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This paper will help to bring out some amazing findings about autonomous prediction and performing action by establishing a connection between the real world with machine learning and Internet Of thing. The purpose of this research paper is to perform our machine to analyze different signs in the real world and act accordingly. We have explored and found detection of several features in our model which helped us to establish a better interaction of our model with the surroundings. Our algorithms give very optimized predictions performing the right action .Nowadays, autonomous vehicles are a great area of research where we can make it more optimized and more multi - performing .This paper contributes to a huge survey of varied object detection and feature extraction techniques. At the moment, there are loads of object classification and recognition techniques and algorithms found and developed around the world. TSD research is of great significance for improving road traffic safety. In recent years, CNN (Convolutional Neural Networks) have achieved great success in object detection tasks. It shows better accuracy or faster execution speed than traditional methods. However, the execution speed and the detection accuracy of the existing CNN methods cannot be obtained at the same time. What's more, the hardware requirements are also higher than before, resulting in a larger detection cost. In order to solve these problems, this paper proposes an improved algorithm based on convolutional model A classic robot which uses this algorithm which is installed through raspberry pi and performs dedicated action.

Predicting the impact of academic papers can help scholars quickly identify the high-quality papers in the field. How to develop efficient predictive model for evaluating potential papers has attracted increasing attention in academia. Many studies have shown that early citations contribute to improving the performance of predicting the long-term impact of a paper. Besides early citations, some bibliometric features and altmetric features have also been explored for predicting the impact of academic papers. Furthermore, paper metadata text such as title, abstract and keyword contains valuable information which has effect on its citation count. However, present studies ignore the semantic information contained in the metadata text. In this paper, we propose a novel citation prediction model based on paper metadata text to predict the long-term citation count, and the core of our model is to obtain the semantic information from the metadata text. We use deep learning techniques to encode the metadata text, and then further extract high-level semantic features for learning the citation prediction task. We also integrate early citations for improving the prediction performance of the model. We show that our proposed model outperforms the state-of-the-art models in predicting the long-term citation count of the papers, and metadata semantic features are effective for improving the accuracy of the citation prediction models.

This paper describes how an anatomy and physiology laboratory class transitioned from a paper-based lab to an online learning platform that updated the curriculum to rely more on face-to-face small group collaboration and peer teaching. Student perceptions of the new format were positive, but halfway through the transition a global pandemic challenged the new instruction method. The face-to-face curriculum had to be adjusted to a virtual format that lacked in-person interaction between the instructor and the students. This switch to virtual labs had an adverse effect on both student perception and student performance in the second half of the semester. Our observations underscore the importance of creating an interactive community when teaching virtually.

Microfluidic paper-based analytical devices (μPADs) have attracted much attention over the past decade. They embody many advantages, such as abundance, portability, cost-effectiveness, and ease of fabrication, making them superior for clinical diagnostics, environmental monitoring, and food safety assurance. Despite these advantages, μPADs lack the high sensitivity to detect many analytes at trace levels than other commercial analytical instruments such as mass spectrometry. Therefore, a preconcentration step is required to enhance their sensitivity. This review focuses on the techniques used to separate and preconcentrate the analytes onto the μPADs, such as ion concentration polarization, isotachophoresis, and field amplification sample stacking. Other separations and preconcentration techniques, including liquid-solid and liquid-liquid extractions coupled with μPADs, are also reviewed and discussed. In addition, the fabrication methods, advantages, disadvantages, and the performance evaluation of the μPADs concerning their precision and accuracy were highlighted and critically assessed. Finally, the challenges and future perspectives have been discussed.

