Documentos donde el Autor es "Singh, Rajesh"

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés In recent years, nanotechnology and materials science have evolved and matured, making it increasingly easier to design and fabricate next-generation 3D microelectronics. The process has changed drastically from traditional 2D microelectronics, resulting in improved performance, higher integration density, and new functionalities. As applications become more complex and power-intensive, this technology can address the demands of high-performance computing, advanced sensors, and cutting-edge communication systems via wearable, flexible devices, etc. To manufacture higher-density microelectronics, recent advances in the fabrication of such 3D devices are discussed. Furthermore, the paper stresses the importance of novel materials and architectures, such as monolithic 3D integration and heterogeneous integration, in overcoming these challenges. We emphasize the importance of addressing complex issues to achieve better performance and higher integration density, which will play an important role in shaping the next generation of microelectronic devices. The multifaceted challenges involved in developing next-generation 3D microelectronic devices are also highlighted. metadata Singh, Niharika; Srivastava, Kingshuk; Kumar, Ajay; Yadav, Neha; Yadav, Ashish; Dubey, Santosh; Singh, Rajesh; Gehlot, Anita; Verma, Ajay Singh; Gupta, Neha; Kumar, Tanuj; Wu, Yongling; Hongyu, Zheng; Mondal, Aniruddha; Pandey, Kailash; Brajpuriya, Ranjeet; Kumar, Shalendra y Gupta, Rajeev mail SIN ESPECIFICAR (2024) Challenges and opportunities in engineering next-generation 3D microelectronic devices: improved performance and higher integration density. Nanoscale Advances, 6 (24). pp. 6044-6060. ISSN 2516-0230

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés This study explored the impact of varying weight percentages of TiMoVWCr high-entropy alloy (HEA) powder addition on A356 composites produced using friction stir processing (FSP). Unlike previous research that often focused on singular aspects, such as mechanical properties, or microstructural analysis, this investigation systematically examined the multifaceted performance of A356 composites by comprehensively assessing the microstructure, interfacial bonding strength, mechanical properties, and wear behavior. The study identified a uniform distribution of TiMoVWCr HEA powder in the composition A356/2%Ti2%Mo2%V2%W2%Cr, highlighting the effectiveness of the FSP technique in achieving homogeneous dispersion. Strong bonding between the reinforcement and matrix material was observed in the same composition, indicating favorable interfacial characteristics. Mechanical properties, including tensile strength and hardness, were evaluated for various compositions, demonstrating significant improvements across the board. The addition of 2%Ti2%Mo2%V2%W2%Cr powder enhanced the tensile strength by 36.39%, while hardness improved by 62.71%. Similarly, wear resistance showed notable enhancements ranging from 35.56 to 48.89% for different compositions. Microstructural analysis revealed approximately 1640.59 grains per square inch for the A356/2%Ti2%Mo2%V2%W2%Cr processed composite at 500 magnifications. In reinforcing Al composites with Ti, Mo, V, W, and Cr high-entropy alloy (HEA) particles, each element imparted distinct benefits. Titanium (Ti) enhanced strength and wear resistance, molybdenum (Mo) contributed to improved hardness, vanadium (V) promoted hardenability, tungsten (W) enhanced wear resistance, and chromium (Cr) provided wear resistance and hardness. Anticipating the potential applications of the developed composite, the study suggests its suitability for the aerospace sector, particularly in casting lightweight yet high-strength parts such as aircraft components, engine components, and structural components, underlining the significance of the investigated TiMoVWCr HEA powder-modified A356 composites. metadata Dwivedi, Shashi Prakash; Sharma, Shubham; Li, Changhe; Zhang, Yanbin; Singh, Rajesh; Kumar, Abhinav; Awwad, Fuad A.; Khan, M. Ijaz y Ismail, Emad A. A. mail SIN ESPECIFICAR (2024) Exploring Microstructural, Interfacial, Mechanical, and Wear Properties of AlSi7Mg0.3 Composites with TiMOVWCr High-Entropy Alloy Powder. ACS Omega, 9 (17). pp. 18813-18826. ISSN 2470-1343

