Reviewerly/exHarmony huggingface dataset:
A Granular Conceptual Model to Define Requirements for Evaluating the Functional Completeness of a Pharmacy Information System

Due to the fact that the existing quality models fail to define the methodologies, tools and techniques used to meet the software product standards, a concern arises to provide and integrate empirically validated models in the software industry.
Study on the Development Process of Several Small Micro-software under the GJB5000A Three-level System

Abstract In order to standardize and normalize the development process of small micro-software, based on the requirements of GJB5000A three-level system, this study is based on the software engineering management technology of process improvement, so as to adapt to the actual management requirements of software.
Security of NewHope Under Partial Key Exposure

Recently, the work of Bolboceanu et al. (Asiacrypt ’19) and the work of Dachman Soled et al. (Mathcrypt ’19) have studied a leakage model that assumes leakage of some fraction of the NTT coordinates of the secret key in RLWE cryptosystems (or equivalently, intentionally sampling secrets with some fraction of NTT coordinates set to 0). This can be viewed as a partial key exposure problem, since for efficiency purposes, secret keys in RLWE cryptosystems are typically stored in their NTT representation. We extend this study by analyzing the security of the NewHope key exchange scheme under partial key exposure of 1∕8-fraction of the NTT coordinates of the parties’ secrets. We adopt the formalism of the decision Leaky-RLWE (Leaky-DRLWE) assumption introduced in the work of Dachman Soled et al. (Mathcrypt ’19), which posits that given leakage on a sufficiently small fraction of NTT coordinates of the secret, the remaining coordinates of the output remain indistinguishable from uniform. We note that the assumption in the work of Dachman Soled et al. (Mathcrypt ’19) is strictly weaker than the corresponding assumption in the work of Bolboceanu et al. (Asiacrypt ’19), which requires that the entire output remain indistinguishable from uniform. We show that, assuming that Leaky-DRLWE is hard for 1∕8-fraction of leakage, the shared key v (which is then hashed using a random oracle) is computationally indistinguishable from a random variable with average min-entropy 237, conditioned on the transcript and leakage, whereas without leakage the min-entropy is 256. Note that 2 ⋅ 1738 number of bits of information are leaked in this leakage model, and so the fact that any entropy remains in the shared 256-bit key is non-trivial.
Classifying Web page features to detect DaaS

A SaaS (Software as a Service) can transparently consume a DaaS (Data as a Service). However, heterogeneous DaaS and its evolution can disrupt the SaaS execution. In such cases, a middleware can provide such interoperability and monitor the DaaS trackback and its evolution by retrieving its metadata. For instance, the middleware MIDAS manually provides such interoperability. Considering the Web and the number of web pages and DaaS available, this task may be time-consuming and unfeasible. To automate this task, it is firstly important to distinguish a DaaS from a typical web page. Thus, this work aims to develop a model to identify DaaS from the Web. We collected a set of features from DaaS and non-DaaS pages to train our model, and we discuss some issues and strengths of our approach. We evaluate precision and recall, but we also measure the performance because this model will be embedded into a crawler in future versions of MIDAS. Our findings achieve high precision and low execution time, which can position our work in a proper direction to MIDAS evolution.
Slave Coordinated Speed Analysis and Coordinated Control Method

Abstract When the container is being repaired, it is necessary to transfer the container to be repaired between the temporary storage area and the repair area. Due to the large size, when manually transported by forklift, the line of sight is blocked, there is a great safety hazard and efficiency. It is relatively low, and it is inconvenient to use a single mobile robot to carry it. Therefore, to solve this problem, a dual-mobile robot collaborative operation system is developed, and two mobile robots are used to move containers together to complete container maintenance and handling. Through the analysis of the cooperative handling of the dual mobile robots, a mathematical model of the cooperative movement of the dual mobile robots is established, and kinematics analysis is carried out to provide a theoretical basis for controlling the cooperative operation of the dual mobile robots.
Problems Arising in the Design of Workstations Based on Augmented Reality

Recently, workstations have been designed and developed based on augmented reality, for assembly/disassembly of complex devices and mechanisms. Augmented reality should help operators by outputting visual information regarding the device structure, action and operation tips. Augmented reality can also be used to inform vehicle drivers and aviation pilots. For example, a pilot will see itinerary and airspeed data on an augmented reality headset, without looking at displays and indicators in the cockpit. These developments are relevant, but for them to be efficient, rigorous research is needed. First, a full-scale description of an operator's (worker's, driver's or pilot's) activity is necessary. This description includes defining goals, setting tasks, describing conditions, actions and operations. Further, augmented reality devices, suitable for the specific operator, should be chosen. Necessary types of visual information display should be described: for example, displaying the inner structure of mechanisms or their images from different angles. An important aspect of design is the choice of methods for system interactions. One should remember that, at work, an operator's hands are busy. That is why the interfaces should not interfere with their main activity. Thus, design and development of workstations based on augmented reality should be conducted together with experts in specific fields, including the operators themselves. One should note the insufficiency of knowledge regarding an augmented reality user's state when he or she is carrying out serious activities. Theoretical and experimental research is required. All this is necessary for the developed systems to be efficient, comfortable and safe.
Region Growing-Based Scheme for Extraction of Text from Scene Images

