Reviewerly/exHarmony huggingface dataset:
Text security segmentation algorithm based on key distribution

Abstract The vector space projection theory of key decomposition problem is proposed. The key decomposition algorithm is given, and the theory and algorithm are introduced into the research of text segmentation problem. A text security recovery for practical secrecy is given. The algorithm is compared with the traditional text segmentation algorithm. It realizes that the text is first divided into N paragraphs, and then the paragraph is mapped to n sub-texts by using the principle of grouping key. If any m sub-texts are owned, the original text can be restored, which provides security for the storage and transmission of important texts.
Analysis of Health Care Services using Meta Search Engine and Web Mining

Many existing page ranking algorithms are used in web mining to display the resultin search engine result page. But this existing algorithms are either best on the inlinks and outlinks of the page or content of the page. Current scenario in India is thatpeople don't know the actual service cost of any hospital. About 50 to 60 percentpeople in India are poor and middle class. They cannot afford the service chargesprovided by the hospital. The service charges of every hospital varies. People facedifficulties in searching the hospital which provides quality services in minimumprice. Most of the people pay unnecessary charges to those hospitals rather thanother hospitals which provides same services in lower price. Proposed system givessolution to all the above problems. The system compares multiple hospitals based onthe area, services, cost, ratings or reviews. According to the people's requirements it provides list of hospitals in filtered format. Based on the results people can decidewhich hospital provides the same services in minimum cost. Our proposed systemworks on the basis of Meta Search Engine, web mining algorithms like contentbased , usage based and structured based algorithm as well so as to find results in minimal optimal time .
X509v3 EAP Parameter Extension

This document specifies an extension to X509v3 certificates for EAP-TLS servers to mitigate some flaws in the specification to the use ofTLS in EAP as specified in RFC5216. The specified extension enablesclients to decide whether to trust the certificate presented by theEAP-TLS server by including information implicitly defined by logincredentials or communication context in the server certificate.
Rootkit inside GPU Kernel Execution

We propose a rootkit installation method inside a GPU kernel execution process which works through GPU context manipulation. In GPU-based applications such as deep learning computations and cryptographic operations, the proposed method uses the feature by which the execution flow of the GPU kernel obeys the GPU context information in GPU memory. The proposed method consists of two key ideas. The first is GPU code manipulation, which is able to hijack the execution flow of the original GPU kernel to execute an injected payload without affecting the original GPU computation result. The second is a self-page-table update execution during which the GPU kernel updates its page table to access any location in system memory. After the installation, the malicious payload is executed only in the GPU kernel, and any no evidence remains in system memory. Thus, it cannot be detected by conventional rootkit detection methods.
Night Time Foreground Pedestrian Detection by Image Processing

The paper accounts for the automated detection of pedestrians associate degree objects that will cause an accident in the dark time from a vehicle mistreatment an automotive visual modality system and a thermal camera. As per the accident survey team of the Asian nation, most of the accident's area unit caused because of the low vision of the drivers that result in the most dangerous and better range of accidents in the dark with relation to daytime. To avoid accidents in the dark time automotive visual modality system is employed. This method includes an IR vision camera that detects the article with the assistance of IR diode and photo-diode pair, this camera can notice the article up to 100 m. Besides the planning of hardware additionally, a software package half for the automated detection of pedestrians is intended just in case of a distracted driver in a way of alcoholic or yawning. The software package for object detection and classification uses trendy digital signal process algorithms like connected element labeling (CCL), a bar chart of headed gradients (HOG), and support vector machine (SVM). Moreover, besides the bestowed visual modality system, our system incorporates a biometric authentication system for asleep and alcoholic driver's mistreatment MTCC and additionally an RGB filter rule to notice the red or inexperienced signal lights of the vehicle and also the traffic signals. And for the restricted field of vision, it uses CMOS image sensing.
Blockchain bringing Paradigm Shift in Indian Governmental Society Functioning

We probably use algorithms in our routine life; the power of the algorithm comes from the fact that technology can follow the steps quickly and accurately. Blockchain is a new-age technological algorithm which has the power to disrupt many industries; very similar to how the Internet was in the early 1990s.And we see countries and states around the world experimenting with that technology. Blockchain has achieved a strapping hold to be converted into a history altering technology that will prelude to a decentralized potential with real-world use cases. Blockchain is putting its whereabouts in emerging countries like India by track building the ecosystems, shaping the civilization, cater issues pertains to humanity, etc. with the help of government functionaries to shape the civilization. In 2019 it had been envisaged that blockchain technology will be adopted by more mainstream sectors. But the query remains unanswerable: “Are we at the height of a history shifting know-how that will coerce enormous social blow, or is blockchain the most up-to-date tech buzzword more smash than objects?”
Implementation of Augmented Reality Technology for the Mobile-Based Introduction of Toraja Traditional Clothes

