Miracle-dz/UniFAR-FTUs huggingface dataset:
Business Process Models Quality : evaluation and improvement

In recent years the problems related to modeling and improving business processes have been of growing interest. Indeed, companies are realizing the undeniable impact of a better understanding and management of business processes (BP) on the effectiveness, consistency, and transparency of their business operations. BP modeling aims at a better understanding of processes, allowing deciders to achieve strategic goals of the company. However, inexperienced systems analysts often lack domain knowledge leading and this affects the quality of models they produce.Our approach targets the problem related to business process modeling quality by proposing an approach encompassing methods and tools for business process (BP) models quality measurement and improvement. We propose to support this modeling effort with an approach that uses domain knowledge to improve the semantic quality of BP models.The main contribution of this thesis is fourfold:1. Exploiting the IS domain knowledge: A business process metamodel is identified.Semantics are added to the metamodel by the mean of OCL constraints.2. Exploiting the application domain knowledge. It relies on domain ontologies. Alignment between the concepts of both metamodels is defined and illustrated.3. Designing of the guided quality process encompassing methods and techniques to evaluate and improve the business process models. Our process propose many quality constraints and metrics in order to evaluat the quality of the models and finally the process propose relevant recommendations for improvement.4. Development of a software prototype “BPM-Quality”. Our prototype implements all theabove mentioned artifacts and proposes a workflow enabling its users to evaluate andimprove CMs efficiently and effectively.We conducted a survey to validate the selection of the quality constraints through a first experience and also conducted a second experiment to evaluate the efficacy and efficiency of our overall approach and proposed improvements.
The Sustainability Practices and Its Effect on Financial Leakages of Star Classified Hotels in Ethiopia

The purpose of this study was to test the effects of sustainability practice on financial leakage. Furthermore, it has aimed at to investigate the effect of the reduction of financial leakage on competitive advantage of star classified hotels from managers’ perspective. A quantitative and cross-sectional approach was applied. Data were collected from all 242 star classified hotel & resorts using a survey questionnaire. To this end, after addressing data screening issues 201 of observations were left for this research analyses. CFA and SEM were applied to validate and to test the structural model respectively. The major findings were the higher sustainability practices of these star classified hotels could not more likely to reduced financial leakage of the studied star classified hotel in Ethiopia. Albeit, this research has brought a valuable insight on dimensions of financial leakage in star classified hotels/resorts has offered and the degree of sustainability practices and its implication for the reduction of financial leakage of star classified hotels in the country. Therefore, hotels in Ethiopia should give due attention for a better sustainability practices implementation so that financial leakage reduced greatly and finally competitiveness of these hotels enhanced.
Multidimensional Scaling Analysis of Controllers' Perceptions of Aircraft Performance Characteristics

Abstract : Thirty full performance level (FPL) en route air traffic control specialists participated in an investigation of the salient features of aircraft mix, a proposed sector complexity factor. Controllers rated the "familiarity" (i.e., frequency of encounter) of 30 selected aircraft. They also provided weight class, engine number, engine type, cruising speed, climb, and descent rate estimates for each aircraft. A matrix of squared Euclidean distances derived from summary estimates (i.e., means of speed, climb, and descent) was used to construct a multidimensional scaling model of the aircraft. Multiple regression interpretation revealed that Dimension 1 was related to engine type, whereas Dimension 2 was associated with weight class. The position of elements in the derived stimulus space indicated that controllers may develop performance-related prototypes through the use of multiple cues derived from a number of sources. Results are presented as justification for further investigation into potential advantages of providing enhanced prediction cues (e.g., engine type and weight class) from a single source, which may increase the efficiency of controller decision making and decrease perceived workload.
High Resolution Numerical Modelling of In-Vehicle Mobile Calls

