Reviewerly/exHarmony huggingface dataset:
AXIOLOGICAL MANAGEMENT OF ARCHITECTURAL SEARCH

The article compares the double coding scheme developed in the theory of postmodernism with the scheme of spectacular communication, borrowed from the field of theater studies. The idea of “critical architecture” has become a prerequisite for the analysis of communicative schemes. The authors interpret it as an interactive movement organized by axiological programs that combine the positions of consciousness, thinking and reflexive control in the genre self-determination, the prescription of theme and style of the architectural work for the purpose of value management of the project search. The authors identify the subject of role disposition, in which the architect emphasizes the dramatic role of the compiler or stylist of the literary text. The method and organizational forms of dispositional thinking, one of which is a critical architecture, rationalizing the design of declarations of artistic directions are considered
Adaptation execution cost definition for a multimedia adaptation decision engine using a neural network

Multimedia content adaptation decision is necessary whenever a multimedia transmission system has multiple adaptations available to adjust the content representation requirements to the present available system resources. The implementation of an adaptation decision module, based on a Markov Decision Process, requires to weight the adaptations, to establish the adaptation plan to deliver the best possible Quality of Experience (QoE) to the user. We present a method, using a feedforward neural network, to determine these costs using two approaches: user and service provider perspectives.
Using Social Media To Support Community Development: A Case Study Of E-Inclusion Intermediaries In Underprivileged Communities Of South Africa

For many marginalized community members e-inclusion intermediaries (e-IIs) are the only accessible and affordable option to access computers and the Internet, yet their use of the provided ICTs is low. This is due to a lack of awareness about e-IIs and ICTs benefits. To create awareness and promote the use of ICTs by community members e-IIs need more effective communication strategies that share information. Social media can be effective in this regard, yet many e-IIs do not utilize their potential. This paper presents findings of a qualitative study that investigated how selected e-IIs in South Africa communicate using social media. The study found that social media can facilitate communication for development by enabling low-cost, participatory communication approaches that build networks to share information, resources and create awareness. Social media are however only effective if they are appropriate for the target audience and used strategically to achieve clear communication objectives.
Early Warning System Framework Proposal, Based on Big Data Environment

Early warning systems are made with the purpose to efficiently recognize deviant and potentially dangerous trends related to company business as early as possible. The Big Data environment gives new opportunities and new approaches in analytical processes. There are numerous ways how to set up early warning systems within a company. The Big Data environment forces companies to apply new ways of thinking and use new disposable data sources. This article gives a novel concept for an early warning system design within a company, which is applicable in different industries. The core of the proposed framework is a hybrid fuzzy expert system which can contain a variety of data mining predictive models responsible for some specific areas as addition to traditional rule blocks. It can also include social network analysis metrics based on linguistic variables and incorporated within the rule blocks. As a part of this framework, SNA methods are also explained and introduced as powerful and unique tool to be used in modern early warning systems.
A Biologically Inspired Saliency Priority Extraction Using Bayesian Framework

In this article, the authors used saliency detection for video streaming problem to be able to transmit regions of video frames in a ranked manner based on their importance. The authors designed an empirically-based study to investigate bottom-up features to achieve a ranking system stating the saliency priority. We introduced a gradual saliency detection model using a Bayesian framework for static scenes under conditions that we had no cognitive bias. To extract color saliency, we used a new feature contrast in Lab color space as well as a k-nearest neighbor search based on k-d tree search technique to assign a ranking system into different colors according to our empirical study. To find the salient textured regions we employed contrast-based Gabor energy features and then we added a new feature as intensity variance map. We merged different feature maps and classified saliency maps using a Naive Bayesian Network to prioritize the saliency across a frame. The main goal of this work is to create the ability to assign a saliency priority for the entirety of a video frame rather than simply extracting a salient area which is widely performed.
Let Vehicles Talk with Images for Smart Vehicular Communication System

In this paper, the need for image analysis and machine learning in the domain to develop smart/intelligent vehicular communication system is succinctly addressed. Like other domains, vehicular communication has to be addressed/cited through the use of big data for several different purposes, such as the vehicle or user authentication, safety and security. Not limited to one of them, the aim of the paper is to show how can we create a panoramic image from a set of images shared by several vehicles at any specific event in the particular vehicular network. The paper is the proof-of-concept prototype to see whether images (via the use of the image- and machine learning-based tools/techniques) can help enhance the driving experience.
Image Filtering with Iterative Wavelet Transform Based Compression

