Social-Media based Online Businesses: New Opportunity for Enhancing Youth Employment in Bangladesh

Bangladesh has seen a significant rise in the number of young people who run businesses on social media sites This trend has been noted in recent years This is a significant contribution to the nation s economy since young people constitute a significant proportion of the total population The purpose of the study is to determine how social media assists young people in starting their enterprises and in educating the younger generation about the difficulties and opportunities that can help improve Bangladesh s economy In addition a questionnaire-based study was conducted to determine whether a low initial investment cost a high-profit ratio simple and direct payment methods and sufficient networking opportunities make businesses more attractive to young entrepreneurs This paper shows that young entrepreneurs are becoming more interested in social-media based business because it gives them a chance to make money and work for themselve

Performance Appraisal and Promotion Practices of Public Commercial Banks in Bangladesh- A Case Study on ACR Method

Purpose- Performance appraisal is crucial for enhancing the productivity of employees working in any sector. This paper investigates the prevailing performance appraisal system and promotion policy of selected public commercial banks (Sonali Bank Ltd, Rupali Bank Ltd, and Agrani Bank Ltd) in Bangladesh. Design/Methodology- The study is a descriptive case of three banks. The researchers interviewed six experienced banking professionals who provided rich data about their respective banks' performance appraisal and feedback systems. The findings of the study are based on the thematic analysis of the respondents’ statements. However, the study also utilized secondary sources for other relevant information. Findings- The study found that all the banks have an established system for evaluating employee performances through ACR with structured criteria for the promotion. The standard criteria include ACR, academic degree, banking diploma, length of service, etc. However, the grading scale for promoting to different positions is differing among the banks. The study also addressed some limitations of the ACR method as rating only by the manager, biasness on ratings, no appraisal feedback to employees etc. Practical Implications- The study seeks to drive the attention of policymakers to utilize their existing performance appraisal system better and design a more effective one with a well-established promotion policy to encourage the employees to give their best effort at the workplace

The Role of HRM Practices in Organized Retailing with Special Reference to Bangalore City

Retailing displayed its significance in India’s market with tremendous contribution to the Indian economy. The development in the organized retail sector has showed the perfect platform to the Indian companies to enter into this sector. The entry of global players in retailing business has created huge challenges to the Indian companies. The organized retailer’s in order to respond to the competition, started to realize the need for efficient man power. The Human Resource practices and the employee satisfaction became the primary concern for the organized retailers. The present study will provide a clear picture on the issues related to the HR practices and its impact on employees. The study will also focus on the various problems and challenges faced by the HR department in procuring and retaining the employees of organized retailing companies

A Novel Feature-Selection Algorithm in IoT Networks for Intrusion Detection

The Internet of Things (IoT) and network-enabled smart devices are crucial to the digitally interconnected society of the present day. However, the increased reliance on IoT devices increases their susceptibility to malicious activities within network traffic, posing significant challenges to cybersecurity. As a result, both system administrators and end users are negatively affected by these malevolent behaviours. Intrusion-detection systems (IDSs) are commonly deployed as a cyber attack defence mechanism to mitigate such risks. IDS plays a crucial role in identifying and preventing cyber hazards within IoT networks. However, the development of an efficient and rapid IDS system for the detection of cyber attacks remains a challenging area of research. Moreover, IDS datasets contain multiple features, so the implementation of feature selection (FS) is required to design an effective and timely IDS. The FS procedure seeks to eliminate irrelevant and redundant features from large IDS datasets, thereby improving the intrusion-detection system’s overall performance. In this paper, we propose a hybrid wrapper-based feature-selection algorithm that is based on the concepts of the Cellular Automata (CA) engine and Tabu Search (TS)-based aspiration criteria. We used a Random Forest (RF) ensemble learning classifier to evaluate the fitness of the selected features. The proposed algorithm, CAT-S, was tested on the TON_IoT dataset. The simulation results demonstrate that the proposed algorithm, CAT-S, enhances classification accuracy while simultaneously reducing the number of features and the false positive rate.publishedVersio

Prevalence of Bombay phenotype among Bangladeshi ‘O’ blood group population

Background: The Bombay blood group, a rare type often confused with ‘O’, poses a critical transfusion risk, requiring specific compatibility with Bombay (Oh) blood. With a lack of data in Bangladesh, this study aimed to establish a comprehensive database for the rare Bombay phenotype, crucial for transfusion safety. Objective was to determine the frequency prevalence of Bombay phenotype among ‘O’ blood group individuals. Methods: A cross-sectional study conducted at Bangabandhu Sheikh Mujib Medical University from January 2020 to June 2021 involved, aseptic collection of 3 ml venous blood sample, with forward and reverse blood grouping revealing a ‘O’ phenotype. Utilizing anti-H lectin resolved discrepancies and confirmed the absence of ‘H’ antigen in individuals with Bombay blood groups. Blood samples of Bombay phenotype individuals showed the following reactions: anti-A (-), anti-B (-), anti-AB (-), anti-H (-), A cells 4+, B cells 4+, O cells 4+. Results: Among 10,000 individuals with apparent blood group ‘O’, 99.97% were identified as ‘O’ blood type, while only 0.03% exhibited the rare Bombay blood group. ABO and Rh-D blood group frequencies varied over the study period, with B +ve at the highest (28.31%) and AB -ve at the lowest (0.21% to 0.23%). Overall, O +ve had the highest frequency (97.29%), and Bombay blood group was rare, with ‘O’ dominating at 99.97%. Conclusions: The study identified a 0.03% prevalence of the Bombay phenotype. Due to its potential confusion with ‘O’ blood group, transfusing ‘O’ blood to Bombay individuals carries a substantial risk of severe hemolytic reactions, including fatal consequences

