Reviewerly/exHarmony huggingface dataset:
Collision-Free Path Finding for Dynamic Gaming and Real Time Robot Navigation

Collision-free path finding is crucial for multi-agent traversing environments like gaming systems. An efficient and accurate technique is proposed for avoiding collisions with potential obstacles in virtual and real time environments. Potential field is a coherent technique but it eventuates with various problems like static map usage and pre-calculated potential field map of the environment. It is unsuitable for dynamically changing or unknown environments. Agents can get stuck inside a local minima incompetent in escaping without a workaround implementation. This paper presents efficient and accurate solutions to find collision free path using potential field for dynamic gaming and real time robot navigation. A surfing game in two testing environments with a Gamecar and a physical robot called Robocar is created with dynamic and solid obstacles. Sensor like proximity, line and ultrasonic are used along with the camera as different agents for path finding. The proposed intelligent agent (IA) technique is compared with other path planing algorithms and games in terms of time complexity, cost metrics, decision making complexity, action repertoire, interagent communication, reactivity and temporally continuous. It traverses for 135 meters(m) in 55.8 seconds(s) covering 20 goals and 419.3 m in 8.7 minutes while avoiding 10 local minimas successfully. Proposed technique shows comparable results to path finding with techniques using neural networks and A* algorithm. Experimental results prove the efficiency with run time overload, time complexity and resource consumption of the proposed technique.
An Approach for Requirements Elicitation using Goal, Question, and Answer

Requirements elicitation is the first step in software development, methods such as data collection, questionnaire, interview, field observation are used in requirements elicitation, either way, the requirements from customer need to be properly extracted. For the interview, the accuracy of requirements elicitation depends on the dialog ability of software engineer (extractor) and customer (respondent). Among software engineers, there is a difference in the ability of requirements elicitation. Besides, it is difficult for experienced software engineers to extract customer requirements without fail. In this paper, in order to extract requirements without omission, the scope of the requirements is determined in advance, and a tree-like requirements decomposition structure is proposed for constructing the requirement questions. At last, a comparative experiment was carried out, and the effectiveness of the approach was positively supported by the experiment result.
On the Study of Shortest-path Problem on Coal-transportation Networks using Dijkstra's Algorithm

In this paper, we consider the shortest problem in the coal transportation network of the thermal power plant. The assumed coal transportation network connects a dedicate ship uploaders for the power plant to each coal-fired generators. We analyze the features of existing coal transportation network and construct the minimum spanning tree. To meet the practical use, the operation modes of transportation paths along with their equipment are considered. Finally, we proposed the shortest path routing algorithm and conclude the results.
A Technique For Determining The Early Detection For Cervical Cancer

Cervical cancer is one of the most common types of cancer among women. More importantly, cervical cancer is because by Human papillomavirus (HPV) and having regular Pap smear tests can detect HPV infection and pre-cancerous cells. Treatment of HPV can stop cervical cancer before it develops into cancer cells. Since the patterns of development of cervical cancer provide multiple opportunities for detection and treatment. This paper is divided into six sections. Section 1 and 2 discuss cervical cancer and various existing screening for cervical cancer. Section 3 provides a brief overview of the work done so far in the field of cervical cancer. Section 4 discusses the proposed mechanism and the results are described in section 5. Finally, section 6 discusses the conclusion drawn from the whole work. In this paper, an attempt has been made to propose an early detection of cervical cancer system based on some existing parameters such as smoking, the number of sexual partner and age of the person. This work has been implemented in Eclipse and analysed using Weka.
Research on Confirming the Rights of Government Data Resources based on Smart Contract

Rights confirmation is the prerequisite and a major problem in the sharing of government data resources. In the traditional sharing model, some problems restrict the sharing and opening of government data, such as unclear rights and responsibilities, unclear boundaries of ownership and use rights, artificial manipulation and so on. Based on the underlying platform of block chain, this paper uses the smart contract technology to ensure the unique data source of government data resources and the separation of the data ownership and data use rights, so as to solve the problem of confirming the rights of government data from the source of data flow.
Efficient Identification of Initial Clusters Centers for Partitioning Clustering Methods

