Local Objectives Research Articles

Learning robust features for indoor scene recognition

As digital image acquisition becomes ubiquitous in recent years, the need for indoor scene recognition becomes more pronounced. Existing methods leverage the features of composing objects in a scene and overlook the adverse impacts of the common objects reoccurring in other scenes. This drawback decreases the feature discrimination between scenes (e.g., living room, dining room, and bedroom) due to reoccurring objects (e.g., tables, chairs, and toys). We propose a method of training convolutional networks by punishing or discounting the local object representations’ predictive ability and encouraging the network to learn global scene layout representations. To retain more vital information for the scene feature representation, we introduce an activation function (with unbounded above, bounded below, smooth, and non-monotonic properties) to allow more low-negative values to flow through the network, discarding high negative values. We evaluate the proposed methods on MIT Indoor 67 and Scene 15 datasets. The experiment findings show that the proposed methods capture global scene concepts and improve performance.

Where will corporate capital flow to? Revisiting the impact of China's pilot carbon emission trading system on investment

As a policy instrument to address climate change, the Carbon Emissions Trading System (ETS) will directly affect the location choice and development strategies of high-emitting firms' off-site investments, which is crucial to achieve optimal allocation of capital factors and coordinated development among regions. Using data of Chinese listed companies from 2007 to 2020, this study assesses for the first time the impact of Carbon Emissions Trading System on regulated firms' off-site investment strategies at the firm level using the Heterogeneity-Robust Difference-in-differences approach. The estimation results indicate that (1) the Carbon Emissions Trading System leads to about 20% reduction in off-site investment by regulated firms, which is mainly reflected in cross-city investment; (2) the heterogeneous investment effect is more obvious in private enterprise groups, but not in state-owned enterprise groups. Government intervention influenced the investment decisions of enterprise groups to make their development strategies more consistent with local economic growth objectives; (3) regulated enterprise groups significantly expanded their production layout locally and reduced off-site production investment; (4) the Carbon Emissions Trading System will promote long-term performance improvement of regulated firms. The above results are enlightening for the construction of Carbon Emissions Trading System in China and provide a new perspective for theoretically assessing the impact of Carbon Emissions Trading System on the competitiveness of enterprises.

The Social-Ecological System of Farmers’ Current Soil Carbon Management in Australian Grazing Lands

Soil carbon sequestration programmes are a way of offsetting GHG emissions, however, it requires agricultural landholders to be engaged in such initiatives for carbon offsets to occur. Farmer engagement is low in market-based programmes for soil carbon credits in Australia. We interviewed long-term practitioners (n = 25) of rotational grazing in high-rainfall lands of New South Wales, Australia to understand their current social-ecological system (SES) of soil carbon management (SCM). The aim was to identify those components of the SES that motivate them to manage soil carbon and also influence their potential engagement in soil carbon sequestration programmes. Utilising first-tier and second-tier concepts from Ostrom’s SES framework, the interview data were coded and identified a total of 51 features that characterised the farmers’ SES of SCM. Network analysis of farmer interview data revealed that the current SES of SCM has low connectivity among the SES features (30%). In four workshops with interviewed farmers (n = 2) and invited service providers (n = 2) the 51 features were reviewed and participants decided on the positioning and the interactions between features that were considered to influence SCM into a causal loop diagram. Post-workshop, 10 feedback loops were identified that revealed the different and common perspectives of farmers and service providers on SCM in a consolidated causal loop diagram. Defining the SES relationships for SCM can identify the challenges and needs of stakeholders, particularly farmers, which can then be addressed to achieve local, national and international objectives, such as SCM co-benefits, GHG reduction, carbon sequestration targets and SDGs.

