Showing papers in "International journal of emerging trends in engineering research in 2022"
TL;DR: A deep learning-based intrusion detection system for the Internet of Things requires consideration of key design principles presented in this paper, and this paper focuses on the IDS implementation on the IoT network.
Abstract: In smart environments, comfort and efficiency are important goals in terms of the quality of human life. Recent developments in Internet of Things (IoT) technology have made it possible to design smart environments. IoT-based smart environments are concerned with security and privacy as key issues. Systems based on the IoT pose a security threat to smart environments. In order to prevent IoT-related security attacks which take advantage of some of these security vulnerabilities, intrusion detection systems (IDSs) designed for IoT environments are crucial. Data generated by connected objects in the age of the IoT provides the basis for big data analytics, which could be employed to identify patterns and identifies anomalies in data. In order to detect intrusions, most cyber security systems employ IDSs, which are used by a variety of techniques and architectures. As opposed to signature-based IDS, anomaly-based IDS learns the normal pattern of system behavior and alerts on abnormal events that occur, as opposed to monitoring monitored events against a database of known intrusion experiences. This paper focuses on the IDS implementation on the IoT network. The use of sensor devices to collect data from smart grid environments has led to smart grids becoming the preferred intrusion target due to the IoTs using advanced information technology. Clouds are data storage systems that provide a variety of smart infrastructure services, such as smart homes and smart buildings, over the internet. A deep learning-based intrusion detection system for the Internet of Things requires consideration of key design principles presented in this paper.
3 citations
TL;DR: Artificial Intelligence (AI) is a digital technology that has been creating numerous breakthroughs across a variety of fields such as Gaming, Mathematics, Education, Natural Language Processing, Computer Vision, Robotics, healthcare, and so on as discussed by the authors .
Abstract: Artificial Intelligence (AI) is a digital technology that has been creating numerous breakthroughs across a variety of fields such as Gaming, Mathematics, Education, Natural Language Processing, Computer Vision, Robotics, healthcare, and so on. The field being dealt with in this article is healthcare which is still an emerging and if not, the most challenging one. This paper goes through a few breakthroughs of AI in healthcare from an industry and research perspective. Some of the ways how AI is being used across various healthcare domains are explained. The discussion goes on by briefing the future scope of AI and how it can make life simpler and more efficient for the stakeholders. Finally, it wraps up by uncovering ways in which AI for healthcare can still be a challenge to software companies and medical practitioners alike by addressing a few major challenges.
2 citations
TL;DR: This paper applies recognition artificial neural network (ANN) for Arabic letters using intensity values of pixels for input of the neural network and results show that ANN with high number of training images have the highest performace.
Abstract: The mechanism that convert and detect the handwriting letters by using machine-encoded forms is called handwriting recognition. The interaction between machines and humans is very important so that the handwriting recognition must be found. The complexity of Arabic letters and the similarity of at least three letters is main challenge to recognize them .Thus, our main challenge is to propose a methodology, implementation and evaluation of Arabic letters recognition system by using Artificial Neural Network approach in order to achieve high accuracy with some techniques will be produced in this paper. In this paper, we apply recognition artificial neural network (ANN) for Arabic letters. We use the intensity values of pixels for input of the neural network. These results show that ANN with high number of training images have the highest performace.
1 citations
TL;DR: The background of climate change, and its corresponding impacts on the environment and every species on our planet is presented in this paper , which provides an overview and deep insights of some major reasons behind the evolution of this problem and illustrates some important steps taken towards the reduction of this extreme problem.
Abstract: In recent decades climate change has become a major threat for our planet due to anthropogenic global warming interconnecting with environmental and other social determinants, constituting an extreme risk of health for every life on earth. The ecology of the earth is facing very bad effects such as inappropriate timing of the monsoon, health risk to the human beings, increasing temperature of the earth, increasing water level of the ocean, missing of some small and even bigger species from ecology, and many more due to climate change. Some major reasons such as decrement in the number of trees and forests and huge emissions of greenhouse gases such as CO2 and chlorofluorocarbon (CFC) are the main factors of climate change. This paper is presented to demonstrate the background of climate change, and its corresponding impacts on the environment and every species on our planet. We cover a wide range of surveys of the research articles published on this issue in the last two decades. This article provides an overview and deep insights of some major reasons behind the evolution of this problem and as well as illustrates some important steps taken towards the reduction of this extreme problem.
