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The category of household and sanitary products is the most important category in the paper industry, because it is related to people’s daily lives all around the world. This category is seeing a rapid increase in consumption, while consumption in other categories, such as printing or writing paper, is presently declining. China is the largest manufacturer, as well as the largest consumer of household and sanitary paper. Nowadays, environmental consciousness and concerns are rising in China and have started to influence customers’ behavior in selecting and using paper products. In the present study, surveys were conducted of the paper industry, the retail market for paper, and end consumers of paper. The relationship between new challenges of the paper industry and consumers’ environmental concerns has been investigated and reported.

Due to the increasing use of the Internet and other online resources, there is tremendous growth in the data of text documents. It is not possible to manage this huge data manually. This has led to the growth of fields like text mining and text summarization. This paper presents a title prediction model for research papers using Recursive Recurrent Neural Network (Recursive RNN) and evaluates its performance by comparing it with sequence-to-sequence models. Research papers published between 2018 and 2020 were obtained from a standard repository, viz. Kaggle, to train the title prediction model. The performance of different versions of Recursive RNN and Seq2Seq was evaluated in terms of training and hold-out loss. The experimental results show that Recursive RNN models perform significantly better than the other models.

Color 3D printing is an important advancement in 3D printing for lifelike personalization, but color reproduction in paper-based color 3D printers suffers from accuracy issues. In this study, 5 color 3D test charts containing 6 thickness-increasing colored stairs with 13 specific colored bars were developed based on a thickness tunable printed layers design. At the same time, color differences and surface images of tested charts with specific layers were both captured under standard conditions. Results demonstrated that the chromatic aberrations and Mean-SSIM values of color bars showed a slight downward trend as the stair thickness increases, while the linear correlations were not obvious. Combined with color SSIM maps analysis, color samples with small differences in color quality can be clearly detected to analyze the color reproduction performance of paper-based color 3D printers. This research provides new ideas for the development of powerful color 3D test chart to check the color reproduction performance of paper-based 3D printers and predict paper-based color 3D printing.

Historically, woven cellulosic paper has attracted scientific attention for its unique advantages of porosity, low cost, versatility, disposability, biocompatibility, and inherent capillary flow [1, 2, 3]. In the seventeenth century, the invention of litmus paper, a pH indicator paper treated with a natural water-soluble dye obtained from lichens, was the first milestone demonstrating the significant potential of paper as a substrate material in analytical applications [1, 4].

The future of sensing and diagnostic devices for developing countries should be, as described by the World Health Organization (WHO), ASSURED: Affordable, Sensitive, Specific, User-friendly, Rapid and robust, Equipment free, and Deliverable to end users [1]. Paper-based sensors using colorimetric approaches are significant because they feature all key factors for ideal diagnostic devices. Conventional sensors, such as enzyme-linked immunosorbent assay (ELISA), are bulky and complex, requiring different functional blocks including transducers, processing units, detection units, and so on, which can delay sensor response [2]. Current technology based on colorimetry is concerned with the miniaturization of size, decreasing cost, permitting in situ use, and achieving freedom from additional instruments. Moreover, colorimetric sensors can be used for the instantaneous detection of analytes (e.g., protein, DNA, small molecules, etc.), by showing a visually detectable color change [3]. The color change or intensity is proportional to the analyte concentration, which indicates that colorimetric assays have capacities beyond binary sensing.

As paper has become an important part of global consumption, there is a necessity to find a balance between production and resources, when an increase in paper production has been observed within past decades. Diverse technologies are being used for paper production one of them being use of enzyme of microbial origin for better bio-pulping and bio-bleaching results along with easier fibre grafting and de-inking. Though there are many applications of such enzymes in this industry, they are still at early development stage. The most essential feature of using enzymes is that it helps in eco-friendly bio-bleaching of pulps. Xylanase, cellulose free xylanase and occasionally use of laccase are the enzymes being used as a better alternative for reduction in the amount of environmental-polluting chlorine. Endo-β-xylanases, belonging to xylanases, is the key enzyme required for the enzymatic bleaching. The main purpose to adopt such techniques is to reduce the requirement of chlorine containing chemicals for bleaching. Enzymes further increases the pulp brightness making it easier for the industry to go chlorine free, along with improving fibre quality, producing better quality fibre. We will now discuss about the pulp industry and how xylanase enzyme helps in improving the productivity and revolution of the industry in detail in this chapter.

