Economic and Social Upgrading of Firms in Football Global Value Chains

Muhammad DANISH,Amira Khattak 한국유통과학회 2020 유통과학연구 Vol.18 No.4

Purpose: Participation of firms in Global Value Chains (GVC) has contributed significantly to the improvement of economic outcomes for firms in developing countries. However, evidence suggests that these economic outcomes are gained at the cost of labourers’ poor working conditions. This research contributes to existing literature on GVCs by investigating the influence of different governance structures on economic and social upgrading of firms participating in GVCs. Furthermore, the research attempts to understand the relationship between economic and social upgrading in GVCs. Research design and methodology: Detailed qualitative primary research was carried out in the football industry of Sialkot, Pakistan. The case study approach was employed, and football firms were the unit of analysis. Semi-structured interviews with firms’ representatives were conducted. Results: Findings reveal that most firms were found in captive, relational and market governance structures. Furthermore, product and process upgrading were witnessed in all firms; however, social upgrading was observed mostly in captive and relational GVCs. Moreover, social upgrading was linked to economic upgrading in captive and relational networks. Conclusions: The findings from the Sialkot football industry reflect that buyers pay higher prices and margins to their suppliers once they upgrade their products and processes.

Improved Stability and Damping Characteristics of LCL-Filter Based Distributed Generation System

Faiz Muhammad Talib,Khan Danish,Khan Muhammad Mansoor,Ali Abdar,Tang Houjun 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.3

The voltage source inverter is a key component in the distributed power generation systems where the LCL -fi lter is a popular choice for interfacing with the grid. However, the well-known resonance issue associated with the LCL -fi lter deteriorates the control performance and risk the inverter system stability. The inverter control design plays a signifi cant role to ensure the quality of the injected grid current and stable operation according to the requirements of grid interconnection standards. This paper deals with an alternative control design method that modifi es the internal damping loop design to improve the stability and damping characteristics. The proposed design employs a compensator across the fi lter and feedbacks the output of the augmented plant at the reference voltage point, and named as parallel feedforward compensation method. The fi lter capacitor current measured for damping loop implementation, and a high-pass fi lter compensator adopted in the proposed confi guration. The proportional capacitor current feedback compensation method is considered for comparative studies. The current loop stability and control performance characteristics are investigated in detail under the resonance frequency and fi lter parameters variation condition. The signifi cant outcomes of the proposed scheme are faster dynamic response, higher delay compensation capability, relatively improved resonance suppression, and potential for better tracking performance. An experimental prototype is developed to validate the effi cacy of the proposed method.

Relationship of the Big Five Personality Traits and Risk Aversion with Investment Intention of Individual Investors

SARWAR, Danish,SARWAR, Bilal,RAZ, Muhammad Asif,KHAN, Hadi Hassan,MUHAMMAD, Noor,AZHAR, Usman,ZAMAN, Nadeem uz,KASI, Mumraiz Khan Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.12

This empirical research is aimed at testing the relationship of the big five personality traits namely openness to experience, extraversion, consciousness, agreeableness, neuroticism, and risk aversion with the investment intention of individual investors belonging to Balochistan, Pakistan. The primary data is collected through a self-administered questionnaire (a structured form that consists of a series of closed-ended and open-ended questions) from a sample of 397 active individual investors belonging to different districts of the province. The data is empirically analyzed by applying the Partial Least Square (PLS) path modeling technique by using the estimation package available in Smart-PLS. The findings of this study suggest that all the variables are statistically significant with investors' investment intention with risk aversion as the strongest predictor. Moreover, openness to experience, extraversion, consciousness, agreeableness, and risk are significantly and positively related to an investor's investment intention, whereas neuroticism is negatively related to an investor's investment intention. The results extended by this study can be used by financial planners and investment bankers to channelize the available financial resources in diversified portfolios. The results will help financial planners to make available diverse investment alternatives for investors in Balochistan, thus catering to their unique needs. Academia must offer courses on contemporary finance paradigm based on behavioral finance to enable future business graduates to make wise financial decisions.

Detection and Recognition of Vehicle License Plates using Deep Learning in Video Surveillance

Farooq, Muhammad Umer,Ahmed, Saad,Latif, Mustafa,Jawaid, Danish,Khan, Muhammad Zofeen,Khan, Yahya International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.11

The number of vehicles has increased exponentially over the past 20 years due to technological advancements. It is becoming almost impossible to manually control and manage the traffic in a city like Karachi. Without license plate recognition, traffic management is impossible. The Framework for License Plate Detection & Recognition to overcome these issues is proposed. License Plate Detection & Recognition is primarily performed in two steps. The first step is to accurately detect the license plate in the given image, and the second step is to successfully read and recognize each character of that license plate. Some of the most common algorithms used in the past are based on colour, texture, edge-detection and template matching. Nowadays, many researchers are proposing methods based on deep learning. This research proposes a framework for License Plate Detection & Recognition using a custom YOLOv5 Object Detector, image segmentation techniques, and Tesseract's optical character recognition OCR. The accuracy of this framework is 0.89.

