Reviewerly/exHarmony huggingface dataset:
FPGA Implementation of Real-Time Soldier Activity Detection based on Neural Network Classifier in Smart Military Suit

The wearable technology carries sufficient potential to incorporate smartness into working of the military workforces like the Military Control Unit, Medical Responders, Backup Unit and War Strategist. The proposed work focuses on real-time soldier activity detection, which is essential for the operation of the smart military suit. The customized Artificial Neural Network (ANN) IP core is developed for the soldier activity classification, which is an integral component of suit gateway design. The multilayer perceptron (7-5-4) classification algorithm is implemented on the low-cost (99$) FPGA evaluation platform by using Xilinx vivado and system generator development tools. The training (70%) and testing (30%) of this ANN design is performed on the UCI human activity dataset. The LabVIEW GUI and IP test design completed the hardware testing of this IP. The presented ANN IP is able to achieve 98.5% classification accuracy by utilizing minimal FPGA (Artix-7 xc7a35t) resources. The implemented ANN design requires only 285 nanoseconds for a classification and consumes 103 milliwatts of dynamic power. The system's accuracy at different development levels is also studied in this work.
Modeling and predicting dynamics of heterogeneous workloads for cloud environments

The services and applications deployed nowadays in cloud environments are characterized by variable intensity and resource requirements. The variability of these workloads coupled with their heterogeneity affects the cost associated with the cloud infrastructure and the performance levels that can be satisfied. In these complex scenarios, resource provisioning policies have to take into account the actual workloads being processed and pro-actively anticipate in a timely manner the changes in workload intensity and characteristics. To support this decision process, we propose an integrated approach - that combines various workload characterization techniques - for modeling and predicting workload access patterns. The application of this approach has shown the importance of identifying models that specifically capture and reproduce the dynamics of these patterns and consider at the same time their peculiarities.
Let's Do Feature Driven Scrum

Agile manifestos are used in the software industry and now it has expanded into the education, teaching, and workspace environment. Agile development methodology is currently being tested in certain non-software systems. It supports better organization and rapid feedback for the users that can be acted upon or modified. Our study presents an amalgamation of Feature Driven Development and Scrum methodologies from Agile into a new ensemble method "Feature Driven Scrum." This ensemble method is implemented in an online study group and an educational workspace environment. The results indicate that Agile goes well in an educational workspace but there are some shortcomings when Agile is used in an online study group.
FORMATION OF PROFESSIONAL COMPETENCES OF PHYSICS TEACHERS

Currently, the problem of training specialists on the basis of the competence-based approach is being actualized. Competence-based approach is the direction of training specialists in knowledge and skills acquired for application in future practical work. The article provides information on the professional competencies of physics teachers and their training system.
Deep Tracking Students Identity and Motion in Classroom

Our focus here is tracking on identity and head pose of students for helping educational teaching in classroom. By using computer vision technology, we are able to extract identity information and head pose from all students in the video stream from the classroom in real-time. Firstly, merging multi-scale feature map for solving the crowd face detection in classroom. Secondly, multiple face recognition and tracking in the classroom, based on the database of student's multi-view facial images. Finally, face landmark detection based on 68 points was improved with neural network. After calculating the three-dimensional angle of the head pose, we attempted to analyze the correlation with the four motion of students by observing time series of the three angle changes, and configured the hybrid model and the training support vector machines (SVM) classifier, to achieve the correct rate of 85.86%.
Development and Trial of a Marine Education Program with an Emphasis on Earth Sciences - Class practice incorporating seabed topography and sea-level change

Current marine education in elementary and secondary education rarely deal with sea-level change in the quaternary period and the submarine topography formed due to this process. Therefore, we developed and implemented an educational marine program incorporating these elements. The contents of the program are as follows:
Outlook Change From Print to E-Resources

Electronic information resources in libraries have made remarkable changes in the users' perceptions towards print resources. A survey among 421 respondents in six state universities in Kerala reveals that the use of e-resources is considered as an advantage and it benefits the academic community. While analyzing the use of e-resources compared to the print resources, the statement 'E-resources affect the reading habit so it is not be encouraged' is rejected because it is not an advantage. All 12 hypotheses set for ‘benefits of electronic resources for accessing scholarly information' are accepted because all the regulatory constructs have significant influence on benefit of e-resources.
Handling Structured Data Using Data Mining Clustering Techniques

