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Computer-Aided Diagnosis for the Early Breast Cancer Detection
Full text linkThe development of the use of medical image processing in the healthcare sector has contributed to enhancing the quality/accuracy of disease diagnosis or early detection because diagnosing a disease or cancer and identifying treatments manually is costly, time-consuming, and requires professional staff. Computer-aided diagnosis (CAD) system is a prominent tool for the detection of different forms of diseases, especially cancers, based on medical imaging. Digital image processing is a critical in the processing and analysis of medical images for the disease diagnosis and detection. This study introduces a CAD system for detecting breast cancer. Once the breast region is segmented from the mammograms image, certain texture and statistical features are extracted. Gray level run length matrix feature extraction technique is implemented to extracted texture features. On the other hand, statistical features such as skewness, mean, entropy, and standard deviation are extracted. Consequently, on the basis of the extracted features, support vector machine and K-nearest neighbor classifier techniques are utilized to classify the segmented region as normal or abnormal. The performance of the proposed approach has been investigated through extensive experiments conducted on the well-known Mammographic Image Analysis Society dataset of mammography images. The experimental findings show that the suggested approach outperforms other existing approaches, with an accuracy rate of 99.7%
ECG Signal Recognition Based on Lookup Table and Neural Networks
Full text linkElectrocardiograph (ECG) signals are very important part in diagnosis healthcare the heart diseases. The implemented ECG signals recognition system consists hardware devices, software algorithm and network connection. An ECG is a non-invasive way to help diagnose many common heart problems. A health-care provider can use an ECG to recognize irregular heartbeats, blocked or narrowed arteries in the heart, whether you have ever had a heart attack, and the quality of certain heart disease treatments. The main part of the software algorithm including the recognition of ECG signals parameters such as P-QRST. Since the voltages at which handheld ECG equipment operate are shrinking, signal processing has become an important challenge. The implemented ECG signal recognition approach based on both lookup table and neural networks techniques. In this approach, the extracted ECG features are compared with the stored features to recognize the heart diseases of the received ECG features. The introduction of neural network technology added new benefits to the system implementing the learning and training process
Acoustic Comfort Evaluation in Traditional Houses and its Impact on Inhabitant Satisfaction in the City of Sulaimani
Full text linkAcoustic comfort is one of the essential needs for people to live in calm and comfort in dwellings. Because of technological and industrial development, noise pollution became one of the big dangers that impacts human psychologically and physiologically. The historical neighborhoods in Sulaimani City are affected by this technological advancement, the demolishing of traditional houses and changed to commercial has increased the environmental noise. Therefore, this research aims to evaluate residents’ satisfaction in traditional houses in term of acoustic conditions, also aims to investigate if the design characteristics of traditional houses have role in providing acoustic comfort, and to promote traditional designs in today’s architecture. The absence of a practical study evaluating acoustic conditions in traditional houses and their impact on inhabitants’ satisfaction in Sulaimani city formed the main problem of the research. The results from the questionnaire and the in situ measurements have shown that, although most of these old houses were demolished and changed to commercial areas, the acoustic environment inside most houses is comfortable and most inhabitants are satisfied with the acoustic conditions. The traditional design turned the houses to be a barrier against transmitting noise whether from outside to inside or vice versa
Prevalence of Vitamin D Deficiency among Pregnant Women in Sulaimaneyah City-Iraq
Full text linkHypovitaminosis D during pregnancy has a negative impact on the mother and infant’s health status. The main source of Vitamin D is sunshine and ultraviolet B for most humans and food sources are often inadequate. The present work has been carried out to demonstrate the prevalence of Vitamin D deficiency among pregnant women in the Sulaimaneyah City/Kurdistan Region of Iraq. Serum samples were collected from 261 pregnant women who attended the Teaching Maternity Hospital and met inclusion criteria and were examined for 25-hydroxyvitamin D using the Roche Elecsys Vitamin D3 assay. Different information included, including sociodemography, body mass index, and obstetric history, was collected using a specific questionnaire form. The study showed a high prevalence of hypovitaminosis D (71.3%) among pregnant women. High socioeconomic classes, blood group A-, and advanced gestational age have been significantly associated with higher Vitamin D levels. Vitamin D deficiency is prevalent in pregnant women in Sulaimani city. Because of the many risk factors of Vitamin D deficiency and a series of health consequences, the government needs to take a step to address the problem, including raising awareness among the community about the burden of the situation and how to increase obtaining optimum Vitamin D from different sources
A Review on IoT Intrusion Detection Systems Using Supervised Machine Learning: Techniques, Datasets, and Algorithms
Full text linkPhysical objects that may communicate with one another are referred to “things” throughout the Internet of Things (IoT) concept. It introduces a variety of services and activities that are both available, trustworthy and essential for human life. The IoT necessitates multifaceted security measures that prioritize communication protected by confidentiality, integrity and authentication services; data inside sensor nodes are encrypted and the network is secured against interruptions and attacks. As a result, the issue of communication security in an IoT network needs to be solved. Even though the IoT network is protected by encryption and authentication, cyber-attacks are still possible. Consequently, it’s crucial to have an intrusion detection system (IDS) technology. In this paper, common and potential security threats to the IoT environment are explored. Then, based on evaluating and contrasting recent studies in the field of IoT intrusion detection, a review regarding the IoT IDSs is offered with regard to the methodologies, datasets and machine learning (ML) algorithms. In This study, the strengths and limitations of recent IoT intrusion detection techniques are determined, recent datasets collected from real or simulated IoT environment are explored, high-performing ML methods are discovered, and the gap in recent studies is identified
