Reviewerly/exHarmony huggingface dataset:
BlurNet: Keeping Collected Data Private with a Neural Network Based Pipeline

Data collection process is required to keep personal information of third parties private. This mandatory obligation has been recently enforced in a growing number of countries by appropriate laws, which forbid recording certain types of data. On the other hand, machine learning solutions based on neural networks, which are used in automotive industry, require a vast amount of data to learn from. The article addresses the problem of collecting camera frames in the form of a video file, where registered pedestrian faces and vehicle license plates are visible to a degree. This allows one to associate them with a particular person, hence they contain personal data. The pipeline for object detection and blurring algorithm is proposed. Processing images is being done by proposed BlurNet neural network based on YOLOv3 architecture. The article describes adaptations for a given data format, as well as modifications to improve the accuracy. Blurring algorithm is described as well. In order to maintain sufficient level of privacy, conducted experiments provide numerical answer regarding the performance of such solution.
CanaryTrap: Detecting Data Misuse by Third-Party Apps on Online Social Networks

Online social networks support a vibrant ecosystem of third-party apps that get access to personal information of a large number of users. Despite several recent high-profile incidents, methods to systematically detect data misuse by third-party apps on online social networks are lacking. We propose CanaryTrap to detect misuse of data shared with third-party apps. CanaryTrap associates a honeytoken to a user account and then monitors its unrecognized use via different channels after sharing it with the third-party app. We design and implement CanaryTrap to investigate misuse of data shared with third-party apps on Facebook. Specifically, we share the email address associated with a Facebook account as a honeytoken by installing a third-party app. We then monitor the received emails and use Facebook's ad transparency tool to detect any unrecognized use of the shared honeytoken. Our deployment of CanaryTrap to monitor 1,024 Facebook apps has uncovered multiple cases of misuse of data shared with third-party apps on Facebook including ransomware, spam, and targeted advertising.
On the Relationship between Internet and Traditional Communication Industry

China's history and culture are long. It is the famous state of etiquette. People through a certain form of rituals and a certain way of cultural activities to carry out their thoughts and feelings. In real life, everyone often uses a series of applications such as traditional letters, business cards, stickers, announcements, essay inscriptions, couplets, modern such as telegraph, fax, express mail, e-mail and so on. These applications include rich ritual content, with a strong cultural color of the Chinese nation. From the earliest Pigeon biography to today's videophone, the traditional communications industry has a complex development process. At diff erent times have diff erent roles, and also has a lot of convenience and inconvenience. Because of this inconvenience, Internet in real life is more widely used, so to a certain extent make up for this shortcoming, this article will focus on the Internet and traditional communications industry in order to explore the relationship between both and the future development trend.
Constructing a provably adversarially-robust classifier from a high accuracy one

Modern machine learning models with very high accuracy have been shown to be vulnerable to small, adversarially chosen perturbations of the input. Given black-box access to a high-accuracy classifier $f$, we show how to construct a new classifier $g$ that has high accuracy and is also robust to adversarial $\ell_2$-bounded perturbations. Our algorithm builds upon the framework of \textit{randomized smoothing} that has been recently shown to outperform all previous defenses against $\ell_2$-bounded adversaries. Using techniques like random partitions and doubling dimension, we are able to bound the adversarial error of $g$ in terms of the optimum error. In this paper we focus on our conceptual contribution, but we do present two examples to illustrate our framework. We will argue that, under some assumptions, our bounds are optimal for these cases.
Automated Configuration of Negotiation Strategies

Bidding and acceptance strategies have a substantial impact on the outcome of negotiations in scenarios with linear additive and nonlinear utility functions. Over the years, it has become clear that there is no single best strategy for all negotiation settings, yet many fixed strategies are still being developed. We envision a shift in the strategy design question from: What is a good strategy?, towards: What could be a good strategy? For this purpose, we developed a method leveraging automated algorithm configuration to find the best strategies for a specific set of negotiation settings. By empowering automated negotiating agents using automated algorithm configuration, we obtain a flexible negotiation agent that can be configured automatically for a rich space of opponents and negotiation scenarios. To critically assess our approach, the agent was tested in an ANAC-like bilateral automated negotiation tournament setting against past competitors. We show that our automatically configured agent outperforms all other agents, with a 5.1% increase in negotiation payoff compared to the next-best agent. We note that without our agent in the tournament, the top-ranked agent wins by a margin of only 0.01%.
PERANCANGAN APLIKASI HASHING FILE MENGGUNAKAN SHA – 224 BERBASIS ANDROID