In the new era, every organization has the capability to store the extremely large amount of data. The continuous rise in the capturing of data is turning it into a huge tomb of data. Such huge data is becoming difficult to get analysed. This constantly growing large data set is making the challenge to the researchers in discovering knowledge from it. Valuable information is buried under the huge collection of data which can be extracted by making the use of Data Mining technique, as it possess the ability to dig out the embedded precious information from the large datasets. Various application areas required this technique, thus, resulted into an evolution of many data mining methods. Though several data mining methods get evolved not all of them were capable to deal with high voluminous data. Numerous computation and data- intensive scientific data analyses are established to compete with the ongoing time. As today's data has got converted to Big data, it now require large-scale data mining analyses to fulfil its scalability and performance requirements. To serve such data, several efficient parallel and concurrent algorithms got applied. The parallel algorithms used different parallelization techniques to manage the huge voluminous data and brought them into real action. Formerly, these techniques were : threads, MPI etc. which produce different performance and usability characteristics. The MPI model was efficient in computing rigorous problems but difficult to bring them into the practical use. Over coming years, Data mining is continuously spreading its root in business and in learning organizations. The new integrated clustering algorithm called CURE became more vigorous to outliers and recognizes those clusters that were having irregular shapes and are of variant size. CURE is formed with the combined features of random sampling and partitioning which assured that the quality of output clusters produced by it is much improved with respect to those clusters that are resulted from the prior algorithms. This paper put focus on CURE clustering technique which found suitable for working with large databases.
Sound matching on the translation of Al-Quran ayat as a learning media for children using mobile-based fast fourier transform and divide conquer algorithm

Abstract In this paper, a sound matching application was built on the pronunciation of Ayat Al-Quran as a learning medium for children using the Fast Fourier Transform (FFT) Algorithm and Divide Conquer (DC) that support learning independently. The system built in the final project is to utilize the Google API feature on android as voice matching. Furthermore, the incoming sound will convert into text form using the Google API. The conversion method used is a Fast Fourier Transform (FFT). The valuation method, Divide Conquer is used by calculating the sound proximity value of the Google API conversion results by matching Arabic text in the database. Based on the testing that has been done on the system testing. The results of the test found 61.1% accuracy for the appropriate reading and 38.9% for inappropriate reading.
Enhancing the Usefulness of Blockchain Technology in Finance Sector

Blockchain technology has become widely popular with the appearance of cryptocurrencies that use the decentralized nature of blockchain in order to exchange funds between their users. In order to verify various needed details during an exchange, consensus mechanisms are used which solve simple but exhaustive calculations. Such operations fulfil their primary goal of verifying, but are a common target of public disapproval due to massive energy consumption and lack of usefulness. This work discusses different approaches and consensus mechanisms with a more useful secondary function, especially focusing on NP-complete problems as mediators in solving complex and resource-heavy problems. A new way of approaching these problems can benefit many areas, like science, healthcare, government and finance, optimizing the current infrastructure and business processes like markets, transactions, insurances, payments and supply chains, or creating more secure, reliable and efficient environment.This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Towards Rehabilitation of Mughal Era Historical Places using 7 DOF Robotic Manipulator

The central aim of this research is to propose a solution to rehabilitate historic places using a robotic manipulator. In this pursuit, the objective is to clean flat or curved surfaces of mihrab/muqarnas and to write lost Arabic inscriptions on spandrel using 7 Degree of freedom (DOF) robotic manipulator. Inverse kinematics solution for 7 DOF is derived by fixing redundant joint and solving the remaining 6 DOF inverse kinematics. Image processing techniques are used to get data from the given image for the robotic calligraphy operation on the spandrel to restore the lost inscriptions. Path planning exercise is implemented to navigate the end-effector on the desired path to write lost inscriptions and to clean curved surfaces of muqarnas. Proposed solutions are verified by simulation using MATLAB. The results showed that the manipulator successfully tracked the given path to perform the desired operation in mihrab as well as calligraphy operation on spandrel.
Quality in Documentation: Key Factor for the Retrieval Process

This work aims to identify the latest progress, techniques and/or models implemented to improve the information quality in the information retrieval process, as well as the defined metrics to evaluate the quality of the content; therefore, a review of research work carried out in the last five years is presented, in the analysis carried out it was shown that 44% of the retrieval systems focus on improving the indexation of the documents allowing better accessibility, which leads to optimal growth at the time of extraction, the other 66% points to the quality of the response of the queries; as a result, it was found that the common factors that affect quality when searching, retrieving and representing the information available to the user, among which are user satisfaction, the quality of the classification and the quality of the text itself.
Face Recognition Based on Interleaved Neighbour Binary Pattern

