Reviewerly/exHarmony huggingface dataset:
The Business Transformation Framework for Managers in Transformation Projects

The success of a business transformation project (BTP) depends on how enterprise architecture, data architecture, and modelling activities are synchronized. These BTPs will not all be successful due to lack of talent and technical expertise of the traditional business transformation managers. The most important reason why business environments fail in business transformation projects is due to the lack of skills of BTMs. That is why the implementation of such BTPs requires a significant knowledge of data architecture and modelling techniques. The authors have based their research on many credible research sources of information like Gartner Inc. There is an essential need for more research on data architecture and modelling concept to support BTPs, where there is a necessity to propose a set of technical and managerial recommendations.
Research on an Improved Coordinating Method Based on Genetic Algorithms and Particle Swarm Optimization

In this article, a hierarchical cooperative algorithm based on the genetic algorithm and the particle swarm optimization is proposed that the paper should utilize the global searching ability of genetic algorithm and the fast convergence speed of particle swarm optimization. The proposed algorithm starts from Individual organizational structure of subgroups and takes full advantage of the merits of the particle swarm optimization algorithm and the genetic algorithm (HCGA-PSO). The algorithm uses a layered structure with two layers. The bottom layer is composed of a series of genetic algorithm by subgroup that contributes to the global searching ability of the algorithm. The upper layer is an elite group consisting of the best individuals of each subgroup and the particle swarm algorithm is used to perform precise local search. The experimental results demonstrate that the HCGA-PSO algorithm has better convergence and stronger continuous search capability, which makes it suitable for solving complex optimization problems.
Simulation of BRKSS Architecture for Data Warehouse Employing Shared Nothing Clustering

The BRKSS Architecture is based upon shared nothing clustering that can scale-up to a large number of computers, increase their speed and maintain the work load. The architecture comprises of a console along with a CPU that also acts as a buffer and stores information based on the processing of transactions, when a batch enters into the system. This console is connected to a switch (p-ports) which is again connected to the c-number of clusters through their respective hubs. The architecture can be used for personal databases and for online databases like cloud through router. This architecture uses the concept of load balancing by moving the transaction among various nodes within the clusters so that the overhead of a particular node can be minimised. In this paper we have simulated the working of BRKSS architecture using JDK 1.7 with Net beans 8.0.2. We compared the result of performance parameters sch as turnaround time, throughput and waiting time with existing hierarchical clustering model.
Formation of Functional Literacy of Primary School Children in the Field of Healthy and Safe Lifestyle

The article discusses the basic principles and specifics of the organization of activities of primary school teachers in the formation of students’&#x0D; knowledge in the field of safe behavior and healthy lifestyle, as well as their development of practical skills in relevant situations. Questions of&#x0D; didactic support are highlighted, target methodological modules are marked. As an example of their use, the development of classes on the topic “My safety when riding a scooter and crossing the roadway” is presented.
Research and implementation of an analytical database testing platform in telecommunication industry

In industry, analytic database is known to be difficult in testing and product selection. The traditional TPC-DS (transaction processing performance council-decisioin support) benchmark [1], which only has one retail scene, is not sufficient enough for database product selection of other business type. To deal with this drawback, an analytical database testing platform which can plug-in a variety of business scenes was developed. The telecommunication scene was also provided to explain the design concept, system architecture and scene development of this testing platform. The platform provides scene plug-in function which is easy to use without any programming background. Users can select and edit scenes according to their own business type to meet the requirements of analytical database testing and selection in different industries.
Research on University Network Security Management Assistant Decision System Based on Semantic Ontology

The research on university network security management assistant decision-making system for massive heterogeneous and multi-source is an important and difficult topic in the construction of university network security system. Firstly, this paper proposes a multi-source heterogeneous university network security knowledge integration strategy based on semantic ontology technology, constructs a network security management auxiliary decision-making knowledge base based on computable and reasoning resources, and designs and develops a university network security management auxiliary decision-making system platform. The system can better realize the support services such as association query, knowledge reasoning and auxiliary decision-making of university network security events, and provides an effective solution for multi-source heterogeneous data integration, knowledge modeling and intelligent management in the field of university network security.
The problem of students’ self-organization and self-development readiness and its possible solutions

