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Maturity of vermicomposted end products obtained from citronella bagasse (CB) and a mixture of citronella bagasse and paper mill sludge (CB + PMS) was determined employing the epigeic earthworm species Eisenia fetida. Two of the primary biological indicators—enzyme assay and germination index—were used for evaluation of vermicompost maturity. The enzyme assay includes the changes in dehydrogenase and urease activities in the final products. The test for germination index was performed on two economically important plant species Abelmoschus esculentus and Solanum melongena. The results revealed a significant increase in dehydrogenase and urease activities in the vermicompost samples over the raw materials and traditional compost. The enhancement was recorded 215.63–225.63% in dehydrogenase and 149.89–249.31% for urease in the end products obtained after 45 days of experimental trials. Further, the higher values of germination index in the vermicompost treatments as against the control confirm the suitability and stability of the vermicomposted final products.

There are many pulp and paper industries all around the globe and in Ethiopia as well different companies are involved in the production and distribution of paper and paper products. Most of the industries especially those in developing countries like Ethiopia produce paper from pulp obtained from wood cellulose. Ethiopia is not producing its pulp and mostly the paper industries depend on imported pulp or recycled paper. There are critical limitations in synthesizing pulp and paper from wood-based cellulose resources mainly the scarcity of wood in some countries and the impact on altering the ecological balance and through frequent deforestation and replantation practice. The present review assesses the potential sources from non-wood resources which can be used as a substitute cellulose raw material for the pulp and paper industry. The study encompasses possible beneficiation routes for manufacturing pulp from non-wood cellulose resources available in Ethiopia for diversified application in the paper industry. With this regard, potential non-wood raw materials for pulping are assed in line with the fulfilment of the target for import substitution strategy, the realization of a safe working environment, and socio-economic betterment of the nation with specific reference to the paper industry.

The authors of the title paper (Journal of Optics 49:181–186, 2020) claim to have grown a so-called urea potassium dichromate (UPDC) by slow evaporation of an aqueous solution containing equimolar amounts of urea and potassium dichromate and characterized it based on a unit cell study. A critical analysis reveals that the claims in the title paper are erroneous. Hence, we reinvestigated the crystal growth reaction and determined the structure of the product crystal. Based on these studies, we prove that due to no chemical reaction between the reagents fractional crystallization of potassium dichromate (K2Cr2O7) occurs and not formation of any so-called UPDC crystal. Taking the title crystal as an example we show the importance of reporting single-crystal structure for new compound characterization.

Educational evaluation helps to improve the learning and teaching process. The learning process can be assessed by the examination system. In the examination system, the learners have to answer a set of questions. The learning assessment ensures improved performance in the educational system. The success of the learning assessment is highly dependent on the listening and understanding ability of each student. The assessment of the question paper can be at two levels—cognitive level assessment and difficulty level. The cognitive level assessment is purely based on Bloom’s Taxonomy and the difficulty level assessment is purely based on the examination marks of each student. This article presents a technical method called Question Paper’s Difficulty Level (QPDL) that helps to identify the difficulty level of each question in the question paper. The QPDL method is incorporate in the implementation of ‘QAUDIT’ web application to assess the difficulty level of the question paper systematically. The systematic analysis to identify the difficulty level of the question paper is made for 239 question papers. Each question paper can be recognized based on three difficulty levels such as High, Moderate and Low.

The medical field has witnessed an exponential growth of wearable devices mainly due to the advancement in wireless communication and antenna technology. There is a demand for wearable antennas, which are lightweight, flexible, and ease of integration into the fabric which suits on-body applications. Therefore, this work presents the design, fabrication, and analysis of two microstrip antennas using denim cloth and stacked photo paper as substrate material. The novelty of these antennas is the use of silver fabric as ground and radiating patch-conducting layer, which has resulted in significant improvement in overall antenna performance. It is observed that our fabricated antennas have exhibited a gain of 8.71 dB with VSWR of 1.32 for denim and gain of 2.45 dB with VSWR of 1.03 for photo paper substrates respectively.