Extraction of text from images is a vital work for every OCR system. Binarization plays a key task for any text segmentation scheme form scene images. Therefore, an effective scheme for binarizatin as well as text extraction from digital images is required. This work presents two effective schemes. First one is binarization and second one is text separation from images. In binarization scheme, Canny’s edge information is added in Savola’s binarization scheme. This binarization scheme provides a number of connected components. Further, we proposed an effective region growing scheme for extraction of text components from the binary image. A number of text specific criteria are defined. Based on these criteria two seed points for non-text and text are generated. Connected component-based region growing scheme is applied based on these seed points. For selection of seed points, information from ground-truth (GT) images of text information and our hand made non-text components information are used. Our schemes are tested on the freely accessible Icdar 2011 Born Digital data set. The performances are quite satisfactory.
Cooperative Analysis on Artificial Neural Network with Optimization Algorithm Based on Social Network

In this paper, we analyze the author cooperation in the artificial neural network combined with optimization algorithm during the past five years based on social network analysis. Over the past decades, with the advent of artificial intelligence (AI), the artificial neural network (ANN) has been a widely used computing model, whereas there are also some drawbacks in the network size, associated storage requirements, and complexity. To address this problem, enhancing ANN with optimization algorithm can further improve the performance, while there is little research focusing on the author cooperation in this crossing field. As a result, we use Bibexcel and Ucinet to analyze the co-occurrence social network of authors in artificial neural network combined with optimization algorithm in this study, in order to explore the current status of author cooperation and further prediction in this field.
Conflict vs causality in event structures

Event structures are one of the best known models for concurrency. Many variants of the basic model and many possible notions of equivalence for them have been devised in the literature. In this paper, we study how the spectrum of equivalences for Labeled Prime Event Structures built by Van Glabbeek and Goltz changes if we consider two simplified notions of event structures: the first one is obtained by removing the causality relation (Coherence Spaces) and the second one by removing the conflict relation (Elementary Event Structures). As expected, in both cases the spectrum turns out to be simplified, since some notions of equivalence coincide in the simplified settings; actually, we prove that removing causality simplifies the spectrum considerably more than removing conflict. Furthermore, we also prove that the labeling of events and a property that we call finitariness strongly influence the spectrum of equivalences in the conflict-free setting, whereas they have no impact on the causality-free spectrum.
Trapping Runtime Faults from Web Service Fault Ontology

The ontology offers a clear considerate of the runtime faults in web services and helps to share this common understanding with users and applications. This paper presents Web Service Fault Ontology and to trap the runtime faults from the Web Services Fault Ontology. Web Service Fault Ontology has been developed to represent the different types of faults that can occur during the interactions between service users, service publishers and service registries: publishing, discovery, binding and execution of web services. Ontology has been proposed to define the intended behavior of web services from the service provider. A sample web service application was developed for testing the proposed model.
Few-Shot Zero-Shot Learning: Knowledge Transfer with Less Supervision

Existing zero-shot learning (ZSL) methods assume that there exist sufficient training samples from seen classes, each annotated with semantic descriptors such as attributes, for knowledge transfer to unseen classes without any training samples. However, this assumption is often invalid because collecting sufficient seen class samples can be difficult and attribute annotation is expensive; it thus severely limits the scalability of ZSL. In this paper, we define a new setting termed Few-Shot Zero-Shot Learning (FSZSL), where only a few annotated images are collected from each seen class (i.e., few-shot). This is clearly more challenging yet more realistic than the conventional ZSL setting. To overcome the resultant image-level attribute sparsity, we propose a novel inductive ZSL model termed sparse attribute propagation (SAP) by propagating attribute annotations to more unannotated images using sparse coding. This is followed by learning bidirectional projections between features and attributes for ZSL. An efficient solver is provided for such knowledge transfer with less supervision, together with rigorous theoretic analysis. With our SAP, we show that a ZSL training dataset can also be augmented by the abundant web images returned by image search engine, to further improve the model performance. Extensive experiments show that the proposed model achieves state-of-the-art results.
A Collaborative Filtering Model based on Matrix Factorization and Trust Information