K-Means is an important and widely used partitioning method of clustering, but it has some drawback like random initialization of center, which may affect the final cluster center. To reach the final cluster center it takes more time as usual. There are many algorithms for the initial center problem and some of them are very useful like k-means++ and canopy, Hartigan-Wong, MacQueen, etc. These algorithms are used in Rstudio and Weka which are very strong tools of machine learning, especially in clustering. In this paper, we propose an algorithm for initializing the centers of k-means and the proposed method is compared with other six well know existing methods and three experiments are done on three data sets and results are compared using clustering parameters. It is found that the proposed method works better as compared to other existing methods.
Intelligent avatars and emotion in medical-based virtual learning environments

The paper presents an overview of the current state of research in intelligent avatars, with a particular focus on the detection and expression of emotions in virtual environments. Our interest lies particularly in the potential use of such tools for the development of medical (mental and physical health) training virtual environments, and virtual simulations and serious games in particular.
Performance Analysis of Queries in RDBMS vs NoSQL

Due to the enormous amount of information getting stored in databases, an extra effort is needed to handle the information so that it is not lost in any way. To avoid the loss of information various methods were introduced and one such technique is introduction of NoSQL using MongoDB. In this paper, a comparison is made between structured Oracle and an unstructured MongoDB, with few identified operations in a controlled environment. The result obtained is then used to realize better performance of the structured or unstructured methods.
Geolocation Tracking and Cloaking of Malicious Web Sites

Web site cloaking is a process in which varying HTML content is delivered to end users based on the attributes associated with the client agent and its interaction patterns. Cloaking poses significant challenges in detection of malicious web sites. The challenge arises due to its simplicity in implementation and its effectiveness in bypassing the detection engines. A malicious web site can deliver a benign content to a requesting client on the server side and consequently bypass detection, regardless of the detection engine used by the client. We performed large-scale real-world experiments to study cloaking techniques used by malicious web sites. We focused our research on malicious web sites using geographical information associated and derived from the IP address and language preferences of a visiting client's browser. Our study validated our hypothesis that client browser's preferred language settings and geographical information of an IP address taken in isolation, change the behaviour of a malicious web site. We also measured the effects of IP geolocation and language settings on the behaviour of malicious web sites irrespective of other factors.
Package recommender systems: A systematic review

This paper presents a systematic review of research into package recommender systems (PRS). PRS recommend a combination of items rather than individual items, for example, multiple attractions to visit on a day trip to a city, trousers and a shirt to wear together, or multiple dishes to make up a m eal. The review provides a framework for considering existing PRS research, and highlights the techniques used for package recommendation and the evaluation methods and metrics employed. It also raises many issues that warrant future research.
Electronic catalogue for mapping mosque potencies

Abstract The existence and purpose of the mosque are vital in Islam. In the mosque, there are some activities related to religious and social life. Although mosque identically used as the centre of religious activity, although there are some potencies can be utilized from mosque such as, economy, education, social, etc. The main idea of this research is to design an electronic catalogue so people can map the information about mosque potencies. In this paper, we use Rational Unified Process (RUP) for research staging and Unified Modelling Language (UML) as a modelling tool. Result of this research is an electronic catalogue application which can provide the mapping of information about mosque potencies and activities related to mosque accurately. We hope with this electronic catalogue, people can be more aware of influences, function, and impact of the mosque to social life around it.
Unscented Kalman Filter Target Tracking Based on Elman Neural Network

Most of target motion models have uncertainties and strong nonlinear characteristics, in the uncertainty processing, the effect of Unscented Kalman Filter (UKF) is remarkable. In order to achieve accurate target tracking, based on the UKF algorithm, this paper uses the ability of dynamic and non-linear approximation of Elman neural network to compensate filtering results of UKF. In addition, this paper explains the shortcomings of Extended Kalman Filter(EKF) algorithm in strong non-linear systems from mechanism. By tracking targets in different motion situations, the emulation results indicate that the algorithm which has proposed in this paper is superior to the traditional UKF and EKF algorithm from filtering accuracy and error stability.
Novel Deblocking Method for Cropped Video

Due to a large amount of data, videos are encoded (data volume reduction) before transmission and storage. However, coded videos have degradations. One of them is called `block noise' that appears block shape degradation on the image. Block noise can be usually reduced by a deblocking filter that reduces the block boundaries. However, the conventional deblocking filter has an issue that it cannot be applied to cropped video with the block noise. Although the deblocking filter reduces the block noise, it also causes blur on the edges in the video. In this paper, we propose a novel deblocking method that can reduce block noise for cropped videos by keeping the edges.
A Novel Approch for Deblurring Colored Images using Blind Deconvolution Algorithm

