Reviewerly/exHarmony huggingface dataset:
The Effect of Electronic Management in Improving the Quality of Internal Audit through Developing the Performance of Internal Auditor: An Empirical Study in the Jordanian Insurance Companies

The purpose of this study is to reveal the impact of electronic business management on improving the quality of internal audit through the development of internal auditors' performance. Study sample consists of (21) internal auditors working in the Jordanian insurance companies. A number of (134) questionnaires were distributed and (106) of those were returned; which are considered as valid for statistical analysis. The study found an impact for the electronic business management on the development of internal auditors' performance in addition to an impact for the development of internal auditors' performance on improving the quality of internal audit. The main recommendation of the study was to emphasize the importance of training internal auditors and improve their capabilities to deal with the information that they use in the insurance companies.
Enhance Object Detection Capability with the Object Relation

The technique of image recognitions is becoming more and more important to identify objects, places, and people. Currently, several deep learning methods on image recognition have been proposed. To identify multiple targets, the notion of region proposal has proposed which uses multiple resolution methods to improve accuracy, such as R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, SSD, and YOLO. However, these improvements are based on pixel. Still, there are uncertain objects which the human eye observes in the surrounding scene. At this time, we make guesses based on other, more clear objects. In the paper, we propose a method for object recognition using the probability of correlation between the objects. When performing object recognition in an image, we calculate the probability of correlation between the objects to adjust the related parameters and the weight values. Our proposed method improve the overall recognition of objects in the image.
Effectiveness of mKRISHI® Personalised Advisory on Water and Soil (PAWS) in dissemination of agricultural information in north-western Himalayan region

The effectiveness of an extension system referred to its ability to meet the farmer needs in providing the new technology which suits to their conditions and results in better production. Recently the demand for information on agricultural practices and technology among the farmers is increasing day by day but fulfilment of these demands exclusively by public agricultural extension system is limited. To address this challenge, information communication technology (ICT) has the immense role in supplementing the extension system. Among the ICT tools, mobile phone, because of its affordability, accessibility, minimum skill requirement, widespread network etc., has emerged as important tool for information and knowledge dissemination to the smallholder and marginal farmers. But it is necessary to study how effective they are in achieving the respective objectives.The present investigation was conducted to study the effectiveness of mKRISHIÂ® PAWS (Personalised Advisory on Water and Soil) in Dehradun district of Uttarakhand state. An ex-post facto research design was used for this study. Total 136 messages were sent to the respondents. The data was collected from 240 beneficiary farmers of the north-western Himalayan region. The effectiveness of the mKRISHIÂ® PAWS in technology advisory and delivery services were measured by developing an effectiveness index for the purpose. Results showed that 93.8% of farmers perceive that quality of information regarding the latest NRM technologies in soil and water conservation was excellent and 83.75% of the farmers felt that the information regarding the latest NRM technologies in soil and water conservation was appropriate to their condition. The study revealed that the extension services delivered by mKRISHIÂ® PAWS were found to be highly effective by majority of the farmers. 34.58% farmers perceived that the mKRISHIÂ® PAWS was very highly effective as a mean of getting their information needs.
Wave Front Phase Imaging of Wafer Geometry Using High Pass Filtering for Improved Resolution

In this paper we show that Wave Front Phase Imaging (WFPI) has good enough lateral resolution and is sensitive enough to measure roughness on a silicon wafer by simply acquiring a simple image of the entire wafer. WFPI is achieved by measuring the reflected light intensity from monochromatic uncoherent light at two different planes along the optical path with the same field of view. We show that the lateral resolution in the current system is 24 μm but can be pushed to less than 5 μm by simply adding more pixels to the image sensor, and that the amplitude resolution limit is 0.3nm. Three 2-inch wafers were measured, and the roughness was revealed by applying a double Gaussian high pass filter to the global topography data.
Utilizing the Generalized Intelligent Framework for Tutoring (GIFT) for Human Factors Education

Human Factors educators teach a variety of different types of classes including in-person, mixed mode, and online. The Generalized Intelligent Framework for Tutoring (GIFT) is a free, open-source domain-independent intelligent tutoring system (ITS) framework that can be leveraged by Human Factors educators for use in their own classes. GIFT includes authoring tools that are easy to use and do not require a background in computer science or ITSs. This demonstration is interactive and shows an overview of the tools and features of GIFT that can be used by Human Factors educators. It also provides context by showing a GIFT course in a Human Factors relevant area, and discusses how GIFT has and can be used in the classroom. As GIFT is open-source and continually being developed, the presenters provide the conference attendees an opportunity to give feedback about useful improvements that could be made to GIFT.
Transient microscopic testing method based on deflectometry

