Reviewerly/exHarmony huggingface dataset:
Learn to Demodulate: MIMO-OFDM Symbol Detection through Downlink Pilots

Reservoir computing (RC) is a special neural network which consists of a fixed high dimensional feature mapping and trained readout weights. In this paper, we consider a new RC structure for MIMO-OFDM symbol detection, namely windowed echo state network (WESN). It is introduced by adding buffers in input layers which brings an enhanced short-term memory (STM) of the underlying neural network through our theoretical proof. A unified training framework is developed for the WESN MIMO-OFDM symbol detector using both comb and scattered pilot patterns, where the utilized pilots are compatible with the structure adopted in 3GPP LTE/LTE-Advanced systems. Complexity analysis reveals the advantages of the WESN based symbol detector over the state-of-the-art symbol detectors such as the linear the minimum mean square error (LMMSE) detection and the sphere decoder when the system is employed with a large number of OFDM sub-carriers. Numerical evaluations corroborate that the improvement of the STM introduced by the WESN can significantly improve the symbol detection performance as well as effectively mitigate model mismatch effects as opposed to existing methods.
An Algebraic Theory for Data Linkage

There are countless sources of data available to governments, companies, and citizens, which can be combined for good or evil. We analyse the concepts of combining data from common sources and linking data from different sources. We model the data and its information content to be found in a single source by an ordered partial monoid, and the transfer of information between sources by different types of morphisms. To capture the linkage between a family of sources, we use a form of Grothendieck construction to create an ordered partial monoid that brings together the global data of the family in a single structure. We apply our approach to database theory and axiomatic structures in approximate reasoning. Thus, ordered partial monoids provide a foundation for the algebraic study for information gathering in its most primitive form.
Pengaruh Promosi Melalui Media Sosial Terhadap Pengambilan Keputusan Kursus Bahasa Inggris Pare Dengan Viral Marketing Sebagai Variabel Intervening

This study aims to determine the effect of promotion through social media on the decision of English language courses at CELL institutions Pare Kediri East Java - English Village with viral marketing as an intervening variable. The population in this study were course participants at the CELL institution Pare Kediri East Java - English Village. The sampling technique uses non-probability sampling technique which is accidental sampling and the number of samples is 100 respondents. This research is quantitative research. Data analysis is used using path analysis (path analysis) with the SPSS version 20.0 application. For the endogenous variable (Y) of this study is the purchase decision, for exogenous variables (X) is promotion through social media, and for intervening variables (Z) is viral marketing. The results of this study indicate that: (1) There is a positive significant influence between promotion through social media on purchasing decisions. (2) There is a positive significant influence between promotion through social media on viral marketing. (3) There is a significant positive influence between viral marketing on purchasing decisions. (4) Yes significant influence between promotion through social media on purchasing decisions with viral marketing as an intervening variable.
Notes on the Rescaled Algorithm for Fuzzy Cognitive Maps

FuzzyHarmati, István Á. Cognitive Maps are network-like decision support tools, where the final conclusion is determined by an iteration process. Although the finalKóczy, László T. conclusion relies on the assumption that the iteration reaches a fixed point, it is not straightforward that the iteration will converge to anywhere, since it can produce limit cycles or chaotic behaviour also. In this paper, we briefly analyse the behaviour of the so-called rescaled algorithm for fuzzy cognitive maps with respect to the existence and uniqueness of fixed points.
Solar-Assisted Smart Solid Waste Dustbin

In the past few decades, the rapid growth of the urbanization rate has taken place, and therefore, plans for sustainable urban planning are required. Using new technologies and a strategic approach, the concept of smart cities is approaching the whole world. A smart city is not built without a smart waste management system. In this article, our model describes the application of “solar-assisted smart solid waste dustbin” for the management of the solid waste system of the city. In our model, the volume of solid wastes has been drastically reduced compared to the conventional process. It reduces the cost of transportation and reduces the odor of waste. First of all, organic waste is ground by grinders and, at the same time, the humidity content is heated to reduce the weight of the waste. Compressors will then compress, and finally, compressed waste materials are stored in the storage unit. The control system is run by solar energy, and the systems are semi-automated. In addition, rented materials are collected by bin to be used for agricultural purposes. Today’s traditional bins will be able to efficiently manage these wastes as they waste their waste on the road, and it may cause insects and mosquito breeding. Dismantling in dirty environments also causes serious illness. It controls through solar energy and is a semi-automatic system; by doing this, we can change the contaminated environment.
Development of Rainwater Harvesting System for Sekolah Menengah Kebangsaan Iskandar Syah Melaka

