Ecological-Based Mining:A Coal-Water-Thermal Collaborative Paradigm in Ecologically Fragile Areas in Western China

A substantial reduction in groundwater level,exacerbated by coal mining activities,is intensifying water scarcity in western China’s ecologically fragile coal mining areas.China’s national strategic goal of achieving a carbon peak and carbon neutrality has made eco-friendly mining that prioritizes the protection and efficient use of water resources essential.Based on the resource characteristics of mine water and heat hazards,an intensive coal-water-thermal collaborative co-mining paradigm for the duration of the mining process is proposed.An integrated system for the production,supply,and storage of mining companion resources is achieved through technologies such as roof water inrush prevention and control,hydrothermal quality improvement,and deep-injection geological storage.An active preventive and control system achieved by adjusting the mining technology and a passive system centered on multiobjective drainage and grouting treatment are suggested,in accordance with the original geological characteristics and dynamic process of water inrush.By implementing advanced multi-objective drainage,specifically designed to address the“skylight-type”water inrush mode in the Yulin mining area of Shaanxi Province,a substantial reduction of 50%in water drillings and inflow was achieved,leading to stabilized water conditions that effectively ensure subsequent safe coal mining.An integrated-energy complementary model that incorporates the clean production concept of heat utilization is also proposed.The findings indicate a potential saving of 8419 t of standard coal by using water and air heat as an alternative heating source for the Xiaojihan coalmine,resulting in an impressive energy conservation of 50.2%and a notable 24.2%reduction in carbon emissions.The ultra-deep sustained water injection of 100 m^(3)·h^(-1)in a single well would not rupture the formation or cause water leakage,and 7.87×10^(5)t of mine water could be effectively stored in the Liujiagou Formation,presenting a viable method for mine-water management in the Ordos Basin and providing insights for green and low-carbon mining.

Improving Transferable Targeted Adversarial Attack for Object Detection Using RCEN Framework and Logit Loss Optimization

Object detection finds wide application in various sectors,including autonomous driving,industry,and healthcare.Recent studies have highlighted the vulnerability of object detection models built using deep neural networks when confronted with carefully crafted adversarial examples.This not only reveals their shortcomings in defending against malicious attacks but also raises widespread concerns about the security of existing systems.Most existing adversarial attack strategies focus primarily on image classification problems,failing to fully exploit the unique characteristics of object detectionmodels,thus resulting in widespread deficiencies in their transferability.Furthermore,previous research has predominantly concentrated on the transferability issues of non-targeted attacks,whereas enhancing the transferability of targeted adversarial examples presents even greater challenges.Traditional attack techniques typically employ cross-entropy as a loss measure,iteratively adjusting adversarial examples to match target categories.However,their inherent limitations restrict their broad applicability and transferability across different models.To address the aforementioned challenges,this study proposes a novel targeted adversarial attack method aimed at enhancing the transferability of adversarial samples across object detection models.Within the framework of iterative attacks,we devise a new objective function designed to mitigate consistency issues arising from cumulative noise and to enhance the separation between target and non-target categories(logit margin).Secondly,a data augmentation framework incorporating random erasing and color transformations is introduced into targeted adversarial attacks.This enhances the diversity of gradients,preventing overfitting to white-box models.Lastly,perturbations are applied only within the specified object’s bounding box to reduce the perturbation range,enhancing attack stealthiness.Experiments were conducted on the Microsoft Common Objects in Context(MS COCO)dataset using You Only Look Once version 3(YOLOv3),You Only Look Once version 8(YOLOv8),Faster Region-based Convolutional Neural Networks(Faster R-CNN),and RetinaNet.The results demonstrate a significant advantage of the proposed method in black-box settings.Among these,the success rate of RetinaNet transfer attacks reached a maximum of 82.59%.

