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Contributions are invited to a new journal special collection on the use of new machine learning methodologies and applications of machine learning to Earth system modeling.

In order to automate the task of correcting handwritten subjective answers, we envision a system that reads such answers and grades them. In this project, we have created a mobile application to achieve this task. We have used the RAKE algorithm to extract key-phrases, which are then embedded using Word2vec model and compared using Word Mover's Distance. Our created model achieved almost human like evaluation accuracy. We have also provided accessibility features to the users with the aim of making this application a one-stop solution to automatic evaluation of handwritten subjective answers.

Wireless communications via reconfigurable intelligent surfaces (RIS) are envisioned to offer unprecedented spectral efficiency gains by smartly inducing phase shifts on the impinging electromagnetic waves at the RIS to reconfigure the underlying propagation environment. This work investigates a multi-user downlink communication system in which the access point, equipped with multiple antennas, serves its associated single-antenna users equipments (UE) with the help of RIS. The proposal is a leakage-based design in which the transmit precoding, the power allocation, and the phase shifts of the RIS, are designed to maximize the minimum signal-to-Ieakage-plus-noise power ratio (SLNR) of the UEs subject to the constraint on the power budget of the access point. The merits of the SLNR-based approach are highlighted, e.g., reduced complexity, and simulation results show that the RIS-aided design can achieve massive MIMO gains with much fewer number of active antennas in the access point as compared to conventional relaying.

Sentiment analysis and opinion mining have developed significantly throughout the last decades. This study aims to assess, amongst many other aspects, people's feelings, opinions, and emotions of someone or something. This review's principal objective is to automatically assess the direction of the review and contrast this with the evaluation made by the reviewers. This will allow scientists to categorize and evaluate reviews cross-sectionally and encourage a scientific article's overall evaluation more critically. An EM-VC ensemble approach has been proposed for analyzing the reviews. This approach uses POS to achieve a syntactic sentence structure. With dictionaries, this syntactic structure enables the semantic orientation of the analysis via the scoring algorithm to be determined. To test the proposed approach's efficiency and performance about the baseline method, some tests have been performed using typical performance metrics like precision, accuracy, F1-score, and recall. The findings reveal that improvements are achieved in binary classification, ternary classification, & five-point classification compared to the existing HS-SVM method. Still, it provides a slight improvement in accuracy in the context of multiclass classification compared to others.

Nitrite is one of the most common carcinogens in daily food. Its simple, rapid, inexpensive, and in-field measurement is important for food safety, based on the requirements of the standard from Codex Alimentarius Commission and China. Using polyacrylonitrile (PAN) and thin layer silica gel (SG), p-aminophenylcyclic acid (SA) and naphthalene ethylenediamine hydrochloride (NEH), as carriers and chromogenic agents, respectively, PAN-NSS as nitrite color sensor is proposed. After fixing and protecting of SA and NEH with layer-upon-layer PAN, the validity period of the test paper can be prolonged from 7 days to more than 30 days. The reproducibility of PAN-NSS preparation is ensured by electrospinning. Combined with PAN-NSS, deep convolutional neural network (DCNN) and APP as a visual monitoring platform, which has the functions of rapid sampling, data processing and transmission, intuitive feedback, etc., and provides a fully integrated detection system for field detection.

Electrochemical paper-based analytical devices (ePADs) are useful analytical devices that serve as point-of-care testing (POCT) devices for various clinical biomarkers in view of their simplicity, portability, and low-cost format. However, multistep reagent manipulation usually restricts the performance of the device for end users. Herein, we developed a sequential ePAD for sequential immunosensing fluid delivery by integrating dual flow behaviors (fast-flow/delayed) within a single paper platform for the simultaneous detection of hepatitis B surface antigen (HBsAg) and hepatitis C core antigen (HCVcAg). In the present work, a fast-flow channel was used for the automated washing of unbound antigens, while a delayed channel was created to store a redox reagent for further electrochemical analysis with a single buffer loading (the analysis time can be completed within 500 s). Hence, the undesirable complex procedure of multi-step reagent manipulation is scarcely needed by the user. The detection limit of the proposed ePAD was as low as 18.2 pg mL−1 for HBsAg and 1.19 pg mL−1 for HCVcAg. In addition, this proposed ePAD was also proven to be effective in real clinical sera from patients to verify its biological applicability. The ePAD sensor shows high promise as an easy-to-use, portable, and extendable sensor for other multiplex biological assays.

