Reviewerly/exHarmony huggingface dataset:
An Occlusion and Noise-aware Stereo Framework Based on Light Field Imaging for Robust Disparity Estimation

Stereo vision is widely studied for depth information extraction. However, occlusion and noise pose significant challenges to traditional methods due to failure in photo consistency. In this paper, an occlusion and noise-aware stereo framework named ONAF is proposed to get a robust depth estimation by integrating the advantages of correspondence cues and refocusing cues from light field(LF). ONAF consists of two special depth cue extractors: correspondence depth cue extractor (CCE) and refocusing depth cue extractor (RCE). CCE extracts accurate correspondence depth cues in occlusion areas based on multi-direction Ray-Epipolar Plane Images(Ray-EPIs) from LF, which are more robust than traditional multi-direction EPIs. RCE generates accurate refocusing depth cues in noise areas, benefitting from the many-to-one integration strategy and the directional perception of texture and occlusion based on multi-direction focal stacks from LF. Attention mechanism is introduced to complementarily fuse CCE and RCE to generate optimum depth maps. The experimental results prove the effectiveness of ONAF, which outperforms state-of-the-art disparity estimation methods, especially in occlusion and noise areas.
Image Watermarking Techniques and Applications

To determine if the data being displayed is real or has been manipulated in any manner, digital image authentication is an essential and cutting-edge directive. Various watermarking methods have been developed to meet industrial purposes. One method of watermarking digital images is to include the watermark data within a multimedia content. It offers a way to guarantee the integrity of the image, it has demonstrated tremendous value in today's technological world. Watermarking is used for content detection and authentication, copyright protection and tamper detection. Steganography is used for hiding secret data inside regular, non-secret file or message so that it cannot be detected and can then be extracted when it gets to its destination. This study reviews current developments in digital image watermarking techniques and provides data on typical procedures. It also discusses the drawbacks of each technique and explore hybrid digital image watermarking methods.
VQA-GNN: Reasoning with Multimodal Knowledge via Graph Neural Networks for Visual Question Answering

Visual question answering (VQA) requires systems to perform concept-level reasoning by unifying unstructured (e.g., the context in question and answer; “QA context”) and structured (e.g., knowledge graph for the QA context and scene; “concept graph”) multimodal knowledge. Existing works typically combine a scene graph and a concept graph of the scene by connecting corresponding visual nodes and concept nodes, then incorporate the QA context representation to perform question answering. However, these methods only perform a unidirectional fusion from unstructured knowledge to structured knowledge, limiting their potential to capture joint reasoning over the heterogeneous modalities of knowledge. To perform more expressive reasoning, we propose VQA-GNN, a new VQA model that performs bidirectional fusion between unstructured and structured multimodal knowledge to obtain unified knowledge representations. Specifically, we inter-connect the scene graph and the concept graph through a super node that represents the QA context, and introduce a new multimodal GNN technique to perform inter-modal message passing for reasoning that mitigates representational gaps between modalities. On two challenging VQA tasks (VCR and GQA), our method outperforms strong baseline VQA methods by 3.2% on VCR (Q-AR) and 4.6% on GQA, suggesting its strength in performing concept-level reasoning. Ablation studies further demonstrate the efficacy of the bidirectional fusion and multimodal GNN method in unifying unstructured and structured multimodal knowledge.
Are Children ‘Lazy Learners’? A Comparison of Natural and Machine Learning of Stress

Do children acquire rules for main stress assignment or do they learn stress in an exemplar-based way? In the language acquisition literature, the former approach has been advocated without exception: although they hear most words produced with their appropriate stress pattern, children are taken to extract rules and do not store stress patterns lexically. The evidence for a rule-based approach is investigated and it will be argued that in the literature this approach is preferred due to an extremely simplified interpretation of exemplar-base d models. We will report experiments showing that Instance-Based Learning, an exemplar-based model, makes the same kinds of stress related errors in production that children make: (i) the amount of production errors is related to metrical markedness, and (ii) stress shifts and errors with respect to the segmental and syllabic structure of words typically take the form of a regularization of stress patterns. InstanceBased Learning belongs to a class of Lazy Learning algorithms. In these algorithms, no explicit abstractions in the form of decision trees or rules are derived;
Improved Convergence of Iterative Ontology Alignment using Block-Coordinate Descent

