Miracle-dz/UniFAR-FTUs huggingface dataset:
www.econstor.eu Prices and Quality Signals

We consider a market-for-lemons model where the seller is a price setter, and, in addition to observing the price, the buyer receives a private noisy signal of the products quality, such as when a prospective buyer looks at a car or house for sale, or when an employer interviews a job candidate. Su¢ cient conditions are given for the existence of perfect Bayesian equilibria, and we analyze equilibrium prices, trading probabilities and gains of trade. In particular, we identify separating equilibria with partial and full adverse selection as well as pooling equilibria. We also study the role of the buyers signal precision, from being completely uninformative (as in standard adverse-selection models) to being completely informative (as under symmetric information). The robustness of results for these two boundary cases is analyzed, and comparisons are made with established models of monopoly and perfect competition. Keywords: lemons, adverse selection, noisy quality signals. JEL codes: C72, D82. SSE/EFI Working Paper Series in Economics and Finance, No. 551. We would like to thank Lars-Göran Mattsson for many inspiring discussions at the beginning of this research project, and Carlos Alos-Ferrer, Tore Ellingsen, Jianjun Miao and Zvika Neeman for comments to an earlier version. Voorneveld thanks the Jan Wallander and Tom Hedelius Foundation for nancial support.
Detecting malicious applications using system services request behavior

Widespread growth in Android malware stimulates security researchers to propose different methods for analyzing and detecting malicious behaviors in applications. Nevertheless, current solutions are ill-suited to extract the fine-grained behavior of Android applications accurately and efficiently. In this paper, we propose ServiceMonitor, a lightweight host-based detection system that dynamically detects malicious applications directly on mobile devices. ServiceMonitor reconstructs the fine-grained behavior of applications based on their interaction with system services (i.e. SMS manager, camera, wifi networking, etc). ServiceMonitor monitors the way applications request system services in order to build a statistical Markov chain model to represent what and how system services are used. Afterwards, we use this Markov chain as a feature vector to classify the application behavior into either malicious or benign using the Random Forests classification algorithm. We evaluated ServiceMonitor using a dataset of 8034 malware and 10024 benign applications and obtaining 96.7% of accuracy rate and negligible overhead and performance penalty.
MFE-HAR: multiscale feature engineering for human activity recognition using wearable sensors

Human activity recognition plays a key role in the application areas such as fitness tracking, healthcare and aged care support. However, inaccurate recognition results may cause an adverse effect on users or even an unpredictable accident. In order to improve the accuracy of human activity recognition, multi-device and deep learning based approaches have been proposed. However, they are not practical on a daily basis due to the limitations that devices are difficult to wear, and deep learning requires large training dataset and incurs expensive computational costs. To address this problem, we propose a novel approach, multiscale feature engineering for human activity recognition (MFE-HAR), which exploits the properties of arm movement from global and local scales using the accelerometer and gyroscope sensors on a single wearable device. Our method takes advantage of having important features at multiple scales over previous single-scale methods. We evaluated the performance of the proposed method on two public datasets and achieved the mean classification accuracy of 93% and 98% respectively. Our proposed system performs better than the state of the art multi-device based approaches, and is more practical for real-world applications.
Examining the energy impact of sorting algorithms on android: an empirical study

With the advent of mobile application development a new software quality concern - energy consumption - was introduced. For mobile software developers knowledge about software and algorithm design choices and their implications on energy consumption is crucial. However, software developers either lack this knowledge or tools to support them in estimating the energy consumption of their applications and therefore are unable to reflect on their design choices. In this empirical study we examine the energy consumption of 12 sorting algorithms and the resulting energy impact when used with different data types. We propose a methodology to obtain energy readings and relate them to application execution traces. Our results show that the choice of data type together with algorithm design can have significant impact on the energy profile of an application.
WiLay: building wi-fi-based human activity recognition system through activity hierarchical relationship

Recently, Wi-Fi-based human activity recognition technique has attracted attentions extensively. Due to its ease of access and low cost, Wi-Fi-based technique achieves great potential on building human activity recognition systems. However, this technique is limited because the Wi-Fi signal is less-informative and susceptible to environmental changes. To build a practical Wi-Fi-base human activity recognition system, in this paper, WiLay, a layer-structured human activity recognition system is proposed. To recognize 7 different activities, WiLay used an activity-oriented process to select and extract features according to the hierarchical relationship between different activities, and trained multiple classifiers to build its layer-structured recognition system. We collected data on several different environments and tested our system. The experimental results with 95.4% accuracy and 89.1% recall rate indicate that our system has very well performance on recognition human activities and is robust to environmental changes.
NextAct: a hybrid approach for high-resolution human activity predictions