Nowadays the development of technology in the field of computer science is growing rapidly. With the rapid development of technology in the field of computer science, information and data require a security and confidentiality because the information becomes a very valuable item. However, with the development of technology there are also many threats of crime against files that users have. One way to maintain the authenticity of information and data is to use hash cryptography. The hash function is an algorithm that converts text / messages into a series of random characters that have the same number of characters. The hash function is used to guarantee the authentication service of messages or files. Algorithms that use hash functions include MD5, SHA-1, SHA-2 (SHA - 224, SHA - 256, SHA - 384, SHA - 512) and others that have their advantages and disadvantages. In designing this application, the cryptographic algorithm used is the SHA-224 algorithm, because SHA-224 has a summary of variable sizes. The file hashing application using the Android-based SHA-224 algorithm, can help users to maintain the authenticity of files from users anywhere and anytime. Users can also compare the authenticity of user files with files that have been hashed.
Capturing Oracle Guided Hiders

Consider a closed environment with static obstacles and mobile agents moving around. There are hider agents that hide from the seeker agents. The seeker has a limited visibility range, and if a hider comes into the visibility region of a seeker, it is considered caught. The practical applications range from gaming to security. In this work, we focus on deterministic capture of hiders, even if they are guided by an Oracle which knows the future positions of seekers. We develop strategies for seekers, having limited visibility ranges, to catch all hiders and establish minimum bounds on the number of seekers required to catch the hiders, on a per strategy basis. We use spatio-temporal graph models and reasoning to formulate and address the problem.
Large Scale Collaborative Detection and Location of Threats in the Electromagnetic Space

In the twenty-first century, the security of the electromagnetic spectrum has tremendous strategic importance to society. In particular, the wireless infrastructure that carries vital services such as 5G cellular networks, communication to aircraft and Global Navigation Satellite System is especially critical. This rapid change is even more impressive considering that in the 1980s the only concern for spectrum management was mostly about radio/television broadcasting and military communications. The allocation of spectrum has become over the years more and more complex with different players and stakeholders that depend on largely of their correct operation. However, today, the cost of commodity radio technology prices is so low that access to it is no longer restricted to governments and network operators. It is now affordable to individuals, giving them the potential to become malicious intruders. More frequent and more sophisticated threats from such infiltrators could wreak havoc and are among the most serious challenges faced by society. Unauthorized transmissions could threaten the operation of networks used by air traffic control systems, police, security and emergency services in populated areas. The SOCRATES (Large Scale Collaborative Detection and Location of Threats in the Electromagnetic Space, Grant G5461) project started in June 2018 and aims to deliver a security system to protect our electromagnetic environment and the services and users that depend upon it. SOCRATES will provide an accurate, autonomous, fast and secure system based on a novel and disruptive IoT (Internet of Things) architecture. By detecting and locating unusual RF signal and source activity it will identify intruders in the electromagnetic space, before a threat can become serious, learning about its physical layer features and its geographic location. By providing the capability to detect, identify and locate potential threats to electromagnetic infrastructure security, SOCRATES represents an important step in ensuring society’s readiness to respond effectively to them. SOCRATES will shield economic and social structures from those who would harm them. In this contribution we present a summary of published results achieved in the first year of the project, how funds from SOCRATES have foster the collaboration between NATO countries Spain and Belgium and partner country Switzerland, including the activities led by Electrosense as partner country.
시진핑시대, 이슬람교중국화정책 연구 ― ｢堅持我國伊斯蘭教中國化方向五年工作規劃綱要(2018—2022)｣을

This paper aims to analyze the Islamic policy of the Chinese government. This paper consists of five chapters. Chapter 1 is an introduction. Chapter 2 analyzes the background of the change in the Islamic policy of the Chinese government from a moderate to a hard line. Chapter 3 analyzes the main contents of ‘Islamic Sinicization’. According to the ｢ Five-Year Work Plan for Upholding the Sinicization of Islam in China (2018-2022)｣, ‘Islamic Sinicization’ can be divided into four aspects. first is to deepen Education on Patriotism and Socialism with Chinese Characteristics. Second is to deepen Efforts on Scriptural Interpretation, Building Islam with Chinese Characteristics. Third is to separate Religion from Life. Fourth is to improve Rules Systems and Regulate Self-Management. Chapter 4 is since the implementation of the ‘Sinicization of Islam policy’, It analyzed the religious reality of Muslim society and the limitations of religious policy. Chapter 5 is the conclusion.
APPLICATION OF POSYANDU GEOGRAPHIC INFORMATION SYSTEM OF PINANG SUB-DISTRICT USING LEAFLET-BASED IGNITER CODE