The scenario of making a mobile phone call inside a vehicle is numerically modeled using a high resolution FDTD gridding; solved by a 3-D full-wave electromagnetic simulation software on a high performance workstation machine with Tesla GPU accelerator. The simulated mobile call inside a vehicle involved; a high resolution human head with shoulder phantom (VH_Head_Model 9), high resolution realistic hand model (posable right-hand), realistic mobile phone handset CAD-models with different antenna types and a vehicle CAD-model (big-sedan Camaro-brand). The impact of the in-vehicle mobile calls on the electromagnetic interaction of the handset antenna and human is anticipated at different operating frequencies, i.e., GSM-900 and GSM-1800, and different handset positions with respect to head, i.e., cheek and tilt-position. A significant degradation in the handset antenna performance was observed due to the presence of the vehicle body while making a mobile call inside. Nevertheless, no change in the peak spatial-average specific absorption rate in head tissues was detected while making a mobile call inside vehicle, as compared with the specific absorption rate due to the mobile call in free-space.
Optimization of Multi-Element Airfoils

Abstract : A review of techniques aimed at maximizing C1/Cd and C1 for multi- element airfoils showed the need for more exhaustive testing of possible configurations of flap deflection, slot geometry and airfoil angle of attack. For a typical 4-element airfoil, the number of possible configurations can easily be in the billions. A new technique, based on evolution strategy, has been developed for the problem of optimizing a multi-element airfoil with respect to its envelope of maximum C1/Cd versus C1. This technique was applied to an airfoil having a slotted leading edge flap and a double-slotted trailing edge flap using an existing computer program for 2D subsonic multi-element airfoils to provide values of aerodynamic coefficients. Although limitations of the program precluded the full determination of the envelope of C1/Cd vs C1 the problem of maximizing C1/Cd for a minimum C1 constraint was solved. The result of testing approximately 400 configurations generated by the random mutation- natural selection procedure of evolution strategy was an 8-fold increase in C1/ Cd iwth a 12% increase in C1 over the initial geometry.
Design of Programmable Baseband Filter for Direct Conversion

Recently, CMOS RF integration has been widely explored in the wireless communication area to save cost, power, and chip area. The direct conversion architecture, rather than a more conventional super-het-erodyne, has been an attractive choice for single-chip integration because of its many advantages. However, the direct conversion architecture has several fundamental problems to solve in achieving performance comparable to a super-heterodyne counterpart. In this paper, we describe a programmable filter for mobile communication terminals using a direct conversion architecture. The proposed filter can be implemented with the active-RC filter and programmed to meet the requirements of different communication standards, including GSM, DECT and WCDMA. The filter can be tuned to select a detail frequency by changing the gate voltage of the MOS resistors. The gain of the proposed architecture can be programmed from 27dB to 72dB using the filter gain and VGA in 3dB steps.
Synthesis and anti-Trypanosoma cruzi profile of the novel 4-thiazolidinone and 1,3-thiazole derivatives

Chagas disease is a serious public health problem in Brazil and world. Caused by the protozoan Trypanosoma cruzi, it is estimated 6-7 million people infected worldwide. The only drug used to treatment is Benzonidazole, but this drug is only effective in the acute phase of the disease. This paper reports the synthesis and the anti-Trypanosoma cruzi activity of 4-thiazolidinone and 1,3-thiazole derivatives based in thiosemicarbazones previously described as potent trypanocidal agent, planned through the bioisosterism strategy. Therefore, the synthesis of 28 aryl-4-thiazolidinones (2a-r and 3a-j) was achieved, which aryl ring possesses halogens atoms in meta and para positions, and the heterocyclic system had lipophilic substituents. These compounds were thus evaluated as anti-T. cruzi agents against epimastigote, trypomastigote and amastigote forms of T. cruzi. Compounds were also tested its toxicity in L929 fibroblasts. In view to investigate a bioisosteric relationship between 1,3-thiazoles and 4-thiazolidinones, eighteen 1,3thiazoles derived from trifluoromethyl thiosemicarbazone (4a-r) were also tested in the same model. It was possible to show that between the 46 tested compounds, those that possess a bromine (2a-r) atom showed better activity compared to compounds substituted by a trifluoromethyl group (3a-j) and to 1,3-thiazole derivatives (4a-r), which were inactive. In general, the 2a-r series showed low toxic profile in the cell line tested. Besides, compound 2h was the most active of then all when compared to the standard Benznidazole. *Correspondence to: Ana Cristina Lima Leite, Laboratório de Planejamento em Química Medicinal, Departamento de Ciências Farmacêuticas, Centro de Ciências da Saúde, Universidade Federal de Pernambuco, 50740-520, Recife, PE, Brazil, E-mail: acllb2003@yahoo.com. br
Reliability analysis of radiation induced fault mitigation strategies in field programmable gate arrays

