Characteristics of Multi-Objective Linear Programming Problem and Multi-Objective Linear Fractional Programming Problem Taking Maximum Value of Multi-Objective Functions

In this paper, a new statistical averaging technique is proposed for finding an optimal solution to a multi-objective linear fractional programming problem (MOLFPP) and multi-objective linear programming problem (MOLPP) by using new arithmetic averaging method and new geometric averaging method. It is significantly noticeable same characteristics among all the technique while taking maximum or minimum among all optimized values for multi-objective functions using simplex algorithm. The characteristics provided from the problems are verified by the numerical examples.

The Application of Analytic Hierarchy Process Method in the Evaluation of Educational Quality in Colleges and Universities

Talent quality is the lifeline of colleges and universities.Based on employment guidance,this paper establishes a student quality evaluation and control system including knowledge,moral character,and ability,and uses the Analytic Hierarchy Process(AHP)method to analyze the factors affecting the quality of education in colleges and universities.In addition,some suggestions are provided to improve the quality of students.

Milestones of Wireless Communication Networks and Technology Prospect of Next Generation(6G)

Since around 1980,a new generation of wireless technology has arisen approximately every 10 years.First-generation(1G)and secondgeneration(2G)began with voice and eventually introduced more and more data in third-generation(3G)and became highly popular in the fourthgeneration(4G).To increase the data rate along with low latency and mass connectivity the fifth-generation(5G)networks are being installed from 2020.However,the 5G technology will not be able to fulfill the data demand at the end of this decade.Therefore,it is expected that 6G communication networks will rise,providing better services through the implementation of new enabling technologies and allowing users to connect everywhere.6G technology would not be confined to cellular communications networks,but would also comply with non-terrestrial communication system requirements,such as satellite communication.The ultimate objectives of this work are to address the major challenges of the evolution of cellular communication networks and to discourse the recent growth of the industry based on the key scopes of application and challenges.The main areas of research topics are summarized into(i)major 6G wireless networkmilestones;(ii)key performance indicators;(iii)future new applications;and(iv)potential fields of research,challenges,and open issues.

Understanding the Challenges of Implementing Green Roofs in Multi-Family Apartment Buildings:A Case Study in Khulna

Green roofs are widely recognized for their multifaceted benefits to the environment,economy,and society,constituting the fundamental pillars of sustainability.These roofs contribute to the enhancement of bio-physical diversity,provision of food resources,regulation of temperature and rainfall-runoff patterns,creation of wildlife habitats,and augmentation of aesthetic and recreational value.While Bangladesh,with its favourable climatic conditions and rapid urbanization,possesses immense potential for harnessing the advantages of green roofs,their adoption remains limited in both research and practical applications within the country.Addressing this research gap,the present study aims to investigate the barriers impeding the implementation of green roofs in existing or new multi-family apartment buildings,focusing specifically on the city of Khulna.Through a combination of case studies and a comprehensive questionnaire survey administered to diverse stakeholders including apartment dwellers/owners,architects,developers,and government officials with varying levels of expertise,this research sheds light on the obstacles hindering Green Roof Implementation(GRI).The identified barriers encompass a lack of governmental policies,inadequate technological advancements,inaccurate estimation of economic benefits,and individual resistance.In light of the perspectives of various GRI stakeholders,strategic proposals encompassing policy,technical,economic,and social dimensions are presented to surmount these barriers.The outcomes of this study contribute to the dissemination of knowledge pertaining to the impediments to GRI implementation,thereby inspiring further research endeavours and enabling decision-makers to formulate robust policies facilitating the widespread adoption of green roofs.

Simulation of Air Flow along Human Lung for Cylindrical Channel of Porous Medium

The steady flow behavior in terminal bronchus of human lung for cylindrical channel of porous medium has been studied. The governing equations have been solved analytically and numerically for cylindrical channel. Finite difference method is incorporated to simulate the problem. The numerical results are compared with square duct channel for different parametric effect. It is observed that the flow rate is increased in cylindrical channel compared to square duct channel for the increasing value of pressure gradient, porosity and permeability. On the contrary, the flow rate is decreased in square duct channel compared to cylindrical channel for increasing value of viscosity. Flow rate in both channels is analyzed and compared for non-porous medium also. It is observed that flow rate is increased very high in cylindrical channel compared to square duct channel for both medium.