The method of multi-objective parametric design of magnetic field active canceling robust system for residential multy-story buildings closed to double-circuit overhead power lines

Aim. Development the method of multi-objective parametric design for robust system of active canceling of magnetic field based on binary preference relations of local objective for multi-objective minimax optimization problem. Methodology. Spatial location coordinates of the compensating winding and the current in the shielding winding were determined during the preference-based multi-objective parametric design of systems of active canceling based on solution of the vector minimax optimization, in whith the vector objective function calculated based on Biot-Savart's law. The solution of this vector minimax optimization problem calculated based on nonlinear Archimedes algorithm. Components of Jacobi matrix and Hesse matrix calculated based on multi-swarm multi-agent optimization. Results. Theoretically and experimentally confirmed the effectiveness of reducing the level of the magnetic field in residential multy-storey old building of a double-circuit overhead power transmission lines with a barrel-type arrangement of wires by means of active shielding with two compensation winding. Originality. The method of multi-objective parametric design for robust system of active canceling of magnetic field based on binary preference relations of local objective for multi-objective minimax optimization problem is developed. Practical value. It is shown the possibility to reduce the level of magnetic field in residential multy-storey old building closed to double-circuit overhead power transmission lines with a barrel-type arrangement of wires by means of system of active canceling with two canceling winding to a level safe for the population with an induction of 0.5 μT.

Weakly-Supervised Semantic Feature Refinement Network for MMW Concealed Object Detection

The concealed object detection in millimeter-wave human body images is a challenging task due to the noise and dim-small objects. Exploiting the spatial dependencies to mine the difference between the object and the noise is vital for the discrimination of objects. However, most approaches ignore the context around the object. In this paper, a concealed object detection framework based on structural context is proposed to suppress noise interference and refine localizable semantic features. The framework consists of two subnetworks, structural region-based multi-scale weakly supervised feature refinement and local context-based concealed object detection. The multi-scale weakly supervised feature refinement is constructed to learn position-aware semantics of objects of various sizes while suppressing background noises in structural regions. Specifically, a multi-scale pooling method is proposed to better localize objects of different sizes, and an object-activated region enhancement module is designed to strengthen object semantic representations and suppress the background interference. Moreover, an adaptive local context aggregation module is designed to integrate the local context around the bounding box in the concealed object detection, which improves the discrimination of the model for the dim-small objects. Experimental results on the AMMW and the PMMW datasets demonstrate that the proposed approach improves detection performance with lower false alarm rates.

Momentum-Based Distributed Continuous-Time Nonconvex Optimization of Nonlinear Multi-Agent Systems via Timescale Separation

This study addresses the distributed nonconvex optimization problem for nonlinear multi-agent systems over a weight-balanced and quasi-strongly connected graph. The purpose is to steer all agents to the optimum of a given global objective function with inputs and outputs on the basis of the actual partial information related to the input and output. Novel momentum-based distributed optimal coordinators are designed to achieve this objective, and the local objective functions should be analytic to replace its convexity. An interconnected system with different timescales is established by converting the overall closed-loop system involving the module of momentum-based distributed optimal coordinators and nonlinear multi-agent systems. The singular perturbation approach is applied to deal with the overall interconnected closed-loop system by timescale separation. A numerical example and an application example with four firefighting unmanned aerial vehicles (UAVs) verify the superiority and effectiveness of the proposed distributed method and extended algorithms. Three momentum-based gradient descent algorithms (basic momentum-based, momentum-based Newton, and projected momentum-based gradient flows) are compared and analyzed.

First 3D modelling of tungsten erosion and migration in WEST discharges adopting a toroidally non-symmetric wall geometry

Numerical analysis is a useful tool to investigate tungsten (W) sources and transport across plasma in W Environment Steady state Tokamak (WEST) plasma discharges, as it highlights physical mechanisms not always directly observable in experiments. Modelling activities were performed to study W erosion from WEST plasma-facing components (PFCs), as well as W migration through the plasma. For the first time, it was adopted a toroidally asymmetric wall geometry consisting of toroidally localized objects representing WEST antennas. To simulate WEST boundary plasma, 3D non-axisymmetric SOLEDGE transport simulations were performed with simplifying assumptions (pure deuterium plasma, a fluid model for neutrals). Results were then used as background for ERO2.0 runs to model W migration. On the sides of the toroidally localized objects, two thin stripes modelled WEST W antenna protections. Simulations suggest that particles eroded from the antennas protections may dominate the core W contamination in the analysed wall configuration. The findings suggest that these 3D non-axisymmetric models may be needed on a broader range of plasma conditions and wall configurations to accurately model the W migration in WEST.