Collaborative filtering (CF) approach is the most efficiency technique for employing as the recommendation system engine. One of the notable types of CF techniques are Singular Value Decomposition (SVD) based techniques. Off-line learning recommendation models use the historical user rating to extract the knowledge. Nevertheless, the difficulties of CF approach are caused from the data sparsity and cold start problems. Aiming to deal with these problems, this research proposed a novel collaborative filtering model relied on matrix factorization technique by incorporate user's trust information into the explicit historical rating scores of users on the items for generating the rating scores prediction model, called Trust-rRSVD. The empirical experiment was established. The accuracy results shown that Trust-rRVSD performed better than the other techniques along with better mitigating the above problems.
Automatic Attendance System Based on Face Recognition Using HOG Features and Cosine Distance

Advancements in machine learning have been applying deeply and widely in numerous fields. Especially, computer vision tasks for object detection in recent years have achieved great performances which are even better than human recognition ability. This work leverages machine learning methods and information systems to present a framework for student attendance combining machine learning-based face recognition algorithm and relational databases to store, recognize, and record student attendance. The proposed method is tested on various scenarios and is expected to apply in practical cases. We investigate the Histogram of Oriented Gradients (HOG) for face detection and to use cosine distance to recognize faces. The purpose of this study is face recognition in real-time i.e. using a webcam, camera of the mobile device, and from a photograph or from a set of faces tracked in a video. We measured the distance between the landmarks and compared the test image with different known encoded image landmarks in the recognition stage. Face Recognition includes extracting features and then recognizing it, in any case, such as brightness, transformations as translation, rotation, and scale image. We recognized that using the HOG algorithm to detect faces improves more and more efficient model and avoids time-consuming.
Enhancing quantum entanglement of the two-mode squeezed vacuum state via multiphoton catalysis

Abstract Multiphoton catalysis is a non-Gaussian operation which has aroused interest recently in quantum information processing. There are two schemes of multiphoton catalysis in the current literature: one uses a beam splitter, while the other uses an optical parametric amplifier. We derive the catalysis operator in the Fock basis for each scheme and find a close relationship between them. We propose to enhance quantum entanglement of the two-mode squeezed vacuum state by performing two-mode multiphoton catalysis independently using two beam splitters. We calculate the optimal entanglement, which is maximized over two independent transmissivities, for the catalyzed states with various pairs of catalysis photon numbers, and find that in each case entanglement is enhanced only when the squeezing parameter is below a certain threshold. We also find that the optimal entanglement is nonzero in the limit of low squeezing, and deduce the analytical forms of the limiting catalyzed state and its entanglement in each case from numerical coefficients.
Reflections and Countermeasures on the Development of Secondary Vocational Teachers’ Teaching Ability Based on AI and Students’ Characteristics

The arrival of the era of artificial intelligence has a great impact on the produce of relationship and mode, resulting in changes in the demand for talents. As an important place to train professional and technical talents, secondary vocational schools need teachers to make changes. Teachers should improve their own educational and teaching ability, and cultivate talents of high-quality, innovative and in line with the needs of social development. By analyzing the development status of artificial intelligence in the field of education and the current students' problems facing teachers (students' characteristics), this paper gives some ideals and suggestions on the development of professional ability of secondary vocational teachers in the era of artificial intelligence.
Fall Detection and Daily Living Activity Recognition Logic Regression

It is a must to bring the fall detection system in to use with the increasing number of elder people in the world, because the most of them tend live voluntarily and at risk of injuries. Falls are dangerous in a few cases and could even lead to deadly injuries. A very robust fall detection system must be built in order to counter this problem. Here, we establish fall detection and recognition of daily live behavior through machine learning system. In order to detect different types of activities, including the detection of falls and day to-day activities, We use 2 shared archives for the accelerating and lateral speed data during this development. Logistic regression is used to determine motions such as drop, walk, climb, sit, stand and lie bases on the accelerating data and data on angular velocities. More specifically, the triaxial acceleration average value is used to achieve fall detection accuracy.
Developing Interpersonal Communication Skills