In recent decades, advances in pulp and paper making involve immense chopping of trees, which consecutively leads to clearing of forests. Rising contest for provisions of wood fibers combined with progressively increasing expenses of wood has caused increased attention in the consumption of agricultural residues for pulp and paper manufacturing in the developed and developing nations. The utilization of natural cellulosic plant residues in pulping and paper production might be necessary since it avoids the necessity for clearance, which presently rises the expenditures of farming and induces ecological deterioration by toxic wastes. The significant goals of this chapter are threefold; (1) to examine the requirements for utilization and improvement of natural cellulosic plant fibers in pulping and paper making; (2) to recognize the various issues related with the utilization of natural plant residues in pulp and paper production, and remedies accessible; and (3) to examine the prospects of various natural cellulosic plant fibers for pulp and paper making and recognize the potential of using pineapple leaf fiber as an alternate source materials in pulp and paper manufacturing mills. Better mechanical characteristics, a renewable resource, and reasonable price are some of the leading aspects that make great prospective of pineapple leaf fibers to be employed as a replacement for conventional wood fibers in pulp and paper production industries.

Pulp and paper industry effluent is constantly associated with degraded and dissolved lignin (≈90%) which creates a serious pollution and toxic effects due to its less biodegradability and high concentration of colour. Hence, lignin in pulp and paper mill effluent is essentially treated prior to its final discharge into the environment. Many physicochemical treatment methods such as electrocoagulation, incineration, ozonation and ultrafiltration are available to handle the lignin waste in black liquor. However, usage of these methods is limited in small- and medium-scale industries due to large minerals, acids and energy consumption which make the technology unsatisfactory. Therefore, there is a need for more practical and economically viable method for treatment of lignin in black liquor especially for small-scale industries. Microbial treatment can be a more suitable and viable technique. In microbial treatment, a wide variety of microbes such as fungi, algae and bacteria have been implicated for lignin biodegradation and decolourization of pulping effluent. Hence, lignin biodegradation by potential indigenous ligninolytic strains could be more suitable due to their biochemical versatility and immense environmental adaptability. This chapter describes introduction to pulp and paper industry effluent, different existing treatment methods and issues and biodegradation of lignin-rich effluent by indigenous ligninolytic microbes.

Pulp and paper mills are considered as core sector industries and are the fifth largest contributor to industrial water pollution globally. During the processing of lignocellulosic material for paper production, a large quantity of brown/black effluent is generated with high BOD, COD, potentially toxic chlorinated compounds, adsorbable organic halides (AOXs), suspended solids, tannins, resin acids, sulfur compounds, and lignins. Lignin and chlorinated derivatives (e.g., ligno-sulfonic acid, resins, phenols, and hydrocarbons) released during pulping and bleaching operations impart dark color and toxicity to the effluent. The discharge of untreated/partially treated effluent into the receiving water bodies results in an increase in BOD/COD, slime growth, thermal problems, scum formation, discoloration, loss of aesthetic quality, and toxicity to the aquatic life. The toxic chlorinated organic compounds and hazardous metals present in wastewater pose serious human health risks through long-term exposure via drinking water and/or through consumption of fish that can bioaccumulate certain toxic metals from the food chain. Hence, several attempts have been made to degrade/detoxify pulp and paper mill wastewater. Keeping in view several disadvantages associated with conventional physicochemical treatment methods, biological methods have drawn the significant attention of the researchers as safer and cost-effective technologies for the treatment of pulp and paper mill effluent. In aforesaid context, present chapter encompasses the problem of environmental contamination due to pulp and paper mill effluent and its adverse effects on the environment and human population. It also highlights novel, energy, and cost-effective environment-friendly technologies to treat pulp and paper mill effluent.

Health and environmental impacts of fossil fuel utilization have urged the need to find alternative bioresources that could act as renewable source of energy called as biofuels. Bioethanol is currently the most produced biofuel. First-generation feedstocks result in food–fuel competition; hence, second-generation feedstocks are mostly preferred, which consist of lignocellulosic biomass, but they have a costly and difficult pre-treatment techniques that will add up to the total cost of the production of bioethanol. Pulp and paper industry is one among the fast-growing industries which simultaneously generates large amount of residues which are disposed in landfills. These residues are wastes from paper making that is rich in monosaccharides or even polysaccharides besides lignin and hence can be used as a proper feedstock for bioethanol production which requires lesser pre-treatment. It acts as zero or negative feedstock cost and has the potential for the production of cellulosic ethanol. The aim is to cover the recent developments and key challenges for the successful introduction of paper mill sludge in the bioethanol production industry. The covered subjects are sustainability of biofuel, paper-making process, Indian scenario of paper mills, and environmental impacts of paper mill sludge along with the pre-treatments employed on paper mill sludge for bioethanol production.

The use of chemicals in the bleaching process is the traditional bleaching process and generated vast amounts of toxic materials in the form of bleach effluents of chemicals used for bleaching. Therefore, the generation of high lignin content incorporation with chlorine-based oxides is responsible for the environmental issue as reproductive damages in humans and aquatic animals. In this chapter have been highlighted some modified bleaching techniques for the mitigation of toxic chemicals released from traditional bleaching process. Hence, usage of enzymatic bleaching method instead of conventional bleaching method is a revolutionary bleaching concept in paper mill. This chapter emphasizes the sustainable utilization of bio enzymes in the pulp industry, along with its efficiency and future challenges. Thus, enzymatic bleaching technique is most significant and eco-friendly as well as cost effective than traditional technique. The enzymes xylanases and laccases are showed the most efficient and cost effective process either alone or in combination with each other. Therefore, laccases play a significant role in the presence of mediators such as ATBS and HBT, etc.

