Reviewerly/exHarmony huggingface dataset:
Research on Side-channel Attack Based on Stochastic Model with Lower Leakage

Abstract Cryptographic algorithm as an important means to ensure information security transmission has been widely concerned, but as the carrier of cryptographic algorithm, the security of encryption equipment is easy to be ignored. With the wide application of encryption equipment in modern society, the existence of side channel analysis technology is a great threat to information security. Stochastic approach (SA) is a method to deal with side-channel attack, based on many experimental studies, combined with Chebyshev filter, it can improve the accurate for attacking and signal to ratio.
Energy-Efficient Resource Management for Federated Edge Learning with CPU-GPU Heterogeneous Computing

Edge machine learning involves the deployment of learning algorithms at the network edge to leverage massive distributed data and computation resources to train artificial intelligence (AI) models. Among others, the framework of federated edge learning (FEEL) is popular for its data-privacy preservation. FEEL coordinates global model training at an edge server and local model training at edge devices that are connected by wireless links. This work contributes to the energy-efficient implementation of FEEL in wireless networks by designing joint computation-and-communication resource management ($\text{C}^2$RM). The design targets the state-of-the-art heterogeneous mobile architecture where parallel computing using both a CPU and a GPU, called heterogeneous computing, can significantly improve both the performance and energy efficiency. To minimize the sum energy consumption of devices, we propose a novel $\text{C}^2$RM framework featuring multi-dimensional control including bandwidth allocation, CPU-GPU workload partitioning and speed scaling at each device, and $\text{C}^2$ time division for each link. The key component of the framework is a set of equilibriums in energy rates with respect to different control variables that are proved to exist among devices or between processing units at each device. The results are applied to designing efficient algorithms for computing the optimal $\text{C}^2$RM policies faster than the standard optimization tools. Based on the equilibriums, we further design energy-efficient schemes for device scheduling and greedy spectrum sharing that scavenges "spectrum holes" resulting from heterogeneous $\text{C}^2$ time divisions among devices. Using a real dataset, experiments are conducted to demonstrate the effectiveness of $\text{C}^2$RM on improving the energy efficiency of a FEEL system.
Perancangan Multi Node Web Server Menggunakan Docker Swarm dengan Metode Highavability

Container-based virtualization is very popular among programming development in a lightweight virtualization because where the Linux kernel can divide resource-using containers to prevent uninterrupted performance between And as a burden divider in tackling the many incoming bandwidth. One of the most commonly used container-based virtualization is Docker. Docker itself is an open source software that can be changed to your liking. Docker containers can be used for clustering Web servers. It aims to reduce "a single point of failure" (SPOF) in a Web server. However, arranging a lot of containers is very complicated, but Docker has an engine to set it up called Docker Swarm. With it in the NGINX management help so that it can cause the resource between hosts is not divided on average. Therefore the research aims to distribute Web server traffic across the host with loadbalancing based on time-based monitoring and failover resources. By winning the low resources or resources used by Docker in the operation of an application that can be virtualized only what is needed
A Device Data EvaluationSystemBased on Hierarchical Weighting Algorithm

Abstract The more applications are supported by a dccloud, the higher quality are required on the fundamental data. This paper developed an evaluation system based on hierarchical weighting decision-making to evaluate the data quality of devices on dccloud. This evaluation system could also evaluate the satisfaction of applications on various devices, and the overall relationship among devices to improve data quality of device models.
Learning End-to-End Action Interaction by Paired-Embedding Data Augmentation

In recognition-based action interaction, robots' responses to human actions are often pre-designed according to recognized categories and thus stiff. In this paper, we specify a new Interactive Action Translation (IAT) task which aims to learn end-to-end action interaction from unlabeled interactive pairs, removing explicit action recognition. To enable learning on small-scale data, we propose a Paired-Embedding (PE) method for effective and reliable data augmentation. Specifically, our method first utilizes paired relationships to cluster individual actions in an embedding space. Then two actions originally paired can be replaced with other actions in their respective neighborhood, assembling into new pairs. An Act2Act network based on conditional GAN follows to learn from augmented data. Besides, IAT-test and IAT-train scores are specifically proposed for evaluating methods on our task. Experimental results on two datasets show impressive effects and broad application prospects of our method.
More than 80% of sequentially bilaterally implanted CI-patients are not treated sufficiently during the bimodal phase

Introduction In the bimodal phase between the two implantations, patients with sequential bilateral CI had shown a worse speech intelligibility than expected according to the literature. Therefore, the course of rehabilitation of this patient group was analyzed in more detail.
차별화된 협동로봇 형태 디자인 개발에 관한 연구 (형태분석법 적용 가능성을 중심으로)