Augmented reality technology is attracting increased attention, given the popularity of the smartphone. The utilisation of the smartphone with AR technology is also enabling mobile augmented reality (MAR) to become accessible. Stereoscopic vision offers users the benefit of depth perception, which can help improve user memory. Therefore, this study aims to investigate the effect on knowledge retention using MAR with stereoscopic vision. An experiment to compare a stereoscopic-based MAR application and a paper-based manual was designed to test the participants’ knowledge retention on a product part and disassembly process. The developed MAR adopted a smartphone and headset case to provide a stereoscopic view to the user. The experiment consisted of both pre-test and post-test phases where the pre-test phase examined the participant’s knowledge about the product, and the post-test phase focused on how much information the participants could recall. The post-test phase was conducted after 48 h following the pre-test phase since long-term memory required several hours in which to stabilise. The results showed that the MAR group had an advantage over the paper-based manual group for both information retentions having a mean score of 8.89 from the MAR group, compared with 6.33 for the paper-based manual group. Moreover, the MAR group was observed to have fewer errors in the post-test with a mean score of 0.53, whereas the paper-based achieved a score of 2.2. This result indicated that the MAR group and the paper-based manual group had equivalent performance in the completion time without the assistance tool. In addition, MAR had a better mean score for the subjective feedback (usefulness = 4.47, ease of use 4.18 and satisfaction = 4.07).

Thermostable cellulases have wide variety of applications and distinctive advantages, but their low titer becomes the hurdle in their commercialization. In the present work, an assessment of optimum levels of significant factors (temperature, moisture ratio, inoculum size, and ammonium sulfate) and the effect of their interactions on production of thermostable CMCase, FPase, and β-glucosidase by Thermoascus aurantiacus RCKK under solid-state fermentation (SSF) was carried out using central composite design (CCD) of response surface methodology (RSM). The study revealed 33, 13, and 8 % improvement in FPase, CMCase, and β-glucosidase production, respectively. Moreover, crude cellulase from T. aurantiacus RCKK efficiently hydrolyzed office waste paper, algal pulp (Gracillaria verulosa), and biologically treated wheat straw at 60 °C with sugar release of about 830 mg/ml, 285 mg/g, and 260 mg/g of the substrate, respectively. The thermostable enzyme from T. aurantiacus RCKK holds potential to be used in biofuel industry.

The paper industry is heavily using energy during all the phases of the manufacturing process. This is especially the case in Nordic mills where pressure ground wood is the source of fiber. The purpose of this case study is to show how energy consumption behaves on a monthly basis in a Finnish paper mill that has several paper machine lines. The research examines different categories of energy usage, as well as the overall costs. The results show that the monthly energy usage varies significantly. The electricity consumption of the case mill is rather steady, but there is significant monthly variation in steam and natural gas consumption. Moreover, steam and electricity unit costs increased significantly when coming to the end of the research period. The longitudinal case data shows that it is difficult to enhance energy consumption per produced unit at the paper mill. One reason for this is the bleak demand outlook for the end products, which often result in downsizing and closing operations inside the integrated unit.

Enterprise imaging governance is an emerging need in health enterprises today. This white paper highlights the decision-making body, framework, and process for optimal enterprise imaging governance inclusive of five areas of focus: program governance, technology governance, information governance, clinical governance, and financial governance. It outlines relevant parallels and differences when forming or optimizing imaging governance as compared with other established broad horizontal governance groups, such as for the electronic health record. It is intended for CMIOs and health informatics leaders looking to grow and govern a program to optimally capture, store, index, distribute, view, exchange, and analyze the images of their enterprise.

Portable communication devices such as WLAN, WiMAX, LTE, ISM, and 5G utilize one or more of the triple bands at (2.3–2.7 GHz, 3.4–3.6 GHz, and 5–6 GHz) and suffer from the effect of multipath problems because they are used in urban regions. To date, no one has performed a review of the antennas used for these types of wireless communications. This study reviewed two types of microstrip antennas (slot and fractal) that have been reported by researchers (as a single element) using a survey that included the evaluation of several important specifications of the antennas in previous research, such as operating bandwidth, gain, efficiency, axial ratio bandwidth (ARBW), and size. The weaknesses in the design of all antennas were carefully identified to determine the most important challenges in the design of these antennas and name the most important limits in the design to be overcome in future research. This study also indicated some antennas that have circular polarization characteristics, the techniques used to generate the circular polarization characteristics, and the challenges. Finally, several suggestions as a guideline for antenna design and future work in designing antennas for Wi-Fi, LTE, and WiMAX communications, according to the market demands, and methods for overcoming the identified limits are presented.

The confluence of significant computational power and inexpensive sensors provides the opportunity to reliably collect large volumes of information from the world and extract humanly useful information resources. This paper reviews a coherent body of work over the last 20+ years focused on development of advanced bio-inspired computing techniques, and their applications primarily for human related data in behaviour and human centered computing. We close with a synthesis proposing an experiment analysis methodology combining these tools.

