Reviewerly/exHarmony huggingface dataset:
Online Social Grievance Redressal using Blockchain

In recent years there has been a sudden growth of online social media. Every day, government accounts receive thousands of messages from the general public in the form of opinions, concerns, and grievances. It becomes an extremely troublesome task for the concerned ministries in the government, to manually ﬁlter out the irrelevant messages and respond to the genuine ones. Also, along these lines, no move is made by the administration services on the significant concerns or the complaints of the general population. In this paper, the endeavor is to develop an Online Social Grievance Redressal System wherein individuals can post their grievances and they would be automatically segregated under that similar category by utilizing learning algorithms. We have considered the Random Forest Algorithm to Categorize and compare the grievances and these outcomes to determine the most effective learning algorithm.
Reverse Prevention Sampling for Misinformation Mitigation in Social Networks

In this work, we consider misinformation propagating through a social network and study the problem of its prevention. In this problem, a bad campaign starts propagating from a set of seed nodes in the network and we use the notion of a limiting (or good) campaign to counteract the effect of misinformation. The goal is to identify a set of k users that need to be convinced to adopt the limiting campaign so as to minimize the number of people that adopt the bad campaign at the end of both propagation processes.This work presents RPS (Reverse Prevention Sampling), an algorithm that provides a scalable solution to the misinformation prevention problem. Our theoretical analysis shows that RPS runs in O((k + l)(n + m)(1/(1 - γ)) log n / e²) expected time and returns a (1 - 1/e - e)-approximate solution with at least 1 - n^{-l} probability (where γ is a typically small network parameter and l is a confidence parameter). The time complexity of RPS substantially improves upon the previously best-known algorithms that run in time Ω(m n k ⋅ POLY(e^{-1})). We experimentally evaluate RPS on large datasets and show that it outperforms the state-of-the-art solution by several orders of magnitude in terms of running time. This demonstrates that misinformation prevention can be made practical while still offering strong theoretical guarantees.
A Study of English Chinese Comparison and Translation Skills based on Computer Network

Abstract Translation should not only be accurate, but also be based on the culture of both languages. This paper expounds the essence of translation, discusses the skills of translation and the complementary role of machine translation in English-Chinese translation in the present era of computer network development.
Context-dependent grammars

This chapter gives an extensive and thorough coverage of grammars that generate languages under various context -related restrictions. First, it covers classical grammars based upon tight context restrictions. Then, it studies context conditional grammars and their variants, including random context grammars, generalized forbidding grammars, semi-conditional grammars, and simple semi-conditional grammars. They all are based upon loose context restrictions. More precisely, they have their rules enriched by permitting and forbidding strings, referred to as permitting and forbidding conditions, respectively. These grammars perform their language-generation process in such a way that they require the presence of permitting conditions and, simultaneously, the absence of forbidding conditions in the rewritten sentential forms.
Investigation on Evaluation Methoi of gooperation Team with Person ani Robot for Service Mission

Recently, many ronots have neen used in an industry field. Mainly, they are engaging in heavy work. But to enlarge the territory of the ronot, it is necessary to correspond to service work using the ronot. Ronots doing heavy work are used at the factory; on the other hand, service work is done in our everyday life. Therefore, opportunities to work with a mixed team consisted of a person and ronots will increase in the service field. We have proposed the design method of this mixed team with the effective role allotment considering anout performance anilities of each team memner for the service mission. Also, the estimation of results of the mission ny this team is necessary for the improvement of the work efficiency. Therefore, in this paper, the evaluation method for the service work of the mixed team is proposed from noth viewpoints of a supervisor of the team and service recipients using the rating method of the anility for occupation.
Choosing the Best Algorithm

We have learned different types of algorithms such as sorting, searching, and graph algorithms, and there are likely to be many possible algorithms which perform the same task. The question is, if we want to search for a value in the list, which type of searching algorithm do we have to choose? By analyzing various algorithms, we will study this question in this chapter.
Integrating Social Media into a Pan-European Flood Awareness System: A Multilingual Approach.

