Reviewerly/exHarmony huggingface dataset:
Культура сетевых коммуникаций цифрового поколения в контексте современных концепций цифровой грамотности (на материалах онлайновой фокус-группы со студентами)

The concepts of digital literacy prevail in the modern discourse on media and information literacy. The authors of these concepts (P. Gilster, H. Jenkins, R. Hobss, D. Belshaw, I. Huvila, and others) consider general cultural, social and communicative meta-competences critical for the formation of a literate person of the digital age. S. Tomas introduces the term “transliteracy” and suggests that it is important to teach the digital generation how to create texts in different types of media. How can these meta-competencies be specified in the culture of digital generation network communications? We found it out at a focus group with students of Siberian universities with the high level of digital competence and experience in creating unique texts in new media. As a result, we found out that the representatives of the digital generation are not only able to assess their technological skills, but also reflect on how they use these skills to solve various communication, research, and creative tasks. It makes them responsible actors of the culture of network communications.
Distributed ledger technology in supply chainsAn information processing view

PurposeLately, supply chain practitioners and academics have shown increasing interest in supply chain transparency (SCT). And, at the same time, both parties turned their attention to distributed ledger technology (DLT) and its potential for supply chain management (SCM) and in particular SCT. However, little is known why organizations seek to enhance SCT with DLT solutions and what capabilities are required for these solutions. Consequently, research and practice lacks an indication how organizations can build up these capabilities. This paper seeks to address these gaps.Design/methodology/approachIn order to explore the drivers to use DLT solutions to enhance SCT, to identify the required capabilities and to answer how organization can build up these capabilities, the authors follow an inductive multiple case study approach. The authors selected five cases in the diamond industry, as these are the pioneers to implement DLT to enhance SCT.FindingsDrawing on information processing theory (IPT), the cases demonstrate that organizations seek to process information across company boundaries via DLT due to a lack of transparency in the industry. In order to adopt and integrate DLT-enhanced SCT solutions, organizations have to build up organizational and interorganizational capabilities. Both types of capabilities require organizational and collaborative effort.Research limitations/implicationsThe study reveals that organizations have to overcome challenges of information processing capabilities (IPC) not only on an organizational level but also on an interorganizational level.Practical implicationsThe study underlines the importance of collaborative effort when seeking to enhance SCT via DLT solutions.Original/valueThis is one of the first studies to explore DLT-enhanced SCT solutions based on empirical data and identify the required capabilities for successful adoption and integration in SCM.
Optimization of Space-time Bandwidth for Shearography

We propose an approach where temporal as well as the spatial phase shifts are utilized simultaneously in order to reduce the number of shots and also the carrier frequency currently employed in digital shearography.
A PLATFORM FOR DETECTION AND RESOLUTION OF CONFLICTS AMONG MULTIPLE NORMS IN MAS (MULTI-AGENT SYSTEMS)

In open MAS, norms are being used to regulate the behavior of the autonomous, heterogeneous and independently designed agents. Norms describe the behavior that can be performed, must be performed, and cannot be performed in the system. One of the main challenges on developing normative systems is that norms may conflict with each other. Norms are in conflict when the fulfillment of one norm violates the other and vice-versa. In previous works, the conflict checkers consider that conflicts can be detected by simply analyzing pairs of norms. However, there may be conflicts that can only be detected when we analyze several norms together. This work present a complete approach for conflict detection and conflict resolution among pairs and multiple norms. The approach for conflict detection is divided into three steps in order to smooth the computational since the problem is intrinsically exponential (SHOHAM; TENNENHOLTZ, 1995). The approach for conflict resolution apply famous strategies found in literature to rewrite or remove conflicting norms. The paper describes a tool, named MuNoCC (Multiple Norms Conflict Checker Tool), that integrate different screens for conflict detection and resolution.  This approach works as a basis to assist MAS literature, defining norms formally, checking conflicts among pairs and multiple norms and resolving the conflicts found.
On the uncertainty product of spherical functions

The uncertainty product of a function is a quantity that measures the trade-off between the space and the frequency localization of the function. Its boundedness from below is the content of various uncertainty principles. In the present paper, functions over the n-dimensional sphere are considered. A formula is derived that expresses the uncertainty product of a continuous function in terms of its Fourier coefficients. It is applied to a directional derivative of a zonal wavelet, and the behavior of the uncertainty product of this function is discussed.
Differential phase metrology using a common-path image inversion interferometer

We use a common-path image inversion interferometer to measure a spatially varying phase. Our system does so without splitting beam paths, offering a practical advantage over traditional interferometric methods.
A Policy Editor for Semantic Sensor Networks.