This paper attempts to propose a methodology to reduce the size of high definition colored images taken by the professional photographers. In this digital era as technology is advancing so fast, high definition photos are captured. But these pictures take a lot of memory space. Therefore data and image compression techniques are in great requirement. The major goal is to find computationally efficient algorithm to significantly reduce the storage size with capability to retrieve the quality of image. The proposed work effectively uses Discrete Wavelet Transform (DWT) and only low frequency part of the image is transmitted, after that further iterations are performed to increase the compression ratio. Numbers of iterations are decided by making a trade-off between compression ratio (CR) and Peak Signal to Noise Ratio (PSNR) value. Arithmetic coding is applied for further compressing the image. To improve the image quality (PSNR) further at higher iteration, filters has been applied. Switching weighted median filter and simple median filter has been studied. Analysis on different window size of median filter has also been done to achieve improved PSNR value.
Identifying facts for chatbot's question answering via sequence labelling using recurrent neural networks

Question answering (QA) is one of the most significant tasks in artificial intelligence (AI) that not yet solved completely. It is a task which requires building data models capable of providing answers to questions expressed in human language. Full question answering involves some form of labelling. Sequence labelling is an important problem in natural language processing. Given a sequence of words, sequence tagging aims to predict a linguistic tag for each word such as the POS tag. The main question is, how can we leverage the sequential nature of data to extract better features and structural dependency between them. In an effort to address this question, this study present attention-based architecture for sequence labelling on deep recurrent neural network (DRNN). To solve the QA problem, it consists of two major steps: identifying the fact and answering the question based on the relevant fact. The study showed that the proposed model provides consistent improvement and outperform then traditional approaches.
An Alternative Development for RCANE Platform

RCANE platform was proposed in our previous work which is a semi-centralized network of parallel blockchain and authorized proof of stakes (APoS). In that paper, the proposed RCANE platform was presented to solve the challenges of previous platforms and comply with our preconceived perspectives of the current political, social, and economic systems to build up an ecosystem for economy, society and politics. In addition, RCANE platform aims to pioneer the ‘content market’, where the cryptographic currency has an intrinsic value and can cover the blind spots of existing currencies, create new profitability by organizing system to give value to contents without monetary value, and establish cryptocurrency ecosystem to create a sustainable business model based on social and economic value to lead the future huge content market. However, the network security and the performance of RCANE platform are still open issues which must be improved. In this paper, an alternative development of the security network and performance of RCANE platform is presented to show its’ advantages in comparison with previous platforms more clearly. The performance of RCANE platform in terms of transaction confirmation time, the number of transaction per second and latency is emphasized.
Processing private queries based on distributed storage in location-based services

With the rapid development of global positioning system, cellular networks and relative technologies, people can request location-based services (LBSs) from the service provider using a handheld device quickly and easily. This greatly facilitates people's life. However, it brings a lot of privacy leakage problems. To reduce it, many methods have been proposed. But, they still don't balance the intensity and efficiency of privacy protection very well. Based on distributed storage and the quadratic residual theorem, this paper proposes a LBS user privacy protection scheme with both security features and efficiency. The traditional encryption method, private information retrieval (PIR), will bring high communication cost and computing pressure on the server side. A distributed storage system architecture can greatly reduce network overhead and the risk that the server will identify the user's real location because requests can be answered by the caching proxies without arriving at the server. To enable encrypted requests to be answered correctly by the caching proxies without being known by proxies, we build an index table. Compared with the similar work, simulation results show that our scheme can effectively reduce user communication and server computing overhead.
On the order sequence of an embedding of the Ree curve

Abstract In this paper we compute the Weierstrass order-sequence associated with a certain linear series on the Deligne–Lusztig curve of Ree type. As a result, we show that the set of Weierstrass points of this linear series consists entirely of 𝔽 q -rational points.
Development of a Light-Tracking and -Redirecting System Actuated by Hand-Gesture Recognition

This paper presents a context-aware light-tracking and -redirecting system guided by hand-gesture recognition. It is conceived as yet another mechanism within an ongoing development of a more intuitive and technically sophisticated Ambient Intelligence / Active and Assisted Living ecosystem. The detailed system consists of individual nodes that are strategically installed across regions of a building-envelope, which enables this latter to draw or deflect direct natural light into or away from specific locations within the built-environment as requested by the user(s) via recognized hand-gestures. Each node is capable of sending and receiving sensed-data continuously via ZigBee with one another as well as with microcontrollers embedded within the interior built-environment. Said microcontrollers are equipped with cameras via which four hand-gestures may be recognized. The first or initializing hand-gesture engages the system and enables it to recognize any of the remaining hand-gestures. The second redirects light towards the position of the detected hand-gesture, while the third redirects it away from said position. Finally, the fourth gesture turns the light-tracking and -redirecting system off.
Improved problem constraints modeling based using classification