The article offers contemporary students the way to form the ability of self-organization and self-development. An example of its implementation in modern universities is given. The priority areas for further improvement of the method are highlighted. The key feature of the proposed approach is that students learn to develop self-organization and self-development skills insitu; within the process of work on their real issues. The educational module«Life Navigation» contains the following educational units: developing students’ skills in formulating vital goals that meet the criteria and indicators of the SMART test, building a personal program of self-development, identification and prevention of potential obstacles, creating a plan to achieve vital goals, coordinate actions with other people, who may influence their plans, to adjust their daily routine according to their goals and plans. The teacher’s aim in this case should familiarize students with algorithms for solving such problems and help to apply them effectively. High results in this work are achieved by means of coaching and tutoring techniques used by teachers. An important feature of the educational module «Life navigation», developed by the authors, is the process of regular setting of specific goals by students for the period between classroom sessions. As part of a study group work this should include subsequent analysis of what has been successfully implemented, why they may not have succeeded with their plans, and what should be done in order to improve their efficiency. An important part of the described approach is the students’ intensive group work. These training groups are a strong resource for students’ motivation for implementing their ideas and for constant practical application of the acquired ability to self-organization and self-development.
On Securing Cloud Storage Using a Homomorphic Framework

In this chapter, a cloud security mechanism is described in which the computation (addition) of messages securely stored on the cloud is possible. Any user encrypts the secret message using the receiver's public key and stores it. Later on, whenever the stored message is required by an authentic user, he retrieves the encrypted message and decrypts it by using his secret key. However, he can also request the cloud for an addition of encrypted messages. The cloud system only computes the requested addition and sends it to the authentic user; it cannot decrypt the stored encrypted messages on its own. This addition of encrypted messages should be the same as the encryption of the addition of original messages. In this chapter, the authors propose a homomorphic encryption technique in which the above-discussed scenario is possible. The cloud securely computes the addition of the encrypted messages which is ultimately the encryption of the addition of the original messages. The security of the proposed encryption technique depends on the hardness of elliptic curve hard problems.
User Satisfaction With Library Information Resources and Services

This chapter deals with the purpose of library resources and services stratification of users of Alagappa University. Users are the most vital component of libraries. Alagappa University Central Library provided the various types of services in RFID, Web OPAC, SMS and e-mail alerts, ETD, DLNET service, mobile-based digital services, etc. The study covers 76 scholars out of 82 questionnaires distributed. The questionnaires were distributed in 10 departments in the Faculty of Arts in Alagappa University. The statistical techniques used for the analysis of data are the frequency, cross tables, descriptive statistics. This chapter describes the use of resources and services, library services, services provided to the users, e-resources access at Alagappa University, scope and limitations of the study, and objectives for using the resources and services. Alagappa University research scholars mostly used the library resources and services.
Patrol Principles

Today, everyone's perspective on safety and security is malleable. For the layman, this is due in part to the 24/7 news coverage. What once were local events occurring in far off towns and states are now covered and shown throughout the country. This level of coverage creates an awareness and anxiety level not seen before in the hearts and minds of the average person. For the security practitioner, the present threats and changing methodologies of perpetrators creates unique challenges which require continuous reviews of security policies, protocols, and procedures.
A Sparsity-Aware Hybrid Collaborative Recommendation Method with Multi-Source Data

Collaborative filtering (CF) is an effective method, which is widely applied in a great deal of recommendation systems. It can extract latent user preferences and item features from user-item rating matrix, by making use of Matrix Factorization (MF)'s technique to generate recommended items. However, the traditional MF based recommendation methods are faced with sparsity problems caused by unavailable and incomplete user-item rating datasets, which greatly degrades the accuracy of recommendation results. To address the sparsity problem caused by unavailable and incomplete datasets, we propose a sparsity-aware hybrid collaborative recommendation approach with multi-source and heterogeneous data in this paper. Firstly, we adopt more abundant and accessible implicit feedback data rather than explicit user-item rating data to overcome the data unavailability issue. Moreover, to address the “Missing not at random” (MSAR) problem with implicit feedback data, we adopt auxiliary data from user profile or item content to generate more accurate user preference and item features; which will be fused into the MF model to generate accurate recommendation results. More specifically, Principal Component Analysis (PCA) and Stacked Denoising Auto Encoder (SDAE) are used as feature extractor, thereby generating user preferences and item features. Finally, we did a lot of experiments on several datasets to assess the proposed recommendation approach. The results indicate that, compared with pure matrix factorization, the hybrid collaborative recommendation model combining extra latent user/item representation can enhance the recommended results' accuracy; while the time consumption is almost the same.
A Survey of Cloud-Based Services Leveraged by Big Data Applications

