Reviewerly/exHarmony huggingface dataset:
A More Efficient Private Set Intersection Protocol Based on Random OT and Balance Hash

Private set intersection (PSI) is a specific application problem in the field of secure multi-party computation. It allows the participants to compute set intersection collaboratively without learning any additional information about the sets. It is a building block for many real-world privacy-related applications. The state-of-the-art PSI protocol is mainly based on Random Oblivious Transfer (ROT) and cuckoo hash. It is efficient enough in computation but needs high communication cost and high network bandwidth. In this paper, we describe a novel PSI protocol based on ROT and balance hash under semi-honest adversary model. Experiments demonstrate that our protocol has better performance than the cuckoo hash based PSI at the expense of leaking a part of the indexes of hash bucket. We have proved that the impact of information leakage on security is almost negligible. In addition, for the purpose of reducing the communication overhead, we utilize cuckoo filter to optimize our protocol.
Research on some key technologies of Hadoop’s cloud GIS

Cloud computing is the product of the development of Internet computing to a certain stage, is the latest result of the evolution of parallel computing, grid computing and other new computing methods. The infinite expansion of cloud computing storage technology can meet the rapid growth of spatial data storage space requirements, powerful computing capabilities for spatial information retrieval, processing, analysis and other high-speed services to ensure. Aiming at the problems of massive data storage, processing, analysis and continuous service faced by GIS, this paper constructs the application of Hadoop-based GIS, and studies some key technologies.
Towards Long-Term Autonomy Based on Temporal Planning

This paper investigates the application of temporal planning to multiple robots in long-term missions, using the OPTIC and POPF temporal planners. We design a new planning domain, motivated by a realistic indoor-outdoor scenario. In particular, we investigate plan concurrency, makespan and plan generation time in the multi-robot problem and propose a schema which has been shown to improve plan quality while significantly reducing planning time for the multi-agent problem. Experiments are done in simulation using ROS and Gazebo, and demonstrated in missions with concurrent actions. The ROSPlan framework is also extended to work with multiple robots and used to integrate the planners in ROS. OPTIC provides the best overall solution considering the domain complexity and mission execution in the environment.
The Role of Structural Reasoning in the Genesis of Graph Theory

The seminal book on graph theory by Dénes Kőnig, published in the year 1936, collected notions and results from precursory works from the mid to late nineteenth century by Hamilton, Cayley, Sylvester and others. More importantly, Kőnig himself contributed many of his own results that he had obtained in the more than twenty years that he had been working on this subject matter. What is noteworthy is the fact that the fundamentals of what he calls directed graphs are taken almost exhaustively from Paul Hertz' 1922 article on structural reasoning about sentences of the form a→b. This is not a fact that is well known in logical circles, even though Kőnig fully acknowledges this in his book. In view of the numerous trends in the recent decades to describe and explicate logical matters by means of graphs, the fact that it was Hertz' foundation of structural reasoning that informed basic notions of graph theory in the first place is highly significant. The main goal of this paper is to summarize Hertz' article and demonstrate how Kőnig integrates the notions and results presented therein in his book. This is followed by an exposition of how and when Hertz' results were reinvented in terms of graph theory. A critical discussion of the opinion expressed by both Hertz and Kőnig that the more general sentences of the form (a1,…,an)→b, introduced by Hertz in a companion article in 1923, cannot be interpreted by graphs concludes this paper.
Author Correction: Multi-qubit Quantum Rabi Model and Multi-partite Entangled States in a Circuit QED System

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.
Extraction of Product Features from Customer’s Perspective Using User Review at the Golf EC Site

Due to the spread of the electronic commerce site (EC site), it changed to an era where shopping can be done without going to a real store through the Internet. Under these circumstances, a review is one of the important information to consider purchasing at the EC site. In this study, we use the reviews posted on golf portal site and we analyze the characteristic of products using a text mining method. Moreover, we extracted characteristic words and we evaluated 6 products of golf.
Open Source Firmware Customization Problem: Experimentation and Challenges

The great advantages of open source code-based projects like the case of open source firmware (OSF) are flexibility and freedom of customization. However, the difficulty inherent to their development process, which can be seen as a software composition issue, is the lack of structured approach and a teachable methodology for efficiently tackling such project. In this paper, we propose a 5-step pedagogical OSF’s customization approach, coupled with an agile development process to guide the learner and ease his comprehension. We experience this approach to prototype WiAFirm, an OpenWRT-based firmware for operating IEEE 802.11x enabled WAP. Two groups of 04 students each were involved. After 2 months of experimentation, the group that applied the approach was able to integrate into the core OpenWRT a custom WifiDog captive portal feature as a built-in package; while the other group had barely understood the goal of customizing an OSF.
Design of Video Monitoring System Based on ARM+DSP Dual Core and Improved Motion Detection Algorithm