Multi Objective PSO with Passive Congregation for Load Balancing Problem

High-level architecture (HLA) and Distributed Interactive Simulation (DIS) are commonly used for the distributed system. However, HLA suffers from a resource allocation problem and to solve this issue, optimization of load balancing is required. Efficient load balancing can minimize the simulation time of HLA and this optimization can be done using the multi-objective evolutionary algorithms (MOEA). Multi-Objective Particle Swarm Optimization (MOPSO) based on crowding distance (CD) is a popular MOEA method used to balance HLA load. In this research, the efficiency of MOPSO-CD is further improved by introducing the passive congregation (PC) method. Several simulation tests are done on this improved MOPSO-CD-PC method and the results showed that in terms of Coverage, Spacing, Non-dominated solutions and Inverted generational distance metrics, the MOPSO-CD-PC performed better than the previous MOPSO-CD algorithm. Hence, it can be a useful tool to optimize the load balancing problem in HLA

From ChatGPT-3 to GPT-4: A Significant Advancement in AI-Driven NLP Tools

Recent improvements in Natural Language Processing (NLP) have led to the creation of powerful language models like Chat Generative Pre-training Transformer (ChatGPT), Google’s BARD, Ernie which has shown to be very good at many different language tasks. But as language tasks get more complicated, having even more advanced NLP tool is essential nowadays. In this study, researchers look at how the latest versions of the GPT language model(GPT-4 & 5) can help with these advancements. The research method for this paper is based on a narrative analysis of the literature, which makes use of secondary data gathered from previously published studies including articles, websites, blogs, and visual and numerical facts etc. Findings of this study revealed that GPT-4 improves the model's training data, the speed with which it can be computed, the flawless answers that it provides with, and its overall performance. This study also shows that GPT-4 does much better than GPT-3.5 at translating languages, answering questions, and figuring out how people feel about things. The study provides a solid basis for building even more advanced NLP tools and programmes like GPT-5. The study will help the AI & LLM researchers, NLP developers and academicians in exploring more into this particular field of study. As this is the first kind of research comparing two NLP tools, therefore researchers suggested going for a quantitative research in the near future to validate the findings of this research

Evaluation of lipid profile pattern and atherogenic index of plasma (AIP) having type-2 diabetes mellitus in Bangladesh

Background: Dyslipidemia has been noted to play an integral role in the pathogenesis and progression of micro and macrovascular complications in Diabetes Mellitus (DM) patients. The study was aimed to evaluate the prevalence and pattern of dyslipidemia and atherogenic index of plasma (AIP) in type 2 diabetes mellitus patients as it has not been reported previously in BangladeshMethods: This cross-sectional study was conducted at Armed Forces Institute of pathology, Bangladesh from November 2016 to October 2017. A total number of 300 patients having diabetes in the age group of 30-60 years have been selected using a non-probability method. Fasting plasma glucose (FPG), serum total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) and triglyceride (TG) levels were estimated by laboratory tests.Results: The prevalence of dyslipidemia in at least one lipid parameter was found in 282 patients (94%), while 18 patients (6%) had no dyslipidemia. High levels of TC, TG and LDL-C were found in 134 (47.3%), 230 (76.7%) and 124 (41.3%) patients, respectively. On the other hand, low levels of HDL-C were found in 180 patients (60%). An increased risk of AIP was found in 298 patients (99.3%), whereas only 2 patients (0.7%) were in low risk. FPG was positively correlated with TC, TG, LDL-C and AIP, while negatively correlated with HDL-C. A significant positive correlation was also observed between FPG and AIP.Conclusions: The Study revealed that dyslipidemia is very common in type 2 diabetic patients and the most common abnormality observed was increased serum triglyceride levels followed by decreased serum HDL-C levels. The AIP is also significantly higher in type 2 diabetic patients

An analysis of energy use, energy intensity and emissions at the industrial sector of Malaysia

Malaysia is a developing country which has transformed itself from more on producer of raw materials to an emerging multisector economy in a span of 40 years. Growth was almost exclusively driven by exports - particularly of electronics. This paper presents the energy consumption trend in Malaysian industrial sector. Malaysian Industrial Development Authority (MIDA) conducts survey to get raw data of energy (Fuel oil, diesel, petrol, kerosene, gas and electricity) consumption behavior for each year. The raw data has been processed by the data processors to analyze the actual behavior of energy consumption in different sub-sectors over that period. Energy intensity which is the key indicator of energy performance of a country and emissions has been calculated. The study was carried out for 2 years in 1988 and 1998. It was found that during the year 1988 and 1998, fuel oil is used more than other fuels. The energy intensity of the nonmetallic section was higher both in the years 1988 and 1998. In the year 1998, the energy intensity of chemical industries was lower. Where as, the energy intensity of wood and chemical industries were low in the year of 1988. The emissions of the food sector are higher both in the year 1988 and 1998. The emissions of the entire sector are more in the year of 1998 compare to the year of 1988. The analysis shows that over all emission is 5 times in the year of 1998 compare to that of 1988