Due to the growing interest in harnessing the hidden significance of data, more and more enterprises are moving to data analytics. Data analytics require the analysis and management of large-scale data to find the hidden patterns among various data components to gain useful insight. The derived information is then used to predict the future trends that can be advantageous for a business to flourish such as customers' likes/dislikes, reasons behind customers' churn and more. In this paper, several techniques for the big data analysis have been investigated along with their advantages and disadvantages. The significance of cloud computing for big data storage has also been discussed. Finally, the techniques to make the robust and efficient usage of big data have also been discussed.
Fusing contextual word embeddings for concreteness estimation

Natural Language Processing (NLP) has a long history, and recent research has focused in particular on encoding meaning in a computable way. Word embeddings have been used for this specific purpose, allowing language tasks to be treated as mathematical problems. Real valued vectors have been generated or employed as word representations for several NLP tasks. In this work, different types of pre-trained word embeddings are fused together to estimate word concreteness. In the evaluation of this task, we have taken into account how much contextual information can affect final results, and also how to properly fuse different word embeddings in order to maximize their performance. The best architecture in our study surpasses the winning solution in the Evalita 2020 competition for the word concreteness task.
Cultural and axiological examination of the content of general education

The paper deals with the possibilities of cultural and axiological examination of the content of textbooks and curricula of general education in Russia. We are talking about such disciplines as Social Studies, History, World Art Culture, Local History, Fundamentals of the spiritual and moral culture of the peoples of Russia, Fundamentals of religious culture and secular ethics. It is shown that axiological components are an obligatory part of the content of these disciplines, regardless of whether they are consciously oriented to being a conductor of any ideology, or to abandon all ideological attitudes. Culturology as the science of value models that generate culture as an integral system of artifacts, implemented in a specific time and place, allows us to identify the axiological content of any of these artifacts, including textbooks and programs. It is within the framework of general education that this is an extremely urgent task, since general education performs an educational function, determining the values of the younger generation and the future of our country.
Insourcing and Outsourcing of Library Technology

This article traces the movement of library technology from in-house systems created and maintained by library personnel to outsourced products bought from and largely controlled by vendors. As well as documenting these changes observations will be made concerning strategic advantages and disadvantages of this move. Focus will be limited to six areas of library technology: OPAC, Discovery Layer, MARC Records, Bindery, Acquisitions and ERM (Electronic Resources Management). Some may argue that these are all components of a central ILS that are created and available. This is true in some cases but not others. For example, Innovative Interfaces has always had an Acquisitions module whereas other ILSs have not. Many libraries still use a spreadsheet or other method to keep track of serials where others have migrated to an ERM. Individual use cases will be covered to demonstrate the benefits and shortcomings of each system.
Introduction

What happened to causality? This is the notion with which we understand nature: some event A causes another event B. According to general relativity, such relations are only feasible through a spacetime, in that it has to allow information to travel from A to B, and spacetimes are dynamical—they are shaped by nearby massive objects. At first sight, it seems that quantum mechanics is consistent with causality: something that happened in a quantum system at point A (say preparation) can be the cause of what happens at a later point B (say measurement). But what happens when we create a superposition of such scenarios?
Matter Transmission

In a world connected by wifi we take the wireless transmission of information for granted. But can matter be similarly transmitted? The matter transmitter described in Milne’s story would of course not work as advertised, but physicists are working on a quantum version of a matter transmitter—a quantum teleporter. Quantum teleportation isn’t quite the equivalent of Milne’s device, or Star Trek’s more famous Transporter, but the technology is sure to change our world in the coming decades.
Block-Chain-Based Security and Privacy in Smart City IoT

The current technology has given arms, hands, and wings to the smart objects-internet of things, which create the centralized data collection and analysis nightmare. Even with the distributed big data-enabled computing, the relevant data filtering for the localized decisions take a long time. To make the IOT data communication smoother and make the devices talk to each other in a coherent way the device data transactions are made to communicate through the block chain, and the applications on the localized destination can take the decisions or complete transaction without the centralized hub communication. This chapter focuses on adding vendor-specific IOT devices to the public or private block chain and the emerging challenges and the possible solutions to make the devices talk to each other and have the decision enablement through the distributed transactions through the block chain technology.
A Computer Vision Framework for Automated Shape Retrieval

