Reviewerly/exHarmony huggingface dataset:
Latest Advancements to the Industry-Leading EPDA Design Flow for Silicon Photonics: Invited Paper

Silicon photonics has emerged from research labs and is currently being used in a range of commercial products, with significant growth expected over the next few years. Current and future applications include transceivers for datacoms in datacenters and 5G, as well as a variety of sensors from medical diagnostics to LIDAR. Even longer-term applications such as artificial intelligence and quantum information technologies are in development. This growth is supported by a wide range of foundries who offer silicon photonic processes, as well as an ecosystem of design tools. We present an innovative design flow for electronic photonic design automation (EPDA) which fully supports industrial product development. This flow combines the best-in-class tools for schematic capture, co-simulation and implementation, combined with the leading photonic solvers for custom component optimization, parameter extraction and photonic compact model development. We discuss how it combines the maturity of EDA with requirements unique to photonic design.
MAPEAMENTO DOS PESQUISADORES QUE PUBLICARAM NO GRUPO DE TRABALHO -4 DA ASSOCIAÇÃO NACIONAL DE PESQUISA E PÓS-GRADUAÇÃO EM CIÊNCIA DA INFORMAÇÃO POR MEIO DA CIENTOMETRIA E SOCIOLOGIA DA CIÊNCIA

This research aims to understand the implicit mechanisms in the researchers' scientific knowledge generation, published papers, the scientific collaboration network formed from the social relations and the social position they occupy in the Field of Information Science.More specifically, the study aims to: identify the research elite publishing in the Working Group 4 -Information and Knowledge Management of the National Association for Research and Post-Graduation in Information Science (ANCIB); understand the mechanisms built to organize the network of scientific collaboration; base the Social Network Analysis from the Sociology of Pierre Bourdieu.As research procedure, data survey was carried out using a summary of the papers presented from 2013 to 2017 in Working Group 4 -Information and Knowledge Management.For the construction of the scientific collaboration network among the researchers and their co-authors, the Social Network Analysis was used.For the development of the last
CODE-BASED HYBRID CRYPTOSYSTEM: COMPARATIVE STUDIES AND ANALYSIS OF EFFICIENCY

In this paper the basic principles of construction and operation of McEliece and Niederreiter cryptosystems based on the use of error-correcting codes were considered. A new hybrid cryptosystem that combines the rules of encryption according to the above-mentioned schemes is proposed. Also, this paper presents the analysis and comparative studies from the standpoint of stability, the volume of public and private keys, length of ciphertext and relative speed of information transmission of the new proposed scheme and McEliece and Niederreiter cryptosystems. It is considered from an analytical point of view and with the help of graphic images. Comparative studies revealed that the hybrid cryptosystem retains the positive aspects of its predecessors, as well as allows us to increase the relative transmission rate with the preservation of the stability indicator to the classical and quantum cryptanalysis. One disadvantage is the increase in decoding time by adding information extracted as in Niederreiter scheme, but the increase in this indicator is not critical. Despite the demonstrated benefits, it remains open to all cryptosystems to reduce the amount of the used key data, which, in the case of quantum computers to maintain stability, still needs to be increased once.
Efficient Extended Diffie-Hellman Key Exchange Protocol

The multi party key exchange is a cryptographic method by which users exchange the shared secrets and generate a common key among themselves using some unique cryptographic algorithms. The cryptographic key exchange has the security threat while transmission over a network channel. Diffie-Hellman approach developed to overcome the problems related to key exchange. It completely changed the method of key exchange over a secured as well as an unsecured network. The algorithm is based on exponential modular calculations for exchanging of the shared secrets and generating common session key. The aim of this approach is for securely generating the common session key. This method dynamically and securely exchanges the keys between the group of members has been applied for group applications such as a distributed database, computing, and group calls. The major limitation of the Diffie-Hellman approach is that it is intensive in case of computation thus, increases the time complexity during the session key generation process. This can be a major problem in the key exchange among systems with a low configuration where a minor degradation in security is not a big problem. The proposed algorithm has similar steps to that of the Diffie-Hellman approach, and a new related scheme is used for sharing session key which overcome the time complexity. The proposed key exchange approach uses modular arithmetic equations to generate and exchange keys and is capable to transfer keys over an insecure network.
Age and level of education impact on expectancy and perceived similarity between virtual and real touristic environments

