Reviewerly/exHarmony huggingface dataset:
Implementation of Blowfish Algorithm and Exploring Key Management & Authentication in Cryptography

In this IT scenario, there is an increase in the malware, spyware and malicious software (or applications) in the network by the attackers, such things need to be sensed and secured by adopting the mechanism to ensure confidentiality, authentication, integrity and availability. The number of Cryptography algorithms has been devised to develop the secret messages. The security attacks encountered essential to be resolved with key management, public key cryptography, protocols and authentication. This paper enlightens the Key distribution, Authentication, Security focuses in the Network and Blowfish algorithm. The implementation of the Blowfish algorithm is done in Netbeans 8.1.
An Image Segmentation Method Based on a Constrained Convex Variant of the Mumford-Shah Model

Image segmentation is a fundamental topic in image processing and computer vision. The Mumford-Shah (M-S) model is one of the most influential image segmentation models and has been researched widely in the last twenty years. In this paper, we propose a two-stage image segmentation method based on the constrained M-S model and the thresholding scheme. In the first stage, we find a smooth solution of the constrained M-S model by using the alternating direction method of multipliers (ADMM). Then the segmentation is obtained by segmenting the smooth solution using the K-means method. Experimental results show that our proposed method performs better and faster than other segmentation methods in the multiphase segmentation such as brain MRI images and artificial images.
Use of the Shearlet Transform and Transfer Learning in Offline Handwritten Signature Verification and Recognition

Despite the growing growth of technology, handwritten signature has been selected as the first option between biometrics by users. In this paper, a new methodology for offline handwritten signature verification and recognition based on the Shearlet transform and transfer learning is proposed. Since, a large percentage of handwritten signatures are composed of curves and the performance of a signature verification/recognition system is directly related to the edge structures, subbands of shearlet transform of signature images are good candidates for input information to the system. Furthermore, by using transfer learning of some pre-trained models, appropriate features would be extracted. In this study, four pre-trained models have been used: SigNet and SigNet-F (trained on offline signature datasets), VGG16 and VGG19 (trained on ImageNet dataset). Experiments have been conducted using three datasets: UTSig, FUM-PHSD and MCYT-75. Obtained experimental results, in comparison with the literature, verify the effectiveness of the presented method in both signature verification and signature recognition.
E-Resources: Perception and Use by Ayurvedic Medical College Library Users of North Karnataka

E-resources are increasingly important to all aspects of teaching and learning. This paper  provides an overview of the utilization of e-resources by the users of 23 Ayurvedic Medical College libraries of North Karnataka. A well-structured questionnaire was administered to the UG students, PG students and the faculty members of 23 Ayurvedic Medical College Libraries of North Karnataka to get required data. 1150 questionnaires were distributed, out of which 1101questionnaires were returned with good response. The study investigates awareness among the users about the availability of e-resource in the library; their usage; satisfaction with the availability of e-resources & infrastructure facility provided in using e-resources; and need of training to increase the utilization of e-resources. Gives suggestions and recommendations for the improvement in the usage of e-resources. Concludes that the users are not much aware about the availability of the e-resources in the library and they feel the need of training in using these e-resources.
Evaluation of Criteria used for Sustainable and Intelligent Transportation System Selection

- Sustainable and intelligent transportation systems aim to make contribution to economy and reduceenvironmental damages by providing a number of benefits namely road safety, efficient city management,energy efficiency, and reduced travel time and fuel consumption. This study presents an intuitionistic fuzzycognitive map (IFCM) application to evaluate the importance degrees of selection criteria of sustainable andintelligent transportation systems. An intuitionistic decision based approach is proposed to evaluate criteria dueto the cause-and-effect relationships among concepts; uncertainty, vagueness, and hesitation in data. Acommittee of three experts that work all as managers in logistics sector in Turkey provide the evaluation ofcausal relations among criteria. They express their opinions by reaching a consensus and the power ofinterrelationships and then concepts’ values are identified employing the iterative formulation of IFCM.
The prosody of presupposition projection in naturally-occurring utterances

In experimental studies, prosodically-marked pragmatic focus has been found to influence the projection of factive presuppositions of utterances like these parents didn’t know the kid was gone (Cummins and Rohde, 2015; Tonhauser, 2016; Djarv and Bacovcin, 2017), supporting question-based analyses of projection (i.a., Abrusan, 2011; Abrusan, 2016; Simons et al., 2017; Beaver et al., 2017). However, no prior work has explored whether this effect extends to naturally-occurring utterances. In a large set of naturally-occurring utterances, we find that prosodically-marked focus influences projection in utterances with factive embedding predicates, but not those with non-factive predicates. We argue that our findings support an account where lexical semantics of the predicate contributes to projection to the extent that they admit QUD alternatives that can be assumed to entail the content of the complement.
NEEDS ANALYSIS IN AN EAP COURSE: A CASE STUDY

