Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimasi Aplikasi SIMAK-BMN untuk Inventarisasi Barang Milik Negara Berbasis Aplikasi Mobile Android

Dalam sebuah satuan kerja atau institusi pemerintah di Negara Republik Indonesia, terdapat barang-barang yang dibeli atau diperoleh atas beban APBN yang kemudian dapat diidentifikasikan sebagai bagian dari Barang Milik Negara (BMN). BMN tersebut dicatat dalam sebuah aplikasi bernama Sistem Informasi Manajemen dan Akuntansi Barang Milik Negara (SIMAK-BMN). Untuk melakukan monitoring BMN yang telah tercatat di aplikasi tersebut, Kuasa Pengguna Anggaran (KPA) dan tim monitoring seringkali menemui beberapa kesulitan. Hal ini diakibatkan dari keterbatasan aplikasi SIMAK-BMN yang belum sepenuhnya mudah dioperasikan untuk keperluan monitoring. Dengan kondisi seperti itu maka pada makalah ini dibahas pengembangan sistem informasi monitoring BMN terpadu dengan melakukan optimasi terhadap database SIMAK-BMN. Sistem yang dibangun dapat dijalankan oleh tim monitoring BMN secara online menggunakan internet. Selain itu, dikembangkan pula sistem monitoring BMN secara mobile yang dapat diinstall pada perangkat smartphone berbasis Android. Sehingga, dalam pengelolaaanya, petugas tim pencatat dan penginventaris BMN dapat menggunakan smartphone mereka untuk membantu memudahkan pekerjaaan inventarisasi dengan melakukan scanning QR Code dari tiap-tiap BMN. Dengan adanya sistem monitoring BMN yang merupakan optimasi dari database SIMAK-BMN tersebut, diharapkan dapat mempermudah fungsi monitoring BMN dan menjadi kontribusi dalam pengembangan sistem monitoring internal suatu satuan kerja di Republik Indonesia serta mendukung kebijakan-kebijakan pengelolaan BMN. AbstractIn a unit or institution in the government of State of the Republic of Indonesia, there are goods obtained at the expense of the APBN which can be identified as the State Goods (BMN). BMN is recorded in an application called the Management Information System and Accounting for State Goods (SIMAK-BMN). To monitor the BMNs that have been recorded in that application, the Budget User Authority (KPA) and the monitoring team often encounter some difficulties. This is due to the limitations of the SIMAK-BMN application which has not been fully operational for monitoring purposes. With such conditions, this study discusses about the development of integrated BMN monitoring information system by optimizing the SIMAK-BMN database. The built system can be run by the BMN monitoring team using the internet. Moreover, also developed a mobile BMN monitoring system that can be installed on Android-based smartphone devices. Thus, in it’s management, BMN registration team can use their smartphone to scanning QR Code from each item of BMN. With the BMN monitoring system which is the optimization of the SIMAK-BMN database, it is expected to facilitate the BMN monitoring function and become a contribution in developing the internal monitoring system of a work unit in the government of Republic of Indonesia as well as supporting the policies of BMN management.
Content-Based Image Retrieval: A Comprehensive User Interactive Simulation Tool for Endoscopic Image Databases

Until few years ago, radiological methods were widely used for the examination and investigation of the digestive tract. Today, wireless capsule endoscopy represents an innovative, noninvasive, effective solution that does not imply a risk of irradiation. Due to the impressive number of images captured on the entire “trip” covered by the video capsule, diagnostic accuracy is greatly improved, also allowing the visualization of certain areas of the digestive tract that were previously inaccessible. Captured images can be analyzed by a specialist who can identify lesions or possible active bleeding within the digestive tract. This paper presents the implementation of a recovery system for endoscopic images based on Content-Based Image Retrieval (CBIR) technique.
Hydrochemical properties, bacterioplankton abundance and biomass in the meromictic Lake Starodworskie in 2004

