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With the increasing use of surveillance cameras, face recognition is being studied by many researchers for security purposes. Although high accuracy has been achieved for frontal faces, the existing methods have shown poor performance for occluded and corrupt images. Recently, sparse representation based classification (SRC) has shown the state‐of‐the‐art result in face recognition on corrupt and occluded face images. Several researchers have developed extended SRC methods in the last decade. This paper mainly focuses on SRC and its extended methods of face recognition. SRC methods have been compared on the basis of five issues of face recognition such as linear variation, non‐linear variation, undersampled, pose variation, and low resolution. Detailed analysis of SRC methods for issues of face recognition have been discussed based on experimental results and execution time. Finally, the limitation of SRC methods have been listed to help the researchers to extend the work of existing methods to resolve the unsolved issues.

Herein we report a quantitative, multiplex assay for disease markers in plasma based on an integrated setup of a portable scanner and a disposable paper-based analytical device (PAD). The quantitative analysis relies on the digital colorimetric reading of the three-layer PAD with 30 assay sites for performing respective chromogenic reactions for plasma uric acid, glucose, and triglyceride, which are considered as important risk factors for cardiovascular diseases. A portable scanner with WiFi transmission capability was used to produce high-quality color images of the PADs and wirelessly transfer them to a smartphone or other mobile devices for data processing. The concentrations of biomarkers in both standard solutions and plasma samples can be directly obtained using a custom-designed smartphone app that is also capable of constructing calibration curves. The detection limits of uric acid, glucose, and triglyceride were determined to be 0.50 mg/dL, 0.84 mmol/L, and 14 mg/dL, respectively, which are below the normal limits and adequate for clinical validation. Owing to the distinct advantages—simple, portable, and cost-effective—this mobile assay protocol can be used for point-of-care (POC) settings or resource-limited situations, and potentially for the diagnosis and prevention of infectious diseases.

Machine learning, a branch of artificial intelligence, is increasingly used in health research, including nursing and maternal outcomes research. Machine learning algorithms are complex and involve statistics and terminology that are not common in health research. The purpose of this methods paper is to describe three machine learning algorithms in detail and provide an example of their use in maternal outcomes research. The three algorithms, classification and regression trees, least absolute shrinkage and selection operator, and random forest, may be used to understand risk groups, select variables for a model, and rank variables’ contribution to an outcome, respectively. While machine learning has plenty to contribute to health research, it also has some drawbacks, and these are discussed as well. In order to provide an example of the different algorithms’ function, they were used on a completed cross-sectional study examining the association of oxytocin total dose exposure with primary cesarean section. The results of the algorithms are compared to what was done or found using more traditional methods.

Efficient methods for solving economic load dispatch (ELD) problems have been provided to build effective multi-objective evolutionary algorithms (MOEAs). ELD is a dynamic bi-objective optimization problem that is strictly limited. The MOEA applications to solve the ELD problems have been published in various publications since the 1990s. This paper explores the state of the art of this direction-related research. It addresses subjects such as standard MOEAs, traditional ELD problems, dynamic ELD problems, wind power integration ELD problems, electric car integration ELD problems and micro-grid ELD problems. Furthermore, several potential directions are also provided for future study.

Heart disease has been one of the ruling causes for death for quite some time now. About 31% of all deaths every year in the world take place as a result of cardiovascular diseases [1]. A majority of the patients remain uninformed of their symptoms until quite late while others find it difficult to minimise the effects of risk factors that cause heart diseases. Machine Learning Algorithms have been quite efficacious in producing results with a high level of correctness thereby preventing the onset of heart diseases in many patients and reducing the impact in the ones that are already affected by such diseases. It has helped medical researchers and doctors all over the world in recognising patterns in the patients resulting in early detections of heart diseases.