Collaborative Robot (Cobot) that can collaborate with humans by fusion with many advanced technologies among industrial robots in the industrial field are attracting attention. In this study, the engineers of Small and Medium Enterprises can directly participate in the cobot design, and ultimately, the possibility of deriving the shape design of the differentiated cobot was studied. The method applied to derive the shape design of differentiated cobot is ‘Morphological Analysis’. First, the design elements of the form of cobots were derived as ‘Link’ and ‘Joint’. In addition, by analyzing the image form of the Link and Joint of the existing cobot, a new form element of the Link and Joint was proposed. In order to quantitatively identify the most discriminating cobot shape design, FGI (Focus Group Interview) was conducted to derive image types of 4 Link and 3 Joint. Then, the most important ‘Shape Combination’ was carried out in morphological analysis, and 12 new cobot shape designs were drawn. Through this, the applicability of the morphological analysis method in the derivation of differentiated cobot shape design was examined.
Comparing Maintainability Index, SIG Method, and SQALE for Technical Debt Identification

There are many definitions of software Technical Debt (TD) that were proposed over time. While many techniques to measure TD emerged in recent times, there is still not a clear understanding about how different techniques compare when applied to software projects. The goal of this paper is to shed some light on this aspect, by comparing three techniques about TD identification that were proposed over time: (i) the Maintainability Index (MI), (ii) SIG TD models, and (iii) SQALE analysis. Considering 20 open source Python libraries, we compare the TD measurements time series in terms of trends and evolution according to different sets of releases (major, minor, and micro), to see if the perception of practitioners about TD evolution could be impacted. While all methods report generally growing trends of TD over time, there are different patterns. SQALE reports more periods of steady states compared to MI and SIG TD. MI is the method that reports more repayments of TD compared to the other methods. SIG TD and MI are the models that show more similarity in the way TD evolves, while SQALE and MI are less similar. The implications are that each method gives slightly a different perception about TD evolution.
Perancangan Keamanan Server Linux Dengan Metode Hardening Pada Layer 1 dan Layer 7

Many person or institutions are still not aware of security on a server, not only rely on IDS and IPS applications and some firewall applications that we can easily find through internet networks. Special security handling is required on servers that are not related to third-party applications. The security design can be implemented through kernel configuration and tweaks that can be done by relying on the default application of an operating system. These applications are very common and can be found in almost all types of Linux server distributions. And there are still many people who do not maximize the security provided by the BIOS (Basic Input Output System) so that the operating system that has been installed and the data stored therein can be easily accessed by parties who are not responsible. Than as a preventive measure so that the data stored can not be accessed haphazardly by people who are not responsible, provided encryption and the sharing of system files that will be installed on the server. In the security steps for account access, the password that is created will be expired and the user cannot use the old password that he has used before
STUDYING THE PHONOLOGY OF THE OLŮKŮMI, IGALA, OWÉ AND YORŮBA LANGUAGES: A COMPARATIVE ANALYSIS.

This study presents a comparative analysis of the phonological systems of the Yorůbá, Owé, Igala and Olůkůmi languages of the Defoid language family of Benue Congo. Data were collected from native speakers using the Ibadan Four Hundred Word List of Basic Items. Using discovered common lexemes in the languages, the classification of the languages sound systems and syllable systems are carried out in order to determine the major patterns of differences and similarities. Some major sound changes were discovered in the lexical items of the languages. The systematic substitutions of sounds also constitute another major finding observed in the languages. It was established in this study that there exists a very strong relationship among these languages. The languages are found to be mutually unintelligible except for Owé that has a degree of mutual intelligibility with Yoruba. The paper concludes that the major reason for divergence is language contact.
Agricultural Expenditures and Food Security: Evidence from Sub Saharan African Countries

This paper sets out to investigate the effects of agricultural expenditures on two dimensions of food security in Sub Saharan Africa from 2000-2016. The Feasible Generalized Least Square (FGLS) econometric technique was applied on data from World Development Indicator, Regional Strategic Alliance and Knowledge Support System (ReSAKSS), the World Governing Indicator, the African Development Indicators, the Food and Agricultural Organisation (FAO) data bases. Our results depicted that public agricultural expenditure has negative and significant effects on food availability and utilization while domestic private agricultural expenditure and human capital foster both dimensions of food security. Foreign aid for agriculture has no effects on food availability but promotes food utilization while economic infrastructure promotes food availability but the effects on food utilization are positive and not significant. On the basis of the results, we recommend that SSA African government should increase the size of public agricultural expenditure, increase the level of economic infrastructures so as to crowd in private agricultural investment, lobby for more foreign aid for agriculture, improve the quality of institutions and design different policies to target different dimensions of food security.
Unsupervised Shape Normality Metric for Severity Quantification

