Reviewerly/exHarmony huggingface dataset:
Application of Radar Imagery to Tectonic, Structural and Geological Studies in Afikpo Basin, Southeastern Benue Trough, Nigeria

Radar imagery was used to identify geological features and the production of geological maps of the Afikpo basin. The essence of this study was to delineate significant geological and geomorphological features that have not been imaged by the traditional ground field mapping. The application of Radar imagery technique will be relevant to the discovery of subsurface structures that will aid the accumulation or concentration of certain economic minerals or natural resources. It will enhance the identification of significant geological information such as lineaments, geologic structures, drainages, etc, that will serve as a guide to the actual ground field work investigation. Results from radar imageries revealed drainage pattern, major geomorphological units, mega lithostratigraphic units, lineaments and structures. The geology of Afikpo basin consist of Cretaceous, Tertiary and Quaternary rocks are recognizable; the highly deformed Cretaceous rocks are characterized by regional lineaments. Some of the rivers are aligned along the regional lineaments. The NW-SE and NE-SW lineaments truncate one another, suggesting different ages for the lineament groups. A few sinistral tensional movements occur in the eastern sector of the basin. The major folds in the Afikpo basin have NE-SW and NW-SE trends, and occur as anticlines and synclines. The basement structuring and basin framework suggest a tectonic setting in the southeastern Benue Trough resulting from the Early Cretaceous opening of the South Atlantic Ocean and interpolate movement in Africa. From the evidence currently available we may conclude that the post Santonian Afikpo basin falls within the transtenstional basin categories associated with transform faults. The regional tectonics interpreted from the radar imageries are likely hydrocarbon related structural features.
Personalized Recommender by Exploiting Domain based Expert for Enhancing Collaborative Filtering Algorithm :PReC

The large amount of information available on the internet initiated various Recommender algorithms to act as an intermediate between number of choices and internet users.Collaborative filtering is one of the most traditional and intensively used recommendation approaches for many commercial services.Despite providing satisfying outcomes, it does have some issues that include source diversity, reliability, sparsity of data, scalability and cold start.Thus, there is a need for further improvement in the current generation of recommender system to achieve a more effective human decision support in a wide variety of applications and scenarios.Personalized Expert based collaborative filtering (PReC) approach is proposed to identify domain specific experts and the use of experts preference enhanced the performance of collaborative filtering recommender systems.A unified framework is proposed that integrates similar users rating data, experts rating and demographic data to reduce the number of pairwise computations from the search space to ensure scalability and enabled fine grained recommendations.The proposed method is evaluated using accuracy metrics MAE, RMSE on the data set collected from MovieLens datasets.
¿Por qué a la didáctica, la epistemología, la informática y a las habilidades matemáticas, les cuesta tanto ingresar a una clase de Matemática?

The approach to teaching is the heart of Mathematical Education and a preferred task of educators and researchers around the world. Epistemology is knowledge about the nature of mathematical knowledge. Digital technologies are the substance with which the symbolic space in which our students live and will live today is built. Mathematical skills are the focus of the curricular reforms of the discipline in recent decades. The school, and in it the Mathematics classroom, resists. Teaching prevails over learning. Adult presentations are more common than students doing Mathematics. There is an emphasis on content and algorithms over the abilities needed for mathematical work. Here we look for the assumptions and beliefs that could serve as a basis for the discrepancy between what is expected to happen in the Mathematics classroom and what is actually observed in it. The analysis seeks to understand what are the forces that hinder or inhibit the necessary evolution of the school and the school system.
Using Partitioning Methods for Mining URL Weight in Social Networks

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Useful Money and Cryptocurrencies

Cryptocurrencies aim at substituting the operations of trusted financial institutions with decentralized operations, including the monetary functions provided by central banks. This article addresses some fundamental questions. Can cryptocurrencies, with no institutions behind them, really function as useful money? Can cryptocurrencies improve our payment system? What are the risks? And how should central banks and other policy makers respond to cryptocurrencies? <b>TOPICS:</b>Currency, portfolio construction, wealth management
Intervening Failure Attribution Perceptions and NWOM with Online Service Recovery Actions: An Abstract

