Palm Tree Coplanar Vivaldi Antenna Array on the Same Substrate Size: Design and Performance Evaluation

This paper aims to describe the performance of the palm tree Coplanar Vivaldi Antenna Array (CVA) that was simulated from 0.25-6.25 GHz in terms of return loss and radiation pattern. Palm Tree Coplanar Vivaldi Antenna is available in four different configurations: single-element, two-element array, four-element array, and an eight-element array. We create a feeding network and radiator patch for two, four, and eight-array antennas. The simulation results demonstrate that the single-element antenna has the best return loss performance and can cover all frequency work from 0.25-6.25 GHz. In contrast, the antenna array can only cover multiband frequency. At 3 GHz, a single-element antenna has a directivity of 8.77 dBi, a sidelobe level of -2.2 dB, and a beamwidth of 63.70. In contrast, an antenna array of 8 elements has a directivity of 15.5 dBi, a sidelobe level of -12.6 dB, and a beamwidth of 80. Using the same substrate size, by configuring the Vivaldi Coplanar antenna to be an array at a frequency of 3 GHz, the 1×8 array antenna has a 6.73dBi improvement in directivity, a 10.4 dB boost in side lobe level, and a 55.70 enhanced in beamwidth performance compared to a single element. According to the simulation findings, the radiation pattern performance of the. Palm Tree CVA is greater than a single element in the same substrate size. Good directivity, SLL, and beamwidth performance make the proposed Palm Tree CVA array suitable for integration in telecommunication, radar, or cognitive radio applications

Forest-friendly pedagogy (PeRIMBA) at indigenous school : risk and risk perceptions

The Forest-friendly pedagogy (PeRIMBA) refers to the implementation of outdoor learning session by using forest elements as the learning aid and site. There are four basic principles of PeRIMBA which known as supportive environment, task divided into small portions, the usage of natural surroundings and the involvement of all the senses. The implementation of PeRIMBA introduces a risk-taking approach that will offer the opportunities for teachers and students to engage in risky activities during learning session. This risky activity may seem daunting but if the risks are well managed, the learning sessions will be meaningful. In promoting meaningful learning especially to the indigenous school, Malaysia Ministry of Education support and highlight two intervention action plan that promote flexible classroom and fun learning. Flexible curriculum delivery is not dependent on classroom learning only and fun learning promotes the integration and application of forest elements. However, this intervention action plan needs further research and study especially in the field of risk. The emergence of a social science perspective in the field of risk research has opened up new perspectives to define, measure, and explain the concept of risk. Some of the new risk components proposed in social science studies such as shock, threat, danger, lack of control, and uncertainty. Moreover, the fear and unknown factors are components that influence the perceptions of risk. The input on risk and risk perception will be an added value to teachers to implement PeRIMBA in their teaching and learning sessions. These concepts then lead to risk perception that, in turn, influenced risk assessment and risk management

A 2.4 GHz Two Stage CMOS Class-F Power Amplifier for Wireless Applications

The design of a 2.4-GHz CMOS class-F power amplifier (PA) for wireless applications is presented in this paper. The class- F PA design is implemented using 0.13-μm CMOS process. It utilizes two stages cascade topology and the transistors are arranged in parallel to reduce the transistor’s on resistance which correspondingly increase the PA efficiency. The simulation results show that the PA delivers 12 dBm output power and 60% power added efficiency (PAE) into a 50 Ω load. The supply voltage is 1.3 V and the chip layout is 0.66 mm²

UWB-based early breast cancer existence prediction using artificial intelligence for large data set

Breast cancer is the most often identified cancer among women and the main reason for cancer-related deaths worldwide. The most effective methods for controlling and treating this disease through breast screening and emerging detection techniques. This paper proposes an intelligent classifier for the early detection of breast cancer using a larger dataset since there is limited researcher focus on that for better analytic models. To ensure that the issue is tackled, this project proposes an intelligent classifier using the Probabilistic Neural Network (PNN) with a statistical feature model that uses a more significant size of data set to analyze the prediction of the presence of breast cancer using Ultra Wideband (UWB). The proposed method is able to detect breast cancer existence with an average accuracy of 98.67%. The proposed module might become a potential user-friendly technology for early breast cancer detection in domestic use

A Flexible and Compact Metamaterial UHF RFID Tag for Remote Sensing in Human Health

This paper presents a miniaturized UHF RFID tag antenna with increased gain using meander line techniques and metamaterial (MTM). The designed tag operates in the UHF RFID frequency band ranging from 860 to 960 MHz. It comprises of meandered lines with two hexagonal split ring resonators (H-SRRs) MTM cells. It is designed on a photo paper as its substrate which is 0.27 mm thick, with a dielectric constant of 3.2 and loss tangent of 0.05. Next, an RFID tag (NXP SL381213 UCODE G2iL chip) with an impedance of 23-j224 Ω is integrated with the proposed antenna to assess its performance in terms of reflection coefficient, antenna gain and maximum reading range. The overall size of the tag is 92 mm x26 mm

Optimized intelligent classifier for early breast cancer detection using ultra-wide band transceiver

