The relationship between salary, benefits and career development with employee satisfaction in Giatmara Kedah

Employee satisfaction is the main factor of any turnover rate in any organization. With satisfied employees, it will be more easier to achieve organization goals or target. This research is to investigate factors of employee satisfaction for trainers of GIATMARA Kedah. The main purpose of the study is to prove the relationship between salary, benefits and career development with employee satisfaction. The study used quantitative method. The population of the study is the trainers of GIATMARA Kedah. The data collected through self-administered questionnaires from 90 trainers of GIATMARA Kedah selected by computerized random selection technique. The questionnaires were adapted from past researchers and the results showed positive relationship between salary, benefits and career development with employee satisfaction. The findings revealed that the trainers of GIATMARA Kedah are satisfied with their work in GIATMARA. This research provides better understanding on the employee satisfaction in GIATMARA Kedah and potential use of findings can b used by the organization as a reference for future research

Adaptive interference mitigation with user grouping for fast transmission in cellular networks

Designing uplink systems which group users with adaptive interference mitigation techniques is the objective of this research. Reduction in error rates and improvement in the energy efficiency is expected with this approach in addition to spectral efficiency. This paper reports a study on interference mitigation and transmission designs for groups of users in the uplinks. New formulations for the interference mitigation are produced based on the minimum mean square error and successive interference cancellation approach. By reducing the interference, the energy efficiency can be maintained and improved although the number of users per group increases. The measured error rates of this approach with user grouping achieve gains between 1 to 3 dB against that of the existing approach. With reduced complexity, the proposed scheme should be viable for practical deployment

Accuracy study of image classification for reverse vending machine waste segregation using convolutional neural network

This study aims to create a sorting system with high accuracy that can classify various beverage containers based on types and separate them accordingly. This reverse vending machine (RVM) provides an image classification method and allows for recycling three types of beverage containers: drink carton boxes, polyethylene terephthalate (PET) bottles, and aluminium cans. The image classification method used in this project is transfer learning with convolutional neural networks (CNN). AlexNet, GoogLeNet, DenseNet201, InceptionResNetV2, InceptionV3, MobileNetV2, XceptionNet, ShuffleNet, ResNet 18, ResNet 50, and ResNet 101 are the neural networks that used in this project. This project will compare the F1-score and computational time among the eleven networks. The F1-score and computational time of image classification differs for each neural network. In this project, the AlexNet network gave the best F1-score, 97.50% with the shortest computational time, 2229.235 s among the eleven neural networks

A review of defense in depth physical security model

Physical security, parameter protection and access control in government agencies especially in State Government localities have suffered severe negligence and disrepair. Local state governments, many established over four decades ago, applied obsolete security and safety measures within its compound. The main problems faced such as building maintenance scheme, lack of security measures and implementation and poorly documented security references are further described in this paper. The foundation of physical security protection design lay the groundwork as a basis of research. Then, mechanical physical protection schemes are investigated to mitigate the lack of safety and security mentioned. To complement these measures, Crime Prevention Through Environmental Design (CPTED) Principles and Security Education, Training and Awareness (SETA) techniques are further explored in hopes to establish an all-encompassing security model. This study will use a mix method design by incorporating qualitative and quantitative analysis. Main data collection came from sets of questionnaires and observation checklists by using CPTED, Physical Security Plan and SETA principles. The finding of this study is to prove whether this model can increase overall security in the State Government localities. This study hopes to propose a complete physical security model that can be reproduced and most importantly, increases overall security in State Government and the Federal Institution compound in general

Analysis of momentous fragmentary formants in Talaqi-like neoteric assessment of Quran recitation using MFCC miniature features of Quranic syllables

