CancerLinker: Explorations of Cancer Study Network

Interactive visualization tools are highly desirable to biologist and cancer researchers to explore the complex structures, detect patterns and find out the relationships among bio-molecules responsible for a cancer type. A pathway contains various bio-molecules in different layers of the cell which is responsible for specific cancer type. Researchers are highly interested in understanding the relationships among the proteins of different pathways and furthermore want to know how those proteins are interacting in different pathways for various cancer types. Biologists find it useful to merge the data of different cancer studies in a single network and see the relationships among the different proteins which can help them detect the common proteins in cancer studies and hence reveal the pattern of interactions of those proteins. We introduce the CancerLinker, a visual analytic tool that helps researchers explore cancer study interaction network. Twenty-six cancer studies are merged to explore pathway data and bio-molecules relationships that can provide the answers to some significant questions which are helpful in cancer research. The CancerLinker also helps biologists explore the critical mutated proteins in multiple cancer studies. A bubble graph is constructed to visualize common protein based on its frequency and biological assemblies. Parallel coordinates highlight patterns of patient profiles (obtained from cBioportal by WebAPI services) on different attributes for a specified cancer studyComment: 7 pages, 9 figure

Room temperature multi gas detection using carbon nanotubes

Gas detection and monitoring are important aspect since it creates an immediate and long term health risk to personnel involved, whether it is in industrial, medical or commercial applications. Conventional metal oxide gas sensors lack flexibility with poor response times and are operated at elevated temperature (200-500°C), which implies that power is required. Nanomaterials offer tremendous opportunities for improved sensor devices due to their smaller size, low power consumption, higher performance, and cheaper than conventional sensors. Carbon nanotubes possess very unique characteristics due to their hollow center, nanometer size and large surface area, and are able to change their electrical resistance drastically when exposed to alkalis, halogens and other gases at room temperature. Hence, carbon nanotubes have the potential to be a better chemical sensor. This study is carried out to investigate the potential application of carbon nanotubes as a gas sensor by measuring the change of electrical resistance of the carbon nanotubes upon gas absorption. The gases used in this study were carbon dioxide (CO2), acetylene (C2H2), ammonia (NH3), natural gas (95% methane, CH4) and hydrogen (H2). Gas sensing properties of carbon nanotube was study; the presence of gas is detected by changing of its electrical resistivity

SOME TRIGONOMETRIC SIMILARITY MEASURES OF COMPLEX FUZZY SETS WITH APPLICATION

Similarity measures of fuzzy sets are applied to compare the closeness among fuzzy sets. These measures have numerous applications in pattern recognition, image processing, texture synthesis, medical diagnosis, etc. However, in many cases of pattern recognition, digital image processing, signal processing, and so forth, the similarity measures of the fuzzy sets are not appropriate due to the presence of dual information of an object, such as amplitude term and phase term. In these cases, similarity measures of complex fuzzy sets are the most suitable for measuring proximity between objects with two-dimensional information. In the present paper, we propose some trigonometric similarity measures of the complex fuzzy sets involving similarity measures based on the sine, tangent, cosine, and cotangent functions. Furthermore, in many situations in real life, the weight of an attribute plays an important role in making the right decisions using similarity measures. So in this paper, we also consider the weighted trigonometric similarity measures of the complex fuzzy sets, namely, the weighted similarity measures based on the sine, tangent, cosine, and cotangent functions. Some properties of the similarity measures and the weighted similarity measures are discussed. We also apply our proposed methods to the pattern recognition problem and compare them with existing methods to show the validity and effectiveness of our proposed methods

Social media analytics with applications in disaster management and COVID-19 events

Social media such as Twitter offers a tremendous amount of data throughout an event or a disastrous situation. Leveraging social media data during a disaster is beneficial for effective and efficient disaster management. Information extraction, trend identification, and determining public reactions might help in the future disaster or even avert such an event. However, during a disaster situation, a robust system is required that can be deployed faster and process relevant information with satisfactory performance in real-time. This work outlines the research contributions toward developing such an effective system for disaster management, where it is paramount to develop automated machine-enabled methods that can provide appropriate tags or labels for further analysis for timely situation-awareness. In that direction, this work proposes machine learning models to identify the people who are seeking assistance using social media during a disaster and further demonstrates a prototype application that can collect and process Twitter data in real-time, identify the stranded people, and create rescue scheduling. In addition, to understand the people’s reactions to different trending topics, this work proposes a unique auxiliary feature-based deep learning model with adversarial sample generation for emotion detection using tweets related to COVID-19. This work also presents a custom Q&A-based RoBERTa model for extracting related phrases for emotions. Finally, with the aim of polarization detection, this research work proposes a deep learning pipeline for political ideology detection leveraging the tweet texts and the expressed emotions in the text. This work also studies and conducts the historical emotion and polarization analysis of the COVID-19 pandemic in the USA and several individual states using tweeter data --Abstract, page iv

UPM sertai persidangan ASAIHL 2017 di Universitas Hasanuddin, Makassar

MAKASSAR, 17 Mei - Universiti Putra Malaysia (UPM) menyertai persidangan The Association of Southeast Asian Institutions of Higher Learning (ASAIHL) tahun 2017 mulai 16 hingga 19 Mei lalu di Universitas Hasanuddin, Makassar, Indonesia

