Fake Review Detection using Data Mining

Online spam reviews are deceptive evaluations of products and services. They are often carried out as a deliberate manipulation strategy to deceive the readers. Recognizing such reviews is an important but challenging problem. In this work, I try to solve this problem by using different data mining techniques. I explore the strength and weakness of those data mining techniques in detecting fake review. I start with different supervised techniques such as Support Vector Ma- chine (SVM), Multinomial Naive Bayes (MNB), and Multilayer Perceptron. The results attest that all the above mentioned supervised techniques can successfully detect fake review with more than 86% accuracy. Then, I work on a semi-supervised technique which reduces the dimension- ality of the input features vector but offers similar performance to existing approaches. I use a combination of topic modeling and SVM for the implementation of the semi-supervised tech- nique. I also compare the results with other approaches that consider all the words of a dataset as input features. I found that topic words are enough as input features to get similar accuracy compared to other approaches where researchers consider all the words as input features. At the end, I propose an unsupervised learning approach named as Words Basket Analysis for fake re- view detection. I utilize five Amazon products review dataset for an experiment and report the performance of the proposed on these datasets

Ageing Effects of Na-Alginate/PEO Spinning Solution on Electrospinnability and Morphology of Nanofibres

Poly(ethylene oxide) (PEO) loaded alginate nano-fibres were produced by electrospinning of the 4 % (w/w) of 70:30 Na-alginate/PEO spinning solution. In this research, the effects of solution viscosity and storage time of the spinning solution on fibre diameter and morphology were studied. Results show that the viscosity of the spinning solution was 2284 cP at the age of day 1, which was dropped slowly and reached at 2184 cP until day 5. However, the viscosity sharply decreased after 5 days of storing and the mean diameter of the fibres remain similar until 20 days though the uniformity of the fibre diameters decreased significantly. At day 40, the viscosity of the spinning solution dropped 48 cP which yields beads-onstring fibres. The solutions of 5 days and 10 days old produced smooth and uniform nanofibres having mean diameter of 133 nm and 132 nm, respectively. They also produced stable electrospinning fibre jet compared to other solutions. Overall, the results revel that the electrospinnability of Naalginate/PEO spinning solution remain suitable until 10 days of storing time

Feasibility Study of Integrated Desizing, Scouring and Bleaching of Cotton Woven Fabric with H2O2 and Investigation of Various Physical Properties with Traditionally Treated Fabric

Pre-treatment plays a significant role for the successful coloration of any kind of natural textile fiber like cotton, wool, flax, silk etc. This research work overview the influence of various types of traditional preparation techniques applied on cotton fiber before coloration such as desizing, scouring and bleaching. The traditional pre-treatment processes consume plenty of environmentally unfriendly chemicals those generate pollution in the effluents. In this research work an endeavour has been made to desize, scour and bleach grey cotton woven fabric simultaneously using caustic soda and hydrogen peroxide. The physical properties like whiteness, percent loss in fabric weight, tensile strength of the treated fabric have been compared with those of the fabric treated to conventional desizing, scouring and bleaching process. It is observed that the whiteness (ready for colouration) obtained by this process is quite satisfactory. Moreover, this process has some other merits such as ecological, economical, energy conserving and time saving aspect

Quality Assessment of Shoe Leather Based on the Properties of Strength and Comfort, Collected from Different Footwear and Leather Industries in Bangladesh

Based on the environmental condition, a shoe manufactured with different suitable materials has to provide optimum comfort and strength features by using high-quality leather parts. The aim of the study is to evaluate the quality of the shoe upper leather in Bangladesh. Ten different types of shoe leather, made from cow hides and goat skins, were collected from different footwear and leather industries in Bangladesh. The research was carried out by using approved methods of analysis as per the International Union of the Society of Leather Technologists and Chemists’ official methods for physical and chemical analysis. Physical and chemical properties, which were studied three times for each of the samples, were tensile strength, percentage of elongation, tearing strength, grain crack resistance, water vapor permeability, flexing endurance, scuff resistance, perspiration fastness, color rub fastness, bond strength of the finish film, the pH, moisture content, chromic oxide content and fat content, respectively. From the study, it has been revealed that samples 02 and 08 were completely unacceptable, samples 04, 05 and 07 were moderately acceptable, and the remaining samples, 01, 03, 06, 09 and 10, were strongly acceptable on the basis of the ISO standard for shoe leather. To get the better quality, the above mentioned tests should be improved, thus the demand and the value of shoe leather, as well as footwear, will be increased and the rejection rate will be decreased gradually

Improvement in Weighting Assignment Process in Analytic Hierarchy Process by Introducing Suggestion Matrix and Likert Scale

Analytic Hierarchy Process (AHP) has been widely used in varieties of decision making processes among several alternatives, where data on pair-wise comparisons are aggregated and the degree of importance of each alternative is quantified. The process of assigning importance or priorities against the alternatives has inherent limitations, which lead to higher possibility of inconsistency. This paper focuses on two basic limitations of the AHP, first one is its inconsistency generated from huge comparisons in judgment matrix and the second one is the use of ranking weightages given by AHP. To eliminate these limitations, this research paper recommends to calculate relative importance among alternatives from the ratings assigned from Likert scale to form a suggestion matrix with zero percent CR before judgment matrix which gives privilege to decision makers to change relative importance within the range of CR. This process intensifies the effectiveness of AHP by reducing time consumption through optimizing inconsistency