Internet of Things (IoT) has drawn important attention in recent years since it has made revolutionary changes in human life. The IoT enables the exchange of information or data in a wide variety of applications such as smart buildings, smart health, smart transport, and so on. As billions of connected things communicate with each other and can interchange sensitive information that may be revealed. Hence, strengthening IoT’s security and preserving users’ privacy is a crucial challenge. The aim of this paper is to provide a comprehensive study of the IoT security. Several IoT security attacks are examined and a taxonomy of the security requirements based on the attacks purposes is proposed. Furthermore, recent security solutions are described and classified based on their application area. Ultimately, open research directions and security challenges are discussed.

Due to the growth of e-commerce, most of the banking transactions are made on the online platform and all these transactions are made on the websites provided by the merchant or the payable apps and because of this the vulnerability of attacks has increased and there are also chances of using fraudulent websites and apps by the attackers though there are many high-security algorithms are been used for safeguarding against vulnerabilities. The way of judging the relation of trust on the online platform has become a major issue, so a proper trust model also needs to be maintained. In this paper, we reviewed various security algorithms which involve cryptographic algorithms, machine learning, anonymization, and masking techniques, blockchain, distributed networks, and many more to provide integrity, privacy, reliability, authentication, security, and risk-less e-commerce platform.

Background: The prostate-specific antigen (PSA) is one of the best markers for detecting prostate cancer. Rapid and real time recognition of PSA biomarker could be helpful in the early diagnosis and efficient treatment of prostate cancer. One of the usual methods to identify this biomarker is ELISA, which has a picomolar detection range but requires specialized personnel and also this technique is time-consuming and expensive. Methods: Cost-effective POC devices are great solutions because they are very cost-effective, sensitive and simple, do not require expert operators and have a high response time in a short time. With that in mind, in this work, a novel and simple label-free paper-based electrochemical immunosensor were designed by using conductive Ag-ink and designed directly by pen on paper technique on the surface of photographic paper, which is a suitable substrate for antibody immobilization, for rapid detection of PSA. Results: Based on the obtained results, under the optimum conditions, the synthesized Ag ink has a great substrate for antibody (Ab) and antigen (Ag) immobilization. The linear range was from 0.001 to 30 μg/L and the obtained low limite of quantification (LLOQ) was 0.001μg/L. This immunosensor also tested in human plasma samples, which had good analytical power. Conclusion: The proposed paper-based immunoassay could be a hopefully new and cheap tool for the diagnosis of other biomarkers.

In this activity, students find the theoretical probabilities of winning a coin toss and a round of the rock, paper, scissors game. They next devise strategies to win and test them out. Students then compare the theoretical probabilities they found with the experimental probabilities.

In this work, some counterexamples are given to refute some results in the paper by Kohli [RAIRO:OR 53 (2019) 1617–1632]. We correct the fault in some of his results.

The development of low-cost analytical devices for on-site water quality monitoring is a critical need, especially for developing countries and remote communities in developed countries with limited resources. Microbial electrochemical cell-based (MXC) biosensors have been quite promising for quantitative and semi-quantitative (often qualitative) measurements of various water quality parameters due to their low cost and simplicity compared to traditional analytical methods. However, conventional MXC biosensors often encounter challenges, such as the slow establishment of biofilms, low sensitivity, and poor recoverability, making them unable to be applied for practical cases. In response, MXC biosensors assembled with paper-based materials demonstrated tremendous potentials to enhance sensitivity and field applicability. Furthermore, the paper-based platforms offer many prominent features, including autonomous liquid transport, rapid bacterial adhesion, lowered resistance, low fabrication cost (

Microfluidic paper-based chips (μPCs) are micro-laboratory analysis systems that use paper instead of traditional microfluidic substrate materials and miniaturize biochemical reactions. Based on traditional 2D μPCs, the novel μPCs are innovative 3D structure chips that are realized by fluid channel construction, channel microvalve, folding and other fluid control methods. In recent years, μPCs have developed rapidly in terms of design and integration and have been widely used in food safety, environmental residue pollution, pathogen detection and other applications. Due to their advantages of low cost, portability and satisfactory thermal stability, they have unique potential in the field of rapid detection. Herein, based on the detailed preparation, we focus on the selection of the paper substrate, microfluidic chip hydrophilic/hydrophobic processing and substrate modification. We highlight the latest research progress of μPCs in rapid detection from 2014 to 2021, and discuss the remaining challenges and future perspectives for further development.

