Reviewerly/exHarmony huggingface dataset:
Solving Random Travelling Salesman Problem using Firefly Algorithm

The firefly algorithm is a recently developed optimization algorithm, which is suitable for solving any kind of discrete optimization problems. This is an algorithm inspired from the nature. In this paper, a firefly algorithm is proposed to solve random traveling salesman problem. The solution to this problem is already proposed by the algorithms like simulated annealing, genetic algorithms and ant colony algorithms. This algorithm is developed to deal with the issue of accuracy and convergence rate in the solutions provided by those algorithms. A comparison of the results produced by proposed algorithm with the results of simulated annealing, genetic algorithms and ant colony algorithm is given. Finally, the effectiveness of the proposed algorithm is discussed.
Artificial Intelligence Techniques for Phishing Detection

The objective of this undertaking is to apply neural systems to phishing email recognition and assess the adequacy of this methodology. We structure the list of capabilities, process the phishing dataset, and execute the Neural Network frameworks. we analyze its exhibition against that of other real Artificial Intelligence Techniques – DT , K-nearest , NB and SVM machine.. The equivalent dataset and list of capabilities are utilized in the correlation. From the factual examination, we infer that Neural Networks with a proper number of concealed units can accomplish acceptable precision notwithstanding when the preparation models are rare. Additionally, our element determination is compelling in catching the qualities of phishing messages, as most AI calculations can yield sensible outcomes with it.
Integrating the Notion of Sustainable Development in Banking: Analysing Historical and Conceptual Framework

In the past three decades, ustainable development has emerged as a new paradigm for development. Contemporary s development discourse puts the onus on every governmental and non-governmental organisation to contribute towards sustainable development. Banks play a critical role in the achievement of sustainable development goals due to its intermediary role in the economy. Recently, various international guidelines and roadmap were developed to promote the notion of sustainable development such as Equator principles, PRI, UNEP FI, and Global reporting initiatives (GRI). The purpose of this paper was to discuss the evolution of the notion of sustainable development vis-à-vis the role of banking institutions in sustainable development and also examined contemporary national and international initiatives that propagate the role of banks towards sustainable development and finally suggested a framework to achieve sustainable development through sustainable banking practices.
Preprocessing the Groundwater Quality data by LSR and QDR techniques

Data mining is the process of identifying patterns and their relationships to solve problems through data analysis. Data mining is utilized to haul out working information from a colossal dataset of any crude information. Environmental mining is one of the wide areas to find impact on environment. Data mining encourages the usage of essential strategies and finds noteworthy information from gigantic measure of environmental information. Data preprocessing techniques are very essential in data mining, which uses various techniques to convert the raw data into a meaningful data to further research work. In this research work, Logical Similarity Replacement (LSR) and Quantity based Discrepancy Replacement (QDR) algorithms are proposed to ascertain the quality of groundwater. The numerical information are preprocessed by the statistical techniques Mean, Median methods and non-numeric information are preprocessed by the proposed LSR and QDR methods to satisfy the fragmented and conflicting information in the dataset. The conflicting and the missing information are corrected by the picked strategies for preprocessing. In the wake of applying these preprocessing systems connected in the dataset, the nature of the informational index is improved.
Pre-Service Teacher Educators’ Experiences of Using Mobile Technologies in the Teaching and Learning of Mathematics and Technology Education for the Fourth Industrial Revolution

This qualitative ethnographic study reports on a project which sought to explore experiences of using mobile technologies, in the teaching and learning of mathematics and technology education. The researchers worked collaboratively to develop curricula featuring the use of mobile devices, in the context of their respective technology and mathematics education flipped lecture rooms, in response to the Fourth Industrial Revolution. Aligned with the module outcomes, mobile devices were used for teaching shapes, angles and design in mathematics and for applying the shapes, angles and design to build rigid structures in technology education. Mishra and Koehler’s Technological, Pedagogical and Content Knowledge model undergirded this study. This chapter advances the rationale that teacher educators’ pedagogical and technological practices cannot be understood without considering their socio-cultural backgrounds. The participants were teacher educators at one university in KwaZulu-Natal. Six teacher educators were purposively selected to participate in this study. Semi-structured interviews and observations were used to generate qualitative data. Data were subjected to content analysis. The findings reveal that teacher educators use mobile technologies to heighten students’ awareness of mathematics and technology in everyday life, to initiate thinking by enabling students to move from the concrete, observable phenomena to abstract understanding of principles and their application to design to solve contextualized problems. Such use of mobile technologies enhances students’ observation, discussion and presentation skills. Moreover, the findings highlight that teacher educators’ pedagogy relating to mobile technologies are impacted by early learning experiences and socio-cultural background. The findings have implications for the Technological, Pedagogical and Content Knowledge model and calls for an extension of the model.
Merkle Hellman Knapsack Cryptosystem based Cloud Auditing Protocol