This paper describes a prototype system that integrates social media analysis into the European Flood Awareness System (EFAS). This integration allows the collection of social media data to be automatically triggered by flood risk warnings determined by a hydro-meteorological model. Then, we adopt a multi-lingual approach to find flood-related messages by employing two state-of-the-art methodologies: language-agnostic word embeddings and language-aligned word embeddings. Both approaches can be used to bootstrap a classifier of social media messages for a new language with little or no labeled data. Finally, we describe a method for selecting relevant and representative messages and displaying them back in the interface of EFAS.
clemensv SOA was never about ESB. SOA is a design principle for loosely coupled services. Microservices is an implementation of SOA.

@clemensv SOA was never about ESB. SOA is a design principle for loosely coupled services. Microservices is an implementation of SOA.
Survey and examination utilizing the 3D model of the early Showa manufactured gear cutting machine

Nippon Institute of Technology industrial technologies museum is keeping about 300 models of the Showa early stage and more than 40000 action drawings made of the original machine tool.
Gradient &#120001; 1 Regularization for Quantization Robustness.

We analyze the effect of quantizing weights and activations of neural networks their loss and derive a simple regularization scheme that improves robustness against post-training quantization. By training quantization-ready networks, our approach enables storing a single set of weights that can be quantized on-demand to different bit-widths as energy and memory requirements of the application change. Unlike quantization-aware training using the straight-through estimator that only targets a specific bit-width and requires access to training data and pipeline, our regularization-based method paves the way for on the fly'' post-training quantization to various bit-widths. We show that by modeling quantization as a $\ell_\infty$-bounded perturbation, the first-order term in the loss expansion can be regularized using the $\ell_1$-norm of gradients. We experimentally validate the effectiveness of our regularization scheme different architectures CIFAR-10 and ImageNet datasets.
Three Dimensional Model Reconstruction of a Cuboid Based on Stereo Vision

Three-dimensional reconstruction of objects is one of the key elements in production processes. Stereo vision is one of the robost techniques in this field. Accuracy of the reconstruction is influenced by several parameters that mainly determined through the calibration process. Besides, symetring of two accquired images effects on the accuracy. In the present research, a three-dimensional model reconstruction system based on stereo vision technique included a camera, a robot, a lightening system, a cubic object, and IMAQ Image Processing and LabVIEW Softwares. The inactive stereo vision was considered such that the images were acquired by the same camera in two different positions. The cuboid model was implemented after camera calibration. The corners of the object were considered to remove the symmetry problems. After comparing the dimensions of the reconstructed model with those of real objects, the maximum error value of the system was obtained as 0.75 mm and the error variance as 0.09 mm.
On Application of Option Design Pattern

With the rapid progress of the computational mechanics, CAE software, such as FEM programs, are having many functions and become more complicated. Because the development shouldn't be stopped, every CAE program should consider future functionality expansions. It is difficult, however, to forecast what types of expansions are required from the future researches. Object-oriented approach appears a promising technique to develop complicated and flexible software. Especially adoption of design patterns fits the purpose. The Option design pattern has been proposed for this purpose by the author, and applied to implement new functions into the existing basic FEM program. In this paper, the experiences of these activities are summarized and a future aspect of the Option pattern will be discussed.
PERENCANAAN INSTALASI PENGOLAHAN AIR LIMBAH (IPAL) KOMUNAL CLUSTER RIVERPLACE PERUMAHAN TIRTASANI KABUPATEN MALANG

Tirtasani Estate doesn’t have communal wastewater treatment which makes the water polluted. To solve those problems, the writer intended to design wastewater treatment plant. This thesis aimed to (1) find the waswater discharge (2) design the wastewater treatment plant (WWTP) system (3) estimate the cost of WWTP manufacturing.The data needed for this design were the map of the housing, Tirtasani estate’s topographic map, Work Unit Price of Malang District 2018. The data were obtained from site surveys.The design resulted in (1) 85.6 m3 / day wastwater discharge (2) wastewater discharge made into f 4” wastewater pipe; 3 unit of 30 m3 WWTP tank with Anaerobic aerobic system ; 3.25 m x 9.5 m x 3.5 m WWTP structure. Keywords: communal, design, WWTP
The Time optimization for polynomial series using a long For in C