Development of Cost-Effective Menstrual Absorbent Pad with Eco-Friendly Antimicrobial Finish

Management of menstrual hygiene is a critical problem for Bangladeshi women and girls as the sanitary pads are expensive. Therefore, purchasing sanitary napkins for incredibly poor and middle-class families is very challenging. Many retail sanitary napkins are available on the local market, but most of them are costly. However, poor women’s are unable to purchase or use high-quality sanitary napkins. Thus, a maximum of nine sanitary napkin pad samples with very cheap raw materials (natural fibres) have been produced in this study. Newly manufactured products even undergo antimicrobial treatment with natural antimicrobial agents such as Tulshi and Aloe Vera accompanied by a simple production process, which ultimately makes the product cheaper and safer for the consumer during use. A maximum of nine samples were produced and compared with commercial samples for cost analysis. The primary objective of this research is to develop such a kind of sanitary napkin that will be cheaper as well as user-friendly in contrast to commercial samples. More interestingly, poor women are not used to wear underwear, because of which they are not interested in using pads as commercial sanitary napkins; panty or other underwear is required. For this reason, an adjustable waistband support is used in this experiment to easily attach the sanitary napkin without any gum. Since menstruation is directly linked to the human reproductive process, it is important for women and girls to manage menstruation appropriately. In addition, the material (especially sanitary napkin core forming materials) used in commercial sanitary napkins is synthetic and may lead to accelerated growth of bacteria and germs by long term use of the pad. The goal of this research was to construct an inexpensive sanitized pad that was treated with Aloe Vera and Tulshi extract. Tulshi and Aloe Vera modified non-woven fabrics incorporate antimicrobial activity against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). Therefore, as it can be used without undergarments, sanitary napkin is not only hygienic but also inexpensive and comfortable with effective protection against leakage. Findings demonstrate the newly developed prototype's substantial design and cost-effectiveness. &nbsp

Application of New Synthetic Fifth Generation Thickeners for Printing Cotton Fabric with Reactive Dyes

In this study,  fifth generation thickener EM620R (polyacrylate emulsion) was developed for reactive printing due to traditional thickener sodium alginate and synthetic thickener caused less saturation of color and increased fabric stiffness.  Printing was evaluated for the depth of the shade as well as other properties. The properties was obtained not only depending on the thickener and reactive dye but also depends on the concentration of NaHCO3, Urea in Printing paste, condition of fixation and storing time.  After comparison with synthetic thickener and sodium alginate on the basis of K/S  value in different situation, AATCC method fastness test; an extra ordinary  result came out which was shown as like EM620R (polyacrylate emulsion) EM620 (polyacrylate emulsion) Sodium Alginate. Although EM620R (polyacrylate emulsion) development solved the problem and increased the properties which create unthinkable impact on the world market for cost effectiveness

Advancing early leukemia diagnostics: a comprehensive study incorporating image processing and transfer learning.

Disease recognition has been revolutionized by autonomous systems in the rapidly developing field of medical technology. A crucial aspect of diagnosis involves the visual assessment and enumeration of white blood cells in microscopic peripheral blood smears. This practice yields invaluable insights into a patient's health, enabling the identification of conditions of blood malignancies such as leukemia. Early identification of leukemia subtypes is paramount for tailoring appropriate therapeutic interventions and enhancing patient survival rates. However, traditional diagnostic techniques, which depend on visual assessment, are arbitrary, laborious, and prone to errors. The advent of ML technologies offers a promising avenue for more accurate and efficient leukemia classification. In this study, we introduced a novel approach to leukemia classification by integrating advanced image processing, diverse dataset utilization, and sophisticated feature extraction techniques, coupled with the development of TL models. Focused on improving accuracy of previous studies, our approach utilized Kaggle datasets for binary and multiclass classifications. Extensive image processing involved a novel LoGMH method, complemented by diverse augmentation techniques. Feature extraction employed DCNN, with subsequent utilization of extracted features to train various ML and TL models. Rigorous evaluation using traditional metrics revealed Inception-ResNet's superior performance, surpassing other models with F1 scores of 96.07% and 95.89% for binary and multiclass classification, respectively. Our results notably surpass previous research, particularly in cases involving a higher number of classes. These findings promise to influence clinical decision support systems, guide future research, and potentially revolutionize cancer diagnostics beyond leukemia, impacting broader medical imaging and oncology domains

Maternal Depression and Its Associated Factors among the Mothers at Narayanganj in Bangladesh

Maternal depression is becoming a serious public health concern in the world day by day. The purpose of the current study was to assess the maternal depression and its associated factors among the mothers of Narayanganj city in Bangladesh. A cross-sectional study was conducted in six different areas at Narayanganj in Dhaka among 377 mothers having children of five to ten years between the periods of May, 2019 to September, 2019. The respondents were selected by simple random sampling method. All data analysis was done by using IBM SPSS version 20.0. The mean age of the pregnant women was 26±4 years. It was found that about 77% of mothers had high depressive symptoms whereas 10.7%, 6.63% and 6.36% of mothers had moderate, mild and no depressive symptoms, respectively.  It was observed that family income, family size, age of children and age at marriage were significantly (p<0.05) associated with maternal depression status. Further investigations might be carried out to assess the effect size of the associated factors mentioned above. Keywords: Maternal depression, mothers, children, associated factors. DOI: 10.7176/JHMN/102-06 Publication date:September 30th 2022