Reviewerly/exHarmony huggingface dataset:
Privacy-Preserving Cost-Optimization for Dynamic Replication in Cloud Data Centers

The cloud Storage Providers (CSPs) present geological documents are put away with a few memory space classes with arranging costs. A noteworthy issue encountering by the cloud customers can be the methods by which to blow this additional room classes for you to serve a license request with a period, contrasting residual job that needs to be done about its materials at any rate aggregate expense. Records intermittent notwithstanding replication approaches have a fundamental activity around appropriated methodologies over the electronic encouraging. In this paper arranged DRA Criteria to determine the technique which will complete a capacity zone strategy in which utilizes the specific Division and even Replication approach to putting away the data. In this procedure, the report will be isolated and these zones will be replicated and blend as demonstrated by the duplication factor before taking care of the idea upon the cloud. Usually, the parts are normally dissipated with the end goal that progressive clients in the electronic encouraging don't hold the areas of any proportionate convenience in this way while a PC is yielded no huge information is emphatically spilled on the attacker. This structure will improve cloud prosperity gauges using Category and Duplication of data on Cloud proposed for Optimal Functionality and Safety gauges reasoning.
중국호텔 종사원이 지각하는 심리적 자본이 조직시민행동과 직무성과에 미치는 영향

This research has aimed to verify the relationship among psychological capital, organizational citizenship behavior and job performance. The results of empirical analysis are as follows: Firstly, according to the results which verify the effects of psychological capital on organizational citizenship behavior, hope, optimism and resilience, the sub-factors of psychological capital, have positive (+) effects on organizational citizenship behavior, while the effects of self-efficacy on organizational citizenship behavior are insignificant. Secondly, according to the results which verify the effects of psychological capital on job performance, self-efficacy and optimism, the sub-factors of psychological capital, have positive (+) effects on job performance, while the effects of hope and resilience on job performance are insignificant. Therefore, that it is necessary for hotel enterprises to introduce human resource management system that can improve the psychological capital of employees is proposed. For example, as for job performance, it is necessary for internal hotel industry to adopt relatively fair personnel system, which means that it is most important to actively respond to work of employees within the hotels so as to provide confidence when executing work in the future. Systematizing correct incentive for goals is also most important.
Mutualized oblivious DNS ($μ$ODNS): Hiding a tree in the wild forest

The traditional Domain Name System (DNS) lacks fundamental features of security and privacy in its design. As concerns of privacy increased on the Internet, security and privacy enhancements of DNS have been actively investigated and deployed. Specially for user's privacy in DNS queries, several relay-based anonymization schemes have been recently introduced, however, they are vulnerable to the collusion of a relay with a full-service resolver, i.e., identities of users cannot be hidden to the resolver. This paper introduces a new concept of a multiple-relay-based DNS for user anonymity in DNS queries, called the mutualized oblivious DNS ($μ$ODNS), by extending the concept of existing relay-based schemes. The $μ$ODNS introduces a small and reasonable assumption that each user has at least one trusted/dedicated relay in a network and mutually shares the dedicated one with others. The user just sets the dedicated one as his next-hop, first relay, conveying his queries to the resolver, and randomly chooses its $0$ or more subsequent relays shared by other entities. Under this small assumption, the user's identity is concealed to a target resolver in the $μ$ODNS even if a certain (unknown) subset of relays collude with the resolver. That is, in $μ$ODNS, users can preserve their privacy and anonymity just by paying a small cost of sharing its resource. Moreover, we present a PoC implementation of $μ$ODNS that is publicly available on the Internet. We also show that by measurement of round-trip-time for queries, and our PoC implementation of $μ$ODNS achieves the performance comparable to existing relay-based schemes.
Multi-Density Attention Network for Loop Filtering in Video Compression

Video compression is a basic requirement for consumer and professional video applications alike. Video coding standards such as H.264/AVC and H.265/HEVC are widely deployed in the market to enable efficient use of bandwidth and storage for many video applications. To reduce the coding artifacts and improve the compression efficiency, neural network based loop filtering of the reconstructed video has been developed in the literature. However, loop filtering is a challenging task due to the variation in video content and sampling densities. In this paper, we propose a on-line scaling based multi-density attention network for loop filtering in video compression. The core of our approach lies in several aspects: (a) parallel multi-resolution convolution streams for extracting multi-density features, (b) single attention branch to learn the sample correlations and generate mask maps, (c) a channel-mutual attention procedure to fuse the data from multiple branches, (d) on-line scaling technique to further optimize the output results of network according to the actual signal. The proposed multi-density attention network learns rich features from multiple sampling densities and performs robustly on video content of different resolutions. Moreover, the online scaling process enhances the signal adaptability of the off-line pre-trained model. Experimental results show that 10.18% bit-rate reduction at the same video quality can be achieved over the latest Versatile Video Coding (VVC) standard. The objective performance of the proposed algorithm outperforms the state-of-the-art methods and the subjective quality improvement is obvious in terms of detail preservation and artifact alleviation.
Research Guides: Faculty Publishing Guide: ORCID: Linking an Existing Account to HeinOnline

