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PSYCHOMETRIC VALIDATION OF ORGANIZATIONAL JUSTICE SCALE FOR SCHOOL TEACHERS IN PAKISTANI CONTEXT 巴基斯坦情境下学校教师组织公平量表的心理测量验证
Pub Date : 2021-09-20 DOI: 10.51380/gujr-37-03-07
M. Aslam, Abid Hussain Chaudhary
Organizational justice is about fairness at the workplace. It is essential to enhance performance and success of every organization. The study was conducted to validate Organizational Justice Scale (OJS) in Punjab, Pakistani public school context developed by Neihoff and Moorman (1993). Sample size consisted of 400 randomly selected public school teachers. This study was based upon quantitative approach and cross- sectional survey design was applied in data collection. The data was collected personally from teachers. Factors analysis techniques EFA and CFA were applied to confirm dimensionality, validity and reliability of Organizational Justice Scale (OJS) in schools of Pakistani context. Results are in support of three dimensional model (distributive, procedural & interactional justice) and generalizability of this scale. Furthermore, the results also established adequate reliability and validity (convergent and discriminant validity) of OJS. Further studies can be conducted to further validate the OJS through different types of data analysis software and techniques. In addition, this scale would be useful for measurement of the organizational justice among teachers in schools.
组织公正是指工作场所的公平。这对提高每个组织的绩效和成功至关重要。本研究旨在验证Neihoff和Moorman(1993)开发的组织公正量表在巴基斯坦旁遮普公立学校情境下的有效性。样本量为随机抽取的400名公立学校教师。本研究采用定量方法,资料收集采用横断面调查设计。数据是亲自从老师那里收集的。采用因素分析技术EFA和CFA对巴基斯坦学校组织公正量表的维度、效度和信度进行验证。结果支持三维模型(分配正义、程序正义和互动正义)和该量表的普遍性。此外,结果还建立了OJS具有足够的信度和效度(收敛效度和判别效度)。进一步的研究可以通过不同类型的数据分析软件和技术来进一步验证OJS。此外,该量表还可用于衡量学校教师的组织公平感。
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引用次数: 1
DO BIG-5 PERSONALITY TRAITS CONTRIBUTE TO EMPLOYEES PERFORMANCE? AN EMPIRICAL EVIDENCE FROM HEIs IN PAKISTAN 大五种人格特征对员工绩效有影响吗?来自巴基斯坦高等教育的经验证据
Pub Date : 2021-09-20 DOI: 10.51380/gujr-37-03-01
Robina Akhtar, Mohamad Nizam Nazarudin, G. Kundi
Several factors influence the employee's personality including psycho-social factors. Previously studies have conducted to investigate the influence of Big-5 traits which impact employee’s performance. This study investigated the influence of Big-5 on the employee’s performance. The study used a cross-sectional survey a 5-point Likert scale was distributed among 163 samples selected randomly. The findings report a significant relationship between the predictors and a criterion variable. The study points those two predictors i.e., openness to experience and emotional control predict 57% variance in criterion variable as compared to the extravert, agreeableness, and conscientiousness. This study concludes that teacher’s centric policies & mechanisms enhance employee trust and confidence and it overcomes the apprehensions, as result, they perform better and contribute more towards the promotion of education and research in higher educational institutions.
影响员工人格的因素有很多,其中包括社会心理因素。以前的研究已经进行了调查大五特质对员工绩效的影响。本研究探讨了大五人格对员工绩效的影响。本研究采用横断面调查法,随机抽取163个样本,采用李克特5分量表。研究结果报告了预测因子和标准变量之间的显著关系。研究指出,与外向性、宜人性和责任心相比,经验开放性和情绪控制性这两个预测因子预测的标准变量方差为57%。本研究认为,以教师为中心的政策机制增强了员工的信任和信心,克服了员工的担忧,从而使员工表现得更好,为促进高等学校的教育和研究做出了更大的贡献。
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引用次数: 0
THE LIGHT TRIAD TRAITS, PSYCHOLOGICAL EMPOWERMENT, CREATIVE SELF-EFFICACY, SELF-RESILIENCE AND INNOVATIVE PERFORMANCE IN ICT OF PAKISTAN 巴基斯坦信息通信技术人员的光三合一特征、心理赋权、创造性自我效能、自我弹性与创新绩效
Pub Date : 2021-09-20 DOI: 10.51380/gujr-37-03-05
I. Khan, Umar Safdar, Zohair Durrani
This study analyses how the Information & Communication Technology sector of managers having light triad traits (altruism, empathy, compassion) associates employee innovative performance through creative self-efficacy, Self-Resilience, and psychological empowerment. This study used pro social trait theory for Light triad traits of managers and employees' perspectives to broaden and build an approach. This study hypothesized a relationship amid Light triad traits, creative self-efficacy, self-resilience and psychological empowerment, which affects the innovative performance of employee. Light triad traits have most substantial positive relationship with innovative performance when employees have high levels of the self-resilience and creative self-efficacy. The psychological empowerment mediates relationship between the Light triad traits and innovative employee performance. Data was collected in total from 650 employees, 500 employees (followers) in which they rated their managers (leaders) and after 1 week, 150 managers (leaders) rated their employee's performance and generated results to support our study hypotheses.