An important use of sensors and actuator networks is to comply with health and safety policies in hazardous environments. In order to deal with increasingly large and dynamic environments, and to quickly react to emergencies, tools are needed to simplify the process of translating high-level policies into executable queries and rules. We present a framework to produce such tools, which uses rules to aggregate low-level sensor data, described using the Semantic Sensor Network Ontology, into more useful and actionable abstractions. Using the schema of the underlying data sources as an input, we automatically generate abstractions which are relevant to the use case at hand. In this demonstration we present a policy editor tool and simulation on which policies can be tested.
What next for quantum computers?

Google appears to have reached “quantum supremacy”, but there is still a long way to go before the technology is useful, reports Chelsea Whyte
Distorted object recognition and identification based on Krawtchouk moments

A reference-free criteria based on Krawtchouk moments is proposed, which shows outstanding robustness against distortion of different kinds, being able to distinguish similar targets with minor difference even when severe distortions have made images indistinguishable.
Rancang Bangun Aplikasi Pencarian Bengkel Dan Cuci Motor Terdekat Berbasis Mobile

As the number of motorcycles users are increasing in Indonesia, so is the problems of the motorcycles that they face. On the other hand, the user of the smartphone is increasing as well. Based on that matters, we can develop an application in order to help the user to cope with their problem easier. The application can help the user to find the nearest garage and motorcycles wash, in order to solve the problems, such as dirty motorcycle, flat tire, the tire burst, oil change, etc. This application was designed to provide some information about the nearest garage, the route to the garage, reveal the comments and send a message to the owner of the garage. Meanwhile, the owner of the garage can see the comments about their garage, receive an order and see the customer location. The testing technique which was used in this research were blackbox and MOS testing. The result of blackbox testing showed that all features can be run as planned, meanwhile, the MOS testing showed the customer respondents value was 84,83% and the owner respondents value was 84,77%.&#x0D; Keywords: Garage location, Motorcycles, Problems of the Motorcycles, Order Service, MOS Testing.
A Analysis Of Mozila Firefox Software Estimation With COCOMO II

In working on a software project, the success of the project must begin with proper planning. If the planning is bad, it will cause project failure. Project failure can be in the form of swelling the cost of the project or project not being completed according to the time specified at the beginning of the plan. Extension of time can result in project cost overruns. To reduce the risk of swelling project costs, the right cost estimation is needed. Estimated project costs are estimates of time and costs including the number of employees working on the project. The cost estimation in this study uses the COCOMO II method. A software is said to be successful if it can be completed in a timely manner. With the appropriate budget and produce software of known quality. Mozila is a browser that is widely used to search for a website but doesn't know much about estimation the cost of making Mozilla therefore using COCOMO II can provide information on how to calculate the estimated cost using COCOMO II and the business of making software in accordance with that method.
ANALISIS PERBANDINGAN PERFORMANSI PENGAMANAN DATA ENKRIPSI DAN DEKRIPSI CITRA DIGITAL BERBASIS TRANSMISI WIRELESS

Data exchange itself is very important to be carried out to provide information in a valid and accurate manner. To know the message widely using text and voice media. Because they are still considered too weak in terms of morality, such as being vulnerable to manipulated data content in the media, the image media is used because it is considered to have a good level of security and is safe compared to the previous media. The media image is needed because it has a much better background than the previous media. But a digital image can be easily replaced, manipulated, removed some objects or shapes, copied, even misused in terms of function and form. Therefore an analysis is made to determine an accurate system and can be implemented on digital image media. The purpose of testing this system is to find out how accurate and safe some of the methods that will process the message cannot be read by unauthorized parties and find out the quality of the image media as an insertion medium in securing the secret message. In addition to knowing whether the process of sending data from server to client affects the performance of RAM software used and the quality of the network during the delivery process. Security data analysis here uses several cryptographic methods, namely for symmetrical keys namely caesar cipher and blowfish and for asymmetrical methods namely elgamal and least significant bit (LSB), it's just that LSB is here as a process of steganography. And the implementation of the security data analysis system here uses visual studio 2017 community to determine quality and accuracy of cryptographic methods and steganography in safeguarding image data, the memory capacity and the speed of delivery network operations using wireshark. From the test results, caesar cipher methods obtained percentage of 100% and blowfish methods obtained percentage of 36.36%, but Blowfish was still better in terms of accuracy, while for elgamal varied between 27.27% and 81.82%, but the method this is much safer than the previous method. The lowest implementation of steganography in the elgamal method was 63.64%. For communication between PCs using RAM, the highest results is the elgamal method in PNG Grayscale format is 159 MB and the resulting QoS are still categorized very well according to TIPHON standards.
PENINGKATAN KEMAMPUAN MEMBACA MELALUI PERMAINAN KARTU HURUF PADA SISWA KELAS I SD NEGERI 05 SIALANG KECAMATAN KAPUR IX KABUPATEN LIMA PULUH KOTA

