Reviewerly/exHarmony huggingface dataset:
A Secure Multi-party Signature Scheme Based on Trust Mechanism

Aiming at the problem of trust, we propose a secure multi-party signature scheme based on trust mechanism. In this scheme, we introduce a trust vector with time-stamped and form a trust matrix composed of multi-dimensional vectors to record the behavior of the participants periodically. Finally, a trusted evaluation mechanism is established for the participants. Under the premise of participant trustworthiness, a secure multi-party dynamic threshold signature scheme is constructed by secret sharing technology. The security analysis shows that the scheme can effectively suppress the vandalism of malicious participants. it is forward security and can resist mobile attacks. Performance analysis shows that the scheme has lower computational complexity and higher execution efficiency.
Ordenagailu bidezko hizkuntza-egiaztatzegintza

Gizarteko beste esparru batzuetan bezala, hizkuntzen ikas-irakas prozesuetan ere goranzko joera du informazioaren eta komunikazioaren teknologien (IKTen) erabilerak, eta fenomeno horrek ateak ireki dizkio orain gutxi arte soilik paperean gauzatzen zen hizkuntzaegiaztatzegintzari. Izan ere, hizkuntzen ezagutza ordenagailu bidez egiaztatzeko eskaintza nabarmen zabaldu da azken hamarkadan. Molde informatizatu horrek erakunde beste aldaera dauzka, eta sistema-aniztasun hori ulertzeko, garrantzitsua da hainbat aldagaitan oinarritutako azterketa egitea, helburu izanik proben ekoizpena errealitateko ekintza omunikatiboetako baldintzetara ekartzea, eta, oro har, hizkuntzen egiaztatzegintza-prozesuak erraztea.
Fox @ the Fireside: Using Strategic Marketing &amp; Outreach to Foster Authentic Scholarly Conversations in the Library

This session highlights the strategic marketing, intentional outreach through liaisons, and event planning that went into developing "Fox @ the Fireside," shares about the program, and invites conversations about other opportunities that might exist for libraries to host and engage in scholarly discussions around campus. Fox @ the Fireside is an event hosted by the George Fox University librarians each semester, designed to showcase the intellectual and creative output of a campus community member or group (student, staff, faculty) and invite the university community to participate in conversation centered around a topic of campus-wide interest. Past programs have showcased art, books, and even LEGO® creations! Through this event, we have created a hospitable, inviting, inclusive space for conversation that furthers the library's mission to be a place for holistic connection, innovative creation, and authentic contribution.
Pulse-Enhanced Two-Photon Interference with Solid State Quantum Emitters

The ability to entangle distant quantum nodes is essential for the construction of quantum networks and for quantum information processing. For solid-state quantum emitters used as qubits, it can be achieved by photon interference. When the emitter is subject to spectral diffusion, this process can become highly inefficient, impeding the achievement of scalable quantum technologies. We study two-photon interference in the context of a Hong-Ou-Mandel (HOM)-type experiment for two separate quantum emitters, with different detunings with respect to a specific target frequency. We evaluate the second order coherences that characterize photon indistinguishability between the two emitters. We find that the two-photon interference operation that is inefficient in the absence of a control protocol, when the two detunings are different and spectral overlap is lessened, can be highly improved by a periodic sequence of $\ensuremath{\pi}$ pulses at a set target frequency. Photon indistinguishability in solid state and other quantum emitters subject to spectral diffusion can thus be enhanced by the proposed pulse sequence and similar external control protocols despite the fluctuations in the environment.
An Adaptive Method For Vehicle Counting Using Digital Image Processing Techniques

In developing nations, many cities are facing challenges that result from the massive number vehicles. So, information about flow of traffic is required for management of traffic. Collecting real-time, reliable and accurate information is crucial for traffic management. The main goal of this paper is to develop an adaptive model that can assess the real-time vehicle counts on roads using digital image processing techniques. By classification and counting the vehicles, estimation of traffic density can be done. Vehicle counting is demanding task due to problems like blurs, varying image resolution etc This paper presents a technique by using digital image processing methods like detecting edges, frame differentiation, filtering analysis etc., The proposed technique has been implemented by using MATLAB. The performance of this method is highly accurate
Morphotectonic Basin of the Shishin Valley - Southwest of Tikrit

