Reviewerly/exHarmony huggingface dataset:
BLogCHAIN: proof-of-concept and pilot testing of a blockchain application prototype for construction logistics in Sweden

Blockchain technology has a potential for construction logistics, also within Sweden.In this paper, a proposal of a blockchain system and its practical implementation is presented (the BLogCHAIN prototype).BLogCHAIN was preliminarily tested during the early construction of a school in Sweden, in November-December 2020.Methodologically, we reviewed studies on blockchain for construction logistics, interviewed the BLogCHAIN testers (suppliers and contractor's operatives), and understood the test's practical outcomes through sociomateriality.Our results include the confirmation of envisioned benefits when implementing BLogCHAIN (e.g.reducing accounting rework), but also a simplification from its initial conceptualization, mainly due to rigidly established work practices. THEORY SociomaterialityThe theory of sociomateriality emphasizes that the material and social aspects of (digital) technologies are inseparable and fused in practice (Orlikowski & Scott, 2008,2016).Actions of utilizing the digital technology are no longer considered to be exclusively human properties, but are performed through interactions between humans and non-humans (Moura & Bispo, 2020).This interactive
Key generation schemes for channel authentication in quantum key distribution protocol

Quantum key distribution (QKD) systems enable secure key generation between two parties. Such systems require an authenticated classical channel for QKD protocols to work. Usually, the initial authentication key for this channel is pre-shared. In this work, methods that are used to renew the pre-shared keys ensuring a high level of security and performance for the subsequent quantum key generation are discussed. The model of QKD systems in terms of the lifecycle of the keys is formalised and a full set of parameters that can be used for key renewal functions is described. A detailed adversary model allows us to compare key renewal schemes by the probabilities of successful attacks and their consequences. As a result, it is shown that a hybrid key renewal scheme, which uses both the auxiliary pre-shared key and a part of the quantum sequence, has the higher security properties among considered schemes and is recommended to be used in QKD systems.
MIXP: Efficient Deep Neural Networks Pruning for Further FLOPs Compression via Neuron Bond

Neuron networks pruning is effective in compressing pre-trained CNNs for their deployment on low-end edge devices. However, few works have focused on reducing the computational cost of pruning and inference. We find that existing pruning methods usually remove parameters without fine-grained impact analysis, making it hard to achieve an optimal solution. This work develops a novel mixture pruning mechanism, MIXP, which can effectively reduce the computational cost of CNNs while maintaining a high weight compression ratio and model accuracy. We propose to remove neuron bond that can effectively reduce convolution computations and weight size in CNNs. We also design an influence factor to analyze the importance of neuron bonds and weights in a fine-grained way so that MIXP could achieve precise pruning with few retraining iterations. Experiments with MNIST, CIFAR-10, and ImageNet datasets demonstrate that MIXP could achieve significantly fewer FLOPs and retraining iterations on four widely-used CNNs than existing pruning methods.
Evaluation of Social Media Impact on UN Agencies in Yemen

Nowadays, the whole world is becoming a small village. Globalization is the fact of living everywhere. The use of the internet and advanced technology integrates with all different life angles and can never be neglected in our daily lives. As part of this technology advancement, social media has broken into our daily lives and you can find these platforms or at least one of them in every home. Social media is now part of any business everywhere, and all businesses now think of it as the first marketing option for all kind of services provided. Starting from the fact that social media is a critical tool for any business, this study analyzes how social media can affect the work of non-profit organizations. The study targets UN agencies in Yemen. To assess and evaluate this impact of social media on UN agencies in Yemen, a questionnaire of 25 questions was constructed and circulated among different people in these agencies. As in the case of other previous studies, the results of this study show that there is a great positive impact of social media on brand awareness, community engagement and organizations performance. Similar to other studies, fundraising is used as purpose of social media use, but it still needs more strategic plans in the future to be applied efficiently. UN agencies have to keep on more strategic plans to keep their social media platforms into their own targets.
Gesture Controlled Mouse Using Arduino

In today's era human-machine interaction is becoming widespread.So, with the introduction of new technologies the gap between machines and humans is being reduced to ease the standard of living.Gestures have played a crucial role in diminishing this gap.This project deals with design and implementation of an accelerometer based hand gesture controlled robot controlled wirelessly using a small low cost, 3-axis accelerometer.A novel algorithm for gesture identification has been developed to replace the approach of conventional controlling mechanism of robots via buttons etc. by an innovative hand gesture based controlling.Using a microcontroller system the program has been written & executed.In the existing system, human hand movements are sensed by the robot through sensors and it follow the same.As the person moves their hand, the accelerometer also moves accordingly sensor displaces and this sensor senses the parameter according to the position of hand.
Applicability of Ordinal Sums of Conjunctive and Disjunctive Functions in Classification