A wealth of ontologies, many of which overlap in their scope, has made aligning ontologies an important problem for the semantic Web. Consequently, several algorithms now exist for automatically aligning ontologies, with mixed success in their performances. Crucial challenges for these algorithms involve scaling to large ontologies, and as applications of ontology alignment evolve, performing the alignment in a reasonable amount of time without compromising on the quality of the alignment. A class of alignment algorithms is iterative and often consumes more time than others while delivering solutions of high quality. We present a novel and general approach for speeding up the multivariable optimization process utilized by these algorithms. Specifically, we use the technique of block-coordinate descent in order to possibly improve the speed of convergence of the iterative alignment techniques. We integrate this approach into three well-known alignment systems and show that the enhanced systems generate similar or improved alignments in significantly less time on a comprehensive testbed of ontology pairs. This represents an important step toward making alignment techniques computationally more feasible.
Discriminative Clustering via Generative Feature Mapping

Existing clustering methods can be roughly classified into two categories: generative and discriminative approaches. Generative clustering aims to explain the data and thus is adaptive to the underlying data distribution; discriminative clustering, on the other hand, emphasizes on finding partition boundaries. In this paper, we take the advantages of both models by coupling the two paradigms through feature mapping derived from linearizing Bayesian classifiers. Such the feature mapping strategy maps nonlinear boundaries of generative clustering to linear ones in the feature space where we explicitly impose the maximum entropy principle. We also propose the unified probabilistic framework, enabling solvers using standard techniques. Experiments on a variety of datasets bear out the notable benefit of our method in terms of adaptiveness and robustness.
Using Mobile Technology in a Construction Management “Hands-On” Laboratory

This study discusses the introduction and use of the iPad mobile device in a freshman level construction management "hands-on" materials and methods laboratory.The devices are incorporated into the course in four ways: (1) for plan reading; (2) for RFI documentation, including the development of the RFI, highlighting of plans, and attachment of photos; (3) for presentation and documentation of "Tool Box" safety meetings; and (4) for documenting Daily Reports.This paper discusses the use of mobile technologies in a "hands-on" laboratory setting, the challenges of the incorporation, lessons learned, and student reactions to the use of the mobile device.
An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach

In this modern era, people utilise the web to share information and to deliver services and products. The information seekers use different search engines (SEs) such as Google, Bing, and Yahoo as tools to search for products, services, and information. However, web spamming is one of the most significant issues encountered by SEs because it dramatically affects the quality of SE results. Web spamming’s economic impact is enormous because web spammers index massive free advertising data on SEs to increase the volume of web traffic on a targeted website. Spammers trick an SE into ranking irrelevant web pages higher than relevant web pages in the search engine results pages (SERPs) using different web-spamming techniques. Consequently, these high-ranked unrelated web pages contain insufficient or inappropriate information for the user. To detect the spam web pages, several researchers from industry and academia are working. No efficient technique that is capable of catching all spam web pages on the World Wide Web (WWW) has been presented yet. This research is an attempt to propose an improved framework for content- and link-based web-spam identification. The framework uses stopwords, keywords’ frequency, part of speech (POS) ratio, spam keywords database, and copied-content algorithms for content-based web-spam detection. For link-based web-spam detection, we initially exposed the relationship network behind the link-based web spamming and then used the paid-link database, neighbour pages, spam signals, and link-farm algorithms. Finally, we combined all the content- and link-based spam identification algorithms to identify both types of spam. To conduct experiments and to obtain threshold values, WEBSPAM-UK2006 and WEBSPAM-UK2007 datasets were used. A promising F-measure of 79.6% with 81.2% precision shows the applicability and effectiveness of the proposed approach.
TAP: An Effective Personality Representation for Inter-Agent Adaptation in Games

Tactical Agent Personality (TAP) is a modeling concept to capture tactical patterns in game agents, based on a personality concept introduced by Tan and Cheng (2007), to allow behavior adaptation to different play styles. We introduced a weighted sequential topology to the actions set to capture tactical preferences rather than individual action preferences. This produces a personality representation of much higher expressive power that improves the adaptation performance and subsequently enables a larger variety of action genres to be adaptable. A TAP-based learning framework is then constructed and it is shown to perform better than the one based on the previous agent personality. Consequently, we also implement an RPG scenario that demonstrates its ability to generate adaptive plausible behavior in a much larger variety of action genres.
A New Short Signature Scheme with Random Oracle from Bilinear Pairings

In this paper, we propose a new and efficient short signature scheme from the bilinear pairings. Our scheme is constructed by bilinear inverse-square Diffie-Hellman problem (BISDHP) and does not require any special hash function. The exact security proofs are also explained in the random Oracle model. We give the implementation and comparison results of our proposed signature scheme with the signature scheme proposed by Boneh, Lynn, Shacham (BLS) and Zhang, Safavi, Susilo (ZSS). Furthermore, we use this signature scheme to construct a ring signature scheme.
Ontology-Based Information Gathering and Categorization from the Internet

