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

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

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

A biofuel cell that can generate electricity using only water is expected to be used as a new energy harvester for an emergency power supply. A new 4-series/4-parallel structured paper-substrate biofuel cell was prepared using a fuel supply paper preloaded with glucose and phosphate buffer salts. When a power generation test was conducted by supplying water to the fuel-preloaded paper, the paper-based biofuel cell produced an output approximately 90% (0.84 mW) of that obtained by supplying a phosphate buffer containing glucose as the electrolyte. The open-circuit voltage was 2.1 V, and an LED could be powered by simply supplying water to the cell without using a booster circuit.

Microfluidic paper-based analytical device has been fabricated and subsequently applied to determine the Vitamin C level of the non-seasonal fruit i.e pineapples, oranges, guavas, and apples in Indonesia. µPAD was prepared by creating a hydrophobic barrier on Whatman Chromatography paper No. 1 in a certain pattern printed using Xerox Colorcube 8580 DN-2. 0.05 µl of 2,6-Dichlorophenolindophenol was dispersed into a detection area on the µPAD devices prior to the addition of 0.2 µl of fruits juice samples. The barrier allowed the fruits juice to flow and alter the color of the reagents through a redox reaction. Vitamin C in fruit juice altered the color of 2.6-Dichlorophenolindophenol reagent into a pinkish color. The changing of the reagent color was then processed using Image J software to determine the RGB intensity level. The results showed that the average amounts of Vitamin C in pineapples, oranges, guavas, and apples are 0.05%, 0.05%, 0.08%, and 0.04% respectively.

FMEA is a widely selected tool for the application of machinery breakdown prevention. This research adopted FMEA technique to reduce and prevent the breakdown of the important equipment of a large commercial paper machine that has capacity of 200,000 tonnes per annum located in the Northeast area of Thailand. This research accomplished the improvement of preventive maintenance in other machines for rapid implementation and improved machine inspections. After implementation, the downtime of paper machine belonging to maintenance department responsibility reduced significantly 5 hours per month by average, machine availability, OEE, and MTBF increased 0.46%, 0.51%, and 10 hours respectively. The machine downtime has been on the downward trend.

Overall Equipment Effectiveness (OEE) is a method of measuring the usage effectiveness of the equipment. This method is known as an application of a Total Productive Maintenance (TPM) program. The ability to clearly identify the source of problem and it causal factors is the main advantage of this method since the improvement effort becomes focused. Pulp and Paper Industries is one of the manufacturing companies that produce dissolving pulp products (rayon fibre). Based on data from the fibre line department, for the period of January - July 2016, the production process of rayon fibre often experienced constraints due to the high downtime and losses in the pulp machine. This is caused of using production process equipment that had not operate optimally. It is important to find out the source of the problem and its causal factors before the company makes any improvement effort. This study aims to identify equipment losses and measure the achievement of OEE values in the pulp machine. The measurement result shows that the average of the effectiveness of pulp machine for the period of January - July 2016 was 74.01% and based on Japan Institute of Plant Maintenance (JIPM) the value has not reached the standard that is > 85%, however, there is still possibility for improvement. One of the loss factors that give the most significant effect on the overall equipment effectiveness of the pulp machine is the reducing speed, where it comprises 27.6% of the loss. One way to minimize the loss is by maintaining the actual speed of operation and maintaining wear on each pulp machine roll.

The Tea packaging paper sack process at PT. Perkebunan Nusantara VIII is done manually using human labor to lift paper sack weighing 40-60 kg. This condition makes it harder for the labor and increases the risk of Musculoskeletal Disorders (MSDs). In the existing condition, the RULA score is seven which have high risk of work accidents. To minimize the risk of MSDs, a proposed work tool is designed using the Ergonomic Function Deployment approach to produce ergonomic tools. The proposed work tool was developed with the ESHCE principle (Effective, Safe, Healthy, Comfortable, and Efficient) which became a variable in meeting the Ergonomic Function Deployment (EFD) approach. The research results showed that the proposed work tools could help workers in carrying out packaging activities with the decrease in the RULA value on the labor’s posture and could reduce processing time because it united all activities in the packaging area. So it can be concluded that the proposed work tools can reduce the risk of MSDs and can help workers to process the packaging of tea with minimum time.