Every region in Indonesia has a traditional clothes that is characteristic of each region, especially the Tanah Toraja that located in the province of South Sulawesi. The Rantepao Art Center building is one of the art buildings located in Tana Toraja, precisely in downtown Rantepao, North Toraja district. The problem is that during this time, the Rantepao art center building only introduces Toraja traditional clothes by means of dialogue, beside of books or catalogs those available there. Efforts are needed on how to present a model of introduction of Toraja traditional clothing and accessories in a more attractive and interactive three-dimensional form. Thus the tourists can easily understand each of the Toraja traditional clothing model and its accessories. We use marker based tracking with Augmented Reality technology. Augmented Reality is a technology that combines marker objects into a real three-dimensional environment and displays them in real time. The results of this study are by displaying three-dimensional images of toraja traditional clothes by using a mobile device to capture images on smartphones, so that visitors of North Toraja regency's art center, both local and international, can see the more attractive appearance of toraja traditional clothes.
Assessing Spatiotemporal Trends of Long Term Temperature over Kharun Watershed Chhattisgarh, India

The study and investigation of temperature trends is quite essential for a country like India, whose economy is largely dependent on agriculture as temperature greatly influences rainfall and evapotranspiration processes. Temperature along with other meteorological parameters largely affect the water availability over a region. Almost 83% water is used in agriculture, 12% is consumed by industries and merely 5% is used for domestic purposes. In the present study, long term trend with temperature data of 64 years (1951-2014) was analyzed for maximum, minimum and mean temperature values. After removal of all significant correlation in the data, Mann-Kendall test (MK) was applied. To identify the trends Sen’s slope estimator was used and the overall percent change for the temperature over the study area was determined. To interpolate the spatial pattern an inverse distance weighted interpolation method (IDW) was used using ArcGIS 10.2.2. The analysis showed a significant increase in the trend of temperature for annual and seasonal series during the entire period over the study area i.e. Kharun watershed, Chhattisgarh, India. These results will be quite helpful and play an important role in managing water resources in the basin and will be useful for future planning of irrigation and agricultural practices.
Epigenesis, Inherited Memories & Moods Lasting over Several Generations

TGD allows to identify quantum correlates of moods in terms of bio-harmonies defined as allowed light 3-chords defining representation of the genetic code. Even bio-molecules would have emotional states, moods affecting gene expression and having thus behavioral correlates. This encourage the view that conditionings correspond to long lasting moods. Also epigenesis could be understood in terms of moods having time span of even several generations. This picture conforms with zero energy ontology allowing to see bio-systems as 4-D systems.
Reference Path Correction for Autonomous Ground Vehicles Driving Over Rough Terrain.

This paper proposes an online reference path correction algorithm for Autonomous Ground Vehicles (AGVs) driving in unstructured environments. Because the reference path which is not in accord with the road geometry cannot be directly executed by AGV, we use a correction baseline, which represents the road geometry, as the guidance to correct reference path. As the road geometry varies according to the road environment, we use the centerline of drivable area extracted with General Regression Neural Network (GRNN) or optimal path generated by multi-resolution local trajectory planner as the correction baseline to correct the distance and curvature errors of the reference path. The proposed algorithm is tested on our experimental autonomous vehicle in the realistic off-road scenarios. Experimental results demonstrated its capability and efficiency to reduce the search space of the local trajectory planner and improve the robustness of tracking the reference path.
Trajectory Planning for Automated Vehicles in Overtaking Scenarios.

Overtaking is a challenging task in the field of autonomous driving, especially on roads with an opposite lane and oncoming vehicles. Since trajectory planning is repeated cyclic it is highly important to trigger the maneuver only if it is guaranteed that collision-free trajectories that satisfy kinematic constraints exist at each planning step. The goal of this paper is to present an algorithm for planning overtaking trajectories on large temporal horizons in real-time. The main idea is as follows: once overtaking is desired by the behavior module an initial trajectory is simulated using a path tracking control algorithm for lane changing combined with a classical PI-controller for approaching the target speed. The controllers are parametrized in a way that the simulated trajectory will satisfy kinematic constraints. If no collisions are detected a corridor containing the simulated trajectory is created to state constraints for a subsequent optimal control problem to relax the trajectory and smooth it to be comfortable to the vehicle passengers.
User Interface for Text and Non-Text Classification

In this paper, we propose a user interface for text and non-text classification. The user interface helps a user revise incorrect classification results without rewriting. The user interface automatically switch between writing mode and revising mode without any interruption, which makes a better interaction between the user and the system. We compare the proposed user interface with a simple interface using check-box for switching between the writing and revising modes. The experimental results show that the average time for revising of the touch interface is shorter than checkbox interface. Users also evaluated the touch interface better than the checkbox interface, since they have to do less step when misclassifications occur.
Source code optimizer using local optimization approach for java based generic code clone detection

