Miracle-dz/UniFAR-FTUs huggingface dataset:
Clustering Unsynchronized Time Series Subsequences with Phase Shift Weighted Spherical k-means Algorithm

Time series have become an important class of temporal data objects in our daily life while clustering analysis is an effective tool in the fields of data mining. However, the validity of clustering time series subsequences has been thrown into doubts recently by Keogh et al. In this work, we review this problem and propose the phase shift weighted spherical k -means algorithm (PS-WSKM in abbreviation) for clustering unsynchronized time series. In PS-WSKM, the phase shift procedure is introduced into the clustering process so that the phase problem is solved effectively. Meanwhile, the subsequences weights are assigned to subsequences to make the algorithm more robust. Experimental results on ECG datasets show that our approach is effective for the problem of unsynchronized time series subsequences clustering, which makes contributions to a wide range of applications, particularly in intelligent healthcare.
English to Yorùbá Machine Translation System using Rule-Based Approach

Rule-based approach is a good approach for Machine Translation System used for language with lots of grammar which Yorùbá language is one. In this paper we present Rule-based approach to Yorúbà Machine Translation System. The popularity of Yorúbà language among the three main languages in Nigeria calls for the need to computerise the language. Transfer Rule-Based Machine Translation is use in the development of the System. It was used because it allows us to use manual tagging of the part of speech (POS). Rewrite rules was developed for the two languages (Yorùbá and English). The data was collected from home domain vocabularies. The re-write rule was verified using Natural Language Toolkits (NLTKs) and implement using python programming language. The system interface gives the user the opportunity to type simple English language sentence and the resulting Yorùbá Translation is displayed. The result shows that the system performance is close to the expert opinion, having considered the scope for which the system is developed. Based on the result gathered there are some issues to address that could be considered in a future work. Keywords—Machine translation, Yorùbá language, rule-based approach, English language, sentence
Teachers' Appreciation of a Collaborative Environment on LOs

Learning Objects (LOs) can be a valuable tool to diffuse pedagogical innovation among teachers. We suggest that LOs repositories should be structured so to become a means to improve the pedagogical quality of teachers’ work, and motivate them to get involved both as users and co-constructors. In this paper we describe LODE (Learning Objects Discussion Environment) a collaborative environment where users share their experience on LOs by commenting the items in the repository, expliciting relations among them and contributing new LOs. A prototype was used with a group of trainee high school teachers. The outcomes of this experience show young teachers’ interest and appreciation for this approach.
PECDSA. How to build a DL-based digital signature scheme with the best proven security

Many variants of the ElGamal signature scheme have been proposed. The most famous is the DSA standard. If computing discrete logarithms is hard, then some of these schemes have been proven secure in an idealized model, either the random oracle or the generic group. We propose a generic but simple presentation of signature schemes with security based on the discrete logarithm. We show how they can be proven secure in idealized model, under which conditions. We conclude that none of the previously proposed digital signature schemes has optimal properties and we propose a scheme named PECDSA.
Evaluation of farm-level impacts of soil fertility management strategies in maize-bean farming systems in Uganda and Tanzania

We conducted an ex ante evaluation of soil fertility management strategies on soil organic matter (SOM), nitrogen balance, greenhouse gas (GHG) emissions, and profitability under three important scenarios: (1) inorganic fertilizers, (2) organic manure, and (3) combined organic manure and inorganic fertilizers. Focus group discussions and household surveys were used to collect data in Rakai, Uganda, and Lushoto, Tanzania. We assessed impact for three farm types (small scale, medium scale, and large scale) using a bioeconomic model: FarmDESIGN. Our main findings are as follows. First, whereas in Lushoto the combined use of organic manure and inorganic fertilizers contributed the most to SOM relative to the baseline for all farm types, in Rakai the same scenario had greater impacts for only mediumand large-scale farms. For small-scale farms, improvement in SOM mostly came from the use of inorganic fertilizers. Second, in both countries, nitrogen balance increased across all scenarios and farm types. Third, the increase in SOM and nitrogen balance was accompanied by an increase in GHG emissions, especially for scenarios with manure or combining manure and inorganic fertilizers. Fourth, impacts were mixed in terms of profitability. In Lushoto, Tanzania, the smallscale farm has the lowest operating profit, while the
Surrogate techniques for testing fraud detection algorithms in credit card operations

Banks collect large amount of historical records corresponding to millions of credit cards operations, but, unfortunately, only a small portion, if any, is open access. This is because, e.g., the records include confidential customer data and banks are afraid of public quantitative evidence of existing fraud operations. This paper tackles this problem with the application of surrogate techniques to generate new synthetic credit card data. The quality of the surrogate multivariate data is guaranteed by constraining them to have the same covariance, marginal distributions, and joint distributions as the original multivariate data. The performance of fraud detection algorithms (in terms of receiver operating characteristic (ROC) curves) using a varying proportion of real and surrogate data is tested. We demonstrate the feasibility of surrogates in a real scenario considering very low false alarm and high disproportion between legitimate and fraud operations.
Multimodularity and Its Applications in Three Stochastic Dynamic Inventory Problems

