Miracle-dz/UniFAR-FTUs huggingface dataset:
Handling of Spatio-Temporal Pattern Queries in Moving Object Database

Moving object database is a collection of geometric data that changing over time. The existence of a moving object database allows database users to express a series of predicates that state events or changes that happened during the movement of a moving object. The class of queries that involve a series of predicates is called the Spatio-temporal pattern (STP) queries. STP query has temporal order constraints on the fulfillment of predicates involved. The implementation of the STP query is unavailable in existing database management systems (DBMSs). Developing a tool to express the STP query needs to be done. This is to allow any kind of questions that could not be asked before.STP query is expressed using the STP predicate which has a design consisting of two parts. The first defines lifted predicates that accept moving object arguments and report the time intervals, during which they are fulfilled. The second part is to define temporal constraints on the predicate fulfillments. Temporal constraints are defined as temporal relationships between pairs of time intervals.Implementation of STP queries is done by providing data structures for moving objects, methods for evaluating operations on moving objects, and functions for defining STP predicates. The implementation is collected into a single package called extension. Extension is a form of tool built on the DBMS to handles STP queries in a moving object database. The extension is built on PostgreSQL which provides spatial data types and operations through PostGIS. The testing of the tool is done by executing several STP queries. The test results show that the tool built successfully handles STP queries in a moving object database.
A Highly Reliable Wearable Device for Fall Detection

A late treated fall may cause irreparable damage or even the death of a human being. This problem gets worse with the older ages of the person suffering the fall. Solutions to this problem do exist in the market but do not appropriately address the reliability of using the proposed devices. None of the existing solutions clearly present their capabilities in terms of testing, operation safety and fault tolerance. This work not only gets structured the offline and online tests to which the device should be exposed, but also proposes the use of hardware and software redundancy to provide for a more reliable solution for the problem. A prototype of a wearable device for fall detection has been developed, that provides for safe operation and tolerate faults, while delivering very low current consumption and low cost, those that are essential specifications to meet the market demands for wearable devices
Polyamine Content in Relation to Embryo Growth and Dedifferentiation in Barley (Hordeum vulgare L.)

Attempts to find correlations between polyamine content and development of zygotic embryos of barley are described here. The acid-extractable fraction of the polyamines putrescine, spermidine, and spermine present in the embryos during development in vivo has been analysed in two varieties, «Golden Promise» and «Bomi», and in the mutant «Riso 1508»
Efficient On-Chip Multicast Routing based on Dynamic Partition Merging

Networks-on-chips (NoCs) have become the mainstream communication infrastructure for chip multiprocessors (CMPs) and many-core systems. The commonly used parallel applications and emerging machine learning-based applications involve a significant amount of collective communication patterns. In CMP applications, multicast is widely used in multithreaded programs and protocols for barrier/clock synchronization and cache coherence. Multicast routing plays an important role on the system performance of a CMP. Existing partition-based multicast routing algorithms all use static destination set partition strategy which lacks the global view of path optimization. In this paper, we propose an efficient Dynamic Partition Merging (DPM)-based multicast routing algorithm. The proposed algorithm divides the multicast destination set into partitions dynamically by comparing the routing cost of different partition merging options and selecting the merged partitions with lower cost. The simulation results of synthetic traffic and PARSEC benchmark applications confirm that the proposed algorithm outperforms the existing path-based routing algorithms. The proposed algorithm is able to improve up to 23% in average packet latency and 14% in power consumption against the existing multipath routing algorithm when tested in PARSEC benchmark workloads.
Predictive Eco-Driving Application Considering Real-World Traffic Flow