In this paper, we propose a new method to develop more intelligent navigation system for the Internet using ontologies. We implemented a system called IICA (Intelligent Information Collector and Analyzer)which helps people to acquire knowledge from information resources on the Internet by gathering and categorizing information. We tested IICA for tasks on the World Wide Web (WWW) and the network news. The results of the experiments indicated that the ontology-based approach enable us to use heterogeneous information resources on the wide-area such as the WWW and the network news.
Reaching Out To High School Girls: The Role Of A Student Organization In Developing An On Campus Technology Workshop

Women and girls will comprise at least half of the available science, engineering, and technology talent pool.Therefore, it becomes imperative to attract more women and girls into these disciplines.In 2002 at Purdue University, the student group Women in Technology invited a select number of high school juniors who were at risk of losing interest in math, science, and computers, and their parents to the Purdue campus for an all-day workshop.The program was planned, designed, and executed by Women in Technology students.Its purpose was to give the high school girls who participated an understanding of the various majors available in the School of Technology through tours, presentations by women faculty from each discipline, a question and answer session with students, and hands-on laboratory experiences.In this paper, we will present an overview of the organization; discuss the lessons learned from the first Women in Technology Workshop, and suggest strategies for developing such workshops into vital components of efforts to recruit more high school girls into the fields of technology, engineering, and science.
LANGUAGE ATTITUDES AMONG COLLEGE-STUDENTS TOWARD ENGLISH IN STAI-JM TANJUNG PURA

This study deals with language attitudes among college students in STAI JM Tanjung Pura toward English. It was aimed in investigating the types of the attitudes among the college-students, the levels of attitudes by the college-students at STAI-JM Tanjung Pura towards English realized and the reason or the factors why do they have the attitude such the way it is. This study used descriptive qualitative method. The subjects of this research were the college-students from Islamic Economics Major (Ekonomi Islam) for second semester in STAI-JM Tanjung Pura. The objects of this study were the language attitudes of the college-students in STAI-JM Tanjung Pura towards English. The data were analysed by applying Interactive models techniques by Miles, Huberman & Saldana analysis. Based on the data analysis, the college-students in STAI-JM Tanjung Pura showed positive attitudes towards English. Then the college-students had positive attitude towards English in the level of receiving, valuing and organizing values. On the other hand the college-students had negative attitude towards English in the level of responding and internalizing values. The college-students had positive attitude towards English because they are proud of using English and they were aware of English language norms. But on the other hand they were not loyal to use English in their daily interaction in the class.  Keywords: attitude , English teacher , gender , languageand teaching activities.
Development Of A Graduate Certificate In Information Assurance

The growing need for information security professionals is well documented.Very few universities offer more than a single cryptography course, and even fewer engineering departments have a presence in this area.The end result is a severe shortage of graduates proficient in the technology and policy issues critical to the security of the information infrastructure.While several universities have started programs to address these needs, this only solves a small part of the problem.According to the National Strategy to Secure CyberSpace 1 released by the president of United States in 2003, "Many cyber vulnerabilities exist because of a lack of cyber security awareness on the part of computer users, systems administrators, technology developers, procurement officials, auditors, chief information officers, chief executive officers, and corporate boards.Such awareness-based vulnerabilities present serious risks to critical infrastructure regardless of whether they exist within the infrastructure itself.A lack of trained personnel and the absence of widely accepted, multi-level certification programs for cyber security professionals complicate the task of addressing cyber vulnerabilities."In response to the need to for additional education Iowa State University and its Information Assurance faculty created an Information Assurance graduate Certificate
Facilitating Graduate Students’ Professional Development: Implementation and Evaluation of Learning Activities

Doctoral education is criticized for its lack of preparation of doctoral students for careers outside of academia [1][2] .Multiple stakeholders including researchers, educators, administrators, and industry leaders have pointed out the necessity to offer systematic training and professional development opportunities to doctoral students to prepare them for a broader range of academic as well as nonacademic career opportunities [3][4][5] .In this context, "Preparing Future Professionals", a graduate-level course, was designed and implemented to facilitate the development of graduate students in their skills, roles, and responsibilities as global citizens and future professionals in business and corporate environment.In the process of facilitating graduate students' professional skills and attributes, the research team developed interactive learning activities that centered on the theme of helping the transition of graduate students' roles to future professionals in businesses and industry.These learning activities cover a variety of critical aspects in the transition to business and industry, such as skills and competencies, career management, organization types and cultures, roles and responsibilities, and balancing career and personal life.These interactive learning activities include, Cultivating Your Professional Identity; CARS (Context, Action, Result, Skills) Impact Statements; Creating a Networking Map; Job Description Analysis; Developing Job Search Strategies;
PENGARUH SEDUHAN RIMPANG KUNYIT KUNING (Curcuma longa Linn.) TERHADAP PEMAHAMAN BACAAN