Exploring sensitive area in the tropical Indian Ocean for El Niño prediction: implication for targeted observation

Based on initial errors of sea temperature in the tropical Indian Ocean that are most likely to induce spring predictability barrier(SPB)for the El Niño prediction,the sensitive area of sea temperature in the tropical Indian Ocean for El Niño prediction starting from January is identified using the CESM1.0.3(Community Earth System Model),a fully coupled global climate model.The sensitive area locates mainly in the subsurface of eastern Indian Ocean.The effectiveness of applying targeted observation in the sensitive area is also evaluated in an attempt to improve the El Niño prediction skill.The results of sensitivity experiments indicate that if initial errors exist only in the tropical Indian Ocean,applying targeted observation in the sensitive area in the Indian Ocean can significantly improve the El Niño prediction.In particular,for SPB-related El Niño events,when initial errors of sea temperature exist both in the tropical Indian Ocean and the Pacific Ocean,which is much closer to the realistic predictions,if targeted observations are conducted in the sensitive area of tropical Pacific,the prediction skills of SPB-related El Niño events can be improved by 20.3%in general.Moreover,if targeted observations are conducted in the sensitive area of tropical Indian Ocean in addition,the improvement of prediction skill can be increased by 25.2%.Considering the volume of sensitive area in the tropical Indian Ocean is about 1/3 of that in the tropical Pacific Ocean,the prediction skill improvement per cubic kilometer in the sensitive area of tropical Indian Ocean is competitive to that of the tropical Pacific Ocean.Additional to the sensitive area of the tropical Pacific Ocean,sensitive area of the tropical Indian Ocean is also a very effective and cost-saving area for the application of targeted observations to improve El Niño forecast skills.

Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean model

With the Regional Ocean Modeling System(ROMS),this paper investigates the sensitive areas in targeted observation for predicting the Kuroshio large meander(LM)path using the conditional nonlinear optimal perturbation approach.To identify the sensitive areas,the optimal initial errors(OIEs)featuring the largest nonlinear evolution in the LM prediction are first calculated;the resulting OIEs are localized mainly in the upper 2500 m over the LM upstream region,and their spatial structure has certain similarities with that of the optimal triggering perturbation.Based on this spatial structure,the sensitive areas are successfully identified,located southeast of Kyushu in the region(29°–32°N,131°–134°E).A series of sensitivity experiments indicate that both the positions and the spatial structure of initial errors have important effects on the LM prediction,verifying the validity of the sensitive areas.Then,the effect of targeted observation in the sensitive areas is evaluated through observing system simulation experiments.When targeted observation is implemented in the identified sensitive areas,the prediction errors are effectively reduced,and the prediction skill of the LM event is improved significantly.This provides scientific guidance for ocean observations related to enhancing the prediction skill of the LM event.

Identification of the sensitive area for targeted observation to improve vertical thermal structure prediction in summer in the Yellow Sea

The sensitive area of targeted observations for short-term(7 d)prediction of vertical thermal structure(VTS)in summer in the Yellow Sea was investigated.We applied the Conditional Nonlinear Optimal Perturbation(CNOP)method and an adjoint-free algorithm with the Regional Ocean Modeling System(ROMS).We used vertical integration of CNOP-type temperature errors to locate the sensitive areas,where reduction of initial errors is expected to yield the greatest improvement in VTS prediction for the selected verification area.The identified sensitive areas were northeast−southwest orientated northeast to the verification area,which were possibly related to the southwestward background currents.Then,we performed a series of sensitivity experiments to evaluate the effectiveness of the identified sensitive areas.Results show that initial errors in the identified sensitive areas had the greatest negative effect on VTS prediction in the verification area compared to errors in other areas(e.g.,the verification area and areas to its east and northeast).Moreover,removal of initial errors through deploying simulated observations in the identified sensitive areas led to more refined prediction than correction of initial conditions in the verification area itself.Our results suggest that implementation of targeted observation in the CNOP-based sensitive areas is an effective method to improve short-term prediction of VTS in summer in the Yellow Sea.

Genetic model and exploration target area of geothermal resources in Hongtang Area, Xiamen, China

The geothermal resources in Fujian Province are mainly hydrothermal resources of medium-low temperature.To better understand the whole process and conditions of heat control in the middle and deep crust,this study focuses on the analysis of heat accumulation model in Hongtang Area of Xiamen,and the main conditions of the model such as faults and sags are explored and interpreted in detail by using gravity and wide-field electromagnetic methods.4 main faults(F33,F2,F12 and HT-F1)and 10 secondary faults(HT-F2,HT-F3,HT-F4,HT-F5,HT-F6,HT-F7,HT-F8,HT-F9,HT-F10 and HT-F11)were inferred,and the distribution range of sags was delineated.The convective geothermal system is composed of four components:Heat source,geothermal reservoir,heat-conductive fault and heat retaining cover,which form a quaternary heat accumulation model.According to the model,the intersection of the main faults F12,HTF1 and F33 can be delineated as the primary target area of geothermal exploration,while the intersection of the secondary faults(F12 and HT-F6;F12 and HT-F2;HT-F9,HT-F10 and F12;F12 and HT-F11;F33 and HT-F3;HT-F8 and HT-F3;HT-F2,HT-F10 and HT-F1)can be delineated as the secondary target area.Borehole DR01,which is located in the primary target area,shows that the water temperature increases from fast to slow in the depth range of 0–500 m,and stays at 36℃below 500 m.The reliability of the heat accumulation model and the target area was tested via geothermal boreholes,which is of great significance to the exploitation and utilization of geothermal resources in Hongtang Area of Xiamen.