In this work, a new method of bricks making based on waste paper has been developed for the thermal insulation of buildings. This method involves converting paper waste into aggregates and combining them with a Portland cement binder. A physical and thermal characterization of the Aggregate of Waste Paper (AWP) is carried out, followed by a structural study by Scanning Electron Microscopy (SEM). Six Paper Brick Types are made with the mass dosage variation of the composite. After drying the bricks in the open air for 28 days, experimental investigations were carried out to determine the density, the water absorption, the compressive and flexural strength, and the propagation speed of ultrasonic waves. In addition, a SEM analysis combined with an Energy-Dispersive X-ray spectroscopy analysis (EDX) is performed to examine the adhesion between the AWP and the cement particles. The characterization results of the aggregates showed a low density and thermal conductivity amounting to170kg/m3 and 0.06 W/m.K, respectively, and the analysis of their microstructure by SEM demonstrated that their structure is composed of randomly distributed fibers. Moreover, the mechanical properties of the paper bricks are more resistant, since the compressive strength varies between 3.43 and 6.43 MPa, and their thermal properties are lower compared to the conventional bricks, from 0,0851 to 0,0978 W/m.K. Therefore, these findings clearly indicate that the newly made bricks represent an innovative solution for thermal insulation in buildings that can also be used as a structural material.

Recently, a group of researchers conducted experimental studies on the high-temperature oxidation behaviour of Si-containing steels and published a series of papers in several international journals. Many of the research “findings” in these papers were inconsistent and contradictory with previous results. Based on the different findings, it was claimed that they arrived at “new insights” to the oxidation behaviour of Si-containing steels and discovered a “new method” to reduce the oxide scale amount generated during reheating of Si-containing steels. After examining the experimental methods used, it was revealed that most of the “new findings” were likely the direct consequence of the use of a very low gas flow rate (30 mL/min) in their experiments. This resulted in an extremely low oxygen supply rate when the oxygen concentration in the experimental gas was low, which in turn limited the reaction rate that could be possibly achieved by gas–steel reaction if abundant gas had been made available. The kinetics results and scale thickness/structures thus produced were therefore misleading, which also led to the erroneous interpretation of the results. This paper comments on the main results presented in these papers and briefly discuss several fundamental issues related to the design of steel oxidation experiments.

The potential of modern regeneration boiler cold end and feedwater system integration with energy system of a paper mill is studied and measures for its better exploitation are proposed and assessed. Mathematical model has been developed, comprising material and heat balances, heat transfer equations, and steam turbine model. Its accuracy has been tested on the design and actual operation of a real system firing 70 t/h of dry solids. The simulation coped with design and measured data very well and also followed the operation changes performed in field tests excellently. Nine proposals aimed at real system efficiency improvement were assessed on the yearly benefit and simple payback period base, with yearly benefit resulting either from marginal fuel savings (scenario 1) or from condensing power production increase (scenario 2). Immediately applicable measures included deaeration at full steam pressure and heat load minimization in the first stage of the boiler feedwater regenerative heating—this novel finding contradicts the boiler design where full load regenerative heating is applied. Further measures increase the internal and external (available in paper mill) heat utilization. Their combination yielded either up to a 7 t/h internal steam consumption decrease (2.25% of nominal boiler steam output, scenario 1) or up to a 1.4 MW electricity production increase (2% of nominal steam turbine power output). Several of the proposed measures merit attention of boiler vendors and paper mills energy managers as viable tools towards low energy intensity pulp and paper mill industrial sector.

Thermochemical heat storage materials for space heating applications such as, ZnSO4 offer high energy storage density, low cost and clean mean of long-term solar energy storage. Herein, we studied the ZnSO4 hydrated salt as potential heat storage material at low temperature and furthermore observed the impact of temperature and concentration on the dehydration/hydration process and enthalpy. The thermal behavior of ZnSO4•7H2O was investigated by applying various dehydration temperatures. The results showed that 85% of water loosed at 100 °C temperature, which released 699 J/g (1.37 GJ/m3) in the dehydration process. The hydration process of ZnSO4.7H2O at 100 °C recovered 541 J/g enthalpies, which delivered 1.1 GJ/m3. Similarly, the dehydration result obtained at 150 °C was the same as showed at 100 °C. However, the enthalpy of hydration was 20% less than prior. The XRD result showed that at higher temperatures agglomeration appeared followed by Van der Waals forces which affect the hydration rate. The result of good cyclability and larger water sorption performance of ZnSO4 make them a promising and suitable for heat storage in space heating application, which can be used as thermochemical heat storage material for thermal storage devices.

Applications of digital micromirror device for lidar are overviewed. A large Lagrange invariant value makes DMD as one of the attractive beam steering transmitter and receiver solutions for a time-of-flight lidar, especially with its an extended angular throw by synchronized pulsed laser illumination.