Emerging anticipatory applications that intervene or proactively support users in daily life require an in-depth understanding of prospective human behavior. However, accurate and fine-grained prediction of human behavior is complex and conventional machine learning approaches show limitations. In this paper, we present a novel approach, namely NextAct, to predict human activities by utilizing temporal and spatial features predicted from calendar events, user routines and sequences of next place predictions for remaining uncertain time slots in between. NextAct hereby makes spatial features in addition to the obvious temporal features available for the human activity predictor. We evaluate our hybrid approach on a four-week user-annotated dataset from 30 participants; we compare our forecasting results against prediction techniques proposed in the literature. The results show an F1-score up to 82.6% and a performance gain up to 16.6% compared to state of the art approaches. We also discuss the cold-start problem of individual models and show that we achieve adequate results after 4 days. NextAct opens a novel way for human activity prediction to proactively support a user and optimize his next activity or day.
Microservices and Containers

The articles in this special section focus on microservices and containers. These services allow an application to be comprised of many independently operating and scalable components, have become a common service paradigm. The ability to construct an application by provisioning these interoperating components has various advantages, including the isolation and independent development of tools such as key-value stores, authentication, logging, and many others. Containers are one type of system infrastructure that is commonly used to support microservices. With container management systems like Docker and orchestration systems like Kubernetes to control applications and dynamically provision their resources, cloud services can be extremely scalable, reliable, and reactive. However, other systems beyond containers can be used to support microservices, and many applications other than microservices benefit from containerization.
[BAS-0 Bioactive Glass-ceramic as a Bony Tissue Replacement (Clinical Experience after a Longterm Interval after Application).].

: The aim of our retrospective study is to show how very circumspect we are to use this method. The clinical symptoms of our patients were lumbalgia or lumboischialgia with or without neurological deficiencies. All these patients were resistent to conservative therapies. We accepted for operation only patients who suffered from protrusions and types of prolaps without perforation of the posterior longitudinal ligament. 179 operations on the vertebral discs were performed in our department between 01. 01. 1992 until 31.12. 1997. Of this number 165 (92 %) were conservative nucleotomies (63 females and 102 males) and 14 patients (8 %) hat percutane nucleotomies and discos-copies (6 females and 8 males). The average age at the time of operation was 49 years (from 12 to 81 years) with patients who had an open operation, whilst the patients who had percutane nucleotomy had an average age of 42 years (26 to 56 years). The time span between postoperative checkups was on average about 40 months (3 years and 4 months). The shortest postoperative checkup period was 2 months and the longest 71 months (5 years and 11 months). Of the 14 cases mentioned we operated 9 patients in the segment L4/5, 4 patients in the segment L5/S1 and one patient in the segment L3/4. In 7 instances it was the right side that was injured and 7 times it was the left side which was injured. We performed all operations under general anaesthesia, the patient lying prone on the abdomen with lumbal lordosis raised as much as possible. We always used an X-ray picture enlarger on two planes. As far as subjective pain is concerned, an analysis of the findings gives the following results: 100 % improvement 6 patients, 80 % improvement 2 patients, 50 % improvement 3 patients, no improvement 3 patients. Five praeoperative existing motorial deficiencies had completely vanished postoperatively. As to eventual complications, we had one patient suffering from a lesion at the root of L4 on the right side with postoperative Spondylodiscitis L3/4 who was treated in a conservative way. When patient selection for this method is critically considered, the advantage of endoscopic operation lies in minimal invasion and rapid rehabilitation is associated with it.
A novel routing metric for IEEE 802.11s-based swarm-of-drones applications

With the proliferation of drones in our daily lives, there is an increasing need for handling their numerous challenges. One of such challenge arises when a swarm-of-drones are deployed to accomplish a specific task which requires coordination and communication among the drones. While this swarm-of-drones is essentially a special form of mobile ad hoc networks (MANETs) which has been studied for many years, there are still some unique requirements of drone applications that necessitates re-visiting MANET approaches. These challenges stem from 3--D environments the drones are deployed in, and their specific way of mobility which adds to the wireless link management challenges among the drones. In this paper, we consider an existing routing standard that is used to enable meshing capability among Wi-Fi enabled nodes, namely IEEE 802.11s and adopt its routing capabilities for swarm-of-drones. Specifically, we propose a link quality metric called SrFTime as an improvement to existing Airtime metric which is the 802.11s default routing metric to enable better network throughput for drone applications. This new metric is designed to fit the link characteristics of drones and enable more efficient routes from drones to their gateway. The evaluations in the actual 802.11s standard indicates that our proposed metric outperforms the existing one consistently under various conditions.
A non-parametric approach to decompose the young adult mortality hump by causes of death