The deflectometry provides an optical testing method with ultra-high dynamic range. In this paper, a microscopic testing method based on deflectometric technique is proposed to quantitatively evaluate the microstructures according to the wavefront aberration. To achieve the real-time and accurate wavefront testing for microstructure evaluation, a colorcoded phase-shifting fringe pattern is applied to illuminate the test object. It avoids the sequential projection of multistep phase-shifting fringes in traditional deflectometry, enabling the transient wavefront testing. The feasibility of the proposed transient microscopic testing method is demonstrated by the experiment. The proposed method enables accurate and transient testing of microstructures with high dynamic range, minimizing the environmental disturbance.
An Innovative Prediction Technique to Detect Pedestrian Crossing Using ARELM Technique

Monitoring Systems of Automobile Industries and Surveillance Systems use operations based on computer vision to identify objects in motion. Most such applications that employ, pattern identification techniques to detect person on road are done through feature mining and classifier development framework. A learned classifier is arranged over the method of recognizing features that are extracted from the video frames. In this paper, classification of pedestrian features is performed and subsequently the presence of pedestrians is predicted. A new classifier, named Asymmetric Least Squared Approximated Rigid Regression Extreme Machine Learning [ARELM] is proposed for the classification and prediction purposes. This classifier combines the strengths of aLs-SVM that deploys the expectile distance as the measurement for boundary values and RELM in handling the multi collinear data. The proposed classifier improves the accuracy in detecting the pedestrians among the navigating things and ensures better prediction, on comparisons with existing classifiers like SVM, BPN used for the same applications.
Development and Realization of "Xi Ma" Moving Target Detection and Tracking

In recent years, marathons have been held frequently in Xi'an, Xi' an marathon for the promotion of urban visibility and the development of urban culture have played a positive role in promoting. With the development of computer vision and image coding technology, the detection and tracking of moving targets has become a hot topic in the field of research. The target detection and tracking system based on "Xi Ma" movement combines XI' an marathon with moving target detection and tracking technology, which provides an effective solution to the problems such as the detection and trajectory tracking of marathon athletes in real competition. The system realizes the construction of the whole frame using Electron frame technology, and realizes the detection and tracking function of the target in the system by means of inter-frame difference method, regional-based convolution neural network and CamShift algorithm. Thus, it provides an effective scheme for the detection and trajectory tracking of marathon runners in real competitions.
Variability Extension to SparkS, a Domain Specific Scripting Language for Electronic Test Equipment

Initial version of SparkS, a domain specific scripting language for calibration automation of electronic test equipment, was designed as a single-task language. As we decided to make the language more powerful over time to make it support variations in equipment models, it also became clear that we need to give language a support for variability. In this work we present our approach for handling variability in SparkS. We also show our design and development of the methodology.
Frequency analysis of entanglement dynamics in coupled quantum oscillators

We study harmonic oscillators connected by periodic or quasi-periodic couplings in a common heat bath. Driving frequencies of couplings play an important role in sustaining entanglement among the oscillators, even in high temperature. Driving amplitudes and relative driving frequencies determine whether entanglement would occur, while the base frequency determines characteristic parameters of entanglement dynamics. Frequency properties of ripples in logarithmic entropy are investigated by FFT, in cases with multiple coupling terms. Finally, frequency landscape is given for controlling entanglement dynamics.
Node Performance Load Balancing Algorithm for Hadoop Cluster

Hadoop is an implementation of MapReduce algorithm[1]. It operates on Distributed, parallel systems. During the execution of MapReduce applications default hash Partitioning algorithm leads to uneven distribution of load among the reducer tasks. Because of this total execution time gets affected. Hence the algorithm is modified in which it collects the local information, combines them and distributes the data in order to avoid skew. Node performance Load Balancing algorithm is used to reduce the imbalance of the load among the reducers. Due to this the execution time taken to complete the task is reduced.
Testing Strategies in an Agile Context