In my talk I will discuss the AI and brain-computer interface (BCI) technologies overview in the context of integration with robotic and biological systems starting from classical Rosenblatt perceptron till current breaking through technologies of BCI that could change the scientific outlook of the field. This is what we currently broadly call now AI and neurotechnology. Two bright examples are ResNet inspired by the projections of a mammalian cortical column and U-Net with close to ResNet ideas and topology. The other interesting cortical column inspired NN architecture is hierarchical temporal memory introduced by the Numenta company. These brain or neuro inspired approaches are widely used in machine learning, computer vision, natural language processing, path planning and broader in robotics.In the neurotechnology field I want to reference a lot of interesting and projects dedicated to BCI. Starting from works of Miguel Nicolelis where researchers connected the robotic hand via a computer system with a motor cortex of a monkey and later Lebedev group demonstrated the adaptation of a mammalian brain to create the representation of robotic limb extending biological limbs. I want to pay the special attention to works of Kevin Warwick that implemented invasive nervous system to nervous system interface and the robot managed by neurons of a rat brain developed and trained during the experiment.The commercial company Neuralink recently demonstrated the most advanced 1536-channel BCI exploiting wireless Blue-tooth interface to record and process a brain activity. Elon Musk in his Neuralink presentation last year demanded that one of the nearest goals of the company is spinal cord injury and the recovery of the lost motor control of limbs. Several projects in neurorehabilitation targeted to the motor control demonstrated recently important success using medical programmed neurostimulators.The perspective but currently in early state of the development is the direction of neurosimulation based models that could be used for the robotic system control (exoskeleton) or as neuroprosthesis as the part of closed loop system for example projects simulating the spinal cord, where I can see interesting future opportunities both in medicine and robotics.

The aim of this work is to classify the dementia stage using microstructural white matter (WM) diffusion kurtosis indices. We develop various class imbalance machine learning methods in classifying the cognitive normals (CN), Alzheimer's disease (AD) and mild cognitive impairment (MCI) individuals. Diffusion-weighted images of 155 subjects were collected with 44 CN, 88 MCI and 23 AD individuals aged between 60 to 96 years. We first perform skull striping using FSL tool along with head motion and artifact correction. We calculate the mean diffusivity, fractional anisotropy from various brain regions of WM indices from diffusion kurtosis imaging (DKI) using tract based spatial statistics. Then we estimate the kurtosis fractional anisotropy of various WM regions. After estimation of all the regional KFA indices, we trained these indices using various class imbalance machine learning classification algorithms, as the sample size is different in all the three groups. We found that balanced random forest classifier was the best classifier with an accuracy of 74% when compared to other methods for 5-fold cross-validation. We conclude that class imbalance machine learning methods are potential in classifying cognitive normals, AD and cognitive impairment individuals.

Agile methodology has been a trending topic over the past two decades. Organizations are establishing agile transformation programs to reap its benefits, and cope with the everchanging business and technology landscape. Yet, making sense of the manifold domains contributing to the success of an agile transformation, and orchestrating them with a great synergy is not a simple task. To navigate in this complexity and establish roadmaps, organizations primarily need to understand where they stand. There are a multitude of Agile Assessment Models (AAM) that are designed with the intent of identifying the state of an agile transformation in an organization. Designing an AAM is a valuable step towards this need, however, such models tend to lack vital aspects. Although “What” is needed seems straightforward, in our research, we are trying to focus on “Why” lacking aspects are vital, and “How” to enable effective and efficient value creation through Agility.

The QNX operating system has emerged as a promising candidate as a base operating system for upcoming domain or vehicle integration computers in centralized automotive E/E. In this work, we look deeper in the Adaptive Partitioning Scheduler offered by QNX with the aim of assessing its suitability in providing temporal isolation and guaranteed execution behavior to different applications. With APS, QNX has introduced budget-based scheduling into a mainstream commercial OS and hence deserves merit. However we also found certain drawbacks in the APS scheduler and in order to mitigate the problems caused by them, we propose some guidelines for system designers to configure their systems efficiently.