Pulp and paper industry is one of the important industrial sectors in India, which consume huge amount of water in the papermaking process. The final wastewater is often characterized by high color, BOD (biochemical oxygen demand), COD (chemical oxygen demand), AOX (adsorbable organic halides), SS (suspended solids), TDS (total dissolved solids), phenolics, heavy metals, and plant components like lignin, tannin, resin acids, and extractives. Finally, these compounds are reached to aquatic and terrestrial ecosystem and causing serious environmental pollution. The generated wastewaters are treated by conventional biological treatment like activated sludge process (ASP) after primary treatment. Biological treatment of paper mill effluent significantly removes BOD, COD, SS, and also COD, but it is insufficient in removal of lignin and chlorophenols due to its low biodegradability and toxicity. During last few decades, several physical and chemical methods have been developed with the aim to use as pre- and posttreatment method. However, application of this technology at large scale is costly. Therefore, bioremediation which involve the use of pollutant-specific microorganism for wastewater treatment has been considered as cost-effective and eco-friendly treatment method. Thus, this chapter provides the updated information on paper processing and wastewater generation and their characteristics and toxicity. Processes based on physicochemical and biological methods for the treatment of pulp and paper mill wastewater have been also discussed.

With the expansion of the printing market and the need of industry restructuring, the improvement of printing product quality can be a key to the industry development. What’s more, the pros and cons of paper surface properties is the important measure of its quality. Researching the correlation between surface properties of paper, such as whiteness, smoothness, gloss, ink absorption, and printing tonal gradation is particularly significant for the improvement of paper quality. Through the test and analysis on the surface properties of different types of paper, the research on the influence of paper surface properties to the printing tonal gradation, and the use of gray relational analysis method, we calculate the influence degree of the surface properties such as surface gloss, whiteness, and efficiency factors to the printing tonal gradation. After a series of experiment and data processing, we draw the conclusion that in the digital printing machine case, for offset paper, as for the influence degree of paper surface properties to printing tonal gradation, the comprehensive ranking from highest to lowest is gloss, whiteness, ink absorption, surface efficiency and smoothness. However, for coated paper, the comprehensive ranking is surface efficiency, gloss, whiteness, ink absorption and smoothness.

Paper and pulp industry is water intensive and has a greater impact on aquatic, surrounding environment and public health. Minimum fresh water usage and emphasis on waste-water recycling/management are key factors for the growth of this industry. Concentration of impurities and toxic substances in processed water mainly limits recycling benefits because it adversely affects processes, equipments and paper quality. Organic wastes are mostly processed through biodegradation and bioremediation using anaerobic digestion (methane production) followed by aerobic digestion (inducing sludge processing). Although, biological processing is economical and eco-friendly but treatment of wastes including non-biodegradable recalcitrant compounds mostly limits its broad application. Therefore, many other innovative approaches have been exploited to tackle this problem. Advanced oxidation process (AOP), novel biodegradable polymeric flocculants, electrocoagulation and photocatalysis etc. are used as alternative ways to facilitate detoxification and recycling. In this chapter, we emphasised and provided an in-depth knowledge about the various wastewater treatment strategies linked to paper and pulp industry.

The threat of increased industrial accidents and extreme explosive activities demands protection of structure against blast loading. The pressure-impulse (P-I) diagrams also called iso-damage diagrams indicates damage level in a structure. In the present investigation, P-I diagrams for sandwich panel with steel face and back-sheets and paper honeycomb core are developed. The numerical approach is used to get series of pressure and impulse points for particular damage level. The damage criteria considered in present study is maximum back sheet deflection. However, core crushing is limited to 5 mm in this investigation for the uniformity of the analysis. Sandwich panel with paper honeycomb core is modelled in ABAQUS/Explicit® and blast load is applied for range of loading i.e. impulsive, dynamic and quasi-static using CONWEP formulation. Based on the analysis performed, P-I diagrams are developed for damage levels of 1%, 1.5%, 2%, 2.5% and 3%.

There were totally 1749 scientific papers published in proceedings of conferences on Man-Machine-Environment System Engineering (MMESE) during 1993 to 2020 since the MMESE was founded in 1981 by guidance of Xuesen Qian with system engineering thought. The results were found by data analysis that 27.90%, 10.29%, 9.26%, 9.89%, 11.78%, 2.69%, 20.01% of the papers were in the subdomains of MMESE named as the Man Character, the Machine Character, the Environment Character, the Man-Machine Relationship, the Man-Environment Relationship, the Machine-Environment Relationship, the Overall Performance of Man-Machine-Environment System in addition to 7.66% under title of Theory and Application Research and 0.51% of Pandect. In the last decade, MMESE went much faster especially in 5.75% growth on the Machine Character, and trend was better and better for internationalization with efforts of main contributors such as the first authors of the papers, publishers, and MMESE committee of SESC.

