Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of the UPC-A Barcode Recognition Algorithm for Smartphone Applications

This paper is about a bar code decoding algorithm developed for smart phone applications. The algorithm consists of bar code data extraction procedure, bar code signal estimation procedure, and bar code decoding procedure. To detect the peak bar code module, a DSTW had been applied because of its outstanding performance in ECG peak detection. In order to minimize errors due to non-uniform light effect, the proposed algorithm was acted as a baseline wandering filter based on module peaks detection. The algorithm had been tested to evaluate the performance under the conditions of blurring, non-uniformed light and white noises. The algorithm had shown excellent performance in reconstruction of bar code decoding, compared to other conventional methods. In order to show the possibility of applying the algorithm to a smart phone, a real UPC-A type 150 bar code pictures obtained from a smart phone camera was applied to the algorithm, achieving the correct recognition rate of 97.33%.
Emissions of PM2.5-bound Polycyclic Aromatic Hydrocarbons and Metals from a Diesel Generator Fueled with Biodiesel Converted from Used Cooking Oil

To elucidate the characteristics of fine particulate matter pollutant emitted from a diesel engine, a fossil-based diesel fuel (D100) and two blended fuels consisting of D100 and waste cooking oil (WCO) convered biodiesel (W) are tested with a diesel engine generator at loads of 1.5 kW and 3.0 kW. The blended fuels contain 20% and 40% W and are referred to as W20 and W40, respectively. The PM2.5 emissions and their polycyclic aromatic hydrocarbon (PAH) and metallic components are investigated. Experimental results show that higher concentrations of PM2.5, PM2.5-bound ΣPAHs and Σmetals, and ΣBaPeq are generated at the 3.0 kW load, with its greater fuel consumption (FC), than the 1.5 kW load. Additionally, of the three fuels, using W20 emits the lowest concentrations of PM2.5, PM2.5-bound ΣPAHs, and ΣBaPeq. Specifically, the reduction in ΣBaPeq mainly results from the effective inhibition of HMW-BaPeq. Conversely, when using W40, the PM2.5-bound Σmetals significantly decreases, and its composition is strongly affected by the metallic content in the fuel. Although W20 and W40 exhibit higher FC (3.0% more) and brake-specific fuel consumption (BSFC; 3.1% more) than D100, they generate lower concentrations of PM2.5 (18.1% less), PM2.5-bound ΣPAHs (22.8% less) and Σmetals (22.0% less), and ΣBaPeq (35.0% less) at both engine loads. The emission factors of these pollutants in the engine exhaust are also reduced , particularly at the higher load (3.0 kW). Accordingly, WCO-based biodiesel additives may decrease the PM2.5, PAHs, and metals exhausted by diesel engines, thus reducing the BaPeq of these emissions.
Is distance teaching more work or less work?

Abstract This article presents data collected in a year‐long study in which the author and his assistants kept detailed records of their time spent teaching and maintaining two comparable university courses. One course was offered online to adult professionals away from campus, the other offered to undergraduates in traditional classrooms on campus. The courses had similar learning objectives, similar student activities, and equally favorable ratings by students. Both were mature courses that required only routine maintenance and revision. The data do not support the widely held belief that teaching an asynchronous online course requires more effort than teaching a comparable synchronous classroom course. Although the distance course required more frequent attention, the total teaching and maintenance time spent per student was less than that required to teach and maintain the classroom course. Categories of teaching tasks are also compared.
Variable rate error control for wireless ATM networks

For mobile wireless ATM networks, error control beyond that provided by the current ATM standards is required to realize reliable communication in this high noise environment. In the proposed scheme the ATM cell header is protected by a relatively powerful FEC code to ensure correct delivery and low cell loss rate. The ATM cell payload is encoded for varying degrees of error protection depending on the type of data contained in the payload. By applying multiple shortened codes to the data field, the same hardware performs the encoding/decoding functions for the different code rates. Analysis shows that significant reductions in cell loss rate (relative to an uncoded system) and varying degrees of payload error protection are realized with a minimal increase in required bandwidth.
Pertumbuhan dan perkembangan larva Musca domestica Linnaeus (Diptera: Muscidae) dalam beberapa jenis kotoran ternak