The Time and Regime Dependencies of Sensitive Areas for Tropical Cyclone Prediction Using the CNOP Method

This study examines the time and regime dependencies of sensitive areas identified by the conditional nonlinear optiflml perturbation （CNOP） method for forecasts of two typhoons. Typhoon Meari （2004） was weakly nonlinear and is herein referred to as the linear case, while Typhoon Matsa （2005） was strongly nonlinear and is herein referred to as the nonlinear case. In the linear case, the sensitive areas identified for special forecast times when the initial time was fixed resembled those identified for other forecast times. Targeted observations deployed to improve a special time forecast would thus also benefit forecasts at other times. In the nonlinear case, the similarities among the sensitive areas identified for different forecast times were more limited. The deployment of targeted observations in the nonlinear case would therefore need to be adapted to achieve large improvements for different targeted forecasts. For both cases, the closer the forecast time, the higher the similarities of the sensitive areas. When the forecast time was fixed, the sensitive areas in the linear case diverged continuously from the verification area as the forecast period lengthened, while those in the nonlinear case were always located around the initial cyclones. The deployment of targeted observations to improve a special forecast depends strongly on the time of deployment. An examination of the efficiency gained by reducing initial errors within the identified sensitive areas confirmed these results. In general, the greatest improvement in a special time forecast was obtained by identifying the sensitive areas for the corresponding forecast time period.

An Adjoint-Free CNOP–4DVar Hybrid Method for Identifying Sensitive Areas in Targeted Observations: Method Formulation and Preliminary Evaluation

This paper proposes a hybrid method, called CNOP–4 DVar, for the identification of sensitive areas in targeted observations, which takes the advantages of both the conditional nonlinear optimal perturbation(CNOP) and four-dimensional variational assimilation(4 DVar) methods. The proposed CNOP–4 DVar method is capable of capturing the most sensitive initial perturbation(IP), which causes the greatest perturbation growth at the time of verification;it can also identify sensitive areas by evaluating their assimilation effects for eliminating the most sensitive IP. To alleviate the dependence of the CNOP–4 DVar method on the adjoint model, which is inherited from the adjoint-based approach, we utilized two adjointfree methods, NLS-CNOP and NLS-4 DVar, to solve the CNOP and 4 DVar sub-problems, respectively. A comprehensive performance evaluation for the proposed CNOP–4 DVar method and its comparison with the CNOP and CNOP–ensemble transform Kalman filter(ETKF) methods based on 10 000 observing system simulation experiments on the shallow-water equation model are also provided. The experimental results show that the proposed CNOP–4 DVar method performs better than the CNOP–ETKF method and substantially better than the CNOP method.

METHOD OF MULTI-TARGET TRACKING IN WIDE AREA SURVEILLANCE AIRBORNE RADAR SYSTEM BASING ON CLUSTERING ANALYSIS

This paper proposed a robust method based on the definition of Mahalanobis distance to track ground moving target. The feature and the geometry of airborne ground moving target tracking systems are studied at first. Based on this feature, the assignment relation of time-nearby target is calculated via Mahalanobis distance, and then the corresponding transformation formula is deduced. The simulation results show the correctness and effectiveness of the proposed method.

Average Damage Caused by Multiple Weapons against an Area Target of Normally Distributed Elements

This paper investigates the effect of launching multiple weapons against an area target of normally distributed elements. We provide an analytical form of the average damage fraction and then apply it to obtain optimal aimpoints. To facilitate the computational efforts in practice, we also consider optimizations over given constrained patterns of aimpoints. Finally, we derive scaling laws for optimal aimpoints and optimal damage fraction with respect to the radius of the area target.