Compared with wood pulp, straw pulp and papermaking, because of lower cost and abundancy of raw material, has become an indispensable approach in paper industry of China. However, its further application is limited by huge water consumption and wastewater discharge. By employing substance flow analysis, this study built up an optimization model and a performance evaluation system of water saving for the water-use network of a straw pulp and paper enterprise, after identifying the problems in present water consumption. Accordingly, an optimization plan was proposed to combine man-made water circulation with natural water circulation system. Additionally, a contrast analysis between the present and optimized water use was conducted. At last, we applied the proposed optimization plan to one of the most important and largest enterprises of straw pulp and paper industry in China as an illustration. Theoretically, water consumption could be reduced by 75.4 % without wastewater discharge after optimization.

A valourising process annexed to a recycling paper mill for converting three plastic-fibre rejects (PFRs) into oil, char and utility energy through pyrolysis provides renewable energy and prevents waste disposal. The economic and technical responses of the process are measured by varying the conversion temperature, feedstock characteristics and energy recovery approach, in order to optimise the processs. Previously measured responses of valourising PFRs were simulated in AspenPlus® according to variations in the fast-pyrolysis temperatures (350–550 °C); the contents of lignocellulosic fibres and plastics; and methods for adding value to excess process heat as steam and/or electricity. Economic models scaled at 540 kg/h were derived to determine the required minimum fuel selling price (MFSP) of the oil product. A base case for heat recovery assumes both steam and electricity. For a PFR stream composing mainly lignocellulose, the MFSP of oils ranged from 341 US$/GJ for pyrolysis at 350 °C to 65 US$/GJ for pyrolysis at 550 °C, while the process at 450 °C was most energy efficient. When only recovering steam from waste energy, the MFSPs were reduced by 6%. Pyrolysis of reject streams with increased plastics contents reduced the MFSP of the oil to 37 US$/GJ, due to the higher calorific value of the products. Increasing the feed rate of PFRs to 2400 kg/h could potentially reduce the MFSP to a market-competitive price of 15.3 US$/GJ, at a scale equivalent to a power-plant of 5MWe. PFRs containing higher proportions of plastics are preferred for valourisation through pyrolysis at 550 °C, while waste energy is best recovered as steam.

In this study pre-treatment of pulp and paper mill sludge was investigated to enhance the energy recovery by anaerobic digestion. Two approaches were followed using hydrolytic enzymes or microbiological treatment at 30 °C. In the first attempt, anaerobic digestion of the whole sludge, no significant improvement of the methane production potential was found. In the second test series only the liquid phase after pre-treatment and solids separation was anaerobically degraded. This option provided up to ten times increased methane production compared to the untreated sample. Sludge mass reduction between 6 and 13 % was achieved after pre-treatment. Moreover this concept can be easily integrated in the established wastewater treatment scheme utilizing an existing upflow anaerobic sludge blanket reactor.

By employing historical case study methodology, this paper examines the transition towards renewable energy and increased energy efficiency in the Swedish pulp and paper industry (PPI) during the 1 ...

The disposal of paper mill sludge through anaerobic digestion (AD) combined pyrolysis was investigated. Two paper mill sludge samples, both with very low lower heating values (LHV) were adopted to compare the energy balance change in the disposal process; and the influence of AD step on the characteristics of chars, including their LHVs, specific area, heavy metal stabilisation, and so on was also studied. The experimental results showed that the biogas (methane) generated from AD step can help to improve energy balance in the pyrolysis processes. As a result, the energy balance for paper mill sludge pyrolysis disposal changed from being in deficit to in surplus when AD step was combined for the sludge of relatively low LHV; or the energy surplus increased. Both the micropore surface area and the LHV of chars decreased. The nutrient elements like P and K in the sludges were partially lost into the AD liquids. But the heavy metals in the chars from the digested sludges were found to be similarly stable to those from the raw sludges when subject to leaching. In general AD combined pyrolysis is proved to be a valid method to dispose paper mill sludge with very low LHV.

There are thousands of pulp and paper mills worldwide. The utilization of the waste they produce is a problem of particular importance. Many methods have already been put forward for the management of the mixture of lime mud and cellulose fibre residues. The chemical nature of its management presents a challenge because it requires costly catalysts and long retention times or raises criticisms about its environmental impacts. Several techno-economic analyses (including various modifications to anaerobic fermentation; combustion; pyrolysis and composting) have been carried out on an almost commercial scale to holistically assess the wide portfolio of management issues. The data obtained indicate that it cannot be clearly concluded that one particular method is the best for dealing with all management issues. However, the conclusions do provide an insight into how processing technologies can be adapted in specific cases.