1 citations
TL;DR: A scheme that will reduce the number of flow entries of IPv6 packets using two multiprotocol label switching tags in Software Defined Networks and can be used by Internet Service Providers for real-time network flow that will provide handling of an unpredictable surge of big-data transmission across network backbone.
Abstract: Software-Defined Networking (SDN) is a technique that breaks the vertical integration of networks by separating the networks’ control logic from the underlying routers and switches that forward the traffic. The performance of SDN network nodes may be degraded due to flow entries that are frequently updated and stored in the network elements. The control plane is flooded by the configuration messages thereby resulting in a trade-off between the number of configuration messages and number of permanent flow entries in the network.The focus of the study is to develop a scheme that will reduce the number of flow entries of IPv6 packets using two multiprotocol label switching tags in Software Defined Networks. An experimental testbed was developed using openvswitch, Ryu controller, OpenFlow version 1.3, IPERF3 and Wireshark. A Mininet kernel was built on Ubuntu Linux 18.04.1 operating system. The IPv6 Hybrid Permanent Flow (HPF) scheme and Non-Permanent Flow (NPF) was used to reduce the number of permanent flow entries and the number of configuration messages from the controller to the Ternary Content Addressable Memory (TCAM) of the Openswitch.The Result shows that IPv6 HPF scheme had a reduction of 63% as against NPF in the network for the dependency of switch per region while 33% reduction in flow entries of the network for the dependency of host per switch. The result can be used by Internet Service Providers (ISPs) for real-time network flow that will provide handling of an unpredictable surge of big-data transmission across network backbone.
1 citations
TL;DR: A collaborative ITS to teach UML is presented that is built to enable students to effectively communicate and share each other's mistakes and is capable of detecting and identifying student errors.
Abstract: Computer-based learning tools called Intelligent Tutoring Systems (ITS) assist students to become better learners by simulating human tutors using Artificial Intelligence (AI) approaches. Students can interact using collaborative ITSs from various locations to study, discuss, and articulate concepts relevant to a certain problem. This paper presents a collaborative ITS to teach UML that is built to enable students to effectively communicate and share each other's mistakes. The ITS is capable of detecting and identifying student errors and offers students suggestions during the problem-solving stage, giving them guidance on how to proceed. The ITS also determines a student's current level of thinking and intellect in order to assign them activities that need more attention. The evaluations conducted for this study revealed that the experimental group had considerably more learning gains (81% scores on the posttest) than the control group, where students only showed a very low significant change in their learning with posttest scores of 46%
1 citations
TL;DR: In this paper , a response surface study was made with a central design composed of three replicates per point to obtain a surface equation that determines the expected roughness value based on the velocity values of cutting speed and fate rate.
Abstract: This research aims to determine the behavior of the surface roughness parameters Ra, Rq and Rz in the milling of poly-ether-ether-ketone PEEK, in terms of the machining variables: cutting speed feed rate and the machining strategy. To solve this problem, a response surface study was made with a central design composed of three replicates per point to obtain a surface equation that determines the expected roughness value based on the velocity values of Cutting speed and fate rate. This model was repeated for each machining strategy analyzed: Raster and Spiral. To find the correct values of Rq and Rzin, the manufacturer could find desirable values; it could be for minor friction pieces or better shape forms. This investigation found that the value of Rq and Rz in milling machining with a Raster and Spiral trajectory increases with increasing feed rate and decreasing with cutting speed. Likewise, it was observed that the Raster technique obtains higher roughness values than by Spiral.
TL;DR: This review article is a reflection of relevant literature where different things have been discussed in regard to the architectural and application perspective of GPS technology and recent research.
Abstract: GPS Communication is of immense importance and has gained a significant amount of interest considering the research perspective. It reflects upon the location of individuals and is also respective of the security-based aspects. It is important to realize that the application of GPS is utilized in multiple domains including Big Data, AI, and Fleet Management Systems. This review article is a reflection of relevant literature where different things have been discussed in regard to the architectural and application perspective. The research aims at providing a better picture of the current trends in GPS technology and recent research.
TL;DR: In this paper , the steady-state performance of a DC motor fed by a non-isolated quadratic DC-DC boost converter was analyzed under a DC shunt motor of 5 HP power rating.
