Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive IEEE 802.15.4 MAC for Throughput and Energy Optimization

IEEE 802.15. 4 defines a popular MAC standard for wireless sensor and actuator networks. With the default parameters, under medium to high load, 802.15. 4 generates excessive collisions and packet losses. Low duty cycles even exacerbate the problem, because more nodes become active after long periods of sleep and contend for channel access. In this paper, we have applied the models that led to the Idle Sense access method for 802.11 to the 802.15. 4 slotted CSMA/CA, taking into account the central role of the coordinator and also the bursty nature of the traffic. Surprisingly, the approach perfectly applies to 802.15. 4 even if the principles of the two access methods fundamentally differ. Based on the model, we propose ABE, an adaptation method that adjusts the contention window to optimal values so that the network obtains high throughput along with low duty cycles leading to low energy consumption. The method converges to near-optimal backoff values even under bursty traffic and for any number of contending nodes.
Multi wavelength study of the gravitational lens system RXS J1131-1231. II. Lens model and source reconstruction

Aims. High angular resolution images of the complex gravitational lens system RXS J1131-1231 (a quadruply imaged AGN with a bright Einstein ring) obtained with the Advanced Camera for Surveys and NICMOS instruments onboard the Hubble Space Telescope are analysed to determine the lens model and to reconstruct the host galaxy. Methods. The lens model is constrained by the relative astrometric positions of the lens and point-like images, and by the extended lensed structures. The non-parametric light distribution is recovered in the source plane by means of back ray-tracing. Results. 1- Precise astrometry and photometry of the four QSO lensed images (A-D) and of the lensing galaxy (G) are obtained. They are found in agreement with an independent study presented in a companion paper. The position and colours of the X object seen in projection close to the lens are found to be only compatible with a satellite galaxy associated with the lens. 2- The Singular Isothermal Ellipsoid plus external shear provides a good fit of the astrometry of images A-D. The positions of extended substructures are also well reproduced. However an octupole ($m=4$) must be added to the lens potential in order to reproduce the observed lens position, as well as the $I_{\rm B}/I_{\rm C}$ point-like image flux ratio. The ellipticity and orientation of the mass quadrupole are found similar to those of the light distribution, fitted by a Sersic profile. The lens ($z=0.295$) is found to be a massive elliptical in a rich environment and showing possible evolution with respect to $z=0$. 3- The host galaxy ($z=0.658$) is found to be a substantially magnified ($M\sim 9$) luminous Seyfert 1 spiral galaxy. The angular resolution is sufficient to see regions where stars are intensively forming. Interaction with a closeby companion is also observed. 4- Finally, in the case of RXS J1131-1231, extended lensed structures do not help much in constraining the lens model.
Password Authentication Schemes: Current Status and Key Issues

Password authentication is one of the simplest and the most convenient authentication mechanisms to deal with secret data over insecure networks. It is more frequently required in areas such as computer networks, wireless networks, remote login systems, operation systems, and database management systems. In this paper, we shall present the result of our survey through all currently available password-authentication-related schemes and get them classified in terms of several crucial criteria. To be critical, most of the existing schemes are vulnerable to various attacks and fail to serve all the purposes an ideal password authentication scheme should. In order to see how different password authentication schemes compare in different situations, we define all possible attacks and goals that an ideal password authentication scheme should withstand and achieve. We should hope that the attacks and goals we offer here can also help future researchers develop better schemes.
Autonomous Camera Control by Neural Models in Robotic Vision Systems

Recently there has been growing interest in creating large-scale simulations of certain areas in the brain. The areas that are receiving the overwhelming focus are visual in nature, which may provide a means to compute some of the complex visual functions that have plagued AI researchers for many decades; robust object recognition, for example. Additionally, with the recent introduction of cheap computational hardware capable of computing at several teraflops, real-time robotic vision systems will likely be implemented using simplified neural models based on their slower, more realistic counterparts. This paper presents a series of small neural networks that can be integrated into a neural model of the human retina to automatically control the white-balance and exposure parameters of a standard video camera to optimize the computational processing performed by the neural model. Results of a sample implementation including a comparison with proprietary methods are presented. One strong advantage that these integrated subnetworks possess over proprietary mechanisms is that ‘attention’ signals could be used to selectively optimize areas of the image that are most relevant to the task at hand.
Optimal Ordering Policy with Stock-Dependent Demand Rate Under Retailer’s Two Stages Trade Credit Financing Using Discounted Cash Flow (DCF) Approach