This guide is intended to introduce ORCID and how it can assist in increasing scholarly impact.
Exploring Multi-dimensional Data via Subset Embedding

Multi-dimensional data exploration is a classic research topic in visualization. Most existing approaches are designed for identifying record patterns in dimensional space or subspace. In this paper, we propose a visual analytics approach to exploring subset patterns. The core of the approach is a subset embedding network (SEN) that represents a group of subsets as uniformly-formatted embeddings. We implement the SEN as multiple subnets with separate loss functions. The design enables to handle arbitrary subsets and capture the similarity of subsets on single features, thus achieving accurate pattern exploration, which in most cases is searching for subsets having similar values on few features. Moreover, each subnet is a fully-connected neural network with one hidden layer. The simple structure brings high training efficiency. We integrate the SEN into a visualization system that achieves a 3-step workflow. Specifically, analysts (1) partition the given dataset into subsets, (2) select portions in a projected latent space created using the SEN, and (3) determine the existence of patterns within selected subsets. Generally, the system combines visualizations, interactions, automatic methods, and quantitative measures to balance the exploration flexibility and operation efficiency, and improve the interpretability and faithfulness of the identified patterns. Case studies and quantitative experiments on multiple open datasets demonstrate the general applicability and effectiveness of our approach.
Partitioning around medoids (PAM) in clustering genre music

Music consists of many genres, so it is difficult to make a standard protocol system to standardize or grouping a music genre if the assessment is only subjective. PAM (Partitioning Around Medoids) is a clustering technique used in troubleshooting Genre of music's clustering process in this research. The parameters used are Average Energy (AE), Tempo, and Music Bar which it is produce a Muster (Music Clustering).  “Muster” is a application that makes up 5 clusters with PAM. 5 clusters are Genre Music with medium Tempo, music with Slow and quiet tempo, music with a less calm feel, music that tends to be loud, strong and fast. Sample data used in this research were 50 data testing, namely from the types of music categories of classical music, jazz, blues, rock, and pop which produced an accuracy rate of 72.66%.
Role of Social Media in Enhancing Agricultural Growth

Social media has been extensively used by rural youth due to tremendous increase in the number of smartphones users during last decade. A survey was conducted during 2018-19 to study the use of social media as a source of agricultural information, use pattern, preference towards different modes of information receiving and sharing, and frequency of use among rural youth. The 200 rural youth were randomly selected from the South-Western Mansa district of Punjab. Results of the study revealed that only ~6 per cent of the young farmers were using Radio as source of information for agriculture. Majority of the young farmers preferred social media viz. Youtube, WhattsApp and Facebook as a source of agricultural information. The young farmers had subscribed agriculture based channels on YouTube for getting agriculture related information. Majority of young farmers had been maintaining 4-5 WhatsApp groups to share and receive information on agriculture and allied fields. Use of PAU Mobile App and Digital Newspaper (Kheti Sandesh) was also popular among farmers. Young farmers observed that use of social media has a significant impact on crop management practices. About one-fourth (~27%) of respondents had increased acreage under recommended crop varieties, ~16.5 per cent had reduced the average number of sprays on rice crop, ~22.5 per cent had been scheduling irrigation based on weather based agro-advisory and ~24.1 per cent were getting information on marketing of crops from social media.
Analisis Transparansi dan Akuntabilitas Pengelolaan Dana Sekolah

This study, entitled the analysis of transparency and accountability in the management of school funds at SMK Plus Nusa Putra. The objectives of this study are: 1) to determine the description of school fund management 2) to find out whether the school has implemented transparency and accountability completely 3) to determine how the implementation of transparency in SMK Plus Nusa Puta. The method used in this research is descriptive qualitative method, how to collect data using direct interviews and data on BOS fund receipts at SMK Plus Nusa Putra. The results of the study indicate that the transparency of fund management at SMK Plus Nusa Putra leads to the transparent category.
Offline Rig - Offline and Cashless Payment