The use of paper-based microfluidics devices (μPADs) for designing rapid, easy, and on-site devices has undergone a dramatic increase in the last few years and the development of applications in the field of forensic science has had concomitant advances. The use of μPADs at the crime scene is finalized not only to obtain a rapid response but also to have crucial information on evidence collection. Several authors have proposed μPADs as alternative approaches to existing tests. These devices are designed to be used on-site without, or minimal, power sources. Furthermore, the technology provides prompt-readouts using a small sample volume, preserving important evidence for instrumental analysis. This review aims to provide a critical evaluation of developed μPADs. The document includes a brief overview on fabrication methods and on detection strategies, and it assesses advantages and limitations of applications related to forensic matters. A final section is devoted to future developments.

We present a rotational terahertz imaging system for inline nondestructive testing (NDT) of press sleeves for the paper industry during fabrication. Press sleeves often consist of polyurethane (PU) which is deposited by rotational molding on metal barrels and its outer surface mechanically processed in several milling steps afterwards. Due to a stabilizing polyester fiber mesh inlay, small defects can form on the sleeve’s backside already during the initial molding, however, they cannot be visually inspected until the whole production processes is completed. We have developed a fast-scanning frequenc-modulated continuous wave (FMCW) terahertz imaging system, which can be integrated into the manufacturing process to yield high resolution images of the press sleeves and therefore can help to visualize hidden structural defects at an early stage of fabrication. This can save valuable time and resources during the production process. Our terahertz system can record images at 0.3 and 0.5 THz and we achieve data acquisition rates of at least 20 kHz, exploiting the fast rotational speed of the barrels during production to yield sub-millimeter image resolution. The potential of automated defect recognition by a simple machine learning approach for anomaly detection is also demonstrated and discussed.

According to recent literature in the field of sustainability, the circular economy (CE) appears to be a thriving opportunity for creating new businesses, although less attention has been paid to the form in which its principles fit into a comprehensive framework that enables companies to design it in a practical way. This paper presents the methodology that has been adopted to pave the way to a coherent reference framework for circular business model innovation and its outstanding design and implementation, taking into consideration the entire value and supply chain. A unique analysis of recent innovations in circular economy models is provided herein, together with an exhaustive analysis of those elements that enable or hinder their implementation. The main interactions among all those critical elements influencing how organisations innovate and operate cooperatively within a CE ecosystem are also evaluated. In addition, a study of five industrial cases in the pulp and paper industry allowed searching for industrial insights and empirical evidence of the relevance of those elements, including observation, document analysis, and interviews. Lastly, the main outcomes of this research are illustrated using the CE reference framework designed when applied to the aforementioned industrial cases, and relevant insights into future improvements are also provided. This research was funded by European Union, grant number 730305, a collaborative research project entitled “New market niches for the pulp and paper industry waste based on circular economy approaches (paperChain)” from the European Union’s Horizon 2020 research and innovation programme.

Microfluidic paper-based analysis devices (μPADs) have undergone tremendous development in recent years and now provide a feasible low-cost alternative to traditional laboratory tests for the diagnosis of many common diseases and disorders. As such, they are of great interest and importance in developing regions of the world with a lack of medical resources and associated infrastructures. This review examines the advances made in microfluidic paper-based diagnostic technology in the past five years and describes the application of microfluidic paper-based assays to the detection of many common human diseases using 3 non-invasive samples sources such as saliva, tears and sweat. The review commences by introducing the basic principles of fluid transport in microfluidic paper-based devices. The structures and actuation systems used in common paper-based devices are then introduced and explained. A systematic review of recent proposals for the application of paper-based devices to the diagnosis of common human diseases is then presented. The review concludes with a brief discussion of the challenges facing the microfluidics paper-based diagnosis field in the coming years and the emerging opportunities for future research.