Study was conducted Morphotectonic detailed Basin Valley Chichen reality in the western and southwestern spend Tikrit, showed a map Morphotectonic interpreted visually space visual improved the existence Fold subsurface led to the formation of abnormalities morphological and lithology in the western valleys of the basin, the research aims to find out the degree influenced by active tectonic regional and local levels. Included methods Morphotectonic analysis used in this region first, study indicators geomorphological activity tectonic They (AF_T_BS_SMF) and then the work of synthesis-by-Form (Overly weight) to move the cursor to the stage of actually stage a (RAT), and the second study analysis of linear structures with implications geological and linked with tectonic movements. The third resulted in the results of the analysis Morphology of the course of the main valley of the basin controlled by a set of geological factors tectonic it. as well as the displacement occurring to him, and finally, it is revealed through aliasing function of the course of the current valley great vulnerability characteristics compositional analysis.
Siglog monthly 204

research-article Siglog monthly 204 Share on Author: Daniela Petrişan Université Paris Diderot Université Paris DiderotView Profile Authors Info & Claims ACM SIGLOG NewsVolume 7Issue 1January 2020 pp 52–73https://doi.org/10.1145/3385634.3385642Online:24 February 2020Publication History 0citation38DownloadsMetricsTotal Citations0Total Downloads38Last 12 Months3Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Food Protein Nutrition and Fully Homomorphic Encryption Algorithms in Cloud Computing Environment

The protein content of peanut is 25% - 36%, which is widely used in meat processing, beverage processing and other fields. Gelation is one of the important functional properties of peanut protein. The main factors affecting the gel formation are peanut globulin and sulphur amino acids.In this paper, the authors analyze the food protein nutrition and fully homomorphic encryption algorithms in cloud computing environment. In cloud computing, all user data is stored on the cloud resource node. When the user needs it, the calculation result of the data is sent to the user through the network. Since all users' data is stored in the cloud, users do not have full control over their private data. Therefore, cloud service providers must provide secure and reliable guarantees. The best way to ensure data security is to encrypt the transmitted data and stored data. This paper introduces the optimization of fully homomorphic encryption algorithms in the cloud computing environment to provide us with the optimal solution.
Evolution Properties of Complex-Valued Memristive Differential-Algebraic Neural Networks

The study of differential-algebraic neural network is a new and fascinating field. In this paper, one kind of novel mathematical expression combining differential equation and algebraic equation is designed. Some sufficient conditions are presented via the mean value theorem of multi-valued differentials and the control theory of differential systems to ensure global asymptotic stability of complex-valued memristive differential-algebraic neural networks. Several criteria are given to assure that a unique equilibrium point of this model is existed, in addition, it is globally asymptotically stable via the properties of nonsingular M-matrices and definitions of stability. It is noteworthy that these conditions are an extension of existing works. Moreover, numerical simulations are given to test theoretical results.
Simplified LSTMS for Speech Recognition

In this paper we explore new variants of Long Short-Term Memory (LSTM) networks for sequential modeling of acoustic features. In particular, we show that: (i) removing the output gate, (ii) replacing the hyperbolic tangent nonlinearity at the cell output with hard tanh, and (iii) collapsing the cell and hidden state vectors leads to a model that is conceptually simpler than and comparable in effectiveness to a regular LSTM for speech recognition. The proposed model has 25% fewer parameters than an LSTM with the same number of cells, trains faster because it has larger gradients leading to larger steps in weight space, and reaches a better optimum because there are fewer nonlinearities to traverse across layers. We report experimental results for both hybrid and CTC acoustic models on three publicly available English datasets: Switchboard 300 hours telephone conversations, 400 hours broadcast news transcription, and the MALACH 176 hours corpus of Holocaust survivor testimonies. In all cases the proposed models achieve similar or better accuracy than regular LSTMs while being conceptually simpler.
Teaching on the Front End

Front-end development skills are a practical necessity for creating impactful "real-world" systems. Yet universities don't often prioritize skills-focused courses such as web or mobile development that teach students to design and implement user-facing systems. We believe our curricula should include these skills and stacks, and that they are a key practice through which foundational CS concepts are applied. While other technology areas have research- or education-focused conferences, front-end programming and design skill-sets are mostly relegated to professional conferences where little time is focused on education. Currently there is no way for people teaching web and mobile development in higher education to easily connect. This BoF will gather as-of-yet unconnected instructors in these areas. We will discuss questions of practice, and share expertise and support around how to best teach these user-focused skills. How can you and your students keep up with rapid changes to programming languages such as JavaScript or Swift? Should teaching focus on a particular framework such as React or Vue (or something else)-and if so which one? What is the role of "no code" tools (e.g., Webflow, Bubble.io) in teaching front-end development? Should you teach front-end courses like a traditional CS course or like a code bootcamp? How can you integrate foundational skills in your web and mobile development courses? Does your department want to teach these practical skills, but lacks the resources, faculty or knowledge to do so? Let's share and discuss.
Prescott Library: Faculty Resources: Digital Books & Magazines

