Reviewerly/exHarmony huggingface dataset:
Pancreatic Cancer Prediction Using Hierarchical Convolutional Neural Network and Visual Geometry Group16 CNN Approach on Accuracy and Specificity Performance Measures

The main aim of the work is to measure the accuracy, sensitivity, and specificity in the detection of pancreatic cancer. Materials and methods: The dataset of 7390 images obtained from Kaggle for training (80%) and testing (20%) of the predictive model developed in Matlab and statistical analysis is done using SPSS software. The hierarchical convolutional neural network (HCNN) is used for developing the model and compared with the visual geometry group (VGG16) based model. Result: The predictive model developed using the HCNN algorithm shows an improvement in accuracy 94.8221.4705, specificity 88.49801.78406, and sensitivity 90.04601.79226 than VGG16 model with accuracy 94.3760, specificity 88.39200.1663, and sensitivity of 88.92600.5808 with the significance of 0.437, 0.497, and 0.165. Conclusion: The outcome of the study confirms that the HCNN based model appears to be of higher accuracy than the VGG16 based model.
An Innovative Method to Enhance the Accuracy of Credit Card Fraud Detection Using Logistic Regression Algorithm by Comparing Random Forest Algorithm

Aim: The objective is to develop a model to predict which transactions could be fraud with a high accuracy rate by using machine learning(ML) methods, such as the innovative Random Forest Algorithm. Materials and Methods: F1 score and accuracy rate are performed on fraud rates transactions in a dataset. The two groups (LR) the sample size is (N=20) and (RF) is (N=20) with G power value = 80. Results: To perform the transactions in the credit card by utilizing the card number, financial balance and client details, and if it is offline, the fraud has to steal the user's details in online transactions, which is not easily recognized by the client and bank authority, which prompts loss of sensitive data. (p&lt;0.05) statistically significant value is compared to the amount and time since last purchase with a confidence level of 95% (=.519). (RF) algorithm is used for detecting credit card fraud. The accuracy is analyzed based on the dataset of 99.3%, where the (LR) has the accuracy of 99.1%. Conclusion: The performance of strategy is measured based on accuracy, F1 score, Precision, Recall. The results seem to be better accuracy for (RF) is 93.3%.
AR Magic Lantern: Group-based Co-Located Augmentation Based on the World-as-Support AR Paradigm

We present the AR Magic Lantern, an augmented reality flashlight that enables its holders to see and interact with situated virtual content that it projects onto the physical surfaces around them. The AR Magic Lantern tracks its position and orientation, so the projected content is truly a part of the physical space and is thus relevant for all members of a group. This makes it especially suitable for implementations of the World-as-Support AR paradigm, where augmented experiences should be shared and situated. We contribute the design principles and methodology used in the development of the hardware and software of the AR Magic Lantern. We also describe the interactive AR experience that we developed for a local cultural heritage site and which will be demoed during CHI 2022.
Investigation for Performance Comparison of Solar Tracking System with Static Solar System

Around the world, sun oriented force has become the third greatest wellspring of vitality after hydro and twist, in this manner, grabbing a worldwide eye. This investigation draws a correlation between the presentation of Solar Tracker and Static Solar System or a nearby planetary group with fixed pivot to evaluate the sunlight based force. By utilizing different sun points, for example, peak, sunlight based elevation, and solar altitude, sun powered irradiance was determined during a day either shady or radiant, while the aggregate vitality created during the entire month was additionally estimated. In addition, for a more clear understanding, proficiency contrasts during a day just as during the entire month were considered as well. The outcomes of simulations show that implementing the sun tracker concept can increase the efficiency of a solar PV system. It has been determined that by implementing the azimuthally tracking system and the elevated tracking system, PV system efficiency is increased by 37% and 12%, respectively.
The age of holistic consolidation and automation of cyber security

Solution saturation is plaguing the cyber security market. Technology has driven the security strategy for security teams for far too long, which only compounds the problem, leaving them with too many tools, and with cross-functionality and gaps remaining in their security posture. Organisations need to shift the way they think about their cyber security challenges and how they can overcome them.
Hybrid Gradient Strategies in Event Focused Web Crawling