This dissertation presents the results of engineering design and analysis of a radiation tolerant, static random-access-memory-based field programmable gate array reconfigurable computer system for use in space flight applications. A custom satellite platform was designed and developed at Montana State University. This platform facilitates research into radiation tolerant computer architectures that enable the use of commercial off-the-shelf components in harsh radiation environments. The computer architectures are implemented on a Xilinx Virtex-6 field programmable gate array, the configuration of which is controlled by a Xilinx Spartan-6 field programmable gate array. These architectures build upon traditional triple modular redundancy techniques through the addition of spare processing resources. The logic fabric is partitioned into discrete, reconfigurable tiles with three tiles active in triple modular redundancy and remaining tiles maintained as spares. A voter circuit identifies design-level faults triggering rapid switch to a spare tile. Blind or readback scrubbing prevents the accumulation of configuration memory faults. The design and results from a variety of integrated system tests are presented as well as a reliability analysis of the radiation effects mitigation strategy used in the system. The research questions addressed by this dissertation are: 1) Does the inclusion of spare circuitry increase system reliability? 2) How do single-points-of-failure affect system reliability? and 3) Does migrating single-points-of-failure to an older technology node (technology partitioning) offer an improvement in reliability?
Spectral possibility distribution of closed connected water and remote sensing statistical inference for lacustrine yellow substance

The traditional ocean color remote sensing usually focuses on using optical inversion models to estimate the properties of in-water components from the above-surface spectra, so we call it the spectrum-concentration (SC) scheme. Unlike the SC scheme, this study proposed a new research scheme, distribution-distribution (DD) scheme, which uses statistical inference models to estimate the possibility distribution of these in-water components, based on the possibility distribution of the observed spectra. The DD scheme has the advantages that (1) it can rapidly give the key and overview information of the interest water, instead of using the SC scheme to compute each image pixel, (2) it can assist the SC scheme to improve their models and parameters, and (3) it can provide more valuable information for better understanding and indicating the features and dynamics of aquatic environment. In this study, based on Landsat-8 images, we analyzed the spectral possibility distributions (SPD) of 688 global water and found many of them were normal, lognormal, and exponential distributions, but with diverse patterns in distribution parameters such as the mean, standard deviation, skewness and kurtosis. Furthermore, we used Monte-Carlo and Hydrolight simulations to study the theoretical and statistical connections between the possibility distributions of in-water components and SPDs. The simulation results were basically consistent with the observations on the real water. Then by using the simulation and ﬁeld measured data, we proposed a bootstrap-based DD scheme and developed some simple statistical inference models to estimate the distribution parameters of yellow substance in lakes. Since DD scheme is still on its early stage, we also suggested some potential and useful topics for the future work.
Chitosan capping enzyme-responsive hollow mesoporous silica nanoplatforms for colon specific drug delivery

