PRACB: A Novel Channel Bonding Algorithm for Cognitive Radio Sensor Networks

Wireless sensor networks (WSNs) can utilize the unlicensed industrial, scientific and medical (ISM) band to communicate the sensed data. The ISM band has been already saturated due to overlaid deployment of WSNs. To solve this problem, WSNs have been powered up by cognitive radio (CR) capability. By using CR technique, WSNs can utilize the spectrum holes opportunistically. Channel bonding (CB) is a technique through which multiple contiguous channels can be combined to form a single wide band channel. By using channel bonding (CB) technique, CR based WSN nodes attempt to find and combine contiguous channels to avail larger bandwidth. In this paper, we show that probability of finding contiguous channels decreases with the increase in number of channels. Moreover, we propose two algorithms of primary radio (PR) activity based channel bonding schemes and compare with sample width algorithm (SWA). The simulation results show that our algorithm significantly avoids PR-CR harmful interference and CB in cognitive radio sensor networks (CRSNs) provides greater bandwidth to CR nodes

NS-2 based simulation framework for cognitive radio sensor networks

In this paper, we propose a simulation model for cognitive radio sensor networks (CRSNs) which is an attempt to combine the useful properties of wireless sensor networks and cognitive radio networks. The existing simulation models for cognitive radios cannot be extended for this purpose as they do not consider the strict energy constraint in wireless sensor networks. Our proposed model considers the limited energy available for wireless sensor nodes that constrain the spectrum sensing process—an unavoidable operation in cognitive radios. Our model has been thoroughly tested by performing experiments in different scenarios of CRSNs. The results generated by the model have been found accurate which can be considered for realization of CRSNs

APLIKASI BELAJAR BERBASIS DIGITAL DAPAT MENINGKATKAN MOTIVASI BELAJAR MAHASISWA

keyword: digital applications, smartphones, motivation The purpose of this study is to measure how the role of digital based learning applications through smartphone facilities can influence learning motivation among students. The method used in this study was to use quantitative descriptive analysis involving 90 (ninety) students using random sampling techniques. This method of collecting data through a questionnaire method supported by the documentation method. Linear regression analysis is a technique used in analyzing this data. Based on the results of this study concluded: (1) There is a significant influence between digital-based learning applications on student learning motivation (2) There is a significant influence between smartphones on student learning motivation (3) There is a significant influence between digital based learning applications and smartphone against student learning motivation. Simultaneously with the presence of digital-based learning applications and through smartphone means can increase student learning motivatio

PREDIKSI POTENSI KEBANGKRUTAN PADA PERUSAHAAN PROPERTI DAN REAL ESTATE YANG TERDAFTAR DI BURSA EFEK INDONESIA PERIODE 2012-2019

Penelitian ini memiliki tujuan untuk (1) memprediksi potensi kebangkrutan terhadap perusahaan properti dan real estate di BEI dengan menggunakan dua model prediksi yaitu model Altman modifikasi Z-score dan model Springate, (2) mengukur tingkat keakuratan pada model prediksi dalam memprediksi potensi kebangkrutan, (3) mengetahui model mana yang memiliki tingkat akurasi paling tinggi. Penelitian ini menggunakan metode analisis data dengan model Altman modifikasi Z-score dan model Springate yang digunakan sebagai alat prediksi potensi kebangkrutan dan uji normalitas sebagai syarat untuk melakukan uji paired sample t test serta uji tingkat akurasi model prediksi kebangkrutan yang digunakan untuk menguji tingkat keakuratan setiap model prediksi. Penelitian ini menggunakan data berdasarkan laporan keuangan milik perusahaan yang diambil dari website masing-masing perusahaan dan melalui idnfinancials.com. Hasil akhir penelitian ini membuktikan bahwa terdapat perbedaan hasil pada model prediksi Altman modifikasi Z-score dengan model Springate dalam memprediksi potensi kebangkrutan dan berdasarkan uji tingkat akurasi, model Altman modifikasi Z-score memiliki tingkat akurasi yang paling tinggi dengan nilai 84,17%, sedangkan model Springate memiliki tingkat keakuratan sebesar 80%. Kata kunci: altman modifikasi z-score, laporan keuangan, model prediksi kebangkrutan, prediksi potensi kebangkrutan, springat

Interface modification of clay and graphene platelets reinforced epoxy nanocomposites: a comparative study

The interface between the matrix phase and dispersed phase of a composite plays a critical role in influencing its properties. However, the intricate mecha-nisms of interface are not fully understood, and polymer nanocomposites are no exception. This study compares the fabrication, morphology, and mechanical and thermal properties of epoxy nanocomposites tuned by clay layers (denoted as m-clay) and graphene platelets (denoted as m-GP). It was found that a chemical modification, layer expansion and dispersion of filler within the epoxy matrix resulted in an improved interface between the filler mate-rial and epoxy matrix. This was confirmed by Fourier transform infrared spectroscopy and transmission electron microscope. The enhanced interface led to improved mechanical properties (i.e. stiffness modulus, fracture toughness) and higher glass transition temperatures (Tg) compared with neat epoxy. At 4 wt% m-GP, the critical strain energy release rate G1c of neat epoxy improved by 240 % from 179.1 to 608.6 J/m2 and Tg increased from 93.7 to 106.4 �C. In contrast to m-clay, which at 4 wt%, only improved the G1c by 45 % and Tg by 7.1 %. The higher level of improvement offered by m-GP is attributed to the strong interaction of graphene sheets with epoxy because the covalent bonds between the carbon atoms of graphene sheets are much stronger than silicon-based clay