Nowadays, ports are in need to maximize their incomes, and this based on the fierce competition. For this reason, all ports stakeholders should be involved to contribute in the design and the development of a policy of scheduling and priority.This project owned by the Vessel Call Service Planning Service in the port of Tanger Med as the "Tanger Med Port Authority", and it output was to report the summarized the work done and the methods behind it.The main goal is to develop a simulator model that includes all kind of operations and the operational process by choosing the appropriate KPIs that are fully reflecting the congestion transferred by port vesselsFirst, it aims to define the operating assumptions and the fundamental concepts on which our simulation model will be based and to present the data that were used for the implementation of the simulation as well as the origin of these data.Secondly, it aims to validate and calibrate the model by presenting some improvements that could be made to the simulator in order to make it more precise and more representative and to ensure automation of the processing of inputs and outputs. While towards the end we conclude with the presentation of congestion situations, the results obtained and their use in decision making.AIS data is another factor has been added to help in getting best results, this helped in vessels planification in/out predictive process while automating the use of our simulator with the AIS Data receipt from SatelliteThis part of project is in to give the smart aspect to our simulator results by using smart technology.

The wide-ranging features of a smartwatch have driven the rapid growth of the smartwatch market as they pique the users’ interests by offering interactive technology that simultaneously promotes fitness and tracks health. Nevertheless, the factors influencing smartwatch adoption among individuals are yet to be comprehended despite the ever-growing popularity of smartwatch usage. Hence, to understand the possible factors in detail, a research model is proposed to indicate the influential underlying factors relative to smartwatch adoption in the Malaysian populace. This study will examine the four proposed dimensions of perceived benefits, healthology, IT innovation, and smartwatch as luxury products. Online questionnaires will be used to collect the research data, while SPSS will be used to run both preliminary research and descriptive analyses, PLS-SEM will be used to further analyze the model.

Speech driven facial animation can be regarded as a speech-to-face translation. Speech driven facial motion synthesis involves Speech analysis and face modeling. This method makes use of still image of a person and speech signals to produce an animation of a talking character. Our method makes use of GAN classifier to obtain better lip synchronizing with audio. GAN methodology also helps to obtain realistic facial expressions thereby making a talking character more effective. Factors such as lip-syncing accuracy, sharpness, and ability to create high -quality faces and natural blinks are taken into consideration by this system. GANs are mainly used in case of image generation as adversarial loss generates sharper and more depictive images. Along with images, GANs can also handle videos easily.

Traffic boards and traffic signals are used to maintain proper traffic through busy roads. They help to recognize the rules to follow when driving the vehicle. These signs warn the distracted driver, and prevent his/her actions which could lead to an accident. We have proposed a system which can help recognize these boards and signals at real time thus avoiding major mishap. A real-time automatic sign detection and recognition can help the driver, significantly increasing his/her safety. Lately traffic sign recognition has got an immense interest lately by large scale companies such as Google, Apple and Volkswagen etc. which is driven by the market needs for intelligent applications such as autonomous driving, driver assistance systems (ADAS), mobile mapping, Mobil eye, Apple, etc. Hence, here, we have implemented to do the same with cost efficient manner using Raspberry Pi. The proposed system detects the traffic board or traffic signals, capture its image which through deep learning approach recognizes the same to give result on dashboard as well it gives the measures of distance from front obstacle which helps to implement brake system if obstacle is near. PiCam is used to capture images of traffic sings and is connected to RaspberryPi. Monitor is used to display required output, showing type of sign and distance of collision. This proposal will avoid large number of accidents occurring at bridges and work in progress area due to automated braking system and simultaneous reduce death ratio.

The influence of gamification on website features is very unclear in the case of e-banking. Therefore, this research aims to develop a theoretical framework that focuses on investigating the effect of gamification (as independent variable) on website features (as a dependent variable)that include ease-of-use, webpage characteristics, website information and website design in the context of e-banking in Washington DC, United states of America.

Flying insect detection, identification, and counting are the key components of agricultural pest management. Insect identification is also one of the most challenging tasks in agricultural image processing. With the aid of machine vision and machine learning, traditional (manual) identification and counting can be automated. To achieve this goal, a particular data acquisition device and an accurate insect recognition algorithm (model) is necessary. In this work, we propose a new embedded system-based insect trap with an OpenMV Cam H7 microcontroller board, which can be used anywhere in the field without any restrictions (AC power supply, WIFI coverage, human interaction, etc.). In addition, we also propose a deep learning-based insect-counting method where we offer solutions for problems such as the “lack of data” and “false insect detection”. By means of the proposed trap and insect-counting method, spraying (pest swarming) could then be accurately scheduled.