In summary, an enzyme-responsive colon specific drug delivery system was developed based on hollow mesoporous silica sphere (HMSS), in which the biodegradable chitosan (CS) was gated on the openings of HMSS through cleavable azo bonds (HMSS-N=N-CS). Doxorubicin (DOX) was encapsulated into the hollow cavity and mesopores of HMSS, and HMSS-N=N-CS/DOX showed a high loading amount of 35.2%. X-ray diffraction (XRD) experiment proved that the DOX loaded in the HMSS-N=N-CS was in a non–crystalline state. In vitro drug release experiments proved that HMSS-N=N-CS/DOX showed an enzyme-responsive drug release property. The grafted CS could increase the biocompatibility and stability of HMSS, and reduce the protein adsorption on the surface of HMSS. The gastrointestinal mucosa irritation and cell cytotoxicity results indicated the good biocompatibility of HMSS and HMSS-N=N-CS. The confocal laser scanning microscope (CLSM) and flow cytometry technique (FCM) results indicated that the cellular uptake of DOX was obviously increased after the HMSS-N=N-CS/DOX was preincubated with colonic enzyme mixture. Cell viability result indicated that HMSS-N=N-CS/DOX incubated with colon enzyme showed an increased cytotoxicity and the IC50 value was three time less than that of HMSS-N=N-CS/DOX group. The present work will lay the foundation for subsequent research on mesoporous carriers for oral colon-specific drug delivery.
Sentiment Classification through Convolutional Neural Network Based Quick Sentiment Analysis

Sentiment Analysis (SA) is characterized as the region of study to analyze individuals' Sentiment, surveys, and mentalities from various languages or from web remarks. SA has spread to each conceivable space like budgetary, medicinal services, online items, internet business to get-togethers, media transmission, political causes and decisions. In the manuscript, a computerized framework, which forms a huge dataset of analysis for viewpoint based decisions is proposed. The sentiments are gathered by Natural Language Processing (NLP) and afterward it is assigned positive, impartial and negative. As the quantity of web information is exponentially expanding, it turns out to be increasingly imperative to create models to investigate the content information consequently. The text may contain different labels, for example, age, gender, nation, sentiment, review etc. Utilizing such labels may carry advantages to some modern fields, such huge numbers of investigations of classification of texts have showed up. As of late, the Convolutional Neural Network (CNN) has been utilized for the process of classification of text and has obtained better results. In the manuscript, Convolutional Neural Network based Quick Sentiment Analysis (CNN-QSA) is proposed for the assignment of sentiment classification. The most main reason for to utilize CNN in SA is that CNN can extract features from global data, and it can think about the relationship among these features. CNN has a convolutional layer to extract data by a larger part of text with convolutional neural system. The proposed CNN-QSA method is compared with the traditional methods and the results show that the proposed method is better than the traditional methods like SVM and Naive Bayes strategies.
Distinguishing Internet-facing ICS devices using PLC programming information

Abstract : The Shodan search engine reveals Industrial Control System (ICS) devices around the globe are directly connected to the Internet. After Shodan's inception in 2009, multiple news reports have focused on the increased threat to infrastructure posed by Shodan. While no attacks to date have been directly attributed to Shodan searches, its existence provides an anonymous reconnaissance platform that facilitates ICS targeting for those actors with both a desire and capability to carry out attacks. Recent research has demonstrated that simple search queries return thousands of ICS devices indexed by Shodan, and the number of newly indexed ICS devices is growing. This research discusses the method used to distinguish the Internet-facing ICS devices indexed by the Shodan search engine. PLC code is obtained by sending specifically crafted CIP request messages to the devices, capitalizing on the fact that authentication is not built in to the CIP application layer protocol. This data allows categorization of Internet-facing devices by comparing PLC code attributes. The results of this research show PLC code can be collected from Internet-facing ICS devices with no significant impact to task execution times. Also, this research demonstrates a method to distinguish Internet-facing ICS devices by function and by Critical Infrastructure sector. This capability develops an understanding of the function and purpose of ICS devices that are being connected to the Internet.
In Silico and In Vitro Study of Synthesized Derivatives of 2-aryl/3, 4-difluro aryl substituted 1, 3, 4-thidiazole-2-amine.