Crawling is defined as the automated and systematic collection of useful web pages with an interconnecting link structure. Live web crawling that is dependent on human, expert-nominated seed URIs is employed for the general construction of event collections. In the focused web crawling technique, the crawler is guided by reference content that pertains to a particular event. With this technique, a focused crawler will attempt to predict if a target URL is directed towards a relevant web page prior to retrieving it. However, it can get trapped within a limited web community and overlook relevant web pages outside its track. For web crawling optimization as well as for the selection of more relevant web pages for retrieval by the crawler, a metaheuristic algorithm is employed. A global searching algorithm’s modification can address the problems. The utilization of basic heuristic algorithms and prohibition techniques forms the basis of the Tabu Search (TS). Swarm intelligence is used by the Particle Swarm Optimization (PSO) to identify an optimization problem’s solution. This is done by a generation of better candidate feature subsets as per a given ﬁtness criteria and rapid convergence towards a global optimum within a set number of iterations. Hence, the proposed gradient-based algorithm will present a more rapid convergence for the PSO than the other variants. A proposal for a hybrid Stochastic Gradient Descent-Particle Swarm Optimization has also been presented in this work.
Design of Efficient Algorithms for Secure Communication Contextual to Internet of Things

The Internet of Things (IoT) has been a popular topic in recent years. Many researchers from all around the world are working hard to overcome IoT security challenges. Addressing security vulnerabilities in the IoT ecosystem, however, is a big challenge due to the diverse nature and scale of nodes and varied devices. The research presents a resource-efficient encryption approach for sensor nodes that is both lightweight and responsive. The introduction of a revolutionary bootstrapping of key method, which has a unique secret key generation capability that can sustain forward and backward secrets simultaneously, is also a significant addition. The suggested security mechanism is based on a numerical computation tool and implemented using an analytical technique. A comparison of performance with similar existing methodologies validates the efficacy of the suggested methodology. The study's findings reveal that the proposed system has improved security and is more practical in terms of lowering resource usage and achieving faster results.
Technology Innovation: Detection of Counterfeit Region in an Image

With availability of advanced photo editing tools today, digital images can be tampered with malicious intention at ease. The image tampering can create various ill effects like false disease diagnosis of medical images, defaming people, hiding evidences, creating false claims etc. Since images are being increasingly used as the most creditable information for inferring various conclusion and judgments in many application scenarios, it is necessary to ensure the authenticity of the image and detect any counterfeit regions in the image. Nowadays tampering can be done in sophisticated manner without leaving any trace and it becomes difficult to detect with naked eye. In this work, we survey the state of art existing works on detection of counterfeit or tampered regions in the images. The survey is done to identify the challenges in existing counterfeit detection techniques.
Study on the Relationship Between VR Sickness and Trajectory of Fixation Point Using HMD

It has been reported that VR sickness can be suppressed by the placement of a fixation point in a field of view. However, the relationship between trajectory of the fixation point and VR sickness reduction effect is not made clear. Therefore, it is attempted that relationship is investigated using HMD in this study.
Basic Study for VR Image Presentation Method and Display Design for Bedridden Patients

VR has been applied to medical treatment and welfare, and there are more and more opportunities for the elderly and recuperators to use VR. However, it is difficult for the elderly and recuperators to wear head-mounted display (HMD) because of the physical burden. In addition, immersive display that covers the user's surroundings is difficult to introduce in medical and welfare environment due to the large size of the equipment. These challenges are particularly significant for bedridden patients. Therefore, we propose a VR image presentation system for bedridden patients that can be used at the bedside without the burden of wearing a device. Through the subject experiments, we confirmed the usefulness of the proposed system regarding the presence and simulator sickness. In addition, we investigated the method of presenting VR images in the lying position, and showed that it is effective to present VR images horizontal to the eyes. Furthermore, we obtained the design parameters of the display shape considering the head posture in the lying position. From these findings, we obtained a guideline for system design considering head posture restrictions for bedridden patients.
Foundations of Library Services: An Introduction for Support Staff (Library Support Staff Handbooks, 7)

"Foundations of Library Services: An Introduction for Support Staff (Library Support Staff Handbooks, 7)." Journal of Electronic Resources Librarianship, 34(1), pp. 83–84
Semi-supervised pedestrian re-identification via a teacher–student model with similarity-preserving generative adversarial networks

