Miracle-dz/UniFAR-FTUs huggingface dataset:
Gosig: a scalable and high-performance byzantine consensus for consortium blockchains

Existing Byzantine fault tolerance (BFT) protocols face significant challenges in safety, scalability, throughput, and latency. We present a new BFT protocol, Gosig, for the consortium blockchains. Gosig guarantees safety even in asynchronous networks fully controlled by adversaries, by combining secret leader selection with multi-round voting. We co-design both the consensus protocol and the underlying gossip network to optimize performance. In particular, we adopt transmission pipelining to fully utilize the network bandwidth while use aggregated signature gossip to reduce the number of messages. These optimizations help Gosig to achieve unprecedented single-chain performance. On a public cloud testbed spanning multiple data centers consisting of 280 nodes across 14 cities on five continents, Gosig achieves over 15,000 transactions per second with 15.8-second confirmation time. When the system scales to 5,000 nodes, Gosig can still achieve 3,000 transactions per second with about 23.9-second confirmation time.
“Living labs” for sustainability

Purpose – Universities can do more to deliver against the sustainable development goals (SDGs), working with faculty, staff and students, as well as their wider stakeholder community and alumni body. They play a critical role in helping shape new ways for the world, educating global citizens and delivering knowledge and innovation into society. Universities can be engines of societal transformation. Using a multiple case study approach, this study aims to explore different ways of strategizing sustainability toward delivering the SDGs are explored in a university setting with an example from the UK, Bulgaria (Europe) and USA. Design/methodology/approach – The first case is a public UK university that adopted enterprise and sustainability as its academic mission to secure differentiation in a disrupted and increasingly marketized global higher education sector; this became a source of inspiration for change in regional businesses and the local community. The second case is a business sector-led sustainability-driven transformation working with a private university in Bulgaria to catalyze economic regeneration and social innovation. Finally, a case from © Wendy Maria Purcell, Heather Henriksen and John D. Spengler. Published in International Journal of Sustainability in Higher Education. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and noncommercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode The authors are grateful to the students, alumni, staff and faculty of the universities involved and to their wider network of business and community stakeholders. Harvard University’s support of the ISCN is acknowledged, and the authors are thankful for the insights and experiences shared through the 2018 ISCN conference. Conflicts of interest: The authors declare no conflicts of interest. Author contributions: Conceptualization, W.P. and J.S. ; Methodology, W.P.; Investigation, W.P., J. S. , H.H. ; Resources, W.P., J.S. , H.H. ; Data Curation, W.P.; Writing-Original Draft Preparation, W.P.; Writing-Review and Editing, W.P., J.S. , H.H. ; Supervision, J.S. ; Project Administration, W.P. Funding: This research received no external funding. Sustainable development goals
A new method for obtaining the inconsistent elements in a decision table based on dominance principle

In this study, using only the dominance relation, we propose a set defining inconsistent elements in the decision table. Then, we show the accuracy of our proposition with an example. We also express the computational complexity comparisons of the proposed method with general method in terms of the number of set intersection operations and the real number comparison operations.
On the use of Kinetography Laban to notate robot action and motion

—Roboticists aim at segmenting robot actions into a sequence of motion primitives in order to simplify the robot programming phase. Choreographers aim at capturing the essence of human body movements within a sequence of symbols that can be understood by dancers. To that extent, roboticists and choregraphers pursue the same quest. This paper reports a pluridisciplinary approach combining a dance notation system (the Kinetography Laban) with a robot programming system (the Stack of Task). Motion scores are used instead of quantitative data to compare and enlighten differences in robot and human movements. We then discuss about plausible origins of these differences taking into account the implicit rules of the Kinetography Laban on how a movement is executed by humans. This comparison, in the light of the Kinetography Laban, opens some challenging questions related to motion segmentation and motion naturalness.
PERFORMANCE CHARACTERISTICS AND ENERGY ANALYSIS OF A 4-STROKE SINGLE CYLINDER DIESEL ENGINE USING DIESEL AND DIESEL-KEROSENE BLENDS