In the digital era, an increasing number of dissatisfied customers turns to brands’ social media outlets (e.g., Facebook brand pages) to vent their frustration following a service failure. This study investigates the circumstances under which a brand’s response to online complaints (i.e., online complaint handling or “webcare”) is able to intervene consumers’ post-complaint inferences about the failure (i.e., failure attributions). Findings indicate that corporate webcare strategies (e.g., no-responses, defensive responses) vary considerably in their ability to alter complainants’ attributions of locus, controllability, and stability. Results, however, also show that this ability depends for the most part on complainants’ earlier experiences with the involved brand: Complainants who had no or only a few bad brand experiences in the past are more receptive to the different types of marketers-initiated webcare (MIW) than consumers with multiple failures. Most importantly, however, this research demonstrates that comments of other consumers (i.e., “brand advocates”) defending the brand with an online comment (i.e., advocate-initiated webcare; AIW) can improve MIW’s effectiveness to mitigate unfavorable attributions. Nevertheless, this can only be achieved when the responses of the two webcare sources (MIW and AIW) are congruent. If well-meant advocates’ responses are incongruent to marketers’ complaint handling strategy (e.g., an accommodative response), disadvantageous failure attributions occur. Additionally, this research demonstrates that the three kinds of attributions are key mediators which determine post-webcare customer satisfaction and negative word-of-mouth intentions. References Available Upon Request
Integrated source of entangled photon pair at telecom wavelength

A compact, robust and high quality on-chip source of entangled photons pair in telecom wavelength is presented. The entangled output state can be changed by means of the chip reconfigurability and its hybrid structure.
Performance improvement of distributed system through load balancing and task scheduling using fuzzy logic

Task scheduling and load balancing in distributed network are the most challenging research area in computer science. In distributed systems, scheduling mechanism has more issues as there is no centralised authority to allocate the workload among multiple processors. Further, handling both load balancing and scheduling at hand is a daunting task. In this paper, we propose a fuzzy-based load balancing and task scheduling technique to optimise the performance of distributed system. Initially, clusters are formed and node with larger buffer availability and high CPU speed is elected as cluster head. Tasks are prioritised into flexible and non-flexible using task prioritising strategy. Non-flexible tasks are prioritised over flexible tasks. For non-flexible tasks, essential information of nodes such as CPU speed, work load and distance from cluster head are made pass through the fuzzy system. Node state is obtained as output. Based on states of node, non-flexible tasks are allocated. Our technique dynamically handles scheduling and load balancing at hand. We use simulation results to prove efficiency of our technique.
Research Guides: COM 287: Persuasive Speaking: Name Speech

A study of the processes involved in attitude change, with emphasis on the preparation and delivery of persuasive messages. Spring 2020
Refocusing in forced photonic quantum walks controlled by liquid crystal gratings

We mimic one dimensional forced quantum walks by using the photonic implementation obtained by means of a sequence of liquid-crystal devices (”g-plates”), which apply polarization-dependent transverse kicks to the photons in the beam. We observed refocusing phenomena for localized initial states.
Token Based Authentication Using IOT

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Web Service Scheduling in Multi-Cloud Environment

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Template-Based Efficient Resource Provisioning and Utilization in Cloud Data-Center

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
The Role of Internet of Things in the Healthcare Industry

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Analysis of K*(STAR) and Fuzzy C-Means Algorithm for Education Completion Performance

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
CHALLENGE OF THE ABUSE OF INFORMATION TECHNOLOGIES FOR PUBLIC INFORMATION

In this article, we view public information as a process of making available data and information through their distribution, primarily in cyberspace.Given that information is the fundamental right of every individual and obligation of public authority, the emergence of a phenomenon called "fake news"
Spatial Modification in the Parameters of Mountain Image Clustering Algorithm

Our proposed method used to overcome the drawbacks of computing values parameters in the mountain algorithm to image clustering. All existing clustering algorithms are required values of parameters to starting the clustering process such as these algorithms have a big problem in computing parameters. One of the famous clustering is a mountain algorithm that gives expected number of clusters, we presented in this paper a new modification of mountain clustering called Spatial Modification in the Parameters of Mountain Image Clustering Algorithm. This modification in the spatial information of image by taking a window mask for each center pixel value to compute distance between pixel and neighborhood for estimation the values of parameters ?, ? that gives a potential optimum number of clusters requiring in image segmentation process. Our experiments show ability the proposed algorithm in image brain segmentation with a quality in the large data sets
Hadoop Map Reduce Over Multiple Distributed Storage System

