http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Comparison of Honeypot System, Types, and Tools
Muhammad Junaid Iqbal,Muhammad Usman Ahmed,Muhammad Asaf International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.11
Network security is now more crucial than ever for consumers, companies, and military clients. Security has elevated to the top of the priority list since the Internet's creation. The evolution of security technology is now better understood. The area of community protection as a whole is broad and dynamic. News from the days before the internet and more recent advancements in community protection are both included in the topic of observation. Recognize current research techniques, previous Defence strategies that were significant, and network attack techniques that have been used before. The security of various domain names is the subject of this article's description of bibliographic research.
Optimized Deep Learning Techniques for Disease Detection in Rice Crop using Merged Datasets
Muhammad Junaid,Sohail Jabbar,Muhammad Munwar Iqbal,Saqib Majeed,Mubarak Albathan,Qaisar Abbas,Ayyaz Hussain International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.3
Rice is an important food crop for most of the population in the world and it is largely cultivated in Pakistan. It not only fulfills food demand in the country but also contributes to the wealth of Pakistan. But its production can be affected by climate change. The irregularities in the climate can cause several diseases such as brown spots, bacterial blight, tungro and leaf blasts, etc. Detection of these diseases is necessary for suitable treatment. These diseases can be effectively detected using deep learning such as Convolution Neural networks. Due to the small dataset, transfer learning models such as vgg16 model can effectively detect the diseases. In this paper, vgg16, inception and xception models are used. Vgg16, inception and xception models have achieved 99.22%, 88.48% and 93.92% validation accuracies when the epoch value is set to 10. Evaluation of models has also been done using accuracy, recall, precision, and confusion matrix.
Characterization and Comparative Evaluation of Milk Protein Variants from Pakistani Dairy Breeds
Iqra Yasmin,Rabia Iqbal,Atif Liaqat,Wahab Ali Khan,Muhamad Nadeem,Aamir Iqbal,Muhammad Farhan Jahangir Chughtai,Syed Junaid Ur Rehman,Saima Tehseen,Tariq Mehmood,Samreen Ahsan,Saira Tanweer,Saima Naz 한국축산식품학회 2020 한국축산식품학회지 Vol.40 No.5
The aim of study was to scrutinize the physicochemical and protein profile of milk obtained from local Pakistani breeds of milch animals such as Nilli-Ravi buffalo, Sahiwal cow, Kajli sheep, Beetal goat and Brela camel. Physicochemical analysis unveiled maximum number of total solids and protein found in sheep and minimum in camel. Buffalo milk contains the highest level of fat (7.45%) while camel milk contains minimum (1.94%). Ash was found maximum in buffalo (0.81%) and sheep (0.80%) while minimum in cow’s milk (0.71%). Casein and whey proteins were separated by subjecting milk to isoelectric pH and then analyzed through sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). The results showed heterogeneity among these species. Different fractions including αS1, αS2, κ-casein, β-casein and β-lactoglobulen (β-Lg) were identified and quantitatively compared in all milk samples. Additionally, this electrophoretic method after examining the number and strength of different protein bands (αS1, αS2, β- CN, α-LAC, BSA, and β-Lg, etc.), was helpful to understand the properties of milk for different processing purposes and could be successfully applied in dairy industry. Results revealed that camel milk was best suitable for producing allergen free milk protein products. Furthermore, based on the variability of milk proteins, it is suggested to clarify the phylogenetic relationships between different cattle breeds and to gather the necessary data to preserve the genetic fund and biodiversity of the local breeds. Thus, the study of milk protein from different breed and species has a wide range of scope in producing diverse protein based dairy products like cheese.
Estimation of Desired Motion Intention and Compliance Control for Upper Limb Assist Exoskeleton
압둘 마난 칸,윤덕원,Khalil Muhammad Zuhaib,Junaid Iqbal,Rui-Jun Yan,Fatima Khan,한창수 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.2
In this paper, we have addressed two issues for upper limb assist exoskeleton. 1) Estimation of DesiredMotion Intention (DMI); 2) Robust compliance control. To estimate DMI, we have employed Extreme LearningMachine Algorithm. This algorithm is free from traditional Neural Network based problems such as local minima,selection of suitable parameters, slow convergence of adaptation law and over-fitting. These problems cause lot ofproblem in tuning the intelligent algorithm for the desired results. Furthermore, to track the estimated trajectory, wehave developed model reference based adaptive impedance control algorithm. This control algorithm is based onstable poles of desired impedance model, forcing the over all system to act as per desired impedance model. It alsoconsiders robot and human model uncertainties. To highlight the effectiveness of the proposed control algorithm, wehave compared it with simple impedance and target reference based impedance control algorithms. Experimentalevaluation is carried on seven degree of freedom upper limb assist exoskeleton. Results describe the effectiveness ofELM algorithm for DMI estimation and robust tracking of the estimated trajectory by the proposed model referenceadaptive impedance control law.
Mian Ashfaq Ali,김창준,김상호,Abdul Manan Khan,Junaid Iqbal,Mohammad Zuhaib Khalil,임동환,한창수 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.2
This article proposes an automatic longitudinal deceleration based method for multi-wheel vehiclerollover safety in autonomous mode. The information of lateral acceleration and vehicle roll angle is used togenerate the longitudinal acceleration at which the vehicle will remain stable to rollover. The lateral and roll dynamicsare coupled with longitudinal dynamics using a potential field function for lateral acceleration. This virtualpotential field is developed on g-g diagram which represents vehicle portrait of lateral and longitudinal accelerationon abscissa and ordinate respectively. The motion of vehicle is represented by a point moving on this phase portraitof g-g diagram. TruckSim model of multi-wheel military vehicle with in-wheel motors is used with this algorithmwhich shows that the vehicle is less susceptible to rollover. The safe longitudinal acceleration is achieved by torquecontrol of in-wheel motors fitted in each wheel. Using this method, the vehicle followed the desired trajectory ashigher speeds which are safe. This is particularly useful for vehicle autonomous driving with rollover stability.
Passivity Based Adaptive Control for Upper Extremity Assist Exoskeleton
한창수,압둘 마난 칸,윤덕원,Mian Ashfaq Ali,Khalil Muhammad Zuhaib,원조,Junaid Iqbal,신규식 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.1
Upper limb assist exoskeleton robot requires quantitative techniques to assess human motor function andgenerate command signal for robots to act in compliance with human motion. To asses human motor function,we present Desired Motion Intention (DMI) estimation algorithm using Muscle Circumference Sensor (MCS) andload cells. Here, MCS measures human elbow joint torque using human arm kinematics, biceps/triceps musclemodel and physiological cross sectional area of these muscles whereas load cells play a compensatory role for thetorque generated by shoulder muscles as these cells measure desire of shoulder muscles to move the arm and notthe internal activity of shoulder muscles. Furthermore, damped least square algorithm is used to estimate DesiredMotion Intention (DMI) from these torques. To track this estimated DMI, we have used passivity based adaptivecontrol algorithm. This control techniques is particular useful to adapt modeling error of assist exoskeleton robotfor different subjects. Proposed methodology is experimentally evaluated on seven degree of freedom upper limbassist exoskeleton. Results show that DMI is well estimated and tracked for assistance by the proposed controlalgorithm.