Graphical View Research Articles

A journey towards the commitments of national education policy 2020 through concept mapping

Objectives: To explore pedagogical goals and concerns in National Education Policy (NEP 2020), Ministry of Human Resource Development, Government of India. The current review tries to find some ways and methods to make learning process enjoyable and meaningful as desired by NEP 2020. The roles of concept mapping in achieving the pedagogical goals of NEP 2020, also objectify this paper. Method/Analysis: In pursuing of the objectives, NEP 2020 and a set of articles related to the topic were explored. This study provides critical analysis and review on the role of concept mapping in achieving the pedagogical goals of NEP 2020. The paper deals with the common concerns of NEP2020 and Concept Mapping. Findings: The outcome of the review is that Concept mapping can offer an effective tool in education for both, teaching and learning process by supporting an active and meaningful learning. Concept maps provide a unique graphical view of how students organize, connect, and synthesize information. Concept maps give students an opportunity to think about the connections between the concepts being learnt and reflect on their understanding of the concept which develops critical thinking of the learners. Further, it provides platform for collaboration, discussion; arriving at shared understandings among members of groups. Concept map can be used to replace rote learning with meaningful and enjoyable learning. Novelty: NEP 2020 has been explored and taken into consideration keenly to find its pedagogical goals. The role of concept mapping in achieving pedagogical goals of NEP 2020 has been highlighted in the present paper. Thus, the paper explores how concept mapping can be an effective tool in contributing to a great extent to meet the pedagogical goals of NEP 2020. Keywords: National Education Policy 2020; Pedagogy; Critical Thinking; Concept Mapping

Microelectronics Design in Educational Apps for Technical Education Learning in Pandemic Eras

In the educational sector where the study was conducted to determine effect of pandemics in the use of microelectronics in design of educational apps for online learning in technical education in Nigeria. The population for the study was 302 people made up of 264 technical college teachers in both public and private schools and 38 school administrators. The instrument for data collection was structured questionnaire. The return rate of the instrument was 96%. Three experts validated the instruments. A pilot study of 10 school administrators and 30 technical college teachers were conducted. Pearson Product Moment Correlation Coefficient was used to test for the reliability. The total reliability coefficient of .79 was obtained for the instrument. Three research questions and three null hypotheses guided the study. Mean and standard deviation were used to answer the research questions, while t test was employed to test the null hypotheses at .05 and .01 levels of significance. Also, MATLAB application was used to give graphical views of critical relations in the study. The major findings were: (1) A good number of private technical education have ICT facilities and staff than most public technical education schools. (2) There is no significant difference between the use of ICT skills of teachers in the pre COVID-19 era because the F-tab of 6.64 and 18.0 at 5% and 1% levels of significances respectively as against F-cal of 0.0014. (3) There is significant difference on the income of technical education administrators since the introduction of EduApps in teaching and learning because the F-tab of 6.64 and 18.0 at 5% and 1% levels of significances respectively as against F-cal of 2.82. It was recommended that technical colleges should be well equipped with Internet of Things facilities and competent technology skilled technical teachers, ICT experts and functional computer laboratory in other to enhance the teaching and learning in technical education.

Predictive data regression technique based carbon nanotube biosensor for efficient patient health monitoring system

In many ways, monitoring the patient's health with appropriate sensors to monitor the hospital’s connection, as if the patient is lying in bed. The previous method of monitoring can be uncomfortable for a variety of reasons. Tracking a growing number of patients requires many trained health professionals and doctors. The proposed predictive data regression technique (PDRT) based carbon nanotubes (CNT) biosensor system has been introduced in the fields like Biomedical. In this analysis technique, the sensor value is compared to the threshold value; if any changes occur, the controller sends the user alert via IoT. The patients are present in this area so that their physicians and many physiological measurements and applications can be seen. Carbon nanotubes (CNT) have been used as electronic mediators and adsorption substrates in biosensors due to their extraordinary electrochemical properties. Explore its potential biosensing applications, platinum, carbon nanomaterials, electrochemical electrode preparation and features. The purpose of this proposal is to maintain a system of inpatient physiological parameters and activity. The physician can see a graphical view of the patient's parameters and a computer system worn by the patient, the Wi-Fi network, and the display. Abnormalities inpatient data are messages sent to the doctor via an IoT system to remind them of the situation. The Proposed Predictive Data Regression Technology (PDRT) system is given a better performance to the user, and it provides the output accuracy.

