Reviewerly/exHarmony huggingface dataset:
Unified and Stable Project: “Ushering in the Future”

Why do we need projects? What is the need to carry out a project? What is the ultimate-goal of any project? These are a few thoughts that crop up in one’s mind while trying to develop and implement any project. The motivations of this paper are to establish the unified functional and non-functional requirements of AnyProject for the first time. Our goal is to enable unification for AnyProject pattern leading to the creation of a stable pattern language and to enable usability for applications across numerous domains and apply for an unlimited number of scenarios. The idea is to compare the existing or traditional model (TM) of a project and software stability model (SSM) of any project using non-functional requirements as criteria for comparison, evaluation, and measurements. The significant findings are: (1) The TM can only be applied to one scenario, unlike the AnyProject Pattern, which can be effectively applied to unlimited scenarios; (2) The TM requires high maintenance costs and limited scalability. On the other hand, the SSM definitively cuts down on costs because it is cognitive knowledge; and (3) In the measurability, the TM fails to model the essential properties of AnyProject. However, the stable model delineates essential properties. As a result, the SSM enables stability and unlimited applicability.
Optimal Camera Positions for Human Identification

Surveillance cameras are being used pervasively in many areas like schools, public places, hospitals, corporates and even in homes in such a way that efficient methods for image/video analysis for processing the data have become a necessity. Various image/video analysis methods can be applied for human identification. But we are unsure of the facial position or angle at which the machine can identify an individual with maximum accuracy and precision. As highly social animals, humans can easily identify each other. They easily recognize each other by face perception. Face Perception is the individual's understanding and interpretation of faces as a result of associated information processing in the brain. But machines work differently from human perception. They may identify human more accurately from another position or angle rather than the front face. This Paper aims to find the relative facial positions or angles at which we could identify individuals with maximum probability by creating a dataset of facial images of different individuals captured at different angles and perform image processing and machine learning on the dataset. We would like to classify the sets of facial positions which can be used for effective human identification and the remaining angles can be ruled out. Then apply this information to position surveillance cameras at different places so that the probability of human identification can be increased. Also, we would also like to identify camera positions that are least effective in identifying humans so that these positions can be avoided while fitting camera.
Expert System Eating Disorder To Youth With The Hybrid Method

The research aims to provide information for the wider community about bulimia nervosa that often afflicts the community especially teenagers. Bulimia nervosa is one type of psychiatric disorder that is habitual that has ingrained from the community itself. No people understand the symptoms or indications of eating disorder in adolescents, and not infrequently among sufferers not doing direct treatment or looking for a direct solution to this disorder. To communicate with doctors also have constraints with time and confusion about what is to be conveyed. Expert system is a solution, this system is able to provide information to researchers about eating disorders in adolescents and provide solutions like a doctor or nutrition expert. It was built using by hybrid method which combines certainty factors and forward chaining.
MR-Anonymization: A Relationship-based Privacy Model

There are several reasons for organizations to publish or share their data. Therefore, ensuring the privacy of individual information is a serious issue. A typical medical organization must publish data about thousands of patients that contain detailed information about each patient. There may be several vulnerable relationships in the data that may lead to identities being exposed. For example, certain diseases are usually associated with groups of a particular age, gender, location, or ethnicity. Data exposure is not limited to specific types of attacks; attackers often try to find vulnerable relationships between data that may lead to exposure of identities. Therefore, the clustering method must be used to find more relationships between large amounts of data. The model provided in this paper aims to improve the concept of data anonymity by proposing an anonymization method that focuses on critical relationships between data. The main idea behind MR-Anonymization is to apply the clustering technique in order to find leakages in such a large dataset.
Current Research Trend on Agile Software Development

In recent years, the software development methodology evolves from the traditional approach to agile software development. This paper attempted to conduct a systematic literature review (SLR) regarding the improved agile software development to tackle its weakness based on recent research papers. Systematic Reviews and Meta-Analyses (PRISMA) as Systematic Literature Review Method (SLR). SLR is the review method which uses some protocols in order to minimize bias in the reviews. The improved of agile software methodology mostly regarding code reusability, usability, project quality, estimation, software delivery, usability, user responses and requirements delivery, communication between members, usability, practical activities, communication between team and stake holder, usability, workflow (learning), problem identification and effort estimation.
Common Data Format in Visual Assembling Guidance Using Augmented Reality