Abstract This paper describes a pedestrian re-identification algorithm, which was developed by integrating semi-supervised learning and similarity-preserving generative adversarial networks (SPGAN). The pedestrian re-identification task aimed to rapidly capture the same target using different cameras. Importantly, this process can be applied in the field of security. Because real-life environments are complex, the number of detected identities is uncertain, and the cost of manual labeling is high; therefore, it is difficult to apply the re-identification model based on supervised learning in real-life scenarios. To use the existing labeled dataset and a large amount of unlabeled data in the application environment, this report proposes a semi-supervised pedestrian re-identification model, which combines a teacher–student model with SPGAN. SPGAN was used to reduce the difference between the target domain and the source domain by transferring the style of the labeled dataset from the source domain. Additionally, the dataset from the source domain was used after the style transfer to pre-train the model; this enabled the model to adapt more rapidly to the target domain. The teacher–student model and the transformer model were then employed to generate soft pseudo-labels and hard pseudo-labels (via iterative training) and to update the parameters through distillation learning. Thus, it retained the learned features while adapting to the target domain. Experimental results indicated that the maps of the applied method on the Market-to-Duke, Duke-to-Market, Market-to-MSMT, and Duke-to-MSMT domains were 70.2, 79.3, 30.2, and 33.4, respectively.
The Potential of Professional Networks in the Formation of Teachers’ Readiness to Exchange Knowledge

Problem and goal. The article actualizes the problem of improving the quality of Russian education by creating conditions for continuous professional development of teachers. It is proposed to intensify the knowledge exchange between them by means of network professional communities. The goal of the article is to describe the potential of network professional communities in the formation of teachers’ readiness to exchange knowledge. Methodology. The methodological basis of the study is a synergetic approach, according to which professional relationships motivate teachers to obtain new knowledge. The network professional community is a single developing and non-linear organism that stimulates professional growth of teachers. Research results. The author’s solutions for the implementation of knowledge exchange in professional communications are described. They were embodied in both formal ways of educating teachers (advanced training, professional retraining) and informal (network professional communities, webinars of current educational problems). The process of forming teachers’ readiness to exchange knowledge is characterized: subjects, methods, and means are presented. The potential of network professional communities acting as a space for updating the methodological solutions of educators and discussion of current problems of teaching modern schoolchildren is indicated. The conclusion is that online professional communities contain the potential to build educators’ readiness to exchange knowledge, and therefore need to improve the tools used for knowledge exchange.
Technology, change and the academic library: Case studies, trends, and reflections

"Technology, change and the academic library: Case studies, trends, and reflections." Journal of Electronic Resources Librarianship, 34(1), pp. 87–88
Topological Corner States in Non-Unitary Coinless Discrete-Time Quantum Walks

The discrete-time quantum walk provides a versatile platform for exploring abundant topological phenomena due to its intrinsic spin-orbit coupling. In this work, we study the non-Hermitian second-order topology in a two-dimensional non-unitary coinless discrete-time quantum walk, which is realizable in the three-dimensional photonic waveguides. By adding the non-unitary gain-loss substep operators into the one-step operator of the coinless discrete-time quantum walk, we find the appearance of the four-degenerate zero-dimensional corner states at Re E = 0 when the gain-loss parameter of the system is larger than a critical value. This intriguing phenomenon originates from the nontrivial second-order topology of the system, which can be characterized by a second-order topological invariant of polarizations. Finally, we show that the exotic corner states can be observed experimentally through the probability distributions during the multistep non-unitary coinless discrete-time quantum walks. Our work potentially pave the way for exploring exotic non-Hermitian higher-order topological states of matter in coinless discrete-time quantum walks.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review : Double Anonymous • Conference submission management system : The submission was divided into two period, namely abstract and full paper submission. The accepted abstracts were suggested to submit the full papers. The authors submitted their manuscript to the official email address of the CITIES Conference, it is citiesconference@gmail.com which was monitored daily by the team in charge in the paper division. Furthermore, the Editors of conference determined the suitable reviewers after the paper submission accepted from the paper division. During the submission, the authors should complete the registration form to indicate their preference to the publication options. The CITIES 2021 Conference provided three options of publication, such as accredited international journal and Scopus indexed proceedings journal. • Number of submissions received : 51 • Number of submissions sent for review : 51 • Number of submissions accepted : 51 • Acceptance Rate (Submissions Accepted / Submissions Received × 100) : 100 • Average number of reviews per paper : 2.01 • Total number of reviewers involved : 24 • Contact person for queries : Name : Vely Kukinul Siswanto Email : vely_ks@urplan.its.ac.id Affiliation : Institute Technology of Sepuluh Nopember
Evaluating Cybersickness in Virtual 3D Models for Anatomy Learning

