Preparation and characterisation of irradiated waste eggshells as oil adsorbent

Adsorption method had been developed by using natural organic adsorbent for the removal of oil because of its ability to bind the oil molecules into the surface of adsorbent. In this study, chicken eggshells waste was used and it undergoes irradiation process with four different amount of dose which was 0.5 kGy, 1.0 kGy, 1.5 kGy, and 2.0 kGy by using Gamma Cell Irradiator. Three equipment had been used for the characterization process which were the Scanning Electron Microscope (SEM), Energy Dispersive X-ray spectroscopy (EDX), and Fourier-Transform Infrared Spectroscopy (FTIR). The adsorption experiment was conducted to calculate the sorption efficiency by using different mass of samples. The result showed that irradiated chicken eggshells powder with 2.0 kGy amount of radiation dose has a best performance as oil adsorbent

Anatomy-Aware Measurement of Segmentation Accuracy

Quantifying the accuracy of segmentation and manual delineation of organs, tissue types and tumors in medical images is a necessary measurement that suffers from multiple problems. One major shortcoming of all accuracy measures is that they neglect the anatomical significance or relevance of different zones within a given segment. Hence, existing accuracy metrics measure the overlap of a given segment with a ground-truth without any anatomical discrimination inside the segment. For instance, if we understand the rectal wall or urethral sphincter as anatomical zones, then current accuracy measures ignore their significance when they are applied to assess the quality of the prostate gland segments. In this paper, we propose an anatomy-aware measurement scheme for segmentation accuracy of medical images. The idea is to create a ``master gold'' based on a consensus shape containing not just the outline of the segment but also the outlines of the internal zones if existent or relevant. To apply this new approach to accuracy measurement, we introduce the anatomy-aware extensions of both Dice coefficient and Jaccard index and investigate their effect using 500 synthetic prostate ultrasound images with 20 different segments for each image. We show that through anatomy-sensitive calculation of segmentation accuracy, namely by considering relevant anatomical zones, not only the measurement of individual users can change but also the ranking of users' segmentation skills may require reordering.Comment: To appear in SPIE Medical Imaging 201

Self-Configuring and Evolving Fuzzy Image Thresholding

Every segmentation algorithm has parameters that need to be adjusted in order to achieve good results. Evolving fuzzy systems for adjustment of segmentation parameters have been proposed recently (Evolving fuzzy image segmentation -- EFIS [1]. However, similar to any other algorithm, EFIS too suffers from a few limitations when used in practice. As a major drawback, EFIS depends on detection of the object of interest for feature calculation, a task that is highly application-dependent. In this paper, a new version of EFIS is proposed to overcome these limitations. The new EFIS, called self-configuring EFIS (SC-EFIS), uses available training data to auto-configure the parameters that are fixed in EFIS. As well, the proposed SC-EFIS relies on a feature selection process that does not require the detection of a region of interest (ROI).Comment: To appear in proceedings of The 14th International Conference on Machine Learning and Applications (IEEE ICMLA 2015), Miami, Florida, USA, 201

The social impact and cultural issues affecting the e-learning performance in Libyan Higher Education institutes

This paper analyses the social impact and cultural issues which affect the e-learning performance in Libyan Higher Education institutes (HEIs). It is described the development and implementation of e-learning systems in various HEIs with the emphasis on the digital gap in Libya and barriers to successful e-learning implementation in these institutions. Also the social impact of using e-learning packages and Internet by young people in Libya is studied and a SWOT analysis of ICT and e-learning in Tripoli University is performed in order to improve the effectiveness of the use of e-learning systems in Libyan HEIs

A hybrid GA–PS–SQP method to solve power system valve-point economic dispatch problems

This study presents a new approach based on a hybrid algorithm consisting of Genetic Algorithm (GA), Pattern Search (PS) and Sequential Quadratic Programming (SQP) techniques to solve the well-known power system Economic dispatch problem (ED). GA is the main optimizer of the algorithm, whereas PS and SQP are used to fine tune the results of GA to increase confidence in the solution. For illustrative purposes, the algorithm has been applied to various test systems to assess its effectiveness. Furthermore, convergence characteristics and robustness of the proposed method have been explored through comparison with results reported in literature. The outcome is very encouraging and suggests that the hybrid GA–PS–SQP algorithm is very efficient in solving power system economic dispatch problem

Agile-SD: A Linux-based TCP Congestion Control Algorithm for Supporting High-speed and Short-distance Networks

