Risk Assessment Approaches in Banking Sector –A Survey

Prediction analysis is a method that makes predictions based on the data currently available. Bank loans come with a lot of risks to both the bank and the borrowers. One of the most exciting and important areas of research is data mining, which aims to extract information from vast amounts of accumulated data sets. The loan process is one of the key processes for the banking industry, and this paper examines various prior studies that used data mining techniques to extract all served entities and attributes necessary for analytical purposes, categorize these attributes, and forecast the future of their business using historical data, using a model, banks\u27 business, and strategic goals

Key Performance Indicators Detection Based Data Mining

One of the most prosperous domains that Data mining accomplished a great progress is Food Security and safety. Some of Data mining techniques studies applied several machine learning algorithms to enhance and traceability of food supply chain safety procedures and some of them applying machine learning methodologies with several feature selection methods for detecting and predicting the most significant key performance indicators affect food safety. In this research we proposed an adaptive data mining model applying nine machine learning algorithms (Naive Bayes, Bayes Net Key -Nearest Neighbor (KNN), Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), J48, Hoeffding tree, Logistic Model Tree) with feature selection wrapper methods (forward and backward techniques) for detecting food deterioration’s key performance indicators. In conclusion the proposed model applied effectively and successfully detected the most significant indicators for meat safety and quality with the aim of helping farmers and suppliers for being sure of delivering safety meat for consumer and diminishing the cost of monitoring meat safety

Credit Card Fraud Detection Using Machine Learning Techniques

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today\u27s banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary losses, not just for financial institutions but also for individuals. as technology and usage patterns evolve, making credit card fraud detection a particularly difficult task. Traditional statistical approaches for identifying credit card fraud take much more time, and the result accuracy cannot be guaranteed. Machine learning algorithms have been widely employed in the detection of credit card fraud. The main goal of this review intends to present the previous research studies accomplished on Credit Card Fraud Detection (CCFD), and how they dealt with this problem by using different machine learning techniques

Methylergometrine-Induced Myocardial Infarction in the Setting of a Cesarean Delivery

A 30-year-old female with no significant past medical history presented to our labor and delivery ward for induction of labor. Due to failure to progress, she was proceeded to cesarean delivery. Intraoperatively, it was noted that her uterus was hypotonic; she required supplemental methylergometrine to control the bleeding from the uterine atony. However, within three minutes of intramuscular (IM) administration, she complained of chest pain. She then subsequently developed pulmonary edema in the postoperative care unit, which required supplemental oxygen. She was found to have elevated troponin and brain natriuretic peptide (BNP), along with radiologic features of fluid overload suggestive of congestive cardiac failure, which all lead to the diagnosis of non-ST myocardial infarction. The patient had a normal computed tomography (CT) pulmonary angiogram, echocardiogram, and serial electrocardiograms (ECGs). She was successfully discharged from the hospital on postoperative day 4 with resolution of her symptoms and improving cardiac enzymes. Cardiology outpatient follow-up was arranged

Emergent Cesarean Delivery in a Patient With Freeman-Sheldon Syndrome Complicated by Preeclampsia, Acute Pulmonary Embolism, and Pulmonary Edema: A Case Report

Freeman-Sheldon syndrome (FSS) is an exceedingly rare congenital disorder with an unspecified prevalence. FSS is caused by a mutation in the embryonic skeletal muscle myosin heavy chain 3 gene. Patients may have facial abnormalities that put them at risk of difficult airway intubation. These facial abnormalities include micrognathia, macroglossia, high-arched palate, prominent forehead, and mid-face hypoplasia. Additionally, skeletal abnormalities such as joint contractures, scoliosis with resultant restrictive lung disease, and camptodactyly (bent fingers) can be noted. These features played an important role in the anesthetic management of our FSS patient. Perioperative planning and optimization were crucial in her anesthetic management as she underwent an urgent cesarean section due to preeclampsia with severe features

Optical properties of zinc borotellurite glass doped with trivalent dysprosium ion

The zinc borotellurite doped with dysprosium oxide glass samples with chemical formula {[(TeO2)0.7(B2O3)0.3]0.7(ZnO)0.3}1−x(Dy2O3)x (where x=0.01, 0.02, 0.03, 0.04 and 0.05 M fraction) were prepared by using conventional melt quenching technique. The structural and optical properties of the proposed glass systems were characterized by using X-ray diffraction (XRD) spectroscopy, Fourier Transform Infrared (FTIR) spectroscopy, and UV–VIS spectroscopy. The amorphous nature of the glass systems is confirmed by using XRD technique. The infrared spectra of the glass systems indicate three obvious absorption bands which are assigned to BO3 and TeO4 vibrational groups. Based on the absorption spectra obtained, the direct and indirect optical band gaps, as well as the Urbach energy were calculated. It is observed that both the direct and indirect optical band gaps increase with the concentration of Dy3+ ions. On the other hand, the Urbach energy is observed to decrease as the concentration of Dy3+ ions increases

Development of Wi-Fi based home energy monitoring system for green internet of things