Classification relies on the rules expressed by domain experts, or on the labeled attribute explaining the output classes.However, such information is not always available.In this work, we explore classification according to aggregation functions of mixed behaviour by the variability in ordinal sums of conjunctive and disjunctive functions.By this approach, entities are classified into three classes: yes, no and maybe including inclination to the classes yes and no.By the proposed approach, domain experts (or ordinal users) explain classification linguistically, without stating IF-THEN rules and labeled output.The applicability is illustrated by two examples.The discussion of the results and further research activities conclude the paper.
Modernization of Education for Medical Students Using a Virtual Reality Clinic

The paper presents the results of a study conducted on the basis of the I.I. Mechnikov North-West State Medical University, aimed at identifying the prospects for the introduction of VR technologies in the medical educational environment. The estimates obtained by questioning 100 students who have passed the equipment testing indicate the possibility of modernizing the educational process by integrating virtual technologies through deep immersion, high comfort when using the simulator, and the possibility of simulating situations from different disciplines.
Network topology detection via uncertainty analysis of an identified static model

In this paper, we propose a methodology to detect the topology of a dynamic network that is based on the analysis of the uncertainty of the static characteristic of the matrix of transfer functions between the external excitations and the node signals.
An Evaluation Dataset and Strategy for Building Robust Multi-turn Response Selection Model

Multi-turn response selection models have recently shown comparable performance to humans in several benchmark datasets.However, in the real environment, these models often have weaknesses, such as making incorrect predictions based heavily on superficial patterns without a comprehensive understanding of the context.For example, these models often give a high score to the wrong response candidate containing several keywords related to the context but using the inconsistent tense.In this study, we analyze the weaknesses of the open-domain Korean Multi-turn response selection models and publish an adversarial dataset to evaluate these weaknesses.We also suggest a strategy to build a robust model in this adversarial environment.
Residual Vector Capsule: Improving Capsule by Pose Attention

The convolutional neural network has significantly improved the accuracy of image recognition; however, it performs in a fragile manner when we apply viewpoint transformation or add noise to the image.Recent studies have proposed new neural networks named capsule.Capsule build the partwhole relationship in the entity through instantiation parameters, and they cluster instantiation parameters layer by layer through routing-by-agreement; therefore, capsule has stronger representational ability and robustness than convolutional neural networks.However, the routing-by-agreement of the capsule network is limited by the prior probability assumption, which performs in an unstable way in recognition accuracy and robustness.To remove the restriction of the prior probability assumption in the routing-by-agreement, we propose a new capsule named the residual vector capsule (RVC), which constructs the routing-byagreement with self-attention.The experimental results show that compared with other capsule networks, RVC achieves competitive classification accuracy on MNIST, Fashion-MNIST, CIFAR-10 and SVHN, improves the viewpoint invariance of the model on SmallNorb, and significantly improves the robustness of the model against white box attacks on CIFAR-10 and SVHN.
PERANCANGAN APLIKASI JALUR PENDAKIAN DAN MONITORING PENDAKI GUNUNG UNGARAN BERBASIS GLOBAL POSITIONING SYSTEM (GPS)

Ungaran Mountain has a height of 2050 meters above sea level, this mountain is suitable for beginner climbers who want to know more about climbing hobbies, Ungaran climbers themselves only take about 3-5 hours, depending on the speed of walking, the climbing route is also quite light and very suitable for heating before starting to climb higher mountains. Thus many novice climbers who want to try to climb and conquer Mount Ungaran, armed with minimal experience of mountain climbing, the risks they face are even greater, ranging from getting lost, being hypothermic to death while climbing. To make it easier for Ungaran mountain climbers who are dominated by novice climbers in this study, the Ungaran Mountaineering Track and Monitoring Application Based on the Global Positioning System (GPS) on the Android System "which was built to make it easier for Ungaran mountain climbers to access information provided by Ungaran mountain climbers. needed to climb Mount Ungaran, and it is also useful for the team at base camp to monitor climbers who climb..
KeyMemoryRNN: A Flexible Prediction Framework for Spatiotemporal Prediction Networks

