Reviewerly/exHarmony huggingface dataset:
Negative Feedback Dynamic Scheduling Algorithm based on Mimic Defense in Cloud Environment

The virtualization technology in cloud environment brings some data and privacy security issues to users. Aiming at the problems of virtual machines singleness, homogeneity and static state in cloud environment, a negative feedback dynamic scheduling algorithm is proposed. This algorithm is based on mimic defense and creates multiple virtual machines to complete user request services together through negative feedback control mechanism which can achieve real-time monitor of the running state of virtual machines. When virtual machines state is found to be inconsistent, this algorithm will dynamically change its execution environment, resulting in the attacker's information collection and vulnerability exploitation process being disrupting. Experiments show that the algorithm can better solve security threats caused by the singleness, homogeneity and static state of virtual machines in the cloud, and improve security and reliability of cloud users.
Intelligent Irrigation System Using Machine Learning Technologies and Internet of Things (IoT)

Scare water resources necessitates technological involvement in irrigation scheduling, that can help to manage water according to the weather condition of different seasons, crop growth stage and landscape information. The proposed method calculates actual water required using machine learning model and Evapotranspiration. The model is trained using real time weather data to predict actual water requirement. Reference Evapotranspiration is calculated with the help of Penman-Monteith Method. Before starting with this real time system proposed model is implemented with the help of past 10 years web scraped weather data. Proposed algorithms of water requirement and Irrigation scheduling is executed on scrapped data. After successful results system is implemented for real time use.Furthermore, system consists of eight Arduino nodes that acting as a slave to read weather, soil landscape and rain data. In addition, three Raspberry-pi equipped with the Wi-Fi module, acting as server to send collected data to a remote web server. These databases are used as input for machine learning algorithm. As per the observations of proposed system water usage is getting reduced in large quantity as compared to the traditional irrigation system used for irrigation.
Sonification of web tracking, Jasmine Guffond: listening back

When, a couple of weeks ago, I installed the add-on Listening Back produced by the Australian sound artist and experimental electronic composer Jasmine Guffond, I didn’t really know what to expect....
“Footsie”: Exploring Physical Human-Machine-Interaction through Flirtatious Furniture

"Footsie" is an interactive kinetic art installation. It inspires to connect people through the counter-intuitive physical interaction that is mediated by flirtatious machines. It consists of a table and four robotic chairs; the chair legs carry the motion of "footsie" and arms caress the back of the participant. While it tackles the controversial culture and social norms on touching others body or being touched, an experimental bodily experience explores new aesthetic interaction between lonely human and a mischievous digital entity. The interaction is provocative in a slightly uncomfortable way, and the paradoxical feelings and stimulating sensations open simultaneous interpretations on the meaning of Human-Machine-Interaction. Through nature inspired design like human spine, flexible muscle of mollusca and a caterpillar's undulating wave motion, these pliable structures were fabricated with 3D printed meta-materials to create the sensual gestures.
pReview: The Artificially Intelligent Conference Reviewer

Currently there are very few AI tools available to conference reviewers to support the academic process. In this paper we present a naive, first attempt at an automated conference reviewer called pReview. pReview provides a paper summary, contribution summary, writing quality analysis, and set of potential related works as well as an intellectual space visualization to aid the busy academics who volunteer their time as conference paper reviewers. To limit the plethora of ethical issues emerging when a computer is left to judge a human creation, pReview and future systems of this variety should be judiciously viewed as review support tools and never as a replacement for the traditional review process.
Design of unmanned guided vehicle for rescue missions

Now a day with the major advancements in the field of vehicle automation, several dangerous and crucial counter terrorist activities is being handled by the sophisticated machines which are not only effective but also responsible for saving human lives. “Unmanned guided vehicle” is built to reduce human loss in terrorist attacks. The robot has been designed to face this attacks in the country. It is equipped with self-powered, radio operated and controller. A Wifi camera has been installed on it, in order to monitor the enemy activities whenever required. It is capable of entering into the enemy field silently there by sending us all the information regarding the enemy such as the weapons that were hold by them etc. This robot would be armed with an automatic weapon mounted onto a turret and a remote operator would be getting a live video feed from the camera to help him manually control both the above mentioned units of the rover. This spy robot can also be used in motels, shopping areas, jewellery show rooms, etc where there is more chance to terrorist’s attacks and robberies. Since human life is always precious, these robots are the replacement of fighters against terrorist in such areas.
Persian Language Understanding in Task-Oriented Dialogue System for Online Shopping

