Perluasan Hutan Mangrove dalam Mitigasi Risiko Bencana Pemanasan Global: Kegiatan PkM di Kawasan Pesisir Muara Angke Jakarta

One of the disasters caused by humans is global warming. Global warming is a big problem that is being faced by all human beings and living things on earth. One of the activities that can be carried out in mitigating the risk of global warming is through Mangrove Ecosystem Rehabilitation. The existence of the Mangrove ecosystem in the coastal area of ​​DKI Jakarta Province is currently experiencing a decline in line with the development that changes the function of the area from a protected function to a cultivation function. One area that has experienced this is the coastal area in Muara Angke which has had a negative impact on the environment, namely the function of protecting and securing the coast will naturally be lost. In this 2021 Community Service program, STMA Trisakti has participated in helping to solve the problem of the rate of degradation of the Mangrove Forest by planting 1000 mangrove seedlings in the Muara Angke Eco-tourism area. The planting was carried out on World Environment Day on 5 June 2021.

Learn2Write: Augmented Reality and Machine Learning-Based Mobile App to Learn Writing

Augmented reality (AR) has been widely used in education, particularly for child education. This paper presents the design and implementation of a novel mobile app, Learn2Write, using machine learning techniques and augmented reality to teach alphabet writing. The app has two main features: (i) guided learning to teach users how to write the alphabet and (ii) on-screen and AR-based handwriting testing using machine learning. A learner needs to write on the mobile screen in on-screen testing, whereas AR-based testing allows one to evaluate writing on paper or a board in a real world environment. We implement a novel approach to use machine learning for AR-based testing to detect an alphabet written on a board or paper. It detects the handwritten alphabet using our developed machine learning model. After that, a 3D model of that alphabet appears on the screen with its pronunciation/sound. The key benefit of our approach is that it allows the learner to use a handwritten alphabet. As we have used marker-less augmented reality, it does not require a static image as a marker. The app was built with ARCore SDK for Unity. We further evaluated and quantified the performance of our app on multiple devices.

Adapted discriminative coupled mappings for low-resolution face recognition with one-shot

Low-resolution face recognition with one-shot is a prevalent problem encountered in law enforcement, where it generally requires to recognize the low-resolution face images captured by surveillance cameras with the only one high-resolution profile face image in the database. The problem is very tough because the available samples is quite few and the quality of unknown images is quite low. To effectively address this issue, this paper proposes Adapted Discriminative Coupled Mappings (AdaDCM) approach, which integrates domain adaptation and discriminative learning. To achieve good domain adaptation performance for small size dataset, a new domain adaptation technique called Bidirectional Locality Matching-based Domain Adaptation (BLM-DA) is first developed. Then the proposed AdaDCM is formulated by unifying BLM-DA and discriminative coupled mappings into a single framework. AdaDCM is extensively evaluated on FERET, LFW, and SCface databases, which includes LR face images obtained in constrained, unconstrained, and real-world environment. The promising results on these datasets demonstrate the effectiveness of AdaDCM in LR face recognition with one-shot.

Capturing cognitive events embedded in the real-world using mobile EEG and Eye-Tracking

The study of cognitive processes underlying natural behaviours implies to depart from computerized paradigms and artificial experimental probes. The aim of the present study is to assess the feasibility of capturing neural markers of visual attention (P300 Event-Related Potentials) in response to objects embedded in a real-world environment. To this end, electroencephalography and eye-tracking data were recorded while participants attended stimuli presented on a tablet and while they searched for books in a library. Initial analyses of the library data revealed P300-like features shifted in time. A Dynamic Time Warping analysis confirmed the presence of P300 ERP in the library condition. Library data were then lag-corrected based on cross-correlation co-efficients. Together these approaches uncovered P300 ERP responses in the library recordings. These findings high-light the relevance of scalable experimental designs, joint brain and body recordings and template-matching analyses to capture cognitive events during natural behaviours.