In digital photography the blur which is caused by motion or camera shake is most common artifact. Due to lack of light or less shutter speed the image becomes blurry and causes significant degradation in image. The information in the image is affected by this effect. In digital imaging recovering the unbluured color image from these images is fundamental research problem. There are various types of blur like motion blur, Gaussian blur etc. Various techniques have been introduced to deblur the images, but specific method is used to deblur specific type of blurring. In this paper, approach is used to deblur the images when we do not have any information about the type of blur. The algorithm is based on blind deconvolution and is used to deblur color image. Algorithm uses damped Richardson-lucy algorithm for each iteration. The algorithm computes blurred image and restores using point spread function (PSF).
Virtual and Augmented Reality for the Visualization of Summarized Information in Smart Cities

In this chapter, authors deal with the problem of visualizing summarized information in a complex system like a smart city. They introduce the topic of smart city in the context of the information revolution that is taking place in the world. Next, they review how this information can be visualized, highlighting immersive 3D methods such as Virtual Reality (VR) and Augmented Reality (AR), which are particularly suitable for these applications, since 2D information does not usually induce a focused and sustained attention. The chapter describes and shows a use case in which VR and Spatial AR (SAR) are used in a smart city system to visualize summarized information about the state and management of the city. The SAR system relies on a multi-projector mapping procedure, and therefore authors also explain the technical details that the calibration and implementation of this type of AR application requires.
Enumeration of Plasmodium Parasites on Thin Blood Smear Digital Microscopic Images

An automated parasite detection is one of the challenges in computer vision and medicine field. Recently, an automated detection system became necessary in order to assist the parasitologist in detecting parasite. However, the development of automated parasite detection had several challenges. Mostly, previous research studies were conducted with the homogeny dataset. Hence, it will become a problem if the research was conducted with various dataset. According to those facts, this study proposed a scheme for detecting Plasmodium parasites. In this study, 46 thin blood smear digital microscopic images of Plasmodium Falciparum with several kinds of pixel intensity were used. The proposed method started by normalizing the data. The normalization result was then segmented by using Otsu thresholding and some operations of morphological operation. Based on the segmentation result, parasite candidate detection was done by storing the location of an object in segmentation result and labeling the object by using BLOB analysis. The result of detection process produced high number of false positive. To reduce the number of false positive, feature extraction process followed by classification process was conducted. Several texture features such as histogram, GLCM and GLRLM were used to extract information of parasite. Classification process was conducted by applying several kernels of SVM classifier. According to the evaluation process, the proposed method has better performance than previous study and successfully distinguish parasite and non-parasite by using the cubic kernel of SVM with accuracy, sensitivity, specificity, PPV and NPV of 97.4%, 100%, 94.8%, 95.1% and 100%, respectively. These results indicated that the proposed scheme is proper in order to assist the expert in detecting Plasmodium parasites effectively.
A Novel Data Masking Method for Securing Medical Image

Providing security for diagnostic and medical data is very essential for preserving privacy and safety of patients. This work present a chaos and DNA based encryption method for securing health care data. Recently, number of chaos and DNA based method has been presented by various researcher to safeguard diagnostic and medical image. However, these models are not efficient against cropping attack. As there exist high correlation among neighboring pixel. Thus, for resisting against cropping attack effective bit scrambling method is required. Firstly, this work present an efficient bit scrambling using logistic sine map and pseudorandom sequence using chaotic system. Then, DNA substitution is performed among them to resist against differential, statistical and cropping attack. Experiment are conducted on standard Lena and medical image. The outcome achieved shows proposed image security model is efficient when compared to existing image security models.
Efficient Technique Image Encryption with Cipher Block Chaining and Gingerbreadman Map