The development of information technology now has reached to all fields and become something very important in life, humans need information that is fast, accurate, and accurate in presenting data. A geographical information system an information processing service that contains data information displayed in a map view, this system can provide information more easily and support health management. Posyandu geographic information systems can help communities to find out where a posyandu is located. Designing a leaflet-based geographical information system on posyandu in Pinang District to search for posyandu located in the Pinang District area of Tangerang City. The results of this study are in the form of a geographic information system that is connected to a google map that can show a map of the location of the community health center and information from each Posyandu in Pinang District, Tangerang City.
Digital picture watermarking technique for security applications

Abstract Digital picture watermarking is employed to stay secret the proprietary info as a watermark within a digital image, to spot the possession. This method has relevancy to any or all pictures. Separate trigonometric function transform (DCT) is employed before inserting the watermark within the host image. The host picture is isolated into 8×8 non-covering hinders preceding DCT application, and therefore the watermark bit is inserted by dynamic distinction between DCT coefficients of contiguous squares. Arnold transform is employed even so disorderly encoding to feature 2-fold block safeguard to the watermark. 3 distinctive variations of the planned calculation are tried and stone-broke down. The reenactment results demonstrate that the planned set up is powerful to the overwhelming majority of the image making ready tasks like JPEG pressure, honing, trimming, middle separating, and so on. To approve the proficiency of the planned technique, the recreation results are contrasted and sure condition of-workmanship systems. The examination results represent that the planned set up performs higher as so much as power, security and imperceptivity. Given the advantages of the planned set up, it alright could also be used in applications like e-social insurance and telemedicine to smartly hide out electronic eudemonia records in therapeutic footage.
Want to Identify, Extract and Normalize Adverse Drug Reactions in Tweets? Use RoBERTa

This paper presents our approach for task 2 and task 3 of Social Media Mining for Health (SMM4H) 2020 shared tasks. In task 2, we have to differentiate adverse drug reaction (ADR) tweets from nonADR tweets and is treated as binary classification. Task3 involves extracting ADR mentions and then mapping them to MedDRA codes. Extracting ADR mentions is treated as sequence labeling and normalizing ADR mentions is treated as multi-class classification. Our system is based on pre-trained language model RoBERTa and it achieves a) F1-score of 58% in task2 which is 12% more than the average score b) relaxed F1-score of 70.1% in ADR extraction of task 3 which is 13.7% more than the average score and relaxed F1-score of 35% in ADR extraction + normalization of task3 which is 5.8% more than the average score. Overall, our models achieve promising results in both the tasks with significant improvements over average scores.
UJI KESESUAIAN STANDAR NILAI HVL FILTER ALUMINIUM PADA PESAWAT SINAR-X MAMMOGRAFI: STUDI KASUS DI RUANG INSTALASI RADIOLOGI RS. SILOAM MAKASSAR

The quality control of X-ray radiation in a radiology device plays an important role in determining the clinical use feasibility. The HVL value test of a filter is very important because it determines the effective of X-ray energy. HVL values indicate the thickness of the absorbent material to absorb X-ray intensity up to half of its original intensity. This research is devoted to testing the feasibility of Mammography equipment in the radiology installation room of Siloam Makassar hospital by comparing two methods of determinations the HVL value in the variation of voltage 23, 25, 27, 29, 31 and 33 kVp. The HVL value that determined from direct methods without filters is used as a base value that to be compared with the HVL value which determined by indirect methods through calculations after the addition of aluminum filter thicks to gradually. HVL values by indirect measurements ranged from 0.268−0.401 mmAl, while by direct measurements between 0.291−0.338 mmAl with a deviation between 1.39−7.90%. The results obtained indicate that the HVL value for all X-ray tube voltage variations from the two methods in use still on ranges the tolerance standard so that it can be reported that the X-ray mammography at the Siloam hospital was declared feasible.
Bayesian Neural Networks for Financial Asset Forecasting

Neural networks are powerful tools for modelling complex non-linear mappings, but they often suffer from overfitting and provide no measures of uncertainty in their predictions. Bayesian techniques ...
Multiscale Deep Neural Networks for Multiclass Tissue Classification of Histological Whole-Slide Images