Paper-based electronics offer a simple and cost-effective means to fabricate flexible devices. Here, we report an efficient pen-on-paper approach to construct metasurfaces on paper with silver units. Further, paper-based metasurfaces are employed to shield the electromagnetic interference which create new opportunities in turning waste paper into a solution for eliminating electromagnetic pollution. Experimental measurements and simulations show that waste paper-based metasurface manufactured in this way exhibits remarkable electromagnetic shielding properties with small thickness (thickness reduced more than 90% compared with that of traditional shielding materials), which makes it an ideal candidate for specific frequency electromagnetic filters. In addition, it can be readily extended to other regions of the electromagnetic spectrum, widened the shielding band by simply scaling the silver units' sizes and utilizing appropriate three-dimensional structures. Having taken performance into consideration, production is also taken into account. Paper-based shields offer both economic and energy benefits when considered on electronic printing, in addition, environment friendly nature and pliability of paper as well as simple fabrication procedure make paper-based metasurfaces promising candidates for the future ‘green’ electronics.

IoT has turned into an amazing system of worldwide and worldwide changes, including numerous internet advisors, interchanges, and information trade. This paper presents state-of-the-art background, introduction, characteristics, challenges, threats, attacks, related work, and security architecture and research limitation of IoT technology. This paper discusses key security issues and attacks over different layers of IOT along with its existing prevention techniques. This paper deals with the security of services used in IoT. In detail, IoT devices are mentioned in this paper, which are the premise of IoT and their significance. In addition, IoT Security Architecture highlights some recent studies. This paper is far from comprehensive and mainly focuses on attacks and IoT devices prevention mechanism and covers related discussion and arguments.

Supply of electrical energy to people living in rural and urban is always an issue as there is always rise in demand and shortage in supply which is mostly due to extinction of widely used source i.e. coal and upgrading to smart home with maximum use of appliances to reduce human work but the fact remains constant that need of power to use this electronic product is always an issue specially to the rural citizens where a minimum requirement of power is also not fulfilled still to many of the places. Thus Smart Energy Management System is the technology and one of the best methods to use electrical energy efficiently and save the energy by means of different method using available and upcoming technology and makes it available and accessible to each and every person. The major contribution will be from the communication technologies specifically wireless technologies enabling for two-way communications and also from renewable energy that integrates solar energy and resources to smart home by utilizing energy in smart way and scheduling and arranging the power flow during peak and off-peak period. A holistic approach addressing the issues of energy supply, demand and pricing is addressed. This paper presents the deep understanding of each method with its implementation along with its result and success of the proposed method in managing the power and saving the electrical energy and how this method proposed will help in introducing and advancing the current system to manage energy with available technologies and keep upgrading in future and for which detailed study is done in this paper with overall conclusion of supporting the ideology and suggesting some effective ways to upgrade the ideology.

This paper investigates the use of Augmented Reality (AR) in pedestrian wayfinding in two aspects. First, an experiment was conducted to understand whether an AR-based mobile platform improves finding the direction of a query destination compared to a paper map. A total of 54 participants were enrolled to represent each group, in which the task was to show the direction of a query point-of-interest (POI). The experiments were carried out at the Beytepe Campus of Hacettepe University. The results suggest that AR-based platform significantly improves the task completion time compared to a paper map. Second, an online questionnaire was conducted to understand the preference of participants in terms of visualising the distances of POIs on an AR-based platform. Four different methods were utilised which vary the colour and size of a POI depending on its distance to the user. The results suggest that the majority of the participants preferred visualising POIs with the same colour but with different sizes depending on their distance to the user. This finding adds further support to the default visualisation adopted in Mapbox, the technology that was used to develop the AR-based platform.

