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The fake job posting has emerged as an alarming cyber-crime during the last few years which affects both job seekers and companies alike. Fraudulent companies and individuals lure job-seekers using multifarious methods on digital media platforms. Although several machine learning-based approaches exist for the automatic detection of fake job posts, they lack high accuracy and show skewed performance on imbalanced data. In addition, the influence of feature selection is not very well studied. This study overcomes these limitations using selective features through Chi-square and principal component analysis (PCA). The influence of dataset imbalance is also investigated through the synthetic minority oversampling technique (SMOTE). The performance of the proposed model is compared with individual machine learning models, as well as, existing state-of-the-art models. Results indicate that using SMOTE with Chi-square-based selective features yields the best results with a 0.99 accuracy using the proposed model. K-fold cross-validation further corroborates these results. [ABSTRACT FROM AUTHOR]

The Biochemistry Section at the Ayub Agricultural Research Institute (AARI) in Faisalabad served as the research hub for our study throughout 2020-21. We delved into the antioxidants and biochemical parameters found in an array of fruits including peach (Prunus persica), grapes (Vitis vinifera), grapefruit (Citrus paradisi), lychee (Litchi chinensis), fig (Ficus carica), plum (Prunus domestica), sweet lime (Citrus limetta), Kuranda (Carissa carandas), kiwi (Actinidia deliciosa), and pear (Pyrus communis). These fruits offer vital nutrition like Vitamin C, ranging from 2.49 in fig to 48.7 in sweet lime, mineral matter is minimum (0.34%) in pear and maximum 6.19% in Lychee, crude fiber was highest (7.26%) in kuranda and lowest (0.82%) in Grapefruit, crude fat was less than 1 in all the fruits except kuranda having crude fat 1.66%. crude protein was also less than one in most of the fruits under study except Fig (2.05%), Plum (3.33%) and Kuranda (1.16%). Total antioxidants were higher in Peach (94.1%) followed by Plum (88.5%), Sweet lime (84.6%) and Fig (83.9%) while lowest value was observed in Kuranda (10.4%). Their adequate consumption not only fortifies the immune system but also serves as a shield against afflictions. Phenols packed abundantly within fruits, stand out as some of the most nutrient-rich components. Total phenols were ranging from 13.8 µg GAE/mL (Grapefruit) to 1182.5 µg GAE/mL (Kuranda). Total sugar lies between 6% (Plum) to 14.3% (Luchee). This paper delves deep into an exhaustive analysis of bioactive compounds, exploring their antioxidant capacities within the most widely cultivated fruits. Our exploration identifies that all the fruits are useful due to one or more nutritious elements. Our findings conclusively advocate the regular consumption of fruits, emphasizing their pivotal role in fostering nutrition and safeguarding against diseases. [ABSTRACT FROM AUTHOR]

Industrial development not only proved to be the forerunner of revolutionary development in financials, it also opened new avenues in Islamic Financial fiqh. In fact, the industrial revolution has created new challenges for Islamic fiqh, which need to be addressed. Now the world has become a global village and business has expanded from a small scale to very large scale in the form of multinational companies. Thus, people from different geographical backgrounds, religious affiliations and fiqh interact with each other. Therefore, due to this mutual trade among traders having different fiqh backgrounds, sometimes face issues due to different fiqhi background. Jurists have difference of opinion in financial matters like Imam Abu Ḥanīfa, Imam Mālik, Imam Shāfiʿī and Imam Ahmad bin Hanbal have different opinions on permissibility or impermissibility of different financial matters. Therefore, it is a challenge to do business and financial dealings with persons having different followings. Many fiqh bodies (institutions) worldwide are working to resolve such issues. These institutions set the standard for Islamic Financial Institutions (IFIs) by addressing such issues by combining different fiqh on predefined parameters. Therefore, the objective of this study is to critically discuss and evaluate the talfīq with respect to financial matters in light of the resolutions of International Islamic fiqh Academy. Being qualitative in nature, this study uses content analysis to achieve its objective. To resolve the issues faced in financial matters, abandoning one fiqh and adopting another is called "talfīq ". Different bodies are working for this in the world and locally in Pakistan as well. They are all working as Sharī ʻah standard setting bodies, for all aspects of the life of the Muslim ummah, including financial matters. One of the standard setting bodies is International Islamic Fiqh Academy Jeddah. Since its inception, the academy has passed resolutions on hundreds of important financial matters, most of which adopted a consolidation approach. Some of these important financial issues are discussed in this paper. The purposes of this academy which is giving a ruling in financial matters, are also discussed in detail. A critical review of isti ṣnā ʿ (It refers to a contract under which an item is purchased before it comes into existence and an order is given for its manufacture.), as a binding contract and penalty clause in case of delayed delivery is particularly presented in this paper. [ABSTRACT FROM AUTHOR]