Eco-approach and departure (EAD) systems in connected vehicles are capable of providing the speed recommendations to drivers so that vehicles can pass through successive intersections at the appropriate instants to save time and energy. However, most of existing control strategies and global optimization algorithms for EAD systems have extremely high requirements for computational resources, which make EAD systems not easy to popularize and apply to real vehicles. To overcome this problem, this paper designs a traffic flow prediction model based on deep learning regression machine, and establishes a dynamic effective red-light duration model based on traffic flow queuing effect. To facilitate real-time update of the optimal speed, a constrained optimization model is proposed as an approximation approach, which can obtain similar optimal results to that of the pseudo-spectral method while greatly reducing calculating time. The effectiveness of the proposed control algorithm for EAD system on passing intersections and energy saving has been validated on the real vehicle under real-world traffic environment. Compared with the uninformed driver, the proposed EAD system saves 2% time and 4.6% energy on average in case that driver is informed and 8% time and 12.1% energy in case of autonomous driving.
Cross-Rack-Aware Updates in Erasure-Coded Data Centers: Design and Evaluation

The update performance in erasure-coded data centers is often bottlenecked by the constrained cross-rack bandwidth. We propose <inline-formula><tex-math notation="LaTeX">${\sf CAU}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">CAU</mml:mi></mml:math><inline-graphic xlink:href="shen-ieq1-2991021.gif"/></alternatives></inline-formula>, a cross-rack-aware update mechanism that aims to mitigate the cross-rack update traffic in erasure-coded data centers. <inline-formula><tex-math notation="LaTeX">${\sf CAU}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">CAU</mml:mi></mml:math><inline-graphic xlink:href="shen-ieq2-2991021.gif"/></alternatives></inline-formula> builds on three design elements: (i) selective parity updates, which select the appropriate parity update approach based on the update pattern and the data layout to reduce the cross-rack update traffic; (ii) data grouping, which relocates and groups updated data chunks in the same rack to further reduce the cross-rack update traffic; and (iii) interim replication, which stores a specified number of temporary replicas for each newly updated data chunk. We evaluate <inline-formula><tex-math notation="LaTeX">${\sf CAU}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">CAU</mml:mi></mml:math><inline-graphic xlink:href="shen-ieq3-2991021.gif"/></alternatives></inline-formula> via trace-driven analysis, local cluster experiments, and Amazon EC2 experiments. We show that <inline-formula><tex-math notation="LaTeX">${\sf CAU}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">CAU</mml:mi></mml:math><inline-graphic xlink:href="shen-ieq4-2991021.gif"/></alternatives></inline-formula> enhances state-of-the-arts by mitigating the cross-rack update traffic as well as maintaining high update performance in both local cluster and geo-distributed environments.
An Effective Energy Management System for Smart Residential Buildings using Binary Particle Swarm Optimization

The increasing power demand and the emergence of smart grids have given access to new opportunities for the energy management system of smart residential buildings that can reduce energy usage. Demand Response (DR) program is one of the most important strategies for implementing the residential building energy management system. The consumer load gets modified depending upon the electricity price provided by the utility so that the consumer electricity bill decreases. This strategy decreases the peak demand by scheduling the schedulable loads from the period when the electricity prices are high for the period when the prices are low with minimal effect on consumer comfort. It reduces the demand and increases the effective utilization of the energy of a residential building. This paper proposes an Effective Energy Management System (E-EMS) for residential buildings that models the problem by considering the uninterruptable and interruptible residential load appliances which can be controlled and their shifting windows constraints. It also manages the battery bank operation for maximum utilization of energy stored so that the wastage of power through dump load is minimum depending upon the Power Export Limit (PEL) defined by the utility. Further, the optimal sizing of renewable energy resources is also carried out for choosing the size of renewable energy resources and battery banks for effective utilization. The results of the proposed system are simulated by using MATLAB software to verify the effectiveness of the proposed strategy to control household appliances and their energy consumption by using BPSO.
Simple Coupled-Line Tunable Bandpass Filter With Wide Tuning Range