This paper focuses on the combination of 360-degree video and virtual reality for improving the touristic experience. Three scenarios were considered in this study: two 360-degree video visualizations, each one related to different touristic places, both presented in an immersive way, followed by an actual visit to those places. By comparing these situations, it was intended to determine the degree of perceived similarity between the virtual and the corresponding real sites, and to analyze if the users' expectancy was fulfilled. This research comprised a qualitative analysis using data collection based on questionnaires, which were applied to a sample consisted of 45 participants. The independent variables of the study were the participants' age and level of education. The results show no statistically significant impact between the two independent variables (users'age and level of education) and perceived similarity and users' expectancy. Our findings suggest that virtual tourism can act as an efficient promotion tool, considering that users' perceived destination image is not compromised regarding their age or level of education.
Keyword Spotting using Dynamic Time Warping and Convolutional Recurrent Networks

This paper proposes a method for keyword spotting, which first converts utterances to grayscale images via a modified Dynamic Time Warping (DTW) algorithm, and then splits the images into frames which are fed in sequence to a Convolutional Recurrent Deep Neural Network (CRDNN). DTW is employed because of its capability to accurately capture similarities between time sequences, while the neural network exploits the textural features of the DTW matrix for classification. We explore three alternative formulations of the DTW algorithm for extracting the similarity matrices, as well as three different conversion methods from the similarity matrix to a gray-scale image. As opposed to previous works, we employ a recurrent network to consider sequential information encoded in image segments. We perform several evaluations on the TIMIT corpus and find that the system reaches a detection performance of 95%.
Applying Academic Theory with Text Mining to Offer Business Insight : Illustration of Evaluating Hotel Service Quality

Now is the time for IS scholars to demonstrate the added value of academic theory through its integration with text mining, clearly outline how to implement this for text mining experts outside of the academic field, and move towards establishing this integration as a standard practice. Therefore, in this study we develop a systematic theory-based text-mining framework (TTMF), and illustrate the use and benefits of TTMF by conducting a text-mining project in an actual business case evaluating and improving hotel service quality using a large volume of actual user-generated reviews. A total of 61,304 sentences extracted from actual customer reviews were successfully allocated to SERVQUAL dimensions, and the pragmatic validity of our model was tested by the OLS regression analysis results between the sentiment scores of each SERVQUAL dimension and customer satisfaction (star rates), and showed significant relationships. As a post-hoc analysis, the results of the co-occurrence analysis to define the root causes of positive and negative service quality perceptions and provide action plans to implement improvements were reported.
Predicting Licenses for Changed Source Code

Open source software licenses regulate the circumstances under which software can be redistributed, reused and modified. Ensuring license compatibility and preventing license restriction conflicts among source code during software changes are the key to protect their commercial use. However, selecting the appropriate licenses for software changes requires lots of experience and manual effort that involve examining, assimilating and comparing various licenses as well as understanding their relationships with software changes. Worse still, there is no state-of-the-art methodology to provide this capability. Motivated by this observation, we propose in this paper Automatic License Prediction (ALP), a novel learning-based method and tool for predicting licenses as software changes. An extensive evaluation of ALP on predicting licenses in 700 open source projects demonstrate its effectiveness: ALP can achieve not only a high overall prediction accuracy (92.5% in micro F1 score) but also high accuracies across all license types.
ANALISA PREDIKSI INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN METODE ARIMA

Investment in the capital market every manager needs to analyze to make decisions so that the right target to produce profits in accordance with what is expected. For that, we need a way to predict the decisions that will be taken in the future. The research objective is to find the best model and forecasting of the composite stock price index (CSPI).&#x0D; Data analysis technique The ARIMA Model time series data from historical data is the basis for forecasting. Secondary data is the closing price of the JCI on July 16 2018 to July 16 2019 to see how accurate the forecasting is done on the actual data at that time.&#x0D; The results of the study that the best Arima model is Arima 2.1.2 with an R-squared value of 0.014500, Schwarz criterion 10.83497 and Akaike info criterion of 10.77973. Results of forecasting actual data are 6394,609, dynamic forecast 6387,551 selisish -7,05799, statistics forecas 6400,653 difference of 6,043909. For investors or the public can use the ARIMA method to be able to predict or predict the capital market that will occur in the next period.
Stethoscope: Crypto Phones with Transparent & Robust Fingerprint Comparisons using Inter Text-Speech Transformations