Face recognition plays a key role in human face identification. This research work proposes a novel method, Interleaved Neighbour Binary Pattern (INBP) and the similarity measure histogram intersection for face recognition. The INBP is used to extract the facial features and improves the recognition rate under minor variations in expression, illumination and orientation. The proposed approach, INBP compares the interleaved neighbours rather than comparing the adjacent neighbours as in the traditional LBP. Extensive experimental results on three widely used face datasets JAFFE, ORL, YALE and OWN DATABASE show that INBP achieves better performance than traditional LBP for face identification under various conditions. The performance of the proposed approach is measured in terms of recognition rate, precision rate, accuracy, recall rate, f-factor and error rate.
Enterprise Service Bus Solution for an Efficient Development of Geodesic Monitoring Systems

Modern constructions are typically monitored with geodesic monitoring systems. One the most important challenges for these systems is represented by the complexity of developing new instance from the ones already set up. The solution introduced herein is based on a service oriented architecture, which in turn relies on an enterprise service bus as its principal component. The monitoring system consists of three principal components: measurement system, data cleaning and integration, and the deformation analysis tool. By employing the herein proposed approach these three components become loosely coupled. Herein, the focus lies on the component performing data cleaning and integration, consisting of three principal chains of services linked either serially or sequentially. The first chain manages the files containing the observations recorded by the tachymeters which perform the object monitoring. The second chain manages the data sent by the humidity and temperature sensors. The third chain performs preliminary analysis functions, and also makes the results public on a website. Error management at bus level is performed by a fourth chain in the ESB: it manages the issues of language level error handling and improves the transparency. Due to the loose coupling characteristics of the system, the components can be developed in parallel. Together with the improved flexibility and the greater reusability, this is a key aspect of a service oriented architecture.
Modeling of algebraic analysis of PRESENT cipher by SAT solvers

Abstract Paper presents approaches to algebraic analysis of the reliability of symmetric block ciphers by solving Boolean satisfiability (SAT) problem. A description of the application of decision search algorithms by the DPLL method is given. The principle of formation of the SAT problem for algebraic analysis of PRESENT cipher is proposed, as well as the parameters of the obtained SAT problems for a different number of cipher rounds and plaintexts.
Eye Gaze Controlled Head-up Display

A myriad of infotainment systems has found its applications in the automobile industry with the burgeoning demand for user comfort and interaction. However, operating such infotainment systems entertain secondary tasks to be carried out at the expense of the primary task of driving. This can increase the cognitive load on the driver and has the potential to keep road safety at stake. This paper presents an intelligent interactive head-up display (HUD) on the windscreen of the driver that does not require them to take eyes off the road while undertaking secondary tasks like playing music, operating vent controls, watching navigation map, and so on. The interactive HUD allows the user to navigate and make selections using eye gaze. The HUD also incorporates provisions to estimate driver’s cognitive load and distraction level. User studies show that the system improves driving performance in terms of mean deviation from lane in an ISO 26022 lane changing task compared to touch screen system and participants can undertake ISO 9241 pointing tasks in less than 2 s on average inside a car.
Design of a Stroboscopic Laser Grating Stripe Projection Device

A three-dimensional measuring system based on a line-structured laser and a high-speed rotating multi-faced prism has been designed and described in detail. The grating fringe can be produced using stroboscopic effect in the system. The relationship between grating stripe and modulation signal and prism rotation speed are analyzed from both theoretical and experimental aspects. At the same time, the grating stripe projection device is applied to the three-dimensional measurement of gypsum section.
Energy-Aware Parallel Computing for Cloud Architecture using ANN

In parallel processing, task scheduling is a way to assign task to different processors. A number of algorithms are used by parallel computing so that the time for executing jobs can be minimized. Presently, there are number of algorithms that are utilized for the enhancement of the execution time of task as well as to reduce the energy utilization. In this research, to resolve the energy consumption problem, the concept of load balancing has been introduced along with the Artificial Bee Colony (ABC) and Artificial Neural Network (ANN) techniques. ABC is used to optimize the properties of processors based on the appropriate selection of fitness function. On the basis of these optimized properties, ANN is trained and hence balance the load so that energy can be optimized along with minimization of makespan.
Towards a human-computer interaction model for voice user interfaces