Natural language understanding is a critical module in task-oriented dialogue systems. Recently, state-of-the-art approaches use deep learning methods and transformers to improve the performance of dialogue systems. In this work, we propose a natural language understanding model with a specific-shopping named entity recognizer using a joint learning-based BERT transformer for task-oriented dialogue systems in the Persian Language. Since there is no published available dataset for Persian online shopping dialogue systems, to tackle the lack of data, we propose two methods for generating training data: fully-simulated and semi-simulated method. We created a simulated dataset with a hybrid of rule-based and template-based generation methods and a semi-simulated dataset where the language generation part is done by a human to increase the quality of the dataset. Our experiments with the natural language understanding module show that a combination of the datasets can improve results. These dataset generation methods can apply in other domains for low-resource languages in task-oriented dialogue systems too to solve the cold start problem of datasets.
The BOW image retrieval algorithm based on the longest common word string constraint

Abstract This paper adds the spatial and semantic relations of the "visual dictionary", the longest common visual word string constraint in the image based on the BoW model. The image is represented at the vocabulary level and the phrase level at the same time. This algorithm can better represent the content of the image, thereby improving the quality of image retrieval. Experiments verify that compared with the BoW model, the accuracy of the BoW image retrieval model based on the longest common word string constraint is well optimized.
Analysis and Design of Agricultural Marketplace Using User Experience

The marketplace is an e-business model that deals with sellers and buyers. In the agricultural sector, the market acts as a direct link between farmers and consumers. So that it can increase and benefit Indonesian farmers. The total users of the agricultural market currently only reach 100,000 users, which is very different from the total users of other general markets which have reached 50 million users. One of the reasons is that 60% of the time is wasted because many users have not yet obtained the information they are looking for. This has an impact on decreasing productivity until it fails. This study will design an agricultural marketplace application design with a User-Centered Design (UCD) approach. This method is a cycle stage starting from production to market applications by implementing quality market services. This production stage is carried out to become a measuring tool for marketplace design to match the standards set and made by the specifications of user requirements. Then the prototype design stage is carried out with a sketch, a wireframe, and the results of this design are implemented into a medium-fidelity prototype. In the evaluation stage of the medium-fidelity prototype, usability testing was carried out using the think-aloud method and the performance results were obtained with a success rate of 77.14%.
Technical and economic analysis on the using of Hibiscus Tiliaceus (Waru) and Boehmeria Nivea (Rami) fibres for fishing vessel mooring rope

Abstract Mooring rope of fishing boat made of synthetic fibre materials such as polypropylene or nylon can bring detrimental impacts to the environment as it is arduous to degrade. Natural fibre rope can potentially substitute the commonly-used undegradable mooring line to prevent further chain impacts. This paper aims to technically and economically analyse the tensile strength of mooring ropes made of two natural fibres, Hybiscus Tiliaceus (Waru) and Boehmeria Nivea (Rami), and to compare them with the former - conventional material manufactured rope. Tensile test, according to ASTM D3822, is performed to measure the tensile strength of the natural fibre ropes twisted into three different diameters (12 mm, 16 mm, 20 mm). Specimens are immersed in seawater for several weeks before testing. As a benchmark, this research examines unimmersed ones. The result shows that immersed Waru fibre ropes with three different diameters are 32.15 MPa, 27.10 MPa, 23.94 MPa, respectively; while for Rami fibre ropes are 37.58 MPa, 29.56 MPa, 24.31 MPa. Waru fibre rope is the most economical one if compared to Rami and synthetic fibre ropes. The manufacturing of mooring rope made of Waru fibres can save 19.4%, 11.5%, and 29.7% for each diameter variation, respectively.
Pattern Recognition of Facial Electromyography (FEMG) Signal for Aceh Language Speech using Naïve Bayes and Learning Vector Quantization (LVQ)

Abstract Facial electromyography is myoelectric signals that formed by human facial muscles. This signal can be acquired by attaching an electrode to the facial muscle that has been connected with an electromyography sensor. When human say certain words, the articulation muscles contract and facial electromyography signals appear in the muscles. This study aims to recognize patterns in facial electromyography signals by classifying signals using naïve bayes and learning vector quantization classifier. Feature extraction used one-dimensional discrete wavelet transforms. Wavelet transform type used wavelet daubechies2 level 5. The transformation produces a level 5 approximation coefficient called a5 and five detail coefficients called d1, d2, d3, d4, and d5. The result of this study show that the average classification accuracy for ho neuk jak sentence using naïve bayes and LVQ classifier was 62.5% and 92.5% respectively. The average classification accuracy for ja’ word using naïve bayes and LVQ classifier was 70% and 92.5% respectively. The average classification accuracy for ja’ wo sentence using naïve bayes and LVQ classifier was 52.5% and 90% respectively. The average classification accuracy for pane word using naïve bayes and LVQ was 70% and 90% respectively. The average classification accuracy for soe word using naïve bayes and LVQ classifier is 85% and 95% respectively. Thus, this study shows that when humans say the words, facial electromyography signals that appear on facial muscles difference for each subject.
zkrpChain: Privacy-Preserving Data Auditing for Consortium Blockchains Based on Zero-Knowledge Range Proofs