Improper Input Validation (IIV) is a dangerous software vulnerability that occurs when a system does not safely handle input data. Although IIV is easy to detect and fix, it still commonly happens in practice; so, why do developers not recognize IIV? Answering this question is key to understand how to support developers in creating secure software systems. In our work, we studied to what extent developers can detect IIV and investigate underlying reasons. To do so, we conducted an online experiment with 146 software developers. In this document, we explain how to obtain the artifact package of our study, the artifact material, and how to use the artifacts.

The CAN (Controller Area Network) signals transmitted in vehicles have great analytical value with the quick development of complex automotive software. The boom in big data creates an opportunity to transmit CAN signals from the in-vehicle network to the big data cloud platform, through which the signal analysis can be conducted. The signals are transmitted from the in-vehicle network to TelematicsBOX via CAN bus and then sent to the big data cloud platform. When using the CAN bus for signal transmission of the in-vehicle network, signals larger than 1 byte need to be unpacked into several 1-byte signals. The general solution of automotive software manufacturers usually uses the model-based development method to unpack the CAN signals, but such method is inefficient. To solve this problem, we develop a CAN signal unpacking tool called AutoToolCSU, which is based on a configured template through a GUI (Graphical User Interface). Compared to the model-based development method, AutoToolCSU not only greatly improves the development efficiency of CAN signal unpacking but also interfaces with the standard development processes of automotive software manufacturers.

Intermittent systems enable continuous and accumulative process execution under constraint or unstable power supply. To enable intermittent computing, process status and data are typically checkpointed from volatile memory (VM) to nonvolatile memory (NVM) before running out of power. After power resumes, these logged data can be loaded back from NVM to VM for continuous execution. Nevertheless, existing approaches rarely considered the energy consumed during moving data and may waste precious power resource over data movement, instead of computation. Such observation motivates us to propose an energy-reduction on-chip memory management (ERCM2) scheme to utilize the high cell density and non-volatility of SpinTransfer Torque RAM (STT-RAM) for enabling a hybrid on chip memory architecture. The experimental results show that the proposed scheme can achieve the access performance close to conventional SRAM-based on-chip memory architecture with lower energy consumption.

Facing the difficulty and inefficiency of creating and maintaining High-Definition (HD) maps in our commercial deployments, we have developed an edge-based crowdsourcing task distribution framework for HD Map in autonomous driving. Our key observation is that: HD map data crowdsourcing exhibits the diminishing marginal utility thus there exists an inflection point for maximum utility, meanwhile its premature convergence of utility will leave some map updates not notified in time. Based on this observation, we develop a periodic crowdsourcing task distribution framework. It discretizes the demands for collecting source data into different periods and uses an optimal stopping rule to terminate the data collection for the maximum crowdsourcing utility. The experimental results verify that our crowdsourcing framework can achieve high time coverage and high efficiency with lower cost.

In autonomous driving, 3D object detection is es-sential as it provides basic knowledge about the environment. However, as deep learning based 3D detection methods are usually computation intensive, it is challenging to support realtime 3D object detection on edge-computing devices in selfdriving cars with limited computation and memory resources. To facilitate this, we propose a compiler-aware pruning search framework, to achieve real-time inference of 3D object detection on the resource-limited mobile devices. Specifically, a generator is applied to sample better pruning proposals in the search space based on current proposals with their performance, and an evaluator is adopted to evaluate the sampled pruning proposal performance. To accelerate the search, the evaluator employs Bayesian optimization with an ensemble of neural predictors. We demonstrate in experiments that for the first time, the pruning search framework can achieve real-time 3D object detection on mobile (Samsung Galaxy S20 phone) with state-of-the-art detection performance.

Graph neural networks (GNN) have achieved state-of-the-art performance on various industrial tasks. However, the poor efficiency of GNN inference and frequent Out-of-Memory (OOM) problem limit the successful application of GNN on edge computing platforms. To tackle these problems, a feature decomposition approach is proposed for memory efficiency optimization of GNN inference. The proposed approach could achieve outstanding optimization on various GNN models, covering a wide range of datasets, which speeds up the inference by up to 3×. Furthermore, the proposed feature decomposition could significantly reduce the peak memory usage (up to 5× in memory efficiency improvement) and mitigate OOM problems during GNN inference.