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Chemical modification of guar gum was done by graft copolymerization of monomer hydroxyethyl methacrylate (HEMA) using azobisisobutyronitrile (AIBN) as initiator. Optimal reaction parameters were settled by varying one reaction condition and keeping the other constant. The optimum reaction conditions worked out were solvent system: binary, [H2O] = 15.00 mL, [acetone] = 5.00 mL, [HEMA] = 82.217× 10−2 mol/L, [AIBN] = 3.333 × 10−2 mol/L, reaction time = 3 h, reaction temperature = 60 °C on to 1.00 g guar gum with Pg = 1694.6 and %GE = 68,704.152. Pure guar gum polymer and grafts were analyzed by several physicochemical investigation techniques like FTIR, SEM, XRD, EDX, and swelling studies. Percent swelling of the guar gum polymer and grafts was investigated at pH 2.2, 7.0, 7.4 and 9.4 concerning time. The finest yield of Ps was recorded at pH 9.4 with time 24 h for graft copolymer. Guar gum and grafted samples were explored for the sorption of toxic dye Bismarck brown Y from the aqueous solution with respect to variable contact time, pH, temperature and dye concentration so as to investigate the stimuli responsive sorption behaviour. Graft copolymers showed better results than guar gum with percent dye uptake (Du) of 97.588 % in 24 h contact time, 35 °C temperature, 9.4 pH at 150.00 ppm dye feed concentration as compared to Guar gum which only showed 85.260 % dye uptake at alike dye fed concentration. The kinetic behaviour of the polymeric samples was evaluated by applying many adsorption isotherms and kinetic models. The value of 1/n was between 0 → 1 showing that there was physisorption of the BB dye that took place on the surface of the polymers. Thermodynamics of BB Y adsorption onto hydrogels was investigated concerning the Van't Hoff equation. -∆G° values obtained from the curve proved the spontanity of the process. Within the context of adsorption efficiency, an investigation was conducted to examine the process of sorption of Bismarck brown Y dye from aqueous solutions. The graft copolymers demonstrated remarkable adsorption abilities, achieving a dye uptake (Du) of 97.588 % over a 24-h period at a temperature of 35 °C, pH level of 9.4, and a dye concentration of 150.00 ppm. The raised adsorption capacity was additionally corroborated by the application of several adsorption isotherms and kinetic models, which indicated that physisorption is the prevailing process/mechanism. Additionally, the thermodynamic research, utilising the Van't Hoff equation, validated the spontaneity of the adsorption phenomenon, as evidenced by the presence of a negative ∆G° values. The thermodynamic analysis revealed herein establishes a strong scientific foundation for the effectiveness of adsorbent composed of graft copolymers based on guar gum. The research conclude the efficiency of the guar gum based grafted copolymers for the water remediation as efficient adsorbents. The captured dye can be re-utilised and the hydrogels can be used for the same purpose in number of cycles. metadata Chopra, Lalita; Sharma, Anika; Chohan, Jasgurpreet Singh; Upadhyay, Viyat Varun; Singh, Rajesh; Sharma, Shubham; Dwivedi, Shashi Prakash; Kumar, Abhinav y Tag-Eldin, Elsayed M. mail SIN ESPECIFICAR (2024) Synthesis and characterizations of super adsorbent hydrogel based on biopolymer, Guar Gum-grafted-Poly (hydroxyethyl methacrylate) (Gg-g-Poly (HEMA)) for the removal of Bismarck brown Y dye from aqueous solution. International Journal of Biological Macromolecules, 256. p. 128518. ISSN 01418130

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés The organic polymer known as Polypyrrole (Ppy) is synthesized when pyrrole monomers are polymerized. Excellent thermal stability, superior electrical conductivity, and environmental stability are all characteristics of Polypyrrole. Chemical oxidative polymerization was used to synthesize Ppy using Ferric chloride (FeCl3) as an oxidizing agent and surfactant CTAB in aqueous solution. Oxidant (FeCl3) to pyrrole varied in different molar ratios (2, 3, 4 and 5). It was found that increasing this ratio up to 4 increases PPy's conductivity. XRD, FTIR, and SEM were used to characterize Ppy. The conductive nature of Ppy was studied by I–V characteristics. The best conductive polymer is studied for the NH3 gas response. metadata Jain, Alok; Nabeel, Ansari Novman; Bhagwat, Sunita; Kumar, Rajeev; Sharma, Shubham; Kozak, Drazan; Hunjet, Anica; Kumar, Abhinav y Singh, Rajesh mail SIN ESPECIFICAR (2023) Fabrication of polypyrrole gas sensor for detection of NH3 using an oxidizing agent and pyrrole combinations: Studies and characterizations. Heliyon, 9 (7). e17611. ISSN 24058440