This case study was done to investigate academic writing at a public university, in relation to student writing needs and the context of academic writing in a writing course at a public university in Malaysia. The study employed the complementarity mixed-method design, where questionnaires and interviews were used to collect the data. The total number of respondents for the questionnaire was 157 (26 EAP lecturers, 22 engineering lecturers, 17 human sciences lecturers and 92 EAP students from the engineering and human sciences faculties). Interviews were done with 15 EAP lecturers, three engineering lecturers, four human sciences lecturers, four EAP/engineering students and four EAP/human sciences students. The objectives of the study were to investigate the EAP lecturers’, the faculty lecturers’, and students’ perceptions of student academic writing needs and the EAP course. The results of the case study revealed that the EAP, engineering and human sciences lecturers as well as the EAP/engineering and EAP/human sciences students had similar and different perceptions with regard to student academic writing needs. Secondly, the majority of the EAP lecturers and students have a positive view towards the EAP course. The present needs (PSA) and the target needs (TSA) that have been identified from the findings can be used as a source of information for other language centres for their academic writing courses. As a start, since the findings also relate the identified needs with specific faculties (engineering and human sciences), this information can be used as a guide to determine the syllabus of a writing course for the related faculties.
An FPGA Realization for Real-Time Depth Estimation in Image Sequences

Marsi, Stefano Carrato, Sergio De Bortoli, Luca Gallina, Paolo Guzzi, Francesco Ramponi, GiovanniThis paper proposes a method for depth estimation in video sequences acquired by a monocular camera mounted on a mobile platform. The proposed algorithm is able to estimate in real time the relative distances of the objects in the field of view exploiting the parallax effect, provided the platform movement complies with a few constraints. The developed system is designed to operate at the input pixel cadence and is thus applicable to any video resolution. The final architecture, using operators no more complex than an adder and a memory that is just a fraction of a frame memory, can be realized in a low-cost FPGA.
Building Oral Language Learning Applications for Android-Based Deaf Students

One way to communicate for the deaf is to use oral language. This is what inspires researchers to create oral language learning applications for Android-based deaf students who aim to help the deaf in learning the oral language to communicate and in1the1learning1process.1The1method1used in this1research1is1research1and1development methods or research1and1development methods, this method is1used1to produce1certain1products1and1test1the1effectiveness1of1these1products1The results obtained are an android application that contains examples of correct pronunciation of the alphabet with media images, video examples and explanatory sentences. From the results of testing to 4 ABK obtained an average percentage of successful pronunciation as 83.6% with these results it can be concluded that this oral language learning application can be an effective oral language learning medium for deaf students.
Studies on the Cultivation of Innovation Ability of Chinese College Students Majoring in Mathematics

To obtain more innovative personnel, the outline of the national program for medium and long term education reform and development in China calls for the reform of the training systems to find new models and explore new methods. Therefore, a series of related researches have been conducted on it in the field of mathematics teaching in college and university in recent years. By using the literature analysis method, through collecting, identifying and sorting out the research on the cultivation of innovation ability of college students majoring in mathematics in recent 10 years, this study summarizes the current situation and strategies of the cultivation. The results showed that the current research mainly focused on the situation and the cultivation strategy. As for the current situation of the cultivation of innovation ability of students majoring in mathematics, the researchers think that the current college curriculum is unreasonable, the cultivation method is not scientific, the practical teaching system is not perfect, the students' consciousness is weak, lacking of the specialized teachers and the evaluation mechanism is not perfect. As for how to cultivate the innovative ability of students majoring in mathematics, the current researchers suggest that we should change the educational concept, optimize the curriculum structure, carry out practical teaching reform, cultivate excellent teachers and build a reasonable evaluation mechanism. Overall, the current research is still relatively scattered, there are many gaps. Therefore, it is suggested that future studies should be conducted in a comprehensive and systematic manner.
"New Education" A Determining Factor of Economic Growth in the 21st Century

In the context of postmodern society, by extrapolation, of postmodern pedagogy, where a special place belongs to the permanent education, it becomes imperative to manifest the new educations, as pedagogical answers to the problems of the present society. Being aware of the problems and values of today's society, mankind has been able to formulate its problem-solving strategies, entailing the values within which they are. The most important type of strategies is the one that realizes the change of mentality. And it is known that any change of mindset occurs effectively and globally through the transformative action of education. In this sense, we believe that the new educational model, called New education, has an overwhelming importance for the economic growth in the 20th century. XXI.
Incremental Object Detection Using Ensemble Modeling and Deep Transfer Learning