The energy has become the essential part of human life which leads to a global challenge for sustainable development. As the conventional fuels are depleting in a very fast manner and hence it becomes important to make some methods either by switching towards alternative fuels or using advanced technologies which will reduce the losses in the existing system. Though a lot of work has been done on the performance and emission analysis of compression ignition engine using diesel and diesel-kerosene blends, still there are some important issues which need to be resolved. In this article, energy analysis of a single cylinder 5 HP water cooled diesel engine has been performed. Based on the analysis, a comparison has been shown through the graphs for diesel and diesel-kerosene blends. At various load condition, the engine performance has been analysed. The percentage energy consumption in every part of the engine at different loads for each blend is shown. When pure diesel is used, the characteristic curve for each performance parameter is smooth. Whereas, energy loses in the case of diesel-kerosene blends through exhaust gases and as unaccounted losses maintain this smooth trend till 20% kerosene level. As the kerosene increases beyond 20%, the exhaust gases and unaccounted losses do not maintain this smooth trend. As engine load is increased, all the fuel blends show a lower value of brake specific fuel consumption (BSFC). At maximum brake power, the value of BSFC is highest for pure diesel and the graph is almost overlapping for the other blends. As the engine load is increased, the brake thermal efficiency (BTE) also increases. When the engine is at no load condition, the BTE shows the lowest value and the highest being at K40.Heat release rate (HRR) increases with higher engine load. Higher the engine load, lower the air-fuel ratio and more is the Heat Release Rate. It can be seen from the graph that at maximum load condition pure diesel has the highest HRR whereas K40 blend has the lowest value of HRR.
Prioritizing Impacts in Environmental and Social Impact Assessment: developing a semi- standardized and participatory approach applied to a golf-based tourism project

Environmental and Social Impact Assessment is an extremely useful tool for identifying and evaluating the social and environmental repercussions of a wide range of projects. Especially when the project and its impacts are very complex, an ESIA can result in the identification of a high number of impacts needing to be prioritized in order to be addressed effectively and efficiently. This paper presents a methodological proposal for the prioritization of impacts within an ESIA based on participatory and social justice criteria. This methodological approach is structured into four main phases: 1) Creating the stakeholders’ platform; 2) Preliminary identification and assessment of impacts; 3) Categorizing and reducing the selection of impacts; 4) Assessing and prioritizing impacts using MCDA. The process is illustrated by its application to an on-going ESIA on a golf-based tourism project in Huelva (Spain).
Conditionally Augmented Temporal Anomaly Reasoner And Convolutional Tracking System (CATARACTS)

Applications of artificial intelligence have been gaining extraordinary traction in recent years across innumerable domains. These novel approaches and technological leaps permit leveraging profound quantities of data in a manner from which to elucidate and ease the modeling of arduous physical phenomena. ExoAnalytic collects over 500,000 resident space object images nightly with an arsenal of over 300 autonomous sensors; extending the autonomy of collection to data curation, anomaly detection, and notification is of paramount importance if elusive events are desired to be captured and classified. Efforts begin with rigorous image annotation of observed glints, streaking stars, and resident space objects; synthetic plumes were generated from both Generative Adversarial Networks as well as manual image augmentation techniques. Preliminary results permitted the successful classification of observed debris generating events from AMC-9, Telkom-1, and Intelsat-29e. After initial proof-of-concept, these events are incorporated into the training pipeline in order to characterize potentially unknown debris generating or anomalous events in future observations. The inclusion of a visual tracking system aides in reducing false alarms by roughly 30%. Future efforts include applications on both historical datamining as well as real-time indications and warnings for satellite analysts in their daily operations while maintaining a low probability of false alarm through detection and tracking algorithm refinement.
ACCIDENT DETECTION AND MONITORING SYSTEM USING IOT

