Reviewerly/exHarmony huggingface dataset:
A closed-loop FDSST algorithm based on SVM

The open-loop nature of target trackers makes them susceptible to degradation caused by background interference and hence target loss. To solve this problem, an improved closed-loop tracking algorithm based on Fast Discriminative Scale Space Tracker (FDSST) is proposed in this paper. The algorithm uses SVM to build a verification module to verify the tracking results, and outputs tracking state information with a state machine. The system uses different update rate adjustment strategies for different states to reduce the impact of background on the tracker. When the target is lost the re-detection module built from the SVM is activated, thus the system has closed-loop characteristics. The results on the OTB50 dataset show that the algorithm outperforms some mainstream algorithms in both success rate and distance accuracy, and has strong resistance to occlusion. The tests on the Hi3559A platform show that the algorithm has great real-time performance.
Creating a Résumé Parsing, Screening and Shortlisting System

The objective of this project is to create a résumé shortlisting system using natural language processing.
News Headline Summarization

Text summarization is all about converting a bunch of paragraphs into a few sentences that explain the whole document’s gist. There are hundreds of applications in every industry, given the amount of text data. Text data is increasing exponentially. A lot of time is needed to analyze, understand, and summarize each piece of it.
Analysis of linkage type sea wave power plant design through motion study and 3D printed modelling

Abstract Sustainable energy generation is becoming increasingly important because of the expected limitations in current energy resources and for reducing pollution. Wave energy generation has seen significant developments in recent years. This research has produced a linkage-type PLTGL design that utilizes ocean waves to raise and lower the float lever and move the linkage mechanism which then causes a back and forth movement of the rack gear which will rotate the pinion and cause the dynamo drive shaft to rotate. Using ocean wave data in the waters of Tanjung Berikat, Bangka Tengah, and with the help of the SolidWorks application, this design is then simulated to determine the resulting movement and rotation. The rotation generated through the simulation can reach 532 Rpm with the assumption that it does not involve friction forces and material loads that exist in the PLTGL design. This design was made in 3D using the CR-10 V3 type 3D printing machine which produced a model with a scale of 25% of the original design. The model is used as a discussion material for designers to improve the design.
Allocation of Vehicle Based on the Availability Using Machine Learning

Allocation of vehicles Based on the Availability using Machine Learning can track/estimate the movement of people and provides real time location to the transportation department enabling them to understand the demand and based on this they might take necessary steps to mitigate the load on their system. This idea leads to better cost efficiency and maintains a constant balance between supply and demand of the transportation system and it also reduces discomfort to the end user. Individually more towards observing the forecast of buses order causing take up as an interconnected job, and individually build an attribute descent element located continuously in the time series algorithm, multi-task learning and SARIMA algorithm towards taking up non-stationary attributes simultaneously. We have considered the previous data record and in addition to that we have included another mobile application wherein we can get the information of the pickup location predicted.
Design of electronic sand table interactive system based on depth enhancement algorithm

In order to better ensure the display effect of electronic sand table, an interactive system design of electronic sand table based on depth enhancement algorithm is proposed. The interactive system structure based on electronic sand table is designed, and the depth enhancement algorithm is used to identify the agent, position tracking agent, speech recognition agent and gesture recognition agent; By optimizing the hardware structure of the system, and improving the system software function and operation process, the operation efficiency of the system is guaranteed. Finally, the usability of the system is tested through experiments. The experimental results show that the design of electronic sand table interactive system based on depth enhancement algorithm has high practicability and fully meets the research requirements.
The Race-Timing Prototype

The disclosure of transient execution attacks, such as Meltdown and Spectre, has once again highlighted the threat of cache side-channel configurations. It has now been demonstrated that the cache hierarchy of modern processors functions as a micro-architectural medium where the transient execution may leak private data, in addition to also serving as an attack surface that adversaries can use to directly spy on victim programs. As a response to tamper the effectiveness of cache side-channel configurations, hardware manufacturers, and most notably AMD, have now opted to reduce the processor&#x2019;s cycle counter resolution to prevent adversaries from mounting side-channels in the higher levels of the cache hierarchy, specially in the L1D cache. This partially works because classic cache side-channel techniques, namely Prime+Probe or Flush+Reload, heavily rely on the processor&#x2019;s cycle counter to detect changes in the cache state, which is normally done by tracking cache hits and misses. Yet, we present The Race-Timing Prototype to prove that devoted adversaries no longer rely on the processor&#x2019;s cycle counter resolution to effectively distinguish cache hits from misses, and that a cache side-channel can still be configured by only utilizing controlled memory race conditions. In view that our implementation is hardware agnostic and does not rely on any proprietary instruction set extension, we demonstrate that our prototype works on processors from both Intel and AMD. Additionally, with propose a new semantic of Out-of-Order Detachment that further allows our Race-Timing measurements to closely match the accuracy of hardware Performance Monitoring Counters to distinguish fast L1D and L2 cache accesses in Intel processors. Ultimately, this work demonstrates that an adversary can exploit a cache side-channel with high-precision timing, and without utilizing cycle counters at all.
BUDI: Building Urban Designs Interactively A Spatial-Based Visualization and Collaboration Platform for Urban Planning

