Miracle-dz/UniFAR-FTUs huggingface dataset:
Public Key Authentication Schemes for Local Area Networks

The invention of public-key cryptography makes many new network applications, such as electronic commerce (CE), possible. However, the widely used Internet is open and unprotected. Therefore, verifying the legitimacy of an individual's public key is very important. Most of the key authentication schemes require one or more trustworthy authorities to authenticate the key of a user. Consequently, the system security is mainly dependent on the honesty of these third parties. Unfortunately, a security solution in wide area networks (for example, the Internet) often cannot be applied to local area networks directly without any modification. Sometimes, a complete rebuild is necessary, especially for performance criteria consideration. In this paper, we propose two simple key authentication schemes that require no certification authorities for computer systems in local area networks, in which a host is responsible for user authentication and it uses a designated password authentication mechanism.
DC-DC Converters Using PID Controller and Pulse Width Modulation Technique

This paper presents a boost converter along with a flyback converter. The Zero Voltage Switching (ZVS) technique is used to achieve soft switching. A bidirectional boost converter is connected with an output module as a Parallel Input Serial Output configuration. The flyback converter with Voltage Doubler Rectifier (VDR) acts as an output module. This connection makes a bidirectional boost converter an active clamp circuit which is connected to the output side in order to extend the step up ratio. A converter with active clamp technique is used to recycle the leakage energy, to eliminate voltage spike due to coupled inductors and also to provide a mechanism to achieve ZVS. To overcome the efficiency degradation during light load due to load dependent soft switching of the ZVS, a control method using Pulse Width Modulation (PWM) proportional to the load current is used.
Performance analysis of FTDSR and AOTDV trust based routing protocols

Ad hoc networks, due to their spontaneous nature, are frequently established in insecure environments and hence become prone to attacks. These attacks are due to the participation of malicious nodes in the network. Routing protocols are a common target of these nodes. A variety of secure routing protocols have been proposed, that make routes secure using cryptographic algorithms. However, in doing so, these protocols need a number of rudiments in both the network establishment and operation phases. In contrast, by observing the honesty in participation by other nodes, trust-based routing protocols discover trusted rather than secure routes in the network. These protocols thus allow rapid deployment along with a vigorously adaptive operation, which conforms to the present network situation. In this paper, we conduct the performance evaluation of four reactive routing protocols in a network with varying speed, network dimension and number of malicious nodes. With the help of comprehensive simulations, we demonstrate that the performance of these protocols is analyzed using Packet delivery ratio, Throughput, End-to-End Delay and Routing Load under similar attacks, traffic, and mobility conditions. However, each routing protocol has its own peculiar advantage making it suitable for application in a particular unplanned environment.
Ondansetron-droperidol combination vs. ondansetron or droperidol monotherapy in the prevention of postoperative nausea and vomiting

Introduction Laparoscopic cholecystectomy is associated with a high incidence of postoperative nausea and vomiting. In this study we investigated comparatively the efficacy of combination therapy with ondansetron plus droperidol versus monotherapy with each agent alone in preventing postoperative nausea and vomiting following elective laparoscopic cholecystectomy. Material and methods One hundred twenty-seven patients who underwent elective laparoscopic cholecystectomy under general anesthesia were included in the study, and assigned to one of the following three groups according to the antiemetic drug given intravenously at the end of the surgery: droperidol 1.25 mg in group D, ondansetron 4 mg in group O, and a combination of droperidol and ondansetron at the doses mentioned above in group D + O. Incidence of postoperative nausea and vomiting, and doses of given rescue antiemetics were recorded during the first postoperative day. The total drug cost per patient spent for postoperative nausea and vomiting management (including prophylactic antiemetics plus rescue postoperative antiemetics) was calculated. Results Combination therapy significantly reduced postoperative nausea and vomiting at 30 min, 3 h and 6 h after surgery compared with group D (p < 0.01 for all time points) and O (p < 0.01 at 30 min, p < 0.05 at 3 h) and required less rescue antiemetic treatment (p < 0.01). Total antiemetic cost analyses revealed no significant differences among the three groups (p > 0.05). Conclusions Pretreatment with ondansetron plus droperidol is more effective than monotherapy in preventing postoperative nausea and vomiting following laparoscopic cholecystectomy, without increasing the cost comparatively.
Using structural relations for checking combinationality of cyclic circuits

Functionality and combinationality are two main issues that have to be dealt with in cyclic combinational circuits, which are combinational circuits containing loops. Cyclic circuits are combinational if nodes within the circuits have definite values under all input assignments. For a cyclified circuit, we have to check whether it is combinational or not. Thus, this paper proposes an efficient two-stage algorithm to verify the combinationality of cyclic circuits. A set of cyclified IWLS 2005 benchmarks are performed to demonstrate the efficiency of the proposed algorithm. Compared to the state-of-the-art algorithm, our approach has a speedup of about 4000 times on average.
Svm Models for Diagnosing Balance Problems Using Statistical Features of the Mtc Signal