本研究分析了具有轻三合一特质(利他主义、共情、同情)的信息与通信技术部门的管理者如何通过创造性自我效能、自我弹性和心理授权来关联员工的创新绩效。本研究运用亲社会特质理论对管理者和员工的光三合一特质视角进行拓展和构建。本研究假设光明三合一特质、创新自我效能感、自我弹性和心理授权对员工创新绩效有影响。当员工的自我弹性和创造性自我效能水平较高时,轻三合一特质对创新绩效的正向影响最为显著。心理授权在光三合一特质与创新员工绩效之间起中介作用。总共收集了650名员工的数据,500名员工(追随者)对他们的经理(领导者)进行了评分,一周后,150名经理(领导者)对他们的员工的表现进行了评分,并得出了支持我们研究假设的结果。
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引用次数: 1
An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model 基于LSTM机器学习模型的逻辑回归准确预测比特币价格
Pub Date : 2021-09-20 DOI: 10.36548/jscp.2021.3.006
H. Andi
In recent years, there has been an increase in demand for machine learning and AI-assisted trading. To extract abnormal profits from the bitcoin market, the machine learning and artificial intelligence (AI) assisted trading process has been used. Each day, the data gets saved for the specified amount of time. These approaches produce great results when integrated with cutting-edge algorithms. The results of algorithms and architectural structures drive the development of cryptocurrency market. The unprecedented increase in market capitalization has enabled the cryptocurrency to flourish in 2017. Currently, the market accommodates totally 1500 cryptocurrencies, all of which are actively trading. It is always possible to mine the cryptocurrency and use it to pay for online purchases. The proposed research study is more focused on leveraging the accurate forecast of bitcoin prices via the normalization of a particular dataset. With the use of LSTM machine learning, this dataset has been trained to deploy a more accurate forecast of the bitcoin price. Furthermore, this research work has evaluated different machine learning methods and found that the suggested work delivers better results. Based on the resultant findings, the accuracy, recall, precision, and sensitivity of the test has been calculated.
近年来,对机器学习和人工智能辅助交易的需求有所增加。为了从比特币市场中提取异常利润,使用了机器学习和人工智能(AI)辅助的交易过程。每天,数据都会保存指定的时间。这些方法与先进的算法相结合会产生很好的结果。算法和架构结构的结果推动了加密货币市场的发展。市值的空前增长使加密货币在2017年蓬勃发展。目前,市场共容纳1500种加密货币,所有加密货币都在活跃交易。挖掘加密货币并使用它来支付在线购物总是可能的。拟议的研究更侧重于通过对特定数据集的规范化来利用比特币价格的准确预测。通过使用LSTM机器学习,该数据集已经过训练,可以对比特币价格进行更准确的预测。此外,本研究工作评估了不同的机器学习方法,发现建议的工作提供了更好的结果。根据所得结果,计算了测试的准确度、召回率、精密度和灵敏度。
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引用次数: 41
TEACHERS PERCEPTION ABOUT PROCESS OF TEACHER EVALUATION: A CASE STUDY OF A PRIVATE UNIVERSITY OF LAHORE 教师对教师评价过程的感知:以拉合尔私立大学为例
Pub Date : 2021-09-20 DOI: 10.51380/gujr-37-03-09
Shahid Rafiq, Shahzada Qaisar
The major premise of this research was to get the perception of university teachers about the process of teacher evaluation in one private university in Lahore. Focusing on the actual practices of teacher evaluation process (TEP), this paper attempts to get opinion of university teachers regarding the effectiveness of TEP. This research was quantitative in its nature in which a survey questionnaire was used to collect data. The population of the study included all the faculty members (both male and female) of the private sector university in Lahore. 150 faculty members were selected through simple random sampling from all faculties/departments of the sampled university. The data was analyzed on SPSS 21. Results were drawn from the interpretation of quantitative data. Results indicated that university teachers had very positive perceptions of the teacher evaluation process. The process of the teacher evaluation contributes to teachers teaching performance a lot.