The use of technological speech recognition systems with a variety of approaches and techniques has grown rapidly in a variety of human-machine interaction applications. Further to this, a computerized assessment system to identify errors in reading the Qur’an can be developed to practice the advantages of technology that exist today. Based on Quranic syllable utterances, which contain Tajweed rules that generally consist of Makhraj (articulation process), Sifaat (letter features or pronunciation) and Harakat (pronunciation extension), this paper attempts to present the technological capabilities in realizing Quranic recitation assessment. The transformation of the digital signal of the Quranic voice with the identification of reading errors (based on the Law of Tajweed) is the main focus of this paper. This involves many stages in the process related to the representation of Quranic syllable-based Recitation Speech Signal (QRSS), feature extraction, non-phonetic transcription Quranic Recitation Acoustic Model (QRAM), and threshold classification processes. MFCC-Formants are used in a miniature state that are hybridized with three bands in representing QRSS combined vowels and consonants. A human-guided threshold classification approach is used to assess recitation based on Quranic syllables and threshold classification performance for the low, medium, and high band groups with performances of 87.27%, 86.86%and 86.33%, respectively

Road markers classification using binary scanning and slope contours

Road markers guide the driver while driving on the road to control the traffic for the safety of the road users. With the booming autonomous car technology, the road markers classification is important in its vision segment to navigate the autonomous car. A new method is proposed in this paper to classify five types of road markers namely dashed, single, double, solid-dashed and dashed-solid which are commonly found on the two lane single carriageway. The classification is using unique feature acquired from the binary image by scanning on each of the images to calculate the frequency of binary transition. Another feature which is the slopes between the two centroids which allow the proposed method, to perform the classification within the same video frame period. This proposed method has been observed to achieve an accuracy value of at least 93%, which is higher than the accuracy value achieved by the existing method

Building a Smart Gardening System and Plant Monitoring Using IoT

Gardening activities usually required a lot of time and gardeners may face varieties of problems such as sticking to the designated watering schedule. Thus, this paper intends to solve these problems by introducing the Smart Gardening System. By using this system, users will be able to control and monitor the watering schedule and the sufficiency of lights while ensuring that the plants are taken care of accordingly. The smart gardening system is different from the normal gardening products that are already available in the market because of the implementation of Internet of Things (IoT) in the system to facilitate the work for its users. By using this home-based system, users can set the watering and lighting schedule automatically by using the designated application via smartphone. Besides, users will also be notified on the moisture level of soil, light-exposure, and the water level in water tank through the application. This will allow the users to monitor the watering system and only come to refill it when the water tank is empty. This system is an advantage as it can run automatically. From this research, the benefit of smart gardening system is proven via the execution of IoT which requires less human intervention for the system to operate. Moreover, the sensors are used to gather and update all the data that is convenience to the user to keep updated on the parameter and information about the plant in a real time without physical present

Review of Environmental Wireless Sensor Networks System and Design

The paper presents the review of wireless system networks development for environmental application. An environmental problem such as climate change requires urgent attention. The use of embedded system and wireless sensors make monitoring possible for areas such as remote and harsh environment. Environment parameters such CO2 and other greenhouse gasses are monitored using the sensor attached to a wireless remote node from a different location and transmitted to the central unit for processing. It is important to use the right type of wireless technology since the remote application requires low power management and resistance to noise. There are several types of modules such as WI-FI, GPRS, Bluetooth, ZigBee and other wireless technology. The related work in this field will be reviewed and factors such as topology, power requirement, and good system design approach will be taken into account for the system review

5G NOMA user grouping using discrete particle swarm optimization approach

Non-orthogonal multiple access (NOMA) technology meets the increasing demand for high-seed cellular networks such as 5G by offering more users to be accommodated at once in accessing the cellular and wireless network. Moreover, the current demand of cellular networks for enhanced user fairness, greater spectrum efficiency and improved sum capacity further increase the need for NOMA improvement. However, the incurred interference in implementing NOMA user grouping constitutes one of the major barriers in achieving high throughput in NOMA systems. Therefore, this paper presents a computationally lower user grouping approach based on discrete particle swarm intelligence in finding the best user-pairing for 5G NOMA networks and beyond. A discrete particle swarm optimization (DPSO) algorithm is designed and proposed as a promising scheme in performing the user-grouping mechanism. The performance of this proposed approach is measured and demonstrated to have comparable result against the existing state-of-the art approach