We use a For loop in the programming language C to optimize lines of code and time in the resolution of polynomial series and we make a comparison between the conventional For and a long For to optimize the execution time, the results show a saving of lines of code and great saving of time for the resolution of polynomials when there is a greater number of terms in the function.
THE EFFECT OF USING SCRAMBLE PARAGRAPH METHOD ON STUDENTS’ ABILITY IN WRITING PROCEDURE TEXT OF THE EIGTH GRADE STUDNET OF SMP NEGERI 2 SATU ATAP BATANG SERANGAN IN ACADEMIC YEAR 2019/2020

The objective of the study was: “to find out whether there is any effect of using scramble paragraph method on students’ ability in writing procedure text of the eigth grade studnet of SMP Negeri 2 Satu Atap Batang Serangan in academic year 2019/2020”. This research was conducted at SMP Negeri 2 Satu Atap Jl. Batang Serangan-Kwala Sawit Kecamatan Batang Serangan Kabupaten Langkat. The population of this study was the whole students of eigth Year Students of SMP Negeri 2 Satu Atap Batang Serangan that consist of four class, namely VIII. With the total number of the students were 132 students. Where students of class VIII-2 totaling 32 people as an experimental class and class VIII-4 totaling 32 people as a control group. In this research method was the type of experimental research which is one type of research which aims to provide an overview of the influence of variables x and y variables. The average pretest control class was 56 and the posttest control group rose to 66. While the experimental class average value obtained for 64.7 pretest and posttest riding on the outcome of 76. This shows that the experimental class was better than the control class. Overall the data comes from a normal population and the entire data homogeneous manifold. Of the survey results revealed that to= 12.1 t criticism at 5% level obtained 1.69 and at level 1% obtained t = 1.31 then 1.31 &lt;12.1&gt; 1.69, then the hypothesis of significant meaning hypothesis proved to be true, namely "There is significant affect of using scramble paragraph method on students ability in writing procedure text of the eigth grade studnet of SMP Negeri 2 Satu Atap Batang Serangan in academic year 2019/2020”.
LSHSL: Remote Library Access: Remote Library Access

This guide will instruct you how to access all of the library's resources remotely or off-campus.
LibGuides: Pandemic Resources for Academic Libraries: Distance Education and Engagement

Updated information, professional development, and resources to support academic and research library personnel during a pandemic.
Interactive Visualization Technique of Molecular Dynamics Simulation by Using HMD and VR

As a new approach of scientific visualization in the field of atomic/molecular (MD) analysis, concepts of interactivity and virtual reality (VR) are integrated in the simulation program by using general-purpose HMD (head-mounted display). The study is discussing the availability and efficiency of such VR-directed microscopic simulations. The present implementation is conducted simply on a general-purpose programming development environment for VR, which becomes popular in making 3D-video-games and so on. The sample of MD simulation consists of several-hundred copper atoms which are interacting by Lennard-Jones-type pairwise potential function. The mechanism of interaction is realized by operating controllers wirelessly connected to the HMD device and it allows us to touch and move single atom or atomic group via displacement or force. It is understood that adequate transformation factors in both length and time scales are required between physical entity computed (atomic regime) and our dwelling VR space.
THE CORRELATION BETWEEN STUDENTS’ HABIT IN WATCHING ENGLISH MOVIE AND LISTENING ACHIEVEMENT (BY FOURTH SEMESTER STUDENTS OF UNIVERSITAS MUHAMMADIYAH PALEMBANG)