Physical paper, in its various forms (e.g. books, leaflets, catalogues), is extensively used in everyday activities, despite any advancements in digital technology and ICT. Inspired by the popularity of this medium, several research efforts have envisioned and pursued a new era of interactive paper, however several challenges still remain to be addressed. On the other hand, recent advancements towards Ambient Intelligence (AmI) and Smart environments, bear the promise of seamless integration of the physical and digital worlds in an intuitive and user-friendly manner. This paper presents InPrinted, a systematic and generic framework supporting physical paper augmentation and user interaction in Ambient intelligence environments. InPrinted enables natural multimodal user interaction with any kind of printed matter in smart environments, providing context aware and anticipation mechanisms, as well as tools and interaction techniques that support the development of applications incorporating printed matter augmentation. InPrinted has been put to practice in the development of various systems, including the Interactive Maps system, facilitating interaction with printed maps as well as their augmentation with digital information. The results of an in-situ observation experiment of the Interactive Maps system are reported, highlighting that interacting with augmented paper is quite easy and natural, while the overall User Experience is positive.

With the speedy progress of network technology and internet applications, protection of digitized data against unauthorized access and modification has become a paramount issue. In order to face this challenge, numerous secret image sharing schemes have been introduced. Secret image sharing scheme is a method used for safeguarding the sensitive digitized image against illegal copying and tempering. The secret image is divided into many random shares in such a way that each share does not reveal any information to the intruders. In this paper, we present a comprehensive survey from over 100 papers which explains the new approaches and challenges. This paper also provides a comparative analysis of different methods based on different properties.

Scientific retrieval systems need to be given domain search terms for searching publications, however, as natural language, search terms provided by users are often fuzzy and limited and some relevant terms are always overlooked in searching. Meanwhile, users always desire to be given domain related keywords to enlighten themselves what other terms can be used for their searching. This paper presents a concepts recommendation model in scientific paper retrieval, in which concepts are extracted from keyword in scientific papers, and some data mining algorithms are used to calculate the similarity between search terms and concepts and do recommendation for users. This model is simple and can be used with small dataset, in which all training data used is from meta data of papers that is easy to acquired. Experimental result hold good precision, which shows that this research not only simplifies searching step and improves the searching quality for users, but also lays the foundation for semantic search.

A paper yarn is recently spotlighted as a new textile material due to its inherent excellent properties such as antibiotic, deodorant, moisture retaining, and absorbency-quick drying properties. However, its poor flexibility and low elongation cause some disadvantages of cut-off and difficulty in tension control in the knitting process. To prevent those disadvantages of the paper yarn, in this study, a production method of hybrid yarn with other synthetic filament yarn was conducted. Four types of the hybrid yarn with paper yarn and polyester and nylon filament yarns were prepared. The maximum breaking stresses of the hybrid yarns were shown at twist number of 600 tpm and 700 tpm of paper/polyester and paper/nylon yarn, respectively. Also there were relatively different morphologies of the hybrid yarns with twist numbers. These facts originated in a stable integration of each single yarn constituting the hybrid yarn. Due to the reinforcing effect of the filament yarn, the hybrid yarn showed an increment in the maximum stress and strain, but a decrease in initial modulus compared to single paper yarn. In addition, irregularity and defective of the hybrid yarn were evaluated with the surface structure of the yarns. The hybrid yarn having maximum breaking stress showed good knitting ability and excellent surface appearance of its knitted fabrics.

In this work, we investigated the thermal conductivity (k-value) and mechanical behavior of a lightweight material containing recycle paper mill waste (RPMW) and cement. RPMW has been characterized using XRF, TG-DTA, and SEM. TG-DTA results confirm the thermal stability of the material prepared (stable up to 300 °C) and SEM monographs clearly indicate the pores and fibrous nature of this material. The influence of temperature and humidity on the thermal conductivity (k-value) of the material was studied, which indicated that k-value increases with temperature and humidity. The insulation property of the RPMW insulation material was tested by various means [flow of hot fluid through pipes (below 200 °C) and joints, temperature dissipation and retention in a glass flask, and as a brick]. Thermal images and histogram of insulation application were obtained and analyzed. Results confirmed that the RPMW insulation material is lightweight (0.6 ± 0.1 g/cc) and has low thermal conductivity (0.4 ± 0.2 W/mK). The thermal insulating effect of RPMW indicates a promising potential as a low-temperature hot insulator.

In recent years, members of the steering committee of the IEEE Requirements Engineering (RE) Conference have discussed paper classification and evaluation criteria for RE papers. The immediate trigger for this discussion was our concern about differences in opinion that sometimes arise in program committees about the criteria to be used in evaluating papers. If program committee members do not all use the same criteria, or if they use criteria different from those used by authors, then papers might be rejected or accepted for the wrong reasons. Surely not all papers should be evaluated according to the same criteria. Some papers describe new techniques but do not report on empirical research; others describe new conceptual frameworks for investigating certain RE problems; others report on industrial experience with existing RE techniques. Other kinds of papers can also be easily recognized. All of these types of papers should be evaluated according to different criteria. But we are far from a consensus about what classes of paper we should distinguish, and what the criteria are for each of these classes.

