Miracle-dz/UniFAR-FTUs huggingface dataset:
PHYTOCHEMICALS , ANTIOXIDANT AND ANTIMICROBIAL PROPERTIES OF Senna alata AND Senna tora LEAF EXTRACTS AGAINST BACTERIAL STRAINS CAUSING SKIN INFECTIONS

A study was carried out to screen for phytochemical constituents and assess the antioxidant and antimicrobial activities of Senna alata and Senna tora leaf extracts. The leaves were first dried at room temperature and 50°C in an oven prior to solvent extraction using ethanol and methanol. The in-vitro qualitative assays showed that both S. alata and S. tora leaf extracts contained bioactive and secondary metabolites components such as tannins, steroids, saponin, terpenoids, glycosides, flavonoids and phenols. The antioxidant activity and capacity test were carried out by conducting free radical of 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity and Ferric reduction antioxidant plasma (FRAP) assays. Both assays showed S. tora leaf extract has higher antioxidant capacity than S. alata leaf extract. The efficacy of these leaf extracts were tested against skin pathogens through agar well diffusion method. S. alata extract showed an inhibition zone (1.15 – 1.59 mm) against Pseudomonas aeruginosa while S. tora extracts exhibited a strong antimicrobial activity against S. epidermidis (inhibition zone of 12 – 16.94 mm) followed by P. aeruginosa (inhibition zone of 1 – 1.59 mm). Nonetheless, no inhibition zone was observed for S. aureus by both leaf extracts. The phytochemicals and antioxidant constituents as well as inhibitory potential on skin pathogens possessed by S. alata and S. tora leave highlighted their potential utilization in the development of natural drugs or cosmetics to treat skin related diseases or infections.
Aging the human face - a statistically rigorous approach

Forensic age progression for the purpose of aging a missing child is a discipline currently dominated by artistic methodologies. In order to improve on these techniques, we present a statistically rigorous approach to the aging of the human face. The technique is based upon a Principal Component Analysis and involves the definition of an aging direction through the model space, using an age-weighted combination of model parameters. Pose and expression compensation methods are also incorporated, allowing faces at a wide variety of pose orientations and expressions to be aged accurately. Near photo-quality images are obtained quickly and the resultant aging effects are realistic and plausible.
Matching soil grid unit resolutions with polygon unit scales for DNDC modelling of regional SOC pool

Abstract. Matching soil grid unit resolution with polygon unit map scale is important to minimize uncertainty of regional soil organic carbon (SOC) pool simulation as their strong influences on the uncertainty. A series of soil grid units at varying cell sizes were derived from soil polygon units at the six map scales of 1:50 000 (C5), 1:200 000 (D2), 1:500 000 (P5), 1:1 000 000 (N1), 1:4 000 000 (N4) and 1:14 000 000 (N14), respectively, in the Tai lake region of China. Both format soil units were used for regional SOC pool simulation with DeNitrification–DeComposition (DNDC) process-based model, which runs span the time period 1982 to 2000 at the six map scales, respectively. Four indices, soil type number (STN) and area (AREA), average SOC density (ASOCD) and total SOC stocks (SOCS) of surface paddy soils simulated with the DNDC, were attributed from all these soil polygon and grid units, respectively. Subjecting to the four index values (IV) from the parent polygon units, the variation of an index value (VIV, %) from the grid units was used to assess its dataset accuracy and redundancy, which reflects uncertainty in the simulation of SOC. Optimal soil grid unit resolutions were generated and suggested for the DNDC simulation of regional SOC pool, matching with soil polygon units map scales, respectively. With the optimal raster resolution the soil grid units dataset can hold the same accuracy as its parent polygon units dataset without any redundancy, when VIV
Design of a high-speed arithmetic datapath

This paper presents the implementation of a 64/32 bit floating-point datapath circuit (WTL3*64). This high-speed CMOS circuit integrates a 2 Kbit six-port register file, an independent 64/32-bit alu, a multiplier, and a divide/square-root unit for IEEE binary floating-point format numbers. It is fabricated using a 1.2 micron two-layer-metal CMOS technology. Operating at 60 ns cycle time, the 165000 transistor/147600 square mil chip provides 33 double-precision Mflops of peak performance. The register file, together with special registers, a flexible input/output interface, features for high level language support, and 1.5 Watts of power facilitate ease of integration of the device into various computer systems. <<ETX>>
A Case Study Using the Community of Inquiry Framework to Analyze Online Discussions in WordPress and Blackboard in a Graduate Course