Digital Library Tools for your use in and outside of the classroom Information on eBooks, audiobooks, digital magazines and more
FAKE CURRENCY RECOGNITION SYSTEM FOR INDIAN NOTES USING IMAGE PROCESSING TECHNIQUES

In the point of economic stability of a nation, circulation and use of the fake currency notes pose major threats. Curbing the use of fake currency notes nowadays becomes digitalized with use of digital image processing algorithms. Counterfeit notes are printed with the utmost precision level to par with the original. So fake currency detection is a difficult task by simple visual inspection and use of digital image processing algorithms come to play a vital role. The conceivable arrangements are there, to utilize either chemical properties of the currency or to utilize its physical appearance for detection. The methodology exhibited in this paper depends on physical appearance of the Indian currency. Image processing algorithms have been embraced to expose the highlights of Indian currency notes, for example, security thread, intaglio printing (RBI logo) and distinguishing proof imprint, which have been received as security highlights of Indian currency. To make the framework increasingly robust and exact, the definitive score of all the three highlights has been intertwined to separate among genuine and fake monetary standards. Another parameter used to quantify the execution of the proposed framework is mean square error, which is roughly 1%. It might be embraced by the everyday citizens too, who frequently face the issue of separating among genuine and fake monetary standards.
Meta-path Reduction with Transition Probability Preserving in Heterogeneous Information Network

Heterogeneous Information Network (HIN) has attracted much attention due to its wide applicability in a variety of data mining tasks. A potentially large number of meta-paths can be extracted from the heterogeneous networks, providing abundant semantic knowledge. However, too many meta-paths may be redundant. Reduction on the number of meta-paths can enhance the effectiveness since some redundant meta-paths provide interferential linkage to the task. Moreover, the reduced meta-paths can reflect the characteristic of the heterogeneous network. In this paper, unlike previous supervised model, we propose a novel algorithm, SPMR (Semantic Preserving Meta-path Reduction), to reduce a set of pre-defined meta-paths in an unsupervised setting. The proposed method is able to evaluate a set of meta-paths to maximally preserve the semantics of original meta-paths after reduction. Experimental results show that SPMR can select a succinct subset of meta-paths which can achieve comparable or even better performance with fewer meta-paths.
The Improvement of Student's Information Literacy Based on the Association of College and Reseach Libraries (ACRL) using Empowering 8

The result of a preliminary study conducted by the researcher showed that the information literacy ofstudents at the Elementary School Teacher (PGSD) Program was low. Therefore, this research was done to understand the effect of Empowering 8 model application in improving student's information literacy. This research used the quasi-experimental method with a pretest-posttest control group design. The research participants were 66 students, consisting of 33 students in the experimentalclass and 33 students in the control class. This research utilized some instruments , including pretest,posttest, questionnaires and observation sheets. The results obtained were: the studeinformation literacy ability based on ARCL experimental class was in the high category. It revealed that application of Empowering 8 model had a positive effect on the student's information literacy.
Wavelet Based Multi-Trend Structure Descriptor for Effective Image Retrieval

We propose a novel descriptor for content based image retrieval called wavelet based multi-trend structure descriptor (WMTSD). The proposed WMTSD is an enhanced approach of multi-trend structure descriptor (MTSD). To diminish the computational cost of MTSD with the preservation of retrieval rate, WMTSD is derived. In order to diminish the time cost, an image is decomposed into optimum level using discrete Haar wavelet transform and it produces multiresolution pyramid image. The multi-resolution pyramid image at optimum level is utilized to estimate the feature descriptor. The optimum level for the decomposition of an image is determined empirically. The proposed WMTSD is exhaustively tested on Corel 1k, Corel 5k, Corel 10k and Caltech benchmark datasets. The experimental study very clearly illustrated that the proposed WMTSD and MTSD attains almost similar retrieval accuracy. But, the time cost of WMTSD is too small then the MTSD which is required more in the era of big data. Euclidean distance measure is adopted to assess the similarity between the images. Precision and Recall are the measures used to assess the proposed approach.
Modeling Cloud Environment for Assessing Denial of Service Attack

Cloud computing allows users to store and process their data in third party data centers. There is a need for secure and reliable measures to be taken to prevent loss of data, authentication problems and other security issues. This paper discusses steps followed to set up a private cloud using an open source software platform, OpenStack. Setting up the private cloud not only ensures the privacy as it eliminates the involvement of a third party cloud service provider but also provides us with a cheaper alternative. A Denial of Service (DoS) attack is a type of security attack where in the main aim is to overload the machine making it inaccessible to legitimate users. To assess DoS attack, we develop a web application running on one of the instances of our cloud. We analyze the DoS attack on this application using a DoS algorithm running on one of the instances in cloud. The performance of the cloud under the attack and without the attack is analyzed and conclusions about the risks involved are drawn. By assessing these risks, the performance degradation of the cloud is visualized using Wireshark and SlowHTTPTest tools.
Short- and long-term memory functions are mimicked through artificial synapse