Cybersickness is an array of symptoms associated with exposure to three-dimensional visualization technology (3DVT) environments, such as virtual reality (VR). It is thought that cybersickness is a type of motion sickness caused by a mismatch in sensory and vestibular input when using these modalities. Symptoms of cybersickness are often akin to those of traditional motion sickness, such as headache and nausea. In the literature, as many as 40-60% of VR users report symptoms of cybersickness, though in our laboratory approximately 20% of users report symptoms of cybersickness. Our past research has shown that the physical environment is often preferred by students, and more effective for learning anatomy, compared to 3DVT environments. We hypothesize that the preference for, and effectiveness of, the physical environment over 3DVT may be a result of cybersickness due to the isolation of the learner from the physical environment. However, no direct measurements of cybersickness or comparisons between 3DVT environments in anatomy are available.Our study involves comparisons of cybersickness during anatomy learning between three 3D modalities: a VR Oculus Quest 2TM headset, an autostereoscopic screen (AlioscopyTM ), and a 3D-printed physical model. Undergraduate students, with no formal anatomy training, will be randomized via a Latin square design to view one of three skeletal models (human hemipelvis, zygomatic bone, or calcaneus) in each of the modalities. Participants may not touch the model but may rotate it along the horizontal plane using an XboxTM controller. Participants will have four minutes to learn ten bony landmarks on the viewed model and will then take an untimed, recognition-based test for landmarks learned before progressing onto the next modality. Cybersickness will be assessed following testing in each modality, via self-reports on the simulation sickness questionnaire (SSQ).We hypothesise that reported cybersickness will be highest for the VR displayed on the head-mounted display of the Oculus Quest 2TM which entirely covers the visual field, compared to learning through the AlioscopyTM screen or the physical model due to the relative lack of isolation of the learner from the physical environment in the last two treatment groups.With the rapid development of 3DVT for use in anatomical education, cybersickness is an important issue in evaluating the quality of 3D modalities. The results of this study will allow educators and students to make informed decisions about the use of 3DVT in anatomy thus preventing uncomfortable physical symptoms associated with learning using 3DVT and improving learning as a result.
Improving Remote Spatial Understanding by Transmitting Spherical Images via Video Chat Applications

Manufacturing functions are often performed by groups of engineers who cooperate and gather at work sites. However, since the beginning of the COVID-19 pandemic, the movement and activities of groups of people have been restricted, especially in indoor spaces. This reduction in travel by engineers also implies a reduction in associated costs. Telepresence technology, which is studied in the field of virtual reality, can be used as a way to reduce travel. Telepresence allows users to engage with a site from a remote location as if they were present. Thus, engineers would be able to participate in a working group without the necessity of physically traveling to the site to cooperate with local manufacturing people. A variety of telepresence systems have been proposed; however, relatively few methods have been widely implemented compared with video chat applications that have recently become an established infrastructure in many companies. This is most likely because most proposed systems use robots, head-mounted displays, or dedicated multi-functional applications that require engineers to learn how to use them. One way to use a video chat application to understand a remote space is to have a remote participant move a camera used in a video chat application. In contrast, many VR social networking services use a viewing method with which users can change their viewing direction on the computer screen. In this study, we demonstrate that a system that allows users to rotate their viewing perspective on a laptop computer screen can provide an easier understanding of a virtual space than a system that requires a remote person to move a webcam. Based on these results, we propose a system that allows users to view a remote location on a laptop computer screen via a video chat application and an off-the-shelf spherical camera, and evaluate its usefulness.
A Dynamic Weighted Averaging Technique for Trust Assessment in Cloud Computing

In the Cloud computing, trust management has become a key requirement for its security as it has an important role where service-interactions take place in an anonymous environment. Trust assessment is an essential part of trust management technology for making any authorization decisions in the Cloud-based trust authorization system. The critical concern in trust assessment is the optimal assignment of weights to different factors that are involved in the trust assessment of the Cloud computing. The paper proposes a weighted averaging method for the Cloud computing paradigm wherein multiple factors are assigned weights dynamically by WMA-OWA functions. The proposed work overcomes the influence of the inflexibility of subjective weight assignment methods wherein weights are assigned manually or subjectively by experts based on their preferences such as random allocation, expert opinion, and, average weight. The experimental result shows that the proposed method can achieve greater flexibility, adaptability, and dynamic adjustment capability in the Cloud computing.
Enhanced Autonomous Driving Through Improved 3D Objects Detection

The detection of 3D objects is fundamental in the field of autonomous driving. The involved computations consist of sets of 3D bounding boxes that determine specific significant objects. The existing scientific contributions generally do not report applied studies that assess the reliability of 3D objects detection considering various weather conditions, including adverse scenarios like heavy rain and thick fog, and also other relevant problematic use cases. This paper presents an applied research process that describes the core of a 3D objects detection system, which considers two particular road topologies, a roundabout and a T-junction. The experimental data is collected through a partnership with several car manufacturers.