We apply the concept of multimodularity in three stochastic dynamic inventory problems in which state and decision variables are economic substitutes. The first is clearance sales of perishable goods. The second is sourcing from multiple suppliers with different lead times. The third is transshipment under capacity constraints. In all three problems, we establish monotone optimal polices with bounded sensitivity. Multimodularity proves to be an effective tool for these problems because it implies substitutability, it is preserved under minimization, and it leads directly to monotone optimal policies with bounded sensitivity.
Improving Traffic Locality in BitTorrent via Biased Neighbor Selection

Peer-to-peer (P2P) applications such as BitTorrent ignore traffic costs at ISPs and generate a large amount of cross-ISP traffic. As a result, ISPs often throttle BitTorrent traffic to control the cost. In this paper, we examine a new approach to enhance BitTorrent traffic locality, biased neighbor selection, in which a peer chooses the majority, but not all, of its neighbors from peers within the same ISP. Using simulations, we show that biased neighbor selection maintains the nearly optimal performance of Bit- Torrent in a variety of environments, and fundamentally reduces the cross-ISP traffic by eliminating the traffic’s linear growth with the number of peers. Key to its performance is the rarest first piece replication algorithm used by Bit- Torrent clients. Compared with existing locality-enhancing approaches such as bandwidth limiting, gateway peers, and caching, biased neighbor selection requires no dedicated servers and scales to a large number of BitTorrent networks.
Robust Distal Tip Cell Pathfinding in the Face of Temperature Stress Is Ensured by Two Conserved microRNAS in Caenorhabditis elegans

Biological robustness, the ability of an organism to maintain a steady-state output as genetic or environmental inputs change, is critical for proper development. MicroRNAs have been implicated in biological robustness mechanisms through their post-transcriptional regulation of genes and gene networks. Previous research has illustrated examples of microRNAs promoting robustness as part of feedback loops and genetic switches and by buffering noisy gene expression resulting from environmental and/or internal changes. Here we show that the evolutionarily conserved microRNAs mir-34 and mir-83 (homolog of mammalian mir-29) contribute to the robust migration pattern of the distal tip cells in Caenorhabditis elegans by specifically protecting against stress from temperature changes. Furthermore, our results indicate that mir-34 and mir-83 may modulate the integrin signaling involved in distal tip cell migration by potentially targeting the GTPase cdc-42 and the beta-integrin pat-3. Our findings suggest a role for mir-34 and mir-83 in integrin-controlled cell migrations that may be conserved through higher organisms. They also provide yet another example of microRNA-based developmental robustness in response to a specific environmental stress, rapid temperature fluctuations.
Error Free Iterative Morphological Decomposition Algorithm for Shape Representation

Problem statement: A generalized skeleton transform allows a shape to be represented as a collection of modestly overlapped octagonal shape parts. One problem with several generalized Morphological skeleton transforms is that they generate noise after decomposition. The noise rate may not be effective for ordinary images; however this effect will be more when applied on printed or handwritten characters. Approach: The present study tackled this issue by applying a noise removal algorithm after morphological decomposition. Results: The algorithm was applied on various types of decomposition images. The Present method was compared with generalized skeleton algorithm and octagon-generating decomposition algorithm. Conclusion: The error rates with original image were evaluated using various error functions. The experimental results indicated that the present decomposition algorithm produces images with good clarity when compared with other algorithms.
Daily Living Skills Training in Virtual Reality to Help Children with Autism Spectrum Disorder in a Real Shopping Scenario

In this paper, we present a study conducted to investigate the feasibility and effectiveness of Virtual Reality (VR) applied to daily living skills (DLS) training of individuals diagnosed with Autism Spectrum Disorder (ASD). In collaboration with a teacher at a school for children and adolescents with mental disorders, a head-mounted display based VR simulation of a supermarket was built and evaluated with the purpose of developing the shopping skills of students diagnosed with ASD. A comparative between-group experiment was conducted on 9 participants, with initiated VR training following a baseline assessment in a real supermarket. After running seven VR training sessions over 10 days for the treatment group, participants were assessed again in the real supermarket. Results show some benefit of training DLS using VR as discussed in the paper.
Assessment of female reproductive endpoints in Sprague-Dawley rats developmentally exposed to Diuron: potential ovary toxicity.