Location-allocation modeling for emergency evacuation planning with GIS and remote sensing:A case study of Northeast Bangladesh

This work developed models to identify optimal spatial distribution of emergency evacuation centers(EECs)such as schools,colleges,hospitals,and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh.The use of location-allocation models(LAMs)for evacuation in regard to flood victims is essential to minimize disaster risk.In the first step,flood susceptibility maps were developed using machine learning models(MLMs),including:Levenberg-Marquardt back propagation(LM-BP)neural network and decision trees(DT)and multi-criteria decision making(MCDM)method.Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic(AUROC)curve.Mathematical approaches in a geographic information system(GIS)for four well-known LAM problems affecting emergency rescue time are proposed:maximal covering location problem(MCLP),the maximize attendance(MA),p-median problem(PMP),and the location set covering problem(LSCP).The results showed that existing EECs were not optimally distributed,and that some areas were not adequately served by EECs(i.e.,not all demand points could be reached within a 60-min travel time).We concluded that the proposed models can be used to improve planning of the distribution of EECs,and that application of the models could contribute to reducing human casualties,property losses,and improve emergency operation.

A Trend Analysis of Temperature and Rainfall to Predict Climate Change for Northwestern Region of Bangladesh

Bangladesh is one in all the foremost climate vulnerable countries of the world. In recent years, climate change studies over the country get plenty of attention by the researchers and policy makers. A substantial quantity of global climate change studies over the country use climate models to estimate future projections and uncertainties. Maximum temperature, precipitation and their potential future changes are evaluated in an ensemble of the 5th Phase Coupled Model Inter-comparison Project (CMIP5) within the Intergovernmental Panel on Climate Change (IPCC) diagnostic exercise for the Fifth Assessment Report (AR5) and the available historical data collected by the Bangladesh Meteorological Department (BMD) during the period 1981-2008 in the north-western region of Bangladesh and also the comparison between these two values. It has been found that average maximum temperature shows a positive trend of increase at a rate of 0.29°C and 5.3°C per century respectively, for BMD data and MPI-ESM-LR (CMIP5) model data. But the rainfall is decreasing at a rate of 8.8 mm and 40.1 mm per century respectively for BMD data and MPI-ESM-LR (CMIP5) model data. It is seen that July was the maximum monsoon rainfall month and January was the lowest rainfall month. The peak frequency is slightly smaller than 12 months, which indicates that the major events are occurring before ending a year compared to the previous year. According to MPI-ESM-LR (CMIP5) model data, future normal temperature on north-western region will be increased at a rate of 1.62°C during the period 2040-2100.

Deep-BERT:Transfer Learning for Classifying Multilingual Offensive Texts on Social Media

Offensive messages on social media,have recently been frequently used to harass and criticize people.In recent studies,many promising algorithms have been developed to identify offensive texts.Most algorithms analyze text in a unidirectional manner,where a bidirectional method can maximize performance results and capture semantic and contextual information in sentences.In addition,there are many separate models for identifying offensive texts based on monolin-gual and multilingual,but there are a few models that can detect both monolingual and multilingual-based offensive texts.In this study,a detection system has been developed for both monolingual and multilingual offensive texts by combining deep convolutional neural network and bidirectional encoder representations from transformers(Deep-BERT)to identify offensive posts on social media that are used to harass others.This paper explores a variety of ways to deal with multilin-gualism,including collaborative multilingual and translation-based approaches.Then,the Deep-BERT is tested on the Bengali and English datasets,including the different bidirectional encoder representations from transformers(BERT)pre-trained word-embedding techniques,and found that the proposed Deep-BERT’s efficacy outperformed all existing offensive text classification algorithms reaching an accuracy of 91.83%.The proposed model is a state-of-the-art model that can classify both monolingual-based and multilingual-based offensive texts.

Numerical Analysis and Design of Photonic Crystal Fiber Based Surface Plasmon Resonance Biosensor

In this paper, a high sensitive photonic crystal fiber (PCF) based surface plasmon resonance (SPR) biosensor is numerically studied. In this structure, as a plasmonic material, gold (Au) is used because of its chemical activeness. And a layer of sensing medium is used outside of the fiber to make the structure effective. Any unknown biomolecular analyte can be detected by placing or flowing it on the metal surface. Guiding properties and results are investigated using Finite element method (FEM). Results show that maximum sensitivity is 4000 nm/RIU, as well as resolution, is 2.5 × 10−5 RIU of the proposed sensor.

Comparison of Classical Method, Extension Principle and α-Cuts and Interval Arithmetic Method in Solving System of Fuzzy Linear Equations

The system of linear equations plays a vital role in real life problems such as optimization, economics, and engineering. The parameters of the system of linear equations are modeled by taking the experimental or observation data. So the parameters of the system actually contain uncertainty rather than the crisp one. The uncertainties may be considered in term of interval or fuzzy numbers. In this paper, a detailed study of three solution techniques namely Classical Method, Extension Principle method and α-cuts and interval Arithmetic Method to solve the system of fuzzy linear equations has been done. Appropriate applications are given to illustrate each technique. Then we discuss the comparison of the different methods numerically and graphically.