The study of a new form of payment that is both cashless and offline and yet tackles the problems of black money and is very secure, is what is introduced here. We can call this an open loop, stored value card system. The aim is not to replace cash or banks which we can never do. Every user is registered and given an NFC card, and a respective pin code. This card can be in any form like a credit card, or also simply a ring. This card performs the same role as a wallet performs to cash. The difference here is that this wallet is highly secure and money can be taken out only by the owner of the money. The money is stored inside the card in the form of an electronic record. We will store Rupee directly in the card. Money is transferred into the card from the bank, using an ATM like device that uses Internet connection. After the withdrawal, the amount is stored in the card locally (no database online). The transaction needs to have a third party (a POS device). This transaction would be both offline and cashless. The whole transaction also happens in a cryptographically secure way that there can be no hacking possible. The Internet is needed only for getting money from the bank (withdrawal). (abstract)
Capelin: Fast Data-Driven Capacity Planning for Cloud Datacenters

Cloud datacenters provide a backbone to our digital society. Crucial to meeting increasing demand while maintaining efficient operation is the activity of capacity planning. Inaccurate capacity planning for cloud datacenters can lead to significant performance degradation, denser targets for failure, and unsustainable energy consumption. Although this activity is core to improving cloud infrastructure, relatively few comprehensive approaches and support tools exist, leaving many planners with merely rule-of-thumb judgement. We propose Capelin, a data-driven, scenario-based capacity planning system for cloud datacenters. We design Capelin to address requirements we have derived from a unique survey of experts in charge of diverse datacenters in several countries. Capelin introduces the notion of portfolios of scenarios, which it leverages in its probing for alternative capacity-plans. At the core of the system, a trace-based, discrete-event simulator enables the exploration of different possible topologies, with support for scaling the volume, variety, and velocity of resources, and for horizontal (scale-out) and vertical (scale-up) scaling. The approach centers around a notion of portfolios of scenarios as a framework for probing alternative decisions and courses of events. Capelin gives detailed quantitative operational information for each scenario, which could facilitate human decisions in capacity planning. We implement and open-source Capelin, and show through comprehensive trace-based experiments it can aid practitioners. Although Capelin is designed to work across many kinds of datacenters, in this work we focus on private-cloud, business-critical workloads, and on public-cloud operations. The results give evidence that choices that seem reasonable and common in practice could be worse by a factor of 1.5-2.0 than the best, in terms of performance degradation or energy consumption. We also show evidence of Capelin identifying meaningful choices that are different from the baseline proposed by a team of professional datacenter engineers. We open-source Capelin and release data artifacts for public inspection and reuse.
Dynamic-OFA: Runtime DNN Architecture Switching for Performance Scaling on Heterogeneous Embedded Platforms

Mobile and embedded platforms are increasingly required to efficiently execute computationally demanding DNNs across heterogeneous processing elements. At runtime, the available hardware resources to DNNs can vary considerably due to other concurrently running applications. The performance requirements of the applications could also change under different scenarios. To achieve the desired performance, dynamic DNNs have been proposed in which the number of channels/layers can be scaled in real time to meet different requirements under varying resource constraints. However, the training process of such dynamic DNNs can be costly, since platform-aware models of different deployment scenarios must be retrained to become dynamic. This paper proposes Dynamic-OFA, a novel dynamic DNN approach for state-of-the-art platform-aware NAS models (i.e. Once-for-all network (OFA)). Dynamic-OFA pre-samples a family of sub-networks from a static OFA backbone model, and contains a runtime manager to choose different sub-networks under different runtime environments. As such, Dynamic-OFA does not need the traditional dynamic DNN training pipeline. Compared to the state-of-the-art, our experimental results using ImageNet on a Jetson Xavier NX show that the approach is up to 3.5x (CPU), 2.4x (GPU) faster for similar ImageNet Top-1 accuracy, or 3.8% (CPU), 5.1% (GPU) higher accuracy at similar latency.
A Motivational Literature Review

Motivating work has in recent two decades drawn scientific and commercial institutions. In the present study, investigators analysed the intensive literature in order to extract all potential motivating parameters, including direct and indirect effects on motivation strategies. This has examined the multidimensionality of motivation from the existing literature and present a conceptual framework based on it, and it is experienced that various motivation techniques (discussed in this study) are having a positive impact on both employee satisfaction and the quality of performance in the organization; however, the model needs to be validated using quantitative measures. For research the different issues discussed in this paper related for workplace morale, a large body of literature has been collected mostly from different publications. To make the study more current only those studies were included which were published in the last two decades. In past research papers few dimensions of motivation were used to explain the different models motivation theory which has direct influence on employee motivation. The novelty of this study lies in its theoretical framework where authors have made an attempt to come up with a construct having dimensions that directly or indirectly influences employee motivation.
PTAuth: Temporal Memory Safety via Robust Points-to Authentication.