Many researchers have assumed one stage trade credit financing. In this study, we considered two levels of trade credit policy using Discounted Cash Flow (DCF) approach. Demand rate is considered to be stock-dependent for the first level (credit demand) and constant for second level (cash demand). Mathematical models are derived under two different circumstances i.e., case I: The permissible delay period is less than or equal to the cycle time and case II: The permissible delay period is greater than or equal to the cycle time for settling the account. An algorithm is provided to determine the optimal order quantity and annual profit. In addition, numerical examples are presented to demonstrate the solution process. Finally, sensitivity analysis of the optimal solution is discussed with respect to different parameters.
Safety Assessment of Mainstream Smoke of Herbal Cigarette

Owing to the increase in price of cigarettes in Korea, herbal cigarettes have received increasing attention as a non-smoking aid; however, its safety has hardly been studied. We analyzed some of the toxic components in the mainstream smoke of herbal cigarettes, performed a mutagenicity test on smoke condensates for safety assessment, and compared the results with the corresponding values of a general cigarette with the same tar content. Herbal cigarette “A” was smoked using automatic smoking machine under ISO conditions in a manner similar to general cigarette “T”. The tar content measured was higher than that inscribed on the outside of a package. The mainstream smoke of herbal cigarette “A” did not contain detectable levels of tobacco-specific nitrosamines and nicotine. Carbon monoxide and benzo(α)pyrene contents in herbal cigarette “A” were higher than those in the general cigarette “T”. The phenolic contents such as hydroquinone, resorcinol, and catechol in herbal cigarette “A” were higher than those in the general cigarette “T”, but cresol contents in herbal cigarette “A” were lower than those in the general cigarette “T”. The content of aromatic amines such as 4-aminobiphenyl in herbal cigarette “A” was higher than that in the general cigarette “T”; however, this difference was not statistically significant. On the other hand, 1-aminonaphthalene, 2-aminonaphthalene, and 3-aminobiphenyl contents in herbal cigarette “A” were lower than those in the general cigarette “T”. The smoke condensates of herbal cigarette “A” exhibited a higher mutagenic potential than the condensates from the general cigarette “T” at the same concentration. We concluded that the mainstream smoke of herbal cigarette contains some toxic components, the smoke condensates of herbal cigarettes are mutagenic similar to general cigarette because of combustion products, and that the evaluation of the chemical and biological safety of all types of herbal cigarettes available on the market.
Left-right party ideology and government policies: A meta-analysis

This paper summarizes how the partisan influence literature assesses the relationship between the left-right party composition of government and policy outputs through a meta-analysis of 693 parameter estimates of the party-policy relationship published in 43 empirical studies. Based on a simplified `combined tests' meta-analytic technique, we show that the average correlation between the party composition of government and policy outputs is not significantly different from zero. A mutivariate logistic regression analysis examines how support for partisan theory is affected by a subset of mediating factors that can be applied to all the estimates under review. The analysis demonstrates that there are clearly identifiable conditions under which the probability of support for partisan theory can be substantially increased. We conclude that further research is needed on institutional and socio-economic determinants of public policy.
A Comprehensive Study in Benchmarking Feature Selection and Classification Approaches for Traditional Malay Music Genre Classification

Machine learning techniques for automated musical genre classification are currently widely studied. With large collections of digital musical files, one approach to classification is to classify by musical genres such as pop, rock and classical in Western music. Beat, pitch and temporal related features are extracted from audio signals and various machine learning algorithms are applied for classification. Features that resulted in better classification accuracies for Traditional Malay Music (TMM), in comparison to western music, in a previous study were beat related features. However, only the J48 classifier was used and in this study we perform a more comprehensive investigation on improving the classification of TMM. In addition, feature selection was performed for dimensionality reduction. Classification accuracies using classifiers of varying paradigms on a dataset comprising ten TMM genres were obtained. Results identify potentially useful classifiers and show the impact of adding a feature selection phase for TMM genre classification.
Consequences of the Combined α-tocopherol, Ascorbic Acid and α-lipoic Acid on the Glutathione, Cholesterol and Fatty Acid Composition in Muscle and Liver of Diabetic Rats

Objective(s): Our objective was to evaluate the effects of a triple antioxidant combination [α-tocopherol (AT), ascorbic acid (AA) and α-lipoic acid (LA); AT+AA+LA] on the cholesterol and glutathione levels, and the fatty acid composition of liver and muscle tissues in diabetic rats. Materials and Methods: Forty-three Wistar rats were randomly divided into five groups. The first group was used as a control. The second, third and fourth groups received STZ (45 mg/kg) in citrate buffer. The fourth and fifth groups were injected with intraperitoneal (IP) 50 mg/kg DL-AT and 50 mg /kg DL-LA four times per week and received water-soluble vitamin C (50 mg/kg) in their drinking water for a period of six weeks. Results: Liver cholesterol levels in the AT+AA+LA group were lower than the control (P<0.05). Glutathione level was lower in D-2 (P<0.05) and were higher in D+AT+AA+LA and AT+AA+LA groups than the control groups (P≤ 0.05). The muscle cholesterol levels in the D-1 and D+AT+AA+LA groups were higher than the control group (P≤ 0.05). The levels of oleic acid were higher in the D-1 group and lower in the D-2 group (P<0.001). The arachidonic acid level in the D-1 and D-2 groups were lower (P<0.05), and higher in the D+AT+AA+LA group. Conclusion: Our results revealed that glutathione levels and the Stearoyl CoA Desaturase enzyme products in liver tissues of diabetic and non-diabetic rats were increased by triple antioxidant mixture.
Efficient Gait-based Gender Classification through Feature Selection