Trip-related falls are a major problem in the elderly population and research in the area has received much attention recently. The focus has been on devising ways of identifying individuals at risk of sustaining such falls. The main aim of this work is to explore the effectiveness of models based on Support Vector Machines (SVMs) for the automated recognition of gait patterns that exhibit falling behavior. Minimum toe clearance (MTC) during continuous walking on a treadmill was recorded on 10 healthy elderly and 10 elderly with balance problems and with a history of tripping falls. Statistical features obtained from MTC histograms were used as inputs to the SVM model to classify between the healthy and balance-impaired subjects. The leave-one-out technique was utilized for training the SVM model in order to find the optimal model parameters. Tests were conducted with various kernels (linear, Gaussian and polynomial) and with a change in the regularization parameter, C, in an effort to identify the optimum model for this gait data. The receiver operating characteristic (ROC) plots of sensitivity and specificity were further used to evaluate the diagnostic performance of the model. The maximum accuracy was found to be 90% using a Gaussian kernel with σ2 = 10 and the maximum ROC area 0.98 (80% sensitivity and 100% specificity), when all statistical features were used by the SVM models to diagnose gait patterns of healthy and balance-impaired individuals. This accuracy was further improved by using a feature selection method in order to reduce the effect of redundant features. It was found that two features (standard deviation and maximum value) were adequate to give an improved accuracy of 95% (90% sensitivity and 100% specificity) using a polynomial kernel of degree 2. These preliminary results are encouraging and could be useful not only for diagnostic applications but also for evaluating improvements in gait function in the clinical/rehabilitation contexts.
Essays on banking, credit and interest rates

This paper addresses three questions. Why do Central Banks change targeted interest rates so seldomly? Can we model the weekly behavior of a targeted interest rate? What are the driving forces behind rate changes? This paper takes the point of view that Central Banks face a fixed cost when adjusting a targeted interest rate and therefore smoothe it by using a discrete policy rule. When modeling interest rate behavior this discrete nature is taken into account by applying a grouped data model to a Swedish data set. Changes in unemployment, inflation, retail sales, industrial production, money growth and U.S. and German interest - and exchange rates are shown to determine Swedish repo rate changes. Probabilities of the target rate being raised, lowered or kept constant are computed. The model has a prediction rate of 88% versus 78% for the best naive estimator.
Dopamine Modulates Release from Corticostriatal Terminals

Normal striatal function is dependent on the availability of synaptic dopamine to modulate neurotransmission. Within the striatum, excitatory inputs from cortical glutamatergic neurons and modulatory inputs from midbrain dopamine neurons converge onto dendritic spines of medium spiny neurons. In addition to dopamine receptors on medium spiny neurons, D2 receptors are also present on corticostriatal terminals, where they act to dampen striatal excitation. To determine the effect of dopamine depletion on corticostriatal activity, we used the styryl dye FM1-43 in combination with multiphoton confocal microscopy in slice preparations from dopamine-deficient (DD) and reserpine-treated mice. The activity-dependent release of FM1-43 out of corticostriatal terminals allows a measure of kinetics quantified by the halftime decay of fluorescence intensity. In DD, reserpine-treated, and control mice, exposure to the D2-like receptor agonist quinpirole revealed modulation of corticostriatal kinetics with depression of FM1-43 destaining. In DD and reserpine-treated mice, quinpirole decreased destaining to a greater extent, and at a lower dose, consistent with hypersensitive corticostriatal D2 receptors. Compared with controls, slices from DD mice did not react to amphetamine or to cocaine with dopamine-releasing striatal stimulation unless the animals were pretreated with l-3,4-dihydroxyphenylalanine (l-dopa). Electron microscopy and immunogold labeling for glutamate terminals within the striatum demonstrated that the observed differences in kinetics of corticostriatal terminals in DD mice were not attributable to aberrant cytoarchitecture or glutamate density. Microdialysis revealed that basal extracellular striatal glutamate was normal in DD mice. These data indicate that dopamine deficiency results in morphologically normal corticostriatal terminals with hypersensitive D2 receptors.
Occupational Health Management in the Lead Industry: The Korean Experience