In this paper, a tunable bandpass filter using coupled line with a wide tuning range is proposed. The proposed filter has a simple structure which is composed of a coupled-line section and two pairs of varactors. Meanwhile, simultaneously tuning on bandwidth and center frequency are introduced by varactors. The tunability is mainly realized by varactors connected to one end of the coupled line and varactors between ports and coupled line provide an impedance matching. A theoretical analysis is presented to illustrate the tunability by using even- and odd-mode theory. Additionally, the detailed effect of the two types of varactors is researched, respectively. To verify the concept, a prototype is designed, fabricated, and measured. The transmission zero exhibited in measurement is introduced by bias circuits. The measured results show that the tunable bandpass filter achieves a tunable center frequency of 0.494-1.257 GHz (87.15%) and a 3-dB bandwidth of 0.282-0.943 GHz (334%).
DeepVision: Deepfakes Detection Using Human Eye Blinking Pattern

In this paper, we propose a new approach to detect Deepfakes generated through the generative adversarial network (GANs) model via an algorithm called DeepVision to analyze a significant change in the pattern of blinking, which is a voluntary and spontaneous action that does not require conscious effort. Human eye blinking pattern has been known to significantly change according to the person’s overall physical conditions, cognitive activities, biological factors, and information processing level. For example, an individual’s gender or age, the time of day, or the person’s emotional state or degree of alertness can all influence the pattern. As a result, Deepfakes can be determined through integrity verification by tracking significant changes in the eye blinking patterns in deepfakes by means of a heuristic method based on the results of medicine, biology, and brain engineering research, as well as machine learning and various algorithms based on engineering and statistical knowledge. This means we can perform integrity verification through tracking significant changes in the eye blinking pattern of a subject in a video. The proposed method called DeepVision is implemented as a measure to verify an anomaly based on the period, repeated number, and elapsed eye blink time when eye blinks were continuously repeated within a very short period of time. DeepVision accurately detected Deepfakes in seven out of eight types of videos (87.5% accuracy rate), suggesting we can overcome the limitations of integrity verification algorithms performed only on the basis of pixels.
Auxin‐stimulated ethylene production in fern gametophytes and sporophytes

The auxins indole-3-acetic acid (IAA) and 2,4-dichlorophenoxyacetic acid (2,4-D) stimulated ethylene production from gametophytes of the fern Pteridium aquilinum (L.) Kuhn. var. latiusculum (Desv) underw. ex Heller and sporophytes of the ferns Matteuccia struthiopteris (L.)Todaro and Polystichum munitum (Kaulf.) Presl. Treatment with Co2+ or l-α -(2-aminoethoxyvinyl)-glycine (AVG) eleminated or significantly reduced the stimulatory effects of IAA. Treatment with 1-aminocyclopropane-1-carboxylic acid (ACC) resulted in significantly greater rates of ethylene production from all tissues tested. Based on their response to auxin, ACC, AVG and Co2+, the ethylene biosynthetic pathway in these three lower vascular plants appears similar to that existing in angiosperms.
A Random Walk Approach for Avoiding Unwanted Users in Competitive Social Network

How to detect influential customers to broadcast advertisements to the maximum range is a key issue in effective viral marketing. If multiple companies sell the same product in viral marketing campaigns, there was competition between them. There may exist some unwanted users who hold hostile opinions, and these users may have a negative effect upon receiving promotional information. The company does not want the advertising information to reach such unwanted users over a period of time. In such competitive advertising, how to propagate the positive influence of its product and avoid it reaching the unwanted users of competitors in the limited time is a critical problem for business product promotion. Motivated by the phenomenon, we study the influence maximization problem with limited unwanted users (IML) in the independent cascade (IC) model. To accelerate the process of the influence propagation simulation, we present a path sampling approach based on the random walk to simulate the process of influence propagation. To avoid the unwanted users, only the influences on the paths reaching the wanted users are calculated at each time step, and the influences reaching the unwanted users are ignored.To reduce the computation time, the paths of the random walk will be recorded to avoid repeated random walks in the subsequent seed selection. To find the optimal influential customers, we employ a greedy scheme to select the top- $k$ most influential nodes as seed nodes. Experimental results over the real-world datasets show that the algorithm we presented can get wider effective influence spreading than other algorithms.
Effect of salinity on reproductive performance of Acanthopagrus latus (Houttuyn) in spawning tanks