The objective of this study was to find out the correlation between students’ habit in watching English movie (X) and listening achievement(Y) by fourth semester students of Universitas Muhammadiyah Palembang There were 47 students taken as the sample of this study who were determined by using purposive sampling technique. The collected data was analyzed by using Pearson Product Moment Correlation and the instruments used were students’ listening scores and questionnaire of students’ habit in watching English movie. Subsequently, the research finding indicated that there was low correlation between students’ habit in watching English movie and listening achievement. It proved by the obtain (0.212) which lower than r table (0.2845). It considered that alternative hypothesis (Ha) in this research was rejected and the null hypothesis (Ho) which stated that there was no correlation between students’ habit in watching English movie and their listening achievement accepted. In conclusion, there was low correlation between students’ habit in watching English movie and their listening achievement.
A Universal Defense System Based on Backtrace Canary for ELF Against Vulnerabilities

With the development of vulnerability exploitation technology, attackers can usually bypass various mitigations provided by the operating system through the combination of multiple vulnerabilities and finally obtain the permission of the server. We analyzed the principles of program function calls and proposed a vulnerability mitigation named Backtrace Canary which is based on the Backtrace Control Flow Graph. We have also implemented a universal vulnerability defense system based on it. Experiments show that the vulnerability defense system is very practical.
Temporal Word Embeddings for Dynamic User Profiling in Twitter.

The research described in this paper focused on exploringthe domain of user profiling, a nascent and contentious technology whichhas been steadily attracting increased interest from the research community as its potential for providing personalised digital services is realised.An extensive review of related literature revealed that limited researchhas been conducted into how temporal aspects of users can be capturedusing user profiling techniques. This, coupled with the notable lack ofresearch into the use of word embedding techniques to capture temporalvariances in language, revealed an opportunity to extend the Random Indexing word embedding technique such that the interests of users couldbe modelled based on their use of language. To achieve this, this workconcerned itself with extending an existing implementation of TemporalRandom Indexing to model Twitter users across multiple granularities oftime based on their use of language. The product of this is a novel technique for temporal user profiling, where a set of vectors is used to describethe evolution of a Twitter user’s interests over time through their use oflanguage. The vectors produced were evaluated against a temporal implementation of another state-of-the-art word embedding technique, theWord2Vec Dynamic Independent Skip-gram model, where it was foundthat Temporal Random Indexing outperformed Word2Vec in the generation of temporal user profiles.
UMP alumni builts the business empire of Caliphs Technology PLT

Never thought of owning a company. When asked when he was younger, Abang Fairul Syarmil Abang Mohd dreamed of becoming a pilot, but who would have thought that his studies in Computer Science at Universiti Malaysia Pahang (UMP) would allow him the opportunity to build his business empire, Caliphs Technology PLT.
LibGuides: M-level and PGCE courses: Working Remotely with SUC Library - FAQs

Library support for Masters level and PGCE students in Stranmillis University College Guidance on resources and using the Library remotely
Deep Binary Tree: Embedded Artificial Intelligence

This lecture introduces Deep Binary Tree (DBT), which was obtained from the investigation of a problem, “How we can give adaptation capability like creatures for machines.” Human brain autonomously conducts modeling of unknown dynamical systems and optimization of their control rules. This autonomous modeling and optimization are outstanding features that many sorts of conventional artificial intelligence failed to reach. DBT realizes autonomous and stable model learning on stand-alone, less resourced environment such as microcomputer. In this lecture, we introduce several application examples including control optimization, anomaly detection, and human-machine interface.
Optimizing CFD Results with Sequential Model-Based Optimization

Sequential model based optimization (SMBO) is an efficient Black-Box function optimization technology used to optimize hyperparameters in the machine learning that take time to learn once. In this paper, we apply the SMBO framework Bayesian optimization and TPE (tree-structured parzen estimator) to CFD optimization and compare the two optimization methods. In the 8-variable pressure drop minimization problem, Bayesian optimization is superior to TPE.
Hidden State Guidance: Improving Image Captioning Using an Image Conditioned Autoencoder.

