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Dissimilarity in the Nuclear Ribosomal DNA Internal Transcribed Spacer Regions of Haplophyllum spp. Founded in Ashdagh Mountain, Sangaw, Kurdistan of Iraq
Full text linkStudying and understanding the changes in the molecular sequences of plants are important to better identification and classifying the species. Internal transcribed spacer (ITS) regions are consider an informative genetic sequence to find out the variation among species of the same genus. In this study, ITS regions of Haplophyllum collected in Ashdagh Mountain were amplified, analyzed, and compared with reference species gathered from gene bank. The results showed that the collected species was closely related to Haplophyllum blanchei and Haplophyllum tuberculatum. In addition, there were differences in the number of the base pairs in the ITS1 region between Haplophyllum sp. and H. blanchei and H. tuberculatum. The transition to transversion ratio between Haplophyllum sp. and H. tuberculatum was lower (=1) than with other species. The results reveals that the studied plant is could be a new species in Iraq. To the best of our knowledge, this study is the first molecular taxonomic study done to identify Haplophyllum species in Ashdagh mountain in Sangaw/Suleimani
Plate Number Recognition based on Hybrid Techniques
Full text linkGlobally and locally, the number of vehicles is on the rise. It is becoming more and more challenging for authorities to track down specific vehicles. Automatic License Plate Recognition becomes an addition to transportation systems automation. Where the extraction of the vehicle license plate is done without human intervention. Identifying the precise place of a vehicle through its license plate number from moving images of the vehicle image is among the crucial activities for vehicle plate discovery systems. Artificial intelligence systems are connecting the gap between the physical world and digital world of automatic license plate detection. The proposed research uses machine learning to recognizing Arabic license plate numbers. An image of the vehicle number plate is captured and the detection is done by image processing, character segmentation which locates Arabic numeric characters on a number plate. The system recognizes the license plate number area and extracts the plate area from the vehicle image. The background color of the number plate identifies the vehicle types: (1) White color for private vehicle; (2) red color for bus and taxi; (3) blue color for governmental vehicle; (4) yellow color for trucks, tractors, and cranes; (5) black color for temporary license; and (6) green color for army. The recognition of Arabic numbers from license plates is achieved by two methods as (1) Google Tesseract OCR based recognition and (2) Machine Learning-based training and testing Arabic number character as K-nearest neighbors (kNN). The system has been tested on 90 images downloaded from the internet and captured from CCTV. Empirical outcomes show that the proposed system finds plate numbers as well as recognizes background color and Arabic number characters successfully. The overall success rates of plate localization and background color detection have been done. The overall success rate of plate localization and background color detection is 97.78%, and Arabic number detection in OCR is 45.56 % as well as in KNN is 92.22%
Enhanced Single Image Dehazing Technique based on HSV Color Space
Full text linkThe clarity of images degrades significantly due to the impact of weather conditions such as fog and haze. Persistent particles scatter light, attenuating reflected light from the scene, and the dispersed atmospheric light will mix with the light received by the camera affecting image contrast in both outdoor and indoor images. Conventionally, the atmospheric scattering model (ATSM) is a model often used to recover hazy images. In ATSM, two unknown factors/parameters must be estimated: Airlight and scene transmission. The accuracy of these estimations has a significant influence on the dehazed image quality. This paper focuses on the first parameter. It introduces a new technique for estimating the airlight based on the HSV color space. The HSV color space is utilized to identify the haziest opaque area in the image. Consequently, the amount of airlight in the selected area is calculated. To assess the effectiveness of the suggested approach, the well-known dataset, RESIDE SOTS, has been used that contains two parts; namely, SOTS-indoor and SOTS-outdoor. Each of dataset includes 500 images. Experimental findings show that the suggested approach outperforms the existing techniques in terms of peak signal-to-noise-ratio and structural similarity index`
Seroprevalence and Molecular Detection of Influenza A Virus (H1N1) in Sulaimani Governorate-Iraq
Full text linkInfluenza A (H1N1) virus is now rapidly scattering across the world. Early detection is one of the most effective measures to stop the further spread of the virus. The current study was aimed to detect influenza A (H1N1) serologically and by polymerase chain reaction (PCR) techniques. From September 2020 to June 2021, three hundred nasopharyngeal swabs and blood samples were collected from Hiwa and Shahid Tahir Hospitals in Sulaimani city. Obtained results revealed that 23.3% of the tested patients were seropositive anti-IgG for Influenza A, while 13.3% showed anti-IgM seropositive results although 10% of the tested cases were with both anti-IgG and anti-IgM seropositive results. Gender, residency, and flu symptoms showed no significant relations with seropositive results (p<0.05) whereas valuable relations were found between seropositive observations and smoking, the previous history of chronic diseases as well as employment status (p<0.05). It was concluded that hematologic investigations (CBC) were not dependable if H1N1 diagnosis and detection. Only 1% of the tested samples showed positive results for influenza A (H1N1) RNA using reverse transcription-PCR
An Intelligent and Precise Method Used for Detecting Gestational Diabetes in the Early Stages
Full text linkThis paper suggests a Naive Bayes classifier technique for identifying and categorizing gestational diabetes mellitus (GDM), GDM is a kind of diabetes mellitus that affects a small proportion of pregnant women but recovers to normal once the baby is born. The Pima Indians Diabetes Dataset was chosen for a comprehensive analysis of this critical and pervasive health disease because it contains 768 patient characteristics acquired from a machine learning source at the University of California, Irvine. The goal of the study is to apply smart technology to categorize diseases with high accuracy and precision, practically free of conceivable and potential faults, to provide satisfying findings. The approach is based on eight major characteristics that are present in the operations that are required to establish a precise and reliable categorization system. This approach involves training and testing on real data, as well as for deciding whether or not to construct a categorization model. The work was compared to earlier work and had a 96% accuracy rating