Based on observations made in class I of Sialang 05 Elementary School, Kapur IX District, Lima Puluh Kota Regency, it appears that the reading ability of class I students is low. This study aims to improve reading skills through the first class Letters Card game of Sialang 05 Elementary School, Kapur IX District, Lima Puluh Kota Regency. This research is a classroom action research with stages of planning, implementation, observation, and reflection. This research was conducted in 2 cycles. Data collection methods used in this study are observation and performance methods. The collected data is then analyzed descriptively quantitatively. The results of the study showed that through letter card games able to improve the reading ability of Grade 1 students at SD Negeri 05 Sialang sub-district of Limestone IX District of Lima Puluh Kota. Therefore the use of letter cards in learning in class I needs to be improved, especially in an effort to improve reading skills.
FocalNet - Foveal Attention for Post-processing DNN Outputs

This paper presents FocalNet - an iterative information extraction algorithm that uses the concept of foveal attention to post-process the outputs of Deep Neural Networks (DNNs) by performing variable sampling of the input/feature space. FocalNet is integrated into an existing task-driven deep learning model without modifying the weights of the network. Layers, at which to perform foveation are automatically selected using a data-driven approach. We apply FocalNet to the task of object detection using a state of the art convolutional detector, RFCN ResNet-101. On the PASCAL VOC 2007 dataset, we are able to achieve a mAP increase of 3.7%. On the MS COCO 2017 validation dataset we achieve an increase in mAP by 0.3%. Further, a higher increase in mAP is observed for a computationally efficient detector (1.7% for Faster R-CNN with ResNet50). In additon to object detection, we show effectiveness of FocalNet to the problem of single object tracking with a 0.5% increase in average IoU on the MOT17 dataset over a simple tracking by detection approach using DNNs.
Stand-alone orthogonally polarized entangled source for quantum applications at telecom wavelength (Conference Presentation)

Photon entanglement has appeared to play a crucial role in the foundation of quantum physics and in the ever-increasing requirements of quantum information processing, quantum communication, quantum sensing and quantum computing. Thus, the industrial development and the characterization of practical entangled photon sources at telecom wavelengths are key element for the deployment of emerging quantum applications, such as Quantum Key Distribution. The photon source is based on a 775 nm pumped type II Periodically Poled Lithium Niobate wave guide (PPLN_WG) designed for generation of orthogonally polarized photon pairs at 1550 nm. Picometer tunability of the converted central wavelength is achieved by using an accurate temperature control of both the PPLN_WG and the laser diode. All optical and electronics elements are embedded in a compact module. This practical photon source is driven by a USB communication port compatible with computer. The main characteristics of the photon source, Coincidence-to-Accidental-Ratio (CAR), brightness, bi-photon spectrum, heralded efficiency, purity, and indistinguishability are measured by using integrated optical benches and a 2-channels very-low-noise InGaAs single photon avalanche counters (G-SPAD). The proposed photon source measurements protocol is also available for the characterization of other photon sources technologies, such as for the Quantum Dots and semiconductor photon sources. We performed two experimental Bell inequality violations by creating polarization entanglement or by using the natural frequency entanglement of our source. Violation by more than five standard deviations Bell inequalities with our setups demonstrate that our photon source is a promising tool for the realization of various distances quantum information experiments.
Investigating the Newly Graduated StudentsExperience after University

Today’s labor market is teeming with software development jobs, and employeesare needed more than ever. With this statement, one would believe it is easy fora newly graduated student to start their ...
Klasifikasi Genre Musik Menggunakan Metode Mel-Frequency Cepstrum Coefficients dan K-Nearest Neighbors Classifier

In the world of music, music has several types of genre genres that can be grouped, there are music genre pop, rock, blues, slow, jazz, metal, dangdut and many more. And for each person must have a genre favorite that is different from one another, but to distinguish it does not need to play music files one by one especially if the number of music files is a lot. Therefore, computer software is needed to distinguish each of these genres in order to make it easier for users to distinguish and group the types of music according to their wishes automatically. By using the MFCC and KNN methods as a classification solution to classify several types of genre streams can be easily resolved. The results achieved from this study reached 52,4% with a K = 13 as the nearest neighboring point.
Mining Discriminative Visual Features Based on Semantic Relations.