Abstract: This paper presents the analysis of steady-state performance of a DC motor fed by a non-isolated quadratic DC-DC boost converter. The proposed quadratic configuration based non-isolated high voltage gain DC-DC converter operating in continuous conduction mode employs one power switch and reduced number of diodes and passive components. Due to single power switch, the switching and conduction losses are reduced thereby improving the converter efficiency. A DC shunt motor of 5 HP power rating is used as load to the proposed converter. The proposed cost-effective converter-fed DC motor operating under no-load is simulated using MATLAB / SIMULINK tool. The steady-state performance characteristics, such as speed, torque, and armature current of the DC motor, are obtained for one particular value of duty ratio of the power switch. The results validate the superior performance of the suggested DC-DC converter-fed DC motor at moderate duty ratio.
TL;DR: In this paper , the authors identify some advantages of TOGAF from different literature, and identify the advantages of different EA frameworks for higher education institution choosing the right EA frameworks are an essential step.
Abstract: mplementation of Enterprise Architecture in Higher Education Institutions (HEI) has become an essential and priority concern due to competitiveness, process complexity, and stakeholder challenges. There are several EA frameworks that available and commonly used. For higher education institution choosing right frameworks are an essential step. TOGAF is one of EA frameworks widely used by HEI. We were trying to identify some advantages of TOGAF from different literature.
TL;DR: Using effective and dependable machine learning approaches to discover trends and anticipate the onset of diabetes in humans would aid in the earlier detection and treatment of the illness.
Abstract: Kidney failure, heart failure, blindness, and stroke are all common complications of diabetes. When we consume, our bodies transform food into sugar or glucose. Our pancreas is meant to release insulin at that point. Insulin is a key that allows glucose to enter and be utilized for energy in our cells. The two most common types of diabetes are Type 1 and Type 2. If diabetes is detected early enough, it can be controlled. Using effective and dependable machine learning approaches to discover trends and anticipate the onset of diabetes in humans would aid in the earlier detection and treatment of the illness. Smoking, diet, stress, sleeping time, exercise, and other factors can help us to determine whether a person is prediabetic or diabetic. This study focuses on recent advances in machine learning that have a significant impact on diabetes detection and diagnosis.
TL;DR: This paper tries to find out what countermeasures best strengthen the confidentiality, integrity and availability (CIA) of the implementation of cloud computing within the DOD by analyzing threats and countermeasures within the context of the ten domains comprising the CISSP Common Body of Knowledge (CBK).
Abstract: Cloud computing is a term, which involves virtualization, distributed computing, networking, software and web services. A cloud consists of several elements such as clients, data center and distributed servers. It includes fault tolerance, high availability, scalability, flexibility, reduced overhead for users, reduced cost of ownership, on demand services etc.Cloud Computing offers better computing through improved utilization and reduced administration and infrastructure costs. Cloud Computing is the sum of Software as a Service (SaaS) and Utility Computing. Cloud Computing is still at its infant stage and a very new technology. Therefore, most of the users are not very confident to adopt it.The main issue that faced the cloud computing is “security”. In this paper, we try to find out what countermeasures best strengthen the confidentiality, integrity and availability (CIA) of the implementation of cloud computing within the DOD This will be done by analyzing threats and countermeasures within the context of the ten domains comprising the Certified Information System Security Professional (CISSP) Common Body of Knowledge (CBK). The ten domains include access control; telecommunications and network security; information security governance and risk management; application security; cryptography; security architecture and design; operations security; business continuity planning and disaster planning; legal regulations, compliance, and investigation; and physical security. The results will provide a comprehensive guide for any Department of DefenseDoD entity attempting to secure its cloud solution.
TL;DR: In this article , the use of TiO2 and ZnO catalysts for removal of textile dyes was mainly focused, mainly focused on the synthesis of photo catalysts was done by sol-gel method.