Consortium blockchain has been widely used in different scenarios, where blockchain members demand that their uploaded data could be audited under their identities without exposing the data themselves. However, so far, no solution of privacy-preserving data auditing has been proposed. To address the problem, we propose zkrpChain, which focuses on protection of the integrity and privacy of the data uploaded by blockchain members while leaving their identities public. In zkrpChain, which is based on Hyperledger Fabric and Bulletproofs, both standard-range and arbitrary-range zero-knowledge range proofs generation and verification are supported. To improve the efficiency, the aggregation of multiple proofs and batch verification are also developed. For further development, we provide the client codes, chaincodes and related APIs. Finally, we conduct experiments to evaluate the performance of zkrpChaln, and the results show that the consumed time (in an 8-thread scheme) of chaincodes and needed on-chain space of zkrpChain are very close to Bulletproofs, which is evaluated in a single-machine environment.
Test Case Generation From Web Usage Information

In the context of SaaS (Software as a Service) where software has to be up and running 7 days a week and 24 hours a day, keeping the requirements specification and related test cases up to date can be difficult. Managing requirements in this context has additional challenges that need to be taken into account, for instance, re-prioritize requirements continuously and identify/update new dependencies among them. When requirements change, related test cases need to be updated accordingly. We claim that extracting and analyzing the usage of the SaaS can help to maintain requirements and test cases updated and contribute to improve the overall quality of the services provided. This paper presents an extension to REQAnalytics. REQAnalytics is a recommendation system that collects information about the usage of a SaaS and generates recommendations to improve the SaaS provided. The evolution involves extending the analysis performed over the sequences of functionalities (requirements) and refining the data provided for Software Requirements Specification, with the purpose of helping the requirements engineers in the requirement maintenance activities, and to improve the overall quality of the services. Furthermore, the extension presented in this paper is able to generate test cases in a regression testing context.
WITHDRAWN: A novel framework to provide security for clinical archives utilizing steganographic discharge control

At present in the advanced world giving security to data being changed through the system plays a key job to safeguard human privacy protection. Numerous documents are being moved from association to association/individuals with the motive of advancement in their business and at times for examination reasons like sales analysis, research. In this process of exchanging that private data of an individual/association gets into the hands of an unapproved individual makes a tremendous danger that specific individual. Among all data discharge, revealing of clinical records makes a lot of risk to individuals since they contain delicate data about individuals. To provide security to the medical document we proposed this paper. Here in this paper, we provide security to our documents during their transformation by using Redactable signatures schemes and steganography. In the process of hiding the patient information in an image, we proposed a Discrete Wavelet Transform (DWT) and the Chinese Remainder Theorem (CRT).
Joint Workload Distribution and Capacity Augmentation in Hybrid Datacenter Networks

In hybrid datacenter networks, wired connections are augmented with wireless links to facilitate data transfers between racks. The usage of mmWave/FSO wireless links enables dynamic bandwidth/capacity allocation with extremely small reconfiguration delay. Also, on-demand workload distribution, where the workload of a job is divided into multiple tasks that can be distributed/routed to different racks to be processed in parallel, allows better utilization of computational resources in data centers. In prior work, the dynamic wireless capacity augmentation and workload distribution decisions were mostly made independently and in a heuristic manner for serving distributed and parallel computing jobs. In this paper, we propose a novel analytical framework and algorithms to jointly optimize both the wireless capacity augmentation and the workload distribution, to minimize the job completion time. We consider workload that is not amenable to pipelining, fully amenable to pipelining, and partially amenable to pipelining. With extensive simulation studies, we show that the gain (in terms of the reduction in the job completion time) can be very substantial when allowing such joint optimization.
Reasoning in the Theory of Heap: Satisfiability and Interpolation

In recent work, we have proposed an SMT-LIB theory of heap tailored to Horn-clause verification. The theory makes it possible to lift verification approaches for heap-allocated data-structures to a language-independent level, and this way factor out the treatment of heap in verification tools. This paper gives an overview of the theory, and presents ongoing research on decision and interpolation procedures.
Frequency Hopping Spread Spectrum to Counter Relay Attacks in PKESs