Privacy-Preserved Distributed Optimization for Multi-Agent Systems With Antagonistic Interactions

This paper is concerned with the privacy-preserving distributed optimization problem for a class of cooperative-competitive multi-agent systems. Each agent only knows its own local objective function and interacts the state information with neighbors through a communication network. By means of the signed graph theory, the antagonistic interactions among agents are considered to characterize both the cooperative and the competitive relationships. With the help of the gauge transformation technique, a structurally balanced undirected signed graph is firstly transformed into a standard undirected graph. Then, the distributed optimization problem subject to signed network is converted into the traditional distributed optimization problem. Subsequently, a novel privacy-preserving distributed optimization algorithm is put forward to 1) minimize the sum of local objective functions; 2) achieve the bipartite consensus for all agents; and 3) avoid the information leakage caused by message exchange among agents, simultaneously. Finally, a simulation example is given to verify the effectiveness of the proposed optimization algorithm.

Agent-Based Decentralized Model Predictive Control for Plants With Multiple Identical Actuators

This article proposes a decentralized model predictive control (DMPC) algorithm without communication for systems consisting of multiple identical, independent actuators acting on a single central plant. The particular system design is relevant for applications where modularity is paramount and for highly dynamic systems, e.g., battery emulator systems controlled by multiple dc–dc converter modules. Each agent, consisting of an actuator and a DMPC, controls a virtually scaled version of the plant to implicitly consider the effects of other agents. The set of DMPCs achieves the same plant performance as a corresponding centralized model predictive controller (CMPC) in unconstrained operation. Also, the states of the independent agents converge toward the globally optimal CMPC solution. This is obtained by dividing the CMPC’s objective function into local objective functions related to the subsystems. The optimality and stability of the DMPC in unconstrained operation are shown analytically. The stability of control input-constrained operation is analyzed by computing the region of attraction. Numerical studies of a battery emulator system compare the performance of the DMPC with the global optimum in detail.

Real-Time Fuzzy Logic Based Energy Management System for Microgrid Using Hardware in the Loop

This research presents a hierarchical energy management strategy for isolated microgrids (MG). The strategy’s objectives are achieved through a master-slave topology where local controllers are managed and controlled through a central controller. This can provide many technical advantages, particularly regarding the microgrid’s performance and the supply of energy. The local controller is designed to meet the local objectives of the microgrid, such as stabilization of DC voltage and maximization of sources’ extracted power. The objectives of the central controller are achieved through a centralized approach based on fuzzy logic to preserve battery life and manage the energy balance between generation and consumption. The microgrid’s performances were investigated under a steady-state and faulty regime. A Hardware in the Loop (HIL) test based on the Simulink platform is established by RT-LAB real-time simulator. Results are presented to validate the proposed hierarchical control. The OP1400 test bench, based on the OP4150 digital simulator, is utilized to test and validate the proposed hierarchical control strategy. The results are compared to international standards IEEE 1547 and IEC 61727, which demonstrate excellent consistency.

A fixed-time gradient algorithm for distributed optimization with inequality constraints

In this paper, a distributed fixed time gradient algorithm for neurodynamic systems is proposed for solving optimization problems with local inequality constraints. The algorithm is designed using fixed time theory and sliding model control techniques, where each agent has a local objective function known only to itself, and the optimal solution of each local objective function sum can be obtained in a fixed time by the information interaction between neighbors under the condition of local inequality constraints. In addition, the upper bound of the fixed time can be obtained and it is proved theoretically that the upper bound of the fixed time is independent of the initial value. Finally, the stability and effectiveness of the algorithm are verified by numerical examples.

Guidelines for Accurate Multi-Temporal Model Registration of 3D Scanned Objects.