This paper designs a video surveillance system that uses TMS320DM6467 dual-core processor as the control core, and puts forward an improved motion detection algorithm named background frame differential method to realize the video image of moving target detection, which uses mathematical morphology filtering method to fill a void in the motion area and remove isolated noise, using high real-time line segment labeled area growth method for detecting the target connected domain so as to realize the identification of moving vehicle. The system has stable performance and good real-time detection effect.
Gradual Sampling Gate for Bidirectional Knowledge Distillation

Knowledge distillation is an efficient approach for model compression. It is based on a unidirectional scheme that transfers knowledge from a large, pre-trained network to a smaller one. A bidirectional scheme was recently proposed that achieved a higher performance than a unidirectional distillation. How-ever, network training is disturbed at the early training stage of bidirectional distillation by the transfer of knowledge between them. We propose a “gradual sampling gate” that controls soft target loss by referring to the training accuracy of each network. Our bidirectional distillation method can improve the accuracy without increasing the computational cost. To evaluate our method, we compare classification accuracies with several network models (ResNet32, ResNet110, Wide ResNet, and DenseNet) over various datasets (CIFAR-10, CIFAR-100, SVHN, and Tiny ImageNet). Experimental results show that our method can effectively train networks and achieve higher accuracies.
FringeMatchNet: effective stereo matching onboard of mobile structured light 3D scanner

Precise and robust 3D model reconstruction is required in various outdoor scenarios such as aircraft inspection, rapid prototyping, and documentation of an archaeological site. This paper is focused on the development of a mobile structured light 3D scanner for online reconstruction. We use a structured light projection for fast data acquisition. We use deep learning based pattern matching to improve accuracy up to 0.1 pixels. Our FringeMatchNet is based on the U-Net architecture. The network produces an estimated shift heatmap with subpixel accuracy. Each pixel (x, y) of the heatmap represents the probability that the shift between the two image patches is equal to (x, y). We generated a large dataset that combines synthetic and real image patches to train our FringeMatchNet. We compare the accuracy of our FringeMatchNet with other stereo matching algorithms both hand-crafted (SGM, LSM) and modern deep learning-based. The evaluation proves that our network outperforms hand-crafted methods and competes with modern state-of-the-art deep learning based algorithms. Our scanner provides the measuring volume of 400 &times; 300 &times; 200 mm for an object distance of 600–700 mm. It combines portability with an object point resolution between 0.2 and 0.1 mm. We made our FringeMatchNet and the training dataset publicly available. Deep learning-based stereo matching using our FringeMatchNet facilitates subpixel registration and allows our scanner to achieve sub-millimeter accuracy in the object space.
DroneBallCup: When Drones Play Volleyball

The ground robots community has setup a competition called the RoboCup [10] (Autonomous Robotics World Cup) to challenge the progress of the technology achieved by both the academy and the industry around a use case that consists in playing football. In this paper we describe a similar approach that we are setting up for autonomous aerial vehicles (drones). The use case is Volleyball.
Analysis and Synthesis of Fountain Sound

Fountains are appealing visual and acoustic additions to outdoor and indoor spaces. By pouring or jetting water, fountains produce pleasant and tranquil sounds of flowing water and water bubbles. The sound of the fountain depends on its water feature style that produces sound with the particular sound level, frequency and temporal envelope characteristics. In this paper, analysis of frequency spectrum and variations in a temporal envelope of the fountain sound are performed. Methods for the synthesis of fountain sound are outlined, including physical modeling synthesis and conventional sampling synthesis using prerecorded sound waveforms.
Developing Social-Media Based Text Corpus for San’ani Dialect (SMTCSD)

This paper aims at developing and designing a social media based text corpus of San'ani Dialect (SMTCSD). The corpus is considered the first in the research area that codifies one of the most popular and spoken dialects in Yemen representing nearly 30% of Yemeni speakers. Our primary objective is a compilation of authentic and unmodified texts gathered from different open-source social media platforms mainly Facebook and Telegram Apps. As a result, we obtained a corpus of 447,401 tokens and 51,073 types with an 11.42% Token:Type Ratio (TTR) that is composed in entirely manual and non-experimental conditions. The corpus represents daily natural conversations which are found in the form of fictional dialogues, representing different situations and topics during the years 2017 and 2018. The data is preprocessed and normalized which then is classified into ten different categories. The analysis of the corpus is made using LancsBox, and different statistical analyses are performed.
A Framework with Enhanced Security for Service Oriented Architecture