BUDI (Building Urban Designs Interactively) is an integrated 3D visualization and remote collaboration platform for complex urban design tasks. Users with different backgrounds can remotely engage in the entire design cycle, improving the quality of the end result. In BUDI, the display and interactive environment were designed to seamlessly expand beyond a traditional two-dimensional surface into a fully immersive three-dimensional space. Clients on various devices connect with servers for different functionalities tailored for various user groups. A demonstration with a local urban planning use-case shows the costs and benefits of BUDI as a geographic information visualization and spatial-based collaborative platform. We consider the trade-offs encountered when trying to make the collaboration seamless. Specifically, we detail the multi-dimensional data visualization and interaction the platform provides, and outline how users can interact with and analyze various aspects of urban design.
Design a bee calling tool using a caller voice and honey scent based on arduino and the blynk application

Abstract Bees have the characteristics of always moving and will settle in one place because of the source of nectar. Bees use smells (pheromones) as a means of communication. In addition, bees also communicate through body movements called dances waggle and have a frequency range of 200 Hz - 300 Hz. Communication on bees serves to contain information about what will be done by a bee colony. Therefore the authors assume that honey bees can be called. So it is necessary to design a tool that can summon honey bees using the caller’s voice and the aroma of honey. The tool is controlled using Bluino and the Blynk app. The test was carried out using the caller’s voice in the frequency range of 265.9 Hz – 297.2 Hz which was obtained from the sound recording process in the bee colony Apis cerana, so the focus of this research was the process of calling bees Apis cerana. The aroma used is the aroma of resisting honey, the aroma of sugar water, and the aroma of bee attractants. From the results of testing using three kinds of scents for 7 days, the number of bees is called as follows. The aroma of honey against 837 tails, the aroma of sugar water 758 tails, and the aroma of attractant bees 118 tails. Based on the results of the study, the bee-calling device using the aroma of resisting honey was more dominant to use.
Design and Implementation of IoT based Cloud enabled Wireless Biometric Monitoring Device

This paper presents the design and implementation of IoT enabled, wireless, cost effective, and low power consuming biometric device that would allow to monitor health attributes of patients remotely. The designed device powered by AtMega microcontroller can sense the medical information such as body temperature, pulse rate, blood pressure, and oxygen saturation using various sensors and push the data onto the cloud server using Wi-Fi. Cloud computing algorithms are incorporated to detect anomalies in the uploaded data. Anomalies can be notified to experts through customizable emails and text messages. A Bluetooth based interactive Android application has also been developed to function as user interface and share medical data.
I <i>general extenders</i> nel testo scritto, tra lessico e punteggiatura

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Computer prediction model for health status using classification tree models and Big data digital image

Breast cancer is the most common cancer for females worldwide. The literature presents a comparison of four machine learning algorithms: Classification Tree, Pruned Classification Tree, Bagging, and Random Forests on the Wisconsin Diagnostic Breast Cancer dataset by measuring the test sensitivity, specificity, precision, negative predictive value, and misclassification error rate. The result shows that the performance of pruned classification tree is better than that of a normal classification tree; aggregated tree models (Bagging and Random Forests) are is better than only use one single decision tree to predict. The best tree model is Random Forests which has the lowest test misclassification error rate of 2.92%.
Ontology Construction and Reasoning of Air Defense and Anti-missile Assistant Decision Based on Distributed Operation