Crypto Phones are emerging apps aimed for end-to-end secure communications. To detect man-in-the-middle (MITM) attacks, traditional Crypto Phones rely upon end-users to verbally exchange and compare a short protocol fingerprint. This requirement is often found to be inconvenient by the users. Hence, most current apps do not mandate fingerprint validation, allowing the users to opt-out, completely disregarding security in favor of usability. Besides, speaking the fingerprints is not free of user errors, which may lead to rejection of benign sessions degrading the user experience. In this paper, we address these fundamental problems by introducing Stethoscope1, a new Crypto Phone model that removes the human user from the loop of fingerprint comparison by using text-to-speech and speech-to-text transformations. Stethoscope automatically performs two tasks on behalf of the user: (1) creating the fingerprint by incorporating a fingerprint speaking tool at the sender side, built on top of a limited-domain text-to-speech engine, and (2) decoding/comparing the fingerprint at the receiver side based on a robust speech-to-text engine. Like the traditional design, Stethoscope relies on the receiver to manually verify the sender's voice to detect sophisticated voice attacks. On the sender side, we design an automated fingerprint speaking tool based on a limited-domain text-to-speech system using reordering of words in a phonetically-distinct word dictionary previously spoken by the user. This tool asks the users to speak all the words in the fingerprint dictionary only once to train the system. On the receiver side, to decode the fingerprint, we design a robust speech-to-text transcription method. We evaluate the effect of automating the fingerprint creation, transfer, and comparison in the Stethoscope design against manual speaker verification with a user study. Our results show that Stethoscope provides a 0% false accept and 0% false reject rate for the fingerprint comparison, while offering a higher level of speaker verification performance compared to traditional Crypto Phones.
Vulnerable Road User Detection using YOLO v3

Detection and classification of vulnerable road users (VRUs) is one of the most crucial blocks in vision based navigation systems used in Advanced Driver Assistance Systems. This paper seeks to evaluate the performance of object classification algorithm, You Only Look Once i.e. YOLO v3 algorithm for the purpose of detection of a major subclass of VRUs i.e. cyclists and pedestrians using the Tsinghua – Daimler dataset. The YOLO v3 algorithm used here requires less computational resources and hence promises a real time performance when compared to its predecessors. The model has been trained using the training images in the mentioned benchmark and have been tested for the test images available for the same. The average IoU for all the truth objects is calculated and the precision recall graph for different thresholds was plotted.
Automatic Detection and Analysis of the “Game Hack” Scam

The “Game Hack” Scam (GHS) is a mostly unreported cyberattack in which attackers attempt to convince victims that they will be provided with free, unlimited “resources” or other advantages for their favorite game. The endgame of the scammers ranges from monetizing for themselves the victims time and resources by having them click through endless “surveys”, filing out “market research” forms, etc., to collecting personal information, getting the victims to subscribe to questionable services, up to installing questionable executable files on their machines. Other scams such as the “Technical Support Scam”, the “Survey Scam”, and the “Romance Scam” have been analyzed before but to the best of our knowledge, GHS has not been well studied so far and is indeed mostly unknown. In this paper, our aim is to investigate and gain more knowledge on this type of scam by following a data-driven approach; we formulate GHS-related search queries, and used multiple search engines to collect data about the websites to which GHS victims are directed when they search online for various game hacks and tricks. We analyze the collected data to provide new insight into GHS and research the extent of this scam. We show that despite its low profile, the click traffic generated by the scam is in the hundreds of millions. We also show that GHS attackers use social media, streaming sites, blogs, and even unrelated sites such as change.org or jeuxvideo.com to carry out their attacks and reach a large number of victims. Our data collection spans a year; in that time, we uncovered 65,905 different GHS URLs, mapped onto over 5,900 unique domains.We were able to link attacks to attackers and found that they routinely target a vast array of games. Furthermore, we find that GHS instances are on the rise, and so is the number of victims. Our low-end estimation is that these attacks have been clicked at least 150 million times in the last five years. Finally, in keeping with similar large-scale scam studies, we find that the current public blacklists are inadequate and suggest that our method is more effective at detecting these attacks.
Using a social platform as an internal communication tool: A case study

In 2017, the Karolinska Institutet University Library conducted a project to replace the existing Intranet with a new improved tool. At the start of the project, we assumed it would result in a new, improved version of the existing Intranet. However, the project group eventually decided to replace the original Intranet with a combination of three tools that we believed would better meet the library staff’s needs.
PARALLEL SOLUTION OF FEATURES SUBSET SELECTION PROCESS FOR HAND-PRINTED CHARACTER RECOGNITION

The existence of a huge amount of features for pattern recognition problems brings to the overloading of the training and exploitation steps of the recognition; also, highly correlated features affect the accuracy of the designed systems negatively.One of the most used ways for tackling this problem is the application of genetic algorithms for the solution of the binary optimization problems that appeared during the features subset selection process.In this paper was used parallel genetic algorithms for the selection of the most informative features in Azerbaijani hand-printed character recognition system by using opportunities of the distributed cluster computing.In this way after the given number of generations most appropriate features with the high recognition rate were selected from the features database.
ANALISIS KETAHANAN AIR DI KOTA TERNATE PROVINSI MALUKU UTARA