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Multi-frequency excitation based full-field laser scanning for improved depth estimation (Conference Presentation)

This paper presents the improved thickness estimation technique using Steady-state excitation Continuous-scanning Laser Doppler Vibrometery(SCLDV). In this study, the wavenumber sensitivity with respect to the thickness variations of a structure, along with the information of wave modes, is utilized to find an optimal interrogation frequency band for SCLDV. In addition, the use of multi-frequency steady-state response is used to improve the accuracy of the thickness variation. By utilizing the wavenumber sensitivity along with the multi-frequency excitations, the proposed SCLDV shows the improved depth estimation, compared to the previous approaches which empirically select the interrogation frequency. For validation of this technique, several experiments were performed on steel plates, which contain corrosion damage with various depth variations. The results showed that the proposed technique is very efficient in detecting and visualizing very small thickness variations of a structure at high speed.
IOT BASED MICRO-SERVO ROBOTIC ARM.

Robotics nowadays is becoming more popular due to various applications. The system implements Inverse Kinematics of a Robotic Arm and increase its working using Artificial Intelligence, by means of object trace. It will help to reach the goal of picking and placing the desired object. Real-Time system is used to reach complex hardware functionality. The aim is to design an algorithm and implement it on a robotic arm having an embedded processor. The detected image is then organized to trace the object in real time. Manipulation is a very important feature of robotics, which is necessary for fulfil simple and difficult tasks from painting cars in a factory to lifting casualty out of rubble. No ideal solution to manipulation has been identified yet that maximizes robustness and minimizes cost. Some particularly important considerations in manipulation are obedience and high fidelity force control. Force sensing and obedience at each robot joint can allow a robot to safely interact in emorphous and unknown environments.
Secure Voting Using Bio-metric Authentication

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Multiple Human Recognition for Networked Camera based Interactive Control in IoT Space

We propose an active color model based method for tracking motions of multiple human using a networked multiple-camera system in IoT space as a human-robot coexistent system. An IoT space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of IoT space as well. One of the main goals of IoT space is to assist humans and to do different services for them. In order to be capable of doing that, IoT space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and IoT space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in IoT space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.
Searching for panacea to management ills: Trust models revisited

This is a literature-based paper addressing a few trust models and studies. Trust is a multi-disciplinary subject occupying a pivotal position in the academic and corporate worlds. Many researchers have examined its impacts on various organisational issues. The impact of trust is much context specific. Some researchers have identified the factors of perceived trustworthiness as capability, benevolence and integrity. It reveals that competence, openness, concern and reliability are the dimensions of trust. Availability, competence, consistency, discreetness, fairness, integrity, loyalty, openness, promise fulfilment and receptivity are the ten conditions of trust, identified by the researchers. Some trust models find that high trust reduces competitive behaviour among the individuals and the organisations. Trust failure involves huge penalties to the organisations. Researchers agree that trust is a strong monitoring tool and it reduces expenditures, and leads to higher productivity. Future researchers may empirically examine various trust dimensions and models in various contexts. Keywords: Trust, trust models/studies, fairness
EVALUATION OF DIFFERENT IMAGE SEGMENTATION METHODS WITH RESPECT TO COMPUTATIONAL SYSTEMS

Image segmentation is a fundamental step in the modern computational vision systems and its goal is to produce amore simple and meaningful representation of the image making it easier to analyze.Image segmentation is a subcategory of image processing of digital images and, basically, it divides a given image into two parts: the object(s) of interest and the background.Image segmentation is typically used to locate objects and boundaries in images and its applicability extends to other methods such as classification, feature extraction and pattern recognition.Most methods are based on histogram analysis, edge detection and regiongrowing.Currently, other approaches are presented such as segmentation by graph partition, using genetic algorithms and genetic programming.This paper presents a review of this area, starting with taxonomy of the methods followed by a discussion of the most relevant ones.