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Español In this investigation, microwave radiation was used alongside a combination of Ni powder, Si powder, and La2O3 (Lanthanum oxide) powder to create surface cladding on SS-304 steel. To complete the microwave cladding process, 900 W at 2.45 GHz was used for 120 s. “Response surface methodology (RSM)” was utilized to attain the optimal combination of microwave cladding process parameters. The surface hardness of the cladding samples was taken as a response. The optimal combination of microwave cladding process parameters was found to be Si (wt.%) of 19.28, a skin depth of 4.57 µm, irradiation time of 118 s, and La2O3 (wt.%) of 11 to achieve a surface hardness of 287.25 HV. Experimental surface hardness at the corresponding microwave-cladding-process parameters was found to be 279 HV. The hardness of SS-304 was improved by about 32.85% at the optimum combination of microwave cladding process parameters. The SEM and optical microscopic images showed the presence of Si, Ni, and La2O3 particles. SEM images of the “cladding layer and surface” showed the “uniform cladding layer” with “fewer dark pixels” (yielding higher homogeneity). Higher homogeneity reduced the dimensional deviation in the developed cladding surface. XRD of the cladded surface showed the presence of FeNi, Ni2Si, FeNi3, NiSi2, Ni3C, NiC, and La2O3 phases. The “wear rate and coefficient of friction” of the developed cladded surface with 69.72% Ni, 19.28% Si, and 11% La2O3 particles were found to be 0.00367 mm3/m and 0.312, respectively. “Few dark spots” were observed on the “corroded surface”. These “dark spots” displayed “some corrosion (corrosion weight loss 0.49 mg)” in a “3.5 wt.% NaCl environment”. metadata Dwivedi, Shashi Prakash; Sharma, Shubham; Sharma, Kanta Prasad; Kumar, Abhinav; Agrawal, Ashish; Singh, Rajesh y Eldin, Sayed M. mail SIN ESPECIFICAR (2023) The Microstructure and Properties of Ni-Si-La2O3 Coatings Deposited on 304 Stainless Steel by Microwave Cladding. Materials, 16 (6). p. 2209. ISSN 1996-1944

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Silicon photonics is rapidly evolving as an advanced chip framework for implementing quantum technologies. With the help of silicon photonics, general-purpose programmable networks with hundreds of discrete components have been developed. These networks can compute quantum states generated on-chip as well as more extraordinary functions like quantum transmission and random number generation. In particular, the interfacing of silicon photonics with complementary metal oxide semiconductor (CMOS) microelectronics enables us to build miniaturized quantum devices for next-generation sensing, communication, and generating randomness for assembling quantum computers. In this review, we assess the significance of silicon photonics and its interfacing with microelectronics for achieving the technology milestones in the next generation of quantum computers and quantum communication. To this end, especially, we have provided an overview of the mechanism of a homodyne detector and the latest state-of-the-art of measuring squeezed light along with its integration on a photonic chip. Finally, we present an outlook on future studies that are considered beneficial for the wide implementation of silicon photonics for distinct data-driven applications with maximum throughput. metadata Gupta, Rajeev; Singh, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Yadav, Neha; Brajpuriya, Ranjeet; Yadav, Ashish; Wu, Yongling; Zheng, Hongyu; Biswas, Abhijit; Suhir, Ephraim; Yadav, Vikram Singh; Kumar, Tanuj y Verma, Ajay Singh mail SIN ESPECIFICAR (2023) Silicon photonics interfaced with microelectronics for integrated photonic quantum technologies: a new era in advanced quantum computers and quantum communications? Nanoscale. ISSN 2040-3364

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Stress is now a serious disease that exists due to changes in working life and food ecosystems around the world. In general, it is difficult for a person to know if they are under stress. According to previous research, temperature, heart rate variability (HRV), humidity, and blood pressure are used to assess stress levels with the use of instruments. With the development of sensor technology and wireless connectivity, people around the world are adopting and using smart devices. In this study, a bio signal detection device with Internet of Things (IoT) capability with a galvanic skin reaction (GSR) sensor is proposed and built for real-time stress monitoring. The proposed device is based on an Arduino controller and Bluetooth communication. To evaluate the performance of the system, physical stress is created on 10 different participants with three distinct tasks namely reading, visualizing the timer clock, and watching videos. MATLAB analysis is performed for identifying the three different levels of stress and obtaining the threshold values as if the person GSR voltage i.e., relaxed for <1.75 volts; Normal: between 1.75 and 1.44 volts and stressed: >1.44 volts. In addition, LabVIEW is used as a data acquisition system, and a Blueterm mobile application is also used to view the sensor reading received from the device through Bluetooth communication. metadata Singh, Rajesh; Gehlot, Anita; Saxena, Ritika; Alsubhi, Khalid; Anand, Divya; Delgado Noya, Irene; Vaseem Akram, Shaik y Choudhury, Sushabhan mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Stress Detector Supported Galvanic Skin Response System with IoT and LabVIEW GUI. Computers, Materials & Continua, 74 (1). pp. 1217-1233. ISSN 1546-2226

