that these successively executed tasks have to share the same duration to avoid the latency and the quality of experience (QoE) of proactive VR streaming depends on the worst performance of the three tasks. In this paper, we jointly optimize the duration of the observation window for predicting tiles and the durations for computing and transmitting the predicted tiles to maximize the QoE given arbitrary predictor and configured resources. We obtain the global optimal solution with closed-form expression by decomposing the formulated problem equivalently into two subproblems. With the optimized durations, we find a resource-limited region where the QoE can be improved effectively by configuring more resources, and a prediction-limited region where the QoE can be improved with a better predictor. Simulation results using three existing tile predictors with a real dataset demonstrate the gain of the joint optimization over the non-optimized counterparts.
LibGuides: Diverse Curriculum: Get Started

This guide is a list of resources to help Professors think about creating a diverse curriculum.
Assessing Cyber Security of Innovations for Climate Disaster Resilience: An Extension to the Test and Implementation Framework of the BRIGAID program

In the coming decades, more frequent and more extensive climate disasters such as coastal and river floods, droughts, extreme weather, and wildfires can be expected worldwide. Innovations will be required to face this grand challenge. The BRIGAID project developed a methodology consisting of a Test- and Implementation Framework and a set of practical tools. BRIGAIDs tools are offered to support efficient development and market introduction of promising innovations. The methodology in its present state still requires an extension to cover cybersecurity issues. It should be assessed what components are key in innovation projects and where and whether cybersecurity is relevant within the TIF. The proposed research will establish an assessment for the cybersecurity readiness of BRIGAID’s innovation projects. The goal here is to give the innovation projects an indication on their level of security and cybersecurity readiness. We selected GM4W and QoAir as representative innovation projects for a case study consisting of a cyber risk assessment. We find that key cyber components for innovation projects benefit the identification and mitigation of cyber threats. When assessing an innovation, the cyber components serve as a starting point of the assessment. We used SecRAM as the risk assessment method in this study and aimed to test whether the method applies to the risk assessment of innovation projects. We conclude that the SecRAM method serves its purpose and applies to the innovation projects in the context of this study. The risk assessments applied to different cases with contrasting structures and enabled us to identify and mitigate cyber threats effectively. The use of SecRAM also applied to the design of the TIF cybersecurity extension. The tool consists of questions that score the innovation projects based on confidentiality, integrity, and availability to raise concerns on the cybersecurity readiness. The acceptance and perceived usefulness of the tool need validation among innovators. Future research should extend the involvement of innovators and experts to the entire risk assessment phase.
Design of a Solver for Multi-Agent Epistemic Planning.

As the interest in Artificial Intelligence continues to grow it is becoming more and more important to investigate formalization and tools that allow us to exploit logic to reason about the world. In particular, given the increasing number of multi-agents systems that could benefit from techniques of automated reasoning, exploring new ways to define not only the world's status but also the agents' information is constantly growing in importance. This type of reasoning, i.e., about agents' perception of the world and also about agents' knowledge of her and others' knowledge, is referred to as epistemic reasoning. In our work we will try to formalize this concept, expressed through epistemic logic, for dynamic domains. In particular we will attempt to define a new action-based language for multi-agent epistemic planning and to implement an epistemic planner based on it. This solver should provide a tool flexible enough to be able to reason on different domains, e.g., economy, security, justice and politics, where reasoning about others' beliefs could lead to winning strategies or help in changing a group of agents' view of the world.
Message from IEEE TrustCom 2019 General Chairs

As the General Chairs and on behalf of the Organizing Committee of the 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom-2019), we would like to express our warmest welcome to all participants that attend the conference and associated workshops/symposia at Rotorua, New Zealand, 5 -8 August, 2019.Rotorua is worldrenowned for its geysers, bubbling mud pools, natural hot springs, adventure sports, and its showcase of the Māori culture.It is also located near other picturesque destinations such as Lake Taupo, Tongariro National Park and the skiing fields at Mount Ruapehu.We are pleased that the TrustCom conference is held in Rotorua this year.A top-ranked conference, IEEE TrustCom has become a premier international conference in the trust, security and privacy areas, aiming at bringing together researchers and practitioners working on trusted computing and communications to present and discuss emerging ideas and trends in this highly challenging research field.IEEE TrustCom 2019 has attracted many high-quality research papers which highlight the foundational work that strives to push beyond limits of existing and emerging technologies, including experimental efforts, innovative systems, and investigations that identify weaknesses in the existing trust, security and privacy services.
LibGuides: Circulations / Lending Services: Holds & Recalls

The main purpose of Circulation /Lending services is for issuing and receiving of library books for the library and other services pertinent to the Lending section. A service that makes the circulation of library materials possible, by implementing proced
Solar parabolic trough thermal energy output forecasting based on K-Nearest Neighbors approach

Abstract Solar thermal output forecasting that is derived from the solar irradiance forecasting, is very much exposed to high forecasting error. This is because of the heavy dependence on the solar irradiance prediction accuracy that could be very low in certain situations owing to the high uncertainty in weather conditions. By considering this fact, this paper proposes to develop a solar thermal output forecasting model using measured solar irradiance data, instead of the predicted data. The proposed model applies K-Nearest Neighbors (K-NN) algorithm to generate 24-hour ahead forecasting data on solar thermal output from a solar parabolic trough system For the purpose of illustrating the forecasting model performance, Kuala Lumpur, Malaysia is used as a case study, with PolyTrough 1800 model is selected as the solar parabolic trough collector under investigation. Simulation has been carried out using Matlab software to verify the effectiveness of the proposed K-NN-based forecasting model. The results show that the model is able to produce acceptable results in certain conditions.
Decolorization of Digital Pathology Images: A Comparative Study

The major demerit of color to gray conversion is the loss of visually important image features.Digital pathology images are treated as the gold Standard for detection of various diseases, especially for the different types of cancer.Digital pathology images are color in nature, i.e. each pixel is a color vector represented by three values.Thus, the processing of these images requires high computational time.If these color images are converted into one dimensional gray images, then processing time can be reduced, which will help the Computer-Aided Diagnosis (CAD) system significantly for accurate classification and detection of different types of diseases.Therefore, this study focuses on the fast conversion of color digital pathology images into gray images.In order to do that, seven well established color to gray conversion, techniques have been employed for producing gray images with salient features.The outcomes have been validated visually and numerically.