Most RNN-based image captioning models receive supervision on the output words to mimic human captions. Therefore, the hidden states can only receive noisy gradient signals via layers of back-propagation through time, leading to less accurate generated captions. Consequently, we propose a novel framework, Hidden State Guidance (HSG), that matches the hidden states in the caption decoder to those in a teacher decoder trained on an easier task of autoencoding the captions conditioned on the image. During training with the REINFORCE algorithm, the conventional rewards are sentence-based evaluation metrics equally distributed to each generated word, no matter their relevance. HSG provides a word-level reward that helps the model learn better hidden representations. Experimental results demonstrate that HSG clearly outperforms various state-of-the-art caption decoders using either raw images or detected objects as inputs.
A perspective on multi-agent communication for information fusion.

Collaborative decision making in multi-agent systems typically requires a predefined communication protocol among agents. Usually, agent-level observations are locally processed and information is exchanged using the predefined protocol, enabling the team to perform more efficiently than each agent operating in isolation. In this work, we consider the situation where agents, with complementary sensing modalities must co-operate to achieve a common goal/task by learning an efficient communication protocol. We frame the problem within an actor-critic scheme, where the agents learn optimal policies in a centralized fashion, while taking action in a distributed manner. We provide an interpretation of the emergent communication between the agents. We observe that the information exchanged is not just an encoding of the raw sensor data but is, rather, a specific set of directive actions that depend on the overall task. Simulation results demonstrate the interpretability of the learnt communication in a variety of tasks.
ABNORMAL CROWD BEHAVIOUR DETECTION BASED ON DEEP LEARNING AND SPARSE REPRESENTATION

This article proposes a new method combining improved principal component analysis network (PCANet) and sparse representation for abnormal crowd behaviour detection on the consideration that “abnormal events are not “normal events.
Improved Approximate Degree Bounds for k-Distinctness.

An open problem that is widely regarded as one of the most important in quantum query complexity is to resolve the quantum query complexity of the k-distinctness function on inputs of size N. While the case of k=2 (also called Element Distinctness) is well-understood, there is a polynomial gap between the known upper and lower bounds for all constants k>2. Specifically, the best known upper bound is O (N^{(3/4)-1/(2^{k+2}-4)}) (Belovs, FOCS 2012), while the best known lower bound for k≥ 2 is Ω(N^{2/3} + N^{(3/4)-1/(2k)}) (Aaronson and Shi, J. ACM 2004; Bun, Kothari, and Thaler, STOC 2018).For any constant k ≥ 4, we improve the lower bound to Ω(N^{(3/4)-1/(4k)}). This yields, for example, the first proof that 4-distinctness is strictly harder than Element Distinctness. Our lower bound applies more generally to approximate degree. As a secondary result, we give a simple construction of an approximating polynomial of degree O(N^{3/4}) that applies whenever k ≤ polylog(N).
How Highly Would Microsoft Rank If it Were a Country? A Comparison of Microsoft Revenues to Nations’ GDP

As of December 31, 2019, Microsoft was the third largest corporation in the world in terms of market capitalization. This paper ranks Microsoft, comparing Microsoft’s revenue to the GDP of the world’s 185 largest nations.
The Level of Organizational Learning for Emergency Preparedness Work on Organizational Immersion in Local Governments - Focusing on the Intermediary Effect of Self-directed Learning -

The purpose of the study is to analyze the relationship between the level of organizational learning related to emergency preparedness of local governments and their members’ self-directed learning ability and organizational immersion. The study was conducted by carrying out a survey of 175 members of the Civil Defense Emergency Preparedness Team in 12 cities and provinces in South Korea. The results are as follows. First, there was a significant correlation among organizational learning, self-directed learning, and organizational immersion of the emergency preparedness organizations. Second, organizational learning had a positive effect on self-directed learning and job immersion of their members. Third, self-directed learning was shown to serve as a mediator between organizational learning and organizational immersion. Findings and limitations are discussed.