— Nowadays we faced the lot of accidents and also many people lose their life due to the accidents. So our project will provide an optimum solution to this drawback. According to this project when a vehicle meets with an accident immediately Vibration sensor and Micro electro mechanical system (MEMS) sensor is used to detects the accident and also send the information to the server. Arduino mega controller sends the alert message through the GSM and GPS. GPS MODEM is used to trace the immediate location of the victim by receiving the information. Then the necessary action can be taken after conforming the location . This paper is useful for detecting the gas inside the vehicle and also measure the heartbeat of the victim.
The Perspective of Tradesmen on Material Wastage in the Construction Industry

Construction material wastage has been identified as a major threat to the environment, cost of delivery, and project duration. This paper sought to identify the significant level of the major sources and factors influencing material wastage from the perspective of tradesmen and to assess the quantities of the various categories of waste on building construction sites in the Upper West Region of Ghana. The study was carried out employing both open and closed-ended questionnaire survey. A total of 150 respondents representing different trades were involved in the study. The findings revealed that frequent design changes and poor design, excessive quantities of materials than required, poor material handling and storage on-site, poor strategy for waste minimization, and poor site management and conditions were the highest-ranking factors that influence construction material waste generation. It was further revealed that wood, sandcrete block, concrete, and metal were the most wasteful construction materials. The study recommended the investment of considerable efforts to ensure due diligence to improve all contractual documents. Contractors should endeavour to employ qualified on-site technical supervising and administrative staff to implement and safeguard effective site management practices to ensure material waste
Cycle Slip Cancellation by Increasing the PFD Detection Range in PLL Circuits

The cycle slip problem in Phase-Locked-Loop circuits is discussed in this article and a solution is presented. This solution consists of a Lock-Detector based circuit, which increases the detection range of the PhaseFrequency Detector. In order to verify the proposed circuit, a PLL in 0. 35μm CMOS was designed and simulated. The PFD and charge pump have an area of 0.005mm and consumes 238μW. The proposed circuit decreases the lock time by almost half of what is required by a conventional PFD, without altering the stability of the loop.
EVALUATION OF THE DIURNAL CYCLE OF MODEL PREDICTED CLOUD LIQUID WATER PATH WITH MSG-SEVIRI OBSERVATIONS

The evaluation of diurnal cycles of cloud Liquid Water path (LWP) in climate models receives relatively little attention. This is partly due to the lack of reference data to evaluate these cycles. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard METEOSAT-8 is the first instrument with the potential to provide accurate information on diurnal cycles of LWP over land and ocean surfaces. This paper evaluates diurnal cycles of LWP in the Regional Atmospheric Climate Model (RACMO) over Europe, using corresponding SEVIRI retrievals. The results show that diurnal cycles of LWP from SEVIRI show large spatial variations in their mean values, time of daytime maximum and daytime normalized amplitude. Over Europe RACMO overestimates LWP by about 75% as compared to SEVIRI. In general, the SEVIRI observed spatial variations in normalized amplitude and daytime maximum of LWP are well captured by RACMO. The best agreement between SEVIRI and RACMO is found over Ocean. Most differences are found in Mediterranean and Continental climate regions, where RACMO tends to predict maximum convection about two hours earlier than SEVIRI. Moreover, RACMO predicts different diurnal cycles than SEVIRI in regions with frequent changes in surface type or weather conditions. In conclusion, the results of this study show that SEVIRI retrieved diurnal cycles of LWP provide a powerful tool for identifying climate model deficiencies.
3D Poses Recovery in Single-Particle Cryo-EM from Learned Pairwise Projection Distances

Single-particle cryo-electron microscopy (cryo-EM) is a technology that allows the observation and the high-resolution 3D structure determination of biomolecules. In this project, the goal is to estimate the angles at which we imaged the 2D projections from a given 3D protein. We developed deep learning models to estimate the angles from learned pairwise projection distances. We designed a two-step method: 1) distance estimation using a Siamese neural network to learn the distance between pairs of projections, and 2) angle recovery that includes a minimization scheme in order to estimate the angles at which each projection was taken. The current results obtained are discussed depending on diﬀerent combination of approaches used and experimental conditions.
Phylogeny of the Yeast Species Isolated from Wild Tiger Lily (Lilium lancifolium Thunb.)