New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System
Full text linkThis article delves into the power of multi-biometric fusion for individual identification. a new feature-level algorithm is proposed that is the Dis-Eigen algorithm. Here, a feature-fusion framework is proposed for attaining better accuracy when identifying individuals for multiple biometrics. The framework, therefore, underpins the new multi-biometric system as it guides multi-biometric fusion applications at the feature phase for identifying individuals. In this regard, the Face-fingerprints of 20 individuals represented by 160 images were used in this framework . Experimental resultants of the proposed approach show 93.70 % identification rate with feature-level fusion multi-biometric individual identification
Molecular detection of Enterotoxigenic Escherichia coli Toxins and Colonization Factors from Diarrheic Children in Pediatric Teaching Hospital, Sulaymaniyah, Iraq
Full text linkEnterotoxigenic Escherichia coli (ETEC) is one well-established causative agent of diarrhea in the developing countries among young children. This prospective study was performed at Laboratories of University of Sulaimani (in Sulaymaniyah City/Iraq) from September to October 2021which aimed to determine the prevalence of ETEC among children and the most prevalence colonization factor (CFA/I) among ETEC. One hundred and twenty-five fresh stool samples were collected from hospitalized – children with diarrhea at Dr. Jamal Ahmed Rashid’s Pediatric Teaching Hospital. The collected samples were cultured on MacConkey and eosin methylene blue agar as selective and differential media for Gram- negative bacteria. Colonies were identified through Gram staining and biochemical tests including: Indole, methyl red, and catalase reaction test. Vitek-2 machine was depended to test some obtained isolates. Most of isolates (60%) showed positive results for E. coli – out of this percentage, 14 (18.66%) were positive for ETEC using polymerase chain reaction assay identifying stable and labile toxins (LTs). It was noticed that all of the ETEC isolates were stable toxin producer isolates whereas LT producer isolates were not identified. Colonization factor 5 (CS5) has been detected among three ETEC isolates (21.42%), meanwhile, 11 isolates (78.57%) have not expressed colonization factors at all
Future IoT Software in Healthcare Also Exploring IoT Industry Application
Full text linkThere has been a great deal of investigation into medical services ability and specialized advancements during the most recent 10 years. To state the obvious, Internet of Things (IoT) has demonstrated insure associating different clinical hardware, sensors, and medical services experts to give top-notch clinical consideration at a distant area. This has upgraded patient security, diminished medical care costs, expanded admittance to medical services benefits, and expanded functional adequacy in the medical care industry. Emerging technologies such as IoT have the potential to transform our lives in many ways. A smart ubiquitous framework can only be built using smart objects in the IoT system, which is its ultimate building pieces. This research surrenders an audit of potential IoT-based innovation applications in medical services conducted to date. This paper records the development of the use of the Healthcare Internet of Things (HIoT) in tending to different medical care worries according to the viewpoints of empowering innovation, medical care administrations, and applications. Besides, potential HIoT framework issues and issues are explored. The current research closes by giving a wellspring of comprehension on the various uses of HIoT with expectations of empowering future scholastics that are quick to chip away at and kick off something new in the field to have a superior handle of the subject. IoT innovation has helped medical care experts in checking and diagnosing an assortment of well-being concerns, estimating an assortment of well-being factors, and giving demonstrative capacities at far-off areas using these standards. The structure and implementation of a specific framework are the subject of this paper. This has moved the medical services industry’s concentrate away from clinics and toward patients
Impact of Technological Burden on Knowledge Management Functions in Jordanian Industrial Companies
Full text linkThe goal of this study is to see how electronic information overload affects knowledge management functions in Jordanian businesses. All Jordanian industrial enterprises registered on the Amman Stock Exchange were included in the study’s sample. Three hundred and seventy-three people were chosen at random from a simple random sample of 30% of the study population of 1242 senior and intermediate managers in the research community. Following the retrieval of the surveys, 206 questionnaires were found to be valid for analysis. It was used to do descriptive and heuristic statistical procedures, like simple and multiple regression analysis. The SPSS.16 application was used to do this. The study ends with the following findings: Electronic information overload (technological overload) has a statistically significant influence on knowledge management functions (acquisition, generation, transmission, exchange, and application) in Jordanian industrial companies. This work made a number of recommendations as a result of its findings, including: Adopting an organizational aspect that suits the nature of the tasks that industrial companies in Jordan perform, as well as providing technical capabilities to reduce the electronic information overload that these companies face while performing their tasks
Determination of Potassium Bromate in Bread Brands in Sulaimani City, Kurdistan-Iraq
Full text linkBread is the most consumed and staple food in many countries worldwide. It is made from dough of flour such as wheat and barley, and water. It usually contains flour improver potassium bromate (KBrO3) which is used by bakers. However, many studies have confirmed the deleterious effects of KBrO3 on human health. Therefore, this study aimed to determine the rate of KBrO3 in five main types of bread in Sulaimani city, Kurdistan-Iraq. The duration of the study was from August 2021 to November 2021. Thirty bread samples were collected from five main products that are extremely consumed by Kurdish citizens. The bread-type products were bakery bread (Nani frn), white hamburger bread (Samun), white bread known as Kurdish bread (Nani Hawrami), pizza, and brown barley bread. Single beam UV–visible spectrophotometer APEL-303 was used for the quantification of KBrO3 in bread samples. The results found that all 30 samples were had KBrO3 residues in their products with different concentrations. Samples of brown barley bread were having the least content of KBrO3 while samples from pizza dough were having the highest concentration of KBrO3. The present study concludes that all bread samples from five major bread types had potassium bromate above the permitted levels allowed by the United States Food and Drug Agency (FDA)