With the rapid development of big data technology, the battlefield situation space of air defense and anti-missile has been extended to six-dimensional space such as land, sea, air, space, network, and electricity. The wide-area distribution of combat resources makes the resource organization more difficult and unable to deal with the rapidly changing battlefield situation in time. According to the different operational requirements of the multi-stage battlefield situation of air defense and anti-missile, based on the concept of distributed operation, this paper decomposes the operational resources according to the functional elements and puts forward a distributed air defense and anti-missile architecture with on-demand service, dynamic adaptation, and independent cooperation. The air defense and anti-missile combat resources auxiliary decision ontology (ADACR) is constructed by ontology modeling, and the combat rules are established based on SWRL language to realize the matching of battlefield situation, combat services, and combat resources, and quickly generate the combat resource organization scheme, to provide strong support for emergency decision-making under complex battlefield situation.
Application of Recommender System in Standardization

Recommender Systems are popular in domains such as Entertainment, Ecommerce, Social, Job however there are many new domains where it can play a useful role. In this Paper, Application of Recommender system is proposed in Standardization area to recommend set of Consortiums to Technology Organizations for membership. Consortiums (such as The Open Group, Object Management Group and others) specialize in one or more than one area(s) and active in Standardization. To formalize their work as International Standard, they Liaison with ISO Sub Committee(s)/Working Group(s) where they work with other Participants and after due process publish the work as formal International Standard. Due to Technological evolution, multiple such Consortiums are emerging as a Long Tail where the most popular Consortium gets more focus than others. In this Paper, the Proposed Recommendation Engine uses the Consortium Focus Area Attributes and membership details to recommend the most suitable set of Consortiums to Technology Organizations.
Intelligent Search Method in Power Grid Based on the Combination of Elasticsearch and Knowledge Graph

The accurate search of professional knowledge in power dispatching systems, enterprise technical standards, and other power business documents is significant for power dispatching personnel to make decisions and improve work efficiency. The existing methods to solve the power search focused on paragraph search, few of which consider locating the question to the precise answer. This paper proposes an intelligent search method based on the combination of Elasticsearch and Knowledge Graph for power dispatching and equipment technology, which improves the accuracy of searching enterprise technical standard documents. This method is based on Elasticsearch to prefilter the contents of paragraphs and reduce the search scope. Further, in a small range of paragraph content, based on the knowledge graph of triples and problems to match fine granularity, to achieve the power enterprise technical standard documents intelligent accurate search. A real-world data set is used in the experiment, and the results verify the effectiveness of the proposed method. Finally, a prototype system for knowledge search of power grid dispatching system is constructed. (Lucene is a set of open sources libraries for full-text search and search, supported and provided by the Apache Software Foundation. Lucene provides a simple but powerful application interface for full-text indexing and searching.)
An Novel Multiple Hypothesis Tracker with Adaptive Clutter Estimation for Heterogeneous Scene

In most existing multiple hypothesis trackers (MHT), the clutter intensity is usually assumed to be prior known, and the clutter intensity can be expressed as the product of the probability density of clutter spatial distribution and the average number of false alarms caused by clutter per scan. To improve the target tracking performance of the MHT in heterogeneous scenes, we proposed a new novel MHT algorithm with clutter estimation based on adaptive Gaussian mixture model (GMM). Firstly, the adaptive GMM is utilized to fit the spatial distribution of the clutter, and the clutter intensity is estimated. Then, the clutter intensity is applied to the MHT method to effectively improve the accuracy of track score calculation and optimal hypothesis track estimation. The simulation results demonstrate that the proposed method obtains better data association accuracy and track maintenance performance than the standard MHT algorithm and the MHT-GMM algorithm in an unknown heterogeneous clutter observation scene.
A New Stegano-Cryptographic Approach for Enhancing Text Data Communication Security

As the use of smartphones, laptops, and computers grows, these devices have become indispensable in our daily lives. We are exchanging a great deal of data via the Internet. Many of this data are very confidential, which include banking credentials, national secrets, and defence strategy, among other things. Steganography and cryptography are two fundamental areas of security that deal with delivering information or data via media like the Internet. Steganography is known as concealing information in a message, while cryptography is the method of encrypting the message. They are both utilized to keep things safe. However, none of them can easily meet the basic security requirements, such as robustness, undetectability etc. As a result, a new technology known as Stegano-Cryptography is being developed, which combines steganography with cryptography to overcome each other's shortcomings and make it harder for attackers to assault or steal important information. This paper proposes a new method where a text is first turned into a stego object using a suitable steganographic technique, and then the stego object is encrypted using the AES encryption algorithm. Thus, this approach can enhance the security of text data communication.
Research on the Construction of Teaching System about BIM Series Courses of Engineering Economics and Management Based on Bayesian Network