Promotion of Purbalingga Tourism Object Using Augmented Reality Location Based Service & Virtual Reality 360° Based on Android

One of the technologies that can be used as an attraction in Purbalingga Regency is Augmented Reality (AR) merging virtual objects with real objects, where those objects can be seen in real-time. And using the Location-Based Service (LBS) method, this method is a service with the main parameters being the position and location of the user. LBS Location Based Service will be enhanced with Google Maps and GPS (Global Positioning System) to find its user position and information about several locations to be visited. Virtual Reality (VR) brings users can interact in a virtual world environment simulated by a computer, so that users feel they are inside. The appearance of the Image object using 3600 panoramic so that it can display images indefinitely and not cut and can look around the image. Application creation is done by Multimedia Development Life Cycle (MDLC) and Unity3D. The application has been successfully operated on the Android operating system with minimum specifications of 2GB RAM and KitKat version 4.4 OS. The results of the study have been conducted through a questionnaire to 15 respondents with 15 questions earned an The total value of the frequency of each question gets a score of 1,009 or a percentage of eligibility of 89,68% starting that the application is well worth using. Based on the black-box test, the application has been running properly and can display Location Based Service and 3600 panoramic and its information.

Deep learning for tilted-wave interferometry

The tilted-wave interferometer is an interferometrical measurement system for the accurate optical form measurement of optical aspheres and freeform surfaces. Its evaluation procedure comprises a high-dimensional inverse problem to reconstruct the form of the surface under test from measured data. Recent work has used a deep learning hybrid approach to solve the inverse problem successfully in a simulation environment. A quantification of the model uncertainty was incorporated using ensemble techniques. In this paper, we expand the application of the deep learning approach from simulations to measured data and show that it produces results similar to those of a state-of-the-art method in a real-world environment.

Experimental Study on the Performance of Rate Adaptation Algorithm in IEEE 802.11g Networks

<p>IEEE 802.11 technology provides a low-cost wireless networking solution. In the last few years, we have seen that the demand for high-bandwidth wireless local area networks increases rapidly, due to the proliferation of mobile devices such as laptops, smart phones and tablet PCs. This has driven the widespread deployment of IEEE 802.11 wireless networks to provide Internet access. However, wireless networks present their own unique problems. Wireless channel is extremely variable and can be affected by a number of different factors, such as collisions, multipath fading and signal attenuation. As such, rate adaptation algorithm is a key component of IEEE 802.11 standard which is used to vary the transmission data rate to match the wireless channel conditions, in order to achieve the best possible performance. Rate adaptation algorithm studies and evaluations are always hot research topics. However, despite its popularity, little work has been done on evaluating the performance of rate adaptation algorithms by comparing the throughput of the algorithm with the throughput of the fixed rates. This thesis presents an experimental study that compares the performance ofMikroTik rate adaptation algorithm andMinstrel rate adaptation algorithm against fixed rates in an IEEE 802.11g network. MikroTik and Minstrel rate adaptation algorithm are most commonly used algorithm around the world. All experiments are conducted in a real world environment in this thesis. In a real world environment, wireless channel conditions are not tightly being controlled, and it is extremely vulnerable to interference of surrounding environment. The dynamic changes of wireless channel conditions have a considerable effect on the performance of rate adaptation algorithms. The main challenge of evaluating a rate adaptation algorithm in a real world environment is getting different experiment behaviours from the same experiment. Experiment results may indicate many different behaviours which due to the leak of wireless environment controlling. Having a final conclusion from those experiment results can be a challenge task. In order to perform a comprehensive rate adaptation algorithm evaluation. All experiments run 20 times for 60 seconds. The average result and stand deviation is calculated. We also design and implement an automation experiment controlling program to help us maintain that each run of experiment is following exactly the same procedures. In MikroTik rate adaptation algorithm evaluation, the results show in many cases that fixed rate outperforms rate adaptation. Our findings raise questions regarding the suitability of the adopted rate adaptation algorithm in typical indoor environments. Furthermore, our study indicates that it is not wise to simply ignore fixed rate. A fine selection of a fixed rate could be made to achieve desired performance. The result ofMinstrel rate adaptation evaluation show that whilst Minstrel performs reasonably well in static wireless channel conditions, in some cases the algorithm has difficulty selecting the optimal data rate in the presence of dynamic channel conditions. In addition, Minstrel performs well when the channel condition improves frombad quality to good quality. However, Minstrel has trouble selecting the optimal rate when the channel condition deteriorates from good quality to bad quality. By comparing the experimental results between the performance of rate adaptation algorithms and the performance of fixed data rate against different factors, the experiment results directly pointed out the weakness of these two rate adaptation algorithms. Our findings from both experiments provide useful information on the design of rate adaptation algorithms.</p>

