Reviewerly/exHarmony huggingface dataset:
Data productive collaborative filtering using deep learning based recommender model

Abstract The term Synergistic Filtering is utilized as a spine in all Commercial Recommendation Systems today. Conventional synergistic separating (CF) strategy does not take in thought successions of client’s appraising, which reflects changes of client’s inclination over some stretch of time. The suggestion undertaking is affected by the profound learning pattern which demonstrates its critical effectiveness. The profound learning based recommender models give a superior detainment of client inclinations, thing highlights and clients things connections history. The proposed structure incorporates three segments: a network factorization demonstrates for the watched rating remaking, a bi-grouping model for the client thing subgroup examination. We recognize uninteresting things that have not been assessed yet rather are presumably going to get low evaluations from customers, and particularly attribute them as low regards. One imperative undertaking in our rating induction structure is the assurance of nostalgic introductions (SO) and qualities of sentiment words. It is on the grounds that deducing a rating from a survey is fundamentally done by removing conclusion words in the audit, and afterward amassing the SO of such words to decide the predominant or normal assumption suggested by the client. The proposed structure and recommend that the system does not depend on a substantial preparing corpus to work. Advance improvement of our rating derivation structure is progressing. Trial results demonstrate that the proposed system indicate changes over the conventional community oriented sifting strategy.
PROSPECTS FOR RESEARCH IN IMPROVING THE EFFICIENCY OF PRODUCTION MEETINGS

Original approaches to enhancing the efficiency of production meetings are developed. Basic hypothesis and promising lines of research that can promote the efficiency of production meetings are reviewed. A number of Russian and foreign scientific journals mistakenly treat some types of operational meetings as brainstorming although some of the procedures contain no mechanisms inherent in brainstorming, which can thus lead to a confusion with their use. We propose to: 1) take into account the difficulties in identify ing the type of meeting procedure; 2) consider and use the existing procedures, techniques and methods for setting goals by the supervisor and their subsequent adjustment; 3) use the basic decision-making models for enterprises and organizations, i.e., select the most appropriate types of meetings proceeding from their advantages and shortcomings; 4) use the psychology of small groups and methods for stimulating small groups and teams. Avoid spontaneous selection of meeting and choose the best category of meeting proceeding from the advantages and disadvantages of this category of meeting among others. It is recommended to use three kinds of selection tasks in the context of group selection theory (selecting of the best or appropriate single object from the given set): selection of subsets in which all L selected best objects are supposed to be used without dropping out any of them, where L &gt; 1; simultaneous selection of the subsets consisting of a different number of elementary alternatives in which it is supposed to use all the selected best objects without dropping out any of them, including the case when one object is selected and compared (elementary motion); application of the results of interrogative logic. It is necessary to objectify the process of searching for compromises (agreement of opinions) of the participants of the meeting, expressed in various non-verbal types of assessments, i.e., to use a discrete or statistical approach to aligning expert rankings of the participants of the meeting. The novelty of the work is expressed by the fact that for the first time an emphasis has been placed on those areas that are usually not associated with an increase in the efficiency of production meetings. Moreover, the scope of the concept of "meeting" has been narrowed, and a special class of production meetings has been identified and described.
Barrier enabled QEMU

Virtual machines can be run inside one physical machine. This advantage enables cloud service providers and data centers to provide the identical and independent services to multiple users with fewer hardware. QEMU, a virtual machine that is used widely, has the two problems. One is performance degradation due to the amplification of the sync operation. The other is that QEMU not support the BarrierFS which uses the barrier enabled I/O stack that can guarantee the order of writes without transfer-and-flush mechanism. In this paper, we apply the fdatabarrier() system call, which is provided by BarrierFS, to address the I/O performance degradation problem due to the amplified sync operations. We also implement the barrier handler in QEMU so that the QEMU can execute the guest with BarrierFS to reduce the I/O latency caused by transfer-and-flush. The barrier handler recognizes the barrier flag in I/O command from guest and transmits the flag to host storage. We evaluate performance of the QEMU applied BarrierFS compared with the original QEMU. We observe I/O throughput using the varmail of filebench as macro benchmark and Mobibench and GNU dd command as micro benchmark. In result of evaluation, throughput of the QEMU applied BarrierFS is improved by maximum of 13x and minimum of 3.9x compared with the original QEMU. Thus, we verified that the barrier enabled QEMU has higher I/O performance than the original QEMU.
Quantum Error-Correcting Codes in the USC Regime