Labor safety at workplaces is a critical human rights concern in all industries around the world. Coal mines are considered one of the most dangerous workplaces and every year thousands of miners around the world die or get severe injuries in mining accidents. To make efficient technology-based accident mitigation plans for such work environments, the analysis of reasons which cause these accidents is of great value. This study contributes to the coal mines domain and proposed an approach using machine learning techniques to identify the reasons for the accidents. In our approach, a dataset containing the causes for accidents in text form that occurred in the past in coal mines has been used. We performed preprocessing to clean text data and then extract features to train the machine learning model using the term frequency-inverse document frequency (TF-IDF) technique. This study proposed the voting-based hybrid classifier (VHC) which is a combination of three individual machine learning models random forest, support vector classifier, and logistic regression using soft voting criteria. Evaluation of the model has been done in terms of accuracy, precision, recall, and f1 score. VHC outperforms all other stat of the art models by achieving the highest 0.96 accuracy score. [ABSTRACT FROM AUTHOR]

Skin lesion detection and classification is always observed as a difficult problem to solve. Manual detection of skin lesions via visual image inspection can be time-consuming and tedious. Automatic diagnosis and classification are considered a critical problem to solve because of the involvement of many factors like different image sizes, hairs in the image, bad color schemes, ruler marker, low-contrast, variation in lesion sizes, and gel bubble. Different methodologies were proposed by the researchers in the Dermatology Pigmented lesion classification. Researchers work on the binary class problem for the detection of Melanocytic lesions from the normal one. This study makes use of the MNIST HAM10000 dataset published by International Skin Image Collaboration. The dataset consists of seven classes of skin cancer diseases. Furthermore in this research, our stacked CNN model proves its superiority by achieving 95.2% accuracy along with data augmentation and image preprocessing techniques. [ABSTRACT FROM AUTHOR]

Currency salam is a financial product in the basket of Islamic finance that facilitates dealings in discounting of bills. Moreover, it allows provision for speculative future currency trading. This article shows that currency salam is prohibited in the light of Islamic rules of riba. Researchers have held three positions about modern currencies. The paper shows that the permissibility of currency salam is derived by combining together these three irreconcilable views about modern currencies. In other words, currency salam is the outcome of a fallacious methodology known as talfeeq which is merely a device of creating legal artifices (hiyal) for satisfying one's desires. It is argued that the permission of currency salam must be rejected because it is riba and it opens up the flood‐gate for financial speculations in the name of Islam. The paper also attempts to draw attention of the regulatory authorities to tackle this issue seriously as it will adversely affect the trust on Islamic banking regarding its Shariah compliance. [ABSTRACT FROM AUTHOR]

The advancement in technology made a significant mark with time, which affects every field of life like medicine, music, office, traveling, and communication. Telephone lines are used as a communication medium in ancient times. Currently, wireless technology overrides telephone wire technology with much broader features. The advertisement agencies and spammers mostly use SMS as a medium of communication to convey their business brochures to the typical person. Due to this reason, more than 60% of spam SMS are received daily. These spam messages cause users' anger and sometimes scam with innocent users, but it creates large profits for the spammer and advertisement companies. This study proposed an approach for the classification of spam and ham SMS using supervised machine learning techniques. The feature extracting techniques such as Term Frequency-Inverse Document Frequency (TF-IDF) and bag-of-words are used to extract features from data. The SMS dataset used was imbalanced, and to solve this problem, we used over-sampling and under-sampling techniques. The support vector classifier, gradient boosting machine, random forest, Gaussian Naive Bayes, and logistics regression are applied on the spam and ham SMS dataset to evaluate the performance using accuracy, precision, recall, and F1 score. The experiment result shows that the random forest classifies spam ham SMS more accurately with 99% accuracy. The proposed model is trained well to identify the SMS category in terms of Ham or Spam with TF-IDF features and oversampling technique. The performance of the proposed approach was also evaluated on the spam email dataset with significant 99% accuracy. [ABSTRACT FROM AUTHOR]