Paper-based sensor is a new analytical technique applicable in healthcare monitoring, environmental monitoring, food quality control, etc. Currently, these technologies are drawing great attention due to ease of fabrication, cost-effectiveness, and their simple, portable, and disposable nature. The inherent qualities of paper, such as availability in large quantities, cheap, lightweight, and biodegradability, are being exploited to develop sustainable devices. The application of paper as a substrate material in litmus paper was dated back to seventeenth century. The semiquantitative detection of glucose in urine and immune chromatographic paper test strips for pregnancy test kits are examples of paper-based sensing devices. Today, microfluidic paper-based sensors with advanced designs involving complex 3D geometrics for handling multiples analytes are under investigation. It is foreseen that advancements in the fabrication and analytical techniques will help in improving the accuracy and sensitivity of paper-based sensors. Different types of detection approaches used in microfluidic paper-based devices are colorimetry, luminescence, electrochemical detection, fluorescence, and surface-enhanced Raman scattering.

Paper-based devices has gained widespread applications with its unique properties like affordability, rapid detection, user-friendliness, sensitivity, specificity etc. These low costs devices are considered as powerful tool for point of care testing because of the inherent microfluidic nature, disposability, flexibility, and ability to store and analyze the sample. With the advancement in fabrication techniques and the requirement of real-time diagnosis and health monitoring, paper-based devices also emerged in the field of wearable diagnostic applications. Depending upon the biocompatibility, paper-based devices are integrated with different materials to be used as in vitro and in vivo wearable devices. In this chapter, we will cover the principles of the paper-based devices along with the evolution of the wearable devices and also briefly review the recent development in the wearable diagnostic devices.

Condenser bushings are considered the Achilles’ heel of power transformers because most of the explosions of transformers relate to their bushings’ failure. Typical bushings monitoring methods measure the tan delta, power factor, and bushings’ capacitance in line frequency. In contrast, the dielectric frequency response (DFR) or the frequency domain spectroscopy (FDS) measures these parameters over a wide frequency range. Some studies have revealed that the FDS curves have distinguished data that help detect bushing failures in their onset. However, there has not been a standard FDS interpretation method. Human experts’ opinions play a considerable role in the interpretation process. In this paper, a finite element method model of a 96 kV oil-impregnated paper bushing is built with different OIP moisture content. The FDS test is simulated under these moisture levels. Seven two-array and six one-array statistical indices are introduced to interpret the FDS results. The results have shown that all six one-array statistical indices, apart from average deviation (AVEDEV) and standard deviation (SD), can be perfect indicators of moisture levels of the OIP. Moreover, they can be used to assess the moisture content of the OIP bushings, and human errors are eliminated using this method.

Due to the non-linear and highly volatile nature of the Stock market, it has become a very challenging task for researchers to make accurate predictions. Improving the efficiency of predictions has become the main goal of many researchers. From the traditional approach of working with historical dossiers to using the latest machine learning and deep learning techniques, researchers are busy finding out the best possible ways of accurate predictions. Many new models are suggested that can make good estimations of stock prices. Investors are interested in knowing both the immediate next-day prices and as well as future share prices in the long run. This paper inspects the algorithms and techniques that are useful for making accurate predictions.

Phyco-remediation of wastewater through microalgae is a promising area; hence, the study focused here is to analyse the growth and biochemical constituents of waste-grown microalgal strain collected from municipality wastewater of Baripada and industrial effluents of Emami Paper Mill, Balasore. Effluent samples were collected and brought to laboratory, and physicochemical parameters of the effluent were characterized. A total of seven microalgal taxa comprising of five cyanobacteria (single species of each genera Scytonema, Leptolyngbya, Pseudospongiococcus, Hapalosiphon, Dolichospermum) and two green algae (i.e. Scenedesmus sp. and Oocystis sp.) were isolated and selected for phyco-remediation potential. The strains were inoculated in different dilutions of effluents, viz. 25%, 50%, 75% and 100%, taking the culture media as positive control. The cultures were maintained at controlled condition, i.e. continuous light of 2400 lux with 25 °C temperature. The growth of algae; pigments such as chlorophylls, carotenoids and biliproteins; total carbohydrate and protein content were determined regularly using spectrophotometer up to 20 days. Scenedesmus sp. and Dolichospermum sp. showed maximum growth in 75% of diluted effluent, but in Hapalosiphon sp. it is 50% except Scytonema sp. which had a maximum growth in 100% effluent. Leptolyngbya showed comparatively maximum response of growth in control to the effluent. The macromolecular content and pigment contents also revealed the same trend as growth for the entire test organism.