Online discussions in a graduate level education course were compared using the Community of Inquiry framework and a Classroom Community survey within a mixed methods case study with concurrent triangulation of data sources. Discussion posts were published in two separate software applications: WordPress and Blackboard. Data collected included online discussion metadata, Community of Inquiry coding of online discussion content, survey responses from students, and an interview with the instructor to identify pedagogical decisions made in the design of the course. Content analysis of the discussion archives described differences in posts published to the two platforms, as well as differences in simultaneous indications of Community of Inquiry presences over time. Five new online discussion timeline visualization methods are presented. Key findings include an emphasis on pedagogical design over software selection in facilitating rich online discussions in the context of a graduate level course, although selection of software may provide signals to participants regarding the instructor’s expectations. Recommendations for reproducing similar research, identification of areas for future research, and recommendations for practice are provided.
Visual KEA: A Visual Model Based on Keywords Extraction Algorithm for Hub Pages

Automatically extracting keywords from webpage is greatly important for focused spider. There are already quite many researches on automatically extracting keywords from content-intensive web pages. However, it is still a challenge to extract keywords automatically from hyperlink-intensive web pages (hub pages). The web page author will often use all kinds of visual strengthening means to prominently demonstrate some glossaries connected with the subject. Therefore, this paper proposes a visual model of web pages, DOM-PIXEL, which regards DOM leaf node of webpage as an image element expressed by a vision vector, in which each component corresponds to one visual emphasis means; the pixel value is from the visual energy. The pixel value reflects the relevance of the corresponding DOM node with respect to subject. These parts strengthened by page author will be highlighted with particular “color” in DOM-PIXEL image. Then, the only request for keywords extraction algorithm is to find these “particular points” with particular “color” automatically. Just because of the intrinsic anti-noise ability of DOM-PIXEL and its visual energy transfer rule, the visual model based keywords extraction algorithm (VisualKEA) proposed in this paper significantly promotes the performance on hub pages.
Space-Diversity Performance as a Function of Antenna Separation

The reduction of multipath fading on line-of-sight microwave radio-relay links by dual space diversity is quantitatively described. One of the main results is a fade reduction factor F that specifies the improvement provided by space diversity as a function of the vertical separation of the receiving antennas, frequency, path length, and the relative size of the antennas in the diversity pair. The results are based on a theoretical analysis of recent experimental data.
The Correlation Of Distribution Of PM NumberEmitted Under Actual Conditions Of Operation ByPC And HDV Vehicles

The paper presents results of tests on particulate matter (PM) in PC and HDV category vehicles fitted with compression ignition engines and various systems of exhaust gas aftertreatment. The measurements were made under actual conditions of use in a city and used portable exhaust gas analyzers belonging to a group of PEMS (Portable Emissions Measurement Systems) – AVL MSS concentration analyzer and TSI EEPS mass spectrometer. The obtained results were processed and coefficients of correlation were determined for PC-PC and PC-HDV. The considerations were made according to Euro 3-5 emission standards. Moreover, the paper discusses a scheme of soot and PM formation as well as describes the influence of exhaust gas aftertreatment systems upon formation of the same.
Semi-custom ASIC technology trends

Some of the high level trends in semi-custom (standard cell and gate array) ASIC technology are identified. Development of ASIC technologies has accelerated to a point where the rate of introduction of new technologies exceeds that of DRAM technology. Implications for process performance, packing density, and cost are discussed. A simple algorithm to model ASIC cost is presented and used to estimate gate and pin counts for optimum costs.
Depfix, a Tool for Automatic Rule-based Post-editing of SMT

Abstract We present Depfix, an open-source system for automatic post-editing of phrase-based machine translation outputs. Depfix employs a range of natural language processing tools to obtain analyses of the input sentences, and uses a set of rules to correct common or serious errors in machine translation outputs. Depfix is currently implemented only for English-to-Czech translation direction, but extending it to other languages is planned.
Bursts and Avalanches: The Dynamics of Polycentric Urban Evolution

Urban construction activities are subject to periods of fast expansion followed by periods of slow growth. Some of these expansions are limited in size, while others are huge. Therefore, it is not surprising that equilibrium-oriented classical models of urban spatial structure are hard pressed to explain the formation of modern cities with polycentric structure and births of subcenters in particular. To understand the development of cities' spatial patterns we present a model of urban spatial dynamics that is driven by two types of real-estate entrepreneurs that differ in their degree of risk aversion. The developers act in the shadow of the city planning board that formulates urban development policy and defines the boundaries of future residential expansions. The model's salient feature is the time lag between the time of purchase of property rights by land developers and the time of the realization of revenues. We assume that this lag varies in space, being much larger in locations that are not zoned for building. It can be reduced by the planning board in cases of high demand for dwellings. We use the model to demonstrate how the interaction between demand for dwellings, the choices taken by each type of developer, and planning policies leads to the creation of new urban subcenters. The model dynamics are characterized by long out-of-equilibrium periods followed by sudden bursts of construction activity that resembles self-organized criticality.
Multi-resolution Keyword Mining Algorithm based on Frequent Pattern Technique