This study explored the relationship between syntactic complexity and rhetorical functions and the relationship between syntactic complexity and level of move/step realization in learner-generated research paper introductions. We created a corpus of 79 introductions written by undergraduate L2 students at intermediate to high-intermediate levels. We annotated the introductions for moves and steps, measured their syntactic complexity at the global, clausal, and phrasal levels, and rated their level of move/step realization across four levels (no, low, intermediate, and high). We conducted one-way MANOVA, one-way ANOVA, Pearson correlation, and stepwise multiple linear regression analyses. We found sentences realizing Reviewing items of previous research function to be significantly longer than other steps in Move1 and to contain significantly more clausal and phrasal complexity features. Sentences performing Claiming centrality function also demonstrated significantly more phrasal complexity features as measured by complex nominals per clause. We also found a higher level of phrasal complexity in introductions with a higher level of move/step realization, which can be attributed to introductions including Step1 and Step3, rather than containing all steps. Our findings imply that there is value in developing explicit instructions on how to use complex structures in performing rhetorical steps in research paper introductions. © 2021 Elsevier Ltd

Paper-based microfluidic devices have undergone rapid development and offered a promising low-cost platform for disease diagnostics in poor-resource areas. Recently, paper-hybrid microfluidic devices have attracted much attention and been applied in various low-cost point-of-care testings, due to multiple merits derived from both paper and other substrates. This chapter summarizes the recent progress of low-cost paper and paper-hybrid microfluidic devices for rapid diagnostics of human diseases. The commonly used fabrication techniques are first introduced, and the applications of numerous paper and paper-hybrid microfluidic devices are then elaborated with an emphasis on rapid disease diagnostics in terms of the nature of biomolecules in three major categories, namely, protein-, gene-, and cell-based diagnostics. Both advantages and disadvantages of using these devices are discussed, followed by the perspectives for broad applications in low-cost diagnostics.

Altres ajuts: Agència per a la Competitivitat de l'Empresa de la Generalitat de Catalunya by FEDER funds, Institució Catalana de Recerca i Estudis Avançats, and ERDF funds In this paper, an organic, fully recyclable and eco-friendly 20-bit inkjet-printed chipless RFID tag is presented. The tag operates in the near field and is implemented by means of chains of resonant elements. The characterization and manufacturing process of the tag, printed with a few layers of a commercial organic ink on conventional paper substrate (DIN A4), are presented, and tag functionality is demonstrated by reading it by means of a custom-designed reader. The tags are read by proximity (through the near field), by displacing them over a resonator-loaded transmission line, and each resonant element (bit) of the tag is interrogated by a harmonic signal tuned to the resonance frequency. The coupling between the reader line and the resonant elements of the tag produce and amplitude modulated (AM) signal containing the identification (ID) code of the tag.

Purpose: This study aimed at implementing lean six sigma to evaluate the productivity and manufacturing waste in the production line of a paper companyMethodology/Approach: The study is a case study in nature. The method illustrates how lean six sigma (LSS) is used to evaluate the existing production process in a paper production company with focus on productivity and manufacturing waste. The study considered a real-time problem of customer’s dissatisfaction. The gathered data is based on machine functionality (up time, down time and cycle time); materials and labour flow at every process stages of the production line. The optimization of the production process was based on lean tools like value stream mapping, process cycle efficiency, Kaizen, 5S and pareto chartFindings: Based on lean six sigma application, it was discovered that the present production performance was below standard and more manufacturing wastes were generated. The present productivity and manufacturing wastes are reported as low process cycle efficiency (23.4 %), low takt time (4.11 sec), high lead time (43200sec), high number of products not conforming to six sigma values, high down time (32.64 %) and excess labour flow (33). After the implementation of the lean six sigma tools for certain period of time, there are lots of improvements in the production line in terms of all the parameters considered.Research Limitation/ Implications: The study has demonstrated an application of lean six sigma in the case of solving real-time problems of productivity and manufacturing wastes which have a direct implication on customer’s satisfaction. The lesson learned and implications presented can still be further modeled using some lean based software for validityOriginality/Value: The study has contributed to the body of knowledge in the field of LSS with focus to process based manufacturing, unlike most literature in the field concentrate more on discrete based manufacturing.