The biggest problem in Ternate City is availability of water and potential for natural disasters, because it is in the fire ring and climate in there is influenced by the tropical and seasonal climate. The purpose of this study is determine the water resistance in Ternate City for 20 th years until 2039. Water requirements are calculated by exponential method projections, the data based on population, industry, livestock and the area of agricultural land. Water availability debit data is based on water resources infrastructure data that has been available in there. Based on the results of the analysis, known that the total requirement of Ternate City in 2039 is 1.427 m3/ sec, total potential of mainstay discharge in 2039 is 43.139 m3/sec and total potention of dependable flow is 3 0.700 m /sec, so it can be concluded that the water demand in there is still not fulfilled to its full potential but has a great potential for reliable debits. So that, infrastructure development planning is needed in the form of as many as 98 pieces of reservoirs with a total reservoir of 5.67 million m3/sec spread across the largest watershed locations in several areas in Ternate City
A User Experience Study of Locomotion Design in Virtual Reality Between Adult and Minor Users

Virtual reality (VR) is an important new technology that is fundamentally changing the way people experience entertainment and education content. Due to the fact that most currently available VR products are one-size-fits-all, the user experience of the content interface and user interaction for children is not well understood compared to that for adults. In this study, we seek to explore user experience of locomotion in VR between healthy adults and healthy minors along both objective and subjective dimensions. We design the experiment where subjects complete a task of moving the body and touching underwater animals using VR controllers. The locomotion in VR is implemented using one of four different modalities, as well as using real-world walking without wearing the VR headset as the baseline. Our results show that physical body movement that mirrors real-world movement exclusively is the least preferred by both adults and minors. However, within the different modalities of controller assisted locomotion, there are variations between adults and minors for preference and challenge levels.
Robust pose estimation using Time-of-Flight imaging

We propose a computer vision algorithm for head pose estimation that is suitable for real time environments. Our solution is based on the depth information provided by a Time of Flight camera, image processing algorithms for facial landmarks detection and support vector machine classification. We study the effect of different factors including head pose angles, background reflective surfaces and computing duration. We identify an extended range of roll, yaw and pitch rotations angles for which the algorithm provides reliable estimates.
Building Simplification - A fabrication method based on Augmented Reality

Digital design techniques have improved significantly to enable designers to design with fewer limitations.However, the construction methods to fabricate these design proposals are still lagging behind due to a lack of skilled labour, material constraints, and the effects of gravity.Augmented reality has been developed in recent years, and this allows users to impose 3D virtual objects onto the real world.This essay will thus discuss whether augmented reality can guide unskilled labourers to complete complex work, thus overcoming one of the constraints on fabrication for complicated construction.This essay covers the results of three augmented reality tests using a Kinect device, a projector, and Microsoft HoloLens.It aims to show that augmented reality can indeed be used to guide unskilled labourers during construction to narrow the gap between complex design methods and basic construction techniques.The results indicate that augmented reality can guide such fabrication and thus improve construction methods.
Archeologia e Calcolatori: un’esperienza pionieristica nel mondo dell’Open Access e dell’Open Science

Online open access circulation of the journal ‘Archeologia e Calcolatori’ started in 2005. International standards developed within the Open Archives Initiative paradigm immediately offered fascinating solutions to disseminate metadata describing the journal’s content. The most relevant protocol for Open Archives implementation is OAI-PMH. Several software applications to support OAI-PMH have been proposed by different institutions and some enjoyed brilliant success. However, in certain situations the deployment of an OAI-PMH conformant repository remained problematic. For small research institutions and university departments, most of the existing OAI applications seemed difficult to implement. In this paper, the author recalls the main steps that guided the journal towards a simplified approach to the OAI implementation, one suited to small and medium-sized archives, creating a system operating now for 15 years.
A Study on Understanding of Visitor Needs in Art Museum: Based on Analysis of Visual Perception Through Eye-Tracking

This study aims to examine the art museum experience of visitors in detail through eye tracking in the aspect of the visitor-centered approach, which is important in the contemporary art museum. To achieve this goal, we conducted the eye-tracking experiment and in-depth interview to grasp the interest and needs of visitors. We suggest the possibility of deriving their interests and needs by studying the gaze data (e.g. duration and the number of fixations) of the visitors in the museum.