Digital image security is now a severe issue, especially when sending images to telecommunications networks. There are many ways where digital images can be encrypted and decrypted from secure communication. Digital images contain data that is important when captured or disseminated to preserve and preserve data. The technique of encryption is one way of providing data on digital images. A key cipher block chaining and Gingerbreadman Map are used in our search to encrypt images. This new system uses simplicity, high quality, enhanced by the vehicle's natural efficiency and the number of the chain. The proposed method is performed for experimental purposes and the experiments are performed in- depth, highly reliable analysis. The results confirm that by referring to several known attacks, the plan cannot be completed. Comparative studies with other algorithms show a slight rise in the security of passwords with the advantages of security of the chain. The results of this experiment are a comparison of button sensitivity and a comparison after encryption and decryption of the initial image using the amount of pixel change rate and unified average change intensity.
Development of Android Application for City Tour Recommendation System Based on Dynamic Programming

Kediri is a transit city and has potential in the tourism sector. This potential will increase along with the number of tourists who come to the tourism object. To make it easier for tourists to visit tourist attractions in Kediri, a guide is needed that can be easily accessed by tourists to go to the desired tourist attractions. Therefore, a city tour modeling system needs to be made that can provide recommendations for optimum routes that can be passed to visit these tourist attractions. On the other hand, many computational studies have examined research on route optimization using the approach of traveling salesman problem and dynamic programming known as the appropriate method to solve these problems. However, the solutions provided are still in the form of studies that have not been implemented on a mobile device. Therefore, in this study, an application will be developed on an Android mobile device that is capable of solving the problem of modeling a city tour in Kediri based on dynamic programming. The application that was built was able to provide recommendations for a city tour route by determining the optimum route that connects tourist attractions to be visited using the traveling salesman problem concept. The test results show that the application features can work and the dynamic programming method applied is able to find the optimum city tour route even though it can only determine the route to connect 9 tourist sites due to the limited computing power on Android devices.
A Robust Feature Fusion Method for Camera-Based Highway Guardrail Detection

The guardrail detection system is an important part of environment perception for intelligent vehicles. In this paper, the problem of camera-based highway guardrail detection is considered. A novel feature fusion method, which combines histograms of oriented gradients (HOG) and local binary pattern (LBP), is proposed. Then, principal components analysis (PCA) is utilized to reduce the dimension of proposed feature fusion set. Using the strategy of sliding window, the guardrail is detected by clustering method. Computer simulations show that the proposed method has better performance than other methods.
Security Analysis of Hash Based Fragile Watermarking Scheme for Image Integrity

In this paper, we analyze the security vulnerabilities of hash based fragile watermarking method for image integrity proposed by Gul and Ozturk. The scheme divides the image into non-overlapping blocks of size 32 × 32 which is further subdivided into four sub-blocks of size 16 × 16. A 256 bit watermark generated using SHA-256 from first three sub-blocks is hidden into the fourth sub-block. Tampered blocks are identified by comparing extracted hash with computed hash value. We observe that this scheme is vulnerable to the modification of fourth subblock, swapping of image blocks, cropping attack, collage attack and vector quantization attack.
Design and Application Development of the Camps Navigation System Based on ArcGIS Runtime SDK for Android : ——Taking the Yunnan Normal University as an example

With the development of Internet communication technology and the widespread popularity of smart-phone, the market for mobile navigation systems has been matured. It is categorized and analyzed by the mobile navigation system appearing in the current mobile navigation market, we found that there are inaccuracies and missing navigation data in the campus area. For this issue, the article uses ArcGIS Runtime and Android as the development platform. to develop campus navigation application software. The campus navigation map is produced by high-resolution remote sensing images, and it has high data space resolution, which effectively improves the data quality. This data uses ArcGIS Online for data cloud storage and management, achieved the interactive updates between data and users and solve the problem of complicated navigation data upgrade. Based on high-precision map data, the software design to achieve campus positioning, walking navigation, driving navigation, and point of interest searching. The mobile navigation system can realize high-precision navigation services in the campus area, so as to achieve better mapping resources for users, and facilitate the travel and life of visitors and college teachers and students on campus.
Restoration of Compressed Picture Based on Lightweight Convolutional Neural Network

In this work, we propose a deep learning-based method to improve the quality of JPEG images. Our proposed network predicts the compression loss of the JPEG image for compensating and restoring the image quality. To solve the color bleeding artifacts often found in JPEG image, our network considering it in our model and objective functions to restore the color channels. Our network is much lighter by using fewer parameters compared to other work, whereas our method can still provide satisfactory and well-restored images for JPEG images as demonstrated in our experiments. Even with the additional handling on the color channels, the number of parameters in our network model is still kept low around 224k.