Reviewerly/exHarmony huggingface dataset:
Randomseed19 at SemEval-2020 Task 10: Emphasis Selection for Written Text in Visual Media

This paper describes our approach to emphasis selection for written text in visual media as a solution for SemEval 2020 Task 10.We used an ensemble of several different Transformer-based models and cast the task as a sequence labeling problem with two tags: 'I' as 'emphasized' and 'O' as 'non-emphasized' for each token in the text.Our approach ranked fourth in this competition.
RETRACTED: Target recognition of basketball sports image based on embedded system and internet of things

Current game conflicts and live footage and video recordings in general, and innovations carry the game's financial cycle image recognition with the help of competitors to find data. In any case, the current situation shows that are still young with innovations recognizing the game image. That's why the uses of this study are to disassemble sports images and identify discoveries as an object for application game images. Cameras, video cameras, sensors Advances Infrared is different, For example, using an innovative visual data capture gadget, it has become the basic query for retrieving visual data, but now, in the age of data explosion, how much display it bears is a slightly larger study to capture the benefits. This is one of the most important issues with computer graphics. The basics and the most important task in film production and assignment is that the survey of images can be done as a result of large screen cracks. This article proposes a ball pollution technology computer game that depends on the screen split calculation coordinates.
Seeking the Source: Criminal Defendants’ Constitutional Right to Source Code

The right to a fair trial is fundamental to American jurisprudence. The Fifth Amendment of the Bill of Rights guarantees “due process,” while the Sixth provides the accused with the right to be “confronted with the witnesses against him.” But “time works changes, brings into existence new conditions and purposes.” So it is with software. From the smartphones we access multiple times a day to more exotic tools—the software “genies” of Amazon Echo and Google Home—software is increasingly embedded in day-to-day life. It does glorious things, such as flying planes and creating CAT scans, but it also has problems: software errors. Software has also found its way into trials. Software’s errors have meant that defendants are often denied their fundamental rights. In this paper, we focus on “evidentiary software”—computer software used for producing evidence—that is routinely introduced in modern courtrooms. Whether from breathalyzers, computer forensic analysis, data taps, or even FitBits, computer code increasingly provides crucial trial evidence. Yet despite the central role software plays in convictions, computer code is often unavailable to examination by the defense. This may be for proprietary reasons—the vendor wishes to protect its confidential software—or it may result from a decision by the government to withhold the code for security reasons. Because computer software is far from infallible—software programs can create incorrect information, erase details, vary data depending on when and how they are accessed—or fail in a myriad of other ways—the only way that the accused can properly and fully defend himself is to have an ability to access the software that produced the evidence. Yet often the defendants are denied such critical access. In this paper, we do an in-depth examination of the problem. Then, providing a variety of examples of software failure and discussing the limitations of technologists’ ability to prove software programs correct, we suggest potential processes for disclosing software that enable fair trials while nonetheless prevent wide release of the code.
Digital Transformation of World Finance

The boundary between the physical and a virtual world is not clearly visible nowadays, the 4.0 industry utilizes artificial intelligence, distributed ledger technology, quantum computing, advanced visualization and other advanced technologies. The surge of capital flows in financial technology is visible wherever we look. Classical businesses face a challenge to connect and create partners with the companies that are technology savvy because this may impact their future success. The strategy for digital business must be thought over very thoroughly since it represents the success threshold in contemporary digital environment. The classic banking system faces the threat or opportunity of an open banking system and banks are forced to be prepared to offer next generation services benefiting from third party channels. The short history on the banking industry including digital banking along, with fintech as a financial institution showing its power to compete sophistically, will shift the studied digital transformation phenomenon into a dilemma whether we indeed face a cashless society challenge, whether the governments should start to accelerate their decisions on Central Bank Digitalized Currency – CBDC or how far several countries already are to become a cashless society. At last, potential security, trust and fraud issues will close this chapter.
Quantitative Evaluation of Software Component Behavior Discovery Approach