Finding out keywords from massive text document is a hard problem because an amount of synonyms are frequently used in a text. This paper proposes a keyword mining algorithm based on analyzing the “frequent patterns” of the words in a text. We use a new method referring the cluster process to determine the words’ relationship by their distances. We firstly extend the FP-tree to a new structure named W3P-Tree which is used to maintain the text information instead of database transactions, then present our mining algorithm following with the growth of W3P-tree.
New method for rapid diagnosis of Hepatitis disease based on reduction feature and machine learning

Hepatitis disease is caused by liver injury. Rapid diagnosis of this disease prevents its development and suffering to cirrhosis of the liver. Data mining is a new branch of science that helps physicians for proper decision making. In data mining using reduction feature and machine learning algorithms are useful for reducing the complexity of the problem and method of disease diagnosis, respectively. In this study, a new algorithm is proposed for hepatitis diagnosis according to Principal Component Analysis (PCA) and Error Minimized Extreme Learning Machine (EMELM). The algorithm includes two stages; in reduction feature phase, missing records were deleted and hepatitis dataset was normalized in [0,1] range. Thereafter, analysis of the principal component was applied for reduction feature. In classification phase, the reduced dataset is classified using EMELM. For evaluation of the algorithm, hepatitis disease dataset from UCI Machine Learning Repository (University of California) was selected. The features of this dataset reduced from 19 to 6 using PCA and the accuracy of the reduced dataset was obtained using EMELM. The results revealed that the proposed hybrid intelligent diagnosis system reached the higher classification accuracy and shorter time compared with other methods.
Application of rf discharges to sputtering

The operation of rf discharges is described and the internal distribution of voltages is considered. The significance of this with respect to sputtering, particularly of insulators, is then discussed. An equivalent circuit for the discharge is presented and the influence of such parameters as pressure and magnetic field on the components of this circuit is described. Finally, energy distributions for positive ions, electrons, and negative ions incident at the substrate during deposition are given.
Well-Defined Processes and Their Effects on Business Process Outsourcing Vendor's Success: an Integrated Framework

Offshore business process outsourcing (BPO) has been prevalent for two decades, but there are many failures. Although some literature analyzes the reason of failures from process viewpoint, there is still not a clear understanding about what are well-defined processes and their effects on BPO vendor’s success are still undisclosed. In this paper, we give a definition of well-defined processes and some criteria to measure them, which fills the gap of absence of a clear definition of well-defined processes. In addition, we propose an integrated framework from production cost economics (PCE), relational exchange theory (RET) and transaction cost economies (TCE) perspectives, through which we talk about how well-defined processes affect BPO vendor’s success. Well-defined processes affect BPO vendor’s success through facilitating internal productivity, strengthening external relationship and improving contract enforcement.
A Design of Direct Memory Access (DMA) Controller For H.264 Encoder

In this paper, an attempt has been made to design the controller applicable for H.264 level3 encoder of baseline profile on full hardware basis. The designed controller module first stores the images supplied from CMOS Image Sensor(CIS) at main memory, and then reads or stores the image data in macroblock unit according to encoder operation. The timing cycle of the DMA controller required to process a macroblock is 478 cycles. In order to verify the our design, reference-C encoder, which is compatible to JM 9.4, is developed and the designed controller is verified by using the test vector generated from the reference C code. The number of cycle in the designed DMA controller is reduced by 40% compared with the cycle of using Xilinx MIG.
A New Concept of Sand Production Prediction: Theory and Laboratory Experiments

Conventional theories of sand production prediction distinguish between compressive (shear) cavity (perforation, borehole) failure, induced by a combination of in-situ stress and drawdown, and tensile cavity failure, induced by the near-cavity pore pressure gradient. This paper shows, using bifurcation theory, that the preference for either compressive or tensile cavity failure only depends on cavity size and on the constitutive properties of the rock, and not on effective near-cavity stress or pore pressure gradient. It is shown that {open_quote}large{close_quote} cavities (e.g. boreholes) always fail in compression rather than in tension. Only for sufficiently small cavities (e.g. perforations) in weak, moist sandstones, compressive failure is suppressed, and tensile failure is possible. The above results deviate significantly from previous sand production prediction concepts. They are further supported by laboratory sand production experiments with {open_quote}large{close_quote} cavities, where sand failure was only observed for near-cavity effective stresses above a certain threshold, independent of applied drawdown (i.e. flow rate). The experiments exhibited no correlation between the (non-) occurrence of sand production and drawdown. From these results, it may be concluded that the primary role of fluid flow in sand production is the transport of loose sand (debris) resulting from compressive failure, rather than failure of themore » intact sandstone itself. « less
Information Retrieval from Civil Engineering Repositories: Importance of Context and Granularity

