Reviewerly/exHarmony huggingface dataset:
Approximate Voronoi cells for lattices, revisited

Abstract We revisit the approximate Voronoi cells approach for solving the closest vector problem with preprocessing (CVPP) on high-dimensional lattices, and settle the open problem of Doulgerakis–Laarhoven–De Weger [PQCrypto, 2019] of determining exact asymptotics on the volume of these Voronoi cells under the Gaussian heuristic. As a result, we obtain improved upper bounds on the time complexity of the randomized iterative slicer when using less than <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:msup> <m:mn>2</m:mn> <m:mrow class="MJX-TeXAtom-ORD"> <m:mn>0.076</m:mn> <m:mi>d</m:mi> <m:mo>+</m:mo> <m:mi>o</m:mi> <m:mo stretchy="false">(</m:mo> <m:mi>d</m:mi> <m:mo stretchy="false">)</m:mo> </m:mrow> </m:msup> </m:math> $2^{0.076d + o(d)}$ memory, and we show how to obtain time–memory trade-offs even when using less than <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:msup> <m:mn>2</m:mn> <m:mrow class="MJX-TeXAtom-ORD"> <m:mn>0.048</m:mn> <m:mi>d</m:mi> <m:mo>+</m:mo> <m:mi>o</m:mi> <m:mo stretchy="false">(</m:mo> <m:mi>d</m:mi> <m:mo stretchy="false">)</m:mo> </m:mrow> </m:msup> </m:math> $2^{0.048d + o(d)}$ memory. We also settle the open problem of obtaining a continuous trade-off between the size of the advice and the query time complexity, as the time complexity with subexponential advice in our approach scales as <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:msup> <m:mi>d</m:mi> <m:mrow class="MJX-TeXAtom-ORD"> <m:mi>d</m:mi> <m:mrow class="MJX-TeXAtom-ORD"> <m:mo>/</m:mo> </m:mrow> <m:mn>2</m:mn> <m:mo>+</m:mo> <m:mi>o</m:mi> <m:mo stretchy="false">(</m:mo> <m:mi>d</m:mi> <m:mo stretchy="false">)</m:mo> </m:mrow> </m:msup> </m:math> $d^{d/2 + o(d)}$ matching worst-case enumeration bounds, and achieving the same asymptotic scaling as average-case enumeration algorithms for the closest vector problem.
Perancangan Sistem Informasi Pergudangan dengan Metode Framework for The Application System Thinking (Fast) Berbasis VBA Macro Excel (Studi Kasus PT. Meidoh Indonesia)

The development of information technology is growing very rapidly, as evidenced by the birth of Industry 4.0. Industry 4.0 has entered all aspects of life, the manufacturing industry and the service industry. One of the purposes of the use of information technology is to increase the effectiveness and efficiency of a process and the company's competitive advantage. PT. Meidoh Indonesia, which is located in Karawang, has begun to apply Industry 4.0 technology, especially in the field of improving material flow. The process of taking employee work equipment is still conventionally using the material request paper. This study aims to design an employee work equipment warehousing information system using the Framework For The Application System Thinking (FAST) method based on VBA Macro Excel. The results showed that this information system makes it easier for employees to make requests for work equipment to support their work. Information systems can reduce times of request material up to 60%. The fastest material request time conventionally takes 15 minutes, while material request time using this warehousing information system only takes 5 minutes.
Understanding Image Retrieval Re-Ranking: A Graph Neural Network Perspective

The re-ranking approach leverages high-confidence retrieved samples to refine retrieval results, which have been widely adopted as a post-processing tool for image retrieval tasks. However, we notice one main flaw of re-ranking, i.e., high computational complexity, which leads to an unaffordable time cost for real-world applications. In this paper, we revisit re-ranking and demonstrate that re-ranking can be reformulated as a high-parallelism Graph Neural Network (GNN) function. In particular, we divide the conventional re-ranking process into two phases, i.e., retrieving high-quality gallery samples and updating features. We argue that the first phase equals building the k-nearest neighbor graph, while the second phase can be viewed as spreading the message within the graph. In practice, GNN only needs to concern vertices with the connected edges. Since the graph is sparse, we can efficiently update the vertex features. On the Market-1501 dataset, we accelerate the re-ranking processing from 89.2s to 9.4ms with one K40m GPU, facilitating the real-time post-processing. Similarly, we observe that our method achieves comparable or even better retrieval results on the other four image retrieval benchmarks, i.e., VeRi-776, Oxford-5k, Paris-6k and University-1652, with limited time cost. Our code is publicly available.
A dual dynamic key chaotic encryption system for industrial cyber-physical systems