During the execution of software systems, their execution data can be recorded. By fully exploiting these data, software practitioners can discover behavioral models describing the actual execution of the underlying software system. The recorded unstructured software execution data may be too complex, spanning over several days, etc. Applying existing discovery techniques results in spaghetti-like models with no clear structure and no valuable information for comprehension. Starting from the observation that a software system is composed of a set of logical components, Liu et al. propose to decompose the software behavior discovery problem into smaller independent ones by discovering a behavioral model per component in [1]. However, the effectiveness of the proposed approach is not fully evaluated and compared with existing approaches. In this paper, we evaluate the quality (in terms of understandability/complexity) of discovered component behavior models in a quantitative manner. Based on evaluation, we show that this approach can reduce the complexity of the discovered model and gives a better understanding.
Ramp rate analysis for forecasting operations in Singapore

The aggregate global horizontal irradiance (GHI) found as the carefully quality controlled mean of 25 radiometric ground stations belonging to the Solar Energy Research Institute of Singapore (SERIS) is assumed to represent the total solar power generation potential for Singapore. Analysing 1,323,459 quality controlled 1-min aggregate GHI measurements (between 2013-05-01 and 2019-12-09), the maximum absolute observed ramp down event from 1-min to the next was 197 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> representing a 26% reduction; the maximum absolute observed ramp up event was 219 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> , representing a 39% increase. The lag time period ( tL) was then extended from 1-min through to 300-min to find the maximum observed delta between any time t and the measurement taken at t+tL. The maximum ramping event increased with increasing tL. Ramp down events are more severe in Singapore, reaching nearly a 900 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> reduction with a lag time greater than an hour; this is due to regular convective cloud systems in the afternoon. For lag times of 5, 10, 15, 30 and 60-mins, the maximum observed ramp up events were 337 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (52%), 362 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (122%), 460 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (163%), 595 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (192%) and 707 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (325%), respectively. The maximum observed ramp down events were 356 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (40%), 439 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (62%), 560 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (67%), 711 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (81%) and 882 Wm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> (88%), respectively.
Representation of Movement-Based Integrated Learning in Different Physical Environments of an Early Education Institution

The aim of this paper is to determine the differences in the representation of children’s integrated learning in an institutional context between standard children’s integrated learning and movement–based integrated learning. The research encompasses two early-aged children’s groups attending city kindergartens. The content analysis method was used; activities were photographed and filmed with video cameras. Movement-based integrated learning has a significant influence on the quality of the educational process
SICKNL: A Dataset for Dutch Natural Language Inference

We present SICK-NL (read: signal), a dataset targeting Natural Language Inference in Dutch. SICK-NL is obtained by translating the SICK dataset of Marelli et al. (2014)from English into Dutch. Having a parallel inference dataset allows us to compare both monolingual and multilingual NLP models for English and Dutch on the two tasks. In the paper, we motivate and detail the translation process, perform a baseline evaluation on both the original SICK dataset and its Dutch incarnation SICK-NL, taking inspiration from Dutch skipgram embeddings and contextualised embedding models. In addition, we encapsulate two phenomena encountered in the translation to formulate stress tests and verify how well the Dutch models capture syntactic restructurings that do not affect semantics. Our main finding is all models perform worse on SICK-NL than on SICK, indicating that the Dutch dataset is more challenging than the English original. Results on the stress tests show that models don't fully capture word order freedom in Dutch, warranting future systematic studies.
Cooling Improvement of the IT Rack by Layout Rearrangement of the A2 Class Data Center Room: A Simulation Study

Information technology (IT) devices that are capable of transferring large data fast will generate more heat discharged into the data center room (DCR).As a result, energy consumption to cool DCR becomes higher.This research aims to study the simulation of airflow and temperature as an indicator of the quality of rack cooling performance in the A2 Class Data Center, and to obtain a new rack layout recommendation that can distribute heat from IT devices to DCR optimally.Simulation was conducted with the help of ANSYS 16.2 software.The meshing sizes used were 645 nodes, 29.304 lines, 10.81.976 hexahedral volumes, and 667.492 quadrilaterals.The solver used was pressure-based, while the sub-viscous setting used the k-ɛ standard turbulence model.The validation of the simulation model was done by comparing the RH values and the temperature of the measurement results from DCR.The study result shows the performance for cooling DCR increased when the rack rearrangement in DCR space was implemented according to the layout of the results of the simulation.The indicator of the cooling performance improvement was the value of the RCI (Rack Cooling Index) which increased by 4.92% while the amount of SHI (Supply Heating Index) decreased by 0.047
Unsupervised Neural Machine Translation for English and Manipuri