Tree species migration to north and expansion in their habitat under future climate: an analysis of eight tree species Khyber Pakhtunkhwa, Pakistan

Durrani Muhammad Abdullah,Raza Rohma,Shakil Muhammad,Sabir Shakeel,Danish Muhammad 한국생태학회 2024 Journal of Ecology and Environment Vol.48 No.1

Background: Khyber Pakhtunkhwa government initiated the Billion Tree Tsunami Afforestation Project including regeneration and afforestation approaches. An effort was made to assess the distribution characteristics of afforested species under present and future climatic scenarios using ecological niche modelling. For sustainable forest management, landscape ecology can play a significant role. A significant change in the potential distribution of tree species is expected globally with changing climate. Ecological niche modeling provides the valuable information about the current and future distribution of species that can play crucial role in deciding the potential sites for afforestation which can be used by government institutes for afforestation programs. In this context, the potential distribution of 8 tree species, Cedrus deodara, Dalbergia sissoo, Juglans regia, Pinus wallichiana, Eucalyptus camaldulensis, Senegalia modesta, Populus ciliata, and Vachellia nilotica was modeled. Results: Maxent species distribution model was used to predict current and future distribution of tree species using bioclimatic variables along with soil type and elevation. Future climate scenarios, shared socio-economic pathways (SSP)2-4.5 and SSP5-8.5 were considered for the years 2041–2060 and 2081–2100. The model predicted high risk of decreasing potential distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios for years 2041–2060 and 2081–2100, respectively. Recent afforestation conservation sites of these 8 tree species do not fall within their predicted potential habitat for SSP2-4.5 and SSP5-8.5 climate scenarios. Conclusions: Each tree species responded independently in terms of its potential habitat to future climatic conditions. Cedrus deodara and P. ciliata are predicted to migrate to higher altitude towards north in present and future climate scenarios. Habitat of D. sissoo, P. wallichiana, J. regia, and V. nilotica is practiced to be declined in future climate scenarios. Eucalyptus camaldulensis is expected to be expanded its suitability area in future with eastward shift. Senegalia modesta habitat increased in the middle of the century but decreased afterwards in later half of the century. The changing and shifting forests create challenges for sustainable landscapes. Therefore, the study is an attempt to provide management tools for monitoring the climate change-driven shifting of forest landscapes.

Prediction Model for Gastric Cancer via Class Balancing Techniques

Danish, Jamil,Sellappan, Palaniappan,Sanjoy Kumar, Debnath,Muhammad, Naseem,Susama, Bagchi,Asiah, Lokman International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.1

Many researchers are trying hard to minimize the incidence of cancers, mainly Gastric Cancer (GC). For GC, the five-year survival rate is generally 5-25%, but for Early Gastric Cancer (EGC), it is almost 90%. Predicting the onset of stomach cancer based on risk factors will allow for an early diagnosis and more effective treatment. Although there are several models for predicting stomach cancer, most of these models are based on unbalanced datasets, which favours the majority class. However, it is imperative to correctly identify cancer patients who are in the minority class. This research aims to apply three class-balancing approaches to the NHS dataset before developing supervised learning strategies: Oversampling (Synthetic Minority Oversampling Technique or SMOTE), Undersampling (SpreadSubsample), and Hybrid System (SMOTE + SpreadSubsample). This study uses Naive Bayes, Bayesian Network, Random Forest, and Decision Tree (C4.5) methods. We measured these classifiers' efficacy using their Receiver Operating Characteristics (ROC) curves, sensitivity, and specificity. The validation data was used to test several ways of balancing the classifiers. The final prediction model was built on the one that did the best overall.

Single shot laser speckle based 3D acquisition system for medical applications

Khan, Danish,Shirazi, Muhammad Ayaz,Kim, Min Young Elsevier 2018 Optics and lasers in engineering Vol.105 No.-