Background: Service Oriented Architecture is one of the acceptable frameworks for application development which provides better functionality such as composability, reliability, reusability, distributed deployment and interoperability which meet enterprises dynamics. So, SOA framework is a point of attraction for consumers. Objective: However, SOA framework fails to provide security at a granular level. Along with SOA functionality, the consumer also needs a secure environment so that each application can be reliable. Methods: SOA functionality like modularity and reusability are helpful in cross-organization context but these quality requirements reduce the security of the applications. In the past years, many security techniques have been provided by different researchers, still, security is a concern of SOA framework. Results: Most of the research focus security enhancement at higher layers of SOA reference architecture only so that SOA functionality remains unaffected. In this paper, the author(s) provided a framework which enhances the security at both the higher layer and lower layer. Conclusion: Also, this framework focuses on security enhancement at the granular level so that application-level security can be enhanced. The author(s) also included a technique to keep SLA similar to the exiting application after the implementation of security at each layer. This framework will be helpful in enhancing the end to end security and reliability of an application.
Alternatives to the Build-or-Buy Decision in Library Automation Software Planning

This chapter reviews some of the typical pros and cons for building and buying software with particular attention to the implications for libraries. Writing specifications is a difficult and sometimes poorly understood process. To build or buy is the basic decision in general computer systems software planning. Making this decision has been a key to successful planning of business data processing since the mid-1960s. However, it is only within the last few years that it has become a true decision in most areas of bibliographic data processing. Good specifications should describe what want the system to do in as much detail as possible in primarily functional or user-oriented terms. In contrast, the possibility of buying software ready-made has a number of points in its favor. In general, it is much cheaper than building. It is simpler in the sense that the library need not become involved in the complexities of managing a software development effort.
Communication Matters

The chapter deals with the potential of smartphones for the ESP class, which is currently taught within a communicative framework at the University of Bucharest. The study begins from a survey conducted among non-philological students, with a view to assessing their opinion on the acceptance of MALL. As the findings confirmed, the instructors' general observation that students would welcome a mobile-integrated course. The first part of this chapter exemplifies how the smartphone can enhance both productive and receptive skills. It provides within concrete scenarios various recommendations of specific applications, methods, or videos to be incorporated in the class, as well as the advantages such enterprises may bring. The last part establishes some general directions for using the smartphone to improve individual types of skills. The chapter concludes that, while receptive skills mainly benefit from mobile technology in terms of efficiency and ease of use, productive skills allow deeper changes in the pedagogical paradigm, thus offering fertile ground for MALL.
Modification of Existing Face Images Based on Textual Description Through Local Geometrical Transformation

The main objective of this paper is to modify the facial features, to change the existing image based on description of height and width of the face components and to generate a transformed image. There are many challenges in dealing with the modification of existing face images which are variations in facial expressions can be a cause for confusion, lack of large-scale supervised datasets, both speed and scalability of system are of prime importance as results are expected in real times. The scope of the study is to test 30 male and female face images from ORL database. The study has been done using MATLAB R2013a .
Ontology Construction for Eldercare Services with an Agglomerative Hierarchical Clustering Method

A high-quality ontology for eldercare service can help deliver high quality eldercare services in increasingly aged and digitized societies because it can serve as a reference for formulating eldercare service standards and exchanging information pertain to eldercare services over the Internet. Improving upon previous work, we proposed an agglomerative hierarchical clustering method to construct such an ontology. This method incorporates longitudinal denoising and the word bag model to achieve accurate results verified by experiment results.
STRIDE: Single-Trip-Time Based Reliable Data Transport Protocol for the Reconfigurable Cloud

In a recent development, reconfigurable clouds become a viable solution to overcome practical problems in clouds, such as scalability, delay, etc., by offloading computation tasks to reconfigurable hardware, FPGA. Several existing techniques, such as TCP/IP Offload Engine (TOE) and Lightweight Transport Layer (LTL), are still hard to be implemented in real-world deployment due to large overhead or stringent dependency of the underlying network. In this paper, we propose STRIDE, a novel inter-FPGA data communication protocol, to provide reliable end-to-end communication which addresses practical problems in deployment. In our design, STRIDE leverages FPGA's abilities through programming, such as precise timestamping, to make more accurate measurement on end-to-end delay and deliver more precise control in managing traffic in cloud. We implement STRIDE on a FPGA-based network experimental platform and demonstrate that STRIDE reduces various hardware resources consumption by 36% to 49% compared to TOE. Additionally, it also improves flow completion time in comparison to TOE by 2.2X. We further demonstrate STRIDE outperforms DCTCP and TCP-Vegas in OMNET simulator by up to 1.8X and 2.3X on average and 99th percentile respectively in large scale setting.
3D Gesture Interface: Japan-Brazil Perceptions