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés In present investigation, the impact of nanoparticle concentration on the machining accomplishment of Hastelloy C-276 has been examined in turning operation. The outputs like temperature, surface roughness, chip reduction coefficient (CRC), tool wear, and friction coefficient along with angle of shear have been estimated. The graphene nanoparticles (GnP) have been blended into soybean oil in distinct weight/volume ratio of 0.5, 1 and 1.5%. The experimental observations revealed that higher concentration of nanoparticles has enhanced the heat carrying capacity of amalgamation by 12.28%, surface roughness (27.88%), Temperature (16.8%), tool wear (22.5%), CRC (17.5%), coefficient of friction (46.36%) and shear angle (15%). Scanning electron microscopy identified nose wear, abrasion, adhesion and loss of tool coating. Further, lower tool wear has been noticed at 1.5% concentration, while the complete failure of insert has been reported during 116 m/min, 0.246 mm/rev having 0.5% concentration. ANOVA results exhibited that surface roughness is highly influenced by speed rate (41.66%) trailed by feed rate (28.16%) and then after concentration (13.68%). Temperature is dominated by cutting speed (69.31%), concentration (14.53%) and feed rate (13.25%). Likewise, tool wear was majorly altered by cutting speed (67.2%) accompanied by feed rate (23.90%) and thirdly concentration of GnP (5.03%). metadata Singh, Gurpreet; Sharma, Shubham; Seikh, A.H.; Li, Changhe; Zhang, Yanbin; Rajkumar, S.; Kumar, Abhinav; Singh, Rajesh y Eldin, Sayed M. mail SIN ESPECIFICAR (2023) A novel study on the influence of graphene-based nanofluid concentrations on the response characteristics and surface-integrity of Hastelloy C-276 during minimum quantity lubrication. Heliyon, 9 (9). e19175. ISSN 24058440

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Currently, sustainability is a vital aspect for every nation and organization to accomplish Sustainable Development Goals (SDGs) by 2030. Environmental, social, and governance (ESG) metrics are used to evaluate the sustainability level of an organization. According to the statistics, 53% of respondents in the BlackRock survey are concerned about the availability of low ESG data, which is critical for determining the organization’s sustainability level. This obstacle can be overcome by implementing Industry 4.0 technologies, which enable real-time data, data authentication, prediction, transparency, authentication, and structured data. Based on the review of previous studies, it was determined that only a few studies discussed the implementation of Industry 4.0 technologies for ESG data and evaluation. The objective of the study is to discuss the significance of ESG data and report, which is used for the evaluation of the sustainability of an organization. In this regard, the assimilation of Industry 4.0 technologies (Internet of Things (IoT), artificial intelligence (AI), blockchain, and big data for obtaining ESG data by an organization is detailed presented to study the progress of advancement of these technologies for ESG. On the basis of analysis, this study concludes that consumers are concerned about the ESG data, as most organizations develop inaccurate ESG data and suggest that these digital technologies have a crucial role in framing an accurate ESG report. After analysis a few vital conclusions are drawn such as ESG investment has benefited from AI capabilities, which previously relied on self-disclosed, annualized company information that was susceptible to inherent data issues and biases. Finally, the article discusses the vital recommendations that can be implemented for future work metadata Saxena, Archana; Singh, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Twala, Bhekisipho; Singh, Aman; Caro Montero, Elisabeth y Priyadarshi, Neeraj mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, elizabeth.caro@uneatlantico.es, SIN ESPECIFICAR (2022) Technologies Empowered Environmental, Social, and Governance (ESG): An Industry 4.0 Landscape. Sustainability, 15 (1). p. 309. ISSN 2071-1050

Artículo Materias > Ciencias Sociales
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Financial management is a critical aspect of firms, and entails the strategic planning, direction, and control of financial endeavors. Risk assessment, fraud detection, wealth management, online transactions, customized bond scheme, customer retention, virtual assistant and so on, are a few of the critical areas where Industry 4.0 technologies intervention are highly required for managing firms' finance. It has been identified from the previous studies that they are limited studies that have addressed the significance and application of integrating of Industry 4.0 technologies such as Internet of Things (IoT), cloud computing, big data, robotic process automation (RPA), artificial intelligence (AI), Blockchain, Digital twin, and Metaverse. With the motivation from the above aspects, this study aims to discuss the role of these technologies in the area of financial management of a firm. Based up on the analysis, it has been concluded that these technologies assist to credit risk management based on real-time data; financial data analytics of risk assessment, digital finance, digital auditing, fraud detection, and AI- and IoT- based virtual assistants. This study recommended that digital technologies be deeply integrated into the financial sector to improve service quality and accessibility, as well as the creation of innovative rules that allow for healthy competition among market participants. metadata Bisht, Deepa; Singh, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Singh, Aman; Caro Montero, Elisabeth; Priyadarshi, Neeraj y Twala, Bhekisipho mail SIN ESPECIFICAR (2022) Imperative Role of Integrating Digitalization in the Firms Finance: A Technological Perspective. Electronics, 11 (19). p. 3252. ISSN 2079-9292