Sorting of products is a very difficult industrial process. Continuous manual sorting creates consistency issues. This paper describes a working prototype designed for automatic sorting of objects based on the metal detector KY-036 sensor was used to detect the colour of the product and the PIC16F628A microcontroller was used to control the overall process. The identification of the colour is based on the frequency analysis of the output of TCS230 sensor. One conveyor belts were used, it controlled by separate DC motors. The belt is for placing the product to be analysed by the colour sensor, having separated compartments, in order to separate the products. The experimental results promise that the prototype will fulfil the needs for higher production and precise quality in the field of automation.

Human muscles can sense external stimuli and generate forces as well. To emulate these capabilities, we design a paper-based transducer capable of both sensing and actuation. Utilizing the origami technique, we develop a soft transducer with attributes of simple structure, easy fabrication and low cost. The origami transducer can function as a deformable capacitive sensor to measure contract forces/pressures. It can achieve a sensitivity up to 0.051 kPa −1, comparable to soft capacitive sensors in the literature. During cyclic tests up to 1000 cycles, this soft sensor exhibits excellent repeatability and negligible hysteresis, thus enabling a high accuracy. On the other hand, this origami transducer can act as a soft actuator to generate haptic feedback. The voltage-induced output force can be 0.4 N, comparable to haptic devices based on soft actuators in the literature. This origami transducer is finally demonstrated for application to breath monitoring of a subject, functioning as both a wearable sensor and actuator. It is believed that paper-based origami transducers can offer a unique option to soft robots and wearable devices, due to their simple design, low cost, and capability for simultaneous sensing and actuation.

Over the past few years, researchers have focused on stimulus-responsive soft materials and their applications in the design of soft actuators. The key factor of the soft actuators to achieve various applications is the programmable and controllable shape deformations. Here, a versatile and simple surface patterning method consisted of pencil drawing and pasting polymer films is proposed to design the soft actuators with programmable deformations. Due to the thermal expansion effect and the hygroexpansion effect, the graphite paper/polymer actuator performs a bending motion with a curvature of 1.4 cm−1 under light irradiation and 1.2 cm−1 under high humidity. Owing to the convenience of the patterning method, different patterns on both two surfaces of the paper substrate are designed without effort. Thus, through tuning the grayscale of the graphite on one surface of the paper, three types of T-shaped actuators can be obtained with different deformations under light irradiation. In addition, by pencil drawing or hydrophobically modifying specific patterns on the two surfaces of the paper, three types of strip-shaped actuators are also proposed to demonstrate that different 3D shape deformations can be obtained under different stimuli. Finally, a helix-shaped actuator inspired by the natural plant tendrils is fabricated by the thermal-induced shaping method. The helix-shaped actuator performs twisting/untwisting motion under different stimuli and can be used as a grasping robot. These results demonstrate the diversified programmability of the graphite paper/polymer actuator. Hence, the simple and versatile programming methods of soft actuators have great potential to be used in the field of biomimetic applications, intelligent robotics, and lab-on-paper devices.

This paper analyses over 89,000 documents between scientific journals and international patents in order to identify main technologies for material pyrolysis (i.e. fluidized bed, hot balls, microwave, plasma, and laser), compare them in terms of technical performances and discover future trends. The predictive model for future trends is based on the evolutionary model of the TRIZ theory, with particular attention to the evolutionary law, “from macro to micro”, which explains how technical systems evolve towards increasingly smaller, controlled, and resource-efficient interactions. In our case, we applied the focus to the interface between the heat source and the pyrolyzed raw material. The proposed evolutionary model showed a substantial alignment with chronological trends, and the model was consistent with both patent trends and those of the scientific literature. To make the analysis quantitatively more robust, a comparison of the different technologies has also been introduced in terms of percentage distribution and the number of patents/papers referring to the different classes of heating rates and reaction temperatures and types of flash/fast/intermediate/slow reaction. Finally, a quantitative metric based on the innovation index has been adopted, to take into account the number of citations normalized on the years of publication. The main outputs of this study identified that radiations-based pyrolysis, involving microscopic interaction, seem more interesting in term of technical performances (i.e. heating rate and reaction temperature), although their technological growth has yet to occur, unlike fluidized bed and hot balls, which typically work at a macroscopic level and seem to have already reached maturity. According to a bibliometric index, laser corpus resulted three time more innovative then fluidized bed reactors papers, especially for heating rates and reactions temperature.