Green Internet of things (IoT) has been heralded as the “next big thing” waiting to be realized in energy-efficient ubiquitous computing. Green IoT revolves around increased machine-to-machine communications and encompasses energy-efficient wireless embedded sensors and actuators that assist in monitoring and controlling home appliances. Energy efficiency in home applications can be achieved by better monitoring of the specific energy consumption by the appliances. There are many wireless standards that can be adopted for the design of such embedded devices in IoT. These communication technologies cater to different requirements and are classified as the short-range and long-range ones. To select the best communication method, this paper surveys various IoT communication technologies and discusses the advantages and disadvantages to develop an energy monitoring system. An IoT device based on the Wi-Fi technology system is developed and tested for usage in the home energy monitoring environment. The performance of this system is then evaluated by the measurement of power consumption metrics. In the efficient deep-sleep mode, the system saves up to 0.3 W per cycle with an average power dissipation of less than 0.1 W/s. Index Terms Energy efficiency, energy monitoring, Internet of things

ZIF‑8 membrane: the synthesis technique and nanofltration application

Membrane technology for water treatment is growing due to the increased demand for clean water and the stringent standard for water quality. Nanofltration (NF) is widely used in membranes for water treatment due to lower energy consumption and higher fux rates. The application was not limited to only water treatment, yet NF showed excellent potential for solvent nanofltration application. The utilization of MOF materials for the preparation of NF membranes to produce composite membranes has attracted more attention among researchers due to the advantages ofered by the material. Zeolitic imidazolate framework-8 (ZIF-8) membrane has been considered a promising MOF membrane with its capabilities and promising per�formance due to the small aperture size of the compounds and the stability towards harsh chemical condition. The purpose of this review is to present the synthesis approaches on the preparation of ZIF-8 membranes and the application of ZIF-8 membrane for NF application. The challenges and prospects of ZIF-8 membranes are also discussed to further stimulate the development and the application of ZIF-8 membrane for NF

Chemosensitivity of three patient-derived primary cultures of canine pericardial mesothelioma by single-agent and combination treatment

IntroductionCanine mesothelioma is a rare malignant tumor that mostly affects body cavities, such as the pericardial and pleural cavities. Chemotherapy plays a crucial role in the treatment of canine mesotheliomas. We aimed to compare the antitumor effects of single-agent and combination chemotherapeutic agents on patient-derived primary cultures of canine pericardial mesothelioma established in this study. We planned to generate xenograft models for future studies.Material and methodsEffusion samples were collected from three dogs with histologically diagnosed pericardial mesothelioma and used for primary culture. Cultured cells were characterized by immunostaining for pan-cytokeratin AE1/AE3, vimentin, Wilms' tumor suppressor gene 1 (WT1), and cytokeratin 5 (CK5). To assess the tumorigenic properties of cells in the effusion and generate a xenograft model, the cell suspension was injected into a severe combined immunodeficient (SCID) mouse either subcutaneously (SC) or intraperitoneally (IP). Lastly, chemosensitivity of established primary cultures against four drugs, doxorubicin, vinorelbine, carboplatin, and gemcitabine, by single-agent treatment as well as combination treatment of carboplatin at a fixed concentration, either 10 or 100 μM, and gemcitabine at different concentrations ranging from 0–1000 μM was assessed by cell viability assay.ResultsPrimary cultures were successfully generated and characterized by dual positivity for AE1/AE3 and vimentin and positive staining for WT-1 and CK5, confirming the mesothelial origin of the cells. In the xenograft models, SC mouse developed a subcutaneous mass, whereas IP mouse developed multiple intraperitoneal nodules. The masses were histopathologically consistent with mesotheliomas. The chemosensitivity assay revealed that carboplatin had the highest anti-tumor effects among the four tested single-agent treatments. Furthermore, carboplatin at 100 μM combined with gemcitabine at clinically relevant doses demonstrated the augmented anti-tumor effects compared to single-agent treatment.Discussion and conclusionPrimary cultures and xenograft models generated in this study could be useful tools for in vitro and in vivo studies of canine mesothelioma. Carboplatin is a highly effective chemotherapeutic agent against canine mesothelioma when used as a sole agent and in combination with gemcitabine

Experimental and theoretical approach on the optical properties of zinc borotellurite glass doped with dysprosium oxide

A series of glass samples with chemical formula {[(TeO2)0.7(B2O3)0.3]0.7(ZnO)0.3}1-x(Dy2O3)x where x=0.01, 0.02, 0.03, 0.04 and 0.05M fraction were synthesized through conventional melt-quenching method. The most common way to fabricate a glass material is by fusion of two or more component oxides followed by their quenching. This technique is known as melt-quenching technique. Kaur et al. (2016) [1] highlighted that the melt-quenching method able to enhance the mechanical properties like hardness and flexural strength of the material. The nature of the glass systems is proven to be amorphous based on the XRD pattern. The FTIR spectra of the glass systems confirm the existence of five bands which are assigned for the BO4, BO3, TeO4 and TeO3 vibrational groups. The density of the glass systems is increased with the addition of Dy2O3 while the molar volume is found to be inversely proportional to the density of the proposed glass. The optical properties of the glasses are determined through the absorption spectra obtained from the UV-VIS spectrophotometer. From the absorption spectra, the indirect and direct optical band gaps and the Urbach energy are found to be inversely proportional to each other. As the molar fraction of the Dy2O3 increased, the optical band gaps are observed to increase as opposed to the Urbach energy. For this glass system, the values of refractive index, electronic polarizability, oxide ion polarizability and the optical basicity are found to decrease as the addition of the dysprosium oxide is increased. From the emission spectra, two intense blue and yellow emission bands are observed, which correspond to the 4F9/2→6H15/2 and 4F9/2→6H13/2 transitions of Dy3+ ions respectively. The CIE chromaticity coordinates of the zinc borotellurite glass systems are found to be located in the white light region