A general classification agent has been developed based on a semantic model for supporting the modelling of problems in the chemical modelling domain. Two case studies are used to illustrate the proposed approach, which stands for a routine that solves the modelling task easily and quicker and less error-prone approach in comparison to the traditional problem.
Policy multi-region integration for video description

As a bridge between video frames and natural text, automatic video description technology can be widely used in real life. The main point of this task is to represent the dynamic information of the video through a compact vector. Most recent progress is to combine the attention mechanism through the encoder-decoder architecture. This paper introduces a novel Policy based Multi-Region Attention Model (PMRAM) that is capable of integrating information from multiple local regions in a video frame by adaptively learning a location policy. And combining temporal attention mechanism to selectively focus on regions under different frames to obtain a compact vector. Our model provides a natural way to fuse temporal-spatial information for video description. While the model is non-differentiable, it can be trained using reinforcement learning methods. We evaluate our approach on two large-scale benchmark datasets: MSVD and TACoS-MultiLevel. Our approach outperforms the current state-of-art on both datasets according to BLEU, METEOR and CIDEr metrics.
An Enhanced and Efficient Multi-View Clustering Trust Inference Approach by GA Model

Multi-view affinity propagation (MAP) methods are widely accepted techniques, measure the within-view clustering and clustering consistency. These suffer from similarity and correlation between clusters. The trust and similarity measured was introduced as a new approach to overcome the problem. But these approaches suffer from low accuracy and coverage due to avoidance of implicit trust. So, a framework called multi-view clustering based on gray affinity (MVC-GA) created by integrating both similarity and implicit trust. Similarity between two clusters is obtained by applying the Pearson Correlation Coefficient-based similarity. It utilizes the collaborative filter-based trust evaluation for each clustered view in terms of the similarity based on the gray affinity nn algorithm. Classification of incomplete occurrences is addressed based on GA Function. Experiments on the benchmark data sets have been performed to validate the proposed framework. It is shown that MVC-GA can improve the multi-view clustering accuracy and coverage.
An Investigation of the Situation of the Using Handheld Devices on Learning Mathematics of High School Teachers in Mainland China

This research was undertaken to investigate of the situation of the using handheld devices on learning mathematics of high school teachers in Mainland China. A questionnaire of "Using Handheld Devices on Learning Mathematics (UHDLM)" was developed. The contents presented were partial results of the project funded by the Ministry of Science and Technology (MOST) of Taiwan. under Grant No. MOST 106-2511-S-275-004 -MY2. Questionnaire of UHDLM was used as the measurement instrument in order to investigate the situation of using handheld devices on learning mathematics. This instrument was developed and revised many times during Feb. to June, 2018. This instrument was developed and revised five times during Feb. to Jun., 2018. Finally, there are 6 problems in the first part, 31 problems each in the second and third part, totally 68 Problems, in the formal questionnaires for high school teachers. The results were drawn as follows: 1. There are 57.8% of mathematics teachers of the high school in Mainland China using handheld devices to assist in learning mathematics. 2. There are 54.3% of the grader 10 that mathematics teachers of the high school in Mainland China use handheld devices to assist in learning mathematics, follows 28.6%, 15.7% for grader 11 and grader 12, respectively. 3. There are 33.9% in how to improve the teaching effect that mathematics teachers use handout to assist in learning mathematics, follows 29.7%, 12.7% for hand-on instruction and GeoGebra, respectively. 4. Among the teachers who did not use the handheld device to assist in teaching, the reason for "not using the computer-related equipment" was the main factor, accounting for 26.9%, followed by I do not know how to use it effectively, accounting for 18.3%. If there are relevant learning opportunities, 93.6% of the teachers are willing to participate.
Media Gambar dan Pesan Berantai sebagai Strategi Efektif Pembelajaran Menyimak Bahasa Indonesia di Sekolah Dasar

This study is a study of the use of chain messages techniques to streamline learning to listen to students in learning Indonesian in grade IV SDN Tarikolot I with legend stories. This research was conducted to improve the ability to listen to students, then the class teacher did not use this chain message technique. In this class action research researchers used Jhon Elliot's model. This research was conducted in three cycles. In each of its actions the researcher uses various data collection tools in the form of tests and non tests. At the implementation of this learning students look very enthusiastic, because in this learning given a piece of story that they must understand and tell a group of friends, so that each student has responsibility. The results of the study showed that learning Indonesian with reading material from a legend could improve the process and ability to listen to students. The learning process every cycle has increased. This can be seen from the average value of the process test in the cycle 1: 66.33; cycle 2: 70.3; and cycle 3: 77.3. The ability to listen to students also experiences an increase in each cycle seen in the average value of the evaluation test cycle 1: 67.5; cycle 2: 71,47; and in the 3: 75.5 cycle. And can also be seen also from the average results of observations of student activities in the cycle 1: 67.04; cycle 2: 73; and in the 3: 76.8 cycle.
The Teaching Complexity of Erasing Pattern Languages with Bounded Variable Frequency

