Performance investigation of a novel water–power cogeneration plant (WPCP) based on humidification dehumidification (HDH) method

Performance analysis of a water-power combined system with air-heated humidification dehumidification process

This paper presents a multiobjective optimization approach for synthesizing water distribution networks involving dual-purpose power plants. The proposed model accounts for environmental, economic, and social objectives by accounting for greenhouse gas emissions, jobs, and net profit. The model considers water and energy demands for domestic, agricultural, and industrial users. Energy is provided through several alternatives including fossil fuels (i.e., natural gas and oil), biofuels (i.e., biomass, biogas, biodiesel, and bioethanol), and solar energy. Water demands are satisfied by fresh water from dams, lakes, rivers, aquifers, and artificial storage tanks. The proposed model is applied to a case study from the Mexican State of Sonora. The results show the viability of the dual-purpose power–water plants, the merits of incorporating solar energy in the system, and the economic, environmental, and social benefits of applying the proposed approach. The optimal solution yields a total annual profit of $MM...

Multiobjective Optimization of Dual-Purpose Power Plants and Water Distribution Networks

Experiments on carbon black production from coal tar via chemical looping pyrolysis were performed in a fluidized bed reactor using natural hematite, hematite/γ-Al2O3 (Fe/Al), and hematite/NiO (Fe/Ni) composites as oxygen carriers (OCs). After 3 redox cycles, thermogravimetric analysis combined with differential scanning calorimetry results show that, in comparison to natural hematite, the oxidation rate of the Fe/Al OC became faster above 700 °C; however, the oxidation performance of the Fe/Ni OC was always poor. The addition of γ-Al2O3 could effectively inhibit carbon deposition; nonetheless, NiO exhibited the opposite effect. On the basis of the burning temperature, the carbon deposition on reduced OCs was mainly hard coke. The X-ray diffraction analysis showed that NiO was not only more effective than γ-Al2O3 to promote the reduction of Fe2O3 in compound OCs but also increased the sintering trend. The scanning electron microscopy analysis indicated the melting of original grains at the surface of the ...

Carbon Deposition and Sintering Characteristics on Iron-Based Oxygen Carriers in the Catalytic Cracking Process of Coal Tar

Today’s advancements in wireless communication technologies have resulted in a tremendous volume of data being generated. Most of our information is part of a widespread network that connects various devices across the globe. The capabilities of electronic devices are also increasing day by day, which leads to more generation and sharing of information. Similarly, as mobile network topologies become more diverse and complicated, the incidence of security breaches has increased. It has hampered the uptake of smart mobile apps and services, which has been accentuated by the large variety of platforms that provide data, storage, computation, and application services to end-users. It becomes necessary in such scenarios to protect data and check its use and misuse. According to the research, an artificial intelligence-based security model should assure the secrecy, integrity, and authenticity of the system, its equipment, and the protocols that control the network, independent of its generation, in order to deal with such a complicated network. The open difficulties that mobile networks still face, such as unauthorised network scanning, fraud links, and so on, have been thoroughly examined. Numerous ML and DL techniques that can be utilised to create a secure environment, as well as various cyber security threats, are discussed. We address the necessity to develop new approaches to provide high security of electronic data in mobile networks because the possibilities for increasing mobile network security are inexhaustible.

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A Systematic Review on Machine Learning and Deep Learning Models for Electronic Information Security in Mobile Networks

Solar power and desalination plant for carbon black industry: Improvised techniques

Effects of Visual Referencing on Backward and Forward Treadmill Walking in VR Environments

A configurable self-calibrated power efficient five-bit error correction code is proposed to correct both single bit random and burst errors up to five bits; providing 100% error correction probability with crosstalk avoidance. It can also correct higher-order error up to 9 bits with an error correction probability tolerance of 73% for on-chip interconnection links. Single error correction and double error detection with extended Hamming code (22,16) is utilised along with standard triplication error correction methods in the proposed code. Self-calibration algorithm and data stream rerouting block are integrated into the error correction code to achieve power efficiency. Reliability, link power consumption, and link swing voltage are estimated using an analytical model used in a network-on-chip. Area, power, and delay of the codec are obtained using Synopsys tools utilising UMC 90 nm technology. The proposed method provides 32–73% power saving and 22.3–60.6% delay reduction with negligible area overhead compared with the state-of-the-art works. Estimated results prove that it provides a 40.5–50% reduction in link swing voltage and link power consumption compared with the state-of-the-art works. The proposed code is more appropriate for on-chip interconnect links where it provides high reliability and low swing voltage with high error correction capability compared with existing codes.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-cdt.2019.0082

Power efficient error correction coding for on-chip interconnection links

Many mental disorders are caused due to improper regulation of the brain and depression is one such. It affects both children and adults and is very common among teenagers. There are many challenges clinicians face regarding the management of this disease. These challenges have prompted the development of various neuroimaging techniques that effectively diagnose the condition. The main techniques are Magnetic resonance imaging (MRI) and Positron emission tomography (PET) which have gained momentum over the years. Advanced MRI techniques help study certain regions of the brain such as hippocampus and amygdala. Effective treatments for depression include antidepressant medications and brain stimulation techniques. Although treatments are effective for a lot of people, there is still room for improvement. This article (1) presents background on depression, its types, symptoms and risk factors; (2) elaborates the neuroimaging techniques used and reviews the various techniques adopted over the years to study depression; and (3) discusses the treatment methods that can be practised to cure depression. KeywordsBrain Stimulation Techniques, Depression,

/pdf/assessment-of-major-depressive-disorders-through-112ib9bvn3.pdf

Sivakumar Rajagopal

Papers

Solar power and desalination plant for carbon black industry: Improvised techniques

Effects of Visual Referencing on Backward and Forward Treadmill Walking in VR Environments

Power efficient error correction coding for on-chip interconnection links

Assessment of Major Depressive Disorders through Neuroimaging Studies and Their Treatment Methods

Area efficient high-performance time to digital converters