This article reports on the design, fabrication, and characterization of an in-pipe worm-like soft robot with pneumatic actuators based on origami paper-fabric composites in which the paper and fabric serve as the skeleton and skin of the robot, respectively. The robot is assembled with an extensor of a bellow-like structure for implementing peristaltic locomotion and a clamp fabricated using a Kresling crease pattern at each end of the robot for anchoring. The performances of the pneumatic actuators, as well as the worm robot, are characterized and their dependence on some material, structural, and pneumatic parameters are investigated. Stepwise inflation of the clamp actuator takes place as the pressurization duration increases. The extension ratio of the extensor has a nonlinear relationship with the pressurization duration. The higher rigidity of the paper with a high weight per unit area can facilitate faster retention near the end of the extension process for the extensor with a small number of creases, while it becomes a resistance for the extension of the extensor with a large number of creases. The softness, lightweight features, low cost, ease to fabricate, modular design, and mobility of the worm robot indicate it has potential to find application in pipeline inspection, etc.

Purpose Identifying the frontiers of a specific research field is one of the most basic tasks in bibliometrics and research published in leading conferences is crucial to the data mining research community, whereas few research studies have focused on it. The purpose of this study is to detect the intellectual structure of data mining based on conference papers. Design/methodology/approach This study takes the authoritative conference papers of the ranking 9 in the data mining field provided by Google Scholar Metrics as a sample. According to paper amount, this paper first detects the annual situation of the published documents and the distribution of the published conferences. Furthermore, from the research perspective of keywords, CiteSpace was used to dig into the conference papers to identify the frontiers of data mining, which focus on keywords term frequency, keywords betweenness centrality, keywords clustering and burst keywords. Findings Research showed that the research heat of data mining had experienced a linear upward trend during 2007 and 2016. The frontier identification based on the conference papers showed that there were five research hotspots in data mining, including clustering, classification, recommendation, social network analysis and community detection. The research contents embodied in the conference papers were also very rich. Originality/value This study detected the research frontier from leading data mining conference papers. Based on the keyword co-occurrence network, from four dimensions of keyword term frequency, betweeness centrality, clustering analysis and burst analysis, this paper identified and analyzed the research frontiers of data mining discipline from 2007 to 2016.

PurposeHow to provide the most useful papers for searchers is a key issue for academic search engines. A lot of research has been carried out to address this problem. However, when evaluating the effectiveness of an academic search engine, most of the previous investigations assume that the only concern of the user is the relevancy of the paper to the query. The authors believe that the usefulness of a paper is determined not only by its relevance to the query but also by other aspects including its publication age and impact in the research community. This is vital, especially when a large number of papers are relevant to the query.Design/methodology/approachThis paper proposes a group of metrics to measure the usefulness of a ranked list of papers. When defining these metrics, three factors, including relevance, publication age and impact, are considered at the same time. To accommodate this, the authors propose a framework to rank papers by a combination of their relevance, publication age and impact scores.FindingsThe framework is evaluated with the ACL (Association for Computational Linguistics Anthology Network) dataset. It demonstrates that the proposed ranking algorithm is effective for improving usefulness when two or three aspects of academic papers are considered at the same time, while the relevance of the retrieved papers is slightly down compared with the relevance-only retrieval.Originality/valueTo the best of the authors’ knowledge, the proposed multi-objective academic search framework is the first of its kind that is proposed and evaluated with a group of new evaluation metrics.