In this paper, we present an embedding-based framework for fine-grained image classification so that the semantic of background knowledge of images can be internally fused in image recognition. Specifically, we propose a semantic-fusion model which explores semantic embedding from both background knowledge (such as text, knowledge bases) and visual information. Moreover, we present a multi-level embedding model extract multiple semantic segmentations of backgroud knowledge. Experimental results on a challenging benchmark CUB-200-2011 dataset verify that our approach outperforms state-of-the-art methods.
An Accelerated Hierarchical Approach for Object Shape Extraction and Recognition

We present a novel automatic supervised object recognition algorithm based on a scale and rotation invariant Fourier descriptors algorithm. The algorithm is hierarchical in nature allowing it to capture the inherent intra-contour spatial relationships between the parent and child contours of an object by building a tree-structure of the top-level contours that make the distinctive features of the object to be recognized. A set of distance metrics are combined to measure the similarity between two objects under the hierarchical model. To test the algorithm, a diverse database of shapes is created and used to train standard classification algorithms, for shape-labeling. The implemented algorithm takes advantage of the multi-threaded architecture and GPU efficient image-processing functions present in OpenCV wherever possible, speeding up the running time and making it efficient for use in real-time applications. The technique is successfully tested on common traffic and road signs of real-world images, with excellent overall performance that is robust to low-to-moderate noise levels.
Optical Attenuation without Absorption

When dealing with statistics, postselection and heralding are known to produce counterintuitive results. By monitoring the state of an ensemble of two-level atoms and considering only the events where the atoms did not get excited, it is theoretically shown that one could induce abnormally large attenuation, whereas the opposite would be expected.
Multi-perspective Feature Generation Based on Attention Mechanism

Selecting features that represent a particular corpus is important to the success of many natural language processing tasks. However, the previous attention-based work only focused on feature augmentation in the lexical level, lacking the exploration of feature enhancement in the sentence level. In this paper, we exploit a novel feature generation method for information retrieval, denoted by Multi-perspective Feature Generation Network (MFGN). We first add features at sentence level from multiple perspectives to enhance sentence representation, then the word level features make second interactive confirmation from two perspectives. After two-level processing for different granularity characteristics, the model complete the retrieval process. It is more in line with the cognitive process of human beings to grasp the overall meaning of sentences and then carefully study the potential meaning of specific words. In the process of feature generation and extraction, text interacts from multiple perspectives, takes into account the information of text itself and the information of text interaction in different levels and multiple granularities. Different kinds of characteristics are distilled according to specific tasks, enhancing the practicability and robustness of the model. MFGN relies solely on the text itself, requires no external knowledge or feature engineering. Experimental results show that our approach outperforms previous work on multiple well-known Retrieval-based question answering datasets. Through the analysis of the experiments, we prove that MFGN provides excellent retrieval and interpretative abilities.
Media Pembelajaran Pengenalan Huruf Alfabet SertaBilangan Dasar Untuk Anak Tuna Rungu Dan WicaraKelas 1 SDLB Mitra Amanda Boyolali

Mitra Amanda Special School (SLB) in Sanggrahan Hamlet, Trayu Village, BanyudonoSubdistrict, Boyolali Regency accommodates and educates children with special needs,one of them is deaf children. This study aims to design building learning mediaapplications to recognize alphabet letters and basic numbers for deaf children and speechclass 1 SDLB Amanda Boyolali partners that are adjusted to the 2013 school curriculum.Application development methods include: Data analysis, Asset Making, StoryboardMaking and Development Process application. Data analysis by conducting interviewsdirectly with teachers who teach deaf students in class 1 of the SLB. Making assets withCorelaw application, assets are images of application interfaces. Storyboard is a sketchdrawing that is used as a plan to show visually how the action of a story takes place. Theprocess of developing applications with Construct 2 on a Core i.3 laptop - Acer AspireE1-471, then the application was changed to an android version using PhoneGhapsoftware so that it can be operated on an Android mobile. The results of this study are inthe form of learning media applications for the introduction of alphabet letters and basicnumbers for deaf children and class 1 SDLB Mitra Amanda Boyolali speech. Testing theapplication with several methods, namely: Testing with blackBox shows that all buttonsfunction properly, Testing on smartphones and desktops where the application can runwell and smoothly, and testing through questionnaires distributed to deaf students,teachers and parents / guardians of students Amanda Mitra SLB obtained from theresults of the questionnaire data that this application is interesting and useful by showingthe results of an average percentage of 80.9%Keywords: Alphabet, Deaf Children, Learning Media, SDLB
Central Embeddings for Extractive Summarization Based on Similarity

In this work we propose using word embeddings combined with unsupervised methods suchas clustering for the multi-document summarization task of DUC (Document Understanding Conference) 2002. We aim to find evidence that semantic information is kept in word embeddings and this representation is subject to be grouped based on their similarity, so that main ideas can be identified in sets of documents. We experiment with different clustering methods to extract candidates for the multi-document summarization task. Our experiments show that our method is able to find the prevalent ideas. ROUGE measures of our experiments are similar to the state of the art, despite the fact that not all the main ideas are found; as our method does not require annotated resources, it provides a domain and language independent way to create a summary.