The paper supports the objective of improved communication with others. The interpersonal communication is one of the most important and fulfilling activities humans can accomplish  but like any activity, it needs to acquire some qualities in individuals, well highlighted in the paper, to proceed with success. The first action in any communication is to clearly outline one‟s communication objective. In the job of communication, we have to deliver our knowledge to the full understanding of our listeners. Each group of listeners will be of a different type, with varying degrees in the power of their understanding. The successful communicator will be he who can judge the person or the crowd of listeners around him and intelligently modulate his speech to the ability, mood and interest of the crowd. Let us learn to love our listeners, and feel a sincere concern for their welfare. We have to thus change our Raaga & Taal according to the quality of our listeners; we must plan how to explain to people of different standards of grasping power. We should keep smiling and have faith in ourselves. We must be flexible and adapt to our partner‟s style and the situation. We should remember that if we aren‟t getting the results we want, we need to change our approach.
Nash embedding: a road map to realizing quantum hardware

The non-Euclidean nature of the mathematical model of quantum circuits leaves open the question of their practical implementation in hardware platforms which necessarily reside in the Euclidean space $\mathbb{R}^3$. On the other hand, reversible circuits are elements of Euclidean spaces, making their physical realization in hardware platforms possible and practical. Here, the quantum circuit model for quantum computing is mapped into that of reversible computing in a mathematically robust fashion using Nash embedding so that every quantum computation can be realized as an equivalent reversible one.
Improved Odometry Motion Models for Differential-like Mobile Robots

To describe the motion of mobile robots we use probabilistic models that take into account the uncertainty inherent in the motion. This work presents an improved odometry model to describe the motion of mobile robots with differential-like drives. The approach presents an improved algorithm to compute the odometry controls which can handle better the case of in-place rotation and backwards motion. It also presents a new odometry model in which the covariance matrix is only dependent of the amount of motion performed by the robot, and the case of in-place rotation is described by a Gaussian approximation. The main advantages of this model are its invariance to the threshold values used to update it in the prediction step of filter algorithms, a better description of the case of in-place motion, and its capability to handle backwards motion.
Authoring and Visualization Tool for Augmented Scenic Performances Prototyping and Experience

There is a growing interest in the use of Augmented Reality technologies in artistic practices for performance execution and its use in the production process. The ability to overlay visual media onto the real world or, more specific onto the performer body in real-time has also captured the imagination of performance artists. Also, directors and choreographers glimpse the uses and applications of augmented reality in their production workflow. These applications provide specific challenges that require adaptations to standard content creation workflows. The present work describes the design and implementation of an authoring application for AR-based performance art, initially developed to support augmented performances but also extended to the prototyping of choreographies and costumes uses. The application enables several virtual augmented effects like images, videos, and 3D models to be attached simultaneously to the performer's body. This paper is presented as an application presentation providing a general view of the proposed solution and describing its development. We may see the effectiveness of the authoring application and establishes concrete requirements for a more generic tool to support the development of Artistic Performances with Augmented Reality.
Bill Cavanaugh: Contributions to the understanding of room acoustics in performance venues through the Concert Hall Research Group

A remarkable role model for acoustics consultants at any point in their career, Bill Cavanaugh was kind, humble, and always willing to share his successes and failures in hopes that we would all be better acousticians. In 1991, several acoustic consulting firms, including Cavanaugh Tocci Associates, came together to form the Concert Hall Research Group. They pooled experience and funds to support research and measurements in the interest of advancing the understanding of acoustics in concert halls. When the original work of collecting measurements from several halls was completed, Bill championed the idea of creating a Summer Institute to continue the advancement of knowledge. The Institute brought together acoustic consultants in performing arts, faculty and researchers in architectural acoustics, and college students studying or interested in architectural acoustic to foster conversations and honest sharing of knowledge in an informal and intimate setting.
The Use of Hypnoteaching Techniques in Improving the Skills of Writing Scientific Articles of the Third Grade Office Administration Students at Giri Taruna Vocational High School Bogor

The purpose of the study is to see an improvement in the skills of the third-grade office administration students at Giri Taruna Vocational High School Bogor in writing scientific articles by using hypnoteaching techniques. The method used in the research is quantitative and qualitative methods. Quantitative analysis is used for data obtained from written test results of scientific articles, both before and after hypnoteaching techniques applied to students. Meanwhile, quantitative data analysis is used for data from field observations, field notes, questionnaires, and interviews. The results show that there is a positive impact on learning by using Hypnoteaching techniques, especially to improve scientific article writing skills. The learning process is more active, innovative, energetic, meaningful, and fun. Before the Hypnoteaching method was carried out, the average grade in writing scientific articles was 56.66. In cycle 1, the average score of the students was 62.70, which did not meet the Minimum Mastery Criteria (MMC) of 75.00. In cycle 2, the students had reached an average score of 76.26, which indicated that they had reached MMC. The study concludes that learning using Hypnoteaching techniques can improve students' scientific article writing skills. Hypnoteaching technique is a useful innovation for teachers in learning Indonesian, especially in writing scientific articles.