Apart from human recognition, gait has lately become a promising biometric feature also useful for prediction of gender. One of the most popular methods to represent gait is the well-known Gait Energy Image (GEI), which conducts to a high-dimensional Euclidean space where many features are irrelevant. In this paper, the problem of selecting the most relevant GEI features for gender classification is addressed. In particular, an ANOVA-based algorithm is used to measure the discriminative power of each GEI pixel. Then, a binary mask is built from the few most significant pixels in order to project a given GEI onto a reduced feature pattern. Experiments over two large gait databases show that this method leads to similar recognition rates to those of using the complete GEI, but with a drastic dimensionality reduction. As a result, a much more efficient gender classification model regarding both computing time and storage requirements is obtained.
Inference and Computation for Stochastic Volatility Models related to Option Pricing

This paper reviews the Black-Scholes theory and studies a number of extensions. In particular, we focus on logarithmic stochastic volatility (SV) models and square-root SV models with jumps. Inference on those models, using Markov chain Monte Carlo methods, is summarized. Generalized Black-Scholes (GBS) pricing formulas are presented as an important step in calibration of SV models using both return and option data. A Gaussian approximation scheme is proposed to significantly reduce the dimensionality of certain stochastic integrals involved in the GBS formulas, which shows a great promise in improving computational efficiency.
Identification of a chemical process for fault detection application

This paper presents the application results concerning the fault detection of a dynamic process using linear system identification and model-based residual generation techniques. The first step of the considered approach consists of identifying different families of linear models for the monitored system in order to describe the dynamic behaviour of the considered process. The second step of the scheme requires the design of output estimators (e.g., dynamic observers or Kalman filters) which are used as residual generators. The proposed fault detection and system identification schemes have been tested on a chemical process in the presence of sensor, actuator, component faults and disturbance. The results and concluding remarks have been finally reported.
Simple performance models of differentiated services schemes for the Internet

Schemes based on the tagging of packets have been proposed as a low-cost way to augment the single class best effort service model of the current Internet by including some kind of service discrimination. Such schemes have a number of attractive features, however, it is not clear exactly what kind of service they would provide to applications. Yet quantifying such service is very important to understand the benefits and drawbacks of the different tagging schemes and of the mechanisms in each scheme (for example how much RED with input and output (RIO) contributes in the assured scheme), and to tackle key performance and economic issues (e.g. the difference in tariff between different service classes would presumably depend on the difference in performance between the classes). The goal in this paper is to obtain a quantitative description of the service provided by tagging schemes. Specifically, we describe and solve simple analytic models of two previously proposed schemes, namely the assured service scheme and the premium service scheme. We obtain expressions for performance measures that characterize the service provided to tagged packets, the service provided to non-tagged packets, and the fraction of tagged packets that do not get the better service they were supposed to. We use these expressions, as well as simulations and experiments from actual implementations, to illustrate the benefits and shortcomings of the schemes.
Qualification de l’emploi, surqualification et rémunération horaire : les mères québécoises sont-elles avantagées par rapport aux mères ontariennes ?

Dans cet article, l’auteur trace un portrait evolutif et comparatif de la situation des meres quebecoises et ontariennes sur le marche du travail a partir d’indicateurs lies a la qualification des emplois, la surqualification et la remuneration. Il ressort de l’analyse que les meres au Quebec apparaissent avoir une situation plus favorable que celles de l’Ontario en etant moins presentes dans l’emploi moins qualifie et en etant aussi moins touchees par le phenomene de la surqualification. De plus, les meres quebecoises se retrouvent moins frequemment a occuper des emplois faiblement remuneres et sont souvent en meilleure posture que leurs homologues de l’Ontario lorsque la comparaison est faite avec les peres. Toutefois, l’enjeu de l’acces aux emplois les mieux remuneres et celui lie au temps de travail demeurent presents dans les deux groupes compares par rapport aux peres.
Efficiency analysis with interval-scale data based on separating hyperplane of decision making units