BACKGROUND Diuron is widely used in agriculture but its deleterious effects on the reproductive system and mammary gland are still poorly understood. This study evaluated whether early-life-stage exposure to Diuron alters puberty onset or susceptibility to mammary carcinogenesis in female Sprague-Dawley rats. METHODS AND RESULTS Pregnant rats received basal diet or diet containing Diuron at 500, 750, and 1,250 ppm, from gestational day 12 to the end of lactation (postnatal day 21 [PND21]). After weaning, female offspring continued receiving basal diet or diet containing Diuron until PND 51. At PND 51, female Sprague-Dawley offspring received a single dose of 50 mg/kg b.w. of 7,12-dimethylbenz(a)anthracene (DMBA) for initiation of mammary carcinogenesis. The animals were sacrificed on PND 51, 75, and 226 to 233 (week 25) for mammary gland morphology, reproductive organs and tumor analysis, respectively. There were no significant differences among groups on vaginal opening, estrous cycle, mammary morphology, or carcinogenesis. However, reductions in ovary weight and corpora lutea were observed at PND 75 in the group treated with Diuron at 1,250 ppm. CONCLUSIONS The findings suggesting that Diuron exposure (1,250 ppm) may have been potentially toxic to the ovaries.
Predicting Restaurant Consumption Level through Social Media Footprints

Accurate prediction of user attributes from social media is valuable for both social science analysis and consumer targeting. In this paper, we propose a systematic method to leverage user online social media content for predicting offline restaurant consumption level. We utilize the social login as a bridge and construct a dataset of 8,844 users who have been linked across Dianping (similar to Yelp) and Sina Weibo. More specifically, we construct consumption level ground truth based on user self report spending. We build predictive models using both raw features and, especially, latent features, such as topic distributions and celebrities clusters. The employed methods demonstrate that online social media content has strong predictive power for offline spending. Finally, combined with qualitative feature analysis, we present the differences in words usage, topic interests and following behavior between different consumption level groups.
On securing IEEE 802.15.4 networks through a standard compliant framework

The IEEE 802.15. 4 standard is widely recognized as one of the most successful enabling technologies for short range low rate wireless communications. Although it provides all the details of both MAC and PHY layers of the protocol stack, the standard also explains specific methodologies to protect MAC packets through symmetric-key cryptography techniques under several security options. However, the orchestration of available security profiles and the management of key negotiation schemes is delegated to upper layers. In support of this feature, this work describes a standard compliant security framework aimed at proposing: (i) different kind of security architectures, (ii) an efficient mechanism for initializing a secure IEEE 802.15. 4 domain, and (iii) a lightweight mechanism to negotiate link keys among devices. Experimental tests have been conducted to demonstrate the behavior of the proposed solution in real environments. Obtained results clearly show that the enabling of security features in constrained nodes requires additional computational efforts, which involve a not negligible growth of communication latencies. Such findings have to be carefully considered when designing and developing enhanced applications in future and secured Internet of Things (IoT) systems.
Biodiversity and Ecosystem Functioning

Species diversity is a major determinant of ecosystem productivity, stability, invasibility, and nutrient dynamics. Hundreds of studies spanning terrestrial, aquatic, and marine ecosystems show that high-diversity mixtures are approximately twice as productive as monocultures of the same species and that this difference increases through time. These impacts of higher diversity have multiple causes, including interspecific complementarity, greater use of limiting resources, decreased herbivory and disease, and nutrient-cycling feedbacks that increase nutrient stores and supply rates over the long term. These experimentally observed effects of diversity are consistent with predictions based on a variety of theories that share a common feature: All have trade-off-based mechanisms that allow long-term coexistence of many different competing species. Diversity loss has an effect as great as, or greater than, the effects of herbivory, fire, drought, nitrogen addition, elevated CO2, and other drivers of environm.
Age-specific prevalence and causes of blindness and visual impairment in an older population: the Rotterdam Study.

OBJECTIVE To study the prevalence and causes of blindness and visual impairment in various age categories of a large population-based study. METHODS For the study, 6775 subjects aged 55 years or older underwent an extensive ophthalmologic screening examination, including measurements of visual acuity and the visual field and fundus photography. The causes of blindness or visual impairment were determined using all screening information and medical records. RESULTS The prevalence of blindness, according to World Health Organization criteria, ranged from 0.1% in subjects aged 55 to 64 years to 3.9% in subjects aged 85 years or older; the prevalence of visual impairment ranged from 0.1% to 11.8%. For persons younger than 75 years, myopic degeneration and optic neuropathy were the most important causes of impaired vision. For persons aged 75 years or older, age-related macular degeneration was the major cause of the increased prevalence of blindness, whereas age-related cataract predominantly caused the increased prevalence of visual impairment. CONCLUSIONS The hierarchy of causes of blindness and visual impairment is highly determined by age. As yet, little can be done to reduce the exponential increase of blindness; however, adequate implementation of surgery to treat cataract could reduce visual impairment by one third. Underuse of ophthalmologic care is a prominent cause of the high frequency of untreated cataracts among the elderly.
Underwater ultra-wideband fingerprinting-based localization