Changes in object morphology can be quantified using 3D optical scanning to generate 3D models of an object at different time points. This process requires registration techniques that align target and reference 3D models using mapping functions based on common object features that are unaltered over time. The goal of this study was to determine guidelines when selecting these localized features to ensure robust and accurate 3D model registration. For this study, an object of interest (tibia bone replica) was 3D scanned at multiple time points, and the acquired 3D models were aligned using a simple cubic registration block attached to the object. The size of the registration block and the number of planar block surfaces selected to calculate the mapping functions used for 3D model registration were varied. Registration error was then calculated as the average linear surface variation between the target and reference tibial plateau surfaces. We obtained very low target registration errors when selecting block features with an area equivalent to at least 4% of the scanning field of view. Additionally, we found that at least two orthogonal surfaces should be selected to minimize registration error. Therefore, when registering 3D models to measure multi-temporal morphological change (e.g., mechanical wear), we recommend selecting multiplanar features that account for at least 4% of the scanning field of view. For the first time, this study has provided guidelines for selecting localized object features that can provide accurate 3D model registration for 3D scanned objects.

Towards local visual modeling for image captioning

In this paper, we study the local visual modeling with grid features for image captioning, which is critical for generating accurate and detailed captions. To achieve this target, we propose a Locality-Sensitive Transformer Network (LSTNet) with two novel designs, namely Locality-Sensitive Attention (LSA) and Locality-Sensitive Fusion (LSF). LSA is deployed for the intra-layer interaction in Transformer via modeling the relationship between each grid and its neighbors. It reduces the difficulty of local object recognition during captioning. LSF is used for inter-layer information fusion, which aggregates the information of different encoder layers for cross-layer semantical complementarity. With these two novel designs, the proposed LSTNet can model the local visual information of grid features to improve the captioning quality. To validate LSTNet, we conduct extensive experiments on the competitive MS-COCO benchmark. The experimental results show that LSTNet is not only capable of local visual modeling, but also outperforms a bunch of state-of-the-art captioning models on offline and online testings, i.e., 134.8 CIDEr and 136.3 CIDEr, respectively. Besides, the generalization of LSTNet is also verified on the Flickr8k and Flickr30k datasets. The source code is available on GitHub: https://www.github.com/xmu-xiaoma666/LSTNet.

Tensor CSRMT System with Horizontal Electrical Dipole Sources and Prospects of Its Application in Arctic Permafrost Regions

When studying horizontally-inhomogeneous media, it is necessary to apply tensor modifications of electromagnetic soundings. Use of tensor measurements is of particular relevance in near-surface electrical prospecting because the upper part of the geological section is usually more heterogeneous than the deep strata. In the Enviro-MT system designed for the controlled-source radiomagnetotelluric (CSRMT) sounding method, two mutually perpendicular horizontal magnetic dipoles (two vertical loops) are used for tensor measurements. We propose a variant of the CSRMT method with two horizontal electrical dipole sources (two transmitter lines). The advantage of such sources is an extended frequency range of 1–1000 kHz in comparison with 1–12 kHz of the Enviro-MT system, greater operational distance (up to 3–4 km compared to 600–800 m), and the ability to measure the signal at the fundamental frequency and its subharmonics. To implement tensor measurements with the equipment of the CSRMT method described in the paper, a technique of creating a time-varying polarization of the electromagnetic field (rotating field) has been developed based on the use of two transmitters with slightly different current frequencies and two mutually-perpendicular transmitter lines grounded at the ends. In this way, we made it possible to change the direction of the electrical and magnetic field polarization continuously. This approach allows realization of the technique of tensor measurements using the new modification of the CSRMT method. In permafrost areas, the hydrogenic taliks are widespread. These local objects are important in the context of study of environmental changes in the Arctic and can be successfully explored by the tensor CSRMT method. For the numerical modeling, a 2D model of the talik was used. Results of the interpretation of synthetic data showed the advantage of bimodal inversion using CSRMT curves of both TM and TE modes compared to separate inversion of TM and TE curves. These new data demonstrate the prospects of the tensor CSRMT method in the study of permafrost regions. The problems that can be solved using the CSRMT method in the Arctic permafrost regions are discussed.