Paper checks may have complex background features including fine lines and patterns, which make forgery more difficult. Also, halftoning techniques are used to produce continuous tones and to prevent copies with void pantograph features. When these kinds of checks are scanned, Moire patterns may occur. These patterns make it difficult for customers to examine the scanned check images on ATM (Automated Teller Machine) displays. They also can decrease the classification accuracy of check recognition systems. In this paper, we propose an algorithm to enhance the perceptual quality of scanned check images by reducing the Moire patterns. The proposed algorithm consists of foreground extraction, Moire detection and Moire removal. Subjective image quality assessment was performed to evaluate the degree of improvement. Experimental results show that the proposed algorithm improves perceptual quality while maintaining check recognition accuracy.

In the paper we present an approach to the automatic detection and identification of important elements in paper documents. This includes stamps, logos, printed text blocks, signatures and tables. Presented approach consists of two stages. The first one includes object detection by means of AdaBoost cascade of weak classifiers and Haar-like features. Resulting image blocks are, at the second stage, subjected to verification based on selected features calculated from recently proposed low-level descriptors combined with certain classifiers representing current machine-learning approaches. The training phase, for both stages, uses bootstrapping, i.e., integrative process, aiming at increasing the accuracy. Experiments performed on large set of digitized paper documents showed that adopted strategy is useful and efficient.

We present a method of setting up a website using the Drupal CMS to publish CRM data. Our setup requires basic technical expertise by researchers who are then able to publish their records in both a human accessible way through HTML and a machine friendly format through RDFa. We begin by examining previous work on Drupal and the CRM and identifying useful patterns. We present the Drupal modules that are required by our setup and we explain why these are sustainable. We continue by giving guidelines for setting up Drupal to serve CRM data easily and we describe a specific installation for our case study which is related to decorated papers alongside our CRM mapping. We finish with highlighting the benefits of our method (i.e. speed and user-friendliness) and we refer to a number of issues which require further work (i.e. automatic validation, UI improvements and the provision for SPARQL endpoints).

A committee has recommended scrapping a rule that requires PhD students to publish articles. A committee has recommended scrapping a rule that requires PhD students to publish articles.

In this paper, we discuss the application of concept of data quality to big data by highlighting how much complex is to define it in a general way. Already data quality is a multidimensional concept, difficult to characterize in precise definitions even in the case of well-structured data. Big data add two further dimensions of complexity: (i) being “very” source specific, and for this we adopt the interesting UNECE classification, and (ii) being highly unstructured and schema-less, often without golden standards to refer to or very difficult to access. After providing a tutorial on data quality in traditional contexts, we analyze big data by providing insights into the UNECE classification, and then, for each type of data source, we choose a specific instance of such a type (notably deep Web data, sensor-generated data, and Twitters/short texts) and discuss how quality dimensions can be defined in these cases. The overall aim of the paper is therefore to identify further research directions in the area of big data quality, by providing at the same time an up-to-date state of the art on data quality.

Exploring massive mobile data for location-based services becomes one of the key challenges in mobile data mining. In this paper, we investigate a problem of finding a correlation between the collective behavior of mobile users and the distribution of points of interest (POIs) in a city. Specifically, we use large-scale cell tower data dumps collected from cell towers and POIs extracted from a popular social network service, Weibo. Our objective is to make use of the data from these two different types of sources to build a model for predicting the POI densities of different regions in the covered area. An application domain that may benefit from our research is a business recommendation application, where a prediction result can be used as a recommendation for opening a new store/branch. The crux of our contribution is the method of representing the collective behavior of mobile users as a histogram of connection counts over a period of time in each region. This representation ultimately enables us to apply a supervised learning algorithm to our problem in order to train a POI prediction model using the POI data set as the ground truth. We studied 12 state-of-the-art classification and regression algorithms; experimental results demonstrate the feasibility and effectiveness of the proposed method.