Availability of bitext dataset has been a key challenge in the conventional machine translation system which requires surplus amount of parallel data. In this work, we devise an unsupervised neural machine translation (UNMT) system consisting of a transformer based shared encoder and language specific decoders using denoising autoencoder and backtranslation with an additional Manipuri side multiple test reference. We report our work on low resource setting for English (en) - Manipuri (mni) language pair and attain a BLEU score of 3.1 for en-mni and 2.7 for mni-en respectively. Subjective evaluation on translated output gives encouraging findings.
Earth Sheltered Housing; Design Concepts for Urban Ground-scrapers

The history of human housing portrays Earth sheltered homes as dwellings originally developed for shelter, warmth and security for the earliest human dwellers.These buildings which originated as subterranean dugouts have evolved into modern housing options over the years.Physical attributes of earth sheltered houses signifies a retreat from surrounding elements into secluded spaces bordered by earth-mass as building covering.Further studies reveal its thermal efficiency between seasons and energy conservation properties due to its thermal mass application.A review of typologies identifies various techniques of its design and construction across the globe.This paper looks at the existing construction typologies of earth sheltered housing from the traditional to modern applications.Four unique subterranean applications were studied which represented the major construction typologies.It further investigates the uniqueness in the design concepts of earth sheltered housing as models for future earth-contact housing needs based on the energy conservation and thermal performance of this category of housing.Earth contact characteristics of these types of houses makes for potential energy conservation in single unit earth sheltered homes; however, large scale concepts consequently possess the potentials for optimization of thermal and energy performance.Hence communal type concepts are presented as ideas for urban scale application of Earth sheltered housing.
Remote Controlled Road Cleaning Vehicle

Abstract Cleaning the house on customary premise is a requesting and testing task particularly when there are kids in the house. In this, we may make a stride towards the arrangement of this issue. The progressions made in innovation of advanced mechanics have made existence of humankind especially simpler and agreeable. This paper depicts a keen street cleaning robot that permits cleaning the street by offering directions to the robot. This robot makes street cleaning measure simple and quick using a remote mechanical cleaning framework. Subject robot works in self-governing mode just as in manual mode alongside extra highlights like planning for explicit time and pack less earth compartment with auto-soil removal component. This work can be helpful in improving way of life of humanity.
Application of neuron networks of deep learning for exposures editing of digital phonograms

Possibility of creation of effective system, which is intended for exposure of tracks of editing in digital phonograms and is built on the basis of neuron networks of the deep learning, is experimentally proven. Sense of experiment consisted in research of ability of the systems on the basis of such networks to expose pauses with tracks of editing. The experimental array of data is created in a voice editor from phonograms written on the different apparatus of the digital audio recording (at frequency of discretisation 44,1 kHz). A preselection of pauses was produced from it, having duration from 100 мs to a few seconds. From 1000 selected pauses the array of fragments of pauses is formed in the automatic (computer) mode, from which the arrays of fragments of pauses of different duration are generated by a dimension about 100 000. For forming of array of fragments of pauses with editing, the chosen pauses were divided into casual character parts in arbitrary correlation. Afterwards, the new pauses were created from it with the fixed place of editing. The general array of all fragments of pauses was broken into training and test arrays. The maximum efficiency, achieved on a test array in the process of educating, was determined. In general case this efficiency is determined by the maximum size of probability of correct classification of fragments with editing and fragments without editing. Scientifically reasonable methodology of exposure of signs of editing in digital phonograms is offered on the basis of neuron networks of the deep learning. The conducted experiments showed that the construction of the effective system is possible for the exposure of such tracks. Further development of methodology must be directed to find the ways to increase the probability of correct binary classification of investigated pauses.
Multi-UAV Collaborative Online Obstacle Avoidance Track Planning