In this research article synthesized derivatives of 2-aryl/3,4-difluro aryl substituted 1,3,4thidiazole-2-amine were investigated in silico way by docked with selected drug target (Dihydrofolate reductase (DHFR); DNA Gyrase; Topoisomerase IV; S-adenosyl homocysteine nucleosidase) for anti-bacterial infections and Pencillin Binding Protein (PDB ID: 1VQQ) & Lanosterol 14 α-demethylase (PDB ID: 4LXJ) for anti-fungal activity. IC50 value and in micro molar levels binding energy is determined which showed potential activity when binded with ligand . NCIM provided culture is used to investigate in vitro activity Gram positive bacterial strains Staphallococcus aureus (Sa2178) Bacillus subtilis (Bs-2239) Gram negative bacterial strains Eschereschia coli (Ec-25744) Klibesiella aerogenus (Ka-2249) Antifungal strains are Aspergillus niger (An-504) and Penicillium Chrysogenum(Pc-709). The comparative study of these two investigated methods are explained. QSAR studies of synthesized derivatives were also highlight and support these investigations.
High Consistency of Structure-Based Design and X-Ray Crystallography: Design, Synthesis, Kinetic Evaluation and Crystallographic Binding Mode Determination of Biphenyl-N-acyl-β-d-Glucopyranosylamines as Glycogen Phosphorylase Inhibitors

Structure-based design and synthesis of two biphenyl-N-acyl-β-d-glucopyranosylamine derivatives as well as their assessment as inhibitors of human liver glycogen phosphorylase (hlGPa, a pharmaceutical target for type 2 diabetes) is presented. X-ray crystallography revealed the importance of structural water molecules and that the inhibitory efficacy correlates with the degree of disturbance caused by the inhibitor binding to a loop crucial for the catalytic mechanism. The in silico-derived models of the binding mode generated during the design process corresponded very well with the crystallographic data.
Establishment and Application of the Spatial Decomposition Method (SDM) for Tunnels Passing Through Large Karst Caves

Karst tunnels commonly pass through large karst caves during their construction and operation. Although treatment technologies are relatively mature, a systematic treatment method to guide the selection of treatment technologies is lacking. To solve this problem, a spatial decomposition method (SDM) of large karst caves is proposed that is based on analyzing the spatial relationship between tunnels and karst caves and summarizing the relevant treatment techniques. In this method, the space between the tunnel and the cavern is divided into eight parts using a space dividing line (SDL), which makes the spatial position relationship between the tunnel and cavern more intuitive. A geometric model of the SDM is established, and the numerical values of each geometric parameter are determined by field surveys and drawings. Constructing a three-dimensional spatial diagram by applying relevant parameters to the geometric model provides a reference for selecting a treatment technology. The SDM of the arch top, arch bottom, and two wings matching the treatment technology is proposed. Seven principles of technical selection—namely, safety, convenience, scientificity, sustainability, economy, feasibility, and openness—are mentioned in order to overcome the difficulty of technology selection due to such factors as technological diversity, materials, equipment, and environment. Finally, the SDM is used to solve the problem of the Shangyuan tunnel passing through a large karst cave. The implementation of the SDM in tunnel construction would represent a significant breakthrough and has important engineering value in solving the problem of tunnel passes through large karst caves.
Performance analysis of LSTM model with multi-step ahead strategies for a short-term traffic flow prediction

In this study, the effect of direct and recursive multi-step forecasting strategies on the short-term traffic flow forecast performance of the Long Short-Term Memory (LSTM) model is investigated. To increase the reliability of the results, analyses are carried out with various traffic flow data sets. In addition, databases are clustered using the k-means++ algorithm to reduce the number of experiments. Analyses are performed for different time periods. Thus, the contribution of strategies to LSTM was examined in detail. The results of the recursive based strategy performances are not satisfactory. However, different versions of the direct strategy performed better at different time periods. This research makes an important contribution to clarifying the compatibility of LSTM and forecasting strategies. Thus, more efficient traffic flow prediction models will be developed and systems such as Intelligent Transportation System (ITS) will work more efficiently. A practical implication for researchers that forecasting strategies should be selected based on time periods.
Insulated ECG electrodes

Insulated, capacitively coupled electrode does not require electrolyte paste for attachment. Other features of electrode include wide range of nontoxic material that may be employed for dielectric because of sputtering technique used. Also, electrode size is reduced because there is no need for external compensating networks with FET operational amplifier.