The paper presents an information system for calculating the main paper-forming parameters of the pulp for given technological and design parameters of the grinding plant. The operation of the system is based on mathematical regression models of the processes that were obtained in the course of experimental studies of knife sets of various types. As input parameters in these models, the rotor speed, knife gap, concentration and degree of grinding of the mass are used. The output parameters are the grinding time, water retention capacity and average fiber length. The developed information system is a network web application with a modular structure. The modules are united by the main interface for the user. Each module implements a regression model for a specific type of headset. At the moment, the system has two modules for calculating the parameters of a percussion type headset and a headset with a curvilinear shape of knives. In the future, it is planned to add the ability to calculate indicators for headsets of other designs. It will also add the ability to solve optimization problems by finding the minimum or maximum value of the output parameters.

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

With the frequent interaction and cooperation between different disciplines in recent years, the number of research papers associated with multiple subjects increased. Correspondingly, some of the existing literatures belong to a single discipline, while others may simultaneously involve more than 2 subjects. At this time, the traditional single-label text classification is not conducive to people obtaining comprehensive and cutting-edge research papers in real life. Thus, it’s of great importance to conduct a multi-label classification of research papers effectively. This paper tests the performance of multi-label learning tasks with text data obtained from the Kaggle website. Firstly, lemmatization and Term Frequency-Inverse Document Frequency (TF-IDF) are used for feature extraction in the pre-processing part. The critical information of text content is statistically analysed, and text content is converted into numerical and high-dimensional vector space. As the traditional single-label classification algorithm is not suitable for the above problem, this paper adopts the Multi-Label K-Nearest Neighbour (ML-KNN) algorithm framework for classification. Experimental results report that the ML-KNN algorithm has achieved better results in multi-label text classification problems than a traditional multi-label algorithm, which proves the effectiveness of the ML-KNN algorithm for text data prediction with multiple subjects. Moreover, the work in this paper is analysed and summarized.

At present, green environmental protection has become a common topic of concern all over the world, and the principle of “low carbonization” is also the focus of designers in the design of paper children’s furniture in the future. How to implement the 4R principle into children’s furniture has become the most important issue for designers at present. This paper summarizes the design principles of children’s furniture, puts forward the design scheme of children’s furniture based on 4R principle, and forecasts the future children’s furniture market.

Various data and information in the form of documents will accompany every activity in an institution. The existence of a reliable management to create, store, record, distribute, and maintain documents is needed to generate dynamic information traffic. In addition, the application of document processing can reduce the use of paper in every activity of an institution which will indirectly reduce excessive forest exploitation. The purpose of this research is to analyse digitizing archive application as an integrated archive management application to reduce the use of paper in every activity of an institution. Qualitative descriptive methods was used as a research methodology. The result of this study based of the analysis of the digitizing archive application that has been done in terms of data and procedures can be concluded that digitizing archive application can reduce the use of paper as a document in various institutional activities.

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

A hypervisor is a computer programme or software that facilitates to create and run multiple virtual machines. It is also known as Virtual Machine Manager (VMM). Due to their popularity, it exploits the attack surface, because the Hypervisor code contains much vulnerability. Since the Hypervisor is a core element of any cloud computing service, it is always on the top priority of the attackers. There are many Software (open source) and Hardware-based Solutions are available in the market to monitor and control the hypervisor activities. This paper summarizes various types of attacks, vulnerabilities, security issues and challenges related to hypervisor and virtual machines.

Digital image processing has numerous applications in many sectors of the world. It expands from initial information registration into methods and thoughts combining pattern recognition, computer vision, and machine learning. The wide utilization has pulled in many researchers to integrate with a range of related specializations. This work gives a study of the latest development and theoretical ideas clarifying an improvement of computer vision particularly with pattern recognition and image processing, utilizing various regions of their field implementation. Digital image processing causes researchers to analyze images to get important data and comprehend information. It utilized a technique of multi-range implementation and huge information analysis. This work aims to focus on the latest studies related to image processing, pattern recognition, and computer vision. In this paper, Computer vision standard has been categorized into groups. For example, pattern recognition, image processing, and AI. Additionally, we give a short clarification of the forward-thinking data about the methods and their realization. This survey is restricted to computer vision, and more research can include detecting the conduct and properties of the object including people actions.