Increasing globalization makes humans need the knowledge to compete globally. One way to increase knowledge is by reading. Reading comprehension is the process of interpreting a reading in order to gain a thorough knowledge of the passage. Therefore it is necessary to consume beverages to improve energy and cognitive function. In this study, the researcher used yellow turmeric rhizome steeping as an enhancer of cognitive function. The objective of this research was to determine the effect of consuming yellow turmeric rhizome steeping on the cognitive function which is reading comprehension. This study was quasi-experimental, comparative using pretest and post-test design, conducted on 30 men aged between 18-22 years. Participants were asked to do a reading comprehension test (pretest) than consume 200 cc of water mixed with 10 grams of yellow turmeric rhizome powder. Participants took rest for 90 minutes and asked to do a reading comprehension test (post-test). The measured data was the reading comprehension test score, in the form of a correct answer of 10 questions. Data were analyzed using Wilcoxon Signed Rank Test. The average score of correct answers increased very significantly, before consuming yellow turmeric steeping was 47,33 to 73,33 after consuming yellow turmeric rhizome steeping with p &lt; 0,001. Therefore yellow turmeric rhizome steeping increases reading comprehension.
MQTT-TLS profile of ACE

This document specifies a profile for the ACE (Authentication andAuthorization for Constrained Environments) to enable authorization inan MQTT-based publish-subscribe messaging system. Proof-of- possessionkeys, bound to OAuth2.0 access tokens, are used to authenticate andauthorize publisher and subscriber clients. The protocol relies on TLSfor confidentiality and server authentication.
Teaching Software Engineering to Undergraduate System Engineering Sudents

This paper describes the software engineering concepts that systems engineering students need to understand in order to effectively work with software engineers who may be members of their system engineering teams, both as students and as practitioners.Ways to introduce this material into systems engineering curricula are addressed.
Efficient clustering technique for k-anonymisation with aid of optimal KFCM

The k-anonymity model is a simple and practical approach for data privacy preservation. To minimise the information loss due to anonymisation, it is crucial to group similar data together and then anonymises each group individually. So that in this paper proposes a novel clustering method for conducting the k-anonymity model effectively. The clustering will be done by an optimal kernel based fuzzy c-means clustering algorithm (KFCM). In KFCM, the original Euclidean distance in the FCM is replaced by a kernel-induced distance. Here the objective function of the kernel fuzzy c-means clustering algorithm is optimised with the help of modified grey wolf optimisation algorithm (MGWO). Based on that, the collected data is grouped in an effective manner. The performance of the proposed technique is evaluated by means of information loss, time taken to group the available data. The proposed technique will be implemented in the working platform of MATLAB.
Mungo and StMungo: Tools for Typechecking Protocols in Java

We present two tools that support static typechecking of communication protocols in Java.Mungo associates Java classes with typestate specifications, which are state machines defining permitted sequences of method calls.StMungo translates a communication protocol specified in the Scribble protocol description language into a typestate specification for each role in the protocol by following the message sequence.Role implementations can be typechecked by Mungo to ensure that they satisfy their protocols, and then compiled as usual with javac.We demonstrate the Scribble, StMungo and Mungo toolchain via a typechecked POP3 client that can communicate with a real-world POP3 server.14.
Single Axis Passive Solar Tracker Performance Evaluation

A passive solar tracker was designed and constructed in GIAD Industrial Complex. The tracker was tested in Soba region, in the premises of the National Energy Research Center. The test consisted of two parts; the first was testing the tracking error by placing a pyranometer on the tracker and comparing the beam radiation readings with that of the maximum theoretical beam radiation possible if the tracker was tracking without errors. The second test was comparing the power output of 8, 50Wp photovoltaic modules attached onto the tracker in tracking mode to the same modules on the tracker fixed in a straight position. The array is inclined to 15.5o facing South. The results showed that most of the tracking error was within the range of 7.37 %. The photovoltaic array comparison test showed that the tracker is most effective in the morning hours from 9:00 to 11:00 and in the afternoon from 15:00 to 17:00. The increase of power output of the tracked array to the fixed array was 12.67% on the day of 9thDecember and 14.39% on the day of 11thApril.