Pulp and paper industries are one of the major sources of environmental pollution that discharge enormous amount of wastewaters containing recalcitrant pollutants into the environment. Wastewaters have high biological oxygen demand (BOD), chemical oxygen demand (COD), total solids (TS), phenols, lignin and its derivatives. High strength of wastewaters containing dark colour and toxic compounds from pulp paper industries causes serious aquatic and soil pollution. On terrestrial region, pulp and paper mill wastewater at high concentration reduces the soil texture and inhibits seed germination, growth and depletion of vegetation, while in aquatic system, it blocks the photosynthesis and decreases the dissolved oxygen (DO) level which affects both flora and fauna and causes toxicity to aquatic ecosystem. The high pollution load from pulp and paper industrial wastewater gradually increases, and hence, there is a need for adequate treatment to reduce these pollution parameters before final discharge into the environment. Thus, this chapter gives detailed information about sources, characteristics, toxicity and physico-chemical and biological methods for the treatment of pulp and paper mill wastes and wastewaters.

The pulp and paper industry produces large quantities of bleaching effluents that are highly colored and contain large concentrations of organic matter. Most of these contaminants mainly lignin and organic matter are difficult to eliminate by conventional wastewater treatment processes. Advanced oxidation processes (AOPs) are used to convert non-biodegradable organic matter to harmless substances. AOPs depend on the production of hydroxyl radicals (.OH) with a redox potential of 2.8 V. These radicals undergo various oxidation processes by reacting with oxygen and convert the organics to CO2 and H2O. The waste effluent for the present study was collected from bleaching process of pulp and paper industry located in Karnataka. Batch experiments were carried out on the effluent using Fenton’s oxidation process. Various doses of FeSO4·7H2O and H2O2 30% W/V were used. All reactions were carried out in triplicate under atmospheric pressure in a dark place, to avoid direct attack of sunlight, with continuous shaking in a water bath maintained at 130 rpm at 30 °C. Lignin concentration was measured using spectrometric procedure at a wavelength of 700 nm. The optimum pH value of 4 was observed. The optimum condition for the maximum removal of COD and lignin was pH 4, H2O2 dosage 2 mg/mL, FeSO4.7H2O 1.8 mg/mL and reaction time 30 min wherein COD removal efficiencies of up to 88% and lignin removal efficiencies of up to 92% were achieved. Hence, Fenton’s oxidation seems to be an efficient and economical treatment technique for pulp and paper mill effluent.

Organic–inorganic and polymer-based non-volatile resistive switching memory devices have gained increasing attention because of their excellent data storage capacity, flexibility, low power consumption, durability and widely used in modern electronics. Among the materials, 2D layered nanomaterial and polymer nanocomposites have attracted increasing attention because they can easily be integrated into electronic and optoelectronic devices due to their easy fabrication process, high storage capacity and promising structural properties. Fabrication of bistable memory devices based on organic–inorganic nanohybrid with charge blocking materials and polymer nanocomposite has been broadly elucidated for their extraordinary material properties. Recent enhancement in flexible memory devices based on organic–inorganic semiconductor dispersed in ferroelectric blend polymer has been investigated thoroughly in this review paper. Recent advancement in 2D layered material, ferroelectric polymer and the development of non-volatile memristive devices is extensively explained to understand their importance in flexible devices. Outstanding memory characteristics such as current on/off ratio, Vset, Vreset retention time, endurance of nanohybrid embedded polymer nanocomposite are also discussed meticulously. Next-generation memristor devices based on 2D nanomaterial and ferroelectric polymer with high speed and high density for developing neuromorphic computing system have been demonstrated.

The 3D printed parts made by using the additive manufacturing (AM) process are presently high in demand due to many advantages. This includes well-known features such as the cost-effective method of producing customized parts made of thermoplastic material and having a shorter lead time for a wider range of applications. However, it has also a few limitations like poor dimensional accuracy and resolution. Thus, this technology is not suitable for parts having interior details. So, it is very much essential that the parts being produced using this technology must be characterized and analyzed accordingly so as to increase their potential use in the present market. For this, a review paper has been made in order to study all the main characteristics affecting the rise in demand of parts. Several statistical and optimization techniques have been examined and reviewed. The optimal parameters corresponding to the specific characteristics causing an effect to a large extent have been observed.

To provide business cases and creative ideas for paper-based color 3D printing applied into the map industry, two map categories including military derivative map market and civilian derivative map market were introduced and analyzed with lots of famous applications. According to the statistic results, the 3D map printed by various 3D printing processes will be attributed to a promising 3D printing application market in China. At last, three flexible business modes were also offered with detail cases and usage development guides based on paper-based color 3D printing process.

Pulp and paper mills are highly complex and integrate many different process areas including Raw material preparation (wood debarking and chips preparation); Pulping (including cooking or refining, washing, screening and cleaning and thickening); Pulp bleaching (if required) and Paper making. The major unit operations are pulping, bleaching and paper making. Brief description of pulp and paper making process is presented in this chapter.