Abstract This paper presents the development of rainwater harvesting (RWH) system at Sekolah Menengah Kebangsaan Iskandar Syah ( SMKIS ), Melaka to promote landscape sustainability. The proposed RWH system deployed an elevated tank, a sequential filter, and a storage tank. A fertigation pond and a turbine were installed as part of the RWH system in Taman Herba to promote an ecosystem for freshwater habitat and to generate energy. The RWH system was used as an alternative water supply to the Taman Herba and the fertigation pond as well as water supply for power generation. It was found that the RWH system has successfully reduced the rainwater flowrate in the existing drainage system by 50.9% and effectively reduced the utility bills for the landscape irrigation and the fertigation pond. The turbine generated 26.6 W power which is adequate to light up a scrolling message board at Taman Herba . Both the fertigation pond and the turbine embellished the Taman Herba landscape and are a good platform for experiential learning for the secondary students in SMKIS .
A New Approach for Efficient Face Detection Using BPV Algorithm Based on Mathematical Modeling

In this paper several face detection algorithms are compared on the basis of mathematical analysis to find out the most efficient algorithm. At first the mathematical model of different face detection algorithms (Camshift, AdaBoost, LBP and Viola Jones algorithms) are analyzed and compared to find out the most efficient one. Mathematical results show that Viola Jones performs best result to detect the face. But in case of Viola Jones, integral image integrates the non-face region pixels with face region pixels as a result, the pixel value redundancy is occurred which degrades its efficiency. To overcome this problem, a new face detection algorithm is proposed in this paper which is named as Break Point Value (BPV) algorithm. The mathematical model of our proposed method is derived where integral images are compared with Local Binary Pattern (LBP) and the compared value is suggested as test value. If the test value is less than or equal to the BPV then the region is a face region and if it is not, the region is a non-face region. Since there is a comparison between integral image value and LBP value of the same pixel region the redundant values are reduced. Furthermore, the use of BPV helps to find out more relevant frames. Thus the proposed method is more efficient face detection process as compared to the previous processes in the field of face detection system.
Abstract 1629: Classification of cancer histology images using deep learning

Abstract Pathological evaluation of tumor tissue images stained with hematoxylin and eosin (H&amp;E) is pivotal and specialists often disagree on the final diagnosis. Meanwhile, automated image analysis approaches have great potential to increase precision of diagnosis, help reduce human error and cut cost. In this study, we utilize various computational methods based on deep learning framework and build a stand-alone diagnostic tool to effectively classify different histopathology images across different types. The dataset of tissue slides from eligible patients with breast cancer/ thyroid cancer consists of 45,000 samples in our hospital. Available tissue samples above were split into a training set, for learning the CNN parameters, and test set, for evaluating its performance. An accuracy of 94% was obtained for non-cancer (i. e. normal or benign) vs malignant (i. e. invasive carcinoma or papillary thyroid carcinoma). In addition, we also demonstrated the utility of our model to discriminate between two subtypes of lung cancer. It provides pathologists or medical technicians a straightforward platform to use without requiring sophisticated computational knowledge, and cancerization would be identified which is not visible under a single microscope. Citation Format: Weidong Xie. Classification of cancer histology images using deep learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1629.
Intelligent Video Surveillance and Early Alarms Method for Railway Tunnel Collapse

Looking at the problem of railway tunnel entrance collapse, this paper proposes a warning system based on intelligent video surveillance. In the image processing algorithm, HSV color space integrating RGB time domain segmentation combined with double threshold image segmentation technique is used to extract the moving object in the monitoring range. The Sobel edge detection operator and the improved Hough transform algorithm are used to extract the characteristics of the rails to determine the size and position of moving objects. Self-adaptive background update mechanism based on Kalman filter theory eliminates the influence of natural conditions such as weather and light. Feature recognition of collapse is realized based on the image processing algorithm. The slope displacement monitor is introduced to achieve real-time early-warning before collapsing. Simulation experiments show that this method can extract the target features accurately, achieve immediate and effective early warning, and cope with the environmental disturbance factors.
Network Analysis of Dark Web Traffic Through the Geo-Location of South African IP Address Space