Background Regulations, study design complexity and amounts of collected and shared data in clinical trials render efficient data handling procedures inevitable. Recent research suggests that electronic data capture can be key in this context but evidence is insufficient. This randomized controlled parallel group study tested the hypothesis that time efficiency is superior when electronic (eCRF) instead of paper case report forms (pCRF) are used for data collection. We additionally investigated predictors of time saving effects and data integrity. Methods This study was conducted on top of a clinical weight loss trial performed at a clinical research facility over six months. All study nurses and patients participating in the clinical trial were eligible to participate and randomly allocated to enter cross-sectional data obtained during routine visits either through pCRF or eCRF. A balanced randomization list was generated before enrolment commenced. 90 and 30 records were gathered for the time that 27 patients and 2 study nurses required to report 2025 and 2037 field values, respectively. The primary hypothesis, that eCRF use is faster than pCRF use, was tested by a two-tailed t-test. Analysis of variance and covariance were used to evaluate predictors of entry performance. Data integrity was evaluated by descriptive statistics. Results All randomized patients were included in the study (eCRF group n = 13, pCRF group n = 14). eCRF, as compared to pCRF, data collection was associated with significant time savings across all conditions (8.29 ± 5.15 min vs. 10.54 ± 6.98 min, p = .047). This effect was not defined by participant type, i.e. patients or study nurses (F(1,112) = .15, p = .699), CRF length (F(2,112) = .49, p = .609) or patient age (Beta = .09, p = .534). Additional 5.16 ± 2.83 min per CRF were saved with eCRFs due to data transcription redundancy when patients answered questionnaires directly in eCRFs. Data integrity was superior in the eCRF condition (0 versus 3 data entry errors). Conclusions This is the first study to prove in direct comparison that using eCRFs instead of pCRFs increases time efficiency of data collection in clinical trials, irrespective of item quantity or patient age, and improves data quality. Trial registration Clinical Trials NCT02649907 .

This paper presents a printed negative index metamaterial for electromagnetic (EM) absorption reduction in portable wireless antenna. The perceptible novelty exhibited in this paper is that EM absorption reduction toward the human head with paper-based metamaterial attachment. This research has been performed using human head phantom integrated in the commercially available CST Microwave Studio software package. The EM absorption has been reduced by 13.2 and 6% at 900 and 1800 MHz, respectively.

Background Electronic Case Report Forms (eCRFs) are increasingly chosen by investigators and sponsors of clinical research instead of the traditional pen-and-paper data collection (pCRFs). Previous studies suggested that eCRFs avoided mistakes, shortened the duration of clinical studies and reduced data collection costs. Methods Our objectives were to describe and contrast both objective and subjective efficiency of pCRF and eCRF use in clinical studies. A total of 27 studies (11 eCRF, 16 pCRF) sponsored by the Paris hospital consortium, conducted and completed between 2001 and 2011 were included. Questionnaires were emailed to investigators of those studies, as well as clinical research associates and data managers working in Paris hospitals, soliciting their level of satisfaction and preferences for eCRFs and pCRFs. Mean costs and timeframes were compared using bootstrap methods, linear and logistic regression. Results The total cost per patient was 374€ ±351 with eCRFs vs. 1,135€ ±1,234 with pCRFs. Time between the opening of the first center and the database lock was 31.7 months Q1 = 24.6; Q3 = 42.8 using eCRFs, vs. 39.8 months Q1 = 31.7; Q3 = 52.2 with pCRFs (p = 0.11). Electronic CRFs were globally preferred by all (31/72 vs. 15/72 for paper) for easier monitoring and improved data quality. Conclusions This study found that eCRFs and pCRFs are used in studies with different patient numbers, center numbers and risk. The first ones are more advantageous in large, low–risk studies and gain support from a majority of stakeholders.

Coal mining and its unfavourable consequences have generated global attention. It has further stimulated the paradoxical debate of development and desolation in the contemporary scenario. Since the coal resources are profusely available in India and it is comparatively less expensive, the country has been largely relying on it for its essential and non-essential consumption needs. Coal resources indirectly fulfil many of the modern requirements and comforts. Consequently, mining of minerals in general and coal in particular has become the prime focus. It helps to generate revenue, augment industrialisation and promote employment opportunities in India. Despite these progressive features, the opencast coal mining activities impose serious threats to the livelihood of the local communities. Based on critical review of the relevant literature, the article seeks to exhibit the mineral reserves and coal mining activities at global, national and regional context. The paper has incorporated a special focus on Odisha—a resource-rich state located in eastern part of India. Particularly, the two existing major coalfields—Talcher and Ib valley, situated in western part of the state—have been emphasised. The manifold adverse externalities of the coal mining practices on the livelihood pattern among the affected people have been assessed. Furthermore, the paper aims to examine the mining-induced threats on different livelihood capitals which has given rise to multiple risks and challenges.