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés MANET is a mobile ad hoc network with many mobile nodes communicating without a centralized module. Infrastructure-less networks make it desirable for many researchers to publish and bind multimedia services. Each node in this infrastructure-less network acts as self-organizing and re-configurable. It allows services to deploy and attain from another node over the ad hoc network. The service composition aims to provide a user’s requirement by combining different atomic services based on non-functional QoS parameters such as reliability, availability, scalability, etc. To provide service composition in MANET is challenging because of the node mobility, link failure, and topology changes, so a traditional protocol will be sufficient to obtain real-time services from mobile nodes. In this paper, the ad hoc on-demand distance vector protocol (AODV) is used and analyzed based on MANET’s QoS (Quality of Service) metrics. The QoS metrics for MANET depends on delay, bandwidth, memory capacity, network load, and packet drop. The requester node and provider node broker acts as a composer for this MANET network. The authors propose a QoS-based Dynamic Secured Broker Selection architecture (QoSDSBS) for service composition in MANET, which uses a dynamic broker and provides a secure path selection based on QoS metrics. The proposed algorithm is simulated using Network Simulator (NS2) with 53 intermediate nodes and 35 mobile nodes of area 1000 m × 1000 m. The comparative results show that the proposed architecture outperforms, with standards, the AODV protocol and affords higher scalability and a reduced network load metadata Ramalingam, Rajakumar; Muniyan, Rajeswari; Dumka, Ankur; Singh, Devesh Pratap; Mohamed, Heba G.; Singh, Rajesh; Anand, Divya y Delgado Noya, Irene mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es (2022) Routing Protocol for MANET Based on QoS-Aware Service Composition with Dynamic Secured Broker Selection. Electronics, 11 (17). p. 2637. ISSN 2079-9292

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés SIN ESPECIFICAR metadata Kimothi, Sanjeev; Thapliyal, Asha; Akram, Shaik Vaseem; Singh, Rajesh; Gehlot, Anita; Mohamed, Heba G.; Anand, Divya; Ibrahim, Muhammad y Delgado Noya, Irene mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, irene.delgado@uneatlantico.es (2022) Big Data Analysis Framework for Water Quality Indicators with Assimilation of IoT and ML. Electronics, 11 (13). p. 1927. ISSN 2079-9292

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Large-scale distributed systems have the advantages of high processing speeds and large communication bandwidths over the network. The processing of huge real-world data within a time constraint becomes tricky, due to the complexity of data parallel task scheduling in a time constrained environment. This paper proposes data parallel task scheduling in cloud to address the minimization of cost and time constraints. By running concurrent executions of tasks on multi-core cloud resources, the number of parallel executions could be increased correspondingly, thereby, finishing the task within the deadline is possible. A mathematical model is developed here to minimize the operational cost of data parallel tasks by feasibly assigning a load to each virtual machine in the cloud data center. This work experiments with a machine learning model that is replicated on the multi-core cloud heterogeneous resources to execute different input data concurrently to accomplish distributive learning. The outcome of concurrent execution of data-intensive tasks on different parts of the input dataset gives better solutions in terms of processing the task by the deadline at optimized cost. metadata Rajalakshmi, N. R.; Dumka, Ankur; Kumar, Manoj; Singh, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Anand, Divya; Elkamchouchi, Dalia H. y Delgado Noya, Irene mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, irene.delgado@uneatlantico.es (2022) A Cost-Optimized Data Parallel Task Scheduling with Deadline Constraints in Cloud. Electronics, 11 (13). p. 2022. ISSN 2079-9292

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Food and agriculture are significant aspects that can meet the food demand estimated by the Food Agriculture Organization (FAO) by 2050. In addition to this, the United Nations sustainable development goals recommended implementing sustainable practices to meet food demand to achieve sustainability. Currently, aquaponics is one of the sustainable practices that require less land and water and has a low environmental impact. Aquaponics is a closed-loop and soil-less method of farming, where it requires intensive monitoring, control, and management. The advancement of wireless sensors and communication protocols empowered to implementation of an Internet of Things- (IoT-) based system for real-time monitoring, control, and management in aquaponics. This study presents a review of the wireless technology implementation and progress in aquaponics. Based on the review, the study discusses the significant water and environmental parameters of aquaponics. Followed by this, the study presents the implementation of remote, IoT, and ML-based monitoring of aquaponics. Finally, the review presents the recommendations such as edge and fog-based vision nodes, machine learning models for prediction, LoRa-based sensor nodes, and gateway-based architecture that are beneficial for the enhancement of wireless aquaponics and also for real-time prediction in the future. metadata Gayam, Kiran Kumari; Jain, Anuj; Gehlot, Anita; Singh, Rajesh; Akram, Shaik Vaseem; Singh, Aman; Anand, Divya; Delgado Noya, Irene y Ahmad, Shafiq mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@unic.co.ao, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, SIN ESPECIFICAR (2022) Imperative Role of Automation and Wireless Technologies in Aquaponics Farming. Wireless Communications and Mobile Computing, 2022. pp. 1-13. ISSN 1530-8669