Industrial Cyber-Physical Systems (ICPS) have higher requirements on the data encryption rate and security performance; meanwhile, the devices in ICPS only support the communication protocols in the lower layers, such as the physical layer and data link layer. However, the existing encryption systems are mostly developed on the application layer and not suitable for the ICPS. Moreover, the other encryption systems, equipped the security function on the link layer, update the keys periodically, and can not satisfy the high-security requirements of ICPS. Therefore, taking the high parallel property of FPGA (Field Programmable Gate Array) into consideration, this letter proposes a Dual Dynamic key chaotic Encryption System (D2ES) for ICPS, which provides the dynamics on the key generation and key update cycle on the data link layer. The system mainly includes an encryption module and a dual dynamic key module to realize the high-security performance. Finally, the proposed D2ES is implemented on FPGA platform, and extensive experiments have been conducted to evaluate its security performance. The experimental results show our D2ES provides more efficient encryption compared with the popular encryption algorithm DES (Data Encryption Standard) and can be applied for ICPS.
The Concept of “The Art of Book” in the Works of Book Scientists of the 1920s

The author uses historiographic analysis, scientologic and bibliological methods to analyse the texts of the leading domestic book scientists of the 1920s, expressed on the art and design of book. The article identifies the range of the most important sources from the point of view of the studied theme. The author traces how the concept of the “art of book” was interpreted by scientists of that period, how it was introduced into science, and what aspects of study of design skills seemed to be the most advanced. Increased interest in the appearance and aesthetic quality of printed publications, which had been observed in the art criticism since the end of the 19th century, moved in the 1920s to the field of academic science. There is a need to concretize the basic concepts of “book art criticism”, specify them in detail in the general system of book science. According to the majority of researchers, the art of book should be understood first of all not as graphic decorations, illustrative additions to the text, but its typographic interpretation, clear coordination of all elements of the book ensemble. This idea was also expressed by the critics of Silver age, but it was the book scientists of the 1920s who especially vigorously promoted it, introduced it into the minds of contemporaries and into scientific circulation, and used it as a methodological basis for their theoretical constructions. M.I. Shchelkunov’s monograph “History, technology, art of book printing” played an important role in the history of “art book science”. It contains a lot of valuable information; however it is largely spoiled by the author’s vulgar-sociological approach to the chosen topic. More successful were the works of A.A. Sidorov “The art of book”, “Book as an object of study and artistic elements of book”, which raised the question of the need to study the forms of book, the laws of its construction, and the ratio of constructive and decorative elements in the design ensemble. The author also considers the statements about the art of book by M.N. Kufaev, A.M. Lovyagin, N.F. Garelin, M.I. Fabrikant, A.G. Fomin, P.M. Dulsky. Attempts by scientists in the 1920s to create a theory of book art, to approach the study of print works from the standpoint of art studies, were not always successful, but nevertheless, they were of great importance for Russian book science, expanded its borders and significantly influenced its further development.
Creating Comfortable Classroom by VAK Learning Styles: Planning for Early Childhood to Interest in Learning English

The objectives of the research were to investigate whether or not creating a comfortable classroom by VAK learning styles as a technique has significant effects for early childhood in learning English and whether or not the students are interested in creating a comfortable Classroom by VAK Learning Styles as a technique in Learning English. This research employed a pre-experimental method by using one group pre-test and post-test design, where the writer did an experiment in a single group only. The population of this research was the students of TK Tri Putri in Makassar Suburb academic year 2019/2020. This research used purposive sampling. The sample consisted of 34 students. Those students should be 5-6 years old. The data was collected by using a writing test and observation checklist. The findings showed that there was an improvement in the students’ English ability after the treatment. The students’ result of the posttest was more significantly improved than the students’ result of the pretest by the mean score of 81.18 &gt; 50.12. The difference of both scores was statistically significant based on the t-test value at significant level 0.05 in which the P-value is lower than the significant level (0.000 &lt; 0.05). The mean score of the students’ interest in cycle 2 was 80 and it was categorized as interested classification.
A New Bio-Inspired Social Spider Algorithm

The concept of bio-inspired algorithms is used in real-world problems to search the efficient problem-solving methods. Evolutionary computation and swarm intelligence are outstanding examples of nature-inspired solution techniques of metahuristics. In this paper, an effort has been made to propose a modified social spider algorithm to solve global optimization problems in the real world. Social spiders used the foraging strategy, vibrations on the spider web to determine the positions of prey. The selection of vibration, estimated new position and calculation of the fitness function, has been furnished in details way as compared to different previously proposed swarm intelligence algorithms. Moreover, experimental result has been carried out by modified social spider on series of widely-used benchmark problem with four benchmark algorithms. Furthermore, a modified form of the proposed algorithm has superior performance as compared to other state-of-the-art metaheuristics algorithms.
Dicke state generation via selective interactions in a Dicke-Stark model