Recently, high-speed and short-distance networks are widely deployed and their necessity is rapidly increasing everyday. This type of networks is used in several network applications; such as Local Area Networks (LAN) and Data Center Networks (DCN). In LANs and DCNs, high-speed and short-distance networks are commonly deployed to connect between computing and storage elements in order to provide rapid services. Indeed, the overall performance of such networks is significantly influenced by the Congestion Control Algorithm (CCA) which suffers from the problem of bandwidth under-utilization, especially if the applied buffer regime is very small. In this paper, a novel loss-based CCA tailored for high-speed and Short-Distance (SD) networks, namely Agile-SD, has been proposed. The main contribution of the proposed CCA is to implement the mechanism of agility factor. Further, intensive simulation experiments have been carried out to evaluate the performance of Agile-SD compared to Compound and Cubic which are the default CCAs of the most commonly used operating systems. The results of the simulation experiments show that the proposed CCA outperforms the compared CCAs in terms of average throughput, loss ratio and fairness, especially when a small buffer is applied. Moreover, Agile-SD shows lower sensitivity to the buffer size change and packet error rate variation which increases its efficiency.Comment: 12 Page

Kita tutup aurat! : aplikasi pembelajaran menutup aurat untuk kanak-kanak

Menutup aurat adalah salah satu kewajipan dalam agama Islam. Oleh itu, pemahaman konsep menutup aurat adalah asas yang perlu dipelajari pada usia muda. Namun begitu, kanak-kanak hanya belajar menutup aurat mengikut konsep teori pembelajaran sahaja di sekolah. Kanak-kanak sukar mengikuti dan memahami pembelajaran yang menggunakan konsep teks dan fakta. Justeru itu, aplikasi pembelajaran yang berkonsepkan pembelajaran mudah alih (m-pembelajaran) yang dinamakan “Kita Tutup Aurat!” mengenai aurat untuk kanak-kanak ini dibangunkan. Aplikasi ini dibangunkan dengan menggunakan model ADDIE kerana kesesuaiannya dalam pembangunan aplikasi pembelajaran. Pengujian aplikasi telah dijalankan oleh 30 responden dari kalangan kanak-kanak sekolah rendah sekitar Parit Raja serta beberapa orang guru. Hasil pengujian menunjukkan lebih 70% responden bersetuju aplikasi yang dibangunkan merupakan satu pendekatan menarik dalam mempelajari dan memahami konsep menutup aurat dalam Islam. Kesimpulannya, aplikasi telah berjaya mencapai objektif yang telah ditentukan kerana ia menepati kehendak pengguna dan mempunyai fungsi-fungsi yang terkandung dalam skop sistem. Secara keseluruhan, implementasi aplikasi pembelajaran ini berpotensi untuk dijadikan kaedah alternatif dalam memahami konsep aurat sekaligus mendidik kanak-kanak untuk menutup aurat dengan sempurna

Graphene-Dielectric Composite Metamaterials: Evolution from Elliptic to Hyperbolic Wavevector Dispersion and The Transverse Epsilon-Near-Zero Condition

We investigated a multilayer graphene-dielectric composite material, comprising graphene sheets separated by subwavelength-thick dielectric spacer, and found it to exhibit hyperbolic isofrequency wavevector dispersion at far- and mid-infrared frequencies allowing propagation of waves that would be otherwise evanescent in a dielectric. Electrostatic biasing was considered for tunable and controllable transition from hyperbolic to elliptic dispersion. We explored the validity and limitation of the effective medium approximation (EMA) for modeling wave propagation and cutoff of the propagating spatial spectrum due to the Brillouin zone edge. We found that EMA is capable of predicting the transition of the isofrequency dispersion diagram under certain conditions. The graphene-based composite material allows propagation of backward waves under the hyperbolic dispersion regime and of forward waves under the elliptic regime. Transition from hyperbolic to elliptic dispersion regimes is governed by the transverse epsilon-near-zero (TENZ) condition, which implies a flatter and wider propagating spectrum with higher attenuation, when compared to the hyperbolic regime. We also investigate the tunable transparency of the multilayer at that condition in contrast to other materials exhibiting ENZ phenomena.Comment: to be published in Journal of Nanophotonic

Providing Dynamic TXOP for QoS Support of Video Transmission in IEEE 802.11e WLANs

The IEEE 802.11e standard introduced by IEEE 802.11 Task Group E (TGe) enhances the Quality of Service (QoS) by means of HCF Controlled Channel Access (HCCA). The scheduler of HCCA allocates Transmission Opportunities (TXOPs) to QoS-enabled Station (QSTA) based on their TS Specifications (TSPECs) negotiated at the traffic setup time so that it is only efficient for Constant Bit Rate (CBR) applications. However, Variable Bit Rate (VBR) traffics are not efficiently supported as they exhibit nondeterministic profile during the time. In this paper, we present a dynamic TXOP assignment Scheduling Algorithm for supporting the video traffics transmission over IEEE 802.11e wireless networks. This algorithm uses a piggybacked information about the size of the subsequent video frames of the uplink traffic to assist the Hybrid Coordinator accurately assign the TXOP according to the fast changes in the VBR profile. The proposed scheduling algorithm has been evaluated using simulation with different variability level video streams. The simulation results show that the proposed algorithm reduces the delay experienced by VBR traffic streams comparable to HCCA scheduler due to the accurate assignment of the TXOP which preserve the channel time for transmission.Comment: arXiv admin note: substantial text overlap with arXiv:1602.0369