Paper is a multi-component material based on plant fibers, technologically joined together into a sheet. Studying paper tasks are assigned to specialists in the forensic-technical examination of documents, to chemists and materials scientists. Examination of paper can be a sub-task to address specific questions set to other types of expertise. Meanwhile, there is not enough attention to this problem in the specialized literature. There are some publications in various compilations or small sections in works devoted to documents’ materials study. Some of the works that reveal the features of the analysis of the materials science characteristics of paper have been written by the paper industry’s technologists and are far from forensic examinations’ specifics and methodological foundations.The article’s main objective is to demonstrate the need for new scientific studies and methodological developments in the forensic-technical examination of documents. The article describes the range of tasks solved by this type of examination, identifies the main opportunities for paper studies.

This paper presents the design, fabrication, and characterization results of a paper-based, low-cost, easy-to-use, comfortable and wearable tactile sensor array for human health monitoring applications. Paper substrate and spray-deposited metallic electrodes and traces are employed to achieve a low fabrication cost. Capacitive sensing scheme employing a deformable triangular PDMS sensing membrane is chosen due to its high sensitivity and zero DC power dissipation. Trade-offs among different sensor array designs are investigated to achieve an optimal design, which consists of a $1\times 5$ sensor array occupying an area of 10 mm $\times10$ mm. Each sensor in the array achieves a nominal capacitance value and sensitivity of approximately 1 pF and 30 fF/mmHg, respectively. Fabricated sensor array can be comfortably attached to an individual’s temporal region and ankle area to monitor real-time blood pressure (BP) pulse waveform with high fidelity, from which heart rate and heart rate variability information can be accurately obtained. In addition, the prototype sensor array demonstrates its capability of detecting atrial fibrillation (AFib) from BP pulse waveform measured from an AFib patient. [2020-0179]

Heavy metal pollution has shown great threat to the environment and public health worldwide. Current methods for the detection of heavy metals require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Various microfluidic paper-based analytical devices have been developed recently as simple, cheap and disposable alternatives to conventional ones for on-site detection of heavy metals. In this review, we first summarize current development of paper-based analytical devices and discuss the selection of paper substrates, methods of device fabrication, and relevant theories in these devices. We then compare and categorize recent reports on detection of heavy metals using paper-based microfluidic devices on the basis of various detection mechanisms, such as colorimetric, fluorescent, and electrochemical methods. To finalize, the future development and trend in this field are discussed.

Nowadays, recommender systems have become one of the main tools and methods for users to search for their interested papers from massive candidates. Considering the above drawbacks, in this paper, we propose a link prediction approach that combines time, keywords and authors information for constructing a new relation graph. Finally, a case study is employed to explain our approach step by step and demonstrate the feasibility of our proposal.

The study is done at a paper company in west java by doing evaluation of waste paper supplier of raw materials with the aim of gaining evaluation criteria supplier and ranking supplier. The process of making evaluation criteria supplier is done by using the method hierarchy (AHP) analytical process and ranking with the approach of the supplier technique for order preference by similarity to (TOPSIS) solution of a problem. according data processing by using both the main criterion used this method produced 6, the quality criteria, delivery, the price of, resources, service, and company management and putting quality criteria as the criteria with the weighting for 30,7 % of as much as. While the supplier of ranking. the best supplier PT. CMN and PT. AMN supplier as the worst alternative supplier of 5. Made with a model evaluation criteria and ranking supplier is expected to supplier evaluation process useful for other types of businesses the same paper companies.

The main objective of this project was to assess an inkless method to collect reference (exemplar) fingerprints as a low-cost, portable, and hygienic technique; for temporary storage and as an alternative to the conventional black ink method. The tested inkless approach requires alcohol-based hand sanitizer gel as the medium and thermal paper as the substrate. The final quality and clarity of fingerprints were examined and compared between the two methods, especially on the basis of medium/substrate and biological sex effects. Two different evaluation systems of visual quality (clarity) were conducted to provide more reliable results: a quality score scheme (QS) and metrics from the FBI's Universal Latent Workstation (ULW). Fingerprints were obtained from 20 individuals (11 males and 9 females) between the ages of 20 and 40; a total of 240 impressions were evaluated. The results provide evidence that the inkless method produces identifiable fingerprints of equivalent quality to the standard ink method, although significantly better for males. The potential of the proposed technique as an alternative to the conventional ink method is proven and corroborated by the two independent systems of visual quality assessments.