In this chapter, we propose to construct relatively large quantum error-correcting codes (QECCs) with the superconducting circuits architecture at the ultrastrong coupling regime. We are able to create highly entangled quantum state commonly known as cluster state by generating entanglement between any pair of qubits within a fraction of a nanosecond. We coin this process “pairwise cluster state generation”.
Development of a Prototype of a Fast Proximity Authentication System for Electronic Medical Record Terminals Based Virtual Desktop Interface

Strict security measures against information leakage are required because the electronic medical record PC terminals store important health information data. Therefore, it is preferable to use a multi-factor authentication method in which users are granted access only after successfully presenting two or more factors to an authentication system: knowledge, possession, and inherence. The time required for these authentication processing is extremely stressful for medical ward staff who frequently log in/log off the electronic medical records. The aim of this study was to develop a proximity authentication system that enables quick two-factor authentication by combining a BLE device and vein authentication. To evaluate the effectiveness of proximity authentication system, the time required for authentication processing was compared between electronic medical record terminals with and without a prototype of a proximity authentication system at medical institutions. The results showed that the mean length of time before the screen startup for electronic medical record terminals with and without a proximity authentication system was 5.89 and 12.28 s, respectively (p < 0.01). The proximity authentication system reduces the time required for authentication for access to electronic medical records and improves medical service efficiency.
Basics of Superconducting Circuits Architecture

In analogy to the cavity QED in quantum optics, the field of circuit QED deals with the study of light and matter interaction on the superconducting chip. In the place of natural atoms and optical laser as in cavity QED, we have artificial atoms and microwave photons propagating on the two-dimensional chip. As this thesis focuses on quantum computation with superconducting qubits, we will briefly look into some basics of the superconducting circuits here.
Quadratic extension to retrace error calibration algorithm for non-null interferometric surface figure testing of nominally flat reflective surfaces

We present a slope dependent calibration algorithm for interferometric surface figure testing. RMS wavefront error is reduced 40.7% (10.8% for linear method) from the uncalibrated measurement for a R/22.7 mirror tested against a flat reference.
Blockchain: Riding the Roller Coaster Towards a Standard

Nakamoto proposed a new solution to transact value via the internet. The internet prior to the advent of bitcoin was primarily a communications environment for non-face-to-face interaction. The Internet developed into a global publishing environment. To carry out a commercial transaction it was necessary to involve some third party who would validate the financial aspects of the transaction. The heart of the bitcoin solution was the blockchain construct, which was designed to dis-intermediate the involvement of the third-party validator, and thus reduce a fiction costs associated with the transaction.The blockchain as originally proposed, with its proof of work consensus protocol, has been shown to have some uncommercial aspects to which researchers globally are attempting to solve. Further, since the blockchain is a distributed environment, commercial compliance requirements can impact the architecture of a blockchain. The architecture of a blockchain must meet the regulatory compliance which could be industry specific such as financial and health regulatory obligations or general such as privacy compliance as in General Data Protection Rules (GDPR). An important issue with the development of new technology that has international reach is that such technology should not become siloed; that is technically isolated. This is where standards especially international standards can assist. Of course, standards by themselves will not necessarily obviate the impediments to interoperability, but if standard interfaces, data structures and standard communication structures can be developed or adopted, then the uptake of blockchain environment will be more likely to be achieved, which could financially benefit the global economy.This paper will analyse some of the issues confronting the further development of blockchain technology and how standards development can assist.
A Survey Paper on Frequent Itemset Mining

Abstract High utility itemsets (HUIs) mining is A creation worry in records mining, that understands finding all itemsets having AN application total a customer demonstrated least programming viewpoint min_util. Visit sets see an imperative portion of in an extremely couple of measurements driving undertakings that decide to peer intriguing purposes of concentrate from databases, like connection guidelines. The mining of connection guidelines is one all educated the basic paying practically no personality to what you show up as though at it issues with those. Move out of mining from a static dealings dataset, the spilling case has liberally additional actualities to search for when and incomprehensibly reasonably essential diverse nature to facilitate. In-visit matters can convey to a close go to some time later thus can’t be overlooked. For the term of this paper we keep an eye on present day situation with obtaining for Frequent Itemset Mining estimations. The outline signally information the deficiencies of the open estimations for HUI and proposes specific picks to overcome the flaws.
Improving Wearable Activity Recognition via Fusion of Multiple Equally-Sized Data Subwindows