Analisis Pengaruh Pariwisata Terhadap Pendapatan Asli Daerah Di Kabupaten Gresik

Tourism is one of the activities that generates the biggest profits or dividends for a country or region. This can be seen from several sectors that have a major influence on local revenue. In this study the authors used quantitative data obtained from institutions related to this research. The variables used by this writer are the number of tourists, the number of hotels, the number of restaurants, and the total income of the tourism sector. The type of data used in this study is time series data in 2010-2017 in the Gresik Regency area and the authors use multiple linear analysis methods, classical assumption tests, and (t) or statistical tests. The results of research conducted by this writer can be concluded that the number of tourists, the number of hotels, the number of restaurants, and the total income of the tourism sector have a positive effect on regional original income in Gresik Regency. This causes researchers to encourage local governments and tourism object managers to continue to carry out promotions and improve the facilities and infrastructure sector in order to attract tourists and tourists to feel safe and comfortable.
 Keywords : Number of Tourists, Number of Hotels, Number of Restaurants, Total Tourism Sector Revenue Regional Own Revenue

Augmented reality-assisted gesture-based teleoperated system for robot motion planning

Purpose The study proposed a human–robot interaction (HRI) framework to enable operators to communicate remotely with robots in a simple and intuitive way. The study focused on the situation when operators with no programming skills have to accomplish teleoperated tasks dealing with randomly localized different-sized objects in an unstructured environment. The purpose of this study is to reduce stress on operators, increase accuracy and reduce the time of task accomplishment. The special application of the proposed system is in the radioactive isotope production factories. The following approach combined the reactivity of the operator’s direct control with the powerful tools of vision-based object classification and localization. Design/methodology/approach Perceptive real-time gesture control predicated on a Kinect sensor is formulated by information fusion between human intuitiveness and an augmented reality-based vision algorithm. Objects are localized using a developed feature-based vision algorithm, where the homography is estimated and Perspective-n-Point problem is solved. The 3D object position and orientation are stored in the robot end-effector memory for the last mission adjusting and waiting for a gesture control signal to autonomously pick/place an object. Object classification process is done using a one-shot Siamese neural network (NN) to train a proposed deep NN; other well-known models are also used in a comparison. The system was contextualized in one of the nuclear industry applications: radioactive isotope production and its validation were performed through a user study where 10 participants of different backgrounds are involved. Findings The system was contextualized in one of the nuclear industry applications: radioactive isotope production and its validation were performed through a user study where 10 participants of different backgrounds are involved. The results revealed the effectiveness of the proposed teleoperation system and demonstrate its potential for use by robotics non-experienced users to effectively accomplish remote robot tasks. Social implications The proposed system reduces risk and increases level of safety when applied in hazardous environment such as the nuclear one. Originality/value The contribution and uniqueness of the presented study are represented in the development of a well-integrated HRI system that can tackle the four aforementioned circumstances in an effective and user-friendly way. High operator–robot reactivity is kept by using the direct control method, while a lot of cognitive stress is removed using elective/flapped autonomous mode to manipulate randomly localized different configuration objects. This necessitates building an effective deep learning algorithm (in comparison to well-known methods) to recognize objects in different conditions: illumination levels, shadows and different postures.

Distributed Time-Varying Convex Optimization With Dynamic Quantization.

In this work, we design a distributed algorithm for time-varying convex optimization over networks with quantized communications. Each agent has its local time-varying objective function, while the agents need to cooperatively track the optimal solution trajectories of global time-varying functions. The distributed algorithm is motivated by the alternating direction method of multipliers, but the agents can only share quantization information through an undirected graph. To reduce the tracking error due to information loss in quantization, we apply the dynamic quantization scheme with a decaying scaling function. The tracking error is explicitly characterized with respect to the limit of the decaying scaling function in quantization. Furthermore, we are able to show that the algorithm could asymptotically track the optimal solution when time-varying functions converge, even with quantization information loss. Finally, the theoretical results are validated via numerical simulation.