Abstract: Advanced oxidation processes (AOPs) are widely used for the removal of recalcitrant organic constituents from industrial and municipal wastewater. This study mainly focused the use of TiO2 and ZnO catalysts for removal of textile dyes. Synthesis of TiO2 and ZnO photo catalysts was done by sol-gel method. These catalysts were used to obtain enhanced photo catalytic action and were coated on glass beads to improve the photo catalytic activity. The synthesized beads were examined using SEM, FTIR and XRD. Synthesized photocatalysts were examined extensively for their photocatalytic activities with Reactive Orange(RO), Reactive Blue(RB), Textile industry Effluent (TIE) and mixture of dyes (RO+RB, RO+RB +TIE) at various concentrations (50ppm, 100ppm). The photocatalytic degradation of RO, RB, TIE, RO+RB and RO+RB +TIE dyes solution (100mg/L and 50mg/L) using TiO2 and ZnO were investigated under UV light irradiation (λ=254nm). Photocatalytic studies revealed that the TiO2 has shown much higher photocatalytic activity than the ZnO catalyst. The photocatalytic activity of the TiO2 catalyst follows the order: Reactive Orange of 50 ppm (80.98%) > Reactive Blue dye of 50 ppm (77.17%)> Reactive Orange dye of 100 ppm (74.98)>Reactive blue of 100 ppm (72%). The photocatalytic activity of the ZnO catalyst follows the order: Reactive Orange of 50 ppm (75.12%) > Reactive Blue dye of 50 ppm (73.98%)> Reactive Blue dye of 100 ppm (71%)>Reactive Orange of 100 ppm (70%).
TL;DR: In this article , the experimental investigation of flexural behaviour of SFRC beam reinforced with GFRP rebar and compared with steel reinforcement beams is presented in a project, in which three beams were casted using SFRC and longitudinally reinforced with girdar rebar.
Abstract: The experimental investigation of flexural behaviour of SFRC beam reinforced with GFRP rebar and compared with steel reinforcement beams is presented in this project. Three beams were casted using SFRC and longitudinally reinforced with GFRP rebar. Three beams were casted with conventional concrete and steel bar. Six beams were casted and tested under two-point load. Along with beam, cube, cylinder and prism were casted and tested for compressive strength, split tensile and flexural strength. To improve the concrete’s property steel fibres were utilized. From testing of beam load vs deflection, load carrying capacity and stiffness were also calculated. The average load carrying capacity of GFRP rebar is 125.3kN and the average load carrying capacity of normal steel is 99.3kN.The highest deflection found in the GFRP rebar and standard steel reinforcement beam at their ultimate load is 21.5mm& 16.87mm respectively. It was also discovered GFRP beam returned to its original position
TL;DR: The study provides a systematic transformation for big data analytics in public health services to increase competitive advantage in the public health sector and defines the data mart architecture as a proposal for implementing big data as an interoperability tool to generate a consistent data.
Abstract: In the pandemic Covid-19, public health sector is the key for managing national health care. According to Ministry of health(MoH) data, there are 9.993 public health service institution (puskesmas) that spread across Indonesia district level. In this study, we focus on puskesmas as the representative of Ministry of health (MoH). Most of the operations and data taken from the public health center such as patients data, health record data, pharmacies data, and more. The Ministry of Health is responsible for many sectors such as health and drug regulation, health service and equipment, illness, pandemic management, health institution, and so on. Responding to numerous roles above, Information Technology is mandatory for all division in the MoH. However, there are hundreds silo applications has been developed in the Ministry of health. As the consequence, puskesmas should operate many applications. In this study, we conduct an empirical study to design an enterprise architecture on data integration and big data using real cases in the Ministry of health. TOGAF ADM Version 9.2 is used to unearth current condition and set the vision that measures the readiness for implementing Big Data technology. We conduct interviews with management and technical staff to analyze the issues and desirable state, and then conduct gap analysis. Our study provides a systematic transformation for big data analytics in public health services to increase competitive advantage in the public health sector. Furthermore, the challenges are hundreds of applications has been running, lack of regulations, and an information technology roadmap, and the absence of software documentation. Our study defines the data mart architecture as a proposal for implementing big data as an interoperability tool to generate a consistent data. Data regulation and standard protocol must be defined clearly
TL;DR: In this paper , the incorporation of different percentages of carbon nanofibers (0.6-1-3 and 5%) in a PPS thermoplastic matrix, with the purpose to establish and understand each one of the variables that control crystallization kinetics.
Abstract: The presence of a reinforcement in polymeric materials can cause alterations in their physical properties, and increase the crystallization rate of their polymeric matrix. Therefore, this research work was oriented toward the incorporation of different percentages of carbon nanofibers (0.6-1-3 and 5%) in a PPS thermoplastic matrix, with the purpose to establish and understand each one of the variables that control crystallization kinetics. The results showed a gradual decrease in crystallization times for contents of up to 5% of CNF, where carbon nanofibers act as nucleation sites, accelerating the crystallization process. According to the values obtained in the Avrami exponent, these fell within a range that oscillates from 2.5 to 3 for pure PPS and PPS/1%CNF which indicates that the presence of carbon nanofibers does not have an effect on the nucleation mechanism of polyphenylene sulphide crystalline phase, thus suggesting crystallization with heterogeneous nucleation and two-dimensional growth with circular geometry
TL;DR: A flywheel-based energy storage system is emerging in the country and in this paper , the landscape of flywheel energy technology is discussed which includes the components of the flywheel system, other energy storage systems, development, and innovations in the local energy sector.