The automatic recognition of physical activities typically involves various signal processing and machine learning steps used to transform raw sensor data into activity labels. One crucial step has to do with the segmentation or windowing of the sensor data stream, as it has clear implications on the eventual accuracy level of the activity recogniser. While prior studies have proposed specific window sizes to generally achieve good recognition results, in this work we explore the potential of fusing multiple equally-sized subwindows to improve such recognition capabilities. We tested our approach for eight different subwindow sizes on a widely-used activity recognition dataset. The results show that the recognition performance can be increased up to 15% when using the fusion of equally-sized subwindows compared to using a classical single window.
Entanglement in a detuned double Jaynes-Cumming model

In this paper, we investigated the entanglement dynamics between two superconducting qubits in the framework of not-resonant double Jaynes-Cummings model taking into account the direct dipole-dipole interaction. We explored the dependence of the atom-atom entanglement on the strength of the dipole-dipole interaction and detuning. The results show these parameters affect the period of negativity oscillations but not the maximum value of entanglement in contrast to two-atom Jaynes-Cummings model with common cavity mode.
Quintic polynomials having Galois closure of genus zero with Galois group A5

Let f(x)=x5+ax3+bx2+cx, where a, b, and c are elements of the finite field k of size q=pt, where p>5 and q≡1 or 4 (mod 5). We determine those f(x)'s for which the Galois closure of k(x)/k(f(x)) is a rational function field with Galois group A5. We then determine the size of the value sets of these polynomials.
Determination of The Ship Motion Direction with Digital Image Processing on Sea Water Surface to Avoid Collisions

Abstract As the largest archipelagic country in the world, Indonesia has 17,499 islands from Sabang to Merauke. There is a country with an area of water greater than the land area. Data on shipping accident investigations from the National Transportation Safety Committee (NTSC) throughout 2010-2016 of fifty-four accident cases at sea, seventeen of which were accidents caused by collisions on ships in Indonesian waters. This is equivalent to twenty percent of accidents that have occurred, a human error causes as many as 80% of collision accidents from the crew or people in the sea transportation system, and natural factors or machinery cause only a few. The success of this research aims to avoid ship breaking, by giving directions on the direction of the ship obtained by the results of digital image processing. This study proposes a digital image processing model on sea surface using object recognition. It used the morphological operation in the preprocessing stage; this method can remove non-uniform illumination and reflection in sea surface. Then, noise in the image data will decrease. The result of this object recognition will be used to determine the direction of ship movement. Experimental results with our own dataset verify the high efficiency of our proposed method.
Facial expression classification using Cross Diagonal Neighborhood Pattern

Abstract Facial Expression Recognition has significant applications in the field of Affective Computing. FER has its significant contribution in the fields like human computer interaction, neurology, psychiatry, image processing, computer vision, affective computing, and information security. This work gives unique and robust FER System by extracting unique and robust face features. This work proposes Cross Diagonal Neighborhood Patterns (CDNP) for unique feature extraction. The CDNP features are further processed by Gray Level Co-occurrence Matrix (GLCM). The derived CDNP-GLCM features are sent to Convolutional Neural Network (CNN) to train various expressions.
Brian Cherney’s Illuminations

Brian Cherney’s Illuminations for string orchestra, composed in 1987, reflects ideas related to Jewish mysticism. Descriptions and accounts of meditation techniques that ultimately lead to visions of light, and even an encounter with the divine, so inspired the composer that he decided to write a piece that re-enacts a meditative cycle. Illuminations is thus a dramatic staging: the listener, as if granted special insight into the mind of someone who is meditating, witnesses how the mind is transformed as it approaches light (or the divine). The composition expresses light and the divine in multiple ways, from the layout of the instruments on stage, to the formal plan of the piece, to the variety of pitch collections heard throughout the work. This article unveils some of the subtle intricacies that make Illuminations so powerfully evocative, and why it remains one of Cherney’s signal achievements.
Acceptability analysis method for evaluate data on twitter using support vector machine