In 1967, the problem of occupational lead exposure came to public attention in Korea. Since then, regular progress has been made in lowering workplace lead exposures, instituting new workplace controls, and implementing health examinations of exposed workers. Past serious lead poisoning episodes made it possible to introduce biological monitoring programs on a voluntary basis in high-lead-exposure facilities in Korea. Industry-specific occupational health services for lead workers in Korea during the last 22 years can be categorized into three phases. During the first phase (1988-1993), efforts were directed at increasing awareness among workers about the hazards of lead exposure, biological monitoring of blood zinc protoporphyrin began, and a respiratory protection program was introduced. During the second phase (1994-1997), a computerized health management system for lead workers was developed, blood-lead measurement was added to biologic monitoring, and engineering controls were introduced in the workplace to lower air-lead levels to comply with air-lead regulations. Finally, during the third phase (1998-present), a new biomarker, bone-lead measurement by X-ray fluorescence, was introduced. Bone-lead measurement proved to be useful for assessing body burden and to demonstrate past lead exposure in retired workers. Occupational health service practice for lead workers, including the industry-specific group occupational health system, has brought considerable success in the prevention of lead poisoning and in reducing the lead burden in Korean lead workers during the last several decades. The successful achievement of prevention of lead poisoning in Korea was a result of the combined efforts of lead workers, employers, relevant government agencies, and academic institutes.
Analysis of Iterative Soft Inter-Cell Interference Cancellation in Cellular MC-CDMA

We address inter-cell interference cancellation (ICIC) within a cellular multi-carrier code division multiple access (MC-CDMA) downlink system. The iterative soft ICIC concept is based on the use of the log-likelihood ratios from the decoding process. This approach shows significant performance gains in the severe cell border area. The iterative ICIC scheme can approach the single-user bound, and therefore, eliminates almost the interference at the cell border. Analysis regarding the convergence behavior of the ICIC strategy to more than one interfering cell are given based on the extrinsic information of the iterative process. Furthermore, a strategy of choosing the strongest interferers to be canceled is investigated which reduces significantly the complexity of the cancellation algorithm.
Cross-modal categorisation of user-generated video sequences

This paper describes the possibilities of cross-modal classification of multimedia documents in social media platforms. Our framework predicts the user-chosen category of consumer-produced video sequences based on their textual and visual features. These text resources---includes metadata and automatic speech recognition transcripts---are represented as bags of words and the video content is represented as a bag of clustered local visual features. The contribution of the different modalities is investigated and how they should be combined if sequences lack certain resources. Therefore, several classification methods are evaluated, varying the resources. The paper shows an approach that achieves a mean average precision of 0.3977 using user-contributed metadata in combination with clustered SURF.
Clustering DNA methylation expressions using nonparametric beta mixture model

The problem of defining the clustering structure in DNA methylation expressions is considered. A Dirichlet process beta mixture model (DPBMM) is proposed that models the DNA methylation data array. The model allows automatic learning of the cluster structure parameters such as the cluster mixing proportion, the models of each cluster, and especially the number of clusters. To enable the learning, we proposed a Gibbs sampling algorithm for computing the posterior distributions, hence the estimates of the parameters. We investigate the performance of the proposed clustering algorithm via simulation.
Comparing ExoVis, Orientation Icon, and In-Place 3D Visualization Techniques

With large volume data sets, it can be difficult to visualize the data all at once. Multiple views can address this problem by displaying details in areas of interest while still keeping track of the global overview. Many “detail and context” techniques exist for volume data, but it is unclear when to use each one. We introduce a new class of methods called ExoVis, an alternative that balances trade-offs of existing techniques. We then heuristically compare ExoVis to existing methods to provide insight into when each technique is appropriate.
Seller Behavior in Stumpage Markets with Imperfect Information

Timber supply analysts often prescribe forest landowner behavior by assuming that owners schedule standing timber or "stumpage" sales to maximize the financial return to their investment in forest land and timber investment (USDA-Forest Service 1982; Hyde 1980; Samuelson 1976; McConnell et al. 1983; Pearse 1967). The primary alternative to this investment hypothesis is a utility maximization hypothesis (Binkley 1979) which maintains that stumpage is sold whenever the utility gained from the sales proceeds is greater than the utility gained from both having the trees for recreational, aesthetic, and other purposes and from holding the trees for future sale. Both of these maintained hypotheses presume the stumpage owner has full information about prices, costs and yields. Neither hypothesis assigns a significant role to the costs of obtaining the information needed to make the sale. Observation suggests that the sale of stumpage takes place in a market where information about quantity, quality, and value of product is costly to obtain. Quantity and quality are usually ascertained from a timber cruise which requires professional skill, training, time, and effort. Value is the result of a tallying process which requires both knowledge of how trees convert to logs and other stumpage products and information on the current prices of these products (Beuter 1971). Stumpage buyers, consulting foresters, and professional timberland managers acquire the necessary skills and knowledge to evaluate stumpage as part of their work. But nonindustrial private woodland owners seldom have the opportunity to develop comparable skills or knowledge. The resulting lack of information creates a situation in which the private nonindustrial owner must decide whether to expend time and money to gain stumpage sales information or to negotiate a stumpage sale with limited information. This paper seeks to develop a model of information acquisition and market behavior by timber owners who face revenue uncertainty. Information is chosen ex ante to maximize the expected utility of wealth, following the Sandmo (1971) approach. Acquired information "shapes" the owner's subjective probability distribution of sales revenue and also may affect the owner's assessment of the value of keeping the timber for recreational, investment, or other purposes. Optimality conditions for information acquisition are presented, and the circumstances in which the owner will find it desirable to collect information are explored. The sales decision of the optimally informed owner is then determined by a comparison between a received bid, the value of having the trees, and a critical bid derived from the optimized revenue distribution. The critical bid is defined as the value which leaves the individual indiffer-
Consumers’ Willingness to Pay for Bacteriophage Technology Treated Fresh Produce