PURPOSE: Breast ultrasound (BUS) is one of the imaging modalities for the diagnosis and treatment of breast cancer. However, the segmentation and classification of BUS images is a challenging task. In recent years, several methods for segmenting and classifying BUS images have been studied. These methods use BUS datasets for evaluation. In addition, semantic segmentation algorithms have gained prominence for segmenting medical images. METHODS: In this paper, we examined different methods for segmenting and classifying BUS images. Popular datasets used to evaluate BUS images and semantic segmentation algorithms were examined. Several segmentation and classification papers were selected for analysis and review. Both conventional and semantic methods for BUS segmentation were reviewed. RESULTS: Commonly used methods for BUS segmentation were depicted in a graphical representation, while other conventional methods for segmentation were equally elucidated. CONCLUSIONS: We presented a review of the segmentation and classification methods for tumours detected in BUS images. This review paper selected old and recent studies on segmenting and classifying tumours in BUS images.

The European Union’s circular economy strategy aims to increase the recycling and re-use of products and waste materials. According to the strategy, the use of industry waste materials and side flows is required to be more effective. In this research, a chemical precipitation method to simultaneously remove ammonium and phosphate from the reject water of anaerobic digestion plant using calcined paper mill sludge and fly ash as a precipitant, was tested. Paper mill sludge is a waste material formed in the paper-making process, and fly ash is another waste material formed in the power plant. Objective of this research was to test whether these industrial waste streams could be used as low cost precipitation chemicals for ammonium and phosphate removal from wastewaters and whether the precipitate could be suitable for fertilizer use. Results indicated that calcined paper mill sludge had high removal efficiency for both ammonium (97%) and phosphate (73%). Fly ash also had good removal efficiency for both ammonium nitrogen (74%) and phosphate (59%) at 20 ± 2 °C. The precipitates contained high concentrations of nitrogen and phosphate and could be used as a recycled fertilizer. Other possible mechanisms for the removal of phosphate and ammonium were considered.

Nowadays, due to modernization or advancement in the Internet of Things (IoT) especially in the Healthcare area, we want to take care of our elders with some monitoring equipment, and the Internet of Things can play a significant role in it. The motivation of writing this paper is to collect the information of various existing Internet of Things Architecture and Communication Techniques used in Healthcare Monitoring System to observe that how efficiently, different researchers have used it. So we have studied different real-time health monitoring system based on diseases which are common in elderly people like diabetes, blood pressure, heart disease, sleep apnea, and cancer, etc. In this real-time health monitoring system, researchers introduced many new measures, communication techniques like ZigBee, Long-Range Wide Area Network (LoRawan), Radio Frequency Identification (RFID). Apart from this, it was also observed that remote monitoring system in Healthcare is incomplete without data processing and early prediction in such diseases. Though, Machine learning provides efficient techniques to extract knowledge from diagnostic medical datasets collected from the patients. That is why we highlighted the current role of various Machine Learning algorithms like Support Vector Machine, K-Nearest Neighbor, Random Forest, etc., for processing of Healthcare data and also helpful to predict the output more precisely.

Recently, virus diseases, such as SARS-CoV, MERS-CoV, and COVID-19, continue to emerge and pose a severe public health problem. These diseases threaten the lives of many people and cause serious social and economic losses. Recent developments in information technology (IT) and connectivity have led to the emergence of Internet of Things (IoT) and Artificial Intelligence (AI) applications in many industries. These industries, where IoT and AI together are making significant impacts, are the healthcare and the diagnosis department. In addition, by actively communicating with smart devices and various biometric sensors, it is expanding its application fields to telemedicine, healthcare, and disease prevention. Even though existing IoT and AI technologies can enhance disease detection, monitoring, and quarantine, their impact is very limited because they are not integrated or applied rapidly to the emergence of a sudden epidemic. Especially in the situation where infectious diseases are rapidly spreading, the conventional methods fail to prevent large-scale infections and block global spreads through prediction, resulting in great loss of lives. Therefore, in this paper, various sources of infection information with local limitations are collected through virus disease information collector, and AI analysis and severity matching are performed through AI broker. Finally, through the Integrated Disease Control Center, risk alerts are issued, proliferation block letters are sent, and post-response services are provided quickly. Suppose we further develop the proposed integrated virus disease control model. In that case, it will be possible to proactively detect and warn of risk factors in response to infectious diseases that are rapidly spreading worldwide and strengthen measures to prevent spreading of infection in no time.

A prediction model is an indispensable tool in business, helping to make decisions, whether in the short, medium, or long term. In this context, the implementation of machine learning techniques in time series forecasting models has a notorious relevance, as information processing and efficient and dynamic knowledge uncovering are increasingly demanded. This paper develops a model called Variable step-size evolving Participatory Learning with Kernel Recursive Least Squares, VS-ePL-KRLS, applied to the forecast of weekly prices for S500 and S10 diesel oil, at the Brazilian level, for biweekly and monthly horizons. The presented model demonstrates a better accuracy compared with analogous models in the literature, without loss of computational performance for all time series analyzed.