Paper artifacts are contaminated by external factors in the process of preservation such as foxing. For the problem of backward technology of rapid detection of foxing on paper artifacts, a method based on hyperspectral imaging technology is proposed to detect foxing spots on paper artifacts. After selecting the region of interest and obtaining the corresponding average reflectance, the difference in the average reflectance is found after comparing the healthy regions with the diseased regions. Using band operation and minimum noise fraction to observe the characteristics of foxing image, although there is overlap in different parts, the distribution distinction between moldy and healthy regions is obvious; K-nearest neighbor method and BP neural network are applied to establish the spectral discrimination model of paper artifacts with foxing spots, and the overall discrimination rate of the two methods is 73.3% and 85%, respectively. The results show that hyperspectral imaging can be used for the identification of foxing spots, but the distinction between different parts is not good, and the discrimination effect still needs to be improved.

It is generally accepted that the latest research findings are published as research papers in journals. Social network analysis (SNA) can offer a perspective from which to analyze technological developments. This work analyzes the development of lithium-ion batteries (LIBs) and electrolytes by SNA based on papers from 2011 to 2015. Three types of social networks, country-, institution-, and research paper-based networks were used. Country-based network analysis shows that major ten countries have a close relationship with respect to technology development. Institution-based network analysis revealed that 48 top institutions publish the most prolifically and that a “small-world” effect exists within the network, indicating excellent knowledge transfer among institutions through citations. Several institutions occupy the center position within the network and have a prominent influence in knowledge transfer as judged by centrality analysis. Research paper-based social networks, consisting of high-citation articles, are grouped into six technology clusters, which exhibit a broad range of knowledge transfer processes regardless of the battery and electrolyte types, indicating underlying closely interwoven relationships. The knowledge transfer path can describe the technology evolution in detail. An overview of technological development status can be thus obtained by this proposed three-level analysis method.

The optical model for reflectance lightness of stereo paper product surface is proposed, which could promote color reproduction study of paper model products and improving color reproduction quality. The reflectance lightness was measured using non-contact measurement method with spectroradiometer, CS2000A, that can measure stereo paper product surface lightness and tristimulus. Once inputting the paper product parameters of surface angle and tone, the model will predict the reflectance lightness for stereo paper product surface. After analyzing statistical information of light transmission, paper product surface reflectance lightness can be obtained. The results showed that prediction model is versatile and easy to use, besides the model quite approached to realistic paper product surface. The optical model simulation system could sufficiently accomplish reflectance lightness, which provides a novel way to predict and reproduce printing quality.

Scientific output, as measured in research published annually, has seen a consistent growth for decades now. As more manuscripts are submitted for publication each year, new publishing venues appear – often as increasingly specialised offshoots of existing journals and conferences. This situation presents scholars with a wealth of publishing venues to consider and choose from for their manuscripts. Surprisingly, we find that the most cited papers are not necessarily found in the highest-ranked journals, while the best conferences dominate in this regard. We find it intriguing that popular Computer Science conferences act like a vacuum of attention, centralising all good publications, while journals are carried less by their renown and thus can attract strong manuscripts even at a low rank. But to what extent does a venue imply a paper’s recognition and popularity? We propose a new approach and processing pipeline, in which we project a heterogeneous publication network, learn representations for papers and classify said papers according to their 2-year citation success. This framework provides a groundwork for a venue recommendation system, a tool for improving paper’s scientific recognition through a better choice of a publishing venue.

Creatinine is a clinically significant analyte used to diagnose kidney condition. However, the literature still lacks in creatinine sensors fulfilling point-of-care testing requirements. In this paper, we have developed colorimetric paper-based creatinine sensors adhering to point-of-care testing principles. The signal readout is accomplished with a smartphone modified with 3D-printed elements and processed with a self-written application compromising computer vision algorithm for automatic detection of the colored zone. Two colorimetric methods – routinely used Jaffe method and an alternative one with 3,5-dinitrobenzoic acid were both tested and compared. Hue channel intensity from HSV color space and green channel from RGB color space was used as the analytical signal in Jaffe and 3,5-dinitrobenzoate method, respectively. For both kinds of sensors the linear range of the response covered the range significant for urinary analysis, with precision, expressed as RSD, below 5%. Limit of quantification for Jaffe method was 1.05 mmol·L−1 whereas it was 0.82 mmol·L−1 for 3,5-dinitrobenzoate method. The utility of the developed sensors to selectively quantify creatinine in undiluted urine was proved using artificial urine samples and the obtained recoveries were in the range from 70 to 129 %.