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

Natural Science Lessons emphasize providing direct experience, to develop competencies in order to explore and understand the natural surroundings scientifically. It is taught to equip students to have knowledge (knowing various ways) and skills (how to do it) that can help students to understand natural phenomena in depth. However, in the learning process, students still have difficulty understanding of the solar system. Inadequate media and conventional learning processes make students’ enthusiastic in participating in learning still low, and this makes learning not as expected by the teacher. In the solar system topic, the teacher expects students to be able to understand the position of the planets in the solar system in order and correctly. The strategy used in the learning process is to apply two-dimensional mind mapping using mase paper balls made of pulp and flashcards made by the teacher. The goal that is expected in the learning process using these strategies and media is to increase the effectiveness of student learning. The research was conducted using the R and D (Research and Development) method using the ADDIE model development method (Analysis, Design, Development, Implementation, Evaluation). Effective learning is active, creative and fun learning for students so that learning outcomes increase. Effectiveness is the level of success achieved from implementing a strategy and learning media, in this case measured from student learning outcomes. The results of the final assessment are in the form of a process assessment and a final assessment.

The results of CFD research using the VOF method with Open Foam open source are presented. In the process of study, we built a digital model allowing us to analyze and predict the process of interaction of the dampening solution with substrate (paper) surface in the measuring cell of the PDA ultrasonic device. Discretization of the area for calculation was created using the blockMesh utility. A block-structural hexahedral computational grid has been constructed. The computational grid area is presented in such a way that the number of cells increases in the direction of the paper sample. The visualization of calculations in the ParaView package coincides with the time intervals obtained on the PDA ultrasonic measuring device. The practical significance of the study lies in the realization of the possibility to evaluate the dampening solution parameters, to control the modes of its supply, taking into account the use of modern papers and printing systems.

Intelligent test paper generation belongs to an important research topic in the field of computer-aided education. Among them, Genetic Algorithm (GA), as an algorithm with high efficiency and performance, is widely used in the intelligent test paper generating system. But generally speaking, traditional GA always has some problems, such as local optimal solution and prematurity. The traditional genetic algorithm is improved in the aspects of the initial population, fitness function and some genetic operators to make it more in line with the requirements of intelligent paper generation, improving the efficiency and success ratio.

Image mining is a method of searching and discovering the valuable information and knowledge from a set of huge image data. Image mining essentially depends on the data mining, digital image processing, machine learning, image retrieval, and artificial intelligence. Image mining is a process which is conducted to extract the hidden information such as image data and the additional pattern that could not be observed from the image. The main problems could face the mining of the collected images can be summarized in two main points: first is the image must be suitable for the mining process and second is the image’s chosen objects and features in order to be treated to extract the most effective route to save the time, and to save the effort. This paper is a survey presents the steps of the image mining process and represented an intensive view on using the image mining to the classify the brain tumors. In addition, it’s proposed a general scheme to accomplish the processes and to analysis the latest techniques which have been used to classify the brain tumors with comparison to the training groups and the amount of accuracy that obtained from the analysis. In addition, the paper compares the relevant and most recent published literature. The high published accuracy claim to be 98% which was obtained using the Deep convolutional neural network (DCNN).

We have investigated the problem of underwater hazy image enhancement and restoration in this paper studied. Underwater image processing has several applications in the field of oceanic research work and scientific applications such as archaeology, geology, underwater environmental assessment, laying of long distance gas pipelines and communication links across the continents which demand geo-referential surveying of the oceanic bed and prospection of ancient shipwreck. There are many difficulties for undersea optical imaging. To submerging a camera in underwater enough space is required. The maneuvering of the camera with the help from remote place or in person at the site is likewise a complex task. However, the major challenge is imposed by underwater medium properties. Underwater haze image enhancement has gained widespread importance with the rapid development of modern imaging equipment. Though, the contrast enhancement of single underwater hazy image is a cumbersome task for scientific exploration and computational application. At extreme depth, because of attenuation in light propagation, the underwater images are susceptible to inferior visibility.