The cloud environment provided the cloud storage services to allow the users for storing, managing and accessing their data through the internet. The user worried about the integrity of data because of their data can be modified by external hackers due to the limited control. The new auditing technology is required for allowing the user to use local storage without worrying about the integrity of the data. An independent entity called Third Party Auditor (TPA) is presented for auditing task rather than putting the burden of task to the user themselves. In our proposed work, the Cloud Auditor (CA) plays the role of monitoring the modifications done to the block by any external hacker if it happens; original data is recovered from its cache log. Every data that transacts between the storage, user and the CA are encrypted with Merkle Hellman Knapsack Cryptosystem based Cloud Auditing Protocol (MHKC-CAP) algorithm. Thus the proposed methodology outperforms the existing algorithms like Message Digest 5 (MD5) algorithm and Advanced Encryption Standard (AES) by means of auditing time around 13 milliseconds and accuracy in terms of False Positive Rate (FPR) and False Negative Rate (FNR) are around 0.67% and 0.5%.
Recognize Objects for Visually Impaired using Computer Vision

Visually impaired people are often unaware of dangers in front of them, even in familiar environments. Due to lack of vision either partial or complete, such people are highly dependent on the sense of hearing to perform day to day activities. One more form of vision impairment is colour blindness. Individuals with colour blindness find it hard to distinguish between colours. This research proposes making software that can help such individuals for solving the unawareness of the surrounding of the visually impaired people which allows them to have a greater awareness of their surroundings. The software needs an input device typically a camera and an audio feedback system. The camera will continuously capture images and the algorithm recognize the objects in the image and output the result using the audio feedback system. The system also proposes to include colour extraction to also correctly identify the colour of the object and a further addition is to identify individuals if enough datasets are provided. If any suspicious/dangerous objects detected in the surrounding the software will inform the user about the imminent danger. This study has analysed Faster R-CNN, SSD (Single Shot MultiBox Detector) and YOLO (You only look once) for their accuracy and rate of object detection. This research also studied different operating scenarios of the device which includes operation at night and operation in various orientations. The results of the object recognition system while using YOLO have an accuracy of 59.7% and 10fps during real-time operation, which is sufficient for assisting visually impaired people in realizing the types and localities of the objects around them.
Ontology Based Thai Chatbot on Social Media Marketing for Community Enterprise

Communicating with customers is the key to maintaining relationships so that customers are loyal to the business. But employees in the organization are unable to support or keep contact with the customer all day, especially for community enterprise with limited budgets. The chatbot is one of the tools that can increase the efficiency of automated communication with customers at all times. This paper presents Thai chatbot on social media marketing for community enterprise using the ontology technique. To develop a semi-automatic approach to create query terms and answers in different styles of response which is related to describe the features of online community product purchases for online buyers with community enterprise. The Longest matching approach was used to increase the capability of the Thai word segmentation, thus providing detailed and accurate information. The results show effectiveness and evaluation in terms of the accuracy of the classification and relationship of ontology and black box testing at the high-level while being used has high consensus both experts and users.
An innovative classroom teaching technology assisted by artificial intelligence of things

Artificial intelligence of things (AIoT), as a technical product of the combination of artificial intelligence and the Internet of things (IoT), is the possibility of innovative education to change the classroom teaching patterns. In practice, the intelligent classroom supported by AIoT is represented by the real-time communication between IoT sensing equipment and intelligent system, which can be diagnosed and analyzed through typical classroom scenes such as cooperation and training during the teaching procedures. To looking back at the evolution of information technology that is applied in the classroom. Although practitioners continue to try to make attempts in technology-enhanced teaching, they have never been able to integrate advanced information technology with education and solve the essential problems of classroom teaching. Since the classroom teaching performance is the fundamental basis for accurately evaluating and diagnosing the teaching effect, intervening in the teaching process, adjusting the teaching mode, and improving the teaching ability. Constructing the AIoT-based teaching performance management system is one of the key directions to solve real classroom problems. It comprehensively constructs a data-driven intelligent system with the help of IoT devices, which captures the multi-modal classroom behavior data of teachers and students’ behaviors in real-time, and carries out feature extraction, data fusion, personalized modeling, and dynamic intervention around teaching problems. Through the practical test of the teaching effect, the AIoT-based classroom teaching management is proved as one kind of sound assistant teaching strategies for effectively monitoring the classroom teaching process and improving the behavior mode of teaching and learning.
Parameter estimation for partially observed nonlinear stochastic system

