Meat mills in Indonesia are not halal certified. Small traders who do not have a food processor facility will choose the public market. This can be done both by traders who sell halal processed food and processed pork. It is necessary to study the content of meat mills in the public market so that it becomes critical evidence of an institution authorized to issue a policy immediately. This study aims to examine the content of porcine DNA in meat mills in Pasar Surya Kota Surabaya using the Real Time PCR (qPCR) method. QPCR amplification was performed using a porcine probe primer with annealing temperature optimization of 60oC. The amplification curve shows an increase in the curve in the positive control (EPC) with a value of Cq 34.00, while the negative control (NTC) is not amplified. The results of this study show that 2 out of 10 samples experienced an increase in the amplification curve on the FAM indicator, meaning that in the meat grinding sample there was a content of porcine DNA. The two samples are 8 and 9 with Cq values of 38.02 and 39.04, respectively. Market Halal Certification must be done immediately.

Biotic stress by Odontoglossum ringspot virus (ORSV) infection causes a decrease in the rate of photosynthesis. This study aimed to determine the pattern of plant-virus interactions through analysis of rbcL and coat protein genes. Virus source was collected from Bogor Botanical Garden. Detection of chloroplast and ORSV using Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) and Polymerase Chain Reaction (PCR), respectively. Analyzed change of nucleotide and amino acid sequences using DNASTAR and MEGA Beta programs. Chloroplast DNA and virus RNA amplification managed to get amplicons at ±599 bp and ±474 bp, respectively. Sequence nucleotides analysis showed point mutations with increased synthesis of Ser, Glu, Pro, dan Arg amino acids. This study revealed a change in sequence of nucleotides and amino acids were thought to be adaptations and physiological responses of host-virus to natural environments in Indonesia.

The Internet of Things (IoTs) is an integrated network including physical devices, mobile robots, cameras, sensors, vehicles, etc. There are many items embedded with electronics, software to support a lot of applications in different fields. These internet-based networks have many different types of data to be transmitted and processed. Either reducing data transmission or lowering energy consumption for such networks is critically considered. Compressed sensing (CS) technique is known as a novel idea to compress and to reconstruct correlated data well with a small certain number of CS measurements. This paper proposes an energy-efficient scheme for data routing for IoTs utilizing CS techniques. The ideas show how to apply CS into IoT applications with different kinds of data like images, video streaming and simply as sensor readings. After the CS sampling process, the IoT system only needs to transmit a certain number of CS measurements instead of sending all collected sensing data. At the receiver side, the system can reconstruct perfectly the original data based on the measurements. Different kinds of IoT data is analyzed to be used with CS. Data routing methods are suggested for suitable cases. Simulation results working on different types of multimedia data are provided to clarify the methods. This work also provides an additional way to protect the sensing data for security purposes in the networks.

Researchers cite papers in order to connect the new research ideas with previous research. For the purpose of finding suitable papers to cite, researchers spend a considerable amount of time and effort. To help researchers in finding relevant/important papers, we evaluated textual and topological similarity measures for citation recommendations. This work analyzes textual and topological similarity measures (i.e., Jaccard and Cosine) to evaluate which one performs well in finding similar papers? To find the importance of papers, we compute centrality measures (i.e., Betweeness, Closeness, Degree and PageRank). After evaluation, it is found that topological-based similarity via Cosine achieved 85.2% and using Jaccard obtained 61.9% whereas textualbased similarity via Cosine on abstract obtained 68.9% and using Cosine on title achieved 37.4% citation links. Likewise, textual-based similarity via Jaccard on abstract obtained 35.4% and using Jaccard on title achieved 28.3% citation links.

Climate change poses a critical risk to the sustainable development of many regions in Vietnam, especially in the Mekong River. In this paper, we show the specific extreme value distributions of rainfall, flow, and crest of salinity based on the hydrological data from 1975 to 2017 in An Giang and Ca Mau provinces in the Mekong Delta. We also derive a theoretical model and validate its accuracy compared to the empirical data over the years. The results demonstrate that the extremely high flows increase in both magnitude and frequency, while the extremely low ones are projected to occur less often under the climate change. The results can further help the local governments reduce the risk of lack water in dry season, control the salinization, and avoid the threat of flooding in the downstream of the Mekong Delta.

Wireless sensor networks (WSNs) provide a lot of emerging applications. They suffer from some limitations such as energy constraints and cooperative demands essential to perform sensing or data routing. The networks could be exploited more effectively if they are well managed with power consumption since all sensors are randomly deployed in sensing areas needed to be observed without battery recharge or remote control. In this work, we proposed some stochastic-based methods to calculate total power consumption for such networks. We model common arbitrary networks with different types of sensing areas, circular and square shapes, then analyze and calculate the power consumption for data transmission based on statistic problems. Almost common data collection methods are employed such as cluster-based, tree-based, neighborhood based and random routing. In each method, the total power consumption is formulated and then simulated to be verified. This paper shows promise that all the formulas could be applied not only on WSNs but also mobile sensor networks (MSNs) while the mobile sensors are considered moving at random positions.

This paper evaluates outage probability (OP) of a cooperative underlay cognitive radio network in the presence of a passive secondary eavesdropper under joint impacts of limited interference from a primary network and hardware impairments. With intercept probability constraint required for the eavesdropper and interference constraint given by a primary receiver, we derive closed-form expressions of transmit power for the secondary transmitters, including source and relays, only relying on the knowledge of statistical channel state information (CSI). Then, a relay selection method is used in the cooperative phase to enhance the OP performance of the considered protocol. For performance evaluation, we derive an exact closed-form expression of OP over Rayleigh fading channel. Finally, we perform Monte Carlo simulations to verify the derived formulas.

Promoting greener experience in urban areas is of utmost importance for urban development and for healthier cities. In this demo, we delineate a multi-disciplinary project for mapping the citizen experience and access to green spaces that can be used at a micro level context for promoting healthier actions, put in a macro level context. We sketch an intelligent monitoring system which collects a multitude of information including brain activities, stress levels, oxygen flow, and mobility data in order to make sense of the user experience in urban settings. The design of the system involves a group of experts (the authors) from different disciplines: health sciences, product design, game design, artificial intelligence and medical technology. We will present a mockup of the system at the workshop, a co-design toolbox and scenario, i.e., a visual or textual map of events illustrating a story of the journey of the interaction of a citizen with the system.

In this demo project we explore quantifiable data engendered by emergent geoplay games as a source, to research the use of urban green space impacts on in health and well-being. By the establishing of an emergent geogame built on a GPS dependent interface for smartphones, one facilitates diverse and unanticipated behavior that produce digital data by movements, actions according to the rules, and documentation. The research will involve the exploration of the empirical data produced by play in green urban spaces in accordance to the core concepts of spatial information, fun and well-being.

Historically woman’s’ health during pregnancy is in hands of doctors. Through monthly clinical visits women are informed about their health. But not all woman have the opportunity to on-site clinical visits or/and woman need constantly support in this hard and unknown journey. This lack of support is worldwide rising the maternal-fetal morbidity and mortality. This paper shows a study towards the design of PREGLOG, a mobile application purely thought for pregnant women to help them overcome any situation which could complicate their pregnancy process, including anomaly logs and useful information about the symptoms they could present during their current pregnancy month. We interviewed specialists in charge of maternal control of women, including three gynecologists and a specialist in Family Medicine, and 10 pregnancies in order to understand pregnancy care and pregnancy doubts, fears, and needs. As a result we obtained valuable insights that will help us to design a prototype which fulfills the main needs for both the patients and the specialists who treat them.