Selective and sensitive detoxification of toxic lead ions from drinking water using lead (II) ion-imprinted interpenetrating polymer linkage

The present study describes a new approach for the lead (II)-imprinted interpenetrating polymer linkage synthesis by ion-imprinted polymers. The development of lead (II) (Pb2+) ion-imprinted polymer by employing the 4-vinyl pyridine as a complexing agent and methacrylic acid as a functional monomer was used for the selective elimination of noxious Pb2+ ions from an aqueous environment. Different analytical techniques have been used for the characterization of synthesized Pb2+ion-imprinted polymeric material such as scanning electron microscopy, energy-dispersive X-ray, and Fourier-transform infrared spectroscopy. During adsorption study, different parameters have been optimized such as pH, agitation time, time study, and adsorbent dose to achieve maximum adsorption capacity. This study well fitted the Langmuir isotherm model, while the kinetic study was well defined by pseudo-second order. The relative selective factor (Kʹ) of Pb2+ ion and coexisting ions was greater than 1 due to the imprinting effect. The maximum adsorption capability of Pb2+ ion-imprinted polymer was 85.47 mg g−1 at pH 6. The developed method obtained a good linear range from 10 to 100 μg L−1 concentration, with a limit of detection (0.74 µg L−1) and a limit of quantification (2.48 µg L−1). The developed methodology was validated by the spiking addition method and obtained good results in accordance with spiking values in real samples. Graphical view of lead (II)-imprinted interpenetrating polymer linkage

Development of a LiDAR-guided section-based tree canopy density measurement system for precision spray applications

An unmanned ground-based canopy density measurement system to support precision spraying in apple orchards was developed to precisely apply pesticides to orchard canopies. The automated measurement system was comprised of a light detection and ranging (LiDAR) sensor, an interface box for data transmission, and a laptop computer. A data processing and analysis algorithm was developed to measure point cloud indices from the LiDAR sensor to describe the distribution of tree canopy density within four sections according to the position of the trellis wires. Experiments were conducted in two orchard sites, one with GoldRush (larger trees) and the other one with Fuji (smaller trees) apple trees. Tree leaves were counted manually from each section separated by trellis wires. Field evaluation results showed a strong correlation of 0.95 (R2 = 89.30%) between point cloud data and number of leaves for the Fuji block and a correlation of 0.82 (R2 = 67.16%) was obtained for the GoldRush block. A strong correlation of 0.98 (R2 = 95.90%) was achieved in the relationship between canopy volume and number of leaves. Finally, a canopy density map was generated to provide a graphical view of the tree canopy density in different sections. Since accurate canopy density information was computed, it is anticipated that the developed prototype system can guide the sprayer unit for reducing excessive pesticide use in orchards.

Recent advancement in cervical cancer diagnosis for automated screening: a detailed review

Cervical cancer is one of the most common and dangerous diseases for women. Initial diagnosis and classification of cervical cancer are to reduce the mortality rate. The Pap smear images are widely employed for the detection of cervical cancer in an automated manner; thereby, it enables reliable and accurate results. Recently, different kinds of soft computing techniques are used to deal with cervical cancer detection. In order to gain insight into recent advancements in the fields of study, this paper analyses most research papers between January 2010 and December 2020. This paper presents the graphical and organized view of the recent research works. The study explored the scope for further research in soft computing methods for the segmentation and classification of cervical cancer. The review also carried out an analysis of cervical cancer detection by categorizing the referred papers into techniques focused on soft computing. This study will provide information for researchers, publishers, and experts to examine emerging research patterns in the field of cervical cancer detection from pap smear images.

Mutation: A graphical view

Mutation: A graphical view

Analysis of the intersection throughput at changes in the traffic flow structure

The paper addresses the throughput of an urban signalized intersection when the traffic flow structure varies widely. In the course of the study, data were collected from a street CCTV camera tracking traffic flows at a single intersection. At the preliminary step during the analysis of the dynamics of vehicles passing the intersection when leaving the queue that formed in front of the red light, it was found that it significantly changes for different types of vehicles. Therefore, the next step was to develop a statistically significant mathematical model of the intersection throughput as a multiple regression equation including all vehicle types under consideration. This model gave us various predictive estimates with the traffic flow structure varied. To obtain a visual representation of the results, we tested a model of category-based traffic flow at the intersection, built on the basis of fuzzy logic methods. This model allowed us to estimate the intersection throughput depending on some uncertain traffic flow factors in a graphic 3D view. The study was oriented towards the development of an algorithm to analyze the time required for a heterogeneous queue of vehicles to pass the intersection in real time. The algorithm can be used in intelligent transportation systems, in particular, in problems related to uninterrupted traffic of unmanned vehicles. The models considered may serve as a good basis for justified decisions on improving the vehicle-to-infrastructure communication (V2I).