More than 250 male and female yellowfin seabream (Acanthopagrus latus) were caught in the creeks near the Mahshar area in the north-west of Persian Gulf using fishhooks to study the effects of salinity on reproductive indices. The experiments were carried out using three salinity treatments (30 ± 1 g L−1, 35 ± 1 g L−1 and 40 ± 1 g L−1) with three replications. A total of six males and three females were randomly introduced to each tank. The survival rate of the broodstock was estimated at more than 90% at different salinity levels and the maximum rate was observed at 30 g L−1 of the experiment rate. The percentage of buoyant eggs was more than 90% at 40 g L−1 and it was significantly different from other treatments. The average number of eggs per female (312 914 ± 65 085), and the average number of eggs per kilogram of female (649 460 ± 173 574) at 40 g L−1 were more than those in the other treatments but no significant differences were observed (P ≤ 0.05). The average percentage of fertilized eggs (86.7%) and the average percentage of hatched larvae (67%) at 40 g L−1 treatment was more than those at 30 g L−1 and 35 g L−1 treatments but no significant differences were observed (P ≤ 0.05). At 40 g L−1 salinity, in all spawning cases, the released eggs were hatched. Overall, the present study has shown that better buoyant eggs of A. latus can be obtained at salinity 40 g L−1. On the other hand, the percentage of fertilized eggs and hatched larvae were not affected by salinity.
The effect of lysine and maize oil in growing and laying diets on the laying performance of crossbred pullets

In a 3 x 3 x 3 factorial experiment, the laying performance of White Leghorn x Australorp pullets, given growing diets (8-20 weeks of age) with the factorial combinations of three levels (4.5, 5.0 and 5.5 g/kg) of lysine and three levels (0, 10 and 20 g/kg) of maize oil and laying diets with 0, 10 and 20 g/kg and 0, 15 and 25 g/kg maize oil from 20 to 52 and 52 to 60 weeks of age, respectively, was measured.In the growing phase, neither the lysine nor maize oil levels in the diet had a significant effect on growth performance. The level of lysine in the growing diet had no effect on subsequent laying performance. There were significant interactions between the levels of maize oil in the growing and laying diets on rate of lay, egg output and feed conversion efficiency. The inclusion of 20g/kg maize oil in the laying diet increased egg weight. None of the dietary treatments had a significant effect on the weights of egg components (yolk, albumen and shell). With increasing level of maize oil in the laying diet, the concentration of myristic, palmitoleic, oleic and linolenic acids in the egg yolk decreased and that of stearic, linoleic and arachidonic acids increased.
Testing Heatsink Faults in Power Transistors by means of Thermal Model

In safety-critical systems, power electronics is widely used, e.g., for driving actuators. High currents and high voltages are often used in power electronics, which may cause considerable heating of the power devices. Hence, different mechanisms for heat dissipation and cooling of power devices are adopted. An excessive temperature increase in the power devices may lead to considerable electrical and mechanical stresses, and overheated electrical devices are subject to more rapid ageing. Therefore, an incorrect behaviour of the dissipation system can seriously damage or even block a safety-critical system. Hence, it is necessary to introduce test mechanisms to check the correct behaviour of the heatsinks. In this paper, we propose a strategy to quantitatively evaluate the effectiveness of a test for the dissipation system. The proposed approach is based on an electrothermal model of the cooling system. It allows one to identify the maximum size of the thermal fault tolerated by the dissipation system before the electrical device break down.
Exploitation rate reference points for West Coast rockfish: Are they robust and are there better alternatives?