In this work, we provided a novel strategy of antibody-free biomarker analysis by in-situ synthesized molecularly imprinted polymers (MIPs) on movable valve microfluidic paper-based electrochemical device (Bio-MIP-ePADs) for clinical detection of biomarkers. The newly movable valves on the device enable continuous and convenient delivery of fluid, which guarantee the performance for fabricating MIPs structure during long time electropolymerization. Moreover, this strategy can directly detect antigens by taking advantage of molecular imprinting on paper-based device, which greatly decreases the cost during clinical testing, reduces the tedious washing procedure and does not need to consider the preservation of the antibody in enzyme linked immunosorbent assay (ELISA). This feature makes the chip suitable for the on-site family treatment or commercial products. To further validate the applicability of this proposed method for clinical diagnostic testing, carcinoembryonic antigen (CEA) was applied as prototyping model target for the clinical analysis. The proposed Bio-MIP-ePADs were cheap, easy to prepare, disposable and provided reliable analysis by comparing with ELISA. We hope the application of this technology will open up a new avenue to the point-of-care testing (POCT).

We present a QR code paper microfluidic colorimetric assay that can exploit the hardware and software on mobile devices, and circumvent sample preparation by directly targeting volatile biomarkers. Our platform is a printable microarray of well-defined reaction regions, which outputs an instant diagnosis by directing the user to a URL containing their test result, while simultaneously storing epidemiological data for remote access and bioinformatics. To assist in the rapid identification of Escherichia coli in bloodstream infections, we employed an existing colorimetric reagent (p-dimethylaminocinnamaldehyde) and adapted its use to detect volatile indole, a biomarker produced by E. coli. Our assay was able to quantitatively detect indole in the headspace of E. coli culture after 12 h of growth (27.0 ± 3.1 ppm), assisting in species-level identification hours earlier than existing methods. Results were confirmed with headspace solid-phase microextraction (HS-SPME) two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-ToFMS), which estimated indole concentration in E. coli culture to average 32.3 ± 5.2 ppm after 12 h of growth. This QR paper microfluidic platform represents a novel development in both telemedicine and diagnostics using volatile biomarkers. We envision that our QR code platform can be extended to other colorimetric assays for real-time diagnostics in low-resource environments.

A paper-based colorimeter for absorbance and concentration measurement of the food colouring dye is proposed. The paper-based colorimeter system consists of a white LED as light source, paper-based cuvette holder, and smartphone light sensor. The paper-based colorimeter with smartphone light sensor is low-cost, mobile and real-time for the detection of colouring dye concentration. The detection response of the paper-based colorimeter system was found to be linear with the colouring dye concentration in the range from 0 to 0.025 g/mL with a correlation coefficient (R2) 0.89±0.04. The experimental results show that this paper-based colorimeter system is highly sensitive and have a potential application, from student labs to small industries.

IMPACT: My work evaluates the impact of electronic data capture/eSource on several aspects of clinical trial efficiency and scale, aiming to demonstrate how eSource can be used to improve the way we run clinical trials. OBJECTIVES/GOALS: Using eSource may increase the efficiency of data collection in clinical trials. However, adoption of eSource has been slow. We reviewed over 100 large multinational clinical trials to analyze how eSource use correlated with trial size, sponsor collaborations, time to complete, and time to publication. METHODS/STUDY POPULATION: We searched ClinicalTrials.gov for completed, interventional, Stage II-IV clinical trials with posted results and an uploaded study protocol document. This produced 3,962 trials. We identified all studies with over 1,200 participants and sites in multiple countries (or at least 100 sites in one country). After eliminating ten studies with duplicate protocols, we had a database of 123 trials. From the ClinicalTrials.gov listing, the study protocol, and any published papers, we determined the start, end, and publication dates, data collection protocol, sponsors and collaborators, and any reasons given for delays for each trial. We performed statistical tests comparing trial delay, participant and country count, and collaboration status (yes or no) between the two groups (eSource users and non-eSource users). RESULTS/ANTICIPATED RESULTS: Of our 123 trials, 60 (48.7%) used eSource, 48 (39.1%) used paper source documentation, and 15 (12.2%) used some combination. We found no statistically significant difference between eSource and non-eSource trials in terms of trial delay (p=0.43), time to publish (p=0.33), collaboration status (p=0.54), number of participants (p=0.36), or number of countries (p=0.12). However, our analysis was limited by what data was publically available. To investigate the effects of eSource on site efficiency, data accuracy, and data security, which are three major factors behind the FDA’s 2013 eSource recommendation, we would need access to proprietary information from trial sponsors. DISCUSSION/SIGNIFICANCE OF FINDINGS: The use of eSource in large multinational clinical trials is not correlated with a change in time to completion or publication nor a higher number of participants or countries. We aim to acquire proprietary data to further analyze the impacts of eSource on trial efficiency, data accuracy, and data security.