We propose a cause-deletion non-parametric approach to decompose the young adult mortality hump by cause of death. This novel method isolates the specific causes that contribute to the temporary deviation of the age-specific mortality rates in early adulthood, irrespective of their share in the absolute number of deaths. We apply our method to US males and females from 1959 to 2010. Preliminary results show that life expectancy is typically reduced by about 1 year for males and 0.2 year for females due to the presence of the hump. For males, accidents used to account for the vast majority of the hump in the 1960s but have been now overtaken by homicides, suicides, and poisoning. For females, traffic accidents have remained the main driver of the variations until now. Moreover, each cause peaks at different ages, suggesting that they may be generated by different underlying processes. 1 Background The young adult mortality hump has been known since at least the second part of the nineteenth century (Thiele, 1871), although it received little attention until the publication of Heligman Pollard’s model of mortality (Heligman and Pollard, 1980). In comparison with senescence, which drives the exponential increase of the force of mortality during the second part of adulthood, and ontogenescence, which explains the decrease of the risk of death in the first years of life, young adult "excess" mortality has never been properly defined, measured, or explained. We suggest using a broad definition for this phenomenon, namely as a "temporary deviation of the aggregate age-specific death rate from the exponential trend due to senescence, during adolescence and/or early adulthood" (Remund, 2015). This feature is most visible in logged mortality rates, rather than absolute rates, which means it is as much a feature of the rate of change over age of morality rates as it is of absolute mortality rates. In fact the hump may or may not be present and visible in a log mortality curve under any absolute level of mortality. To compare humps between curves, it is thus necessary to adjust somehow for the overall mortality level, i.e. relate it to the full age pattern of mortality. Common age-cause decompositions of mortality differences miss this key aspect of the hump. The study of the leading causes of death in early adulthood using raw age-specific death rates has already been attempted (Heuveline, 2002; Blum, 2009), but this approach suffers from two drawbacks. First, the contribution to the hump must depend on the shape of the cause-specific forces of mortality and not on the absolute levels of age-specific death rates. Second, the age range considered should not be arbitrary fixed but instead adjusted to the period of life that is affected by excess mortality in each population. Institut national d’études démographiques & University of Geneva Max Planck Institute for Demographic Research Institut national d’études démographiques
Uneven-aged silviculture of Scots pine in Bohemia and Central Spain: comparison study of stand reaction to transition and long-term selection management

The achievement of sustainable forest management requires the incorporation of ongoing environmental changes into long-term planning. Moreover, in time of climatic change and changing company demands, importance of Scots pine (Pinus sylvestris L.) is still increasing at the expense of other tree species due to its low ecological requirements. The aim of the study was to compare the structure and production of Scots pine stands managed under different silvicultural systems on four research plots, assess the structural and diversity indices, and analyse the increment structure using tree-ring dating in the Czech Republic and Spain. Area of study was Western Bohemian and Guadarrama Mountain range in Central Spain. The results indicate that stand volume on the investigated plots ranged from 231 to 441 m3∙ha–1 with tree density 276–996 trees∙ha–1. Intensively managed (uneven-aged) permanent research plots showed increased growth on basal area. The difference was evident also for older trees. The transition to uneven-aged forest does not negatively influence stocking and wood production and provide higher benefits for diversity and structural complexity in comparison to regular stands.
A Factorial Study Of Fibre Cement Roofing Sheet Manufacturing

Some concerns had been expressed in the past over the difficulties associated with achieving a first-pass manufacturing success which serves to obviate the efforts inherent in patching and fixing a troublesome product always. Incidentally, achievement of such a manufacturing feat requires a major shift in philosophy of product design and process technology. This study seeks to identify an omnium-gatherum of unique variables that influence quality and productivity improvement with a view to providing insight into their inter correlations so that by properly tricking on their affinities, desirable quality attributes can be achieved. A novel combination of two statistical techniques, Kendall Coefficient of Concordance and Principal Component Analysis (PCA) was adopted. The former was used to analyze data matrix generated by thirteen Judges who were requested to rank the sixty one variables in merit order sequentiality upon which basis an index of concordance in ranking among the judges was computed as w = 0.43 and the latter further analyzed the outcomes of the questionnaires crafted with top thirty of the well ordered variables, purposively selected, using statisttiXL software. The results obtained by Kendall Coefficient of Concordance suggested that the functional role of Hatsheck processing machine is outstanding. On the other hand, the result by PCA indicates that significant parsimony was achieved in data reduction from thirty to mere eleven. Further, product series, wielding a factor loading of 0.859, appear to appeal most to customers’ preferences. This study has helped to clarify thinking in the productivity of fibre cement roofing sheet and cladding manufacturing world. Keywords—Fibre cement sheet, Foam lamella, omnium-gatherum, Principal Component Analysis, Product integrity.
Cantonese porcelain classification and image synthesis by ensemble learning and generative adversarial network