With the increasing number of images generated every day, textual annotation of images for image mining becomes impractical and inefficient. Thus, computer vision based image retrieval has received considerable interest in recent years. One of the fundamental characteristics of any image representation of an object is its shape which plays a vital role to recognize the object at primitive level. Keeping this view as the primary motivational focus, we propose a shape descriptive frame work using a multilevel tree structured representation called Hierarchical Convex Polygonal Decomposition (HCPD). Such a frame work explores different degrees of convexity of an object’s contour-segments in the course of its construction. The convex and non-convex segments of an object’s contour are discovered at every level of the HCPD-tree generation by repetitive convex-polygonal approximation of contour segments. We have also presented a novel shape-string-encoding scheme for representing the HCPD-tree which allows us touse the popular concept of string-edit distance to compute shape similarity score between two objects. The proposed framework when deployed for similar shape retrieval task demonstrates reasonably good performance in comparison with other popular shape-retrieval algorithms.
Fall Behavior Recognition Based on Deep Learning and Image Processing

Accidental fall detection for the elderly who live alone can minimize the risk of death and injuries. In this article, we present a new fall detection method based on "deep learning and image, where a human body recognition model-DeeperCut is used. First, a camera is used to get the detection source data, and then the video is split into images which can be input into DeeperCut model. The human key point data in the output map and the label of the pictures are used as training data to input into the fall detection neural network. The output model then judges the fall of the subsequent pictures. In addition, the fall detection system is designed and implemented with using Raspberry Pi hardware in a local network environment. The presented method obtains a 100% fall detection rate in the experimental environment. The false positive rate on the test set is around 1.95% which is very low and can be ignored because this will be checked by using SMS, WeChat and other SNS tools to confirm falls. Experimental results show that the proposed fall behavior recognition is effective and feasible to be deployed in home environment.
Literature Review

C and C++ are perhaps the most important programming languages due to its high performance. However, these programs all suffer from memory corruption issues such as out-of-bound accesses or object use-after-free bugs.
Formalizing equivalence between real number completeness and intermediate value theorem

This paper reports on the formalization of the completeness of intermediate value theorem. This theorem as a fundamental property of continuous function on a closed interval, can be used to solve the existence of roots of equations. The intermediate value theorem is usually regarded as a corollary of completeness theorem of real number. In fact, completeness theorem of real number also can be derived from the intermediate value theorem. This formalization is based on the formal system we developed strictly following Landau’s “Foundations of Analysis”. Dedekind fundament theorem has been proved in this system, and further we prove the supremum theorem. Then we formally verify the equivalence between supremum theorem and intermediate value theorem, which shows its completeness. All the proof has been checked by Coq, and the proof process is normalized, rigorous and reliable.
Exploring Privacy Notification and Control Mechanisms for Proximity-Aware Tablets

In hospitals, offices and other settings, professionals face the challenge of accessing and sharing sensitive content in public areas. As tablets become increasingly adopted in work environments, it is important to explore ways to support privacy that are appropriate for tablet use in dynamic, mobile workflows. In this research we consider how spatial information can be utilized to support both individual and collaborative work in a natural way while respecting data privacy. We present a proof-of-concept implementation of a proximity-aware tablet, and a range of privacy notification and control mechanisms designed for such a tablet. Results from a user study support the idea that interpersonal distance and orientation can be used to mediate privacy management for tablet interfaces. Selecting a specific design for privacy threat notification and response is highly context-dependent—for example, in health care the first priority is to not impede the fluid exchange of information.
Master-slave Control System of Data glove and Manipulator based on Multi-sensor Fusion

To solve the problems of large measurement error and poor reliability of the traditional data glove using a single sensor, a master-slave control system of the manipulator based on the data glove was designed using multi-sensor fusion technology. The structure of the master-slave system of the manipulator based on the data glove is introduced, and the multi-sensor data acquisition and processing method and the design scheme of the master-slave control system are analyzed. Test results of the manipulator to follow the position of human hand verily the effectiveness of the master-slave control system designed, and provide a good solution for using the data glove to accurately control the manipulator to complete various tasks.