Object detection is a subset of computer vision that can be accomplished using machine learning. The main process of object detection using machine learning model is model training with images containing objects of interest. However, the model training need a lot of training images. In addition, to improve the model ability to detect addition class of object, it need to be re-trained with both old and new image datasets. It is a time and computation consuming process. This paper proposes an incremental object detection model without re-training the old images. An ensemble model and transfer learning approach are used. The proposed model consist of three parts, two object detection sub-models and a decision model, which are a pre-trained model, a transferred-model and an ensemble model respectively. To illustrate the proposed model, the trained YOLO algorithm training with eighty object categories, 330,000 total images, from COCO image dataset is selected as the pre-trained model. It also be used as an initial model to train the transferred-model using transfer learning technique. Only new images are used for transferred-model training. The ensemble model with the bagging technique is used as a final classifier for choosing the best decision from both sub-models. Using our proposed model, the need of both the number of training dataset and the training time are reduced. Only several hours are needed for model training with three new object categories, 3,000 total images. The experimental results show that the proposed model achieve high performance on test image dataset with 93.33% accuracy.
The Research and Application of Cloud Printing Platform Based on Improved AES-RSA Encryption Algorithm

With the development of cloud computing and Internet technology, the traditional printing mode can no longer meet the needs of users, so the cloud printing mode comes into being. However, most of today's Cloud Print operators only focus on the introduction of special services, while ignoring the security factors to ensure the operation of the platform, and there are hidden dangers of personal file information leakage. In view of the shortcomings of traditional printing methods, this paper takes the Internet as the starting point, integrates printing resources, builds a shared printing platform, and provides convenient printing services for cloud printing users. At the same time, Hash algorithm is added on the basis of AES-RSA hybrid encryption algorithm, and the algorithm is combined with software functions to effectively solve the security problems existing in the existing cloud printing platform.
Neural speech synthesis for resource-scarce languages.

Presented in: Proceedings of the South African Forum for Artificial Intelligence, Cape Town, 4-6 December 2019
Risks and Opportunities in the Cryptocurrency Market

The financial industry is subject to a new technological age through the evolution of the cryptocurrencies, people exploring a continuous rise of interest in investing on alternative basis mechanisms. This paper aims to give an overview of the blockchain technology and its potential, with its applicability on the cryptocurrency market. We illustrate the main challenges that the cryptocurrencis must overcome in order to achieve the customersâ€™ approval, which is strongly related to trust and cybersecurity issues. A comparative analysis of the two major cryptocurrencies emphasizes the risks and the opportunities offered by the cryptocurrency market, but also the main threats that must be addressed. Moreover, the consequences of the cryptocurrencies development for both national and international financial systems are evaluated, leading to the idea of a freedom-associated concept, where the lack of a third-party financial authority requires a significant change of perceptions and has the premises to fundamentally transform the traditional payment methods.
Solving brachistochrone problem via scaling functions of Daubechies wavelets

In this paper, we proposed an effective method based on the scaling function of Daubechies wavelets for the solution of the brachistochrone problem. An analytic technique for solving the integral of Daubechies scaling functions on dyadic intervals is investigated and these integrals are used to reduce the brachistochrone problem into algebraic equations. The error estimate for the brachistochrone problem is proposed and the numerical results are given to verify the effectiveness of our method.
Traditional Accounting with Decentralised Ledger Technology

Distributed ledger technology is by some believe to be the accounting system of the future, replacing the centuries-old double-entry accounting paradigm, as it has desirable characteristics such as tamper-resistance. However, it might suffer from technology lock-in as double-entry bookkeeping, due to its long-standing history, has offered the conceptual foundations for many laws, regulations and business practices. While some of these laws, regulations and practices might become obsolete as a result of distributed ledger technology, some might still prove to be valuable in a new technological context. While aiming at unlocking the potential of distributed ledger technology in an accounting context, we also want to preserve the wisdom of accounting craftsman. For this reason, it is the aim of this paper to offer a bi-directional mapping between traditional double-entry bookkeeping and innovative paradigms that have proven their value in decentralised systems, of which distributed ledger technology is an exponent. This paper offers such a mapping for the Resource-Event-Agent paradigm.
Design and Construction of a NASA Airborne and Field Investigation Inventory