Received: 10 January 2015 / Revised: 11 February 2015/ Accepted: 3 June 2015 Copyright c 2015 The Korean Society of Environmental Agriculture This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
The Role of Communication Mode in Auditor-Client Interactions: Insights from Staff Auditors

Research suggests that staff auditors are more comfortable interacting with client personnel through email than face-to-face and that this choice of communication mode has the potential to impact audit outcomes. However, very little is known about how staff auditors choose a communication mode and its effects on their client interactions. Therefore, we present survey-based evidence that the majority of staff auditors prefer to interact with the client face-to-face but use face-to-face and email relatively equally. Auditors who primarily email the client place less value on client connection, and those who prefer email report feeling more communication anxieties related to the client. Importantly, the use of face-to-face communication is associated with more positive and productive client interactions. Firms can use the results of our study to understand the factors influencing staff auditors' preference for and use of different communication modes and its effect on audit outcomes, particularly as remote work increases.
DESIGNING USABILITY EVALUATION METHODOLOGY IN THE CASE OF OPENSCOUT PORTAL

: Today we have a range of complex (web) applications, where user interface developers are insufficiently aware of the criteria of usability as a key qualitative factor of the system, which measures the consistency of the product with the needs, goals and requirements of end users. Therefore many users have difficulties when interacting with a system which adversely affects on their effectiveness, efficiency and satisfaction and have possible negative influence on decision to its future adoption (i.e., user acceptance). This paper introduces a methodology of usability evaluation of the OpenScout portal (http://learn.openscout.net) where a combination of usability evaluation methods (UEMs) (i.e. Heuristic Evaluation, Eye-tracking etc.) is deployed to address the particularities of the portal and specific research goals: identification of usability problems (UPs) as well as user experience (UX) profiles from which HCI experts can prepare redesign proposals for the prototype improvement.
Anomalous Parity-Time Symmetry Transition away from an Exceptional Point

Parity-time (PT ) symmetric systems have two distinguished phases, e.g., one with real energy eigenvalues and the other with complex conjugate eigenvalues. To enter one phase from the other, it is believed that the system must pass through an exceptional point, which is a non-Hermitian degenerate point with coalesced eigenvalues and eigenvectors. In this letter we reveal an anomalous PT transition that takes place away from an exceptional point in a nonlinear system: as the nonlinearity increases, the original linear system evolves along two distinct PT -symmetric trajectories, each of which can have an exceptional point. However, the two trajectories collide and vanish away from these exceptional points, after which the system is left with a PT -broken phase. We first illustrate this phenomenon using a coupled mode theory and then exemplify it using paraxial wave propagation in a transverse periodic potential.
Korean Dependency Parsing Model based on Transition System using Head Final Constraint