Penggunaan Komputer Di Kalangan Guru-Guru Sekolah Menengah Di Daerah Seremban, Negeri Sembilan

Pendidikan masa kini mengalami perubahan yang mendadak dan berubah ke arah pembentukanmasyarakat bermaklumat selaras dengan visi negara untuk menjadi tunggak dalam perkembanganteknologi maklumat. Sehubungan itu, guru memainkan peranan yang penting untuk merealisasikan visitesebut. Objektif kajian ini adalah untuk mengenal pasti tahap penggunaan komputer di kalangan guruguru,mengenal pasti sejauh mana guru menggunakan kemudahan komputer dalam proses pengajaran danpembelajaran dan mengenal pasti masalah penggunaan komputer. Sampel kajian terdiri daripada 98 orangguru yang dipilih secara rawak dari empat buah sekolah menengah di Negeri Sembilan. Data diperolehimelalui borang soal selidik dan dianalisis dengan menggunakan perisian SPSS ( Statistical Package ForSocial Sciences ) versi 11.0. Dapatan kajian menunjukkan tahap penggunaan komputer responden masihrendah berpunca daripada kekurangan kemudahan komputer dan pengetahuan tentang komputer. Kajianjuga mendapati bahawa kekangan utama penggunaan komputer dalam proses pengajaran danpembelajaran adalah komputer sekolah sering diserang virus, bilangan komputer adalah tidak mencukupidi sekolah, komputer dan mesin cetak di sekolah selalu rosak, sekolah kurang menganjurkan kursusdalaman berkaitan computer dan tiadanya kemudahan LCD di dalam kelas. Oleh itu dicadangkan pihakKementerian Pelajaran Malaysia lebih proaktif dalam membekalkan komputer di sekolah danmendedahkan guru yang sedang berkhidmat dengan latihan berasaskan komputer untuk menanganicabaran era siber pendidikan di Sekolah Bestari nanti

Effects of radiation and plant population on growth and yield attributes of wheat

Radiation plays a crucial role for growth and yield of wheat. A field experiment was conducted at the Field Laboratory of Agrotechnology Discipline of Khulna University in Bangladesh during November 2018 to March 2019 to study the effect of radiation levels and plant population on growth and yield attributes of wheat. The study was set out in the randomized complete block design with four radiation levels (full sunlight, 75% light, 55% light, 25% light) and three plant population densities (160 plant/m2, 200 plant/m2, 230 plant/m2) that replicated thrice. Growth and yield attributes of wheat were generally similar between two light levels (full sunlight, 75% light) and two plant densities (200 plant/m2, 230 plant/m2). However, the attributes were usually minimum at 25% light. The interaction effect of full sunlight or 75% light with optimal (200 plant/m2) or maximal (230 plant/m2) plant densities produced statistically similar plant height, leaf number, tiller number, total dry matter, grain yield, straw yield, and biological yield. Therefore, combination of 75% light with 230 plant/m2 is suggested for growing wheat in light limited areas and in agroforestry system with acceptable yield

Initial experience in implementation of open entry and recognition of prior learning in OUM

Malaysia is one of the first developing nations to introduce the Open Entry and Recognition of Prior Learning (RPL) in its education system. Open University Malaysia (OUM) has taken the challenge to provide lifelong learning opportunities and greater access to education through this mode. Traditionally, the entry to higher learning was limited and based on academic qualification criteria. However, with the new mode of entry, experiential learning is acknowledged and accepted as the qualifying requirement. This paper reports on the importance of Open Entry and RPL in enhancing knowledge society and an initial experience of implementing these initiatives in OUM. It also looks into the processes and procedures applied for executing the national agenda. The analysis here will be useful to establish guidelines for effective implementation of open entry and recognition of prior learning in countries, which have common context as in Malaysia

Identification and characterization of the lactic acid bacteria isolated from Malaysian fermented fish (Pekasam)

Recently researchers are interested with the biotherapeutic potential of probiotics in gut disease treatment. The bacteria are generally regarded as a safe, have a stability of usage and originate from the natural resources. The study aims to identify and characterize the potential probiotic Lactic Acid Bacteria (LAB) isolated from Malaysian fermented fish product known as Pekasam. Fourty isolates obtained were firstly screened for their antagonism activities against the common pathogenic bacteria; Esherichia coli, Staphylococcus aureus and Klebsiella sp. Our study revealed only three (labeled as L8, L20 and S1) of the isolates tested showed broad antimicrobial effects towards the pathogenic bacteria. All of the isolates were also γ-hemolytic and tolerant to various pH (pH 3, 5 and 7.5) and 0.3% (w/v) bile salts. The bacteria isolates of strain L8 and L20 were susceptible to seven antibiotics tested except vancomycin and tetracycline whereas S1 was resistant to all antibiotics. Phenotypic tests revealed that both bacteria isolates of strain L8 and L20 were Bacillus megaterium while S1 was Pediococcus pentosaceus whereas 16S rRNA gene sequence analysis showed potential bacteria isolates of strain L8 and L20 belonged to the Lactobacillus plantarum (99% similarity) and S1 was characterized as Lactobacillus pentosus (100% similarity) respectively. Our present study showed that the probiotics of strain L8, L20 and S1 isolated from the fermented fish (Pekasam) exhibited the potential probiotic properties to be developed as biotherapeutic agents