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés In December 2019, a group of people in Wuhan city of Hubei province of China were found to be affected by an infection called dark etiology pneumonia. The outbreak of this pneumonia infection was declared a deadly disease by the China Center for Disease Control and Prevention on January 9, 2020, named Novel Coronavirus 2019 (nCoV-2019). This nCoV-2019 is now known as COVID-19. There is a big list of infections of this coronavirus which is present in the form of a big family. This virus can cause several diseases that usually develop with a serious problem. According to the World Health Organization (WHO), 2019-nCoV has been placed as the modern generation of Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) coronaviruses, so COVID-19 can repeatedly change its internal genome structure to extend its existence. Understanding and accurately predicting the mutational properties of the genome structure of COVID-19 can form a good leadership role in preventing and fighting against coronavirus. In this research paper, an analytical approach has been presented which is based on the k-means cluster technique of machine learning to find the clusters over the mutational properties of the COVID-19 viruses’ complete genome. This method would be able to act as a promising tool to monitor and track pathogenic infections in their stable and local genetics/hereditary varieties. This paper identifies five main clusters of mutations with as best in most cases in the coronavirus that could help scientists and researchers develop disease control vaccines for the transformation of coronaviruses. metadata Dumka, Ankur; Verma, Parag; Singh, Rajesh; Bhardwaj, Anuj; Alsubhi, Khalid; Anand, Divya; Delgado Noya, Irene y Aparicio Obregón, Silvia mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, irene.delgado@uneatlantico.es, silvia.aparicio@uneatlantico.es (2022) Intelligent Approach for Clustering Mutations’ Nature of COVID-19 Genome. Computers, Materials & Continua, 72 (3). pp. 4453-4466. ISSN 1546-2226

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Coronavirus (COVID-19) has impacted nearly every person across the globe either in terms of losses of life or as of lockdown. The current coronavirus (COVID-19) pandemic is a rare/special situation where people can express their feelings on Internet-based social networks. Social media is emerging as the biggest platform in recent years where people spend most of their time expressing themselves and their emotions. This research is based on gathering data from Twitter and analyzing the behavior of the people during the COVID-19 lockdown. The research is based on the logic expressed by people in this perspective and emotions for the suffering of COVID-19 and lockdown. In this research, we have used a Long Short-Term Memory (LSTM) network model with Convolutional Neural Network using Keras python deep-learning library to determine whether social media platform users are depressed in terms of positive, negative, or neutral emotional out bust based on their Twitter posts. The results showed that the model has 88.14% accuracy (representation of the correct prediction over the test dataset) after 10 epochs which most tweets showed had neutral polarity. The evaluation shows interesting results in positive (1), negative (–1), and neutral (0) emotions through different visualization. metadata Dumka, Ankur; Verma, Parag; Singh, Rajesh; Kumar Bisht, Anil; Anand, Divya; Moaiteq Aljahdali, Hani; Delgado Noya, Irene y Aparicio Obregón, Silvia mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, divya.anand@uneatlantico.es, SIN ESPECIFICAR, irene.delgado@uneatlantico.es, silvia.aparicio@uneatlantico.es (2022) A Novel Deep Learning Based Healthcare Model for COVID-19 Pandemic Stress Analysis. Computers, Materials & Continua, 72 (3). pp. 6029-6044. ISSN 1546-2226