In the previous decade, the mixing between chaotic supposition and cryptography frames considers a significant field of data security. Chaos-based image encryption is given a lot of attention in the exploration of data security moreover a great deal of picture encrypting calculations have been proposed concerning chaotic maps. Because of some inveterate highlights of media like information limit and high information excess, the encryption of images not quite the same as that of texts; accordingly it is hard to deal with them by conventional encryption strategies. This paper presents a short review of robust digital watermarking systems that used chaotic algorithms such as Logistic, Tent, Baker, Hyper, Fibonacci, and Arnold maps for encryption of the data presented in several years.

Keywords are used to facilitate searches, inaccurate keyword determination, which can result in searches for journals that do not match the intended title. To overcome this, it is necessary to implement a keyword search in the abstract using deep learning methods from a journal to produce the right keywords that will distinguish journals from one another. The purpose of this study is to implement a keyword search system in abstracts using the Bidirectional Encoder Representations from Transformers (BERT) method as an abstract word search system that produces keyword answers that have context according to the desired keyword results. The results of this study get optimal results in the epoch 500, and from these results using a dataset with of 444 training data and 10 test data for testing.

The paper cutting machine using eye-mark sensor is used to cut the papers in equal and accurate dimensions. The main principle of this method is used to reduce the human power and time consumption by eliminating the wastage of the raw materials. Eye-mark sensor is used to sense the colour present on the paper and make the machine to cut on the place where the paper is marked. It has a transmitter and the receiver which the sends the light signal through transmitter and it senses the colour. The sensed signal is received through the receiver. When the signal is received the roller motor is stopped and the cutter motor is started. The cutter motor completes its rotation and again the paper roll is feed. This system can be applicable for paper cutting industry and it is a low cost solution which increases the production process.

Musculoskeletal Disorders (MSD) is one of the ergonomic risks due to manual activity, non-neutral posture and repetitive motion. The purpose of this study is to measure risk and implement ergonomic interventions to reduce the risk of MSD on the paper pallet assembly work station. Measurements to work posture are done by Ovako Working Posture Analysis (OWAS) methods and Rapid Entire Body Assessment (REBA) method, while the measurement of work repetitiveness was using Strain Index (SI) method. Assembly processes operators are identified has the highest risk level. OWAS score, Strain Index, and REBA values are 4, 20.25, and 11. Ergonomic improvements are needed to reduce that level of risk. Proposed improvements will be developed using the Quality Function Deployment (QFD) method applied with Axiomatic House of Quality (AHOQ) and Morphological Chart. As the result, risk level based on OWAS score & REBA score turn out from 4 & 11 to be 1 & 2. Biomechanics analysis of the operator also shows the decreasing values for L4-L5 moment, compression, joint shear, and joint moment strength.

In today’s competitive world, companies are required to increase productivity and produce high-quality products while managing their operational efficiency. This leads a firm to involve its performing suppliers by taking into account multiple factors. For small and medium-sized enterprises (SMEs), despite its importance, supplier selection is less considered. In this study, a case study for evaluating supplier selection factors in a small-medium scale paper manufacturer in Indonesia is demonstrated using the fuzzy best-worst method (fuzzy BWM). The BWM method that provides a structurally consistent factors comparison through the best and the worst criteria is extended using a fuzzy set to address the ambiguity from decision-makers’ judgement. The evaluation includes five supplier criteria: service, flexibility and delivery, reputation, quality, and purchasing cost. To determine the fuzzy criteria’ weights, the nonlinearly constrained optimization problem was introduced. The result indicated that the best and the worst criteria were respectively service and purchasing cost, while the service criterion was weakly crucial than quality. Besides, the Fuzzy BWM has also provided high consistency in the comparison. The optimal weights determined in this study can be applied for ranking suppliers for further attempts.