Augmented Reality (AR) gains increased attention over the past few years. It becomes recognized as a valuable tool for a casual user and for a business/industry customer. One of the biggest problems of AR is lack of a common data protocol that would allow creating a data scheme independently of technology that will be used by the end user. This factor slows down the evolution of augmented reality as an everyday technology. ARAssembler is a project that is using our data format for assembling instructions used in augmented reality aided software. Instructions are shared between multiple client applications. The scheme can be used on any device regardless of the technology that it is using. The only task that needs to be done by the client application is to use a common data model and prepare actions/animations based on the scheme. The scheme can be used in any way, to present an object picker, or to create a visual version of paper instruction. Assembly tasks and AR technology are currently a very important topic in this area of research, that is why we decided to focus our prototype on the possibility of creating a step-by-step guidebook and reconstructing it on a client mobile application. Both ends of the project (recorder, client) are based on a mobile device as those are currently the most available augmented reality platform.
Stochastic Radial Basis Neural Networks

Stochastic spiking Neural Networks (SNN) is a new neural modeling oriented to include the intrinsic stochastic processes present in the brain. One of the main advantages of this kind of modeling is that they can be easily implemented in a digital circuit, thus taking advantage of this mature technology. In this paper we propose a digital design for stochastic spiking neurons oriented to high-density hardware implementation. We compare the proposal with other neural models, comparing in terms of speed, area and precision. As is shown, the circuit proposal is able to provide competitive results when comparing with other works present in the literature.
An Information Visualization Method for Computer Teaching

Based on the analysis of the present situation of the visual system of network teaching, this paper puts forward a question-answering visualized system for network teaching with real-time interaction function, to solve the practical problems which need to be demonstrated by special software in the question-answering of network teaching. We classify and combines an efficient, concise and WEB-based remote visual teaching and answering system, establishes the model of the whole system, analyzes the functional modules of each part of the system, develops the flow chart and the visualization program Then, the function of WEB pages under B/S-like mode are tested and it shows that the algorithm visualization of our model has positive significance for popularizing visual teaching and improvement for visual teaching effect.
Proofs, according to Silvio: Silvio Micali's turing lecture

research-article Share on Proofs, according to Silvio: Silvio Micali's Turing lectureProviding Sound Foundations for Cryptography: On the Work of Shafi Goldwasser and Silvio MicaliOctober 2019 Pages 157–171https://doi.org/10.1145/3335741.3335748Published:04 October 2019Publication History 0citation43DownloadsMetricsTotal Citations0Total Downloads43Last 12 Months1Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
BLUE filter with fused range estimation

The non-linear filter is subject to divergence for close-range target tracking; an adaptive best linear unbiased estimation (BLUE) filter with fused range estimation is presented. After proposing the notion of predicted range, the weighted estimation of the predicted and measured ranges is used in the converted measurement model to track the target. The adaptive BLUE filtering parameters with Rayleigh range measurement are derived. Simulation results show the adaptive BLUE filter exhibits better robustness and accuracy with modest computational burden.
A Systematic Mapping Study of Architectural Models for Achieving Utility in the Cloud

Abstract Cloud computing is an important model that allows for information exchange between the various aspects of the Cloud using different service types and models. The issue of deciding a specific research scopemostly in terms of architectural models used in achieving utility in the Cloud, is usually a complex process for a researcher. However, a review or survey paper assists in easily identifying likely topics of research. The objective of this work is to carry out a systematic mapping study of architectural models for achieving utility in the Cloud. A systematic mapping research allows for categorization in a subject area using a scheme based on certain classification process. The scheme used in this paper was categorized into three facets namely: topic, research and contribution facets. The results showed for example that, 30.77% of the papers reviewed on architectural models for achieving utility in Cloud computing are related to evaluation research. The breakdown identified that 5.98% of the evaluation research dealt with design, 6.84% considered applications, 10.26% focused on performance models, 3.42% discussed implementation, 1.71% was on platforms and 2.56% dealt with component models. This study vividly identified gaps in the field of architectural models for achieving utility in the Cloud. This will stimulate interest for advanced studies by both researchers and industry practitioners.
A Comparative Study on Korea and Singapore's Professional Development Activities for teachers - Focused on the TALIS 2013 Results

