http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Israr AHMAD,Shuhymee Bin AHMAD 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.4
The study aims to investigate the mediating effect of strategic planning on the relationship between managerial skills and the performance of small- and medium-sized enterprises (SMEs) in Punjab, Pakistan. Stratified proportionate probability sample method was used to select the 265 SMEs. The study applied a structural equation model (SEM) to analyze the proposed research hypotheses by using PLS-SEM. This research examines the direct and indirect effects of strategic planning on the performance of SMEs using the SEM test. The results indicate the positive effect of managerial skills on SMEs’ performance and also suggested that strategic planning mediates the relationship between managerial skills and SMEs’ performance. In addition, the role of managerial skills on the usage of the company’s resources is highly influential through strategic planning. Strategic planning has been found to impact significantly and positively on the relationship between managerial skills and performance of SMEs in Punjab, Pakistan. The findings suggested that, in devising appropriate strategies for SMEs, the effect of managerial skills on the utilization of the firm’s resources can be more effective to the firm’s performance. In short, the utilization of a firm’s resources through a proper planning is more essential for the sustainability of SMEs.
Hydrothermal Synthesis of Fe Based MOFs with Energy Economy Approach
Israr, Farrukh,Kim, Duk Kyung,Kim, Yeongmin,Oh, Seung Jin,Ng, Kim Choon,Chun, Wongee The Korean Society for Energy 2015 에너지공학 Vol.24 No.2
The mesoporous metal organic framework structure Fe-BTC was successfully synthesized by hydrothermal process with noticeable yield. The synthesis operation was conducted at intermediate temperature and for shortened operation time as compared to conventional procedures. This process approach with reduced operating temperature and shortened operation time may open an opportunity window towards process economy with reduction in energy consumption. A simple mathematical approach of diffraction indexing using X-ray diffraction patterns of synthesized powder was employed to confirm its crystalline nature and to investigate its high temperature stability. The crystallite size was calculated by using Debye-Scherrer equation.
Cost effective and low energy consuming hydrothermal synthesis of Ni based MOF
Israr, Farrukh,Kim, Duk Kyung,Kim, Yeongmin,Oh, Seung Jin,Ng, Kim Choon,Chun, Wongee The Korean Society for Energy 2015 에너지공학 Vol.24 No.2
The mesoporous metal organic framework structure of Ni-BTC was successfully synthesized in a low temperature and short operation time via hydrothermal synthesis process. Such operational route virtuously consumed less electrical and thermal energy. It proved time saving along with acceptable product yield (38%). The product was characterized through FESEM, FT-IR, XRD and $N_2$ gas adsorption measurement. Hightemperature stability of synthesized MOF was gauged by diffraction indexing of XRD patterns of as synthesized and heat treated samples of MOFs. The mathematically calculated particle size of Ni-BTC was found to be 42nm.
A Survey on Deep Convolutional Neural Networks for Image Steganography and Steganalysis
( Israr Hussain ),( Jishen Zeng ),( Xinhong ),( Shunquan Tan ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.3
Steganalysis & steganography have witnessed immense progress over the past few years by the advancement of deep convolutional neural networks (DCNN). In this paper, we analyzed current research states from the latest image steganography and steganalysis frameworks based on deep learning. Our objective is to provide for future researchers the work being done on deep learning-based image steganography & steganalysis and highlights the strengths and weakness of existing up-to-date techniques. The result of this study opens new approaches for upcoming research and may serve as source of hypothesis for further significant research on deep learning-based image steganography and steganalysis. Finally, technical challenges of current methods and several promising directions on deep learning steganography and steganalysis are suggested to illustrate how these challenges can be transferred into prolific future research avenues.
Akhter Israr,Jalal Ahmad,Kim Kibum 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.5
To understand daily events accurately, adaptive pose estimation (APE) systems require a robust context-aware model and optimal feature selection methods. In this paper, we propose a novel gait event detection (GED) system that consists of saliency silhouette detection, a robust body parts model and a 2D stick-model followed by a hierarchical optimization algorithm. Furthermore, the most prominent context-aware features such as energy, 0–180° intensity and distinct moveable features are proposed by focusing on invariant and localized characteristics of human postures in diff erent event classes. Finally, we apply Grey Wolf optimization and a genetic algorithm to discriminate complex postures and to provide appropriate labels to each event. In order to evaluate the performance of proposed GED, two public benchmark datasets, UCF101 and YouTube, are examined via the n -fold cross validation method. For the two benchmark datasets, our proposed method detects the human body key points with 82.4% and 83.2% accuracy respectively. Also, it extracts the context-aware features and fi nally recognizes the gait events with 82.6% and 85.0% accuracy, respectively. Compared with other well-known statistical and state-of-the-art methods, our proposed method outperforms other similarly tasked methods in terms of posture detection and recognition accuracy.