Rewinding machines are used in the paper converting industrial sector to unroll paper veils from large source reels and wind them around smaller rolls, for the production of paper logs to be used in household activities. Many different types of rewinding machine exist, and they are mostly based on stapling devices which automatically unroll a large coil of paper, roll it up around a new log, stop the veil allowing it to be torn off, unload the completed paper log, and reload a new paper core to be rolled up. Winding units generally include a primary and a secondary roller, supplying the desired rotational speed for winding, and a pressure unit consisting of a pressure roller in contact with the paper log being rolled up, which assures adequate containment and avoids the paper log to escape. All known systems have some mechanical limitations, mainly due to the contact of the pressure roller with the paper log, causing instabilities and vibrations, particularly when working with soft paper veils. This limits the maximum possible winding speed. The aim of this paper is it to present a detailed kinematic analysis of a novel pressure unit which overcomes the aforementioned limitation.

Objectives. This study aimed to determine the types and frequency of pen-paper observational methods (OMs) used by Iranian practitioners and to identify their errors in selecting and implementing these methods. Methods. This was a systematic review and analytical study of papers in which the OMs had been used. Scientific databases were analyzed from September 1970 to September 2018. Errors were determined based on a list of wrong practices both in the selection and implementation of methods. Three ergonomists carried out the process of identifying errors independently. Results. The most frequently used methods were rapid upper limb assessment (RULA), quick exposure check (QEC) and rapid entire body assessment (REBA), respectively. Errors in selecting and implementing pen-paper OMs were 53.3 and 36.4%, respectively. Conclusions. Despite the abundant number of pen-paper OMs, Iranian practitioners use few of them. The high rate of errors can indicate a lack of knowledge and skills among practitioners for selecting and implementing OMs. The development of decision-making tools may help practitioners to select appropriate pen-paper OMs for assessing different types of tasks.

This paper presents a monolithic manufacturing process to realize active-matrix meshed TFT arrays on foil with physical voids between pixels, realizing membrane-like structures for use in biometrics-under-display applications. Moreover, however, the concept enables new applications in the biomedical electronics domain.

This letter presented a pencil-on-paper-based ecofriendly capacitive touchpad fabricated through a low-cost lab- and solvent-free fabrication process. Economical, readily available, and biodegradable materials, such as pencil and paper, have been used for sensor fabrication. A touchpad based on five such sensors has been developed and evaluated by using it as a user control interface to on/off LEDs and displaying results on LCD and mobile app. The graphite sensors in the user interface have been shielded from the direct interaction of humans and the environment using changeable cling film to make the interface reliable and reusable. The interface can be used in different conditions and users by changing the shielding film. Simultaneously, the system's functionality will remain consistent and functioned similarly to the conventional touch sensors and buttons. These recyclable and easily arrayed touch sensor-based keypads can contribute to future developments in disposable and lightweight interfaces for human–machine interface, medical and healthcare applications, smart packaging, security monitoring, and consumer products.

Along with the unceasing growth of worldwide economic and the associated issues on resources, energy and environment, clean energy generating technologies that are based on recyclable materials, if possible, may become the future trend of development. Here, we report the design of a cheap, lightweight, and recyclable single-electrode triboelectric nanogenerator (TENG) that utilizes waste paper as the triboelectric material. Under the current strategy, we successfully developed green energy machines without vastly increasing the mining of various critical minerals around the world. The as-designed TENG could not only collect and convert mechanical energy into electricity with sound efficiency, but also has the merit for continuous reuse and quick construction. The maximum output power density is as high as 171 mW·m−2 at a resistance of 130 MΩ and could be integrated into a book for monitoring reading actions, thus providing a new approach to the low-cost, green and sustainable self-powered electronic systems.