Breast Cancer is most popular and growing disease in the world. Breast Cancer is mostly found in the women. Early detection is a way to control the breast cancer. There are many cases that are handled by the early detection and decrease the death rate. Many research works have been done on the breast cancer. The Most common technique that is used in research is machine learning. There are many previous researches that conducted through the machine learning. Machine learning algorithms like decision tree, KNN, SVM, naïve bays etc. gives the better performance in their own field. But now days, a new developed technique is used to classify the breast cancer. The new developed technique is deep learning. Deep learning is used to overcome the drawbacks of machine learning. A deep learning technique that is mostly used in data science is Convolution neural network, Recurrent neural network, deep belief network etc. deep learning algorithms gives the better results as compared to machine learning. It extracts the best features of the images. In our research, CNN is used to classify the images. Basically our research is based on the images and CNN is most popular technique to classify the images. In present paper, reviews of all authors are conducted.

All of 1,647 top papers for Computer Science, Information Systems from 2009 to 2019, which included 1,642 highly cited papers and 32 hot papers. All papers were written in English, from 69 countries/territories and listed in 115 journals. Top 5 core journals were IEEE Communications Surveys and Tutorials, Information Sciences, IEEE Access, IEEE Internet of Things Journal, MIS Quarterly. The research was separated 9 clusters.

This paper describes the problem of intelligent paper grouping and its mathematical model. By optimizing and improving the traditional dynamic programming algorithm, its space complexity is reduced from O(nb) to O(b). At the same time, the flexibility of dynamic programming algorithm is increased by using marker function and tracking algorithm, and the result composition is tracked to obtain the optimal solution. Finally, through several experiments, the improved dynamic programming algorithm is compared with the greedy algorithm and brute force algorithm, and it is found that the improved dynamic programming algorithm has a very good result and is with high efficiency when applied to the simple test paper. It is the most recommended algorithm among the two algorithms compared in this paper.

This article analyzes the common classifications of computer test paper algorithms. This article includes random method, backtracking method, genetic algorithm, random location search method, ant colony algorithm, gene expression algorithm, etc. The author obtains the expected calculated values by studying the technologies of setting control parameters, creating initial populations, calculating individual fitness, optimizing preservation strategies, performing genetic operations, and generating new populations. The author’s purpose is to improve the application effect of the computer test paper algorithm and the practicability of the information in the question bank.

The problem of the planning of pulp and paper production has been investigated, a complex of model and algorithmic programs as well as a software of an automated system of planning and calculating of the cutting methods on a longitudinal slitting machine (LSM) is expected to be a result of this planning. An integrated model for planning paper production and multi-stage cutting of rolled and sheet products has been proposed based on methods, models and algorithms of optimal cutting from the condition of the ensuring the products orders fulfillment with minimal losses. A scientifically based method and algorithm of generating a set of acceptable ways of rolls cutting, criteria of generating a set of acceptable ways of rolls cutting as well as an integer algorithm of the result of the problem solving have been considered. All real restrictions encountered in the manufacturing sector have been taken into account. The results of the planning models usage for real production process have been presented.

Examination paper analysis is important for students to improve their learning efficiency. Traditional paper examination papers are difficult to sort out, which makes collecting mistakes for future review both time-consuming and laborious, either by handwriting or existed software tools. To easy the process, we propose a layout analysis method combined with the conditional generative adversarial network (CGAN). The traditional semantic segmentation structure is improved and used as a generator in the network, while a discriminator is designed to make the segmentation results more accurate. The motivation is that the discriminator can judge the authenticity of the image, so it can help reduce the unreasonable phenomenon in the semantic segmentation results of the generator. The experimental results show that by this method the examination paper image can be welly split into various components, which provides convenience for further sorting and analysis of the examination paper images.

This system uses the STM32F103 single-chip microcomputer as the control center, and the capacitance-to-digital converter FDC2214 collects the current paper value, performs data collection and transmits it to the main control single-chip microcomputer. Methods: Calculate accurate data through Kalman filtering, and accurately calculate and display the number of measured paper sheets on this basis. The device also sets a buzzer to accurately short circuit alarm. The circuit structure of the entire system is simple, and the reliability is high. Results: The system has high precision and fast speed, and can complete the basic requirements and expansion requirements of the problem. Although it is limited by time and venue, it can also have a high reference value for the design of practical applications such as detecting the number of banknotes. Conclusions: Experimental test results show that this design can complete the basic indicators required by the topic and play part of the content. This paper focuses on the hardware design, software design and test result analysis of the system.