The user interaction with computer systems has evolved over the years, from Command Line Interfaces (CLIs), Graphics User Interfaces (GUIs), Natural User Interfaces (NUIs) and actually Voice User Interfaces (VUIs). The use of VUIs is increasingly common, increasing user attention, facilitating the execution of tasks of users with non-technical training and taking advantages that hands and eye free interfaces provide in many situations. However, it is necessary to identify which elements are essentials for a great user experiences, what attributes need to be evaluated and which HCI testing methods apply to evaluate them.
miet: an R package for region of interest analysis from magnetic reasonance images

In a medical imaging study, a set of magnetic resonance imaging (MRI) data is generally stored as a hierarchy of folders containing MRI volumes.These volumes may correspond to a variety of e.g.subjects, subject-types, centers, acquisition types that structures the folders naming and hierarchy.Here is an example of such structure:
Algorithm for HTML Preprocessing in Email Messages

The paper presents an algorithm for preprocessing the HTML code of email messages; this is used in email client applications (such as Gmail App and Microsoft Outlook). The purpose is to create an easy-to-use tool, automatically inserting pre-declared styles from the <;head> tag to <;body> tag of the HTML document. The algorithm implements the main steps of the language processing: lexical analysis, symbol table construction, parsing and generation of preprocessed HTML code. These steps are described in the paper. Experimental results of running the algorithm are presented.
Gesture recognition by learning local motion signatures using smartphones

In recent years, gesture or activity recognition is an important area of research for the modern health care system. An activity is recognized by learning from human body postures and signatures. Presently all smartphones are equipped with accelerometer and gyroscopes sensors, and the reading of these sensors can be utilized as an input to a classifier to predict the human activity. Although the human activity recognition gained a notable scientific interest in recent years, still accuracy, scalability and robustness need significant improvement to cater as a solution of most of the real world problems. This paper aims to fill the identified research gap and proposes Grid Search based Logistic Regression and Gradient Boosting Decision Tree multistage prediction model. UCI - BAR dataset has been used to perform Gesture recognition by learning local motion signatures. The proposed approach exhibits improved accuracy over preexisting techniques concerning to human activity recognition.
Cooperative ant colony optimization for a hierarchical scheduling problem

Abstract An important part of modern integrated decision support systems in any area is scheduling. At the same time, domain knowledge can be extremely complex and includes numerous restrictions and process rules, which makes the corresponding optimization problem highly complicated. This paper is based on a hierarchical problem structure where the top-level problem is the travelling salesman problem, and the nested resource-constrained project scheduling problem is replaced by the simulation model. Cooperative ant colony optimization as well as other biology-inspired algorithms were evaluated on a set of generated problems, and the obtained experimental results are presented here.
Development of camlearn as mobile learning media for photography equipment course

Abstract Limited learning facilities in vocational high schools is one of the problems in vocational education. Not every schools with multimedia department have enough standard cameras. The solution and also the goal of this research is to discuss the development of Camlearn as mobile learning media that can be used in the multimedia department. Camlearn is an android-based mobile application that discusses the types of cameras and photography equipment. This research applies the steps of ADDIE research method including Analyze, Design, Development, Implementation, and Evaluation. Analysis, design and development activities are based on material requirements analysis that has been carried out using a questionnaire and interview methods for students, teachers and vice-principals of curriculum with a Likert Scale consisting of three research variables namely material aspects, media aspects, and application functionality. The results of the application product feasibility on the material suitability aspects are 80%, the media conformity aspects are 82%, and the product functionality aspects are 82%. Based on the results of the product development testing, it can be concluded that this research product has met the minimum eligibility test so that it can be declared feasible to be used as a learning media in the learning process.
Traffic Resolution Algorithms, Machine Learning and Sensors

Traffic detection software or applications already exist in the market today, be it embedded as a small aspect of a navigation app or a complete standalone individual platform but all of them have a sole purpose to detect the magnitude of traffic i.e. cars present in a particular area or a road. These technologies are also embedded many platforms which incorporate technologies like IoT and big data analytics which can determine the speed and location and even predict the many outcomes based on the heat signatures, fuel level, carriage etc. of many vehicles and help in live monitoring of such. Though all these technologies help in avoiding the traffic but no such technology can help in resolving the traffic once you are stuck in one. This paper talks about a proposition of a solution which by utilizing the present technologies in the market like mapping of traffic threshold and density analysis which works together with machine learning based algorithms and IoT enabled vehicles and passing instructions computed by the algorithm to each of the vehicles can help in achieving and resolving one of the most prominent problems faced by mankind today.