Abstract: A 20-year Philippine energy roadmap was released by the Department of Energy that covers national renewable energy program, and a framework of energy storage systems. The energy plan entails increasing the share of renewable energy sources in the power mix and the use of energy storage systems to further increase efficiency and effectiveness of electric power delivery in the country. A flywheel-based energy storage system is emerging in the country and in this paper, the landscape of flywheel energy technology is discussed which includes the components of the flywheel system, other energy storage systems, development, and innovations in the local energy sector, as well as the opportunities and impact of flywheel energy technology in the Philippine economy. Moreover, flywheel technology implementation poses challenges in terms of research and development towards reaching its full potential and growth in fabrication, manufacturability, deployment, quality assurance, data analytics, and systems integration.
TL;DR: This paper is a review on the use of GANs for acoustical signals enhancement where speech signal is used as acoustic signal and its limitations, feature sets used as input to GAN, limitations, performance evaluation measures and future directions are provided.
Abstract: Acoustic signals enhancement is an important research topic. It has many applications like cochlear implants, speech and speaker recognition, hearing aids, mobile phones etc. The signals processed by these system are always susceptible to noises. Hence, algorithms are required to extract clean signal from noisy ones. Nowadays , deep neural network are the most sought after tool for signal enhancement. Generative Adversarial Network(GAN) is also one of the recent approaches applied to signal enhancement domain. More work is performed by GANs in image and video processing. To the best of my knowledge no review work on the usage of GANs for acoustic signal enhancement have been done. This paper is a review on the use of GANs for acoustical signals enhancement where speech signal is used as acoustic signal. The paper provides in a summarized manner about the basic GAN architectures and its limitations, feature sets used as input to GAN, limitations, performance evaluation measures and future directions.
TL;DR: In this paper , a new control strategy for single-phase photovoltaic inverters connected to the electrical power distribution network is proposed, where robust PI controllers, a boost chopper and an LCL filter are used.
Abstract: This paper focuses on a new control strategy for single-phase photovoltaic inverters connected to the electrical power distribution network. The inverter studied is single-phase H bridge, equipped with a robust control strategy by sinusoidal duty cycle modulation. This new control strategy offers the advantage over the control strategy. Most used control in its first approximation (PWM control technique): A low Hardware complexity; a variable modulation frequency/period; a topology of modulation with feedback. This inverter structure is further composed of the robust PI controllers, a boost chopper and an LCL filter. The low voltage electrical network to which this inverter is connected is materialized and simulated by a voltage source of characteristics 230V-15A-50Hz and synchronized to the latter by a phase-locked loop (PLL). In this article, the main components of the grid-connected PV power plant are modeled and simulated under Matlab/Simulink as well as the simulation of the global behavior of the entire network+PV inverter and the results obtained are presented.
TL;DR: A novel mathematical morphology edge detection algorithm is proposed to detect lungs CT medical image edge and it is a better compromise method between noise smoothing and edge orientation, but the computation is more complex than general morphological edge detection algorithms.
Abstract: In this paper, a novel mathematical morphology edge detection algorithm is proposed to detect lungs CT medical image edge. It is a better method for edge information detecting and noise filtering than differential operation, which is sensitive to noise. And it is a better compromise method between noise smoothing and edge orientation, but the computation is more complex than general morphological edge detection algorithms
TL;DR: In this paper , the microstructure and corrosion behavior of nanocrystalline SUS304 by dry ice shot peening has been investigated in detail in terms of phase transformation.