Objective Providing instruction for assembly tasks is essential in modern manufacturing industry, as well as in households for customers that buy products to be assembled at home. Recent technological developments might be able to assist in completing an assembly task faster and more accurately. The aim of this study was to evaluate whether performance and usability differs when instructions for an assembly task are presented on digital glasses versus paper. Methods Participants (n = 63) completed one of three versions of an assembly task (between-subject-design) with LEGO® bricks: (1) with paper instruction (P), (2) with text instructions presented stepwise via digital glasses (GT), (3) with stepwise text and auditory instruction (in parallel) on digital glasses (GA). Outcome measures on performance were completion time and errors. Furthermore, usability was measured by the User Experience Questionnaire, the Standardized Usability Questionnaire, the Post-Study Usability Questionnaire, and cognitive processing skills were assessed by the Trail Making Test and different versions of the Eriksen Flanker Task. Analyses were adjusted for the confounding factors age, gender, experience with glasses and LEGO, and problems with instruction. Results Findings indicate that task completion was faster with the paper instructions compared to both versions of instruction via digital glasses (GT, GA). We observed no difference in accuracy and usability between the instructions. “Novelty” was rated higher for instructions for both GT and GA, compared to P. Discussion Results show that instructions on digital glasses may not always be more effective for assembly than the traditional paper-based instructions. Further studies are necessary to investigate whether effectiveness may depend on task complexity, target group, experience of the user with task and device, and how the information is presented.

Our community publishes peer-reviewed journal, magazine, and conference papers and articles sharing a commitment to originality and to quality content and writing. These papers vary in their characteristics and style, depending on their objectives and their targeted readership. The IEEE Publication Services and Products Board (PSPB) Operations Manual (OM) also provides guidelines differentiating these paper types. There is confusion sometimes, however, concerning the features of magazine papers in particular. Some authors, especially early-career authors, do not fully appreciate certain differences between magazine papers and their journal, transaction, and letter counterparts. This can create a challenge for magazine editors and may result in delay, or rejection, of papers that could have been accepted if written with a better understanding of what magazines are about. We focus our attention here on this issue as it applies to IEEE Communications Magazine (ComMag) in particular. Our goal is to help our new and/or young authors who want to publish in ComMag to customize their writing to the nature of this magazine and enable them to author papers with higher chances of acceptance.

A single-sheet 3-dimensional paper-based microfluidic analytical device (3D-μPAD) has a user-friendly compact format that eliminates any potential for user alignment error compared to the stacking and folding format. However, achieving sophisticated analysis is still a challenge because forming a complex 3D microfluidic network sufficient for performing analysis in a single sheet of paper is difficult. Here, we present the first report of automatic multistep digital analysis in a single-sheet 3D-μPAD created by controlling the penetration of different wax inks into paper. Simple printing of different wax inks with different spreading properties produces different dimension microchannels in paper. This controllable change in the dimensions of the microchannels results in different flow rates of fluid in each microchannel. Based on the spatial resolution of the microchannels, our strategy enables programming of microfluidic flow through manipulation of the fluidic time delay. This approach creates 3D-μPADs capable of sequential fluid delivery and multistep biochemical reactions with single loading of a sample solution. The methodology can be further expanded to combination with digital assays to measure the concentration of a target analyte by simply counting the number of colored bars at a fixed time. It does not require any external instruments to analyze the measurement of the target analyte concentration. The significance of this work lies in the promising potential for automatic multistep digital assays in a low-cost and easy-to-use paper-based format that can be integrated with a roll-to-roll process for commercial-scale manufacturing.