Testing in an Agile context is extremely important, not only with its function to ensure quality but also to guide development efforts into the right direction. This is related to a shift in testing paradigms, with quality being viewed as a factor early on in product development, rather than a late-stage reactive activity. It also requires the application of different approaches, such as automation, to enable the flow of potentially shippable product increments. Many teams find themselves stuck into the old ways of testing, especially as they work on legacy systems. However, investment in upskilling quality experts, applying the proper tools, and changing the way testing is done can bring tremendous value and opportunities for innovation. Proper change management needs to be applied to enable teams transition successfully into an Agile mindset and new practices.
Objective reality of subjectivity: descriptors of sociality

The article discusses the features of psychological states in the context of the overall development of human culture. Culture is a combination of material and spiritual values accumulated by mankind in the process of development and a way of establishing social and personal interaction, that is, a way of suppressing or developing society of certain personality traits. Culture, being an extremely broad concept, has the status of a philosophical category, since it contains all the variety of semantic contexts created by three main worldviews: religion, science and philosophy.
Research on pedestrian occlusion detection based on SSD algorithm

As a basic identification technology, pedestrian detection provides technical support for many areas such as security monitoring and autonomous driving, and has a wide range of application scenarios. Based on the Single Shot MultiBox Detector (SSD) target detection algorithm, this paper trains a pedestrian detection system based on the SSD target detection framework with a self-built occlusion pedestrian dataset for the specific target of occlusion pedestrians. The test set and the re-annotated INRIA test set were used to compare the HOG+SVM based pedestrian detection system and the trained SSD model in OpenCV. The experimental results show that the detection effect of the SSD model is significantly better than the traditional pedestrian detection system based on HOG+SVM. The features learned by the deep convolutional neural network are more robust.
Global Smart Card ID Using RFID: Realization of Worldwide Human Mobility for Universal Validation

Today, human still carry number of cards to authenticate their identities across the globe. Smart cards possess potential to substitute all other existing IDs by smart card IDs at national and global level. Contemporary issues of terrorism and illegal migrants across many international borders too support the cause of seeking a viable solution. This paper has examined the evolution and necessity of human identification along with current worldwide scenario of existing national IDs. Integration of biometrics with smart card technology presents a strong authentication tool to the identity card holder. This paper offers an insight into the feasibility and technological aspects of this potential application. A recent trend of using radio-frequency identification (RFID) and biometric technologies for personal identification in e-passports and other applications too paves the way to explore a global identity solution [1]. However, apart from the technological challenges, there are policy and legal constraints imposed by various governments across the globe which acts as a barrier and has been briefly touched upon in this paper. In order to accommodate the massive global IDs, an IPv6-based numbering scheme has been proposed for identity registration and data access of every human across the globe in this research paper. The state-of-art technologies and IoT with its widespread usage facilitates this proposal of integrated global ID solution incorporating smart card with RFID and biometric technologies against a multipurpose universal ID framework [2]. This study has also highlighted the future promises and the major research impact of the proposed application.
Research and Simulate of Real-Time Particle Systems Based on GPU-Acceleration

Study on realistic simulation of natural scenery has always been one of the difficult and focused problems in the field of computer graphics. In order to solve the problem of time-consuming and inaccurate simulation of particle system, this paper proposed a particle system simulation based on GPU acceleration. This method used the geometric modeling of the particle system to extract the external characteristics of the flame and analyzed the influence of two external forces of gravity and wind force. It also introduced the simplex noise to control the particle behavior, and combined texture mapping, particle collision and other technologies to make sure better realistic quality and high efficiency. Experiments testify that the method can satisfy the requirement of the reality and the real-time of fire simulation, which got more realistic simulation effect. And further improvements had been made compared with the traditional flame simulation method.
Long/Short-Term Appearance Modeling and Two-Step Association for Multi-Object Tracking

Vision-based multi-object tracking has many potential applications in intelligent transportation systems and intelligent vehicles. Tracking by detection, as a popular approach to multi-object tracking, first obtains detection responses from video sequence and then associates them into tracks for every object. Existing tracking-by-detection methods can work well in constrained scenarios. However, in those complicated scenarios with occlusion and adverse illumination conditions, the detection stage is deteriorated and thus makes it difficult to track objects accurately. In this paper, we present a robust tracker that represents object appearance using stable temporal features and associates the detection responses through a two-step association process. We propose to use Bi-LSTM (Bidirectional Long Short-Term Memory) to model object appearance and obtain reliable temporal features. Then, we estimate the affinity between tracks and detections based on multiple cues including appearance, motion and shape, and integrate the affinity into a two-step association procedure. Our method is verified on MOT datasets and the experimental results are promising as compared to the state-of-the-art.
Students' Initiative Development Technologies