Passive keyless entry and start systems (PKESs) have been widely deployed in modern cars. These systems have brought many advantages over their predecessors and are considered more secure. However, they are subject to a new type of attack, known as relay attack. Due to this attack, hundreds of cars have been stolen in many countries. Since then, car manufacturers as well as insurance companies have been experiencing an endless nightmare. Researchers have also been working into proposing solutions, mainly based on distance-bounding protocols and sensing technologies, to counter relay attacks but none of the solutions came out with a fundamental mitigation. In this paper, we apply FHSS (Frequency Hopping Spread Spectrum) transmission technique as a physical-layer countermeasure to mitigate relay attacks. By hopping from one frequency to another, within a wide bandwidth, and following a per-session secret-shared frequency hopping sequence, the communication between the car and its associated keyfob can be hidden from the attackers as long as the latter are not aware of the hopping sequence.
Unmanned driving intelligent algorithm simulation platform

Based on the development of unmanned driving systems worldwide, this chapter mainly uses the skills of software simulation to design a train control platform. The simulation process and the display process can use modular design, which help users to modify and improve programs. The train dynamics model is adopted in the simulation platform, so fixed train operation–related algorithms and the control methods designed by the user can be used in the system. The software development process generally refers to software design ideas and implementation methods. In the process of software design, the first step is to determine the goal of the software to be realized, and then the modeling, design, and programming of the software are carried out. At the same time, this chapter simulates and compares the performance of various intelligent driving algorithms. The characteristics of various algorithms are analyzed based on experimental results.
A causal model of factors affecting azimuth and altitude learning by smart phone in astronomy

Abstract In present, physics learning management has developed into learning technology from easy to complex levels with many developed media increased. Smart phone is one of all media use in many automatically. In this paper, researcher used instruction of a causal model of factor affecting azimuth and altitude learning by smart phone in astronomy using by rotating the position, finding the angle of the star in the sky which tells the coordinates of the star from applications created used by cell phones and Wi-Fi. It was suggested that student using their phones to download a free app that would monitor frequencies and send data to a processing facility. Methods for teaching and learning that students have analysed solve problems that are linked to the problems of everyday situations and conclusions through the team’s idea to solving problems of inequality in access to quality education of students who are far away and the practice of research practices that can be used to develop educational institutions. The results indicated that the adjusted model was consistent with empirical data. Goodness of fit measures were found to be: χ 2 = 271.59, df = 149, p-value = 0.00063, GFI = 0.95, RMSEA = 0.042.
Designated Verifier Signature Transformation: A New Framework for One-Time Delegating Verifiability

Designated verifier signature (DVS) is a variant of digital signature which can designate a verifier to verify signatures. The main difference between message authentication code and DVS is that no shared key is initially set in DVS. In this paper, we propose a new notion, designated verifier signature transformation (DVST), which allows a cloud server to convert a DVS to a multi-designated verifier signature (MDVS) as long as the original verifier provides a token to the server. For more flexible use, the converted signature can support verification with more than threshold number of designated verifiers. Accordingly, a specific security definition is formalized as token unforgability. Our construction is proposed and built from bilinear map with security analysis.
Analysis on Yu et al.’s dynamic algorithm for canonic DBC

Recently, Yu et al. presented an algorithm for a canonic DBC of a positive integer n by solving certain subproblems recursively and it requires O((logn)2loglogn) bit operations and O((logn)2) bits of memory. This is currently the most efficient recoding type algorithm for canonic DBCs when balanced computing power and memory are available. In this paper, we present a memory efficient algorithm to compute a nearly DBC from the idea of Yu et al. We present a simple overview of Yu et al.'s algorithm focusing on canonic DBC and refine Yu et al.'s proof for range of the leading term of canonic DBCs. By using the refined range, we suggest how to improve the efficiency of Yu et al.'s algorithm computationally and present an algorithm for nearly canonic DBC with memory requirement O(logn). We also present experimental comparison on the Hamming weights of Yu et al.'s algorithm, tree based algorithm, the classic greedy DBC algorithm, and our memory efficient algorithm.
From Fully Supervised to Blind Digital Anastylosis on DAFNE Dataset

Anastylosis is an archaeological term consisting in a reconstruction technique whereby an artefact is restored using the original architectural elements. Experts can sometimes imply months or years to carry out this task counting on their expertise. Software procedures can represent a valid support but several challenges arise when dealing with practical scenarios. This paper starts from the achievements on DAFNE challenge, with a traditional template matching approach which won the third place at the competition, to arrive to discuss the critical issues that make the unsupervised version, the blind digital anastylosis, a hard problem to solve. A preliminary solution supported by experimental results is presented.