Abstract: Microstructure and corrosion behavior of nanocrystalline SUS304 by dry ice shot peening has been investigated in detail in term of phase transformation. SUS304 as metastable austenitic stainless has excellent corrosion resistance and induced martensite by shot peening process. However, the SUS304 has quite low strength which is difficult to wear as metallic component. The dry ice shot peening process was carried out on SUS304 surface for one and three hours. The microstructure was observed by transmission electron microscope (TEM) and scanning electron microscope (SEM) equipped with electron back-scattered diffraction (EBSD). The phase transformation was analyzed by X-ray diffraction (XRD). The corrosion testing was carried out in 3.5% NaCl solution. The result indicated that the grain size of SUS304 surface was finer by deformation due to dry ice shot peened process. The hardness was improved properly by the increasing the shot peened time, and the corrosion resistance was increased. The XRD results showed that three hours shot peening process induced martensite phase of SUS304 by 15 m thickness. It can be summarized that the dry ice shot peening can be induced phase transformation due to high deformation on the SUS304 surface
TL;DR: In this article , a hybrid model that combines SVM and Naive Bayes (NBSVM) framework was used to detect fake news with an accuracy of 84.85%.
Abstract: The increasing consumption of news on social media platforms is mainly due to its cheap and attractive nature and it’s capable of spreading the fake news. The spread of fake news has negative effects on society. Some people make it up to get attention or gain political gain. Machine learning and deep learning techniques have been developed to detect fake news. However, they tend to generate inaccurate reports. To detect fake news, we used a Hybrid model that combines SVM and Naive Bayes (NBSVM) framework. It was able to classify the news with an accuracy of 84.85%. This model was tested and trained on a fake news challenge dataset. We used various evaluation metrics (precision, recall, F1- measure, etc.) to measure the model's efficiency
TL;DR: In this paper , a solar powered DC motor control system is considered and simulations are performed using various controllers and H-Bridge Buck Boost converter. But the simulation results are executed and compared for different controllers using MATLAB/SIMULINK environment.
Abstract: In this paper, the solar powered DC motor control system is considered and simulations are performed using various controllers and H-Bridge Buck Boost converter. The parameters varied are: irradiance and temperature. When input parameters are changed abruptly, such as sudden rise or fall in temperature or irradiance, DC motor performance is observed. These parameters are changed separately, keeping other parameter constant. The main aim is to obtain smooth DC motor control and operation under all input conditions. The simulations results are executed and compared for different controllers using MATLAB/SIMULINK environment.
TL;DR: Deep learning based Convolutional Neural Network is used for feature and their combination classification and the performance of the model is evaluated in terms of accuracy which demonstrates the feature selection techniques are able to improve the classification accuracy and also minimize the resource utilization.
Abstract: The digital images are the data storage method which stores the real world information on a matrix based on pixels. The images are now become very valuable due to increasing applications in medical, engineering, and social. Therefore, Image processing and Classification plays an essential role. In this paper, we are investigating the employment of three different features i.e., shape, color and texture for image classification. In addition, the combined feature is also used for demonstrating the impact on classifier. The Deep learning based Convolutional Neural Network is used for feature and their combination classification. In this experiment, Diabetic Retinopathy Detection dataset is used.The performance of the model is evaluated in terms of accuracy which demonstrates the feature selection techniques are able to improve the classification accuracy and also minimize the resource utilization
TL;DR: An efficient multidisciplinary application of hydrogel-based bio-inks implied in 3D bio-printing is provided, that needs appropriate attention, such as integrity, strength of biomaterials, cells, and biomolecules utilizing 3D bioprinting, as well as multi-material and multicellular biopprinting.
Abstract: Biomaterials printing of three-dimensional (3D) type gives an excellent alternative in the production of allograft organs and tissues to overcome the incidences of organ shortages and donor scarcities. With the present shortage of readily viable and available organs for transplantation, the medical field is encountered with the shortage in supply and an increasing organs demand. In last decade, regenerative medicine and tissue engineering (TE) continue to give alternative methods for artificial organs and tissues. Current research presents those implying hydrogels as a bio-inks of cell laden type for the 3D tissue fabrication builds allows an immunogenicity lack, sine the bio-ink based on hydrogel is specific of patient and described from biopolymers which illustrate extraordinary biodegradability and biocompatibility, lowered rejection of organs, enhanced viability of organs, and increased the supply based on demand. Although enough evidence leads researchers and scientists to conclude the efficient and safe procedure of seeding biomaterials, cells, and biomolecules utilizing 3D bioprinting, there are several restrictions, that needs appropriate attention, such as integrity, strength of biomaterials, cost, and volumetric bioprinting, as well as multi-material and multicellular bioprinting. In this paper, we are providing the overview of various applications of hydrogels as bio-inks implied in 3D bio-printing. Moreover, article provides an efficient multidisciplinary application of hydrogel-based bio-inks
TL;DR: In this paper , a case study is presented in which an adaptation solution is given to a transport system for the transport of food in a poultry industry in Colombia, in this case the conditions of the land communication routes of the company with its environment are not the best.