How did you do that The value of externalising knowledge in graphic design

This paper aims to study graphic designers' views on knowledge, considering the challenges faced by the field today. Expressing thoughts about what is needed for a graphic designer to build professional confidence, interview respondents mentioned topics like historical knowledge as well as feedback and presentation skills. To facilitate the navigation of the ever-changing graphic design landscape and to build a solid professional identity, externalising tacit knowledge is a key issue. The study finds that graphic designers mainly talk about their design work when presenting to clients, primarily with the aim of convincing them to accept new proposals. A case can therefore be made for the necessity of developing graphic designers' skills when it comes to explicating design processes with the aim of making it clear to non-designers what it actually is that a graphic designer knows and does, as well as building a stronger theoretical foundation for the profession.

КРЕАТИВНЫЙ НЕЙМИНГ НИЖЕГОРОДСКИХ ЗАВЕДЕНИЙ ОБЩЕСТВЕННОГО ПИТАНИЯ: ГРАФИЧЕСКИЙ АСПЕКТ

The purpose of the research is to analyze the creative naming of Nizhny Novgorod public catering establishments (restaurants, cafes, bars, burgers, coffee shops, pizzerias) from the point of view of graphics. The source of the material for the study was the personal card index of ergonyms. During the course of study, the following research methods were applied: general scientific method, particularly generalization, interpretation and classification of material, word-formation analysis and pragmatic analysis. It was discovered that innovations created by means of graphic hybridization act as a productive way of influencing the consumer. Ergonyms-innovations are easy to remember, have expressiveness, form positive associations, identify the institution. The analysis of the material showed that the most productive patterns of graphic hybridization were monographixation (33%), polygraphixation (47%) and tographixation (18%). It is noted that for a more powerful impact on the recipient, the nominators combine different paterns in one ergonym (2%).

Personalized Book Recommendation System using Machine Learning Algorithm

As the amounts of online books are exponentially increasing due to COVID-19 pandemic, finding relevant books from a vast e-book space becomes a tremendous challenge for online users. Personal recommendation systems have been emerged to conduct effective search which mine related books based on user rating and interest. Most of these existing systems are user-based ratings where content-based and collaborative-based learning methods are used. These systems' irrationality is their rating technique, which counts the users who have already been unsubscribed from the services and no longer rate books. This paper proposed an effective system for recommending books for online users that rated a book using the clustering method and then found a similarity of that book to suggest a new book. The proposed system used the K-means Cosine Distance function to measure distance and Cosine Similarity function to find Similarity between the book clusters. Sensitivity, Specificity, and F Score were calculated for ten different datasets. The average Specificity was higher than sensitivity, which means that the classifier could re-move boring books from the reader's list. Besides, a receiver operating characteristic curve was plotted to find a graphical view of the classifiers' accuracy. Most of the datasets were close to the ideal diagonal classifier line and far from the worst classifier line. The result concludes that recommendations, based on a particular book, are more accurately effective than a user-based recommendation system.

Strategic planning research through fifty years of long range planning: A bibliometric overview

Long Range Planning (LRP) is the first journal focused on strategic planning. It was created in 1968 by the Long Range Planning Society, and it celebrated its 50 th anniversary in 2018. This event led to the presentation of a complete bibliometric study aimed at identifying the most significant results that occurred in the journal during this period. For this purpose, bibliometric data were collected from the Web of Science Core Collection database, and two bibliometric approaches were used to analyze the journal's publications: a performance analysis and a graphical mapping of the literature. The first of these uses a wide range of productivity and influence indicators that include the number of publications and citations, the h-index, and citations by paper, among others. The second approach uses the VOSviewer software to deliver a graphical view of the various intellectual connections within LRP. The results of both bibliometric approaches are consistent and confirm LRP as a leading journal in strategic planning and management, with increasing participation of authors and universities from countries around the world.