Lalat rumah ( Musca domestica ) merupakan serangga urban yang dapat berperan sebagai vector penyakit. Serangga ini umumnya menggunakan limbah organik sebagai sumber makanan bagi larvanya. Area peternakan merupakan salah satu bentuk industri yang menghasilkan limbah organic yang memiliki potensi sebagai media hidup bagi larva lalat rumah. Area peternakan di Indonesia umumnya terletak pada lokasi yang berdekatan dengan perumahan penduduk sehingga diperlukan suatu metoda untuk pengendalian populasi lalat rumah pada daerah peternakan. Penelitian ini bertujuan untuk mengetahui tingkat perkembangan dari larva lalat rumah yang hidup pada berbagai jenis kotoran ternak. Kotoran yang digunakan adalah kotoran ayam, sapi dan kuda, sedangkan untuk kontrol digunakan bekatul yang merupakan pakan standar pemeliharaan larva lalat rumah di laboratorium. Hasil penelitian menunjukkan bahwa larva yang hidup pada kotoran kuda memiliki laju perkembangan paling tinggi (5 hari), akan tetapi memiliki tingkat keberhasilan hidup larva (30%), berat pupa (6,8 ± 0,141 g), dan berat imago betina (4,9 ± 0,14 g) terendah di antara materi uji lainnya. Hal ini mengindikasikan kualitas nutrisi yang rendah pada kotoran ini. Hasil penelitian ini perlu dilanjutkan dengan penelitian pada faktor-faktor yang mempengaruhi pertumbuhan populasi secara langsung, seperti tingkat fekunditas lalat betina dan keberhasilan hidup telur. Dengan penambahan data-data baru pada penelitian lanjutan diharapkan metoda pengendalian populasi lalat rumah pada daerah peternakan dapat didesain dengan tepat.
IMPACT OF RANDOM DATA ERRORS ON PARAMETER ESTIMATION IN HYDROLOGIC MODELING

ABSTRACT Parameter uncertainty in hydrologic models is due, in part, to random errors in input data used for calibration. This work investigates the impact of various error distributions associated with input data on the final estimated parameter values using three different estimation criteria. Errors in precipitation data were found to introduce more uncertainty into parameter estimates than errors in runoff data. Parameter uncertainty increased as the level of error introduced into input data increased. Correlated errors in the input data greatly increased the uncertainty associated with parameter estimates.
Privacy-aware Messaging on Smartphone Mesh Network

Wireless Mesh Networks are presented as a low cost cooperative solution for wireless connectivity, having numerous applications in areas as businesses, homes, disaster, emergency or transport. In order to provide connectivity, routing has been studied extensively, however security has been neglected by research, leaving vulnerabilities that can be exploited by malicious users. Consequently arming users with security mechanisms resistant to common types of wireless networks attack is critical. Aiming to provide anonymity in discovery and privacy in communication, systems security solutions were researched trying to find the best of each to combine into securing a chat application. Intending to create and implement a fully distributed security protocol for wireless mesh applications, where mobile nodes are able to safely communicate, without a server certification, through serverless XMPP protocol. From an inspired combination of analysed solutions and the inclusion of some innovation a mutual authentication security scheme was designed that makes use of the phone number as the key pre-shared information. To identify and secure users, password security using stretch and salt are combined into a authentication scheme that filters the known users in the network and establishes secure communications with them. At the same time users remain anonymous with the use of a pseudonym linkable to their identity. Using open source android there was developed a chat application for WMN based on serverless XMPP and implementing decentralized security procedures that enable users to communicate safely with very good performance. This excellent user experience is provided through careful design of the functions that at the same time prevent attempts on user privacy.
Acquisition of voicing neutralization and alternations in Dutch