Abstract: In many parts of the world, product transport systems must adapt and provide a solution to the conditions imposed in certain situations, in this sense, in this article a case study is presented in which an adaptation solution is given to a transport system. transport of food in a Poultry Industry in Colombia, in this case the conditions of the land communication routes of the company with its environment are not the best, which causes innumerable problems in the production of the company, therefore an adaptation was made to a transport car anchored to a tractor, which effectively facilitates the transportation of food and products inside and outside the company's facilities, which has implemented this system in all its plants.
TL;DR: Internet of thing (IoT) is a concept of technology that has a purpose or benefit in providing access to information and communication on a large scale and also allows controlling several objects that can interconnect and form systems that can help human work in various fields and inVarious fields.
Abstract: Internet of thing (IoT) is a concept of technology that has a purpose or benefit in providing access to information and communication on a large scale and also allows controlling several objects that can interconnect and form systems that can help human work in various fields and in various fields. profession.
TL;DR: In this paper , a double function machine was designed and manufactured to deal with agricultural waste in the villages of Sempu-Banyuwangi and Arjasa-Jember, East Java, Indonesia.
Abstract: Agricultural waste is huge in the villages as a by-product of harvesting. Without proper management, they become useless or even a danger to the society and environment. This paper aims to describe a report on the community service activities of the authors in an attempt to resolve the agricultural waste in the Villages of Sempu-Banyuwangi and Arjasa-Jember, East Java, Indonesia. Two types of wastes were identified: cattle dungs and by-products of the agricultural harvests. These two wastes would be chopped or crushed to reuse either as compost or cattle feed. Therefore, a double function machine was designed and manufactured. The main cutters were made of a used chainsaw blade. A strainer was added to sieve the crushed cattle dung. This machine was powered by a 6.5 HP gasoline engine. Both cattle dung and agricultural waste could be crushed or chopped into small pieces. It is double hoppers: upper and side for different tasks.
TL;DR: The result obtained from the experiment shows promising result in summarization of Wolaita text, and the researcher justified the model performance with ROUGE evaluation metrics by comparing the system summaries with the expert summaries.
Abstract: Text summarization is the mechanism of summarizing a huge document comprising vast amount of information which is difficult to overcome and understand its message easily in any written documents for whatever languages without losing its entire message. A short and precise document which conveys intended information for the user in demand is expected in this information age. In addition to that, summarizing a document with vast amount of information is very difficult and time consuming specially for less resourced and technologically unfavored languages. Therefore in this study, the researcher proposed to address such problems for Wolaita by using graph based extractive text summarization approach. To attain the goal of this study the researcher prepared 92 documents for the study, explored extractive text summarization with graph-based approach to address the problems, performed text preprocessing tasks and finally developed text summarization model by using TextRank algorithms. The researcher used 92 documents, performed 92 various experiments, on documents and experimental results and findings were discussed in detail. To evaluate the model performance, three different expert summaries were collected for documents and computed system generated summaries with ROUGE evaluation metric. The researcher justified it with ROUGE evaluation metrics by comparing the system summaries with the expert summaries. The result obtained from the experiment shows promising result in summarization of Wolaita text. Finally, the experimental result of a 61.16% recall, 60.69% precision and 60.46% f-measures were obtained.
TL;DR: In this article , the effect of triple layer anti-reflection coating (TLARC) on the surface of silicon cell theoretically was investigated and the results showed reduction in reflectance of silicon solar cell down to less than 3% in the wavelength range 400-1200 nm with conversion efficiency 21.6% for TLARC (MgF2/Si3N4/TiO2).
Abstract: In present work an attempt has been made to investigate the effect of triple layer anti-reflection coating (TLARC) on the surface of silicon cell theoretically. In this regard, MgF2, Si3N4, and TiO2 have been used to design anti-reflection coatings (ARC). Reflection spectra for single double and triple layer ARCs have been evaluated numerically using transfer matrix method (TMM). Numerically calculated reflection spectra for single, double, and triple layer anti-reflection coatings further used in PC1D simulator to study the performance of silicon solar cell. Result shows reduction in reflectance of silicon solar cell down to less than 3% in the wavelength range 400 – 1200 nm with conversion efficiency 21.6% for TLARC (MgF2/Si3N4/TiO2).