Abstract Physicochemical and microbiological examinations were conducted on the meromictic Lake Starodworskie located in Olsztyn. The temperature profile revealed a characteristic, small increase in temperature at a depth between 13 and 14 m, and permanent anaerobic conditions in the deeper water layers. Accumulation of dissolved mineral substances enhanced the thermal stability of the lake waters; electrolytic conductivity values in the water deeper than 15 m oscillated within the range of 533 - 568 μS cm-1.
Piaget ethnographer

Although there have been extensive discussions of Piaget's theory, relatively little attention has been given to his research methods. Indeed, where Piaget's methods have been discussed they have generally been attacked for what are perceived as limitations and inadequacies. However, both in his work based on observations of infants and particularly in the clinical interviews with children and adolescents Piaget's research can be seen as a striking demonstration of the power of the systematic use of qualitative methods. Piaget's work in fact offers a paradigmatic example of an interpretive methodology in developmental psychology, not only for the intimate relations between interview and theory evident in all his research, but also for the argument through which the research is presented to the reader. As well as reviewing the clinical interview itself, this article also considers the different logics of research evident in this method and in that used by Piaget's critics.
Changes of rumen pH, fermentation and microbial population as influenced by different ratios of roughage (rice straw) to concentrate in dairy steers

SUMMARY The current study was designed to determine the effect of roughage to concentrate ratio (R : C) on rumen pH, fermentation and bacterial population in dairy steers. Four rumen fistulated dairy steers (170±20 kg) were randomly assigned according to a 4×4 Latin square design, in which the steers were fed with four dietary treatments with different R : C ratios of 0·8 : 0·2, 0·6 : 0·4, 0·4 : 0·6 and 0·2 : 0·8, respectively. All animals were kept in individual pens and received feed according to the respective R : C ratios at 0·025 body weight (BW)/d; urea-treated rice straw (prepared using 3·5 kg urea+100 kg water sprayed onto 100 kg of rice straw) was used as a roughage source. The experiment was conducted for four periods of 21 days each. During the first 14 days, feed intake was measured and the animals were then moved to metabolism crates for total urine and faecal collection for 7 days. Total dry matter intake (DMI) was similar among treatments. Energy intake increased as the proportion of concentrate in the diet increased. Apparent digestibilities of dry matter (DM), organic matter (OM) and crude protein (CP) were improved, while neutral detergent fibre (NDF) and acid detergent fibre (ADF) were reduced when the levels of concentrate increased. A decreasing ratio of R : C reduced rumen pH linearly, from 6·4 to 5·9 at 0·2 : 0·8. High levels of concentrate impacted on volatile fatty acids (VFA) molar proportions and decreased acetate (C2) linearly, while propionate (C3) was increased, leading to decreased C2 : C3 ratio. Numbers of protozoa, fungi and proteolytic bacteria were not affected by R : C ratio. Cellulolytic bacteria decreased linearly while amylolytic bacteria increased linearly with 0·60 and 0·80 concentrates. Quantitative polymerase chain reaction (qPCR) based on 16S RNA revealed that Fibrobacter succinogenes numbers were increased when steers were fed with R : C ratio of 0·8 : 0·2. Conjugated linoleic acid (CLA)-producing bacteria, especially those of Butyrivibrio fibrisolvens, increased linearly with R : C ratios of 0·8 : 0·2 and 0·6 : 0·4, while Megasphaera elsdenii, a lactate-utilizing bacterium and reported producer of trans-10, cis-12 CLA increased linearly with R : C ratio of 0·8 : 0·2. In addition, microbial CP synthesis increased quadratically when steers were fed high levels of concentrate. However, the efficiency microbial N synthesis (EMNS) based on OM, truly digested in the rumen, was not affected by different R : C ratios. From the current study, it can be concluded that roughage to concentrate ratio of 0·4 : 0·6 had positive effects for the creation of healthy rumen (rumen pH and ecology), and improved energy intake and rumen fermentation, particularly propionic acid and microbial protein synthesis, in dairy steers fed urea-treated rice straw as a roughage source.
Checkerboard artifacts free convolutional neural networks