The recent public disclosure of mass surveillance of electronic communication, involving powerful government authorities, has drawn the public’s attention to issues regarding Internet privacy. For almost a decade now, there have been several research efforts towards designing and deploying open-source, trustworthy, and reliable systems that ensure users’ anonymity and privacy. These systems operate by hiding the true network identity of communicating parties against eavesdropping adversaries. TOR, acronym for The Onion Router, is an example of such a system. Such systems relay the traffic of their users through an overlay of nodes that are called Onion Routers and are operated by volunteers distributed across the globe. Such systems have served well as anti-censorship and anti-surveillance tools. The implementation of TOR allows an individual to access the Dark Web, an area of the Internet said to be of a much larger magnitude than the Surface Web. The Dark Web has earned a connotation as a sort of immense black market, associated with terrorist groups, child pornography, human trafficking, sale of drugs, and conspiracies, and hacking Dark Web research has received significant national and international press coverage. However, to date, little or no research has been conducted on the illicit usage TOR usage by South Africans. To date, there has yet to be a study that characterizes the usage of a real deployed anonymity service. Observations and analysis obtained are presented by participating in the TOR network. The primary goal is to elicit TOR usage by South Africans. In particular, interest is focused in answering the following question: In sampling the results, it reflects that the main usage of TOR in a South African Context is to access social media websites.
An Axiomatic System for a Physical or Digital but Continuous 3-Dimensional Euclidean Geometry, Without Infinite Many Points

This paper is concerned with finding an axiomatic system, so as to define the 3-dimensional Euclidean space, without utilizing the infinite ,that can imply all the known geometry for practical applied sciences and engineering applications through computers , and for more natural and perfect education of young people in the Euclidean geometric thinking.In other words by utilizing only finite many visible and invisible points and only finite sets, and only real numbers with finite many digits, in the decimal representation.The inspiration comes from the physical matter , rigid, liquid and gaseous, which consists of only finite many particles in the physical reality.Or from the way that continuity is produced in a computer screen from only finite many invisible pixels .We present such a system of axioms and explain why it is chosen in such a way.The result is obviously not equivalent, in all the details, with the classical Euclidean geometry.Our main concern is consistency and adequacy but not independence of the axioms between them.It is obvious that within the space of a single paper, we do not attempt to produce all the main theorems of the Euclidean geometry, but present only the axioms.
Investigating Recommendation Algorithms for Escape Rooms

An escape room is a physical puzzle solving game, where participants solve a series of riddles within a limited time to exit a locked room. Escape rooms differ in their theme, environment, and difficulty, and people hence often differ on their preferences over escape rooms. As such, recommendation systems can help people in deciding which room to visit. In this paper, we describe the properties of the escape rooms recommendation problem, with respect to other popular recommendation problems. We describe a dataset of reviews collected within a current system. We provide an empirical comparison between a set of recommendation algorithms over two problems, top-N recommendation and rating prediction. In both cases, a KNN method performed the best.
Development of Operation System for Electric Wheelchair by Voluntary Movements of Head

Recent almost developed countries like Japan, senior people are increasing. In such as aging society, supplying human resource to care the senior people doesn't catch up with its demands. Therefore, the societies encourage the cared elderly people become to manage to live by themselves in their life. To realize such as the society of independent elderly people, many assistive machines and tools are developed. In particular, electric wheelchairs are very effective to keep and improve their Quality of Life (QOL). In this study, to promote the use of electric wheelchairs, a novel operation system for electric wheelchair using pointing device (Hands-Free Operation-Interface) is proposed. The proposed system can operate an electric wheelchair without body action. To investigate operation system of the wheelchair, its driving performance is compared with driving using a standard joystick under same slalom course running. There were some obstacles in the slalom course, driver needed to drive the electric wheelchair and make own way around these obstacles to goal. In this experiment, success-ratio and running time are compared between Hands-Free Operation-Interface and standard joystick operation to evaluate the operability of the systems. As a result, it is suggested that success-ratio is depended on operators, and the average of success-ratio is 67 %. Also running time is observed that depended on driving ability of operators. Therefore, these results showed that practice and adapting of users are necessary to drive the electric wheelchair using the proposed operation system. In addition, this study showed some direction for controlling the system safely.
ETSB: Energy Trading System Based on Blockchain

The emergence of blockchain solves the trust problem of the traditional energy trading mode, making the distributed multi-energy system possible and providing technical support for the new energy trading system. Therefore, a kind of energy trading system based on blockchain is proposed. The ETSB model is established firstly, and the definition of ETSB is expanded. The ETSB is a four-tuples, including node set, data set, consensus mechanism and intelligent contract, which are all newly constructed according to the characteristics of energy trading. On the basis of ETSB architecture, the potential security risks of ETSB are analyzed hierarchically. Finally, a complete security protection mechanism is proposed for those system vulnerabilities.
An Innovative Platform for Creating Audience-Specific Gamified Cultural Tourism Guides Where Art, Tradition and Culture, Technology and Business Converge

