Enhancing individual employability skills: A case study of Universiti Teknologi MARA Pahang

The increase in the number of graduates is not commensurate with the number of jobs available. This has created a fortuitous situation for employers who have the advantage in selecting the best and rejecting the rest. In this study, student engagement, curriculum design and teaching methods have been selected as the independent variables, while the employability skills, as a dependent variable. They will be tested in order to determine whether there is a relationship among them. For the purpose of data analysis, a survey had been done to the UiTM Pahang’s final semester students by using the Simple Random Sampling. The result reveals positive relationships between those variables and enhancing students’ employability skills. The numbers of questionnaires distributed were 200, where 170 respondents had returned their questionnaire which consists of 85%. After data screening, 4 questionnaire are rejected due to invalid or incomplete, thus, 166 questionnaires used in the final analysis. The correlation coefficient for the Student Engagement (Behavioural) with Employability Skills (Analytical Skills, Soft Skills and Non- Technical Skills) is 0.537, 0.440, 0.482 p<0.00, Student Engagement (Emotional) with Employability Skills (Analytical Skills, Soft Skills and Non-Technical Skills) is 0.747, 0.615, 0.635, p<0.00, Teaching Method with Employability Skills (Analytical Skills, Soft Skills and Non-Technical Skills) is 0.707, 0.594, 0.589, p<0.00 and for the Curriculum Design (Coursework) with Employability Skills (Analytical Skills, Soft Skills and Non-Technical Skills) is 0.692, 0.613, 0.642, p<0.00, While, Pearson Correlation Curriculum Design (Internship) with Employability Skills (Analytical Skills, Soft Skills and Non-Technical Skills) is 0.593, 0.455, 0.497 p<0.00. Thus, it is crucial for the organization to put a great emphasize on the significant roles played by these three variables in enhancing student employability skills

DTMF and CLIP decoding in a noisy area using adaptive approach

Multi-frequency signals are greatly used in telecommunication fields. Signaling and speech are such an example of multi-frequency signals exchanging through the telecommunication networks. Extracting the frequencies embedded in these signals is very useful for a lot of operations: like filtering, decoding, compressing….We propose in this paper adaptive technique to process in real time multi-frequency signals and extracting the frequencies that they contain. Keywords: DTMF, CLIP, Noise, Adaptive, Real Tim

Patterns of Attachment to Spouse in Battered Women: A Comparative Study between Jordanian and Algerian Women

The current study aimed at detecting the level and type of attachment in battered women. The study sample consisted of (290) women divided into two sections (207) Jordanian women and (173) Algerian women. To answer the questions of the study; the arithmetical averages, standard deviations, t-tests for groups, and tests for the two independent groups were used. The results of the study showed that the dominant attachment pattern among battered women was the avoidance pattern followed by the safe mode and the anxiety pattern.  Results also showed that there are significant differences between Jordanians and Algerian women in the pattern of attachment to the benefit of Jordanians. There were no statistically significant differences in the safe pattern between Algerian and Jordanian women. There were no statistically significant differences in the anxiety pattern between Algerian and Jordanian women. Keywords: Attachment patterns, Spouse, Battered women

Conductance of Water-sorbed Activated Carbon: Differentiation of Flow Direction

The conductance of a piece of activated carbon immersed in water has been measured at several different temperatures. The upward and downward flow Qf water as well as the flow in the horizontal direction in the same piece was made possible by using various arrangements of the apparatus. The rate of increase in the conductance has been interpreted as the rate of flow of water into the pores of activated carbon

Effectiveness and suitability of vapor heat treatment in disinfestation of export mango fruit, cultivar Abu Samaka, from fruit flies

&nbsp;&nbsp;&nbsp; Sudan has a great potential for the export of mango (Mangifera Indica L.) but fruit flies, mainly Bactrocera dorsalis (Hendel), Ceratitis cosyra (Walker), C. capitata (Wiedmann) and B. zonata (Saunders) are threatening the export industry. The countries importing mango require disinfestation treatment against fruit flies as a quarantine regulation. Effectiveness and suitability of vapor heat treatment (VHT) for disinfestation of the Sudanase mango cultivar Abu Samaka were undertaken in this study. In the VHT, the relative humidity of the treatment chamber was maintained at 99.7% and the temperature of the fruit pulp was raised gradually to reach 46.7°C in 5 hours then kept at this degree for 30 minutes before hydro-cooling for 20 minutes. For evaluation of the effectiveness of the treatment, naturally and artificially infested fruits were examined for fruit flies after treatment and compared with their respective untreated samples. To assess suitability of the treatment with respect to quality of the mango fruit, respiration rate, peel color, weight loss, flesh firmness, ascorbic acid content, total soluble solids, titratable acidity and reducing sugars were measured in the treated and control fruits.&nbsp; The VHT was found effective in disinfestation of the mango cultivar Abu Samka from fruit flies and did not adversely affect the fruit market quality and increased the shelf life