한국어 의존 파싱은 문장 내 단어의 지배소를 찾음으로써 문장의 구조적 중의성을 해소하는 작업이다. 지 배소 후위 원칙은 단어의 지배소는 자기 자신보다 뒤에 위치한다는 원리로, 한국어 구문분석을 위하여 널 리 사용되는 원리이다. 본 연구에서는 한국어 지배소 후위 원리를 의존 파싱을 위한 트랜지션 시스템의 제약 조건으로 적용하여 2가지 트랜지션 시스템을 제안한다. 제안 모델은 기존 트랜지션 시스템 중 널리 사용되는 arc-standard와 arc-eager 알고리즘에 지배소 후위 제약을 적용한 포워드(forward) 기반 트랜 지션 시스템과, 트랜지션 시스템의 단점인 에러 전파(error propagation)를 완화시키기 위하여 arc-eager 알고리즘의 lazy-reduce 방식을 적용한 백워드(backward) 기반 트랜지션 시스템이다. 실험은 세종 구구 조 말뭉치를 의존구조로 변환하여 실험하였고, 실험 결과 백워드 기반 트랜지션 시스템이 포워드 방식보 다 우수한 성능을 보였다. 기존 연구와의 비교를 위하여 기존 연구를 조사하였지만 세부 실험 환경이 서 로 달라서 직접적인 비교는 어려웠다. 제안하는 시스템의 최고 성능은 UAS 92.85%, LAS 90.82% 이다.
Learning Core Word Alignments for Statistical Machine Translation

2 Proposal 2.1 Background A statistical machine translation system basically consists of a language model and a translation model, where the former generates output text in the target language and the later deduces the translation from the source text to the target text. Typically, the translation model is trained on sentencealigned bilingual texts and the model outputs a series of translation rules coupled with probabilities. Different levels of linguistic knowledge can be extracted from the bilingual texts and incorporated in the translation rules, yet in all cases word-level correspondences in the source and target are critical. Word alignment is thus the basis of higher translation models. For almost 20 years, automatic word alignment has been dominantly performed by the IBM Models, which infer word-to-word correspondences by the EM algorithm. A ‘NULL’ word token is added to each source and target sentence such that unaligned words are represented by alignments with the ‘NULL‘ token. To capture many-to-one alignments, a fertility model is added since IBM Model 3 to explicitly model how many source words are to be aligned to each target word. The IBM Models are implemented by GIZA++[7] , a freely available SMT toolkit that further symmetrizes and grows the many-to-one alignments bi-directionally, yielding many-to-many word alignments. GIZA++ is widely used by many SMT systems at the earliest word alignment step. Unsupervised word alignment by the IBM Models practically has the shortcoming, among others, of biasing to function words in the alignments. Although function words usually do not have correspondence in the other language, they are often included in automatic many-to-many word alignments as a result of their high frequencies, and thus reducing the chance for correct content-to-content word alignments. According to this observation, the NULL alignments in the IBM Models may not be strong enough to capture word insertion and deletion in the translation process.
Optimization of on-State Viscostiy for MR Fluid Using Anova Approach

Magneto Rheological (MR) fluids are capable of altering their rheological characteristics like yield stress, viscosity etc. under the influence of applied magnetic field. In the “off” state condition, the MR fluids have the viscosity in the range of 0.1-1.0 Pa-s. Under the presence of magnetic field, their viscosity increases significantly within a few milliseconds resulting in the change of its microstructure from liquid to semi-solid phase. The objective of the present investigation is to develop an optimal combination of constituents of MR fluid which could give high on-state viscosity. For this, an experimental set-up has been developed and designed to magnetize the MR fluid and to determine its on-state viscosity. An L-18 orthogonal array with various input parameters (constituents) affecting the fluid characteristics is designed and used to optimize the on-state viscosity of the MR fluid. It is found that on-state viscosity of MR fluids mainly depends on the volume fraction of the iron particles and type of carrier fluid used in MR fluid formulation. The optimal combination of these input parameters for MR fluid are found to be as Mineral oil with a volume percentage of 67%, iron powder of 300 mesh size with a volume percentage of 32%, oleic acid with a volume percentage of 0.5% and tetra-methylammonium-hydroxide with a volume percentage of 0.7%. This optimal combination of input parameters has given on-state viscosity of 573.094 Pa-s. An experimental confirmation test on the optimized MR fluid sample has been then carried out and the response parameter thus obtained has found matching quite well (less than 1% error) with the numerically obtained values. This research will help the design engineers to fabricate an improved MR based devices mainly for automotive and other sectors.