Little is known regarding effects of azo-dyes on soil organic matter cycling in soil. Therefore, this lab study was carried out in Government College University Faisalabad to understand effects of varying concentrations (100, 200, 400 mg kg-1 ) of reactive black (RB5), direct red (DR) and, acid yellow (AY) on soil organic matter cycling in a sandy loam, a clay loam, and a loam. Soils were mixed with the aforementioned dyes and incubated in lab for 636 hrs. Results revealed that DR induced change of -52 to +53%, -8 to -58%, and -50 to +8% on soil respiration rate in sandy loam, loam and clay loam soils respectively in first 160 h of incubation. RB5 induced a change of -52 to +49%, -38 to +9%, and -67 to -15% whereas, the AY induced a change of -54 to +36%, -34 to +24%, and -75 to -6% in respiration rate in sandy loam, loam and clay loam soils respectively during the same incubation time. The microbial biomass C (MBC) did not show any significant change in response to any azo dye in loam soil. Metabolic quotient indicated that the clay loam soil experienced the highest toxicity in response to DR and RB5 among the three soils. Overall, our study shows that not all the dyes are toxic to SOM cycling and that is dependent on the type of the azo dye as well as the intrinsic characteristics of the soils. [ABSTRACT FROM AUTHOR]

With the global spread of COVID-19, the governments advised the public for adopting safety precautions to limit its spread. The virus spreads from people, contaminated places, and nozzle droplets that necessitate strict precautionary measures. Consequently, different safety precautions have been implemented to fight COVID-19 such as wearing a facemask, restriction of social gatherings, keeping 6 feet distance, etc. Despite the warnings, highlighted need for such measures, and the increasing severity of the pandemic situation, the expected number of people adopting these precautions is low. This study aims at assessing and understanding the public perception of COVID-19 safety precautions, especially the use of facemask. A unified framework of sentiment lexicon with the proposed ensemble EB-DT is devised to analyze sentiments regarding safety precautions. Extensive experiments are performed with a large dataset collected from Twitter. In addition, the factors leading to a negative perception of safety precautions are analyzed by performing topic analysis using the Latent Dirichlet allocation algorithm. The experimental results reveal that 12% of the tweets correspond to negative sentiments towards facemask precaution mainly by its discomfort. Analysis of change in peoples' sentiment over time indicates a gradual increase in the positive sentiments regarding COVID-19 restrictions. [ABSTRACT FROM AUTHOR]

Purpose: Since 2004, Pakistan carried the banking sector under the umbrella of the Islamic financial paradigm, consequently the Islamic Banking Industry (IBI) placed an upright position in the banking and financial market of Pakistan. In this context, this study aims to analyze the effect of Shariah-compliant products of the IBI on the pace of economic growth in Pakistan. Design/methodology/approach: The data set covered 13 Pakistani Islamic banks comprising four full-fledged Islamic banks and 9 conventional banks holdings standalone Islamic Branches, for the period 2004–2019. Considering nature of the empirical model and data set, the estimation was carried out with the Pooled Ordinary least squares estimation technique. Findings: The findings of the study reveal that Shariah-compliant products have a positive effect on the pace of economic growth. This indication is based on the fact that five out of six Shariah-compliant products hold positive signs and are statistically significant. In addition, the empirical evidence shows that at large conventional financial sector signifies its role in the Shariah-compliant products and pace of economic growth nexus. Among the control variables, foreign direct investment, human capital, trade openness, inflation and private credit pose negative, whereas money supply and stock market capitalization have a positive effect on the pace of economic growth in Pakistan. Findings of the study points towards the fact that Shariah-compliant financing has great potential to enhance the economic growth of Pakistan therefore to touch the sustainable development goals (SDGs). Practical implications: Having played a significant role in the growth process, Islamic bankers should portray a positive image of their industry to the government authorities. The government should design a public policy to encourage Islamic modes of finance at a macro level to increase the pace of economic growth and therefore SDGs realization. Originality/value: Findings of the study present new insight into the application of Shariah-compliant products of IBI toward the realization of SDGs in case of Pakistan. [ABSTRACT FROM AUTHOR]

Sustainable development means that human societies survive and meet their needs without compromising the ability of future generations to meet their needs. It is as if existing resources are to be preserved for future generations and the resources that we are running out of are to be reduced or used in such a way that they remain usable for a long time. In modern times, due to population expansion and overuse of natural resources, resources are dwindling day by day and the world's population is not benefiting from these resources. Therefor the concept of sustainable development has become very popular globally and the United Nations Educational, Scientific and Cultural Organization (UNESCO) also introduced the Sustainable Development Goals (SDGs 2030) to ensure the balanced and sustainable economic and social development of human society. [ABSTRACT FROM AUTHOR]