This work describes an unsupervised method to objectively quantify the abnormality of general anatomical shapes. The severity of an anatomical deformity often serves as a determinant in the clinical management of patients. However, experiential bias and distinctive random residuals among specialist individuals bring variability in diagnosis and patient management decisions, irrespective of the objective deformity degree. Therefore, supervised methods are prone to be misled given insufficient labeling of pathological samples that inevitably preserve human bias and inconsistency. Furthermore, subjects demonstrating a specific pathology are naturally rare relative to the normal population. To avoid relying on sufficient pathological samples by fully utilizing the power of normal samples, we propose the shape normality metric (SNM), which requires learning only from normal samples and zero knowledge about the pathology. We represent shapes by landmarks automatically inferred from the data and model the normal group by a multivariate Gaussian distribution. Extensive experiments on different anatomical datasets, including skulls, femurs, scapulae, and humeri, demonstrate that SNM can provide an effective normality measurement, which can significantly detect and indicate pathology. Therefore, SNM offers promising value in a variety of clinical applications.
Proposed Model for Feature Extraction for Vehicle Detection

A feature is a prominent interest point in an image that can be used for a different task processing of image besides computer vision based on processes for object recognition. The features could be extracted by mathematical models that detect deep variations in texture, detect edges, or color. The selected features must have global definition within the defined problem vehicle detection. The focus of this paper is on detection of vehicle, Extraction of Region of Interest for the feature which is represented globally their module might produce a model intended for encoding of images’ features dependency technique can be applied. In this paper, We offer an extremely robust, capable, method aimed at creation of image feature vector for vehicle detection model system with both feature extraction also global feature representation method for both inter classes sameness and also the intra-class variation, thus to overcome the problem of multiplicity and ambiguity issues.
PENERAPAN METODE HILL CLIMBING UNTUK MENDIAGNOSA PENYAKIT GANGGUAN SARAF BERBASIS ANDROID

This research intend to apply Hill Climbing method to system for diagnose nervous disorders by making an application using android programming. In this system there is symptoms of nervous diseases data which the authors get directly from the results of interviews with a neurologist in the place where author doing research. Hill Climbing method is used to look for possible diseases of nervous disorders by observing the symptoms experienced by the user. The results of the implementation of the system by applying Hill Climbing method to diagnose nervous disorders showed that this method can provide the result of temporary diagnosis in the form of early information about the possibility of disease which suffered by the user.
Методическая работа кафедры социологии БГУ

The article presents the main directions of the methodical work at the department of sociology of the Belarusian State University: development and approval of educational program documentation; introduction of distance learning; use of innovative approaches and methods for teaching academic disciplines; participation of the teaching staff in scientific-methodical conferences; cooperation with personnel customers. It is noted that the most important trend of higher education is the strengthening of the practice-oriented training of specialists. The issues of formation of universal and professional competences of students in higher education institutions are actualized.
An Approach to Explanations for Public Radio Recommendations

Explanations are a key concept of public-service remits. For their linear program, public broadcasters regularly report on how they reflect diversity and balance in their program. For personalized public media, however, explanations must be different, as not one, but thousands of individual playouts have to be explained. We propose an approach how to design explanations for content-based radio recommendations based on word embedding approaches and evaluate the acceptance of our explanations with interviews of test listeners. As a result, we reveal a paradox-test listeners appreciate to have explanations, but at the same time do not intend to use the explanation feature often.
Trajectory Planning for Cooperative Autonomous Valet Parking

This paper presents the concepts and implementation of an automated valet parking algorithm with major focuson the trajectory planner and its cooperation with a parking management system. Trajectory planner approachesfor parking and autonomous driving are explained and validated with simulation and experimental tests.
World-Consistent Video-to-Video Synthesis

Video-to-video synthesis (vid2vid) aims for converting high-level semantic inputs to photorealistic videos. While existing vid2vid methods can achieve short-term temporal consistency, they fail to ensure the long-term one. This is because they lack knowledge of the 3D world being rendered and generate each frame only based on the past few frames. To address the limitation, we introduce a novel vid2vid framework that efficiently and effectively utilizes all past generated frames during rendering. This is achieved by condensing the 3D world rendered so far into a physically-grounded estimate of the current frame, which we call the guidance image. We further propose a novel neural network architecture to take advantage of the information stored in the guidance images. Extensive experimental results on several challenging datasets verify the effectiveness of our approach in achieving world consistency - the output video is consistent within the entire rendered 3D world. https://nvlabs.github.io/wc-vid2vid/
Identification and Citation of Digital Research Resources