In the case of information overload of academic papers, the demand for academic paper recommendation is increasing. Most of the existing paper recommendation methods only utilize scholar friendship or paper content information, and ignore the influence of temporal weight on research interest, and hence they are hard to obtain good recommendation quality. Aiming at this problem, the method HNTA for academic paper recommendation based on the combination of heterogeneous network and temporal attributes is proposed. HNTA firstly constructs a heterogeneous network composed of different types of entities to calculate the similarity between two papers, and then the temporal attribute is introduced into scholars’ research interests which are divided into instant interests and continuous interests to calculate the similarity between scholars and papers. Finally, by weighting the above two similarities, the purpose of recommending papers to scholars is achieved. Overall, HNTA can not only comprehensively utilize both relationships of scholars and the content information of papers, but also it considers the impact of the temporal weight of scholars' research interests. By conducting comparative experiments on the data set of the real academic social network: SCHOLAT, the results show that HNTA performs better than traditional paper recommendation methods.

Analysis of images with deep learning and machine learning has recently show more accuracy in medical image processing. The paper review the major machine learning methods is used for the extraction of retinal fundus image. It describes how hardware has been modified according to time for retinal eye segmentation that device is helpful for the environment and also useful for humans The algorithms used for image extraction, clear and noise-free Images of different color scales are used to improve image quality. The paper gives a review of how researchers and scientists have been trying different methods to improve vessel segmentation in the future.

This paper focuses on the comparison of various methods and quantity of electrical power generation in the countries as Turkey, United Arab Emirates and Germany including sources of electricity and comparison with India is highlighted. In this paper, there is an outlook of various power generation techniques adopted, and the amount of the power with the help of various means are highlighted and put for the immediate comparison. It is also discussed that a brief outlook of power generation and their comparison show the significance of the geographical, climatic and political situations emphasis on the methods of their power generations, respectively. In different countries, the nature of electrical power generation has shown with graphical form on the account of percentage utilization of energies in recent year. Various power generation methods like thermal, wind, solar, gas, nuclear, hydro electricity, other renewable energy sources, etc., are discussed in details. A detailed comparison of cost of generated power and cost of a single unit per person according to the respective country has been discussed. By knowing this, it may be analyzed that different sources of power generation can be compared with the power generated in India. With the help of this, analysis and comparing to the utilization of different types of sources for the purpose of generation of electricity by different countries can be understood including source for production of electricity as compared to renewable source of energy.

In this paper, we discuss, any work must be reproducible in order to influence research and contribute to our profession's knowledge. Nevertheless, studies show that 70% of university laboratory work cannot reproduce. Reproducible work with not always available data sets or procedures not clearly specified is uncommon in software engineering and complex specifications engineering. The lack of reproducible research prevents development, which means that researchers must replicate a scratch study. The RE researcher will read conference papers, find empirical articles and then review data that can (if available) be replicated in the empirical report. This paper deals with two aspects of the problem and discusses in RE articles, RE documents and theoretical documents. In learning and development of an automatic classification in RE and empirical document identification, recent conference papers and RE documents have been utilized. They use the ERRC approach for performing supervised lecture classifications using natural language therapy and machine learning. Our software is equated with a fundamental keyword approach. We study the paper collections from the engineering conference sponsored by IEEE on Requirements and the International Software Testing and Evaluation Symposium sponsored by IEEE in order to test our process. In all but a few cases, we examine that the procedure of ERRC worked superior than the reference procedure.

Uniqueness is inherited in every individual. Each individual links with another individual forming some social organization. Social organization in common places some trends or norms that influence each of its members. Thus, each individual ascribes common liking or behavior. Analysis of this behavioral pattern leads to the development of a recommender system, which helps to predict and determine the preference an individual ought to opt. Recommender system proves significant in e-commerce marketing strategies. Besides, recommender system finds its application in academics, health, entertainment, etc. This paper proposes a probabilistic model research paper recommender system using naive Bayes algorithm. The originality this paper incorporates is to classify the instances of the target paper into attributes such as title, reference, citation, calculated conditional probability and label them into recommendation or not. Deploying naive Bayes classifier, the evaluation of the current research is done generating the confusion matrix and hence calculated accuracy, precision, recall and F-measure. We have achieved an accuracy of 90.47%.

The paper presents a model that will predict the acceptance of the paper for a particular conference. The model is designed for the conferences, which accept researches done researches in the Machine Learning domain. The dataset that is used to develop this model is the ICLR 2017 (International Conference Of Learning Representation). The model gives its prediction based on extracted features. The features that most of the conferences consider are Number of References, Number of Figures, Number of Tables, Bag of words for ML related terms, etc. Some more features are taken into consideration to give better results such as Length of Title, Frequency of ML related words, Number of ML algorithms, Average length of sentences. The model is trained on the above-mentioned dataset, which contains 70 accepted and 100 rejected papers. For the prediction, different Machine Learning algorithms are used. The model is trained by applying algorithms such as Logistic Regression, Decision Tree, Random Forest, KNN, and SVM. The comparative study of different algorithms on the dataset gives the result that Decision Tress works effectively by providing 85% accuracy.