In this work a new location fingerprinting-based localization algorithm is proposed for an underwater medium by utilizing ultra-wideband (UWB) signals. In many conventional underwater systems, localization is accomplished by utilizing acoustic waves. On the other hand, electromagnetic waves haven't been employed for underwater localization due to the high attenuation of the signal in water. However, it is possible to use UWB signals for short-range underwater localization. In this work, the feasibility of performing localization for an underwater medium is illustrated by utilizing a location-based fingerprinting approach. Existing algorithms for an indoor environment are evaluated in this project for an underwater medium. These algorithms are based on a neural networks or maximum likelihood estimator. Further, we also consider a classical k-nearest neighbors (KNN) approach. In addition, by employing the concept of compressive sampling, we propose a sparsity-based localization approach for which we define a system model exploiting the spatial sparsity. Moreover, a recently proposed grid mismatching algorithm is also adapted to the current localization framework and its performance is evaluated. Finally, the performance of the proposed methods is compared with the existing fingerprinting-based localization approaches.
An epidemiology-based model as a tool to monitor the outbreak of inappropriateness in tumor marker requests: a national scale study

Abstract Background: Evaluation of appropriateness of laboratory tests on the basis of individual requests remains a serious problem as the clinical question is usually not reported with the test order. This study explored the comparison of the rate of tumor marker orders with cancer prevalence as a putative indicator of inappropriateness. Methods: Tumor marker orders (2011 and 2012) were obtained from the Ministry of Health and cancer prevalence from the Italian Association of Cancer Registries. The rate of tumor marker orders was matched with demographic data and tumor prevalence and examined by using the confidence interval approach. Region-to-region and year-to-year variations were also examined. Focus was placed on CEA, CA125, CA19.9 and CA15.3. Results:Tumor markers ordered in Italy were 13,207,289 in 2012 (221.3/1000 individuals). Given an estimated prevalence of 2,243,953 cancer cases, 7.04 tumor markers appear to be requested for each prevalent case of epithelial cancer per year. The rate of requests of CEA, CA125, CA19.9 and CA15.3 (in aggregate 5,834,167 requests in 2012, 44.2% of total) from the first and the last ranked region (96 and 244/1000 individuals) are significantly different (p<0.01). Region-to-region differences do not correspond to any known variation of prevalence in the different regions. Conclusions: The developed approach provides a proxy indicator of inappropriateness showing that tumor markers are overused in Italy and their ordering pattern is not related to tumor prevalence. The model is suitable to be validated in other laboratory tests used in diseases whose prevalence is known.
The Impact of Macroeconomic Indicators on the Movement of CROBEX

Many research showed a high degree of correlation between the US and European capital markets, partly due to industrial‒financial linkages of the United States and Europe, and partly due to the influence of psychological factors on the behavior of individuals, and the concept of behavioral finance. However, it can be assumed that the movement of the value of an observed index does not depend solely on the change of values of the S & P 500 index. Accordingly and in line with rational economic theory, this paper examines the link between changes in the value of selected macroeconomic indicators and the value of the main share Croatian capital market index CROBEX. The results indicate that of the nine initially observed variables, movement of CROBEX can be described and further explained by changes in the value of average wages, parity rate and dollar, the kuna and the euro and the kuna and the Swiss franc.
Invariance of an Extended Technology Acceptance Model Across Gender and Age Group.

In this study, we examined the likelihood of a TAME (extended technology acceptance model), in which the interrelationships among computer self-efficacy, perceived usefulness, intention to use and self-reported use of computer-mediated technology were tested. In addition, the gender- and age- invariant of its causal structure were evaluated. The data were collected from a self-reported questionnaire administered to 477 administrative staff of a public university in Malaysia. The results of structural equation modeling supported the adequacy of TAME. Although the TAME’s causal structure was applicable to both male and female staff, age group appeared to moderate the structural relationships among the constructs of interest.
Cross-Border Spillovers from Fiscal Stimulus

The global recession of 2008-09 has revived interest in the international repercussions of domestic policy choices. This paper focuses on the case of fiscal stimulus, investigating cross-border spillovers from an increase in exhaustive government spending on the basis of a two-country business cycle model. Our model allows spillovers to be affected by a range of features, including trade elasticities, the size and openness of economies, as well as financial imperfections. Beyond these well-known determinants, however, we highlight the central importance of policy frameworks, notably the medium-term debt consolidation regime. We consider the plausible case in which a temporary debt-financed increase in government spending gives rise to higher future taxes along with some reduction in spending over time. The anticipated spending reversal not only strengthens the domestic stimulus effect but also enhances positive cross-border spillovers through its impact on global long-term interest rates. Thus, our findings lend support to the notion that coordinated short-term stimulus policies are most effective when coupled with credible medium-term consolidation plans featuring at least some spending restraint.