According to the repositioned training goal of civil engineering talents based on BIM technology, the existing teaching system of engineering economics and management courses should be reformed based on the engineering application value of BIM technology and combined with the current situation of social demand for BIM application talents of civil engineering specialty. According to the observation and statistics of the professional knowledge required by the market, the paper seeks the most likely Bayesian network model and puts forward a teaching system construction method based on Bayesian network. On the basis, the paper could further analyze the individual learning process, evaluate the suitability of relevant individuals according to the results, and put forward teaching suggestions.
The Multiclass Classification of Objects Based on Multispectral Images Recognition

This article considers the solution to the multiclass classification of objects with the help of its multispectral images. To solve this problem, we use a neural network, which we created in Python, using the libraries TensorFlow and Keras. The article analyses similar projects and describes the stages of choosing methods for solving the problem, establishing the optimal parameters of the neural network model, its creation, training, and use.
Using the neural network in clinical systems

Abstract The article examines the identification of human bone fractures using convoluted neural networks. The method of recognition of photographs of patients is intended for automated systems of identification and video recording of images. Convolutional neural networks have a number of advantages, such as invariability when reducing or increasing image size, immunity to photo movements and deviations, changes in image perspective, and many other image errors. In addition, convolutional neural networks allow you to combine neurons at a local level in two dimensions, connect photographic elements in any place, and also reduce the total number of weights. The work describes a multi-layer convolutional network. The layers of which it consists are divided into two types: convolutional and sub-selective. Of interest is the use of the principle of weighting in the work. This principle allows you to reduce the number of characteristics of the neural network that can be trained. Network training is based on the rule of minimizing empirical error. This rule is based on the algorithm of inverse error propagation. This algorithm provides an instant calculation of the gradient of a complex function of several variables in case the function itself is predefined. Neural network training is based on probabilistic method. This method leads to more optimal results due to interference in the restructuring of network weights. The work confirms the axiomatics of the applied neural network, its architecture and its learning algorithm.
Fixed Attribute Value Removal Method and Anomaly Based Profiled Method, An SQLi Detection Effectiveness Study

In this work, performance of two existing SQL injection detection methods is compared and analysed together. The first existing method uses removal of SQL query attribute values method, and the other one uses database profiling technique in detecting malicious SQL query in SQL injection attacks. Both detection method algorithms are implemented and tested using SQL query log generated from DVWA and Mutillidae web applications. Analysis and evaluation from results of the experiment showed that detection method based on the considered database profiling method is found to be much flexible and more effective. Nevertheless, it was found that the former method still has some room of improvement that could be done. Therefore, improvement on the former method is proposed that increase the effectiveness of the method to distinguish non-malicious query and the malicious query during the SQL injection detection process.
Individual Independent Work as a Means to Raise the Quality of Future Technology Teachers’ Professional Training

The paper aims to reveal the influence of individual independent work on future technology teachers’ professional training. The article introduces the notion “individual independent work”, determines the purposes of individual independent work, reveals its specificity, considers the potential of individual approach as a means to improve the efficiency of future technology teachers’ independent work. Scientific originality of the study involves developing the methodology of organizing individual independent work, which allows improving educational process quality. The research findings are as follows: the author proposes measures to increase the efficiency of individual independent work, justifies the thesis that individual independent work contributes to improving professional training quality.
Campus Computer Network Construction Simulation and Cyber Security Technology

Abstract With the rapid development of the network age, the network has become an indispensable part of our daily life and work. Computer network is also an indispensable part in campus. How to build a suitable computer network according to the campus environment has become an important problem. Then, while improving the level of network security management, it helps the school carry out its work smoothly. Therefore, this paper expounds the construction scheme of campus computer network, so as to help the campus computer network more perfect.
Features of patriotic education of persons studying in educational institutions of the Ministry of Internal Affairs of Russia

The latest changes made by the state to the content of the Federal State Educational Standard for Higher and Secondary Education reflect the increased attention paid to the educational component of the unified educational and training process implemented by all educational organizations in the territory of the Russian Federation. Planning and implementation of educational impact on students has now become an independent element of the educational process. We believe that a purposeful process of educational activity is unthinkable without such a basic element as patriotic education. This study is devoted to the peculiarities of the processes of organization and practical implementation of patriotic education of persons studying at universities and educational institutions of the Ministry of Internal Affairs of Russia.