We propose a method to create selective interactions with Dicke-Stark model by means of a time-dependent perturbation theory. By choosing the proper rotating framework, we find that the time oscillating terms depend on the number of atomic excitations and the number of photonic excitations. Consequently, the Rabi oscillation between selective states can be realized by properly choosing the frequency of the two-level system. The second order selective interactions can also be studied with this method. Then various states, such as Dicke states, superposition of Dicke states and GHZ states, can be created by means of such selective interactions. The numerical results show that high fidelity Dicke states and Greenberger-Horne-Zeilinger states can be created by choosing the proper frequency of the two-level system and controlling the evolution time.
On the possible phenomenological autonomy of virtual realities

In the following article, I examine Martin Heidegger’s philosophy of dwelling with a view to its importance for the concept of ‘place’. It is my interest to show how a phenomenological concept of place can elucidate the phenomenology of virtual reality. I begin by contextualising the investigation through a presentation of Jeff Malpas’ concept of the non-autonomy of the virtual, and argue for a clearer understanding of the notion of causal non-autonomy. Furthermore, I argue that the autonomy or lack thereof of virtual reality should not lead to the conclusion that virtual reality cannot be experienced and examined as a self-standing entity; that in order to properly understand virtual reality, we cannot limit ourselves to the reductionistic view presented by Malpas, but must account also for the phenomenology of experiencing virtuality – and under such a phenomenological consideration, the distinctions made between non-virtual and virtual reality are made more diffuse. I then argue that we can plausibly accept that places may exist in virtual reality, despite current technological and practical limitations. In addition, I go on to consider some possible metaphysical differences between virtual and non-virtual places.
Efficient Heuristic Generation for Robot Path Planning with Recurrent Generative Model

Robot path planning is difficult to solve due to the contradiction between optimality of results and complexity of algorithms, even in 2D environments. To find an optimal path, the algorithm needs to search all the state space, which costs a lot of computation resource. To address this issue, we present a novel recurrent generative model (RGM) which generates efficient heuristic to reduce the search efforts of path planning algorithm. This RGM model adopts the framework of general generative adversarial networks (GAN), which consists of a novel generator that can generate heuristic by refining the outputs recurrently and two discriminators that check the connectivity and safety properties of heuristic. We test the proposed RGM module in various 2D environments to demonstrate its effectiveness and efficiency. The results show that the RGM successfully generates appropriate heuristic in both seen and new unseen maps with a high accuracy, demonstrating the good generalization ability of this model. We also compare the rapidly-exploring random tree star (RRT*) with generated heuristic and the conventional RRT* in four different maps, showing that the generated heuristic can guide the algorithm to find both initial and optimal solution in a faster and more efficient way.
Active Object Recognition Based on Prior Feature Distribution Table

In this paper, an active object recognition (AOR) method based on a prior feature distribution table (PFDT) is proposed. According to the distribution information of predetermined features on each object in the model base, the prior feature distribution table is created. Taking it as input, a feature decision tree (FDT) is constructed for object recognition and viewpoint planning (VP). To determine the next best viewpoint, we transform it into an optimization problem that is solved with the tree dynamic programming algorithm. Experiments show that the proposed method can achieve the object recognition task with the minimum average number of viewpoints.
The Information Strategy of University Education and Teaching Management in the Era of Cloud Computing and Big Data

This paper focuses on the analysis of the informatization strategy of university education and teaching management in the era of cloud computing and big data. Firstly, it analyzes the current situation of university education and teaching management informatization in the era of cloud computing and big data, analyzes and designs a set of information management system through a collaborative filtering algorithm, realizes parameter setting, and then explains and discusses it from several aspects In the era of cloud computing and big data, the implementation measures of university education and teaching management informatization are designed to provide reference materials for relevant research.
Impact of Social Media Promotion on Customer Purchase Intention of Commercial Banks Services

Banking sector these days are providing many products/services to the customers in a competitive way. Using social media promotion is a strong tool to reach the prospective and regular customers in the cost effective and time efficient way. So, in this way this research attempts to measure the impact of social media promotion on customer purchase intention of commercial banks services. Descriptive and causal research design was used. Convenience sampling method was used to collect sample. Primary cross- section data were collected. Two hundred samples were approached and data were collected from them. Partial Least Square Structure Equation Modeling (PLS-SEM) was used to measure the research model. The research confirmed customer awareness, customer engagement, product/service perception and trust has significant impact on customer purchase intention of banks services. Banks management should focus on the importance of social media to enhance these factors.
Classification of Intentional Eye-blinks using Integration Values of Eye-blink Waveform