The traditional Chinese folk paper-cutting art has a long history. It is a traditional folk art form created by working people to satisfy their spiritual and material pursuits. It originates from life and returns to life. With the pace of the times, folk paper-cutting has undergone an innovative transformation and development through the interweaving, penetration and integration of contemporary design concepts. Through the combination of network big data, it provides a large number of references for modern graphic design decoration and function combination, graphic context inheritance, color language, modeling language, etc.

Most recognition is based on identifying features, but specialization for face recognition in primates relies on a different mechanism, termed ‘holistic processing’ where facial features are bound together into a gestalt which is more than the sum of its parts. Here, we test whether individual face recognition in paper wasps also involved holistic processing using a modification of the classic part-whole test in two related paper wasp species: Polistes fuscatus , which use facial patterns to individually identify conspecifics, and Polistes dominula , which lacks individual recognition. We show that P. fuscatus use holistic processing to discriminate between P. fuscatus face images but not P. dominula face images. By contrast, P. dominula do not rely on holistic processing to discriminate between conspecific or heterospecific face images. Therefore, P. fuscatus wasps have evolved holistic face processing, but this ability is highly specific and shaped by species-specific and stimulus-specific selective pressures. Convergence towards holistic face processing in distant taxa (primates, wasps) as well as divergence among closely related taxa with different recognition behaviour ( P. dominula , P. fuscatus ) suggests that holistic processing may be a universal adaptive strategy to facilitate expertise in face recognition.

We believe the switch to a digital pathology (DP) workflow is imminent and it is essential to understand the economic implications of conversion. Many aspects of the adoption of DP will be disruptive and have a direct financial impact, both in short term costs, such as investment in equipment and personnel, and long term revenue potential, such as improved productivity and novel tests. The focus of this whitepaper is to educate pathologists, laboratorians and other stakeholders about the business and monetary considerations of converting to a digital pathology workflow. The components of a DP business plan will be thoroughly summarized, and guidance will be provided on how to build a case for adoption and implementation as well as a roadmap for transitioning from an analog to a digital pathology workflow in various laboratory settings. It is important to clarify that this publication is not intended to list prices although some financials will be mentioned as examples. The authors encourage readers who are evaluating conversion to a DP workflow to use this paper as a foundational guide for conducting a thorough and complete assessment while incorporating in current market pricing. Contributors to this paper analyzed peer-reviewed literature and data collected from various institutions, some of which are mentioned. Digital pathology will change the way we practice through facilitating patient access to expert pathology services and enabling image analysis tools and assays to aid in diagnosis, prognosis, risk stratification and therapeutic selection. Together, they will result in the delivery of valuable information from which to make better decisions and improve the health of patients.

Generating question papers is a tedious and time-consuming operation. This study uses Python to construct a fuzzy logic-based model for autonomous paper creation. With the aid of a huge number of questions saved in the database, college officials may create a fully personalised question paper. The programme may be used to produce question papers based on the examination level, which may include unit tests. It enables the authorities to pick and choose from the syllabus's chapters. The programme makes use of a database to use the question paper, which might include hundreds of questions. The programme generates a collection of random questions on which the question does not appear. The programme is a great tool for quickly generating question papers and so saving time and effort.