本研究的主要前提是了解拉合尔一所私立大学教师对教师评价过程的看法。本文从教师评价过程的实践出发,试图了解高校教师对教师评价过程有效性的看法。本研究在其性质上是定量的,其中使用调查问卷来收集数据。本研究的人口包括拉合尔私立大学的所有教职员工(包括男性和女性)。通过简单随机抽样从抽样大学的所有院系/部门中选出150名教职员工。数据采用SPSS 21进行分析。结果来自定量数据的解释。结果显示,大学教师对教师评鉴过程有非常正面的看法。教师评价的过程对教师的教学绩效有很大的影响。
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引用次数: 3
Stochastic Geometry and Performance Analysis of Large Scale Wireless Networks 大规模无线网络的随机几何与性能分析
Pub Date : 2021-09-20 DOI: 10.36548/jtcsst.2021.3.001
J. Chen, Kong-Long Lai
Stochastic Geometry has attained massive growth in modelling and analysing of wireless network. This suits well for analysing the performance of large scale wireless network with random topologies. Analytical framework is established to evaluate the performance of the network. Here we have created a mathematical model for uplink analysis and the gain of uplink and downlink is obtained. Then ad-hoc network architecture is designed and the performance of the network is compared with the traditional method. Finally, a new scheduling algorithm is developed for cellular network and the gain parameter is quantified with the help of Stochastic Geometry tool. The accuracy is acquired from extensive Monte Carlo simulator.
随机几何在无线网络建模和分析方面取得了巨大的发展。这很适合分析具有随机拓扑结构的大规模无线网络的性能。建立了评价网络性能的分析框架。在此,我们建立了上行链路分析的数学模型,得到了上行链路和下行链路的增益。然后设计了自组织网络体系结构,并与传统方法进行了性能比较。最后,提出了一种新的蜂窝网络调度算法,并利用随机几何工具对增益参数进行了量化。精度是通过广泛的蒙特卡罗模拟器获得的。
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引用次数: 4
AN INVESTIGATION ON ROLE OF STRESS ON ACADEMIC PERFORMANCE OF STUDENTS 压力对学生学习成绩影响的调查
Pub Date : 2021-09-20 DOI: 10.51380/gujr-37-03-04
Y. H. Mughal
The purpose of the study is to investigate the role of stress upon academic performance of students. Stress is faced by each individual in academic, professional as well as daily routine life. The current study has identified different sources of stress which might be controlled to enhance academic performance of students. For this purpose cross-sectional design survey approach was conducted from two different universities from the different faculties. The development of scientific knowledge in current study is based on the positivism philosophy. The non probability convenience sampling technique was used. Population of the study was students from public and private universities. 210 students have participated in the study. Cronbach alpha, correlation and regression were used for analysis of data. SPSS 25 was used. Findings of study revealed that scale adopted from past studies was found reliable and there is significant positive relationship between factors of stress and academic performance of students. It was also found that academic factors were most dominant factors which played significant role in affecting students’ performance. This study is original contribution and has extended the body of knowledge of stress and student academic performance.
本研究的目的是探讨压力对学生学习成绩的影响。压力是每个人在学术、职业和日常生活中都要面对的。目前的研究已经确定了不同的压力来源,这些压力可以通过控制来提高学生的学习成绩。为此,我们从两所不同的大学的不同院系进行了横断面设计调查。当代科学知识的发展是以实证主义哲学为基础的。采用非概率方便抽样技术。研究对象为公立和私立大学的学生。210名学生参与了这项研究。数据分析采用Cronbach alpha、相关和回归分析。采用SPSS 25统计软件。研究结果表明,以往研究采用的量表是可靠的,压力因素与学生学业成绩之间存在显著的正相关关系。研究还发现,学业因素是影响学生学业成绩的最主要因素。本研究具有原创性,扩展了压力与学生学习成绩的知识体系。
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引用次数: 0
PUSH AND PULL FACTORS OF NEGATIVE SOCIAL BEHAVIOURS AMONG SECONDARY SCHOOL STUDENTS 中学生负性社会行为的推拉因素
Pub Date : 2021-09-20 DOI: 10.51380/gujr-37-03-06
Syed Zubair Haider, Uzma Munawar, Shaista Noreen
Education is considered critical for both showing positive behaviour and regulating negative social behaviour and affecting the social attitudes by improving one's ability to perceive others. Hence, this research examined the push and pull factors of Negative Social Behaviour among secondary school students. In this research, we collect data over two self-developed questionnaires. Thus, total 500 students (252 female, 248 male) and 120 teachers (60 male, 60 female) from 04 districts of Punjab were selected conveniently. The EFA revealed 06 dimensions possibly be extracted from two questionnaires designed for the students and teachers separately. Multilevel analyses mean SD, Pearson correlation, and independent-sample t-test were performed. Findings reveal that parents’ conflicts, peer’ bullying, teachers’ insulting behaviours and students’ sarcastic attitude are the major push factors that cause de-motivation and promote NSB among students. These factors severely influence students’ personality, and as a result, students lost study interest, behave roughly and violate the institutions’ rules.