Abstract We explore several aspects of the robustness of exploitation rate reference points as a management tool. The spawner−recruit curve is an important consideration when developing exploitation rate reference points. The spawner−recruit curves for West Coast rockfish Sebastes spp. suggest low productivity compared with other stocks, but our ability to produce reliable estimates of productivity is hindered by the scarcity of reliable, fishery-independent surveys, the short time span of the data, high aging error, and the low exploitation levels. Implementation of reference exploitation rates usually assumes that we can estimate the absolute stock size and the ratio of current to virgin stock size. We show that management by reference exploitation rates is not robust to overestimation of stock size; in such cases, overexploited stocks will continue to be overexploited. We also show that if F 55% exploitation rates (i.e., rates that reduce the spawning potential per recruit to 55% of its value in the un.
An Optimal Regulation Method for Parallel Water-Intake Pump Group of Drinking Water Treatment Process

Electricity consumption of pump group accounts for a significant proportion of cost in water distribution system (WDS). This paper discusses the optimal regulation method for parallel water-intake pump group consisting of fixed-frequency pumps and variable-frequency pumps. For this purpose, the regulation strategy for the water level of clean water tank is designed, and then the intake water flow of parallel pump group is calculated. For overall optimazing operation of parallel water-intake pump group, the mimimization of electricity consumption is performed within the constraints of limited pressure fluctuations of WDS and required flow of water supply. Dynamic programming algorithm and particle swarm optimization algorithm are employed to solve the optimization problem with constraints. Experimental studies have been conducted and the results show that 4.20% electricity-saving can be achieved by using the proposed optimal regulation method.
An Evolutionary Algorithm for Multi and Many-Objective Optimization With Adaptive Mating and Environmental Selection

Multi-objective evolutionary algorithms (MOEAs) have received immense recognition due to their effectiveness and efficiency in tackling multi-objective optimization problems (MOPs). Recently, numerous studies on MOEAs revealed that when handling many-objective optimization problems (MaOPs) that have more than three objectives, MOEAs encounter challenges and the behavior of MOEAs resembles a random walk in search space as the proportion of nondominated solutions increases subsequently. This phenomenon is commonly observed in most classical Pareto-dominance-based MOEAs (PDMOEAs) such as NSGA-II, SPEAII, as these algorithms face difficulties in guiding the search process towards the optimal Pareto front due to lack of selection pressure. From the literature, it is evident that incorporating sum of normalized objectives into the framework of MOEAs would enhance the converging capabilities. Hence, in this work, we propose a novel multi-objective optimization algorithm with adaptive mating and environmental selection (ad-MOEA) which effectively incorporates the concept of sum of objectives in the mechanisms of mating and environmental selection to control the convergence and diversity adaptively. To demonstrate the effectiveness of the proposed ad-MOEA, we have conducted experiments on 26 test problems that includes DTLZ, WFG and MaOP test suites. Along with the benchmark problem, we have analyzed the performance of the proposed approach on real-world problems. The experimental results demonstrate the effectiveness of the proposed method with respect to the state-of-art methods.
Lake sturgeon (Acipenser fulvescens) growth chronologies

We used annual increments in the pectoral fin rays of lake sturgeon (Acipenser fulvescens) to assess growth synchrony. We based our decision criteria on correlation among individual chronologies developed from samples collected in the Saskatchewan River, Saskatchewan, and Lake St. Clair and the Mattagami River, Ontario. Initially, correlations among chronologies were not significant within these three populations. However, as mean ageing error was reduced, correlations among chronologies increased to significant levels in samples from the Saskatchewan River and Lake St. Clair. Correlations were not significant among consistently aged fish sampled from the Mattagami River. We conclude that interannual growth variation in lake sturgeon is influenced by population-wide extrinsic factors in some populations. Our results suggest that both growth synchrony and ageing error should be quantified during the construction of growth chronologies for all organisms.