Assessment of FNAC Using 23-Gauge Needle in the Diagnosis of Thyroid Lesions with Cyto-Histopathological Correlation
- Thamer H. Alghamdi
- Reseived: 29 November, 2021 Received in Revised Form: 26 December, 2021 Accepted: 2 January, 2022
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Background: Thyroid diseases are among the commonest disorders of endocrine system worldwide. Fine needle aspiration cytology (FNAC) is the most reliable screening test and easy, cost-effective procedure in diagnosing thyroid lesions. Objective: to assess the frequency of Bethesda system diagnostic categories and correlation of FNAC results with histopathology. Material and Methods: This study was conducted on 634 thyroid FNA smears received between January 2015 and December 2019. Cytological findings were compared to histopathology in cases had surgical excision. Results: Out of 617 of thyroid FNAC smears, ND/US category comprised 129 (20.9%). 381 (60.7%) were diagnosed as benign; atypia of undetermined significance (AUS)/follicular lesion of undetermined significance (AUS/FLUS) comprised 77 cases (12.5%). Follicular neoplasm (FN)/suspicious for follicular neoplasm (FN/SFN) included 11 (1.8%), 3 (0.5%) cases were diagnosed as SM, and 16 cases (2.6%) were within malignant category. Sensitivity, specificity, PPV, NPV and accuracy of FNAC were 82.8%, 94%, 88.9%, 90.4% and 89.9% respectively. Conclusion: FNAC is a highly sensitive and specific procedure in diagnosing different thyroid lesions thereby help in decreasing number of surgeries in benign lesions
Performance Analysis of Full and Semi Signals Integration Approaches in Digital Telecommunication Systems
- Ashraf M. Aziz Shawki A. Saad Ahmed S. Shalaby, Mohamed Mostafa
- Reseived: 9 November 2021 Received in Revised Form: 20 March, 2022 Accepted: 21 March, 2022
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Signals integration is used in digital telecommunication systems to reduce the multipath effect. The two main approaches for signals integration in diversity telecommunication systems are full and semi signals integration. In full signals integration systems, there are multiple receivers producing very large number of bits and the entire signals integration system is closely resembled analog multiple receivers implementations. This approach achieves the optimum performance at the expense of high cost and complexity. In semi signals integration systems, only few number of bits are used after preliminary processing of signals at each individual receiver. This method could reduce system complexity and cost at the expense of overall performance degradation. This paper provides performance analysis of full and semi signals integration approaches in digital telecommunication systems in case of non-coherent differential phase shift keying receivers with Gaussian noise and Rician fading stochastic model. The performance loss due to semi signals integration is analyzed for different number of information bits.
Developing Empirical Models to Estimate Evaporation Rate from the Wadi Alaqiq Reservoir
- Khalid A. Alkhuzai
- Reseived: 28 January 2022 Received in Revised Form: 12 May, 2022 Accepted: 18 May, 2022
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Evaporation loss is an important component of the hydrological cycle; the precise estimation of evaporation rates from various water sources plays an important role in the planning, design, and operation of natural water resources, particularly in arid regions such as the Kingdom of Saudi Arabia (KSA). Estimating evaporation from the Wadi Alaqiq reservoir is a significant issue for decision-makers; hence, it would be useful to develop an empirical model to calculate evaporation from the dam lake directly using meteorological data. To achieve this, meteorological data, including data on evaporation, relative humidity, temperature, vapor pressure, pressure, and wind speed, were collected and processed for the Wadi Alaqiq dam. Two popular empirical equations in hydrology by Meyer and Harbeck were selected as base points for developing new equations to calculate evaporation from the Wadi Alaqiq reservoir. Calibration was performed for the two equations with the measured records of evaporation; the Meyer equation was robust and provided estimates of measured evaporation with reasonably acceptable accuracy, and its performance was found to be better than that of the Harbeck equation. Using the selected equations and based on the measured climatic data for the Wadi Alaqiq dam and with the help of hydrological and mathematical analyses, new coefficients were developed for the Meyer and Harbeck equations to fit the evaporation calculation from the Wadi Alaqiq reservoir. To develop new coefficients for the developed equations, a methodology based on optimization using three different objective functions was applied. The first objective function was based on minimizing absolute error by applying statistical analysis using Microsoft Excel; the second objective function was a 45-degree line to equality between the measured and calculated evaporation; the third objective function was convergence. These functions helped to produce values of optimized coefficients for the developed equations. Two equations, based on the Meyer and Harbeck equations, were developed to estimate evaporation from the reservoir of the Wadi Alaqiq dam.
An Intelligent Approach for Improving Students’ Performance
- Sami A. Al Ghamdi
- Reseived: 18 January 2022 Received in Revised Form: 15 May, 2022 Accepted: 19 May, 2022
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The employment of data mining approaches to resolve educational tasks have increases tremendously in the past decade. This paper investigates the efficiency of employing a combination of data mining techniques to extract insightful knowledge from students’ information. Particularly, association rules algorithm known as Apriori algorithm is used to find rules between courses. In addition, a decision tree classifier known as J48 is applied on the data to predict students’ performance. The data went through a features selection process where features with high influence were selected. Experiments are performed on WEKA, a data mining and machine learning open-source software, on a real-world dataset collected from the Information Systems department at Al-Baha university. The results show that J48 classifier outperformed two other classifiers (IBk and Naïve Bayes) in terms of accuracy.