Patterns provide a concise, syntactic way of describing a set of strings, but their expressive power comes at a price: a number of fundamental decision problems concerning (erasing) pattern languages, such as the membership problem and inclusion problem, are known to be NP-complete or even undecidable, while the decidability of the equivalence problem is still open; in learning theory, the class of pattern languages is unlearnable in models such as the distribution-free (PAC) framework (if $$\mathcal {P}/poly \ne \mathcal {NP}/poly$$ ). Much work on the algorithmic learning of pattern languages has thus focussed on interesting subclasses of patterns for which positive learnability results may be achieved. A natural restriction on a pattern is a bound on its variable frequency – the maximum number m such that some variable occurs exactly m times in the pattern. This paper examines the effect of limiting the variable frequency of all patterns belonging to a class $$\varPi $$ on the worst-case minimum number of labelled examples needed to uniquely identify any pattern of $$\varPi $$ in cooperative teaching-learning models. Two such models, the teaching dimension model as well as the preference-based teaching model, will be considered.
Saccade Information Based Directional Heat Map Generation for Gaze Data Visualization

Heat map is an important tool for eye tracking data analysis and visualization. It is very intuitive to express the area watched by observer, but ignores saccade information that expresses gaze shift. Based on conventional heat map generation method, this paper presents a novel heat map generation method for eye tracking data. The proposed method introduces a mixed data structure of fixation points and saccades, and considers heat map deformation for saccade type data. The proposed method has advantages on indicating gaze transition direction while visualizing gaze region.
Study on Precision Improvement of Ship’s Position Measurement Using Multiple Cameras

The authors have been considering a lookout support system using cameras at a ship. In previous studies, a stereo imaging system was proposed to measure the locations of other ships. However, in the case of long-distance measurement, the previous results have often included a large margin of error due to slightly less accurate gaze detection for the target ship. This research paper describes our effort to improve the accuracy of long-distance position measurement by using a three-camera stereo vision system. Our experimental results show that errors can be reduced when using three cameras compared with the outcome obtained with two cameras. However, they also indicate that a systematic error can be observed even from the results of three camera measurement depending on methods of computation. The authors have analyzed the cause of this error through a numerical simulation.
Relevance of Web 2.0 for Library Services in Digital Era

This chapter is on relevance of Web 2.0 for library services in digital era. Web 2.0 tools play crucial role in effective service delivery of librarians. The study covers awareness, utilization, benefits, and challenges that affect the use of Web 2.0 by librarians for effective service delivery. The concepts generally implied that Web 2.0 can be used by librarians as information acquisition tools to gather information from sources outside libraries (e.g., blogs and wikis), information dissemination tools (such as RSS feeds), information organization tools that facilitate storage and subsequent retrieval of information (social bookmarking and tagging), and information sharing tools that facilitate the bilateral flow of information between libraries and patrons (social networking and media sharing sites). This chapter examines the concept of digital libraries and highlights the major features of a digital library and how it can be used. The potentials of digital library are very crucial as means of access to knowledge and information that will facilitate development.
Joint Detect and Track for Target under Angular Deception Jamming

Cross-eye jamming is a typical angular deception jamming type for monopulse radar, and it induces an angular error by artificially creating a false target and deceiving the radar to detect and track it. In this paper, the random finite set model for cross-eye jamming scenario is established, and a joint detect and track algorithm based on probability hypothesis density filters is proposed to detect the releasing of cross-eye jamming, distinguish the target and jamming, and realize the accurate state estimation and stable tracking for true target. Simulation results verify the effectiveness of the proposed method.
Data Analytics in Steganography

Now a day's Digital communication has many advantages like good quality, flexibility in editing, high accuracy and fidelity, data compression, etc. As there is quick or sudden improvement and demand in technology of today's computer network, but this area consists some privacy issues, manipulations of data, and its data authentications. In present modern eras the organisations are having top priority as protection of data, which can be achieved by using digital communication. For this, data can be kept secret or can hide the data as unknown data with an Digital steganography which is an advance technique.