This paper is concerned with the parameter estimation problem for partially observed nonlinear stochastic system. The suboptimal estimation of the state is obtained by constructing the extended Kalman filtering equation. The likelihood function is provided based on state estimation equation. The strong consistency of the estimator is proved by applying maximal inequality for martingales, Borel-Cantelli lemma and uniform ergodic theorem. An example is provided to verify the effectiveness of the method.
An Efficient Image Denoising Method based on Bilateral filter Model and Neighshrink SURE

In all the instances of image acquisition, transmission and storage, the unwanted noise gets into the information content of the image and thereby introduces an unpleasant visual quality to the observer. So the field of image processing has produced a lot of image denoising algorithms and techniques to improve the visual quality of the image. Since noise cannot be reduced to zero practically, the need for faithful and efficient denoising techniques to produce almost noiseless images demands a systematic research work in the field of denoising methods. The denoising process using a bilateral filter even though produces improvement in the image quality, it does not show consistency when the noise level is high and also the peak signal to noise ratio (PSNR) and Image quality Index (IQI) do not show any improvement. This paper proposes an improved algorithm that incorporates the function of bilateral filter model and wavelet thresholding using Neighshrink SURE method. The results show significant improvement in both PSNR and IQI values with respect to the four standard test images under various noise conditions.
Hybrid Animation: Implementation of Three-Dimensional (3D) Animation

Abstract In the 21st century, much progress has been made following the industrial revolution 4.0. Therefore, the field of animation has also been injected into technological advances. The transmission of information is difficult to convey accurately and interactively to users. In providing users with more exposure and convenience in a more attractive and convenient way. Therefore, animation and motion capture are the best options for use today. As a result, the results of this project can have a huge impact on the animation industry in making video or animation more interesting 3D animation.
Methodological Support Improvement as Condition for Students' Competences Development

Methodical support is an integral part of educational process. Under the conditions of reforming Russian educational system, its updating becomes an objective necessity. Teachers’ methodological activity as a whole acquires new features and needs improvement which is of particular interest to researchers, thus actualizing the need to consider this issue. In this article the authors reveal the essence of teachers’ methodological activities considering importance of this process both for teachers and for students. Since methodological activity in educational framework acquires new meaning, additional development in this area is required to form methodological support at a high level. Therefore, the purpose of the article is to improve methodological support to perfect students' competencies development. The authors proposed updated methodological support in the courses of general professional cycle. To test effectiveness of the proposed development the authors conducted a study. Improvement of methodological support in the framework of updated educational process contributed to improvement of students' competencies development. The obtained results confirmed effectiveness of updated methodological support in the courses of general professional cycle.
Cloud resource orchestration optimisation based on ARIMA

The problem of resources management in the cloud environment, focusing on the platform as a service (PaaS), satisfying the demands of users, and relieving the load on the server in high concurrency, requires attention. After analysing the resource orchestration technology on PaaS, this paper presents a dynamic orchestration optimisation framework based on autoregressive integrated moving average model (ARIMA) model. The architecture is based on an OpenStack infrastructure as a service (IaaS), and combines with Cloudify, a resource orchestration software on the PaaS. Adjustments may be made in advance by predicting the resource consumption in the next time period. Experiments showed that this architecture can effectively shorten the concurrent response time and improve the utilisation of memory.
Impact of Cloud Database in Medical Healthcare Records Based On Secure Access