An eminent study in morphological acquisition is Jean Berko’s (1958) paper entitled “The child’s learning of English morphology”. In her study, she examined children’s productive knowledge of English allomorphs using a methodology called the Wug Test. Children were tested on their application of plural allomorphs: English words ending in final voiced obstruents, sonorants, and vowels take a /-z/ suffix (e.g. dogs [dgz]), words ending in final voiceless obstruents take a /-s/ suffix (e.g. cats [kaets]) and words with final sibilants take an /z/ suffix (e.g. buses [bs z]). To test productive knowledge, children were shown pictures of non-words in the singular and asked for the plural, as for nonwords they cannot fall back on memory. For example, “This is a wug. Now there is another one. There are two of them. There are two _____ (p. 165)”. Berko found that while children aged four and five years displayed some productive knowledge, they were variable in their application of the different allomorphs. This example of plural suffix allomorphy shows how morphology (i.e. adding a plural suffix) and phonology (classically thought to involve voicing assimilation and vowel insertion) can interact. The suffix alternation is thought to be both regular and productive, which means it is acquired relatively early (Bernhardt & Stemberger, 1998). Since the publication of Berko’s study, the Wug Test has been used to look at first and second language acquisition (Snow & Hoefnagel-Hoehle, 1978), in children with Specific Language Impairments (Goad & Rebellati, 1994; Leonard, Eyer, Bedore & Grela, 1997; Oetting & Rice, 1993), and in a variety of phonological and morphological contexts (most famously the English past tense) across different languages such as Dutch (Kerkhoff, 2004), Hungarian (MacWhinney, 1978), Spanish (Bybee & Pardo, 1981; Kernan & Blount, 1966),
Implementation of genetic algorithm based on hardware optimization

The genetic algorithm (GA) has been known as a method of solving large-scale optimization problems with complex constraints in various applications. Since a major drawback of the GA is that it needs a long computation time, the hardware implementations of GA processors (GAP) have been focused on in recent studies. We propose a more efficient GAP based on steady-state GA, modified survival-based GA, and modified tournament selection. In addition, by employing the efficient pipeline parallelization and handshaking protocol in our GAP, almost 50% of the computation speed-up can be achieved over survival-based GA which runs one million crossovers per second (1 MHz).
Weighted-outer-product associative neural network

A weighted outer product learning (WOPL) scheme for associative memory neural network is presented in which learning orders are incorporated to the Hopfield model. WOPL can be guaranteed to achieve correct recall of some stored datums no matter whether or not they are stable in the Hopfield model, and whether the number of stored datums is small or large. A technically sufficient condition is also discussed for how to suitably choose learning orders to fully utilize WOPL for correct recall of as many stored datums as possible.
Study on the Method of Channel Siltation Recognition Based on SVM

A method to recognize the channel siltation using support vector machine (SVM) is developed. The method is based on the system that the transducer arrays are laid out respectively on each side of the channel. Through the analysis of sonar signal acquired by data acquisition unit, the features to recognize the siltation are extracted. By recognizing verification of the siltation in one channel, the results show that the method can recognize the channel siltaion correctly. Compare with the traditional approaches of ANN, the method has the advantages of high recognition precision (>90%).
P‐14: An Image Processing Model of Contrast Perception and Discrimination of the Human Visual System

An multi‐layered image processing model of the primary visual system was built to simulate the center‐surround effect on apparent contrast perception and contrast discrimination at the suprathreshold level. The simulation revealed that the mechanisms for apparent contrast perception and contrast discrimination were instinctually different. We questioned the reliability of the perceptual image quality models that were based on the results of contrast discrimination experiments.
A Multi-Step Neural Control for Motor Brain-Machine Interface by Reinforcement Learning