Influence of Magnetic Field, Thermal Radiation and Brownian Motion on Water-Based Composite Nanofluid Flow Passing Through a Porous Medium

This paper explored the effects of a three-dimensional water composite nanofluid fluid flow between two horizontal parallel platelets in a rotating device. Different criteria contrast the flow properties of the conventional fluid (water), nanofluid cup-water, Al2O3 and composite Nanofluid. Through efficient transformations, nonlinear dimensional equations are translated into dimensional expressions. For the resolution of the dimensionless Ordinary differential equations system, a semi-analytical analytical homotopy technique is used. In order to test flow, heat, and mass transmission, a graphical analysis was performed with various variables. Relevant and Graphic view with skin friction numerical values, Nusselt local count and the Sherwood counters. The magnetic parameter has been shown to speed up. Heat transmission also improves through thermophoresis, magnetic field and thermophoresis, whilst thermophoresis, Schmidt numbers and Brownian motion help to reduce the mass transmission.

Web-Based Attendance Monitoring System

Wireless attendance monitoring system is a system developed to track student attendance during school days. This project features student’s ID Card tapping in the terminal and displays student profile in the portal. An area for announcements is also added in the portal aside from sending it via SMS. More so, it also features an admin panel, including a dashboard that displays reports in graphical view for easy system monitoring as well as it has full wireless computing technology. The software and technologies used in this project are Raspberry Pi, Database Server, RFID Reader, Arduino NMCU, Python, PHP, MySQL, Bootstrap, and CSS.

Beyond Interoperability with The Single Patient Viewer: A Clinical Portal to Access Integrated Patient Records

IntroductionIn the Western Cape Province of South Africa, a wealth of patient-level data is collected through many separate electronic systems, which share a unique health identifier. However, clinicians primarily access paper folders, which can be unreliable, difficult to locate and are at risk of loss. Patients frequently attend multiple facilities and their information may not be accessible across facilities, hampering continuity of care.
 Objectives and ApproachFacilitated by the unique health identifier, a provincial Health Information Exchange (HIE), harmonises patient level data from routine systems into a health information exchange daily. The Single Patient Viewer (SPV) has been developed as a prototype web-based electronic health record and data access portal. SPV integrates clinical data for a single patient both longitudinally and cross-sectionally, in tabular and graphical views, to assist clinicians in rapid information discovery. The application is designed as a web application that calls a multi-purpose API that facilitates interoperability with the HIE.
 ResultSPV is in an extended pilot phase with over 200 clinicians using the portal, either for clinical care provision, or for clinical audit activities. The application has evolved to include referral, follow-up (voice call and messaging) and reporting functionality.
 In the past 6 months, over 17,000 patients have been viewed with an average daily search of 150 patients. An anonymised user survey with 52 participants showed that users felt that SPV was enjoyable to use, easy to learn, innovative, and supportive and valuable to their work.
 Conclusion / ImplicationsSPV has been developed as a global public good project and will be made freely available once matured. A unique feature of the development of SPV is that clinicians were using it while it was being built, enabling constant clinical user feedback. SPV demonstrates the value of integrating health data for clinical viewing while interoperable systems mature.

On Topological Indices of mth Chain Hex-Derived Network of Third Type

In theoretical chemistry, the numerical parameters that are used to characterize the molecular topology of graphs are called topological indices. Several physical and chemical properties like boiling point, entropy, heat formation, and vaporization enthalpy of chemical compounds can be determined through these topological indices. Graph theory has a considerable use in evaluating the relation of various topological indices of some derived graphs. In this article, we will compute the topological indices like Randić, first Zagreb, harmonic, augmented Zagreb, atom-bond connectivity, and geometric-arithmetic indices for chain hex-derived network of type 3 CHDN3(m,n) for different cases of m and n. We will also compute the numerical computation and graphical view to justify our results.Mathematics Subject Classification: 05C12, 05C90