Study of electric field an magnetic field affected biological cells

This paper presents the elaboration on effect of electric field and magnetic field to biological cells. Electroporation has become important parameter in treatment cancer or tumour cells. By using electric field or magnetic field, membrane cell will undergo process electroporation where membrane cell structures being altered for induce apoptosis process

Genetic diversity of Ardi goat based on microsatellite analysis

The aim of this study was to analyze the genetic variability of Ardi goats found in the central regions of the kingdom of Saudi Arabia using 14 microsatellite markers. Allelic richness was considerably high in this population indicating high genetic polymorphism as expected heterozygozity was 0.675. Furthermore, the population showed deviation from Hardy-Weinberg equilibrium in seven loci. Mean polymorphic information content value was found to be 0.553. Inbreeding coefficient was 0.183 suggesting moderate level of inbreeding. There was also no-significant heterozygote excess on basis of different models of infinite allele. These tests along with the mode-shift test of Ardi goat indicated no bottleneck recently. Thus, it can be recommended that the Ardi genetic variability should be maintained for its unique genetic resources, and there is a scope for further improvement in productivity through an appropriate management and breeding program. In general, results of this study can be used to establish a base of national conservation strategy of Ardi goat population in Saudi Arabia.Key words: Ardi goat, genetic diversity, microsatellite markers, inbreeding, bottleneck

Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation

Herbage mass yield and composition estimation is an important tool for dairy farmers to ensure an adequate supply of high quality herbage for grazing and subsequently milk production. By accurately estimating herbage mass and composition, targeted nitrogen fertiliser application strategies can be deployed to improve localised regions in a herbage field, effectively reducing the negative impacts of over-fertilization on biodiversity and the environment. In this context, deep learning algorithms offer a tempting alternative to the usual means of sward composition estimation, which involves the destructive process of cutting a sample from the herbage field and sorting by hand all plant species in the herbage. The process is labour intensive and time consuming and so not utilised by farmers. Deep learning has been successfully applied in this context on images collected by high-resolution cameras on the ground. Moving the deep learning solution to drone imaging, however, has the potential to further improve the herbage mass yield and composition estimation task by extending the ground-level estimation to the large surfaces occupied by fields/paddocks. Drone images come at the cost of lower resolution views of the fields taken from a high altitude and requires further herbage ground-truth collection from the large surfaces covered by drone images. This paper proposes to transfer knowledge learned on ground-level images to raw drone images in an unsupervised manner. To do so, we use unpaired image style translation to enhance the resolution of drone images by a factor of eight and modify them to appear closer to their ground-level counterparts. We then ... ~\url{www.github.com/PaulAlbert31/Clover_SSL}.Comment: 11 pages, 5 figures. Accepted at the Agriculture-Vision CVPR 2022 Worksho

Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation

Sward species composition estimation is a tedious one. Herbage must be collected in the field, manually separated into components, dried and weighed to estimate species composition. Deep learning approaches using neural networks have been used in previous work to propose faster and more cost efficient alternatives to this process by estimating the biomass information from a picture of an area of pasture alone. Deep learning approaches have, however, struggled to generalize to distant geographical locations and necessitated further data collection to retrain and perform optimally in different climates. In this work, we enhance the deep learning solution by reducing the need for ground-truthed (GT) images when training the neural network. We demonstrate how unsupervised contrastive learning can be used in the sward composition prediction problem and compare with the state-of-the-art on the publicly available GrassClover dataset collected in Denmark as well as a more recent dataset from Ireland where we tackle herbage mass and height estimation.Comment: 3 pages. Accepted at the 29th EGF General Meeting 202

Diagnostic value of Anti-CCP antibodies compared with Rheumatoid factor in Rheumatoid arthritis patients.

Citrullinated proteins have been discovered in the joints of patients with rheumatoid arthritis but not in other forms of joint disease. The citrullinated proteins in the joints correspond to the presence of the citrulline antibodies in the blood and suggest a possible role for these antibodies in the development of rheumatoid arthritis. The present study assessed the recent diagnostic value of anti-cyclic citrullinated antibodies (CCP) compared with rheumatoid factor (RF) in patients with rheumatoid arthritis. One hundred blood samples were collected from RA patients and thirty from apparently healthy group. Sera from each subject were tested for anti- CCP and RF by enzyme linked immunosorbent assay (ELISA). The majority of patients were females (84%), with a female: male ratio 5.2:1. The results indicated that anti-CCP postivity for RA patients was (69%) when compared with the healthy group (0.0%), which was highly significant in RA in comparison with control groups (P<0.001). The current study revealed that the sensitivity and specificity of Anti-CCP appeared the highest (69%) in comparison with low (47%) sensitivity for RF. Moreover, the specificity of Anti-CCP was very high (100%), while the specificity of RF was high (90%)