Abstract The first model centres around believability at the client level, tackling different elements of information stream into a registered validity rating. The next model specifies a methodology to find believability score for singular tweets. We built up the system for validity on Face book by evaluating the validity of: (i) the reliability of the web sources discussing a case, (ii) the dialect style of the articles revealing the case and, (iii) their position. We at that point gathered the preparation information for making a model utilizing Support Vector Machine (SVM). Furthermore the standardization technique is essential advance for purifying information before utilizing the machine learning strategy to order information. The outcome demonstrate that Naïve Bayes to identify the Fake news has precision 96.08%. We distinguish basic examples of transiently agent discussion subgraphs and speak to their subjects utilizing Latent Dirichlet Allocation (LDA) demonstrating. We break down how the information had proliferated, and the moves were made in light of the source. The component retweet was considered as a proportion of examination to upgrade the reliability of the spread information. The performance of our positioning calculation essentially upgraded when we connected re-positioning system.
On Girls Bra Design for the Demand of User

Good bra design has an important impact on the healthy development of women’s chest, especially on the breast health of adolescent girls. This paper selected Guangzhou, Guangdong Province, China for field interviews and questionnaires to collect girls’ needs and expectations for bra design. Principal Component Analysis (PCA) was used to select the demand factors that have a greater impact on bra design: chest protection, corrective posture, size standards and pain relief, and the weight ratio of different factors was defined. It is found that protecting the chest and correcting posture are the most important requirements of bra design for adolescent girls. Establishing the size standard of underwear for adolescent girls and alleviating the pain during development are important complements to the optimization strategy, which can provide basic data support for further optimization research of underwear design for adolescent girls.
Multi-core with ht technology to solve data lake complex problems

Abstract Technology is taking its lead towards growth and it should be timely used properly for complex problems. Everything is available with us and it should be planned properly for better technology and its usage. This paper deals with core technology that will save time and cost for high resolution images. Which are used for movies, virtual games and simulations? Multi-cores are not new to the society; they are taken their shape into different transitions. Now we are in dual core technology with more processors and speed. We can utilize the cores properly if we have software technology. Main objective of this paper is to utilize cores proper for specific work with interrelating them. Finally they have to be organized properly with governance of the software. For performance HT Technology is used to select core for specific job. By selecting different cores we can gain performance, same way increase the speed and high resolution of images.
Learning the Graph Edit Costs: What Do We Want to Optimise?

Graph edit distance has become an important tool in structural pattern recognition since it allows us to measure the dissimilarity of attributed graphs. One of its main constraints is that it requires an adequate definition of edit costs, which are application dependent. These costs eventually determine which graphs are considered similar or not in a concrete application. Several methods have been presented to learn these costs to avoid manually setting them. They are based on different techniques ranging from probabilistic methods to neural networks or known optimisation algorithms. The aim of this paper is twofold. On the one hand, we list them and summarize their features. On the other hand, we empirically analyse the behaviour of the proposed optimisation functions. We conclude that these functions return different edit costs and therefore, they have to be considered application dependent and not only a technicality of the method, as it has been considered so far.
Entanglement between two atoms taking into account a Stark shift

We considered a quantum model consisting of two effective two-level atoms interacting with a single-mode thermal cavity field through two-photon transitions. We explored the entanglement dynamics between two atoms, and studied the effect of the Stark shift on the entanglement. The results showed that for a separable initial atomic state the Stark shift enhances the amount of atom-atom entanglement induced by the thermal field. For entangled atomic state the Stark shift reduces the the atom-atom entanglement oscillations.
Systematic research on vocal art performance and human voice science based on wireless sensors

In the performance of vocal music, the human body noise science is a problem that cannot be ignored. The wrong pronunciation often causes noise diseases. It is necessary to analyze the localization of vocal noise. Based on this article, the research of vocal art performance and human noise science based on wireless sensor system is studied. At first, this article briefly describes the relationship between vocal art performance and human noise, and then puts forward the importance of noise localization. Aiming at the problem of noise localization, several target localization algorithms are proposed. At the same time, these algorithms are weighted to reduce the complexity and improve the calculation accuracy. The simulation results test confirmed the effectiveness of the target location weighting algorithm without increasing the computational complexity, and the calculation accuracy was significantly improved.
The application of the matrix decomposition recommendation algorithm based on attribute coupling is studied in the internet of things

Traditional information recommendation system using only the user’s score is calculated and recommended, although to a certain extent, can obtain the implied characteristics of users or resources, but the lack of enough semantic interpretation, affecting the effects of recommendation. This article studied and analyzed the recommendation based on attribute coupled matrix decomposition algorithm in the application of Internet of things, on the foundation of the matrix decomposition model successively introduced global offset and time offset, in order to improve the prediction accuracy and the quality is recommended. In this paper, the algorithm is proved by experiment and the prediction accuracy of the algorithm is improved.