본 연구는 국제 비교의 관점에서 우리나라의 교사 전문성 개발 실태를 객관적으로 진단하여 교원 정책에 반영할 정책적 방안을 얻고자 하였다. 이를 위하여 OECD 2013 교수-학습 국제조사(TALIS) 결과 가운데 교사 전문성 개발 영역을 중심으로 우리나라와 싱가포르의 교사 전문성 개발 실태를 비교&#8228;분석하였다. 주요 분석 결과는 다음과 같다. 우리나라 교사들은 첫째, 입직 프로그램을 비롯하여 다양한 유형의 전문성 개발에 대한 참여 수준이 싱가포르에 비해 저조하였다. 둘째, 전문성 개발을 위해 제공받는 비금전적 지원에서도 싱가포르에 비해 크게 열악하였다. 셋째, 고용주의 지원 부족을 전문성 개발 참여를 저해하는 요인이라고 인식하는 비율이 싱가포르보다 압도적으로 높았다. 이러한 연구 결과를 토대로, 단위학교 중심의 자발적 교사학습공동체를 활성화해야 한다는 것, 교사들의 요구를 반영하여 전문성 개발 기회를 확보하는 제도적 지원 체제를 구축해야 한다는 것, 교사로 하여금 전문성 향상에 매진할 수 있도록 학교장이 격려하고 배려하는 리더십을 발휘해야 한다는 것을 제언하였다.The purpose of this study is to take political measures of reflection on the teacher policy by objectively diagnosing the status of teacher s professional development in Korea in the perspective of international comparison. For this, the status of teacher s professional development in Korea and Singapore have been compared and analyzed focused on the thematic area of teacher professional development among the OECD(2013) TALIS(Teaching and Learning International Survey) report. The results of main analysis are as follows. First of all, Korean teachers had low participation level for professional development of various types including induction programs compared to Singapore. Second, the non-monetary support provided for professional development was very bad compared to Singapore. Third, the rate of recognizing lack of employer support as a factor that inhibits professional development participation was much higher than Singapore. Based on these research results, the suggestions were made to activate the voluntary professional learning community focusing on unit schools, and to construct the institutional support system that secures the opportunity of professional development by reflecting the demands of teacher, and to display of leadership that encourage and consider have to be made by the head principal so that the teacher could focus on professional improvement.
A Probabilistic View on Erotetic Argumentation Within Language

This paper deals with the phenomenon of erotetic argumentation, which is characterized by a speaker using premises to argue in favor of a question rather than a proposition as in standard cases of argumentation. We discuss some properties of erotetic argumentation and propose a Bayesian formalisation for these properties based on the idea that erotetic argumentation is marked by an increase of entropy rather than a decrease as in the standard cases. We then examine a series of natural language argumentative constructions (adversative conjunction, disjunction, epistemic modals and questions) and their (in)compatibility with erotetic argumentation. We conclude with a brief look at other types of semantic messages (imperatives and exclamatives) and the possibility of also targeting them as conclusions of an argument.
Inference Methods for One Class of Systems with Many Fuzzy Inputs

The paper presents the inference methods for fuzzy systems of Mamdani type, which, for many fuzzy inputs and for any t-norms, are implemented with polynomial computational complexity. Center of sums and the discrete version of the center of gravity methods are applied for the rule base at the defuzzification stage. The network structures of the systems corresponding to these methods are given.
Improved User Experience in Digital Library through Advanced Content Synthesizing

In the process of exploitation of the digital libraries and their resources, it is necessary to offer flexible tools for content synthesis, using basic human brain activities in the content selection process. The aim is to offer the user the opportunities to experience the feeling of accessibility of the provided objects; better benefit and effect of exploring the digital service, immersing in the presented information environment; motivation to continue using the resource, receiving emotional experience; and so long. This paper is focused on content synthesizing activity trying to give new solutions for improved user experience in digital libraries.
Demonstration of a Stream Reasoning Platform on Low-End Devices to Enable Personalized Real-Time Cycling Feedback

During amateur cycling training, analyzing sensor data in real-time would allow riders to receive immediate feedback on how they are performing, and adapt their training accordingly. In this paper, a solution with Semantic Web technologies is presented that gives such real-time personalized feedback, by integrating the data streams with domain knowledge, rider profiles & other context data. This solution consists of a stream reasoning engine running on a low-end Raspberry Pi device, and a tablet app showing feedback based on the continuous query results. To demonstrate this in a static environment, a virtual training app is presented, allowing a user to simulate an amateur cycling training.
Towards language-parametric semantic editor services based on declarative type system specifications

New programming languages often lack good IDE support, as developing advanced semantic editor services takes additional effort. In previous work we discussed the operational requirements of a constraint solver that leverages the declarative type system specification of a language to provide language-parametric semantic editor services. In this work we describe the implementation of our solver as a two stage process: inference and search. An editor-service specific search strategy determines how and where the search is conducted, and when it terminates. We are currently implementing and evaluating this idea.
Precise methods for distinguishing S‐box faults in laser injection attacks