The present paper is about the flapping mechanism of a paper locked inside a file. The investigation consists of visualization of flapping phenomenon and acoustic measurements resulting from the flapping. The normal ceiling fan is used as a source for the flow. The axial flow is converted to wall jet flow by using a surface perpendicular to the axis of the fan. The file placed with an offset from the fan which produces instabilities and in turn triggers the flapping mechanism. A super slow-motion camera is used to record the phenomenon and a microphone is used for acoustic measurements. The time-series results reveal the intermittent nature of the flow. The acoustic measurements reveal the noise sources and their frequencies via Fast Fourier Transformation.

The paper parameters were selected for a computer model using open source software to predict their interaction with the dampening solution in an offset printing machine and in an ultrasonic measuring device. The indices characterizing the penetration of alcohol-free and alcohol dampening solutions with 5% and 10% content of isopropyl alcohol into the structure of offset coated papers on PDA c02 ultrasonic measuring device were obtained and analyzed. The surface profiles of coated offset papers are obtained on a Micro Measure 3D Station three-dimensional non-contact profilometer for constructing the surface geometry of papers in a graphical interface. A tstartswelling value was found characterizing the time of the beginning of fiber swelling in the paper structure, which will allow setting the time for calculating the numerical model. The obtained t95 and USI 70 indices are recommended for an indirect assessment of the identity of a computer model to the actual conditions for the onset of interaction and penetration of dampening solutions into the paper pores.

Scheduling is one of the most important classes of combinatorial problems. One of the first problem to be studied in the scheduling theory is the problem of minimizing the makespan in flowshop. In flowshop, the products which is produced have the same sequences. The heuristic algorithms are the key to solving the problem with the optimal solution. To find or to approach nearer to the optimal solution, the meta-heuristic algorithms can be used and the heuristic algorithms as the first solution. One of heuristic algorithm that can be used is Campbell, Dudek and Smith (CDS). Also, the meta-heuristic algorithms that can be used are Tabu Search and Genetic Algorithm. The aim of this paper is to know the gap among the other methods in flowshop scheduling system to reach the optimum makespan.

Improved streamflow forecasting is considered an important task for researchers and water resources managers. However, streamflow forecasting is often challenging owing to the complexity of hydrologic systems. The accuracy of streamflow forecasting mainly depends on the input data from rainfall. Hence, this is important to make the estimation of rainfall as accurate as possible result in achieve an economical design of watershed management, water budget studies, reservoir operation, and flood forecasting and control. Most of the previous research was highlighted, an optimal rain gauge network is necessary to provide high quality rainfall estimates. The goal of this paper is to provide a concise review of several studies on the optimal design of a rain gauge network models to enhance the accuracy of streamflow forecasting. This study had two components. First, the design of an optimal rain gauge network using the kriging-based geostatistical approach based on the variance reduction framework. Second, the uses of optimization technique for minimizing the kriging variance in order to optimize rain gauge networks. Additionally, a discussion of both techniques to design an optimal rain gauge network is presented. A well designed rain gauge network is capable of providing accurate rainfall estimates with an optimal number of rain gauge network density. This paper closes with a set of recommendations for what observations and capabilities are needed in the future to advance our understanding of an optimal rain gauge network design and their location for improving the estimate of aerial rainfall.

In the modern era Computerized Numeric control (CNC) machines are widely used in most of the industries around the world. Nowadays this technology has been used in almost all industries for different operations like cutting, milling, welding, etc. This paper presents the design and manufacturing of a solar powered, portable LASER CNC machine for cutting paper and fabric. The design procedure includes the calculations for finding torque required to run the machine, Factor of Safety etc. Modelling and analysis of the machine is carried out using soft wares like Solid Works and Ansys. The electronic circuit included in the assembly will convert the G-Codes into movements of CNC machine. Incorporation of Solar panels into the assembly helped to make this CNC machine work on clean energy. The results show that the machine is feasible at a reasonable cost for applications where speed and repeatability is achieved while not compromising on accuracy.

