Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data

ABSTRACT The extent of oil palm plantations has increased rapidly in Malaysia over the past few decades. To evaluate ecological effects and economic values, it is important to produce an accurate oil palm map for Malaysia. The Phased Array Type L-band Synthetic Aperture Radar (PALSAR) on the Advance Land Observing Satellite (ALOS) is useful in land-cover mapping in tropical regions under all-weather conditions. In this study, PALSAR-2 images from 2015 were used for oil palm mapping with maximum likelihood classifier (MLC)-based supervised classification. The processed PALSAR-2 data were resampled to multiple coarser resolutions (50, 100, 250, 500, and 1000 m), and then used to investigate the effect of speckle in oil palm mapping. Both independent testing samples and inventories from the Malaysia Palm Oil Board (MPOB) were used to evaluate the mapping accuracy. The oil palm mapping result indicates 50–500 m to be a good resolution for either retaining spatial details or reducing speckle noise of PALSAR-2 images. Among which, the best overall mapping accuracies and average oil palm accuracies reached 94.50% and 89.78%, respectively. Moreover, the oil palm area derived from the 100-m resolution map is 6.14 million hectares (Mha), which is the closest to the official MPOB inventories (~8.87% overestimation).
Distributed Computation Particle Filters on GPU Architectures for Real-Time Control Applications

We present the design, analysis, and real-time implementation of a distributed computation particle filter on a graphic processing unit (GPU) architecture that is especially suited for fast real-time control applications. The proposed filter architecture is composed of a number of local subfilters that can share limited information among each other via an arbitrarily chosen abstract connected communication topology. We develop a detailed implementation procedure for GPU architectures focusing on distributed resampling as a crucial step in our approach, and describe alternative methods in the literature. We analyze the role of the most important parameters such as the number of exchanged particles and the effect of the particle exchange topology. The significant speedup and increase in performance obtained with our framework with respect to both available GPU solutions and standard sequential CPU methods enable particle filter implementations in fast real-time feedback control systems. This is illustrated via experimental and simulation results using a real-time visual servoing problem of a robotic arm capable of running in closed loop with an update rate of 100 Hz, while performing particle filter calculations that involve over one million particles.
Modeling Study on a Typical Dust Storm Over the Tarim Basin, Northwest China

A modeling study with the GOCART dust emission scheme and ACM2 PBL scheme implemented into an air quality model WRF-Chem (Weather Research and Forecasting model with chemistry) was conducted to simulate a typical dust event over the Tarim basin that occurred on 27 April to 1 May 2015. There were strong wind injects into Tarim Basin accompanied by a cold frontal system driving dust emission and transport for a dust storm. The dust storm event over the Tarim basin could be classified into three processes with 1)the westerly wind from the Pamirs Plateau, 2)the cold air invasion from the northeast basin and 3)the northerly cold air crossing the Tianshan Mountains into the basin. This simulation depicted the three-dimensional structure of dust aerosols in the typical sandstorm over the Tarim Basin, Northwest China.
Tales of the Tail: Hardware, OS, and Application-level Sources of Tail Latency

Interactive services often have large-scale parallel implementations. To deliver fast responses, the median and tail latencies of a service's components must be low. In this paper, we explore the hardware, OS, and application-level sources of poor tail latency in high throughput servers executing on multi-core machines. We model these network services as a queuing system in order to establish the best-achievable latency distribution. Using fine-grained measurements of three different servers (a null RPC service, Memcached, and Nginx) on Linux, we then explore why these servers exhibit significantly worse tail latencies than queuing models alone predict. The underlying causes include interference from background processes, request re-ordering caused by poor scheduling or constrained concurrency models, suboptimal interrupt routing, CPU power saving mechanisms, and NUMA effects. We systematically eliminate these factors and show that Memcached can achieve a median latency of 11 μs and a 99.9th percentile latency of 32 μs at 80% utilization on a four-core system. In comparison, a naïve deployment of Memcached at the same utilization on a single-core system has a median latency of 100 μs and a 99.9th percentile latency of 5 ms. Finally, we demonstrate that tradeoffs exist between throughput, energy, and tail latency.
Business Domain Modelling using an Integrated Framework

This paper presents an application of a “Systematic Soft Domain Driven Design Framework” as a soft systems approach to domain-driven design of information systems development. The framework combining techniques from Soft Systems Methodology (SSM), the Unified Modelling Language (UML), and an implementation pattern known as “Naked Objects”. This framework have been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, and a real case study “Information Retrieval System for academic research” is used, in this paper, to show further practice and evaluation of the framework in different business domain. We argue that there are advantages from combining and using techniques from different methodologies in this way for business domain modelling. The framework is overviewed and justified as multimethodology using Mingers multimethodology ideas.
Cost effectiveness of adding magnetic resonance imaging to the usual management of suspected scaphoid fractures