The experiment was conducted at Biochemistry Section, Ayub Agricultural Research Institute, Faisalabad Pakistan, during the year 2017-18 to assess the total phenols and antioxidants potential of mango, grapes, banana, guava, mulberry, strawberry, loquat, melon, apricot and phalsa. Fruits samples were obtained from the market of Faisalabad Pakistan, washed, dry at room temperature, extracted their juice/pulp. Thejuice was stored at 4 °C for further analysis. Juice samples were processed for Vitamin-C, pH, TSS, total phenolics and total antioxidant capacity. The results showed that among all the ten fruits vitamin C was higher in mango (24.33 mg/100 mL) followed by phalsa (19.74 mg/100 mL) and Grapes (11.25 mg/100 mL), whereas lower value was observed in melon (3.3 mg/100 mL) and loquat (3.4 mg/100 mL). Vitamin C for other fruits lies between these. Highly acidic pH of fresh juices of all the fruits was observed except in melon (5.82) and guava (5.38) which is less acidic. Percentage of TSS was higher in phalsa, mulberry and mangoes (13.8, 13.5 and 13.9% respectively) and lesser in melon (5.6%). Antioxidant capacity (% DPPH reduction) was found higher in grapes (91.9%) and mango (91.2%) which was statistically at par with melon (90.9%), while lesser value was observed in mulberry (51.6%). Total phenolics were significantly higher in grapes (1266.4 pg GAE/mL), whereas minimum phenolic contents were found in melon (4.1 pg GAE/mL). Therefore, it was concluded that grapes are more nutritious and healthy fruit than other. [ABSTRACT FROM AUTHOR]

The current study was carried out in order to assess the effects of micronutrients (B, Fe, Zn) on the yield and quality of Kinnow (Citrus reticulata Blanco). Citrus is an important fruit crop of Pakistan and micronutrients are not only important for yield and quality of citrus but also for the human health. This experiment consisted of different soil treatments and foliar applications of B, Zn and Fe either alone or in combinations. The results revealed that the highest concentrations of these three micronutrients in soil were found where 20 g B, 40 g Zn and 100 g Fe were applied per plant, respectively through soil application. The highest concentrations of these micronutrients in the leaves of Kinnow were found in the individual treatments of foliar spray of 0.03 % B, 0.1 % Zn and 0.25 % Fe, respectively, followed by the combined application of B, Zn and Fe with concentration of 0.03%, 0.1% and 0.25%. Soil that had combined treatment, B: 10 g plant-1, Zn: 20 g plant-1, Fe: 50 g plant-1 gave the highest yield of fruit and juice content. Fruit drop was the highest in control and the lowest for 20 g B soil application. Total sugars, reducing sugars and TSS were the highest for 40 g Zn as soil application, followed by the combined treatment of B:10 g plant-1, Zn:20 g plant-1, Fe:50 g plant-1 . The non-reducing sugars were the highest in the case of combined soil application of B, Zn and Fe. It is concluded that the micronutrients application is a suitable approach for increasing the quality and yield of Kinnow [ABSTRACT FROM AUTHOR]

OBJECTIVE: To determine the quantitative comparison of handgrip strength between cardiac patients and age matched healthy controls using a handheld dynamometer. METHODS: This quantitative comparison cross-sectional study was th conducted at University of Lahore Teaching Hospital, Lahore from 17, th October 2017 to 5 February 2018. Twenty cardiac and twenty age matched healthy participants were selected using consecutive (non-probability) sampling technique. After approval from ethical committee, data was collected using questionnaire. Measurements were taken of grip strength of both hands by using Jammer Dynamometer. This method was repeated three times in order to obtain mean value of both hands. RESULTS: In this study 40 subjects were studied with mean age of the participants as 62.08±7.63years. Among them 23(57.5%) were male and 17(42.5%) were female. Mean age of males were 65±7.37years whereas mean age of females were 64.11±7.75years. Out of twenty cardiac patients, 12(60%) male and 5 (25%) female were suffering from myocardial infarction, 3(15%) female had angina. Twenty participants of age-matched healthy individual group included 11 (55%) males and 9 (45%) females. In quantitative comparison of the dominant handgrip strength of cardiac patients (54.28 ± 27.75) and age matched healthy control (74.78±30.33) there was noteworthy difference in mean values of both groups with significant p-value of 0.032 whereas in the strength of non-dominant hand grip in cardiac patients (54.11±26.46) and age matched healthy control (71.03±29.25), no significant difference was recorded. CONCLUSION: Grip strength of dominant hand is less in cardiac patients as compared to healthy normal individual with significant relationship whereas there is no significant difference among non-dominant hand strength in both groups. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To determine the quantitative comparison of handgrip strength between cardiac patients and age matched healthy controls using a handheld dynamometer. METHODS: This quantitative comparison cross-sectional study was th conducted at University of Lahore Teaching Hospital, Lahore from 17th, th October 2017 to 5th February 2018. Twenty cardiac and twenty age matched healthy participants were selected using consecutive (non-probability) sampling technique. After approval from ethical committee, data was collected using questionnaire. Measurements were taken of grip strength of both hands by using Jammer Dynamometer. This method was repeated three times in order to obtain mean value of both hands. RESULTS: In this study 40 subjects were studied with mean age of the participants as 62.08±7.63years. Among them 23(57.5%) were male and 17(42.5%) were female. Mean age of males were 65±7.37years whereas mean age of females were 64.11±7.75years. Out of twenty cardiac patients, 12(60%) male and 5 (25%) female were suffering from myocardial infarction, 3(15%) female had angina. Twenty participants of age-matched healthy individual group included 11 (55%) males and 9 (45%) females. In quantitative comparison of the dominant handgrip strength of cardiac patients (54.28 ± 27.75) and age matched healthy control (74.78±30.33) there was noteworthy difference in mean values of both groups with significant p-value of 0.032 whereas in the strength of non-dominant hand grip in cardiac patients (54.11±26.46) and age matched healthy control (71.03±29.25), no significant difference was recorded. CONCLUSION: Grip strength of dominant hand is less in cardiac patients as compared to healthy normal individual with significant relationship whereas there is no significant difference among non-dominant hand strength in both groups. [ABSTRACT FROM AUTHOR]