Accurate recognition of modern and traditional porcelain styles is a challenging issue in Cantonese porcelain management due to the large variety and complex elements and patterns. We propose a hybrid system with porcelain style identification and image recreation modules. In the identification module, prediction of an unknown porcelain sample is obtained by logistic regression of ensembled neural networks of top-ranked design signatures, which are obtained by discriminative analysis and transformed features in principal components. The synthesis module is developed based on a conditional generative adversarial network, which enables users to provide a designed mask with porcelain elements to generate synthesized images of Cantonese porcelain. Experimental results of 603 Cantonese porcelain images demonstrate that the proposed model outperforms other methods relative to precision, recall, area under curve of receiver operating characteristic, and confusion matrix. Case studies on image creation indicate that the proposed system has the potential to engage the community in understanding Cantonese porcelain and promote this intangible cultural heritage.
Efficient Real Single-Tone Frequency Estimator Based on a Normalized IIR Notch Filter

A novel unbiased frequency estimator for a single real-valued sinusoid in white noise is proposed, which is based on a normalized second-order Infinite Impulse Response (IIR) notch filter, an can be seen as an extension of the Pisarenko Harmonic Decomposer (PHD) estimator. The new estimator inherits the simplicity of the PHD estimator and the high accuracy and selectivity achieved by an IIR filter. As the coefficient determining the pole angle of the IIR notch filter depends on the unknown frequency value, an iterative scheme is proposed in which this coefficient is computed from the frequency estimate from the previous iteration. An analytic expression for the Mean Square Error at each iteration is derived. Simulation results show that this iterative method can approach the Cramer-Rao Lower Bound in a few iterations under different Signal to Noise Ratio levels, provided that the data record length is sufficiently large.
GRAPHICAL DURATION MODELS

Graphical models use graphs to represent conditional independence relationships among random variables. In this paper, the possibility of defining a special type of graphs including nodes to represent point processes has been explored: this could be relevant to the analysis of event history data, i.e. of data consisting of times and types of observed events, together with some explanatory variables observed on a number of individuals; survival analysis and duration models are particular cases. The idea consists of representing a whole process by a single node. The resulting models will be called graphical duration models.
MORPHOLOGICAL CHANGES IN ARTIFICIALLY REARED ONE YEAR OLD SEA TROUT (SALMO TRUTTA L.) DURING SPRING

Morphological parameters and their changes common for artificially reared one year old sea trout were examined from January to May the year 2013 to determine whether these parameters indicated the smoltification in one year old sea trout and whether these fish achieved smolts stage. Fish were reared in flow-through and recirculation systems in hatcheries based on three different rivers (Brasla, Daugava, Venta basin). Sea trout were examined in the Latvia University of Agriculture, Faculty of Veterinary Medicine, Institute of Food and Environmental Hygiene and in the Institute of Food Safety, Animal Health and Environment BIOR, Laboratory of Aquaculture and Fish Pathology. To appreciate fish growth stage condition index, hepatosomatic index, spleen index was calculated and silvering level was evaluated. The fish condition index decreased in all hatcheries and flow-through and recirculation rearing systems from January to April and increased in May. Spleen index was the most stable parameter and did not change a lot showing that fish did not have migratory stress in April and May. Silvering level increased from January to April but suddenly the increase became slower in May without reaching the top level. These results made us to consider that one year old sea trout parrs released in May 2013 probably did not become smolts before release and they had to stay in river for one additional year until reaching pronounced smolt stage.
Exchange Option Pricing Approach to Deposit Insurance Premium for Korean Life Insurance

This paper aims to investigate the risk-based premium rates of the Korea Deposit Insurance Corporation (KDIC), particularly focusing on life insurance firms. To accomplish this, we employ the exchange option model based on the assumption that assets and liabilities follow lognormal diffusion processes. Further, we incorporate the discount rate of expenses based on a purchase-and-assumption to consider the characteristics of the life insurance sector. To estimate premium rates between 2010 and 2017, we use the empirical data of Korean life insurance firms and asset indexes from 2000 to 2016. The result provides evidence that life insurance companies in Korea have been generally charged higher premium rates than they should be charged. The result also shows that most of the healthy life insurance companies aid a smaller number of risky companies in Korea. Finally, our result indicates that premium rates tend to be more sensitive to correlation between assets and liabilities under capital deficiencies. Exchange Option Pricing Approach to Deposit Insurance Premium for Korean Life Insurance*