Kurdish Kurmanji Lemmatization and Spell-checker with Spell-correction
Full text linkThere are many studies about using lemmatization and spell-checker with spell-correction regarding English, Arabic, and Persian languages but only few studies found regarding low-resource languages such as Kurdish language and more specifically for Kurmanji dialect, which increased the need of creating such systems. Lemmatization is the process of determining a base or dictionary form (lemma) for a specific surface pattern, whereas spell-checkers and spell-correctors determine whether a word is correctly spelled also correct a range of spelling errors, respectively. This research aims to present a lemmatization and a word-level error correction system for Kurdish Kurmanji Dialect, which are the first tools for this dialect based on our knowledge. The proposed approach for lemmatization is built on morphological rules, and a hybrid approach that relies on the n-gram language model and the Jaccard Coefficient Similarity algorithm was applied to the spell-checker and spell-correction. The process results for lemmatization, as detailed in this article, rates of 97.7% and 99.3% accuracy for noun and verb lemmatization, correspondingly. Furthermore, for spell-checker and spell-correction, accordingly, accuracy rates of 100% and 90.77% are attained
Missing value imputation Techniques: A Survey
Full text linkNumerous of information is being accumulated and placed away every day. Big quantity of misplaced areas in a dataset might be a large problem confronted through analysts due to the fact it could cause numerous issues in quantitative investigates. To handle such misplaced values, numerous methods were proposed. This paper offers a review on different techniques available for imputation of unknown information, such as median imputation, hot (cold) deck imputation, regression imputation, expectation maximization, help vector device imputation, multivariate imputation using chained equation, SICE method, reinforcement programming, non-parametric iterative imputation algorithms, and multilayer perceptrons. This paper also explores a few satisfactory choices of methods to estimate missing values to be used by different researchers on this discipline of study. Furthermore, it aims to assist them to discern out what approach is commonly used now, the overview may additionally provide a view of every technique alongside its blessings and limitations to take into consideration of future studies on this area of study. It can be taking into account as baseline to solutions the question which techniques were used and that is the maximum popular
Exploring the Relationship between Attitudes and Blood Glucose Control among Patients with Type 2 Diabetes Mellitus in Chamchamal Town, Kurdistan, Iraq
Full text linkBackground: Diabetes mellitus type 2 is an endocrine disorder characterized by a progressive elevation in blood glucose levels. It is a persistent and incapacitating illness that may result in mortality if not properly managed. Objectives: The objective of this research is to explore the relationship between the attitudes of individuals with type 2 diabetes mellitus and their ability to regulate blood glucose levels. In particular, the study aims to investigate the potential correlation between participants’ attitudes and their capacity to manage blood glucose levels following their participation in an educational program. Moreover, the research seeks to analyze the association between individuals’ attitudes and diabetes control. Ultimately, the study intends to evaluate the levels of participants’ attitudes through appropriate measures. Materials and Methods: The study is designed as a cross-sectional investigation and utilizes data from a diabetic outpatient center in Chamchamal. The study population consists of outpatients from the evening public clinic and chronic disease control center. Participants are required to complete questionnaires on their diabetes attitude. The study was conducted between August 11, 2019, and January 5, 2022. To explore the efficacy of the attitude with diabetes control, we used a correlation coefficient test and a t-test with P-value of 0.05 as our alpha level of significance. Results and Conclusion: The study found that the majority of patients with type 2 diabetes mellitus had low levels of educational attainment, were married and had insufficient monthly income. In addition, 85% of the patients reported not smoking, and 48.3% were classified as overweight. These findings highlight the need for health-care providers to consider sociodemographic factors in the management of diabetes mellitus
A Review of Computer Vision–Based Traffic Controlling and Monitoring
Full text linkDue to the rapid increase of the population in the world, traffic signal controlling and monitoring has become an important issue to be solved with regard to the direct relation between the number of populations and the cars’ usage. In this regard, an intelligent traffic signaling with a rapid urbanization is required to prevent the traffic congestions, cost reduction, minimization in travel time, and CO2 emissions to atmosphere. This paper provides a comprehensive review of computer vision techniques for autonomic traffic control and monitoring. Moreover, recent published articles in four related topics including density estimation investigation, traffic sign detection and recognition, accident detection, and emergency vehicle detection are investigated. The conducted survey shows that there is no fair comparison and performance evaluation due to the large number of involved parameters in the abovementioned four topics which can control the traffic signal controlling system such as (computation time, dataset availability, and an accuracy)
A Boundary Integral Equation Method for Computing Numerical Conformal Mappings onto the Disk with Rectilinear Slit and Spiral Slits Regions
Full text linkThis article proposes a boundary integral equation method for computing numerical conformal mappings of bounded multiply connected region Ω onto the disk with rectilinear slit and spiral slits regions, Ω1 and Ω2 Initially, the process involves calculating the boundary value of the canonical region. Cauchy’s integral formula can then be used to compute the mapping of the interior values. The effectiveness of the proposed method is demonstrated using several numerical examples