Most previous recurrent neural networks for spatiotemporal prediction have difficulty in learning the long-term spatiotemporal correlations and capturing skip-frame correlations. The reason is that the recurrent neural networks update the memory states only using information from the previous time step node and the networks tend to suffer from gradient propagation difficulties. We propose a new framework, KeyMemoryRNN, which has two contributions. The first is that we propose the KeyTranslate Module to extract the most effective historical memory state named keyword state, and we propose the KeyMemory-LSTM which uses the keyword state to update the hidden state to capture the skip-frame correlation. In particular, KeyMemoryLSTM has two training stages. In the second stage, KeyMemoryLSTM adaptively skips the update of some time step nodes to build a shorter memory information flow to alleviate the difficulty of gradient propagation to learn the long-term spatiotemporal correlations. The second is that both KeyTranslateModule and KeyMemoryLSTM are flexible additional modules, so we can apply them to most RNN-based prediction networks to build KeyMemoryRNN with different base network. The KeyMemoryRNN achieves the state-of-the-art on three spatiotemporal prediction tasks, and we provide ablation studies and memory analysis to verify the effectiveness of KeyMemoryRNN.
The Impact of Blockchain Technologies for the Agriculture Development and Sustainability

Global warming has changed our environment and our society at a high speed.Luckily for us, scientists and researchers have worked around the clock on technologies that could ease the effects of the principal sectors of the economy -agriculture and manufacturing.Although, in the last two to three decades, services have been on a continuous evolutionary pattern, and, more or less, have attracted the spotlight, the fundamentalism of the first two sectors of the economy continues to daunt on our society, and, particularly, on the management and technologies behind it.The current paper addresses the necessity of breaking the existing business model in agriculture, and describes the architecture behind a new model that pertains to the innovative data-sharing capabilities of the blockchain for the ultimate purpose of agricultural development and sustainability.The study was designed around a content analysis on previous research, and added on the alignment to the new potential business model for smart agriculture using blockchain technologies.
A Quality Assessment Instrument for Systematic Literature Reviews in Software Engineering

Background: Systematic literature reviews (SLRs) have become a standard practice as part of software engineering (SE) research, although their quality varies.To build on the reviews, both for future research and industry practice, they need to be of high quality.Aim: To assess the quality of SLRs in SE, we put forward an appraisal instrument for SLRs.Method: A well-established appraisal instrument from research in healthcare was used as a starting point to develop the instrument.It is adapted to SE using guidelines, checklists, and experiences from SE.The first version was reviewed by four external experts on SLRs in SE and updated based on their feedback.To demonstrate its use, the updated version was also used by the authors to assess a sample of six selected systematic literature studies. Results:The outcome of the research is an appraisal instrument for quality assessment of SLRs in SE.The instrument includes 15 items with different options to capture the quality.The instrument also supports consolidating the items into groups, which are then used to assess the overall quality of an SLR. Conclusion:The presented instrument may be helpful support for an appraiser in assessing the quality of SLRs in SE.
The scaling of PGA with IV2p and its potential for Earthquake Early Warning in Thessaly (Central Greece)

The main goal of an Earthquake Early Warning System (EEWS) is to estimate the expected peak ground motion of the destructive S-waves using the first few seconds of P-waves, thus becoming an operational tool for real-time seismic risk management in a short timescale. EEWSs are based on the use of scaling relations between parameters measured on the initial portion of the seismic signal, after the arrival of the first wave. Herein, using the abundant seismicity that followed the 3 March 2021 Mw=6.3 earthquake in Thessaly we propose scaling relations for PGA, from data recorded by local permanent stations, as a function of the integral of the squared velocity (IV2p). The IV2p parameter was estimated directly from the first few seconds-long signal window (tw) after the P-wave arrival. Scaling laws are extrapolated for both individual and across sites (i.e., between a near-source reference instrument and a station located close to a target). The latter approach is newly investigated, as local site effects could have a significant impact on recorded data. Considering that further study on the behavior of IV2p is necessary, there are indications that this parameter could be used in future on-site single‐station earthquake early warning operations for areas affected by earthquakes located in Thessaly, as itpresents significant stability.
A Knowledge Based Word Sense Disambiguation in Telugu Language