Breast cancer is the most common cancer diagnosed in women and the leading cause of cancer-related deaths among women worldwide. The death rate is high because of the lack of early signs. Due to the absence of a cure, immediate treatment is necessary to remove the cancerous cells and prolong life. For early breast cancer detection, it is crucial to propose a robust intelligent classifier with statistical feature analysis that considers parameter existence, size, and location. This paper proposes a novel Multi-Stage Feature Selection with Binary Particle Swarm Optimization (MSFS–BPSO) using Ultra-Wideband (UWB). A collection of 39,000 data samples from non-tumor and with tumor sizes ranging from 2 to 7 mm was created using realistic tissue-like dielectric materials. Subsequently, the tumor models were inserted into the heterogeneous breast phantom. The breast phantom with tumors was imaged and represented in both time and frequency domains using the UWB signal. Consequently, the dataset was fed into the MSFS–BPSO framework and started with feature normalization before it was reduced using feature dimension reduction. Then, the feature selection (based on time/frequency domain) using seven different classifiers selected the frequency domain compared to the time domain and continued to perform feature extraction. Feature selection using Analysis of Variance (ANOVA) is able to distinguish between class-correlated data. Finally, the optimum feature subset was selected using a Probabilistic Neural Network (PNN) classifier with the Binary Particle Swarm Optimization (BPSO) method. The research findings found that the MSFS–BPSO method has increased classification accuracy up to 96.3% and given good dependability even when employing an enormous data sample

Existing and emerging breast cancer detection technologies and its challenges: a review

Breast cancer is the most leading cancer occurring in women and is a significant factor in female mortality. Early diagnosis of breast cancer with Artificial Intelligent (AI) developments for breast cancer detection can lead to a proper treatment to affected patients as early as possible that eventually help reduce the women mortality rate. Reliability issues limit the current clinical detection techniques, such as Ultra-Sound, Mammography, and Magnetic Resonance Imaging (MRI) from screening images for precise elucidation. The capability to detect a tumor in early diagnosis, expensive, relatively long waiting time due to pandemic and painful procedure for a patient to perform. This article aims to review breast cancer screening methods and recent technological advancements systematically. In addition, this paper intends to explore the progression and challenges of AI in breast cancer detection. The next state of the art between image and signal processing will be presented, and their performance is compared. This review will facilitate the researcher to insight the view of breast cancer detection technologies advancement and its challenges

Adolescent to Adolescent Transformation Program- Nurturing, Enhancing and Promoting Adolescents’ Healthy Habit (ATAP-NEPAH): Curbing Social Problems Among Adolescents in Kelantan Through Peer-To-Peer Health Education

The objectives of ATAP-NEPAH are to enhance and nurture healthy habits among adolescents as well as to empower adolescents in inculcating these healthy habits among them. Health education through peer-to-peer approach is used to instill the knowledge on important areas such as sexual and reproductive health, smoking, substance abuse, illegal street racing (rempit) and mental health. Specific modules were developed by experts (lecturers) in multidisciplinary fields in collaboration with Malaysian Association for Adolescent Health (MAAH), National Population and Family Development Board (NPFDB), Reproductive Health Association of Kelantan (REHAK) and Rhaudatus Sakinah Kelantan. The trained Medical Students Facilitator Team (MSFT) of USM became trainers to secondary one school students. The selected school students were trained by the medical students to become peer educators to their juniors and peers. There was improvement in the readiness level of peer educators, knowledge and attitude towards healthy habits and risky behaviors of other school students after the intervention

Characterization of greater middle eastern genetic variation for enhanced disease gene discovery

The Greater Middle East (GME) has been a central hub of human migration and population admixture. The tradition of consanguinity, variably practiced in the Persian Gulf region, North Africa, and Central Asia1-3, has resulted in an elevated burden of recessive disease4. Here we generated a whole-exome GME variome from 1,111 unrelated subjects. We detected substantial diversity and admixture in continental and subregional populations, corresponding to several ancient founder populations with little evidence of bottlenecks. Measured consanguinity rates were an order of magnitude above those in other sampled populations, and the GME population exhibited an increased burden of runs of homozygosity (ROHs) but showed no evidence for reduced burden of deleterious variation due to classically theorized ‘genetic purging’. Applying this database to unsolved recessive conditions in the GME population reduced the number of potential disease-causing variants by four- to sevenfold. These results show variegated genetic architecture in GME populations and support future human genetic discoveries in Mendelian and population genetics

Quadruple band MIMO dielectric resonator antenna for 5G SUB-6 GHz applications

A quadruple band with L-slotted multiple-input-multiple-output (MIMO) square dielectric resonator antenna (SDRA) for fifth generation (5G) applications at the sub-6 GHz band is presented, which can cover 5G new radio band N77 (3.3–4.2) GHz and N79 (4.4–5) GHz. The proposed structure consists of a single SDRA mounted on a substrate excited by an aperture slot underneath dielectric resonators (DR)s. The performance of SDRA is improved by introducing L-shaped slot on the central part of DRA. Results show that the MIMO SDRA antenna achieves S11\u3c-10 dB and S21\u3c=-15 dB for all resonant frequencies at 3.5 GHz, 4 GHz, 4.6 GHz, and 5 GHz, indicating good performance of the antenna at the desired frequencies. The maximum realized gain is 5.61 dB and 5.01 dB at port 1, 4 GHz and port 2, 4.6 GHz, respectively. The radiation efficiencies are acceptable for all resonant frequencies. Moreover, the proposed antenna design achieved good envelop correlation coefficient (ECC) and diversity gain (DG) at the desired frequencies. Thus, the antenna can be used for 5G sub-6 GHz applications