Delineation of Prospecting Prospect Area Based on Maximum Entropy Model

Taking the Dapingzhang copper-polymetallic deposit in Yunnan Province, China as the research object, the maximum entropy model was used to extract the mining information, and the mineral resource prediction model was established by using the exploration data of the deposit and related regions in this area, so as to determine the prospecting prospect area in the study area. In this paper, the Jacknife analysis module of maximum entropy model is used to quantitatively rank the importance of 39 geochemical element variables, and finally obtain the prospecting prospect map of the study area. The research results show that the Dapingzhang mining area has the potential to find hidden ore in the deep and surrounding areas, and the northern and southern ends and western sides of the rock ore control structural belt in the eastern region of the mining area have good prospecting prospects. The research results provide an important basis for the deployment of follow-up exploration work in the study area, and the maximum entropy model has a good application effect in mineral resources exploration.

A CALCULATING METHOD OF THE KILL PROBABILITY ATTACK AREA FOR AAM

This paper provides a calculating method which can be used in calculation of the kill probability attack area for every AAM. At first, attack area of AAM and kill probability of every characteristic point are obtained by combining trajectory calculation with kill probability calculation. Then, coordinates of a fire point relative to standard kill probability value in terms of standardization method are found. At last, equivalent kill probability curve equations are formulated by means of curve fitting method.

Online task planning method of anti-ship missile based on rolling optimization

Based on the wave attack task planning method in static complex environment and the rolling optimization framework, an online task planning method in dynamic complex environment based on rolling optimization is proposed. In the process of online task planning in dynamic complex environment,online task planning is based on event triggering including target information update event, new target addition event, target failure event, weapon failure event, etc., and the methods include defense area reanalysis, parameter space update, and mission re-planning. Simulation is conducted for different events and the result shows that the index value of the attack scenario after re-planning is better than that before re-planning and according to the probability distribution of statistical simulation method, the index value distribution after re-planning is obviously in the region of high index value, and the index value gap before and after re-planning is related to the degree of posture change.

A quantitative method for calculating irradiation area of laser target designator

In laser-guided bomb attacking process,the target indication from the laser target designator is the premise for the bomb to hit the target accurately.Considering the lack of quantitative study of the irradiation area of the laser target designator,this paper,based on the existing aircraft motion model and the laser transmission model,uses two aircraft as respectively the carrier of the laser-guided bomb and the carrier of the laser designator and proposes a method to calculate the global irradiation area of the airborne laser designator.By using the proposed algorithm,the global irradiation area when attacking a large flat target or a large spherical target is simulated respectively.Finally,according to the simulation results,the influences of different factors on the shapes of the irradiation area are discussed in detail.

Land Use Regionalization in Poor Counties in Mountainous Areas Based on Targeted Poverty Alleviation

Land use regionalization is a strategic measure for the rational use,management and protection of land resources based on local conditions.Based on the needs of targeted poverty alleviation and rural revitalization strategy and the analysis on the natural and socioeconomic conditions,characteristics of land resources,and the current status of land use in Luquan County,corresponding regionalization indices were selected from four aspects:economic environment conditions,socioeconomic conditions,land resources and land use structure,and poverty alleviation and development level,a scientific and feasible index system for land use regionalization was constructed,and land use in Luquan County was regionalized by using systematic cluster analysis method.The results show that the 16 townships(towns)of Luquan County were divided into four land use regions,poverty alleviation region for development of new town and characteristic industries in the southwest(I),agricultural development and ecological poverty alleviation region in central mountainous area(II),poverty alleviation region for development of characteristic agriculture and tourism towns in eastern plateau mountainous area(III),and poverty alleviation region for development of characteristic industries and protection of land economy in the northern alpine valley area(IV).In addition,suggestions were put forward for the rational use of land in each region.

Poverty Alleviation in the Poor Mountainous Areas of Western China by Supporting Industry: A Case Study of Xundian Hui and Yi Autonomous County in Yunnan Province

Poverty alleviation by supporting industry is a key measure to promote the poverty alleviation of relocated households. Taking Xundian County, the first county in Yunnan Province that has been lifted out of poverty, as an research case, this article analyzes and summarizes the industry-supporting poverty alleviation achievements and successful experience of two typical relocation areas (Shanhou Village and Eyang Village) in Xundian County. Practice has shown that the key to industry-supporting poverty alleviation lies in targetedness to strengthen the participation of poor farmers in industrial development. The interests of poverty alleviation entities should be linked by market mechanism to establish a benign interaction between all parties for win-win situation, thereby effectively guaranteeing the long-term and healthy development of poverty alleviation by supporting industry.