Aiming at the problem of online cooperative flight trajectory planning for multiple UAVs, a curvilinear trajectory planning method based on velocity obstacle method is proposed. The three-dimensional model of mission planning battlefield is established by using satellite elevation data. An improved Pythagorean Hodograph (PH) curve trajectory planning method is proposed for the problem of curvature constraint in UAV track planning. By introducing the adaptive chaos optimization strategy into the estimation distribution algorithm, an estimation distribution algorithm based on adaptive chaos optimization (AC-EDA) is presented to avoid blind trial and error of curve programming parameters. The improved particle sedimentation method is used to extend the two-dimensional trajectory to three-dimensional space, and the principle of the velocity obstacle method is combined with the PH curve planning method to find a suitable insertion point when facing the threat of a dynamic target, and realize the combination of curved trajectory planning and obstacle avoidance behavior.
Commonsense Knowledge Adversarial Dataset that Challenges ELECTRA

Commonsense knowledge is critical in human reading comprehension. While machine comprehension has made significant progress in recent years, the ability in handling commonsense knowledge remains limited. Synonyms are one of the most widely used commonsense knowledge. Constructing adversarial dataset is an important approach to find weak points of machine comprehension models and support the design of solutions. To investigate machine comprehension models' ability in handling the commonsense knowledge, we created a Question and Answer Dataset with common knowledge of Synonyms (QADS). QADS are questions generated based on SQuAD 2.0 by applying commonsense knowledge of synonyms. The synonyms are extracted from WordNet. Words often have multiple meanings and synonyms. We used an enhanced lesk algorithm to perform word sense disambiguation to identify synonyms for the context. ELECTRA achieves the state-of-art result on the SQuAD 2.0 dataset in 2019. With about 1/10 scale, ELECTRA can achieve similar performance as BERT does. However, QADS shows that ELECTRA has little ability to handle commonsense knowledge of synonyms. In our experiment, ELECTRA-small can achieve 70% accuracy on SQuAD 2.0, but only 20% on QADS. ELECTRA-large did not perform much better. Its accuracy on SQuAD 2.0 is 88% but dropped significantly to 26% on QADS. In our earlier experiments, BERT, although also failed badly on QADS, was not as bad as ELECTRA. The result shows that even top-performing NLP models have little ability to handle commonsense knowledge which is essential in reading comprehension.
Efficient single round attribute-based authenticated key exchange protocol

Attribute-Based Authenticated Key Exchange (ABAKE) protocols allow two or more users to establish a shared key and achieve mutual authentication over an insecure network, while providing fine-grained access control over transmitted data. The existing ABAKE protocols are very inefficient, requiring a large number (polynomial in the size of the access policies) of pairing and exponentiation operations. This presents a major hindrance in the real-world deployment of these protocols. In this work, we present a construction of ABAKE protocol where the number of pairing operations is constant (to be precise only 7) and the number of exponentiation operations is linear to the number of clauses in the disjunctive normal form representing the general access policies. To this end, we construct an Attribute-Based Signcryption (ABSC) scheme with constant number of pairings, and use it as the main building block in our ABAKE construction. This also gives the first construction of ABSC schemes with constant number of pairings for general purpose access policies in the standard model. Another important and desirable feature of our ABAKE construction is that it is round-optimal, i.e. it is a single round protocol. We analyse the security of our ABAKE construction in the Attribute-Based extended Canetti-Krawzyck (ABeCK) model, and prove its security assuming the hardness of a variant of the Bilinear Diffie-Hellman Exponent problem in the random oracle model.
Textural Analysis of Liver Tumor using Watershed Segmentation based on Statistical and Geometrical features

The liver diseases can define as the tumor or disorder that can affect the liver and causes deformation in its shape. The early detection and diagnose of the tumor using CT medical images, helps the detector to specify the tumor perfectly. This search aims to detect and classify the liver tumor depending on the use of a computer (image processing and textural analysis) helps in getting an accurate diagnosis. The methods which are used in this search depend on creating a binary mask used to separate the liver from the origins of the other in the CT images. The threshold has been used as an early segmentation. A Process, the watershed process is used as a classification technique to isolate the tumor which is cancer and cyst.&#x0D; The test images are taking five for cancer case and five for the cyst, the geometrical and statistical features are calculated for both cases to identify the identity for each case. The statistical features are obtained from the gray level co-occurrence matrix which is contrast, homogeneity, correlation and energy. The geometrical features are the area of the tumor, the circumference and irregularity. The irregularity tends to lose one of the cyst cases than for cancer because of its shape in more regular than cancer.