Objective: To determine the cost effectiveness of a magnetic resonance imaging scan (MRI) within 5 days of injury compared with the usual management of occult scaphoid fracture. Methods: All patients with suspected scaphoid fractures in five hospitals were invited to participate in a randomised controlled trial of usual treatment with or without an MRI scan. Healthcare costs were compared, and a cost effectiveness analysis of the use of MRI in this scenario was performed. Results: Twenty eight of the 37 patients identified were randomised: 17 in the control group, 11 in the MRI group. The groups were similar at baseline and follow up in terms of number of scaphoid fractures, other injuries, pain, and function. Of the patients without fracture, the MRI group had significantly fewer days immobilised: a median of 3.0 (interquartile range 3.0–3.0) v 10.0 (7–12) in the control group (p = 0.006). The MRI group used fewer healthcare units (median 3.0, interquartile range 2.0–4.25) than the control group (5.0, 3.0–6.5) (p = 0.03 for the difference). However, the median cost of health care in the MRI group ($594.35 AUD, $551.35–667.23) was slightly higher than in the control group ($428.15, $124.40–702.65) (p = 0.19 for the difference). The mean incremental cost effectiveness ratio derived from this simulation was that MRI costs $44.37 per day saved from unnecessary immobilisation (95% confidence interval $4.29 to $101.02). An illustrative willingness to pay was calculated using a combination of the trials measure of the subjects’ individual productivity losses and the average daily earnings. Conclusions: Use of MRI in the management of occult scaphoid fracture reduces the number of days of unnecessary immobilisation and use of healthcare units. Healthcare costs increased non-significantly in relation to the use of MRI in this setting. However, when productivity losses are considered, MRI may be considered cost effective, depending on the individual case.
Local environment rather than past climate determines community composition of mountain stream macroinvertebrates across Europe

Community assembly is determined by a combination of historical events and contemporary processes that are difficult to disentangle, but eco‐evolutionary mechanisms may be uncovered by the joint analysis of species and genetic diversity across multiple sites. Mountain streams across Europe harbour highly diverse macroinvertebrate communities whose composition and turnover (replacement of taxa) among sites and regions remain poorly known. We studied whole‐community biodiversity within and among six mountain regions along a latitudinal transect from Morocco to Scandinavia at three levels of taxonomic hierarchy: genus, species and haplotypes. Using DNA barcoding of four insect families (>3100 individuals, 118 species) across 62 streams, we found that measures of local and regional diversity and intraregional turnover generally declined slightly towards northern latitudes. However, at all hierarchical levels we found complete (haplotype) or high (species, genus) turnover among regions (and even among sites within regions), which counters the expectations of Pleistocene postglacial northward expansion from southern refugia. Species distributions were mostly correlated with environmental conditions, suggesting a strong role of lineage‐ or species‐specific traits in determining local and latitudinal community composition, lineage diversification and phylogenetic community structure (e.g., loss of Coleoptera, but not Ephemeroptera, at northern sites). High intraspecific genetic structure within regions, even in northernmost sites, reflects species‐specific dispersal and demographic histories and indicates postglacial migration from geographically scattered refugia, rather than from only southern areas. Overall, patterns were not strongly concordant across hierarchical levels, but consistent with the overriding influence of environmental factors determining community composition at the species and genus levels.
Bottom-up disjoint-support decomposition based on cofactor and boolean difference analysis

This paper presents a new approach for Boolean decomposition based on the Boolean difference and cofactor analysis. Two simple tests provide sufficient and necessary conditions to identify AND and exclusive-OR (XOR) decompositions. The proposed method can decompose an n-input function in O(n . log n) cofactor and O(n) equivalence test operations. Recently, 2-to-1 multiplexers (MUX) have also been used to perform such decomposition. However, MUX with more inputs has been neglected. We provide sufficient and necessary conditions to obtain MUX decompositions of functions with an arbitrary number of inputs.
Interferon Response and Viral Evasion by Members of the Family Rhabdoviridae