In Today’s world technologies such as Internet of Things, Cloud Computing as well as Fog Computing are growing at an exponential rate which depend upon each other directly or indirectly. The Internet of Things can be described as a network of substantial matter such as cars, washing machines, refrigerator which can interact with each other through internet. Billions of devices will be IoT enabled in near future and generate enormous amount of data but IoT devices has some limitations like storage capabilities, processing capabilities and utilization of resources which can only be handled by integrating it with cloud technology. Cloud model provide environment in which software, Infrastructure, sharable pool of configurable resources, virtual environment, sensors, hardware and database is provided as a utility for IoT devices and users. In cloud computing paradigm some limitations exist for example distance of the data source from multi-hop, geological unified structure, latency, heterogeneity and many more. To address such limitations, Fog computing approach can be used to bring computing assets nearer to IoT devices. Fog computing is an enhancement of the cloud-based Network and computing services. It provides computational and storage services of cloud proximate to IoT devices. This paper provides an overview regarding the cloud computing uses in IoT devices and issues or problems that occur during integration. Handling of problems that occurs during integration of cloud with IoT can be done through fog computing. The purpose of this survey is to understand the concept of fog computing to improve the existing system of Integration of Cloud with IoT.

Wireless technology these days is very quickly becoming crescent. A network that was recently wired to get online was required. Just wired phones have been a thing of the past. In the past four decades, mobile networks have thrived immensely. The starting point was the 1G cellular concept where ‘G’ stances for generation linkages. This had fully developed very rapidly, generating 1G, 2G, 3G and gradually transferring into 4G from generation to generation. And now people are utilizing the 4G networks. 5G network will nearly stretch its wings to conquer this complex world of cell technology. Integrated 5G work is continuing, with complete service planned in 2020. The development of 5G technology is the perfect solution for the many problems facing us today with today’s innovations. 5G will become an intelligent technology that will limit to a single global uniform body the number of different innovations. This paper is mostly about the evolution of mobile wireless networks like 1G and 5G as well as how they vary and their benefits and drawbacks.

Background: The performance outcome model in qualitative technique analysis can determine the mechanical interactions between a performance outcome and the factors that yield such results in sports techniques. Very little attention has been received for badminton forehand shots for such model work, considering the significance of this technical skill as fundamental to play badminton and as important offensive shots. Objective: This study proposes a performance outcome model that associates performance criteria and relevant mechanical variables in the badminton forehand shot technique. Methods: Literature review provided the basis of model development. The Literature research in this paper was conducted in the following databases; PubMed, ScienceDirect, Google Scholar Medline, Pedro, and Cinahl. An additional search (including relevant grey literature) was also done on the internet through ResearchGate. Relevant literature research related to the keywords such as biomechanics of badminton, badminton forehand shot, biomechanical analysis, badminton performance, racquet sports, performance indicators, technique analysis and technique models were included and reviewed. Results: The results managed to present a synthesis of the literature review and provided constructive discussions as a basis to propose a performance outcome model that illustrates mechanical interactions that contribute to badminton forehand and shot technique performance. Conclusions: This model manages to find mechanical relationships and allows for a better grasp of understanding the association between performance criteria and mechanics in the badminton forehand shot technique, which is bases on the kinetic chain principle through the body segmental coordination.

Machine learning methods are being successfully applied in various domains of human activity, including optics. Can they become a universal instrument capable of improving user aspect of photonic devices? Is their application a necessary element of such improvement? Answers to fundamental questions arising from application of machine learning methods in ultrashort-pulsed lasers are discussed. Future prospects and current fundamental limitations of such methods are analysed.