The unity of the word, pattern and practice requires the development of initiative among students. The formative influence should serve to ensure sustainable organization mechanisms and the development of student initiative resources, as well as behavior management. Based on the results of the study, we came to the conclusion that the technology for the development of initiative in students should be carried out on the basis of the “show an example - explain - train” behavior model.
Communication Optimization of Compute-Intensive Clusters Based on Software-Defined Networks

Data transmission among nodes in compute-intensive cluster with MapReduce is a major performance bottleneck. In order to optimize network communication performance, a distributed data mapping model is constructed for big data computing jobs. Firstly, the mapping model extracts the spatio-temporal features of the input data of computing jobs, and optimizes job data layout by replacing storage locality with communication locality. Secondly, decision-space transformation is used to classify calculation jobs, and big data calculation jobs are divided into two categories: communication-intensive and non-intensive. Finally, the data communication of computing cluster is managed by software-defined network, and communication-intensive jobs are mapped to nodes of high-quality link by using global sensing capability of software-defined network to improve the communication performance of intermediate data. Experiments show that the model has better communication optimization effect for data communication-intensive jobs, and data transmission delay is reduced from 4.2% to 5.7%. Therefore, this communication optimization scheme is suitable for data center or large-scale cluster communication optimization, and adapts to various big data scheduling strategies and multiple network topologies.
Route Planning for Vehicles with UAVs Based on Set Covering

Due to the complexity of the last mile delivery, the emerging business called “just-in-time delivery” often has a strict service range limit. As a newly received method for last mile delivery, the UAVUAV can expand the service range of just-in-time delivery with the assistance of vehicles. This paper proposes a model based on the set covering model to locate the UAVUAV take-off point. After that, an improved ant colony algorithm is used to obtain the locationLocation result. Finally, the customer’s allocation method is proposed. Both methods are tested with randomly generated data and proved to be effective. It provides a reference for the future practice of the just-in-time delivery business.
Effective approach to protect images by using both cryptography and steganography

We proposed a new method of protective covering of images by using crystography which is a combination of both cryptography and steganography. We have applied a crystography in a different way. In this paper, first the image is segmented and then those segmented parts are encrypted by the different encryption algorithms. We have explained this in separate sections. In Section I, introduction of the approach, in Section II, discussed about the history of this approach, in Section III, discussed about the procedure of this approach, in Section IV showed the experiment results, in Section V, comparison of the existing system and proposed system. Finally conclude.
Psychological and pedagogical follow-up of younger students with special abilities in terms of global education

The main approaches to the model designing of psychological and pedagogical follow-up of students in the context of contemporary global challenges are disclosed in the article; the designing principles, the structure of the model of psychological and pedagogical follow-up of students with special educational opportunities are also described in the article; it also presents humanitarian technology of psychological and pedagogical guiding and support for students with special educational capabilities, changing the position of the teacher in educational and extracurricular activities.
Realization Methods of Computer-aided Diagnosis System of Medical Images

In this paper, medical images are used to realize the Computer-Aided Diagnosis (CAD) system, which develops targeted solutions to existing problems. Relying on the MiCOM platform, this system has collected and collated cases of all kinds, based on which a unified data model is constructed according to the gold standard derived by deducting each instance. Afterwards, the object segmentation algorithm is employed to segment the diseased tissues. Edge modification and feature extraction are performed for the tissue block segmented. The features extracted are classified by applying support vector machines or the Naive Bayesian classification algorithm. From the simulation results, the CAD system developed in this paper allows the realization of diagnosis and treatment and sharing of data resources.
Contract Statements Knowledge Service for Chatbots

Towards conversational agents that are capable of handling more complex questions on contractual conditions, formalizing contract statements in a machine readable way is crucial. However, constructing a formal model which captures the full scope of a contract proves difficult due to the overall complexity its set of rules represent. Instead, this paper presents a top-down approach to the problem. After identifying the most relevant contract statements, we model their underlying rules in a novel knowledge engineering method. A user-friendly tool we developed for this purpose allows to do so easily and at scale. Then, we expose the statements as service so they can get smoothly integrated in any chatbot framework.