Researchers find biological short- and long-term memory mechanisms can be imitated in neural networks using precise engineering of magnetic tunnel junction stacks.
Dimensionality Reduction based Colour Image Watermarking in Frequency Domain using Integrated Transformation Techniques

Watermarking plays a vital role in many aspects. It protects important contents such as images from content theft. Watermark on image informs others about the image ownership, so that the image cannot be used without authorization. Hence, robust and accurate watermarking is extremely important. Therefore, the objective of this paper is to develop a modified digital colour image watermarking technique with increased robustness and higher accuracy. In order to attain this objective, this paper proposes a watermarking scheme that focuses on aspect pruning and dimensionality reduction of information. In addition, the performance of the modified watermarking approach is enhanced by integrating singular value decomposition (SVD). A comparative analysis was carried out with various existing watermarking algorithms and a satisfactory result with improved accuracy rate was obtained when tested with existing watermarking schemes for different noise attacks.
Digitalisering av grammofonskivor : En analys och jämförelse av arbetet vid Kungliga biblioteket och Sveriges Radios Grammofonarkiv

This master thesis is an attempt to analyze and compare the work being done to digitize the phonograph record collections of The National Library of Sweden (KB) and the Record archive of the Swedis ...
HYBRID MOBILE APPLICATION DEVELOPMENT IN APPZILLON MADP

In today’s world there are more mobile users than desktop/laptop users. As mobile devices are integral part of today’s life, it’s safe to say that mobile apps have substantial effects in our daily life. Digital platform has soon become an integral part of every enterprise’s DNA. Legacy systems are slowly transforming into efficient digital solutions and early adaptors stand to gain a lot in the digital race. So as building a good quality mobile app is important, you need a trusted and secured mobile application development platform to go with. Several factors come into the pictures while developing a mobile app; such as investment, time to market, better UI experience, availability of resources, and easy access to the development platform as major ones. There have been debates over native mobile apps vs. hybrid mobile apps, then again choosing a hybrid MADP seem to be more reasonable and profitable than a native MADP when you consider above reasons. Appzillon, the flagship product of I-exceed technology solution private limited, is a hybrid MADP, where you can build Omni-channel apps for smartphones, tablets, feature phones, desktops and laptops. Appzillon provides Microapp/Microservice architecture and low code visual design approach where developers code less and develop more functionalities in less time with less dependencies.
CASE STUDY FOR MIGRATION FROM ON PREMISE TO CLOUD

The cloud computing has acquired a great deal of attraction, the possibility for minimizing over and under provisioningthrough enabling a ﬂexible sharing resource and allocation is still large. In this article, a complete analysis towards development ofmigration method from on premise to cloud will be presented. First we deﬁne cloud computing that includes three service models;platform, infrastructure, and software as a service over a network connection. This work demonstrates the issues which the decisionmakers are facing in the case of evaluating the feasibility of the migration legacy system in organization into cloud computing.Furthermore, describes our technology toolkit, which has developed to support this process. The efﬁciency of the proposed technologytoolkit has being evaluated under testing as a case study that is exploring options to choosing deployment and cloud service models.
Static Detection of Design Patterns in Class Diagrams

Teaching Object-Oriented design on the class diagram level is often a cumbersome effort. Requiring the use of specific design patterns helps the students in structuring their design properly. However, checking whether students used the right design pattern can be a very time-intensive task due to the variety of possibilities of creating structure using design patterns on the high-level class diagrams. For the same reason, it is hard for students to check for themselves whether their solution fulfills the basic requirements that are required by the instructor with respect to the use of design patterns. Efficiency and the quality of design pattern education can be improved by automatic detection of design patterns in UML class diagrams. We introduce a new method to detect design patterns in class diagrams, together with a prototype of a tool that uses this new method. Using this tool, an instructor needs less effort to review solutions of design exercises since the tool can check the basic class requirements automatically. Consequently, an instructor can focus on the more high-level requirements that were set in the exercise and students can easier check for themselves whether their design satisfies the basic required properties on the pattern level. The method offers static decidability for those design patterns, that are identified by structural properties e.c. the names of the classes and their associations. It is non-duplicating. That is a specific occurrence of a design pattern is not reported multiple times. The method not only detects all 16 static Gang of Four design patterns without false positives or false negatives, but also it can detect redundant relations. Our tool contributes to the quality and efficiency of design pattern education, both for students and instructors.
Quantum algorithms of interest on NISQ machines

I will explore a few possibilities for quantum algorithms and quantum simulations of interest on NISQ machines.