Rancang Bangun Real Count E-voting Menggunakan Mikrokontroler

The purpose of this research is to implement an embeded system in a form of a device that can provide e-voting services and a realcount process that can quickly accumulate votes. With this device, it is expected to be a solution to conventional elections that are still prone to fraud, wasteful costs, and inefficient.
 This device applies NFC technology. Voter’s idcard is used as an identifier, the UID of voter’s idcard is read by the NFC reader and the verification process is running. Voters are entitled to vote if the voters' idcard number is verified and registered in the database. Here the voter will be allowed to proceed for choosing their preferred candidate from the pushbuttons. This device is expected to be saved huge cost by using pushbuttons instead of ballot papers.
 This device uses the SIM808 module as a data communication medium to send http packages containing uid and vote values to the webserver, to be further matched in a table in the database. When voters vote, the uid of the voter is stored in the results table in the following database with the value of the vote, and if an idcard with the same uid votes again, then the latest vote values will not be store. This method prevents duplication which often happens in conventional voting system. After whole voting ends, the final result is displayed on a web page in a graphical view for the satisfaction of voters. Voting and counting has become much faster and easier as the system doesn't really require counting personnel, therefore there has been a substantial reduction in the number of remuneration that is paid to them. This result menu can only be accessed after the specified time.

Causal graphical views of fixed effects and random effects models.

Despite the long-standing discussion on fixed effects (FE) and random effects (RE) models, how and under what conditions both methods can eliminate unmeasured confounding bias has not yet been widely understood in practice. Using a simple pretest-posttest design in a linear setting, this paper translates the conventional algebraic formalization of FE and RE models into causal graphs and provides intuitively accessible graphical explanations about their data-generating and bias-removing processes. The proposed causal graphs highlight that FE and RE models consider different data-generating models. RE models presume a data-generating model that is identical to a randomized controlled trial, while FE models allow for unobserved time-invariant treatment-outcome confounding. Augmenting regular causal graphs that describe data-generating processes by adding the computational structures of FE and RE estimators, the paper visualizes how FE estimators (gain score and deviation score estimators) and RE estimators (quasi-deviation score estimators) offset unmeasured confounding bias. In contrast to standard regression or matching estimators that reduce confounding bias by blocking non-causal paths via conditioning, FE and RE estimators offset confounding bias by deliberately creating new non-causal paths and associations of opposite sign. Though FE and RE estimators are similar in their bias-offsetting mechanisms, the augmented graphs reveal their subtle differences that can result in different biases in observational studies.

Performance analysis of distributed storage clusters based on kernel and userspace traces

SummaryDistributed storage systems are commonly used in modern computing. They are highly scalable and offer data replication and fault tolerance. The complexity of those systems makes them difficult to debug using traditional tools. The existing tools are able to evaluate the overall performance of such systems but they do not provide enough information to find the root cause of performance issues. In this article, we propose a tracing‐based performance analysis framework for storage clusters. We use a tracing strategy that reduces the tracing overhead in production systems. The traces collected from the different storage nodes are correlated and used to generate a data model that represents the cluster. Userspace tracing is used to gather data from the storage daemons, while Kernel tracing is used to provide detailed information about operating system internals such as disk queues, network queues and process scheduling. Efficient data structures are used to store the model and to generate metrics and graphical views. Our tool is used in different real world scenarios and is able to investigate interesting performance problems including I/O latencies, data replication and storage nodes failures.

The Impact and Importance of Fabric Image Preprocessing for the New Method of Individual Inter-Thread Pores Detection

Abstract The paper describes the impact and importance of preprocessing methods of fabric image for detection of inter-thread pores (ITP), which is a new method of individual ITP identification. The aim of this experiment is to identify precisely every individual ITP of fabric structure by using optimal preprocessing algorithm for further quantitative, morphometric structural analysis of specialized fabrics (barriers, industrial filters, composites, others) in context of air permeability, flow resistance, UV radiation, viruses penetration, thermal comfort by estimation fabric porosity, especially macroporosity parameters and cover factor. The correct identification of individual ITP depends on the acquisition method and the preprocessing algorithm. It was conducted by analyzing the adaptation of digital image preprocessing methods for two structures of plain weave fabric in two magnification zooms, 1.25 and 0.8. Preprocessing operations were performed in the area of spatial operations of the image. The optimal preprocessing algorithm includes low-pass filtering, histogram equalization, nonlinear filtering, thresholding, and morphological operation. This algorithm was selected based on the factors developed by the author (ITP detection, RID factor—a difference between the real and model ITP areas) which rely on the ITP size, shape, and location. The graphic view of the ITP contour position on the fabric image is a verification element in the optimal preprocessing algorithm. The presented results of the air permeability of two different plain weave structures confirm the need to optimize the algorithm of pre-image processing methods to precisely detect each individual ITP in the fabric image.