AbstractInformation about the design and construction of buildings can be structured in a particular way. This is especially correct given the increasing complexity of building product models and the emergence of building information models with project documents linked to them. In addition, engineers usually have distinct information needs. Research shows that engineers working with building information models place particular importance on the understanding of retrieved content before using it or applying it and that exploration of context is essential for this understanding. Both these factors (the nature of engineering content and the information needs of engineers) make general information retrieval techniques for computing relevance and visualizing search results less applicable in civil engineering information retrieval systems. This paper argues that granularity is a fundamental concept that needs to be considered when measuring relevance and visualizing search results in information retrieval sys.
Optimization of the deployment of temperature nodes based on linear programing in the internet of things

The Internet of Things emphasizes the concept of objects connected with each other, which includes all kinds of wireless sensor networks. An important issue is to reduce the energy consumption in the sensor networks since sensor nodes always have energy constraints. Deployment of thousands of wireless sensors in an appropriate pattern will simultaneously satisfy the application requirements and reduce the sensor network energy consumption. This article deployed a number of sensor nodes to record temperature data. The data was then used to predict the temperatures of some of the sensor node using linear programming. The predictions were able to reduce the node sampling rate and to optimize the node deployment to reduce the sensor energy consumption. This method can compensate for the temporarily disabled nodes. The main objective is to design the objective function and determine the constraint condition for the linear programming. The result based on real experiments shows that this method successfully predicts the values of unknown sensor nodes and optimizes the node deployment. The sensor network energy consumption is also reduced by the optimized node deployment.
An Enhancement in Service Broker Policy for Cloud- Analyst

Cloud computing means storing and accessing data and programs over the Internet instead of one’s personal computer's hard drive. The cloud is an analogy for the Internet. Now a day, it becomes very popular due to new trend and technology. It deals with large amount of data, so, it is necessary to simulate the behavior of cloud in real time environment. For this purpose, the simulation tool such as, cloud-analyst, cloudSim, are commonly used, which has been provided by laboratory CLOUD. The simulator cloud analyst uses different load balancing policy, service broker strategy with different parameters and has used as per requirement. This paper presents an improvement in service broker strategy, which enhances the performance of data center.
A TCP-Aware Link Layer Protocol Based on Selective-repeat ARQ with No Resequencing

A link layer protocol based on SR (Selective-Repeat) ARQ (Automatic Repeat reQuest) is required to achieve high performance over a lossy and large delay link. In spite of its effectiveness, SR ARQ has problems of large resequencing delay and bursty packet output due to the resequencing function. To mitigate these problems, this paper proposes a scheme where the resequencing is not performed by a receiver of SR ARQ, but by TCP end to end. The proposed scheme has advantages of scalability with regard to link bandwidth, the number of TCP connections on the link, and the size of the TCP window. It also preserves the end-to-end semantics of TCP and requires no modification to the existing TCP. To suppress unnecessary retransmissions by TCP, a sender of SR ARQ is aware of retransmitted TCP data packets and drops duplicate ACKs due to out-of-order packets, which are caused by the lack of resequencing by SR ARQ. The effectiveness of this proposed scheme is evaluated by simulations, which show that it attains high performance in comparison with other schemes.
Complexity of computing reachable workspaces for redundant manipulators

The complexity ofcomputing 3D workspaces forjoint limited redundant manipulators is examined. Different types of reachable workspace volume and reachable workspace boundary problems are defined. Each type of volume problem is at least as hard as its corresponding type of boundary problem and each problem type is at least NP hard. New efficient and adaptive workspace point computation techniques are proposed (e. g. based on nonlinear programming) after complexity analyses of the corresponding decision problems.
Combining Musicological Knowledge About Chords and Keys in a Simultaneous Chord and Local Key Estimation System

In this paper, we present a probabilistic framework for the simultaneous estimation of chords and keys from audio. The framework is formulated in terms of acoustic models for both keys and chords, and a prior model that contains musicological knowledge about chords and keys. The latter consists of a compound of four components: a duration and a change model for both keys and chords. This division allows us to modify each of the components separately and to choose the most appropriate sources of knowledge for each of them. Furthermore, this makes it easier to interpret their role and their relevance in the estimation procedure. We compared multiple configurations of our system, increasing in complexity. This has permitted us to explore the relation between keys and chords, and the importance of integrating prior musicological knowledge into an automatic estimation system. It was found that chord estimation scores mostly depend on the integration of durational knowledge, while key estimation also requires prior information about the broader context.