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Wearable monitoring devices are in demand in recent times for monitoring daily activities including exercise. Moreover, it is widely utilizing for preventing injuries of athletes during a practice session and in few cases, it leads to muscle fatigue. At present, emerging technology like the internet of things (IoT) and sensors is empowering to monitor and visualize the physical data from any remote location through internet connectivity. In this study, an IoT-enabled wearable device is proposing for monitoring and identifying the muscle fatigue condition using a surface electromyogram (sEMG) sensor. Normally, the EMG signal is utilized to display muscle activity. Arduino controller, Wi-Fi module, and EMG sensor are utilized in developing the wearable device. The Time-frequency domain spectrum technique is employed for classifying the three muscle fatigue conditions including mean RMS, mean frequency, etc. A real-time experiment is realized on six different individuals with developed wearable devices and the average RMS value assists to determine the average threshold of recorded data. The threshold level is analyzed by calculating the mean RMS value and concluded three fatigue conditions as >2 V: Extensive); 1–2 V: Moderate, and <1 V: relaxed. The warning alarm system was designed in LabVIEW with three color LEDs to indicate the different states of muscle fatigue. Moreover, the device is interfaced with the cloud through the internet provided with a Wi-Fi module embedded in wearable devices. The data available in the cloud server can be utilized for forecasting the frequency of an individual to muscle fatigue. metadata Gehlot, Anita; Singh, Rajesh; Siwach, Sweety; Vaseem Akram, Shaik; Alsubhi, Khalid; Singh, Aman; Delgado Noya, Irene y Choudhury, Sushabhan mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, irene.delgado@uneatlantico.es, SIN ESPECIFICAR (2022) Real Time Monitoring of Muscle Fatigue with IoT and Wearable Devices. Computers, Materials & Continua, 72 (1). pp. 999-1015. ISSN 1546-2226

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés According to the World Health Organization (WHO), Parkinson’s disease (PD) is a neurodegenerative disease of the brain that causes motor symptoms including slower movement, rigidity, tremor, and imbalance in addition to other problems like Alzheimer’s disease (AD), psychiatric problems, insomnia, anxiety, and sensory abnormalities. Techniques including artificial intelligence (AI), machine learning (ML), and deep learning (DL) have been established for the classification of PD and normal controls (NC) with similar therapeutic appearances in order to address these problems and improve the diagnostic procedure for PD. In this article, we examine a literature survey of research articles published up to September 2022 in order to present an in-depth analysis of the use of datasets, various modalities, experimental setups, and architectures that have been applied in the diagnosis of subjective disease. This analysis includes a total of 217 research publications with a list of the various datasets, methodologies, and features. These findings suggest that ML/DL methods and novel biomarkers hold promising results for application in medical decision-making, leading to a more methodical and thorough detection of PD. Finally, we highlight the challenges and provide appropriate recommendations on selecting approaches that might be used for subgrouping and connection analysis with structural magnetic resonance imaging (sMRI), DaTSCAN, and single-photon emission computerized tomography (SPECT) data for future Parkinson’s research. metadata Rana, Arti; Dumka, Ankur; Singh, Rajesh; Panda, Manoj Kumar y Priyadarshi, Neeraj mail SIN ESPECIFICAR (2022) A Computerized Analysis with Machine Learning Techniques for the Diagnosis of Parkinson’s Disease: Past Studies and Future Perspectives. Diagnostics, 12 (11). p. 2708. ISSN 2075-4418

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Parkinson’s disease (PD) is a neurodegenerative disease that affects the neural, behavioral, and physiological systems of the brain. This disease is also known as tremor. The common symptoms of this disease are a slowness of movement known as ‘bradykinesia’, loss of automatic movements, speech/writing changes, and difficulty with walking at early stages. To solve these issues and to enhance the diagnostic process of PD, machine learning (ML) algorithms have been implemented for the categorization of subjective disease and healthy controls (HC) with comparable medical appearances. To provide a far-reaching outline of data modalities and artificial intelligence techniques that have been utilized in the analysis and diagnosis of PD, we conducted a literature analysis of research papers published up until 2022. A total of 112 research papers were included in this study, with an examination of their targets, data sources and different types of datasets, ML algorithms, and associated outcomes. The results showed that ML approaches and new biomarkers have a lot of promise for being used in clinical decision-making, resulting in a more systematic and informed diagnosis of PD. In this study, some major challenges were addressed along with a future recommendation metadata Rana, Arti; Dumka, Ankur; Singh, Rajesh; Panda, Manoj Kumar; Priyadarshi, Neeraj y Twala, Bhekisipho mail SIN ESPECIFICAR (2022) Imperative Role of Machine Learning Algorithm for Detection of Parkinson’s Disease: Review, Challenges and Recommendations. Diagnostics, 12 (8). p. 2003. ISSN 2075-4418

