Impact of Cross-Validation on Machine Learning Models for Early Detection of Intrauterine Fetal Demise.

Intrauterine fetal demise in women during pregnancy is a major contributing factor in prenatal mortality and is a major global issue in developing and underdeveloped countries. When an unborn fetus passes away in the womb during the 20th week of pregnancy or later, early detection of the fetus can help reduce the chances of intrauterine fetal demise. Machine learning models such as Decision Trees, Random Forest, SVM Classifier, KNN, Gaussian Naïve Bayes, Adaboost, Gradient Boosting, Voting Classifier, and Neural Networks are trained to determine whether the fetal health is Normal, Suspect, or Pathological.

Computational Intelligence in Cancer Diagnostics: A Contemporary Review of Smart Phone Apps, Current Problems, and Future Research Potentials.

Cancer is a dangerous and sometimes life-threatening disease that can have several negative consequences for the body, is a leading cause of mortality, and is becoming increasingly difficult to detect. Each form of cancer has its own set of traits, symptoms, and therapies, and early identification and management are important for a positive prognosis. Doctors utilize a variety of approaches to detect cancer, depending on the kind and location of the tumor.

Leveraging Computational Intelligence Techniques for Diagnosing Degenerative Nerve Diseases: A Comprehensive Review, Open Challenges, and Future Research Directions.

Degenerative nerve diseases such as Alzheimer's and Parkinson's diseases have always been a global issue of concern. Approximately 1/6th of the world's population suffers from these disorders, yet there are no definitive solutions to cure these diseases after the symptoms set in. The best way to treat these disorders is to detect them at an earlier stage.

AI-Powered Blockchain Technology for Public Health: A Contemporary Review, Open Challenges, and Future Research Directions.

Blockchain technology has been growing at a substantial growth rate over the last decade. Introduced as the backbone of cryptocurrencies such as Bitcoin, it soon found its application in other fields because of its security and privacy features. Blockchain has been used in the healthcare industry for several purposes including secure data logging, transactions, and maintenance using smart contracts.

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

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.

A Joint Resource Allocation, Security with Efficient Task Scheduling in Cloud Computing Using Hybrid Machine Learning Techniques.

The rapid growth of cloud computing environment with many clients ranging from personal users to big corporate or business houses has become a challenge for cloud organizations to handle the massive volume of data and various resources in the cloud. Inefficient management of resources can degrade the performance of cloud computing. Therefore, resources must be evenly allocated to different stakeholders without compromising the organization's profit as well as users' satisfaction.

Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies.

Cloud computing has become integral lately due to the ever-expanding Internet-of-things (IoT) network. It still is and continues to be the best practice for implementing complex computational applications, emphasizing the massive processing of data. However, the cloud falls short due to the critical constraints of novel IoT applications generating vast data, which entails a swift response time with improved privacy.

Performance Assessment of Certain Machine Learning Models for Predicting the Major Depressive Disorder among IT Professionals during Pandemic times.

Major depressive disorder (MDD) is the most common mental disorder in the present day as all individuals' lives, irrespective of being employed or unemployed, is going through the depression phase at least once in their lifetime. In simple terms, it is a mood disturbance that can persist for an individual for more than a few weeks to months. In MDD, in most cases, the individuals do not consult a professional, and even if being consulted, the results are not significant as the individuals find it challenging to identify whether they are depressed or not.

Fluid-Structure Coupling Effects in a Dual U-Tube Coriolis Mass Flow Meter.

Coriolis mass flowmeters are highly customized products involving high-degree fluid-structure coupling dynamics and high-precision manufacture. The typical delay from from order to shipment is at least 4 months. This paper presents some important design considerations through simulation and experiments, so as to provide manufacturers with a more time-efficient product design and manufacture process.

Performance Comparison of Advanced Ceramic Cladding Approaches via Solid-State and Traditional Welding Processes: A Review.

Ceramic coating has applications in enhancing the material's properties and can significantly improve the material's usability in varied temperatures and adverse operating conditions and widen its applicability scope. It can add to the various properties such as wear resistance, high-temperature degradation, thermal conductivity, material toughness, tensile strength, corrosion resistance, friction reduction, electric insulation, and the lifespan of the material. Various techniques have been suggested and implemented to achieve ceramic coating on a metal surface, each having their respective advantages and disadvantages.

Improved Diver Communication System by Combining Optical and Electromagnetic Trackers.

The increasing need for observation in seawater or ocean monitoring systems has ignited a considerable amount of interest and the necessity for enabling advancements in technology for underwater wireless tracking and underwater sensor networks for wireless communication. This type of communication can also play an important role in investigating ecological changes in the sea or ocean-like climate change, monitoring of biogeochemical, biological, and evolutionary changes. This can help in controlling and maintaining the production facilities of outer underwater grid blasting by deploying unmanned underwater vehicles (UUVs).

Sensor-Assisted Assessment of the Tribological Behavior Patterns of AA7075 Hybrid MMC Reinforced with Multi-Wall Carbon Nanotubes and Pulverized Fuel Ash.

In recent years, the deployment of sensors and other ancillary technologies has turned out to be vital in the investigation of tribological behavioral patterns of composites. The tribological behavioral patterns of AA7075 hybrid metal matrix composites (MMCs) reinforced with multi-wall carbon nanotubes (MWCNTs), and pulverized fuel ash (PFA) were investigated in this work. The stir casting technique was used to fabricate the composites.

Realizing a Novel Friction Stir Processing-Enabled FWTPET Process for Strength Enhancement Using Firefly and PSO Methods.