Influence of Lycra Content and Stitch Length on the Dimensional and Physical Characteristics of Lycra Back Plaited Cotton (LBPC) Single Jersey Fabrics

The physical and dimensional characteristics, i.e. course and wale spacing, stitch density, tightness factor, diameter, porosity, dimensional stability and bursting strength of single jersey knitted items containing lycra yarn with the variations in stitch length and lycra content have been examined and a detail investigation on the lycra filament has been discussed in this study. Six different samples were knitted with identical cotton and lycra yarn but different in lycra contents and stitch length. After conditioning in a controlled environment, all the samples were tested as per the established methods. After analyzing the test results, noticeable effects of variations in stitch length and lycra content on physical and dimensional characteristics of single jersey knitted fabric has been found. As smaller the stitch length and as greater the lycra content, the dimensional stability and bursting strength are better;on the other hand, the air permeability is lower.

Impact of Stone Enzyme Wash and Acid Wash Based on Denim Garments

The aim of this project is to find out the changes that occur in physical properties of denim when it is subjected to enzyme stone and acid wash or to find out the impact of enzyme stone and acid wash. 97% cotton 3% elastomer twill, weave 3/1, construction 72 × 40/9 × 7 indigo dyed denim fabric leg panels as per lab standard recipe are used here to examine. Firstly, desizing was done as pre-treatments and after treatment was silicon softener. After washing process, different samples from both washing are going to express different behavior on physical properties. This experiment is done to find out the discrimination in tearing strength, shrinkage %, color fastness to wash, color fastness to rubbing, pH rate between stone enzyme wash and acid wash of denim garments.

Describing Fuzzy Membership Function and Detecting the Outlier by Using Five Number Summary of Data

One of the most important activities in data science is defining a membership function in fuzzy system. Although there are few ways to describe membership function like artificial neural networks, genetic algorithms etc.;they are very complex and time consuming. On the other hand, the presence of outlier in a data set produces deceptive results in the modeling. So it is important to detect and eliminate them to prevent their negative effect on the modeling. This paper describes a new and simple way of constructing fuzzy membership function by using five-number summary of a data set. Five states membership function can be created in this new method. At the same time, if there is any outlier in the data set, it can be detected with the help of this method. Usually box plot is used to identify the outliers of a data set. So along with the new approach, the box plot has also been drawn so that it is understood that the results obtained in the new method are accurate. Several real life examples and their analysis have been discussed with graph to demonstrate the potential of the proposed method. The results obtained show that the proposed method has given good results. In the case of outlier, the proposed method and the box plot method have shown similar results. Primary advantage of this new procedure is that it is not as expensive as neural networks, and genetic algorithms.

Assessment of Runoff, Sediment Yields and Nutrient Loss Using the Swat Model in Upper Indus Basin of Pakistan

The main objective of this study is to understand the runoff, sediment yield and water quality of the Upper Indus River Basin of Pakistan. To achieve this goal, specific objectives have been met which include, setup of a hydrological model using Soil and Water Assessment Tool (SWAT) then calibration and validation of the hydrological model using river discharges and in the end investigating the performance of the hydrological model by SWAT. This research will have great impacts on socio-economic conditions of Pakistan because study of upper Indus River basin is imperative to provide data needed for its management, and to warrant that it is sustainable to support the increasing population and conservational flows. A set of programmable mapping components MapWindow Geographic Information System (GIS) was used which is an open source GIS based mapping application. It is SWAT used spatially distributed information on elevation, land use, slope and soil. The program Sequential Uncertainty Fitting ver.2 (SUFI-2) in a combination of uncertainty analysis and calibration of outputs was used in SWAT-CUP. SWAT model used input data, which have climate information to obtain results. The observed climate data of temperature gauges and rain gauge were used as input in the SWAT model;the calibration results for three discharge stations were produced. The initial P-factor value was satisfactory but more iteration to attempt narrow uncertainty band with improving goal function, resulted in small percentage of observed data within uncertainty band. A warm up period of three years (1979-1982) was used for simulation of SWAT model. The model was calibrated for selected three catchments for the period 1982-2000 and validated for period 2001-2010. Results are quite comparable with the observed flows.

The Outbreeding Enhancement and Correlation Studies in F₁Hybrids of Hexaploid Wheat (<i>Triticum aestivum</i>L.) Cultivars