Introduction Lab-on-a-Chip systems are innovative tools which can be used in the field of life sciences. They find applications e.g. in single cell analysis or cytotoxicity tests [1]. Despite the growing popularity of the use of microsystems in biological research, there is a lack of microsystems that may be used in the electrochemotherapy (ECT) studies. ECT is a antitumor therapy, based on an application of electroporation (EP) during standard chemotherapy (CT). EP uses external electric field to form hydrophilic pores in the cells membrane. Electropores are additional migration pathway for molecules which enhanced their delivery into cells [2]. ECT allows to use lower concentration of drug and reduces side effects in comparison to standard chemotherapy [3]. We develop a Lab-on-a-Chip microsystem for cell electroporation that could be used to examine the effectiveness of chemotherapy as well as for evaluation the effectiveness of electrochemotherapy. Microsystem fabrication The microsystem is made of polydimethylsiloxane (PDMS) and glass. Casting method was used to obtained the microchannels and microchambers in PDMS layer. Pairs of gold electrodes were arranged parallelly along the microchannel with microchambers at the distance of 2 mm. The microsystem allows simultaneous culturing of normal and tumor cells. There are four rows of microchambers for each cell line: I - cells not exposed to compound or electric field (control), II - electroporated cells not exposed to compound (control for EP), III – cells electroporated with compound (simulating condition of ECT), IV - cells incubated with compound (simulating condition of CT). In this way, it is possible to evaluate and compare the effectiveness of two types of therapeutic procedures. Method The microchip was sterilized using 70% ethanol and UV radiation. After that, the cell suspension was introduced using a peristaltic pump at a speed of 3.5 µl/min. After 24 h of incubation, the cells medium (control) and the solution of the test compound were respectively introduced into the microsystem, nextly the cells were electroporated. Cell observations were performed using an inverted fluorescence microscope. In addition, fluorescence intensity measurements of the introduced molecules were carried out using a multi-well plate reader. The AlamarBlue test was performed to determine cell viability. For this purpose, a 10% AlamarBlue solution was introduced into the microsystem, than fluorescence intensity was measured at λex=558 nm and λem= 585 nm. Results and Conclusions To determine the optimal electroporation parameters (pulse length, their number, voltage) preliminary experiments were led using propidium iodide (PI). Tests were carried out for two skin cell lines: normal HaCaT and tumor A375. Two sets of parameters were examined: 1 pulse 10 ms and 8 pulses 0.1 ms, each in three voltage variants: 150, 180 and 200V. Cell viability after electroporation was determined. It was found that there were no significant changes in the cell viability after electroporation with the voltage lower than 200V. The efficiency of PI delivery into cells was confirmed by microscopic observation as well as determined by fluorescence intensity measurements. Significantly lower PI level inside cells (at the level of 30%) using 8 pulses 0.1 ms for both cell lines was observed. The best efficiency of PI delivery (about 90%) was observed when 1 pulse of 180V lasting 10 ms was applied. In addition, cell morphology was observed and cells parameters such as: shape factor, sphericity, convexity and elongation were determined. It was confirmed that the electroporation of cells does not change their morphology. Based on the obtained results it was concluded that the optimal electroporation conditions for HaCaT and A375 cell lines are: 1 pulse 10 ms 180V. References [1] Grabowska-Jadach I., Haczyk M., Drozd M., Fischer A., Pietrzak M., Malinowska E., Brzózka Z., "Evaluation of biological activity of quantum dots in a microsystem", Electrophoresis, 2016, 35, 165-177. [2] Yarmush M. L., Golberg A., Sersa G., Kotnik T., Miklavcic D., “Electroporation-based Technologies for Medicine:Principles, Applications and Challenges”, Annual Review of Biomedical Engineering, 2014, 16, 295-320. [3] Calvet Ch. Y., L. Mir M., "The promising allianceof anti-cancerelectrochemotherapywithimmunotherapy", Cancer Metastasis Review, 2016, 35, 165-177. This work was realized with the frame of project Preludium no 2018/31/N/ST4/02922.

Highlights • Evidence synthesis (including systematic reviews, scoping reviews, and more) involves many complementary areas of expertise: methods, information retrieval, statistics, and clinical knowledge. • Few individual peer reviewers have all the requisite knowledge to evaluate all aspects of evidence synthesis manuscripts. • Segmented peer review as proposed by Dinakaran et al offers a good solution to the challenges of rigorously peer reviewing evidence synthesis manuscripts.

This paper briefly describes Amanda(1), a framework for mediating collective discussions in distance learning environments. The objective of this framework is to help tutors achieve better results from group discussions and improve knowledge transfer among the participants. The overall idea is to organize the group discussion in an argumentation tree and involve the participants in successive discussion activities. The coordination of the discussion is made by a set of intelligent mechanisms which reason over the discussion and propose new interactions among the participants. Amanda advances the discussion by generating progressive discussion cycles until a desired set of target conditions are observed. At each discussion cycle, the system redistributes discussion tasks among the participants to ensure a desired degree of agreement and participation among them. In this short paper we describe the underlying coordination principles and the use of knowledge models for producing natural language questions.