In the future generation would development of new technologies, such as cloud computing, Internet of things (IOT), used in the medical field from concept to practice. Health care medical field is the major import role in cloud computing. The E-medical record contains the Healthcare providers HIS, but its deployment process slow due to high cost and high maintenance cost. In this paper study, electronic medic records with cloud-based security and access rights. In the cloud data ware house contained for all hospital patients details. Cloud middleware gives a platform for electronic healthcare system. It is provides to secure access the medical health record only authorized users and avoid unauthorized user. In this paper, proposed cloud computing design, which enables the secure and collaborative E-medical records among the all the hospitals with case of access rights.
An Efficient MRI Brain Image Registration and Wavelet Based Fusion

Over last few decades, 3D reconstruction of medical images becomes advance technique in medical image processing. Reconstruction of 2D images of such data sets into 3D volumes, via registration of 2D sections had become a most interesting topic. In current years, MRI has been used for many medical analysis applications. The proposed system considered MRI images are taken from the same view, different times or acquired by different imaging modalities to increase the information. T1, T2 and PD MRI are taken as an input; T2 image is registered with a reference of T1 image using affine transformation, the registered T2 image is fused with T1 using DWT. The Fused T1T2 image is taken as reference image to register PD image using B-Spline transformation. DT-CWT technique is used to fuse the T1T2 image with registered PD image. The performance of the system shows that the proposed system gives more information by fusing T1T2PD images.
A Survey of Elementary and Intermediate Learners’ Attitudes towards the use of Vietnamese by Teachers in General English Classes

This study was conducted in order to figure out the attitudes of Vietnamese EFL students towards their mother language use in teaching English classes.45 elementary-level students and 34 pre-intermediatelevel ones at 2 English centers in Ho Chi Minh City, Vietnam, were asked to fill out a 12-item questionnaire adapted from the ones of the three previous researchers including Prodromou (2002), Bateman (2008) and Afzal (2013).The result revealed that the students of both English levels have positive answers towards their L1 using in L2 classes as a beneficial way to give further explanation on difficult grammar points and the confused vocabulary's meanings.
Video summarisation based on motion estimation using speeded up robust features

Video summarisation (VS) is a technique to extract keyframes from a video based on video contents. It provides user with a brief representation of video contents to semantically understand the video. This paper aims to present video summarisation based on motion between consecutive video frames. The motion between frames is represented by affine and homograph transformation. The video frames are represented by a set of speeded up robust features (SURF). The keyframes are extracted in a sequential manner by successively comparison with the previously declared keyframe based on motion. The validity of the proposed algorithms is demonstrated on videos from Internet, YouTube dataset and Open Video Project. The proposed work is evaluated by comparing it with different classical and state-of-the-art video summarisation methods reported in the literature. The experimental results and performance analysis validates the effectiveness and efficiency of the proposed algorithms.
Forest Labs., LLC v. Sigmapharm Labs., LLC United States Court of Appeals of the Federal Circuit, 2019 918 F.3d 928

Biotechnology Law ReportVol. 38, No. 3 As presented by Chris HolmanForest Labs., LLC v. Sigmapharm Labs., LLC United States Court of Appeals of the Federal Circuit, 2019 918 F.3d 928Edited for Biotechnology Law Report by CHRISTOPHER M. HOLMAN*Published Online:7 Jun 2019https://doi.org/10.1089/blr.2019.29120.cmhAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 38Issue 3Jun 2019 InformationCopyright 2019, Mary Ann Liebert, Inc., publishersTo cite this article:Forest Labs., LLC v. Sigmapharm Labs., LLC United States Court of Appeals of the Federal Circuit, 2019 918 F.3d 928.Biotechnology Law Report.Jun 2019.182-187.http://doi.org/10.1089/blr.2019.29120.cmhPublished in Volume: 38 Issue 3: June 7, 2019PDF download
Activities of JICA on disaster prevention and achievement of JICA project in Period 1

The Japan International Cooperation Agency (JICA) has supported various natural disaster prevention activities in Vietnam in accordance with the "Sendai Framework for Disaster Risk Reduction 2015-2030".From 2007 to 2017, around 90 percent of the total damages in Vietnam were accounted by water-related natural disasters.JICA implemented several
Data-Sharing and -Searching Scheme to Share and Search Data Securely by Iot Smart Devices

In a few documents, cloud support safe information distribution plans be exhibited whereby clients be able to impart their information to other people/among a gathering through the cloud. This article proposes a proficient records distribution plan to allow savvy gadgets toward securely share records with others at the edge about cloud-helped Internet of Things (IoT). We additionally plan a safe looking through suggest to look through required records within possess/shared information on capability.