<P><B>Abstract</B></P> <P>The state of the art techniques used by medical practitioners to extract the three-dimensional (3D) geometry of different body parts requires a series of images/frames such as laser line profiling or structured light scanning. Movement of the patients during scanning process often leads to inaccurate measurements due to sequential image acquisition. Single shot structured techniques are robust to motion but the prevalent challenges in single shot structured light methods are the low density and algorithm complexity. In this research, a single shot 3D measurement system is presented that extracts the 3D point cloud of human skin by projecting a laser speckle pattern using a single pair of images captured by two synchronized cameras. In contrast to conventional laser speckle 3D measurement systems that realize stereo correspondence by digital correlation of projected speckle patterns, the proposed system employs KLT tracking method to locate the corresponding points. The 3D point cloud contains no outliers and sufficient quality of 3D reconstruction is achieved. The 3D shape acquisition of human body parts validates the potential application of the proposed system in the medical industry.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A single shot 3D acquisition system based on stereophotogrammetry and laser speckle projection is presented for anthropometric measurements. </LI> <LI> The stereo correspondence is established by tracking the feature points using KLT feature tracker instead of laser speckle correlation. </LI> <LI> The acquisition of the 3D point clouds by the proposed system contains no outliers and the number of 3D points is sufficient to create the 3D mesh of the measuring part. </LI> <LI> Experiments are performed to estimate the measurement accuracy of the system. </LI> </UL> </P>

Novel Secure Hybrid Image Steganography Technique Based on Pattern Matching

( Ali Hamza ),( Danish Shehzad ),( Muhammad Shahzad Sarfraz ),( Usman Habib ),( Numan Shafi ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.3

The secure communication of information is a major concern over the internet. The information must be protected before transmitting over a communication channel to avoid security violations. In this paper, a new hybrid method called compressed encrypted data embedding (CEDE) is proposed. In CEDE, the secret information is first compressed with Lempel Ziv Welch (LZW) compression algorithm. Then, the compressed secret information is encrypted using the Advanced Encryption Standard (AES) symmetric block cipher. In the last step, the encrypted information is embedded into an image of size 512 × 512 pixels by using image steganography. In the steganographic technique, the compressed and encrypted secret data bits are divided into pairs of two bits and pixels of the cover image are also arranged in four pairs. The four pairs of secret data are compared with the respective four pairs of each cover pixel which leads to sixteen possibilities of matching in between secret data pairs and pairs of cover pixels. The least significant bits (LSBs) of current and imminent pixels are modified according to the matching case number. The proposed technique provides double-folded security and the results show that stego image carries a high capacity of secret data with adequate peak signal to noise ratio (PSNR) and lower mean square error (MSE) when compared with existing methods in the literature.

3D Registration Using Inertial Navigation System And Kinect For Image-Guided Surgery

JoonYoung Bang,Shirazi Muhammad Ayaz,Khan Danish,Soo-in Park,Hyunki Lee,Min Young Kim 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10

When 3d image registration using 2d image by hand-held scanner, the most important thing is pose estimation and object surface measure. The relationship between images is important to image registration. In this paper suggest 3d registration using Kinect and INS. The Kinect and INS are integrated on rigid body to improve the accuracy of estimate pose. It can complement the disadvantages of each sensor through the sensor fusion of INS and vision sensor position to make more precise estimates. Using purposed system can measure the three-dimensional shape of a variety of objects, and also can obtain an accurate image in a medical imaging applications which require precision application and apply in Image-guided surgery.

Effect of once-a-day milk feeding on behavior and growth performance of pre-weaning calves

Mushtaq Syed Husnain,Hussain Danish,Hifz-ul-Rahman,Naveed-ul-Haque Muhammad,Ahmad Nisar,Sardar Ahmad Azeem,Chishti Ghazanfar Ali 아세아·태평양축산학회 2024 Animal Bioscience Vol.37 No.2

Objective: The objectives of the present study were to evaluate the effects of once-a-day milk feeding on growth performance and routine behavior of preweaning dairy calves. Methods: At 22nd day of age, twenty-four Holstein calves were randomly assigned to one of two treatment groups (n = 12/treatment) based on milk feeding frequency (MF): i) 3 L of milk feeding two times a day; ii) 6 L of milk feeding once a day. The milk feeding amount was reduced to half for all calves between 56 and 60 days of age and weaning was done at 60 days of age. To determine the increase in weight and structural measurements, each calf was weighed and measured at 3 weeks of age and then at weaning. The daily behavioral activity of each calf was assessed from the 22nd day of age till weaning (60th day of age) through Nederlandsche Apparatenfabriek (NEDAP) software providing real-time data through a logger fitted on the calf’s foot. Results: There was no interaction (p≥0.17) between MF and sex of the calves for routine behavioral parameters, body weight and structural measurements. Similarly, there was no effect of MF on routine behavioral parameters, body weight and structural measurements. However, the sex of the calves affected body weight gain in calves. Male calves had 27% greater total body weight and average daily gain than female calves. There was no effect of the sex of the calves on behavioral measurements. Collectively, in the current study, no negative effects of a once-a-day milk feeding regimen were found on routine behavioral and growth parameters of preweaning calves in group housing. Conclusion: Once-a-day milk feeding can be safely adopted in preweaning calves from 22nd day of age.