Brain-machine interfaces (BMIs) decode cortical neural spikes of paralyzed patients to control external devices for the purpose of movement restoration. Neuroplasticity induced by conducting a relatively complex task within multistep, is helpful to performance improvements of BMI system. Reinforcement learning (RL) allows the BMI system to interact with the environment to learn the task adaptively without a teacher signal, which is more appropriate to the case for paralyzed patients. In this work, we proposed to apply Q(λ)-learning to multistep goal-directed tasks using users neural activity. Neural data were recorded from M1 of a monkey manipulating a joystick in a center-out task. Compared with a supervised learning approach, significant BMI control was achieved with correct directional decoding in 84.2% and 81% of the trials from naïve states. The results demonstrate that the BMI system was able to complete a task by interacting with the environment, indicating that RL-based methods have the potential to develop more natural BMI systems.
A new heuristic for rectilinear Steiner trees

A heuristic algorithm for finding RSTs (rectilinear Steiner trees) is presented. The algorithm was run on a large number of randomly generated data sets. However, the algorithm performed exceptionally well for several data sets, namely, it found steiner trees whose total length was 15 to 18% less than the total length of the corresponding RMSTs (rectilinear minimum spanning trees). The time complexity of the heuristic is O(N log N). The heuristic algorithm is described, and an example is presented. The time complexity of the heuristic and its performance in comparison with well-established techniques are analyzed. The authors also present a graph comparing the lengths of minimum spanning trees to that of the Steiner trees obtained by the heuristic for different values of N. Some possible improvements and variations of the algorithm are suggested. <<ETX>>
Oxide Semiconductor Thin‐Film Transistors: A Review of Recent Advances

Transparent electronics is today one of the most advanced topics for a wide range of device applications. The key components are wide bandgap semiconductors, where oxides of different origins play an important role, not only as passive component but also as active component, similar to what is observed in conventional semiconductors like silicon. Transparent electronics has gained special attention during the last few years and is today established as one of the most promising technologies for leading the next generation of flat panel display due to its excellent electronic performance. In this paper the recent progress in n‐ and p‐type oxide based thin‐film transistors (TFT) is reviewed, with special emphasis on solution‐processed and p‐type, and the major milestones already achieved with this emerging and very promising technology are summarizeed. After a short introduction where the main advantages of these semiconductors are presented, as well as the industry expectations, the beautiful history of TFTs is revisited, including the main landmarks in the last 80 years, finishing by referring to some papers that have played an important role in shaping transparent electronics. Then, an overview is presented of state of the art n‐type TFTs processed by physical vapour deposition methods, and finally one of the most exciting, promising, and low cost but powerful technologies is discussed: solution‐processed oxide TFTs. Moreover, a more detailed focus analysis will be given concerning p‐type oxide TFTs, mainly centred on two of the most promising semiconductor candidates: copper oxide and tin oxide. The most recent data related to the production of complementary metal oxide semiconductor (CMOS) devices based on n‐ and p‐type oxide TFT is also be presented. The last topic of this review is devoted to some emerging applications, finalizing with the main conclusions. Related work that originated at CENIMAT|I3N during the last six years is included in more detail, which has led to the fabrication of high performance n‐ and p‐type oxide transistors as well as the fabrication of CMOS devices with and on paper.
Centroid-Based and Bayesian Algorithms Performance

Since, the amount of textual information available on the web is estimated by terra bytes. Then, there should be an efficient algorithm to summarize such information. The algorithm would speed up the process of information reading, information accessing and decision making process. This paper investigates Bayesian classifier (BC) and a Centroid -Based algorithm (CBA) performance in terms of Arabic text summarization problem (ATS). Both algorithms are implemented as a software program. The Centroid -Based algorithm (CBA) extracts the most important sentences in a document or a set of documents (cluster). This algorithm starts computing the similarity between two sentences and evaluating the centrality of each sentence in a cluster based on centrality graph. Then the algorithm extracts the most important sentences in the cluster to include them in a summary. Whereas the Bayesian algorithm categorizes each sentence to be in text summary or out of text summary classes depends on its features vector. Both algorithms are evaluated by human participants and by an automatic metrics. Arabic NEWSWIRE-a corpus is used as a data set in the algorithms evaluation. The F-measure is obtained for both algorithms results. The Centroid -Based algorithm records 0.7199 and the Bayesian algorithm records 0.623. Thereforethe Centroid -Based algorithm (CBA) outperforms the Bayesian algorithm. The CBA results show that, the CBA is a robust algorithm compared to BC. It show a low deviation average that means the CBA gives similar result either contains bugs or not compared to BC. It is able to compress or reduce the text into 25% of its original size without losing the main idea behind the original text. This property makes the algorithm distinguishable among others used for the same purpose. Also, it outperforms all those techniques which are included in this paper when it is used for Arabic text summarization. General Terms: AI Applications, NLP, Text Mining and AI Algorithms.
UN MODELO DE SISTEMA COLABORATIVO SUPERVISADO PARA LA GESTIÓN DOCUMENTAL