Like many animal viruses, those of the Rhabdoviridae family, are able to antagonize the type I interferon response and cause disease in mammalian hosts. Though these negative-stranded RNA viruses are very simple and code for as few as five proteins, they have been seen to completely abrogate the type I interferon response early in infection. In this review, we will discuss the viral organization and type I interferon evasion of rhabdoviruses, focusing on vesicular stomatitis virus (VSV) and rabies virus (RABV). Despite their structural similarities, VSV and RABV have completely different mechanisms by which they avert the host immune response. VSV relies on the matrix protein to interfere with host gene transcription and nuclear export of anti-viral mRNAs. Alternatively, RABV uses its phosphoprotein to interfere with IRF-3 phosphorylation and STAT1 signaling. Understanding the virus-cell interactions and viral proteins necessary to evade the immune response is important in developing effective vaccines and therapeutics for this viral family.
Comparative and Analysis of Biometric Systems

– Biometric as the science of recognizing an individual based on his or her physical or behavioral traits, it is beginning to gain acceptance as a legitimate method for determining an individual identity. Biometric have now been deployed in various commercial, civilian, and national security applications. Biometric described overview of various biometric techniques and the need to be addressed form making biometric technology an effective tool for providing information security .
Performance analysis for facial expression recognition under salt and pepper noise with median filter approach

Facial expression provides an important behavioural measure for studies of emotion, cognitive processes, and social interaction. Facial expression recognition has recently become a promising research area. In face recognition, the simple process of face recognition system should go through image data retrieval, face detection, facial feature extraction and face recognition. However, some researches focus on the part of face recognition system, such as face detection, face recognition, or algorithms dealing with certain drawbacks issues such as illumination, occlusion, noise, and angle. Thus, in this research we have considered the facial changes as represented by face emotions from JAFFE Database results for different noise levels. The proposed system consists of three modules. The first module read the images face of three different emotions such as happy, fear and surprise. Those images are flawed with different level of salt and pepper noise. Then filter is applied on the corrupted images with average and median filter. The second module constructs PCA that are responsible for feature extraction, while the third module extracts the features by processing the image and measuring dimensions of PCA using k-NN and NN. Using the proposed classifiers, some experimental results have been obtained. It is found that the highest percentage of accuracy is 71.43 % and 83.96 % for K-NN and NN classifier respectively.
Japanese-Chinese Cross-Language Information Retrieval: An Interlingua Approach

Electronically available multilingual information can be divided into two major categories: (1) alphabetic language information (English-like alphabetic languages) and (2) ideographic language information (Chinese-like ideographic languages). The information available in non-English alphabetic languages as well as in ideographic languages (especially, in Japanese and Chinese) is growing at an incredibly high rate in recent years. Due to the ideographic nature of Japanese and Chinese, complicated with the existence of several encoding standards in use, efficient processing (representation, indexing, retrieval, etc.) of such information became a tedious task. In this paper, we propose a Han Character (Kanji) oriented Interlingua model of indexing and retrieving Japanese and Chinese information. We report the results of mono- and cross- language information retrieval on a Kanji space where documents and queries are represented in terms of Kanji oriented vectors. We also employ a dimensionality reduction technique to compute a Kanji Conceptual Space (KCS) from the initial Kanji space, which can facilitate conceptual retrieval of both mono- and cross- language information for these languages. Similar indexing approaches for multiple European languages through term association (e.g., latent semantic indexing) or through conceptual mapping (using lexical ontology such as, WordNet) are being intensively explored. The Interlingua approach investigated here with Japanese and Chinese languages, and the term (or concept) association model investigated with the European languages are similar; and these approaches can be easily integrated. Therefore, the proposed Interlingua model can pave the way for handling multilingual information access and retrieval efficiently and uniformly.
Feeding ecology of Bathyclarias nyasensis (Siluroidei: Claridae) from Lake Malawi

In Malawi, fish contribute about 60-80% to the country's animal protein supply. The greater proportion (> 50%) comes from Lake Malawi. Bathyclarias nyasensis and other clariid catfish contribute up to > 20% of the total catches. Catches of Bathyclarias nyasensis in the inshore area of the south-east arm of Lake Malawi are declining and a management plan for the fishery is essentially lacking. There is paucity of biological data that precludes the use of any option to manage the species. The principal aim of the thesis was to define the ecological role B. nyasensis, the most abundant and common of the Bathyclarias species. By examining life history characteristics within a food web context, it was hypothesized that the study would provide an insight into the interrelationships between species, and, hence form the basis for the development of a rational exploitation strategy for the species. The study was undertaken in the south-east arm of Lake Malawi (9° 30'S, 14° 30'S). The principal objectives of the study were to investigate the feeding ecology of B. nyasensis by examining morphological characters and structures associated with feeding, diet of B. nyasensis, food assimilated in the species using carbon (a! 3C) isotope analysis, daily food ~ consumption rate for B. nyasensis; and to relate the feeding ecology to life history traits such as age, growth, and some aspects oft4e reproductive biology of B. nyasensis. The suitability of sectioned pectoral spines and sagittal otoliths to age B. nyasensis was assessed. Due to reabsorption of growth zones with increasing spine lumen diameter with fish size, and the relatively low number of spines that could be aged reliably, only otoliths were used. The maximum age for B. nyasensis was estimated at 14 vears. Growth 1,={42+(81 1.8_ 421.8}x l_e-O.05(t-l)}1/1.8 was best was described by the four parameter Schnute me l_e-(-O·05)(lI)
MATEP: Monitoring and Analysis Tool for E-Learning Platforms