Article 2. Structural position of suites and strata of the “Bug series”

The name “Bug Series” was introduced into the Precambrian stratigraphic scheme of the Ukrainian Shield more than half a century ago. During this period, ideas about the composition and age of the series changed several times, but at the same time, until recently, the opinion of various studies about its stratigenic nature remained unchanged. In recent years, a number of publications have appeared in which other views on the origin of the “Bug series” are expressed. Initially, they concerned only individual petrographic groups, such as carbonate and magnetite-bearing rocks, which were attributed to endogenous (magmatic) origin. Later, an opinion was expressed about the nonstratigenic origin of the entire “Bug Series”, and some authors propose to abandon the dismemberment of the Early Precambrian granulite complexes into suites altogether. These ideas are based only on the materials of the study of local objects obtained by drilling and geophysical methods, and they do not take into account the results of regional geological and stratigraphic studies. Simultaneously with new ideas about the genesis of the “Bug series”, an attempt is being made to link its origin with faults and to revise its age.
 In order to discuss the problem of the “Bug series”, a series of publications has been prepared, presenting the main generalizations of many years of regional geological and thematic studies on the composition, structure, stratigraphic and structural position of the units belonging to the “Bug series”. The cycle consists of three separate articles. The first article characterizes the composition of subdivisions and rock associations included in the “Bug series” in the current Precambrian stratigraphic scheme of the Ukrainian Shield. In this second article of the cycle, ideas about the structural position of the “Bug series” and its subdivisions are considered. For a long time there was an opinion that the “Bug series” performed synclines “superimposed” on the ancient foundation. These ideas we-re convincingly refuted more than half a century ago on the example of the stratotype section of the Bug series in the area of Zavallia [Vinogradov, 1970], but sometimes some researchers still adhere to them. The data presented in this article indicate that all units that now belong to the “Bug series” are suites and strata that are part of a single Bug Area granulite complex and occupy a clearly defined stratigraphic and structural position in its section. Ideas about the connection of the “Bug series” with “superimposed” synclines or faults do not have any reliable justification.

Addressing Peripherality in Italy: A Critical Comparison between Inner Areas and Territorial Capital-Based Evaluations

As highlighted by the UN 2030 Agenda, sustainable development is a complex and multidimensional issue that can be effectively implemented and reached at the local level. This implies the evaluation of differences and disparities between territories in order to define local priorities and support cohesion policy objectives. This need has been addressed by the Italian “National Strategy for Inner Areas”, which aims to support the growth of territories with a continuous economic and population decline. However, Inner Areas are identified by a set of indicators related to the low accessibility to Services of General Interest, neglecting other important factors that contribute to this condition. This paper proposes a critical analysis of this measurement and of the related “territorialization” of Inner Areas, by introducing a more comprehensive assessment model based on the concept of Territorial Capital (TC), which highlights a more nuanced understanding of complexities and diversities related to the potential development of a territory. In particular, the proposed model evaluates eight TC dimensions (human, social, cognitive, infrastructural, productive, relational, environmental and settlement capital), which cover a broad spectrum of Sustainable Development Goals (SDGs). In order to accurately demonstrate the differences between the results of the two evaluation methods, this paper presents the results of a case study application concerning all 377 municipalities, which compose the Autonomous Region of Sardinia (Italy). The findings of this study confirm the potential of an approach based on the Territorial Capital for place-based policymaking. TC, in fact, can become relevant for defining local priorities and supporting complex decisions, allowing governments to better design and tailor interventions for the effective and efficient management of available resources. Furthermore, these results pose new questions for future research developments in the field of sustainable and equitable development.

A stochastic averaging gradient algorithm with multi‐step communication for distributed optimization

AbstractThis paper studies distributed convex optimization problems over an undirected network where all nodes cooperate to minimize a sum of local objective functions. Each local objective function is further assumed to be an average of several convex instantaneous functions. By incorporating the stochastic averaging gradient into the distributed first‐order primal‐dual method, a stochastic averaging gradient algorithm with multi‐step communication is proposed to solve the optimization problem. For each node, one randomly selected gradient of an instantaneous function is evaluated per iteration, which effectively reduces the computation cost of the algorithm. Based on conditions of strong convexity and Lipschitz continuity of the local instantaneous functions, a linear convergence rate of the proposed algorithm is guaranteed. Numerical simulations on the logistic regression problem demonstrate the performance of the algorithm and correctness of the theoretical results.