NASA conducts airborne and field investigations that produce a wealth of valuable research data. Unfortunately, this data is often scattered across individual scientist hard drives or NASA Distributed Active Archive Centers and it can be difficult to locate and retrieve. Although satellite data has been successfully consolidated by tools such as EarthData Search, airborne and field investigation data present unique challenges stemming from the variability of temporal, spatial, platform, and instrument metadata. To address these difficulties with data retrieval and metadata variability, the Interagency Implementation and Concepts Team established an Airborne Data Management Group to improve airborne data search, understanding, access, and use. Surveys have been conducted of end users in order to build query lists that will drive the augmentation and standardization of existing metadata. Detailed metadata was then laboriously compiled from present and historic airborne and field investigations to build a database that will enable intelligent data search and retrieval. The inventory structure and function will be described and demonstrated. The purpose of this presentation is to bring awareness to this effort, to highlight and describe the issues and complications in development, and to increase user interest prior to public release in 2020.
Industry Analysis on Online Education

This paper aims at sorting out the underlying business logic of online education industry -- customer acquisition cost, user conversion and user retention, exploring the driving forces of online education industry change -- impact of COVID-19 and policy support, emerging internet capabilities and applications, demand for educational resources with high quality. Competition analysis is carried out on several well-known online education platforms such as TAL, GSX, VIPKID, Koolearn, Ape Coaching and Job Help. Strategy group map is drawn based on the two variables of customer acquisition cost and teaching mode. Then the paper demonstrates superior understanding of industry key success factors and executes the overall assessment of the current and future attractiveness of the industry.
媛쒖씤?뺣낫 ?먰빐諛곗긽梨낆엫 蹂댁옣?쒕룄???곸젏怨?怨쇱젣

Today, our society is exposed to cyber threats, such as the leakage of personal information, as various systems are connected and operated organically...
Commercial Solutions for Classified (CSfC): Harnessing the Power of Industry

CEOs of Fortune 500 companies, CIOs of federal/state/local agencies, and average citizens are all concerned about protecting their important information. The National Security Agency protects the nation’s most critical National Security Systems (NSS) and information against cyber-attacks by hardening and defending the cyber infrastructure. Every classified bit of U.S. information traveling across the global infrastructure is protected and encrypted by devices that NSA either certifies, designs, keys or approved for use.Technological advances have given data owners greater flexibility in accomplishing their business and missions; however, these advances come with a price because every connected device on interconnected global networks now becomes a potential access point for cyber adversaries. The hard truth is despite the fact the U.S. is stronger defensively than it has ever been the number of cyber threats facing the nation have never been greater.National Security System users require secure access to data anytime/anywhere in order to make timely mission decisions. NSA must be agile and flexible in order to meet the demand signals for rapid deployments of robust cybersecurity encryption solutions. The Agency has a long, proud history of designing/building/testing/fielding/supporting proprietary Government-Off-The-Shelf encryption solutions. It also has a history of strong public-private partnerships with commercial industry. Because of these enduring partnerships, NSA has been able to expand its suite of cybersecurity encryption solutions to include, where appropriate, the use of commercial products and technologies to protect classified National Security System information.Commercial Solutions for Classified (CSfC) is how NSA is executing its commercial cybersecurity encryption strategy whereby commercial products are architected together in precise ways to protect classified information. CSfC is founded on the principle that properly configured layered solutions can provide sufficient protection of classified data in a variety of different applications.The oral presentation will highlight CSfC’s many activities while also serving as a foundational introduction for those unfamiliar with the initiative. The target audience is everyone interested in learning how they can better protect their sensitive information. Below are the major topics covered during the oral presentation:
Using Human-Centered Design to Prototype Police Call for Help System

This paper illustrates the possibility of arriving at an innovative solution by using a human-centered design (UCD) method to create a call for help System for the police and sheriff's patrol officer in the line of duty. When the police officer is in urgent and dangerous situation, the system could be activated and get help from local police department. The solution was designed using a UCD work kit. Brainstorming generated patterns that led to possible solutions. The best and the most effective solution, a SOS belt, was prototyped using concept poster and sketching.
Design and implementation of ITS Architecture based on Big Data

Abstract With the progress of social economy and the rapid development of transportation industry, in the face of the rapid growth of urban road traffic data, this paper puts forward the design scheme of intelligent traffic analysis system based on Hadoop. In this paper, HBase distributed database is used to store urban road static RDF data, hive data warehouse is used to store urban road traffic data, and MapReduce programming model is used to store massive and heterogeneous urban road traffic data The urban road traffic data are analyzed, and the whole scheme is verified by the prototype system.