Investigating customer churn in banking:a machine learning approach and visualization app for data science and management

Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and,after that,end their connection with the bank.Therefore,customer retention is essential in today’s extremely competitive banking market.Additionally,having a solid customer base helps attract new consumers by fostering confidence and a referral from a current clientele.These factors make reducing client attrition a crucial step that banks must pursue.In our research,we aim to examine bank data and forecast which users will most likely discontinue using the bank’s services and become paying customers.We use various machine learning algorithms to analyze the data and show comparative analysis on different evaluation metrics.In addition,we developed a Data Visualization RShiny app for data science and management regarding customer churn analysis.Analyzing this data will help the bank indicate the trend and then try to retain customers on the verge of attrition.

Development and Biochemical Composition Assessment of Fish Powders from Bangladeshi Indigenous Fish Species and Shelf-Life Characteristics Evaluation During 90 Days of Room Temperature (27°C - 30°C) Storage

In Bangladesh, Fish is a major source of daily protein intake of millions of people but most of the fishes are consumed here as fresh fish which is highly susceptible to damage during transportation and marketing. Therefore, an innovative approach was undertaken to process the fish to avoid damage and extend shelf-life while preserving the nutritional qualities to facilitate the more efficient use of fish as a source of protein and other essential nutrients. This study was conducted to develop some dried protein-enriched fish powders from some commonly consumed fish species in Bangladesh and the nutritional, sensorial, and safety qualities were assessed. Five indigenous abundant fish species including small indigenous fish (SIS) and carp fishes namely Awaous grammepomus, Channa punctata, Puntius puntio, Hypophthalmichthys molitrix and Labeo rohita were used for the preparation of dried protein-enriched fish powders. Biochemical, trace elements, sensorial, total viable count (TVC), pH, peroxide value, and moisture reconstitution during 90 days storage period were performed by standard analytical methods. The moisture, protein, fat, ash, carbohydrate (including fiber), and energy contents were ranged from (6.84% to 8.85%), (70.80% to 75.80%), (5.85% to 8.04%), (7.66% to 9.19%), (3.14% to 6.01%) and (367.50% to 379.61% kcal)/100g respectively. Highest content of protein was found in A. grammepomus (75.80%) samples and the lowest in H. molitrix (70.80%) samples. Maximum calcium content was found in sample L. rohita (2.54 g/kg) and minimum in C. punctate as (2.43 g/kg). Maximum iron content was found in H. molitrix (0.15 g/kg) and minimum in A. grammepomus. As for the phosphorous content the L. rohita samples contained the highest (1.4 g/kg) and the lowest in C. punctate (0.73 g/kg) samples. The pH, peroxide value (mEq of O2/kg of fat), and moisture reconstitution (g/100g) during 90 days were ranged from (5.30 to 8.17), (8.60 to 16.77), and (6.84 to 13.83) respectively. Microbial loads over the 90 days period were in acceptable range at the end of 90 days storage period. On the basis of biochemical qualities, sensorial and microbial attributes our findings suggest that the dried fish powders are enriched with macro and micro-nutrients especially proteins and could safely be used at least up to 3 months for food applications.

Improved Self-Pruning for Broadcasting in Ad Hoc Wireless Networks

Reducing number of forwarding nodes is the main focus of any broadcasting algorithm designed for ad-hoc wireless networks. All reliable broadcasting techniques can be broadly classified under proactive and reactive approaches. In proactive approach, a node selects a subset of its neighbors as forwarding node and announces the forwarding node list in the packet header during broadcast. On the other hand, no such forwarding list is generated in reactive approach. Rather, a node (cognitively) determines by itself whether to forward the packet or not based on neighbor information. Dominant pruning and Self-pruning are two example techniques that fall under proactive and reactive approach respectively. Between the two methods, dominant pruning shows better performance than self-pruning in reducing number of forwarding nodes as they work with extended neighbor knowledge. However, appended forwarding node list increases message overhead and consumes more bandwidth. As a result, the approach becomes non-scalable in large networks. In this paper, we propose a reactive broadcasting technique based on self-pruning. The proposed approach dubbed as “Improved Self-pruning based Broadcasting (ISB)” algorithm completes the broadcast with smaller packet header (i.e., with no overhead) but uses extended neighbor knowledge. Simulation results show that ISB outperforms dominant pruning and self-pruning. Furthermore, as the network gets more spread and denser, ISB works remarkably well.

IoT Based Nurse Activities Monitoring and Controlling System

IoT technology has emerged as a valuable tool in modern healthcare, providing real-time monitoring of patients, effective management of healthcare, and proper administration of patient information. The proposed system aims to develop a system that can prevent backward blood flow from stopping saline fluid, as well as monitor the temperature, heart rate, and oxygen level of patients by using multiple sensors like weight, temperature and heart rate, etc. Additionally, the proposed system can monitor the room temperature and humidity for contributing to the patient’s overall comfort. In emergency situations, it includes an emergency push button for quick alert medical staff and initiates timely interventions. It is designed to support nurses and doctors in monitoring patients and providing timely interventions to prevent complications.

Heterogeneous length-of-stay modeling of post-acute care residents in the nursing home with competing discharge dispositions

Post-acute care(PAC)residents in nursing homes(NHs)are recently hospitalized patients with medically complex diagnoses,ranging from severe orthopedic injuries to cardiovascular diseases.A major role of NHs is to maximize restoration of PAC residents during their NH stays with desirable discharge outcomes,such as higher community discharge likelihood and lower re/hospitalization risk.Accurate prediction of the PAC residents’length-of-stay(LOS)with multiple discharge dispositions(e.g.,community discharge and re/hospitalization)will allow NH management groups to stratify NH residents based on their individualized risk in realizing personalized and resident-centered NH care delivery.Due to the highly heterogeneous health conditions of PAC residents and their multiple types of correlated discharge dispositions,developing an accurate prediction model becomes challenging.Existing predictive analytics methods,such as distribution-/regression-based methods and machine learning methods,either fail to incorporate varied individual characteristics comprehensively or ignore multiple discharge dispositions.In this work,a data-driven predictive analytics approach is considered to jointly predict the individualized re/hospitalization risk and community discharge likelihood over time in the presence of varied residents’characteristics.A sampling algorithm is further developed to generate accurate predictive samples for a heterogeneous population of PAC residents in an NH and facilitate facility-level performance evaluation.A real case study using large-scale NH data is provided to demonstrate the superior prediction performance of the proposed work at individual and facility levels through comprehensive comparison with a large number of existing prediction methods as benchmarks.The developed analytics tools will allow NH management groups to identify the most at-risk residents by providing them with more proactive and focused care to improve resident outcomes.

My Medical Career in China

“Amid the blasts of firecrackers the old year is over.”Fireworks light up a new year,also a new chapter of my stories in China.As always,I look forward with expectation toward the new chapter,whatever it will be.Hello,ChapterⅩⅢ,my 13th year in China.

医路向中国

“爆竹声中一岁除,春风送暖入屠苏。”噼噼啪啪的鞭炮声又一次开启了我的中国故事的新篇章。每次开启新的一章时,我都是既期待又好奇。而今,我的第十三章,你好!我在脑海中抚摸着今年还未曾书写的页面,思绪却飞到了纸张已经微微泛黄的第一章,不禁感慨时间的飞逝,但当初的那种兴奋到现在都让我感觉书页滚烫。18岁的我青涩懵懂,踏上中国土地的那一刻,内心却莫名坚定。嘴里说着自己学的变调汉语,双腿则是一刻不停,我的大学生活就此开启。