The friction welding of tube to tube plate using an external tool (FWTPET) is widely deployed in several industrial applications, such as aerospace, automotive, and power plants. Moreover, for achieving a better tensile strength and hardness in the weld zone, the friction stir processing (FSP) technique was incorporated into the FWTPET process for joining aluminum alloys (AA6063 tube, AA6061 tube plate). Furthermore, it has to be noted that FWTPET was applied for joining the AA6063 tube to the AA6061 tube plate, and FSP was deployed for reinforcing the weld zone with carbon nanotube (CNT) and silicon nitride (SiN) particles, thereby attaining the desirable mechanical properties.

Thermal-Feature System Identification for a Machine Tool Spindle.

The internal temperature is an important index for the prevention and maintenance of a spindle. However, the temperature inside the spindle is undetectable directly because there is no space to embed a temperature sensor, and drilling holes will reduce its mechanical stiffness. Therefore, it is worthwhile understanding the thermal-feature of a spindle.

Vibration of a Rotating Micro-Ring under Electrical Field Based on Inextensible Approximation.

The problem of vibrations of rotating rings has been of interest for its wide applications in engineering, such as the vibratory ring gyroscopes. For the vibratory ring gyroscopes, the vibration of a micro ring is usually actuated and sensed by means of electrostatics. The analytical models of electrostatic microstructures are complicated due to their non-linear electromechanical coupling behavior.

Parameter Estimation of the Thermal Network Model of a Machine Tool Spindle by Self-made Bluetooth Temperature Sensor Module.

Thermal characteristic analysis is essential for machine tool spindles because sudden failures may occur due to unexpected thermal issue. This article presents a lumped-parameter Thermal Network Model (TNM) and its parameter estimation scheme, including hardware and software, in order to characterize both the steady-state and transient thermal behavior of machine tool spindles. For the hardware, the authors develop a Bluetooth Temperature Sensor Module (BTSM) which accompanying with three types of temperature-sensing probes (magnetic, screw, and probe).

The stiffness variation of a micro-ring driven by a traveling piecewise-electrode.

In the practice of electrostatically actuated micro devices; the electrostatic force is implemented by sequentially actuated piecewise-electrodes which result in a traveling distributed electrostatic force. However; such force was modeled as a traveling concentrated electrostatic force in literatures. This article; for the first time; presents an analytical study on the stiffness variation of microstructures driven by a traveling piecewise electrode.

Enhance the pyroelectricity of polyvinylidene fluoride by graphene-oxide doping.

The high quality properties and benefits of graphene-oxide have generated an active area of research where many investigations have shown potential applications in various technological fields. This paper proposes a methodology for enhancing the pyro-electricity of PVDF by graphene-oxide doping. The PVDF film with graphene-oxide is prepared by the sol-gel method.

CMOS-MEMS test-key for extracting wafer-level mechanical properties.

This paper develops the technologies of mechanical characterization of CMOS-MEMS devices, and presents a robust algorithm for extracting mechanical properties, such as Young's modulus, and mean stress, through the external electrical circuit behavior of the micro test-key. An approximate analytical solution for the pull-in voltage of bridge-type test-key subjected to electrostatic load and initial stress is derived based on Euler's beam model and the minimum energy method. Then one can use the aforesaid closed form solution of the pull-in voltage to extract the Young's modulus and mean stress of the test structures.

The electromechanical behavior of a micro-ring driven by traveling electrostatic force.

There is no literature mentioning the electromechanical behavior of micro structures driven by traveling electrostatic forces. This article is thus the first to present the dynamics and stabilities of a micro-ring subjected to a traveling electrostatic force. The traveling electrostatic force may be induced by sequentially actuated electrodes which are arranged around the flexible micro-ring.

A flexible proximity sensor fully fabricated by inkjet printing.

A flexible proximity sensor fully fabricated by inkjet printing is proposed in this paper. The flexible proximity sensor is composed of a ZnO layer sandwiched in between a flexible aluminum sheet and a web-shaped top electrode layer. The flexible aluminum sheet serves as the bottom electrode.

Review on the modeling of electrostatic MEMS.

Electrostatic-driven microelectromechanical systems devices, in most cases, consist of couplings of such energy domains as electromechanics, optical electricity, thermoelectricity, and electromagnetism. Their nonlinear working state makes their analysis complex and complicated. This article introduces the physical model of pull-in voltage, dynamic characteristic analysis, air damping effect, reliability, numerical modeling method, and application of electrostatic-driven MEMS devices.

Exploring threshold operation criteria of biostimulation for azo dye decolorization using immobilized cell systems.

This follow-up study provided an evaluation on threshold operation criteria of biostimulation in immobilized cell systems (ICSs) with Aeromonas hydrophila onto packing materials Porites corals. Essential nutrients in appropriate flow rate for biostimulation were inevitably required to maintain maximum attached cell population for cost-effective biodecolorization. With the method of "graphical reconstruction", the most economically feasible strategy of medium stimulation for color removal was quantitatively revealed.

Real time monitoring of temperature of a micro proton exchange membrane fuel cell.

Silicon micro-hole arrays (Si-MHA) were fabricated as a gas diffusion layer (GDL) in a micro fuel cell using the micro-electro-mechanical-systems (MEMS) fabrication technique. The resistance temperature detector (RTD) sensor was integrated with the GDL on a bipolar plate to measure the temperature inside the fuel cell. Experimental results demonstrate that temperature was generally linearly related to resistance and that accuracy and sensitivity were within 0.

Biophysical micromixer.

In this study a biophysical passive micromixer with channel anamorphosis in a space of 370 μm, which is shorter than traditional passive micromixers, could be created by mimicing features of vascular flow networks and executed with Reynolds numbers ranging from 1 to 90. Split and recombination (SAR) was the main mixing method for enhancing the convection effect and promoting the mixing performance in the biophysical channel. The 2D numerical results reveal that good mixing efficiency of the mixer was possible, with ε(mixing) = 0.