Environmental research infrastructures are often built on a large number of distributed observational or experimental sites, run by hundreds of scientists and technicians, financially supported and administrated by a large number of institutions. It becomes very important to acknowledge the data sources and their providers. There is also a strong need for common data citation tracking systems that allow data providers to identify downstream usage of their data so as to demonstrate their importance and show the impact to stakeholders and the public. This chapter highlights identification and citation in environmental RIs, reviews available technologies and develops common services for these operations. This chapter presents a suggested common system design for Identification and Citation, as well as an outline for negotiations and discussions with publishers and other actors in the scholarly data management and curation world.
Dynamic Relational Inference in Multi-Agent Trajectories

Inferring interactions from multi-agent trajectories has broad applications in physics, vision and robotics. Neural relational inference (NRI) is a deep generative model that can reason about relations in complex dynamics without supervision. In this paper, we take a careful look at this approach for relational inference in multi-agent trajectories. First, we discover that NRI can be fundamentally limited without sufficient long-term observations. Its ability to accurately infer interactions degrades drastically for short output sequences. Next, we consider a more general setting of relational inference when interactions are changing overtime. We propose an extension ofNRI, which we call the DYnamic multi-AgentRelational Inference (DYARI) model that can reason about dynamic relations. We conduct exhaustive experiments to study the effect of model architecture, under-lying dynamics and training scheme on the performance of dynamic relational inference using a simulated physics system. We also showcase the usage of our model on real-world multi-agent basketball trajectories.
APLIKASI AUGMENTED REALITY PADA BUKU CERITA BILINGUAL “THE SHRIMP AND THE CRAB”

Abstrak : Tujuan dari penelitian ini membahas mengenai pengembangan aplikasi berbasis teknologi augmented reality pada buku cerita berjudul “The Shrimp and The Crab” studi kasus SD Negeri 2 Tibubeneng. Penelitian ini dilakukan dengan menggunakan metode Luther-Sutopo. Bahasa pemrograman yang digunakan untuk membuat aplikasi augmented reality adalah C# dengan menggunakan unity 3D dan vuforia. Penelitian ini berhasil mengembangkan aplikasi augmented reality pada buku cerita yang berjudul “ The Shrimp and The Crab - Sang Udang dan Sang Kepiting”. Aplikasi ini dikembangkan secara bilingual. Dalam penelitian ini, kualitatif data didapatkan dari wawancara, observasi, dan juga studi pustaka, sedangkan kuantitatif data diperoleh dari angket. Pengujian aplikasi diuji menggunakan black box dan kuesioner. Di akhir studi, peneliti mengungkap bahwa 90% dari responden yaitu 1 guru, 33 siswa dan 33 orang tua siswa menyatakan aplikasi ini telah layak untuk digunakan. Abstract: This study discusses the development of augmented reality technology-based applications in the story book entitled The Shrimp and The Crab case study at SD Negeri 2 Tibubeneng. This research was conducted using Luther-Sutopo method. The programming language used to make augmented reality applications is C # by using unity 3D and vuforia. This research succeeded in developing an augmented reality application in the story book entitled “ The Shrimp and The Crab - Sang Udang dan Sang Kepiting”. The aplication was developed bilingually. In this research, qualitative data was collected through interview, observation, and literature studies, while quantitative data are obtained from questionnaires. A black box testing and questionnaire were used to test the application. At the end of the study, researchers revealed that 90% of respondent is 1 teacher, 33 students and 33 parents stated that this application was suitable for use.
ANALISIS HARGA AIR PADA AIR PERMUKAAN UNTUK USAHA TANI PADI SAWAH DI SUBAK BENGKEL, KECAMATAN KEDIRI, KABUPATEN TABANAN

Bengkel Subak is the widest subak in Kediri District, Tabanan Regency. Subak Bengkel has a total area of 329 hectares, which is divided into 19 Tempek, which is some kind of grouping. Bengkel Subak is located on two villages, Bengkel Village and Pangkung Tibah Village. The water acquisition is also agreed based on the water debit in each place. This study aims to determine the price of water used by farmers in Subak Bengkel paddy farming, also to know the influence of production and constraints factors experienced in rice farming. The results calculation with the use of value of marginal product (VMP) approach showed that the price of water for irrigated paddy in Subak Bengkel was Rp 413,593.85 / ha / year, around 206,796.92 / ha / planting season or around Rp 206.79 / m3, where the most influential factor is seedlings with an elasticity coefficient of 0.861 affecting production of 8.61 percent. The most common obstacle experienced by Subak Bengkel farmers is the pest in the form of crabs that damage the rice field dike. In the future, Bengkel Subak will include water discharge as an production input in rice farming for appreciation of water resources.