The tourism and travel sector is trying to provide different facility using a large amount of data collected from different tourism web sites. The tourist easily retrieves to reviews, evidence of different tourists and accesses them properly. It helps tourists have made the planning of visit to tourism place. So that, a major challenge faced by tourism sector is to utilize the accumulate information for detecting tourist preferences. Unfortunately, some user's comments are irrelevant and complex for understanding and long-winded these become hard for recommendation. Aspect based sentiment classification methods have shown promise in overcome the issue. In existing not much work on aspect based sentiment with classification. Here in this paper represents a framework of aspect based sentiment classification recommendation system that will not only identify the aspects very efficiently but can perform classification task with high accuracy using machine learning algorithms. This framework helps tourists to find better tourist spot, hotels, restaurant and resort in a city, and here performance has been evaluated by conducting experiments on Yelp and foursquare real-time datasets.

Cognitive deficits are a core feature of mental and behavioral disorders, leading to poor treatment adherence and functionality. Virtual reality (VR) methodologies are promising solutions for cognitive interventions in psychiatry once they provide greater ecological validity. This study assessed and compared two content-equivalent cognitive training (CT) interventions, delivered in desktop VR (Reh@City v2.0) and paper-and-pencil (Task Generator (TG)) formats, in patients with mental and behavioral disorders. 30 patients were randomly assigned to the Reh@City v2.0 group and the TG group. Both groups of patients underwent a time-matched 24-sessions intervention. Neuropsychological assessments were performed at baseline, post-intervention, and follow-up. A within-groups analysis revealed significant improvements in visual memory and depressive symptomatology after the Reh@City intervention. The TG group improved in processing speed, verbal memory, and quality of life (social relationships and environmental domains). Between groups, Reh@City led to a greater reduction in depressive symptomatology, whereas the TG group showed higher improvements in social relationships aspects of quality of life. At follow-up, previous gains were maintained and new improvements found in the Reh@City (global cognitive function, language, visuospatial and executive functions) and the TG groups (attention). The Reh@City significantly reduced depressive symptomatology, and the TG led to greater improvements in processing speed, abstraction, and social relationships domain of quality of life at follow-up. Both interventions were associated with important cognitive, emotional, and quality of life benefits, which were maintained after two months. Reh@City and TG should be considered as complementary CT methods for patients with mental and behavioral disorders. Trial registration The trial is registered at ClinicalTrials.gov, number NCT04291586.

In this paper, we will deliberate how to control robot car using Wi-Fi module through a webpage using computer or smartphone. The advantage of using robot car is it can be used for various purposes like this project can be modified quite easily to include a spy camera as well that can stream the videos to the user over Wi-Fi. Attempts would be made to use solar cells instead of the regular lithium-ion battery for the project. This robot car can also be used to push the objects from one place to another. This project will be enhanced with better Wi-Fi which would enable long distance communication.

Educational Data Mining (EDM) is a platform for learning and exploring from data to get essential information and generate the unique pattern which will help study, analyse and skill student performance in academic. Various data mining methods can be apply to filter the data from data warehouse to implement data mining techniques which helps student for taking decisions for better outcome. The model which can be use in Educational data mining must be a constructive and descriptive model applied on data warehouse and must gather very accurate data for enhance the performance of study. Regression analysis can also be used to develop a model to use as study tool; it can be used dependent or independent variables. If the model is enough perfect for using as study tool then every cluster of data must be use that model to fetch the resultant data. Sometimes educational data mining is considered as overall performance of students, but each student has its own level of understanding the contents so that method must also be enough flexible for every one ; for fulfilling this requirement educational method can be complex, but once it is constructed then it will helpful for every one. This paper is describing various data mining techniques and their proper uses.