Abstract It is well-known that a number of convolutional neural networks (CNNs) generate checkerboard artifacts in both of two processes: forward-propagation of upsampling layers and backpropagation of convolutional layers. A condition for avoiding the artifacts is proposed in this paper. So far, these artifacts have been studied mainly for linear multirate systems, but the conventional condition for avoiding them cannot be applied to CNNs due to the non-linearity of CNNs. We extend the avoidance condition for CNNs and apply the proposed structure to typical CNNs to confirm whether the novel structure is effective. Experimental results demonstrate that the proposed structure can perfectly avoid generating checkerboard artifacts while keeping the excellent properties that CNNs have.
Smart Search over Enciphered Data for Cloud Computing: A Survey

: With the advancement of information technologies particularly cloud storage used outsourcing data. Now a day’s users store a large amount of data on the cloud but it’s untrusted and we store secure data on the cloud. The concept of searchable encryption provides a promising direction in solving the privacy problem when outsourcing data to the cloud. Such schemes allow users to store their data in an encrypted format an untrusted server and then delegate the server to search on their behalf by issuing a trapdoor (i.e. encrypted keyword). This paper gives a detailed survey of various methods for searchable encryption schemes.
Modeling and Fuzzy Command Approach to Stabilize the Wind Generator

In this paper, a problem of mechanical modeling and robustly stabilization of a wind system formed by a turbine, a driving shaft and an induction machine, is considered. To overcome the complexity and the non-linearity of the system, the model of the wind generator is approximated by a Takagi-Sugeno fuzzy model. Hence, to stabilize the obtained fuzzy model, two command approaches were developed. They are the fuzzy controller using the parallel distributed compensation (PDC) and the H∞ controller based-fuzzy observer. Numerical optimization problems using linear matrix inequality (LMI) and convex techniques are used to analyze the stability of the wind generator. Finally, simulation examples illustrating the control performance and dynamic behavior of the wind generator under various command approaches are presented.
Karyological analysis and genome size in Milium (Gramineae) with special reference to polyploidy and chromosomal evolution

Karyotypes, nuclear DNA amounts, and meiotic behaviour are presented for Milium effusum L. (2n = 28), Milium montianum Parl. (2n = 22), and two cytotypes of Milium vernale Bieb. (2n = 8, 10). The bimodal karyotype of M. montianum (8 large and 14 small chromosomes) is described for the first time. Evidence from C-banding and geographical distribution suggests an ancient interracial allopolyploid origin for M. effusum (2n = 28). Although M. montianum is undoubtedly allopolyploid, its parentage is unconfirmed. A strong resemblance between the M. vernale (2n = 8) karyotype and the eight large chromosomes in M. montianum suggests a common ancestry. It is possible that a diploid form of M. effusum contributed the remaining 14 chromosomes. A selective loss of DNA sequences from the smaller chromosomes during the subsequent reorganization of the allopolyploid genome may have enhanced the bimodality of the karyotype. Geographical distribution and a change in the breeding system support the direction of the change .
Can Case Systems Generate the Flexible Medium Necessary for the Educational Environment?

However, learning is often non-linear and seldom homogeneous over any given student population. Thus, script oriented software is only of limited value for student bodies with diverse learning styles. Moreover, educators have seldom studied formal logic and consequently find great difficulty in the logical problems involved in programming in C, Prolog and Lisp. Thus, the content of educational software is defined by the medium in such a way that the original goal, education, is obscured if not totally effaced.
Comparison of various neural network-based models for retinal lesion analysis