The traditional data envelopment analysis (DEA) model can evaluate the relative efficiencies of a set of decision making units (DMUs) with ratio scale inputs and outputs, but it cannot handle interval scale data. This study develop an approach to efficiency analysis to deal with both interval-scale data and ratio scale data. This approach introduces a measure of inefficiency and identifies efficient units as is done in DEA models with VRS technology. The basic idea in the approach is to obtain a separating hyperplane of DMUs so that the hyperplane can separate the maximum number of DMUs whose performances are not better than a DMU under evaluation, from the rest of the DMUs. Performance measure is defined as a ratio of not-better units to all units. Also, this paper presents a relationship between the performance measures with those in DEA models with VRS technology.
Efficient Caching for IP Lookups

IP address lookups form a critical component of the internet routing infrastructure. Typically based on trie-based structures and related extensions, the problem has several similarities to other applications of dictionaries in data compression, information retrieval, etc. The extreme need for speed in IP lookups has prompted considerable research in development of appropriate data structures, and algorithmic and architectural innovations. Relatively less attention has focused on optimally utilizing available hardware for performance. This paper addresses the problem of cache optimizations for IP lookups and other applications of trie-based structures. We present a technique, called Minimum Average Path Enumeration (MAPLE) that relies on lookup traces to optimize cache hit ratios for a single-level LRU cache. We extend this method to multilevel caches and present a novel prefetching scheme that works in conjunction with MAPLE. We show experimentally in the context of 4and 8-way associative caches that our techniques yield performance close to optimal for any cache replacement policy. This result is of considerable significance since, in addition to providing considerable speedups (up to 56%) over conventional trie memory placement techniques, it shows that (approximations to) LRU caches are near-optimal for this application.
On a Relationship between the Correct Probability of Estimation from Correlated Data and Mutual Information

Let $X$, $Y$ be two correlated discrete random variables. We consider an estimation of $X$ from encoded data $\varphi(Y)$ of $Y$ by some encoder function $\varphi(Y)$. We derive an inequality describing a relation of the correct probability of estimation and the mutual information between $X$ and $\varphi(Y)$. This inequality may be useful for the secure analysis of crypto system when we use the success probability of estimating secret data as a security criterion. It also provides an intuitive meaning of the secrecy exponent in the strong secrecy criterion.
Anticipatory grieving among parents living with a child with cancer.

AIM This paper is a report of a comparative study of anticipatory grief of parents of children newly diagnosed with cancer and those whose children were diagnosed 6-12 months earlier. BACKGROUND Public perceptions of cancer as a fatal illness persist despite improved prognosis for children. Parents may experience feelings of despair, hopelessness, and worthlessness - the most common psychological expressions of anticipatory grief. With a focus on developing more effective therapeutic intervention, healthcare professionals have developed greater interest in the concept of anticipatory grief. METHOD One hundred and forty parents, divided between 'newly diagnosed' and '6-12 months after diagnosis' groups, were recruited in 2006 from two hospitals representative of the healthcare sector in Jordan. Structured interviews were conducted to assess anticipatory grief, using the Marwit and Meuser Caregiver Inventory: Childhood Cancer. Analysis was performed using t-tests. RESULTS Fewer than half of the parents in both groups reported being at peace with themselves and their situation in life. Parents of newly diagnosed children reported more severe anticipatory grief responses than those in the second group. No statistically significant differences were found in responses between mothers and fathers. CONCLUSION Healthcare professionals should encourage parents to discuss negative feelings related to their child's illness and potential outcome. Hospital policies need to include the provision and promotion of support group services for parents, and nurses should encourage parents to exploit such services.
Uncovering Potential Attribute Relevance via MIA-Processing in Data Mining

The purpose of a classification learning algorithm is to accurately and efficiently map an input instance to an output class label, according to a set of labeled instances. In which data preprocessing, especially feature selection (FS) and continuous feature discretization (CFD), are considered as the significant issues. Since the quality of the data highly affects the result of a learning problem. Especially in medical domain, symptoms are interacted with each other; a compound symptom always could reveal more accurate diagnostic results. Therefore, a useless attribute by itself may become potentially relevant by providing hidden supportive information to other attributes. In this paper, our MIA-processing methods focus on uncovering hidden attributes relevance during FS and CFD. Our methods hence minimize the uncertainty and at the same time maximize the final classification accuracy. The empirical results demonstrate a comparison of performance of various classification algorithms on several real-life datasets from UCI repository
An algorithm for counting circuits: application to real-world and random graphs

We introduce an algorithm which estimates the number of circuits in a graph as a function of their length. This approach provides analytical results for the typical entropy of circuits in sparse random graphs. When applied to real-world networks, it allows to estimate exponentially large numbers of circuits in polynomial time. We illustrate the method by studying a graph of the Internet structure.