The United States is remarkably safe, when it comes to food supply. Nevertheless, food can become contaminated with a variety of germs. According to reports by a food safety group of the Centers for Disease Control and Prevention, food-borne illness caused by bacteria such as E. coli and salmonella not only take a huge toll on American consumers’ health but they cost the United States an estimated $152 billion annually in health care and other losses. To curb this increasing phenomenon, there has been a reintroduction of bacteriophage in the treatment of bacteria on raw foods. This study utilized a survey questionnaire administered by telephone to consumers in four different states; Alabama, Georgia, North Carolina, and South Carolina. In this study, as in other willingness to pay studies, a binary Logit model was employed to estimate consumers’ WTP an additional amount for fresh produce treated with bateriophage technology. The Logit model expresses consumers’ WTP as a function of income, education, race, gender and geographical location (States). Based on the estimation results, income was found to be significant at the 5 percent level in determining a consumer’s WTP. In this particular study, Caucasians were willing to pay an additional amount relative to other races at the 10 percent significance level. Also, where a consumer lived (State) was found to be significant with consumers in the states of Georgia and North Carolina having higher WTP relative to Alabama and South Carolina.
Robust actuator fault detection for an induction motor via genetic-algorithm optimisation

In this study, an application of genetic algorithm optimization-based fault detection for an induction motor with actuator faults is addressed. The frequencies of the modelling errors are identified from the Fourier transform of the measurement outputs, and a multi-objective cost function is constructed for minimizing the effects from the dominant modelling errors components while maximizing the influences from the actuator faults to the residual. Abrupt faults and incipient faults are both investigated, also the effectiveness of the proposed fault detection methods are demonstrated by using experimental/simulation studies of the induction motor.
A Novel approach for clustering textual information in various emails using text data mining technique

Clustering is the technique used for data reduction. It divides the data into groups based on pattern similarities such that each group is abstracted by one or more representatives. Recently, there is a growing emphasis on exploratory analysis of very large datasets to discover useful patterns. This paper explains extracting the useful knowledge represented by clusters from textual information contained in a large number of emails for text and data mining techniques. E-mail data that are now becoming the dominant form of inter and intra organizational written communication for many companies. The sample texts of two mails are verified for data clustering. The cluster shows the similar emails exchanged between the users and finding the text similarities to cluster the texts. In this paper the use of Pattern similarities i.e., the similar words exchanged between the users by considering the different Threshold values are made for the purpose. The threshold value shows the frequency of the words used. The representation of data is done using a vector space model.
En busca de un buen marco de referencia predictivo para la inflación en Chile

En este articulo investigamos la precision y estabilidad de las proyecciones de corto plazo de la inflacion en Chile provenientes de una determinada subfamilia extendida de modelos SARIMA que denominamos ESARIMA. Las proyecciones ESARIMA son comparadas con las provenientes de encuestas y de simples modelos univariados, incluyendo algunos que han sido tradicionalmente utilizados como marcos de referencia predictivos en la bibliografia. Nuestros resultados indican que el error cuadratico medio fuera de muestra de las proyecciones ESARIMA es menor que el de los metodos univariados considerados, cuando el horizonte predictivo varia de 1 a 4 meses. En horizontes superiores, los peores representantes de nuestra familia ESARIMA comienzan a ser superados por los mejores marcos de referencia univariados. Al comparar con la encuesta de expectativas economicas, los resultados van en la direccion opuesta: la encuesta es mas precisa que la subfamilia ESARIMA en todos los horizontes. En general nuestros resultados son estadisticamente significativos a niveles de confianza usuales. Observamos tambien que la familia ESARIMA ofrece proyecciones mas estables que los marco de referencia univariados, pero menos estables que las provenientes de la encuesta de analistas.