To study the impact of extraction process parameters on Baume and solid content of extraction solution in paper-process reconstituted tobacco production, artificial neural network and ensemble learning methods are utilized to build the prediction models for the extraction process in the paper. The prediction models describe the influencing factors such as amount of adding water, extraction water temperature, feed mixing time, squeezing time, centrifuge frequency, squeezing dryness and screw pump frequency on Baume and solid content of extraction solution. It is found that the ensemble learning model is better than the artificial neural network model by the comparison of the prediction results of these two models. The influencing parameters of the solid content and Baume are optimized by genetic algorithm based on the ensemble learning model to improve the product quality of the extraction solution. The experimental results show that the proposed models are helpful to improve the product quality of the paper-making reconstituted tobacco.

Mathematical average of word embeddings is a common baseline for sentence embedding techniques which typically fall short of the performance of more complex models such as BERT and InferSent. There has been significant improvement in the field of sentence embeddings and especially towards the development of universal sentence encoder that can be used for transfer learning in a wide variety of downstream tasks. Academic paper retrieval systems are widely used in academic institutions to store and categorise scientific papers and find connections between them using citation links, but these methods do not account for the content of the papers. For unsupervised clustering of these papers, a new approach of sentence embeddings is proposed using concatenated power means sentence embeddings and centroid sentence embeddings. The sentence embeddings so created are clustered using K-means clustering algorithm. The results show a clear increase of 47.94% in cosine distance of nearest papers using concatenated power means sentence embeddings with respect to baseline centroid embeddings for the highest performing GloVe models proving that the computationally inexpensive P-Means clustering sentence embeddings can be used for unsupervised clustering of scientific research papers using their abstracts.

Solid waste generated from food mainly contains various organic compounds such as carbohydrates, lipids, and proteins. These biodegradable wastes mainly released from food, agricultural, household, and hospitality segments. The waste material produced from food is frequently burned or discarded into open areas, which may also become a source of many severe health and environmental problems. The management of waste material generated from food is done by transform into various value-added products, like phytochemicals, food supplements, bioactive materials, dietary fibers, safe to eat and important oils, biofertilizers, biofuels, and single-cell proteins (SCP). Every year, enormous amounts of solid waste (sludge) from the wastewater treatment of paper manufactures have been created. They might be dumped into the landfill if they have heavy metals lower than the standard of the Department of Industrial Work and the Ministry of Industry. Nowadays, the area of landfills is quite limited whereas solid waste has been accumulated. In the case of waste from agriculture biomass, a few of them are mixed with soil or applied as ingredients of the fertilizer. On the other hand, the value of the wastes is fairly low. Hence, the manufacture of value-added products, such as furniture cardboard, and packaging and the agricultural product from solid wastes could be useful. This chapter is mainly focused on the modification of the solid waste from agriculture, paper, and food by searching the suitable technology for producing value-added products such as biofuels, bioenergy, agricultural products, phytochemicals, bio fertilizers, enzymes, and single-cellproteins.

Renewable or recycled materials have been widely used in the construction industry to achieve a sustainable target. As a kind of short cellulose fibre, a massive amount of waste paper fibre was generated annually from the industrial and construction sectors. However, the research on the use of waste paper fibres in construction/building materials is limited. The feasibility and sustainability of papercrete used as a building material were investigated based on a Life Cycle Assessment (LCA) method by analysing its characteristics compared to four production scenarios. LCA results demonstrate waste paper fibres used as the cement substitute in concrete benefit to reduce the environmental impact compared to traditional disposal.

Renewed interest for volatile organic compound (VOC) sensors using nanomaterials are increasing due to several limitations of existing commercially available sensors for healthcare, food quality, and environmental applications. A disposable, flexible, and room temperature, paper-based formaldehyde sensor has been developed using graphene quantum dot ink as the sensing material. The PEDOT:PSS conductive ink acts as an electrode on the porous paper substrate with graphene quantum dot ink as sensing material making the device novel, low cost, and potential candidate for large area roll to roll solution process-able formaldehyde sensors fabrication. The sensitivity is measured for a concentration varying from 7 to 20 ppm exposure of formaldehyde at ambient temperature at dry air condition. The sensor device shows a sensitivity of 0.26% at 15 ppm HCHO. The p-type GQDs reveal a resistance increment of the sensing film in presence of reducing gas HCHO, which is explained using charge transfer dynamics between sensing film and HCHO molecules. The finding may lead to new opportunities in flexible formaldehyde sensors operating at room temperature for healthcare applications.