The Initial Errors in the Tropical Indian Ocean that Can Induce a Significant “Spring Predictability Barrier” for La Nina Events and Their Implication for Targeted Observations

Initial errors in the tropical Indian Ocean(IO-related initial errors) that are most likely to yield the Spring Prediction Barrier(SPB) for La Ni?a forecasts are explored by using the CESM model.These initial errors can be classified into two types.Type-1 initial error consists of positive sea temperature errors in the western Indian Ocean and negative sea temperature errors in the eastern Indian Ocean,while the spatial structure of Type-2 initial error is nearly opposite.Both kinds of IO-related initial errors induce positive prediction errors of sea temperature in the Pacific Ocean,leading to underprediction of La Nina events.Type-1 initial error in the tropical Indian Ocean mainly influences the SSTA in the tropical Pacific Ocean via atmospheric bridge,leading to the development of localized sea temperature errors in the eastern Pacific Ocean.However,for Type-2 initial error,its positive sea temperature errors in the eastern Indian Ocean can induce downwelling error and influence La Ni?a predictions through an oceanic channel called Indonesian Throughflow.Based on the location of largest SPB-related initial errors,the sensitive area in the tropical Indian Ocean for La Nina predictions is identified.Furthermore,sensitivity experiments show that applying targeted observations in this sensitive area is very useful in decreasing prediction errors of La Nina.Therefore,adopting a targeted observation strategy in the tropical Indian Ocean is a promising approach toward increasing ENSO prediction skill.

From anti-poverty to revitalization: Exploring the path of sustainable development in poverty-stricken areas

On the basis of analyzing the internal logic of rural revitalization and targeted poverty alleviation, it has made a path analysis of the decision-making to overcome poverty and effectively strengthen the rural revitalization. Grasping the internal unity of Marxism and the socialist theory system with Chinese characteristics, profoundly expounding the 'comprehensive' rural revitalization and 'concentration'targeted poverty alleviation, 'long-term' rural revitalization and 'stage' targeted poverty alleviation, and'active' rural revitalization Corresponding to the 'passive' targeted poverty alleviation, it corresponds to the philosophical logic of the materialist dialectic, the law of the unity of opposites, the law of mutual change of quality, and the law of negation of negation. It points out the path of targeted poverty alleviation work under the rural revitalization strategy: scientifically compiling the functional spatial planning of poor rural areas;party building leads the transformation of concepts;industrial development is expanding in depth;and public services are advancing to market.

Real Time Vehicular Traffic Simulation for Black Hole Attack in the Greater Detroit Area

Vehicular Ad-hoc Networks (VANETs) technology has recently emerged, and gaining significant attention from the research because it is promising technologies related to Intelligent Transportation System (ITSs) and smart cities. Wireless vehicular communication is employed to improve traffic safety and to reduce traffic congestion. Each vehicle in the ad-hoc network achieves as a smart mobile node categorized by high mobility and forming of dynamic networks. As a result of the movement of vehicles in a continuous way, VANETs are vulnerable to many security threats so it requisites capable and secure communication. Unfortunately, Ad hoc networks are liable to varied attacks like Block Hole attacks and Grey Hole attacks, Denial of service attacks, etc. Among the most known attacks are the Black Hole attacks while the malicious vehicle is able to intercept the data and drops it without forwarding it to the cars. The main goal of our simulation is to analyze the performance impact of black hole attack in real time vehicular traffic in the Greater Detroit Area using NS-2 and SUMO (Simulation of Urban). The simulation will be with AODV protocol.

MULTI-FIGHTER COORDINATED MULTI-TARGET ATTACK SYSTEM

A definition of self-determined priority is used in airfight decision firstly. A scheme of grouping the whole fighters is introduced, and the principle of target assignment and fire control is designed. Based on the neutral network, the decision algorithm is derived and the whole coordinated decision system is simulated. Secondly an algorithm for missile-attacking area is described and its calculational result is obtained under initial conditions. Then the attacking of missile is realized by the proportion guidance. Finally, a multi-target attack system. The system includes airfight decision, estimation of missile attack area and calculation of missile attack procedure. A digital simulation demonstrates that the airfight decision algorithm is correct. The methods have important reference values for the study of fire control system of the fourth generation fighter.