The development of ICT has created a gap between computing processes and the huge volume of available information. Institutions need tools for knowledge management in collaborative environments and these tools should guarantee certain level of quality of service. By other hand, Web services are to become in the industry standard for interoperability but they are far away of providing the required robustness level. This paper proposes to adapt the MAS principles of electronic contracting at supervising knowledge management processes for knowledge sharing using web services, and to apply the descriptive capacity of OWL, as a formal semantic language in order to improve the autonomy of underneath computing processes. A SupervIsed CoLlabOrative System model (SICLOS) was defined –supervised from a global perspective, based on the semantic management of actions and resources. Dynamic processes control is improved and thereby, the knowledge management service. In this paper, the achieved results are discussed.
Estimating Plans along with Cost in Multiple Query Processing Environments by Applying Particle Swarm Optimization Technique

The Main idea of multiple query processing is to optimize a set of queries together and execute the common operations once. Major tasks in multiple query processing are common operation or expression identification and global execution plan construction. Query plans are generally derived from registered continuous queries. They are composed of operators, which perform the actual data processing, queries which buffer data as it moves between operators to hold state of operators. The complex part is to decompose queries and query plans and rearrange the sub queries and query plans on the network. The main functions to achieve an optimal query distribution are usually minimizing network usage and minimizing response time of queries. While dealing with query distribution problem, the challenges like modeling topology of the network, decomposing queries into some sub queries and sub query placement may be occurred. Operators are the basic data processing units in a query plan. An operator takes one or more streams as input and produces a stream as output. As in the traditional database management system, a plan for query connects a set of operators in a tree. The output of a child operator forms an input of its parent operator. In this paper it is aimed to retrieve the cost of query plans as well as cost of particles of swarm in multiple query processing environments by applying particle swarm optimization techniques.
GDF: Dealing with High-throughput Genotyping Multiplatform Data for Medical and Population Genetic Applications

Background: A number of different high throughput genotyping platforms have arisen recently. These platforms generate large amounts of genotyping data which is subsequently processed and stored in public and/or private databases. Both, the variety of platforms employed by the different laboratories and the large amount of data they generate, entail serious problems for data managing in most laboratories. Some public or private software packages available today solve some important needs, but they deal with the data from a point of view that the researcher may probably not share, and no supervision of the results (e.g. genotyping inconsistencies or summaries of the genotyping data) may be performed. Results: The main goal of the Genotyping Data Filter (GDF) software is to allow the researcher to locally manage large numbers of genotypes generated by the most standard genotyping platforms, obtaining statistics and summaries of the genotyping experiments whilst maintaining their privacy. GDF also allows the user to supervise the data such that the researcher can easily evaluate important parameters, including the proportion of missing data in samples and single nucleotide polymorphisms (SNPs), Hardy-Weinberg equilibrium, etc. Additionally, GDF parses the raw data into different text formats needed as input files in popular software packages frequently used in medical and population genetic applications. Conclusions: GDF is a Perl program that efficiently process data from various genotyping platforms, allowing researchers to easily inspect their own genotyping data and to parse it for a wide spectrum of well-known specialized analysis software. It has been prepared to be run through a user friendly web interface on the most common cases, but it can also be run as a local script on personal computers, or even supercomputers for very large-scale projects.