Today in India about 40% of waste remains uncollected and hence is not recycled. This paper presents a novel solution providing a low-cost infrastructure in the areas where the traditional recycling chain of waste pickers—Kabadiwallah—Traders—Recyclers is broken because of absence of waste pickers. Such areas were identified for this work—big housing societies, eateries, food courts and canteens in various organization. To segregate all types of recyclable wastes (predominantly plastic, aluminum and paper) generated in these areas and further processing it to reduce its volume and storing it separately to send it to respective recycling plants is the basic functioning of the proposed solution. The increase in flow and speed of recyclable waste in the recycle chain are typical outcomes of the work.

Different types of paper and different basis weight of the same paper are selected in order to study the relationship between paper and color reproduction. Comparing with the reference data set, the influence of paper on color reproduction is analyzed from the color difference and color gamut. The results show that the colorimetric value of paper is more closer to the reference data set, the average color difference of patches is more smaller. The color reproduction ability of offset paper is weaker than that of other paper in the experiment. The color reproduction ability of different basis weight of the same paper is also slightly different. Therefore, the type and basis weight of the paper affect the color reproduction. In the process of printing proofs, it is considered that paper has a certain impact on color reproduction.

There has been growing concern regarding environment and human health owing to rise in environmental pollution. The paper industry released huge quantity of toxic effluent into the surrounding environment which inhibits the photosynthetic activity of aquatic biota, crop growth, etc., and thus has adverse effects on health, soil properties, and relative mobility in the soil profile. Hence, several aspects for management of pulp and paper effluent such as chemical, biological and mechanical treatments, recycling, monitoring, toxicology, environmental impact, and sustainable practice have been carried out. Further, various strategies need to be developed to determine the nature and extent of contaminants to natural resources. Presently, bioremediation methods using terrestrial and aquatic plants as well as microorganisms are considered more favorable for treating various industrial effluents. Although all bioremediation processes using microorganisms are appropriate for wastewater treatment, the integrated approach of yeast treatment process showed higher contaminant removal efficiencies with reduced energy costs and sustainable production of biodiesel. Thus, the utmost need of the hour is to synchronize environmental friendliness by using these methods over conventional methods owing to their reduced chemical and biological sludge production, more efficiency, and low cost.

Automation in every domain is today’s need, so in question paper setting also. The proposed system is automation of paper setting and identification of difficulty level of questions and question papers, which uses blooms taxonomy categorization to classify the questions in easy, medium and high categories. By using blooms taxonomy, the difficulty level of question can be identified, which is helpful in generating qualitative question paper. While categorizing questions, system uses natural language pre-processing techniques, which are understood by computer and also uses Latent Dirichlet Allocation algorithm. Based on paper setter’s requirement, paper setting is done; also, if user wants to check difficulty level of any question paper then this is also done by proposed system using NLP. The paper setting using difficulty measure is right benchmark for evaluating student’s efficiency. Automation of paper setting improves the speed, and difficulty level module improves the quality.

Metal additive manufacturing (AM) is also referred to as 3D printing and rapid prototyping. It is a revolutionary technology that produces 99.99% dense parts directly from 3D CAD data using the powder bed fusion process known as direct metal laser sintering (DMLS). Metal 3D printing is an ideal process for complex oil and gas components, custom medical guides, part-consolidated aerospace parts and tough functional prototypes. This paper reviews about the introduction to metal 3D printing. It covers the basic principles of SLM and DMLS, the key benefits and limitations of the technology.

With the development of artificial intelligence ushered in the third wave, how to develop artificial intelligence in the future has become the focus of attention. This article first introduces the basic situation of the development of artificial intelligence, and secondly analyzes the development context of artificial intelligence based on the data of the paper. It then analyzes the hotspots of artificial intelligence application according to the patent data, and finally, it summarizes and forecasts the development trend of artificial intelligence related fields.

In this paper, a comparison of the various methods and quantity of electrical power generation of countries like Australia, Argentina, New Zealand, Mexico, and India is highlighted. It is required to get the outlook of the various power generation techniques, and the amount of the power the other countries are generating. It has been also shown the power generation methods of different countries in graphical form and on the account of percentage utilization of energies in recent year. Various power generation methods like thermal, wind, solar, gas, nuclear, and hydro are been taken into consideration. With the help of this, we may analyze different sources of power generation and compare of the above four countries power generated and compared with the power generated in India. With the help of this study and comparison, it can be observed also that the utilization of different types of sources for the purpose of generation of electricity by different countries and how such countries are major dependent on thermal power source for the production of electricity as compared to renewable source of energy.

This precis presents a research concept paper for Leading Organizations of the Future: it specifies the primary reasons for undertaking the proposed study, states the problem to be examined, particularizes the research question, articulates the conceptual framework for the expanded literature review while flagging one key text, and justifies what methods of data collection and analysis would underpin next steps.