Digital realities and gaming combined with existing communication technologies offer tremendous opportunities in the development of strategic innovative marketing. In parallel, the cultural and creative industry is in need of new platforms through which museum staff, cultural organizations, tourism and related industry will have access to a set of easy-to-use authoring tools that facilitate the creation and maintenance of personalized gamified cultural travel guides in the form of mobile apps. In this framework, this research paper focuses on the design, implementation and evaluation of a cultural guide authoring platform and applications which offer multilingual, 3D and Augmented Reality (AR) gamified experiences to mobile users. The respective apps developed can be ported on many platforms and with these 3D tools a non-experienced user can in a few minutes easily create a city guide with articles, routes, mini-games and AR content using only drag and drop features. At the same time the mobile applications present city guides and general tourism information and services to the users.
Immersive learning experiences for understanding complex systems

Complexity is core part of our lives. Aware or not, people need to understand and communicate complex ideas and perspectives. Understanding and communicating complexity can be facilitated through interactive simulations. Doing so in the physical world is often impractical, however. Users and developers are overloaded with information and ambiguity, costs are prohibitive, and unsupervised physical simulations raise safety concerns. Novel immersive technology might hold the key to transforming how we tackle understanding and communicating complexity. In this position paper, we propose empowering user agency and perception to take part in complex learning experiences and create their own, combining two factors: enhanced visual and spatial context provided by location-awareness, immersive environments, and somatic, embodied agency; and enhanced cultural and social context by leveraging as input methods the rich semantics of cultural-social gestures and rituals. To deem the feasibility of this argument, we propose developing two culture-aware prototypes, one for the Confederated Salish and Kootenai Tribes in Montana, United States, and another for a Western Europe cultural context.
IFLA Library Reference Model, RDA, and Serials in a Nutshell

IFLA Library Reference Model (IFLA LRM) represents the consolidation of Functional Requirements for Bibliographic Records (FRBR) and the two other conceptual models of the Functional Requirements (FR) family, the Functional Requirements for Authority Data (FRAD) and the Functional Requirements for Subject Authority Data (FRSAD). IFLA LRM includes a specific section (5.8) devoted to serials. The RDA Steering Committee adopted IFLA LRM as the conceptual model for the development of RDA in November 2016. The 3R (RDA Toolkit Restructure and Redesign) Project’s purpose is partly to make RDA compatible with the IFLA LRM. A beta version of the English-language content of the RDA Toolkit, which incorporates the IFLA LRM, was released in June 2018. This column explores, in lay terms, serials in relation to the IFLA LRM and the RDA Toolkit Restructure and Redesign (3R) Project. The beta version of the restructured and redesigned RDA Toolkit introduces several new concepts relating to serials.
Research on Load Balancing Algorithm Optimization Based on Spark Platform

Spark is an efficient big data processing platform based on memory computing. However, the default task scheduling algorithm in Spark does not take into account the difference in capability and resource usage of nodes under the Spark cluster. Therefore, an uneven load on the nodes might be resulted with the high-capability node in idle state and the low-capability node in high-load state which will affect the work efficiency. To this end, we propose an adaptive task execution node allocation algorithm based on the ant colony-simulated annealing algorithm. The proposed algorithm optimizes the Spark cluster task execution node allocation method based on the resource usage of the node, which is used to achieve the purpose of load balancing. Experiments show that in comparison with the task scheduling algorithm of the Spark cluster, the task scheduling algorithm proposed in this paper has a significant improvement in cluster load balancing and task completion time.
TEACHING READING COMPREHENSION USING JIGSAW TECHNIQUE

English is foreign language in Indonesia. In English, reading is one of skill that must be mastered by students. By mastering reading skill, it can be easier for student to comprehend the text that they read. However many students not understand how to comprehend the English text well, it caused by inapropriate technique used by the teacher in English teaching. According to the problem an appropriate technique should be applied to improve their reading comprehension. The aims of the research is to find out whether there is any improvement in the students’ reading comprehension using jigsaw technique. In this research, the writer uses pre-experimental design.The researcher takes 30 students as the sample of this research. The instrument of this research is a test uses in pre-test and post-test.The result of this research presents that the jigsaw technique is successful to improve the students’ reading comprehension. It can be sees from paired samples t-test that there is a significant difference for the pre-test score (M = 52.33 SD = 22.234) and post-test (M = 80.17 SD = 9.048), t (29) = -9.275 , p &lt;0.05. It can be concludes that the jigsaw technique improves the students’ reading comprehension.