Web-based learning environments are extensively used nowadays. At the moment of designing, implementing and managing e-learning courses, there have to be defined guidelines that guarantee the quality and excellence of these processes as well as controls of evaluation that assure the above mentioned quality. In this respect, in the LMS (learning management systems) the teacher has not got tools for assessing and measuring the performance of the students in their virtual courses. Therefore, we have developed a monitoring and analysis tool for e-learning platforms (MATEP) in the University of Cantabria (Spain) which is described in this paper.
Road junction detection from 3D point clouds

Detecting changing traffic conditions is of primal importance for the safety of autonomous cars navigating in urban environments. Among the traffic situations that require more attention and careful planning, road junctions are the most significant. This work presents an empirical study of the application of well known machine learning techniques to create a robust method for road junction detection. Features are extracted from 3D pointclouds corresponding to single frames of data collected by a laser rangefinder. Three well known classifiers-support vector machines, adaptive boosting and artificial neural networks-are used to classify them into “junctions” or “roads”. The best performing classifier is used in the next stage, where structured classifiers-hidden Markov models and conditional random fields-are used to incorporate contextual information, in an attempt to improve the performance of the method. We tested and compared these approaches on datasets from two different 3D laser scanners, and in two different countries, Germany and Brazil.
Multistage Artificial Neural Network Short-Term Load Forecasting Engine With Front-End Weather Forecast

A significant portion of the operating cost of utilities comes from energy production. To minimize the cost, unit commitment (UC) scheduling can be used to determine the optimal commitment schedule of generation units to accommodate the forecasted demand. The load forecast is a prerequisite for UC planning. The projected load of up to seven days is important for the allocation of generation resources. Hour-ahead forecast is used for optimally dispatching online resources to supply the next hour load. This paper addresses the systematic design of a multistage artificial-neural-network-based short-term load forecaster (ANNSTLF). The developed ANNSTLF engine has been utilized in a real utility system. The performance analysis over the past year shows that a majority of the forecast error was detected in a consistent period with a large temperature forecast error. The enhancement of ANNSTLF is proposed to improve the forecasting performance. The comparison of forecasting accuracy due to this enhancement is analyzed.
Design of ultra-low-power CMOS amplifiers based on flicker noise reduction

In this paper, a weak inversion technique for recycling folded cascode (RFC) and folded cascode (FC) operational amplifier design with flicker noise reduction is presented. Flicker noise is the dominant noise source in silicon MOSFET's especially in low frequency. A new formulation for input referred flicker noise in weak inversion region is also presented and an efficient tradeoff between input refereed flicker noise power and frequency response is performed for optimum design in weak inversion region. This procedure will be useful for all of CMOS weak inversion amplifiers. The proposed technique significantly enhances the conventional noise performance of FC and RFC amplifier. The theoretical analysis is verified in 0.18 μm CMOS technology.
Scalable mining of large disk-based graph databases

Mining frequent structural patterns from graph databases is an interesting problem with broad applications. Most of the previous studies focus on pruning unfruitful search subspaces effectively, but few of them address the mining on large, disk-based databases. As many graph databases in applications cannot be held into main memory, scalable mining of large, disk-based graph databases remains a challenging problem. In this paper, we develop an effective index structure, ADI (for adjacency index), to support mining various graph patterns over large databases that cannot be held into main memory. The index is simple and efficient to build. Moreover, the new index structure can be easily adopted in various existing graph pattern mining algorithms. As an example, we adapt the well-known gSpan algorithm by using the ADI structure. The experimental results show that the new index structure enables the scalable graph pattern mining over large databases. In one set of the experiments, the new disk-based method can mine graph databases with one million graphs, while the original gSpan algorithm can only handle databases of up to 300 thousand graphs. Moreover, our new method is faster than gSpan when both can run in main memory.