Identification and analysis of laser-induced lesions on the retina can be challenging in both the research and clinical settings depending on the age of a lesion and the imaging modality used for detection. Previous research exploring retinal damage thresholds utilized the consensus of an expert panel to confirm energies required for minimal visible lesions, a method that includes some subjectivity. Because of this, there is a desire to develop an image processing architecture to accurately locate retinal laser lesions in images generated from clinically relevant modalities. Issues such as imaging aberrations inducing circular artifacts, perceived stretch in lesions, and differences in the appearance of lesions across the dataset preclude use of traditional image processing tools. A database containing images of laser lesions has been developed in order to provide a reference for researchers and clinicians. In this work, we explored using various Convolutional Neural Network (CNN) architectures and preprocessing techniques to more objectively identify and analyze retinal laser lesions. Specifically, we developed frequency domain filtering techniques in order to emphasize lesion qualities. We consider this task to be one of image segmentation to make the networks somewhat size invariant. Since the lesions account for a small amount of the image pixels, we implemented an intersection-based loss function. We evaluated the performance of our trained networks against more complicated architecture variants. Additionally, we trained a network to segment and classify lesions as the result of photochemical, photomechanical or photothermal damage.
Delay Distribution Based Remote Data Fetch Scheme for Hadoop Clusters in Public Cloud

SUMMARY Apache Hadoop and its ecosystem have become the de facto platform for processing large-scale data, or Big Data, because it hides the complexity of distributed computing, scheduling, and communication while providing fault-tolerance. Cloud-based environments are becoming a popular platform for hosting Hadoop clusters due to their low initial cost and limitless capacity. However, cloud-based Hadoop clusters bring their own challenges due to contradictory design principles. Hadoop is designed on the shared-nothing principle while cloud is based on the concepts of consolidation and resource sharing. Most of Hadoop’s features are designed for on-premises data centers where the cluster topology is known. Hadoop depends on the rack assignment of servers (con(cid:12)gured by the cluster administrator) to calculate the distance between servers. Hadoop calculates the distance be-tween servers to (cid:12)nd the best remote server from which to fetch data from when fetching non-local data. However, public cloud environment providers do not share rack information of virtual servers with their tenants. Lack of rack information of servers may allow Hadoop to fetch data from a remote server that is on the other side of the data center. To overcome this problem, we propose a delay distribution based scheme to (cid:12)nd the closest server to fetch non-local data for public cloud-based Hadoop clusters. The proposed scheme bases server selection on the delay distributions between server pairs. Delay distribution is calculated measuring the round-trip time between servers periodically. Our experiments observe that the proposed scheme outperforms conventional Hadoop nearly by 12% in terms of non-local data fetch time. This reduction in data fetch time will lead to a reduction in job run time, especially in real-world multi-user clusters where non-local data fetching can happen frequently.
Molecular diagnosis of trichodorid species from Portugal

A PCR-RFLP assay was developed for the identification of trichodorid nematodes belonging to Nanidorus, Paratrichodorus and Trichodorus genera. Using the variability of the 18S SSU rDNA gene, this method provides a new molecular diagnosis tool which allows identification within mixed samples of trichodorid and non-trichodorid species, differentiation of juveniles, and represents an alternative to the difficult and time consuming phenotyping of similar species. Based on the alignment of previously obtained 18S rDNA nucleotide sequences of trichodorids from Portugal, a pair of selective primers was designed in conserved regions to allow the amplification of a variable region located at the 3′ end of the gene in all known Portuguese species. The 615 bp PCR product showed nucleotide variability enabling the generation of restriction fragment patterns which were consistent among populations of the same species but allowed discrimination of trichodorids at the species level. The proposed protocol was tested and proved effective with 12 trichodorid species from Portugal (N. minor, P. allius, P. anemones, P. divergens, P. hispanus, P. pachydermus, P. porosus, T. beirensis, T. lusitanicus, T. primitivus and two other Trichodorus species, A and B) and six non-indigenous trichodorid populations (N. minor, P. allius, P. anemones, P. pachydermus, P. porosus and T. primitivus).
A shape memory alloy–actuated soft crawling robot based on adaptive differential friction and enhanced antagonistic configuration