Experimental Study on the Performance of Rate Adaptation Algorithm in IEEE 802.11g Networks

<p>IEEE 802.11 technology provides a low-cost wireless networking solution. In the last few years, we have seen that the demand for high-bandwidth wireless local area networks increases rapidly, due to the proliferation of mobile devices such as laptops, smart phones and tablet PCs. This has driven the widespread deployment of IEEE 802.11 wireless networks to provide Internet access. However, wireless networks present their own unique problems. Wireless channel is extremely variable and can be affected by a number of different factors, such as collisions, multipath fading and signal attenuation. As such, rate adaptation algorithm is a key component of IEEE 802.11 standard which is used to vary the transmission data rate to match the wireless channel conditions, in order to achieve the best possible performance. Rate adaptation algorithm studies and evaluations are always hot research topics. However, despite its popularity, little work has been done on evaluating the performance of rate adaptation algorithms by comparing the throughput of the algorithm with the throughput of the fixed rates. This thesis presents an experimental study that compares the performance ofMikroTik rate adaptation algorithm andMinstrel rate adaptation algorithm against fixed rates in an IEEE 802.11g network. MikroTik and Minstrel rate adaptation algorithm are most commonly used algorithm around the world. All experiments are conducted in a real world environment in this thesis. In a real world environment, wireless channel conditions are not tightly being controlled, and it is extremely vulnerable to interference of surrounding environment. The dynamic changes of wireless channel conditions have a considerable effect on the performance of rate adaptation algorithms. The main challenge of evaluating a rate adaptation algorithm in a real world environment is getting different experiment behaviours from the same experiment. Experiment results may indicate many different behaviours which due to the leak of wireless environment controlling. Having a final conclusion from those experiment results can be a challenge task. In order to perform a comprehensive rate adaptation algorithm evaluation. All experiments run 20 times for 60 seconds. The average result and stand deviation is calculated. We also design and implement an automation experiment controlling program to help us maintain that each run of experiment is following exactly the same procedures. In MikroTik rate adaptation algorithm evaluation, the results show in many cases that fixed rate outperforms rate adaptation. Our findings raise questions regarding the suitability of the adopted rate adaptation algorithm in typical indoor environments. Furthermore, our study indicates that it is not wise to simply ignore fixed rate. A fine selection of a fixed rate could be made to achieve desired performance. The result ofMinstrel rate adaptation evaluation show that whilst Minstrel performs reasonably well in static wireless channel conditions, in some cases the algorithm has difficulty selecting the optimal data rate in the presence of dynamic channel conditions. In addition, Minstrel performs well when the channel condition improves frombad quality to good quality. However, Minstrel has trouble selecting the optimal rate when the channel condition deteriorates from good quality to bad quality. By comparing the experimental results between the performance of rate adaptation algorithms and the performance of fixed data rate against different factors, the experiment results directly pointed out the weakness of these two rate adaptation algorithms. Our findings from both experiments provide useful information on the design of rate adaptation algorithms.</p>

Changes in Aquatic Lives Due to Changes in Environments

Currently, the world environment is changing more rapidly than at any other time. These changes have immense effects on aquatic life forms, from microscopic plankton to large fish (1). Some of the relevant stressors, amongst many, are temperature, salinity, and water pH, all of which are variables that directly impact living organisms present in the concerned aquatic environments (2). Scientists have found a correlation with physiological, morphological, and molecular changes in living organisms due to environmental fluctuations. In any aquatic ecosystem, photosynthetic primary producers are the basis of other life forms, and it is now established that environmental change has many detrimental effects on these primary producers; thus aquatic ecosystems. For example, increasing temperatures can reduce the productivity, cell size, and overall growth of many aquatic organisms, also a significant cause for coral bleaching (3,4).

Decision-Making

Decision-making (DM) has been studied from two main perspectives: cognitive and ecological. Findings indicate that experts have advanced DM skills that enhance performance. The underlying mechanisms of DM skills relate to the attention and anticipation capacities to function without interruption under pressure of time and to counter various sources of stress (e.g., self-regulation and coping strategies). There are still many questions that must be addressed to fully account for the DM process and apply the findings in a real-world environment. The most urgent questions relate to the neurophysiological mechanisms underlying DM, team DM processes, training and measuring DM, making creative decisions, and comprehending the process of coaches’ DM during competitive conditions and other real-life situations.