The article deals with the actual problem of managing the paper printing properties using factor analysis methods. The analysis of the stone debris method allowed us to prove the combination of data in three ways: the interaction of the ink with the paper surface, which controls the optical density of the print, the value of dot gain; structural properties of the surface, which determine the effusing ability of the paper, printing slip; features of the distribution of the ink layer, which change the parameters of the prints resolution, font resolution threshold, print contrast. The identified factors allowed to simplify the task of rational decision making. As a result of the analysis of a set of technological parameters, i.e. the composition by fiber, filling, surface treatment and mass sizing, production of paper within the improved printing properties was achieved. Changes have been made in the technology of producing uncoated printing paper under the conditions of IUE “Paper Mill” Goznak. The analysis of the quality of management was carried out on the basis of the integral method and made up 92%.

One of the most important topics that concern many researchers is how to make information that has a high degree of confidentiality hidden and not accessible except by the people who have the authority to view it, images are one of the most important multimedia that can be used as a cover to include the data, because the image contains how much A huge amount of data that can include confidential information in it, as well as the image is one of the most multimedia that is sent and received thus that the process of messaging with pictures does not arouse suspicion, this research provided a detailed study of a group of articles that used the image as a cover in the inclusion of information Confidentiality, and focus was on the most important domains of strength in each article. Articles were studied from 2013 to 2020 that were published at the containers of Scopes, and Google Scholar.

The Intrusion-detection systems (IDS) is currently one of the most important security tools. However, an IDS-based hybrid model offers better results than crime detection using the same algorithm. However, hybrid models based on conventional algorithms still face different problems. The objective of this study was to provide information on the most important assumptions and limitations of close hybrid analysis based on criminal analysis and to analyze the limitations of the new machine learning algorithm (FLN) to obtain IDS-based advice.

This article analyzes the noise signal of the packaging machine coupling through artificial intelligence technology, performs feature extraction and analysis on it, and realizes the status recognition and health analysis of the device. This method can successfully analyze the machinery and equipment to find the manual inspection. The problem that is neglected, the method of monitoring packaging equipment through noise energy is a new method with great potential for the actual plant environment.

Due to the rise of diverse finite element software, the needs to understand each of the software interface for optimization of the software usage is increasing among new users. Many researchers had roughly done their software explanation through a few simple methods such as clarifying the software user interface and framework to enhance user benefit with their software. They also provide conclusion for the explanation with a proper justification of an analysis or through interviewing user experiences. The three steps had been proven to be effective in term of giving recognition of software to new users with different background field. This paper will review the standard definition of a graphical user interface that many existing finite element software had completed and how it was exposed to the user. Also, how the software framework function for user to obtain a reliable data out of it and finally the validation of the enlighten framework and GUI for users ease in each model analysis.

This study to review scientific articles from some of the international journal, published from 2005 to 2017. This study focused on articles that discuss how reduce grounding resistance. The article is discussed systematically, criticized, and analyzed. To secure the system from the disorder, we need to design a system. This system was later known with the grounding system. The criteria used in the review journal is focused in terms of: how reduce grounding resistance with electrode be planted a single or parallel, giving conductive material/reducing material, including some of the methods used in reduce grounding resistance specific to regions with high soil resistivity, and the obstacles faced. The discussion on the above issue is a major problem in the article. The article that reviewed published in language of United Kingdom from 2005 to 2017. The analysis of reviewing 20 journal produces two staples of the discussion is existing problems in the grounding system and optimal way in reduce grounding resistance. The reduction of resistance on the location of the grounding that have very high soil resistivity needs to be done, some way is offered in several articles that are discussed so that it could be a guideline the planners in designing a grounding system that is safe and appropriate for the system to be secured.

Start your abstract here… As there is a development in surge hour gridlock especially in the midst of the apex hours of the day, it is difficult to stop the vehicle in the halting opening. To handle this issue we are proposing sagacious halting system. So we are proposing a Shrewd ceasing system which enables the customer to find the nearest halting domain and gives openness of halting spaces in that individual ceasing zone. It prevalently revolve around diminishing the time in finding the halting openings and moreover it keeps up a vital separation from the unnecessary voyaging. Along these lines it decreases the fuel use. This system uses Cloud Computing and Internet of things