Correct treatment of urothelial carcinoma patients is dependent on accurate grading and staging of the cancer tumour. This is determined manually by a pathologist by examining the histological whole-slide images (WSI). The large size of these images makes this a time-consuming and challenging task. The WSI contain a variety of tissue types, and a method for defining diagnostic relevant regions would have several advantages for visualization as well as further input to automated diagnosis systems. We propose an automatic multiscale method for classification of tiles from WSI of urothelial carcinoma patients into six classes. Three architectures based on convolutional neural network (CNN) were tested: MONO-CNN (400x), DI-CNN (100x/400x) and TRI-CNN (25x/100x/400x). The preliminary results show that the two multiscale models performed significantly better than the mono-scale model, achieving an F1-score of 0.986, substantiating that utilising multiple scales in the model aids the classification accuracy.
Fundamentals of Delineation of Area of Mineral and hot Water Potential in Duyen Hai area, Hung Ha district, Thai Binh Province, Viet Nam for Exploration Purpose

Mineral and hot water is a valuable resource that can be used for nursing and physiotherapy, making bottled water, making beverage and healing, exploiting useful minerals, energy extraction, even cultivation spirulina and other purposes. Hot groundwater was discovered during the 90s of the 20th century in Duyen Hai commune, Hung Ha district, Thai Binh province, but no exploration and evaluation studies were conducted to determine the potential of the mineral and hot water in the area. Spatial distribution of groundwater temperature and the total mineralization in the study area of the mineral and hot water occurrence and its surrounding area has allowed to identify the area of mineral and hot water origin, and that the hot water belongs to average hot water with a temperature of about 49 degrees Celsius. Analyzing the tectonic structure has showed that the mineral and hot water is formed at an area surrounded by three class-2 faults, which have a vertical displacement amplitude of 100 m - 1,000 m and a destructive zone of over 100 m. This is an area with favorable conditions to bring geothermal source and dissolved minerals in surrounding rocks to groundwater in the above aquifers. The approach presented in the paper can be applied to conduct research on potential mineral and hot water in other areas: determine values of some mineral and hot water parameters such as temperature and TDS, compile maps of spatial distribution of the parameters, clarify characteristics of tectonic structure relevant to anomaly of high temperature and TDS.
THE EVALUATION OF ACCIDENT DATA BY USINGEXISTING PREDICTIVE MODEL FOR JOHOR ANDSELANGOR STATE

Road accidents are common inevitable occurrences over the world, in average Malaysiaestimated 19 persons are killed every single day. The two states contributing to MalaysiaÂs highest fatalaccidents are Selangor and Johor. In the year 2017, Selangor and Johor recorded respectively 154,958 and76,121 accidents as well as fatalities of 1,087 and 1,067 cases. This study evaluates these accident data for thestates of Johor and Selangor with existing predictive models. Fatalities are predicted for both states in 5 yearsfrom 2019 until 2024. The accident data can be studied in relation to the type of fatality includes serious injury,slightly injury and damage or with the dependent variables of vehicle type and number of registered motorvehicle. The study found that the analysis from RehanÂs model and AminuddinÂs model produced soundingresults among the studied predictive models. The findings from RehanÂs model predictions are preferable andthe predicted trends shows that by 2025, there will be 2,743 fatalities due to road accidents in the state ofSelangor and 2,346 in Johor and can be related to the results of increasing population and vehicles in the states.
ACTIVITY PATTERN RECOGNITION USING SMARTPHONES

It is a noteworthy computational undertaking to give exact data in regards to the movement performed by a human and discover examples of their conduct. Applications can be formed and different issues in spaces of computer-generated reality, wellbeing and medicinal, excitement and security can be unravelled with progressions in human movement Recognition (HAR) frameworks. HAR is a functioning field for investigating for over 10 years, yet certain perspectives should be routed to improve the framework and alter the manner in which people connect with cell phones. This exploration gives an all-encompassing perspective on human action Recognition framework engineering and talks about different issues related to the structure viewpoints. It further endeavours to grandstand the decrease in computational expense and critical accomplishment in precision by strategies that include choice. It likewise endeavours to present the utilization of intermittent neural systems to take in highlights from the long arrangements of time arrangement information, which can contribute towards improving exactness and also in diminishing reliance on space information for surveillance.
Designing Blended Learning Materials for Functional Texts in Fiction Study

In fiction study traditional class is complicated. It always challenges to teach students fiction. They do not appreciate literature pieces as much as teacher used to in those good old days. It notices that students these days do not read many literature pieces or getting students to read the text before class. This happens also in Elements of Prose class in English Department at UIN Sunan Kalijaga. One solution to this problem that is discussed in this study is mixed method between face to face-classroom with online learning that is called blended learning. Blended learning goes beyond barriers of time, location, and culture and has created many enhanced opportunities for learners and instructors. It is effective because it allows students to read e-book versions and in classroom time, they are more focus and active on meaningful activities related with their learning materials.