Gestures are used naturally in communication, and use with modern computer systems is becoming increasingly feasible and applicable for interaction. Analyzing how gesture interfaces are perceived in different parts of the world can help in understanding possible weak and strong points, allowing for different improvements to the interfaces. This study aims to analyze how different technological familiarization levels impacts the user experience of gestural interfaces. Our work describes the findings of an experiment that was replicated in two countries: Brazil and Japan. In each experiment, 20 subjects tested two applications; one had a mouse-based interface and the other a gesture-based interface. User experience was measured using questionnaires from AttrakDiff. Subjectivity and abstract concepts largely differed, but major agreement was found regarding room for improvement of the pragmatist quality of the gestural interface in order to be embraced by the average user.
Analysis of temporal alignment for Video Classification

Thanks to their sucess on image recognition, deep neural networks achieve best classification accuracy on videos. However, traditional methods or shallow architectures remain competitive and combinations of different network types are the usual chosen approach. A reason for this less important impact of deep methods for video recognition is the motion representation. The time has a stronger redundancy, and an important elasticity compared to the spatial dimensions. The temporal redundancy is evident, but the elasticity within an action class is well less considered. Several instances of the action still widely differ by their style and speed of execution. In this article, we analyze the temporal dimension by focusing on its singular dynamism, and we focus on the normalization of temporal elasticity on sequences to reduce speed variation within a class. We propose a framework to temporally align video instance in a classification task using the latest temporal warping method, Generalized Canonical Time Warping (GCTW). We evaluate our strategy on video datasets where the intra-class variations lie in temporal dimension rather than in spatial dimensions. Finally, we show the interest of accounting for temporal elasticity for a better video classification and we draw perspectives on more efficient ways to normalize simultaneously temporal and spatial intra-class variations.
Smooth Methods in Head-Driven Statistical Models for Parsing

Handling the data sparseness question is a main way to further enhance the system performances of Head-driven statistical parsing models. Two smoothing methods are proposed to mitigate remaining data-sparseness problems. The first smoothing method is that two word classification algorithms based on word similarity have been developed, which employ the mutual information of two words that are adjoining words or have semantic relationship to define word similarity and word-class similarity. The second smoothing method is to decompose the generation of each internal rule into a sequence of smaller steps, and then to make conditional independence assumptions to incorporate the Part-Of-Speech tags of adjoining words or adjoining phrase tags into the probability computation of the context-free rules, the incorporating additional context information into the syntactic parsing models is very useful for improving the system performances of syntactic parsing. The two category-based statistical analysis models are tested through experiments. The improved parsing model 2 has far better system performances than head-driven parsing model: recall reaches 87.89%, accuracy reaches 88.62, and F-measure is enhanced 8.10% compared with the head-driven analysis method.
Study on Career Education for the Age of Computerization with Benefit of Inconvenience

This paper aims to introduces a challenge in career education for university students then further argues about the possibility of next generation career development methodology assuming the future Human Computer Interaction. The career education utilizes innovation methodology based on Benefit of Inconvenience (BI), which is called “Fubeneki” in Japanese. In this research, we analyzed the sample ideas of BI systems submitted by participant students in lectures and workshops in which BI concept was introduced and then, recognized typical misunderstandings of BI. In addition, we explored the results of a survey conducted on the students and business persons. The survey results of the participant students were compared with those of the business persons to argue expected connection between the innovation with BI and future methodology for career education.
Analysis of Voice Styles Using i-Vector Features

Many adjectives have been used to describe voice characteristics, yet it is challenging to define sound style precisely using quantitative measure. In this paper, we attempt to tackle the voice style classification problem based on techniques designed for speaker recognition. Specifically, we employ i-vector, a widely adopted feature in speaker identification, and support vector machine (SVM), for style classification. In order to verify the reliability of i-vector, we conduct pilot study, including noise sensitivity, minimum voice duration, and mimicry style test. In this study, we define eight voice styles and collect appropriate voice data to process and verify our hypothesis through the experiment. The results indicate that i-vector can indeed be utilized to classify voice styles that are commonly perceived in daily life.