The concept of discounting is a most important issue in the world of economics and finance from both conventional and Islamic perspective, because it relates to capital and interest. Islamic finance cannot depend on the conventional techniques of capital budgeting because of interest. Conventional capital budgeting techniques involve time value of money and discounting the future cash flows in this respect which is strictly prohibited in Islam. There are two aspects of discounting; evaluation tool and consideration. A few scholars have discussed the time value of money and discounting in different aspects but all studies ignored the role of discounting as an evaluation tool. They also did not distinguish the time value of money from the concept time value of commodity. The purpose of this study is to answer the question whether discounting as an evaluation tool is permissible in Islamic perspective or not? The study will also differentiate the time value of money from time value of commodity. The study also clarifies that there is no objection in taking time value of money just for sake of capital budgeting and what is prohibited is time value of money taken as consideration. [ABSTRACT FROM AUTHOR]

Currently, the high complexity of video contents has posed the following major challenges for fast retrieval: (1) efficient similarity measurements, and (2) efficient indexing on the compact representations. A video-retrieval strategy based on fuzzy c-means (FCM) is presented for querying by example. Initially, the query video is segmented and represented by a set of shots, each shot can be represented by a key frame, and then we used video processing techniques to find visual cues to represent the key frame. Next, because the FCM algorithm is sensitive to the initializations, here we initialized the cluster center by the shots of query video so that users could achieve appropriate convergence. After an FCM cluster was initialized by the query video, each shot of query video was considered a benchmark point in the aforesaid cluster, and each shot in the database possessed a class label. The similarity between the shots in the database with the same class label and benchmark point can be transformed into the distance between them. Finally, the similarity between the query video and the video in database was transformed into the number of similar shots. Our experimental results demonstrated the performance of this proposed approach. [ABSTRACT FROM AUTHOR]

Regular inspection of railway track health is crucial for maintaining safe and reliable train operations. Factors, such as cracks, ballast issues, rail discontinuity, loose nuts and bolts, burnt wheels, superelevation, and misalignment developed on the rails due to non-maintenance, pre-emptive investigations and delayed detection, pose a grave danger and threats to the safe operation of rail transport. The traditional procedure of manually inspecting the rail track using a railway cart is both inefficient and prone to human error and biases. In a country like Pakistan where train accidents have taken many lives, it is not unusual to automate such approaches to avoid such accidents and save countless lives. This study aims at enhancing the traditional railway cart system to address these issues by introducing an automatic railway track fault detection system using acoustic analysis. In this regard, this study makes two important contributions: data collection on Pakistan railway tracks using acoustic signals and the application of various classification techniques to the collected data. Initially, three types of tracks are considered, including normal track, wheel burnt and superelevation, due to their common occurrence. Several well-known machine learning algorithms are applied such as support vector machines, logistic regression, random forest and decision tree classifier, in addition to deep learning models like multilayer perceptron and convolutional neural networks. Results suggest that acoustic data can help determine the track faults successfully. Results indicate that the best results are obtained by RF and DT with an accuracy of 97%. [ABSTRACT FROM AUTHOR]