Fault attack is a type of active attack which retrieves the secret key by injecting computational faults. Laser is one of the most common fault injection methods. When attacking substitution-permutation networks-ciphers, S-box is often chosen as the laser injection target. However, the adversary has to know whether the S-box is corrupted or not after each injection, which was difficult in real-world attacks. Two analysing methods to distinguish the S-box faults for different ciphers is proposed in this Letter. A laser-based physical experiment is carried out to verify the authors' methods on Advanced Encryption Standard and PRESENT ciphers on an ATmega163L microcontroller. Experimental results show that their methods can precisely distinguish S-box faults merely using dozens of ciphertexts.
Interactive proofs for lattice problems

research-article Share on Interactive proofs for lattice problems Author: Daniele Micciancio View Profile Authors Info & Claims Providing Sound Foundations for Cryptography: On the Work of Shafi Goldwasser and Silvio MicaliOctober 2019 Pages 565–597https://doi.org/10.1145/3335741.3335763Published:04 October 2019Publication History 0citation84DownloadsMetricsTotal Citations0Total Downloads84Last 12 Months1Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
DPANet: A Novel Network Based on Dense Pyramid Feature Extractor and Dual Correlation Analysis Attention Modules for Colon Glands Segmentation

Accurate segmentation of glands from histology images is a crucial step to obtain reliable morphological statistics for quantitative diagnosis. However, this task is formidable because of the enormous variability in glandular appearance and the difficulty in distinguishing between glandular and non-glandular histological structures. To address this challenge, a novel neural network is proposed to effectively extract benign or malignant colon glands from histology images. Our network has the following innovations: (1) Under the same resolution space, multi-receptive field pyramid features are captured from dense multi-rate dilated convolution architecture with sounder dilated rate setting for accurate gland segmentation. (2) Furthermore, the extracted features are down-sampled by B-spline algorithm to provide different resolution information for the network. (3) Specifically, we embed spatial-channel soft attention modules before each deconvolution operation in the decoder phase, which can better reintegrate features and support clear semantic similarity for network. All these unique operations boost the performance of our method on gland segmentation task. We achieve state-of-the-art performance on the publicly available Warwick-QU dataset.
Transfer Learning Approach to Fine-Grained Image Classification

This paper deals with fine-grained image classification in which instances from different classes share common parts but have wide variation in shape and appearance. Introduction gives a short review of existing works on this topic such as weakly supervised learning, discriminative localization network. Various approaches to the solution were considered and the method of the transfer of learning for the fine-grained image classification is considered as one the most promising methods. Convolutional neural networks are used. The approach demonstrates its effectiveness and allowed obtaining high accuracy of recognition on the dog breed recognition problem. Next step is to add more breeds and improve the recognition result.
Using an Existing Website as a Queryable Low-Cost LOD Publishing Interface

Maintaining an Open Dataset comes at an extra recurring cost when it is published in a dedicated Web interface. As there is not often a direct financial return from publishing a dataset publicly, these extra costs need to be minimized. Therefore we want to explore reusing existing infrastructure by enriching existing websites with Linked Data. In this demonstrator, we advised the data owner to annotate a digital heritage website with JSON-LD snippets, resulting in a dataset of more than three million triples that is now available and officially maintained. The website itself is paged, and thus hydra partial collection view controls were added in the snippets. We then extended the modular query engine Comunica to support following page controls and extracting data from HTML documents while querying. This way, a SPARQL or GraphQL query over multiple heterogeneous data sources can power automated data reuse. While the query performance on such an interface is visibly poor, it becomes easy to create composite data dumps. As a result of implementing these building blocks in Comunica, any paged collection and enriched HTML page now becomes queryable by the query engine. This enables heterogenous data interfaces to share functionality and become technically interoperable. This is a print-version of a paper first written for the Web. The Web-version is available at https://brechtvdv.github.io/Article-Using-an-existing-website-as-a-queryable-low-cost-LOD-publishing-interface/ .
Double Peaks Detection for Object Tracking

The kernel correlation filter tracker (KCF) predicts the object position based on the maximum value of the response map, but the response value of the real target is not always the maximum value of the response map. An improved kernel correlation filter tracker based on double peaks detection is proposed. Firstly, the peak-to-sidelobe ratio (PSR) of the target was calculated according to the response map obtained by the KCF algorithm. When the PSR is smaller than the empirical threshold, the highest peak and the second highest peak were detected in the response map, and then the PSR of response maps were calculated respectively in peaks. The position of the target was determined by bigger PSR. Finally, the template adopted an adaptive update strategy and the update process of the target template was optimized by PSR of response map. Experimental results show that the improved KCF increased the distance accuracy by 6.9% and the success rate by 5.5% with less time consumption.