Source code optimization techniques is a technique that is widely used by many researchers and programmers to enhance a software system. It is applied for enhancements especially in terms of performance, time execution, optimizing size of code etc. There are three main available approaches for source code optimization, that is Local Optimization, Global Optimization, and Inter-Procedural Optimization. In addition, this research aims to improve the Generic Code Clone Detection (GCCD) model. GCCD tool is a prototype which is used for detecting code clones. Before enhancing the GCCD model with source code optimization, this research will study about multiple code optimization techniques, its approaches and also the overall structure and processes of GCCD model in order to apply code optimization as part of the process in the GCCD model. Besides that, this research focuses only on the local optimization approach. To obtain the results, datasets from the Bellon’s benchmark for Java will be used for evaluation purposes. There are four (4) steps in the method used in this research, first step is to review the GCCD model and its functions in order to understand its processes and how the model works. Second step is to review code optimization techniques. Third step is to apply code optimization technique as part of the process in GCCD model. The fourth step is to compare the enhanced and original version of the GCCD prototype tool as an evaluation. As a result of this research, an enhanced version of the GCCD prototype is created by implementing and integrating code optimization processes into the GCCD model which will aid the prototype tool to detect better quality code clones. As a conclusion, the improved and enhanced GCCD prototype tool will run in accordance with its original functions without having to change its expected output but can be executed with a better performance.
Poster: simFIDO – FIDO2 User Authentication with simTPM

WebAuthn as part of FIDO2 is a new standard for two-factor and even password-less user authentication to web-services. Leading browsers, like Google Chrome, Microsoft Edge, and Mozilla Firefox, support the WebAuthn API. Unfortunately, the availability of hardware authenticators that support FIDO2 authentication is still focused heavily on desktop computers, while for mobile devices, only a limited choice of suitable authenticators is available to users (few roaming authenticators with wireless connectivity and evenfewer built-in platform authenticators on mobile devices). This creates a void for users, in particular users of older device generations that lack platform authenticators and the right connectivity, to authenticate themselves with WebAuthn to web-services.In this poster, we present the idea of simFIDO, a FIDO2 setup using a recently developed simTPM as (platform) authenticator for mobile devices and even as roaming authenticator offered by mobile devices to connected computers. The move-ability property of the key storage of simTPM makes the users’ lives easier for credentialportability between devices. In particular, a seamless integration of simTPM with non-mobile devices through phones will help to create a kind of universal authentication setup using FIDO2.Although we present the concrete design and implementationof a SIM card-based FIDO2 authenticator, we hope this poster will contribute to the discussion about how and in which form hardware authenticators can be made available to users.
SYSTRAN @ WAT 2019: Russian-Japanese News Commentary task

This paper describes Systran’s submissions to WAT 2019 Russian-Japanese News Commentary task. A challenging translation task due to the extremely low resources available and the distance of the language pair. We have used the neural Transformer architecture learned over the provided resources and we carried out synthetic data generation experiments which aim at alleviating the data scarcity problem. Results indicate the suitability of the data augmentation experiments, enabling our systems to rank first according to automatic evaluations.
Pendampingan dan pelatihan Google APP dan design grafis pada eksekutif Muhammadiyah D.I. Yogyakarta

Executive Secretary in the Muhammadiyah D.I. Yogyakarta in carrying out its technical duties, namely compiling Term of References (TOR) activities, arranging the schedule of leadership activities, as well as making quotes or flayers containing the socialization of activities and leadership recommendations that can be disseminated on social media often experience difficulties. The problem that often arises in the form of the compilation of TOR is quite long because it is waiting for the leadership's approval, less creative preaching of the virtual world. To facilitate the tasks of the executive secretary in overcoming the problem, a tool is needed. Tools that are very likely to be used for this are the google app which is quite popular and easy to use and has been integrated with a smartphone. Meanwhile, for the sake of making the proposal template design and activity socialization flayer, the leadership committee will use the Corel Draw application. So to facilitate the Muhammadiyah executive, it is necessary to arrange a Mentoring and Training Program for the Utilization of Google App and Corel Draw. This training is expected to specifically provide executives with ease in carrying out their duties and generally make Muhammadiyah D.I. Yogyakarta is easier to manage its program activities besides that the world of Muhammadiyah's online da’wah is increasingly creative.
Comparative evaluation of tabu search hyper-heuristic against its low-level meta-heuristic constituents