This article presents a soft crawling robot prototype with a simple architecture inspired by inchworms. The robot functionally integrates the torso (body) and feet in a monolithic curved structure that only needs a single shape memory alloy coil and differential friction to actuate it. A novel foot configuration is proposed, which makes the two feet, with an anti-symmetrical friction layout, can be alternately anchored, to match the contraction–recovery sequence of the body adaptively. Based on the antagonistic configuration between the shape memory alloy actuator and the elastic body, a vertically auxiliary spring was adopted to enhance the interaction mechanism. Force and kinematic analysis was undertaken, focusing on the parametric design of the special foot configuration. A miniature robot prototype was then 3D-printed (54 mm in length and 9.77 g in weight), using tailored thermoplastic polyurethane elastomer as the body material. A series of experimental tests and evaluations were carried out to assess its performance under different conditions. The results demonstrated that under appropriate actuation conditions, the compact robot prototype could accomplish a relative speed of 0.024 BL/s (with a stride length equivalent to 27% of its body length) and bear a load over five times to its own weight.
Indução in vitro da germinação de sementes de Oncidium flexuosum (Orchidaceae) por fungos micorrízicos rizoctonióides

Symbiotic in vitro seed germination and protocorm development of Oncidium flexuosum is described for the first time. O. flexuosum seeds were inoculated with ten mycorrhizal isolates, originally obtained from the mycorrhiza of ten neotropical Brazilian orchid species, including O. flexuosum. One of the isolates belongs to Epulorhiza repens, two to Epulorhiza epiphytica, six to Ceratorhiza spp. , and one to Rhizoctonia sp. Seeds inoculated with the M2 isolate of Ceratorhiza sp. , originally isolated from the root system of wild O. flexuosum, promoted seed germination within 7 days and about 30% of the seedlings produced leaves after 50 days of incubation, all of which presented pelotons in some protocorm and rhizoid cells. The other isolates stimulated seed germination, although they did not lead to an ideal protocorm development. Seeds incubated in the absence of the mycorrhizal fungi failed to germinate. The degree of specificity and dependence of O. flexuosum from mycorrhizal fungi thus was evident. Aspects of the specificity, anatomy of the plant-fungus interaction and the importance of the fungal strain selection prior to the use of mycorrhizal fungi for the symbiotical O. flexuosum cultivation from seeds are discussed.
Sentiment analysis and resources for informal Arabic text on social media

Online content posted by Arab users on social networks does not generally abide by the grammatical and spelling rules. These posts, or comments, are valuable because they contain users’ opinions towards different objects such as products, policies, institutions, and people. These opinions constitute important material for commercial and governmental institutions. Commercial institutions can use these opinions to steer marketing campaigns, optimize their products and know the weaknesses and/ or strengths of their products. Governmental institutions can benefit from the social networks posts to detect public opinion before or after legislating a new policy or law and to learn about the main issues that concern citizens. However, the huge size of online data and its noisy nature can hinder manual extraction and classification of opinions present in online comments. Given the irregularity of dialectal Arabic (or informal Arabic), tools developed for formally correct Arabic are of limited use. This is specifically the case when employed in sentiment analysis (SA) where the target of the analysis is social media content. This research implemented a system that addresses this challenge. This work can be roughly divided into three blocks: building a corpus for SA and manually tagging it to check the performance of the constructed lexicon-based (LB) classifier; building a sentiment lexicon that consists of three different sets of patterns (negative, positive, and spam); and finally implementing a classifier that employs the lexicon to classify Facebook comments. In addition to providing resources for dialectal Arabic SA and classifying Facebook comments, this work categorises reasons behind incorrect classification, provides preliminary solutions for some of them with focus on negation, and uses regular expressions to detect the presence of lexemes. This work also illustrates how the constructed classifier works along with its different levels of reporting. Moreover, it compares the performance of the LB classifier against Naive Bayes classifier and addresses how NLP tools such as POS tagging and Named Entity Recognition can be employed in SA. In addition, the work studies the performance of the implemented LB classifier and the developed sentiment lexicon when used to classify other corpora used in the literature, and the performance of lexicons used in the literature to classify the corpora constructed in this research. With minor changes, the classifier can be used in domain classification of documents (sports, science, news, etc.). The work ends with a discussion of research questions arising from the research reported.