We propose a method to automatically classify eye-blink types using the eye-blink waveform integral value. The method is assumed to apply to an input interface using eye and It performs automatic detection of intentional blinks. Attempts to treat eye gestures and blinks as input channels in addition to conventional gaze input has studied due to the spread of gaze tracking and gaze input interfaces recently. However, classifying the eye-blink type as intentional or spontaneous using existing eye-blink classification methods is difficult because eye-blinks are highly individual motions that are significantly influenced by various conditions. Therefore, in this research, we construct a more robust measurement environment, which does not require a strict setting such as fixing the relative distance between the face and the camera even for non-contact measurement. In order to realize this, we defined new feature parameters are defined to correct the individual differences from moving image measuring by Web camera to assume applying on mobile interface. The proposed method performs automatic detection of intentional blinks by automatically determining the threshold of blink types based on the waveform integration value as new feature parameter. We also constructed a blink measurement system to evaluate the proposed method and evaluated the proposed method by experiment. The system splits the interlaced image field into disparate fields for blink measurement with sufficient temporal resolution. It then extracts the waveform feature parameters and automatically classifies the eye-blink types. Experimental results show successful classification of intentional eye-blinks with 86% average accuracy, thus demonstrated the high accuracy of the proposed method compared to conventional methods based on eye-blink duration.
A Repository of Resources and Exemplars for the Cloud Curriculum

The increasing adoption of cloud computing is driving a demand for skills which needs to be addressed in higher education. However, the nature of the field presents significant challenges for educators. The body of knowledge associated with cloud computing is not well established, and many educators may not be comfortable with cloud computing concepts. Furthermore the services offered by the major cloud service providers (CSPs) tend to evolve rapidly.On the other hand, there is a wealth of up-to-date teaching and learning material available, much of it supported by the CSPs and provided free to students. The aim of the resource described here is to help instructors to define learning goals and identify suitable materials when designing their own cloud curriculum. Through the efforts of a series of ITiCSE Working Groups, a set of Knowledge Areas (KAs) for Cloud has been defined, and a canonical list of Learning Objectives (LOs) which align with the KAs has been developed. A repository has been created which contains: the definitive set of KAs and LOs; information on available teaching resources that align with the LOs; and exemplar modules that demonstrate the viability of using these to construct units of learning. The ongoing development of the repository and the use of the resources is described. It is proposed that the repository will form the core of and be maintained by an online community.
Influenza Global Scholarly Publications in the Mirror of the Co-Word Analysis Technique

1- Assistant Prof. of LIS, Department of Information Management, Regional Information Center for Science & Technology (RICeST), Shiraz, Iran , farshiddanesh@ricest.ac.ir 2- Graduated of knowledge and Information Science, Shemiranat Public Libraries Office, Tehran, Iran 3- Ph.D. in knowledge and Information Science, Department of knowledge and Information Science, School of Psychology and Educational Sciences, Kharazmi University, Tehran, Iran
Learning Continuous Image Representation with Local Implicit Image Function

How to represent an image? While the visual world is presented in a continuous manner, machines store and see the images in a discrete way with 2D arrays of pixels. In this paper, we seek to learn a continuous representation for images. Inspired by the recent progress in 3D reconstruction with implicit neural representation, we propose Local Implicit Image Function (LIIF), which takes an image coordinate and the 2D deep features around the coordinate as inputs, predicts the RGB value at a given coordinate as an output. Since the coordinates are continuous, LIIF can be presented in arbitrary resolution. To generate the continuous representation for images, we train an encoder with LIIF representation via a self-supervised task with super-resolution. The learned continuous representation can be presented in arbitrary resolution even extrapolate to x30 higher resolution, where the training tasks are not provided. We further show that LIIF representation builds a bridge between discrete and continuous representation in 2D, it naturally supports the learning tasks with size-varied image ground-truths and significantly outperforms the method with resizing the ground-truths.
Design and Implementation of a Lossless Compression System for Hyperspectral Images

Despite its popularity, the hyperspectral image compression algorithm recommended by the Consultative Committee for Space Data Systems (CCSDS) faces a long delay of the feedback loop and complex computations in the modes of band sequential (BSQ) and band interleaved by line (BIL). After analyzing the features of the CCSDS algorithm, this paper proposes a forward prediction method based on the xc7k325tffg9000 field programmable gate array (FPGA) chip (Xilinx Inc.), and adjusts the calculation flow of the CCSDS algorithm, aiming to shorten the time delay in the feedback loop. In addition, full-pipeline construction was implemented on FPGA board to realize real-time processing of data, and dynamic configuration of image parameters. Through functional simulation and off-board test, it is learned that, for the speed-insensitive path, the optimized algorithm can realize the complex operations of the original algorithm with less hardware resources; for hyperspectral image data with an effective input bit width of 12bit, the proposed method can reach a maximum operating frequency of 103MHz, and the data throughput of 103M samples per second (1.237Gbps).