Hyper-heuristics present a superior form of hybridization of meta-heuristics. Unlike typical meta-heuristic hybridization, which requires low-level integration of two or more metaheuristics, hyper-heuristics offer meta level separation (as domain barrier) of each participating low-level meta-heuristic and permit adaptive selection between them. Owing to the prospects of improving the generality of its application to general optimization problems, this paper evaluates the performance of a Tabu search based hyper-heuristic (called HHH) against its individual low-level meta-heuristic (LLH) constituents. The results based on its application to t-way test suite generation problem indicate that HHH outperforms all its individual LLH constituents consisting of particle swarm optimization (PSO), global neighbourhood algorithm (GNA), cuckoo search (CS) algorithm and teaching learning-based opthnization algorithm (TLBO). However, there is a time performance penalty as overhead to perform the nmtime adaptive selection of each LLH.
Adaptive Graph Planning Protocol: An Adaption Approach to Collaboration in Open Multi-agent Systems

The adaptive system requires each agent to provide effective adaptive scheme in runtime according to dynamic changes in the environment. This paper offers an Adaptive Graph Planning Protocol (AGPP) that uses the Goal-Capability-Commitment (GCC) meta-model to dynamically reconstruct. The method uses the concept of capability to represent the executable capabilities possessed by the Agent, and introduces the concept of context state to represent the dynamic environment in the adaptive system. The adaptive graph planning protocol generation method is optimized by calculating the semantic matching degree of the context state. To evaluate the effectiveness of our approach, we provide an experimental scheme based on intelligent robot parking system (IRPS). This scheme verifies the execution time efficiency of this method and the adaptive efficiency of offline in case of emergency.
Ultrasound Findings of MammographicallyDense Breasts in a Sample of Iraqi Female PatientsDOI:https

Background: Breast problems including breast cancer have been increasing in Iraq during the recent years. Yet, early detection and screening programs using mammography mainly with complementary ultrasound had dramatically decreased the mortality rates from this emerging disease.&#x0D; Objective: To assess the dense breast detected by mammography for the presence of any hidden&#x0D; suspicious lesion by using ultrasound.&#x0D; Patients and methods: this is a cross - sectional study on 53 female patients who came for breast cancer&#x0D; screening or attended the Breast Clinic in the Oncology Teaching Hospital of the Medical City Complex in Baghdad –Iraq. The study was conducted from January to October 2018. Two -view mammography was done for each breast, and those with dense breasts underwent further ultrasound assessment done by a board-&#x0D; certified radiologist.&#x0D; Results: The mean age for the 53 patients included in the study was 48 years. Mammographic findings&#x0D; showed that heterogeneous fibroglandular tissue density was present in (89%) of the study population.&#x0D; Suspicious or clearly defined mass(es) by mammograph were seen in 16 (30%) of the patients, while no&#x0D; mass was identified in (22%). Ultrasound findings we re as follows: Suspicious mass in (75%) of the cases&#x0D; and benign lesions such as simple cysts or fibroadenoma in (9%). The results showed that ultrasound has&#x0D; upgraded 12 cases that were diagnosed as BI -RADS I/II to BI-RADS IV/V and this represented (23%) of&#x0D; the cases. On the other hand, the mammogram and the ultrasound were in concordance for BI RADS&#x0D; IV/V in 28 cases (54%). The positive predictive value of the ultrasound and the mammogram for BI -&#x0D; RADS IV and V breast lesions is 72% for BI - RADS IV and 95% for BI - RADS V for ultrasound and that of mammograph is 83% for BI - RADS IV 80% for BI- RADS V, while the negative predictive value of mammograph is 55% for BI - RADS I/II 25% for BI - RADS III.&#x0D; Conclusion: Dense breast is still an important problematic issue in mammographic screening as it may&#x0D; obscure small lesions, for which, ultrasound is proved to be a complementary and essential targeting tool&#x0D; in the assessment process.
Spatial Condition in Intuitionistic Fuzzy C-Means Clustering for Segmentation of Teeth in Dental Panoramic Radiographs

Dental panoramic radiographs heavily depend on the performance of the segmentation method due to the presence of unevenly illumination and low contrast of the images. Conditional Spatial Fuzzy C-mean (csFCM) Clustering have been proposed to achieve through the incorporation of the component and added in the FCM to cluster grouping. This algorithm directs with consideration conditioning variables that consider membership value. However, csFCM does not consider Intuitionistic Fuzzy Set to take final membership and final non-membership value into account, the effect does not wipe off the deviation by illumination and low contrast of the images completely for improvement to skip some scope. In this current paper, we introduced a new image segmentation method namely Conditional Spatial in Intuitionistic Fuzzy C-Means Clustering for Segmentation of Teeth in Dental Panoramic Radiographs. Our proposed method adds hesitation function aiming to settle the indication of the knowledge lack that belongs to the final membership function to get a better segmentation result. The experiment result shows this method achieves better segmentation performance with misclassification error (ME) and relative foreground area error (RAE) values are 4.77 and 4.27 respectively.