Remaining idle time aware intelligent channel bonding schemes for cognitive radio sensor networks

Channel bonding (CB) is a technique used to provide larger bandwidth to users. It has been applied to various networks such as wireless local area networks, wireless sensor networks, cognitive radio networks, and cognitive radio sensor networks (CRSNs). The implementation of CB in CRSNs needs special attention as primary radio (PR) nodes traffic must be protected from any harmful interference by cognitive radio (CR) sensor nodes. On the other hand, CR sensor nodes need to communicate without interruption to meet their data rate requirements and conserve energy. If CR nodes perform frequent channel switching due to PR traffic then it will be difficult to meet their quality of service and data rate requirements. So, CR nodes need to select those channels which are stable. By stable, we mean those channels which having less PR activity or long remaining idle time and cause less harmful interference to PR nodes. In this paper, we propose two approaches remaining idle time aware intelligent channel bonding (RITCB) and remaining idle time aware intelligent channel bonding with interference prevention (RITCB-IP) for cognitive radio sensor networks which select stable channels for CB which have longest remaining idle time. We compare our approaches with four schemes such as primary radio user activity aware channel bonding scheme, sample width algorithm, cognitive radio network over white spaces and AGILE. Simulation results show that our proposed approaches RITCB and RITCB-IP decrease harmful interference and increases the life time of cognitive radio sensor nodes

Relapse patterns in NMOSD: evidence for earlier occurrence of optic neuritis and possible seasonal variation

Neuromyelitis optica spectrum disorders (NMOSD) and multiple sclerosis (MS) show overlap in their clinical features. We performed an analysis of relapses with the aim of determining differences between the two conditions. Cases of NMOSD and age- and sex-matched MS controls were collected from across Australia and New Zealand. Demographic and clinical information, including relapse histories, were recorded using a standard questionnaire. There were 75 cases of NMOSD and 101 MS controls. There were 328 relapses in the NMOSD cases and 375 in MS controls. Spinal cord and optic neuritis attacks were the most common relapses in both NMOSD and MS. Optic neuritis (p P = 0.002) were more common in NMOSD and other brainstem attacks were more common in MS (p P = 0.065). Optic neuritis and transverse myelitis are the most common types of relapse in NMOSD and MS. Optic neuritis tends to occur more frequently in NMOSD prior to the age of 30, with transverse myelitis being more common thereafter. Relapses in NMOSD were more severe. A seasonal bias for relapses in spring-summer may exist in NMOSD

JHDM1B/FBXL10 is a nucleolar protein that represses transcription of ribosomal RNA genes

JHDM1B is an evolutionarily conserved and ubiquitously expressed member of the JHDM (JmjC-domain-containing his- tone demethylase) family1\u20133. Because it contains an F-box motif, this protein is also known as FBXL10 (ref. 4). With the use of a genome-wide RNAi screen, the JHDM1B worm orthologue (T26A5.5) was identified as a gene that regulates growth5. In the mouse, four independent screens have identified JHDM1B as a putative tumour suppressor by retroviral insertion analysis6\u20139. Here we identify human JHDM1B as a nucleolar protein and show that JHDM1B preferentially binds the transcribed region of ribosomal DNA to repress the transcription of ribosomal RNA genes. We also show that repression of ribosomal RNA genes by JHDM1B is dependent on its JmjC domain, which is necessary for the specific demethylation of trimethylated lysine 4 on histone H3 in the nucleolus. In agreement with the notion that ribosomal RNA synthesis and cell growth are coupled processes, we show a JmjC-domain-dependent negative effect of JHDM1B on cell size and cell proliferation. Because aberrant ribosome biogenesis and the disruption of epigenetic control mechanisms contribute to cellular transformation, these results, together with the low levels of JHDM1B expression found in aggressive brain tumours, suggest a role for JHDM1B in cancer development

Suppression of PGE2 production via disruption of MAPK phosphorylation by unsymmetrical dicarbonyl curcumin derivatives

Curcumin is an important molecule found in turmeric plants and has been reported to exhibit some profound anti-inflammatory activities by interacting with several important molecular targets found in the mitogen-activated protein kinase and NF-κβ pathways. As part of our continuing effort to search for new anti-inflammatory agents with better in vitro and in vivo efficacies, we have synthesized a series of new unsymmetrical dicarbonyl curcumin derivatives and tested their effects on prostaglandin E2 secretion level in interferon-γ/lipopolysaccharide-activated macrophage cells. Among those, five compounds exhibited remarkable suppression on prostaglandin E2 production with IC50 values ranging from 0.87 to 18.41 µM. The most potent compound 17f was found to down-regulate the expression of cyclooxygenase-2 mRNA suggesting that this series of compounds could possibly target the mitogen-activated protein kinase signal transduction pathway. Whilst the compound did not affect the expression of the conventional mitogen-activated protein kinases, the results suggest that it could disrupt the phosphorylation and activation of the proteins particularly the c-Jun N-terminal kinases. Finally, the binding interactions were examined using the molecular docking and dynamics simulation approaches