The current study was conducted in the experimental field of the Department of Biotechnology and Genetic Engineering, Faculty of Life Science, University of Development Alternative, Dhaka, Bangladesh during the winter season 2017-2018. The study was performed to reduce the heterotic effect and phenotypic correlation among numerous yield characters for F1 hybrids of hexaploid wheat (Triticum aestivum L.). The experimental design has consisted of six parental variants (Sonalika, Balaka, Prodip, Kanchan, Agrahani and Protiva), which were crossed and nine possible cross combinations (F1 hybrids) (Prodip × Agrahani, Balaka × Agrahani, Prodip × Protiva, Protiva × Agrahani, Agrahani × Kanchan, Kanchan × Sonalika, Protiva × Prodip, Sonalika × Agrahani, and Prodip × Kanchan) were obtained. The experimental fields were selected and arranged in a randomized complete block design with four replicates, where eight characters were studied. The mean square of the analysis of variance showed that the hybrids differed significantly (p ≤ 0.01) for all studied characters except for maturity to 75% of days and height of the plant, while the parents only had no differences in grain yield. The mean square of the parent and the F1 hybrid indicated that considerable heterosis existed in the F1 hybrids. In general, correlation coefficients indicated that the maturity to 75% of days was significant but negatively correlated with most of the yield traits, suggesting that the genotypes which became mature early may have lower yields. Plant height was also negatively correlated with grain spike−1, seed index, and harvest index. The grain yield plant−1 was significant and positively correlated with all yield traits. Correlation indicates that single or multiple production-related ingredients can be used as selection time to select plants with higher yield traits with larger grains.

Study on the Physical and Mechanical Properties of Al-Powder Reinforced Bioactive Glass: Ceramic Composite Material

Glass-ceramic samples, having composition of SiO2-35, CaO-45, Na2O-10 and P2O5-10 in weight ratio were prepared through sintering route. Glass powder was reinforced by Al powder. The strength of glass-ceramic composite was found to be temperature dependent, and it varies with the addition of Al powder. Flexural strength increases with the increase of powder addition and sintering temperature, however, decreases with the increase of sintering time. There is an optimum temperature (>1100℃) above which flexural strength of all samples decreases. Bulk density changes to a higher value as the addition of Al-powder increases up to 3% by weight above which density decreases slowly. On the other hand, apparent porosity and water absorption decrease with the increase of percentage of Al powder added. Porosity and water absorption also showed a dependent characteristic on sintering time and sintering temperature.

Study on the Presence of Filament Yarn in Jamdani Saree in Bangladesh

Jamdani weaving is one of the oldest heredities of Bangladesh. From the beginning 100% cotton yarn was used to produce high quality jamdani saree. The weavers were the finest with weaving skills. Higher yarn count yarns were used to weave the jamdani saree. In course of time at present manmade fibres are also used to produce jamdani saree. The use of filament yarn may have eased the manufacturing difficulties, but the jamdani saree is missing its originality without 100% cotton. In this project, random jamdani saree sample was collected to identify the fibre composition. Samples of filament were also collected from the manufacturer and tested. It was evident that instead of cotton yarn in warp and weft silk and polyester filament yarn were used.

Arithmetic Operations of Generalized Trapezoidal Picture Fuzzy Numbers by Vertex Method

In this article, we define the arithmetic operations of generalized trapezoidal picture fuzzy numbers by vertex method which is assembled on a combination of the (α, γ, β)-cut concept and standard interval analysis. Various related properties are explored. Finally, some computations of picture fuzzy functions over generalized picture fuzzy variables are illustrated by using our proposed technique.

Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor networks.This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies.The proposed algorithms lack algorithm-specific parameters and metaphorical connotations.The proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned solutions.The proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing protocol.We compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)algorithms.The efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base station.The experimental results were compared with those obtained using the Jaya optimization algorithm.The proposed algorithms exhibited the best performance.The proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base station.

Effects of loose deposits on debris flow processes in the Aizi Valley, southwest China

Loose deposits, rainfall and topography are three key factors that triggering debris flows.However, few studies have investigated the effects of loose deposits on the whole debris flow process.On June 28, 2012, a catastrophic debris flow occurred in the Aizi Valley, resulting in 40 deaths.The Aizi Valley is located in the Lower Jinsha River,southwestern Sichuan Province, China. The Aizi Valley debris flow has been selected as a case for addressing loose deposits effects on the whole debris flow process through remote sensing, field investigation and field experiments. Remote sensing interpretation and laboratory experiments were used to obtain the distribution and characteristics of the loose deposits, respectively. A field experiment was conducted to explore the mechanics of slope debris flows, and another field investigation was conducted to obtain the processes of debris flow formation, movement and amplification. The results showed that loose deposits preparation, slope debris flow initiation,gully debris flow confluence and valley debris flow amplification were dominated by the loose deposits.Antecedent droughts and earthquake activities may have increased the potential for loose soil sources in the Aizi Valley, which laid the foundation for debris flow formation. Slope debris flow initiated under rainfall, and the increase in the water content as well as the pore water pressure of the loose deposits were the key factors affecting slope failure. The nine gully debris flows converged in the valley, and the peak discharge was amplified 3.3 times due to a blockage and outburst caused by a large boulder. The results may help in predicting and assessing regional debris flows in dry-hot and seismic-prone areas based on loose deposits, especially considering large boulders.