Telugu (తెలుగు) is one of the Dravidian languages which are morphologically rich. As within the other languages, it too consists of ambiguous words/phrases which have one-of-a-kind meanings in special contexts. Such words are referred as polysemous words i.e. words having a couple of experiences. A Knowledge based approach is proposed for disambiguating Telugu polysemous phrases using the computational linguistics tool, IndoWordNet. The task of WSD (Word sense disambiguation) requires finding out the similarity among the target phrase and the nearby phrase. In this approach, the similarity is calculated either by means of locating out the range of similar phrases (intersection) between the glosses (definition) of the target and nearby words or by way of finding out the exact occurrence of the nearby phrase's sense in the hierarchy (hypernyms/hyponyms) of the target phrase's senses. The above parameters are changed by using the intersection use of not simplest the glosses but also by using which include the related words. Additionally, it is a third parameter 'distance' which measures the distance among the target and nearby phrases. The proposed method makes use of greater parameters for calculating similarity. It scores the senses based on the general impact of parameters i.e. intersection, hierarchy and distance, after which chooses the sense with the best score. The correct meaning of Telugu polysemous phrase could be identified with this technique
The Trade-offs of Domain Adaptation for Neural Language Models

This work connects language model adaptation with concepts of machine learning theory.We consider a training setup with a large outof-domain set and a small in-domain set.We derive how the benefit of training a model on either set depends on the size of the sets and the distance between their underlying distributions.We analyze how out-of-domain pretraining before in-domain fine-tuning achieves better generalization than either solution independently.Finally, we present how adaptation techniques based on data selection, such as importance sampling, intelligent data selection and influence functions, can be presented in a common framework which highlights their similarity and also their subtle differences.
Budaya Berhibur Menerusi Aplikasi Smule Dalam Karya Arca Instalasi

This research project is an interpretation of a societal phenomenon in terms of the culture of using digital application for leisure and entertainment especially regarding the human behaviour and its obsession of using these applications in the social media platforms. This idea was translated by using the idea of an installation of a fabricated sculpture. The idea of how the digital media plays a major role for leisure and its obsession was inspired by the artist Scott Snibbe. This reference includes on how netizens utilize and share their interests and interactions with these digital media, games and other kinds of digital media entertainments. The method used for this practical studio research are through self critical evaluation, studio experimentation and contextual reviews. This research project was intended to contribute to the field of fine arts in terms of collecting symbolic visual narratives and its issues of the collective culture in regarding of leisure and entertainment and its popularity as a life style today. With hope this research project will give a major impact in terms of understanding towards its trend and the digital entertainment itself. The variation, the ever changing content of its application has impacted the popular culture itself through its spirit and behaviour, the wants and needs projected by the new expression of consumerism.
Wordwall Application as a Media to Improve Arabic Vocabulary Mastery of Junior High School Students

This study used wordwall application as a learning medium based on educational games. This study aims to determine the effectiveness of the wordwall application in increasing the mastery of Arabic vocabulary. This research used a quantitative approach with the research subjects of class VIII. The type of research is quantitative associative which aims to determine the effect or relationship between two or more variables. The data collection methods were interviews, questionnaires, tests, and documentation. The data analysis used a comparative analysis by comparing the pretest and posttest values (related sample t-test). This study revealed the following: (1) Media creation was done by logging into wordwall.net in order to be able to choose the desired shape according to certain needs. (2) There was a significant difference in terms of the pretest score which is smaller than the posttest score (45.63 &lt; 77.50), (3) there was a difference in the average pretest and posttest outcomes with sig value of 0.000 (&lt;0.05). (4) The percentage of N-Gain was 56.6%, which was categorized as quite effective. Based on the data analysis, it was concluded that the wordwall application was quite effective in increasing the mastery of Arabic vocabulary (Students mastered 25 vocabularies for each theme and according to government standards). Furthermore, the wordwall application could increase the fun, interest, enthusiasm and motivation of students in learning Arabic vocabulary.
Introduction to Blockchain

The current monetary system has many issues associated with it like double spending, standard transaction fees, financial crisis, centralized power and private ledgers. Blockchain provides a remedy to all these ills by its basic structure, zero or minimal transaction fees and by providing a public ledger system which is visible to everyone who is the part of blockchain which makes it free from complications like double spending and financial crisis. Blockchain is basically a continuously growing list of records or public distributed ledger system called blocks linked and secured suing cryptography. Each block has multiple transaction details associated with it. It was introduced in the year 2009 by Satoshi Nakamoto, who is believed to be a Japanese man, born in 1974. Given the features and universal nature of the Blockchain, which include decentralized ledger system, proof of work and cryptography, one can appreciate that its implementation could result in far reaching changes in all domains.