Summary Coronavirus disease (COVID‐19) has spread all across the world. Low‐ and medium‐income countries are more affected economically and socially compared to developed countries due to the lack of a rapid, robust, and affordable testing infrastructure. Furthermore, the high cost of real‐time polymerase chain reaction (PCR) system, sophisticated user‐handling procedure, and high expense of the conventional clinical tests are the root causes of the less accessibility of the testing systems to the users. In this study, a COVID‐19 Point‐of‐Care (POC) ecosystem model is proposed for the low‐ and medium‐income countries (or energy deprived countries) that will facilitate the technological development with locally available fabrication components. In addition, the nontechnological development phases have also been discussed, which encompasses the collaboration among academia, local as well as government bodies, and entrepreneurial ventures. In addition, a hypothetical design of a microfluidic paper‐based analytical (μPADs) POC platform is proposed to detect COVID‐19 analyte using unprocessed patient‐derived saliva, which is a miniaturized form‐factor of conventional real‐time polymerase chain reaction (PCR) technique. The device contains four major reaction zones, which are sample zone, buffer zone, loop‐mediated isothermal amplification (LAMP) Master Mix zone, Ethylenediamine tetraacetic acid (EDTA) zone, and sensor zone. To obtain quicker test results and easier operation, a handheld image acquisition technique is introduced in this study. It is hypothesized that in a remote setting, the proposed design could be used as an initial guideline to develop a POC COVID‐19 testing system, which may be simple, easy‐to‐use, and cost‐effective., A COVID‐19 Point‐of‐Care (POC) model is proposed that will facilitate the technological development with locally available fabrication components. To obtain quicker test results and easier operation, a handheld image acquisition technique is introduced. The proposed design could be used as an initial guideline to develop a POC COVID‐19 system, which may be simple, easy‐to‐use, and cost‐effective.

Life cycle assessment (LCA) is an attractive approach to implement the waste management system in terms of environmental sustainability. The variety of environmental options has been made an emerge...

Background Display signage is ubiquitous and essential in hospitals to serve several clerical, operational, and clinical functions, including displaying notices, providing directions, and presenting clinical information. These functions improve efficiency and patient engagement, reduce errors, and enhance the continuity of care. Over time, signage has evolved from analog approaches such as whiteboards and handwritten notices to digital displays such as liquid crystal displays, light emitting diodes, and, now, electronic ink displays. Electronic ink displays are paper-like displays that are not backlit and show content by aligning microencapsulated color beads in response to an applied electric current. Power is only required to generate content and not to retain it. These displays are very readable, with low eye strain; minimize the emission of blue light; require minimal power; and can be driven by several data sources, ranging from virtual servers to electronic health record systems. These attributes make adapting electronic ink displays to hospitals an ideal use case. Objective In this paper, we aimed to outline the use of signage and displays in hospitals with a focus on electronic ink displays. We aimed to assess the advantages and limitations of using these displays in hospitals and outline the various public-facing and patient-facing applications of electronic ink displays. Finally, we aimed to discuss the technological considerations and an implementation framework that must be followed when adopting and deploying electronic ink displays. Methods The public-facing applications of electronic ink displays include signage and way-finders, timetables for shared workspaces, and noticeboards and bulletin boards. The clinical display applications may be smaller form factors such as door signs or bedside cards. The larger, ≥40-inch form factors may be used within patient rooms or at clinical command centers as a digital whiteboard to display general information, patient and clinician information, and care plans. In all these applications, such displays could replace analog whiteboards, noticeboards, and even other digital screens. Results We are conducting pilot research projects to delineate best use cases and practices in adopting electronic ink displays in clinical settings. This will entail liaising with key stakeholders, gathering objective logistical and feasibility data, and, ultimately, quantifying and describing the effect on clinical care and patient satisfaction. Conclusions There are several use cases in a clinical setting that may lend themselves perfectly to electronic ink display use. The main considerations to be studied in this adoption are network connectivity, content management, privacy and security robustness, and detailed comparison with existing modalities. Electronic ink displays offer a superior opportunity to future-proof existing practices. There is a need for theoretical considerations and real-world testing to determine if the advantages outweigh the limitations of electronic ink displays.