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Abierto Inglés Mold breakout is one of the significant problems in a continuous casting machine (caster). It represents one of the key areas within the steel production facilities of a steel plant. A breakout event on a caster will always cause safety hazards, high repair costs, loss of production, and shutdown of the caster for a short while. In this paper, a logic-judgment-based mold breakout prediction system has been developed for a continuous casting machine. This system developed new algorithms to detect the different sticker behaviors. With more algorithms running, each algorithm is more specialized in the other behaviors of stickers. This new logic-based breakout prediction system (BOPS) not only detects sticker breakouts but also detects breakouts that takes place due to variations in casting speed, mold level fluctuation, and taper/mold problems. This system also finds the exact location of the breakout in the mold and reduces the number of false alarms. The task of the system is to recognize a sticker and prevent a breakout. Moreover, the breakout prediction system uses an online thermal map of the mold for process visualization and assisting breakout prediction. This is done by alerting the operating staff or automatically reducing the cast speed according to the location of alarmed thermocouples, the type of steel, the tundish temperature, and the size of the cold slab width. By applying the proposed model in an actual steel plant, field application results show that it could timely detect all 13 breakouts with a detection ratio of 100%, and the frequency of false alarms was less than 0.056% times/heat. It has the additional advantage of not needing a lot of learning data, as most neural networks do. Thus, this new logical BOPS system should not only detect the sticker breakouts but also detect breakouts taking place due to variations in casting speed and mold level fluctuation. metadata Ansari, Md Obaidullah; Ghose, Joyjeet; Chattopadhyaya, Somnath; Ghosh, Debasree; Sharma, Shubham; Sharma, Prashant; Kumar, Abhinav; Li, Changhe; Singh, Rajesh y Eldin, Sayed M. mail SIN ESPECIFICAR (2022) An Intelligent Logic-Based Mold Breakout Prediction System Algorithm for the Continuous Casting Process of Steel: A Novel Study. Micromachines, 13 (12). p. 2148. ISSN 2072-666X

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés At this time, efforts are being made on a worldwide scale to accomplish sustainable development objectives. It has, thus, now become essential to investigate the part of technology in the accomplishment of these Sustainable Development Goals (SDGs), as this will enable us to circumvent any potential conflicts that may arise. The importance of wastewater management in the accomplishment of these goals has been highlighted in the study. The research focuses on the role of fourth industrial revolution in meeting the Sustainable Goals for 2030. Given that water is the most important resource on the planet and since 11 of the 17 Sustainable Goals are directly related to having access to clean water, effective water management is the most fundamental need for achieving these goals. The age of Industry 4.0 has ushered in a variety of new solutions in many industrial sectors, including manufacturing, water, energy, healthcare, and electronics. This paper examines the present creative solutions in water treatment from an Industry-4.0 viewpoint, focusing on big data, the Internet of Things, artificial intelligence, and several other technologies. The study has correlated the various concepts of Industry 4.0 along with water and wastewater management and also discusses the prior work carried out in this field with help of different technologies. In addition to proposing a way for explaining the operation of I4.0 in water treatment through a systematic diagram, the paper makes suggestions for further research as well. metadata Pandey, Shivam; Twala, Bhekisipho; Singh, Rajesh; Gehlot, Anita; Singh, Aman; Caro Montero, Elisabeth y Priyadarshi, Neeraj mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, aman.singh@uneatlantico.es, elizabeth.caro@uneatlantico.es, SIN ESPECIFICAR (2022) Wastewater Treatment with Technical Intervention Inclination towards Smart Cities. Sustainability, 14 (18). p. 11563. ISSN 2071-1050

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Currently, two-wheelers are the most popular mode of transportation, driven by the majority the people. Research by the World Health Organization (WHO) identifies that most two-wheeler deaths are caused due to not wearing a helmet. However, the advancement in sensors and wireless communication technology empowers one to monitor physical things such as helmets through wireless technology. Motivated by these aspects, this article proposes a wireless personal network and an Internet of Things assisted system for automating the ignition of two-wheelers with authorization and authentication through the helmet. The authentication and authorization are realized with the assistance of a helmet node and a two-wheeler node based on 2.4 GHz RF communication. The helmet node is embedded with three flex sensors utilized to experiment with different age groups and under different temperature conditions. The statistical data collected during the experiment are utilized to identify the appropriate threshold value through a t-test hypothesis for igniting the two-wheelers. The threshold value obtained after the t-test is logged in the helmet node for initiating the communication with the two-wheeler node. The pairing of the helmet node along with the RFID key is achieved through 2.4 GHZ RF communication. During real-time implementation, the helmet node updates the status to the server and LABVIEW data logger, after wearing the helmet. Along with the customization of hardware, a LABVIEW data logger is designed to visualize the data on the server side. metadata Gehlot, Anita; Singh, Rajesh; Kuchhal, Piyush; Kumar, Adesh; Singh, Aman; Alsubhi, Khalid; Ibrahim, Muhammad; Gracia Villar, Santos y Breñosa, Jose mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, josemanuel.brenosa@uneatlantico.es (2021) WPAN and IoT Enabled Automation to Authenticate Ignition of Vehicle in Perspective of Smart Cities. Sensors, 21 (21). p. 7031. ISSN 1424-8220