Temporal memory corruptions are commonly exploited software vulnerabilities that can lead to powerful attacks. Despite significant progress made by decades of research on mitigation techniques, existing countermeasures fall short due to either limited coverage or overly high overhead. Furthermore, they require external mechanisms (e.g., spatial memory safety) to protect their metadata. Otherwise, their protection can be bypassed or disabled. To address these limitations, we present robust points-to authentication, a novel runtime scheme for detecting all kinds of temporal memory corruptions. We built a prototype system, called PTAuth, that realizes this scheme on ARM architectures. PTAuth contains a customized compiler for code analysis and instrumentation and a runtime library for performing the points-to authentication as a protected program runs. PTAuth leverages the Pointer Authentication Code (PAC) feature, provided by the ARMv8.3 and later CPUs, which serves as a simple hardware-based encryption primitive. PTAuth uses minimal in-memory metadata and protects its metadata without requiring spatial memory safety. We report our evaluation of PTAuth in terms of security, robustness and performance using 150 vulnerable programs from Juliet test suite and the SPEC CPU2006 benchmarks. PTAuth detects all three categories of heap-based temporal memory corruptions, generates zero false alerts, and slows down program execution by 26% (this number was measured based on software-emulated PAC; it is expected to decrease to 20% when using hardware-based PAC). We also show that PTAuth incurs 2% memory overhead thanks to the efficient use of metadata.
Teacher’s Reinforcement in Teaching English at the Second Year of State Islamic Senior High School 2 Kuantan Singingi

This research was aimed to find out the teacher’s reinforcement in teaching English at the second year of State Islamic Senior High School 2 Kuantan Singingi. The subjects of this research were an English teacher and 5 students. This research was qualitative method with descriptive technique. In gathering the data, researcher distributed interview and observation to determine what components of reinforcement used by the teacher in teaching English. The result of this research showed that the English teacher at the second year of State Islamic Senior High School 2 Kuantan Singingi used verbal and non-verbal reinforcement in teaching English. For verbal reinforcement, the teacher used “reinforcement with words and reinforcement with sentence”. For non-verbal reinforcement, the teacher used “gestural reinforcement, proximity reinforcement, contact reinforcement, activity reinforcement and token reinforcement”. The reinforcement mostly often used by the teacher in teaching English is the reinforcement with words (22%), whereas the reinforcement that is rarely used by the teacher is token reinforcement (6%).
PENGGALIAN KARAKTERISTIK PENGGUNA PADA FASE ELISITASI PERANGKAT LUNAK MENGGUNAKAN USER PERSONA

Requirements elicitation is activities aimed at finding the needs of a system through communication with system users. The purpose of requirements elicitation is to find out what problems have been encountered. User persona is a fictional representation of the ideal user. The software developer will begin the design process by conducting user research, establishing communication with the target user and identifying exactly what they need with the product to be made. Personas are generally based on these users and combine the needs, goals, and behavior patterns observed from the target audience. This study aims to determine information systems related to the characteristics and needs of users of the software, so that the data generated in the form of qualitative data from prospective users. By using the hypotheses that are made, which will later be analyzed and used as a basis for developing projects. The results of this study are information in accordance with user needs that will be implemented using a use case and software prototype.
PEMANFAATAN LIMBAH BATUBARA FLY ASH SEBAGAI ADSORBEN UNTUK PENYERAPAN ZAT TOKSIN PIRIDIN UTILIZATION OF COAL FLY ASH WASTE AS ADSORBENT FOR THE ADSORPTION OF PYRIDINE TOXINS

PEMANFAATAN LIMBAH BATUBARA FLY ASH  SEBAGAI ADSORBEN UNTUK PENYERAPAN ZAT TOKSIN PIRIDIN UTILIZATION OF COAL FLY ASH WASTE AS ADSORBENT FOR THE ADSORPTION OF PYRIDINE TOXINS
Pendampingan Sistem Monitoring Absensi dan Pelanggaran Siswa Berbasis WEB dan BOT Telegram

The purpose of this web-based student attendance and student violation information system assistance and telegram bot is to make it easier for schools and student guardians to monitor disciplinary and student violation levels, so that the school can use it in this case SMP Nurul Jadid as evaluation material and consideration for making an Existing policies and regulations at Nurul Jadid Middle School, Telegram Bot are functioned to attend students by the teacher, so that the results of teacher input will be immediately recapitulated by the system, while for the website it is made using the CodeIgniter Framework to facilitate recording related attendance and student violations , while the mentoring process is carried out to the discipline and student affairs department so that later it will be disseminated to all teachers at Nurul Jadid Middle School.
LibGuides: Early Childhood Reading Support: Early Reading Advocacy

Understanding how early literacy will empower your little one, with practice tools and resources to get you started