教育被认为是表现积极行为和调节消极社会行为以及通过提高一个人感知他人的能力来影响社会态度的关键。因此,本研究探讨中学生负性社会行为的推拉因素。在本研究中,我们通过两个自行开发的问卷收集数据。因此,旁遮普省04个地区的500名学生(252名女学生,248名男学生)和120名教师(60名男教师,60名女教师)被方便地选中。全民教育揭示了可能从分别为学生和教师设计的两份问卷中提取的06个维度。采用多水平均值SD分析、Pearson相关分析和独立样本t检验。研究发现,家长冲突、同伴欺凌、教师侮辱行为和学生讽刺态度是导致学生去动机和促进非自觉行为的主要推动因素。这些因素严重影响了学生的个性,导致学生失去学习兴趣,行为粗鲁,违反学校规则。
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引用次数: 0
AN INVESTIGATION ON COVID-19 CONSPIRACY THEORY BELIEFS AMONGST PAKISTANI MUSLIMS 对巴基斯坦穆斯林新冠肺炎阴谋论信仰的调查
Pub Date : 2021-09-20 DOI: 10.51380/gujr-37-03-10
Mujeeba Ashraf
With the COVID-19 pandemic gripping world, there has been an alarming increase in role of conspiracy theories generated surrounding COVID-19. Thus, this research aims to understand what conspiracy beliefs Pakistani Muslims may possess about COVID-19. The research followed correlational research design. The data was collected through an online self-reported COVID-19 Conspiracies Belief Questionnaire from 110 Pakistani Muslims with a mean age of 25.40 and SD of 5.73. Descriptive statistics explained that 59%, 60%, 79% of the participants agree with the conspiracy that it accidentally escaped from the Chinese lab, planted by the American Army in China to destroy China's economy, and it is a punishment from Allah for human sins respectively. Chi-square analysis revealed that females believe more in conspiracies as compare to male research participants. Moreover, binary logistic regression explained that COVID-19 is a way to control the world by developing psychological fear. The findings may enable local and national governing bodies to develop the knowledge-based strategies to tackle conspiracy beliefs.
随着COVID-19大流行席卷全球,围绕COVID-19产生的阴谋论的作用惊人地增加。因此,本研究旨在了解巴基斯坦穆斯林可能对COVID-19持有什么样的阴谋信念。本研究遵循相关研究设计。数据通过在线自我报告的新冠肺炎阴谋信仰问卷收集,调查对象为110名巴基斯坦穆斯林,平均年龄25.40岁,SD为5.73。描述性统计说明,59%、60%、79%的参与者分别认同“意外逃出中国实验室”、“美军在中国栽植破坏中国经济”和“安拉对人类罪恶的惩罚”的阴谋论。卡方分析显示,女性比男性更相信阴谋论。此外,二元逻辑回归解释说,新冠病毒是通过产生心理恐惧来控制世界的一种方式。这些发现可能使地方和国家管理机构能够制定基于知识的策略来解决阴谋论。
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引用次数: 0
Construction of LWCNN Framework and its Application to Pedestrian Detection with Segmentation Process LWCNN框架的构建及其在行人分割检测中的应用
Pub Date : 2021-09-20 DOI: 10.36548/jiip.2021.3.008
R. Kanthavel
To solve the challenges in traffic object identification, fuzzification, and simplification in a real traffic environment, it is highly required to develop an automatic detection and classification technique for roads, automobiles, and pedestrians with multiple traffic objects inside the same framework. The proposed method has been evaluated on a database with complicated poses, motions, backgrounds, and lighting conditions for an urban scenario where pedestrians are not obstructed. The suggested CNN classifier has an FPR of less than that of the SVM classifier. Confirming the significance of automatically optimized features, the SVM classifier's accuracy is equal to that of the CNN. The proposed framework is integrated with the additional adaptive segmentation method to identify pedestrians more precisely than the conventional techniques. Additionally, the proposed lightweight feature mapping leads to faster calculation times and it has also been verified and tabulated in the results and discussion section.
为了解决真实交通环境中交通对象识别、模糊化和简化的难题,迫切需要开发一种对同一框架内多个交通对象的道路、汽车和行人进行自动检测和分类的技术。该方法已经在一个具有复杂姿势、运动、背景和照明条件的数据库上进行了评估,该数据库是在行人不受阻碍的城市场景中进行的。本文提出的CNN分类器的FPR小于SVM分类器。证实了自动优化特征的重要性,SVM分类器的准确率与CNN相当。该框架与附加的自适应分割方法相结合,比传统技术更精确地识别行人。此外,提出的轻量级特征映射导致更快的计算时间,它也在结果和讨论部分得到了验证和列表。
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引用次数: 0
期刊
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